replace() for value substitution in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the replace() function do in pandas?

It substitutes specified values in a DataFrame or Series with new values you provide.

beginner

How do you replace all occurrences of the value 0 with 100 in a pandas DataFrame?

Use df.replace(0, 100) to change all 0 values to 100.

intermediate

Can replace() handle multiple values at once? How?

Yes, by passing a dictionary like {old_value: new_value, ...} to replace multiple values in one call.

intermediate

What happens if you use replace() without assigning the result back to the DataFrame?

The original DataFrame stays the same because replace() returns a new DataFrame by default and does not modify in place unless inplace=True is set.

beginner

How can you replace values only in a specific column using replace()?

Apply replace() on that column like df['column_name'].replace(old, new).

What is the correct way to replace all 'cat' values with 'dog' in a pandas Series named pets?

A pets.replace('cat', 'dog')

B pets.substitute('cat', 'dog')

C pets.change('cat', 'dog')

D pets.update('cat', 'dog')

The replace() method is used to substitute values in pandas objects.

Which argument makes replace() change the DataFrame without needing assignment?

A inplace=True

B modify=True

C change=True

D update=True

Setting inplace=True modifies the DataFrame directly.

How do you replace multiple values at once in pandas?

A By using <code>replace_all()</code>

B By calling <code>replace()</code> multiple times

C By passing a dictionary to <code>replace()</code>

D By using <code>substitute()</code>

A dictionary like {old1: new1, old2: new2} lets you replace many values in one call.

If you want to replace values only in one column, what should you do?

A Use <code>replace()</code> with a column name argument

B Use <code>replace()</code> on the whole DataFrame

C Use <code>replace_column()</code>

D Use <code>replace()</code> on that column only

Applying replace() on a single column changes values only there.

What does df.replace(0, 100) do?

A Adds 100 to all 0 values

B Replaces all 0 values with 100 in the DataFrame

C Deletes all 0 values

D Replaces all 100 values with 0 in the DataFrame

It substitutes every 0 with 100 in the DataFrame.

Explain how to use replace() to change multiple values in a pandas DataFrame.

Think about how you can map old values to new ones in one step.

Describe the difference between using replace() with and without the inplace=True argument.

Consider if the original data changes immediately or not.