how to drop columns in pandas

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how to drop columns in pandas

#To delete the column without having to reassign df
df.drop('column_name', axis=1, inplace=True) 
# Let df be a dataframe
# Let new_df be a dataframe after dropping a column

new_df = df.drop(labels="column_name", axis=1)

# Or if you don't want to change the name of the dataframe
df = df.drop(labels="column_name", axis=1)

# Or to remove several columns
df = df.drop(['list_of_column_names'], axis=1)

# axis=0 for 'rows' and axis=1 for columns
note: df is your dataframe

df = df.drop('coloum_name',axis=1)
# 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 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 contains 'C','D','E'
df = df.drop(['B', 'C'], axis=1)
df.drop(['colonna da togliere'], axis=1)

Final Thoughts

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Hi, I'm Ranjith a full-time Blogger, YouTuber, Affiliate Marketer, & founder of Coder Diksha. Here, I post about programming to help developers.

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