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


[ad_1]

Data & code used on this Tutorial: https://github.com/KeithGalli/pandas
Python Pandas Documentation: http://pandas.pydata.org/pandas-docs/secure/

Let me know when you have any questions!

In this video we stroll by means of most of the elementary ideas to make use of the Python Pandas Data Science Library. We begin off by putting in pandas and loading in an instance csv. We then have a look at alternative ways to learn the information. Read a column, rows, particular cell, and so on. Also methods to learn information primarily based on conditioning. We then transfer into some extra superior methods to kind & filter information. We have a look at making conditional modifications to our information. We additionally begin doing mixture stats utilizing the groupby perform. We completed the video speaking about how you’d work with a really giant dataset (many gigabytes)

I spotted as I add this video there are some extra issues I wish to discuss in a later video. The very first thing that involves thoughts instantly is utilizing the apply() perform on a dataframe to change the information utilizing a customized or lambda perform. If you could have questions on this or the rest earlier than I get round to creating a component 2, be happy to put in writing me a observe within the feedback.

If you loved this video, be sure you throw it a like and ensure to subscribe to not miss any future movies!

Thanks for watching pals! Happy coding! 🙂

———————————————
Follow me on social media!
Instagram | https://www.instagram.com/keithgalli/
Twitter | https://twitter.com/keithgalli

⭐ Kite is a free AI-powered coding assistant that may allow you to code quicker and smarter. The Kite plugin integrates with all the highest editors and IDEs to offer you sensible completions and documentation when you’re typing. I’ve been utilizing Kite for six months and I like it! https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=keithgalli&utm_content=description-only

———————————————
Link to authentic supply of knowledge from Kaggle: https://www.kaggle.com/abcsds/pokemon

———————————————
Video Outline!
0:00 – Why Pandas?
1:46 – Installing Pandas
2:03 – Getting the information used on this video
3:50 – Loading the information into Pandas (CSVs, Excel, TXTs, and so on.)
8:49 – Reading Data (Getting Rows, Columns, Cells, Headers, and so on.)
13:10 – Iterate by means of every Row
14:11 – Getting rows primarily based on a selected situation
15:47 – High Level description of your information (min, max, imply, std dev, and so on.)
16:24 – Sorting Values (Alphabetically, Numerically)
18:19 – Making Changes to the DataBody
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, and so on.)
31:47 – Filtering Data (primarily based on a number of circumstances)
35:40 – Reset Index
37:41 – Regex Filtering (filter primarily based on textual patterns)
43:08 – Conditional Changes
47:57 – Aggregate Statistics utilizing Groupby (Sum, Mean, Counting)
54:53 – Working with giant quantities of knowledge (setting chunksize)

————————-
If you’re curious to learn the way I make my tutorials, try this video: https://youtu.be/LEO4igyXbLs

*I exploit affiliate hyperlinks on the merchandise that I like to recommend. I’ll earn a purchase order fee or a referral bonus from the utilization of those hyperlinks.

supply
[ad_2]

Comment List

  • Keith Galli
    November 8, 2020

    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! 🙂

    Let me know if you have any questions

  • Keith Galli
    November 8, 2020

    thank you so much and it is clear and very useful for the beginner just like me. thanks from Taiwan

  • Keith Galli
    November 8, 2020

    Is it still informative after 2 years?

  • Keith Galli
    November 8, 2020

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

  • Keith Galli
    November 8, 2020

    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")

  • Keith Galli
    November 8, 2020

    Amazing!

  • Keith Galli
    November 8, 2020

    good stuff 🙂
    i hate SMS-es too lol lol

  • Keith Galli
    November 8, 2020

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

  • Keith Galli
    November 8, 2020

    Thanks for the videos. Very much appreciated

  • Keith Galli
    November 8, 2020

    Thanx for such a great video. helped me a lot

  • Keith Galli
    November 8, 2020

    THIS CHANNEL IS FUCKIN LIT

  • Keith Galli
    November 8, 2020

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

  • Keith Galli
    November 8, 2020

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

  • Keith Galli
    November 8, 2020

    This video is just glorious

  • Keith Galli
    November 8, 2020

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

  • Keith Galli
    November 8, 2020
  • Keith Galli
    November 8, 2020
  • Keith Galli
    November 8, 2020
  • Keith Galli
    November 8, 2020
  • Keith Galli
    November 8, 2020

    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.

  • Keith Galli
    November 8, 2020

    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.

  • Keith Galli
    November 8, 2020

    Thank you so much.

  • Keith Galli
    November 8, 2020

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

  • Keith Galli
    November 8, 2020

    awesome videos bro …thanks

  • Keith Galli
    November 8, 2020

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

  • Keith Galli
    November 8, 2020

    Very Useful. Tks alot

Write a comment