Do you want to know the details about “how to drop columns in pandas”. If yes, you’re in the correct article.
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.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
df = df.drop(['B', 'C'], axis=1)
df.drop(['colonna da togliere'], axis=1)
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