Throughout this notebook, we will practice computing descriptive statistics to explore and summarize a dataset. Before getting started, watch the associated instructional video and complete the in-video question. All of the code we will be implementing and related instructions are contained in this notebook.
Earlier in the program, you learned about the process of exploratory data analysis, or EDA, from discovering to presenting your data. Whenever a data professional works with a new dataset, the first step is to understand the context of the data during the discovering stage. Often, this involves discussing the data with project stakeholders and reading documentation about the dataset and the data collection process. After that, the data professional moves on to data cleaning and addresses issues like missing data, incorrect values, and irrelevant data. Computing descriptive stats is a common step to take after data cleaning.
In this notebook, we will use descriptive stats to get a basic understanding of the literacy rate data for each district in your education dataset.