astype() for type conversion in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to convert the 'age' column to integer type.

Pandas

df['age'] = df['age'].[1]('int')

Drag options to blanks, or click blank then click option'

Aconvert

Bchange_type

Cto_int

Dastype

Attempts:

3 left

💡 Hint

Common Mistakes

Using a non-existent method like 'convert' or 'to_int'.

Trying to assign a string directly without conversion.

The astype() method is used to convert the data type of a pandas Series or DataFrame column.

2fill in blank

medium

Complete the code to convert the 'price' column to float type.

Pandas

df['price'] = df['price'].[1]('float')

Drag options to blanks, or click blank then click option'

Ato_float

Bchange_type

Castype

Dconvert

Attempts:

3 left

💡 Hint

Common Mistakes

Using methods that do not exist in pandas.

Passing the wrong type string.

Use astype('float') to convert a column to float type in pandas.

3fill in blank

hard

Complete the code to convert the 'score' column to string type.

Pandas

df['score'] = df['score'].[1]('str')

Drag options to blanks, or click blank then click option'

Achange_type

Bastype

Cto_str

Dconvert

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the Python type str instead of the string 'str'.

Using a non-existent method.

The astype() method requires the type as a string like 'str', not the Python str type directly.

4fill in blank

hard

Fill both blanks to create a new column 'is_adult' with boolean type based on 'age' >= 18.

Pandas

df['is_adult'] = (df['age'] [1] 18).[2]('bool')

Drag options to blanks, or click blank then click option'

A>=

Bastype

C<

Dconvert

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong comparison operators like '<'.

Using a non-existent method for type conversion.

Use the comparison operator >= to check if age is at least 18, then convert the result to boolean with astype('bool').

5fill in blank

hard

Fill both blanks to create a dictionary with word lengths for words longer than 3 characters.

Pandas

lengths = {word: [1] for word in words if len(word) [2] 3}

Drag options to blanks, or click blank then click option'

A:

Blen(word)

C>

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong dictionary syntax.

Using '<' instead of '>' for filtering.

The dictionary comprehension uses : to separate keys and values, len(word) to get the length, and > to filter words longer than 3 characters.