The query function is new to me. It is similar to applying filters on the database, but definitely faster for generating results. Thank you for sharing!
Thank you! Glad you liked the video. Today I will upload a 4min tips video on how to use Python's Pathlib module (to work with file paths & directories in Python) 😃
Thank you very much! If you are looking for ideas, please do video about advanced combinations of groupby function and other methods. Anyway, thank you for short description in this video too :)
Fantastisch! Kurz und sehr informativ! I've been using Pandas for a few months now and everything in this except groupby() was new to me. I can't believe I've watched two Pandas tutorials and this is the first time I've learned about query().
Coming from a T-SQL background a lot of these functions seem to "make sense" as in they are idiomatic to what I wish to do with datasets. But I am glad to see working examples of this.
Hi Sven, once again saw ur informative video. How to write SQL query displaying strings (select * from friend LIKE %string %) using pandas. I tried with str.contains but literally failed..
I learned query thru your (awesome) streamlit tutorials. Didn't know about cut, super useful. Do you know how to cut in multiple dimensions? Say in this case, gender and tip? To produce an occurrence chart?
Thank you very much for watching the video and your comment. I receive many requests for creating individual solutions. As much as I want to help, I simply do not find the time in my daily schedule to develop & test all the different requests. I hope you can understand. Thank you
Your videos are on the next level buddy! Keep it up. But, can you start with Machine Learning and Deep Learning course only the coding part that can be understood by everyone?
Thanks! I was thinking about doing some Machine Learning tutorials, but I think there are already many excellent tutorials here on RU-vid. For now, I will stick to office (Excel) automation, visualisations fun Python projects :)
Hi Maz Kaibil, thanks so much for your kind words! I'm really glad to hear that my videos have been helpful and that you've learned some new things from them. It's always great to hear when my content has made a positive impact on someone's life. 👍
Very good! Could you make a tutorial on data handling inside def, for loop functions? I wanted to know the importance of putting lines of code inside def functions for optimization.
This is awesome! Saved and liked this video. I am actually working on groupby now to better master it for visuals. Not the best at setting up filters(using number or most of the time counting strings and numbers) and then using it in my groupbys to graph them. That said here is something really cool I found out. Making a new column filter and inserting it in the position I want for better comparing df.insert(1, “new column’s name”, df[“column1”] / df[“column2”]) What the above does is inserts at index 1 a new column named whatever, and based on a condition(in this case dividing) so simple but 🤯
Thanks for watching. I guess, you want to first insert a new column with the reject_ratio. Example: df['reject_ratio'] = df['defects'] / df['production'] I hope this helps!
@@asankacool1, I do not know your data(frame), but perhaps you are looking for the cumsum function of pandas: pandas.pydata.org/docs/reference/api/pandas.DataFrame.cumsum.html
