python读csv格式文档并用matplotlib绘制图表

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

fileName = 'sitka_weather_07-2014.csv'
with open(fileName) as f:
    reader = csv.reader(f)
    header_row = next(reader)
    # print(header_row)

    # for index, column_header in enumerate(header_row):  # 在同时需要index和value值的时候可以使用 enumerate
    #     # print(index, column_header)

    dates,hights = [], []

    for row in reader:
        current_date = datetime.strptime(row[0], '%Y-%m-%d')
        dates.append(current_date)
        hights.append(int(row[1]))

    print(hights)

    fig = plt.figure(dpi=128, figsize=(10, 6))
    plt.plot(dates, hights, c='red')
    # 设置图形的格式
    plt.title("Dialy high temperatures,July 2014", fontsize=24)
    plt.xlabel('', fontsize=16)
    fig.autofmt_xdate()
    plt.ylabel("Temperature (F)", fontsize=16)
    plt.tick_params(axis='both', which='major', labelsize=16)
    plt.savefig("temperature.png", bbox_inches='tight')
    plt.show()

　　运行结果

temperature.png

现在开始读取全年并展示，代码如下：

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

fileName = 'sitka_weather_2014.csv'
with open(fileName) as f:
    reader = csv.reader(f)
    header_row = next(reader)

    dates,hights, lows = [], [], []

    for row in reader:
        current_date = datetime.strptime(row[0], '%Y-%m-%d')
        dates.append(current_date)
        hights.append(int(row[1]))
        lows.append(int(row[3]))

    fig = plt.figure(dpi=128, figsize=(10, 6))
    plt.plot(dates, hights, c='red', alpha=0.5)
    plt.plot(dates, lows, c='blue', alpha=0.5)
    plt.fill_between(dates, hights, lows, facecolor='blue', alpha=0.1)
    # 设置图形的格式
    plt.title("Dialy high temperatures, 2014", fontsize=24)
    plt.xlabel('', fontsize=16)
    fig.autofmt_xdate()
    plt.ylabel("Temperature (F)", fontsize=16)
    plt.tick_params(axis='both', which='major', labelsize=16)
    plt.savefig("temperature.png", bbox_inches='tight')
    plt.show()

　　运行效果：

python读csv格式文档并用matplotlib绘制图表

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