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Hello HN, author here. If you've ever wanted to get into data analysis, this is my best attempt at getting you past that first hump. A lot of these concepts are

Hello HN, author here. If you've ever wanted to get into data analysis, this is my best attempt at getting you past that first hump. A lot of these concepts are easier than you might think.

bussiere 8y ago
Thanks for the tutorial, it's really what i was looking to give to some friends.
pyrenan 8y ago
Thanks for this. This is very useful for a beginner.
lesss365 8y ago
This is a perfect out-of-tutor-session reference for my novice data analysis pupils. Will be sharing with them later today. Thank you!
qwerty456127 8y ago
Thank you very much. I would certainly love to read more and more about Pandas (or anything) written this style and go deeper in the subject. Are you going to write more? Can you (or anybody) recommend where (a book, a YouTube channel, a website or whatever) do I continue from the point where you intro ends? As for now all I use of Pandas is a datetime-indexed array of real numbers + simple vector operations on its columns but I feel like I would like to take a learning/career path to becoming a Pandas expert.
- jalammar 8y ago
  A reasonable next step would be pick up a dataset that interests you (in a domain you're comfortable with) and explore it with pandas. Kaggle has a bunch of data sets (https://www.kaggle.com/datasets https://www.kaggle.com/datasets) in various domains. You can look at the "Kernels" where other users often use pandas to uncover insights and show you their process. Thanks for the kind words!
- happy-go-lucky 8y ago
  You may want to check this out: > Short hands-on challenges to perfect your data manipulation skills https://www.kaggle.com/learn/pandas https://www.kaggle.com/learn/pandas Also this: > Things in Pandas I Wish I'd Known Earlier http://nbviewer.jupyter.org/github/rasbt/python_reference/blob/master/tutorials/things_in_pandas.ipynb http://nbviewer.jupyter.org/github/rasbt/python_reference/bl...
- skadamat 8y ago
  Hey there, I'm involved with Dataquest and we have a Pandas and NumPy fundamentals course where we dive into more intermediate concepts like vectorization, key data structures, and the key functions. https://www.dataquest.io/course/pandas-fundamentals https://www.dataquest.io/course/pandas-fundamentals We use a similar approach to the OP. Lots of diagrams and visual aids and you always work with a real dataset.
reacharavindh 8y ago
Very pleasant to read. I will pass this to my wife who is an accounting professor trying to break ground into using Python/Pandas/Numpy instead of Stata. I really enjoyed your style of writing and use of visual examples. I wish for such an explainer for SQL. If you made that as a book, you can tun with my money.

Hello HN, author here. If you've ever wanted to get into data analysis, this is my best attempt at getting you past that first hump. A lot of these concepts are easier than you might think.

bussiere 8y ago

Thanks for the tutorial, it's really what i was looking to give to some friends.

pyrenan 8y ago

Thanks for this. This is very useful for a beginner.

lesss365 8y ago

This is a perfect out-of-tutor-session reference for my novice data analysis pupils. Will be sharing with them later today. Thank you!

qwerty456127 8y ago

Thank you very much. I would certainly love to read more and more about Pandas (or anything) written this style and go deeper in the subject. Are you going to write more? Can you (or anybody) recommend where (a book, a YouTube channel, a website or whatever) do I continue from the point where you intro ends? As for now all I use of Pandas is a datetime-indexed array of real numbers + simple vector operations on its columns but I feel like I would like to take a learning/career path to becoming a Pandas expert.

jalammar 8y ago
A reasonable next step would be pick up a dataset that interests you (in a domain you're comfortable with) and explore it with pandas. Kaggle has a bunch of data sets (https://www.kaggle.com/datasets https://www.kaggle.com/datasets) in various domains. You can look at the "Kernels" where other users often use pandas to uncover insights and show you their process. Thanks for the kind words!
happy-go-lucky 8y ago
You may want to check this out: > Short hands-on challenges to perfect your data manipulation skills https://www.kaggle.com/learn/pandas https://www.kaggle.com/learn/pandas Also this: > Things in Pandas I Wish I'd Known Earlier http://nbviewer.jupyter.org/github/rasbt/python_reference/blob/master/tutorials/things_in_pandas.ipynb http://nbviewer.jupyter.org/github/rasbt/python_reference/bl...
skadamat 8y ago
Hey there, I'm involved with Dataquest and we have a Pandas and NumPy fundamentals course where we dive into more intermediate concepts like vectorization, key data structures, and the key functions. https://www.dataquest.io/course/pandas-fundamentals https://www.dataquest.io/course/pandas-fundamentals We use a similar approach to the OP. Lots of diagrams and visual aids and you always work with a real dataset.

reacharavindh 8y ago

Very pleasant to read. I will pass this to my wife who is an accounting professor trying to break ground into using Python/Pandas/Numpy instead of Stata. I really enjoyed your style of writing and use of visual examples. I wish for such an explainer for SQL. If you made that as a book, you can tun with my money.