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ENH: formatting integers in FloatIndex as floats #12207

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42 changes: 42 additions & 0 deletions doc/source/whatsnew/v0.18.0.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -185,6 +185,48 @@ In addition, ``.round()``, ``.floor()`` and ``.ceil()`` will be available thru t
s
s.dt.round('D')


Formatting of integer in FloatIndex
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Integers in ``FloatIndex``, e.g. 1., are now formatted with a decimal point
and a ``0`` digit, e.g. ``1.0`` (:issue:`11713`)

This change affects the display in jupyter, but also the output of IO methods
like ``.to_csv`` or ``.to_html``

Previous Behavior:

.. code-block:: python

In [2]: s = Series([1,2,3], index=np.arange(3.))

In [3]: s
Out[3]:
0 1
1 2
2 3
dtype: int64

In [4]: s.index
Out[4]: Float64Index([0.0, 1.0, 2.0], dtype='float64')

In [5]: print(s.to_csv(path=None))
0,1
1,2
2,3


New Behavior:

.. ipython:: python

s = Series([1,2,3], index=np.arange(3.))
s
s.index
print(s.to_csv(path=None))


.. _whatsnew_0180.enhancements.other:

Other enhancements
Expand Down
10 changes: 6 additions & 4 deletions pandas/core/format.py
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Expand Up @@ -2115,7 +2115,9 @@ def _format_strings(self):
abs_vals = np.abs(self.values)

# this is pretty arbitrary for now
has_large_values = (abs_vals > 1e8).any()
# large values: more that 8 characters including decimal symbol
# and first digit, hence > 1e6
has_large_values = (abs_vals > 1e6).any()
has_small_values = ((abs_vals < 10**(-self.digits)) &
(abs_vals > 0)).any()

Expand Down Expand Up @@ -2367,7 +2369,7 @@ def just(x):

def _trim_zeros(str_floats, na_rep='NaN'):
"""
Trims zeros and decimal points.
Trims zeros, leaving just one before the decimal points if need be.
"""
trimmed = str_floats

Expand All @@ -2379,8 +2381,8 @@ def _cond(values):
while _cond(trimmed):
trimmed = [x[:-1] if x != na_rep else x for x in trimmed]

# trim decimal points
return [x[:-1] if x.endswith('.') and x != na_rep else x for x in trimmed]
# leave one 0 after the decimal points if need be.
return [x + "0" if x.endswith('.') and x != na_rep else x for x in trimmed]


def single_column_table(column, align=None, style=None):
Expand Down
30 changes: 15 additions & 15 deletions pandas/tests/test_format.py
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Expand Up @@ -204,7 +204,7 @@ def test_repr_chop_threshold(self):
self.assertEqual(repr(df), ' 0 1\n0 0.0 0.5\n1 0.5 0.0')

with option_context("display.chop_threshold", 0.6):
self.assertEqual(repr(df), ' 0 1\n0 0 0\n1 0 0')
self.assertEqual(repr(df), ' 0 1\n0 0.0 0.0\n1 0.0 0.0')

with option_context("display.chop_threshold", None):
self.assertEqual(repr(df), ' 0 1\n0 0.1 0.5\n1 0.5 -0.1')
Expand Down Expand Up @@ -753,7 +753,7 @@ def test_to_html_with_empty_string_label(self):

def test_to_html_unicode(self):
df = DataFrame({u('\u03c3'): np.arange(10.)})
expected = u'<table border="1" class="dataframe">\n <thead>\n <tr style="text-align: right;">\n <th></th>\n <th>\u03c3</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>0</td>\n </tr>\n <tr>\n <th>1</th>\n <td>1</td>\n </tr>\n <tr>\n <th>2</th>\n <td>2</td>\n </tr>\n <tr>\n <th>3</th>\n <td>3</td>\n </tr>\n <tr>\n <th>4</th>\n <td>4</td>\n </tr>\n <tr>\n <th>5</th>\n <td>5</td>\n </tr>\n <tr>\n <th>6</th>\n <td>6</td>\n </tr>\n <tr>\n <th>7</th>\n <td>7</td>\n </tr>\n <tr>\n <th>8</th>\n <td>8</td>\n </tr>\n <tr>\n <th>9</th>\n <td>9</td>\n </tr>\n </tbody>\n</table>'
expected = u'<table border="1" class="dataframe">\n <thead>\n <tr style="text-align: right;">\n <th></th>\n <th>\u03c3</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>0.0</td>\n </tr>\n <tr>\n <th>1</th>\n <td>1.0</td>\n </tr>\n <tr>\n <th>2</th>\n <td>2.0</td>\n </tr>\n <tr>\n <th>3</th>\n <td>3.0</td>\n </tr>\n <tr>\n <th>4</th>\n <td>4.0</td>\n </tr>\n <tr>\n <th>5</th>\n <td>5.0</td>\n </tr>\n <tr>\n <th>6</th>\n <td>6.0</td>\n </tr>\n <tr>\n <th>7</th>\n <td>7.0</td>\n </tr>\n <tr>\n <th>8</th>\n <td>8.0</td>\n </tr>\n <tr>\n <th>9</th>\n <td>9.0</td>\n </tr>\n </tbody>\n</table>'
self.assertEqual(df.to_html(), expected)
df = DataFrame({'A': [u('\u03c3')]})
expected = u'<table border="1" class="dataframe">\n <thead>\n <tr style="text-align: right;">\n <th></th>\n <th>A</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>\u03c3</td>\n </tr>\n </tbody>\n</table>'
Expand Down Expand Up @@ -1916,12 +1916,12 @@ def test_to_string_format_na(self):
'B': [np.nan, 'foo', 'foooo', 'fooooo', 'bar']})
result = df.to_string()

expected = (' A B\n'
'0 NaN NaN\n'
'1 -1 foo\n'
'2 -2 foooo\n'
'3 3 fooooo\n'
'4 4 bar')
expected = (' A B\n'
'0 NaN NaN\n'
'1 -1.0 foo\n'
'2 -2.0 foooo\n'
'3 3.0 fooooo\n'
'4 4.0 bar')
self.assertEqual(result, expected)

def test_to_string_line_width(self):
Expand Down Expand Up @@ -3760,8 +3760,8 @@ def test_misc(self):
def test_format(self):
obj = fmt.FloatArrayFormatter(np.array([12, 0], dtype=np.float64))
result = obj.get_result()
self.assertEqual(result[0], " 12")
self.assertEqual(result[1], " 0")
self.assertEqual(result[0], " 12.0")
self.assertEqual(result[1], " 0.0")

def test_output_significant_digits(self):
# Issue #9764
Expand Down Expand Up @@ -3793,15 +3793,15 @@ def test_output_significant_digits(self):
def test_too_long(self):
# GH 10451
with pd.option_context('display.precision', 4):
# need both a number > 1e8 and something that normally formats to
# need both a number > 1e6 and something that normally formats to
# having length > display.precision + 6
df = pd.DataFrame(dict(x=[12345.6789]))
self.assertEqual(str(df), ' x\n0 12345.6789')
df = pd.DataFrame(dict(x=[2e8]))
self.assertEqual(str(df), ' x\n0 200000000')
df = pd.DataFrame(dict(x=[12345.6789, 2e8]))
df = pd.DataFrame(dict(x=[2e6]))
self.assertEqual(str(df), ' x\n0 2000000.0')
df = pd.DataFrame(dict(x=[12345.6789, 2e6]))
self.assertEqual(
str(df), ' x\n0 1.2346e+04\n1 2.0000e+08')
str(df), ' x\n0 1.2346e+04\n1 2.0000e+06')


class TestRepr_timedelta64(tm.TestCase):
Expand Down