自己寫的代碼

#文件1.pyimport csvimport matplotlib.pyplot as pltfrom datetime import datetimefrom read_fun import read_fundeath_valley_whe = 'death_valley_2014.csv' sitka_whe = 'sitka_weather_2014.csv't1,t2 = [],[] d1,d2 = [],[]with open(death_valley_whe) as f:reader = csv.reader(f)header_row = next(reader)read_fun(reader,t1,d1)with open(sitka_whe) as f1:reader = csv.reader(f1)header_row = next(reader)read_fun(reader,t2,d2)fig = plt.figure(dpi=128,figsize=(10,6)) plt.plot(d1,t1,alpha =0.5) #plt.plot(dates2,sitka_mean_tem,c='blue',alpha=0.5) plt.title("Temperature in death valley and sitka whether",fontsize=10) fig.autofmt_xdate() plt.xlabel("date",fontsize = 10) plt.ylabel("temperature Dead-valley(red) and Sitka(blue)",fontsize=10) plt.tick_params(axis='both',which='major',labelsize=10) plt.ylim(10,120)plt.show() #文件 read_fun.py from datetime import datetime def read_fun(reader,tempus,dates):for row in reader:try:date = datetime.strptime(row[0],'%Y-%m-%d')mean_tem = row[2]except ValueError:print(date + " , missing data ")else:tempus.append(mean_tem)dates.append(date)print(date)

已經解決。

自己分析，如果日期集合和溫度集合都是正確的，那么不該出現錯誤，后來自己把日期集合數出來，沒錯，但是把溫度集合數出來如下：

['42', '47', '46', '47', '44', '40', '44', '40', '42', '44', '47', '50', '46', '50', '50', '50', '50', '48', '48', '49', '45', '52', '46', '54', '54', '48', '50', '52', '54', '60', '52', '44', '40', '40', '39', '41', '45', '50', '56', '57', '62', '54', '54', '56', '58', '60', '', '56', '61', '52', '53', '54', '55', '56', '56', '55', '62', '52', '50', '48', '51', '59', '58', '64', '62', '58', '60', '62', '58', '58', '56', '58', '62', '62', '68', '57', '54', '56', '61', '62', '62', '62', '62', '58', '58', '55', '64', '60', '58', '54', '51', '50', '58', '54', '63', '65', '67', '74', '70', '72', '68', '70', '66', '69', '70', '70', '71', '70', '72', '72', '65', '60', '65', '64', '58', '58', '63', '70', '69', '70', '75', '75', '80', '72', '60', '59', '66', '64', '69', '68', '70', '70', '75', '80', '84', '80', '74', '64', '61', '64', '68', '77', '79', '83', '82', '84', '75', '76', '80', '75', '80', '76', '78', '81', '81', '82', '88', '90', '88', '86', '84', '86', '78', '78', '81', '78', '74', '78', '82', '84', '83', '83', '84', '86', '85', '81', '86', '86', '88', '94', '91', '90', '90', '88', '88', '92', '92', '90', '86', '84', '86', '91', '93', '90', '90', '88', '86', '87', '85', '86', '86', '90', '88', '92', '89', '94', '88', '88', '90', '91', '91', '87', '76', '80', '82', '82', '82', '83', '86', '84', '85', '86', '87', '85', '83', '84', '84', '88', '82', '78', '77', '82', '84', '81', '80', '80', '80', '83', '84', '85', '88', '82', '85', '85', '82', '81', '82', '86', '84', '80', '79', '80', '82', '82', '84', '87', '87', '86', '84', '75', '77', '78', '77', '78', '76', '82', '76', '68', '64', '68', '70', '70', '68', '68', '71', '73', '73', '74', '72', '74', '70', '70', '72', '66', '67', '74', '64', '66', '65', '70', '70', '66', '64', '67', '68', '74', '64', '60', '62', '62', '64', '62', '54', '52', '53', '50', '57', '60', '61', '62', '62', '62', '56', '56', '59', '60', '54', '49', '44', '46', '52', '52', '55', '50', '52', '47', '48', '51', '53', '52', '60', '59', '50', '47', '55', '56', '53', '52', '51', '52', '52', '48', '52', '50', '47', '43', '42', '41', '47', '44', '42', '37', '50', '52', '48', '47', '42', '37', '38', '33']

純粹都是字符型的。但是畫圖縱坐標要求是數值類型的變量（實屬類型的），到此，恍然大悟，忘記把字符型數據進行轉換了,解決方法如下：

把 文件read_fun.py 第7行的變為如下形式：

mean_tem = int(row[2])

自己后來又優化了下代碼：

#文件1.pyimport csvfrom matplotlib import pyplot as pltfrom datetime import datetimefrom fun import read_fundeath_valley_whe = 'death_valley_2014.csv' sitka_whe = 'sitka_weather_2014.csv' #t1,d1代表死亡峽谷的日期和平均氣溫 #t2,d2代表錫特卡的日期和平均氣溫 t1,t2 = [],[] d1,d2 = [],[]read_fun(death_valley_whe,t1,d1) read_fun(sitka_whe,t2,d2)fig = plt.figure(dpi=128,figsize=(10,6)) plt.plot(d1,t1,c='red',alpha =0.5) plt.plot(d2,t2,c='blue',alpha=0.5) plt.title("Temperature in death valley and sitka whether",fontsize=10) fig.autofmt_xdate() plt.xlabel("date",fontsize = 10) plt.ylabel("temperature Dead-valley(red) and Sitka(blue)",fontsize=10) plt.tick_params(axis='both',which='major',labelsize=10) plt.show() #文件 fun.pyfrom datetime import datetime import csvdef read_fun(file_var,tempus,dates):with open(file_var) as f:reader = csv.reader(f)header_row = next(reader)for row in reader:try:date = datetime.strptime(row[0],'%Y-%m-%d')#mean_tem 是平均氣溫，這里必須轉換成int形式#因為文件內的數據默認不是int類型的，可能是字符串類型的或者字符類型的mean_tem = int(row[2])except ValueError:print(date," , missing data ")else:tempus.append(mean_tem)dates.append(date)

最后，作為一個復習，自己又把自己家鄉（內蒙古烏蘭察布市）2021年的全年最高氣溫和最低氣溫畫了一個圖，具體過程如下：

先從烏蘭察布市天氣網站下載2021年的全年氣溫，下載是1個月1個月地下載，還有很多不必要的數據，下載下來后自己用c++語言把需要的日期、最高氣溫、最低氣溫提取出來（其余不要，不會用python提取數據。只能用c++了），最后處理出來的數據如下：第一列代表日期，第二列代表這一天的最低氣溫，第三列代表這一天的最高氣溫，自己也把它放在date_file.csv文件中，不得不說，計算機處理重復性的事情還真是一絕，編好代碼不到1秒給你處理完畢，如下：

2021-01-01,-8,-18 2021-01-02,-7,-20 2021-01-03,-7,-22 2021-01-04,-14,-23 2021-01-05,-13,-30 2021-01-06,0,-30 2021-01-07,-19,-27 2021-01-08,-13,-21 2021-01-09,-7,-19 2021-01-10,-8,-17 2021-01-11,-10,-17 2021-01-12,-4,-14 2021-01-13,-3,-10 2021-01-14,0,-16 2021-01-15,-10,-21 2021-01-16,-12,-19 2021-01-17,-8,-16 2021-01-18,-1,-12 2021-01-19,3,-13 2021-01-20,2,-14 2021-01-21,1,-15 2021-01-22,3,-11 2021-01-23,3,-11 2021-01-24,3,-10 2021-01-25,0,-14 2021-01-26,-4,-14 2021-01-27,-5,-22 2021-01-28,-8,-17 2021-01-29,-1,-12 2021-01-30,0,-10 2021-01-31,0,-16 2021-02-01,-11,-21 2021-02-02,-8,-16 2021-02-03,-5,-13 2021-02-04,1,-10 2021-02-05,2,-9 2021-02-06,4,-13 2021-02-07,-2,-13 2021-02-08,0,-10 2021-02-09,5,-11 2021-02-10,8,-4 2021-02-11,12,-9 2021-02-12,8,-4 2021-02-13,6,-7 2021-02-14,-4,-15 2021-02-15,0,-16 2021-02-16,-9,-17 2021-02-17,-1,-13 2021-02-18,7,-6 2021-02-19,9,-1 2021-02-20,12,-1 2021-02-21,12,-7 2021-02-22,4,-7 2021-02-23,3,-6 2021-02-24,8,-6 2021-02-25,7,-7 2021-02-26,7,-4 2021-02-27,5,-4 2021-02-28,-3,-9 2021-03-01,-1,-10 2021-03-02,5,-6 2021-03-03,8,-3 2021-03-04,11,-5 2021-03-05,0,-9 2021-03-06,3,-8 2021-03-07,8,-6 2021-03-08,9,-5 2021-03-09,11,-1 2021-03-10,12,0 2021-03-11,13,-1 2021-03-12,9,-5 2021-03-13,11,-1 2021-03-14,14,-7 2021-03-15,0,-10 2021-03-16,3,-6 2021-03-17,6,-2 2021-03-18,2,-2 2021-03-19,3,-6 2021-03-20,-1,-10 2021-03-21,3,-7 2021-03-22,9,-3 2021-03-23,14,0 2021-03-24,13,-3 2021-03-25,16,5 2021-03-26,14,-1 2021-03-27,16,-4 2021-03-28,6,-6 2021-03-29,9,-4 2021-03-30,16,1 2021-03-31,11,3 2021-04-01,9,1 2021-04-02,9,-2 2021-04-03,6,-6 2021-04-04,11,-1 2021-04-05,11,-1 2021-04-06,12,-3 2021-04-07,13,-1 2021-04-08,16,1 2021-04-09,16,3 2021-04-10,15,5 2021-04-11,11,2 2021-04-12,2,-8 2021-04-13,6,-4 2021-04-14,13,1 2021-04-15,10,-3 2021-04-16,4,-5 2021-04-17,13,-2 2021-04-18,17,1 2021-04-19,22,6 2021-04-20,22,6 2021-04-21,19,6 2021-04-22,15,5 2021-04-23,20,3 2021-04-24,13,5 2021-04-25,12,7 2021-04-26,15,1 2021-04-27,9,-1 2021-04-28,10,1 2021-04-29,6,0 2021-04-30,8,0 2021-05-01,13,1 2021-05-02,22,8 2021-05-03,19,1 2021-05-04,8,1 2021-05-05,18,3 2021-05-06,8,0 2021-05-07,20,4 2021-05-08,15,6 2021-05-09,20,5 2021-05-10,21,8 2021-05-11,25,7 2021-05-12,17,8 2021-05-13,19,10 2021-05-14,22,7 2021-05-15,13,5 2021-05-16,17,6 2021-05-17,20,10 2021-05-18,22,10 2021-05-19,23,10 2021-05-20,20,9 2021-05-21,26,13 2021-05-22,25,6 2021-05-23,13,2 2021-05-24,13,4 2021-05-25,24,8 2021-05-26,18,6 2021-05-27,18,4 2021-05-28,22,9 2021-05-29,25,10 2021-05-30,25,11 2021-05-31,16,4 2021-06-01,19,5 2021-06-02,14,5 2021-06-03,17,8 2021-06-04,20,8 2021-06-05,25,13 2021-06-06,25,13 2021-06-07,27,12 2021-06-08,18,9 2021-06-09,19,7 2021-06-10,25,13 2021-06-11,26,14 2021-06-12,28,16 2021-06-13,23,16 2021-06-14,26,14 2021-06-15,27,16 2021-06-16,16,10 2021-06-17,21,10 2021-06-18,23,11 2021-06-19,24,11 2021-06-20,27,12 2021-06-21,28,12 2021-06-22,28,15 2021-06-23,18,15 2021-06-24,21,15 2021-06-25,26,15 2021-06-26,27,16 2021-06-27,28,15 2021-06-28,29,17 2021-06-29,28,14 2021-06-30,27,13 2021-07-01,28,14 2021-07-02,21,12 2021-07-03,22,13 2021-07-04,26,15 2021-07-05,23,12 2021-07-06,25,14 2021-07-07,25,15 2021-07-08,28,16 2021-07-09,30,18 2021-07-10,32,17 2021-07-11,29,15 2021-07-12,17,16 2021-07-13,30,20 2021-07-14,31,19 2021-07-15,28,18 2021-07-16,29,18 2021-07-17,24,17 2021-07-18,26,16 2021-07-19,27,17 2021-07-20,27,16 2021-07-21,24,16 2021-07-22,22,15 2021-07-23,26,17 2021-07-24,28,18 2021-07-25,27,16 2021-07-26,26,14 2021-07-27,23,15 2021-07-28,24,16 2021-07-29,25,14 2021-07-30,29,16 2021-07-31,26,12 2021-08-01,22,11 2021-08-02,25,16 2021-08-03,18,13 2021-08-04,25,14 2021-08-05,24,13 2021-08-06,26,14 2021-08-07,28,15 2021-08-08,23,13 2021-08-09,26,13 2021-08-10,25,12 2021-08-11,25,11 2021-08-12,26,12 2021-08-13,26,14 2021-08-14,26,14 2021-08-15,25,13 2021-08-16,27,15 2021-08-17,27,15 2021-08-18,25,15 2021-08-19,24,13 2021-08-20,22,10 2021-08-21,26,14 2021-08-22,25,11 2021-08-23,24,8 2021-08-24,14,8 2021-08-25,15,9 2021-08-26,18,7 2021-08-27,20,9 2021-08-28,19,9 2021-08-29,21,9 2021-08-30,23,13 2021-08-31,22,13 2021-09-01,24,12 2021-09-02,25,13 2021-09-03,26,13 2021-09-04,16,10 2021-09-05,15,8 2021-09-06,20,10 2021-09-07,23,11 2021-09-08,23,10 2021-09-09,21,8 2021-09-10,28,12 2021-09-11,26,12 2021-09-12,25,13 2021-09-13,22,13 2021-09-14,23,13 2021-09-15,17,11 2021-09-16,18,6 2021-09-17,21,8 2021-09-18,20,11 2021-09-19,17,8 2021-09-20,19,7 2021-09-21,20,6 2021-09-22,24,10 2021-09-23,25,11 2021-09-24,19,11 2021-09-25,20,9 2021-09-26,18,9 2021-09-27,21,7 2021-09-28,23,6 2021-09-29,22,6 2021-09-30,19,2 2021-10-01,19,5 2021-10-02,24,10 2021-10-03,16,4 2021-10-04,7,2 2021-10-05,9,3 2021-10-06,8,0 2021-10-07,13,2 2021-10-08,12,5 2021-10-09,12,-1 2021-10-10,9,-3 2021-10-11,12,-5 2021-10-12,14,6 2021-10-13,12,6 2021-10-14,13,-1 2021-10-15,6,-9 2021-10-16,6,-5 2021-10-17,10,-2 2021-10-18,10,-9 2021-10-19,7,-5 2021-10-20,10,-7 2021-10-21,8,-6 2021-10-22,9,-6 2021-10-23,12,-3 2021-10-24,13,-1 2021-10-25,13,-2 2021-10-26,10,-6 2021-10-27,11,-3 2021-10-28,10,0 2021-10-29,12,-5 2021-10-30,9,-6 2021-10-31,6,-7 2021-11-01,9,-4 2021-11-02,8,-3 2021-11-03,10,-3 2021-11-04,13,0 2021-11-05,14,-7 2021-11-06,-7,-15 2021-11-07,-9,-16 2021-11-08,-5,-11 2021-11-09,-2,-6 2021-11-10,4,-10 2021-11-11,1,-8 2021-11-12,3,-7 2021-11-13,6,-6 2021-11-14,5,-10 2021-11-15,3,-8 2021-11-16,6,-8 2021-11-17,5,-5 2021-11-18,6,-9 2021-11-19,4,-8 2021-11-20,1,-12 2021-11-21,-7,-17 2021-11-22,-5,-13 2021-11-23,2,-11 2021-11-24,2,-8 2021-11-25,5,-11 2021-11-26,5,-7 2021-11-27,7,-4 2021-11-28,7,-5 2021-11-29,-2,-12 2021-11-30,-6,-12 2021-12-01,-1,-12 2021-12-02,2,-10 2021-12-03,4,-10 2021-12-04,5,-8 2021-12-05,4,-12 2021-12-06,2,-13 2021-12-07,2,-6 2021-12-08,2,-8 2021-12-09,1,-9 2021-12-10,2,-10 2021-12-11,-2,-17 2021-12-12,-5,-15 2021-12-13,-2,-13 2021-12-14,-1,-11 2021-12-15,0,-15 2021-12-16,-9,-21 2021-12-17,-11,-21 2021-12-18,-6,-12 2021-12-19,0,-10 2021-12-20,2,-11 2021-12-21,3,-13 2021-12-22,2,-12 2021-12-23,-5,-19 2021-12-24,-14,-26 2021-12-25,-15,-22 2021-12-26,-6,-17 2021-12-27,-3,-15 2021-12-28,-2,-18 2021-12-29,-4,-13 2021-12-30,-3,-14 2021-12-31,-1,-15

?接下來就是寫python3代碼處理數據，畫圖了：

#wlcb_tem.pyimport csv from datetime import datetime from matplotlib import pyplot as plt from read_fun import read_fun#讀入烏蘭察布2021年全年日期、最高氣溫和最低氣溫 dates = [] highs = [] lows = [] read_fun(dates,highs,lows)#畫圖分析 fig = plt.figure(dpi = 128,figsize=(10,6)) plt.plot(dates,highs,c='red',alpha=0.5) plt.plot(dates,lows,c='blue',alpha=0.5)plt.title("Ulanqab City daily high(red) and low(blue) temperatures - 2021") plt.xlabel("",fontsize=14) plt.ylabel("Temperature (Celsius)") plt.tick_params(axis='both',which='major',labelsize=14) fig.autofmt_xdate() plt.fill_between(dates,highs,lows,alpha=0.1)plt.show() #read_fun.pyimport csv from datetime import datetime #dates:日期集合 #highs:最高氣溫集合 #lows:最低氣溫集合 def read_fun(dates,highs,lows):file_name = "date_file.csv"with open(file_name) as f:reader = csv.reader(f)header_row = next(reader)for row in reader:try:date = datetime.strptime(row[0],"%Y-%m-%d")#必須把兩個氣溫都轉換成int類型，不然畫圖y軸坐標會亂碼high = int(row[1])low = int(row[2])except ValueError:print(date,",data missing.")else:dates.append(date)highs.append(high)lows.append(low)

總結

以上是生活随笔為你收集整理的python的16.1节课后练习16-2比较希特卡和死亡谷的气温的问题，最后图像为什么出现乱码？的全部內容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網站內容還不錯，歡迎將生活随笔推薦給好友。