Python Crash Course: Part 14 - pandas Tutorial

Skills with pandas are an absolute requirement for doing analytics and data science with Python! This pandas tutorial is a crash course in what you need to know.
After completing this crash course series, you will have the foundational Python skills to take additional analytics, data science, and machine learning courses using Python.
☕ If you found this content useful and would like to support the channel, you can buy me a coffee: www.buymeacoffee.com/DaveOnData
--------------------------------------------------------------------------------------------
VIDEO CHAPTERS
--------------------------------------------------------------------------------------------
00:00 Intro
00:32 Get the Files
01:49 A Great pandas Book
02:19 Intro to DataFrames
03:38 Intro to Series Objects
06:44 pandas Fundamentals
21:15 Numeric Columns
28:58 String Columns
44:59 Datetime Columns
53:26 Visualizing Columns
01:03:29 Indexes
01:08:53 Filtering DataFrames
01:41:20 Mutating Data
01:53:25 Data Wrangling
02:09:12 Joining DataFrames
02:23:40 Pivoting DataFrames
--------------------------------------------------------------------------------------------
FREE DATA SCIENCE CRASH COURSES
--------------------------------------------------------------------------------------------
If you're ready to see what Python skills make possible, be sure to check out my FREE on-demand data science crash courses!
Here's what you get with any of these courses:
1️⃣ On-Demand: Watch the course when it fits your schedule
2️⃣ PDF of all slides
3️⃣ All Python code as a Jupyter Notebook
4️⃣ All data so you can experiment
5️⃣ Resources to continue your learning.
Data science with Python. You've got this if you want it:
💻 Decision Trees with Python:
bit.ly/DecisionTreesWithPython
💻 Tuning Decision Trees with Python:
bit.ly/TuningDecisionTreesWit...
💻 Logistic Regression with Python:
bit.ly/LogisticRegressionWith...
💻 Cluster Analysis with Python:
bit.ly/ClusterAnalysisWithPython
--------------------------------------------------------------------------------------------
GET THE FILES
--------------------------------------------------------------------------------------------
Here's the GitHub where you can download the CSVs used in this pandas tutorial:
github.com/DaveOnData/PythonC...
#pythonforbeginners #pythoncrashcourse #pythoncourse #pythonprogramming #pythontutorial #python

[@-Hussainnn]

no way a 3hr tutorial on pandas!

[@DaveOnData]

Yep! Following the 80/20 Rule for pandas is still a lot of topics. 🤣

[@B-Ravity]

Great stuff David! Thanks for the video .

[@DaveOnData]

@B-Ravity - Thank you! I hope you and many others find the tutorial series useful.

[@michaelt312]

The video we knew we needed but didn't think anyone would ever give us. THANK YOU!!

[@DaveOnData]

@michaelt312 - You are most welcome! I hope many professionals find the tutorial series useful.

[@scottbrewer474]

Love the method chaining with assign - I'm always looking for new tips! Only difference in my workflow would be to shift the lines within the chaining parens to be under the new object with an indent to better use that white space as linters yell if lines get too long. Not sure if that's 'standard practice', but I like that pattern.

[@scottbrewer474]

Like:
new_df = (
df
.assign(lambda ...)
)

[@DaveOnData]

@scottbrewer474 - Method chaining for creating fluent interfaces is common in other OO programming languages. I've never been able to quite figure out why so many Pythonistas don't write their code this way.

[@user-nw8it2ju2f]

Dziękujemy.

[@theautisticside]

Like_thousand = 👍 * 1000

[@DaveOnData]

Woohoo! Glad you like the tutorial - even though it is a long one.