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1
Intro
2
Existing Kaggle Datasets
3
Finding Public Flight Data
4
Checking the CSV in IPython
5
Creating a Kaggle Dataset
6
Dalle2 Dataset Image
7
Data Exploration
8
Understanding Features
9
More Data Cleaning
10
Plotly Express Plot
11
Plotting Cancellation Rates
12
Realizing it's Partial Data
13
Downloading More Data
14
Data Filtering
15
Final Plot Works
16
Bye Bye
Description:
Embark on a comprehensive live coding session that guides you through the process of creating a flight delay dataset using Python and Pandas on Kaggle. Learn how to pull airline flight data, explore existing datasets, and navigate public flight information sources. Gain hands-on experience in data cleaning, feature understanding, and visualization techniques using Plotly Express. Follow along as the instructor encounters and resolves real-time challenges, including dealing with partial data and downloading additional information. By the end of this tutorial, you'll have created a Kaggle dataset, generated visualizations, and gained valuable insights into the intricacies of working with flight delay data.

Flight Delay Dataset Creation

Rob Mulla
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