In [1]:

    

import pandas as pd
df = pd.read_csv('the_final_countdown2.csv', sep=",", encoding = 'utf-8', engine = 'python')


    

In [7]:

    

ChangeInViolations = [0]

for i in range(1,len(df)):
    x = i
    y = x-1
    if df.iloc[x,1] == df.iloc[y,1]:
        v = df.iloc[x,14] - df.iloc[y,14]
        ChangeInViolations.append(v)
    else:
        ChangeInViolations.append(0)


    

In [8]:

    

ChangeInViolations = pd.Series(ChangeInViolations)
df['ChangeInViolations'] = ChangeInViolations.values


    

In [9]:

    

Asian = ['Szechuan','Cantonese','Hot Pot','Malaysian','Shanghainese','Singaporean','Cambodian','Mongolian',
    'Teppanyaki','Ramen','Taiwanese','Traditional Chinese','Thai','Vietnamese','Korean','Japanese','Chinese','Oriental']
French = ['French']
Sandwiches = ['Sandwiches']
FastFood = ['Fast Food']
Burgers = ['Burgers']
Italian = ['Italian']
Hawaiian = ['Hawaiian']
Southern = ['Southern']
Mexican = ['Mexican','New Mexican Cuisine']
LatinAmerican = ['Latin-American']
MiddleEastern = ['Middle Eastern']
Greek = ['Greek']
American= ['American (Traditional)','American (New)']
Donuts = ['Donuts']
Indian =['Indian']
Seafood = ['Seafood']
Desserts = ['Desserts']
Salad = ['Salad']
Pizza = ['Pizza']


    

In [10]:

    

ct = [Asian,French,Sandwiches,FastFood,Burgers,Italian,Hawaiian,Southern,Mexican,LatinAmerican,
               MiddleEastern,Greek,American,Donuts,Indian,Seafood,Desserts,Salad,Pizza]


    

In [11]:

    

def cuisineType(z):
    columnName = []
    for i in range(len(df)):
        y = 0
        for x in z:
            if x in df.iloc[i,4]:
                columnName.append(1)
                break
            else:
                y += 1
                if y == len(z):
                    columnName.append(0)
    
    return columnName


    

In [12]:

    

colname = 1
for Type in ct:
    newcol = cuisineType(Type)
    newcol = pd.Series(newcol)
    df[colname] = newcol.values
    colname += 1


    

In [13]:

    

df.rename(columns ={1:"IsAsian",2:'IsFrench',3:'IsSandwiches',4:'IsFastFood',5:'IsBurgers',6:'IsItalian',7:'IsHawaiian',
                   8:'IsSouthern',9:'IsMexican',10:'IsLatinAmerican',11:'IsMiddleEastern',12:'IsGreek',13:'IsAmerican',
                   14:'IsDonuts',15:'IsIndian',16:'IsSeafood',17:'IsDesserts',18:'IsSalad',19:'Pizza'},inplace=True)


    

In [14]:

    

rt = ['Buffets','Sushi Bars','Delis','Sports Bars','Bakeries','Pubs','Caterers','Diners','Cafes','Bars']


    

In [15]:

    

def restaurantType(x):
    restaurant = []
    for i in range(len(df)):
        if x in df.iloc[i,4]:
            restaurant.append(1)
        else:
            restaurant.append(0)
    
    return restaurant


    

In [16]:

    

for Type in rt:
    colname = 'Is'+ Type
    newcol = restaurantType(Type)
    newcol = pd.Series(newcol)
    df[colname] = newcol.values


    

In [17]:

    

df.to_csv('the_final_countdown_New.csv')


    

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