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analysis-of-food-items-from-mc-donald-

McDonald's is the world's largest restaurant chain by revenue,serving over 69 million customers daily in over 100 countries across 37,855 outlets as of 2018. Although McDonald's is best known for its hamburgers, cheeseburgers and french fries, they feature chicken products, breakfast items, soft drinks, milkshakes, wraps, and desserts. The McDonald's Corporation revenues come from the rent, royalties, and fees paid by the franchisees, as well as sales in company-operated restaurants. According to two reports published in 2018, McDonald's is the world's second-largest private employer with 1.7 million employees (behind Walmart with 2.3 million employees). As of 2020, McDonald's has the ninth-highest global brand valuation. This report will show all the Nutrition value of the food items , this will also show the different food items and their categories.

case-study-on-anova-using-salarydataset-and-eda-and-pca-using-educaton-12th-std

Salary is hypothesized to depend on educational qualification and occupation. To understand the dependency, the salaries of 40 individuals are collected and each person’s educational qualification and occupation are noted. Educational qualification is at three levels, High school graduate, Bachelor, and Doctorate. Occupation is at four levels, Administrative and clerical, Sales, Professional or specialty, and Executive or managerial. A different number of observations are in each level of education – occupation combination. Conduct hypothesis test to get the inferences.

clustering-case-study-on-bank-marketing-cart-rf-ann-case-study-to-provide-recommendations-to-manage

linear-regression-case-study-on-gem-stones-co-ltd.--logistic-regression-and-lda-case-study-on-holi

A company Gem Stones co ltd, which is a cubic zirconia manufacturer. We are provided with the dataset containing the prices and other attributes of almost 27,000 cubic zirconia (which is an inexpensive diamond alternative with many of the same qualities as a diamond). The company is earning different profits on different prize slots. We have to help the company in predicting the price for the stone on the bases of the details given in the dataset so it can distinguish between higher profitable stones and lower profitable stones so as to have better profit share. Also, provide with the best 5 attributes that are most important.

pandas-profiling-eda

uber-drive

The project is based on the trips made by Uber drivers. Here, we are analyzing different aspects of the trips by doing Exploratory Data Analysis

wholesale-customer-survey-a-b-shingles

Statistical methods for decision making