Python - Introduction to DataFrames (English Version) | Pandas | Numpy | Series | DataFrames

Python Tutorial - Introduction to DataFrames (English Version) | Python Pandas | Numpy | Series | DataFrames

Python Tutorial - In this video we will be learning about the Python introductory libraries such as Pandas.

What we are learning in this video:

Today we are learning about the basics of Pandas Library and understanding the handling of Data by generating data into rows and columns by means of Series & List and then converting them into DataFrames. We will also understand how to add or delete the columns and rename it as well.

What is Pandas in Python ?

The most often used open source Python library for data science, data analysis, and machine learning activities is called Pandas. It is constructed on top of Numpy, a different package that supports multi-dimensional arrays.

What is Pandas in Python?
Pandas provides high-level data structures and functions designed to make working with structured or tabular data fast, easy, and expressive. The primary objects in pandas are the DataFrame, a tabular, column-oriented data structure with both row and column labels, and the Series, a one-dimensional labeled array object.

What Can You Do With DataFrames Using Pandas?

Pandas makes it simple to do many of the time consuming, repetitive tasks associated with working with data, including:

* Data cleansing
* Data fill
* Data normalization
* Merges and joins
* Data visualization
* Statistical analysis
* Data inspection
* Loading and saving data


Download Jupyter Notebook here:
https://drive.google.com/file/d/1EU_lkGVBea4luWvsrJt1SceJj-dmZbYA/view?usp=sharing

Join SaadPyTech Community by following:

- Website: www.SaadPyTech.com
- GitHub: https://github.com/saadpython
- Twitter: https://twitter.com/SaadPyTech
- YouTube: @Saad PyTech
- Instagram: www.instagram.com/saadpytech

What advantages does Python offer?

Python programming has a wide range of functionality and may be used to create algorithms, scripts, and data structures, as well as to scrape the web.

Applications written in Python cover a wide range of tasks related to data analytics, automation, artificial intelligence, and data visualization.

Due to the abundance of open-source Python modules, such as scikit-learn, pandas, SciPy, Matplotlib, and NumPy, as well as frameworks like Flask and Django, Python is a favourite among data scientists.

Businesses that use Python programming:

Insurance: Making use of machine learning to produce business insights
Retail Banking: Versatile data processing and transformation
Aerospace: Observing deadlines for software systems
Finance: Utilizing data mining to find cross-selling opportunities
Business Services: Financial data access via API
Hardware: Automating network management
Healthcare: Predicting the course of a disease
Consulting Services: Individual web development
InfoTech: Modernizing IT
Software: Making legacy software extensible

Tags
#pandas #pythonpandas #numpy #pythontutorial #python #pythonprogramming #data #datastructures #pythonforbeginners


Background Music:
------------------------------------------------------------------------------
Music by Luke Bergs:
▶Youtube: https://youtu.be/Uu-Hl6gKysU
▶Spotify: https://spoti.fi/37O7TkS
▶Soundcloud: https://bit.ly/37JG9hB
▶Facebook: https://bit.ly/2JOvnhT
▶Instragram: https://bit.ly/2JKGqsy
------------------------------------------------------------------------------