Question

的Python

我从Wunderground获得了122天的天气数据，没有相等的采样间隔时间。以下是我的数据示例：

Bangor Weather Data from Wunderground
Datetime,Temp(F),Precip(in.),Snow (in.),PET(in./day),Baro(mBar)
    2015-12-02 01:30:00,1.1,0.3,0.0,0.45524647117649564,1017.5 
    2015-12-02 01:53:00,1.1,0.3,0.0,0.45524647117649564,1017.6 
    2015-12-02 02:20:00,1.1,0.3,0.0,0.45524647117649564,1017.2 
    2015-12-02 02:53:00,1.7,0.5,0.0,0.500024812603692,1016.7 
    2015-12-02 02:55:00,1.7,0.3,0.0,0.500024812603692,1016.5 
    2015-12-02 03:09:00,1.1,0.3,0.0,0.45524647117649564,1016.1 
    2015-12-02 03:33:00,1.1,0.5,0.0,0.45524647117649564,1016.1 
    2015-12-02 03:53:00,1.7,0.8,0.0,0.500024812603692,1016.1 
    2015-12-02 04:34:00,1.7,0.5,0.0,0.500024812603692,1015.1 
    2015-12-02 04:46:00,1.7,0.5,0.0,0.500024812603692,1015.1 
    2015-12-02 04:53:00,1.7,0.8,0.0,0.500024812603692,1015.1 
    2015-12-02 05:13:00,1.7,0.0,0.0,0.500024812603692,1014.4

我希望获得整个数据集的每日积雪（重置为新的一天）。我希望我的输出看起来像：

    2015-12-01,0.0
    2015-12-02,0.0
    2015-12-03,1.0
    2015-12-04,3.0
    2015-12-05,0.0
    2015-12-06,1.0

我如何使用pandas来做到这一点？

Answer 1

这就是你想要的吗？

df.groupby(df.Datetime.dt.date)['Snow (in.)'].sum()

这将为您提供每天的雪量（总和）

Answer 2

您也可以使用：

df['Snow (in.)'].resample('D').sum()

使用pandas按天计算累积数据总和

2 个答案: