8000 DOCS: Updated NDFrame.astype docs by topper-123 · Pull Request #17203 · pandas-dev/pandas · GitHub
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DOCS: Updated NDFrame.astype docs #17203

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Merged
merged 5 commits into from
Aug 9, 2017
Merged

DOCS: Updated NDFrame.astype docs #17203

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a41eb2f
Add examples to NDFrame.astype docs
Aug 8, 2017
d9b9411
Polishing NDFrame.astype doc string
Aug 8, 2017
b366925
NDFrame.astype doc string, adding part with copy=False
Aug 8, 2017
43e2760
NDFrame.astype doc string, adding 'See also' part
Aug 9, 2017
c90160a
NDFrame.astype doc string, some further cleanup
Aug 9, 2017
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NDFrame.astype doc string, some further cleanup
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tp committed Aug 9, 2017
commit c90160ad67ac82cb1c4f6952be7ca333520b5b3a
29 changes: 15 additions & 14 deletions pandas/core/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3610,7 +3610,7 @@ def blocks(self):
mapping={True: 'raise', False: 'ignore'})
def astype(self, dtype, copy=True, errors='raise', **kwargs):
"""
Cast a pandas object to new dtype ``dtype``.
Cast a pandas object to a specified dtype ``dtype``.

Parameters
----------
Expand All @@ -3620,7 +3620,9 @@ def astype(self, dtype, copy=True, errors='raise', **kwargs):
column label and dtype is a numpy.dtype or Python type to cast one
or more of the DataFrame's columns to column-specific types.
copy : bool, default True.
Return a copy when ``copy=True`` (be really careful with this!).
Return a copy when ``copy=True`` (be very careful setting
``copy=False`` as changes to values then may propagate to other
pandas objects).
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maybe add something like ", and copy=False has only effect when the specified dtype is equivalent to the existing dtype" ?

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Hmm, I consciously made it clearer but not-too-specific, as I don't really know how copy does its thing, and I doubt this is used so often.

I suggest to leave it as it is. Is that ok?

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yes, that is fine

errors : {'raise', 'ignore'}, default 'raise'.
Control raising of exceptions on invalid data for provided dtype.

Expand Down Expand Up @@ -3650,15 +3652,15 @@ def astype(self, dtype, copy=True, errors='raise', **kwargs):
1 2
dtype: int64

Convert to pd.Categorial:
Convert to categorical type:

>>> ser.astype('category')
0 1
1 2
dtype: category
Categories (2, int64): [1, 2]

Convert to ordered pd.Categorial with custom ordering:
Convert to ordered categorical type with custom ordering:

>>> ser.astype('category', ordered=True, categories=[2, 1])
0 1
Expand All @@ -3667,16 +3669,15 @@ def astype(self, dtype, copy=True, errors='raise', **kwargs):
Categories (2, int64): [2 < 1]

Note that using ``copy=False`` and changing data on a new
pandas object may propagate changes upwards:

>>> cat1 = pd.Series([1,2], dtype='category')
>>> cat2 = cat1.astype('category', copy=False)
>>> cat2[0] = 2
>>> cat1 # note that cat1[0] is changed too
0 2
1 2
dtype: category
Categories (2, int64): [1, 2]
pandas object may propagate changes:

>>> s1 = pd.Series([1,2])
>>> s2 = s1.astype('int', copy=False)
>>> s2[0] = 10
>>> s1 # note that s1[0] has changed too
0 10
1 2
dtype: int64

See also
--------
Expand Down
0