Data Science with Python! Joining Tables Without a Common Column

Tutorial on how to join two tables (or data sets) without a common column. Given two different data sets on power outages and power stations locations in Pennsylvania we will combine the data sets by computing the euclidean distance between the location of the power stations and the area where the power outages occurred. We will also use the Meteostat API to pull in weather data which we will append to our pandas DataFrame.

The notebook can be found in the "Data Science with Python" folder within the below repo. GitHub Repo - https://github.com/ad17171717/YouTube-Tutorials

CONNECT: LinkedIn: https://www.linkedin.com/in/adrian-dolinay-frm-96a289106/ GitHub: https://github.com/ad17171717 Twitter: https://twitter.com/DolinayG

------Video Chapters------ 0:00 - Intro 0:56 - Loading in the data and checking for missing values 6:06 - Comparing the time frame of the data sets 7:15 - Filtering down to distinct power station values 8:22 - Creating a new column for Latitude & Longitude 9:48 - Euclidean distance example 11:23 - Computing the distance between data sets & joining the data 14:34 - Checking our calculation on a small sample of the data 16:06 - Checking our calculation against Google Maps 17:07 - Utilizing Meteostat's API to pull down weather data 22:05 - Saving the weather data into a pandas DataFrame 23:01 - Joining the power outage data and weather data 25:01 - References and additional learning ... https://www.youtube.com/watch?v=36wQC65wdAg