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Exam Cheat Sheet |
Cheat sheet for quizzes and exams |
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This cheat sheet has been modified from the Data 6 Python Reference and includes all of the functions and table methods that you will need for the final exam.
| Function | Description | Input | Output |
| str(val) | Converts val to a string | A value of any type | The value as a string |
| int(num) | Converts num to an int | A numerical value (string or float) | The value as an int |
| float(num) | Converts num to a float | A numerical value (string or int) | The value as a float |
| len(arr) | Returns the length of arr | array or list | int: the length of the array or list |
| max(arr) or min(arr) | Returns the maximum or minimum value in arr | array or list | The maximum or minimum value the array (usually an int) |
| sum(arr) | Returns the sum of the values in arr | array or list | int or float: the sum of the values in the array |
| abs(num) | Returns the absolute value of num | int or float | int or float |
| Function | Description | Input | Output |
| make_array(val1, val2, ...) | Makes a NumPy array with the inputted values | A sequence of values | An array with those values |
| np.mean(arr) or np.average(arr) | Calculates the average value of arr | An array of numbers | float: array average |
| np.arange(stop), np.arange(start, stop), or np.arange(start, stop, step) | Creates an array of numbers starting at start, going up in increments of step (default is 1), and going up to but excluding stop. | int or float | array |
| np.append(arr, item) | Appends item to the end of arr. Does not modify the original array. | 1. array to append to
2. item to append (any type) | array: a new array with the appended item |
| arr.item(i) | Returns the i-th item in an array (remember Python indices start at 0!) | int | Depends on array type|
| Function | Description | Input | Output |
| tbl.with_column(name, values) | Adds an extra column onto tbl with the label name and values as the column values | 1. string: name of the new column
2. array: values in the column | Table: a copy of the original table with the new column |
| tbl.column(col) | Returns the values in a column | string or int: the column name or index | array: the values in that column |
| tbl.num_rows, tbl.num_columns | Computes the number of rows or columnsin tbl | None | int: number of rows or columns in the table |
| tbl.select(col1, col2, ...) | Creates a copy of tbl only with the selected columns | string or int: the column name(s) or index(es) to be included in the table | Table with the selected columns |
| tbl.drop(col1, col2, ...) | Creates a copy of tbl without the selected columns | string or int: the column name(s) or index(es) to be dropped from the table | Table without the selected columns |
| tbl.sort(column_name) | Sorts the rows of tbl by the values in the column_name column. | 1. string or int: name or index of the column to sort
2. (Optional) descending=True | Table: a copy of the original table sorted by the column |
| tbl.where(column, predicate) | Creates a copy of tbl containing only the rows where the value of column matches the predicate. See Table.where predicates below. | 1. string or int: column name or index
2. are.(...) predicate | Table: a copy of the original table with only the rows that match the predicate |
| tbl.take(row_indices) | Creates a table with only the rows at the given indices. row_indices is either an array of indices or an integer corresponding to one index. | int or array: indices of rows to be included in the table | Table: copy of the original table with the rows at the given indices |
| tbl.apply(function) or tbl.apply(function, col1, col2, ...) | Returns an array of values resulting from applying a function to each item in a column. | 1. Function: function to apply to column
2. (Optional) string or int: the column name(s) or index(es) to apply the function to | array containing an element for each value in the original column after applying the function |
| tbl.group(column, function) | Groups rows in tbl by unique values in a column. Values in the other columns are aggregated by count (by default) or the optional argument function. | 1. string: column on which to group
2. (Optional) Function: function to aggregate values in cells (defaults to counting rows) | Table a new groupped table |
| tbl.pivot(col1, col2, values, collect) | Creates a pivot table where each unique value in col1 has its own column and each unique value in col2 has its own row. Counts or aggregates values from a third column, collected with some function. | 1. string: column in tbl for the pivot table columns
2. string: column in tbl for the pivot table rows
3. (Optional) string: column in tbl for the pivot table values
4. (Optional) Function: how the values are collected | Table: a new pivot table |
| tblA.join(colA, tblB, colB) | Generate a table with the columns of tblA and tblB, containing rows for all values in colA and colB that appear in tblA and tblB, respectively. | 1. string: name of column in tblA
2. Table: the other table
3. (Optional) string: the name of the shared column in tblB | Table: a new combined table |
|tbl.sample(k, with_replacement, weights) | A new table where n rows are randomly sampled from the original table; by default, k=tbl.num_rows. Default is with replacement. For sampling without replacement, use argument with_replacement=False. For a non-uniform sample, provide a third argument weights=distribution where distribution is an array or list containing the probability of each row.|Table|Table: A new table with k randomly sampled rows.|
| Function | Description | Input | Output |
| tbl.barh(categories) or tbl.barh(categories, values) | Displays a horizontal bar chart with bars for each category in the column categories. values specifies the column corresponding to the size of each bar. | 1. string: name of the column with categories
2. (Optional) string: name of categories column | None: draws a bar chart |
| tbl.hist(column) | Generates a histogram of the numerical values in column. | string: name of the column | None: draws a histogram |
| tbl.plot(x_column, y_column) or tbl.plot(x_column) | Draws a line plot consisting of one point for each row in tbl. If only x_column is specified, plot will plot the rest of the columns on the y-axis with different colored lines. | 1. string: name of the column on the x-axis
2. string: name of the column on the y-axis | None: draws a line graph |
| tbl.scatter(x_column, y_column) | Draws a scatter plot consisting of one point for each row in tbl. | 1. string: x-axis column
2. string: y-axis column | None: draws a scatter plot |
These functions can be passed in as the second argument to tbl.where(..) and act as a condition by which to select rows from tbl.
| Predicate | Description |
| are.equal_to(Z) | Equal to Z (can be an int, float or string) |
| are.above(x), are.above_or_equal_to(x) | Greater than (or equal to) x |
| are.below(x), are.below_or_equal_to(x) | Less than (or equal to) x |
| are.between(x,y), are.between_or_equal_to(x,y) | Greater than (or equal to) x, and less than (or equal to) y |
| are.strictly_between(x,y) | Greater than x and less than y |
| are.contained_in(A) | True if it is a substring of A (if Ais a **string**) or an element ofA(ifAis an **array**) | |are.containing(S)| Contains the stringS` |
| Syntax | Description |
| if <if expression>:
<if body>
elif <elif expression>:
<elif body>
else:
<else body>| Executes the code in <if body> only if <if expression> evaluates to True. If <if expression> is False, checks <elif expression> and executes code in <elif body> if True. Otherwise, executes the code in <else body> |
| for <element> in <sequence>:
<for body> | Repeats code in <for body> for each <element> in <sequence> (array, string, etc.), assigning <element> to each value in <sequence> one at a time |
| while <boolean expression>:
<while_body> | Repeats code in <while body> while <boolean expression> is True |
| Name | Symbol | Usage | | Equal | == | x == y | | Not equal | != | x != y | | Greater than | > | x > y | | Greater than or equal to | >= | x >= y | | Less than | < | x < y | | Less than or equal to | <= | x <= y |
| Symbol | Usage | Value |
| and | a and b | True if both a and b are True, False otherwise |
| or | a or b | True if at least one of a and b are True, False otherwise |
| not | not a | True if a is False, False if a is True |
| Function | Description | Input | Output |
| np.random.seed(seed) | Selects one of np.random's pre-generated 'random' sequences and starts at the beginning of the sequence. Each time the function is re-run it will restart the random numbers generated by np.random.randint at the beginning of the sequence corresponding to the given seed. | int: seed number | None |
| np.random.randint(low, high, size) | Generates size many random numbers between low (inclusive) and high (exclusive) using a pre-generated sequence of random numbers (corresponding to the specified seed). | 1. int: minimum value that can be generated
2. int: the first value that cannot be generated (upper endpoint) 3. int: the number of random numbers to be generated. | int: a random number or array: a array of length size of random numbers |
| np.random.choice(choices, n) | Selects n items at random from the array of choices. Each element in the array has an equal chance of being selected each time the function is called. | array: the choices of values to choose from, int: the number of values chosen | int(s), string(s), etc: the random selection |