import pandas as pd
numbers = [
[1, 2, 3],
[4, 5, 6],
[7, 8, 9]
]
df = pd.DataFrame(numbers)
condition = df.loc[:, 1:2] < 4
df[condition]
0 1 2
0 NaN 2.0 3.0
1 NaN NaN NaN
2 NaN NaN NaN
Why am I getting these wrong results, and what can I do to get the correct results?
Boolean condition has to be Series, but here your selected columns return DataFrame:
print (condition)
1 2
0 True True
1 False False
2 False False
So for convert boolean Dataframe to mask use DataFrame.all for test if all Trues per rows or
DataFrame.any if at least one True per rows:
print (condition.any(axis=1))
print (condition.all(axis=1))
0 True
1 False
2 False
dtype: bool
Or select only one column for condition:
print (df.loc[:, 1] < 4)
0 True
1 False
2 False
Name: 1, dtype: bool
print (df[condition.any(axis=1)])
0 1 2
0 1 2 3