Charles Kelly explains how to use Jupyter Notebook to evaluate data science problems.
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- [Instructor] Throughout this course,…I'll be using Jupyter Interactive Notebooks…to illustrate Pandas and Python.…You can learn more about Jupyter Interactive Notebooks…at their homepage.…I found these tutorials to be very helpful.…These links will guide you to each tutorial.…If you scroll down, you'll see more information…about the types of Jupyter interactive notebook users.…With respect to notebooks,…there are at least two roles…or types of users.…The first role is that of students,…readers, viewers, learners and so forth.…
In this role, people can read a notebook as a digital book…or interact with a live book.…The second role is a notebook developer.…In this role, people create notebooks…that other people such as students and readers will use.…In this chapter, we will examine…the role of notebook developer.…In the other chapters within this course,…we will use notebooks as students and learners.…In an interactive notebook, you can do simple things…like use a print statement from Python.…
For example, I'm copying from the final version of this file…
Watch this course to gain an overview of Pandas. Charles Kelly helps you get started with time series, data frames, panels, plotting, and visualization. All you need is a copy of the free and interactive Jupyter Notebook app to practice and follow along.
- Using the Markdown language and Jupyter Notebook
- Creating objects
- Selecting objects
- Using operations
- Merging data
- Creating series
- Creating data frames
- Creating panels
- Annotating plots and data frame plots
Skill Level Intermediate
Introduction to Data Analysis with Pythonwith Michele Vallisneri2h 16m Intermediate
NumPy Data Science Essential Trainingwith Charles Kelly3h 54m Intermediate
SQL for Data Reporting and Analysiswith Emma Saunders2h 16m Intermediate
1. Introduction to Notebooks
2. Pandas Overview
4. Data Frames and Panels
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