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changing pandas.dataframe methods from boolean to bool
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pandas/core/frame.py

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Original file line numberDiff line numberDiff line change
@@ -1542,7 +1542,7 @@ def from_records(
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Parameters
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----------
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data : ndarray (structured dtype), list of tuples, dict, or DataFrame
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index : string, list of fields, array-like
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index : str, list of fields, array-like
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Field of array to use as the index, alternately a specific set of
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input labels to use
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exclude : sequence, default None
@@ -3461,7 +3461,7 @@ def insert(self, loc, column, value, allow_duplicates=False):
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----------
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loc : int
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Insertion index. Must verify 0 <= loc <= len(columns)
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column : string, number, or hashable object
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column : str, number, or hashable object
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label of the inserted column
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value : int, Series, or array-like
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allow_duplicates : bool, optional
@@ -5197,7 +5197,7 @@ def swaplevel(self, i=-2, j=-1, axis=0):
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Parameters
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----------
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i, j : int, string (can be mixed)
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i, j : int, str (can be mixed)
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Level of index to be swapped. Can pass level name as string.
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Returns
@@ -5723,12 +5723,12 @@ def update(
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Parameters
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----------%s
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index : string or object, optional
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index : str or object, optional
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Column to use to make new frame's index. If None, uses
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existing index.
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columns : string or object
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columns : str or object
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Column to use to make new frame's columns.
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values : string, object or a list of the previous, optional
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values : str, object or a list of the previous, optional
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Column(s) to use for populating new frame's values. If not
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specified, all remaining columns will be used and the result will
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have hierarchically indexed columns.
@@ -6231,7 +6231,7 @@ def unstack(self, level=-1, fill_value=None):
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Parameters
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----------
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level : int, string, or list of these, default -1 (last level)
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level : int, str, or list of these, default -1 (last level)
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Level(s) of index to unstack, can pass level name
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fill_value : replace NaN with this value if the unstack produces
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missing values
@@ -6305,7 +6305,7 @@ def unstack(self, level=-1, fill_value=None):
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``frame.columns.name`` or 'variable'.
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value_name : scalar, default 'value'
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Name to use for the 'value' column.
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col_level : int or string, optional
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col_level : int or str, optional
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If columns are a MultiIndex then use this level to melt.
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Returns

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