- ๐ฏ We will see in this
hands-on training notebook
how to effectively diagnose and treat missing data in Python. - ๐ The majority of data science work often revolves around pre-processing data, and making sure it's ready for analysis. However, we will be covering how transform our raw data into accurate insights. In this notebook, we will see:
- Import data into
pandas
, and use simple functions to diagnose problems in our data. - Visualize missing and out of range data using
missingno
andseaborn
. - Apply a range of data cleaning tasks that will ensure the delivery of accurate insights.
- Make sure we have a clean dataset ready for data analysis.
- Import data into
- ๐ซ Feel free to contact me if anything is wrong or if anything needs to be changed ๐! [email protected]
labrijisaad / exploratory-data-analysis-in-python Goto Github PK
View Code? Open in Web Editor NEWIn this project, we will see in a hands-on training jupyter notebook how to effectively diagnose and deal with missing data in Python.