Learn how to perform regression analysis using Python and how to interpret the results.
- [Instructor] We're going to build on…what we learned in the last video.…Now with Python, we've gone ahead…and we've opened up the application,…and we've set up our notebook by bringing in our packages.…This time there are a few of them.…Go ahead and execute this code by running the cell.…If you recall, we'll select that cell…and then shift + enter.…This has brought our packages into the platform…and has set us up to begin our work with the analysis here.…Now let's connect to our data source.…In this case, we'll be connecting to our CSV file.…
Again, we've already written that line in,…and we're just going to go ahead and run it…with a shift and a return.…Let's see a quick snapshot of our data,…just to insure we have access to…what we thought we should have access to.…I'm going to type in this variable…that we assigned to our data frame here.…I'm going to run the command head(),…and I'm just going to input three here as a configuration.…That'll just give us the first three rows of our data.…You can see we got something very similar to what we saw…
In this course, discover how to gain valuable insights from large data sets using specific languages and tools. Follow Chris DallaVilla as he walks through how to use R, Python, and Tableau to perform data modeling and assess performance. As Chris dives into these concepts, he shares specific case studies that come directly from his own work with clients. Plus, he shares three essential—and practical—best practices for data-driven marketing that you can use to bolster your organization's marketing performance.
- Installing R, Python, and Tableau
- Navigating the UI for R, Python, and Tableau
- Using R, Python, and Tableau
- Exploratory analysis
- Performing regression analysis
- Performing a cluster analysis
- Performing a conjoint assessment
- Stakeholder alignment
Skill Level Intermediate
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1. Software Installation
2. Data, Exploratory Analysis, and Performance Analysis
3. Inference and Regression Analysis
5. Cluster Analysis
6. Conjoint Analysis
7. Best Practices
Next steps1m 8s
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