How can you remove columns with NaN, +inf, and -inf values? All solutions I see here, mention only rows, but imagine I have a set of features from each element in the dataframe, how can I remove only the columns that contain +inf, -inf and NaN from each row in the dataframe?
Remove nan, +inf, -inf values columns from a dataframe
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1 Answers
First replace() inf and -inf with nan:
df = pd.DataFrame({'a':[1,2,3], 'b':[4,np.nan,6], 'c':[7,8,np.inf]})
df = df.replace([np.inf, -np.inf], np.nan)
# a b c
# 0 1 4.0 7.0
# 1 2 NaN 8.0
# 2 3 6.0 NaN
Then use the axis param of dropna() to switch between row- and column-based behavior:
df.dropna() # default axis=0 is row-based
# a b c
# 0 1 4.0 7.0
df.dropna(axis=1) # axis=1 or axis='columns' is column-based
# a
# 0 1
# 1 2
# 2 3
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