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t=e===g.asterisk?k.star:k.modulo,n=1,s=C.charCodeAt(w.pos+1);e===g.asterisk&&s===g.asterisk&&(n++,s=C.charCodeAt(w.pos+2),t=k.exponent),s===g.equalsTo&&C.charCodeAt(w.pos+2)!==g.greaterThan&&(n++,t=k.assign),Ae(t,n)}(e);case g.verticalBar:case g.ampersand:return void function(e){const t=C.charCodeAt(w.pos+1);if(t!==e){if(e===g.verticalBar){if(t===g.greaterThan)return void Ae(k.pipeline,2);if(t===g.rightCurlyBrace&&I)return void Ae(k.braceBarR,2)}t!==g.equalsTo?Ae(e===g.verticalBar?k.bitwiseOR:k.bitwiseAND,1):Ae(k.assign,2)}else C.charCodeAt(w.pos+2)===g.equalsTo?Ae(k.assign,3):Ae(e===g.verticalBar?k.logicalOR:k.logicalAND,2)}(e);case g.caret:return void(C.charCodeAt(w.pos+1)===g.equalsTo?Ae(k.assign,2):Ae(k.bitwiseXOR,1));case g.plusSign:case g.dash:return void function(e){const t=C.charCodeAt(w.pos+1);t!==e?t===g.equalsTo?Ae(k.assign,2):e===g.plusSign?Ae(k.plus,1):Ae(k.minus,1):Ae(k.preIncDec,2)}(e);case g.lessThan:return void function(){const 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n=this.tokens.identifierName();if(e&&"key"===n){null!==t&&this.tokens.appendCode(t.replace(/[^\n]/g,"")),this.tokens.removeToken(),this.tokens.removeToken();const e=this.tokens.snapshot();this.processPropValue(),t=this.tokens.dangerouslyGetAndRemoveCodeSinceSnapshot(e);continue}this.processPropName(n),this.tokens.replaceToken(": "),this.processPropValue()}else if(this.tokens.matches1(k.jsxName)){const e=this.tokens.identifierName();this.processPropName(e),this.tokens.appendCode(": true")}else{if(!this.tokens.matches1(k.braceL))break;this.tokens.replaceToken(""),this.rootTransformer.processBalancedCode(),this.tokens.replaceToken("")}this.tokens.appendCode(",")}return t}processPropName(e){e.includes("-")?this.tokens.replaceToken(`'${e}'`):this.tokens.copyToken()}processPropValue(){this.tokens.matches1(k.braceL)?(this.tokens.replaceToken(""),this.rootTransformer.processBalancedCode(),this.tokens.replaceToken("")):this.tokens.matches1(k.jsxTagStart)?this.processJSXTag():this.processStringPropValue()}processStringPropValue(){const e=this.tokens.currentToken(),t=this.tokens.code.slice(e.start+1,e.end-1),n=qe(t),s=function(e){let t="";for(let n=0;n<e.length;n++){const s=e[n];if("\n"===s)if(/\s/.test(e[n+1]))for(t+=" ";n<e.length&&/\s/.test(e[n+1]);)n++;else t+="\n";else if("&"===s){const{entity:s,newI:o}=Me(e,n+1);t+=s,n=o-1}else t+=s}return JSON.stringify(t)}(t);this.tokens.replaceToken(s+n)}processAutomaticChildrenAndEndProps(e){e===Y.StaticChildren?(this.tokens.appendCode(" children: ["),this.processChildren(!1),this.tokens.appendCode("]}")):(e===Y.OneChild&&this.tokens.appendCode(" children: "),this.processChildren(!1),this.tokens.appendCode("}"))}processChildren(e){let t=e;for(;;){if(this.tokens.matches2(k.jsxTagStart,k.slash))return;let e=!1;if(this.tokens.matches1(k.braceL))this.tokens.matches2(k.braceL,k.braceR)?(this.tokens.replaceToken(""),this.tokens.replaceToken("")):(this.tokens.replaceToken(t?", ":""),this.rootTransformer.processBalancedCode(),this.tokens.replaceToken(""),e=!0);else if(this.tokens.matches1(k.jsxTagStart))this.tokens.appendCode(t?", ":""),this.processJSXTag(),e=!0;else{if(!this.tokens.matches1(k.jsxText)&&!this.tokens.matches1(k.jsxEmptyText))throw new Error("Unexpected token when processing JSX children.");e=this.processChildTextElement(t)}e&&(t=!0)}}processChildTextElement(e){const t=this.tokens.currentToken(),n=this.tokens.code.slice(t.start,t.end),s=qe(n),o=function(e){let t="",n="",s=!1,o=!1;for(let r=0;r<e.length;r++){const i=e[r];if(" "===i||"\t"===i||"\r"===i)s||(n+=i);else if("\n"===i)n="",s=!0;else{if(o&&s&&(t+=" "),t+=n,n="","&"===i){const{entity:n,newI:s}=Me(e,r+1);r=s-1,t+=n}else t+=i;o=!0,s=!1}}s||(t+=n);return JSON.stringify(t)}(n);return'""'===o?(this.tokens.replaceToken(s),!1):(this.tokens.replaceToken(`${e?", ":""}${o}${s}`),!0)}getDevSource(e){return`{fileName: ${this.getFilenameVarName()}, ${e}}`}getFilenameVarName(){return this.filenameVarName||(this.filenameVarName=this.nameManager.claimFreeName("_jsxFileName")),this.filenameVarName}}function Be(e){const t=e.charCodeAt(0);return t>=g.lowercaseA&&t<=g.lowercaseZ}function qe(e){let t=0,n=0;for(const s of e)"\n"===s?(t++,n=0):" "===s&&n++;return"\n".repeat(t)+" ".repeat(n)}function Me(e,t){let n,s="",o=0,r=t;if("#"===e[r]){let t,s=10;if(r++,"x"===e[r])for(s=16,r++,t=r;r<e.length&&((i=e.charCodeAt(r))>=g.digit0&&i<=g.digit9||i>=g.lowercaseA&&i<=g.lowercaseF||i>=g.uppercaseA&&i<=g.uppercaseF);)r++;else for(t=r;r<e.length&&Fe(e.charCodeAt(r));)r++;if(";"===e[r]){const o=e.slice(t,r);o&&(r++,n=String.fromCodePoint(parseInt(o,s)))}}else for(;r<e.length&&o++<10;){const t=e[r];if(r++,";"===t){n=Re.get(s);break}s+=t}var i;return n?{entity:n,newI:r}:{entity:"&",newI:t}}function Fe(e){return e>=g.digit0&&e<=g.digit9}function $e(e,t){const n=Le(t),s=new Set;for(let o=0;o<e.tokens.length;o++){const t=e.tokens[o];if(t.type!==k.name||t.isType||t.identifierRole!==J.Access&&t.identifierRole!==J.ObjectShorthand&&t.identifierRole!==J.ExportAccess||t.shadowsGlobal||s.add(e.identifierNameForToken(t)),t.type===k.jsxTagStart&&s.add(n.base),t.type===k.jsxTagStart&&o+1<e.tokens.length&&e.tokens[o+1].type===k.jsxTagEnd&&(s.add(n.base),s.add(n.fragmentBase)),t.type===k.jsxName&&t.identifierRole===J.Access){Be(e.identifierNameForToken(t))&&e.tokens[o+1].type!==k.dot||s.add(e.identifierNameForToken(t))}}return s}class Ke{__init(){this.nonTypeIdentifiers=new Set}__init2(){this.importInfoByPath=new Map}__init3(){this.importsToReplace=new Map}__init4(){this.identifierReplacements=new Map}__init5(){this.exportBindingsByLocalName=new Map}constructor(e,t,n,s,o,r,i){this.nameManager=e,this.tokens=t,this.enableLegacyTypeScriptModuleInterop=n,this.options=s,this.isTypeScriptTransformEnabled=o,this.keepUnusedImports=r,this.helperManager=i,Ke.prototype.__init.call(this),Ke.prototype.__init2.call(this),Ke.prototype.__init3.call(this),Ke.prototype.__init4.call(this),Ke.prototype.__init5.call(this)}preprocessTokens(){for(let e=0;e<this.tokens.tokens.length;e++)this.tokens.matches1AtIndex(e,k._import)&&!this.tokens.matches3AtIndex(e,k._import,k.name,k.eq)&&this.preprocessImportAtIndex(e),this.tokens.matches1AtIndex(e,k._export)&&!this.tokens.matches2AtIndex(e,k._export,k.eq)&&this.preprocessExportAtIndex(e);this.generateImportReplacements()}pruneTypeOnlyImports(){this.nonTypeIdentifiers=$e(this.tokens,this.options);for(const[e,t]of this.importInfoByPath.entries()){if(t.hasBareImport||t.hasStarExport||t.exportStarNames.length>0||t.namedExports.length>0)continue;[...t.defaultNames,...t.wildcardNames,...t.namedImports.map((({localName:e})=>e))].every((e=>this.shouldAutomaticallyElideImportedName(e)))&&this.importsToReplace.set(e,"")}}shouldAutomaticallyElideImportedName(e){return this.isTypeScriptTransformEnabled&&!this.keepUnusedImports&&!this.nonTypeIdentifiers.has(e)}generateImportReplacements(){for(const[e,t]of this.importInfoByPath.entries()){const{defaultNames:n,wildcardNames:s,namedImports:o,namedExports:r,exportStarNames:i,hasStarExport:a}=t;if(0===n.length&&0===s.length&&0===o.length&&0===r.length&&0===i.length&&!a){this.importsToReplace.set(e,`require('${e}');`);continue}const c=this.getFreeIdentifierForPath(e);let l;l=this.enableLegacyTypeScriptModuleInterop?c:s.length>0?s[0]:this.getFreeIdentifierForPath(e);let u=`var ${c} = require('${e}');`;if(s.length>0)for(const e of s){u+=` var ${e} = ${this.enableLegacyTypeScriptModuleInterop?c:`${this.helperManager.getHelperName("interopRequireWildcard")}(${c})`};`}else i.length>0&&l!==c?u+=` var ${l} = ${this.helperManager.getHelperName("interopRequireWildcard")}(${c});`:n.length>0&&l!==c&&(u+=` var ${l} = ${this.helperManager.getHelperName("interopRequireDefault")}(${c});`);for(const{importedName:e,localName:t}of r)u+=` ${this.helperManager.getHelperName("createNamedExportFrom")}(${c}, '${t}', '${e}');`;for(const e of i)u+=` exports.${e} = ${l};`;a&&(u+=` ${this.helperManager.getHelperName("createStarExport")}(${c});`),this.importsToReplace.set(e,u);for(const e of n)this.identifierReplacements.set(e,`${l}.default`);for(const{importedName:e,localName:t}of o)this.identifierReplacements.set(t,`${c}.${e}`)}}getFreeIdentifierForPath(e){const t=e.split("/"),n=t[t.length-1].replace(/\W/g,"");return this.nameManager.claimFreeName(`_${n}`)}preprocessImportAtIndex(e){const t=[],n=[],s=[];if(e++,(this.tokens.matchesContextualAtIndex(e,m._type)||this.tokens.matches1AtIndex(e,k._typeof))&&!this.tokens.matches1AtIndex(e+1,k.comma)&&!this.tokens.matchesContextualAtIndex(e+1,m._from))return;if(this.tokens.matches1AtIndex(e,k.parenL))return;if(this.tokens.matches1AtIndex(e,k.name)&&(t.push(this.tokens.identifierNameAtIndex(e)),e++,this.tokens.matches1AtIndex(e,k.comma)&&e++),this.tokens.matches1AtIndex(e,k.star)&&(e+=2,n.push(this.tokens.identifierNameAtIndex(e)),e++),this.tokens.matches1AtIndex(e,k.braceL)){const n=this.getNamedImports(e+1);e=n.newIndex;for(const e of n.namedImports)"default"===e.importedName?t.push(e.localName):s.push(e)}if(this.tokens.matchesContextualAtIndex(e,m._from)&&e++,!this.tokens.matches1AtIndex(e,k.string))throw new Error("Expected string token at the end of import statement.");const o=this.tokens.stringValueAtIndex(e),r=this.getImportInfo(o);r.defaultNames.push(...t),r.wildcardNames.push(...n),r.namedImports.push(...s),0===t.length&&0===n.length&&0===s.length&&(r.hasBareImport=!0)}preprocessExportAtIndex(e){if(this.tokens.matches2AtIndex(e,k._export,k._var)||this.tokens.matches2AtIndex(e,k._export,k._let)||this.tokens.matches2AtIndex(e,k._export,k._const))this.preprocessVarExportAtIndex(e);else if(this.tokens.matches2AtIndex(e,k._export,k._function)||this.tokens.matches2AtIndex(e,k._export,k._class)){const t=this.tokens.identifierNameAtIndex(e+2);this.addExportBinding(t,t)}else if(this.tokens.matches3AtIndex(e,k._export,k.name,k._function)){const t=this.tokens.identifierNameAtIndex(e+3);this.addExportBinding(t,t)}else this.tokens.matches2AtIndex(e,k._export,k.braceL)?this.preprocessNamedExportAtIndex(e):this.tokens.matches2AtIndex(e,k._export,k.star)&&this.preprocessExportStarAtIndex(e)}preprocessVarExportAtIndex(e){let t=0;for(let n=e+2;;n++)if(this.tokens.matches1AtIndex(n,k.braceL)||this.tokens.matches1AtIndex(n,k.dollarBraceL)||this.tokens.matches1AtIndex(n,k.bracketL))t++;else if(this.tokens.matches1AtIndex(n,k.braceR)||this.tokens.matches1AtIndex(n,k.bracketR))t--;else{if(0===t&&!this.tokens.matches1AtIndex(n,k.name))break;if(this.tokens.matches1AtIndex(1,k.eq)){const e=this.tokens.currentToken().rhsEndIndex;if(null==e)throw new Error("Expected = token with an end index.");n=e-1}else{if(Q(this.tokens.tokens[n])){const e=this.tokens.identifierNameAtIndex(n);this.identifierReplacements.set(e,`exports.${e}`)}}}}preprocessNamedExportAtIndex(e){e+=2;const{newIndex:t,namedImports:n}=this.getNamedImports(e);if(e=t,!this.tokens.matchesContextualAtIndex(e,m._from)){for(const{importedName:e,localName:t}of n)this.addExportBinding(e,t);return}if(e++,!this.tokens.matches1AtIndex(e,k.string))throw new Error("Expected string token at the end of import statement.");const s=this.tokens.stringValueAtIndex(e);this.getImportInfo(s).namedExports.push(...n)}preprocessExportStarAtIndex(e){let t=null;if(this.tokens.matches3AtIndex(e,k._export,k.star,k._as)?(e+=3,t=this.tokens.identifierNameAtIndex(e),e+=2):e+=3,!this.tokens.matches1AtIndex(e,k.string))throw new Error("Expected string token at the end of star export statement.");const n=this.tokens.stringValueAtIndex(e),s=this.getImportInfo(n);null!==t?s.exportStarNames.push(t):s.hasStarExport=!0}getNamedImports(e){const t=[];for(;;){if(this.tokens.matches1AtIndex(e,k.braceR)){e++;break}const n=Ne(this.tokens,e);if(e=n.endIndex,n.isType||t.push({importedName:n.leftName,localName:n.rightName}),this.tokens.matches2AtIndex(e,k.comma,k.braceR)){e+=2;break}if(this.tokens.matches1AtIndex(e,k.braceR)){e++;break}if(!this.tokens.matches1AtIndex(e,k.comma))throw new Error(`Unexpected token: ${JSON.stringify(this.tokens.tokens[e])}`);e++}return{newIndex:e,namedImports:t}}getImportInfo(e){const t=this.importInfoByPath.get(e);if(t)return t;const n={defaultNames:[],wildcardNames:[],namedImports:[],namedExports:[],hasBareImport:!1,exportStarNames:[],hasStarExport:!1};return this.importInfoByPath.set(e,n),n}addExportBinding(e,t){this.exportBindingsByLocalName.has(e)||this.exportBindingsByLocalName.set(e,[]),this.exportBindingsByLocalName.get(e).push(t)}claimImportCode(e){const t=this.importsToReplace.get(e);return this.importsToReplace.set(e,""),t||""}getIdentifierReplacement(e){return this.identifierReplacements.get(e)||null}resolveExportBinding(e){const t=this.exportBindingsByLocalName.get(e);return t&&0!==t.length?t.map((e=>`exports.${e}`)).join(" = "):null}getGlobalNames(){return new Set([...this.identifierReplacements.keys(),...this.exportBindingsByLocalName.keys()])}}var He=n(9320);function Ve({code:e,mappings:t},n,s,o,r){const i=function(e,t){const n=new Array(t.length);let s=0,o=t[s].start,r=0;for(let i=0;i<e.length;i++)i===o&&(n[s]=o-r,s++,o=t[s].start),e.charCodeAt(i)===g.lineFeed&&(r=i+1);return n}(o,r),a=new He.GenMapping({file:s.compiledFilename});let c=0,l=t[0];for(;void 0===l&&c<t.length-1;)c++,l=t[c];let u=0,h=0;l!==h&&(0,He.maybeAddSegment)(a,u,0,n,u,0);for(let m=0;m<e.length;m++){if(m===l){const e=l-h,s=i[c];for((0,He.maybeAddSegment)(a,u,e,n,u,s);(l===m||void 0===l)&&c<t.length-1;)c++,l=t[c]}e.charCodeAt(m)===g.lineFeed&&(u++,h=m+1,l!==h&&(0,He.maybeAddSegment)(a,u,0,n,u,0))}const{sourceRoot:p,sourcesContent:d,...f}=(0,He.toEncodedMap)(a);return f}const Ue={require:'\n import {createRequire as CREATE_REQUIRE_NAME} from "module";\n const require = CREATE_REQUIRE_NAME(import.meta.url);\n ',interopRequireWildcard:"\n function interopRequireWildcard(obj) {\n if (obj && obj.__esModule) {\n return obj;\n } else {\n var newObj = {};\n if (obj != null) {\n for (var key in obj) {\n if (Object.prototype.hasOwnProperty.call(obj, key)) {\n newObj[key] = obj[key];\n }\n }\n }\n newObj.default = obj;\n return newObj;\n }\n }\n ",interopRequireDefault:"\n function interopRequireDefault(obj) {\n return obj && obj.__esModule ? obj : { default: obj };\n }\n ",createNamedExportFrom:"\n function createNamedExportFrom(obj, localName, importedName) {\n Object.defineProperty(exports, localName, {enumerable: true, configurable: true, get: () => obj[importedName]});\n }\n ",createStarExport:'\n function createStarExport(obj) {\n Object.keys(obj)\n .filter((key) => key !== "default" && key !== "__esModule")\n .forEach((key) => {\n if (exports.hasOwnProperty(key)) {\n return;\n }\n Object.defineProperty(exports, key, {enumerable: true, configurable: true, get: () => obj[key]});\n });\n }\n ',nullishCoalesce:"\n function nullishCoalesce(lhs, rhsFn) {\n if (lhs != null) {\n return lhs;\n } else {\n return rhsFn();\n }\n }\n ",asyncNullishCoalesce:"\n async function asyncNullishCoalesce(lhs, rhsFn) {\n if (lhs != null) {\n return lhs;\n } else {\n return await rhsFn();\n }\n }\n ",optionalChain:"\n function optionalChain(ops) {\n let lastAccessLHS = undefined;\n let value = ops[0];\n let i = 1;\n while (i < ops.length) {\n const op = ops[i];\n const fn = ops[i + 1];\n i += 2;\n if ((op === 'optionalAccess' || op === 'optionalCall') && value == null) {\n return undefined;\n }\n if (op === 'access' || op === 'optionalAccess') {\n lastAccessLHS = value;\n value = fn(value);\n } else if (op === 'call' || op === 'optionalCall') {\n value = fn((...args) => value.call(lastAccessLHS, ...args));\n lastAccessLHS = undefined;\n }\n }\n return value;\n }\n ",asyncOptionalChain:"\n async function asyncOptionalChain(ops) {\n let lastAccessLHS = undefined;\n let value = ops[0];\n let i = 1;\n while (i < ops.length) {\n const op = ops[i];\n const fn = ops[i + 1];\n i += 2;\n if ((op === 'optionalAccess' || op === 'optionalCall') && value == null) {\n return undefined;\n }\n if (op === 'access' || op === 'optionalAccess') {\n lastAccessLHS = value;\n value = await fn(value);\n } else if (op === 'call' || op === 'optionalCall') {\n value = await fn((...args) => value.call(lastAccessLHS, ...args));\n lastAccessLHS = undefined;\n }\n }\n return value;\n }\n ",optionalChainDelete:"\n function optionalChainDelete(ops) {\n const result = OPTIONAL_CHAIN_NAME(ops);\n return result == null ? true : result;\n }\n ",asyncOptionalChainDelete:"\n async function asyncOptionalChainDelete(ops) {\n const result = await ASYNC_OPTIONAL_CHAIN_NAME(ops);\n return result == null ? true : result;\n }\n "};class We{__init(){this.helperNames={}}__init2(){this.createRequireName=null}constructor(e){this.nameManager=e,We.prototype.__init.call(this),We.prototype.__init2.call(this)}getHelperName(e){let t=this.helperNames[e];return t||(t=this.nameManager.claimFreeName(`_${e}`),this.helperNames[e]=t,t)}emitHelpers(){let e="";this.helperNames.optionalChainDelete&&this.getHelperName("optionalChain"),this.helperNames.asyncOptionalChainDelete&&this.getHelperName("asyncOptionalChain");for(const[t,n]of Object.entries(Ue)){const s=this.helperNames[t];let o=n;"optionalChainDelete"===t?o=o.replace("OPTIONAL_CHAIN_NAME",this.helperNames.optionalChain):"asyncOptionalChainDelete"===t?o=o.replace("ASYNC_OPTIONAL_CHAIN_NAME",this.helperNames.asyncOptionalChain):"require"===t&&(null===this.createRequireName&&(this.createRequireName=this.nameManager.claimFreeName("_createRequire")),o=o.replace(/CREATE_REQUIRE_NAME/g,this.createRequireName)),s&&(e+=" ",e+=o.replace(t,s).replace(/\s+/g," ").trim())}return e}}function ze(e,t,n){(function(e,t){for(const n of e.tokens)if(n.type===k.name&&!n.isType&&Z(n)&&t.has(e.identifierNameForToken(n)))return!0;return!1})(e,n)&&function(e,t,n){const s=[];let o=t.length-1;for(let r=e.tokens.length-1;;r--){for(;s.length>0&&s[s.length-1].startTokenIndex===r+1;)s.pop();for(;o>=0&&t[o].endTokenIndex===r+1;)s.push(t[o]),o--;if(r<0)break;const i=e.tokens[r],a=e.identifierNameForToken(i);if(s.length>1&&!i.isType&&i.type===k.name&&n.has(a))if(te(i))Ge(s[s.length-1],e,a);else if(ne(i)){let t=s.length-1;for(;t>0&&!s[t].isFunctionScope;)t--;if(t<0)throw new Error("Did not find parent function scope.");Ge(s[t],e,a)}}if(s.length>0)throw new Error("Expected empty scope stack after processing file.")}(e,t,n)}function Ge(e,t,n){for(let s=e.startTokenIndex;s<e.endTokenIndex;s++){const e=t.tokens[s];e.type!==k.name&&e.type!==k.jsxName||t.identifierNameForToken(e)!==n||(e.shadowsGlobal=!0)}}class Xe{__init(){this.usedNames=new Set}constructor(e,t){Xe.prototype.__init.call(this),this.usedNames=new Set(function(e,t){const n=[];for(const s of t)s.type===k.name&&n.push(e.slice(s.start,s.end));return n}(e,t))}claimFreeName(e){const t=this.findFreeName(e);return this.usedNames.add(t),t}findFreeName(e){if(!this.usedNames.has(e))return e;let t=2;for(;this.usedNames.has(e+String(t));)t++;return e+String(t)}}var Je=n(9361);const Ye={Transform:Je.union(Je.lit("jsx"),Je.lit("typescript"),Je.lit("flow"),Je.lit("imports"),Je.lit("react-hot-loader"),Je.lit("jest")),SourceMapOptions:Je.iface([],{compiledFilename:"string"}),Options:Je.iface([],{transforms:Je.array("Transform"),disableESTransforms:Je.opt("boolean"),jsxRuntime:Je.opt(Je.union(Je.lit("classic"),Je.lit("automatic"),Je.lit("preserve"))),production:Je.opt("boolean"),jsxImportSource:Je.opt("string"),jsxPragma:Je.opt("string"),jsxFragmentPragma:Je.opt("string"),keepUnusedImports:Je.opt("boolean"),preserveDynamicImport:Je.opt("boolean"),injectCreateRequireForImportRequire:Je.opt("boolean"),enableLegacyTypeScriptModuleInterop:Je.opt("boolean"),enableLegacyBabel5ModuleInterop:Je.opt("boolean"),sourceMapOptions:Je.opt("SourceMapOptions"),filePath:Je.opt("string")})},{Options:Qe}=(0,Je.createCheckers)(Ye);function Ze(){re(),fn(!1)}function et(e){re(),ot(e)}function tt(e){Un(),st(e)}function 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s=t.currentIndex(),o=t.currentToken().rhsEndIndex;if(null==o)throw new Error("Expected rhsEndIndex on class field assignment.");for(t.nextToken();t.currentIndex()<o;)e.processToken();let i;r?(i=n.claimFreeName("__initStatic"),c.push(i)):(i=n.claimFreeName("__init"),a.push(i)),u.push({initializerName:i,equalsIndex:s,start:g,end:t.currentIndex()})}else s&&!f||h.push({start:o,end:t.currentIndex()})}return t.restoreToSnapshot(o),s?{headerInfo:r,constructorInitializerStatements:i,instanceInitializerNames:[],staticInitializerNames:[],constructorInsertPos:l,fields:[],rangesToRemove:h}:{headerInfo:r,constructorInitializerStatements:i,instanceInitializerNames:a,staticInitializerNames:c,constructorInsertPos:l,fields:u,rangesToRemove:h}}function io(e,t){for(e.nextToken();e.currentToken().contextId!==t;)e.nextToken();for(;co(e.tokenAtRelativeIndex(-1));)e.previousToken()}function ao(e){const t=[];e.nextToken();const n=e.currentToken().contextId;if(null==n)throw new Error("Expected context ID on 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t=e.currentIndex();for(;!e.matches1AtIndex(t,k.braceR);)t++;return e.matchesContextualAtIndex(t+1,m._from)&&e.matches1AtIndex(t+2,k.string)}function mo(e){(e.matches2(k._with,k.braceL)||e.matches2(k.name,k.braceL)&&e.matchesContextual(m._assert))&&(e.removeToken(),e.removeToken(),e.removeBalancedCode(),e.removeToken())}function ko(e,t,n,s){if(!e||t)return!1;const o=n.currentToken();if(null==o.rhsEndIndex)throw new Error("Expected non-null rhsEndIndex on export token.");const r=o.rhsEndIndex-n.currentIndex();if(3!==r&&(4!==r||!n.matches1AtIndex(o.rhsEndIndex-1,k.semi)))return!1;const i=n.tokenAtRelativeIndex(2);if(i.type!==k.name)return!1;const a=n.identifierNameForToken(i);return s.typeDeclarations.has(a)&&!s.valueDeclarations.has(a)}class go extends De{__init(){this.hadExport=!1}__init2(){this.hadNamedExport=!1}__init3(){this.hadDefaultExport=!1}constructor(e,t,n,s,o,r,i,a,c,l,u,h){super(),this.rootTransformer=e,this.tokens=t,this.importProcessor=n,this.nameManager=s,this.helperManager=o,this.reactHotLoaderTransformer=r,this.enableLegacyBabel5ModuleInterop=i,this.enableLegacyTypeScriptModuleInterop=a,this.isTypeScriptTransformEnabled=c,this.isFlowTransformEnabled=l,this.preserveDynamicImport=u,this.keepUnusedImports=h,go.prototype.__init.call(this),go.prototype.__init2.call(this),go.prototype.__init3.call(this),this.declarationInfo=c?po(t):ho}getPrefixCode(){let e="";return this.hadExport&&(e+='Object.defineProperty(exports, "__esModule", {value: true});'),e}getSuffixCode(){return this.enableLegacyBabel5ModuleInterop&&this.hadDefaultExport&&!this.hadNamedExport?"\nmodule.exports = exports.default;\n":""}process(){return this.tokens.matches3(k._import,k.name,k.eq)?this.processImportEquals():this.tokens.matches1(k._import)?(this.processImport(),!0):this.tokens.matches2(k._export,k.eq)?(this.tokens.replaceToken("module.exports"),!0):this.tokens.matches1(k._export)&&!this.tokens.currentToken().isType?(this.hadExport=!0,this.processExport()):!(!this.tokens.matches2(k.name,k.postIncDec)||!this.processPostIncDec())||(this.tokens.matches1(k.name)||this.tokens.matches1(k.jsxName)?this.processIdentifier():this.tokens.matches1(k.eq)?this.processAssignment():this.tokens.matches1(k.assign)?this.processComplexAssignment():!!this.tokens.matches1(k.preIncDec)&&this.processPreIncDec())}processImportEquals(){const e=this.tokens.identifierNameAtIndex(this.tokens.currentIndex()+1);return this.importProcessor.shouldAutomaticallyElideImportedName(e)?uo(this.tokens):this.tokens.replaceToken("const"),!0}processImport(){if(this.tokens.matches2(k._import,k.parenL)){if(this.preserveDynamicImport)return void this.tokens.copyToken();const e=this.enableLegacyTypeScriptModuleInterop?"":`${this.helperManager.getHelperName("interopRequireWildcard")}(`;this.tokens.replaceToken(`Promise.resolve().then(() => ${e}require`);const t=this.tokens.currentToken().contextId;if(null==t)throw new Error("Expected context ID on dynamic import invocation.");for(this.tokens.copyToken();!this.tokens.matchesContextIdAndLabel(k.parenR,t);)this.rootTransformer.processToken();return void this.tokens.replaceToken(e?")))":"))")}if(this.removeImportAndDetectIfShouldElide())this.tokens.removeToken();else{const e=this.tokens.stringValue();this.tokens.replaceTokenTrimmingLeftWhitespace(this.importProcessor.claimImportCode(e)),this.tokens.appendCode(this.importProcessor.claimImportCode(e))}mo(this.tokens),this.tokens.matches1(k.semi)&&this.tokens.removeToken()}removeImportAndDetectIfShouldElide(){if(this.tokens.removeInitialToken(),this.tokens.matchesContextual(m._type)&&!this.tokens.matches1AtIndex(this.tokens.currentIndex()+1,k.comma)&&!this.tokens.matchesContextualAtIndex(this.tokens.currentIndex()+1,m._from))return this.removeRemainingImport(),!0;if(this.tokens.matches1(k.name)||this.tokens.matches1(k.star))return this.removeRemainingImport(),!1;if(this.tokens.matches1(k.string))return!1;let e=!1,t=!1;for(;!this.tokens.matches1(k.string);)(!e&&this.tokens.matches1(k.braceL)||this.tokens.matches1(k.comma))&&(this.tokens.removeToken(),this.tokens.matches1(k.braceR)||(t=!0),(this.tokens.matches2(k.name,k.comma)||this.tokens.matches2(k.name,k.braceR)||this.tokens.matches4(k.name,k.name,k.name,k.comma)||this.tokens.matches4(k.name,k.name,k.name,k.braceR))&&(e=!0)),this.tokens.removeToken();return!this.keepUnusedImports&&(this.isTypeScriptTransformEnabled?!e:!!this.isFlowTransformEnabled&&(t&&!e))}removeRemainingImport(){for(;!this.tokens.matches1(k.string);)this.tokens.removeToken()}processIdentifier(){const e=this.tokens.currentToken();if(e.shadowsGlobal)return!1;if(e.identifierRole===J.ObjectShorthand)return this.processObjectShorthand();if(e.identifierRole!==J.Access)return!1;const t=this.importProcessor.getIdentifierReplacement(this.tokens.identifierNameForToken(e));if(!t)return!1;let n=this.tokens.currentIndex()+1;for(;n<this.tokens.tokens.length&&this.tokens.tokens[n].type===k.parenR;)n++;return this.tokens.tokens[n].type===k.parenL?this.tokens.tokenAtRelativeIndex(1).type===k.parenL&&this.tokens.tokenAtRelativeIndex(-1).type!==k._new?(this.tokens.replaceToken(`${t}.call(void 0, `),this.tokens.removeToken(),this.rootTransformer.processBalancedCode(),this.tokens.copyExpectedToken(k.parenR)):this.tokens.replaceToken(`(0, ${t})`):this.tokens.replaceToken(t),!0}processObjectShorthand(){const e=this.tokens.identifierName(),t=this.importProcessor.getIdentifierReplacement(e);return!!t&&(this.tokens.replaceToken(`${e}: ${t}`),!0)}processExport(){if(this.tokens.matches2(k._export,k._enum)||this.tokens.matches3(k._export,k._const,k._enum))return this.hadNamedExport=!0,!1;if(this.tokens.matches2(k._export,k._default))return this.tokens.matches3(k._export,k._default,k._enum)?(this.hadDefaultExport=!0,!1):(this.processExportDefault(),!0);if(this.tokens.matches2(k._export,k.braceL))return this.processExportBindings(),!0;if(this.tokens.matches2(k._export,k.name)&&this.tokens.matchesContextualAtIndex(this.tokens.currentIndex()+1,m._type)){if(this.tokens.removeInitialToken(),this.tokens.removeToken(),this.tokens.matches1(k.braceL)){for(;!this.tokens.matches1(k.braceR);)this.tokens.removeToken();this.tokens.removeToken()}else this.tokens.removeToken(),this.tokens.matches1(k._as)&&(this.tokens.removeToken(),this.tokens.removeToken());return this.tokens.matchesContextual(m._from)&&this.tokens.matches1AtIndex(this.tokens.currentIndex()+1,k.string)&&(this.tokens.removeToken(),this.tokens.removeToken(),mo(this.tokens)),!0}if(this.hadNamedExport=!0,this.tokens.matches2(k._export,k._var)||this.tokens.matches2(k._export,k._let)||this.tokens.matches2(k._export,k._const))return this.processExportVar(),!0;if(this.tokens.matches2(k._export,k._function)||this.tokens.matches3(k._export,k.name,k._function))return this.processExportFunction(),!0;if(this.tokens.matches2(k._export,k._class)||this.tokens.matches3(k._export,k._abstract,k._class)||this.tokens.matches2(k._export,k.at))return this.processExportClass(),!0;if(this.tokens.matches2(k._export,k.star))return this.processExportStar(),!0;throw new Error("Unrecognized export syntax.")}processAssignment(){const e=this.tokens.currentIndex(),t=this.tokens.tokens[e-1];if(t.isType||t.type!==k.name)return!1;if(t.shadowsGlobal)return!1;if(e>=2&&this.tokens.matches1AtIndex(e-2,k.dot))return!1;if(e>=2&&[k._var,k._let,k._const].includes(this.tokens.tokens[e-2].type))return!1;const n=this.importProcessor.resolveExportBinding(this.tokens.identifierNameForToken(t));return!!n&&(this.tokens.copyToken(),this.tokens.appendCode(` ${n} =`),!0)}processComplexAssignment(){const e=this.tokens.currentIndex(),t=this.tokens.tokens[e-1];if(t.type!==k.name)return!1;if(t.shadowsGlobal)return!1;if(e>=2&&this.tokens.matches1AtIndex(e-2,k.dot))return!1;const n=this.importProcessor.resolveExportBinding(this.tokens.identifierNameForToken(t));return!!n&&(this.tokens.appendCode(` = ${n}`),this.tokens.copyToken(),!0)}processPreIncDec(){const e=this.tokens.currentIndex(),t=this.tokens.tokens[e+1];if(t.type!==k.name)return!1;if(t.shadowsGlobal)return!1;if(e+2<this.tokens.tokens.length&&(this.tokens.matches1AtIndex(e+2,k.dot)||this.tokens.matches1AtIndex(e+2,k.bracketL)||this.tokens.matches1AtIndex(e+2,k.parenL)))return!1;const n=this.tokens.identifierNameForToken(t),s=this.importProcessor.resolveExportBinding(n);return!!s&&(this.tokens.appendCode(`${s} = `),this.tokens.copyToken(),!0)}processPostIncDec(){const e=this.tokens.currentIndex(),t=this.tokens.tokens[e],n=this.tokens.tokens[e+1];if(t.type!==k.name)return!1;if(t.shadowsGlobal)return!1;if(e>=1&&this.tokens.matches1AtIndex(e-1,k.dot))return!1;const s=this.tokens.identifierNameForToken(t),o=this.importProcessor.resolveExportBinding(s);if(!o)return!1;const r=this.tokens.rawCodeForToken(n),i=this.importProcessor.getIdentifierReplacement(s)||s;if("++"===r)this.tokens.replaceToken(`(${i} = ${o} = ${i} + 1, ${i} - 1)`);else{if("--"!==r)throw new Error(`Unexpected operator: ${r}`);this.tokens.replaceToken(`(${i} = ${o} = ${i} - 1, ${i} + 1)`)}return this.tokens.removeToken(),!0}processExportDefault(){let e=!0;if(this.tokens.matches4(k._export,k._default,k._function,k.name)||this.tokens.matches5(k._export,k._default,k.name,k._function,k.name)&&this.tokens.matchesContextualAtIndex(this.tokens.currentIndex()+2,m._async)){this.tokens.removeInitialToken(),this.tokens.removeToken();const e=this.processNamedFunction();this.tokens.appendCode(` exports.default = ${e};`)}else if(this.tokens.matches4(k._export,k._default,k._class,k.name)||this.tokens.matches5(k._export,k._default,k._abstract,k._class,k.name)||this.tokens.matches3(k._export,k._default,k.at)){this.tokens.removeInitialToken(),this.tokens.removeToken(),this.copyDecorators(),this.tokens.matches1(k._abstract)&&this.tokens.removeToken();const e=this.rootTransformer.processNamedClass();this.tokens.appendCode(` exports.default = ${e};`)}else if(ko(this.isTypeScriptTransformEnabled,this.keepUnusedImports,this.tokens,this.declarationInfo))e=!1,this.tokens.removeInitialToken(),this.tokens.removeToken(),this.tokens.removeToken();else if(this.reactHotLoaderTransformer){const e=this.nameManager.claimFreeName("_default");this.tokens.replaceToken(`let ${e}; exports.`),this.tokens.copyToken(),this.tokens.appendCode(` = ${e} =`),this.reactHotLoaderTransformer.setExtractedDefaultExportName(e)}else this.tokens.replaceToken("exports."),this.tokens.copyToken(),this.tokens.appendCode(" =");e&&(this.hadDefaultExport=!0)}copyDecorators(){for(;this.tokens.matches1(k.at);)if(this.tokens.copyToken(),this.tokens.matches1(k.parenL))this.tokens.copyExpectedToken(k.parenL),this.rootTransformer.processBalancedCode(),this.tokens.copyExpectedToken(k.parenR);else{for(this.tokens.copyExpectedToken(k.name);this.tokens.matches1(k.dot);)this.tokens.copyExpectedToken(k.dot),this.tokens.copyExpectedToken(k.name);this.tokens.matches1(k.parenL)&&(this.tokens.copyExpectedToken(k.parenL),this.rootTransformer.processBalancedCode(),this.tokens.copyExpectedToken(k.parenR))}}processExportVar(){this.isSimpleExportVar()?this.processSimpleExportVar():this.processComplexExportVar()}isSimpleExportVar(){let e=this.tokens.currentIndex();if(e++,e++,!this.tokens.matches1AtIndex(e,k.name))return!1;for(e++;e<this.tokens.tokens.length&&this.tokens.tokens[e].isType;)e++;return!!this.tokens.matches1AtIndex(e,k.eq)}processSimpleExportVar(){this.tokens.removeInitialToken(),this.tokens.copyToken();const e=this.tokens.identifierName();for(;!this.tokens.matches1(k.eq);)this.rootTransformer.processToken();const t=this.tokens.currentToken().rhsEndIndex;if(null==t)throw new Error("Expected = token with an end index.");for(;this.tokens.currentIndex()<t;)this.rootTransformer.processToken();this.tokens.appendCode(`; exports.${e} = ${e}`)}processComplexExportVar(){this.tokens.removeInitialToken(),this.tokens.removeToken();const e=this.tokens.matches1(k.braceL);e&&this.tokens.appendCode("(");let t=0;for(;;)if(this.tokens.matches1(k.braceL)||this.tokens.matches1(k.dollarBraceL)||this.tokens.matches1(k.bracketL))t++,this.tokens.copyToken();else if(this.tokens.matches1(k.braceR)||this.tokens.matches1(k.bracketR))t--,this.tokens.copyToken();else{if(0===t&&!this.tokens.matches1(k.name)&&!this.tokens.currentToken().isType)break;if(this.tokens.matches1(k.eq)){const e=this.tokens.currentToken().rhsEndIndex;if(null==e)throw new Error("Expected = token with an end index.");for(;this.tokens.currentIndex()<e;)this.rootTransformer.processToken()}else{const e=this.tokens.currentToken();if(Q(e)){const t=this.tokens.identifierName();let n=this.importProcessor.getIdentifierReplacement(t);if(null===n)throw new Error(`Expected a replacement for ${t} in \`export var\` syntax.`);se(e)&&(n=`${t}: ${n}`),this.tokens.replaceToken(n)}else this.rootTransformer.processToken()}}if(e){const e=this.tokens.currentToken().rhsEndIndex;if(null==e)throw new Error("Expected = token with an end index.");for(;this.tokens.currentIndex()<e;)this.rootTransformer.processToken();this.tokens.appendCode(")")}}processExportFunction(){this.tokens.replaceToken("");const e=this.processNamedFunction();this.tokens.appendCode(` exports.${e} = ${e};`)}processNamedFunction(){if(this.tokens.matches1(k._function))this.tokens.copyToken();else if(this.tokens.matches2(k.name,k._function)){if(!this.tokens.matchesContextual(m._async))throw new Error("Expected async keyword in function export.");this.tokens.copyToken(),this.tokens.copyToken()}if(this.tokens.matches1(k.star)&&this.tokens.copyToken(),!this.tokens.matches1(k.name))throw new Error("Expected identifier for exported function name.");const e=this.tokens.identifierName();if(this.tokens.copyToken(),this.tokens.currentToken().isType)for(this.tokens.removeInitialToken();this.tokens.currentToken().isType;)this.tokens.removeToken();return this.tokens.copyExpectedToken(k.parenL),this.rootTransformer.processBalancedCode(),this.tokens.copyExpectedToken(k.parenR),this.rootTransformer.processPossibleTypeRange(),this.tokens.copyExpectedToken(k.braceL),this.rootTransformer.processBalancedCode(),this.tokens.copyExpectedToken(k.braceR),e}processExportClass(){this.tokens.removeInitialToken(),this.copyDecorators(),this.tokens.matches1(k._abstract)&&this.tokens.removeToken();const e=this.rootTransformer.processNamedClass();this.tokens.appendCode(` exports.${e} = ${e};`)}processExportBindings(){this.tokens.removeInitialToken(),this.tokens.removeToken();const e=fo(this.tokens),t=[];for(;;){if(this.tokens.matches1(k.braceR)){this.tokens.removeToken();break}const n=Ne(this.tokens);for(;this.tokens.currentIndex()<n.endIndex;)this.tokens.removeToken();if(!(n.isType||!e&&this.shouldElideExportedIdentifier(n.leftName))){const e=n.rightName;"default"===e?this.hadDefaultExport=!0:this.hadNamedExport=!0;const s=n.leftName,o=this.importProcessor.getIdentifierReplacement(s);t.push(`exports.${e} = ${o||s};`)}if(this.tokens.matches1(k.braceR)){this.tokens.removeToken();break}if(this.tokens.matches2(k.comma,k.braceR)){this.tokens.removeToken(),this.tokens.removeToken();break}if(!this.tokens.matches1(k.comma))throw new Error(`Unexpected token: ${JSON.stringify(this.tokens.currentToken())}`);this.tokens.removeToken()}if(this.tokens.matchesContextual(m._from)){this.tokens.removeToken();const e=this.tokens.stringValue();this.tokens.replaceTokenTrimmingLeftWhitespace(this.importProcessor.claimImportCode(e)),mo(this.tokens)}else this.tokens.appendCode(t.join(" "));this.tokens.matches1(k.semi)&&this.tokens.removeToken()}processExportStar(){for(this.tokens.removeInitialToken();!this.tokens.matches1(k.string);)this.tokens.removeToken();const e=this.tokens.stringValue();this.tokens.replaceTokenTrimmingLeftWhitespace(this.importProcessor.claimImportCode(e)),mo(this.tokens),this.tokens.matches1(k.semi)&&this.tokens.removeToken()}shouldElideExportedIdentifier(e){return this.isTypeScriptTransformEnabled&&!this.keepUnusedImports&&!this.declarationInfo.valueDeclarations.has(e)}}class xo extends De{constructor(e,t,n,s,o,r,i,a){super(),this.tokens=e,this.nameManager=t,this.helperManager=n,this.reactHotLoaderTransformer=s,this.isTypeScriptTransformEnabled=o,this.isFlowTransformEnabled=r,this.keepUnusedImports=i,this.nonTypeIdentifiers=o&&!i?$e(e,a):new Set,this.declarationInfo=o&&!i?po(e):ho,this.injectCreateRequireForImportRequire=Boolean(a.injectCreateRequireForImportRequire)}process(){if(this.tokens.matches3(k._import,k.name,k.eq))return this.processImportEquals();if(this.tokens.matches4(k._import,k.name,k.name,k.eq)&&this.tokens.matchesContextualAtIndex(this.tokens.currentIndex()+1,m._type)){this.tokens.removeInitialToken();for(let e=0;e<7;e++)this.tokens.removeToken();return!0}if(this.tokens.matches2(k._export,k.eq))return this.tokens.replaceToken("module.exports"),!0;if(this.tokens.matches5(k._export,k._import,k.name,k.name,k.eq)&&this.tokens.matchesContextualAtIndex(this.tokens.currentIndex()+2,m._type)){this.tokens.removeInitialToken();for(let e=0;e<8;e++)this.tokens.removeToken();return!0}if(this.tokens.matches1(k._import))return this.processImport();if(this.tokens.matches2(k._export,k._default))return this.processExportDefault();if(this.tokens.matches2(k._export,k.braceL))return this.processNamedExports();if(this.tokens.matches2(k._export,k.name)&&this.tokens.matchesContextualAtIndex(this.tokens.currentIndex()+1,m._type)){if(this.tokens.removeInitialToken(),this.tokens.removeToken(),this.tokens.matches1(k.braceL)){for(;!this.tokens.matches1(k.braceR);)this.tokens.removeToken();this.tokens.removeToken()}else this.tokens.removeToken(),this.tokens.matches1(k._as)&&(this.tokens.removeToken(),this.tokens.removeToken());return this.tokens.matchesContextual(m._from)&&this.tokens.matches1AtIndex(this.tokens.currentIndex()+1,k.string)&&(this.tokens.removeToken(),this.tokens.removeToken(),mo(this.tokens)),!0}return!1}processImportEquals(){const e=this.tokens.identifierNameAtIndex(this.tokens.currentIndex()+1);return this.shouldAutomaticallyElideImportedName(e)?uo(this.tokens):this.injectCreateRequireForImportRequire?(this.tokens.replaceToken("const"),this.tokens.copyToken(),this.tokens.copyToken(),this.tokens.replaceToken(this.helperManager.getHelperName("require"))):this.tokens.replaceToken("const"),!0}processImport(){if(this.tokens.matches2(k._import,k.parenL))return!1;const e=this.tokens.snapshot();if(this.removeImportTypeBindings()){for(this.tokens.restoreToSnapshot(e);!this.tokens.matches1(k.string);)this.tokens.removeToken();this.tokens.removeToken(),mo(this.tokens),this.tokens.matches1(k.semi)&&this.tokens.removeToken()}return!0}removeImportTypeBindings(){if(this.tokens.copyExpectedToken(k._import),this.tokens.matchesContextual(m._type)&&!this.tokens.matches1AtIndex(this.tokens.currentIndex()+1,k.comma)&&!this.tokens.matchesContextualAtIndex(this.tokens.currentIndex()+1,m._from))return!0;if(this.tokens.matches1(k.string))return this.tokens.copyToken(),!1;this.tokens.matchesContextual(m._module)&&this.tokens.matchesContextualAtIndex(this.tokens.currentIndex()+2,m._from)&&this.tokens.copyToken();let e=!1,t=!1,n=!1;if(this.tokens.matches1(k.name)&&(this.shouldAutomaticallyElideImportedName(this.tokens.identifierName())?(this.tokens.removeToken(),this.tokens.matches1(k.comma)&&this.tokens.removeToken()):(e=!0,this.tokens.copyToken(),this.tokens.matches1(k.comma)&&(n=!0,this.tokens.removeToken()))),this.tokens.matches1(k.star))this.shouldAutomaticallyElideImportedName(this.tokens.identifierNameAtRelativeIndex(2))?(this.tokens.removeToken(),this.tokens.removeToken(),this.tokens.removeToken()):(n&&this.tokens.appendCode(","),e=!0,this.tokens.copyExpectedToken(k.star),this.tokens.copyExpectedToken(k.name),this.tokens.copyExpectedToken(k.name));else if(this.tokens.matches1(k.braceL)){for(n&&this.tokens.appendCode(","),this.tokens.copyToken();!this.tokens.matches1(k.braceR);){t=!0;const n=Ne(this.tokens);if(n.isType||this.shouldAutomaticallyElideImportedName(n.rightName)){for(;this.tokens.currentIndex()<n.endIndex;)this.tokens.removeToken();this.tokens.matches1(k.comma)&&this.tokens.removeToken()}else{for(e=!0;this.tokens.currentIndex()<n.endIndex;)this.tokens.copyToken();this.tokens.matches1(k.comma)&&this.tokens.copyToken()}}this.tokens.copyExpectedToken(k.braceR)}return!this.keepUnusedImports&&(this.isTypeScriptTransformEnabled?!e:!!this.isFlowTransformEnabled&&(t&&!e))}shouldAutomaticallyElideImportedName(e){return this.isTypeScriptTransformEnabled&&!this.keepUnusedImports&&!this.nonTypeIdentifiers.has(e)}processExportDefault(){if(ko(this.isTypeScriptTransformEnabled,this.keepUnusedImports,this.tokens,this.declarationInfo))return this.tokens.removeInitialToken(),this.tokens.removeToken(),this.tokens.removeToken(),!0;if(!(this.tokens.matches4(k._export,k._default,k._function,k.name)||this.tokens.matches5(k._export,k._default,k.name,k._function,k.name)&&this.tokens.matchesContextualAtIndex(this.tokens.currentIndex()+2,m._async)||this.tokens.matches4(k._export,k._default,k._class,k.name)||this.tokens.matches5(k._export,k._default,k._abstract,k._class,k.name))&&this.reactHotLoaderTransformer){const e=this.nameManager.claimFreeName("_default");return this.tokens.replaceToken(`let ${e}; export`),this.tokens.copyToken(),this.tokens.appendCode(` ${e} =`),this.reactHotLoaderTransformer.setExtractedDefaultExportName(e),!0}return!1}processNamedExports(){if(!this.isTypeScriptTransformEnabled)return!1;this.tokens.copyExpectedToken(k._export),this.tokens.copyExpectedToken(k.braceL);const e=fo(this.tokens);let t=!1;for(;!this.tokens.matches1(k.braceR);){const n=Ne(this.tokens);if(n.isType||!e&&this.shouldElideExportedName(n.leftName)){for(;this.tokens.currentIndex()<n.endIndex;)this.tokens.removeToken();this.tokens.matches1(k.comma)&&this.tokens.removeToken()}else{for(t=!0;this.tokens.currentIndex()<n.endIndex;)this.tokens.copyToken();this.tokens.matches1(k.comma)&&this.tokens.copyToken()}}return this.tokens.copyExpectedToken(k.braceR),this.keepUnusedImports||!e||t||(this.tokens.removeToken(),this.tokens.removeToken(),mo(this.tokens)),!0}shouldElideExportedName(e){return this.isTypeScriptTransformEnabled&&!this.keepUnusedImports&&this.declarationInfo.typeDeclarations.has(e)&&!this.declarationInfo.valueDeclarations.has(e)}}class _o extends De{constructor(e,t,n){super(),this.rootTransformer=e,this.tokens=t,this.isImportsTransformEnabled=n}process(){return!!(this.rootTransformer.processPossibleArrowParamEnd()||this.rootTransformer.processPossibleAsyncArrowWithTypeParams()||this.rootTransformer.processPossibleTypeRange())||(this.tokens.matches1(k._enum)?(this.processEnum(),!0):this.tokens.matches2(k._export,k._enum)?(this.processNamedExportEnum(),!0):!!this.tokens.matches3(k._export,k._default,k._enum)&&(this.processDefaultExportEnum(),!0))}processNamedExportEnum(){if(this.isImportsTransformEnabled){this.tokens.removeInitialToken();const e=this.tokens.identifierNameAtRelativeIndex(1);this.processEnum(),this.tokens.appendCode(` exports.${e} = ${e};`)}else this.tokens.copyToken(),this.processEnum()}processDefaultExportEnum(){this.tokens.removeInitialToken(),this.tokens.removeToken();const e=this.tokens.identifierNameAtRelativeIndex(1);this.processEnum(),this.isImportsTransformEnabled?this.tokens.appendCode(` exports.default = ${e};`):this.tokens.appendCode(` export default ${e};`)}processEnum(){this.tokens.replaceToken("const"),this.tokens.copyExpectedToken(k.name);let e=!1;this.tokens.matchesContextual(m._of)&&(this.tokens.removeToken(),e=this.tokens.matchesContextual(m._symbol),this.tokens.removeToken());const t=this.tokens.matches3(k.braceL,k.name,k.eq);this.tokens.appendCode(' = require("flow-enums-runtime")');const n=!e&&!t;for(this.tokens.replaceTokenTrimmingLeftWhitespace(n?".Mirrored([":"({");!this.tokens.matches1(k.braceR);){if(this.tokens.matches1(k.ellipsis)){this.tokens.removeToken();break}this.processEnumElement(e,t),this.tokens.matches1(k.comma)&&this.tokens.copyToken()}this.tokens.replaceToken(n?"]);":"});")}processEnumElement(e,t){if(e){const e=this.tokens.identifierName();this.tokens.copyToken(),this.tokens.appendCode(`: Symbol("${e}")`)}else t?(this.tokens.copyToken(),this.tokens.replaceTokenTrimmingLeftWhitespace(":"),this.tokens.copyToken()):this.tokens.replaceToken(`"${this.tokens.identifierName()}"`)}}const yo="jest",To=["mock","unmock","enableAutomock","disableAutomock"];class bo extends De{__init(){this.hoistedFunctionNames=[]}constructor(e,t,n,s){super(),this.rootTransformer=e,this.tokens=t,this.nameManager=n,this.importProcessor=s,bo.prototype.__init.call(this)}process(){return!(0!==this.tokens.currentToken().scopeDepth||!this.tokens.matches4(k.name,k.dot,k.name,k.parenL)||this.tokens.identifierName()!==yo)&&(!function(e){let t,n=e[0],s=1;for(;s<e.length;){const o=e[s],r=e[s+1];if(s+=2,("optionalAccess"===o||"optionalCall"===o)&&null==n)return;"access"===o||"optionalAccess"===o?(t=n,n=r(n)):"call"!==o&&"optionalCall"!==o||(n=r(((...e)=>n.call(t,...e))),t=void 0)}return n}([this,"access",e=>e.importProcessor,"optionalAccess",e=>e.getGlobalNames,"call",e=>e(),"optionalAccess",e=>e.has,"call",e=>e(yo)])&&this.extractHoistedCalls())}getHoistedCode(){return this.hoistedFunctionNames.length>0?this.hoistedFunctionNames.map((e=>`${e}();`)).join(""):""}extractHoistedCalls(){this.tokens.removeToken();let e=!1;for(;this.tokens.matches3(k.dot,k.name,k.parenL);){const t=this.tokens.identifierNameAtIndex(this.tokens.currentIndex()+1);if(To.includes(t)){const t=this.nameManager.claimFreeName("__jestHoist");this.hoistedFunctionNames.push(t),this.tokens.replaceToken(`function ${t}(){${yo}.`),this.tokens.copyToken(),this.tokens.copyToken(),this.rootTransformer.processBalancedCode(),this.tokens.copyExpectedToken(k.parenR),this.tokens.appendCode(";}"),e=!1}else e?this.tokens.copyToken():this.tokens.replaceToken(`${yo}.`),this.tokens.copyToken(),this.tokens.copyToken(),this.rootTransformer.processBalancedCode(),this.tokens.copyExpectedToken(k.parenR),e=!0}return!0}}class vo extends De{constructor(e){super(),this.tokens=e}process(){if(this.tokens.matches1(k.num)){const e=this.tokens.currentTokenCode();if(e.includes("_"))return this.tokens.replaceToken(e.replace(/_/g,"")),!0}return!1}}class Io extends De{constructor(e,t){super(),this.tokens=e,this.nameManager=t}process(){return!!this.tokens.matches2(k._catch,k.braceL)&&(this.tokens.copyToken(),this.tokens.appendCode(` (${this.nameManager.claimFreeName("e")})`),!0)}}class wo extends De{constructor(e,t){super(),this.tokens=e,this.nameManager=t}process(){if(this.tokens.matches1(k.nullishCoalescing)){const e=this.tokens.currentToken();return this.tokens.tokens[e.nullishStartIndex].isAsyncOperation?this.tokens.replaceTokenTrimmingLeftWhitespace(", async () => ("):this.tokens.replaceTokenTrimmingLeftWhitespace(", () => ("),!0}if(this.tokens.matches1(k._delete)){if(this.tokens.tokenAtRelativeIndex(1).isOptionalChainStart)return this.tokens.removeInitialToken(),!0}const e=this.tokens.currentToken().subscriptStartIndex;if(null!=e&&this.tokens.tokens[e].isOptionalChainStart&&this.tokens.tokenAtRelativeIndex(-1).type!==k._super){const t=this.nameManager.claimFreeName("_");let n;if(n=e>0&&this.tokens.matches1AtIndex(e-1,k._delete)&&this.isLastSubscriptInChain()?`${t} => delete ${t}`:`${t} => ${t}`,this.tokens.tokens[e].isAsyncOperation&&(n=`async ${n}`),this.tokens.matches2(k.questionDot,k.parenL)||this.tokens.matches2(k.questionDot,k.lessThan))this.justSkippedSuper()&&this.tokens.appendCode(".bind(this)"),this.tokens.replaceTokenTrimmingLeftWhitespace(`, 'optionalCall', ${n}`);else if(this.tokens.matches2(k.questionDot,k.bracketL))this.tokens.replaceTokenTrimmingLeftWhitespace(`, 'optionalAccess', ${n}`);else if(this.tokens.matches1(k.questionDot))this.tokens.replaceTokenTrimmingLeftWhitespace(`, 'optionalAccess', ${n}.`);else if(this.tokens.matches1(k.dot))this.tokens.replaceTokenTrimmingLeftWhitespace(`, 'access', ${n}.`);else if(this.tokens.matches1(k.bracketL))this.tokens.replaceTokenTrimmingLeftWhitespace(`, 'access', ${n}[`);else{if(!this.tokens.matches1(k.parenL))throw new Error("Unexpected subscript operator in optional chain.");this.justSkippedSuper()&&this.tokens.appendCode(".bind(this)"),this.tokens.replaceTokenTrimmingLeftWhitespace(`, 'call', ${n}(`)}return!0}return!1}isLastSubscriptInChain(){let e=0;for(let t=this.tokens.currentIndex()+1;;t++){if(t>=this.tokens.tokens.length)throw new Error("Reached the end of the code while finding the end of the access chain.");if(this.tokens.tokens[t].isOptionalChainStart?e++:this.tokens.tokens[t].isOptionalChainEnd&&e--,e<0)return!0;if(0===e&&null!=this.tokens.tokens[t].subscriptStartIndex)return!1}}justSkippedSuper(){let e=0,t=this.tokens.currentIndex()-1;for(;;){if(t<0)throw new Error("Reached the start of the code while finding the start of the access chain.");if(this.tokens.tokens[t].isOptionalChainStart?e--:this.tokens.tokens[t].isOptionalChainEnd&&e++,e<0)return!1;if(0===e&&null!=this.tokens.tokens[t].subscriptStartIndex)return this.tokens.tokens[t-1].type===k._super;t--}}}class Co extends De{constructor(e,t,n,s){super(),this.rootTransformer=e,this.tokens=t,this.importProcessor=n,this.options=s}process(){const e=this.tokens.currentIndex();if("createReactClass"===this.tokens.identifierName()){const t=this.importProcessor&&this.importProcessor.getIdentifierReplacement("createReactClass");return t?this.tokens.replaceToken(`(0, ${t})`):this.tokens.copyToken(),this.tryProcessCreateClassCall(e),!0}if(this.tokens.matches3(k.name,k.dot,k.name)&&"React"===this.tokens.identifierName()&&"createClass"===this.tokens.identifierNameAtIndex(this.tokens.currentIndex()+2)){const t=this.importProcessor&&this.importProcessor.getIdentifierReplacement("React")||"React";return t?(this.tokens.replaceToken(t),this.tokens.copyToken(),this.tokens.copyToken()):(this.tokens.copyToken(),this.tokens.copyToken(),this.tokens.copyToken()),this.tryProcessCreateClassCall(e),!0}return!1}tryProcessCreateClassCall(e){const t=this.findDisplayName(e);t&&this.classNeedsDisplayName()&&(this.tokens.copyExpectedToken(k.parenL),this.tokens.copyExpectedToken(k.braceL),this.tokens.appendCode(`displayName: '${t}',`),this.rootTransformer.processBalancedCode(),this.tokens.copyExpectedToken(k.braceR),this.tokens.copyExpectedToken(k.parenR))}findDisplayName(e){return e<2?null:this.tokens.matches2AtIndex(e-2,k.name,k.eq)||e>=2&&this.tokens.tokens[e-2].identifierRole===J.ObjectKey?this.tokens.identifierNameAtIndex(e-2):this.tokens.matches2AtIndex(e-2,k._export,k._default)?this.getDisplayNameFromFilename():null}getDisplayNameFromFilename(){const e=(this.options.filePath||"unknown").split("/"),t=e[e.length-1],n=t.lastIndexOf("."),s=-1===n?t:t.slice(0,n);return"index"===s&&e[e.length-2]?e[e.length-2]:s}classNeedsDisplayName(){let e=this.tokens.currentIndex();if(!this.tokens.matches2(k.parenL,k.braceL))return!1;const t=e+1,n=this.tokens.tokens[t].contextId;if(null==n)throw new Error("Expected non-null context ID on object open-brace.");for(;e<this.tokens.tokens.length;e++){const t=this.tokens.tokens[e];if(t.type===k.braceR&&t.contextId===n){e++;break}if("displayName"===this.tokens.identifierNameAtIndex(e)&&this.tokens.tokens[e].identifierRole===J.ObjectKey&&t.contextId===n)return!1}if(e===this.tokens.tokens.length)throw new Error("Unexpected end of input when processing React class.");return this.tokens.matches1AtIndex(e,k.parenR)||this.tokens.matches2AtIndex(e,k.comma,k.parenR)}}class Ao extends De{__init(){this.extractedDefaultExportName=null}constructor(e,t){super(),this.tokens=e,this.filePath=t,Ao.prototype.__init.call(this)}setExtractedDefaultExportName(e){this.extractedDefaultExportName=e}getPrefixCode(){return"\n (function () {\n var enterModule = require('react-hot-loader').enterModule;\n enterModule && enterModule(module);\n })();".replace(/\s+/g," ").trim()}getSuffixCode(){const e=new Set;for(const n of this.tokens.tokens)!n.isType&&ee(n)&&n.identifierRole!==J.ImportDeclaration&&e.add(this.tokens.identifierNameForToken(n));const t=Array.from(e).map((e=>({variableName:e,uniqueLocalName:e})));return this.extractedDefaultExportName&&t.push({variableName:this.extractedDefaultExportName,uniqueLocalName:"default"}),`\n;(function () {\n var reactHotLoader = require('react-hot-loader').default;\n var leaveModule = require('react-hot-loader').leaveModule;\n if (!reactHotLoader) {\n return;\n }\n${t.map((({variableName:e,uniqueLocalName:t})=>` reactHotLoader.register(${e}, "${t}", ${JSON.stringify(this.filePath||"")});`)).join("\n")}\n leaveModule(module);\n})();`}process(){return!1}}const Eo=new Set(["break","case","catch","class","const","continue","debugger","default","delete","do","else","export","extends","finally","for","function","if","import","in","instanceof","new","return","super","switch","this","throw","try","typeof","var","void","while","with","yield","enum","implements","interface","let","package","private","protected","public","static","await","false","null","true"]);function So(e){if(0===e.length)return!1;if(!G[e.charCodeAt(0)])return!1;for(let t=1;t<e.length;t++)if(!z[e.charCodeAt(t)])return!1;return!Eo.has(e)}class No extends De{constructor(e,t,n){super(),this.rootTransformer=e,this.tokens=t,this.isImportsTransformEnabled=n}process(){return!!(this.rootTransformer.processPossibleArrowParamEnd()||this.rootTransformer.processPossibleAsyncArrowWithTypeParams()||this.rootTransformer.processPossibleTypeRange())||(this.tokens.matches1(k._public)||this.tokens.matches1(k._protected)||this.tokens.matches1(k._private)||this.tokens.matches1(k._abstract)||this.tokens.matches1(k._readonly)||this.tokens.matches1(k._override)||this.tokens.matches1(k.nonNullAssertion)?(this.tokens.removeInitialToken(),!0):this.tokens.matches1(k._enum)||this.tokens.matches2(k._const,k._enum)?(this.processEnum(),!0):!(!this.tokens.matches2(k._export,k._enum)&&!this.tokens.matches3(k._export,k._const,k._enum))&&(this.processEnum(!0),!0))}processEnum(e=!1){for(this.tokens.removeInitialToken();this.tokens.matches1(k._const)||this.tokens.matches1(k._enum);)this.tokens.removeToken();const t=this.tokens.identifierName();this.tokens.removeToken(),e&&!this.isImportsTransformEnabled&&this.tokens.appendCode("export "),this.tokens.appendCode(`var ${t}; (function (${t})`),this.tokens.copyExpectedToken(k.braceL),this.processEnumBody(t),this.tokens.copyExpectedToken(k.braceR),e&&this.isImportsTransformEnabled?this.tokens.appendCode(`)(${t} || (exports.${t} = ${t} = {}));`):this.tokens.appendCode(`)(${t} || (${t} = {}));`)}processEnumBody(e){let t=null;for(;!this.tokens.matches1(k.braceR);){const{nameStringCode:n,variableName:s}=this.extractEnumKeyInfo(this.tokens.currentToken());this.tokens.removeInitialToken(),this.tokens.matches3(k.eq,k.string,k.comma)||this.tokens.matches3(k.eq,k.string,k.braceR)?this.processStringLiteralEnumMember(e,n,s):this.tokens.matches1(k.eq)?this.processExplicitValueEnumMember(e,n,s):this.processImplicitValueEnumMember(e,n,s,t),this.tokens.matches1(k.comma)&&this.tokens.removeToken(),t=null!=s?s:`${e}[${n}]`}}extractEnumKeyInfo(e){if(e.type===k.name){const t=this.tokens.identifierNameForToken(e);return{nameStringCode:`"${t}"`,variableName:So(t)?t:null}}if(e.type===k.string){const t=this.tokens.stringValueForToken(e);return{nameStringCode:this.tokens.code.slice(e.start,e.end),variableName:So(t)?t:null}}throw new Error("Expected name or string at beginning of enum element.")}processStringLiteralEnumMember(e,t,n){null!=n?(this.tokens.appendCode(`const ${n}`),this.tokens.copyToken(),this.tokens.copyToken(),this.tokens.appendCode(`; ${e}[${t}] = ${n};`)):(this.tokens.appendCode(`${e}[${t}]`),this.tokens.copyToken(),this.tokens.copyToken(),this.tokens.appendCode(";"))}processExplicitValueEnumMember(e,t,n){const s=this.tokens.currentToken().rhsEndIndex;if(null==s)throw new Error("Expected rhsEndIndex on enum assign.");if(null!=n){for(this.tokens.appendCode(`const ${n}`),this.tokens.copyToken();this.tokens.currentIndex()<s;)this.rootTransformer.processToken();this.tokens.appendCode(`; ${e}[${e}[${t}] = ${n}] = ${t};`)}else{for(this.tokens.appendCode(`${e}[${e}[${t}]`),this.tokens.copyToken();this.tokens.currentIndex()<s;)this.rootTransformer.processToken();this.tokens.appendCode(`] = ${t};`)}}processImplicitValueEnumMember(e,t,n,s){let o=null!=s?`${s} + 1`:"0";null!=n&&(this.tokens.appendCode(`const ${n} = ${o}; `),o=n),this.tokens.appendCode(`${e}[${e}[${t}] = ${o}] = ${t};`)}}class jo{__init(){this.transformers=[]}__init2(){this.generatedVariables=[]}constructor(e,t,n,s){jo.prototype.__init.call(this),jo.prototype.__init2.call(this),this.nameManager=e.nameManager,this.helperManager=e.helperManager;const{tokenProcessor:o,importProcessor:r}=e;this.tokens=o,this.isImportsTransformEnabled=t.includes("imports"),this.isReactHotLoaderTransformEnabled=t.includes("react-hot-loader"),this.disableESTransforms=Boolean(s.disableESTransforms),s.disableESTransforms||(this.transformers.push(new wo(o,this.nameManager)),this.transformers.push(new vo(o)),this.transformers.push(new Io(o,this.nameManager))),t.includes("jsx")&&("preserve"!==s.jsxRuntime&&this.transformers.push(new Pe(this,o,r,this.nameManager,s)),this.transformers.push(new Co(this,o,r,s)));let i=null;if(t.includes("react-hot-loader")){if(!s.filePath)throw new Error("filePath is required when using the react-hot-loader transform.");i=new Ao(o,s.filePath),this.transformers.push(i)}if(t.includes("imports")){if(null===r)throw new Error("Expected non-null importProcessor with imports transform enabled.");this.transformers.push(new go(this,o,r,this.nameManager,this.helperManager,i,n,Boolean(s.enableLegacyTypeScriptModuleInterop),t.includes("typescript"),t.includes("flow"),Boolean(s.preserveDynamicImport),Boolean(s.keepUnusedImports)))}else this.transformers.push(new xo(o,this.nameManager,this.helperManager,i,t.includes("typescript"),t.includes("flow"),Boolean(s.keepUnusedImports),s));t.includes("flow")&&this.transformers.push(new _o(this,o,t.includes("imports"))),t.includes("typescript")&&this.transformers.push(new No(this,o,t.includes("imports"))),t.includes("jest")&&this.transformers.push(new bo(this,o,this.nameManager,r))}transform(){this.tokens.reset(),this.processBalancedCode();let e=this.isImportsTransformEnabled?'"use strict";':"";for(const o of this.transformers)e+=o.getPrefixCode();e+=this.helperManager.emitHelpers(),e+=this.generatedVariables.map((e=>` var ${e};`)).join("");for(const o of this.transformers)e+=o.getHoistedCode();let t="";for(const o of this.transformers)t+=o.getSuffixCode();const n=this.tokens.finish();let{code:s}=n;if(s.startsWith("#!")){let o=s.indexOf("\n");return-1===o&&(o=s.length,s+="\n"),{code:s.slice(0,o+1)+e+s.slice(o+1)+t,mappings:this.shiftMappings(n.mappings,e.length)}}return{code:e+s+t,mappings:this.shiftMappings(n.mappings,e.length)}}processBalancedCode(){let e=0,t=0;for(;!this.tokens.isAtEnd();){if(this.tokens.matches1(k.braceL)||this.tokens.matches1(k.dollarBraceL))e++;else if(this.tokens.matches1(k.braceR)){if(0===e)return;e--}if(this.tokens.matches1(k.parenL))t++;else if(this.tokens.matches1(k.parenR)){if(0===t)return;t--}this.processToken()}}processToken(){if(this.tokens.matches1(k._class))this.processClass();else{for(const e of this.transformers){if(e.process())return}this.tokens.copyToken()}}processNamedClass(){if(!this.tokens.matches2(k._class,k.name))throw new Error("Expected identifier for exported class name.");const e=this.tokens.identifierNameAtIndex(this.tokens.currentIndex()+1);return this.processClass(),e}processClass(){const e=ro(this,this.tokens,this.nameManager,this.disableESTransforms),t=(e.headerInfo.isExpression||!e.headerInfo.className)&&e.staticInitializerNames.length+e.instanceInitializerNames.length>0;let n=e.headerInfo.className;t&&(n=this.nameManager.claimFreeName("_class"),this.generatedVariables.push(n),this.tokens.appendCode(` (${n} =`));const s=this.tokens.currentToken().contextId;if(null==s)throw new Error("Expected class to have a context ID.");for(this.tokens.copyExpectedToken(k._class);!this.tokens.matchesContextIdAndLabel(k.braceL,s);)this.processToken();this.processClassBody(e,n);const o=e.staticInitializerNames.map((e=>`${n}.${e}()`));t?this.tokens.appendCode(`, ${o.map((e=>`${e}, `)).join("")}${n})`):e.staticInitializerNames.length>0&&this.tokens.appendCode(` ${o.map((e=>`${e};`)).join(" ")}`)}processClassBody(e,t){const{headerInfo:n,constructorInsertPos:s,constructorInitializerStatements:o,fields:r,instanceInitializerNames:i,rangesToRemove:a}=e;let c=0,l=0;const u=this.tokens.currentToken().contextId;if(null==u)throw new Error("Expected non-null context ID on class.");this.tokens.copyExpectedToken(k.braceL),this.isReactHotLoaderTransformEnabled&&this.tokens.appendCode("__reactstandin__regenerateByEval(key, code) {this[key] = eval(code);}");const h=o.length+i.length>0;if(null===s&&h){const e=this.makeConstructorInitCode(o,i,t);if(n.hasSuperclass){const t=this.nameManager.claimFreeName("args");this.tokens.appendCode(`constructor(...${t}) { super(...${t}); ${e}; }`)}else this.tokens.appendCode(`constructor() { ${e}; }`)}for(;!this.tokens.matchesContextIdAndLabel(k.braceR,u);)if(c<r.length&&this.tokens.currentIndex()===r[c].start){let e=!1;for(this.tokens.matches1(k.bracketL)?this.tokens.copyTokenWithPrefix(`${r[c].initializerName}() {this`):this.tokens.matches1(k.string)||this.tokens.matches1(k.num)?(this.tokens.copyTokenWithPrefix(`${r[c].initializerName}() {this[`),e=!0):this.tokens.copyTokenWithPrefix(`${r[c].initializerName}() {this.`);this.tokens.currentIndex()<r[c].end;)e&&this.tokens.currentIndex()===r[c].equalsIndex&&this.tokens.appendCode("]"),this.processToken();this.tokens.appendCode("}"),c++}else if(l<a.length&&this.tokens.currentIndex()>=a[l].start){for(this.tokens.currentIndex()<a[l].end&&this.tokens.removeInitialToken();this.tokens.currentIndex()<a[l].end;)this.tokens.removeToken();l++}else this.tokens.currentIndex()===s?(this.tokens.copyToken(),h&&this.tokens.appendCode(`;${this.makeConstructorInitCode(o,i,t)};`),this.processToken()):this.processToken();this.tokens.copyExpectedToken(k.braceR)}makeConstructorInitCode(e,t,n){return[...e,...t.map((e=>`${n}.prototype.${e}.call(this)`))].join(";")}processPossibleArrowParamEnd(){if(this.tokens.matches2(k.parenR,k.colon)&&this.tokens.tokenAtRelativeIndex(1).isType){let e=this.tokens.currentIndex()+1;for(;this.tokens.tokens[e].isType;)e++;if(this.tokens.matches1AtIndex(e,k.arrow)){for(this.tokens.removeInitialToken();this.tokens.currentIndex()<e;)this.tokens.removeToken();return this.tokens.replaceTokenTrimmingLeftWhitespace(") =>"),!0}}return!1}processPossibleAsyncArrowWithTypeParams(){if(!this.tokens.matchesContextual(m._async)&&!this.tokens.matches1(k._async))return!1;const e=this.tokens.tokenAtRelativeIndex(1);if(e.type!==k.lessThan||!e.isType)return!1;let 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It tests whether two samples come from the same population distribution. To conduct a permutation test:"]}),(0,s.jsxs)(t.ol,{children:["\n",(0,s.jsx)(t.li,{children:"Shuffle the group labels (i.e. the Trues and Falses) to generate two new samples under the null."}),"\n",(0,s.jsx)(t.li,{children:"Compute the test statistic (i.e. the difference in group means)."}),"\n",(0,s.jsx)(t.li,{children:"Repeat steps 1 and 2 to generate an empirical distribution of the test statistics (i.e. the difference in group means)."}),"\n",(0,s.jsx)(t.li,{children:"See where the observed statistic lies in the empirical distribution. If, in our simulations, we rarely saw a difference in group means as extreme as the observed difference in group means, we have evidence to reject the null."}),"\n"]})]}),"\n",(0,s.jsx)(t.admonition,{type:"note",children:(0,s.jsx)(t.p,{children:"While shuffling, the size of the two new samples should be the same as the observed samples."})}),"\n",(0,s.jsxs)(t.p,{children:["The diagram below provides an overview of conducting a permutation test, although it references a different dataset. ",(0,s.jsx)(t.a,{href:"https://www.jwilber.me/permutationtest/",children:"Here"})," is another useful visualization. For additional helpful visual guides, please visit the ",(0,s.jsx)(t.a,{href:"https://dsc10.com/diagrams/",children:"Diagrams"})," site."]}),"\n",(0,s.jsx)(r.A,{src:"https://docs.google.com/presentation/d/e/2PACX-1vSovXDonR6EmjrT45h4pY1mwmcKFMWVSdgpbKHC5HNTm9sbG7dojvvCDEQCjuk2dk1oA4gmwMogr8ZL/embed?start=true&loop=false&delayms=3000&rm=minimal",sourceLink:"https://docs.google.com/presentation/d/1TTWoQ7FU4tzBGc7EskF6WYccIn1BWQbTSizAiFc2p2o/edit?usp=sharing"}),"\n",(0,s.jsx)(t.hr,{}),"\n",(0,s.jsx)(t.h2,{id:"code-example",children:"Code Example"}),"\n",(0,s.jsx)(t.h3,{id:"1-state-the-questionhypothesis",children:"1. State the question/hypothesis"}),"\n",(0,s.jsxs)(t.admonition,{title:"Hypotheses",type:"info",children:[(0,s.jsx)(t.p,{children:"We will test the following pair of hypotheses at the standard p = 0.05 significance level:"}),(0,s.jsxs)(t.ul,{children:["\n",(0,s.jsxs)(t.li,{children:[(0,s.jsx)(t.strong,{children:"Null Hypothesis:"})," In the population, weights of dogs and cats have the ",(0,s.jsx)(t.strong,{children:"same"})," distribution, and the observed differences in our samples are due to random chance."]}),"\n",(0,s.jsxs)(t.li,{children:[(0,s.jsx)(t.strong,{children:"Alternative Hypothesis:"})," In the population, dogs and cats have ",(0,s.jsx)(t.strong,{children:"different"})," weights, on average. The observed differences in our samples cannot be explained by random chance alone."]}),"\n"]})]}),"\n",(0,s.jsxs)(t.p,{children:['Since the alternative hypothesis is of the form "A and B are different," the ',(0,s.jsx)(t.strong,{children:"test statistic"})," should measure distance and use an absolute value."]}),"\n",(0,s.jsxs)(t.p,{children:[(0,s.jsxs)(t.span,{className:"katex",children:[(0,s.jsx)(t.span,{className:"katex-mathml",children:(0,s.jsx)(t.math,{xmlns:"http://www.w3.org/1998/Math/MathML",children:(0,s.jsxs)(t.semantics,{children:[(0,s.jsx)(t.mrow,{children:(0,s.jsx)(t.mo,{children:"\u2234"})}),(0,s.jsx)(t.annotation,{encoding:"application/x-tex",children:"\\therefore"})]})})}),(0,s.jsx)(t.span,{className:"katex-html","aria-hidden":"true",children:(0,s.jsxs)(t.span,{className:"base",children:[(0,s.jsx)(t.span,{className:"strut",style:{height:"0.6922em"}}),(0,s.jsx)(t.span,{className:"mrel amsrm",children:"\u2234"})]})})]})," We use ",(0,s.jsx)(t.strong,{children:"absolute difference in group means"})," as the test statistic."]}),"\n",(0,s.jsx)(t.hr,{}),"\n",(0,s.jsx)(t.h3,{id:"2-query-the-dataframe",children:"2. Query the DataFrame"}),"\n",(0,s.jsx)(t.p,{children:"Since we want to compare the distributions of only cats and dogs, we need to make sure to only include the relevant pieces of data (e.g., cats and dogs weights)."}),"\n",(0,s.jsx)(t.pre,{children:(0,s.jsx)(t.code,{className:"language-python",children:"# Create a boolean Series that references which rows fulfill either condition.\nquerying_condition = (full_pets.get('Species') == 'dog') | (full_pets.get('Species') == 'cat')\n# Query.\ncats_dogs = full_pets[querying_condition]\n# Display the first 5 rows only.\ncats_dogs.take(np.arange(5)) \n"})}),"\n",(0,s.jsx)(a.A,{data:'{"columns":["ID","Species","Color","Weight","Age","Is_Cat","Owner_Comment"],"index":[0,1,2,3,4],"data":[["dog_001","dog","black",40.0,5.0,false," There are no bad dogs, only bad owners."],["cat_001","cat","golden",1.5,0.2,true,"My best birthday present ever!!!"],["cat_002","cat","black",15.0,9.0,true,"****All you need is love and a cat.****"],["dog_002","dog","white",80.0,2.0,false,"Love is a wet nose and a wagging tail."],["dog_003","dog","black",25.0,0.5,false,"Be the person your dog thinks you are."]]}'}),"\n",(0,s.jsx)(t.hr,{}),"\n",(0,s.jsx)(t.h3,{id:"3-create-a-function-to-calculate-test-statistic",children:"3. Create a function to calculate test statistic"}),"\n",(0,s.jsx)(t.p,{children:"Since our hypotheses depend on the test statistic, create a function to be able to calculate it during every trial of our permutation test."}),"\n",(0,s.jsx)(t.pre,{children:(0,s.jsx)(t.code,{className:"language-python",children:"def difference_in_means(cats_dogs):\n \"\"\"\n Calculate the absolute difference in the mean weight of dogs and cats.\n ---\n Input:\n cats_dogs: a DataFrame containing the columns 'Species' and 'Weight'.\n ---\n Output:\n The absolute difference in the mean weight of dogs and cats.\n \"\"\"\n means = cats_dogs.groupby('Species').mean()\n return np.abs((means.get('Weight').loc['dog'] - means.get('Weight').loc['cat']))\n"})}),"\n",(0,s.jsx)(t.p,{children:(0,s.jsx)(t.em,{children:"Note: Although we can simply do this in the for-loop shown in the next step, we can practice good coding habits by separating our code into readable bits!"})}),"\n",(0,s.jsx)(t.hr,{}),"\n",(0,s.jsx)(t.h3,{id:"4-simulate-the-permutation-test",children:"4. Simulate the permutation test"}),"\n",(0,s.jsx)(t.pre,{children:(0,s.jsx)(t.code,{className:"language-python",children:"n = 500 # Number of simulations.\nstatistics = np.array([]) # Array to keep track of the difference in means for each iteration.\nfor i in np.arange(n): # Run the simulation `n` number of times\n # 1. Shuffle the species.\n shuffled = cats_dogs.assign(Species=np.random.permutation(cats_dogs.get('Species')))\n\n # 2. Compute the test statistic.\n statistic = difference_in_means(shuffled)\n\n # 3. Save the result.\n statistics = np.append(statistics, statistic)\n"})}),"\n",(0,s.jsxs)(t.p,{children:["This code will run the permutation test 500 times, but a different reasonable number can be used instead. It is ",(0,s.jsx)(t.strong,{children:"crucial"})," to keep track of the difference in means each time our for-loop runs so that the number of simulated values can be displayed."]}),"\n",(0,s.jsx)(t.hr,{}),"\n",(0,s.jsx)(t.h3,{id:"5-conclusion",children:"5. Conclusion"}),"\n",(0,s.jsx)(t.pre,{children:(0,s.jsx)(t.code,{className:"language-python",children:'observed = difference_in_means(cats_dogs)\np_value = np.count_nonzero(statistics >= observed) / n\n\nprint("The observed value of the test statistic is:", observed)\nprint("The p-value is:", p_value)\n'})}),"\n",(0,s.jsxs)(t.p,{children:[(0,s.jsx)(t.strong,{children:"The observed value of the test statistic is: 30.361111111111107"})," ",(0,s.jsx)("br",{}),"\n",(0,s.jsx)(t.strong,{children:"The p-value is: 0.004"})]}),"\n",(0,s.jsx)(t.p,{children:"Using a significance level of 0.05:"}),"\n",(0,s.jsx)(t.admonition,{title:"Conclusion",type:"info",children:(0,s.jsxs)(t.ul,{children:["\n",(0,s.jsx)(t.li,{children:"Under the null hypothesis, we rarely see a difference greater than the observed value."}),"\n",(0,s.jsxs)(t.li,{children:["Therefore, we ",(0,s.jsx)(t.strong,{children:"reject"})," the null hypothesis: the evidence implies that the two groups do not come from the same distribution."]}),"\n",(0,s.jsx)(t.li,{children:"Still, we cannot conclude that species causes a different weight because there may be other confounding variables."}),"\n"]})}),"\n",(0,s.jsx)(t.hr,{}),"\n",(0,s.jsx)(t.h3,{id:"6-extra",children:"6. Extra"}),"\n",(0,s.jsx)(t.p,{children:"Let's see how our observed statistic compares to the overall simulated values!"}),"\n",(0,s.jsx)(t.pre,{children:(0,s.jsx)(t.code,{className:"language-python",children:"# Create the histogram.\nbpd.DataFrame().assign(statistics=statistics).plot(kind='hist', bins=20, density=True, ec='w')\n# Don't worry about this line - you won't need to know it for this course!\nplt.axvline(x=observed, c='black', linewidth=4, label='population difference in means')\n"})}),"\n",(0,s.jsx)(t.p,{children:(0,s.jsx)(t.img,{alt:"Distribution",src:n(8803).A+"",width:"576",height:"413"})}),"\n",(0,s.jsxs)(t.p,{children:["From this graph, we can tell that there is barely any data to the ",(0,s.jsx)(t.strong,{children:"right"})," of the black vertical line (our observed test statistic), meaning we have a very low p-value!"]})]})}function p(e={}){const{wrapper:t}={...(0,i.R)(),...e.components};return t?(0,s.jsx)(t,{...e,children:(0,s.jsx)(u,{...e})}):u(e)}},8597:(e,t,n)=>{n.d(t,{A:()=>i});n(6540);var s=n(4848);const i=e=>{let{data:t}=e,n=[],i=[],a="",r=[];if(t){const e=JSON.parse(t);n=e.columns||[],i=e.data||[],a=e.indexName||"Index",r=e.index||[]}return(0,s.jsx)("div",{className:"dataframe-container",children:(0,s.jsxs)("table",{className:"dataframe-table",children:[(0,s.jsx)("thead",{children:(0,s.jsxs)("tr",{children:[(0,s.jsx)("th",{children:a}),n.map(((e,t)=>(0,s.jsx)("th",{children:e},t)))]})}),(0,s.jsx)("tbody",{children:i.map(((e,t)=>(0,s.jsxs)("tr",{children:[(0,s.jsx)("td",{className:"index-value",children:r[t]}),e.map(((e,t)=>{return(0,s.jsx)("td",{children:(n=e,"boolean"==typeof n?n.toString().charAt(0).toUpperCase()+n.toString().slice(1):n)},t);var n}))]},t)))})]})})}},5158:(e,t,n)=>{n.d(t,{A:()=>a});var s=n(6540),i=n(4848);const a=function(e){let{src:t,sourceLink:n,width:a="100%",height:r="100%",paddingBottom:o="56.25%"}=e;const[l,c]=(0,s.useState)(0);return(0,i.jsxs)(i.Fragment,{children:[(0,i.jsx)("div",{style:{position:"relative",height:"0",paddingBottom:o,overflow:"hidden",maxWidth:"100%"},children:(0,i.jsx)("iframe",{src:t,style:{position:"absolute",top:0,left:0,width:a,height:r,frameBorder:"0",allowFullScreen:!0}},l)}),(0,i.jsx)("div",{style:{display:"flex",justifyContent:"center",margin:"20px 0"},children:(0,i.jsx)("a",{href:n,target:"_blank",rel:"noopener noreferrer",children:"(Source)"})}),(0,i.jsx)("div",{style:{display:"flex",justifyContent:"center",margin:"10px 0"},children:(0,i.jsx)("button",{onClick:()=>{c((e=>e+1))},style:{backgroundColor:"#4CAF50",color:"white",padding:"10px 20px",border:"none",borderRadius:"5px",cursor:"pointer",outline:"none",fontSize:"16px",fontWeight:"bold",boxShadow:"0 4px 8px rgba(0,0,0,0.1)",transition:"background-color 0.3s"},onMouseOver:e=>e.currentTarget.style.backgroundColor="#45a049",onMouseOut:e=>e.currentTarget.style.backgroundColor="#4CAF50",children:"Restart Diagram"})})]})}},8803:(e,t,n)=>{n.d(t,{A:()=>s});const s=n.p+"assets/images/permutation-test-fae4df12733e667b05989b96bf08d9a9.png"},8453:(e,t,n)=>{n.d(t,{R:()=>r,x:()=>o});var s=n(6540);const i={},a=s.createContext(i);function r(e){const t=s.useContext(a);return s.useMemo((function(){return"function"==typeof e?e(t):{...t,...e}}),[t,e])}function o(e){let t;return t=e.disableParentContext?"function"==typeof e.components?e.components(i):e.components||i:r(e.components),s.createElement(a.Provider,{value:t},e.children)}}}]); \ No newline at end of file +"use strict";(self.webpackChunkbpd_reference=self.webpackChunkbpd_reference||[]).push([[9894],{6171:(e,t,n)=>{n.r(t),n.d(t,{assets:()=>d,contentTitle:()=>l,default:()=>p,frontMatter:()=>o,metadata:()=>c,toc:()=>h});var s=n(4848),i=n(8453),a=n(8597),r=n(5158);const o={sidebar_position:7,sidebar_label:"Permutation Test",title:"Permutation Test",tags:["querying","functions","for-loop","histogram"]},l=void 0,c={id:"statistical-inference/permutation_test",title:"Permutation Test",description:"Concept",source:"@site/docs/statistical-inference/permutation_test.md",sourceDirName:"statistical-inference",slug:"/statistical-inference/permutation_test",permalink:"/bpd-reference/docs/statistical-inference/permutation_test",draft:!1,unlisted:!1,editUrl:"https://github.com/dsc-courses/bpd-reference/tree/main/docs/statistical-inference/permutation_test.md",tags:[{label:"querying",permalink:"/bpd-reference/docs/tags/querying"},{label:"functions",permalink:"/bpd-reference/docs/tags/functions"},{label:"for-loop",permalink:"/bpd-reference/docs/tags/for-loop"},{label:"histogram",permalink:"/bpd-reference/docs/tags/histogram"}],version:"current",sidebarPosition:7,frontMatter:{sidebar_position:7,sidebar_label:"Permutation Test",title:"Permutation Test",tags:["querying","functions","for-loop","histogram"]},sidebar:"statsSidebar",previous:{title:"Hypothesis Test",permalink:"/bpd-reference/docs/statistical-inference/hypothesis_test"},next:{title:"The Standard Normal Distribution",permalink:"/bpd-reference/docs/statistical-inference/standard_normal_distribution"}},d={},h=[{value:"Concept",id:"concept",level:2},{value:"Code Example",id:"code-example",level:2},{value:"1. State the question/hypothesis",id:"1-state-the-questionhypothesis",level:3},{value:"2. Query the DataFrame",id:"2-query-the-dataframe",level:3},{value:"3. Create a function to calculate test statistic",id:"3-create-a-function-to-calculate-test-statistic",level:3},{value:"4. Simulate the permutation test",id:"4-simulate-the-permutation-test",level:3},{value:"5. Conclusion",id:"5-conclusion",level:3},{value:"6. Extra",id:"6-extra",level:3}];function u(e){const t={a:"a",admonition:"admonition",annotation:"annotation",code:"code",em:"em",h2:"h2",h3:"h3",hr:"hr",img:"img",li:"li",math:"math",mo:"mo",mrow:"mrow",ol:"ol",p:"p",pre:"pre",semantics:"semantics",span:"span",strong:"strong",ul:"ul",...(0,i.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(t.h2,{id:"concept",children:"Concept"}),"\n",(0,s.jsx)(t.admonition,{title:"Key Idea",type:"tip",children:(0,s.jsx)(t.p,{children:"We use a permutation test to test whether two samples are drawn from the same population."})}),"\n",(0,s.jsxs)(t.admonition,{title:"Terminology",type:"info",children:[(0,s.jsxs)(t.p,{children:[(0,s.jsx)(t.strong,{children:"Permutation"}),": A permutation of a sequence is a rearrangement of the elements in that sequence."]}),(0,s.jsxs)(t.ul,{children:["\n",(0,s.jsx)(t.li,{children:"Example: 'BAC' and 'CAB' are both permutations of the string 'ABC'."}),"\n",(0,s.jsx)(t.li,{children:"We create permutations by shuffling."}),"\n"]}),(0,s.jsxs)(t.p,{children:[(0,s.jsx)(t.strong,{children:"Permutation tests:"})," A permutation test is a type of A/B test (and a type of hypothesis test). It tests whether two samples come from the same population distribution. To conduct a permutation test:"]}),(0,s.jsxs)(t.ol,{children:["\n",(0,s.jsx)(t.li,{children:"Shuffle the group labels (i.e. the Trues and Falses) to generate two new samples under the null."}),"\n",(0,s.jsx)(t.li,{children:"Compute the test statistic (i.e. the difference in group means)."}),"\n",(0,s.jsx)(t.li,{children:"Repeat steps 1 and 2 to generate an empirical distribution of the test statistics (i.e. the difference in group means)."}),"\n",(0,s.jsx)(t.li,{children:"See where the observed statistic lies in the empirical distribution. If, in our simulations, we rarely saw a difference in group means as extreme as the observed difference in group means, we have evidence to reject the null."}),"\n"]})]}),"\n",(0,s.jsx)(t.admonition,{type:"note",children:(0,s.jsx)(t.p,{children:"While shuffling, the size of the two new samples should be the same as the observed samples."})}),"\n",(0,s.jsxs)(t.p,{children:["The diagram below provides an overview of conducting a permutation test, although it references a different dataset. ",(0,s.jsx)(t.a,{href:"https://www.jwilber.me/permutationtest/",children:"Here"})," is another useful visualization. For additional helpful visual guides, please visit the ",(0,s.jsx)(t.a,{href:"https://dsc10.com/diagrams/",children:"Diagrams"})," site."]}),"\n",(0,s.jsx)(r.A,{src:"https://docs.google.com/presentation/d/e/2PACX-1vSovXDonR6EmjrT45h4pY1mwmcKFMWVSdgpbKHC5HNTm9sbG7dojvvCDEQCjuk2dk1oA4gmwMogr8ZL/embed?start=true&loop=false&delayms=3000&rm=minimal",sourceLink:"https://docs.google.com/presentation/d/1TTWoQ7FU4tzBGc7EskF6WYccIn1BWQbTSizAiFc2p2o/edit?usp=sharing"}),"\n",(0,s.jsx)(t.hr,{}),"\n",(0,s.jsx)(t.h2,{id:"code-example",children:"Code Example"}),"\n",(0,s.jsx)(t.h3,{id:"1-state-the-questionhypothesis",children:"1. State the question/hypothesis"}),"\n",(0,s.jsxs)(t.admonition,{title:"Hypotheses",type:"info",children:[(0,s.jsx)(t.p,{children:"We will test the following pair of hypotheses at the standard p = 0.05 significance level:"}),(0,s.jsxs)(t.ul,{children:["\n",(0,s.jsxs)(t.li,{children:[(0,s.jsx)(t.strong,{children:"Null Hypothesis:"})," In the population, weights of dogs and cats have the ",(0,s.jsx)(t.strong,{children:"same"})," distribution, and the observed differences in our samples are due to random chance."]}),"\n",(0,s.jsxs)(t.li,{children:[(0,s.jsx)(t.strong,{children:"Alternative Hypothesis:"})," In the population, dogs and cats have ",(0,s.jsx)(t.strong,{children:"different"})," weights, on average. The observed differences in our samples cannot be explained by random chance alone."]}),"\n"]})]}),"\n",(0,s.jsxs)(t.p,{children:['Since the alternative hypothesis is of the form "A and B are different," the ',(0,s.jsx)(t.strong,{children:"test statistic"})," should measure distance and use an absolute value."]}),"\n",(0,s.jsxs)(t.p,{children:[(0,s.jsxs)(t.span,{className:"katex",children:[(0,s.jsx)(t.span,{className:"katex-mathml",children:(0,s.jsx)(t.math,{xmlns:"http://www.w3.org/1998/Math/MathML",children:(0,s.jsxs)(t.semantics,{children:[(0,s.jsx)(t.mrow,{children:(0,s.jsx)(t.mo,{children:"\u2234"})}),(0,s.jsx)(t.annotation,{encoding:"application/x-tex",children:"\\therefore"})]})})}),(0,s.jsx)(t.span,{className:"katex-html","aria-hidden":"true",children:(0,s.jsxs)(t.span,{className:"base",children:[(0,s.jsx)(t.span,{className:"strut",style:{height:"0.6922em"}}),(0,s.jsx)(t.span,{className:"mrel amsrm",children:"\u2234"})]})})]})," We use ",(0,s.jsx)(t.strong,{children:"absolute difference in group means"})," as the test statistic."]}),"\n",(0,s.jsx)(t.hr,{}),"\n",(0,s.jsx)(t.h3,{id:"2-query-the-dataframe",children:"2. Query the DataFrame"}),"\n",(0,s.jsx)(t.p,{children:"Since we want to compare the distributions of only cats and dogs, we need to make sure to only include the relevant pieces of data (e.g., cats and dogs weights)."}),"\n",(0,s.jsx)(t.pre,{children:(0,s.jsx)(t.code,{className:"language-python",children:"# Create a boolean Series that references which rows fulfill either condition.\nquerying_condition = (full_pets.get('Species') == 'dog') | (full_pets.get('Species') == 'cat')\n# Query.\ncats_dogs = full_pets[querying_condition]\n# Display the first 5 rows only.\ncats_dogs.take(np.arange(5)) \n"})}),"\n",(0,s.jsx)(a.A,{data:'{"columns":["ID","Species","Color","Weight","Age","Is_Cat","Owner_Comment"],"index":[0,1,2,3,4],"data":[["dog_001","dog","black",40.0,5.0,false," There are no bad dogs, only bad owners."],["cat_001","cat","golden",1.5,0.2,true,"My best birthday present ever!!!"],["cat_002","cat","black",15.0,9.0,true,"****All you need is love and a cat.****"],["dog_002","dog","white",80.0,2.0,false,"Love is a wet nose and a wagging tail."],["dog_003","dog","black",25.0,0.5,false,"Be the person your dog thinks you are."]]}'}),"\n",(0,s.jsx)(t.hr,{}),"\n",(0,s.jsx)(t.h3,{id:"3-create-a-function-to-calculate-test-statistic",children:"3. Create a function to calculate test statistic"}),"\n",(0,s.jsx)(t.p,{children:"Since our hypotheses depend on the test statistic, create a function to be able to calculate it during every trial of our permutation test."}),"\n",(0,s.jsx)(t.pre,{children:(0,s.jsx)(t.code,{className:"language-python",children:"def difference_in_means(cats_dogs):\n \"\"\"\n Calculate the absolute difference in the mean weight of dogs and cats.\n ---\n Input:\n cats_dogs: a DataFrame containing the columns 'Species' and 'Weight'.\n ---\n Output:\n The absolute difference in the mean weight of dogs and cats.\n \"\"\"\n means = cats_dogs.groupby('Species').mean()\n return np.abs((means.get('Weight').loc['dog'] - means.get('Weight').loc['cat']))\n"})}),"\n",(0,s.jsx)(t.p,{children:(0,s.jsx)(t.em,{children:"Note: Although we can simply do this in the for-loop shown in the next step, we can practice good coding habits by separating our code into readable bits!"})}),"\n",(0,s.jsx)(t.hr,{}),"\n",(0,s.jsx)(t.h3,{id:"4-simulate-the-permutation-test",children:"4. 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Extra",id:"6-extra",level:3}];function c(e){const t={admonition:"admonition",annotation:"annotation",code:"code",em:"em",h2:"h2",h3:"h3",hr:"hr",img:"img",li:"li",math:"math",mo:"mo",mrow:"mrow",ol:"ol",p:"p",pre:"pre",semantics:"semantics",span:"span",strong:"strong",ul:"ul",...(0,o.R)(),...e.components};return(0,n.jsxs)(n.Fragment,{children:[(0,n.jsx)(t.h2,{id:"concept",children:"Concept"}),"\n",(0,n.jsx)(t.admonition,{title:"Key Idea",type:"tip",children:(0,n.jsx)(t.p,{children:"We use a hypothesis test to test whether a sample was drawn from a population."})}),"\n",(0,n.jsxs)(t.admonition,{title:"Terminology",type:"info",children:[(0,n.jsxs)(t.p,{children:[(0,n.jsx)(t.strong,{children:"Hypothesis Test"}),": A process that test whether a sample was drawn from a population, given a population distribution and a sample."]}),(0,n.jsx)(t.p,{children:"To conduct a hypothesis test:"}),(0,n.jsxs)(t.ol,{children:["\n",(0,n.jsx)(t.li,{children:"Simulate the experiment many times under the assumption that the null hypothesis is true."}),"\n",(0,n.jsx)(t.li,{children:"Compute a test statistic on each of the simulated samples, as well as on the observed sample."}),"\n",(0,n.jsx)(t.li,{children:"Look at the resulting empirical distribution of test statistics and see where the observed test statistic falls. If it seems like an atypical value (too large or too small), we reject the null hypothesis; otherwise, we fail to reject the null."}),"\n"]})]}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h2,{id:"code-example",children:"Code Example"}),"\n",(0,n.jsx)(t.h3,{id:"1-state-the-questionhypothesis",children:"1. State the question/hypothesis"}),"\n",(0,n.jsxs)(t.admonition,{title:"Hypotheses",type:"info",children:[(0,n.jsx)(t.p,{children:"We will test the following pair of hypotheses at the standard p = 0.05 significance level."}),(0,n.jsxs)(t.ul,{children:["\n",(0,n.jsxs)(t.li,{children:[(0,n.jsx)(t.strong,{children:"Null Hypothesis:"}),' The proportion of "white" dogs among dogs is ',(0,n.jsx)(t.strong,{children:"equal"}),' to the proportion of "white" pets in the overall population.']}),"\n",(0,n.jsxs)(t.li,{children:[(0,n.jsx)(t.strong,{children:"Alternative Hypothesis:"}),' The distribution of "white" dogs among dogs is ',(0,n.jsx)(t.strong,{children:"greater than"}),' the proportion of "white" pets in the overall population.']}),"\n"]})]}),"\n",(0,n.jsxs)(t.p,{children:['Since the alternative hypothesis is of the form "A is ',(0,n.jsx)(t.strong,{children:(0,n.jsx)(t.em,{children:"greater than"})}),' B," the ',(0,n.jsx)(t.strong,{children:"test statistic"})," should measure ",(0,n.jsx)(t.strong,{children:"signed difference"})," rather than absolute difference."]}),"\n",(0,n.jsxs)(t.p,{children:[(0,n.jsxs)(t.span,{className:"katex",children:[(0,n.jsx)(t.span,{className:"katex-mathml",children:(0,n.jsx)(t.math,{xmlns:"http://www.w3.org/1998/Math/MathML",children:(0,n.jsxs)(t.semantics,{children:[(0,n.jsx)(t.mrow,{children:(0,n.jsx)(t.mo,{children:"\u2234"})}),(0,n.jsx)(t.annotation,{encoding:"application/x-tex",children:"\\therefore"})]})})}),(0,n.jsx)(t.span,{className:"katex-html","aria-hidden":"true",children:(0,n.jsxs)(t.span,{className:"base",children:[(0,n.jsx)(t.span,{className:"strut",style:{height:"0.6922em"}}),(0,n.jsx)(t.span,{className:"mrel amsrm",children:"\u2234"})]})})]})," We use ",(0,n.jsx)(t.strong,{children:"the difference in proportions"})," of white dogs among dogs and white pets in the overall poplulation as the test statistic."]}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h3,{id:"2-calculate-the-overall-proportion",children:"2. Calculate the overall proportion"}),"\n",(0,n.jsx)(t.p,{children:"We first compute the proportion of white pets in the overall population, which will be used for calculating the test statistic."}),"\n",(0,n.jsx)(t.pre,{children:(0,n.jsx)(t.code,{className:"language-python",children:"#Method 1: Obtain a series of boolean values (1s and 0s), and calculate the mean\noverall_prop = (full_pets.get('Color')=='white').mean()\n\n#Method 2: Query the DataFrame and obtain the proportion by using .shape[0]\n#overall_prop = full_pets[full_pets.get('Color')=='white'].shape[0]/full_pets.shape[0]\n\noverall_prop\n"})}),"\n",(0,n.jsx)(t.p,{children:"0.2631578947368421"}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h3,{id:"3-create-a-function-to-calculate-test-statistic",children:"3. Create a function to calculate test statistic"}),"\n",(0,n.jsx)(t.p,{children:"Create a function to calculate the test statistic during every trial of our hypothesis test."}),"\n",(0,n.jsx)(t.pre,{children:(0,n.jsx)(t.code,{className:"language-python",children:'def difference_in_proportions(dogs_prop, overall_prop):\n """\n Calculate the difference in proportions of white dogs among dogs and white pets in the overall population.\n ---\n Input:\n dogs_prop: the proportion of white dogs among all dogs.\n overall_prop: the proportion of white pets in the overall population.\n ---\n Output:\n The difference in proportions of white dogs among dogs and white pets in the overall population.\n """\n return dogs_prop - overall_prop\n'})}),"\n",(0,n.jsx)(t.p,{children:(0,n.jsx)(t.em,{children:"Note: Although we can simply do this in the for-loop shown in the next step, we can practice good coding habits by separating our code into readable bits!"})}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h3,{id:"4-compute-the-observed-statistic",children:"4. Compute the observed statistic"}),"\n",(0,n.jsx)(t.pre,{children:(0,n.jsx)(t.code,{className:"language-python",children:"# Query the DataFrame to only include dogs\ndogs_df = full_pets[full_pets.get('Species') == 'dog']\n# Compute the observed proportion of white dogs among all dogs\nobs_dogs_prop = (dogs_df.get('Color') == 'white').mean()\n# Calculate the observed statistic\nobserved_stat = difference_in_proportions(obs_dogs_prop, overall_prop)\nobserved_stat\n"})}),"\n",(0,n.jsx)(t.p,{children:"0.18128654970760233"}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h3,{id:"4-simulate-the-hypothesis-test-under-the-null-hypothesis",children:"4. Simulate the hypothesis test under the null hypothesis"}),"\n",(0,n.jsx)(t.pre,{children:(0,n.jsx)(t.code,{className:"language-python",children:'n = 500 # Number of simulations.\ntest_statistics = np.array([]) # Array to keep track of the test statistic for each iteration.\nfor i in np.arange(n): # Run the simulation `n` number of times\n # 1. Simulate the dogs distribution\n \n # Calculte the smaple size (number of dogs)\n sample_size = dogs_df.shape[0]\n \n # Under the null hypothesis, proportion of "white" dogs among dogs is equal to the proportion of white pets among the overall population\n model_proportions = np.array([obs_dogs_prop, 1-obs_dogs_prop]) \n \n # Calculate the the proportion of white dogs among all dogs.\n simulation_proportion = np.random.multinomial(sample_size, model_proportions)[0] / sample_size\n \n # 2. Compute the test statistic\n test_stat = difference_in_proportions(simulation_proportion, overall_prop)\n\n # 3. Save the result\n test_statistics = np.append(test_statistics, test_stat)\n'})}),"\n",(0,n.jsxs)(t.p,{children:["This code will run the permutation test 500 times, but a different reasonable number can be used instead. It is ",(0,n.jsx)(t.strong,{children:"crucial"})," to keep track of the test statistic each time our for-loop runs so that the number of simulated values can be stored."]}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h3,{id:"5-conclusion",children:"5. Conclusion"}),"\n",(0,n.jsx)(t.pre,{children:(0,n.jsx)(t.code,{className:"language-python",children:'p_value = np.count_nonzero(test_statistics >= observed_stat) / n\n\nprint("The observed value of the test statistic is:", observed_stat)\nprint("The p-value is:", p_value)\n'})}),"\n",(0,n.jsxs)(t.p,{children:[(0,n.jsx)(t.strong,{children:"The observed value of the test statistic is:"})," 0.18128654970760233 ",(0,n.jsx)("br",{}),"\n",(0,n.jsx)(t.strong,{children:"The p-value is:"})," 0.616"]}),"\n",(0,n.jsx)(t.p,{children:"Using a significance level of 0.05:"}),"\n",(0,n.jsx)(t.admonition,{title:"Conclusion",type:"info",children:(0,n.jsxs)(t.ul,{children:["\n",(0,n.jsx)(t.li,{children:"Under the null hypothesis, there is a sufficiently large probability of seeing a difference greater than the observed value. The data are consistent with the null hypothesis."}),"\n",(0,n.jsxs)(t.li,{children:["Since our p-value is greater than 0.05, we ",(0,n.jsx)(t.strong,{children:"fail to reject"})," the null hypothesis."]}),"\n"]})}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h3,{id:"6-extra",children:"6. Extra"}),"\n",(0,n.jsx)(t.p,{children:"Let's see how our observed statistic compares to the overall simulated values!"}),"\n",(0,n.jsx)(t.pre,{children:(0,n.jsx)(t.code,{className:"language-python",children:"# Create the histogram.\nbpd.DataFrame().assign(test_statistics=test_statistics).plot(kind='hist', bins= 10, density=True, ec='w')\n# Don't worry about these lines - you won't need to know it for this course!\nplt.axvline(x=observed_stat, c='black', linewidth=4);\nyticks = plt.gca().get_yticks()\nplt.yticks(yticks, np.round(yticks * 0.1, 2))\nplt.show()\n"})}),"\n",(0,n.jsx)(t.p,{children:(0,n.jsx)(t.img,{alt:"Distribution",src:s(2527).A+"",width:"640",height:"480"})}),"\n",(0,n.jsxs)(t.p,{children:["From this graph, we can see that more than half of the data are to the ",(0,n.jsx)(t.strong,{children:"right"})," of the black vertical line (our observed test statistic), meaning we have a relatively high p-value!"]})]})}function p(e={}){const{wrapper:t}={...(0,o.R)(),...e.components};return t?(0,n.jsx)(t,{...e,children:(0,n.jsx)(c,{...e})}):c(e)}},8597:(e,t,s)=>{s.d(t,{A:()=>o});s(6540);var n=s(4848);const o=e=>{let{data:t}=e,s=[],o=[],i="",r=[];if(t){const e=JSON.parse(t);s=e.columns||[],o=e.data||[],i=e.indexName||"Index",r=e.index||[]}return(0,n.jsx)("div",{className:"dataframe-container",children:(0,n.jsxs)("table",{className:"dataframe-table",children:[(0,n.jsx)("thead",{children:(0,n.jsxs)("tr",{children:[(0,n.jsx)("th",{children:i}),s.map(((e,t)=>(0,n.jsx)("th",{children:e},t)))]})}),(0,n.jsx)("tbody",{children:o.map(((e,t)=>(0,n.jsxs)("tr",{children:[(0,n.jsx)("td",{className:"index-value",children:r[t]}),e.map(((e,t)=>{return(0,n.jsx)("td",{children:(s=e,"boolean"==typeof s?s.toString().charAt(0).toUpperCase()+s.toString().slice(1):s)},t);var s}))]},t)))})]})})}},5158:(e,t,s)=>{s.d(t,{A:()=>i});var n=s(6540),o=s(4848);const i=function(e){let{src:t,sourceLink:s,width:i="100%",height:r="100%",paddingBottom:a="56.25%"}=e;const[l,h]=(0,n.useState)(0);return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)("div",{style:{position:"relative",height:"0",paddingBottom:a,overflow:"hidden",maxWidth:"100%"},children:(0,o.jsx)("iframe",{src:t,style:{position:"absolute",top:0,left:0,width:i,height:r,frameBorder:"0",allowFullScreen:!0}},l)}),(0,o.jsx)("div",{style:{display:"flex",justifyContent:"center",margin:"20px 0"},children:(0,o.jsx)("a",{href:s,target:"_blank",rel:"noopener noreferrer",children:"(Source)"})}),(0,o.jsx)("div",{style:{display:"flex",justifyContent:"center",margin:"10px 0"},children:(0,o.jsx)("button",{onClick:()=>{h((e=>e+1))},style:{backgroundColor:"#4CAF50",color:"white",padding:"10px 20px",border:"none",borderRadius:"5px",cursor:"pointer",outline:"none",fontSize:"16px",fontWeight:"bold",boxShadow:"0 4px 8px rgba(0,0,0,0.1)",transition:"background-color 0.3s"},onMouseOver:e=>e.currentTarget.style.backgroundColor="#45a049",onMouseOut:e=>e.currentTarget.style.backgroundColor="#4CAF50",children:"Restart Diagram"})})]})}},2527:(e,t,s)=>{s.d(t,{A:()=>n});const n=s.p+"assets/images/hypothesis-test-776f8723e19318f4f91020489482dcf5.png"},8453:(e,t,s)=>{s.d(t,{R:()=>r,x:()=>a});var n=s(6540);const o={},i=n.createContext(o);function r(e){const t=n.useContext(i);return n.useMemo((function(){return"function"==typeof e?e(t):{...t,...e}}),[t,e])}function a(e){let t;return t=e.disableParentContext?"function"==typeof e.components?e.components(o):e.components||o:r(e.components),n.createElement(i.Provider,{value:t},e.children)}}}]); \ No newline at end of file +"use strict";(self.webpackChunkbpd_reference=self.webpackChunkbpd_reference||[]).push([[972],{3007:(e,t,s)=>{s.r(t),s.d(t,{assets:()=>l,contentTitle:()=>r,default:()=>p,frontMatter:()=>i,metadata:()=>a,toc:()=>h});var n=s(4848),o=s(8453);s(8597),s(5158);const i={sidebar_position:6,sidebar_label:"Hypothesis Test",title:"Hypothesis Test",tags:["querying","functions","for-loop","histogram"]},r=void 0,a={id:"statistical-inference/hypothesis_test",title:"Hypothesis Test",description:"Concept",source:"@site/docs/statistical-inference/hypothesis_test.md",sourceDirName:"statistical-inference",slug:"/statistical-inference/hypothesis_test",permalink:"/bpd-reference/docs/statistical-inference/hypothesis_test",draft:!1,unlisted:!1,editUrl:"https://github.com/dsc-courses/bpd-reference/tree/main/docs/statistical-inference/hypothesis_test.md",tags:[{label:"querying",permalink:"/bpd-reference/docs/tags/querying"},{label:"functions",permalink:"/bpd-reference/docs/tags/functions"},{label:"for-loop",permalink:"/bpd-reference/docs/tags/for-loop"},{label:"histogram",permalink:"/bpd-reference/docs/tags/histogram"}],version:"current",sidebarPosition:6,frontMatter:{sidebar_position:6,sidebar_label:"Hypothesis Test",title:"Hypothesis Test",tags:["querying","functions","for-loop","histogram"]},sidebar:"statsSidebar",previous:{title:"P-value",permalink:"/bpd-reference/docs/statistical-inference/p_value"},next:{title:"Permutation Test",permalink:"/bpd-reference/docs/statistical-inference/permutation_test"}},l={},h=[{value:"Concept",id:"concept",level:2},{value:"Code Example",id:"code-example",level:2},{value:"1. 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Extra",id:"6-extra",level:3}];function c(e){const t={admonition:"admonition",annotation:"annotation",code:"code",em:"em",h2:"h2",h3:"h3",hr:"hr",img:"img",li:"li",math:"math",mo:"mo",mrow:"mrow",ol:"ol",p:"p",pre:"pre",semantics:"semantics",span:"span",strong:"strong",ul:"ul",...(0,o.R)(),...e.components};return(0,n.jsxs)(n.Fragment,{children:[(0,n.jsx)(t.h2,{id:"concept",children:"Concept"}),"\n",(0,n.jsx)(t.admonition,{title:"Key Idea",type:"tip",children:(0,n.jsx)(t.p,{children:"We use a hypothesis test to test whether a sample was drawn from a population."})}),"\n",(0,n.jsxs)(t.admonition,{title:"Terminology",type:"info",children:[(0,n.jsxs)(t.p,{children:[(0,n.jsx)(t.strong,{children:"Hypothesis Test"}),": A process that test whether a sample was drawn from a population, given a population distribution and a sample."]}),(0,n.jsx)(t.p,{children:"To conduct a hypothesis test:"}),(0,n.jsxs)(t.ol,{children:["\n",(0,n.jsx)(t.li,{children:"Simulate the experiment many times under the assumption that the null hypothesis is true."}),"\n",(0,n.jsx)(t.li,{children:"Compute a test statistic on each of the simulated samples, as well as on the observed sample."}),"\n",(0,n.jsx)(t.li,{children:"Look at the resulting empirical distribution of test statistics and see where the observed test statistic falls. If it seems like an atypical value (too large or too small), we reject the null hypothesis; otherwise, we fail to reject the null."}),"\n"]})]}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h2,{id:"code-example",children:"Code Example"}),"\n",(0,n.jsx)(t.h3,{id:"1-state-the-questionhypothesis",children:"1. 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Calculate the overall proportion"}),"\n",(0,n.jsx)(t.p,{children:"We first compute the proportion of white pets in the overall population, which will be used for calculating the test statistic."}),"\n",(0,n.jsx)(t.pre,{children:(0,n.jsx)(t.code,{className:"language-python",children:"#Method 1: Obtain a series of boolean values (1s and 0s), and calculate the mean\noverall_prop = (full_pets.get('Color')=='white').mean()\n\n#Method 2: Query the DataFrame and obtain the proportion by using .shape[0]\n#overall_prop = full_pets[full_pets.get('Color')=='white'].shape[0]/full_pets.shape[0]\n\noverall_prop\n"})}),"\n",(0,n.jsx)(t.p,{children:"0.2631578947368421"}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h3,{id:"3-create-a-function-to-calculate-test-statistic",children:"3. Create a function to calculate test statistic"}),"\n",(0,n.jsx)(t.p,{children:"Create a function to calculate the test statistic during every trial of our hypothesis test."}),"\n",(0,n.jsx)(t.pre,{children:(0,n.jsx)(t.code,{className:"language-python",children:'def difference_in_proportions(dogs_prop, overall_prop):\n """\n Calculate the difference in proportions of white dogs among dogs and white pets in the overall population.\n ---\n Input:\n dogs_prop: the proportion of white dogs among all dogs.\n overall_prop: the proportion of white pets in the overall population.\n ---\n Output:\n The difference in proportions of white dogs among dogs and white pets in the overall population.\n """\n return dogs_prop - overall_prop\n'})}),"\n",(0,n.jsx)(t.p,{children:(0,n.jsx)(t.em,{children:"Note: Although we can simply do this in the for-loop shown in the next step, we can practice good coding habits by separating our code into readable bits!"})}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h3,{id:"4-compute-the-observed-statistic",children:"4. Compute the observed statistic"}),"\n",(0,n.jsx)(t.pre,{children:(0,n.jsx)(t.code,{className:"language-python",children:"# Query the DataFrame to only include dogs\ndogs_df = full_pets[full_pets.get('Species') == 'dog']\n# Compute the observed proportion of white dogs among all dogs\nobs_dogs_prop = (dogs_df.get('Color') == 'white').mean()\n# Calculate the observed statistic\nobserved_stat = difference_in_proportions(obs_dogs_prop, overall_prop)\nobserved_stat\n"})}),"\n",(0,n.jsx)(t.p,{children:"0.18128654970760233"}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h3,{id:"4-simulate-the-hypothesis-test-under-the-null-hypothesis",children:"4. Simulate the hypothesis test under the null hypothesis"}),"\n",(0,n.jsx)(t.pre,{children:(0,n.jsx)(t.code,{className:"language-python",children:'n = 500 # Number of simulations.\ntest_statistics = np.array([]) # Array to keep track of the test statistic for each iteration.\nfor i in np.arange(n): # Run the simulation `n` number of times\n # 1. Simulate the dogs distribution\n \n # Calculte the smaple size (number of dogs)\n sample_size = dogs_df.shape[0]\n \n # Under the null hypothesis, proportion of "white" dogs among dogs is equal to the proportion of white pets among the overall population\n model_proportions = np.array([obs_dogs_prop, 1-obs_dogs_prop]) \n \n # Calculate the the proportion of white dogs among all dogs.\n simulation_proportion = np.random.multinomial(sample_size, model_proportions)[0] / sample_size\n \n # 2. Compute the test statistic\n test_stat = difference_in_proportions(simulation_proportion, overall_prop)\n\n # 3. Save the result\n test_statistics = np.append(test_statistics, test_stat)\n'})}),"\n",(0,n.jsxs)(t.p,{children:["This code will run the permutation test 500 times, but a different reasonable number can be used instead. It is ",(0,n.jsx)(t.strong,{children:"crucial"})," to keep track of the test statistic each time our for-loop runs so that the number of simulated values can be stored."]}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h3,{id:"5-conclusion",children:"5. Conclusion"}),"\n",(0,n.jsx)(t.pre,{children:(0,n.jsx)(t.code,{className:"language-python",children:'p_value = np.count_nonzero(test_statistics >= observed_stat) / n\n\nprint("The observed value of the test statistic is:", observed_stat)\nprint("The p-value is:", p_value)\n'})}),"\n",(0,n.jsxs)(t.p,{children:[(0,n.jsx)(t.strong,{children:"The observed value of the test statistic is:"})," 0.18128654970760233 ",(0,n.jsx)("br",{}),"\n",(0,n.jsx)(t.strong,{children:"The p-value is:"})," 0.616"]}),"\n",(0,n.jsx)(t.p,{children:"Using a significance level of 0.05:"}),"\n",(0,n.jsx)(t.admonition,{title:"Conclusion",type:"info",children:(0,n.jsxs)(t.ul,{children:["\n",(0,n.jsx)(t.li,{children:"Under the null hypothesis, there is a sufficiently large probability of seeing a difference greater than the observed value. The data are consistent with the null hypothesis."}),"\n",(0,n.jsxs)(t.li,{children:["Since our p-value is greater than 0.05, we ",(0,n.jsx)(t.strong,{children:"fail to reject"})," the null hypothesis."]}),"\n"]})}),"\n",(0,n.jsx)(t.hr,{}),"\n",(0,n.jsx)(t.h3,{id:"6-extra",children:"6. Extra"}),"\n",(0,n.jsx)(t.p,{children:"Let's see how our observed statistic compares to the overall simulated values!"}),"\n",(0,n.jsx)(t.pre,{children:(0,n.jsx)(t.code,{className:"language-python",children:"# Create the histogram.\nbpd.DataFrame().assign(test_statistics=test_statistics).plot(kind='hist', bins= 10, density=True, ec='w')\n# Don't worry about these lines - you won't need to know it for this course!\nplt.axvline(x=observed_stat, c='black', linewidth=4);\nyticks = plt.gca().get_yticks()\nplt.yticks(yticks, np.round(yticks * 0.1, 2))\nplt.show()\n"})}),"\n",(0,n.jsx)(t.p,{children:(0,n.jsx)(t.img,{alt:"Distribution",src:s(2491).A+"",width:"640",height:"480"})}),"\n",(0,n.jsxs)(t.p,{children:["From this graph, we can see that more than half of the data are to the ",(0,n.jsx)(t.strong,{children:"right"})," of the black vertical line (our observed test statistic), meaning we have a relatively high p-value!"]})]})}function p(e={}){const{wrapper:t}={...(0,o.R)(),...e.components};return t?(0,n.jsx)(t,{...e,children:(0,n.jsx)(c,{...e})}):c(e)}},8597:(e,t,s)=>{s.d(t,{A:()=>o});s(6540);var n=s(4848);const o=e=>{let{data:t}=e,s=[],o=[],i="",r=[];if(t){const e=JSON.parse(t);s=e.columns||[],o=e.data||[],i=e.indexName||"Index",r=e.index||[]}return(0,n.jsx)("div",{className:"dataframe-container",children:(0,n.jsxs)("table",{className:"dataframe-table",children:[(0,n.jsx)("thead",{children:(0,n.jsxs)("tr",{children:[(0,n.jsx)("th",{children:i}),s.map(((e,t)=>(0,n.jsx)("th",{children:e},t)))]})}),(0,n.jsx)("tbody",{children:o.map(((e,t)=>(0,n.jsxs)("tr",{children:[(0,n.jsx)("td",{className:"index-value",children:r[t]}),e.map(((e,t)=>{return(0,n.jsx)("td",{children:(s=e,"boolean"==typeof s?s.toString().charAt(0).toUpperCase()+s.toString().slice(1):s)},t);var s}))]},t)))})]})})}},5158:(e,t,s)=>{s.d(t,{A:()=>i});var n=s(6540),o=s(4848);const i=function(e){let{src:t,sourceLink:s,width:i="100%",height:r="100%",paddingBottom:a="56.25%"}=e;const[l,h]=(0,n.useState)(0);return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)("div",{style:{position:"relative",height:"0",paddingBottom:a,overflow:"hidden",maxWidth:"100%"},children:(0,o.jsx)("iframe",{src:t,style:{position:"absolute",top:0,left:0,width:i,height:r,frameBorder:"0",allowFullScreen:!0}},l)}),(0,o.jsx)("div",{style:{display:"flex",justifyContent:"center",margin:"20px 0"},children:(0,o.jsx)("a",{href:s,target:"_blank",rel:"noopener noreferrer",children:"(Source)"})}),(0,o.jsx)("div",{style:{display:"flex",justifyContent:"center",margin:"10px 0"},children:(0,o.jsx)("button",{onClick:()=>{h((e=>e+1))},style:{backgroundColor:"#4CAF50",color:"white",padding:"10px 20px",border:"none",borderRadius:"5px",cursor:"pointer",outline:"none",fontSize:"16px",fontWeight:"bold",boxShadow:"0 4px 8px rgba(0,0,0,0.1)",transition:"background-color 0.3s"},onMouseOver:e=>e.currentTarget.style.backgroundColor="#45a049",onMouseOut:e=>e.currentTarget.style.backgroundColor="#4CAF50",children:"Restart Diagram"})})]})}},2491:(e,t,s)=>{s.d(t,{A:()=>n});const n=s.p+"assets/images/hypothesis-test-776f8723e19318f4f91020489482dcf5.png"},8453:(e,t,s)=>{s.d(t,{R:()=>r,x:()=>a});var n=s(6540);const o={},i=n.createContext(o);function r(e){const t=n.useContext(i);return n.useMemo((function(){return"function"==typeof e?e(t):{...t,...e}}),[t,e])}function a(e){let t;return t=e.disableParentContext?"function"==typeof e.components?e.components(o):e.components||o:r(e.components),n.createElement(i.Provider,{value:t},e.children)}}}]); \ No newline at end of file diff --git a/assets/js/f095f4cd.e4b62aed.js b/assets/js/f095f4cd.268e680e.js similarity index 99% rename from assets/js/f095f4cd.e4b62aed.js rename to assets/js/f095f4cd.268e680e.js index 1694c558..067bb2dd 100644 --- a/assets/js/f095f4cd.e4b62aed.js +++ b/assets/js/f095f4cd.268e680e.js @@ -1 +1 @@ -"use strict";(self.webpackChunkbpd_reference=self.webpackChunkbpd_reference||[]).push([[28],{8406:(e,A,t)=>{t.r(A),t.d(A,{assets:()=>d,contentTitle:()=>o,default:()=>h,frontMatter:()=>r,metadata:()=>l,toc:()=>c});var n=t(4848),a=t(8453),s=t(8597),i=t(5158);const r={sidebar_position:8,sidebar_label:"Boostrapping and Confidence Intervals",title:"Bootstrapping and Confidence Intervals",tags:["for-loop","histogram"]},o=void 0,l={id:"statistical-inference/bootstrapping",title:"Bootstrapping and Confidence Intervals",description:"Concept",source:"@site/docs/statistical-inference/bootstrapping.md",sourceDirName:"statistical-inference",slug:"/statistical-inference/bootstrapping",permalink:"/bpd-reference/docs/statistical-inference/bootstrapping",draft:!1,unlisted:!1,editUrl:"https://github.com/dsc-courses/bpd-reference/tree/main/docs/statistical-inference/bootstrapping.md",tags:[{label:"for-loop",permalink:"/bpd-reference/docs/tags/for-loop"},{label:"histogram",permalink:"/bpd-reference/docs/tags/histogram"}],version:"current",sidebarPosition:8,frontMatter:{sidebar_position:8,sidebar_label:"Boostrapping and Confidence Intervals",title:"Bootstrapping and Confidence Intervals",tags:["for-loop","histogram"]},sidebar:"statsSidebar",previous:{title:"Standard Units, Correlation, Regression",permalink:"/bpd-reference/docs/statistical-inference/standard_units"},next:{title:"Hypothesis Test vs. Permutation Test",permalink:"/bpd-reference/docs/statistical-inference/concept check/hypothesis_vs_permutation"}},d={},c=[{value:"Concept",id:"concept",level:2},{value:"Code Example",id:"code-example",level:2},{value:"1. Take a random sample of size 12 from the <code>full_pets</code> DataFrame.",id:"1-take-a-random-sample-of-size-12-from-the-full_pets-dataframe",level:3},{value:"2. Find the observed parameter",id:"2-find-the-observed-parameter",level:3},{value:"3. Bootstrap the sample 10,000 times with replacement",id:"3-bootstrap-the-sample-10000-times-with-replacement",level:3},{value:"4. Create a 95% confidence interval",id:"4-create-a-95-confidence-interval",level:3},{value:"5. Conclusion",id:"5-conclusion",level:3},{value:"6. Extra",id:"6-extra",level:3}];function p(e){const A={a:"a",admonition:"admonition",code:"code",h2:"h2",h3:"h3",hr:"hr",img:"img",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,a.R)(),...e.components};return(0,n.jsxs)(n.Fragment,{children:[(0,n.jsx)(A.h2,{id:"concept",children:"Concept"}),"\n",(0,n.jsx)(A.admonition,{title:"Key Idea",type:"tip",children:(0,n.jsx)(A.p,{children:"We use a bootstrapping to estimate the distribution of the sample statistic to see how different our it could have been. We use confidence intervals to define a range that captures most of the bootstrapped distribution of the sample statistic."})}),"\n",(0,n.jsxs)(A.admonition,{title:"Terminology",type:"info",children:[(0,n.jsxs)(A.p,{children:[(0,n.jsx)(A.strong,{children:"Bootstrapping"}),": Bootstrapping is a type of hypothesis test that involves resampling from a single sample to estimate the\ndistribution of the sample statistic. It answers the question of how different the sample statistic could have been if given a different sample. To conduct bootstrapping:"]}),(0,n.jsxs)(A.ol,{children:["\n",(0,n.jsx)(A.li,{children:"Resample from the original sample with replacement."}),"\n",(0,n.jsx)(A.li,{children:"Calculate the sample statistic on the bootstrapped resample."}),"\n",(0,n.jsx)(A.li,{children:"Save the results into an array."}),"\n",(0,n.jsx)(A.li,{children:"Repeat steps 1 through 3 to generate an empirical distribution of the test statistic."}),"\n",(0,n.jsx)(A.li,{children:"Calculate the confidence interval and see if the observed statistic lies in it. If the observed statistic is not\nin our confidence interval, we have evidence to reject the null."}),"\n"]}),(0,n.jsxs)(A.p,{children:[(0,n.jsx)(A.strong,{children:"Confidence Intervals:"})," A confidence interval is a range that captures most of the distribution of the bootstrapped sample statistic in\nthe hopes of also containing the true population parameter within it. If\nwe were to construct a 95% confidence interval, we aren't saying that there is a 95% chance that the true population parameter lies in the\ninterval as the interval either contains it or it doesn't. Instead, we are saying that approximately 95% of the time, the intervals you\ncreate will contain the true population parameter. For example, if we generated 100 confidence intervals, about 95 of them will have the\ntrue population parameter."]})]}),"\n",(0,n.jsx)(A.admonition,{type:"note",children:(0,n.jsx)(A.p,{children:"When resampling, the size of the resample should be the same as the original sample with replacement."})}),"\n",(0,n.jsx)(A.p,{children:"The diagram below provides an overview of conducting bootstrapping, although it references a different dataset."}),"\n",(0,n.jsx)(i.A,{src:"https://docs.google.com/presentation/d/e/2PACX-1vS_iYHJYXSVMMZ-YQVFwMEFR6EFN3FDSAvaMyUm-YJfLQgRMTHm3vI-wWJJ5999eFJq70nWp2hyItZg/embed?start=true&loop=false&delayms=3000&rm=minimal",sourceLink:"https://docs.google.com/presentation/d/1oYakqMdI7z61BthvgWUJvbT21bKTXg01KmAibglepBI/edit?usp=sharing"}),"\n",(0,n.jsxs)(A.p,{children:["The diagram below provides an overview of creating confidence intervals, although it references a different situation. For additional helpful visual guides, please visit the ",(0,n.jsx)(A.a,{href:"https://dsc10.com/diagrams/",children:"Diagrams"})," site."]}),"\n",(0,n.jsx)(i.A,{src:"https://docs.google.com/presentation/d/e/2PACX-1vTaPZsueXI6fey_5cj2Y1TevkR1joBvpwaWVsZNvgBlnJSrw1EiBLHJywkFH_QNLU5Tdr6JZgDrhFxG/embed?start=true&loop=false&delayms=3000&rm=minimal",sourceLink:"https://docs.google.com/presentation/d/1l5GVyl60FrornEaZnGL6REV4gjEydRncNVi6k1hHUsA/edit?usp=sharing"}),"\n",(0,n.jsx)(A.hr,{}),"\n",(0,n.jsx)(A.h2,{id:"code-example",children:"Code Example"}),"\n",(0,n.jsxs)(A.h3,{id:"1-take-a-random-sample-of-size-12-from-the-full_pets-dataframe",children:["1. Take a random sample of size 12 from the ",(0,n.jsx)(A.code,{children:"full_pets"})," DataFrame."]}),"\n",(0,n.jsxs)(A.p,{children:["Let's say we didn't have access to all of the information in the ",(0,n.jsx)(A.code,{children:"full_pets"})," DataFrame and were only able to collect a sample of 12 pets."]}),"\n",(0,n.jsx)(A.pre,{children:(0,n.jsx)(A.code,{className:"language-python",children:"# Magic to ensure that we get the same results every time this code is run. \nnp.random.seed(42)\n\n# sample\npets_sample = full_pets.sample(12, replace=False)\npets_sample\n"})}),"\n",(0,n.jsx)(s.A,{data:'{"columns":["Unnamed: 0","ID","Species","Color","Weight","Age","Is_Cat","Owner_Comment"],"index":[18,14,4,13,10,7,6,3,2,15,17,8],"data":[[18,"cat_006","cat","black",3.0,0.5,true,"No, thank you!"],[14,"dog_007","dog","white",50.0,6.1,false,"No, thank you!"],[4,"dog_003","dog","black",25.0,0.5,false,"Be the person your dog thinks you are."],[13,"ham_003","hamster","black",0.5,0.1,false,"No, thank you!"],[10,"dog_006","dog","golden",35.0,4.0,false,"No, thank you!"],[7,"cat_003","cat","black",10.0,0.0,true,"No, thank you!"],[6,"ham_002","hamster","golden",0.25,0.2,false,"No, thank you!"],[3,"dog_002","dog","white",80.0,2.0,false,"Love is a wet nose and a wagging tail."],[2,"cat_002","cat","black",15.0,9.0,true,"****All you need is love and a cat.****"],[15,"ham_004","hamster","golden",0.25,0.2,false,"No, thank you!"],[17,"dog_009","dog","white",30.0,4.8,false,"No, thank you!"],[8,"dog_004","dog","black",45.0,6.7,false,"No, thank you!"]]}'}),"\n",(0,n.jsx)(A.hr,{}),"\n",(0,n.jsx)(A.h3,{id:"2-find-the-observed-parameter",children:"2. Find the observed parameter"}),"\n",(0,n.jsx)(A.p,{children:"In this case, we are interested in finding the median weight of the entire population."}),"\n",(0,n.jsx)(A.pre,{children:(0,n.jsx)(A.code,{className:"language-python",children:"pets_sample = full_pets.sample(12, replace=False)\nprint('Median of pets_sample weight:', pets_sample.get('Weight').median())\n"})}),"\n",(0,n.jsx)(A.p,{children:"Median of pets_sample weight: 20.0"}),"\n",(0,n.jsx)(A.hr,{}),"\n",(0,n.jsx)(A.h3,{id:"3-bootstrap-the-sample-10000-times-with-replacement",children:"3. Bootstrap the sample 10,000 times with replacement"}),"\n",(0,n.jsx)(A.p,{children:"Since we were only able to collect one random sample from the full population, we can't be sure if this singular guess predicts the\ntrue population parameter well. We can't go out and collect\nanother random sample, so we will resample from the original sample with replacement to simulate what could've been."}),"\n",(0,n.jsx)(A.pre,{children:(0,n.jsx)(A.code,{className:"language-python",children:"boot_medians = np.array([])\nfor i in np.arange(10000):\n # 1. resample the data\n resample = pets_sample.sample(pets_sample.shape[0], replace=True)\n\n # 2. calculate the median of the resample\n boot_median = resample.get('Weight').median()\n\n # 3. append the median to the array\n boot_medians = np.append(boot_medians, boot_median)\n"})}),"\n",(0,n.jsx)(A.p,{children:"This code will create 10,000 bootstrapped samples and calculate the median for each of them, but a different\nreasonable number can be used instead. Since these samples are all random, the information in each sample and\nmedian will be different from one another."}),"\n",(0,n.jsx)(A.hr,{}),"\n",(0,n.jsx)(A.h3,{id:"4-create-a-95-confidence-interval",children:"4. Create a 95% confidence interval"}),"\n",(0,n.jsx)(A.p,{children:"Instead of using a single number to estimate the true population parameter, we create a range of where we think it is."}),"\n",(0,n.jsx)(A.pre,{children:(0,n.jsx)(A.code,{className:"language-python",children:"# Get the 95% confidence interval\nleft = np.percentile(boot_medians, 2.5) # 2.5th percentile\nright = np.percentile(boot_medians, 97.5) # 97.5th percentile\n"})}),"\n",(0,n.jsx)(A.p,{children:"Remember that the 95% confidence interval does not mean we have a 95% chance of containing the true population parameter. It means\nthat about 95% of all intervals we create will contain the true population parameter."}),"\n",(0,n.jsx)(A.hr,{}),"\n",(0,n.jsx)(A.h3,{id:"5-conclusion",children:"5. Conclusion"}),"\n",(0,n.jsx)(A.pre,{children:(0,n.jsx)(A.code,{className:"language-python",children:"left, right\n"})}),"\n",(0,n.jsx)(A.p,{children:"(1.75, 40.0)"}),"\n",(0,n.jsx)(A.admonition,{title:"Conclusion",type:"info",children:(0,n.jsxs)(A.ul,{children:["\n",(0,n.jsx)(A.li,{children:"From this interval, we are 95% confident that the true population median lies somewhere between 1.75 and 40."}),"\n",(0,n.jsx)(A.li,{children:"We have no way of knowing where exactly in this interval does the true population median falls or even if it is contained at all."}),"\n",(0,n.jsx)(A.li,{children:"What we do know is that if we were to repeat the process and generate multiple confidence intervals, roughly 95% of them will\ncontain the true population median."}),"\n"]})}),"\n",(0,n.jsx)(A.hr,{}),"\n",(0,n.jsx)(A.h3,{id:"6-extra",children:"6. Extra"}),"\n",(0,n.jsx)(A.p,{children:"Let's look at the distribution of the bootstrapped medians!"}),"\n",(0,n.jsx)(A.pre,{children:(0,n.jsx)(A.code,{className:"language-python",children:"# Create the histogram.\n# Plot the histogram of boot_medians\nplt.hist(boot_medians, bins=20, density=True, ec = 'w')\n\nplt.show()\n"})}),"\n",(0,n.jsx)(A.p,{children:(0,n.jsx)(A.img,{alt:"Distribution",src:t(7370).A+"",width:"556",height:"413"})}),"\n",(0,n.jsxs)(A.p,{children:["A 95% confidence level means that ",(0,n.jsx)(A.strong,{children:"approximately 95% of the time, the intervals you create through this process will contain the true population parameter"}),"."]})]})}function h(e={}){const{wrapper:A}={...(0,a.R)(),...e.components};return A?(0,n.jsx)(A,{...e,children:(0,n.jsx)(p,{...e})}):p(e)}},8597:(e,A,t)=>{t.d(A,{A:()=>a});t(6540);var n=t(4848);const a=e=>{let{data:A}=e,t=[],a=[],s="",i=[];if(A){const 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check/hypothesis_vs_permutation"}},d={},c=[{value:"Concept",id:"concept",level:2},{value:"Code Example",id:"code-example",level:2},{value:"1. Take a random sample of size 12 from the <code>full_pets</code> DataFrame.",id:"1-take-a-random-sample-of-size-12-from-the-full_pets-dataframe",level:3},{value:"2. Find the observed parameter",id:"2-find-the-observed-parameter",level:3},{value:"3. Bootstrap the sample 10,000 times with replacement",id:"3-bootstrap-the-sample-10000-times-with-replacement",level:3},{value:"4. Create a 95% confidence interval",id:"4-create-a-95-confidence-interval",level:3},{value:"5. Conclusion",id:"5-conclusion",level:3},{value:"6. Extra",id:"6-extra",level:3}];function p(e){const A={a:"a",admonition:"admonition",code:"code",h2:"h2",h3:"h3",hr:"hr",img:"img",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,a.R)(),...e.components};return(0,n.jsxs)(n.Fragment,{children:[(0,n.jsx)(A.h2,{id:"concept",children:"Concept"}),"\n",(0,n.jsx)(A.admonition,{title:"Key Idea",type:"tip",children:(0,n.jsx)(A.p,{children:"We use a bootstrapping to estimate the distribution of the sample statistic to see how different our it could have been. We use confidence intervals to define a range that captures most of the bootstrapped distribution of the sample statistic."})}),"\n",(0,n.jsxs)(A.admonition,{title:"Terminology",type:"info",children:[(0,n.jsxs)(A.p,{children:[(0,n.jsx)(A.strong,{children:"Bootstrapping"}),": Bootstrapping is a type of hypothesis test that involves resampling from a single sample to estimate the\ndistribution of the sample statistic. It answers the question of how different the sample statistic could have been if given a different sample. To conduct bootstrapping:"]}),(0,n.jsxs)(A.ol,{children:["\n",(0,n.jsx)(A.li,{children:"Resample from the original sample with replacement."}),"\n",(0,n.jsx)(A.li,{children:"Calculate the sample statistic on the bootstrapped resample."}),"\n",(0,n.jsx)(A.li,{children:"Save the results into an array."}),"\n",(0,n.jsx)(A.li,{children:"Repeat steps 1 through 3 to generate an empirical distribution of the test statistic."}),"\n",(0,n.jsx)(A.li,{children:"Calculate the confidence interval and see if the observed statistic lies in it. If the observed statistic is not\nin our confidence interval, we have evidence to reject the null."}),"\n"]}),(0,n.jsxs)(A.p,{children:[(0,n.jsx)(A.strong,{children:"Confidence Intervals:"})," A confidence interval is a range that captures most of the distribution of the bootstrapped sample statistic in\nthe hopes of also containing the true population parameter within it. If\nwe were to construct a 95% confidence interval, we aren't saying that there is a 95% chance that the true population parameter lies in the\ninterval as the interval either contains it or it doesn't. Instead, we are saying that approximately 95% of the time, the intervals you\ncreate will contain the true population parameter. For example, if we generated 100 confidence intervals, about 95 of them will have the\ntrue population parameter."]})]}),"\n",(0,n.jsx)(A.admonition,{type:"note",children:(0,n.jsx)(A.p,{children:"When resampling, the size of the resample should be the same as the original sample with replacement."})}),"\n",(0,n.jsx)(A.p,{children:"The diagram below provides an overview of conducting bootstrapping, although it references a different dataset."}),"\n",(0,n.jsx)(i.A,{src:"https://docs.google.com/presentation/d/e/2PACX-1vS_iYHJYXSVMMZ-YQVFwMEFR6EFN3FDSAvaMyUm-YJfLQgRMTHm3vI-wWJJ5999eFJq70nWp2hyItZg/embed?start=true&loop=false&delayms=3000&rm=minimal",sourceLink:"https://docs.google.com/presentation/d/1oYakqMdI7z61BthvgWUJvbT21bKTXg01KmAibglepBI/edit?usp=sharing"}),"\n",(0,n.jsxs)(A.p,{children:["The diagram below provides an overview of creating confidence intervals, although it references a different situation. For additional helpful visual guides, please visit the ",(0,n.jsx)(A.a,{href:"https://dsc10.com/diagrams/",children:"Diagrams"})," site."]}),"\n",(0,n.jsx)(i.A,{src:"https://docs.google.com/presentation/d/e/2PACX-1vTaPZsueXI6fey_5cj2Y1TevkR1joBvpwaWVsZNvgBlnJSrw1EiBLHJywkFH_QNLU5Tdr6JZgDrhFxG/embed?start=true&loop=false&delayms=3000&rm=minimal",sourceLink:"https://docs.google.com/presentation/d/1l5GVyl60FrornEaZnGL6REV4gjEydRncNVi6k1hHUsA/edit?usp=sharing"}),"\n",(0,n.jsx)(A.hr,{}),"\n",(0,n.jsx)(A.h2,{id:"code-example",children:"Code Example"}),"\n",(0,n.jsxs)(A.h3,{id:"1-take-a-random-sample-of-size-12-from-the-full_pets-dataframe",children:["1. Take a random sample of size 12 from the ",(0,n.jsx)(A.code,{children:"full_pets"})," DataFrame."]}),"\n",(0,n.jsxs)(A.p,{children:["Let's say we didn't have access to all of the information in the ",(0,n.jsx)(A.code,{children:"full_pets"})," DataFrame and were only able to collect a sample of 12 pets."]}),"\n",(0,n.jsx)(A.pre,{children:(0,n.jsx)(A.code,{className:"language-python",children:"# Magic to ensure that we get the same results every time this code is run. \nnp.random.seed(42)\n\n# sample\npets_sample = full_pets.sample(12, replace=False)\npets_sample\n"})}),"\n",(0,n.jsx)(s.A,{data:'{"columns":["Unnamed: 0","ID","Species","Color","Weight","Age","Is_Cat","Owner_Comment"],"index":[18,14,4,13,10,7,6,3,2,15,17,8],"data":[[18,"cat_006","cat","black",3.0,0.5,true,"No, thank you!"],[14,"dog_007","dog","white",50.0,6.1,false,"No, thank you!"],[4,"dog_003","dog","black",25.0,0.5,false,"Be the person your dog thinks you are."],[13,"ham_003","hamster","black",0.5,0.1,false,"No, thank you!"],[10,"dog_006","dog","golden",35.0,4.0,false,"No, thank you!"],[7,"cat_003","cat","black",10.0,0.0,true,"No, thank you!"],[6,"ham_002","hamster","golden",0.25,0.2,false,"No, thank you!"],[3,"dog_002","dog","white",80.0,2.0,false,"Love is a wet nose and a wagging tail."],[2,"cat_002","cat","black",15.0,9.0,true,"****All you need is love and a cat.****"],[15,"ham_004","hamster","golden",0.25,0.2,false,"No, thank you!"],[17,"dog_009","dog","white",30.0,4.8,false,"No, thank you!"],[8,"dog_004","dog","black",45.0,6.7,false,"No, thank you!"]]}'}),"\n",(0,n.jsx)(A.hr,{}),"\n",(0,n.jsx)(A.h3,{id:"2-find-the-observed-parameter",children:"2. Find the observed parameter"}),"\n",(0,n.jsx)(A.p,{children:"In this case, we are interested in finding the median weight of the entire population."}),"\n",(0,n.jsx)(A.pre,{children:(0,n.jsx)(A.code,{className:"language-python",children:"pets_sample = full_pets.sample(12, replace=False)\nprint('Median of pets_sample weight:', pets_sample.get('Weight').median())\n"})}),"\n",(0,n.jsx)(A.p,{children:"Median of pets_sample weight: 20.0"}),"\n",(0,n.jsx)(A.hr,{}),"\n",(0,n.jsx)(A.h3,{id:"3-bootstrap-the-sample-10000-times-with-replacement",children:"3. Bootstrap the sample 10,000 times with replacement"}),"\n",(0,n.jsx)(A.p,{children:"Since we were only able to collect one random sample from the full population, we can't be sure if this singular guess predicts the\ntrue population parameter well. We can't go out and collect\nanother random sample, so we will resample from the original sample with replacement to simulate what could've been."}),"\n",(0,n.jsx)(A.pre,{children:(0,n.jsx)(A.code,{className:"language-python",children:"boot_medians = np.array([])\nfor i in np.arange(10000):\n # 1. resample the data\n resample = pets_sample.sample(pets_sample.shape[0], replace=True)\n\n # 2. calculate the median of the resample\n boot_median = resample.get('Weight').median()\n\n # 3. append the median to the array\n boot_medians = np.append(boot_medians, boot_median)\n"})}),"\n",(0,n.jsx)(A.p,{children:"This code will create 10,000 bootstrapped samples and calculate the median for each of them, but a different\nreasonable number can be used instead. Since these samples are all random, the information in each sample and\nmedian will be different from one another."}),"\n",(0,n.jsx)(A.hr,{}),"\n",(0,n.jsx)(A.h3,{id:"4-create-a-95-confidence-interval",children:"4. Create a 95% confidence interval"}),"\n",(0,n.jsx)(A.p,{children:"Instead of using a single number to estimate the true population parameter, we create a range of where we think it is."}),"\n",(0,n.jsx)(A.pre,{children:(0,n.jsx)(A.code,{className:"language-python",children:"# Get the 95% confidence interval\nleft = np.percentile(boot_medians, 2.5) # 2.5th percentile\nright = np.percentile(boot_medians, 97.5) # 97.5th percentile\n"})}),"\n",(0,n.jsx)(A.p,{children:"Remember that the 95% confidence interval does not mean we have a 95% chance of containing the true population parameter. It means\nthat about 95% of all intervals we create will contain the true population parameter."}),"\n",(0,n.jsx)(A.hr,{}),"\n",(0,n.jsx)(A.h3,{id:"5-conclusion",children:"5. Conclusion"}),"\n",(0,n.jsx)(A.pre,{children:(0,n.jsx)(A.code,{className:"language-python",children:"left, right\n"})}),"\n",(0,n.jsx)(A.p,{children:"(1.75, 40.0)"}),"\n",(0,n.jsx)(A.admonition,{title:"Conclusion",type:"info",children:(0,n.jsxs)(A.ul,{children:["\n",(0,n.jsx)(A.li,{children:"From this interval, we are 95% confident that the true population median lies somewhere between 1.75 and 40."}),"\n",(0,n.jsx)(A.li,{children:"We have no way of knowing where exactly in this interval does the true population median falls or even if it is contained at all."}),"\n",(0,n.jsx)(A.li,{children:"What we do know is that if we were to repeat the process and generate multiple confidence intervals, roughly 95% of them will\ncontain the true population median."}),"\n"]})}),"\n",(0,n.jsx)(A.hr,{}),"\n",(0,n.jsx)(A.h3,{id:"6-extra",children:"6. Extra"}),"\n",(0,n.jsx)(A.p,{children:"Let's look at the distribution of the bootstrapped medians!"}),"\n",(0,n.jsx)(A.pre,{children:(0,n.jsx)(A.code,{className:"language-python",children:"# Create the histogram.\n# Plot the histogram of boot_medians\nplt.hist(boot_medians, bins=20, density=True, ec = 'w')\n\nplt.show()\n"})}),"\n",(0,n.jsx)(A.p,{children:(0,n.jsx)(A.img,{alt:"Distribution",src:t(6558).A+"",width:"556",height:"413"})}),"\n",(0,n.jsxs)(A.p,{children:["A 95% confidence level means that ",(0,n.jsx)(A.strong,{children:"approximately 95% of the time, the intervals you create through this process will contain the true population parameter"}),"."]})]})}function h(e={}){const{wrapper:A}={...(0,a.R)(),...e.components};return A?(0,n.jsx)(A,{...e,children:(0,n.jsx)(p,{...e})}):p(e)}},8597:(e,A,t)=>{t.d(A,{A:()=>a});t(6540);var n=t(4848);const a=e=>{let{data:A}=e,t=[],a=[],s="",i=[];if(A){const 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e.languages.kotlin["class-name"];var t={"interpolation-punctuation":{pattern:/^\$\{?|\}$/,alias:"punctuation"},expression:{pattern:/[\s\S]+/,inside:e.languages.kotlin}};e.languages.insertBefore("kotlin","string",{"string-literal":[{pattern:/"""(?:[^$]|\$(?:(?!\{)|\{[^{}]*\}))*?"""/,alias:"multiline",inside:{interpolation:{pattern:/\$(?:[a-z_]\w*|\{[^{}]*\})/i,inside:t},string:/[\s\S]+/}},{pattern:/"(?:[^"\\\r\n$]|\\.|\$(?:(?!\{)|\{[^{}]*\}))*"/,alias:"singleline",inside:{interpolation:{pattern:/((?:^|[^\\])(?:\\{2})*)\$(?:[a-z_]\w*|\{[^{}]*\})/i,lookbehind:!0,inside:t},string:/[\s\S]+/}}],char:{pattern:/'(?:[^'\\\r\n]|\\(?:.|u[a-fA-F0-9]{0,4}))'/,greedy:!0}}),delete e.languages.kotlin.string,e.languages.insertBefore("kotlin","keyword",{annotation:{pattern:/\B@(?:\w+:)?(?:[A-Z]\w*|\[[^\]]+\])/,alias:"builtin"}}),e.languages.insertBefore("kotlin","function",{label:{pattern:/\b\w+@|@\w+\b/,alias:"symbol"}}),e.languages.kt=e.languages.kotlin,e.languages.kts=e.languages.kotlin}(T),T.languages.c=T.languages.extend("clike",{comment:{pattern:/\/\/(?:[^\r\n\\]|\\(?:\r\n?|\n|(?![\r\n])))*|\/\*[\s\S]*?(?:\*\/|$)/,greedy:!0},string:{pattern:/"(?:\\(?:\r\n|[\s\S])|[^"\\\r\n])*"/,greedy:!0},"class-name":{pattern:/(\b(?:enum|struct)\s+(?:__attribute__\s*\(\([\s\S]*?\)\)\s*)?)\w+|\b[a-z]\w*_t\b/,lookbehind:!0},keyword:/\b(?:_Alignas|_Alignof|_Atomic|_Bool|_Complex|_Generic|_Imaginary|_Noreturn|_Static_assert|_Thread_local|__attribute__|asm|auto|break|case|char|const|continue|default|do|double|else|enum|extern|float|for|goto|if|inline|int|long|register|return|short|signed|sizeof|static|struct|switch|typedef|typeof|union|unsigned|void|volatile|while)\b/,function:/\b[a-z_]\w*(?=\s*\()/i,number:/(?:\b0x(?:[\da-f]+(?:\.[\da-f]*)?|\.[\da-f]+)(?:p[+-]?\d+)?|(?:\b\d+(?:\.\d*)?|\B\.\d+)(?:e[+-]?\d+)?)[ful]{0,4}/i,operator:/>>=?|<<=?|->|([-+&|:])\1|[?:~]|[-+*/%&|^!=<>]=?/}),T.languages.insertBefore("c","string",{char:{pattern:/'(?:\\(?:\r\n|[\s\S])|[^'\\\r\n]){0,32}'/,greedy:!0}}),T.languages.insertBefore("c","string",{macro:{pattern:/(^[\t 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t=/\/\*(?:[^*/]|\*(?!\/)|\/(?!\*)|<self>)*\*\//.source,n=0;n<2;n++)t=t.replace(/<self>/g,(function(){return 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T.languages.go["class-name"],function(e){var t=/\b(?:alignas|alignof|asm|auto|bool|break|case|catch|char|char16_t|char32_t|char8_t|class|co_await|co_return|co_yield|compl|concept|const|const_cast|consteval|constexpr|constinit|continue|decltype|default|delete|do|double|dynamic_cast|else|enum|explicit|export|extern|final|float|for|friend|goto|if|import|inline|int|int16_t|int32_t|int64_t|int8_t|long|module|mutable|namespace|new|noexcept|nullptr|operator|override|private|protected|public|register|reinterpret_cast|requires|return|short|signed|sizeof|static|static_assert|static_cast|struct|switch|template|this|thread_local|throw|try|typedef|typeid|typename|uint16_t|uint32_t|uint64_t|uint8_t|union|unsigned|using|virtual|void|volatile|wchar_t|while)\b/,n=/\b(?!<keyword>)\w+(?:\s*\.\s*\w+)*\b/.source.replace(/<keyword>/g,(function(){return 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e.languages.kotlin["class-name"];var t={"interpolation-punctuation":{pattern:/^\$\{?|\}$/,alias:"punctuation"},expression:{pattern:/[\s\S]+/,inside:e.languages.kotlin}};e.languages.insertBefore("kotlin","string",{"string-literal":[{pattern:/"""(?:[^$]|\$(?:(?!\{)|\{[^{}]*\}))*?"""/,alias:"multiline",inside:{interpolation:{pattern:/\$(?:[a-z_]\w*|\{[^{}]*\})/i,inside:t},string:/[\s\S]+/}},{pattern:/"(?:[^"\\\r\n$]|\\.|\$(?:(?!\{)|\{[^{}]*\}))*"/,alias:"singleline",inside:{interpolation:{pattern:/((?:^|[^\\])(?:\\{2})*)\$(?:[a-z_]\w*|\{[^{}]*\})/i,lookbehind:!0,inside:t},string:/[\s\S]+/}}],char:{pattern:/'(?:[^'\\\r\n]|\\(?:.|u[a-fA-F0-9]{0,4}))'/,greedy:!0}}),delete e.languages.kotlin.string,e.languages.insertBefore("kotlin","keyword",{annotation:{pattern:/\B@(?:\w+:)?(?:[A-Z]\w*|\[[^\]]+\])/,alias:"builtin"}}),e.languages.insertBefore("kotlin","function",{label:{pattern:/\b\w+@|@\w+\b/,alias:"symbol"}}),e.languages.kt=e.languages.kotlin,e.languages.kts=e.languages.kotlin}(T),T.languages.c=T.languages.extend("clike",{comment:{pattern:/\/\/(?:[^\r\n\\]|\\(?:\r\n?|\n|(?![\r\n])))*|\/\*[\s\S]*?(?:\*\/|$)/,greedy:!0},string:{pattern:/"(?:\\(?:\r\n|[\s\S])|[^"\\\r\n])*"/,greedy:!0},"class-name":{pattern:/(\b(?:enum|struct)\s+(?:__attribute__\s*\(\([\s\S]*?\)\)\s*)?)\w+|\b[a-z]\w*_t\b/,lookbehind:!0},keyword:/\b(?:_Alignas|_Alignof|_Atomic|_Bool|_Complex|_Generic|_Imaginary|_Noreturn|_Static_assert|_Thread_local|__attribute__|asm|auto|break|case|char|const|continue|default|do|double|else|enum|extern|float|for|goto|if|inline|int|long|register|return|short|signed|sizeof|static|struct|switch|typedef|typeof|union|unsigned|void|volatile|while)\b/,function:/\b[a-z_]\w*(?=\s*\()/i,number:/(?:\b0x(?:[\da-f]+(?:\.[\da-f]*)?|\.[\da-f]+)(?:p[+-]?\d+)?|(?:\b\d+(?:\.\d*)?|\B\.\d+)(?:e[+-]?\d+)?)[ful]{0,4}/i,operator:/>>=?|<<=?|->|([-+&|:])\1|[?:~]|[-+*/%&|^!=<>]=?/}),T.languages.insertBefore("c","string",{char:{pattern:/'(?:\\(?:\r\n|[\s\S])|[^'\\\r\n]){0,32}'/,greedy:!0}}),T.languages.insertBefore("c","string",{macro:{pattern:/(^[\t 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t=/\/\*(?:[^*/]|\*(?!\/)|\/(?!\*)|<self>)*\*\//.source,n=0;n<2;n++)t=t.replace(/<self>/g,(function(){return 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T.languages.go["class-name"],function(e){var t=/\b(?:alignas|alignof|asm|auto|bool|break|case|catch|char|char16_t|char32_t|char8_t|class|co_await|co_return|co_yield|compl|concept|const|const_cast|consteval|constexpr|constinit|continue|decltype|default|delete|do|double|dynamic_cast|else|enum|explicit|export|extern|final|float|for|friend|goto|if|import|inline|int|int16_t|int32_t|int64_t|int8_t|long|module|mutable|namespace|new|noexcept|nullptr|operator|override|private|protected|public|register|reinterpret_cast|requires|return|short|signed|sizeof|static|static_assert|static_cast|struct|switch|template|this|thread_local|throw|try|typedef|typeid|typename|uint16_t|uint32_t|uint64_t|uint8_t|union|unsigned|using|virtual|void|volatile|wchar_t|while)\b/,n=/\b(?!<keyword>)\w+(?:\s*\.\s*\w+)*\b/.source.replace(/<keyword>/g,(function(){return 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b/blog/archive/index.html @@ -2,7 +2,7 @@ <html lang="en" dir="ltr" class="plugin-blog plugin-id-default" data-has-hydrated="false"> <head> <meta charset="UTF-8"> -<meta name="generator" content="Docusaurus v3.2.1"> +<meta name="generator" content="Docusaurus v3.3.2"> <title data-rh="true">Archive | bpd @@ -10,9 +10,9 @@ - - - + + +diff --git a/blog/first-blog-post/index.html b/blog/first-blog-post/index.html index fdf1b4f2..aae4f0b4 100644 --- a/blog/first-blog-post/index.html +++ b/blog/first-blog-post/index.html @@ -2,7 +2,7 @@ - +First Blog Post | bpd @@ -10,9 +10,9 @@ - - - + + +diff --git a/blog/index.html b/blog/index.html index e19812e0..a8934ff8 100644 --- a/blog/index.html +++ b/blog/index.html @@ -2,7 +2,7 @@ - +First Blog Post
· One min readDocusaurus Core TeamLorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
Blog | bpd @@ -10,9 +10,9 @@ - - - + + +Welcome
· One min readDocusaurus maintainerFront End Engineer @ FacebookDocusaurus blogging features are powered by the blog plugin.
diff --git a/blog/long-blog-post/index.html b/blog/long-blog-post/index.html index b2e2429f..52add315 100644 --- a/blog/long-blog-post/index.html +++ b/blog/long-blog-post/index.html @@ -2,7 +2,7 @@ - +Long Blog Post | bpd @@ -10,9 +10,9 @@ - - - + + +Long Blog Post
· 3 min readMaintainer of DocusaurusThis is the summary of a very long blog post,
diff --git a/blog/mdx-blog-post/index.html b/blog/mdx-blog-post/index.html index 1cd92342..186c72c0 100644 --- a/blog/mdx-blog-post/index.html +++ b/blog/mdx-blog-post/index.html @@ -2,7 +2,7 @@ - +MDX Blog Post | bpd @@ -10,9 +10,9 @@ - - - + + +MDX Blog Post
· One min readDocusaurus maintainerBlog posts support Docusaurus Markdown features, such as MDX.
diff --git a/blog/tags/docusaurus/index.html b/blog/tags/docusaurus/index.html index 509d6065..0df111b8 100644 --- a/blog/tags/docusaurus/index.html +++ b/blog/tags/docusaurus/index.html @@ -2,7 +2,7 @@ - +4 posts tagged with "docusaurus" | bpd @@ -10,9 +10,9 @@ - - - + + +4 posts tagged with "docusaurus"
View All TagsWelcome
· One min readDocusaurus maintainerFront End Engineer @ FacebookDocusaurus blogging features are powered by the blog plugin.
diff --git a/blog/tags/facebook/index.html b/blog/tags/facebook/index.html index 037f053f..34c17ed0 100644 --- a/blog/tags/facebook/index.html +++ b/blog/tags/facebook/index.html @@ -2,7 +2,7 @@ - +One post tagged with "facebook" | bpd @@ -10,9 +10,9 @@ - - - + + +One post tagged with "facebook"
View All TagsWelcome
· One min readDocusaurus maintainerFront End Engineer @ FacebookDocusaurus blogging features are powered by the blog plugin.
diff --git a/blog/tags/hello/index.html b/blog/tags/hello/index.html index 39d8e38e..c271c219 100644 --- a/blog/tags/hello/index.html +++ b/blog/tags/hello/index.html @@ -2,7 +2,7 @@ - +2 posts tagged with "hello" | bpd @@ -10,9 +10,9 @@ - - - + + +2 posts tagged with "hello"
View All TagsWelcome
· One min readDocusaurus maintainerFront End Engineer @ FacebookDocusaurus blogging features are powered by the blog plugin.
diff --git a/blog/tags/hola/index.html b/blog/tags/hola/index.html index d992d1d6..df17fb27 100644 --- a/blog/tags/hola/index.html +++ b/blog/tags/hola/index.html @@ -2,7 +2,7 @@ - +One post tagged with "hola" | bpd @@ -10,9 +10,9 @@ - - - + + +diff --git a/blog/tags/index.html b/blog/tags/index.html index 65c77991..a6791b7c 100644 --- a/blog/tags/index.html +++ b/blog/tags/index.html @@ -2,7 +2,7 @@ - +One post tagged with "hola"
View All TagsFirst Blog Post
· One min readDocusaurus Core TeamLorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
Tags | bpd @@ -10,9 +10,9 @@ - - - + + + diff --git a/blog/welcome/index.html b/blog/welcome/index.html index 3e1e9e53..376bb70a 100644 --- a/blog/welcome/index.html +++ b/blog/welcome/index.html @@ -2,7 +2,7 @@ - +Welcome | bpd @@ -10,9 +10,9 @@ - - - + + +Welcome
· One min readDocusaurus maintainerFront End Engineer @ FacebookDocusaurus blogging features are powered by the blog plugin.
diff --git a/docs/category/if-statements/index.html b/docs/category/if-statements/index.html index a34a1bfd..d7702379 100644 --- a/docs/category/if-statements/index.html +++ b/docs/category/if-statements/index.html @@ -2,7 +2,7 @@ - +if-statements | bpd @@ -10,9 +10,9 @@ - - - + + +diff --git a/docs/category/querying/index.html b/docs/category/querying/index.html index 40a0ff8b..8d540df7 100644 --- a/docs/category/querying/index.html +++ b/docs/category/querying/index.html @@ -2,7 +2,7 @@ - +Querying | bpd @@ -10,9 +10,9 @@ - - - + + +diff --git a/docs/documentation/Functions/Applying Functions/index.html b/docs/documentation/Functions/Applying Functions/index.html index 3977d002..c8f39662 100644 --- a/docs/documentation/Functions/Applying Functions/index.html +++ b/docs/documentation/Functions/Applying Functions/index.html @@ -2,7 +2,7 @@ - +Querying
Create a new dataframe containing only rows satisfying a condition
📄️ df[]
df[condition]
Applying Functions | bpd @@ -10,9 +10,9 @@ - - - + + +Applying Functions
df.get(column_name).apply(function_name)diff --git a/docs/documentation/Functions/Writing Functions/index.html b/docs/documentation/Functions/Writing Functions/index.html index 192373ef..96d167b7 100644 --- a/docs/documentation/Functions/Writing Functions/index.html +++ b/docs/documentation/Functions/Writing Functions/index.html @@ -2,7 +2,7 @@ - +Writing Functions | bpd @@ -10,9 +10,9 @@ - - - + + +Writing Functions
def function_name(parameters):diff --git a/docs/documentation/Grouping/aggregation/count()/index.html b/docs/documentation/Grouping/aggregation/count()/index.html index ab8c40a9..c45bb509 100644 --- a/docs/documentation/Grouping/aggregation/count()/index.html +++ b/docs/documentation/Grouping/aggregation/count()/index.html @@ -2,7 +2,7 @@ - +count() | bpd @@ -10,9 +10,9 @@ - - - + + +count()
df.groupby(column_name).count()diff --git a/docs/documentation/Grouping/aggregation/max()/index.html b/docs/documentation/Grouping/aggregation/max()/index.html index 0ef92252..28bf8c1d 100644 --- a/docs/documentation/Grouping/aggregation/max()/index.html +++ b/docs/documentation/Grouping/aggregation/max()/index.html @@ -2,7 +2,7 @@ - +max() | bpd @@ -10,9 +10,9 @@ - - - + + +max()
df.groupby(column_name).max()diff --git a/docs/documentation/Grouping/aggregation/mean()/index.html b/docs/documentation/Grouping/aggregation/mean()/index.html index 4612d34d..a2aca22a 100644 --- a/docs/documentation/Grouping/aggregation/mean()/index.html +++ b/docs/documentation/Grouping/aggregation/mean()/index.html @@ -2,7 +2,7 @@ - +mean() | bpd @@ -10,9 +10,9 @@ - - - + + +mean()
df.groupby(column_name).mean()diff --git a/docs/documentation/Grouping/aggregation/median()/index.html b/docs/documentation/Grouping/aggregation/median()/index.html index 0077b669..731575c6 100644 --- a/docs/documentation/Grouping/aggregation/median()/index.html +++ b/docs/documentation/Grouping/aggregation/median()/index.html @@ -2,7 +2,7 @@ - +median() | bpd @@ -10,9 +10,9 @@ - - - + + +median()
df.groupby(column_name).median()diff --git a/docs/documentation/Grouping/aggregation/min()/index.html b/docs/documentation/Grouping/aggregation/min()/index.html index e4a5e85b..4a7d31d9 100644 --- a/docs/documentation/Grouping/aggregation/min()/index.html +++ b/docs/documentation/Grouping/aggregation/min()/index.html @@ -2,7 +2,7 @@ - +min() | bpd @@ -10,9 +10,9 @@ - - - + + +min()
df.groupby(column_name).min()diff --git a/docs/documentation/Grouping/aggregation/sum()/index.html b/docs/documentation/Grouping/aggregation/sum()/index.html index fed6f084..f7a740f4 100644 --- a/docs/documentation/Grouping/aggregation/sum()/index.html +++ b/docs/documentation/Grouping/aggregation/sum()/index.html @@ -2,7 +2,7 @@ - +sum() | bpd @@ -10,9 +10,9 @@ - - - + + +sum()
df.groupby(column_name).sum()diff --git a/docs/documentation/Grouping/groupby/index.html b/docs/documentation/Grouping/groupby/index.html index 2ff05c94..5cc6d0fc 100644 --- a/docs/documentation/Grouping/groupby/index.html +++ b/docs/documentation/Grouping/groupby/index.html @@ -2,7 +2,7 @@ - +groupby | bpd @@ -10,9 +10,9 @@ - - - + + +groupby
df.groupby(column_name)diff --git a/docs/documentation/accessing-data/df.columns/index.html b/docs/documentation/accessing-data/df.columns/index.html index b283773e..24b11d52 100644 --- a/docs/documentation/accessing-data/df.columns/index.html +++ b/docs/documentation/accessing-data/df.columns/index.html @@ -2,7 +2,7 @@ - +df.columns | bpd @@ -10,9 +10,9 @@ - - - + + +df.columns
df.columnsdiff --git a/docs/documentation/accessing-data/df.get()/index.html b/docs/documentation/accessing-data/df.get()/index.html index 9f51c028..7659582f 100644 --- a/docs/documentation/accessing-data/df.get()/index.html +++ b/docs/documentation/accessing-data/df.get()/index.html @@ -2,7 +2,7 @@ - +df.get() | bpd @@ -10,9 +10,9 @@ - - - + + +df.get()
df.get(column_name)diff --git a/docs/documentation/accessing-data/df.index/index.html b/docs/documentation/accessing-data/df.index/index.html index dcf7d953..45f5a725 100644 --- a/docs/documentation/accessing-data/df.index/index.html +++ b/docs/documentation/accessing-data/df.index/index.html @@ -2,7 +2,7 @@ - +df.index | bpd @@ -10,9 +10,9 @@ - - - + + +
