Extract a function
While developing a model to predict college graduations, you wrote the code below to get the z-scores of students' yearly GPAs (z-scores indicate standard deviation from the mean). Now you're ready to turn it into a production-quality system, so you need to do something about the repetition. Writing a function to calculate z-scores would improve it.
# Standardize the GPAs for each year
df['y1_z'] = (df.y1_gpa - df.y1_gpa.mean()) / df.y1_gpa.std()
df['y2_z'] = (df.y2_gpa - df.y2_gpa.mean()) / df.y2_gpa.std()
df['y3_z'] = (df.y3_gpa - df.y3_gpa.mean()) / df.y3_gpa.std()
df['y4_z'] = (df.y4_gpa - df.y4_gpa.mean()) / df.y4_gpa.std()
Note: df is a pandas DataFrame where each row is a student with 4 columns of yearly student GPAs: y1_gpa, y2_gpa, y3_gpa, y4_gpa.
This exercise is part of the course
Writing Functions in Python
Exercise instructions
- Finish the function so that it returns the z-scores of a column.
- Use the function to calculate the z-scores for each year (
df['y1_z'],df['y2_z'], etc.) from the raw GPA scores (df.y1_gpa,df.y2_gpa, etc.).
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
def standardize(column):
"""Standardize the values in a column.
Args:
column (pandas Series): The data to standardize.
Returns:
pandas Series: the values as z-scores
"""
# Finish the function so that it returns the z-scores
z_score = (____ - ____.____()) / ____.____()
return z_score
# Use the standardize() function to calculate the z-scores
df['y1_z'] = ____
df['y2_z'] = ____
df['y3_z'] = ____
df['y4_z'] = ____