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DOC: Updated resample.py and groupby.py to fix SA04 Errors
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-12
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pandas/core/groupby/groupby.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -79,8 +79,8 @@ class providing the base-class of operations.
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_common_see_also = """
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See Also
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--------
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Series.%(name)s
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DataFrame.%(name)s
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Series.%(name)s : Apply a function %(name)s to a Series.
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DataFrame.%(name)s : Apply a function %(name)s to each row or column of a DataFrame.
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"""
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_apply_docs = dict(

pandas/core/resample.py

Lines changed: 13 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -131,7 +131,7 @@ def __iter__(self):
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See Also
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--------
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GroupBy.__iter__
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GroupBy.__iter__ : Generator yielding sequence of (name, subset object) for each group
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"""
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self._set_binner()
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return super().__iter__()
@@ -235,9 +235,9 @@ def pipe(self, func, *args, **kwargs):
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"""
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See Also
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--------
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DataFrame.groupby.aggregate
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DataFrame.resample.transform
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DataFrame.aggregate
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DataFrame.groupby.aggregate : Aggregate using callable, string, dict, or list of string/callables
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DataFrame.resample.transform : Transforms the Series on each group based on the given function.
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DataFrame.aggregate: Aggregate using one or more operations over the specified axis.
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"""
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)
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@@ -453,8 +453,8 @@ def pad(self, limit=None):
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See Also
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--------
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Series.fillna
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DataFrame.fillna
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Series.fillna: Fill NA/NaN values using the specified method.
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DataFrame.fillna: Fill NA/NaN values using the specified method.
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"""
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return self._upsample("pad", limit=limit)
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@@ -828,8 +828,8 @@ def asfreq(self, fill_value=None):
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See Also
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--------
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Series.asfreq
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DataFrame.asfreq
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Series.asfreq: Convert TimeSeries to specified frequency.
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DataFrame.asfreq: Convert TimeSeries to specified frequency.
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"""
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return self._upsample("asfreq", fill_value=fill_value)
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@@ -915,8 +915,11 @@ def quantile(self, q=0.5, **kwargs):
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See Also
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--------
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Series.quantile
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Return a series, where the index is q and the values are the quantiles
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DataFrame.quantile
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Return a DataFrame, where the columns are the columns of self, and the values are the quantiles.
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DataFrameGroupBy.quantile
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Return a DataFrame, where the coulmns are groupby columns, and the values are its quantiles.
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"""
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return self._downsample("quantile", q=q, **kwargs)
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@@ -1072,7 +1075,7 @@ def _upsample(self, method, limit=None, fill_value=None):
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See Also
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--------
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.fillna
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.fillna: Fill NA/NaN values using the specified method.
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"""
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self._set_binner()
@@ -1208,7 +1211,7 @@ def _upsample(self, method, limit=None, fill_value=None):
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See Also
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--------
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.fillna
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.fillna: Fill NA/NaN values using the specified method.
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"""
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# we may need to actually resample as if we are timestamps

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