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DOC/TST: dtype param in read_fwf #14768

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11 changes: 11 additions & 0 deletions doc/source/io.rst
Original file line number Diff line number Diff line change
Expand Up @@ -1268,11 +1268,22 @@ is whitespace).
df = pd.read_fwf('bar.csv', header=None, index_col=0)
df

.. versionadded:: 0.20.0

``read_fwf`` supports the ``dtype`` parameter for specifying the types of
parsed columns to be different from the inferred type.

.. ipython:: python

pd.read_fwf('bar.csv', header=None, index_col=0).dtypes
pd.read_fwf('bar.csv', header=None, dtype={2: 'object'}).dtypes

.. ipython:: python
:suppress:

os.remove('bar.csv')


Indexes
'''''''

Expand Down
9 changes: 9 additions & 0 deletions doc/source/whatsnew/v0.20.0.txt
Original file line number Diff line number Diff line change
Expand Up @@ -34,6 +34,15 @@ The ``dtype`` keyword argument in the :func:`read_csv` function for specifying t
pd.read_csv(StringIO(data), engine='python').dtypes
pd.read_csv(StringIO(data), engine='python', dtype={'a':'float64', 'b':'object'}).dtypes

The ``dtype`` keyword argument is also now supported in the :func:`read_fwf` function for parsing
fixed-width text files.

.. ipython:: python

data = "a b\n1 2\n3 4"
pd.read_fwf(StringIO(data)).dtypes
pd.read_fwf(StringIO(data), dtype={'a':'float64', 'b':'object'}).dtypes

.. _whatsnew_0200.enhancements.other:

Other enhancements
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20 changes: 20 additions & 0 deletions pandas/io/tests/parser/test_read_fwf.py
Original file line number Diff line number Diff line change
Expand Up @@ -345,3 +345,23 @@ def test_variable_width_unicode(self):
header=None, encoding='utf8')
tm.assert_frame_equal(expected, read_fwf(
BytesIO(test.encode('utf8')), header=None, encoding='utf8'))

def test_dtype(self):
data = ''' a b c
1 2 3.2
3 4 5.2
'''
colspecs = [(0, 5), (5, 10), (10, None)]
result = pd.read_fwf(StringIO(data), colspecs=colspecs)
expected = pd.DataFrame({
'a': [1, 3],
'b': [2, 4],
'c': [3.2, 5.2]}, columns=['a', 'b', 'c'])
tm.assert_frame_equal(result, expected)

expected['a'] = expected['a'].astype('float64')
expected['b'] = expected['b'].astype(str)
expected['c'] = expected['c'].astype('int32')
result = pd.read_fwf(StringIO(data), colspecs=colspecs,
dtype={'a': 'float64', 'b': str, 'c': 'int32'})
tm.assert_frame_equal(result, expected)