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DOC: add warning to append about inefficiency #17017

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Jul 19, 2017
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DOC: add warning to append about inefficiency #17017

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32 changes: 32 additions & 0 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4618,6 +4618,11 @@ def append(self, other, ignore_index=False, verify_integrity=False):
the DataFrame's index, the order of the columns in the resulting
DataFrame will be unchanged.

Iteratively appending rows to a DataFrame can be more computationally
intensive than a single concatenate. A better solution is to append
those rows to a list and then concatenate the list with the original
DataFrame all at once.

See also
--------
pandas.concat : General function to concatenate DataFrame, Series
Expand Down Expand Up @@ -4648,6 +4653,33 @@ def append(self, other, ignore_index=False, verify_integrity=False):
2 5 6
3 7 8

The following, while not recommended methods for generating DataFrames,
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Hmmm...I'm not sure if you need to demonstrate both methods. The latter is probably sufficient. In any case, if you are going to demonstrate this for DataFrame, you should do a similar demo for Series.

show two ways to generate a DataFrame from multiple data sources.

Less efficient:

>>> df = pd.DataFrame(columns=['A'])
>>> for i in range(5):
... df = df.append({'A'}: i}, ignore_index=True)
>>> df
A
0 0
1 1
2 2
3 3
4 4

More efficient:

>>> pd.concat([pd.DataFrame([i], columns=['A']) for i in range(5)],
... ignore_index=True)
A
0 0
1 1
2 2
3 3
4 4

"""
if isinstance(other, (Series, dict)):
if isinstance(other, dict):
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12 changes: 12 additions & 0 deletions pandas/core/series.py
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Expand Up @@ -1522,6 +1522,18 @@ def append(self, to_append, ignore_index=False, verify_integrity=False):
verify_integrity : boolean, default False
If True, raise Exception on creating index with duplicates

Notes
-----
Iteratively appending to a Series can be more computationally intensive
than a single concatenate. A better solution is to append values to a
list and then concatenate the list with the original Series all at
once.

See also
--------
pandas.concat : General function to concatenate DataFrame, Series
or Panel objects

Returns
-------
appended : Series
Expand Down