Python Data Script for Coursera

Python Data Script for Coursera

import pandas
import numpy

pandas.set_option('display.float_format', lambda x: '%f'%x)

data = pandas.read_csv('datasets/ool_pds.csv', low_memory=False)
data.columns = map(str.upper, data.columns)

print(len(data))
print(len(data.columns))

# 
data["W1_A11"] = data["W1_A11"].convert_objects(convert_numeric=True)
data["W1_K1_B"] = data["W1_K1_B"].convert_objects(convert_numeric=True)
data["W1_K1_A"] = data["W1_K1_A"].convert_objects(convert_numeric=True)
data["W1_K1_C"] = data["W1_K1_C"].convert_objects(convert_numeric=True)
data["W1_K1_D"] = data["W1_K1_D"].convert_objects(convert_numeric=True)
data["W1_B4"] = data["W1_B4"].convert_objects(convert_numeric=True)


# Pull and print variables
print("In all cases, -1 = Refusal to answer")
print("Days of week watching news; 1 = None, 2 = One...., 8 = Seven")
news = data["W1_A11"].value_counts(sort=True, normalize=True)
print(news)

print("Police Trust; 1 = Always, 4 = Never")
police = data["W1_K1_B"].value_counts(sort=True, normalize=True)
print(police)

print("Govt Trust; 1 = Always, 4 = Never")
govt = data["W1_K1_A"].value_counts(sort=True, normalize=True)
print(govt)

print("Legal System Trust; 1 = Always, 4 = Never")
lsystem = data["W1_K1_C"].value_counts(sort=True, normalize=True)
print(lsystem)

print("Public School Trust; 1 = Always, 4 = Never")
pschool = data["W1_K1_D"].value_counts(sort=True, normalize=True)
print(pschool)

print("Anger About Country; 1 = Extremely Angry, 5 = Not Angry at All")
anger = data["W1_B4"].value_counts(sort=True, normalize=True)
print(anger)