I only landed on this lecture while seeking to understand the basics of generalized logistic growth function and Richard's curve. It is even more enlightening to learn about applications of the function/model. Thank you very much for putting such a good content out.

Thank you. Just what I needed. ps Good to know new hotkeys 😀

this video just randomly popped up but thats the actual way to learn code man glad you r teaching code this way

Python?

kee it up🙌🙌

First. Also that's rad. Now I learned something I never would think to leran.

Can you make a data analysis video with real world data that you have previously done in your job if not confedential

you will update your course?

Thanks a lot. I really enjoyed reading through the code. Also was introduced to Seaborn too. Nice work sharing this :)

1) 0:49 CMD (as Admin): pip install tabula-py. (java installed previously) 2)

Do you think Tabula work for all generated text pdf?

Not sure how to choose from the many python packages to extract data from a PDF.. PyMuPDF, PyPDF2 , PDFplumber, tabula-py, etc.. For example, what if the PDF is a scan of a paper document.. i.e. it's crooked, and quality is bad. Is there one that does it best? Or maybe I should use AI (ChatGPT + GPT4Vision/Ai PDF) to do an OCR, then have it extract the data? Also any suggestions how to get the values from specific columns in a text file. For example, I have text files with data like this: #Time (HHH:MM:SS): 002:34:02 # T(ms) BUS CMD1 CMD2 FROM SA TO SA WC TXST RXST ERROR DT00 DT01 DT02 DT03 DT04 DT05 DT06 DT07 # ===== === ==== ==== ==== == ==== == == ==== ==== ====== ==== ==== ==== ==== ==== ==== ==== ==== 816 B0 D84E BC RT27 2 14 D800 2100 0316 0000 0000 0000 0000 CCCD 0000 817 A0 DC50 RT27 2 BC 16 D800 2120 0000 4080 3000 0000 3000 0000 0000 #Time (HHH:MM:SS): 002:34:03 # T(ms) BUS CMD1 CMD2 FROM SA TO SA WC TXST RXST ERROR DT00 DT01 DT02 DT03 DT04 DT05 DT06 DT07 # ===== === ==== ==== ==== == ==== == == ==== ==== ====== ==== ==== ==== ==== ==== ==== ==== ==== 056 B0 D84E BC RT27 2 14 D800 2100 0316 0000 0000 0000 0000 CCCD 0000 057 A0 DC50 RT27 2 BC 16 D800 2120 0000 4080 3000 0000 3000 0000 0000 How can get just the data from DT00 thru DT07 into an array, without doing lots of preprocessing to scrub out the repeating #Time headers that appear throughout the file?

Thank you sir

you said seaborn but it doesn't work on seaborn (displot)

I written a long complex code for this lol p=df.groupby(['dept', 'sex'])['sex'].count() x=df.groupby('dept')['sex'].count() r = 100*p/x return pd.DataFrame(r).rename(columns={'sex':'percent'})['percent'].round(1).reset_index().pivot(index='dept', columns=['sex'], values='percent')

You said: "it's trial and error, until you get it right" I think that's why "camelot" is better. You can get visual output (with matplotlib) so you don't need to guess iteratively.

AttributeError: module 'tabula' has no attribute 'read_pdf' everytime it is showing this error

Awesome content - subscribed!

Can you use this method of wrapping the labels for heatmaps?

I just wanted to say thank you sir. i know this video is a couple years old but I still pull it up to watch whenever I need to add miniconda to a compy 👍

Very cool tricks! Who would have thought that using Pandas and Python can this be fun! :By the way, do you give discount to "Master Data Analysis with Python"? :)

I just discovered your channel! I'm ecstatic! :)

There is no "Live-Tutorials" under the Assignment tab.

Please subscribe if you like these kind of advanced pandas tutorials!

Never seen .sum() used in that fashion. Slick. Learn something new every day.

Very good delivery. well done.

Beautiful!!! Thanks for sharing this info!!!

Cool!

i didnt got the deploy option in files menu , im using simple jyupter notebook why?

This is such an underrated video. Ty.

Thank-you!!!

Thx

Great!

😳 ｐｒｏｍｏｓｍ

Great !

Would have been helpful to put the code on git...great video nonetheless!

Really impressive skills. I learned a lot.

2a: maybe cleaner with .loc instead of np.where

nice video! Didn’t know that you could assign functions to a variable.

CovidImages need to be invested more than half19

Character In the video It's great, I like it a lot $$

Great!

I came with four ways: 1. extend method of a list 2. from itertools use chain 3. nested list comprehension 4. sum builtin method.

Nice series. How do you make the cells horizontally aligned at kzbin.info/www/bejne/h2ispaWuebxkr6M ?

In 01. What is Pandas ju have bug in calling DB: right syntax is engine = create_engine('sqlite:///../../data/databases/neurIPS.db'), use only two "../"

This setup takes more than 500 MBs disk space.

thanks for this!

very nice way of presenting it ;-)

But I want missing values in each column. Meaning missing value in each column / total value in each column. Totla value in each column = missing value + non Missing value.

I am getting this error please resolve..................................................................... Failed to post to Medium Returned error message below "FileNotFoundError: [Errno 2] No such file or directory: 'Desktop\\\\DLCVNLP\\\\Tensorflow_2.x.ipynb' Traceback (most recent call last): File \"C:\\Users\\admin\\anaconda3\\lib\\site-packages\ bformat\\__init__.py\", line 138, in read buf = fp.read() AttributeError: 'WindowsPath' object has no attribute 'read'