Answers for "remove some columns from dataframe"

1

remove columns from a dataframe python

# Import pandas package
import pandas as pd

# create a dictionary with five fields each
data = {
'A':['A1', 'A2', 'A3', 'A4', 'A5'],
'B':['B1', 'B2', 'B3', 'B4', 'B5'],
'C':['C1', 'C2', 'C3', 'C4', 'C5'],
'D':['D1', 'D2', 'D3', 'D4', 'D5'],
'E':['E1', 'E2', 'E3', 'E4', 'E5'] }

# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
#drop the 'A' column from your dataframe df 
df.drop(['A'],axis=1,inplace=True)
df

#-->df contains 'B','C','D' and 'E'
#in this example you will change your dataframe , if you don't want to ,
#just remove the in place parameter and assign your result to an other variable 

df1=df.drop(['B'],axis=1)
#-->df1 contains 'C','D','E'
df1
Posted by: Guest on January-27-2022
1

delete unnamed coloumns in pandas

# Best method so far.
df = df.loc[:, ~df.columns.str.contains('^Unnamed')]
Posted by: Guest on May-24-2021
0

remove columns that start with pandas

cols = [c for c in df.columns if c.lower()[:6] != 'string']
df=df[cols]
Posted by: Guest on March-16-2021

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