3.读取CSV文件并进行可视化处理

import csv
import matplotlib.pyplot as plt
from datetime import datetime
plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签
plt.rcParams['axes.unicode_minus']=False #用来正常显示负号

filename = 'sitka_weather_07-2018_simple.csv'
highs = []
dates = []
with open(filename) as f:
    reader = csv.reader(f)
    header_row = next(reader)
    # print(header_row)

    for row in reader:
        current_time = datetime.strptime(row[2],'%Y-%m-%d')
        high = int(row[5])
        highs.append(high)
        dates.append(current_time)
    print(highs)
    # for index,column_header in enumerate(header_row):
    #     print(index,column_header)
fig ,ax =plt.subplots()
ax.plot(dates,highs,c='red')

fig.autofmt_xdate() #用来获取倾斜的标签，防止标签遮挡
ax.set_title("2018年七月每日最高温度",fontsize=24)
ax.set_xlabel('',fontsize='16')
ax.set_ylabel('温度(F)',fontsize='16')
plt.show()

可视化效果：

import csv
import matplotlib.pyplot as plt
from datetime import datetime
plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签
plt.rcParams['axes.unicode_minus']=False #用来正常显示负号

filename = 'Data/sitka_weather_2018_simple.csv'
highs = []
dates = []
lows = []
with open(filename) as f:
    reader = csv.reader(f)
    header_row = next(reader)
    # print(header_row)

    for row in reader:
        current_time = datetime.strptime(row[2],'%Y-%m-%d')
        high = int(row[5])
        low = int(row[6])
        highs.append(high)
        dates.append(current_time)
        lows.append(low)
    print(highs)
    # for index,column_header in enumerate(header_row):
    #     print(index,column_header)
fig ,ax =plt.subplots()
ax.plot(dates,highs,c='red',alpha=0.5)
ax.plot(dates,lows,c='red',alpha=0.5) #alpha参数设置颜色透明度
ax.fill_between(dates,highs,lows,facecolor='blue',alpha=0.8) #指定出填充区域

fig.autofmt_xdate() #用来获取倾斜的标签，防止标签遮挡
ax.set_title("2018年七月每日最高温度",fontsize=24)
ax.set_xlabel('',fontsize='16')
ax.set_ylabel('温度(F)',fontsize='16')
plt.show()

可视化：