Python for Data Analysis
Learn to Wrangle and perform Exploratory Data Analysis
What you will learn
This 5-day workshop will be hands-on learning of data analysis with the Python programming language, and is aimed at beginners. You will work with different basic and complex data structures in Python. You will also understand the use of various modules including numpy, pandas, and matplotlib for data analysis and visualization. At the end of the workshop you’ll learn how to perform data analysis and share your insights using various charts in Jupyter notebooks and Excel workbooks.
Key skills & technologies
- Pandas for Data Wrangling.
- Numpy (NumPy) for its array data structure and data manipulation functions.
- matplotlib and seaborn for its graph plotting functions.
- Jupyter notebook as your development and collaboration environment.
- Microsoft Excel and Google Forms as data sources for analysis, Microsoft Excel for insights output
There are six modules in the Python for Data Analysis workshop. Each module introduces one or two core data analysis concepts while working through the practical implementation.
- Types (strings, lists, dictionaries, and more
- Control Flow (if-then statements, looping)
- Organizing code (functions, modules, packages)
- Reading and writing files
- Overview of Object-Oriented Programming (OOP)
DAY 2: NUMPY (Introduction to NumPy and 2D plotting. The NumPy package is presented as a tool for rapidly manipulating and processing large data sets. 2D plotting is introduced with matplotlib)
- Understanding the N-dimensional data structure
Indexing arrays by slicing or more generally with indices or masks
Basic operations and manipulations on N-dimensional arrays
DAY 3: ACCESSING DATA FROM MULTIPLE SOURCES
- Reading and writing data from local files (.txt,.csv,.xls, .json, etc)
Reading data from remote files
Scraping tables from web pages (.html)
Making the most of the powerful read_table method
- Working with Pandas data structures: Series and DataFrame
- Accessing your data: indexing, slicing, fancy indexing, boolean indexing
- Data wrangling, including dealing with dates and times and missing data
- Adding, dropping, selecting, creating, and combining rows and columns
DAY 4: DATABASE ACCESS AND DATA WRANGLING
- Database access with DB-API2 and SQLAlchemy
- Executing SQL commands from Pandas
- Loading database data into a DataFrame
- Combining and manipulating DataFrames: merge, join, concatenate
DAY 4: DATA VISUALIZATION
- Understanding the structure of a Figure
- Data visualization: scatter plots, line plots, box plots, bar charts, and histograms with matplotlib
- Customizing plots: important attributes and arguments
DAY 5: DATA ANALYSIS
- Split-apply-combine with DataFrames
- Data summarization and aggregation methods
- Pandas powerful groupby method
- Reshaping, pivoting, and transforming your data
- Simple and rolling statistics
Is it for me?
- Do I need any programming experience to attend?You don’t need previous experience in Python as the workshop will cover the basics. Nonetheless, it is useful if you’ve done programming in another programming language.
- What will I be doing?In three day you will implement, evaluate and optimize your data transformations, and perform exploratory data analysis using real-world datasets in Python. As part of this workshop, you will familiarize yourself with several best practices such as tidying data prior to transformation.
- What age is this for?This workshop is suitable for university students and professionals.
- Do I need a computer?It is best if you bring your own laptop.
- What’s the experience like?The workshops are very hands-on and you will learn by doing. After the first 30 minutes of the workshop you will already be coding! Our instructors are always there to help you if you get stuck.
Call us at (214)-997-6100 if you have special circumstances or looking for dedicated corporate training