Context

Veganism is one emergent topic which many people are not aware of. So, by having a big dataset of these news, it can be developed something in order to rise awareness of this topic

Acknowledgements

These news come from: Plant Based News: https://plantbasednews.org/ VegNews: https://vegnews.com/ Vegconomist: https://vegconomist.com/

BackgroundVegetarians have been shown to have better metabolic profiles than non-vegetarians, and vegetarianism has potential beneficial effects on cardiovascular disease. However, there is a lack of studies on vegetarians that examine both metabolic profiles and lifestyle habits, such as physical activity, smoking habits, and dietary patterns, which are equally important in the context of cardiovascular disease. We explored whether a vegetarian diet is associated with both metabolic traits and lifestyle habits by assessing cardiovascular health (CVH) metrics.MethodsThis was a cross-sectional study conducted in a Taiwanese population. Data collected between 2000 and 2016 were extracted from the MJ Health database. Participants aged 40 years and older without cardiovascular disease were included. CVH metrics included smoking habits, blood pressure, total cholesterol, serum glucose, body mass index, physical activity, and healthy diet score. Vegetarian participants were full-time vegetarians who did not consume meat or fish. All the data were assessed from self-report questionnaires, physical examinations, and blood analyses following standard protocol. Multiple logistic regression analysis was used to evaluate the association between vegetarianism and CVH metrics.ResultsOf 46,287 eligible participants, 1,896 (4.1%) were vegetarian. Overall, vegetarians had better CVH metrics (OR = 2.09, 95% CI = 1.84–2.37) but lower healthy diet scores (OR = 0.41, 95% CI = 0.33–0.51) after adjustment. No difference in physical activity (OR = 0.86, 95% CI = 0.73–1.02) was identified between vegetarians and non-vegetarians. Additionally, vegetarians had higher whole grain intake (OR = 2.76, 95% CI = 2.28–3.35) and lower sugar-sweetened beverage consumption (OR = 1.36, 95% CI = 1.18–1.58).ConclusionsOur results suggested that vegetarians had better overall ideal CVH metrics but lower ideal healthy diet scores than non-vegetarians, which was likely due to the lack of fish consumption in this population group. When assessing CVH metrics and healthy diet scores for vegetarians, metrics and scores chosen should be suitable for use with vegetarian populations.

The basic idea of analyzing the Zomato dataset is to get a fair idea about the factors affecting the establishment of different types of restaurant at different places in Bengaluru, aggregate rating of each restaurant, Bengaluru being one such city has more than 12,000 restaurants with restaurants serving dishes from all over the world. With each day new restaurants opening the industry has’nt been saturated yet and the demand is increasing day by day. Inspite of increasing demand it however has become difficult for new restaurants to compete with established restaurants. Most of them serving the same food. Bengaluru being an IT capital of India. Most of the people here are dependent mainly on the restaurant food as they don’t have time to cook for themselves. With such an overwhelming demand of restaurants it has therefore become important to study the demography of a location. What kind of a food is more popular in a locality. Do the entire locality loves vegetarian food. If yes then is that locality populated by a particular sect of people for eg. Jain, Marwaris, Gujaratis who are mostly vegetarian. These kind of analysis can be done using the data, by studying the factors such as • Location of the restaurant • Approx Price of food • Theme based restaurant or not • Which locality of that city serves that cuisines with maximum number of restaurants • The needs of people who are striving to get the best cuisine of the neighborhood • Is a particular neighborhood famous for its own kind of food.

“Just so that you have a good meal the next time you step out”

The data is accurate to that available on the zomato website until 15 March 2019. The data was scraped from Zomato in two phase. After going through the structure of the website I found that for each neighborhood there are 6-7 category of restaurants viz. Buffet, Cafes, Delivery, Desserts, Dine-out, Drinks & nightlife, Pubs and bars.

Phase I,

In Phase I of extraction only the URL, name and address of the restaurant were extracted which were visible on the front page. The URl's for each of the restaurants on the zomato were recorded in the csv file so that later the data can be extracted individually for each restaurant. This made the extraction process easier and reduced the extra load on my machine. The data for each neighborhood and each category can be found here

Phase II,

In Phase II the recorded data for each restaurant and each category was read and data for each restaurant was scraped individually. 15 variables were scraped in this phase. For each of the neighborhood and for each category their onlineorder, booktable, rate, votes, phone, location, resttype, dishliked, cuisines, approxcost(for two people), reviewslist, menu_item was extracted. See section 5 for more details about the variables.

Acknowledgements The data scraped was entirely for educational purposes only. Note that I don’t claim any copyright for the data. All copyrights for the data is owned by Zomato Media Pvt. Ltd..

Inspiration I was always astonished by how each of the restaurants are able to keep up the pace inspite of that cutting edge competition. And what factors should be kept in mind if someone wants to open new restaurant. Does the demography of an area matters? Does location of a particular type of restaurant also depends on the people living in that area? Does the theme of the restaurant matters? Is a food chain category restaurant likely to have more customers than its counter part? Are any neighborhood similar ? If two neighborhood are similar does that mean these are related or particular group of people live in the neighborhood or these are the places to it? What kind of a food is more popular in a locality. Do the entire locality loves vegetarian food. If yes then is that locality populated by a particular sect of people for eg. Jain, Marwaris, Gujaratis who are mostly vegetarian. There are infacts dozens of question in my mind. lets try to find out the answer with this dataset.

For detailed discussion of the business problem, please visit this link

Please visit this link to find codebook cum documentation for the data

GITHUB LINk : https://github.com/mohitbhadauria02/Zomato-Dataset-using-Exploratory-Data-Analysis.git

1. Introduction The purpose of this project was to analyze consumer preferences for restaurant attributes to identify the most desirable configurations for restaurants. This analysis focused on four key attributes of restaurant experiences: 1. Cuisine: Asian, American, Italian, Mexican 2. Dietary Considerations: No Dietary Restrictions, Vegan-Vegetarian, Keto, Pescatarian 3. Ambiance: Family Friendly, Fine Dining, Live Entertainment, Bar/Tavern 4. Menu Type: À la carte, Pre-set, Buffet, Seasonal Understanding consumer preferences for these attributes is essential for restaurant owners and marketers to tailor their offerings to meet customer demand effectively. (Kotler & Keller, 2016) The survey sought to uncover which combinations of these attributes would resonate most with the target audience and to identify statistically significant patterns in preferences.

2. Survey Design and Data Collection 2.1 Goal of the Survey The goal of the survey was to identify the most preferred restaurant configuration among respondents by: • Determining which specific attributes (e.g., cuisine type, ambiance) were most popular. • Understanding the intensity of preferences for different options within each attribute. • Using statistical methods to evaluate whether the observed differences in preferences were meaningful and significant. This information would help restaurant businesses make informed decisions about menu design, ambiance choices, and dietary offerings.

2.2 Survey Structure The survey contained a key question: "What would be the ideal type of restaurant you would like to have? (Please select one option for each attribute):" • Cuisine: Asian, American, Italian, Mexican • Dietary Considerations: No Dietary Restrictions, Vegan-Vegetarian, Keto, Pescatarian • Ambiance: Family Friendly, Fine Dining, Live Entertainment, Bar/Tavern • Menu Type: À la carte, Pre-set, Buffet, Seasonal Participants were asked to select one option from each attribute category, resulting in four responses per participant.

2.3 Survey Methodology The survey used a Ranked Choice and MaxDiff Scaling hybrid approach: 1. Ranked Choice: Participants ranked their preferred options within each attribute. This method allowed for a straightforward analysis of the most and least popular options for each attribute. Why Ranked Choice? (Tideman & Richardson, 1976) o It is simple for respondents to understand and complete. o It provides clear insights into preference hierarchies for each category. 2. MaxDiff Scaling (Best-Worst Scaling): Implicitly embedded in the design, MaxDiff allowed us to calculate scores by comparing the most and least preferred options, effectively capturing the intensity of preferences. Why MaxDiff? (Louviere, Hensher, & Swait, 2000) o It helps identify which options are strongly favored or disfavored. o It avoids the bias of traditional rating scales (e.g., everyone ranking everything as "highly preferred").

2.4 Data Collection The survey data was collected from respondents using an online platform. Each respondent’s answers for the four attributes were recorded in a structured format. The data included 285 valid responses, with the following key attributes: • Q10_1: Cuisine (Asian, American, Italian, Mexican) • Q10_2: Dietary Considerations (No Dietary Restrictions, Vegan-Vegetarian, Keto, Pescatarian) • Q10_3: Ambiance (Family Friendly, Fine Dining, Live Entertainment, Bar/Tavern) • Q10_4: Menu Type (À la carte, Pre-set, Buffet, Seasonal)

3. Methodology for Analysis 3.1 Descriptive Analysis The raw counts for each option in Q10_1 to Q10_4 were calculated to determine the most frequently selected preferences within each attribute.

3.2 Statistical Testing To evaluate whether the observed differences in preferences were statistically significant, Chi-Square tests of independence were conducted for each attribute. The null hypothesis for each test stated that the proportions of preferences were evenly distributed across all categories.

Zomato Bangalore Restaurants

About this Dataset

Zomato is one of the most-used apps to find food and restaurants in and around one locality to order and check reviews. Zomato has not only solved the problem of ordering food sitting at your home but also has provided a single platform to know more details about each restaurant. This tabular dataset consists of all restaurants in Bangalore. Bangalore is one of the metro countries of India and is also one of the favorite spots for foodies with a variety of cuisines and street food available. The city of students, working professionals, and youth filling up every space, Bangalore is the location to be a foodie, and Zomato taking the highest orders in the country also comes from Bangalore. This data has ratings and review details, the cuisines available, the approximate price for two persons, etc.

Dataset collected on 26th March 2022

Other Location Restaurant Database

• Zomato Kolkata Restaurants

Interesting Task Ideas

1. Which restaurant is famous in different localities in Kolkata?
2. Which cuisines are the most famous in different localities?
3. What is the highest rating restaurant for any particular cuisines?
4. What is the best restaurant for each category (Dine-In, Delivery, Takeaway, Vegetarian)

Dataset for other locations coming soon.

Let me know which locations would be great for the dataset.

Check my other datasets

A substantial body of evidence points to the heritability of dietary preferences. While vegetarianism has been practiced for millennia in various societies, its practitioners remain a small minority of people worldwide, and the role of genetics in choosing a vegetarian diet is not well understood. Dietary choices involve an interplay between the physiologic effects of dietary items, their metabolism, and taste perception, all of which are strongly influenced by genetics. In this study, we used a genome-wide association study (GWAS) to identify loci associated with strict vegetarianism in UK Biobank participants. Comparing 5,324 strict vegetarians to 329,455 controls, we identified one SNP on chromosome 18 that is associated with vegetarianism at the genome-wide significant level (rs72884519, β = -0.11, P = 4.997 x 10−8), and an additional 201 suggestively significant variants. Four genes are associated with rs72884519: TMEM241, RIOK3, NPC1, and RMC1. Using the Functional Mapping and Annotation (FUMA) platform and the Multi-marker Analysis of GenoMic Annotation (MAGMA) tool, we identified 34 genes with a possible role in vegetarianism, 3 of which are GWAS-significant based on gene-level analysis: RIOK3, RMC1, and NPC1. Several of the genes associated with vegetarianism, including TMEM241, NPC1, and RMC1, have important functions in lipid metabolism and brain function, raising the possibility that differences in lipid metabolism and their effects on the brain may underlie the ability to subsist on a vegetarian diet. These results support a role for genetics in choosing a vegetarian diet and open the door to future studies aimed at further elucidating the physiologic pathways involved in vegetarianism.

Context

I was always fascinated by the food culture of Bengaluru. Restaurants from all over the world can be found here in Bengaluru. From United States to Japan, Russia to Antarctica, you get all type of cuisines here. Delivery, Dine-out, Pubs, Bars, Drinks,Buffet, Desserts you name it and Bengaluru has it. Bengaluru is best place for foodies. The number of restaurant are increasing day by day. Currently which stands at approximately 12,000 restaurants. With such an high number of restaurants. This industry hasn't been saturated yet. And new restaurants are opening every day. However it has become difficult for them to compete with already established restaurants. The key issues that continue to pose a challenge to them include high real estate costs, rising food costs, shortage of quality manpower, fragmented supply chain and over-licensing. This Zomato data aims at analysing demography of the location. Most importantly it will help new restaurants in deciding their theme, menus, cuisine, cost etc for a particular location. It also aims at finding similarity between neighborhoods of Bengaluru on the basis of food. The dataset also contains reviews for each of the restaurant which will help in finding overall rating for the place.

Content

The basic idea of analyzing the Zomato dataset is to get a fair idea about the factors affecting the establishment of different types of restaurant at different places in Bengaluru, aggregate rating of each restaurant, Bengaluru being one such city has more than 12,000 restaurants with restaurants serving dishes from all over the world. With each day new restaurants opening the industry has’nt been saturated yet and the demand is increasing day by day. Inspite of increasing demand it however has become difficult for new restaurants to compete with established restaurants. Most of them serving the same food. Bengaluru being an IT capital of India. Most of the people here are dependent mainly on the restaurant food as they don’t have time to cook for themselves. With such an overwhelming demand of restaurants it has therefore become important to study the demography of a location. What kind of a food is more popular in a locality. Do the entire locality loves vegetarian food. If yes then is that locality populated by a particular sect of people for eg. Jain, Marwaris, Gujaratis who are mostly vegetarian. These kind of analysis can be done using the data, by studying the factors such as • Location of the restaurant • Approx Price of food • Theme based restaurant or not • Which locality of that city serves that cuisines with maximum number of restaurants • The needs of people who are striving to get the best cuisine of the neighborhood • Is a particular neighborhood famous for its own kind of food.

“Just so that you have a good meal the next time you step out”

The data is accurate to that available on the zomato website until 15 March 2019. The data was scraped from Zomato in two phase. After going through the structure of the website I found that for each neighborhood there are 6-7 category of restaurants viz. Buffet, Cafes, Delivery, Desserts, Dine-out, Drinks & nightlife, Pubs and bars.

Phase I,

In Phase I of extraction only the URL, name and address of the restaurant were extracted which were visible on the front page. The URl's for each of the restaurants on the zomato were recorded in the csv file so that later the data can be extracted individually for each restaurant. This made the extraction process easier and reduced the extra load on my machine. The data for each neighborhood and each category can be found here

Phase II,

In Phase II the recorded data for each restaurant and each category was read and data for each restaurant was scraped individually. 15 variables were scraped in this phase. For each of the neighborhood and for each category their online_order, book_table, rate, votes, phone, location, rest_type, dish_liked, cuisines, approx_cost(for two people), reviews_list, menu_item was extracted. See section 5 for more details about the variables.

Acknowledgements

The data scraped was entirely for educational purposes only. Note that I don’t claim any copyright for the data. All copyrights for the data is owned by Zomato Media Pvt. Ltd..

Inspiration

I was always astonished by how each of the restaurants are able to keep up the pace inspite of that cutting edge competition. And what factors should be kept in mind if someone wants to open new restaurant. Does the demography of an area matters? Does location of a particular type of restaurant also depends on the people living in that area? Does the theme of the restaurant matters? Is a food chain category restaurant likely to have more customers than its counter part? Are any neighborhood similar ? If two neighborhood are similar does that mean these are related or particular group of people live in the neighborhood or these are the places to it? What kind of a food is more popular in a locality. Do the entire locality loves vegetarian food. If yes then is that locality populated by a particular sect of people for eg. Jain, Marwaris, Gujaratis who are mostly vegetarian. There are infacts dozens of question in my mind. lets try to find out the answer with this dataset.

For detailed discussion of the business problem, please visit this link

Please visit this link to find codebook cum documentation for the data

GITHUB LINk : https://github.com/poddarhimanshu/Coursera_Capstone

Characteristics of vegetarian and control populations.

Proportion of the 2020 US human population who could be fed with food energy savings associated with vegan diets.