In [5]:
import pandas as pd
import numpy as np

In [2]:
df = pd.read_csv('/Users/jonahwilliams/Documents/SFPD.csv')

In [3]:
df.head()


Out[3]:
Category Descript Date Time PdDistrict Resolution X Y
0 OTHER OFFENSES TRAFFIC VIOLATION 9/21/15 23:36 NORTHERN ARREST, BOOKED -122.433407 37.778423
1 NON-CRIMINAL LICENSE PLATE, RECOVERED 9/21/15 23:36 NORTHERN ARREST, BOOKED -122.433407 37.778423
2 LARCENY/THEFT GRAND THEFT BICYCLE 9/21/15 23:20 NORTHERN NONE -122.432952 37.805052
3 PROSTITUTION LOITERING FOR PURPOSE OF PROSTITUTION 9/21/15 23:20 TENDERLOIN ARREST, BOOKED -122.408202 37.786885
4 ASSAULT INFLICT INJURY ON COHABITEE 9/21/15 23:03 MISSION ARREST, BOOKED -122.419729 37.748221

In [9]:
df['Category'] = df['Category'].map(lambda x: x.replace(',',' '))
df['Resolution'] = df['Resolution'].map(lambda x: x.replace(',',' '))
df['Descript'] = df['Descript'].map(lambda x: x.replace(',',' '))

In [14]:
df['UTC'] = pd.to_datetime(df['Date'] + ' ' + df['Time'])

In [16]:
df = df.drop(['Date', 'Time'], axis=1)

In [17]:
df.head()


Out[17]:
Category Descript PdDistrict Resolution X Y UTC
0 OTHER OFFENSES TRAFFIC VIOLATION NORTHERN ARREST BOOKED -122.433407 37.778423 2015-09-21 23:36:00
1 NON-CRIMINAL LICENSE PLATE RECOVERED NORTHERN ARREST BOOKED -122.433407 37.778423 2015-09-21 23:36:00
2 LARCENY/THEFT GRAND THEFT BICYCLE NORTHERN NONE -122.432952 37.805052 2015-09-21 23:20:00
3 PROSTITUTION LOITERING FOR PURPOSE OF PROSTITUTION TENDERLOIN ARREST BOOKED -122.408202 37.786885 2015-09-21 23:20:00
4 ASSAULT INFLICT INJURY ON COHABITEE MISSION ARREST BOOKED -122.419729 37.748221 2015-09-21 23:03:00

In [ ]: