Python编程：从入门到实践 16章 下载数据

16 下载数据

16.1 CSV文件格式

16.1.1 分析CSV文件头

1. import csv
3. filename = 'sitka_weather_07-2014.csv'
4. with open(filename) as f:
5.     reader = csv.reader(f)
6.     header_row = next(reader)
7.     print(header_row)

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16.1.2 打印文件头及其位置

1. import csv
3. filename ='sitka_weather_07-2014.csv'
4. with open(filename) as f:
5.     reader = csv.reader(f)
6.     header_row = next(reader)
7.    
8.     for index,cloum_header in enumerate(header_row):
9.         print(index,cloum_header)

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16.3.1 提取并读取数据

1. import csv
3. # 从文件中获取最高气温
4. filename = 'sitka_weather_07-2014.csv'
5. with open(filename) as f:
6.     reader = csv.reader(f)
7.     header_row = next(reader)
8.    
9.     highs = []
10.     for row in reader:
11.         highs.append(row[1])
12.         
13.     print(highs)

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1. import csv
3. #从文件中获取最高气温
4. filename = 'sitka_weather_07-2014.csv'
5. with open(filename) as f:
6.     reader = csv.reader(f)
7.     header_row = next(reader)
8.    
9.     highs = []
10.     for row in reader:
11.         high = int(row[1])
12.         highs.append(high)
13.         
14.     print(highs)

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16.1.4 绘制气温图标

1. import csv
3. from matplotlib import pyplot as plt
5. # 从文件中获取最高气温
6. filename = 'sitka_weather_07-2014.csv'
7. with open(filename) as f:
8.     reader = csv.reader(f)
9.     header_row = next(reader)
10.    
11.     highs = []
12.     for row in reader:
13.         high = int(row[1])
14.         highs.append(high)
15.         
16. # 根据数据绘制图形
17. fig = plt.figure(dpi=128,figsize=(10,6))
18. plt.plot(highs,c='red')
20. #设置图形的格式
21. plt.title("Daily high temperatures, July 2014",fontsize = 24)
22. plt.xlabel('',fontsize=16)
23. plt.ylabel("Temperature (F)", fontsize=16)
24. plt.tick_params(axis='both', which='major', labelsize=16)
26. plt.show()

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16.1.5模块datetime

1. from datetime import datetime
2. first_date = datetime.strptime('2014-7-1','%Y-%m-%d')
3. print(first_date)

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16.1.6 在图表中添加日期

1. import csv
2. from datetime import datetime
3. from matplotlib import pyplot as plt
5. #从文件中获取日期和最高气温
6. filename = 'sitka_weather_07-2014.csv'
7. with open(filename) as f:
8.     reader = csv.reader(f)
9.     header_row = next(reader)
10.    
11.     dates,highs = [],[]
12.     for row in reader:
13.         current_date = datetime.strptime(row[0],"%Y-%m-%d")
14.         dates.append(current_date)
15.         high = int(row[1])
16.         highs.append(high)
17.         
18. # 根据数据绘制图形
19. fig = plt.figure(dpi=128,figsize=(10,6))
20. plt.plot(dates,highs,c='red')
22. # 设置图形的格式
23. plt.title("Daily high temperatures, July 2014", fontsize=24)
24. plt.xlabel('',fontsize=16)
25. fig.autofmt_xdate()
26. plt.ylabel("Temperature (F)", fontsize=16)
27. plt.tick_params(axis='both',which='major',labelsize=16)
29. plt.show()

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16.1.7覆盖更长的时间

1. import csv
2. from datetime import datetime
3. from matplotlib import pyplot as plt
5. # 从文件中获取日期和最高气温
6. filename = 'sitka_weather_2014.csv'
7. with open(filename) as f:
8.     reader = csv.reader(f)
9.     header_row = next(reader)
10.    
11.     dates,highs = [],[]
12.     for row in reader:
13.         current_date = datetime.strptime(row[0],"%Y-%m-%d")
14.         dates.append(current_date)
15.         high = int(row[1])
16.         highs.append(high)
17.         
18. # 根据数据绘制图形
19. fig = plt.figure(dpi=128,figsize=(10,6))
20. plt.plot(dates,highs,c='red')
22. plt.title("Daily high temperatures - 2014", fontsize=24)
23. plt.xlabel('', fontsize=16)
24. fig.autofmt_xdate()
25. plt.ylabel("Temperature (F)", fontsize=16)
26. plt.tick_params(axis='both',which='major',labelsize=16)
28. plt.show()

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16.1.8 再绘制一个数据系列

1. import csv
2. from datetime import datetime
3. from matplotlib import pyplot as plt
5. # 从文件中获取日期和最高气温
6. filename = 'sitka_weather_2014.csv'
7. with open(filename) as f:
8.     reader = csv.reader(f)
9.     header_row = next(reader)
10.    
11.     dates, highs, lows = [], [], []
12.     for row in reader:
13.         current_date = datetime.strptime(row[0],"%Y-%m-%d")
14.         dates.append(current_date)
15.         
16.         high = int(row[1])
17.         highs.append(high)
18.         
19.         low = int(row[3])
20.         lows.append(low)
21.         
22.         # 根据数据绘制图形
23. fig = plt.figure(dpi=128,figsize=(10,6))
24. plt.plot(dates,highs,c='red')
25. plt.plot(dates,lows,c='blue')
27. plt.title("Daily high temperatures - 2014", fontsize=24)
28. plt.xlabel('', fontsize=16)
29. fig.autofmt_xdate()
30. plt.ylabel("Temperature (F)", fontsize=16)
31. plt.tick_params(axis='both',which='major',labelsize=16)
33. plt.show()

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16.1.9 给图片区域着色

1. import csv
2. from datetime import datetime
3. from matplotlib import pyplot as plt
5. # 从文件中获取日期和最高气温
6. filename = 'sitka_weather_2014.csv'
7. with open(filename) as f:
8.     reader = csv.reader(f)
9.     header_row = next(reader)
10.    
11.     dates, highs, lows = [], [], []
12.     for row in reader:
13.         current_date = datetime.strptime(row[0],"%Y-%m-%d")
14.         dates.append(current_date)
15.         
16.         high = int(row[1])
17.         highs.append(high)
18.         
19.         low = int(row[3])
20.         lows.append(low)
21.         
22. # 根据数据绘制图形
23. fig = plt.figure(dpi=128,figsize=(10,6))
24. plt.plot(dates,highs,c='red',alpha=0.5)
25. plt.plot(dates,lows,c='blue',alpha=0.5)
26. plt.fill_between(dates, highs, lows, facecolor='blue', alpha=0.1)
28. plt.title("Daily high temperatures - 2014", fontsize=24)
29. plt.xlabel('', fontsize=16)
30. fig.autofmt_xdate()
31. plt.ylabel("Temperature (F)", fontsize=16)
32. plt.tick_params(axis='both',which='major',labelsize=16)
34. plt.show()

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