Columns of all None treated differently than all np.nan

[alistairewj]

Maybe a bit niche, but ran into this issue with lineplot: if there is a column of all np.nan, then it is ignored, but if there is a column of all None, then it makes the plot really wacky.

Generate some data:

import pandas as pd
import numpy as np
import pdvega
%matplotlib inline

# generate some data
np.random.seed(111)
df = pd.DataFrame(np.random.randn(50, 4), 
        index=pd.date_range('1/1/2000', periods=50),
                  columns=list('ABCD'))
df = df.cumsum()

# this plot is fine
df.vgplot()

# this column is ignored in the plot
df['nan'] = np.nan
df.vgplot()

(looks the same as above)

# this column makes everything weird
df['none'] = None
df.vgplot()

Oddly enough this doesn't happen if the A and B columns are int:

np.random.seed(111)
df = pd.DataFrame(np.random.randint(low=0, high=5, size=[50, 2]), 
        index=pd.date_range('1/1/2000', periods=50),
                  columns=list('AB'))
df = df.cumsum()

# add a column of all none
df['nan'] = np.nan

# add a column of all none
df['none'] = None
df.vgplot()