Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

///Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)

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Data & code used in this Tutorial:
Python Pandas Documentation:

Let me know if you have any questions!

In this video we walk through many of the fundamental concepts to use the Python Pandas Data Science Library. We start off by installing pandas and loading in an example csv. We then look at different ways to read the data. Read a column, rows, specific cell, etc. Also ways to read data based on conditioning. We then move into some more advanced ways to sort & filter data. We look at making conditional changes to our data. We also start doing aggregate stats using the groupby function. We finished the video talking about how you would work with a very large dataset (many gigabytes)

I realized as I upload this video there are some additional things I want to talk about in a later video. The first thing that comes to mind immediately is using the apply() function on a dataframe to alter the data using a custom or lambda function. If you have questions on this or anything else before I get around to making a part 2, feel free to write me a note in the comments.

If you enjoyed this video, be sure to throw it a like and make sure to subscribe to not miss any future videos!

Thanks for watching friends! Happy coding! πŸ™‚

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Link to original source of data from Kaggle:

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Video Outline!
0:00 – Why Pandas?
1:46 – Installing Pandas
2:03 – Getting the data used in this video
3:50 – Loading the data into Pandas (CSVs, Excel, TXTs, etc.)
8:49 – Reading Data (Getting Rows, Columns, Cells, Headers, etc.)
13:10 – Iterate through each Row
14:11 – Getting rows based on a specific condition
15:47 – High Level description of your data (min, max, mean, std dev, etc.)
16:24 – Sorting Values (Alphabetically, Numerically)
18:19 – Making Changes to the DataFrame
18:56 – Adding a column
21:22 – Deleting a column
22:14 – Summing Multiple Columns to Create new Column.
24:14 – Rearranging columns
28:06 – Saving our Data (CSV, Excel, TXT, etc.)
31:47 – Filtering Data (based on multiple conditions)
35:40 – Reset Index
37:41 – Regex Filtering (filter based on textual patterns)
43:08 – Conditional Changes
47:57 – Aggregate Statistics using Groupby (Sum, Mean, Counting)
54:53 – Working with large amounts of data (setting chunksize)

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By |2020-11-08T10:34:01+00:00November 8th, 2020|Python Video Tutorials|26 Comments

26 Comments

  1. Keith Galli November 8, 2020 at 10:34 am - Reply

    Video Outline!
    0:45 – Why Pandas?
    1:46 – Installing Pandas
    2:03 – Getting the data used in this video
    3:50 – Loading the data into Pandas (CSVs, Excel, TXTs, etc.)
    8:49 – Reading Data (Getting Rows, Columns, Cells, Headers, etc.)
    13:10 – Iterate through each Row
    14:11 – Getting rows based on a specific condition
    15:47 – High Level description of your data (min, max, mean, std dev, etc.)
    16:24 – Sorting Values (Alphabetically, Numerically)
    18:19 – Making Changes to the DataFrame
    18:56 – Adding a column
    21:22 – Deleting a column
    22:14 – Summing Multiple Columns to Create new Column.
    24:14 – Rearranging columns
    28:06 – Saving our Data (CSV, Excel, TXT, etc.)
    31:47 – Filtering Data (based on multiple conditions)
    35:40 – Reset Index
    37:41 – Regex Filtering (filter based on textual patterns)
    43:08 – Conditional Changes
    47:57 – Aggregate Statistics using Groupby (Sum, Mean, Counting)
    54:53 – Working with large amounts of data (setting chunksize)

    Thanks for watching friends! πŸ™‚

    Let me know if you have any questions

  2. Elwin Mentaram November 8, 2020 at 10:34 am - Reply

    2 years after this video was posted, I'm here watching and learning Tons of stuff. Thanks man!!!!

  3. Mohamed Selim November 8, 2020 at 10:34 am - Reply

    For those have issues reading excel file :

    In cmd window :
    pip install openpyxl
    pip install xldr

    df_xlsx=pd.read_excel('pokemon_data.xlsx' , engine="openpyxl")

  4. Brikena Liko November 8, 2020 at 10:34 am - Reply

    Amazing!

  5. Gordon Yeong November 8, 2020 at 10:34 am - Reply

    good stuff πŸ™‚
    i hate SMS-es too lol lol

  6. Don Geo November 8, 2020 at 10:34 am - Reply

    Thank you brother, it really helped. Keep on making.

  7. Aaicha Gho November 8, 2020 at 10:34 am - Reply

    Thanks for the videos. Very much appreciated

  8. Aziz Zafar November 8, 2020 at 10:34 am - Reply

    Thanx for such a great video. helped me a lot

  9. Kejor November 8, 2020 at 10:34 am - Reply

    THIS CHANNEL IS FUCKIN LIT

  10. Ouyang Sicong November 8, 2020 at 10:34 am - Reply

    This is the best tutorial I have found ever, thank you so much for sharing these skills.

  11. ToTo Toys Entertainment November 8, 2020 at 10:34 am - Reply

    i watched more than 10 different videos about pandas, this is the most easy and understandable one. Worth your time!

  12. ruben November 8, 2020 at 10:34 am - Reply

    This video is just glorious

  13. yinstein yyds November 8, 2020 at 10:34 am - Reply

    In 15:26, what if i want to select both 'Grass' and 'Fire', could you show me how can I do that?

  14. Wi Fine November 8, 2020 at 10:34 am - Reply
  15. Wi Fine November 8, 2020 at 10:34 am - Reply
  16. Wi Fine November 8, 2020 at 10:34 am - Reply
  17. Wi Fine November 8, 2020 at 10:34 am - Reply
  18. ATRAPS November 8, 2020 at 10:34 am - Reply

    Day 1 on my journey to learn data analysis with python, this vid and kaggle's free pandas course is just what i needed to give me more motivation to keep learning.

  19. No Name November 8, 2020 at 10:34 am - Reply

    What the hell, I imagined this topic in afternoon and video recommended after only few hours. And the shocking fact I didn't even searched about this topic from many days.

  20. Sai Sarath November 8, 2020 at 10:34 am - Reply

    Thank you so much.

  21. Zhanibek Zhussupov November 8, 2020 at 10:34 am - Reply

    Only 1% worst thing of this video – god damn Ads!

  22. Nasser Al-Ostath November 8, 2020 at 10:34 am - Reply

    awesome videos bro …thanks

  23. Mmathen P November 8, 2020 at 10:34 am - Reply

    Why don't this work on an excel file. I almost did the same thing!

  24. Anonymous M November 8, 2020 at 10:34 am - Reply

    Very Useful. Tks alot

  25. boom1111111111111111 November 8, 2020 at 10:34 am - Reply

    Impressive. I'd pay to watch you crush kaggle things.

  26. REVERSE ROGUE November 8, 2020 at 10:34 am - Reply

    14:10 use
    for index, row in df.iterrows():
    print(index, row['Name'])

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