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https://github.com/manisharora96/indian-cuisine-analysis

This Project comprises of some interesting facts and observations that people might not know about Indian cuisine.
https://github.com/manisharora96/indian-cuisine-analysis

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This Project comprises of some interesting facts and observations that people might not know about Indian cuisine.

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# Indian-Cuisine-Analysis

This Project comprises of some interesting facts and observations that people might not know about Indian cuisine.



Indian Cuisine Analysis

indianfood.jpg



Indian Cuisine consists of a variety of regional and traditional cuisines native to the Indian Subcontinent. Given the diversity in soil, climate, culture, ethnic groups, and occupations, these cuisines vary substantially and use locally available spices, herbs, vegetables, and fruits. Indian food is also heavily influenced by religion, cultural choices and traditions. Historical events such as invasions, trade relations, and colonialism have played a role in introducing certain foods to this country.



The cuisine of India is one of the world's most diverse cuisines, characterized by its sophisticated and subtle use of the many spices, vegetables, grains and fruits grown across India. The cuisine of each geographical region includes a wide assortment of dishes and cooking techniques reflecting the varied demographics of the ethnically diverse Indian subcontinent.



This notebook comprises of some interesting facts and observations that people might not know about Indian cuisine.



Table of Contents

Proportion of Vegetarian and Non-Vegetarian dishes

Number of dishes based on regions

State-wise Distribution of Indian Sweets

Number of dishes based on courses of meal

Proportion of Flavor Profiles

Ingredients used in Indian desserts

Ingredients used in South-Indian cuisine

List of Indian dishes that are sweet in flavor but not desserts

Ingredients used in North-Indian cuisine

Overall Ingredients used in Indian cuisine

Comparing preparation time and cooking time for Veg and Non Veg dishes

Maharashtra Food - Mini Infograph

Punjab Food - Mini Infograph

South Indian Cuisine Food-Mini Infograph

Ingredients used in Vegetarian food

Ingredients used in Non Vegetarian food

Top 10 snacks with shortest cooking time

Top 10 snacks with longest cooking time

Top 10 main courses with shortest cooking time

Top 10 main courses with longest cooking time

import numpy as np

import pandas as pd

import geopandas as gpd

import matplotlib.pyplot as plt

%matplotlib inline

import random

from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot

import plotly.express as px

import plotly.graph_objects as go

import plotly.figure_factory as ff

from plotly.colors import n_colors

from plotly.subplots import make_subplots

init_notebook_mode(connected=True)

import cufflinks as cf

cf.go_offline()

from wordcloud import WordCloud , ImageColorGenerator

from PIL import Image

!python3.7 -m pip install --upgrade pip

!pip install pywaffle

from pywaffle import Waffle 

Requirement already satisfied: pip in /opt/conda/lib/python3.7/site-packages (20.3.3)

Requirement already satisfied: pywaffle in /opt/conda/lib/python3.7/site-packages (0.6.1)

Requirement already satisfied: matplotlib in /opt/conda/lib/python3.7/site-packages (from pywaffle) (3.2.1)

Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.7/site-packages (from matplotlib->pywaffle) (0.10.0)

Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib->pywaffle) (2.4.7)

Requirement already satisfied: numpy>=1.11 in /opt/conda/lib/python3.7/site-packages (from matplotlib->pywaffle) (1.18.5)

Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib->pywaffle) (1.2.0)

Requirement already satisfied: python-dateutil>=2.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib->pywaffle) (2.8.1)

Requirement already satisfied: six in /opt/conda/lib/python3.7/site-packages (from cycler>=0.10->matplotlib->pywaffle) (1.14.0)

df = pd.read_csv('../input/indian-food-101/indian_food.csv')

df=df.replace(-1,np.nan)

df=df.replace('-1',np.nan)

df.head()

name	ingredients	diet	prep_time	cook_time	flavor_profile	course	state	region

0	Balu shahi	Maida flour, yogurt, oil, sugar	vegetarian	45.0	25.0	sweet	dessert	West Bengal	East

1	Boondi	Gram flour, ghee, sugar	vegetarian	80.0	30.0	sweet	dessert	Rajasthan	West

2	Gajar ka halwa	Carrots, milk, sugar, ghee, cashews, raisins	vegetarian	15.0	60.0	sweet	dessert	Punjab	North

3	Ghevar	Flour, ghee, kewra, milk, clarified butter, su...	vegetarian	15.0	30.0	sweet	dessert	Rajasthan	West

4	Gulab jamun	Milk powder, plain flour, baking powder, ghee,...	vegetarian	15.0	40.0	sweet	dessert	West Bengal	East

df.shape

(255, 9)

The dataset consists of about 255 Indian dishes and 9 columns associated with each of them.



The 9 columns are as follows:-



name : name of the dish



ingredients : main ingredients used



diet : type of diet - either vegetarian or non vegetarian



prep_time : preparation time



cook_time : cooking time



flavor_profile : flavor profile includes whether the dish is spicy, sweet, bitter, etc



course : course of meal - starter, main course, dessert, etc



state : state where the dish is famous or is originated



region : region where the state belongs



All the observations in this notebook are based on these 255 dishes. There are many more dishes in Indian Cuisine!