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Sarra NebliSarra99
Sarra Nebli
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Fixing CI errors
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‎janitor/functions/adorn.py‎

Lines changed: 56 additions & 83 deletions
Original file line numberDiff line numberDiff line change
@@ -28,35 +28,32 @@ def tabyl(
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Returns:
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A DataFrame representing the summary table.
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Example :
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>>> data = {
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... "Category": ["A", "B", "A", "B", "A", "B"],
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... "Subcategory": ["X", "X", "Y", "Y", "X", "X"],
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... "Value": [1, 2, 3, 4, 5, 6],
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... "Category": ["A", "A", "B", "B", "C", "C", "A", "B", "C", "A"],
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... "Subcategory": ["X", "Y", "X", "Y", "X", "Y", "X", "Y", "X", "X"],
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... "Region": ["North", "South", "East", "West", "North",
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... "South", "East", "West", "North", "East"],
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... "Value": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
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... }
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>>> df = pd.DataFrame(data)
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>>> result = adorn_percentages(df, col1="Category",
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col2="Subcategory", axis="row", fmt=True, include_ns=True)
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>>> result = tabyl(df, "Category", "Subcategory", show_percentages=True,
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... percentage_axis="row")
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>>> print(result)
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| Category | X | Y |
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|----------|---------|---------|
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| A | 50.0% (2) | 50.0% (2) |
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| B | 66.7% (2) | 33.3% (1) |
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Subcategory Category X Y
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0 A 3.0 (75.00%) 1.0 (25.00%)
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1 B 1.0 (33.33%) 2.0 (66.67%)
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2 C 2.0 (66.67%) 1.0 (33.33%)
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>>> result = adorn_percentages(df, col1="Category",
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col2="Subcategory", axis="col", fmt=True)
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>>> result = tabyl(df, "Category", "Subcategory",
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... show_percentages=True, percentage_axis="col")
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>>> print(result)
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| Category | X | Y |
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|----------|---------|---------|
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| A | 33.3% (1) | 50.0% (3) |
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| B | 66.7% (2) | 50.0% (3) |
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In this example:
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- The table shows counts and row-wise percentages for the `Category` and
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`Subcategory` columns.
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- The first row for Category 'A' shows 50.0% for X and 50.0% for Y,
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with counts in parentheses.
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- The second row for Category 'B' shows 66.7% for X and 33.3% for Y.
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Subcategory Category X Y
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0 A 3.0 (50.00%) 1.0 (25.00%)
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1 B 1.0 (16.67%) 2.0 (50.00%)
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2 C 2.0 (33.33%) 1.0 (25.00%)
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"""
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if col1 not in df.columns:
@@ -132,28 +129,29 @@ def adorn_totals(df, col1, col2, axis=0):
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:param axis: 0 to add a 'Total' row, 1 to add a 'Total' column
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:return: DataFrame with a 'Total' row/column added
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Example:
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>>> data = {
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... "Category": ["A", "B", "A", "B", "A", "B", "A", "B"],
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... "Subcategory": ["X", "X", "Y", "Y", "X", "X", "Y", "Y"],
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... "Value": [1, 2, 3, 4, 5, 6, 7, 8],
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... }
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>>> df = pd.DataFrame(data)
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>>> result = adorn_totals(df, col1="Category", col2="Subcategory", axis=0)
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>>> print(result)
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Category X Y Total
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A 6 12 18
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B 6 12 18
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Total 12 24 36
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Example:
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>>> data = {
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... "Category": ["A", "B", "A", "B", "A", "B", "A", "B"],
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... "Subcategory": ["X", "X", "Y", "Y", "X", "X", "Y", "Y"],
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... "Value": [1, 2, 3, 4, 5, 6, 7, 8],
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... }
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>>> df = pd.DataFrame(data)
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>>> result = adorn_totals(df, "Category", "Subcategory", axis=0)
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>>> print(result)
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Subcategory Category X Y
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0 A 2 2
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1 B 2 2
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Total NaN 4 4
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>>> result = adorn_totals(df, "Category", "Subcategory", axis=1)
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>>> print(result)
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Subcategory Category X Y Total
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0 A 2 2 4
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1 B 2 2 4
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>>> result = adorn_totals(df, col1="Category", col2="Subcategory", axis=1)
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>>> print(result)
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Category X Y Total
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A 3 3 6
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B 3 3 6
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Total 6 6 12
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"""
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# Generate the crosstab using tabyl with the two specified columns
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pivot = tabyl(df, col1, col2)
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@@ -182,47 +180,22 @@ def adorn_percentages(
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df, col1, col2, axis="row", fmt=True, include_ns=False, decimal_places=1
183181
):
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"""
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Adds percentages to a crosstab generated by tabyl, with options to format
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and include raw counts, and also control the behavior
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of adorn_pct_formatting and adorn_ns.
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:param df: DataFrame used to generate the crosstab
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:param col1: First column to create the crosstab
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:param col2: Second column to create the crosstab
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:param axis: 'row' to add percentages by row, 'col' for column percentages,
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'all' for global percentages
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:param fmt: If True, formats percentages as strings
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(e.g., "12.5%"), else returns numeric values.
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:param include_ns: If True, includes raw counts alongside percentages.
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:param decimal_places: Number of decimal places for the percentages
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:param thousand_separator: Whether to add a thousand separator to the counts
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:param percent_format: Whether to format as percentages
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:return: DataFrame with percentages and optional formatting and raw counts
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Example:
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Example:
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>>> data = {
205-
... "Category": ["A", "B", "A", "B", "A", "B"],
206-
... "Subcategory": ["X", "X", "Y", "Y", "X", "X"],
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... "Value": [1, 2, 3, 4, 5, 6],
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... }
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>>> df = pd.DataFrame(data)
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>>> result = adorn_percentages(df, col1="Category",
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col2="Subcategory", axis="row", fmt=True, include_ns=True)
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>>> print(result)
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Category X Y
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A 20% (1) 80% (4)
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B 33.33% (2) 66.67% (4)
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219-
>>> result = adorn_percentages(df, col1="Category",
220-
col2="Subcategory", axis="col", fmt=True)
221-
222-
>>> print(result)
223-
Category X Y
224-
A 33.33% (1) 50% (3)
225-
B 66.67% (2) 50% (3)
183+
Adds percentages to a crosstab generated by tabyl, with options to format
184+
and include raw counts, and also control the behavior
185+
of adorn_pct_formatting and adorn_ns.
186+
187+
:param df: DataFrame used to generate the crosstab
188+
:param col1: First column to create the crosstab
189+
:param col2: Second column to create the crosstab
190+
:param axis: 'row' to add percentages by row, 'col' for column percentages,
191+
'all' for global percentages
192+
:param fmt: If True, formats percentages as strings
193+
(e.g., "12.5%"), else returns numeric values.
194+
:param include_ns: If True, includes raw counts alongside percentages.
195+
:param decimal_places: Number of decimal places for the percentages
196+
:param thousand_separator: Whether to add a thousand separator to the counts
197+
:param percent_format: Whether to format as percentages
198+
:return: DataFrame with percentages and optional formatting and raw counts
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227200
"""
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# Generate the crosstab using tabyl with the two specified columns

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