Adding and Dropping Columns

A new column is an assignment, and drop returns a new table by default.

A derived column

Assigning to a name that does not exist creates it. The right-hand side is an ordinary column expression, so it lines up row by row.

import pandas as pd

df = pd.DataFrame({"price": [10.0, 20.0]})
df["with_tax"] = df["price"] * 1.08
print(df)

Dropping returns a copy

drop hands back a new table and leaves yours alone unless you reassign. This surprises people who expect it to act in place.

import pandas as pd

df = pd.DataFrame({"a": [1], "b": [2]})
smaller = df.drop(columns=["b"])
print(list(smaller.columns))
print(list(df.columns))

Exercise

Try It Yourself

Write add_total(df) that returns a new table with a total column equal to price times quantity, leaving the table it was given unchanged.

import pandas as pd

def add_total(df):
    # A new table with a total column.
    return df

print(add_total(pd.DataFrame({"price": [2.0], "quantity": [3]})))

Press Run to see output

Check Your Understanding

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