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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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10 changes: 8 additions & 2 deletions doc/source/io.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -135,8 +135,14 @@ usecols : array-like or callable, default ``None``
be positional (i.e. integer indices into the document columns) or strings
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]``.
`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]``. To
instantiate a DataFrame from ``data`` with element order preserved use
``pd.read_csv(data, usecols=['foo', 'bar'])[['foo', 'bar']]`` for columns
in ``['foo', 'bar']`` order or
``pd.read_csv(data, usecols=['foo', 'bar'])[['bar', 'foo']]`` for
``['bar', 'foo']`` 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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7 changes: 6 additions & 1 deletion pandas/io/parsers.py
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Expand Up @@ -102,7 +102,12 @@
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=[0, 1]`` is the same as ``[1, 0]``.
To instantiate a DataFrame from ``data`` with element order preserved use
``pd.read_csv(data, usecols=['foo', 'bar'])[['foo', 'bar']]`` for columns
in ``['foo', 'bar']`` order or
``pd.read_csv(data, usecols=['foo', 'bar'])[['bar', 'foo']]``
for ``['bar', 'foo']`` order.

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