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  3. Analyzing Marketing Campaigns with pandas
  • 1

    Pandas

    Free

    In this chapter, you will review pandas basics including importing datasets, exploratory analysis, and basic plotting.

  • 2

    Exploratory Analysis & Summary Statistics

    In this chapter, you will learn about common marketing metrics and how to calculate them using pandas. You will also visualize your results and practice user segmentation.

  • 3

    Conversion Attribution

    In this chapter, you will build functions to automate common marketing analysis and determine why certain marketing channels saw lower than usual conversion rates during late January.

  • 4

    Personalization A/B Test

    In this chapter, you will analyze an A/B test and learn about the importance of segmentation when interpreting the results of a test.

Initializing

Exercise

Building a conversion function

You've been doing a lot of repetitive calculations. Anytime you notice repetition in your work, consider automation. The more of the low-variance work you can automate, the more time you will have to explore new and interesting data science topics at work. This will both impress your marketing stakeholders and be more fun!

Since you know the format of the marketing DataFrame will remain the same over time, you can build a function to enable you to calculate conversion rate across any sub-segment you want on the fly.

In this exercise, you will build a function that takes a DataFrame and list of column names and outputs the conversion rate across the column(s).

Instructions

100 XP
  • Isolate rows in the user inputted dataframe where users were converted, then group by the list of user inputted column_names and count the number of unique converted users.
  • Group the user inputted dataframe by the list of user inputted column_names and calculate the total number of users.
  • Fill any missing values in conversion_rate with 0.