DOC/TST: dtype param in read_fwf (pandas-dev#14768)

Author: chris-b1

doc/source/io.rst

@@ -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
 '''''''
 

doc/source/whatsnew/v0.20.0.txt

@@ -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

pandas/io/tests/parser/test_read_fwf.py

@@ -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)