Using Data Science Tools in Python (v1.0)
More and more organizations are turning to data science to help guide business decisions. Regardless of industry, the ability to extract knowledge from data is crucial for a modern business to stay competitive. One of the tools at the forefront of data science is the Python ® programming language. Python’s robust libraries have given data scientists the ability to load, analyze, shape, clean, and visualize data in easy to use, yet powerful, ways. This course is designed for experienced programmers and those with a solid working knowledge of computing technology looking to gain the skills needed to successfully use these key libraries to extract useful insights from data, and as a result, provide great value to the business.
Course Objectives
In this course, you will use various Python tools to load, analyze, manipulate, and visualize business data. You will:
- Set up a Python data science environment. Manage and analyze data with NumPy arrays. Manipulate and modify data with NumPy arrays. Manage and analyze data with pandas DataFrames. Manipulate, modify, and visualize data with pandas DataFrames. Visualize data with Matplotlib and Seaborn
Agenda
- Select Python Data Science Tools
- Set Up an Environment Using Jupyter Notebook
- Create NumPy Arrays
- Load and Save NumPy Data
- Analyze Data in NumPy Arrays
- Manipulate Data in NumPy Arrays
- Modify Data in NumPy Arrays
- Create Series and DataFrames
- Load and Save pandas Data
- Analyze Data in DataFrames
- Slice and Filter Data in DataFrames
- Manipulate Data in DataFrames
- Modify Data in DataFrames
- Plot DataFrame Data
- Create and Save Simple Line Plots
- Create Subplots
- Create Common Types of Plots
- Format Plots
- Streamline Plotting with Seaborn
FREE
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Course Type: Instructor Led