Is there a way to eliminate the green column a, that shows up even after specifying grouping by column a and restricting to columns f and g for histogram, without delving into matplotlib or using a for loop?
axes = dfs.hist(column=['f', 'g'], by='a', layout=(1, 3), legend=True, bins=np.linspace(0, 8, 10),
sharex=True, sharey=True)
It appears there is a bug within the pandas library causing issues with numeric dtype columns. The problem seems to arise when using `by` as a numeric dtype column, as it likely subsets the DataFrame to the labels in `column` and `by` before plotting, which can be problematic for numeric values.
To work around this issue, you can either create non-numeric labels for the column defining your 'by', or if you prefer not to change your data, simply reassign the type to `object` just before plotting.
import pandas as pd
import numpy as np
df = pd.DataFrame({'length': np.random.normal(0, 1, 1000),
'width': np.random.normal(0, 1, 1000),
'a': np.random.randint(0, 2, 1000)})
# Issue arises with a numeric dtype for `by` column
df.hist(column=['length', 'width'], by='a', figsize=(4, 2))
https://i.stack.imgur.com/khZfd.png
# Functions correctly when column type is object
(df.assign(a=df['a'].astype('object'))
.hist(column=['length', 'width'], by='a' , figsize=(4, 2)))
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