In the below example df.columns return the first n columns. Use columns param to specify the columns and inplace=True to apply the change on the existing DataFrame. You can also use DataFrame.drop() method to remove the first n columns. For example df.iloc, substitute n with the integer number specifying how many columns you wanted to delete. Use DataFrame.iloc the indexing syntax with n as an integer to select the first n columns from pandas DataFrame. Use iloc, drop(), pop(), and del keyword methods to drop the top/first n columns from the pandas DataFrame. Delete First N Columns of Pandas DataFrame 'Duration':,ĭf = pd.DataFrame(technologies,index=index_labels)Ģ.4 Using del keyword to Drop Last N Columns of Pandas DataFraīy iterating over the last n column names of pandas DataFrame and for each of them select the column by passing column name in subscript operator to remove last N columns.ģ. Our DataFrame contains column names Courses, Fee, Duration, and Discount. Now, let’s create a DataFrame with a few rows and columns, execute these examples, and validate the results.

# Using del keyword to drop first n columns # Using DataFrame.pop() to drop first n columns # Using drop() function to delete first n columnsĭf.drop(columns=df.columns,axis=1, inplace=True) # Using DataFrame.iloc to drop first n columns # Using del keyword to drop last n columns # Using DataFrame.pop() to drop last n columns # Using drop() function to delete last n columnsĭf.drop(columns=df.columns, axis=1, inplace=True) # Using DataFrame.iloc to drop last n columns

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