Summary

In this chapter, you have learned how to structure datasets by arranging them in a tabular format. Then, you learned how to combine data from multiple sources. You also learned how to get rid of duplicates and needless columns. Along with that, you discovered how to effectively address missing values in your data. By learning how to perform these steps, you now have the skills to make your data ready for further analysis.

Data processing and wrangling are the most important steps in marketing analytics. Around 60% of the efforts in any project are spent on data processing and exploration. Data processing when done right can unravel a lot of value and insights. As a marketing analyst, you will be working with a wide variety of data sources, and so the skills you have acquired in this chapter will help you to perform common data cleaning and wrangling tasks on data obtained in a variety of formats.

In the next chapter, you will enhance your understanding of pandas and...