Learn the basics of Python coding and its data structure such as strings, lists, tuples, sets, and dictionaries.
In this session, the extraction of specific patterns from text will be practiced by leveraging the regular expression model. The os module will be discussed to create files and folders in an automated way. The pause model will be taught to schedule code execution.
In the second day of this class, the Pandas and Numpy modules will be used to collect, cleanse, and transform datasets. Data extraction from Google sheets will be discussed. The topic of data visualization will be covered with the modules Matplotlib and Seaborn.
Topics covered in this class include:
- Using the Jupyter Notebook.
- Basics syntax of the Python and the data structure.
- Regular expressions (re) module and practice data extraction from text.
- Creating files and folder with the os module.
- Managing date variables with the datetime module.
- Best practices of the pause module to schedule code executions.
- Using the libraries Pandas and Numpy to collect, transform, and summarize data.
- Practice I/O datasets in an automated fashion. Read static and dynamic-datasets, execute manipulation, and write out the summary data.
- Combining data from various sources and create master files.
- Managing Google Sheets with Python.
- Creating bar charts, pie charts, line charts, scatter plots with Matplotlib, and Seaborn.
- Saving charts into jpeg, pdf, png, eps files. Leverage the datetime module to tracks charts versions.
About the Instructor: Arafat Mokhtar
Arafat Mokhtar is a Business Intel Engineer at Stanford School of Medicine, who supports the Human Resources Group with data collections, validation, cleansing, and analytics to provide actionable data insights used by leadership management to make data-driven decisions on the organization workforce. He develops code to automate data analytics processes, proposes data solutions, and develops measurable business metrics.
Arafat holds a Ph.D. in Particle Physics and spent several years as a postdoctoral fellow at SLAC National Accelerator Laboratory. He has 10+ years of teaching experience and conducted a number of Python and R training sessions for Stanford Technology Training Programs.
University IT Technology Training classes are only available to Stanford University staff, faculty, or students. A valid SUNet ID is needed in order to enroll in a class.