import csv 
import sys
import pandas as pd
import scipy as sp
import numpy as np

import matplotlib
import matplotlib.pyplot as plt
#%matplotlib inline
import datetime as dt

filename = open(sys.argv[1])
#sys.argv[1]
reader = csv.reader(filename, delimiter = ',')

next(reader)
agencyComplaints = {}

for line in reader:
    agency = line[3]
    day_time = dt.datetime.strptime(line[1], "%m/%d/%Y %H:%M:%S %p")
    day = day_time.strftime('%Y-%m-%d')

    #day = day_time.strftime('%b %d %Y')

    if agency in agencyComplaints:
        if day in agencyComplaints[agency]:
            agencyComplaints[agency][day] += 1
        else: 
            agencyComplaints[agency][day] = 1
    else:
        dictCnt = {} 
        dictCnt[day] = 1
        agencyComplaints[agency] = dictCnt
        
nypd = agencyComplaints['NYPD']
df_nypd = pd.DataFrame(nypd.items(), columns=['date','count']) 

tlc = agencyComplaints['TLC']
df_tlc = pd.DataFrame(tlc.items(), columns=['date','count'])

dpr = agencyComplaints['DPR']
df_dpr = pd.DataFrame(dpr.items(), columns=['date','count'])
 
df = pd.merge(df_nypd, df_tlc, on='date')
df1 = pd.merge(df, df_dpr, on = 'date')

df1.columns = ['date', 'NYPD', 'TLC', 'DPR']
df2 = df1.sort(columns='date', ascending=True)

for index, line in df2.iterrows():
    s = dt.datetime.strptime(line[0], '%Y-%m-%d')
    s1 = s.strftime('%b %d %Y')
    df2.loc[index, 'date'] = s1

df3 = df2.set_index('date')
df3.plot()
plt.ylabel("Number of Complaints")
plt.xlabel("Date")
plt.title("Number of Complaints Over Time")

plt.show()

34c4289e9ec11aeb3a176fcd419b809356179b18
<mask token>

<mask token>
next(reader)
<mask token>
for line in reader:
    agency = line[3]
    day_time = dt.datetime.strptime(line[1], '%m/%d/%Y %H:%M:%S %p')
    day = day_time.strftime('%Y-%m-%d')
    if agency in agencyComplaints:
        if day in agencyComplaints[agency]:
            agencyComplaints[agency][day] += 1
        else:
            agencyComplaints[agency][day] = 1
    else:
        dictCnt = {}
        dictCnt[day] = 1
        agencyComplaints[agency] = dictCnt
<mask token>
for index, line in df2.iterrows():
    s = dt.datetime.strptime(line[0], '%Y-%m-%d')
    s1 = s.strftime('%b %d %Y')
    df2.loc[index, 'date'] = s1
<mask token>
df3.plot()
plt.ylabel('Number of Complaints')
plt.xlabel('Date')
plt.title('Number of Complaints Over Time')
plt.show()

<mask token>
filename = open(sys.argv[1])
reader = csv.reader(filename, delimiter=',')
next(reader)
agencyComplaints = {}
for line in reader:
    agency = line[3]
    day_time = dt.datetime.strptime(line[1], '%m/%d/%Y %H:%M:%S %p')
    day = day_time.strftime('%Y-%m-%d')
    if agency in agencyComplaints:
        if day in agencyComplaints[agency]:
            agencyComplaints[agency][day] += 1
        else:
            agencyComplaints[agency][day] = 1
    else:
        dictCnt = {}
        dictCnt[day] = 1
        agencyComplaints[agency] = dictCnt
nypd = agencyComplaints['NYPD']
df_nypd = pd.DataFrame(nypd.items(), columns=['date', 'count'])
tlc = agencyComplaints['TLC']
df_tlc = pd.DataFrame(tlc.items(), columns=['date', 'count'])
dpr = agencyComplaints['DPR']
df_dpr = pd.DataFrame(dpr.items(), columns=['date', 'count'])
df = pd.merge(df_nypd, df_tlc, on='date')
df1 = pd.merge(df, df_dpr, on='date')
df1.columns = ['date', 'NYPD', 'TLC', 'DPR']
df2 = df1.sort(columns='date', ascending=True)
for index, line in df2.iterrows():
    s = dt.datetime.strptime(line[0], '%Y-%m-%d')
    s1 = s.strftime('%b %d %Y')
    df2.loc[index, 'date'] = s1
df3 = df2.set_index('date')
df3.plot()
plt.ylabel('Number of Complaints')
plt.xlabel('Date')
plt.title('Number of Complaints Over Time')
plt.show()

import csv
import sys
import pandas as pd
import scipy as sp
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import datetime as dt
filename = open(sys.argv[1])
reader = csv.reader(filename, delimiter=',')
next(reader)
agencyComplaints = {}
for line in reader:
    agency = line[3]
    day_time = dt.datetime.strptime(line[1], '%m/%d/%Y %H:%M:%S %p')
    day = day_time.strftime('%Y-%m-%d')
    if agency in agencyComplaints:
        if day in agencyComplaints[agency]:
            agencyComplaints[agency][day] += 1
        else:
            agencyComplaints[agency][day] = 1
    else:
        dictCnt = {}
        dictCnt[day] = 1
        agencyComplaints[agency] = dictCnt
nypd = agencyComplaints['NYPD']
df_nypd = pd.DataFrame(nypd.items(), columns=['date', 'count'])
tlc = agencyComplaints['TLC']
df_tlc = pd.DataFrame(tlc.items(), columns=['date', 'count'])
dpr = agencyComplaints['DPR']
df_dpr = pd.DataFrame(dpr.items(), columns=['date', 'count'])
df = pd.merge(df_nypd, df_tlc, on='date')
df1 = pd.merge(df, df_dpr, on='date')
df1.columns = ['date', 'NYPD', 'TLC', 'DPR']
df2 = df1.sort(columns='date', ascending=True)
for index, line in df2.iterrows():
    s = dt.datetime.strptime(line[0], '%Y-%m-%d')
    s1 = s.strftime('%b %d %Y')
    df2.loc[index, 'date'] = s1
df3 = df2.set_index('date')
df3.plot()
plt.ylabel('Number of Complaints')
plt.xlabel('Date')
plt.title('Number of Complaints Over Time')
plt.show()

import csv 
import sys
import pandas as pd
import scipy as sp
import numpy as np

import matplotlib
import matplotlib.pyplot as plt
#%matplotlib inline
import datetime as dt

filename = open(sys.argv[1])
#sys.argv[1]
reader = csv.reader(filename, delimiter = ',')

next(reader)
agencyComplaints = {}

for line in reader:
    agency = line[3]
    day_time = dt.datetime.strptime(line[1], "%m/%d/%Y %H:%M:%S %p")
    day = day_time.strftime('%Y-%m-%d')

    #day = day_time.strftime('%b %d %Y')

    if agency in agencyComplaints:
        if day in agencyComplaints[agency]:
            agencyComplaints[agency][day] += 1
        else: 
            agencyComplaints[agency][day] = 1
    else:
        dictCnt = {} 
        dictCnt[day] = 1
        agencyComplaints[agency] = dictCnt
        
nypd = agencyComplaints['NYPD']
df_nypd = pd.DataFrame(nypd.items(), columns=['date','count']) 

tlc = agencyComplaints['TLC']
df_tlc = pd.DataFrame(tlc.items(), columns=['date','count'])

dpr = agencyComplaints['DPR']
df_dpr = pd.DataFrame(dpr.items(), columns=['date','count'])
 
df = pd.merge(df_nypd, df_tlc, on='date')
df1 = pd.merge(df, df_dpr, on = 'date')

df1.columns = ['date', 'NYPD', 'TLC', 'DPR']
df2 = df1.sort(columns='date', ascending=True)

for index, line in df2.iterrows():
    s = dt.datetime.strptime(line[0], '%Y-%m-%d')
    s1 = s.strftime('%b %d %Y')
    df2.loc[index, 'date'] = s1

df3 = df2.set_index('date')
df3.plot()
plt.ylabel("Number of Complaints")
plt.xlabel("Date")
plt.title("Number of Complaints Over Time")

plt.show()
