import pandas as pd
df=pd.read_csv('311_Constituent_Services_Daily_Calls.csv')
df.head()
'service_request_id',
'service_name',
'requested_datetime',
'source',
'description',
'status_description',
'updated_datetime',
'service_subtype',
'neighborhood_district',
'closed_date',
'location',
'address',
df.columns=['service_request_id',
'service_name',
'requested_datetime',
'source',
'description',
'status_description',
'updated_datetime',
'service_subtype',
'neighborhood_district',
'closed_date',
'location',
'address',
]
df['lat']=df.location.apply(lambda x : x.split('\n')[2].split(',')[0][1:])
df['long']=df.location.apply(lambda x : x.split('\n')[2].split(',')[1][:-1])
df['requested_datetime']=pd.to_datetime(df['requested_datetime'])
df['updated_datetime']=pd.to_datetime(df['updated_datetime'])
df['closed_date']=pd.to_datetime(df['closed_date'])
df['requested_datetime']=df['requested_datetime'].dt.strftime('%Y%m%dT%H:%MZ')
df['updated_datetime']=df['updated_datetime'].dt.strftime('%Y%m%dT%H:%MZ')
df['closed_date']=df['closed_date'].dt.strftime('%Y%m%dT%H:%MZ')
df.head()
df.to_csv('311_geo_report.csv',index=False)