Python 102: Introduction to Data Analysis
Stack Overflow data indicates the increasing use of Python. Possibly spurred by its data science friendliness - a couple decades worth of scientific packages have made Python an incredibly productive and versatile.
This beginner course will guide you through the core libraries in PyData ecosystem: Numpy, Pandas, and matplotlib(optional). By taking the course, you will be familiar with the fundamental data analysis methods in Python using NumPy and Pandas.
What you will learn:
Understand the data analysis ecosystem in Python.
Learn how to use the pandas data analysis library to analyze data sets
Analyze real datasets to better understand techniques for data analysis
Create basic plots of data using MatPlotLib (bonus)
Part 1 Python Data Analysis Libraries
Data Analysis Components
Data Analysis Steps
Python Data Analysis Libraries
Part 2 Numpy Overview
Selecting and Slicing ,Filtering Array
Part 3 Data Analysis with Pandas
Import/Export Data - CSV, Excel, Internet
Part 4 Data Visualization with Matplotlib & Seaborn(bonus)
Who Should Attend?
Those are interested in learning data analysis.
Analysts who want to better understand a technical approach to analyzing data.
Students should know how to run, at a minimum, basic program in python.
About the Instructor:
Ocean Li Haiyang has 7 years’ of experience writing Python code. Currently working as a software engineer in an investment bank, he helps to build the corporate in-house risk management system. To meet the requirements of the front office user, the job entails trade capturing, risk & regulation reports generation/automation, market data retrieving, time series analysis and visualization. As a senior developer, he is also required to teach Python Foundations to junior developers.