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Welcome to this lesson on matplotlib! As we just learned, matplotlib is a Python library used for making graphs. It’s commonly used by research scientists and data scientists, among other professionals. Matplotlib makes it easy to turn tabular data (data in a spreadsheet, table, or .csv) into basic visualizations.

In this lesson we will…

• Learn about five basic chart types
• Review the general structure of matplotlib code
• Make a line chart to compare temperature data from around the world
• Explore the line chart: change style options, adjust axes, and add title and legend

In the Jupyter notebook to the right, we’ll start by importing `matplotlib.pyplot` as `plt`, and importing a dataset of average monthly temperatures around the world.

### Instructions

1.

Let’s practice running the first two Jupyter cells to load our packages and display the chart correctly.

1. Select the code cell beginning `# load matplotlib and pandas` (click anywhere in the cell)
2. Click the `Run` button or the `Shift`+`Enter/Return` keys (see image below)
3. Click the `Save` button or use the `Control/Command`+`S` keys to save your work
4. Repeat this process for the cell that says `# display charts correctly`.
5. Click the `Test Work` button below the Jupyter Notebook to check if you’ve completed the Checkpoint!

If you’ve successfully completed the Checkpoint, you’ll get a green check at the top of the checkpoint. When all checkpoints are complete, the `Next` button at the bottom right will become clickable.

2.

We’ll need some data to get a data visualization going! We’re going to look at monthly average temperatures from around the world. Run the cell that says `## load in the data`, then Save the notebook and click Test Work. Refer back to the steps in Checkpoint 1 if needed.

3.

With our data loaded, let’s take a peek at what matplotlib can do. The next code block is all set up: still no need to type anything, just Run the cell that says `# make a line chart`, hit Save, then Test Work. Once you’re done, you can click `Next` to move on to the next exercise.