P2-Prediction of Google App's Ratings

In this project, I have done the data analysis of Google App's rating.

The data is taken from the kaggle.

Following Modules are used in the project: Pandas, Numpy, Seaborn, and Matplotlib

The following are the steps performed to get the desired result.

1. Read Data
2. Inspecting the data
3. checking the shape, describe
4. making boxplot and checking the outliers
5. making the histogram
6. using the info() function to check the null values

Data Cleaning

• count the missing values in the dataframe
• count the number of missing values in each column
• check how many ratings are having more than 5 outliers
• removing the outliers
• again making boxplot and histogram
• removes columns that are 90% empty

Data Imputation and Manipulation

• fill the null values with appropriate values using the aggregate functions as mean, median and mode
• count the number of null values in each column and removing it
• check and correct the format of price, reviews and ratings

Data Visualization