Apply the foundational skills in Introduction to Python and Intermediate Python courses to manipulate and visualize movie and TV data.
In these projects, I’ll apply the skills I learned in Introduction to Python and Intermediate Python to solve a real-world data science problem. I’ll press “watch next episode” to discover if Netflix’s movies are getting shorter over time and which guest stars appear in the most popular episode of "The Office", using everything from lists and loops to pandas and matplotlib.
This project helps me gain experience in an essential data science skill — exploratory data analysis, which allows me to perform critical tasks such as manipulating raw data and drawing conclusions from plots I create of the data.
Dig into a real-world Netflix movie dataset using everything from lists and loops to pandas and matplotlib.
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Loading a friend's data into a dictionary
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Creating a DataFrame from a dictionary
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A visual inspection of our data
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Loading the rest of the data from a CSV
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Filtering for movies!
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Creating a scatter plot
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Digging deeper
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Marking non-feature films
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Plotting with color!
10.What next?
In this project, we'll work with a dataset of used cars from eBay Kleinanzeigen, a classifieds section of the German eBay website.
The dataset was originally scraped and uploaded to Kaggle. We've made a few modifications from the original dataset that was uploaded to Kaggle:
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Introduction
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Cleaning Column Names
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Initial Exploration and Cleaning
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Exploring the Odometer and Price Columns
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Exploring the date columns
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Dealing with Incorrect Registration Year Data
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Exploring Price by Band
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Storing Aggregate Data in a DataFrame
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Next Steps