Merging Multiple DataFrames | Merging More Than Two DataFrames | Conditional Merge | Advance Level

Merging Multiple DataFrames | Merging More Than Two DataFrames | Conditional Merge | Merge with Where Condition | Sub Query
This video is an advance level video about merging the dataframes, which doesn't just tells you how to merge multiple tables but also explains how you can do the conditional Merge useing .Query function just like we do sub queries in SQL.
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Tags -
Join,
Merge,
Merge on Multiple Columns,
Merge on columns which are not named same
You can download the script used in this video using -
File Name - merging_multiple_dataframes.py
URL - github.com/LEARNEREA/Python/t...
You can download the files used in the video using -
File Name - org_details.xlsx
URL - github.com/LEARNEREA/Python/t...
Hash Tags -
#Python #Pandas #Merging #Joins #Learnerea #DataScience

[@user-nf7ww2et4m]

Thank you for the great explanation,
How would you implement a join condition different than equal, like for example ">=" or usign case in the join condition like we do in sql?
Thanks

[@alndr4u]

Thank you sir 🙏🏻

[@learnerea]

All the best

[@1979ligesh]

Thanks

[@learnerea]

Thank you very much, keep watching

[@alphanelmas1662]

What if we have couple of more dataframes that needs to be merge. Using .merge() every time would be tedious. Isn't there any other way to solve that issue

[@learnerea]

you can try these -
Concatenation: If you have data frames with the same columns but different rows, you can use the pd.concat() function to concatenate them vertically. This function concatenates data frames along a particular axis and can be used to combine multiple data frames into a single data frame.
Joining: If you have data frames with different columns but the same index or column names, you can use the df.join() function to join them horizontally. This function merges data frames based on their index or column names and can be used to combine data frames that share common keys.
Appending: If you have data frames with the same columns and want to add more rows, you can use the df.append() function to append new rows to an existing data frame. This function appends rows to the end of the data frame and can be used to combine data frames that have the same structure.
Merge with loop: If you have a list of data frames that you want to merge, you can use a loop to iterate through the list and merge each data frame with the previous one. This can be a more efficient way to merge multiple data frames than using .merge() every time.

[@alphanelmas1662]

Thanks for the reply :)

[@Kngdmio]

@@learnerea I never thought of merging with a loop - that’s way better than .merge() forever

[@vishvadeepmohanpandey129]

Can You make another video on Query Part which you have inserted

[@learnerea]

would you mind mentioning the timeframe where you see me inserting the queries..