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[DOCS] Add example of how to preserve order of columns with usecols. #19746

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Feb 21, 2018
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[DOCS] Add example of how to preserve order of columns with usecols. #19746

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d2bd6c3
Add example of how to preserve order of columns with usecols.
Feb 18, 2018
f137bd0
Encase usecols in double back ticks for consistency. Change column na…
Feb 18, 2018
68efc4b
Add line to separate examples.
Feb 18, 2018
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6 changes: 5 additions & 1 deletion doc/source/io.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -136,7 +136,11 @@ usecols : array-like or callable, default ``None``
that correspond to column names provided either by the user in `names` or
inferred from the document header row(s). For example, a valid array-like
`usecols` parameter would be ``[0, 1, 2]`` or ``['foo', 'bar', 'baz']``.
Element order is ignored, so ``usecols=[0, 1]`` is the same as ``[1, 0]``.
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can you add a blank line before the additions.

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Sure thing. Please refer to 68efc4b

Element order is ignored, so ``usecols=[0, 1]`` is the same as ``[1, 0]``. Element
order is ignored, so usecols=[1,0] is the same as [0,1]. To instantiate a
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Could you put these usecols=[] in double back ticks as well? And commas between the elements.

Finally, I have a slight preference for using names like ['foo', 'bar'] instead of [0, 1], even though it's a bit longer.

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@EricChea EricChea Feb 18, 2018 •
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Done. Please refer to f137bd0

I went ahead and encased usecols in double back ticks.

Updated column names per your suggestion. I was originally trying to keep consistent with the line before Element order is ignored, so usecols=[0, 1] is the same as [1, 0].

DataFrame with element order preserved use ``pd.read_csv(usecols=[0, 1])[[0, 1]]``
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it should be “pd.read_csv(usecols=[0, 1])[[1, 0]]” ？

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Yep.

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@EricChea EricChea Feb 18, 2018 •
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Thanks for catching that. Fixed in commit f137bd0

for columns in ``[1, 0]`` order or ``pd.read_csv(usecols=[0, 1])[[0, 1]]``
for ``[0, 1]`` order.

If callable, the callable function will be evaluated against the column names,
returning names where the callable function evaluates to True:
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5 changes: 4 additions & 1 deletion pandas/io/parsers.py
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Expand Up @@ -102,7 +102,10 @@
that correspond to column names provided either by the user in `names` or
inferred from the document header row(s). For example, a valid array-like
`usecols` parameter would be [0, 1, 2] or ['foo', 'bar', 'baz']. Element
order is ignored, so usecols=[1,0] is the same as [0,1].
order is ignored, so usecols=[1,0] is the same as [0,1]. To instantiate a
DataFrame with element order preserved use
``pd.read_csv(usecols=[0, 1])[[0, 1]]`` for columns in ``[1, 0]``
order or ``pd.read_csv(usecols=[0, 1])[[0, 1]]`` for ``[0, 1]`` order.

If callable, the callable function will be evaluated against the column
names, returning names where the callable function evaluates to True. An
Expand Down