head(self, n=5)
Similar to .apply(lambda x: x.head(n))
, but it returns a subset of rows from the original DataFrame with original index and order preserved ( as_index
flag is ignored).
If positive: number of entries to include from start of each group. If negative: number of entries to exclude from end of each group.
Subset of original Series or DataFrame as determined by n.
Return first n rows of each group.
DataFrame.groupby
Apply a function groupby to each row or column of a DataFrame.
Series.groupby
Apply a function groupby to a Series.
>>> df = pd.DataFrame([[1, 2], [1, 4], [5, 6]],This example is valid syntax, but we were not able to check execution
... columns=['A', 'B'])
... df.groupby('A').head(1) A B 0 1 2 2 5 6
>>> df.groupby('A').head(-1) A B 0 1 2See :
The following pages refer to to this document either explicitly or contain code examples using this.
pandas.core.groupby.indexing.GroupByPositionalSelector
pandas.core.groupby.indexing.GroupByPositionalSelector.__getitem__
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