Appending & Merging Dataframes (concat, merge, join, ...) - Pandas | Python ~ Episode 5

Published: 01 March 2022
on channel: David Weiss

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Hey Coders! As mentioned before, pandas can be thought of as SQL on steroids for python. One of the hallmarks of SQL is the ability to join two tables together based on a related column. In pandas, you can also do this, but with many more features and functionality. The best way to perform an inner/left/right/outer/cross join is by using the pd.merge method. However, pandas also allows you to combine two dataframes vertically using the concat method. Everyday pandas consists of using one or more of these methods, so be sure to watch the entire video and take time to practice these functions on your own!

Check out the source code on GitHub:
https://github.com/davidtheweiss/pand...

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🧑‍💻 Pandas Documentation: https://pandas.pydata.org/docs/refere...

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🕒 Timestamps
0:00 Intro
1:13 Importing pandas and displaying our data
2:39 Adding new columns to a DataFrame
7:34 Using insert() to place column in specific position
9:50 Adding new rows to a DataFrame
11:16 append() stacks dataframes vertically
14:30 concat() can stack vertically or horizontally
17:50 merge() is used to perform a SQL join
27:00 join() joins on dataframe index
30:35 tl;dr
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