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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

Visualizing daily marketing reach

In the previous exercise, you created a daily_users DataFrame, which contained the number of users who subscribed each day. While this was a great first step, it is challenging to interpret daily trends by looking at a table. To make it easier for you and your business stakeholders to notice subscriber trends, you will visualize your results using a line plot.

Instructions

100 XP
  • Use the .plot() method to visualize the results of date_served.
  • Add the title 'Daily users' and the y-axis label 'Number of users'.
  • Rotate the x-axis labels by 45 degrees.
  • Display the plot.