Learn how to perform a basic exploratory analysis in Python.
- [Instructor] In the last video,…we created a heat map with R.…Let's do something similar with Python.…I have my Jupyter environment open and ready to go.…If you need help on how to open up the application,…please refer to the video from earlier on in this course.…Now, keep in mind that these hashtags denote…a comment, so what we have here in our exercise file…are cells with comments that speak to…exactly what we're going to be creating…and what we're going to be doing in this overall process.…The process of bringing in additional packages…is something to mention, too.…
With both R and Python, there are times where…you'll need additional functionality…in addition to what's already out of the box.…And a lot of times what you'll do is use packages.…So we're going to go ahead and bring the Pandas package,…which is a popular package for Python,…in by typing out import pandas as pd.…And I'm going to go ahead and click Shift and Return.…Now, let me point that out.…Shift and Return.…
If I just selected Return,…that would open up the ability to create more code.…
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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