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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

Test and visualize conversion function

You've done the hard work of building your conversion rate function—now it's time to test it out! Automating your analyses can be time-consuming up front, but this is where it all pays off.

In this exercise, you'll see how quickly you can calculate the conversion rate. A task that in previous lessons took multiple steps. By automating the repetitive parts of your work, you'll be able to spend more time doing complex analyses.

Instructions

100 XP
  • Use your conversion_rate() function to calculate the conversion rate in marketing by date_served and age_group and store your results in age_group_conv.
  • Unstack age_group_conv at level equal to 1 and wrap that in a call to pd.DataFrame() to create age_group_df.
  • Create a line chart to display your results from age_group_df.