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Python for Marketing

Video Introducing this tutorial

Accelerate your marketing with Python

1. The Role of Python in Marketing
Why Python is great for marketers
Why Python is valuable for marketers

2. Loading and Exploring Your Data
Introduction to pandas
Installing Jupyter
Importing Google Analytics data
Importing Google Search Console data
Importing Facebook and AdWords data
Accessing the Google Trends API
Visualizing Google data
Plotting Facebook and Google Ads data
Visualizing Google Trends data

3. Cleaning, Wrangling, and Joining Your Data
Introduction to data wrangling
Fixing Google Analytics page data
Preparing data to be grouped
Creating new datasets with Groupby
Rebuilding Google Analytics data
Dropping columns
Replacing missing Facebook Ad data
Merging Google Analytics and Search Console
Saving your data to a CSV

4. Visualizing Marketing Data in Python
Custom visualizations in Python
Import, explore, and plot a basic chart
Creating Matplotlib subplots
Plotting a secondary y-axis
Adding x and y labels to a plot
Rotating xticks labels on plot
Adding a legend to a plot
Adding a title to your plot
Adding annotations to plots
Switching between Matplotlib styles
Using a scatter plot in Seaborn
Customizing a scatter plot in Seaborn
Creating a Facebook Ads heatmap in Seaborn

5. Working with Timeseries
Time series notebook
Fixing missing values
Resampling time series data
Rolling average plots
Plotting weekly PPC and CPC data
Adding dynamic annotations to a plot

6. Calculating, Filtering, and Creating New Metrics
Introduction to calculating and filtering
Calculating metrics
Filtering data

7. Creating Helpful Alerts
Intro to alert calculations
Creating simple alerts
Calculating two date ranges
Creating alerts with actions

Next steps