notebook.community



In [37]:

    
import pandas as pd
from matplotlib.pyplot import pie, axis, show
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
matplotlib.style.use('ggplot')



In [2]:

    
fine_df_file = '../data/interim/fine_enriched_parking_violations.tsv'



In [3]:

    
df = pd.read_csv(fine_df_file, sep='\t', parse_dates=['ticket_issue_datetime'])
df['counter'] = 1
df['dmv_area'] =  (df.rp_plate_state=='DC') | (df.rp_plate_state=='MD') | (df.rp_plate_state=='VA')



In [4]:

    
df.columns









    Out[4]:





Index(['x', 'y', 'objectid', 'rowid_', 'holiday', 'violation_code',
       'violation_description', 'location', 'rp_plate_state', 'body_style',
       'address_id', 'streetsegid', 'xcoord', 'ycoord', 'filename',
       'ticket_issue_datetime', 'fine', 'counter', 'dmv_area'],
      dtype='object')

Select Only Violations that are DC, Maryland or Virginia



In [5]:

    
selected_states = set(['DC', 'MD', 'VA'])



In [6]:

    
dmv_df = df[(df.rp_plate_state=='DC') | (df.rp_plate_state=='MD') | (df.rp_plate_state=='VA') ]



In [14]:

    
by_state = dmv_df.groupby('rp_plate_state').counter.sum()
by_state.plot(kind='bar')









    Out[14]:





<matplotlib.axes._subplots.AxesSubplot at 0x1540f15f8>



In [42]:

    
by_fines = dmv_df.groupby('rp_plate_state').fine.sum()



In [45]:

    
by_fines.plot(kind='bar')









    Out[45]:





<matplotlib.axes._subplots.AxesSubplot at 0x115eea9b0>



In [19]:

    
dmv_df.set_index("ticket_issue_datetime", inplace=True)



In [28]:

    
state_by_year = dmv_df.groupby([pd.TimeGrouper('12M'), 'rp_plate_state' ]).fine.sum()



In [41]:

    
state_by_year.unstack().plot.bar()









    Out[41]:





<matplotlib.axes._subplots.AxesSubplot at 0x13ab294a8>



In [ ]: