API: Preserve int columns in to_dict('index') (pandas-dev#20444)

Author: reidy-p

doc/source/whatsnew/v0.23.0.txt

@@ -716,6 +716,7 @@ Other API Changes
 - :func:`Series.str.replace` now takes an optional `regex` keyword which, when set to ``False``, uses literal string replacement rather than regex replacement (:issue:`16808`)
 - :func:`DatetimeIndex.strftime` and :func:`PeriodIndex.strftime` now return an ``Index`` instead of a numpy array to be consistent with similar accessors (:issue:`20127`)
 - Constructing a Series from a list of length 1 no longer broadcasts this list when a longer index is specified (:issue:`19714`, :issue:`20391`).
+- :func:`DataFrame.to_dict` with ``orient='index'`` no longer casts int columns to float for a DataFrame with only int and float columns (:issue:`18580`)
 
 .. _whatsnew_0230.deprecations:
 

pandas/core/frame.py

@@ -1102,7 +1102,8 @@ def to_dict(self, orient='dict', into=dict):
                            for k, v in zip(self.columns, np.atleast_1d(row)))
                     for row in self.values]
         elif orient.lower().startswith('i'):
-            return into_c((k, v.to_dict(into)) for k, v in self.iterrows())
+            return into_c((t[0], dict(zip(self.columns, t[1:])))
+                          for t in self.itertuples())
         else:
             raise ValueError("orient '%s' not understood" % orient)
 

pandas/tests/frame/test_convert_to.py

@@ -5,6 +5,7 @@
 import pytest
 import pytz
 import collections
+from collections import OrderedDict, defaultdict
 import numpy as np
 
 from pandas import compat
@@ -288,3 +289,29 @@ def test_frame_to_dict_tz(self):
         ]
         tm.assert_dict_equal(result[0], expected[0])
         tm.assert_dict_equal(result[1], expected[1])
+
+    @pytest.mark.parametrize('into, expected', [
+        (dict, {0: {'int_col': 1, 'float_col': 1.0},
+                1: {'int_col': 2, 'float_col': 2.0},
+                2: {'int_col': 3, 'float_col': 3.0}}),
+        (OrderedDict, OrderedDict([(0, {'int_col': 1, 'float_col': 1.0}),
+                                   (1, {'int_col': 2, 'float_col': 2.0}),
+                                   (2, {'int_col': 3, 'float_col': 3.0})])),
+        (defaultdict(list), defaultdict(list,
+                                        {0: {'int_col': 1, 'float_col': 1.0},
+                                         1: {'int_col': 2, 'float_col': 2.0},
+                                         2: {'int_col': 3, 'float_col': 3.0}}))
+    ])
+    def test_to_dict_index_dtypes(self, into, expected):
+        # GH 18580
+        # When using to_dict(orient='index') on a dataframe with int
+        # and float columns only the int columns were cast to float
+
+        df = DataFrame({'int_col': [1, 2, 3],
+                        'float_col': [1.0, 2.0, 3.0]})
+
+        result = df.to_dict(orient='index', into=into)
+        cols = ['int_col', 'float_col']
+        result = DataFrame.from_dict(result, orient='index')[cols]
+        expected = DataFrame.from_dict(expected, orient='index')[cols]
+        tm.assert_frame_equal(result, expected)