使用csv模块处理CSV(逗号分割的值)格式存储的天气数据

csv/highs_lows.py

+import csv
+from datetime import datetime
+
+from matplotlib import pyplot as plt
+
+# 从文件中获取每天的最高温度
+filename = 'sitka_weather_07-2014.csv'
+with open(filename) as f:
+	reader = csv.reader(f)
+	# next(reader)函数是返回reader阅读器的下一行，目前只调用了一次，所以是头行
+	header_row = next(reader)
+	# 打印头行，header_row它是一个列表
+	# print(header_row)
+	# enumerate() 获取每个元素的索引及其值
+	for index, column_header in enumerate(header_row):
+		print(index, column_header)
+
+	# 第二列每天的最高温度
+	dates, highs = [], []
+	for row in reader:
+		current_date = datetime.strptime(row[0], '%Y-%m-%d')
+		print(current_date)
+		dates.append(current_date)
+		high = int(row[1])
+		highs.append(high)
+
+	print(dates)
+	print(highs)
+
+	# 根据数据绘制图形
+	fig = plt.figure(dpi=128, figsize=(10, 6))
+	plt.plot(dates, highs, c='red')
+
+	# 设置图形的格式
+	plt.title("Daily high temperatures, July 2014", fontsize=24)
+	plt.xlabel("", fontsize=16)
+	# 绘制斜的日期标签
+	fig.autofmt_xdate()
+	plt.ylabel("Temperature (F)", fontsize=16)
+	plt.tick_params(axis='both', which='major', labelsize=16)
+
+	plt.show()

csv/highs_lows2.py

+import csv
+from datetime import datetime
+
+from matplotlib import pyplot as plt
+
+# 从文件中获取每天的最高温度
+filename = 'sitka_weather_2014.csv'
+with open(filename) as f:
+	reader = csv.reader(f)
+	# next(reader)函数是返回reader阅读器的下一行，目前只调用了一次，所以是头行
+	header_row = next(reader)
+	# 打印头行，header_row它是一个列表
+	# print(header_row)
+	# enumerate() 获取每个元素的索引及其值
+	for index, column_header in enumerate(header_row):
+		print(index, column_header)
+
+	# 第二列每天的最高温度
+	dates, highs, lows = [], [], []
+	for row in reader:
+		current_date = datetime.strptime(row[0], '%Y-%m-%d')
+		print(current_date)
+		dates.append(current_date)
+
+		high = int(row[1])
+		highs.append(high)
+
+		low = int(row[3])
+		lows.append(low)
+
+	print(dates)
+	print(highs)
+
+	# 根据数据绘制图形
+	fig = plt.figure(dpi=128, figsize=(10, 6))
+	plt.plot(dates, highs, c='red')
+	plt.plot(dates, lows, c='blue')
+
+	# facecolor指定填充区域的颜色
+	plt.fill_between(dates, highs, lows, facecolor='blue', alpha=0.1)
+	# 设置图形的格式
+	plt.title("Daily high and low temperatures - 2014", fontsize=24)
+	plt.xlabel("", fontsize=16)
+	# 绘制斜的日期标签
+	fig.autofmt_xdate()
+	plt.ylabel("Temperature (F)", fontsize=16)
+	plt.tick_params(axis='both', which='major', labelsize=16)
+
+	plt.show()

csv/highs_lows3.py

+import csv
+from datetime import datetime
+
+from matplotlib import pyplot as plt
+
+# 从文件中获取每天的最高温度
+filename = 'death_valley_2014.csv'
+with open(filename) as f:
+	reader = csv.reader(f)
+	# next(reader)函数是返回reader阅读器的下一行，目前只调用了一次，所以是头行
+	header_row = next(reader)
+	# 打印头行，header_row它是一个列表
+	# print(header_row)
+	# enumerate() 获取每个元素的索引及其值
+	for index, column_header in enumerate(header_row):
+		print(index, column_header)
+
+	# 第二列每天的最高温度
+	dates, highs, lows = [], [], []
+	for row in reader:
+		try:
+			current_date = datetime.strptime(row[0], '%Y-%m-%d')
+			high = int(row[1])
+			low = int(row[3])
+		except ValueError:
+			print(current_date, '错误数据')
+		else:
+			dates.append(current_date)
+			highs.append(high)
+			lows.append(low)
+
+	# 根据数据绘制图形
+	fig = plt.figure(dpi=128, figsize=(10, 6))
+	plt.plot(dates, highs, c='red')
+	plt.plot(dates, lows, c='blue')
+
+	# facecolor指定填充区域的颜色
+	plt.fill_between(dates, highs, lows, facecolor='blue', alpha=0.1)
+	# 设置图形的格式
+	title = "Daily high and low temperatures - 2014\nDeath Valley CA"
+	plt.title(title, fontsize=20)
+	plt.xlabel("", fontsize=16)
+	# 绘制斜的日期标签
+	fig.autofmt_xdate()
+	plt.ylabel("Temperature (F)", fontsize=16)
+	plt.tick_params(axis='both', which='major', labelsize=16)
+
+	plt.show()

csv/sitka_weather_07-2014.csv

+AKDT,Max TemperatureF,Mean TemperatureF,Min TemperatureF,Max Dew PointF,MeanDew PointF,Min DewpointF,Max Humidity, Mean Humidity, Min Humidity, Max Sea Level PressureIn, Mean Sea Level PressureIn, Min Sea Level PressureIn, Max VisibilityMiles, Mean VisibilityMiles, Min VisibilityMiles, Max Wind SpeedMPH, Mean Wind SpeedMPH, Max Gust SpeedMPH,PrecipitationIn, CloudCover, Events, WindDirDegrees
+2014-7-1,64,56,50,53,51,48,96,83,58,30.19,30.00,29.79,10,10,10,7,4,,0.00,7,,337
+2014-7-2,71,62,55,55,52,46,96,80,51,29.81,29.75,29.66,10,9,2,13,5,,0.14,7,Rain,327
+2014-7-3,64,58,53,55,53,51,97,85,72,29.88,29.86,29.81,10,10,8,15,4,,0.01,6,,258
+2014-7-4,59,56,52,52,51,50,96,88,75,29.91,29.89,29.87,10,9,2,9,2,,0.07,7,Rain,255
+2014-7-5,69,59,50,52,50,46,96,72,49,29.88,29.82,29.79,10,10,10,13,5,,0.00,6,,110
+2014-7-6,62,58,55,51,50,46,80,71,58,30.13,30.07,29.89,10,10,10,20,10,29,0.00,6,Rain,213
+2014-7-7,61,57,55,56,53,51,96,87,75,30.10,30.07,30.05,10,9,4,16,4,25,0.14,8,Rain,211
+2014-7-8,55,54,53,54,53,51,100,94,86,30.10,30.06,30.04,10,6,2,12,5,23,0.84,8,Rain,159
+2014-7-9,57,55,53,56,54,52,100,96,83,30.24,30.18,30.11,10,7,2,9,5,,0.13,8,Rain,201
+2014-7-10,61,56,53,53,52,51,100,90,75,30.23,30.17,30.03,10,8,2,8,3,,0.03,8,Rain,215
+2014-7-11,57,56,54,56,54,51,100,94,84,30.02,30.00,29.98,10,5,2,12,5,,1.28,8,Rain,250
+2014-7-12,59,56,55,58,56,55,100,97,93,30.18,30.06,29.99,10,6,2,15,7,26,0.32,8,Rain,275
+2014-7-13,57,56,55,58,56,55,100,98,94,30.25,30.22,30.18,10,5,1,8,4,,0.29,8,Rain,291
+2014-7-14,61,58,55,58,56,51,100,94,83,30.24,30.23,30.22,10,7,0,16,4,,0.01,8,Fog,307
+2014-7-15,64,58,55,53,51,48,93,78,64,30.27,30.25,30.24,10,10,10,17,12,,0.00,6,,318
+2014-7-16,61,56,52,51,49,47,89,76,64,30.27,30.23,30.16,10,10,10,15,6,,0.00,6,,294
+2014-7-17,59,55,51,52,50,48,93,84,75,30.16,30.04,29.82,10,10,6,9,3,,0.11,7,Rain,232
+2014-7-18,63,56,51,54,52,50,100,84,67,29.79,29.69,29.65,10,10,7,10,5,,0.05,6,Rain,299
+2014-7-19,60,57,54,55,53,51,97,88,75,29.91,29.82,29.68,10,9,2,9,2,,0.00,8,,292
+2014-7-20,57,55,52,54,52,50,94,89,77,29.92,29.87,29.78,10,8,2,13,4,,0.31,8,Rain,155
+2014-7-21,69,60,52,53,51,50,97,77,52,29.99,29.88,29.78,10,10,10,13,4,,0.00,5,,297
+2014-7-22,63,59,55,56,54,52,90,84,77,30.11,30.04,29.99,10,10,10,9,3,,0.00,6,Rain,240
+2014-7-23,62,58,55,54,52,50,87,80,72,30.10,30.03,29.96,10,10,10,8,3,,0.00,7,,230
+2014-7-24,59,57,54,54,52,51,94,84,78,29.95,29.91,29.89,10,9,3,17,4,28,0.06,8,Rain,207
+2014-7-25,57,55,53,55,53,51,100,92,81,29.91,29.87,29.83,10,8,2,13,3,,0.53,8,Rain,141
+2014-7-26,57,55,53,57,55,54,100,96,93,29.96,29.91,29.87,10,8,1,15,5,24,0.57,8,Rain,216
+2014-7-27,61,58,55,55,54,53,100,92,78,30.10,30.05,29.97,10,9,2,13,5,,0.30,8,Rain,213
+2014-7-28,59,56,53,57,54,51,97,94,90,30.06,30.00,29.96,10,8,2,9,3,,0.61,8,Rain,261
+2014-7-29,61,56,51,54,52,49,96,89,75,30.13,30.02,29.95,10,9,3,14,4,,0.25,6,Rain,153
+2014-7-30,61,57,54,55,53,52,97,88,78,30.31,30.23,30.14,10,10,8,8,4,,0.08,7,Rain,160
+2014-7-31,66,58,50,55,52,49,100,86,65,30.31,30.29,30.26,10,9,3,10,4,,0.00,3,,217