In this project, I analysed the dataset of Human Resource of a company with offices in two different countries and in five cities. The analysis is based on the details such as Age, Gender, Avg salary of each department, Location,commute distance of the employees etc. After the analysis, I got the answers to the questionlike- Average salary according of each gender, location and departments, number of employees in each department and in each city and country.Min and max salary of each department. Avg salary of each department and also cleaned the data a bit and updated few columns.Also analysed the commute distance and age of employees and came to a conclusion.
In this project, I analysed the dataset of a startup foodchain who wants to start their foodchain in India. With the help of the dataset, I got answers to the types of foods recipes available in India based on many conditions as the foodchain focuses on healthy food and for every people irrespective of the health condition they have. The analysis was made on the cook time and prep time taken for cooking each dish, food recipes based on certain health conditions, types of flavours available and so on.
In this project, I cleaned the data of a huge metropolitan city. This is kind a advanced cleaning, which I learnt recently. Bascially, I spilt few columns as they we're combined, later I added new columns and updated them with the spilted one's. Then, I removed duplicate values and null values in the data and performed self join and also changed the datatype of a column. Now the data has cleaned and useful for analysis purpose.