A collection of resources for pandas (Python) and related subjects. Pull requests are very welcome!
Contents: This is an unofficial collection of resources for learning pandas, an open source Python library for data analysis. Here you will find videos, cheat-sheets, tutorials and books / papers. The curated list is divided into three parts:
The videos below were collected in July of 2018. They are all directly related to pandas, and the Level of a video is quantified roughly as follows:
Title | Speaker | Uploader | Time | Views | Year | Level |
---|---|---|---|---|---|---|
Pandas tutorial for Data Science | Bikram Kundu | - | > 01:20 | 2K+ | 2022 | :smiley: |
Python for Data Analysis using Pandas part 1 & part 2 [repo] | tommyod | na | 2:19 | 100 | 2019 | :smiley: |
Data Science Best Practices with pandas [repo] | Kevin Markham | PyCon | 3:23 | 1000 | 2019 | :smiley: |
Thinking like a Panda | Hannah Stepanek | PyCon | 0:36 | 700 | 2019 | :smiley: |
Analyzing Census Data with Pandas [repo] | Sergio Sánchez | PyCon | 3:15 | 600 | 2019 | :smiley: |
Pandas is for Everyone [repo] | Daniel Chen | PyCon | 3:18 | 600 | 2019 | :smiley: |
:star: Pandas From The Ground Up [repo] | Brandon Rhodes | PyCon 2015 | 2:24 | 91000 | 2015 | :smiley: |
Introduction Into Pandas [repo] | Daniel Chen | Python Tutorial | 1:28 | 46000 | 2017 | :smiley: |
Introduction To Data Analytics With Pandas [repo] | Quentin Caudron | Python Tutorial | 1:51 | 25000 | 2017 | :smiley: |
Pandas for Data Analysis [repo] | Daniel Chen | Enthought | 3:45 | 13000 | 2017 | :sweat_smile: |
Optimizing Pandas Code [repo] | Sofia Heisler | PyCon 2017 | 0:29 | 12000 | 2017 | :sweat_smile: |
A Visual Guide To Pandas | Jason Wirth | Next Day Video | 0:26 | 49000 | 2015 | :smiley: |
Analyzing and Manipulating Data with Pandas [repo] | Jonathan Rocher | Enthought | 3:33 | 22000 | 2016 | :smiley: |
Time Series Analysis [repo] | Aileen Nielsen | PyCon 2017 | 3:11 | 9000 | 2017 | :sweat_smile: |
Predicting sports winners with pandas | Robert Layton | PyCon Australia | 0:38 | 13000 | 2015 | :sweat_smile: |
Pandas from the Inside [repo] [2016 talk] | Stephen Simmons | PyData | 1:17 | 3000 | 2017 | :scream: |
Pandas part 1 & part 2 [repo] | Joris Van den Bossche | EuroSciPy | 3:03 | 1000 | 2017 | :smiley: |
Pandas: .head() to .tail() [repo] | Tom Augspurger | PyData | 1:26 | 3000 | 2016 | :sweat_smile: |
Performance Pandas (london) [repo] | Jeff Reback | PyData | 0:43 | 2000 | 2015 | :sweat_smile: |
Performance Pandas (NYC) [repo] | Jeff Reback | PyData | 1:26 | 3000 | 2015 | :sweat_smile: |
Python Data Science with pandas [repo] | Matt Harrison | JetBrainsTV | 1:09 | 2000 | 2018 | :smiley: |
What is the Future of Pandas [slides] | Jeff Reback | PyData | 0:31 | 4000 | 2017 | :smiley: |
Introduction to Python for Data Science [repo] | Skipper Seabold | PyData | 3:18 | 300 | 2018 | :smiley: |
Pandas for Better (and Worse) Data Science [repo] | Kevin Markham | PyCon 2018 | 3:21 | 3000 | 2018 | :smiley: |
Know of a recent, good video? Send a pull request! :+1:
Title | Speaker | Uploader | Time | Views | Keyword | Year | Level |
---|---|---|---|---|---|---|---|
NumPy Beginner [repo] | Alexandre Chabot LeClerc | Enthought | 2:47 | 56000 | NumPy | 2016 | :sweat_smile: |
Machine Learning | Andreas Mueller & Sebastian Raschka | Enthought | 3:03 | 47000 | sklearn | 2016 | :sweat_smile: |
The Python Visualization Landscape | Jake VanderPlas | PyCon 2017 | 0:33 | 21000 | python | 2017 | :smiley: |
JupyterLab: Building Blocks for Interactive Computing | Brian Granger | Enthought | 0:29 | 28000 | jupyter | 2016 | :smiley: |
Machine Learning with Scikit Learn [repo] | Andreas Mueller & Kyle Kastner | Enthought | 3:22 | 48000 | sklearn | 2015 | :sweat_smile: |
Machine Learning for Time Series Data in Python | Brett Naul | Enthought | 0:24 | 24000 | cesium | 2016 | :smiley: |
Computational Statistics [repo] | Allen Downey | Enthought | 2:05 | 10000 | scipy | 2017 | :sweat_smile: |
Time Series Analysis [repo] | Aileen Nielsen | PyCon 2017 | 3:11 | 9000 | pandas | 2017 | :sweat_smile: |
Learning TensorFlow | Robert Layton | PyCon Australia | 0:40 | 18000 | tensorflow | 2016 | :sweat_smile: |
JupyterHub: Deploying Jupyter Notebooks | Min Ragan Kelley & Thomas Kluyver | PyData | 1:36 | 17000 | jupyter | 2016 | :smiley: |
Applied Time Series Econometrics | Jeffrey Yau | PyData | 1:39 | 17000 | statsmodels | 2016 | :sweat_smile: |
Machine Learning with scikit learn [repo] | Andreas Mueller & Alexandre Gram | Enthought | 3:10 | 8000 | sklearn | 2017 | :sweat_smile: |
Introduction to Numerical Computing with NumPy | Dillon Niederhut | Enthought | 2:27 | 8000 | NumPy | 2017 | :smiley: |
Dask - A Pythonic Distributed Data Science Framework | Matthew Rocklin | PyCon 2017 | 0:46 | 7000 | dask | 2017 | :sweat_smile: |
Introduction to Statistical Modeling with Python [repo] | Christopher Fonnesbeck | PyCon 2017 | 3:19 | 7000 | scipy | 2017 | :sweat_smile: |
Fully Convolutional Networks for Image Segmentation | Daniil Pakhomov | Enthought | 0:20 | 7000 | scipy | 2017 | :smiley: |
Exploratory data analysis in python [repo] | Chloe Mawer & Jonathan Whitmore | PyCon 2017 | 2:54 | 7000 | scipy | 2017 | :smiley: |
Libraries for Deep Learning with Sequences | Alex Rubinsteyn | PyData | 0:44 | 23000 | scipy | 2015 | :sweat_smile: |
Numba - Tell Those C++ Bullies to Get Lost [repo] | Gil Forsyth & Lorena Barba | Enthought | 2:25 | 5000 | numba | 2017 | :sweat_smile: |
Deploying Interactive Jupyter Dashboards | Philipp Rudiger | Enthought | 0:18 | 5000 | jupyter | 2017 | :sweat_smile: |
Data Science Using Functional Python | Joel Grus | PyData | 0:44 | 18000 | python | 2015 | :sweat_smile: |
Anatomy of matplotlib [repo] | Benjamin Root & Joe Kington | Enthought | 3:18 | 18000 | matplotlib | 2015 | :sweat_smile: |
Anatomy of matplotlib [repo] | Benjamin Root | Enthought | 3:02 | 4000 | matplotlib | 2017 | :sweat_smile: |
Data Science is Software [repo] | Peter Bull & Isaac Slavitt | Enthought | 2:12 | 9000 | jupyter | 2016 | :smiley: |
Machine Learning with Scikit Learn [repo] | Jake VanderPlas | PyData | 1:34 | 16000 | sklearn | 2015 | :sweat_smile: |
Using Jupyter notebooks [repo] | Ioanna Ioannou | PyCon Australia | 0:28 | 8000 | jupyter | 2016 | :sweat_smile: |
Parallel Python: Analyzing Large Datasets [repo] | Matthew Rocklin | Enthought | 3:05 | 7000 | scipy | 2016 | :scream: |
Keynote: Project Jupyter | Brian Granger | Enthought | 0:48 | 7000 | jupyter | 2016 | :sweat_smile: |
matplotlib beginner tutorial [repo] | Nicolas Rougier | Enthought | 2:59 | 6000 | matplotlib | 2016 | :sweat_smile: |
Awesome Big Data Algorithms | Titus Brown | Next Day Video | 0:39 | 41000 | python | 2013 | :scream: |
All About Jupyter | Brian Granger | PyData | 0:39 | 11000 | jupyter | 2015 | :sweat_smile: |
PyMC: Markov Chain Monte Carlo | Chris Fonnesbeck | Enthought | 0:20 | 9000 | pyMC | 2014 | :sweat_smile: |
Jupyter Advanced Topics Tutorial [repo] | Jonathan Frederic & Matthias Bussonier | Enthought | 2:48 | 4000 | jupyter | 2015 | :scream: |
Using randomness to make code much faster | Rachel Thomas | SF Python | 0:54 | 1000 | scipy | 2017 | :sweat_smile: |
Python Profiling & Performance | Mahmoud Hashemi | SF Python | 0:28 | 1000 | python | 2016 | :sweat_smile: |
Using List Comprehensions and Generator Expressions | Trey Hunner | PyCon 2018 | 3:21 | 3000 | python | 2018 | :sweat_smile: |
Foundations of Numerical Computing | Scott Sanderson | PyCon 2018 | 3:22 | 1000 | python | 2018 | :sweat_smile: |
Title | Speaker | Uploader | Time | Views | Keyword | Year | Level |
---|---|---|---|---|---|---|---|
:star: So you want to be a Python expert? | James Powell | PyData | 1:54 | 28000 | python | 2017 | :scream: |
:star: Transforming Code into Beautiful, Idiomatic Python | Raymond Hettinger | Next Day Video | 0:48 | 340000 | python | 2013 | :smiley: |
:star: Builtin Superheroes | David Beazley | David Beazley | 0:44 | 12000 | python | 2016 | :sweat_smile: |
How to become a Data Scientist in 6 months | Tetiana Ivanova | PyData | 0:56 | 148000 | misc | 2016 | :smiley: |
Modern Dictionaries | Raymond Hettinger | SF Python | 1:07 | 44000 | python | 2016 | :sweat_smile: |
Keynote on Concurrency | Raymond Hettinger | SF Python | 1:13 | 15000 | python | 2017 | :sweat_smile: |
The Fun of Reinvention | David Beazley | David Beazley | 0:52 | 11000 | python | 2017 | :scream: |
Being a Core Developer in Python | Raymond Hettinger | SF Python | 1:02 | 19000 | python | 2016 | :smiley: |
Visualizing Geographic Data | Christopher Roach | PyData | 0:31 | 14000 | python | 2016 | :smiley: |
Python's Class Development Toolkit | Raymond Hettinger | Next Day Video | 0:45 | 80000 | python | 2013 | :sweat_smile: |
The Other Async (Threads + Async = ❤️) - YouTube | David Beazley | David Beazley | 0:47 | 5000 | python | 2017 | :scream: |
Functional Programming with Python | Mike Müller | Next Day Video | 0:27 | 44000 | python | 2013 | Novice |
Building a Recommendation Engine using Python | Anusua Trivedi | PyData | 0:37 | 11000 | python | 2015 | Novice |
Iterations of Evolution | David Beazley | David Beazley | 0:34 | 2000 | python | 2017 | Novice |
"Good Enough" IS Good Enough! | Alex Martelli | SF Python | 0:53 | 4000 | python | 2016 | Novice |
Automating Code Quality | Kyle Knapp | PyCon 2018 | 0:30 | 3000 | python | 2018 | :sweat_smile: |
The books below are perhaps of an even more general nature.
Every video is below.
Title | Speaker | Uploader | Time | Views | Keyword | Year | Level |
---|---|---|---|---|---|---|---|
How to become a Data Scientist in 6 months | Tetiana Ivanova | PyData | 0:56 | 148000 | misc | 2016 | :snake: |
Introduction Into Pandas | Daniel Chen | Python Tutorial | 1:28 | 46000 | pandas | 2017 | :snake: |
So you want to be a Python expert? | James Powell | PyData | 1:54 | 28000 | python | 2017 | :snake::snake::snake: |
NumPy Beginner [repo] | Alexandre Chabot LeClerc | Enthought | 2:47 | 56000 | NumPy | 2016 | :snake: :snake: |
Introduction To Data Analytics With Pandas | Quentin Caudron | Python Tutorial | 1:51 | 25000 | pandas | 2017 | :snake: |
Transforming Code into Beautiful, Idiomatic Python | Raymond Hettinger | Next Day Video | 0:48 | 340000 | python | 2013 | :snake: |
Machine Learning | Andreas Mueller & Sebastian Raschka | Enthought | 3:03 | 47000 | sklearn | 2016 | :snake: :snake: |
Pandas From The Ground Up [repo] | Brandon Rhodes | PyCon 2015 | 2:24 | 91000 | pandas | 2015 | :snake: :snake: |
Modern Dictionaries | Raymond Hettinger | SF Python | 1:07 | 44000 | python | 2016 | :snake: :snake: |
The Python Visualization Landscape | Jake VanderPlas | PyCon 2017 | 0:33 | 21000 | python | 2017 | :snake: |
Keynote on Concurrency | Raymond Hettinger | SF Python | 1:13 | 15000 | python | 2017 | :snake::snake: |
Pandas for Data Analysis [repo] | Daniel Chen | Enthought | 3:45 | 13000 | pandas | 2017 | :snake::snake: |
JupyterLab: Building Blocks for Interactive Computing | Brian Granger | Enthought | 0:29 | 28000 | jupyter | 2016 | :snake: |
Optimizing Pandas Code for Speed and Efficiency | Sofia Heisler | PyCon 2017 | 0:29 | 12000 | pandas | 2017 | :snake: :snake: |
A Visual Guide To Pandas | Jason Wirth | Next Day Video | 0:26 | 49000 | pandas | 2015 | :snake: |
Machine Learning with Scikit Learn [repo] | Andreas Mueller & Kyle Kastner | Enthought | 3:22 | 48000 | sklearn | 2015 | :snake: :snake: |
Machine Learning for Time Series Data in Python | Brett Naul | Enthought | 0:24 | 24000 | cesium | 2016 | :snake: |
The Fun of Reinvention | David Beazley | David Beazley | 0:52 | 11000 | python | 2017 | :snake::snake::snake: |
Analyzing and Manipulating Data with Pandas [repo] | Jonathan Rocher | Enthought | 3:33 | 22000 | pandas | 2016 | :snake: |
Computational Statistics [repo] | Allen Downey | Enthought | 2:05 | 10000 | scipy | 2017 | :snake: :snake: |
Being a Core Developer in Python | Raymond Hettinger | SF Python | 1:02 | 19000 | python | 2016 | :snake: |
Time Series Analysis [repo] | Aileen Nielsen | PyCon 2017 | 3:11 | 9000 | pandas | 2017 | :snake: :snake: |
Learning TensorFlow | Robert Layton | PyCon Australia | 0:40 | 18000 | tensorflow | 2016 | :snake: :snake: |
JupyterHub: Deploying Jupyter Notebooks | Min Ragan Kelley & Thomas Kluyver | PyData | 1:36 | 17000 | jupyter | 2016 | :snake: |
Applied Time Series Econometrics | Jeffrey Yau | PyData | 1:39 | 17000 | statsmodels | 2016 | :snake: :snake: |
Machine Learning with scikit learn [repo] | Andreas Mueller & Alexandre Gram | Enthought | 3:10 | 8000 | sklearn | 2017 | :snake: :snake: |
Introduction to Numerical Computing with NumPy | Dillon Niederhut | Enthought | 2:27 | 8000 | NumPy | 2017 | :snake: |
Dask - A Pythonic Distributed Data Science Framework | Matthew Rocklin | PyCon 2017 | 0:46 | 7000 | dask | 2017 | :snake: :snake: |
Introduction to Statistical Modeling with Python [repo] | Christopher Fonnesbeck | PyCon 2017 | 3:19 | 7000 | scipy | 2017 | :snake: :snake: |
Fully Convolutional Networks for Image Segmentation | Daniil Pakhomov | Enthought | 0:20 | 7000 | scipy | 2017 | :snake: |
Exploratory data analysis in python [repo] | Chloe Mawer & Jonathan Whitmore | PyCon 2017 | 2:54 | 7000 | scipy | 2017 | :snake: |
Visualizing Geographic Data | Christopher Roach | PyData | 0:31 | 14000 | python | 2016 | :snake: |
Builtin Superheroes | David Beazley | David Beazley | 0:44 | 12000 | python | 2016 | :snake: :snake: |
Python's Class Development Toolkit | Raymond Hettinger | Next Day Video | 0:45 | 80000 | python | 2013 | :snake: :snake: |
Libraries for Deep Learning with Sequences | Alex Rubinsteyn | PyData | 0:44 | 23000 | scipy | 2015 | :snake: :snake: |
The Other Async (Threads + Async = ❤️) - YouTube | David Beazley | David Beazley | 0:47 | 5000 | python | 2017 | :snake: :snake: :snake: |
Numba - Tell Those C++ Bullies to Get Lost [repo] | Gil Forsyth & Lorena Barba | Enthought | 2:25 | 5000 | numba | 2017 | :snake: :snake: |
Deploying Interactive Jupyter Dashboards | Philipp Rudiger | Enthought | 0:18 | 5000 | jupyter | 2017 | :snake: :snake: |
Eyal Trabelsi - Practical Optimisations for Pandas | Eyal Trabelsi | Europython | 0:45 | 5000 | jupyter | 2020 | :snake: :snake: |
Data Science Using Functional Python | Joel Grus | PyData | 0:44 | 18000 | python | 2015 | :snake: :snake: |
Pandas from the Inside | Stephen Simmons | PyData | 1:20 | 9000 | pandas | 2016 | :snake: :snake: :snake: |
Anatomy of matplotlib [repo] | Benjamin Root & Joe Kington | Enthought | 3:18 | 18000 | matplotlib | 2015 | :snake: :snake: |
Anatomy of matplotlib [repo] | Benjamin Root | Enthought | 3:02 | 4000 | matplotlib | 2017 | :snake: :snake: |
Data Science is Software [repo] | Peter Bull & Isaac Slavitt | Enthought | 2:12 | 9000 | jupyter | 2016 | :snake: |
Machine Learning with Scikit Learn [repo] | Jake VanderPlas | PyData | 1:34 | 16000 | sklearn | 2015 | Novice |
Using Jupyter notebooks | Ioanna Ioannou | PyCon Australia | 0:28 | 8000 | jupyter | 2016 | Novice |
Parallel Python: Analyzing Large Datasets [repo] | Matthew Rocklin | Enthought | 3:05 | 7000 | scipy | 2016 | Novice |
Functional Programming with Python | Mike Müller | Next Day Video | 0:27 | 44000 | python | 2013 | Novice |
Predicting sports winners with pandas and scikit-learn | Robert Layton | PyCon Australia | 0:38 | 13000 | pandas | 2015 | Novice |
Keynote: Project Jupyter | Brian Granger | Enthought | 0:48 | 7000 | jupyter | 2016 | Novice |
matplotlib beginner tutorial [repo] | Nicolas Rougier | Enthought | 2:59 | 6000 | matplotlib | 2016 | Novice |
Awesome Big Data Algorithms | Titus Brown | Next Day Video | 0:39 | 41000 | python | 2013 | Novice |
Pandas from the Inside | Stephen Simmons | PyData | 1:17 | 3000 | pandas | 2017 | Novice |
All About Jupyter | Brian Granger | PyData | 0:39 | 11000 | jupyter | 2015 | Novice |
Building a Recommendation Engine using Python | Anusua Trivedi | PyData | 0:37 | 11000 | python | 2015 | Novice |
Iterations of Evolution | David Beazley | David Beazley | 0:34 | 2000 | python | 2017 | Novice |
"Good Enough" IS Good Enough! | Alex Martelli | SF Python | 0:53 | 4000 | python | 2016 | Novice |
PyMC: Markov Chain Monte Carlo | Chris Fonnesbeck | Enthought | 0:20 | 9000 | pyMC | 2014 | Novice |
Jupyter Advanced Topics Tutorial [repo] | Jonathan Frederic & Matthias Bussonier | Enthought | 2:48 | 4000 | jupyter | 2015 | Novice |
Using randomness to make code much faster | Rachel Thomas | SF Python | 0:54 | 1000 | scipy | 2017 | Novice |
Python Profiling & Performance | Mahmoud Hashemi | SF Python | 0:28 | 1000 | python | 2016 | Novice |