The 44 most used Python Pandas, Numpy and Matplotlib codes!
Posted on 24 Feb 03:28 | by huayting | 70 views
The 44 most used Python Pandas, Numpy and Matplotlib codes!
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 228 MB | Duration: 42m
What you'll learn
You will learn about Python itself the basics of Data Science
You will get to learn Pandas, a software library written, for the Python programming language for data manipulation and analysis
And you will learn Numpy, which is the fundamental package for scientific computing with Python
Finally you will learn Matplotlib, a data visualization and graphical plotting library for Python and numpy
Requirements
There is no required skill needed, just some basic knowledge about statistics could help
Description
To introduce myself, I am mr D.
Jeffrey and after getting my Bachelors of Economics I started to work out many Key Performance Indicators for SME's and the government. I have worked with Excel, Tableau, Power BI, SQL and found out that Python takes data to a higher level. In three steps I will take you through the 44 most used Python codes of Pandas, Numpy and Matplotlib. With real examples per code and very clear to understand. Since Python is the number one programming language, this is an added value to your curriculum. Numpy is known for it's strong posibilities in Data Science, while Numpy covers the mathematical part. Matplotlib is used to ploth beautifull graphs. With Python, the average salary of $100.000 is worth it. And many areas like physics, economics, etc are using data. After a short introduction, I will take you through the most common codes.
Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
What is NumPy NumPy is a Python library used for working with arrays. It also has functions for working in domain of linear algebra, fourier transform, and matrices.
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
Give this course a try and have fun learning.
Who this course is for
Bners and intermediates, who are wandering, what codes are mostly used in the industry
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