Pandas 101

on YouTube ↗34m

" summary

Loads two real datasets (Melbourne weather and Brisbane nowtap beer checkins) with pandas and Wakari/Anaconda, cleans messy CSV rows, converts floats to datetime and sets a time-index, resamples and plots series showing a 10-degree drop in an hour, merges venues and checkins, groupbys and pivots to find top beers and venue variety (MC has the most), isolates beer "temptress" with 16 recent Temptress check-ins, shares runnable notebooks and GitHub code so examples actually execute.

AI-written summary · about

" chapters (15)

1. 0:00Intro
2. 0:45Who is this for
3. 1:25First tip
4. 2:08Anaconda
5. 2:46Why use pandas
6. 3:08Features
7. 3:33Loading Data
8. 4:11Reading Data
9. 5:40DataFrame
10. 6:39Import CSV
11. 7:08Clean Data
12. 9:14Nulls
13. 14:51Recap
14. 15:29Analysis
15. 21:40Second Data Set

" related talks

• 01h 31mPandas, Data Wrangling & Data ScienceKrishna Sankar · PyData San Francisco 2016
• 01h 26mPandas: .head() to .tail()Tom Augspurger · PyData Chicago 2016
• 01h 52mIntroduction to data analytics with pandasQuentin Caudron · PyData Seattle 2017
• 21mHow to use Pandas EfficientlyHossein Mortazavi · PyData Yerevan 2022
• 01h 24mIntroduction to Data-Analysis with PandasAlexander CS Hendorf · PyData Berlin 2017
• 01h 21mPandas from the InsideStephen Simmons · PyData DC 2016
• 44mIntroduction to PandasJason Myers · PyOhio 2014
• 01h 27mCleaning and Tidying Data in PandasDaniel Chen · PyData DC 2018