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feature wanted: pd.DataFrame.info() should show line numbers #17304 #28696

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feature wanted: pd.DataFrame.info() should show line numbers #17304 #28696

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28 changes: 28 additions & 0 deletions doc/source/whatsnew/v1.0.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -294,6 +294,34 @@ ExtensionArray
- Bug in :class:`arrays.PandasArray` when setting a scalar string (:issue:`28118`, :issue:`28150`).
-

Output Formatting Enhancements
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

- :func:`DataFrame.info` now shows line numbers for the columns summary (:issue:`17304`)

.. ipython:: python

df = pd.DataFrame({
'int_col': [1, 2, 3, 4, 5],
'text_col': ['alpha', 'beta', 'gamma', 'delta', 'epsilon'],
'float_col': [0.0, 0.25, 0.5, 0.75, 1.0]})
df.info()

Previous Behavior:

.. code-block:: python

In [1]: df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Data columns (total 3 columns):
int_col 5 non-null int64
text_col 5 non-null object
float_col 5 non-null float64
dtypes: float64(1), int64(1), object(1)
memory usage: 200.0+ bytes



Other
^^^^^
Expand Down
71 changes: 45 additions & 26 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2332,9 +2332,11 @@ def info(
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Data columns (total 3 columns):
int_col 5 non-null int64
text_col 5 non-null object
float_col 5 non-null float64
#. Column Non-Null Count & Dtype
--- ------ ----------------------
0 int_col 5 non-null int64
1 text_col 5 non-null object
2 float_col 5 non-null float64
dtypes: float64(1), int64(1), object(1)
memory usage: 248.0+ bytes

Expand Down Expand Up @@ -2373,19 +2375,23 @@ def info(
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1000000 entries, 0 to 999999
Data columns (total 3 columns):
column_1 1000000 non-null object
column_2 1000000 non-null object
column_3 1000000 non-null object
#. Column Non-Null Count & Dtype
--- ------ ----------------------
0 column_1 1000000 non-null object
1 column_2 1000000 non-null object
2 column_3 1000000 non-null object
dtypes: object(3)
memory usage: 22.9+ MB

>>> df.info(memory_usage='deep')
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1000000 entries, 0 to 999999
Data columns (total 3 columns):
column_1 1000000 non-null object
column_2 1000000 non-null object
column_3 1000000 non-null object
#. Column Non-Null Count & Dtype
--- ------ ----------------------
0 column_1 1000000 non-null object
1 column_2 1000000 non-null object
2 column_3 1000000 non-null object
dtypes: object(3)
memory usage: 188.8 MB
"""
Expand All @@ -2404,48 +2410,61 @@ def info(
return

cols = self.columns
cols_count = len(cols)

# hack
if max_cols is None:
max_cols = get_option("display.max_info_columns", len(self.columns) + 1)
max_cols = get_option('display.max_info_columns', cols_count + 1)

max_rows = get_option("display.max_info_rows", len(self) + 1)

if null_counts is None:
show_counts = (len(self.columns) <= max_cols) and (len(self) < max_rows)
show_counts = (cols_count <= max_cols) and (len(self) < max_rows)
else:
show_counts = null_counts
exceeds_info_cols = len(self.columns) > max_cols
exceeds_info_cols = cols_count > max_cols

def _verbose_repr():
lines.append("Data columns (total %d columns):" % len(self.columns))
space = max(len(pprint_thing(k)) for k in self.columns) + 4
lines.append('Data columns (total '
'{count} columns):'.format(count=cols_count))
space = max(len(pprint_thing(k)) for k in cols)
len_column = len(pprint_thing('Column'))
space = max(space, len_column) + 4
space_num = len(pprint_thing(cols_count))
len_id = len(pprint_thing(' #.'))
space_num = max(space_num, len_id) + 2
counts = None

tmpl = "{count}{dtype}"
header = _put_str(' #.', space_num) + _put_str('Column', space)
if show_counts:
counts = self.count()
if len(cols) != len(counts): # pragma: no cover
raise AssertionError(
"Columns must equal counts "
"({cols:d} != {counts:d})".format(
cols=len(cols), counts=len(counts)
)
)
tmpl = "{count} non-null {dtype}"

'({cols_count} != {count})'.format(
cols_count=cols_count, count=len(counts)))
col_header = 'Non-Null Count & Dtype'
tmpl = '{count} non-null {dtype}'
else:
col_header = 'Dtype'
tmpl = '{count}{dtype}'
header += col_header

lines.append(header)
lines.append(_put_str('-' * len_id, space_num) +
_put_str('-' * len_column, space) +
'-' * len(pprint_thing(col_header)))
dtypes = self.dtypes
for i, col in enumerate(self.columns):
for i, col in enumerate(cols):
dtype = dtypes.iloc[i]
col = pprint_thing(col)

line_no = _put_str(' {num}'.format(num=i), space_num)
count = ""
if show_counts:
count = counts.iloc[i]

lines.append(
_put_str(col, space) + tmpl.format(count=count, dtype=dtype)
)
lines.append(line_no + _put_str(col, space) +
tmpl.format(count=count, dtype=dtype))

def _non_verbose_repr():
lines.append(self.columns._summary(name="Columns"))
Expand Down
36 changes: 29 additions & 7 deletions pandas/tests/frame/test_repr_info.py
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Original file line number Diff line number Diff line change
Expand Up @@ -219,7 +219,9 @@ def test_info_memory(self):
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 2 entries, 0 to 1
Data columns (total 1 columns):
a 2 non-null int64
#. Column Non-Null Count & Dtype
--- ------ ----------------------
0 a 2 non-null int64
dtypes: int64(1)
memory usage: {} bytes
""".format(
Expand All @@ -229,6 +231,26 @@ def test_info_memory(self):

assert result == expected

def test_info_without_null_counts(self):
df = pd.DataFrame({'a': [1, 2]})
buf = StringIO()
df.info(buf=buf, null_counts=False)
buf.seek(0)
lines = buf.readlines()
result = ''.join(lines[:-1])
expected = textwrap.dedent('''\
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 2 entries, 0 to 1
Data columns (total 1 columns):
#. Column Dtype
--- ------ -----
0 a int64
dtypes: int64(1)
''')
assert result == expected



def test_info_wide(self):
from pandas import set_option, reset_option

Expand Down Expand Up @@ -263,8 +285,8 @@ def test_info_duplicate_columns_shows_correct_dtypes(self):
frame.info(buf=io)
io.seek(0)
lines = io.readlines()
assert "a 1 non-null int64\n" == lines[3]
assert "a 1 non-null float64\n" == lines[4]
assert ' 0 a 1 non-null int64\n' == lines[5]
assert ' 1 a 1 non-null float64\n' == lines[6]

def test_info_shows_column_dtypes(self):
dtypes = [
Expand All @@ -285,20 +307,20 @@ def test_info_shows_column_dtypes(self):
df.info(buf=buf)
res = buf.getvalue()
for i, dtype in enumerate(dtypes):
name = "{i:d} {n:d} non-null {dtype}".format(i=i, n=n, dtype=dtype)
name = '%s %d non-null %s' % (i, n, dtype)
assert name in res

def test_info_max_cols(self):
df = DataFrame(np.random.randn(10, 5))
for len_, verbose in [(5, None), (5, False), (10, True)]:
for len_, verbose in [(5, None), (5, False), (12, True)]:
# For verbose always ^ setting ^ summarize ^ full output
with option_context("max_info_columns", 4):
buf = StringIO()
df.info(buf=buf, verbose=verbose)
res = buf.getvalue()
assert len(res.strip().split("\n")) == len_

for len_, verbose in [(10, None), (5, False), (10, True)]:
for len_, verbose in [(10, None), (5, False), (12, True)]:

# max_cols no exceeded
with option_context("max_info_columns", 5):
Expand All @@ -307,7 +329,7 @@ def test_info_max_cols(self):
res = buf.getvalue()
assert len(res.strip().split("\n")) == len_

for len_, max_cols in [(10, 5), (5, 4)]:
for len_, max_cols in [(12, 5), (5, 4)]:
# setting truncates
with option_context("max_info_columns", 4):
buf = StringIO()
Expand Down