3. Python's Statistical Toolbox

Activity 3.01: Revisiting the Communities and Crimes Dataset

Solution

1. The libraries can be imported, and pandas can be used to read in the dataset as follows:

   import pandas as pd
   import numpy as np
   import matplotlib.pyplot as plt
   import seaborn as sns
   df = pd.read_csv('CommViolPredUnnormalizedData.txt')
   df.head()

   Your output should be the following:

   Figure 3.29: The first five rows of the dataset

2. To replace the special character with the np.nan object, we can use the following code:

   df = df.replace('?', np.nan)

3. To compute the actual count for the different age groups, we can simply use the expression df['population'] * df['agePct...'], which computes the count in a vectorized way:

   age_groups = ['12t21', '12t29', '16t24', '65up']
    
   for group in age_groups:
       df['ageCnt' + group] = (df['population'] * \
     ...