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https://github.com/justmarkham/pandas-videos

Jupyter notebook and datasets from the pandas video series
https://github.com/justmarkham/pandas-videos

data-analysis data-cleaning data-science jupyter-notebook pandas python tutorial

Last synced: 6 days ago
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Jupyter notebook and datasets from the pandas video series

Host: GitHub
URL: https://github.com/justmarkham/pandas-videos
Owner: justmarkham
Created: 2016-03-31T17:39:41.000Z (over 8 years ago)
Default Branch: master
Last Pushed: 2024-03-05T19:28:51.000Z (9 months ago)
Last Synced: 2024-11-21T02:59:19.544Z (21 days ago)
Topics: data-analysis, data-cleaning, data-science, jupyter-notebook, pandas, python, tutorial
Language: Jupyter Notebook
Homepage: https://courses.dataschool.io/pandas-in-30-days
Size: 1.84 MB
Stars: 2,154
Watchers: 198
Forks: 1,929
Open Issues: 0
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml

Awesome Lists containing this project

awesome-data-science-resources - Pandas Tutorial Videos
awesome-data-science-resources - Pandas Tutorial Videos
awesome-hacking-lists - justmarkham/pandas-videos - Jupyter notebook and datasets from the pandas video series (Jupyter Notebook)

README

        # Python pandas video series

The series is also available as a [free online course](https://courses.dataschool.io/pandas-in-30-days) that includes updated content, exercises, and a certificate of completion.

## 📺 Videos ([playlist](https://www.youtube.com/playlist?list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y))

1. [What is pandas? (Introduction to the Q&A series)](https://www.youtube.com/watch?v=yzIMircGU5I&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=1) (6:24)

2. [How do I read a tabular data file into pandas?](https://www.youtube.com/watch?v=5_QXMwezPJE&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=2) (8:54)

3. [How do I select a pandas Series from a DataFrame?](https://www.youtube.com/watch?v=zxqjeyKP2Tk&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=3) (11:10)

4. [Why do some pandas commands end with parentheses (and others don't)?](https://www.youtube.com/watch?v=hSrDViyKWVk&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=4) (8:45)

5. [How do I rename columns in a pandas DataFrame?](https://www.youtube.com/watch?v=0uBirYFhizE&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=5) (9:36)

6. [How do I remove columns from a pandas DataFrame?](https://www.youtube.com/watch?v=gnUKkS964WQ&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=6) (6:35)

7. [How do I sort a pandas DataFrame or a Series?](https://www.youtube.com/watch?v=zY4doF6xSxY&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=7) (8:56)

8. [How do I filter rows of a pandas DataFrame by column value?](https://www.youtube.com/watch?v=2AFGPdNn4FM&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=8) (13:44)

9. [How do I apply multiple filter criteria to a pandas DataFrame?](https://www.youtube.com/watch?v=YPItfQ87qjM&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=9) (9:51)

10. [Your pandas questions answered!](https://www.youtube.com/watch?v=B-r9VuK80dk&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=10) (9:06)

11. [How do I use the "axis" parameter in pandas?](https://www.youtube.com/watch?v=PtO3t6ynH-8&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=11) (8:33)

12. [How do I use string methods in pandas?](https://www.youtube.com/watch?v=bofaC0IckHo&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=12) (6:16)

13. [How do I change the data type of a pandas Series?](https://www.youtube.com/watch?v=V0AWyzVMf54&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=13) (7:28)

14. [When should I use a "groupby" in pandas?](https://www.youtube.com/watch?v=qy0fDqoMJx8&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=14) (8:24)

15. [How do I explore a pandas Series?](https://www.youtube.com/watch?v=QTVTq8SPzxM&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=15) (9:50)

16. [How do I handle missing values in pandas?](https://www.youtube.com/watch?v=fCMrO_VzeL8&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=16) (14:27)

17. [What do I need to know about the pandas index? (Part 1)](https://www.youtube.com/watch?v=OYZNk7Z9s6I&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=17) (13:36)

18. [What do I need to know about the pandas index? (Part 2)](https://www.youtube.com/watch?v=15q-is8P_H4&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=18) (10:38)

19. [How do I select multiple rows and columns from a pandas DataFrame?](https://www.youtube.com/watch?v=xvpNA7bC8cs&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=19) (21:46)

20. [When should I use the "inplace" parameter in pandas?](https://www.youtube.com/watch?v=XaCSdr7pPmY&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=20) (10:18)

21. [How do I make my pandas DataFrame smaller and faster?](https://www.youtube.com/watch?v=wDYDYGyN_cw&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=21) (19:05)

22. [How do I use pandas with scikit-learn to create Kaggle submissions?](https://www.youtube.com/watch?v=ylRlGCtAtiE&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=22) (13:25)

23. [More of your pandas questions answered!](https://www.youtube.com/watch?v=oH3wYKvwpJ8&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=23) (19:23)

24. [How do I create dummy variables in pandas?](https://www.youtube.com/watch?v=0s_1IsROgDc&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=24) (13:13)

25. [How do I work with dates and times in pandas?](https://www.youtube.com/watch?v=yCgJGsg0Xa4&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=25) (10:20)

26. [How do I find and remove duplicate rows in pandas?](https://www.youtube.com/watch?v=ht5buXUMqkQ&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=26) (9:47)

27. [How do I avoid a SettingWithCopyWarning in pandas?](https://www.youtube.com/watch?v=4R4WsDJ-KVc&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=27) (13:29)

28. [How do I change display options in pandas?](https://www.youtube.com/watch?v=yiO43TQ4xvc&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=28) (14:55)

29. [How do I create a pandas DataFrame from another object?](https://www.youtube.com/watch?v=-Ov1N1_FbP8&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=29) (14:25)

30. [How do I apply a function to a pandas Series or DataFrame?](https://www.youtube.com/watch?v=P_q0tkYqvSk&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=30) (17:57)

31. **Bonus:** [How do I use the MultiIndex in pandas?](https://www.youtube.com/watch?v=tcRGa2soc-c&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=31) (25:00)

32. **Bonus:** [How do I merge DataFrames in pandas?](https://www.youtube.com/watch?v=iYWKfUOtGaw&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=32) (21:48)

33. **Bonus:** [4 new time-saving tricks in pandas](https://www.youtube.com/watch?v=-NbY7E9hKxk&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=33) (14:50)

34. **Bonus:** [5 new changes in pandas you need to know about](https://www.youtube.com/watch?v=te5JrSCW-LY&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=34) (20:54)

35. **Bonus:** [My top 25 pandas tricks](https://www.youtube.com/watch?v=RlIiVeig3hc&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=35) (27:37)

36. **Bonus:** [21 more pandas tricks](https://www.youtube.com/watch?v=tWFQqaRtSQA&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=36) (24:39)

37. **Bonus:** [Data Science Best Practices with pandas (PyCon 2019)](https://www.youtube.com/watch?v=dPwLlJkSHLo&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=37) (1:44:16)

38. **Bonus:** [Your pandas questions answered! (webcast)](https://www.youtube.com/watch?v=CWRKgBtZN18&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=38) (1:56:01)

## 📓 Jupyter Notebooks

- [Python pandas Q&A series](http://nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/pandas.ipynb) (videos 1 to 30)

- [How do I use the MultiIndex in pandas?](http://nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/pandas_multiindex.ipynb) (video 31)

- [How do I merge DataFrames in pandas?](http://nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/pandas_merge.ipynb) (video 32)

- [4 new time-saving tricks in pandas](http://nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/pandas_tricks.ipynb) (video 33)

- [5 new changes in pandas you need to know about](http://nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/pandas_changes.ipynb) (video 34)

- [My top 25 pandas tricks](http://nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/top_25_pandas_tricks.ipynb) (video 35)

- [21 more pandas tricks](http://nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/21_more_pandas_tricks.ipynb) (video 36)

- [Data Science Best Practices with pandas (PyCon 2019)](https://nbviewer.jupyter.org/github/justmarkham/pycon-2019-tutorial/blob/master/tutorial.ipynb) (video 37)

## 📊 Datasets

Filename | Description | Raw File | Original Source | Other

--- | --- | --- | --- | ---

[chipotle.tsv](data/chipotle.tsv) | Online orders from the Chipotle restaurant chain | [bit.ly/chiporders](http://bit.ly/chiporders) | [The Upshot](https://github.com/TheUpshot/chipotle) | [Upshot article](http://www.nytimes.com/interactive/2015/02/17/upshot/what-do-people-actually-order-at-chipotle.html)

[drinks.csv](data/drinks.csv) | Alcohol consumption by country | [bit.ly/drinksbycountry](http://bit.ly/drinksbycountry) | [FiveThirtyEight](https://github.com/fivethirtyeight/data/tree/master/alcohol-consumption) | [FiveThirtyEight article](http://fivethirtyeight.com/datalab/dear-mona-followup-where-do-people-drink-the-most-beer-wine-and-spirits/)

[imdb_1000.csv](data/imdb_1000.csv) | Top rated movies from IMDb | [bit.ly/imdbratings](http://bit.ly/imdbratings) | [IMDb](http://www.imdb.com/search/title?groups=top_1000&sort=user_rating&view=simple) | [Web scraping script](https://github.com/justmarkham/DAT5/blob/master/code/08_web_scraping.py)

[stocks.csv](data/stocks.csv) | Small dataset of stock prices | [bit.ly/smallstocks](http://bit.ly/smallstocks) | [DataCamp](https://www.datacamp.com/courses/manipulating-dataframes-with-pandas?tap_a=5644-dce66f&tap_s=280411-a25fc8) | 

[titanic_test.csv](data/titanic_test.csv) | Testing set from Kaggle's Titanic competition | [bit.ly/kaggletest](http://bit.ly/kaggletest) | [Kaggle](https://www.kaggle.com/c/titanic) | [Data dictionary](https://www.kaggle.com/c/titanic/data)

[titanic_train.csv](data/titanic_train.csv) | Training set from Kaggle's Titanic competition | [bit.ly/kaggletrain](http://bit.ly/kaggletrain) | [Kaggle](https://www.kaggle.com/c/titanic) | [Data dictionary](https://www.kaggle.com/c/titanic/data)

[u.data](data/u.data) | Movie ratings by MovieLens users | [bit.ly/movielensdata](http://bit.ly/movielensdata) | [GroupLens](http://grouplens.org/datasets/movielens/100k/) | [Data dictionary](http://files.grouplens.org/datasets/movielens/ml-100k-README.txt)

[u.item](data/u.item) | Movie information from MovieLens | [bit.ly/movieitems](http://bit.ly/movieitems) | [GroupLens](http://grouplens.org/datasets/movielens/100k/) | [Data dictionary](http://files.grouplens.org/datasets/movielens/ml-100k-README.txt)

[u.user](data/u.user) | Demographic information about MovieLens users | [bit.ly/movieusers](http://bit.ly/movieusers) | [GroupLens](http://grouplens.org/datasets/movielens/100k/) | [Data dictionary](http://files.grouplens.org/datasets/movielens/ml-100k-README.txt)

[ufo.csv](data/ufo.csv) | Reports of UFO sightings from 1930-2000 | [bit.ly/uforeports](http://bit.ly/uforeports) | [National UFO Reporting Center](http://www.nuforc.org/webreports.html) | [Web scraping script](https://github.com/josiahdavis/josiahdavis.github.io/blob/master/supporting%20material/get_ufo_data.py)