Missing-Value-Treatment

Prevention and handling of missing data

Missing Value Treatment

Missing values in data is a common phenomenon in real world problems. Knowing how to handle missing values effectively is a required step to reduce bias and to produce powerful models. In this model pandas.DataFrame.fillna() method is used to handle the missing values.

To study more about pandas.DataFrame.fillna() refer link -To run this code you may need Jupyter Notebook

Jupyter Notebook Installation

• Jupyter Notebook is availabe online or can be downloaded using link
• Jupyter notebook can also be installed using Anaconda where all the packages are pre-installed. Anaconda download link.