python可视化

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime, timezone

# fig = plt.figure(figsize=(3, 3))  #figsize 表示图的比例
# ax1 = fig.add_subplot(2,1,1)
# ax2 = fig.add_subplot(2,1,2)

# ax1.plot(np.random.randint(1,5,5), np.arange(5))
# ax2.plot(np.arange(10)*3, np.arange(10))
# plt.show()

unrate = pd.read_csv(r"D:\untitled\UNRATE.csv")
unrate['DATE'] = pd.to_datetime(unrate['DATE'])

unrate['MONTH'] = unrate['DATE'].dt.month
# fig = plt.figure(figsize = (6,3))
# plt.plot(unrate[0:12]['MONTH'],unrate[0:12]['VALUE'],c='red')
# plt.plot(unrate[12:24]['MONTH'],unrate[12:24]['VALUE'],c='blue')
# plt.show()

fig = plt.figure(figsize = (10,6))
colors = ['red','blue','green','orange','black']  #颜色循环代码 重要
for i in range(5):
start_index = i*12
end_index = (i+1)*12
subset = unrate[start_index:end_index]
label = str(1948 + i)
plt.plot(subset['MONTH'], subset['VALUE'], c=colors[i], label=label)

plt.legend(loc='best') #图例记住
plt.xlabel('Month, Integer')
plt.ylabel('Unemployment Rate, Percent')
plt.title('Monthly Unemployment Trends, 1948-1952')
plt.show()