df.loc[:, (df != 0).any(axis=0)]
Here is a break-down of how it works:
In [74]: import pandas as pd
In [75]: df = pd.DataFrame([[1,0,0,0], [0,0,1,0]])
In [76]: df
Out[76]:
0 1 2 3
0 1 0 0 0
1 0 0 1 0
[2 rows x 4 columns]
df != 0
creates a boolean DataFrame which is True where df
is nonzero:
In [77]: df != 0
Out[77]:
0 1 2 3
0 True False False False
1 False False True False
[2 rows x 4 columns]
(df != 0).any(axis=0)
returns a boolean Series indicating which columns have nonzero entries. (The any
operation aggregates values along the 0-axis -- i.e. along the rows -- into a single boolean value. Hence the result is one boolean value for each column.)
In [78]: (df != 0).any(axis=0)
Out[78]:
0 True
1 False
2 True
3 False
dtype: bool
And df.loc
can be used to select those columns:
In [79]: df.loc[:, (df != 0).any(axis=0)]
Out[79]:
0 2
0 1 0
1 0 1
[2 rows x 2 columns]
To "delete" the zero-columns, reassign df
:
df = df.loc[:, (df != 0).any(axis=0)]
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