FoodRec.py

import pandas as pd
import numpy as np

#Reading in the .json file#
df_b = pd.read_json('yelp_academic_dataset_business.json', lines=True)

#Drop useless categories

drop_columns = ['hours','is_open', 'address', 'city', 'state', 'postal_code', 'latitude', 'longitude'] #Dropping these categories cause we dont need it. Could be more.
df_b = df_b.drop(drop_columns, axis=1)

#This sets the output to show EVERYTHING. If you only want to see one row, set the first 'None' to 1. I just wanted to see the different column names.
pd.set_option("display.max_rows", 10 , "display.max_columns", None)

#A dataframe containing ONLY places that have the restaurant category.
restaurants = df_b[df_b['categories'].str.contains('Restaurants', case = False, na = False)]

#This will let you see ALL the restaurant categories(Asian, Mexican, Fast Food, etc.)
#df_explode = restaurants.assign(categories = restaurants.categories.str.split(', ')).explode('categories')
#print(df_explode.categories.value_counts())


#This should return a dataframe containing any and all asian restaurants. Rinse and repeat for all other groups.
#template name = restaurants[restaurants['categories'].str.contains('',case=False,na=False)]
asian = restaurants[restaurants['categories'].str.contains('Chinese|Japanese|Sushi Bars|Asian Fusion|Indian|Thai|Vietnamese|Korean|Bubble Tea|Ramen|Dim Sum|Taiwanese|Hot Pot|Pan Asian|Szechuan|Malaysian|Indonesian|Poke', case=False, na=False)]
asian = asian.sort_values(by = 'review_count', ascending = False)

american = restaurants[restaurants['categories'].str.contains('American|Burgers|Breakfast|Chicken Wings|Barbeque|Steakhouses|Diners|Hot Dogs|Fast Food|Sandwiches|Cheesesteaks',case=False,na=False)]
american = american.sort_values(by = 'review_count', ascending = False)

italian = restaurants[restaurants['categories'].str.contains('Pizza|Italian',case=False,na=False)]
italian = italian.sort_values(by = 'review_count', ascending = False)

bars = restaurants[restaurants['categories'].str.contains('Nightlife|Bars|Sports Bars|Pubs|Beer|Wine Bars|Juice Bars|Beer Bar|Hookah Bars|Cocktail Bars',case=False,na=False)]
bars = bars.sort_values(by = 'review_count', ascending = False)

fast_food = restaurants[restaurants['categories'].str.contains('Fast Food',case=False,na=False)]
fast_food = fast_food.sort_values(by = 'review_count', ascending = False)

diners = restaurants[restaurants['categories'].str.contains('Diners',case=False,na=False)]
diners = diners.sort_values(by = 'review_count', ascending = False)

dessert = restaurants[restaurants['categories'].str.contains('Bakeries|Desserts|Ice Cream|Donuts|Creperies|Patisserie|Waffles',case=False,na=False)]
dessert = dessert.sort_values(by = 'review_count', ascending = False)

sandwiches = restaurants[restaurants['categories'].str.contains('Sandwiches|Delis|Bagels|Hot Dogs',case=False,na=False)]
sandwiches = sandwiches.sort_values(by = 'review_count', ascending = False)

coffee = restaurants[restaurants['categories'].str.contains('Coffee|',case=False,na=False)]
coffee = coffee.sort_values(by = 'review_count', ascending = False)

japanese = restaurants[restaurants['categories'].str.contains('Japanese|Sushi|Ramen',case=False,na=False)]
japanese = japanese.sort_values(by = 'review_count', ascending = False)

korean = restaurants[restaurants['categories'].str.contains('Korean',case=False,na=False)]
korean = korean.sort_values(by = 'review_count', ascending = False)

indian = restaurants[restaurants['categories'].str.contains('Indian',case=False,na=False)]
indian = indian.sort_values(by = 'review_count', ascending = False)

chinese = restaurants[restaurants['categories'].str.contains('Chinese|Dim Sum|Cantonese|Szechuan',case=False,na=False)]
chinese = chinese.sort_values(by = 'review_count', ascending = False)

mediterranean = restaurants[restaurants['categories'].str.contains('Mediterranean',case=False,na=False)]
mediterranean = mediterranean.sort_values(by = 'review_count', ascending = False)

vegetable_people = restaurants[restaurants['categories'].str.contains('Salad|Vegetarian',case=False,na=False)]
vegetable_people = vegetable_people.sort_values(by = 'review_count', ascending = False)

thai = restaurants[restaurants['categories'].str.contains('Thai',case=False,na=False)]
thai = thai.sort_values(by = 'review_count', ascending = False)

vietnamese = restaurants[restaurants['categories'].str.contains('Vietnamese',case=False,na=False)]
vietnamese = vietnamese.sort_values(by = 'review_count', ascending = False)

halal = restaurants[restaurants['categories'].str.contains('Halal',case=False,na=False)]
halal = halal.sort_values(by = 'review_count', ascending = False)

mexican = restaurants[restaurants['categories'].str.contains('Mexican|Tacos|Tex-Mex|Latin American',case=False,na=False)]
mexican = mexican.sort_values(by = 'review_count', ascending = False)
mexican = mexican[~mexican.categories.str.contains("Fast Food") ]


print("Please select which food genre you'd like to see: ")
name = input("Asian\nAmerican\nItalian\nBars\nFast Food\nDiners\nDessert\nSandwiches\nCoffee\nJapanese\nKorean\nIndian\nChinese\nMediterranean\nVegetarian\nThai\nVietnamese\nHalal\nMexican\n")

if(name == 'asian' ):
    print(asian)

if(name == 'american' ):
    print(american)

if(name == 'italian' ):
    print('italian')

if(name == 'bars' ):
    print(bars)

if(name == 'fast food' ):
    print(fast_food)

if(name == 'diners' ):
    print(diners)

if(name == 'dessert' ):
    print(dessert)

if(name == 'sandwiches' ):
    print(sandwiches)

if(name == 'coffee' ):
    print(coffee)

if(name == 'japanese' ):
    print(japanese)

if(name == 'korean' ):
    print(korean)

if(name == 'indian' ):
    print(indian)

if(name == 'chinese' ):
    print(chinese)

if(name == 'Mediterranean' ):
    print(mediterranean)

if(name == 'vegetarian' ):
    print(vegetarian)

if(name == 'thai' ):
    print(thai)

if(name == 'vietnamese' ):
    print(vietnamese)

if(name == 'halal' ):
    print(halal)

if(name == 'mexican' ):
    print(mexican)