matplot画图处理

Posted 2021-06-06 WILLPOWER-

月份	私家车	旅游巴士	穿梭巴士	货车及货柜车	车辆总数	按月总增长
2018年10月	5,754 (32.56%)	2,338 (13.23%)	9,288 (52.56%)	290 (1.64%)	17,670
2018年11月	32,597 (31.22%)	24,588 (23.55%)	43,871 (42.01%)	3,371 (3.34%)	104,427
2018年12月	45,073 (37.88%)	23,142 (19.45%)	45,485 (38.22%)	5,302 (4.46%)	119,002	▲14.0%
2019年1月	44,863 (42.46%)	16,803 (15.90%)	36,981 (35.00%)	7,020 (6.64%)	105,667	▼11.2%
2019年2月	55,117 (48.03%)	17,435 (15.19%)	38,763 (33.78%)	3,429 (2.99%)	114,744	▲8.6%
2019年3月	60,954 (47.31%)	16,200 (12.57%)	43,272 (33.59%)	8,407 (6.53%)	128,833	▲12.3%
2019年4月	68,921 (48.44%)	17,515 (12.31%)	48,026 (33.75%)	7,831 (5.5%)	142,293	▲10.4%
2019年5月	79,217 (53.33%)	15,562 (10.48%)	46,355 (31.21%)	7,421 (4.99%)	148,546	▲4.4%
2019年6月	72,448 (53.34%)	14,580 (10.74%)	41,423 (30.50%)	7,362 (5.42%)	135,813	▼8.6%
2019年7月	75,220 (53.30%)	14,426 (10.22%)	43,213 (30.62%)	8,271 (5.86%)	141,130	▲3.9%
2019年8月	72,701 (54.98%)	14,609 (11.05%)	36,844 (27.86%)	8,081 (6.11%)	132,235	▼6.3%
2019年9月	65,838 (58.83%)	12,014 (10.73%)	26,149 (23.36%)	7,918 (7.07%)	111,919	▼15.4%
2019年10月	78,290 (63.49%)	10,855 (8.80%)	26,426 (21.43%)	7,740 (6.28%)	123,311	▲10.2%
2019年11月	71,447 (63.97%)	9,505 (8.51%)	23,081 (20.67%)	7,648 (6.85%)	111,681	▼9.4%
2019年12月	77,530 (62.05%)	12,565 (10.06%)	26,787 (21.44%)	8,060 (6.45%)	124,942	▲11.9%
2020年1月	72,441 (63.78%)	12,396 (10.91%)	21,850 (19.24%)	6,897 (6.07%)	113,584	▼9.1%
2020年2月	25,152 (61.67%)	3,260 (7.99%)	7,098 (17.40%)	5,278 (12.94%)	40,788	▼64.1%
2020年3月	26,123 (55.76%)	2,582 (5.51%)	9,522 (20.33%)	8,618 (18.40%)	46,845	▲14.8%
2020年4月	313 (3.65%)	90 (1.05%)	678 (7.90%)	7,497 (87.40%)	8,578	▼81.7%
2020年5月	289 (3.26%)	94 (1.06%)	700 (7.90%)	7,773 (87.77%)	8,856	▲3.2%
2020年6月	320 (3.09%)	23 (0.22%)	779 (7.53%)	9,230 (89.16%)	10,352	▲16.9%
2020年7月	525 (4.86%)	4 (0.04%)	947 (8.76%)	9,336 (86.35%)	10,812	▲4.4%

import re
import pandas as pd
from matplotlib import pyplot as plt

dataPath = './test.txt'
dataframe = pd.read_csv(dataPath, sep="\\t")

def Process(df:pd.DataFrame, name:str):
    reler = re.compile(r"\\d.* ")
    for i in range(df.shape[0]):
        data = df[name][i]
        search = reler.search(data)
        s, e = search.start(), search.end()
        df[name][i]= data[s:e].replace(',',"")

Process(dataframe, '私家车')
Process(dataframe, '旅游巴士')
Process(dataframe, '穿梭巴士')
Process(dataframe, '货车及货柜车')
dataframe
dataframe['私家车'] =  dataframe['私家车'].astype('int')
dataframe['旅游巴士'] =  dataframe['旅游巴士'].astype('int')
dataframe['穿梭巴士'] =  dataframe['穿梭巴士'].astype('int')
dataframe['货车及货柜车'] =  dataframe['货车及货柜车'].astype('int')
dataframe.set_index('月份', inplace=True)
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
dataframe.plot(xlabel = '港珠澳大桥香港口岸使用量', )
plt.grid()
plt.show()

画不同的样式的线

import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
x = np.linspace(-1*np.pi, np.pi, 100)
y = np.sin(x)
y1 = np.cos(x)
plt.plot(x, y, linestyle = '--')
plt.plot(x, y1, linestyle = '-.')
plt.show()

linestyle取值可为'-', '--', '-.', ':', 'None', ' ', '', 'solid', 'dashed', 'dashdot', 'dotted'

标注线是什么

plt.plot(x, y, linestyle = '--' , label = '--')
plt.plot(x, y1, linestyle = '-.', label = '-.')
plt.legend()

正常显示中文标签

加上plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示中文标签即可

限制图形的坐标范围

plt.axis([0,16, 0, 150])分别为[xstart, xend, ystart, yend]

强行改变坐标的值

比如上述坐标，我想将其范围改为-100-100
那么使用在计算的时候用x,但是绘图的时候用x1即可

import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
x = np.linspace(-1*np.pi, np.pi, 100)
y = np.sin(x)
y1 = np.cos(x)
x1 = np.linspace(-100, 100, 100)
# x2 = [str(m).split('.')[0] for m in x1 ]
plt.plot(x1, y, linestyle = '--' , label = '--')
plt.plot(x1, y1, linestyle = '-.', label = '-.')
# plt.xticks(x2)
plt.legend()
plt.show()