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When you type this command into the terminal, it will launch a local web server on your computer. Be sure to activate the environment in the terminal using the command conda activate earth-analytics-python before running the jupyter notebook command. NOTE: If you get an error jupyter: command not found, this means that you have not activated the conda environment that you installed for this textbook. You can use Shell (Terminal) to open Jupyter Notebook with the command, Jupyter Notebook. earth-analytics under your home directory) using cd directory-name.You can then check that the current working directory has been updated ( pwd). Git Bash for Windows or the terminal on Mac or Linux).Ĭhange the current working directory to your desired directory (e.g. Use Bash to Change to Your Working Directoryīegin by opening your terminal (i.e. Be sure to activate the environment in the terminal using the command conda activate earth-analytics-python before launching Jupyter Notebook. IMPORTANT: the jupyter notebook command requires that you have Jupyter Notebook installed on your computer! Jupyter Notebook was installed when you created the earth-analytics-python environment as a part of the setup for this textbook. It is ideal (but not required) to launch Jupyter Notebook from the working directory where all of the notebook files that you wish to use live, so you can easily access the files you need.

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First, you need to know how to open Jupyter Notebook, which is done in the Terminal.

Throughout this chapter, you will learn how to use Jupyter Notebook to write and document your Python code. Launch Jupyter Notebook From the Terminal

Create and open Jupyter Notebook files (.

Launch and close a Jupyter Notebook session.

Intro-to-earth-data-science-textbook Home

Chapter 19: Intro to Functions in Python.

Chapter 17: Conditional Statements in Python.

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Chapter 16: Write Clean Expressive Code.

SECTION 7 WRITE EFFICIENT, CLEAN CODE USING OPEN SOURCE PYTHON.

SECTION 6 SCIENTIFIC DATA STRUCTURES IN PYTHON.

Chapter 10: Get Started with Python Variables and Lists.

Chapter 7: Git/GitHub For Version Control.

SECTION 2 FILE FORMATS FOR EARTH DATA SCIENCE.

Chapter 1 Open reproducible science workflows.

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