Python for Data Analysis: Pandas Data Frames

This video covers the basics of pandas data frames in Python.

Subscribe:

This is lesson 9 of a 30-part introduction to the Python programming language for data analysis and predictive modeling. Link to the code notebook below:

Python for Data Analysis: Pandas Data Frames

Link to the previous lesson on Numpy Arrays:

This guide does not assume any prior exposure to Python, programming or data science. It is intended for beginners with an interest in data science and those who might know other programming languages and would like to learn Python.

I will create the videos for this guide such that you should be able to learn a lot just watching on YouTube, but to get the most out of the guide, it is recommended that you create a Kaggle account so that you can copy and edit each lesson so that you can follow along and run code yourself.

Introduction to Python Playlist:

Link to the Python for Data Analysis written guide index page:

[fereshtehkhojastehmehr]

thanks for explaining everything well.

[Mahmoud-yskt]

it is very useful, thank you very much

[dataotechingriding]

does anyone happen to know which titanic package to install to follow along with the video?

[OluwaseunAdegboye-lzdc]

Since they are mutable, you can add items or elements as you desire later in your implementation.

[thecaptain]

There is one thing which is really not clear for me: In any real case I can think of, the numpy or panda dataset creation is dynamic as the number of rows / columns is not known and one cannot be expected to know it at the moment of creating the program text; hence the question: How to create a numpy or panda dataset dynamically?