Numerical Computing with Python

How to do it...

1. Load in the college dataset and execute the same operations as the previous recipe to get only the numeric columns that are of interest:

>>> college = pd.read_csv('data/college.csv', index_col='INSTNM')>>> cols = ['MD_EARN_WNE_P10', 'GRAD_DEBT_MDN_SUPP']>>> for col in cols:        college[col] = pd.to_numeric(college[col], errors='coerce')>>> college_n = college.select_dtypes(include=[np.number])>>> criteria = college_n.nunique() == 2>>> binary_cols = college_n.columns[criteria].tolist()>>> college_n = college_n.drop(labels=binary_cols, axis='columns')

2. Find the maximum of each column with the max method:

>>> college_n.max().head()SATVRMID         765.0
SATMTMID         785.0
UGDS          151558.0
UGDS_WHITE         1.0
UGDS_BLACK         1.0
dtype: float64

3. Use the ...