爬取12个月天气数据/csv数据去除符号并转存为新的csv/绘出最高气温与最低气温折线图并显示在一个表里面

纪念一下搞出来的一个东西，不过都是参考网上的，只懂一些表面的，不会深层的东西，欢迎批评指正

1.爬取2019年7月到2020年6月阜阳地区的天气：

#爬取气温代码
months = []
for year in (2019,):
    for month in range(6,12):
        months.append("%d%02d"%(year, month+1))
for year in (2020,):
    for month in range(0,6):
        months.append("%d%02d"%(year, month+1))
todo_urls = [
    f"http://tianqi.2345.com/t/wea_history/js/{month}/58203_{month}.js"

    for month in months
]
import requests

datas = []
for url in todo_urls:
    r = requests.get(url)
    if r.status_code!=200:
        raise Exception()
    # 去除javascript前后的字符串，得到一个js格式的JSON
    data = r.text.lstrip("var weather_str=").rstrip(";")
    datas.append(data)
import demjson
demjson.decode(datas[0])
tqInfos = demjson.decode(datas[0])["tqInfo"]
# 解析所有月份的数据
all_datas = []

for data in datas:
    tqInfos = demjson.decode(data)["tqInfo"]
    all_datas.extend([x for x in tqInfos if len(x)>0])
len(all_datas)
import csv

with open('./fy_tianqi_2019-2020.csv', 'w', newline='', encoding='utf-8') as csv_file:
    writer = csv.writer(csv_file)

    columns = ['ymd', 'bWendu', 'yWendu', 'tianqi', 'fengxiang', 'fengli', 'aqi', 'aqiInfo', 'aqiLevel']
    writer.writerow(columns)

    for data in all_datas:
        writer.writerow([data[column] for column in columns])

爬出来的数据示例：

2.去除上csv表中的摄氏度符号，并转存为新的csv：

#去除摄氏度符号，再转存为datadatadata.csv
import re
#正则去标
import csv
import codecs
import json
import pandas as pd
import numpy
"""
def etl(content):
    content = re.sub("[℃]+", " ", content)
    content = re.sub(r" {2,}", " ", content)
    return content
"""
list = []
with open('fy_tianqi_2019-2020.csv', 'rt',encoding='UTF-8') as f:
    reader = csv.reader(f)
    header_row = next(reader)
    for row in reader:
        for word in row:
            str2 = word.replace('℃', '')
            list.append(str2)
            #print(str2)
#print(list)
#将一维列表转置为二维列表，方便后面转存
b=numpy.array(list).reshape(344,9)
print(b)
print(numpy.shape(b))
#给新表添加表头
name = ["ymd","bWendu","yWendu","tianqi","fengxiang","fengli","aqi","aqiInfo","aqiLevel"]
csv_list = pd.DataFrame(columns=name, data=b)
#转存为新的csv表
csv_list.to_csv('datadatadata1.csv')

如下，转存好的已经去除了摄氏度符号：

3.根据上面的数据表可视化出12个月的最高气温和最低气温变化图，并将两个折线图显示在一个表里面

#画出最高气温和最低气温的天气折线图
import csv
with open('datadatadata.csv', 'rt',encoding="utf-8") as f:
    reader = csv.reader(f)
    header_row = next(reader)
    #for row in reader:
      #  print(row)
    date = []
    max_temperature = []
    low_temperature = []
    for row in reader:
        #date.append(row[1])
        max_temperature.append(int(row[2]))
        low_temperature.append(int(row[3]))
print(max_temperature)
import matplotlib.pyplot as plt

plt.plot(max_temperature,c='red')
plt.plot(low_temperature,c='blue')
plt.title("The Daily high and low temperstures of FuYang -2019_7——2020_6",fontsize=24)
plt.show()