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ENH: provide a null_counts keyword to df.info() to force showing of null counts #8701

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merged 1 commit into from
Nov 2, 2014
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ENH: provide a null_counts keyword to df.info() to force showing of null counts #8701

merged 1 commit into from
Nov 2, 2014
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jreback
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@jreback jreback commented Nov 1, 2014

Allows run-time control of showing of null-counts with df.info() (similar to what we allow with for example memory_usage in that this will override the default options for that call)

In [2]: df = DataFrame(1,columns=range(10),index=range(10))

In [3]: df.iloc[1,1] = np.nan

Default for a small frame (currently) is to show the non-null counts

In [5]: df.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 10 entries, 0 to 9
Data columns (total 10 columns):
0    10 non-null float64
1    9 non-null float64
2    10 non-null float64
3    10 non-null float64
4    10 non-null float64
5    10 non-null float64
6    10 non-null float64
7    10 non-null float64
8    10 non-null float64
9    10 non-null float64
dtypes: float64(10)
memory usage: 880.0 bytes

# allow it to be turned off
In [6]: df.info(null_counts=False)
<class 'pandas.core.frame.DataFrame'>
Int64Index: 10 entries, 0 to 9
Data columns (total 10 columns):
0    float64
1    float64
2    float64
3    float64
4    float64
5    float64
6    float64
7    float64
8    float64
9    float64
dtypes: float64(10)
memory usage: 880.0 bytes

When you have a big frame, right now you need to set max_info_rows to control this option

In [7]: pd.set_option('max_info_rows',5)           

In [8]: df.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 10 entries, 0 to 9
Data columns (total 10 columns):
0    float64
1    float64
2    float64
3    float64
4    float64
5    float64
6    float64
7    float64
8    float64
9    float64
dtypes: float64(10)
memory usage: 880.0 bytes

# force it to show
In [9]: df.info(null_counts=True)
<class 'pandas.core.frame.DataFrame'>
Int64Index: 10 entries, 0 to 9
Data columns (total 10 columns):
0    10 non-null float64
1    9 non-null float64
2    10 non-null float64
3    10 non-null float64
4    10 non-null float64
5    10 non-null float64
6    10 non-null float64
7    10 non-null float64
8    10 non-null float64
9    10 non-null float64
dtypes: float64(10)
memory usage: 880.0 bytes

@jreback jreback added API Design Output-Formatting __repr__ of pandas objects, to_string labels Nov 1, 2014
@jreback jreback added this to the 0.15.1 milestone Nov 1, 2014
jreback
jreback reviewed Nov 1, 2014
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pandas/tests/test_format.py

with option_context('display.max_info_rows',5,'display.max_info_columns',5):
check(None, False)
check(True, False)
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@jorisvandenbossche I think this is a bug actually, e.g. if you have a really small info display it doesn't display any column counts, but prob a minor point.

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I don't follow I think. Shouldn't this new kwarg null_counts not overrule if the frame is larger than max_info_rows/columns ?

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it should and does, but the display is simply not printed out (too many columns), so this is sort of not-applicable.

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ah, yes, I see, in such a case, the null_count option has just no effect. I don't really think it is a bug. You could warn that it is ignored in such case if it is specified, but doesn't seem that necesarilly.

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yep, ok on the name null_counts? This is really just for an interactive session where you don't want to keep resetting max_info_rows.

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yep, ok on the name!

@jreback jreback force-pushed the show_counts branch 2 times, most recently from 8c79317 to a95549e Compare November 2, 2014 14:56
jreback added a commit that referenced this pull request Nov 2, 2014
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Merge pull request #8701 from jreback/show_counts
1746df2 
ENH: provide a null_counts keyword to df.info() to force showing of null counts
@jreback jreback merged commit 1746df2 into pandas-dev:master Nov 2, 2014
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