DataFrames are flexible! Easily create new columns or remove unnecessary ones:
# Add new column
df['revenue'] = df['sales'] * df['price']
# From existing columns
df['full_name'] = df['first_name'] + ' ' + df['last_name']
# Drop columns
df.drop(columns=['temp_col'], inplace=True)
# Or create a new DF without modifying original
clean_df = df.drop(columns=['old_col1', 'old_col2'])
Next up 👉 Dealing with Missing Values
