Brandon Rhodes - Pandas From The Ground Up - PyCon 2015 

This has to be one of the best videos introductions to Pandas out there, the simple structure of a dataset of movies provided the well thought exercises to test knowledge and to easily see the power of the library. My applause to Brandon I unlocked a new awesome tool to use.

Wow...this guy is a good teacher! Extremely valuable tutorial on pandas.

Excellent training and teaching ! I wish Brandon was featured on every PyCon conference.

Absolutely excellent tutorial. If you're trying to become proficient in manipulating datasets in Python, this is your video. Really, really good.

Excellent introduction to Pandas!!! It's a long one, but it's certainly worth it. I recommend watching it first, then going back to rework the examples later.

37:10 sort is replaced with sort_values in newer versions

16:00 -- Loading titles.csv and cast.csv 19:32 -- Basic dataframe operations [ len(df), df.head(), df.tail(), selecting columns, 28:08 - Compute on series data, 30:13 - Filter data, 36:53 - Sorting, 38:08 - Basic maneuvers cheat sheet, 40:06 - Filtering dataframe based on null values ] 45:15 -- String operations 48:30 -- [ series.value_counts(), series.sort_index() ] 53:57 -- Some plot basics 1:00:00 -- Indexes [ 1:05:07 - df.set_index(['column']), 1:06:30 - df.loc[], 1:10:42 - multiple indexes, 1:12:20 - Multiple lookup in a multi-indexed dataframe, 1:13:18 - df.reset_index(), 1:51:41 - Index append example ] 1:21:43 -- Grouping [ 1:28:42 - Groupby custom columns that are instantly created ] 1:33:47 -- Stacking and Unstacking operations 1:55:22 -- Cheat sheet 1:55:36 -- Exercises 2:06:28 -- Datetime operation 2:08:29 -- Merge operation [ 2:14:44 - Merging a table with itself ] 2:12:22 -- Pivot operation 2:19:20 -- Data cleanup operation

For anyone having trouble getting the .csv files: Don't download the zip from the slide url, it's incomplete. Download it from github.com/brandon-rhodes/pycon-pandas-tutorial and follow the readme.

Great tutorial! When you 'unstack' the last time (at 1:50:00) Pandas is doing what you want (many columns with 1 row of data). Note that's why when you did g['extra'] it added a 'row', which was actually a column (how the square bracket assign normally works).

The Github link to the materials: github.com/brandon-rhodes/pycon-pandas-tutorial/

Effective tutor. Liked a lot the way of speaking about Pandas

18 downvotes Please explain what did you miss on this absolutely *free* & *amazing* tutorial

I am enjoying it so far but after watching another course I understand that "div" operator (mentioned here around the 29th minute) is nothing else but a floor division rather than the truncation (although it provides the very same results for positive numbers). To mention more, python 3.6+ (at least what I know of) will have two operations that work well with each other: "//" and "%" and these two will complement each other in obtaining an original number using the following equation and as an example using a following fraction where we let n to be a nominator and d to be a denominator: (n/d) , n = d * (n // d) + n % d . I hope it helps!

1:37:46 my respect for the man elevated immensely... 1:49:14 even more respect....

i usually don't trust anyone who pronounces it "dah-ta", but this guy is cool

Best pandas indicator ever

Aspire to be Web Developer ( Web Application Developer / Tool Builder ). While I'm just starting out, I'm wrestling with Python and Data Presentation in HTML. Hopefully this video will assist in that area.Thanks for sharing...

Informative, Entertaining and Clever. What more can you ask for?

For a collection of 18+ pandas video tutorials, and more, see this GitHub repo: github.com/tommyod/awesome-pandas

Outstanding Tutorial!!!

Finally got there.... DON'T go to the releases directory as per the slides in the video! Go to github.com/brandon-rhodes/pycon-pandas-tutorial and download the zip with the button on the right. Then follow the "Detailed instructions" at the bottom which include the data file downloads. BTW I have no idea where the slides are they are not on speakerdeck (and it's search facility is crap, does an OR so you get long long listings).

Great stuff! Thanks Brandon

I love this guy. He is like Sigmund Freud from python.

Anyone else find that they have fewer titles than he does? Followed the instructions on his github..

Tom Cruise comes out in the summer, this guy awesome!

Brilliant!!

I am getting an error when running the data frames in the first example even when using the encoding='utf-8' anyone have this issues?

Where can I get the above data set can any one share the link?

The Tutorial is great. However when I try to run the BUILD.py to convert the data file. I found the following error : No such file or directory:''genres.list.gz" Any idea how to solve ? Would any one want to send me the csv file ? Thanks !

where can i get the data set of the above video?

I am not able to see the data/titles.csv file in the github link given by Brandon. Has it been moved somewhere else? Can someone upload those files and send a link to it?

I'm going to do a silly comment please don't take it seriously but I did a most casted actor as 'Himself' and the top result came to be 'Adolf Hitler', where is his IMDb page?

The ftp berlin site with the 4 imdb files wants authentication - popup asking for username and password. Any Help?

I can't even do the first thing in the ipython notebook. Hitting enter does absolutely nothing but jump to the next line and wait for me to type more. What is wrong here? Why can't I do a single thing?

awesome

I have an error on the forst exercise : File data/cast.csv does not exist Where do I get that ?

Is this video stil up-to-date to understand Pandas ore someone can suggest something better? I'can't find the data/titles.csv (the zip file desappeared..)

how do we get data/titles.csv?

I cannot find "data" folder.

I watched nearly all available introductions to pandas here on youtube... If you found this video, you can stop searching. Brandon is an awesome teacher and the lecture itself is pure gold. The 2,5 hours are well spend.

The link he gives in the slides uses code that is depreciated. Here is the current link github.com/brandon-rhodes/pycon-pandas-tutorial

where can I find the datasets used in this tutorial?

Anyone watching this in modern times: I found I had to use pd.read_csv() rather than pd.DataFrame.from_csv() (I think read_csv is deprecated) sort() has been replaced with sort_values() to sort by columns, and sort_index() to sort by index.

Can someone please upload the datasets (in the form of .csv into zip file) and share the link? This will be really helpful .

This is *the best* tutorial on pandas that I've taken. My coursera course didn't covered pandas properly so I was actually learning it in bits and pieces. This tutorial is to the rescue. The most in-depth tutorial on pandas. This is premium education. Okay, I'm gonna stop now lol

The Github repository contains all of the Notebooks, but not the data, presumably because it is massive. IIt does include a script to download it for you, (see the README). It takes ages to download, so run it in the background while you are watching this.

By far the best tutorial on Pandas. Brandon's energy is remarkable. Not once I got bored or lost during the session.

Incredible lecture, with accompanying exercises thoughtfully conceived and well-integrated. Bravo!

I've seen Many tutorials on Pandas, but this one stands out. Brandon's a phenomenal teacher. A truly gifted one. I wish many more tutorials from him.

I don't think the BUILD.py handles utf-8 correctly in recent versions of python (the resulting csv files didn't contain utf-8 text)

Thank you for posting this tutorial. I've been struggling with pandas but hopefully now I get to know a bunch of things from this talk.

Brandon is a legend! This is the best teacher EVER!!! Thank you so much!!!

A truly excellent tutorial - many thanks, Brandon!

If you get an encoding error even whilst using encoding='utf-8' , try using encoding='ISO-8859-1', fixed the problem for me

got this errror when i tried to build.py is this normal? UnicodeEncodeError: 'charmap' codec can't encode character '\x99' in position 38: character maps to the 3 csv is there but i'm not sure if its going to be the same

Brandon and Jake made the PyCon 2015 a perfect one.

@23:20 The B-key works if Settings/Tex Editor Key Map is set to 'emacs' in JupyterLab. It does not work in mode 'default'.

If you are working with the latest anaconda,Sort method has been deprecated ,please use sort_value as described @ pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.sort_values.html

@2:05:03 He says we need to unstack first for the type, do the fraction, and then unstack for n in order to get the correct fractions, otherwise we have to do the steps 3 times, however, I checked and unstacking everything at once gives the same results. Is it an upgrade for pandas that allows us to do it now (2019) and it coulnd't be done before (2015)?

Kudos Brandon, a really excellent tutorial. A great intro to pandas and great inside info. Thank you!

Great tutorial, finally a Pandas tutorial in a reasonable pace :)

great tutorial, thank you, lively and full of choice insights :)

Really good tutorial! I didn't know anything about pandas and could follow and complete all the exercises. Nice work Brandon :)

Can the Jupyter Notebook of this course be shared here. I would like to practice the exercises in this session.

Was looking forward to this but can't get it up and running. :(

Excellent video...I wish I find some more training materials of such high quality

Best pandas tutorial and awesome notebooks for practice i've seen . Thank you very much Brandon Rhodes!

I cannot find the data folder in the github ripo

Start this tutorial right from Brandon's github - This way you will get the video, all notebooks, and the right input data for your DataFrames. github.com/brandon-rhodes/pycon-pandas-tutorial

Wow... what a great crash course to Pandas

There is no 'data/titles.csv' and 'data/cast.csv' file in the tutorials folder. Where do I get them from?

Great tutorial on Pandas, takes it at a good pace with all the exercises and solutions available. Great teaching style, thanks a load

Great stuff! The amount of work put in is incredible! I am only into my first hour, but i really love that we have exercises (a bunch of them!!) to work with and seal pandas into one's head. Thank you so much!

Anyone else get this error? $ python BUILD.py File "BUILD.py", line 4 ^ SyntaxError: invalid syntax

36:46 people have names but movies have a title......hahaha....awesome tutorial..!!

Where do i get this file from ? This one where he is typing all this.

This is the best Pandas tutorial I found on RU-vid! Well worth the time to watch!

Wonderful tutorial.

Very helpful, Brandon. Thank you!

Excellent job.

I thought I knew Pandas well, but still learned so much!

This is a great exercise. On the other hand, the guide on Github is not for Windows users. As I beginner, I spent 3-4 hours to import the dataset and failed. The guide on Github assumes everyone is using Linux or Mac OS. With the help of an expert, I could import and used this dataset. It's so great!

This video was super helpful, thank you!

Thanks a lot, useful and entertaining...

Outstanding video. One of the best 'Introductions' to Pandas !

He's a great teacher! It was a well spent 2.5 hrs.

Brandon Rhodes, thank you for the amazing session.

Still one of the best tutorials for Pandas.

trying to do the accompanying exercises but any question relating to the "cast.csv" dataset takes an extremely long time to execute as this file seems to be massive. Anyone else have the same problem and is there a way around it to make doing the exercises quicker? awesome tutorial by the way!

%%time is not giving the time in jupyter

it is amazing, i can use the skill in my work,i love it.

That guy is awesome

Awesome lecture!!

great stuff, thanks for the lesson!

Amazing presentation!!

Brandon... excellent talk.

Brandon marry me

THANK YOU

Gold

Excellent tutorial. Particularly helpful for me was the explanation of unstack and stack.