Learning Pandas for Data Analysis? Start Here.

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  • čas přidán 12. 06. 2024
  • A high paced overview of many of the pandas core functionality. As one of the most popular libraries in all of programming, Pandas is an essential tool for learning data wrangling. Watch this video to get a good foundational understanding of what is possible.
    Intro to Jupyter: • Jupyter Notebook Compl...
    Kaggle notebook made by a viewer! www.kaggle.com/code/lizhechen...
    Download the dataset here: www.kaggle.com/datasets/robik...
    Timeline:
    00:00 Intro
    00:57 Importing Pandas
    01:26 Data I/O
    01:51 Reading From Files
    03:03 Writing to Files
    03:36 DataFrame Basics
    04:57 DataFrame Summary
    06:12 Subsetting Columns
    07:19 Select dtypes
    07:34 Select as Series vs DataFrame
    07:58 .loc and .iloc
    09:37 .loc Filter Expressions
    10:50 .query
    11:31 Summary Statistics
    12:10 .agg
    12:53 Sumarizing Categoricals
    13:43 rank, shift, cumsum
    14:44 Rolling methods
    15:21 Clip
    15:41 Groupby
    16:44 New Columns
    17:33 Sorting
    18:30 Missing Data
    19:33 Combining Data
    19:55 concat
    21:01 Merge DataFrames
    21:52 Merge Suffixes
    22:34 Bonus
    Check out my other videos:
    Data Pipelines: Polars vs PySpark vs Pandas: • The BEST library for b...
    Polars for Data Science: • Polars: The Next Big P...
    Speed up Pandas Dataframes: • This INCREDIBLE trick ...
    Avoid These Pandas Mistakes: • 25 Nooby Pandas Coding...
    Links to my stuff:
    * CZcams: youtube.com/@robmulla?sub_con...
    * Discord: / discord
    * Twitch: / medallionstallion_
    * Twitter: / rob_mulla
    * Kaggle: www.kaggle.com/robikscube
  • Věda a technologie

Komentáře • 106

  • @robmulla
    @robmulla  Před 9 měsíci +12

    Want to follow along with the same dataset and python environment? Big thanks to someone who made a kaggle notebook with this entire tutorial: www.kaggle.com/code/lizhecheng/pandas-2-0-1-tutorial/notebook
    Just fork the notebook and explore the data with pandas!

  • @spacephenix9849
    @spacephenix9849 Před 9 měsíci +55

    This is a masterpiece Rob. A condensed pandas course. Wow. Even regular Data Scientist can refresh their mind or discover tips and tricks they are not used to use such as the query methods. And what I like the most, it all fits within 23 minutes. I would love to have such videos for some of the other commons libs.

  • @elu1
    @elu1 Před 9 měsíci +13

    This is truly incredible! It's the finest pandas tutorial available on the internet, offering a remarkable balance of breadth and depth.

  • @SmadeX2
    @SmadeX2 Před 9 měsíci +3

    This is the best video on pandas I’ve seen so far (and I’ve seen dozens). Thank you so much for keeping your explanations short and up to the point!!! Gonna use the video as my top 1 reference resource when I feel stuck!

  • @sojourner5294
    @sojourner5294 Před 2 měsíci +2

    Thank You so much for putting this together Rob, you make it look so easy and it's well explained and very clear. I really appreciate you for sharing this with everyone !

  • @thomaskwesimwaba9151
    @thomaskwesimwaba9151 Před 9 měsíci +1

    Thank you for the videos Rob, your hard work is highly appreciated.

  • @chauhanknight07
    @chauhanknight07 Před 3 měsíci +6

    This 20 min video is equivalent to 2hrs of other youtube videos...masterpiece

    • @robmulla
      @robmulla  Před 3 měsíci

      Thanks! Tell your friends.

  • @paveluhliar
    @paveluhliar Před měsícem

    Thanks for this video. Packed with info, but still easy to follow, no small talk… Really appreciate your effort!

  • @samanvithajanga
    @samanvithajanga Před 9 měsíci +1

    Wonderful channel for beginner data analysts & learned a lot of concepts from you…. Great work man

  • @PaulMcKillop
    @PaulMcKillop Před 9 měsíci +1

    Thanks, Rob. That's a great summary of the features. Really useful!

  • @irfanshaikh262
    @irfanshaikh262 Před 9 měsíci

    Thank u very much.
    I can now officially announce and recommend this video to my friends as one stop pandas tutorial and solution.
    Thanks Rob

  • @franciseigbe2796
    @franciseigbe2796 Před 9 měsíci

    I can tell even before watching this video that's its great!!! You're such a great tutor.

  • @mikep4981
    @mikep4981 Před 9 měsíci +4

    This video is fantastic. informative, concise and a strong foundation for pandas. Most importantly, it is easy to understand and follow along. Thanks for the video, I'm subscribing!

    • @robmulla
      @robmulla  Před 9 měsíci +1

      Really appreciate the feedback. Glad you found it easy to follow. I was a little worried it might be too fast.

    • @mikep4981
      @mikep4981 Před 9 měsíci +2

      @@robmulla I typically take notes when watching videos like this so I am accustomed to pausing. In my opinion it's better when there isn't much filler in between so that it's easy to get to the next point or move back to where you want.

  • @kiara4345
    @kiara4345 Před 8 měsíci

    This is great work!! Thank you very much for putting it out here!!

  • @IsraRM
    @IsraRM Před 9 měsíci +1

    Great video Rob, I would love to see you explaining Machine Learning and Deep Learning models, from theory to practice using scikit-learn, Keras or Pytorch. You really made things look easy. Can't wait to see another of your awesome videos.

  • @kamranzamanni6826
    @kamranzamanni6826 Před 9 měsíci

    Very easy to follow along, thank you!

  • @okok-sc2cx
    @okok-sc2cx Před 9 měsíci

    Thank you so much ❣️ I have watched your previous pandas video, but this had everything ❤ it was awesome ❤
    I understood everything except for to write csv,
    Thank you so much for this amazing video ❤

  • @syedhaider0916
    @syedhaider0916 Před 9 měsíci

    Not enough half way through and I can tell this video is gold.

  • @nusratsayyed8560
    @nusratsayyed8560 Před 9 měsíci +1

    Thanks Rob for sharing the knowledge and experience to data community 😊

  • @chriskeo392
    @chriskeo392 Před 7 měsíci

    One of my favorite teachers

  • @user235fhrdiib
    @user235fhrdiib Před 8 měsíci

    It is solid tutorial for Data Geeks. Thank you)

  • @Arctect
    @Arctect Před 9 měsíci +1

    Very cool ninja panda style!!! So useful and like a real pro awesome!!!

  • @DavidPonzio-up8ln
    @DavidPonzio-up8ln Před 3 měsíci

    Good Intro! Thanks!

  • @whatisagoodusernamehere
    @whatisagoodusernamehere Před 9 měsíci +3

    we are waiting for the next part! I personally wanna see sth on visualization!

    • @robmulla
      @robmulla  Před 9 měsíci +1

      Thanks for the feedback. I’ll keep that in mind for the next video.

  • @phamtienthinh1795
    @phamtienthinh1795 Před 4 měsíci +1

    It took me 2 hours and 30 minutes to revise pandas, but it's worth it

  • @dailinchibasgoico6508
    @dailinchibasgoico6508 Před 6 měsíci

    Thanks for sharing your knowledge

  • @gamerfisch5117
    @gamerfisch5117 Před 9 měsíci +2

    Nice Video Rob. This helped me a lot :)

  • @sandie_jr
    @sandie_jr Před 2 měsíci +1

    Thanks Rob!

  • @ronbzalen
    @ronbzalen Před 9 měsíci +1

    Great tip on renaming the multi index columns!!

  • @enricomendiola9952
    @enricomendiola9952 Před 3 měsíci

    Thank you Rob 😊

  • @lucasoliveirapaes
    @lucasoliveirapaes Před 8 měsíci

    Thanks for the content, Rob! it's really excellent! Can you do another video like this but with numpy?

  • @alfonsourquidi9778
    @alfonsourquidi9778 Před 2 měsíci

    Thank you for this lesson and all your work. As always, I learn so much from you! Any chance you'd do a video lesson on data cleaning? 🙏

  • @TATAWAKO
    @TATAWAKO Před 9 měsíci

    Magic Rob! hopefully be like you one day

  • @level10peon
    @level10peon Před 9 měsíci +2

    I've been learning Pandas for a couple of years on and off now, and have even used it a little at work, and yet there were still a few things in here I didn't know about. The rolling method in particular is a game changer, I've been manually creating functions to do that and now I can just do it in one line of code (and likely faster than my hacked together functions).

    • @mark-dy9zo
      @mark-dy9zo Před 6 měsíci +1

      Can you give an example of a rolling method application? I'm curious

    • @andrewmk8514
      @andrewmk8514 Před 4 měsíci

      ​@@mark-dy9zomoving averages

  • @tmb8807
    @tmb8807 Před 7 měsíci

    Thanks for this. Straight to the point. Great!
    Do you think Polars is going to be especially disruptive? I’ve been using it a bit and I can’t believe how much faster it is at a lot of things. But pandas is very entrenched (and probably has slightly more friendly syntax).

  • @mathiaz943
    @mathiaz943 Před 9 měsíci

    Great stuff!

  • @Dongnanjie
    @Dongnanjie Před 5 měsíci

    Thank you Rob!!!

  • @ruanstg
    @ruanstg Před 9 měsíci +1

    Thanks for the great Video!
    How did you manipulate that folder with bunch of.csv files to put fit all together in the df? And how to deal with irregular datas in a typical case like this?
    Have you already done some tutorial explaining and detailing these kind of tasks?

  • @therealrucleshe7662
    @therealrucleshe7662 Před 6 měsíci +1

    this vid is a gem

    • @robmulla
      @robmulla  Před 6 měsíci

      Thanks! Glad you liked it.

  • @teddybear7949
    @teddybear7949 Před 9 měsíci

    Great video as always ! Would be Nice to have the same one with polars

  • @vinsensilitonga9148
    @vinsensilitonga9148 Před 8 měsíci +1

    Great lesson

  • @therickestpicklerick
    @therickestpicklerick Před 6 měsíci

    Perfect!

  • @andrewmk8514
    @andrewmk8514 Před 4 měsíci

    Hi. I wish I watched this before my last project. Hope you will do an advanced series.

  • @vmartme
    @vmartme Před 9 měsíci

    Thanks!

  • @Blahcub
    @Blahcub Před 9 měsíci

    I'm wanting to ask a bit more of a meta question. How much time do you spend outside of work on your skills? How much passion or drive do you have and what are your routines? I work in medical ML and came across your EDA video and wanted to get a successful person's view on how to improve and grow.

  • @rubenagurcia906
    @rubenagurcia906 Před 10 dny

    amazing!!

  • @ProfitPioneers69
    @ProfitPioneers69 Před 4 měsíci +1

    Thanks bro

  • @prashlovessamosa
    @prashlovessamosa Před 9 měsíci

    Thanks Rob 😁.

  • @swannschilling474
    @swannschilling474 Před 2 měsíci

    Awesome ❤

  • @Arkantosi
    @Arkantosi Před 9 měsíci

    Great as always! Now get to work and make tutorials for seaborn and matplotlib :)

  • @bassamsaleh8034
    @bassamsaleh8034 Před 9 měsíci +1

    thanks for the video, one request though, can we have the same dataset so we can follow along.

  • @enricomendiola9952
    @enricomendiola9952 Před 3 měsíci +1

    Hello Rob great video! I have a question, how do you enable the description of the methods that you use. They are showing on the right when you type in the ‘dot’.

    • @robmulla
      @robmulla  Před 3 měsíci

      Thanks. With Jupyter you just do shift-tab

  • @obayram4615
    @obayram4615 Před 9 měsíci

    WERY NİCE .. THANKS FOR YOUR EFFORTSS :))

  • @twink276
    @twink276 Před 9 měsíci

    This is great

  • @CaribouDataScience
    @CaribouDataScience Před 9 měsíci +1

    Are you streaming this evening?

  • @alirezashahinmehr
    @alirezashahinmehr Před 2 měsíci

    It was really helpful, but I think you missed a section for converting data types in dataframes, specially for date types. thank you very much for this summary.

  • @MaxTheKing289
    @MaxTheKing289 Před 9 měsíci

    Masterpiece thanks thief!

  • @txreal2
    @txreal2 Před 9 měsíci +1

    Do you have a panda functions cheat sheet (df functions) available? Thanks. Follower 👍

  • @prashlovessamosa
    @prashlovessamosa Před 9 měsíci +4

    Thanks Rob 15 min done still 7 to go.

  • @Shahidma58
    @Shahidma58 Před 9 měsíci

    Hi Rob, Please start some series on Tableau. Regards.

  • @bisiadeyemo3082
    @bisiadeyemo3082 Před 5 měsíci

    @robmulla do you know a website or where I can find data cleaning exercises or challenges? I want to practice cleaning different kinds of data, any suggestions will be helpful

  • @ravishmahajan9314
    @ravishmahajan9314 Před 4 měsíci

    Hi, i have one silly question. How do you get intellisense i.e. functions menu for each object and for each function, the whole list of available parameters. Which IDE you are using ?
    It really helps to focus on use case rather than mugging up the function names and their syntax.

  • @thecaptain2000
    @thecaptain2000 Před 9 měsíci +1

    nice, if would be useful if you could put a link for downloading your dataset so we could play around with your data while you explain, it would be appreciated, for example I would need to see by myself what the difference reindexing does when combining datasets, it is not immediately obvious to me and would require some test and comparisons

    • @robmulla
      @robmulla  Před 9 měsíci

      The datset is on kaggle. Check out this notebook where someone linked the dataset and included the tutorial code: www.kaggle.com/code/lizhecheng/pandas-2-0-1-tutorial/notebook

  • @bisiadeyemo3082
    @bisiadeyemo3082 Před 5 měsíci

    Hi, does anybody know a website or where I can find data cleaning exercises or challenges? I want to practice cleaning different kinds of data, any suggestions will be helpful

  • @jahunmoayedzadeh9194
    @jahunmoayedzadeh9194 Před 6 měsíci

    I’m sorry I know this will sound dumb to you guys but how is it listing all option after writing a part of if. Like read_ ( then a whole bunch of different commands like read_csv and so on)? I’m using jupyter lab everyday and haven’t seen that ! Cool

  • @SuperSumittanwar
    @SuperSumittanwar Před 3 měsíci

    Hey Rob! Any resouce to download and handson with parquest file

  • @ryanzhan1513
    @ryanzhan1513 Před 2 měsíci

    Hi Rob,how to read the details of function in jupyter lab just like 2:22

  • @pabloarizono8398
    @pabloarizono8398 Před 9 měsíci +2

    hi! What plugin do you use to see the details of each function?

    • @robmulla
      @robmulla  Před 9 měsíci +1

      Great question! Shift-tab in jupyterlab.

  • @Christianboy2231
    @Christianboy2231 Před 19 dny

    Can u tell me where u execute ur code/ How do I get to the same terminal

  • @am0x01
    @am0x01 Před 9 měsíci

    Hi @robmulla
    In Handling Missing Data chapter, would be nice, if you could provide your insight as the best approach and what is normally recommended to do, if it is fillna or dropna, I know that it could be subjective to the task at hand, but having insight as expert would be nice.

  • @kancharlasrimannarayana7068
    @kancharlasrimannarayana7068 Před 8 měsíci

    cover EDA for time series data

  • @s.joseph4838
    @s.joseph4838 Před 9 měsíci

    I'm new to Data Science. Type every information on my jupyter lab. And im getting error and not dine. I don't understand this, smh what I'm im doing wrong

  • @chrisw1462
    @chrisw1462 Před 28 dny

    Nice dictionary.

  • @Artyom_E
    @Artyom_E Před 9 měsíci

    🤗

  • @AyahuascaDataScientist
    @AyahuascaDataScientist Před 9 měsíci +1

    Doesn’t appear as tho you really used the power of pandas 2.0 with the backend pyarrow default param and checking for nulls/data types :-(

  • @sunnykumar-iz7bq
    @sunnykumar-iz7bq Před 4 měsíci

    1:52 min. how to get that dropdown option

  • @prashlovessamosa
    @prashlovessamosa Před 9 měsíci +1

    Hello Rob.

  • @aldocastillo1194
    @aldocastillo1194 Před 9 měsíci

    how to get the data of this video

  • @datawithtess
    @datawithtess Před 9 měsíci

    Its time for you to show us hiw to build a dashboard

  • @fakhreddinemilouchi6013
    @fakhreddinemilouchi6013 Před 8 měsíci

    Great refresher, but too fast for tutorial. I suggest breaking it in chuncks.

  • @fisherh9111
    @fisherh9111 Před 3 měsíci +1

    is this guy AI generated? His jawline is too perfect.

    • @robmulla
      @robmulla  Před 3 měsíci

      No AI. I’m a real person.

  • @user-xn8wg6yw7g
    @user-xn8wg6yw7g Před 4 měsíci

    Helpful overview. Good content. But way too fast. Not everyone has an IQ of 150, Mr Mulla. Slow down..