CSV数据（一）

import csv
from matplotlib import pyplot as plt

filename = 'sitka_wather.csv'

# 打开文件，存储在f中
with open(filename) as f:
    reader = csv.reader(f)

    # 用next函数获取第一行的值
    header_row = next(reader)
    print(header_row)
    header_two = next(reader)   #获取第二行的值
    print(header_two)

    # s对列表使用enumerate()来获取每个元素的索引和值
    # for index,column_header in enumerate(header_row):
    #     print(index,column_header)

    #从文件中获取时间和最高气温,并将字符串转换成数字
    highs = []
    for row in reader:
        hight = int(row[1])  #从第二行开始获取数据
        highs.append(hight)
    print(highs)

# 根据数据绘制图形
fig = plt.figure(dpi=128,figsize=(5,3))
# 将温度传给plot()
plt.plot(highs,c='red')

# 设置图形的格式
plt.title("Daily high temperatures,July 2014",fontsize=12)
plt.xlabel('',fontsize=8)
fig.autofmt_xdate()  #将标签制斜，避免重叠
plt.ylabel('Temperature(F)',fontsize=8)
plt.tick_params(axis='both',which='major',labelsize=8)

plt.show()


执行如下：



CSV文件如下：
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
2014/7/1,64,56,50,53,51,48,96,83,58,30.19,30,29.79,10,10,10,7,4,,0,7,,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,,0,6,,110
2014/7/6,62,58,55,51,50,46,80,71,58,30.13,30.07,29.89,10,10,10,20,10,29,0,6,Rain,213
2014/7/7,61,57,55,56,53,51,96,87,75,30.1,30.07,30.05,10,9,4,16,4,25,0.14,8,Rain,211
2014/7/8,55,54,53,54,53,51,100,94,86,30.1,30.06,30.04,10,6,2,12,5,23,0.84,8,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
2014/7/11,57,56,54,56,54,51,100,94,84,30.02,30,29.98,10,5,2,12,5,,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,,0,6,,318
2014/7/16,61,56,52,51,49,47,89,76,64,30.27,30.23,30.16,10,10,10,15,6,,0,6,,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,,0,8,,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,,0,5,,297
2014/7/22,63,59,55,56,54,52,90,84,77,30.11,30.04,29.99,10,10,10,9,3,,0,6,Rain,240
2014/7/23,62,58,55,54,52,50,87,80,72,30.1,30.03,29.96,10,10,10,8,3,,0,7,,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
2014/7/27,61,58,55,55,54,53,100,92,78,30.1,30.05,29.97,10,9,2,13,5,,0.3,8,Rain,213
2014/7/28,59,56,53,57,54,51,97,94,90,30.06,30,29.96,10,8,2,9,3,,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,,0,3,,217