In [1]:

import matplotlib.pyplot as plt
import pandas as pd

In [2]:

plt.rc('figure', figsize=(10, 8))
plt.style.use('seaborn-white')

In [3]:

data = pd.read_csv(r'examples/age_data.csv')
data.head()

Out[3]:

	Age	All_Devs	Python	JavaScript
0	18	17784	20046	16446
1	19	16500	17100	16791
2	20	18012	20000	18942
3	21	20628	24744	21780
4	22	25206	30500	25704

In [4]:

ages = data['Age']
dev_salaries = data['All_Devs']
py_salaries = data['Python']
js_salaries = data['JavaScript']

In [5]:

# fill entire area under python plotted area

overall_median = 57287

plt.plot(ages, dev_salaries, color='#444444', linestyle='--', label='All Devs')
plt.plot(ages, py_salaries, label='Python')


# plt.fill_between(ages, py_salaries, alpha=0.25)

# fill between the overall median
# plt.fill_between(ages, py_salaries, alpha=0.25, y2=overall_median)

# filling only when a condition is met
# fill with green when we are above the median salary
plt.fill_between(ages, py_salaries, alpha=0.25, y2=overall_median, color='green',
                where=(py_salaries > overall_median), interpolate=True)

# fill with red when we are below the median salary
plt.fill_between(ages, py_salaries, alpha=0.25, y2=overall_median, color='red',
                where=(py_salaries <= overall_median), interpolate=True)


# interpolate - make sure certain x-intersections don't get clipped

plt.legend()
plt.title('Median Salary (USD) by Age')
plt.xlabel('Ages')
plt.ylabel('Median Salary (USD)')
plt.show()

In [6]:

# fill area between two different plots


plt.plot(ages, dev_salaries, color='#444444', linestyle='--', label='All Devs')
plt.plot(ages, py_salaries, label='Python')


# filling only when a condition is met
# fill with green when we are above the median salary
plt.fill_between(ages, py_salaries, alpha=0.25, y2=dev_salaries, color='green',
                where=(py_salaries > dev_salaries), interpolate=True,
                label='Above AVG')

# fill with red when we are below the median salary
plt.fill_between(ages, py_salaries, alpha=0.25, y2=dev_salaries, color='red',
                where=(py_salaries <= dev_salaries), interpolate=True,
                label='Below AVG')


# interpolate - make sure certain x-intersections don't get clipped

plt.legend()
plt.title('Median Salary (USD) by Age')
plt.xlabel('Ages')
plt.ylabel('Median Salary (USD)')
plt.show()