Navigate Select ESC Close

Exploratory Data Analysis in Pandas | Python Pandas Tutorials

2023-06-06 Education
234.2k
5.1k
257
Alex The Analyst
Alex The Analyst
1.4m subscribers

Unlock all features

FREE: Get instant access to 10 AI summaries, chats, or transcripts per day.

Description

Take my Full Python Course Here: https://www.analystbuilder.com/courses/pandas-for-data-analysis In this series we will be walking through everything you need to know to get started in Pandas! In this video, we learn about Exploratory Data Analysis in Pandas. Dataset in GitHub: https://github.com/AlexTheAnalyst/PandasYouTubeSeries/blob/main/world_population.csv Code in GitHub: https://github.com/AlexTheAnalyst/PandasYouTubeSeries/blob/main/Pandas%20101%20-%20Exploratory%20Data%20Analysis%20in%20Pandas.ipynb Favorite Pandas Course: Data Analysis with Pandas and Python - https://bit.ly/3KHMLlu ____________________________________________ SUBSCRIBE! Do you want to become a Data Analyst? That's what this channel is all about! My goal is to help you learn everything you need in order to start your career or even switch your career into Data Analytics. Be sure to subscribe to not miss out on any content! ____________________________________________ RESOURCES: Coursera Courses: 📖Google Data Analyst Certification: https://coursera.pxf.io/5bBd62 📖Data Analysis with Python - https://coursera.pxf.io/BXY3Wy 📖IBM Data Analysis Specialization - https://coursera.pxf.io/AoYOdR 📖Tableau Data Visualization - https://coursera.pxf.io/MXYqaN Udemy Courses: 📖Python for Data Analysis and Visualization- https://bit.ly/3hhX4LX 📖Statistics for Data Science - https://bit.ly/37jqDbq 📖SQL for Data Analysts (SSMS) - https://bit.ly/3fkqEij 📖Tableau A-Z - http://bit.ly/385lYvN *Please note I may earn a small commission for any purchase through these links - Thanks for supporting the channel!* ____________________________________________ BECOME A MEMBER - Want to support the channel? Consider becoming a member! I do Monthly Livestreams and you get some awesome Emoji's to use in chat and comments! https://www.youtube.com/channel/UC7cs8q-gJRlGwj4A8OmCmXg/join ____________________________________________ Websites: 💻Website: AlexTheAnalyst.com 💾GitHub: https://github.com/AlexTheAnalyst 📱Instagram: @Alex_The_Analyst ____________________________________________ 0:00 Intro 1:51 First Look at Data 3:45 Info() 4:40 Describe() 5:47 Counting all Null Values 7:09 Count of Unique Values 8:15 Sorting on Values 10:40 Correlation between Columns 11:53 Heatmap using Seaborn 14:43 Grouping Data 25:02 Visualizing Grouped Data 26:17 Boxplots for Outliers 29:07 Data Types of Columns 30:41 Outro *All opinions or statements in this video are my own and do not reflect the opinion of the company I work for or have ever worked for*

Top Comments (10)

@OkallTheAnalyst 2024-02-26

Incase you are running into an error at minute 11:12, add numeric_only = True to the corr. i.e df.corr(numeric_only = True).

162 13 replies
@santiagofajardo4949 2023-06-08

Hello, at minute 24:24, I managed to reverse the range of column names using [5:13][::-1]. The expression [::-1] is used to reverse ranges and it is very useful: df2 = df.groupby('Continent')[df.columns[5:13][::-1]].mean(numeric_only=True).sort_values(by='2022 Population', ascending=False) df2 Thank you very much, Mr. Alex, for these tutorials.

158 4 replies
@pbp7 2023-08-21

Man, “Oceania” was so funny 😂, tks for the class!

93
@adekeyedamola320 2024-12-17

If you are having any at 16:59, that's because you are looking for the mean of other datatypes apart from numbers. To resolve this, include numeric_only=True in your mean function, as in "df.groupby('Continent').mean(numeric_only=True)"

51 2 replies
@satrapech6107 2023-08-29

the correction of df.corr() is: numeric_columns = df.select_dtypes(include=[np.number]) correlation_matrix = numeric_columns.corr correlation_matrix()

48 14 replies
@JW-pu1uk 2023-06-06

This is absolutely top tier content. I can't stress this enough to people new, or going into the DA/DS field: you WILL be exploring and cleaning data sets much more than you will be visualizing and building models. Thanks for this, Alex!

48
@lajota-7 2023-12-15

Oceania is one of the 7 Continents (North America, South America, Europe, Asia, Africa, Oceania, Antartica). It's basically Australia and the countries (islands) around it. Hope that helps!

29 3 replies
@kartikgupta370 2023-12-05

We can also write this to save time writing all the column names in the list "df2 = df.groupby('Continent')[df.columns[12:4:-1]].mean(numeric_only=True).sort_values(by='2022 Population', ascending=False) "

16
@pradiptisimkhada292 2023-06-06

I just finished all the videos in you bootcamp playlist few hours ago and I'm excited to do this again..

5
@tranguyen4462 2024-03-31

omg I laughed out loud at the "Oceania" part ;)))) Alex is so funny and brutally honest about things he didn't know ;)))

1

Unlock the Data Inside
Turn Videos into Knowledge

  • Get FREE 10/day: transcripts, summaries, chats
  • Chat with videos, export text & PDF
  • $1 free API credit for RAG, chatbots & research

Free forever plan • All features unlocked

App screenshot