Data analysis is one of the fastest growing fields, and Python is one of the best tools to solve these problems. In this course, Getting Started with Data Analysis Using Python, you'll learn how to use Python to collect, clean, analyze, and persist data. First, you'll discover techniques including persisting data with csv files, pickle files, and databases, along with the ins and outs of basic SQL and Sqlite command line. Next, you'll delve into data analysis and how to use common data structures, such as lists, dictionaries, tuples, and sets. Additionally, you'll learn how to use these structures and apply these skills to widely available stock market data. Finally, you'll explore pygal, a Python library for data visualization. When you're finished with this course, you'll have the necessary knowledge to efficiently build stunning charts and graphs utilizing data analysis in Python.
Who is this course for?
This course is for Excel power users or individuals who are new to data analysis and interested in learning about how Python applies to it.
Why is data visualization important?
Data visualizations make big and small data easier for the human brain to understand, and visualization also makes it easier to detect patterns, trends, and outliers in groups of data. Good data visualizations should place meaning into complicated datasets so that their message is clear and concise.
What is Pygal?
Pygal is a Python module that creates SVG (Scalable Vector Graphics) graphs/charts in a variety of styles. Pygal is highly customize-able, yet also extremely simplistic, which is a very rare combination. You can make line graphs, bar graphs, histograms, pie charts, maps, and a whole lot more.
What is SQLite?
SQLite is a relational database management system contained in a C library. In contrast to many other database management systems, SQLite is not a client–server database engine. Rather, it is embedded into the end program.
What are tuples in Python?
A tuple is an immutable list of Python objects which means it can not be changed in any way once it has been created. Unlike sets, tuples are an ordered collection.
Terry has over 15 years’ experience in software development from business applications to embedded systems. He has worked at a variety of government agencies and private firms including: California Senate, Office Legislative Counsel, and Space Systems Loral. In his spare time, Terry enjoys hiking and spending time with his family.
Course Overview Hi, my name's Terry Toy. Welcome to Getting Started with Data Analysis using Python. I've been programming for over 15 years, and Python is a great language to learn. So if you're an Excel power user, or perhaps new to data analysis, I welcome you to this course. In this course, we'll learn not only about Python, but specifically how to apply it to data analysis. We'll learn how to collect, clean, persist, analyze, and how to create stunning data visualizations. The core of this course is analyzing data, and we'll learn about data structures such as lists, dictionaries, tuples, and sets, and we'll apply these structures to market analysis, because there's so much information about the stock market. And regarding to persisting data, we're going to learn how to work with CSV files and SQLite, a relational database. We'll learn how to insert and collect data, and store it all within a database, then how to retrieve that data, whether from a CSV file or a SQLite database, and to build our data structures, our lists, our dictionaries, our tuples, and then use that to analyze our data, and then build stunning visualizations. So I'm excited; I hope you'll join me in this course. Let's learn about Python and data analysis.