Numerical Computing with Python

How to do it...

1. Read in the college dataset, and drop any rows that have missing values in either the UGDS, SATMTMID, or SATVRMID columns. We must have non-missing values for each of these three columns:

>>> college = pd.read_csv('data/college.csv')>>> subset = ['UGDS', 'SATMTMID', 'SATVRMID']>>> college2 = college.dropna(subset=subset)>>> college.shape(7535, 27)>>> college2.shape(1184, 27)

2. The vast majority of institutions do not have data for our three required columns, but this is still more than enough data to continue. Next, create a user-defined function to calculate the weighted average of just the SAT math scores:

>>> def weighted_math_average(df):        weighted_math = df['UGDS'] * df['SATMTMID'] return int(weighted_math.sum() / df['UGDS'].sum()) ...