处理CSV文件格式的数据并用matplotlib可视化

#encoding:utf-8

import csv
from matplotlib import pyplot as plt
from datetime import datetime

#从文件中获取日期和最高气温
filename = 'death_valley_2014.csv'  #死亡谷数据
with open(filename) as f:
    reader = csv.reader(f)
    header_row = next(reader)
    '''
    #打印文件头及其位置
    for index, column_header in enumerate(header_row):
        print(index, column_header)
    '''

    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:      #捕捉ValueError
            print(current_date, "missing data")
        else:
            dates.append(current_date)
            highs.append(high)
            lows.append(low)


    #print(highs)

    fig = plt.figure(dpi = 128, figsize = (10, 6))
    plt.plot(dates, highs, c = 'red', alpha = 0.5)      #Alpha表示透明度
    plt.plot(dates, lows, c = 'Blue', alpha = 0.5)
    plt.fill_between(dates, highs, lows, facecolor = 'Blue', alpha = 0.1)   #填充颜色

    #设置图形格式
    plt.title("Daily high and low temperatures - 2014\nDeath Vally", fontsize = 24)
    plt.xlabel(" ", fontsize = 16)
    plt.ylabel("Temperature(F)", fontsize = 16)
    fig.autofmt_xdate()     #绘制斜的标签， 防止日期重叠
    plt.tick_params(axis = 'both', which = 'major', labelsize = 16)

    #设置x轴, y轴开始的位置
    #plt.axis([dates[0], dates[-1], 0, 80])   #方法1
    plt.xlim(dates[0], dates[-1])       #方法2
    plt.ylim(0, max(highs) + 10)

    plt.show()