The main objective of this article is to cover the steps involved in Data pre-processing, Feature Engineering, and different stages of Exploratory Data Analysis, which is an essential step in any research analysis.
Data pre-processing, Feature Engineering, and EDA are fundamental early steps after data collection. Still, they are not limited to where the data is simply visualized, plotted, and manipulated, without any assumptions, to assess the quality of the data and building models.
importing libraries
which are required for this project.
Reading Dataset
- import data frame
- checking the first 5 rows
- exploring the info for the d-type of each column in the data frame
- finding duplicates & null values
Data Wrangling(cleaning)
- removing the unnecessary columns and converting the d-type.
By using the ".describe()" method we can get basic stats values of our data set.
Doing Exploratory Analysis
- Univariate
- Bi-variate
- multivariate
Timeline analysis
Conclusion.