Data cleaning

Data cleaning is an important step in the process of data wrangling. A good amount of time is spent on identifying the right data source and cleaning the data. Pandas provides a lot of functionalities for cleaning your data.

The exact activities that are required during this phase are different for each type of dataset. Certain data sources will have data that requires only minimal cleaning and certain other data sources might require a lot of cleaning activities before the dataset can be used in your project. You could also use the output of data exploration activities to understand the level of cleaning activities to be performed on the data.

Data cleansing with Pandas

In order to demonstrate the data cleaning steps, we will use the seat_type table from our database. This table only has minimal data volume, so we will insert some data before we proceed with data cleansing.

The data in seat_type looks like the screenshot here. It has three columns for the...