Beginner's Guide to Python Data Analysis & Visualization
What you'll learn
- Experienced with N-dimensional array, Series, and DataFrame
- Perform data analysis with Python 3
- Be very confident when using Pandas and Numpy
- Gain extensive knowledge of how pandas works
Course content
- Preview02:54
- 04:44Install Anaconda
- 00:21Prepare the datasets
- Preview04:19
Requirements
- Follow a step-by-step guide to download and install software.
- Basic knowledge about Python is an asset but not required.
- Curiosity, courage, and faith.
Description
==> Become a Data scientist!
==> Make astonishing graphics!
This is the most comprehensive, yet straightforward, course for learning Python data science on Udemy! Whether you have never touched data science before, need a refresh on Pandas basics, or want to learn about the advanced features of Pandas, THIS COURSE IS FOR YOU!
If you never touched Python before, there is a Python crush section to get you started in 30 minutes! If you knew Python, use it to brush up your knowledge!
There are a lot of highlight points in this course. Paricularly, you will learn HOW TO:
- Perform Linear Regression Analysis
- Understand Linear Regression Analysis result
- Pandas series creation, selection, and other operations.
- Import CSV data
- Import Excel data
- Transform your array
- Select part of your data by column, row, or even condition!
- Rename your columns
- Change your index
- Delete columns
- Insert columns
- Make pie plots, scatter plots, series plots, heat-maps, and histograms!
- Numpy arrays
- Perform array indexing, slicing, and iterating.
- Generate descriptive statistics.
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In addition to the Udemy 30-day money back gurantee, you have my personal gurantee that you will love what you learn in this course. If you ever have any questions, please don't hesitate to post it in the course discussion board or message us directly. We will do our best to get back to you as soon as possible!
Jobs in data analysis, especially financial analysis, are pletiful. And because of the imense extensibility, python is growing to be the most popular data science tool! Pandas is the solely most important library you should know to perform analysis! This course will walk you through the very origin or Pandas and show you step-by-step, how Pandas is designed and used! Being able to use Pandas will give you strong background to dive depper into data analysis faithfully!
Is it too much to spend a few hours to add a critical skill on your resume? So what are you waiting for? Learn Pandas in a way that will advance your career and increase your knowledge!
What are you waiting for? This course won't stay at this price forever, click "Take this course" now and embark your amazing journal today!
See you in the course!
-- Alan Yue
Who this course is for:
- Anyone interested in data science
- Anyone interested in learning python, pandas, numpy
- Anyone curious about this world, about all the information flowing around us.
Instructors
![Alan H Yue](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.1 Instructor Rating
- 1,023 Reviews
- 12,389 Students
- 7 Courses
Alan is a professional Wealth & Insurance Analyst at HSBC Bank for 2 years. He is a SAS and Python master. He writes in SAS and Python in his everyday data analysis works.
Before that, he worked at Reitmans Canada, Ltd. as a Pricing Analyst.
He enjoys discovering the insights with data analysis. He first studied Marketing as his Bachelor's degree, then turned to pursue his master degree in Finance in Montreal.
With his courses, Alan wants to make data analysis skills available for every millennial to learn - without the struggles and frustrations.
On Udemy, over 6000+ students around the globe are learning SAS & Python data analysis skills from Alan.
- 4.2 Instructor Rating
- 248 Reviews
- 3,410 Students
- 1 Course
Rake has been working as a data analyst for more than 7 years. He has profound knowledge in Creadit Analysis, Portfolio Investment, and Risk Management. Rake believes in the power of data and that the full potential of data is interpreted through proper analysis, his interests are focusing on the impact of big data and data mining on the financial sector.