<jupyter_start><jupyter_text>Scores  Introduction:This time you will create the data.***Exercise based on [Chris Albon](http://chrisalbon.com/) work, the credits belong to him.*** Step 1. Import the necessary libraries<jupyter_code>import pandas as pd
import matplotlib.pyplot as plt<jupyter_output><empty_output><jupyter_text>Step 2. Create the DataFrame that should look like the one below.<jupyter_code>raw_data = {
    'first_name' : ['Jason','Molly','Tina','Jake','Amy'],
    'last_name' : ['Miller','Jacobson','Ali','Milner','Cooze'],
    'age'       : [42,52,36,24,73],
    'female'    : [0,1,1,0,1],
    'preTestScore': [4,24,31,2,3],
    'postTestScore':[25,94,57,62,70]
}
studentData = pd.DataFrame(raw_data)
studentData<jupyter_output><empty_output><jupyter_text>Step 3. Create a Scatterplot of preTestScore and postTestScore, with the size of each point determined by age Hint: Don't forget to place the labels<jupyter_code>plt.scatter(studentData.preTestScore,studentData.postTestScore,s=studentData.age,c = studentData.female)
plt.xlabel('Pre Test Score')
plt.ylabel('Post Test Score')
plt.title ('Pre - Post Test Score Scatter Plot')

plt.show()<jupyter_output><empty_output><jupyter_text>Step 4. Create a Scatterplot of preTestScore and postTestScore. This time the size should be 4.5 times the postTestScore and the color determined by sex  BONUS: Create your own question and answer it.<jupyter_code>def gender(x):
    if x == 1:
        return 'female'
    else:
        return 'male'

studentData['gender'] = studentData['female'].apply(gender)
studentData
plt.scatter(studentData.preTestScore,studentData.postTestScore,s=studentData.age)


plt.show()<jupyter_output><empty_output>
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