Value Counts Analysis | Pandas Data Analysis Tutorial #4 | Percentage and Frequency

[@mariobohme8703]

I find it very helpful that you explain the content with practical use cases.

[@absentdata]

Thanks! Yes, I wanted to make sure that you can see application of the functions! If you have any suggestions or use-cases. Don't hesitate to ask!

[@Olimpico230]

thank you so so so so much. You just made my school project so much easier

[@absentdata]

Glad I could help!

[@mokus603]

Always worth to watch your videos!

[@absentdata]

THANK YOU!

[@dhamuvj331]

Clearly Explained!

[@osoriomatucurane9511]

Awesome, EDA just using value_counts()!
By the way, I could not see any stament importing the visualization library. Could you explain me what library are you using to access those exploratory plots? Are they pandas native or python????

[@absentdata]

Matplotlib is a part of Pandas so you can do simple plotting with just Pandas. For more styling you need to import the full matplotlib library

[@Islamic_stories4u]

Wonderfull explaination!😃

[@absentdata]

Glad you think so!

[@absentdata]

Share if you think it helps

[@eatbreathedatascience9593]

df[['Departments ','salary']].value_counts() means I don't have to do a groupby on Department first ??

[@sithembisomdlalose4806]

what a nice video lesson 👏 what if I wanted to do a value count for all columns or the entire dataframe at once ? is it possible?

[@absentdata]

Yes you can do this with a "for" loop. See below:
for i in df.columns:
print(df[i].value_counts())

[@sithembisomdlalose4806]

@@absentdata Thank you so much

[@BlueSkyGoldSun]

What is wrong with your videos ??
I had to watch 3 AD videos !! in 11 min length Tutorial !!!