From the course: Machine Learning and AI Foundations: Recommendations

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Explore our product recommendation data set

Explore our product recommendation data set

From the course: Machine Learning and AI Foundations: Recommendations

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Explore our product recommendation data set

- [Narrator] The user review data for our project is in a file called movie ratings data set.csv. We also have a list of movie titles in movies.csv. Both of these files are simple comma separated data that you can open in any spreadsheet program, like Microsoft Excel. But data sets are usually too large to open directly, so we'll use Python to preview the data. Let's look at view data.py. First, we use pandas read csv command to load the data set into a data table. A data table is similar to a spreadsheet. It has columns and rows just like a spreadsheet, and you can perform many of the same operations on the data as you can with a spreadsheet. Next, we're going to grab the first 100 rows of data, then we'll use pandas to html function to convert that data into a webpage. Pandas provides lots of cool helper functions like this to make it easy to view your data. Next, we'll write out the html data to a file, and then we'll open it in our web browser using Python's built-in web browser…

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