From b967346749c2a73222a733180d72b719abdf213d Mon Sep 17 00:00:00 2001 From: lshpaner Date: Fri, 26 Jul 2024 23:02:51 -0700 Subject: [PATCH] updated class_esrd_outcomes documentation --- docs/.doctrees/environment.pickle | Bin 3726390 -> 3735395 bytes docs/.doctrees/usage_guide.doctree | Bin 143115 -> 149101 bytes docs/_sources/usage_guide.rst.txt | 107 ++++++++++++++++++++-------- docs/searchindex.js | 2 +- docs/usage_guide.html | 108 ++++++++++++++++++++++------- source/usage_guide.rst | 107 ++++++++++++++++++++-------- 6 files changed, 242 insertions(+), 82 deletions(-) diff --git a/docs/.doctrees/environment.pickle b/docs/.doctrees/environment.pickle index 8d80fe081e37798bf28fa6f47c014be3d680f13b..724f963f749552fd40ff81427584c03b604a701f 100644 GIT binary patch literal 3735395 zcmeEv34k0&b+&b^R$ASXE#G!q*w$*D`{z?96x$ zNoyl80Xve@`AL2cm?L*W0tpEO0tqDW^Cv(^@`nWYLlOcxOfCo^Bq7Hi_<#QIy{hW2 z>gnD&c6M>V0?&3=Raez}_1>$h_g=kvyyp#zE?aaN{qr|eN^Y)jKIIh7=E}vwv{R_o 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years: The number of years to use in the condition. :param str duration_col: The name of the column containing the duration data. - :param str prefix: (`optional`) Custom prefix for the new column name. If None, no prefix is added. + :param str prefix: (`optional`) Custom prefix for the new column name. If ``None``, no prefix is added. :param bool create_years_col: (`optional`) Whether to create the 'years' column. Default is True. :returns: ``pd.DataFrame``: The modified DataFrame with the new column added. -This function creates a new column in the DataFrame which is populated with a 1 or a 0 based on whether the ESRD condition (eGFR < 15) is met within the specified number of years. If `create_years_col` is set to True, it calculates the 'years' column based on the `duration_col` provided. If False, it uses the `duration_col` directly. The new column is named using the specified prefix and number of years, or just the number of years if no prefix is provided. +This function creates a new column in the DataFrame which is populated with a ``1`` or a ``0`` based on whether the ESRD condition (eGFR < 15) is met within the specified number of years. If ``create_years_col`` is set to ``True``, it calculates the 'years' column based on the ``duration_col`` provided. If ``False``, it uses the ``duration_col`` directly. The new column is named using the specified prefix and number of years, or just the number of years if no prefix is provided. + + +**Example Usage** + +.. code-block:: python + + from kfre import class_esrd_outcome + +.. code-block:: python + + # 2-year outcome + df = class_esrd_outcome( + df=df, + col="ESRD", + years=2, + duration_col="Follow-up YEARS", + prefix=None, + create_years_col=False, + ) + + # 5-year outcome + df = class_esrd_outcome( + df=df, + col="ESRD", + years=5, + duration_col="Follow-up YEARS", + prefix=None, + create_years_col=False, + ) + + +.. raw:: html + +

+ +.. table:: + :align: left + + + ====== =============== =============== + Index 2_year_outcome 5_year_outcome + ====== =============== =============== + 0 0 0 + 1 1 1 + 2 0 0 + 3 1 1 + 4 0 0 + ====== =============== =============== + Batch Risk Calculation for Multiple Patients @@ -435,6 +488,30 @@ This function is designed to compute the risk of chronic kidney disease (CKD) ov The ``sex_col`` must contain strings (case-insensitive) indicating either `female` or `male`. +**Example Usage** + +.. code-block:: python + + df = add_kfre_risk_col( + df=df, + age_col="Age", + sex_col="SEX", + eGFR_col="eGFR-EPI", + uACR_col="uACR", + dm_col="Diabetes (1=yes; 0=no)", + htn_col="Hypertension (1=yes; 0=no)", + albumin_col="Albumin_g_dl", + phosphorous_col="Phosphate_mg_dl", + bicarbonate_col="Bicarbonate (mmol/L)", + calcium_col="Calcium_mg_dl", + num_vars=8, + years=(2, 5), + is_north_american=False, + copy=False # Modify the original DataFrame directly + ) + # The resulting DataFrame 'df' now includes new columns with risk + # predictions for each model and time frame + .. raw:: html
@@ -459,29 +536,3 @@ This function is designed to compute the risk of chronic kidney disease (CKD) ov 69.92 Male 0 0 12.0 74.299919 1 1 0.524577 0.174712 0.190458 0.551506 0.305670 0.806220 81.14 Female 1 1 15.0 59.683881 0 0 0.255029 0.073213 0.068968 0.237542 0.060353 0.244235 ======== ====== ======================== ========================== ========= ============ ================ ================ ================ ================ ================ ================ ================ ================ - - -**Example Usage** - -.. code-block:: python - - df = add_kfre_risk_col( - df=df, - age_col="Age", - sex_col="SEX", - eGFR_col="eGFR-EPI", - uACR_col="uACR", - dm_col="Diabetes (1=yes; 0=no)", - htn_col="Hypertension (1=yes; 0=no)", - albumin_col="Albumin_g_dl", - phosphorous_col="Phosphate_mg_dl", - bicarbonate_col="Bicarbonate (mmol/L)", - calcium_col="Calcium_mg_dl", - num_vars=8, - years=(2, 5), - is_north_american=False, - copy=False # Modify the original DataFrame directly - ) - 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Classifying ESRD Outcome by 2 and 5 Year Outcomes

col (str) – The column name with ESRD (should be eGFR < 15 flag).

  • years (int) – The number of years to use in the condition.

  • duration_col (str) – The name of the column containing the duration data.

  • -
  • prefix (str) – (optional) Custom prefix for the new column name. If None, no prefix is added.

  • +
  • prefix (str) – (optional) Custom prefix for the new column name. If None, no prefix is added.

  • create_years_col (bool) – (optional) Whether to create the ‘years’ column. Default is True.

  • @@ -518,7 +518,66 @@

    Classifying ESRD Outcome by 2 and 5 Year Outcomes -

    This function creates a new column in the DataFrame which is populated with a 1 or a 0 based on whether the ESRD condition (eGFR < 15) is met within the specified number of years. If create_years_col is set to True, it calculates the ‘years’ column based on the duration_col provided. If False, it uses the duration_col directly. The new column is named using the specified prefix and number of years, or just the number of years if no prefix is provided.

    +

    This function creates a new column in the DataFrame which is populated with a 1 or a 0 based on whether the ESRD condition (eGFR < 15) is met within the specified number of years. If create_years_col is set to True, it calculates the ‘years’ column based on the duration_col provided. If False, it uses the duration_col directly. The new column is named using the specified prefix and number of years, or just the number of years if no prefix is provided.

    +

    Example Usage

    +
    from kfre import class_esrd_outcome
    +
    +
    +
    # 2-year outcome
    +df = class_esrd_outcome(
    +    df=df,
    +    col="ESRD",
    +    years=2,
    +    duration_col="Follow-up YEARS",
    +    prefix=None,
    +    create_years_col=False,
    +)
    +
    +# 5-year outcome
    +df = class_esrd_outcome(
    +    df=df,
    +    col="ESRD",
    +    years=5,
    +    duration_col="Follow-up YEARS",
    +    prefix=None,
    +    create_years_col=False,
    +)
    +
    +
    +
    + +First 5 Rows of Outcome Data + +
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

    Index

    2_year_outcome

    5_year_outcome

    0

    0

    0

    1

    1

    1

    2

    0

    0

    3

    1

    1

    4

    0

    0

    Batch Risk Calculation for Multiple Patients

    @@ -581,6 +640,28 @@

    Batch Risk Calculation for Multiple PatientsImportant

    The sex_col must contain strings (case-insensitive) indicating either female or male.

    +

    Example Usage

    +
    df = add_kfre_risk_col(
    +    df=df,
    +    age_col="Age",
    +    sex_col="SEX",
    +    eGFR_col="eGFR-EPI",
    +    uACR_col="uACR",
    +    dm_col="Diabetes (1=yes; 0=no)",
    +    htn_col="Hypertension (1=yes; 0=no)",
    +    albumin_col="Albumin_g_dl",
    +    phosphorous_col="Phosphate_mg_dl",
    +    bicarbonate_col="Bicarbonate (mmol/L)",
    +    calcium_col="Calcium_mg_dl",
    +    num_vars=8,
    +    years=(2, 5),
    +    is_north_american=False,
    +    copy=False  # Modify the original DataFrame directly
    +)
    +# The resulting DataFrame 'df' now includes new columns with risk
    +# predictions for each model and time frame
    +
    +
    diff --git a/source/usage_guide.rst b/source/usage_guide.rst index 2ad1953..41dc2de 100644 --- a/source/usage_guide.rst +++ b/source/usage_guide.rst @@ -366,12 +366,65 @@ Classifying ESRD Outcome by 2 and 5 Year Outcomes :param str col: The column name with ESRD (should be eGFR < 15 flag). :param int years: The number of years to use in the condition. :param str duration_col: The name of the column containing the duration data. - :param str prefix: (`optional`) Custom prefix for the new column name. If None, no prefix is added. + :param str prefix: (`optional`) Custom prefix for the new column name. If ``None``, no prefix is added. :param bool create_years_col: (`optional`) Whether to create the 'years' column. Default is True. :returns: ``pd.DataFrame``: The modified DataFrame with the new column added. -This function creates a new column in the DataFrame which is populated with a 1 or a 0 based on whether the ESRD condition (eGFR < 15) is met within the specified number of years. If `create_years_col` is set to True, it calculates the 'years' column based on the `duration_col` provided. If False, it uses the `duration_col` directly. The new column is named using the specified prefix and number of years, or just the number of years if no prefix is provided. +This function creates a new column in the DataFrame which is populated with a ``1`` or a ``0`` based on whether the ESRD condition (eGFR < 15) is met within the specified number of years. If ``create_years_col`` is set to ``True``, it calculates the 'years' column based on the ``duration_col`` provided. If ``False``, it uses the ``duration_col`` directly. The new column is named using the specified prefix and number of years, or just the number of years if no prefix is provided. + + +**Example Usage** + +.. code-block:: python + + from kfre import class_esrd_outcome + +.. code-block:: python + + # 2-year outcome + df = class_esrd_outcome( + df=df, + col="ESRD", + years=2, + duration_col="Follow-up YEARS", + prefix=None, + create_years_col=False, + ) + + # 5-year outcome + df = class_esrd_outcome( + df=df, + col="ESRD", + years=5, + duration_col="Follow-up YEARS", + prefix=None, + create_years_col=False, + ) + + +.. raw:: html + +
    + + First 5 Rows of Outcome Data + +
    + +.. table:: + :align: left + + + ====== =============== =============== + Index 2_year_outcome 5_year_outcome + ====== =============== =============== + 0 0 0 + 1 1 1 + 2 0 0 + 3 1 1 + 4 0 0 + ====== =============== =============== + Batch Risk Calculation for Multiple Patients @@ -435,6 +488,30 @@ This function is designed to compute the risk of chronic kidney disease (CKD) ov The ``sex_col`` must contain strings (case-insensitive) indicating either `female` or `male`. +**Example Usage** + +.. code-block:: python + + df = add_kfre_risk_col( + df=df, + age_col="Age", + sex_col="SEX", + eGFR_col="eGFR-EPI", + uACR_col="uACR", + dm_col="Diabetes (1=yes; 0=no)", + htn_col="Hypertension (1=yes; 0=no)", + albumin_col="Albumin_g_dl", + phosphorous_col="Phosphate_mg_dl", + bicarbonate_col="Bicarbonate (mmol/L)", + calcium_col="Calcium_mg_dl", + num_vars=8, + years=(2, 5), + is_north_american=False, + copy=False # Modify the original DataFrame directly + ) + # The resulting DataFrame 'df' now includes new columns with risk + # predictions for each model and time frame + .. raw:: html
    @@ -459,29 +536,3 @@ This function is designed to compute the risk of chronic kidney disease (CKD) ov 69.92 Male 0 0 12.0 74.299919 1 1 0.524577 0.174712 0.190458 0.551506 0.305670 0.806220 81.14 Female 1 1 15.0 59.683881 0 0 0.255029 0.073213 0.068968 0.237542 0.060353 0.244235 ======== ====== ======================== ========================== ========= ============ ================ ================ ================ ================ ================ ================ ================ ================ - - -**Example Usage** - -.. code-block:: python - - df = add_kfre_risk_col( - df=df, - age_col="Age", - sex_col="SEX", - eGFR_col="eGFR-EPI", - uACR_col="uACR", - dm_col="Diabetes (1=yes; 0=no)", - htn_col="Hypertension (1=yes; 0=no)", - albumin_col="Albumin_g_dl", - phosphorous_col="Phosphate_mg_dl", - bicarbonate_col="Bicarbonate (mmol/L)", - calcium_col="Calcium_mg_dl", - num_vars=8, - years=(2, 5), - is_north_american=False, - copy=False # Modify the original DataFrame directly - ) - # The resulting DataFrame 'df' now includes new columns with risk - # predictions for each model and time frame - df