This repository focuses on using simple lines of code with several Python packages(pandas-profiling, sweetviz, dtales) that does the extensive detailed Exploratory Data Analysis by producing several uni-variate statistics
Exploratory Data Analysis is an important step in the world of Machine Learning. Using the below packages will enable us to explore and analyze the data quicker with simple lines of code
Step 1: The dataset used for this analysis is stored in the repository with name "German_Credit.csv". To understand the definition of the fields, you can refer to the Excel file "Original file with data dictionary".
Step 2: Notebook "Simple_EDA_Packages.ipynb" contains the original code, comments and screenshots of the output. I have converted the Notebook code into PDF and placed in the same directory
Step 3: Images used in Notebook were included in the "Images" directory with in this repository
Step 4: Upon executing the lines of code for each package, you can see the report generated by the browser where you can toggle, hover the statistics and variables. All the EDA packages are interactive
