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| 1 | +# -*- coding: utf-8 -*- |
| 2 | +# @Author: manjusv |
| 3 | +# @Date: 2019年07月09日 12:17:17 |
| 4 | +# @Last Modified by: manjusv |
| 5 | +# @Last Modified time: 2019年07月09日 12:35:34 |
| 6 | + |
| 7 | +from matplotlib import pyplot as plt |
| 8 | + |
| 9 | +plt.style.use('fivethirtyeight') |
| 10 | + |
| 11 | +ages_x = [25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35] |
| 12 | + |
| 13 | +# Median Developer Salaries by Age |
| 14 | +dev_y = [38496, 42000, 46752, 49320, 53200, |
| 15 | + 56000, 62316, 64928, 67317, 68748, 73752] |
| 16 | +plt.plot(ages_x, dev_y, color='k', linestyle='--', marker='o', label='All Devs') |
| 17 | + |
| 18 | +# Median Python Developer Salaries by Age |
| 19 | +py_dev_y = [45372, 48876, 53850, 57287, 63016, |
| 20 | + 65998, 70003, 70000, 71496, 75370, 83640] |
| 21 | +plt.plot(ages_x, py_dev_y, color='b', linestyle='-', marker='o', label='Python') |
| 22 | + |
| 23 | +# Median JavaScript Developer Salaries by Age |
| 24 | +js_dev_y = [37810, 43515, 46823, 49293, 53437, |
| 25 | + 56373, 62375, 66674, 68745, 68746, 74583] |
| 26 | +plt.plot(ages_x, js_dev_y, label='JavaScript') |
| 27 | + |
| 28 | + |
| 29 | +plt.title("Median Salary (USD) by age") |
| 30 | +plt.xlabel("Ages") |
| 31 | +plt.ylabel("median Salary (USD)") |
| 32 | +plt.legend() |
| 33 | +plt.tight_layout() |
| 34 | +plt.savefig('plot.png') |
| 35 | +plt.show() |
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