Learn
Modifying DataFrames
Performing Column Operations

In the previous exercise, we learned how to add columns to a DataFrame.

Often, the column that we want to add is related to existing columns, but requires a calculation more complex than multiplication or addition.

For example, imagine that we have the following table of customers.

Name Email
JOHN SMITH [email protected]
Jane Doe [email protected]
joe schmo [email protected]

It’s a little annoying that the capitalization is different for each row. Perhaps we’d like to make it more consistent by making all of the letters uppercase.

We can use the `apply` function to apply a function to every value in a particular column. For example, this code overwrites the existing `'Name'` columns by applying the function `upper` to every row in `'Name'`.

``````from string import upper

df['Name'] = df.Name.apply(upper)``````

The result:

Name Email
JOHN SMITH [email protected]
JANE DOE [email protected]
JOE SCHMO [email protected]

### Instructions

1.

Apply the function `lower` to all names in column `'Name'` in `df`. Assign these new names to a new column of `df` called `'Lowercase Name'`. The final DataFrame should look like this:

Name Email Lowercase Name
JOHN SMITH [email protected] john smith
Jane Doe [email protected] jane doe
joe schmo [email protected] joe schmo