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diff --git a/tutorials/module_4/4.7_Data_Visualization_and_Presentation.md b/tutorials/module_4/4.7_Data_Visualization_and_Presentation.md new file mode 100644 index 0000000..f97721b --- /dev/null +++ b/tutorials/module_4/4.7_Data_Visualization_and_Presentation.md @@ -0,0 +1,72 @@ +#data #visualization +# Data Visualization and Presentation + +## How to represent data scientifically + +Remember PCC: +1. Purpose +2. Composition +3. Color + +## Plotting with Matplotlib +### Simple plot +You've probably seen the `matplotlib` package being imported at the top of the scripts. Matplotlib allows us to create static, animated and interactive visualizations in Python. It can even create publication quality plots. + +Initialize +```python +import numpy as np +import matplotlib.pyplot as plt +``` +Prepare data +```python +x = np.linspace(0,10*np.pi,1000) +y = np.sin(x) +``` +Render +```python +fig, ax = plt.subplots() +ax.plot(X,Y) +plt.show() +``` + + +### Customizing plots +subplots, twin axis, labels, annotations + +Colormaps and figure aesthetics. + + + + +### Other types of plots +- `scatter` +- `bar` +- `imshow` +- `contourf` +- `pie` +- `hist` +- `errorbar` +- `boxplot` + +## Plotting different types of data + + + +## Plotting for reports and publication quality graphs +Now that you've + + +### Saving figures +save formats + figure size + bitmap vs vector format + + + + +## Problem: +Using pandas to plot spectroscopy data from raw data + + +## Problem: +Create a muli-panel figure showing raw data, fitted curve and residuals. Format with consistent style, legend, and color scheme for publication-ready quality.
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