I know this has to have been addressed before, but I cannot seem to find an answer that works
I have the columns that I want to test the condition against and I want to remove all rows where their value in any of the three columns is above a given value.
x a b c d
1 2 1 3 4
2 3 5 2 2
3 3 3 3 2
4 1 2 3 3
if I ran against this dataframe, with my cutoff value being anything greater than 3, then I should be returned with
x a b c d
3 3 3 3 2
4 1 2 3 3
If your dataframe is df then df[~df[df>3].any(axis=1)]
df[~(df.gt(3)).any(1)] is faster.
You can remove rows like:
import pandas as pd
import numpy as np
df.loc[df.x>=3,:]
You can also use conditions using numpy logical_and and logical_or if you have upper and lower limit
df = df.loc[np.logical_and(dd.x<=3,df.x<=0),:]
You can also use ~
df.loc[~df.x.isin([1,2]),:]
Something like this should work.
cols = ["a" , "b" , "c"]
greater_than_3 = (df[cols]>3).any(axis=1)
df = df[!greater_than_3]
