# The usual preamble
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

# Make the graphs a bit prettier, and bigger
pd.set_option('display.mpl_style', 'default')
plt.rcParams['figure.figsize'] = (15, 5)


# This is necessary to show lots of columns in pandas 0.12. 
# Not necessary in pandas 0.13.
pd.set_option('display.width', 5000) 
pd.set_option('display.max_columns', 60)

complaints = pd.read_csv('../data/311-service-requests.csv')

complaints[:5]

noise_complaints = complaints[complaints['Complaint Type'] == "Noise - Street/Sidewalk"]
noise_complaints[:3]

complaints['Complaint Type'] == "Noise - Street/Sidewalk"

is_noise = complaints['Complaint Type'] == "Noise - Street/Sidewalk"
in_brooklyn = complaints['Borough'] == "BROOKLYN"
complaints[is_noise & in_brooklyn][:5]

complaints[is_noise & in_brooklyn][['Complaint Type', 'Borough', 'Created Date', 'Descriptor']][:10]

pd.Series([1,2,3])

np.array([1,2,3])

pd.Series([1,2,3]).values

arr = np.array([1,2,3])

arr != 2

arr[arr != 2]

is_noise = complaints['Complaint Type'] == "Noise - Street/Sidewalk"
noise_complaints = complaints[is_noise]
noise_complaints['Borough'].value_counts()

noise_complaint_counts = noise_complaints['Borough'].value_counts()
complaint_counts = complaints['Borough'].value_counts()

noise_complaint_counts / complaint_counts

noise_complaint_counts / complaint_counts.astype(float)

(noise_complaint_counts / complaint_counts.astype(float)).plot(kind='bar')