Data Analysis with Python for Excel Users - Full Course

Learn how to use Python and Pandas for data analysis. This course will be especially helpful if you have experience with Excel, but that is not required. Learn how to create pivot tables, work with data, and make visualizations using Python, Pandas, and Jupyter Notebook.
💻 Source Code & Datasets: github.com/ifrankandrade/pyth...
🔗 Datasets: drive.google.com/drive/folder...
✏️ Course developed by Frank Andrade.
🔗 KZbin Channel: / frankandrade5
🔗 PDF Python Cheat Sheet for this Course: artificialcorner.com/p/redeem...
🔗 My Complete Python Courses for Data Analysis & Data Science: www.udemy.com/user/frank-andr...
⭐️ Course Contents ⭐️
⌨️ (0:00:00) Intro
⌨️ (0:01:48) Install Python and Jupyter Notebook with Anaconda
⌨️ (0:03:53) Jupyter Notebook Interface
⌨️ (0:13:56) Cell Types and Cell Mode
⌨️ (0:21:34) Jupyter Notebook Shortcuts
⌨️ (0:26:39) Module 1 - Hello World
⌨️ (0:30:30) Data Type
⌨️ (0:39:10) Variables
⌨️ (0:46:53) Lists
⌨️ (1:11:14) Dictionaries
⌨️ (1:21:50) IF Statement
⌨️ (1:28:04) FOR Loop
⌨️ (1:33:49) Functions
⌨️ (1:40:59) Modules
⌨️ (1:44:41) Module 2 -Introduction to Pandas
⌨️ (1:51:08) How to create a dataframe
⌨️ (2:07:34) How to show a dataframe
⌨️ (2:14:24) Basic Attributes, Functions and Methods
⌨️ (2:26:17) Selecting One Column from a Dataframe
⌨️ (2:32:13) Selecting Two or More Columns from a Dataframe
⌨️ (2:37:50) Add New Column to a Dataframe (Simple Assignment)
⌨️ (2:47:51) Operations in dataframes
⌨️ (2:56:04) The value_counts() method
⌨️ (3:00:16) Sort a DataFrame with the sort_values() method
⌨️ (3:09:56) Module 3: Introduction to Pivot Tables in Pandas
⌨️ (3:14:42) The pivot() method
⌨️ (3:20:49) The pivot_table() method
⌨️ (3:29:00) Data Visualization with Pandas (New Dataset + Pivot Table)
⌨️ (3:38:38) Lineplot
⌨️ (3:43:05) Barplot
⌨️ (3:50:52) Piechart
⌨️ (3:54:36) Save Plot and Export Pivot Table
🎉 Thanks to our Champion and Sponsor supporters:
👾 Raymond Odero
👾 Agustín Kussrow
👾 aldo ferretti
👾 Otis Morgan
👾 DeezMaster
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[@quincylarsonmusic]

That is one gorgeous cheat sheet. Thanks for everything you're doing for the global developer community, Frank. This course is gold.

[@levarish]

Can you please share the link for the cheat sheet?

[@Thalescosta592]

@@levarish it's in the video description

[@AlexisAndradeMonteiro]

BEST PYTHON COURSE i EVER SEEN. i LITERALLY ENJOYED AND SPEND MY WEEKEND CONSUMING THESE CONTENT WITH PLEASURE. THANK YOU FOR YOUR MASSIVE SUPPORT FRANK

[@Tradewithsimpleminded]

Don't know where you watching this from my brother but I wished you all the best in life ❤️❤️

[@mrCetus]

That's the best content I've seen on jupyter and pandas so far! well done champ! I've spent my whole weekend going along on this course and I totally love it! Very well structured and full of examples you can run and you can test out on your own. had a minor set back on opening the csv file dgp but added the encoding parameter: df_gdp = pd.read_csv("gdp.csv" , encoding="latin-1")

[@ThePyCoach]

Thanks :)

[@nournissan1786]

I just finished this python course and I have to say it was so fascinating to learn about this language. Frank did a great job at breaking everything down !!

[@mansasow]

Thanks for this tutorial! It would have also been nice to show how to concatenate or merge multiples data frames (inner, left, right join).

[@dondata718]

Just finished this video. It is my first introduction to python and you did an excellent job. I appreciate this thanks

[@shishirdutt]

Hi Frank! Many thanks for creating this wonderful course. You have taken humungous efforts for creating such a long and flawless content for everyone to learn. Highly commendable efforts!!

[@victoriabraimoh8994]

Frank went all out with this course. perfect beginner course. hope we all make you proud

[@swagat457]

Amazing content Frank.. How effortlessly you explained everything in the most simplistic way.. Thank you

[@kku6749]

Best Tutorial on Python for Data Analytics I have seen so far... Your approach is commendable. Well done! I need to see more of your contents. This is good stuff!

[@malwalsabino519]

I am a decent Excel user who has been so reluctant to learn any programming language. Your video changed my mind and after few hours of watching this video, I feel I can learn the basics of python in a short period of time. Your teaching style is amazing and your ability to explain things is fascinating. Thank you so much.

[@marcoventura9451]

A very good begginer's course; it covers the basics of Python with Juipter Notebook IDE in a simple and understable way.

[@gimiemini3034]

I have just finished this. Love it. So easy to follow and Frank was amazing. best video so far.

[@dimasjimenez3396]

Extraordinary content, crystal clear explanation. Pure gold. We should be able to like the video a couple of times. Thanks a ton for such an wonderful content.

[@jessicaliu8885]

Great course! Thank you so much! Spent a half day finishing the course. Very Helpful!

[@imadias1926]

Best INSTRUCTOR with the best English accent that we can easily understand and you never miss any step for running Python, even though I'm a beginner but now I know How to use python because of this video 😍, some tutorial they skip some step and even we try to follow their instructions but we got lost 😊😊😊Thank you Instructor ❤

[@caessar_mando]

one of the best if not the best tutorial this channel has ever presented. Excellent job!

[@lcastellanosm]

I still didn't finish the full course but I already find it very useful and well explained. Thank you Frank!

[@boknows8263]

have you finished it by now?

[@gorkemoncul6565]

@@boknows8263 Not yet

[@boknows8263]

@@gorkemoncul6565 he will never finish it, he is watching TV now lol

[@robertspalding5635]

Frank Andrade, thank you for the best, and most helpful tutorial of this type and this subject that I have ever seen.

[@sindiso_ndlovu]

No words can express how great your work is, thank you so much

[@tim64163]

Fantastically explained, thank you so much. Clear, easy to understand and shows some good examples.

[@usuis8541]

GENSHIN PREACH

[@ajitmagar1195]

Nicely explained and step by step coverage of "whole" topic. ....Thank you Sir.

[@richardfinney2548]

Brilliant tutorial! You are a very gifted presenter.

[@CodewithAby]

Great course, broken down like ABC. Thanks Frank

[@michal.tomczyk]

Enjoyed every last second of it. Great job!

[@ItsTheBookah]

Thanks for the amazing tutorial Frank! For people getting the unicode error: df_gdp = pd.read_csv('gdp.csv', encoding='latin-1')

[@abdala-in-tech]

Thanks man!!

[@fififb8616]

Very clear and concise instructions! Thank you very much!

[@stathistsamis8964]

as a junior data analyst i found this video very useful keep going my friend!!!

[@youtubewzd2196]

The course is really good but has a few caveats: 1. The Dataframe CSV for the short .pivot() method demonstration is not included. 2. The file gdp.csv is in Windows-1252 encoding in the zip file. This cannot be imported into a Dataframe without prior recoding into UTF-8. 3. The .pivot_table() example throws a FutureWarning. I had to list all features in values=['Quantity', 'Rating',...] to make it working. The problem comes from the attempt to sum non-numerical values. So only include columns with numerical values in values=[ ].

[@priyavarshanrg700]

This Channel deserves 100M Subscribers Hats Off You Guys👏👏👏

[@anthonynjoroge4641]

From Kenya much Appreciated - Asante Sana-

[@geekyprogrammer4831]

I already know Frank for writing exceptional technical articles! Good to see you here too 😁😁

[@thepycoachES]

Nice meeting you on KZbin too! :)

[@nriezedichisom1676]

This was a refresher course for me but notwithstanding, I learnt a whole lot.. Well done

[@nriezedichisom1676]

You are an excellent teacher but your KZbin channel has very little content. Can you upload more videos?

[@thepycoachES]

@@nriezedichisom1676 Sure! More videos coming soon on my channel

[@leasunsun]

Watched it during Chrismas Holiday. Enjoyed it and learned something new. Thank you!

[@AmG895]

Thank you 🙏 you have explained so well. Amazing video. Learned a lot!

[@InnovativeIdeas-mp7up]

The presentation is engaging and makes it easy to follow the instructions.

[@TheAl217]

Thank you for taking the time to create this course and sharing your knowledge with others. Just some constructive criticism here, based on my experience using Excel for many years. In my opinion people looking to move to pandas from Excel are serious users of this package. I didn't find content here that will make me think I really need to move away from Excel to gain this capability. Also Excel's PowerQuery has a lot of powerful transformation capabilities. Instead of doing the visualizations, people may have benefitted more from examples covering merge, groupby, stack, unstack, melt, resampling and even how list comprehensions can be used to add columns based on conditions.

[@robertstahl8835]

My thoughts as well

[@selcukdoven]

Thanks for basic and effective course and plus English sound is perfect 👍

[@cesarramos3569]

Great video Frank!! regards from Peru

[@rafimaulana8294]

Definitely the best Python course for a data analyst who wants to level up from sql and excel only!!! Would recommend it!

[@focus1007]

Sir currently I am working in excel only..will this course help me in getting job? I mean is it sufficient to land a job as data analyst? Pls guide🙏

[@rafimaulana8294]

​@@focus1007 for an entry level actually a combination of sql+excel only is fine, but as you level up you'll eventually need Python/R. I was like that too at first.

[@focus1007]

@@rafimaulana8294 thankyou so much fr replying🙏...sir so acc to you ,can i start applying for data analyst with the knowledge of excel and SQL only? Or should i learn anything else also?

[@rafimaulana8294]

@@focus1007 Yes, but try learning any data viz either google data studio/tableau/power BI. This would make an extra bonus point and quite easy to learn.

[@focus1007]

@@rafimaulana8294 thankyou so much sir for replying..means a lot to me🙏

[@Tlholo7]

Love it. Thanks a lot, Frank! 🎉

[@valentindumitru6648]

very clear and simple explanations , thank you!

[@jmchisanga3]

I love this content it's well structured with lots of examples to make you understand and master it without any problem. 🇿🇲

[@giantdutchviking]

Did you happen to run into issues making a line graph? I used the provided code in the tutorial but keep getting errors I need matplotlib.

[@Delianur]

Excellent... thanks you mr Frank Andrade

[@elfridhasman4181]

Thank You Very Much, Much Much More❤️, Love From Indonesia

[@user-kj4ni1rx4b]

God bless you for this project, I learned a lot from it.

[@arpanrastogi2844]

Like the way you have explained the concepts - thanks Frank. Not sure if I missed out, but I could not find anything related to tuples between the timestamp 0:39:10 to 1:21:50. Is it explained later?

[@DJ-ct6so]

Excellent, very well explained. Very nice use of Jupyter notebooks. Many thanks for uploading.

[@culturapoliticaycomputador9999]

Thank you for share this! I recommend this video for everyone wants to learn some basics of python, numpy and pandas is awesome.

[@mohamad5005]

Great and simple to mind tutorial

[@timothyfleur7596]

Thank you very much, this was very informative and explained in detail!

[@amadikechidera2613]

Very nice course, you are truly blessed

[@seifaya3724]

good job Frank .. really it's very interesting highly recommended

[@KingLiongWong]

This is a very good course for me, help me a lot. Thank you very much.

[@kevinliew3916]

Great introduction for everyday use!

[@davidgitau8825]

Good learning here! The data should however be available for download to easily practice.

[@jasimmhj1526]

Amazing deep learning. Thankyou

[@belezaesaude1101]

Estou muito feliz por ter me inscrito e ter acesso a este conteúdo.

[@sesematactivities2024]

THANKS FRANK, YOU MADE ME UNDERSTAND PANDAS

[@mrchuz0]

I didn't understand the use of the lambda function in the ordering section (3:09:40), as you are trying to lower() the values but none of those are becoming lower. Could you explain deeper what failed there?

[@Aivanello]

Thank you so much. This is a great course.

[@MahmudYuldashev]

Thank you so much. This is what I was looking for!

[@hannsflip]

Great tutorial, was really explanatory, and really easy to catch up-

[@nomad_grant]

cheat sheet is no longer available through the link :( any chance you have an alternative download link for that? It looked very helpful! Fantastic video by the way. The pace was perfect for me!

[@user-jt4en7zg4c]

Thank you Frank, this is so useful

[@bsnljkd]

Great Course! Thanks

[@ladydi8712]

Thank you so much, looking for more data analyst course!! Im a noob helped so much👍

[@ici6308]

Wonderful tuto. Very well explained !

[@user-ok5sm5ff1o]

Amazing course big thanks!

[@victorgigreat1160]

Frank that was excellent work.

[@ThinhLe-eh9re]

Thank you very much Frank ❤

[@INTELLIGENCE_Revolution]

I was going to watch another video. But Frank’s voice was nicer to listen to 😂

[@mazyar79]

Thanks so much Frank! I'm just diving into the course and so far it's been amazing! I just tried to get the Cheat Sheet sent to me but I received an error: "Account is cancelled and can not accept new subscribers." Is there another way I can receive the Cheat Sheet? Much appreciated in advance.

[@bensl3308]

3:23:26 df_sales.pivot_table(index="Gender",aggfunc="sum") TypeError: datetime64 type does not support sum operations What to do ?

[@bensl3308]

The only thing, that works for me! df_sales.groupby("Gender").sum(numeric_only=True)

[@muhdbasiirzulkifle5090]

Thank you for your guidance 😃

[@jeanillecogtas]

nag throwback lng.... those were the days.....

[@jhillyt]

Great corse Frank! Thank you for sharing. I'm just about to the end and I'm getting error loading the gdp.csv? 'UnicodeDecodeError' Any advice on this? Thanks in advance... UPDATE: saved csv as excel and was able to parse the file.....

[@Dongnanjie]

Love it. Thank you so much!

[@ankurchanda1112]

Conditional formatting is probably the most powerful feature of Excel. Would be tough to replicate these features (say highlighting duplicate values) in Python. Or no?

[@kunalrath5352]

In the section on reading a csv file to create a Dataframe, the syntax used by you, i.e df_exams = pd.read_csv('file_name.csv') doesn't execute as the file local directory is gonna be whole different as when tried in different PC local systems. Instead we can try using df_exams = pd.read_csv(r"file_name.csv") This syntax works perfectly.

[@tical_fm]

You're right, i also used the second option.

[@vignesh28kk]

i tried both the medthod, its not working

[@vignesh28kk]

Do we need to include the path of that csv file?

[@tical_fm]

@@vignesh28kk I copied the path of the file

[@georgelam1878]

could someone advise where to download "StudentsPerformance.csv" file used in the course

[@michelfilipebr]

Excellent course! Help me to come through. :)

[@user-sj9wp9zg1d]

Колко интересно за гледане, благодаря за видеото

[@mahmoudalaref189]

Great ❤️

[@rahul28thakur]

Thank you Frank !!

[@poojaj1996]

got "TypeError: datetime64 type does not support sum operations ", @3.24. how to drop columns contains datetime64 type?

[@princeademuwagun7870]

Extremely nice.... thank you.

[@thungivan3650]

congrats!!

[@Behappytruthfully]

Thanks. I am trying to learn at 55😊

[@william1000]

Great video thanks for posting

[@Energy_with_Majd]

Very helpful thank you 🙏

[@mhn17]

Excuse me, off topic question, I just want to know how did you add the bracket symbols and the single quote symbols to both sides of the selected string, like in 2:53:04? Btw, thank you so much. The course is helpful and easy to follow for such a new data learner like me.

[@thepycoachES]

First, you have to select the text and then press either the [ or ' key. Hope that helps!

[@arionrares7764]

Is this only for Excel or any other program like the one from LibreO?

[@saplay3372]

Great job sir

[@georgejachvliani2288]

Very good tutorial .Thank you

[@boom78]

Questions: does Jupyter Notebook have a feature to show the cursor horizontal location? PEP 8 says to limit lines to 79 characters, but I cannot tell where this is. Also, it the common style to put spaces in-between operators but not when including function arguments?

[@sudheerkumarhegdea8151]

I have watched this course which is excellent. i need intermediate to advanced pandas for excel users. please share me video

[@F13TUN]

Perfect Thanks شكرا

[@benjaminphilips3737]

Best python tutorial at least for me

[@md.moniruzzaman7944]

execellent tutorial for a beginner