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How to remove lines according to different conditions?
📁 python, numpy, pandas
there is a data frame and I need to delete lines from it in which the value of the column a is more than 50. This operation is successfully performed by the code:
Import pandas as pd import numpy as nprondf = PD.Dataframe ([ 256 , 4 , 24 , 51 ], [ 24 ,, 25 , 34 , 200 ], [ 300 , 12 , 45 , 11 ], [ 34 , 19 , 2 , 34 ], [ 75 , 76 , 19 , 11 ], [ 42 , 89 , 29 , 101 ], [ 54 , 104 , 11 , 12 ]]) df.reneame ({ 0 : 'a' a 'a' a `` ", 1 : 'b' , 2 : 'c' , 3 : 'd' d '}, Axis = 1 , inplace = true ) df_without_noise = df.drop (df [ 'a' ] & gt; 250 ) [ 0 ]) and it tus out DATA-HIGHLIGHTED = ""> A B C D 1 24 25 34 200 3 34 19 2 34 4 75 76 19 11 5 42 89 29 101 6 54 104 11 12
Then you need to remove the lines in which the column
df_without_noise = df_without_noise.drop (np.where (df_without_noise [] & gt; 50 ) [ 0 ]) but displays the error:
keyeroror: '[2] not found in Axis'
In this case, the column in contains values of more than 50.
how to remove lines with them? DATA-HIGHLIGHTED = ""> A B C D 1 24 25 34 200 3 34 19 2 34
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