Chapter 5: Data Visualization and Profiling
When you are transforming data, you usually need to explore your data in order to get a good understanding of how you can shape it to get insights from it. You may need to check for missing values, ensure consistency within a column, obtain a count of unique values, plot a histogram, get the top n values, or produce descriptive analytics. Optimus gives us tools to make all this and more happen.
In this chapter, we will deep dive into the profilers and their data types that we saw in Chapter 3, Data Wrangling, and see how we can fully take advantage of this feature to perform operations with specific data to set, drop, or replace values as you require.
Optimus can also give information about the quality of the data and provides the tools to process and transform our data easily.
The topics we will be covering in this chapter are as follows:
- Data quality
- Exploratory data analysis
- Data profiling
- Cache and flushing...
