astype() for type conversion in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the astype() method do in pandas?

The astype() method changes the data type of a pandas Series or DataFrame column to a specified type, like integer, float, or string.

beginner

How do you convert a column named 'age' in a DataFrame df to integers using astype()?

You use df['age'] = df['age'].astype(int) to convert the 'age' column to integer type.

beginner

Can astype() convert a column with numbers stored as strings to numeric types?

Yes, astype() can convert string numbers like '10' to numeric types like int or float, as long as the strings are valid numbers.

intermediate

What happens if you try to convert a column with non-numeric strings to a numeric type using astype()?

It will raise an error because astype() cannot convert non-numeric strings to numbers directly.

intermediate

How can you convert multiple columns in a DataFrame to different types using astype()?

You can pass a dictionary to astype() like df = df.astype({'col1': 'int', 'col2': 'float'}) to convert multiple columns at once.

What is the correct way to convert a pandas Series s to float type?

A s.astype(float)

B astype(s, float)

C s.convert(float)

D convert(s, float)

The correct syntax is s.astype(float) to convert the Series to float type.

If a DataFrame column has values ['1', '2', 'three'], what happens when you run df['col'].astype(int)?

A The column converts successfully to integers.

B It raises an error due to 'three' not being numeric.

C It converts 'three' to NaN automatically.

D It converts all values to strings.

Conversion fails because 'three' is not a numeric string, causing an error.

Which of these is a valid argument for astype() to convert to string type?

A All of the above

B 'string'

C str

D 'str'

You can use 'str', 'string', or the Python type str to convert to string type.

How do you convert multiple columns to different types in one step?

A df.type({'col1': 'int', 'col2': 'float'})

B df.convert({'col1': 'int', 'col2': 'float'})

C df.change_type({'col1': 'int', 'col2': 'float'})

D df.astype({'col1': 'int', 'col2': 'float'})

Passing a dictionary to astype() converts multiple columns at once.

What type of object can astype() be used on?

A pandas Series

B pandas DataFrame

C Both Series and DataFrame

D Only Python lists

astype() works on both pandas Series and DataFrame objects.

Explain how to use astype() to convert a DataFrame column from string to integer type. Include what happens if the strings are not numeric.

Think about what happens when conversion is impossible.

Describe how to convert multiple columns in a DataFrame to different data types using astype().

Use a dictionary inside astype()