Better error message when using DataFrame.hist() without numerical columns

[goretkin]

pandas version: 0.16.2
matplotlib version 1.4.3 (and produced different error message on older version)

import numpy as np
import pandas as pd

df = pd.DataFrame(np.random.rand(10,2))
df_o = df.astype(np.object)
df_o.hist()

ValueError                                Traceback (most recent call last)
<ipython-input-1-26253737011d> in <module>()
      4 df = pd.DataFrame(np.random.rand(10,2))
      5 df_o = df.astype(np.object)
----> 6 df_o.hist()

/usr/local/lib/python2.7/dist-packages/pandas/tools/plotting.pyc in hist_frame(data, column, by, grid, xlabelsize, xrot, ylabelsize, yrot, ax, sharex, sharey, figsize, layout, bins, **kwds)
   2764     fig, axes = _subplots(naxes=naxes, ax=ax, squeeze=False,
   2765                           sharex=sharex, sharey=sharey, figsize=figsize,
-> 2766                           layout=layout)
   2767     _axes = _flatten(axes)
   2768 

/usr/local/lib/python2.7/dist-packages/pandas/tools/plotting.pyc in _subplots(naxes, sharex, sharey, squeeze, subplot_kw, ax, layout, layout_type, **fig_kw)
   3244 
   3245     # Create first subplot separately, so we can share it if requested
-> 3246     ax0 = fig.add_subplot(nrows, ncols, 1, **subplot_kw)
   3247 
   3248     if sharex:

/usr/local/lib/python2.7/dist-packages/matplotlib/figure.pyc in add_subplot(self, *args, **kwargs)
    962                     self._axstack.remove(ax)
    963 
--> 964             a = subplot_class_factory(projection_class)(self, *args, **kwargs)
    965 
    966         self._axstack.add(key, a)

/usr/local/lib/python2.7/dist-packages/matplotlib/axes/_subplots.pyc in __init__(self, fig, *args, **kwargs)
     62                     raise ValueError(
     63                         "num must be 0 <= num <= {maxn}, not {num}".format(
---> 64                             maxn=rows*cols, num=num))
     65                 if num == 0:
     66                     warnings.warn("The use of 0 (which ends up being the "

ValueError: num must be 0 <= num <= 0, not 1

[TomAugspurger]

We (only?) plot numeric types (df._get_numeric_data IIRC).

What's you use here that you're getting object dtypes? Integer NaNs? You'll typically want to avoid object dtypes since they're much slower for numeric operations.

[goretkin]

I agree with what you're saying, and I think a suitable fix would include a more explicit check for the dtypes and show an error. As it is, I spent some time trying to figure out what the issue was, especially because the string representation of the DataFrame doesn't show the dtypes.

I am using floats and integers, but by accident, when I constructed the DataFrame, all entries were NaN objects, and then I populated the DataFrame in a loop.

[datapythonista]

An error message like hist method requires numerical columns, nothing to plot or anything clearer would be useful.

[zhanwenchen]

Any progress on this? It took me quite a few hours to realize it was a dtype error.

[TomAugspurger]

Still open. Interested in submitting a PR to fix it?

…

On Tue, Aug 21, 2018 at 10:06 AM zhanwenchen ***@***.***> wrote: Any progress on this? It took me quite a few hours to realize it was a dtype error. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#10444 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ABQHIrdc3hje4W1xv92Y3_uxXpg7nC0Rks5uTCHbgaJpZM4FMPtc> .

[den-run-ai]

@TomAugspurger i get a nonsense error here from a dataframe with 2 columns, but not when histogramming them one at a time as a series:

ValueError: num must be 1 <= num <= 0, not 1

traceback:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-41-7cfbfac10616> in <module>()
      1 dfi['ml_data'][
----> 2     ['duration_', 'duration__']].dropna().astype('timedelta64[D]').astype(float).hist(bins=20)

/usr/local/lib/python3.6/dist-packages/pandas/plotting/_core.py in hist_frame(data, column, by, grid, xlabelsize, xrot, ylabelsize, yrot, ax, sharex, sharey, figsize, layout, bins, **kwds)
   2176     fig, axes = _subplots(naxes=naxes, ax=ax, squeeze=False,
   2177                           sharex=sharex, sharey=sharey, figsize=figsize,
-> 2178                           layout=layout)
   2179     _axes = _flatten(axes)
   2180 

/usr/local/lib/python3.6/dist-packages/pandas/plotting/_tools.py in _subplots(naxes, sharex, sharey, squeeze, subplot_kw, ax, layout, layout_type, **fig_kw)
    235 
    236     # Create first subplot separately, so we can share it if requested
--> 237     ax0 = fig.add_subplot(nrows, ncols, 1, **subplot_kw)
    238 
    239     if sharex:

/usr/local/lib/python3.6/dist-packages/matplotlib/figure.py in add_subplot(self, *args, **kwargs)
   1072                     self._axstack.remove(ax)
   1073 
-> 1074             a = subplot_class_factory(projection_class)(self, *args, **kwargs)
   1075 
   1076         self._axstack.add(key, a)

/usr/local/lib/python3.6/dist-packages/matplotlib/axes/_subplots.py in __init__(self, fig, *args, **kwargs)
     62                     raise ValueError(
     63                         "num must be 1 <= num <= {maxn}, not {num}".format(
---> 64                             maxn=rows*cols, num=num))
     65                 self._subplotspec = GridSpec(rows, cols)[int(num) - 1]
     66                 # num - 1 for converting from MATLAB to python indexing

ValueError: num must be 1 <= num <= 0, not 1

colab notebook:

INSTALLED VERSIONS

commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.14.33+
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.22.0
numpy: 1.14.5
matplotlib: 2.1.2

[datapythonista]

@denfromufa do you want to fix it?

Here you have the general documentation on how to do it: https://pandas.pydata.org/pandas-docs/stable/contributing.html

The fix should be easy, just checking the type and raising an exception with a useful message.

[den-run-ai]

@datapythonista i don't agree on this solution - it should just work. why raise an exception when histogram works for each series? however i did not have a chance to debug this yet.

[datapythonista]

if you make it work even better, feel free to send a PR for it.