| Les deux révisions précédentes Révision précédente Prochaine révision | Révision précédente Prochaine révisionLes deux révisions suivantes |
| teaching:progappchim:pandas [2021/01/31 17:55] – [Exemples divers] villersd | teaching:progappchim:pandas [2021/03/02 11:07] – [Exemples divers] villersd |
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| ===== Références ===== | ===== Références ===== |
| * [[https://www.tutorialspoint.com/python_pandas/index.htm]] | * [[https://www.tutorialspoint.com/python_pandas/index.htm]] |
| | * [[https://towardsdatascience.com/top-4-repositories-on-github-to-learn-pandas-1008cb769f77|Top 4 Repositories on GitHub to Learn Pandas - Some of the most popular repositories to brush up on Pandas for beginners and experts alike]] Byron Dolon, Medium, Jul 21, 2020 |
| | * [[https://github.com/guipsamora/pandas_exercises|GitHub - guipsamora/pandas_exercises: Practice your pandas skills!]] |
| | * [[https://github.com/justmarkham/pandas-videos|GitHub - justmarkham/pandas-videos: Jupyter notebook and datasets from the pandas Q&A video series]] |
| | * [[https://github.com/ajcr/100-pandas-puzzles|GitHub - ajcr/100-pandas-puzzles: 100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)]] |
| | * [[https://github.com/justmarkham/pycon-2019-tutorial|GitHub - justmarkham/pycon-2019-tutorial: Data Science Best Practices with pandas]] |
| * [[https://medium.com/@devopslearning/introduction-to-pandas-for-data-analysis-c14bb9b1c21b]] (limité) | * [[https://medium.com/@devopslearning/introduction-to-pandas-for-data-analysis-c14bb9b1c21b]] (limité) |
| * [[http://www.firstpythonnotebook.org/index.html|First Python Notebook. A step-by-step guide to analyzing data with Python and the Jupyter Notebook]] (The course will teach you how to use pandas to read, filter, join, group, aggregate and rank structured data. You will also learn how to record, remix and republish your analysis using the Jupyter Notebook) → commencer au chapitre 3 "Import pandas into a Jupyter Notebook" | * [[http://www.firstpythonnotebook.org/index.html|First Python Notebook. A step-by-step guide to analyzing data with Python and the Jupyter Notebook]] (The course will teach you how to use pandas to read, filter, join, group, aggregate and rank structured data. You will also learn how to record, remix and republish your analysis using the Jupyter Notebook) → commencer au chapitre 3 "Import pandas into a Jupyter Notebook" |
| * [[https://towardsdatascience.com/effectively-visualize-data-across-time-to-tell-better-stories-2a2c276e031e|Effectively visualize data across time to tell better stories]] (Pandas & Plotly) | * [[https://towardsdatascience.com/effectively-visualize-data-across-time-to-tell-better-stories-2a2c276e031e|Effectively visualize data across time to tell better stories]] (Pandas & Plotly) |
| * [[https://medium.com/analytics-vidhya/statistical-analysis-in-python-using-pandas-27c6a4209de2|Statistical Analysis in Python using Pandas]] Tanvi Penumudy, Medium, dec 31, 2020 | * [[https://medium.com/analytics-vidhya/statistical-analysis-in-python-using-pandas-27c6a4209de2|Statistical Analysis in Python using Pandas]] Tanvi Penumudy, Medium, dec 31, 2020 |
| | * [[https://towardsdatascience.com/an-ultimate-cheat-sheet-for-data-visualization-in-pandas-f7bc239c9937|An Ultimate Cheat Sheet for Data Visualization in Pandas - All the Basic Types of Visualization That Is Available in Pandas and Some Advanced Visualization That Are Extremely Useful and Time Savers]] Rashida Nasrin Sucky, Medium, 15/02/2021 (dataset, jupyter) |
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