text: #!/usr/bin/env python
  
  import pandas as pd 
  pd.set_option('display.max_rows', 15500)
  pd.set_option('display.max_columns', 55500)
  pd.set_option('display.width', 551000)
  data = pd.read_csv("crimemar14.csv")
  data.head()
  
  newdata = data["Datetime"].str.split("@", n = 1, expand = True)
  
  data["date"] = newdata[0]
  
  data["time"] = newdata[1]
  data.head()
  
  data["time"]= pd.to_datetime(data["time"],format=' %I:%M %p' ).dt.time
  
  data["date"]= pd.to_datetime(data["date"],errors='coerce' )
  data["day"]= data["date"].dt.day
  data["dayname"]= data["date"].dt.day_name()
  data["dayofweek"] = data["date"].dt.dayofweek
  data["monthname"] = data["date"].dt.month_name()
  data['Datetime'] = pd.to_datetime(data["Datetime"],format='%m/%d/%Y @ %I:%M %p',errors='coerce')
  data.head()
  
  daycrime = data.groupby('Crime_Type')['day'].value_counts()
  
  daycrime = data.groupby('Crime_Type')['monthname'].value_counts()
  
  crimetypes = [ "Arson", "Assault", "Burglary", "Disturbing the Peace", "Drugs / Alcohol Violations", "DUI", "Fraud", "Homicide", "Motor Vehicle Theft", "Robbery", "Sex Crimes", "Theft / Larceny", "Vandalism", "Vehicle Break-In / Theft", "Weapons"]
  
  df = pd.DataFrame()
  
  #for crime in crimetypes:
  
  d1 = daycrime["Assault"]
  df["Type"] = d1
  #print(df)
  crimes = daycrime.index
  for x in daycrime["Assault"]:
     print(x)
  
    #df.append(d1)
  
  data
  daystreetcrime = data["Street_Address"].str.split(" ", n = 2, expand = True)
  data['StreetName'] = daystreetcrime[2]
  streetofcrime = data.groupby('dayname')['StreetName'].value_counts()
  
  print(streetofcrime)
  