Colleagues, level up your programming skills in the “Intermediate Python” training by creating visualizations using Matplotlib and manipulating DataFrames with pandas. This four-hour intermediate course will help you to build on your existing Python skills and explore new Python applications and functions that expand your repertoire and help you work more efficiently. [18 Videos - 87 Exercises]. Dictionaries offer an alternative to Python lists, while the pandas dataframe is the most popular way of working with tabular data. Learn logic, control flow, filtering and loops. Skill-based training modules include: 1) Matplotlib - Data visualization is a key skill for aspiring data scientists. Matplotlib makes it easy to create meaningful and insightful plots. In this chapter, you’ll learn how to build various types of plots, and customize them to be more visually appealing and interpretable, 2) Dictionaries & Pandas - learn about the dictionary, an alternative to the Python list, and the pandas DataFrame, the de facto standard to work with tabular data in Python. You will get hands-on practice with creating and manipulating datasets, and you’ll learn how to access the information you need from these data structures, 3) Logic, Control Flow and Filtering - Boolean logic is the foundation of decision-making in Python programs. Learn about different comparison operators, how to combine them with Boolean operators, and how to use the Boolean outcomes in control structures. You'll also learn to filter data in pandas DataFrames using logic, and 4) Loops - There are several techniques you can use to repeatedly execute Python code. While loops are like repeated if statements, the for loop iterates over all kinds of data structures. Learn all about them in this chapter.
Enroll today (teams & execs are welcome): https://datacamp.pxf.io/Y9EOPB
Download your free Python, R, TensorFlow and PyTorch - Career Transformation Guide.
For your reading pleasure consider:
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Much career success, Lawrence E. Wilson - Online Learning Central (share with your team)