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https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html
https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html
== Cheatsheets ==
==Cheatsheets==
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Matplotlib_Cheat_Sheet.pdf
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Matplotlib_Cheat_Sheet.pdf
plt.tight_layout()
plt.tight_layout()
plt.savefig('plot.png')
plt.savefig('plot.png')
plt.show()
</syntaxhighlight>
==== Fill between ====
<syntaxhighlight lang="python3">
import pandas as pd
from matplotlib import pyplot as plt
data = pd.read_csv('data.csv')
ages = data['Age']
dev_salaries = data['All_Devs']
py_salaries = data['Python']
js_salaries = data['JavaScript']
plt.plot(ages, dev_salaries, color='#444444',
linestyle='--', label='All Devs')
plt.plot(ages, py_salaries, label='Python')
overall_median = 57287
plt.fill_between(ages, py_salaries, dev_salaries,
where=(py_salaries > dev_salaries),
interpolate=True, alpha=0.25, label='Above Avg')
plt.fill_between(ages, py_salaries, dev_salaries,
where=(py_salaries <= dev_salaries),
interpolate=True, color='red', alpha=0.25, label='Below Avg')
plt.legend()
plt.title('Median Salary (USD) by Age')
plt.xlabel('Ages')
plt.ylabel('Median Salary (USD)')
plt.tight_layout()
plt.show()
plt.show()
</syntaxhighlight>
</syntaxhighlight>