Matplotlib中将以色彩、标记进行分组的线标记为同一组

Matplotlib中将以色彩、标记进行分组的线标记为同一组

目标效果：

import numpy as np
import pandas as pd
import datetime
import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from dateutil import parser

df_ferrara = pd.read_csv('WeatherData/ferrara_270615.csv')
df_milano = pd.read_csv('WeatherData/milano_270615.csv')
df_mantova = pd.read_csv('WeatherData/mantova_270615.csv')
df_ravenna = pd.read_csv('WeatherData/ravenna_270615.csv')
df_torino = pd.read_csv('WeatherData/torino_270615.csv')
df_asti = pd.read_csv('WeatherData/asti_270615.csv')
df_bologna = pd.read_csv('WeatherData/bologna_270615.csv')
df_piacenza = pd.read_csv('WeatherData/piacenza_270615.csv')
df_cesena = pd.read_csv('WeatherData/cesena_270615.csv')
df_faenza = pd.read_csv('WeatherData/faenza_270615.csv')

# 读取温度和日期数据
y1 = df_ravenna['temp']
x1 = df_ravenna['day']
y2 = df_faenza['temp']
x2 = df_faenza['day']
y3 = df_cesena['temp']
x3 = df_cesena['day']
y4 = df_milano['temp']
x4 = df_milano['day']
y5 = df_asti['temp']
x5 = df_asti['day']
y6 = df_torino['temp']
x6 = df_torino['day']

# 把日期从 string 类型转化为标准的 datetime 类型
day_ravenna = [parser.parse(x) for x in x1]
day_faenza = [parser.parse(x) for x in x2]
day_cesena = [parser.parse(x) for x in x3]
day_milano = [parser.parse(x) for x in x4]
day_asti = [parser.parse(x) for x in x5]
day_torino = [parser.parse(x) for x in x6]

# 调用 subplots() 函数，重新定义 fig, ax 变量
fig, ax = plt.subplots()
plt.xticks(rotation=70)

hours = mdates.DateFormatter('%H:%M')
ax.xaxis.set_major_formatter(hours)

#这里需要画出三根线，所以需要三组参数， 'g'代表'green'

l1 = ax.plot(day_ravenna,y1,'r',day_faenza,y2,'r',day_cesena,y3,'r',label="Near")
l2 = ax.plot(day_milano,y4,'g',day_asti,y5,'g',day_torino,y6,'g',label="Far")
red_patch = mpatches.Patch(color='red', label='Near')
green_patch = mpatches.Patch(color='green', label='Far')
ax.legend(handles=[red_patch, green_patch])

如果使用一般的办法将会获得下图效果：

通常使用的代码：

import matplotlib.patches as mpatches
# 读取温度和日期数据
y1 = df_ravenna['temp']
x1 = df_ravenna['day']
y2 = df_faenza['temp']
x2 = df_faenza['day']
y3 = df_cesena['temp']
x3 = df_cesena['day']
y4 = df_milano['temp']
x4 = df_milano['day']
y5 = df_asti['temp']
x5 = df_asti['day']
y6 = df_torino['temp']
x6 = df_torino['day']

# 把日期从 string 类型转化为标准的 datetime 类型
day_ravenna = [parser.parse(x) for x in x1]
day_faenza = [parser.parse(x) for x in x2]
day_cesena = [parser.parse(x) for x in x3]
day_milano = [parser.parse(x) for x in x4]
day_asti = [parser.parse(x) for x in x5]
day_torino = [parser.parse(x) for x in x6]

# 调用 subplots() 函数，重新定义 fig, ax 变量
fig, ax = plt.subplots()
plt.xticks(rotation=70)

hours = mdates.DateFormatter('%H:%M')
ax.xaxis.set_major_formatter(hours)

#这里需要画出三根线，所以需要三组参数， 'g'代表'green'

l1 = ax.plot(day_ravenna,y1,'r',day_faenza,y2,'r',day_cesena,y3,'r',label="Near")
l2 = ax.plot(day_milano,y4,'g',day_asti,y5,'g',day_torino,y6,'g',label="Far")
ax.legend()

Reference:
蓝桥云课：使用 Python 3 进行气象数据分析
Matplotlib legend guide

标签：为同,temp,标记,df,parser,Matplotlib,parse,csv,day
来源： https://blog.csdn.net/LikiLyn/article/details/120815885