21 more pandas tricks

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  • Опубликовано: 22 авг 2024

Комментарии • 72

  • @dataschool
    @dataschool  2 года назад +12

    THANKS for watching! 🙌 Which trick are you most excited to start using? CLICK REPLY and let me know!

  • @rezaghari828
    @rezaghari828 2 года назад +2

    That was really Helpful, man! Glad that I saw your tweet in my timeline!

    • @dataschool
      @dataschool  2 года назад +1

      That’s great to hear, thanks Reza! 🙌

  • @pivotai525
    @pivotai525 2 года назад +1

    I was becoming sad that you were no longer making pandas videos. What a come back like that of Real Madrid :)). Thanks Kevin!!

  • @frankgiardina205
    @frankgiardina205 2 года назад +2

    Lots of time savers here thanks well done

    • @dataschool
      @dataschool  2 года назад

      You're very welcome, Frank!

  • @Kristina_Tsoy
    @Kristina_Tsoy 2 года назад +3

    Thank you so much! Your tutorials are the best

  • @fj0n452
    @fj0n452 2 года назад +1

    What a great video! Thanks!

  • @sheikirfan2652
    @sheikirfan2652 6 месяцев назад +1

    Great tutorial ❤

  • @horoshuhin
    @horoshuhin 2 года назад +1

    love it. I really enjoyed this video. thanks for the quality content

    • @dataschool
      @dataschool  2 года назад

      That’s awesome to hear, thank you! 🙏

  • @carloseduardocorreacoimbra4040
    @carloseduardocorreacoimbra4040 2 года назад +1

    Thanks a lot for the excellent tricks (25 + 21) ! Really amazing and useful.

  • @nothingDone-ei2fj
    @nothingDone-ei2fj 10 месяцев назад

    I completed 36 videos in this series. Thanks a lot Kevin for such amazing tutorial.

    • @dataschool
      @dataschool  7 месяцев назад +1

      That is awesome to hear! Congratulations!

  • @immanuelsuleiman7550
    @immanuelsuleiman7550 2 года назад +2

    excellent as always

  • @pabloxD75
    @pabloxD75 2 года назад +1

    Great tips, holy! there is always something new to learn.

  • @hyakushiki23
    @hyakushiki23 8 месяцев назад

    Even after re-watching them, your videos are outstanding.

    • @dataschool
      @dataschool  7 месяцев назад

      Thank you so much! 🙏

  • @gabrielreilly7010
    @gabrielreilly7010 2 года назад +1

    I love these videos. I always learn so much.

    • @dataschool
      @dataschool  2 года назад

      What a nice thing to say, thank you so much! 🙏

  • @kissnicky7001
    @kissnicky7001 2 года назад +2

    Thanks so much,really helpful

    • @dataschool
      @dataschool  2 года назад

      Glad it was helpful to you! 🙌

  • @yd_
    @yd_ 2 года назад +3

    Cool. pandas and numpy seem to have a ton of functions and it’s hard to remember them all. Would appreciate a video focused on multilevel data frames, as I always forget how to index, etc those.

    • @dataschool
      @dataschool  2 года назад +1

      I actually have a video about the MultiIndex! Here it is: ruclips.net/video/tcRGa2soc-c/видео.html

  • @amitnikhate630
    @amitnikhate630 2 года назад +1

    Hi Kevin, Thank you for creating such amazing contents. These videos are really helpful for doing real time projects. I wanted to request you to make video on particular topic. if you can make video on how to use pandas to write, read and edit google sheets, that would be very helpful. It can include putting values in range of cells as well as one cell in google sheet, reading data, etc. If there is already any video you have made on this topic, let me know.

  • @Yuri-to8uj
    @Yuri-to8uj 2 года назад +1

    amazing content!!

  • @dariuszspiewak5624
    @dariuszspiewak5624 2 года назад +2

    Hi Kevin. The most important question of all: How to remember all of those things? Do you have any means? Any way that lets you retain the tricks/knowledge in your mind for longer? Would you please share any thoughts on that? Thanks.

    • @dataschool
      @dataschool  Год назад +1

      Great question! I don't have a system for memorization, rather it just comes naturally the more I use something. However, I also don't worry about forgetting, because I usually remember where to look in order to refresh my memory. Thus, my advice is (1) practice, and (2) keep track of good resources so that you can look up things easily whenever you forget. Hope that helps!

  • @TimePasser
    @TimePasser 2 года назад +1

    I miss your videos , man. Best like to best tutor. 👌

  • @DartEremite
    @DartEremite 2 года назад +1

    Thank you 😊😊

  • @pietraderdetective8953
    @pietraderdetective8953 2 года назад +1

    Great tips and tricks as always!
    do you have a tutorial video about writing efficient pandas code? for example implementing vectorization?
    I've watched plenty of your videos but I think I haven't seen one about the topic

    • @dataschool
      @dataschool  2 года назад +1

      Thanks very much! I think this video might be of interest to you: ruclips.net/video/dPwLlJkSHLo/видео.html

    • @pietraderdetective8953
      @pietraderdetective8953 2 года назад +1

      Awesome, will check that out!

  • @shubhi2194
    @shubhi2194 2 года назад

    Thank you for you amazing videos! Super informative and helpful, as always.

    • @dataschool
      @dataschool  2 года назад

      That's so nice of you to say! You're very welcome! 🙌

  • @yerriswamym323
    @yerriswamym323 Год назад +2

    Hi Kevin, Thanks for the insightful video. I love your videos and courses they are so subtle and impactful. Would it be possible for you to make a video on Python Class/objects? Its a daunting concept for someone like me (not from coding background) who has limited understanding of OOPs. Additionally I have observed that many coders use python classes for ML scripts/pipeline, scripting files on Github. So it would be helpful if you could make an video on the same.
    Thanks in advance !!

    • @dataschool
      @dataschool  Год назад

      Thanks for your suggestion! I'll consider it for the future. For now, maybe start here: ruclips.net/p/PL-osiE80TeTsqhIuOqKhwlXsIBIdSeYtc
      Hope that helps!

  • @souraneelmandal7912
    @souraneelmandal7912 2 года назад +1

    How to use text classification approach where target column is bigram word...?
    Can you please show us ..?

  • @bobiq
    @bobiq Год назад

    Just doing your datacamp RI Police course. It's a really well laid out course and I think you're adorable. :-)

  • @faizanwar_
    @faizanwar_ 2 года назад

    Sir , please make a video on user defined functions in pandas dataframe

  • @petroliumengineer
    @petroliumengineer 2 года назад +1

    This resample methood is incredibly useful
    Thanks a ton

    • @dataschool
      @dataschool  2 года назад

      I agree! It really helped me once I started thinking of resample as a groupby for datetime data.

  • @tramphone6414
    @tramphone6414 Год назад

    good

  • @hyakushiki23
    @hyakushiki23 2 года назад

    Hi Kevin, I hear a lot about API's. Maybe one day you can demo how to create a basic custom API.

    • @dataschool
      @dataschool  2 года назад

      Thanks for your suggestion!

  • @georgiyveter6391
    @georgiyveter6391 Год назад

    Hi, for example I have a table, which I've got by left outer join:
    person - vehicle
    dad - car
    dad - motorcycle
    dad - bicycle
    mom - car
    mom - bicycle
    son - None/NA/NaN/NaT
    How to group by person and count with condition (car and motorcycle)?
    When I use for example:
    df = df.groupby(['person'])['vehicle'].apply(lambda x: x[x == 'car'].count())
    But I can't use a list in condition lambda x: x[x in ['car']], pandas says:
    ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

  • @sachinrathi4197
    @sachinrathi4197 2 года назад +1

    why below code is not giving any output
    pd.testing.assert_series_equal(df.c, df.d, check_names=False, check_dtype=False)

    • @dataschool
      @dataschool  2 года назад +1

      Great question! The assertion passed, thus no error was raised, thus no output was generated. If you're new to assertions, just try running assert(1==1) and assert(1==2) in Python, and you'll see that when an assertion passes, there is no output. Hope that helps!

  • @dvinkster
    @dvinkster 2 года назад

    Thanks for the tips.
    Q: How crosstab provided the results compared to pivot where no target value 'Survived' is provided
    Unable to view the Notebook from link provided. Please re upload

    • @dataschool
      @dataschool  2 года назад

      Great question! With the pivot table, I just selected a column with no missing values (Survived in this case) and counted them. With crosstab, it automatically does a count, so you don't need to select a specific column.
      Regarding the notebook, you can view it here: github.com/justmarkham/pandas-videos/blob/master/21_more_pandas_tricks.ipynb
      Hope that helps!

  • @nguyenhuuuc2311
    @nguyenhuuuc2311 2 года назад +1

    The meaning of 🐼 is 46!

  • @Mortz76
    @Mortz76 2 года назад +1

    jupyter notebook link broken

    • @dataschool
      @dataschool  2 года назад

      You can use this link instead: github.com/justmarkham/pandas-videos/blob/master/21_more_pandas_tricks.ipynb

  • @firefouuu
    @firefouuu 2 года назад +2

    On tips 14, I think a better solution is to use df.style to display all columns and rows of your DataFrame. If you have a lot of rows and are only interested in the columns just use df.head().style

    • @dataschool
      @dataschool  2 года назад

      Love it! Thank you for sharing! 🙌

  • @user-vd2ui5uk2s
    @user-vd2ui5uk2s Год назад

    Hi Kevin, a question question, why the code (titanix.SibSp > 0).astype(' int ') can set different integers into 0 and 1?

    • @dataschool
      @dataschool  Год назад +1

      Great question! The boolean value True gets converted to 1, and False gets converted to 0. Hope that helps!