如何使用Pandas数据框中其他列的条件语句求和一列中的值？

Question

I have a dataframe having 5 columns and 25552 rows. The dataframe structure as follows:

mydf.head(4)

station       date         Lat    Lon       prcp
USC00397992   1998-10-01   44.26  -99.44    0.5
USC00397993   1998-10-01   44.01  -100.35   1.2
USC00397994   1998-10-01   45.65  -97.12    1.1
USC00397995   1998-10-01   43.90  -99.52    0.7

There are many distinct stations in station column and the date column has dates range from 1998-10-01 to 1999-06-30. Also, each distinct station has distinct lat and Lon. The prcp column is a record of precipitations for respective dates. Now I want to find the sum of prcp values for each station date range from 1999-05-01 to 1999-05-07. I want output like this:

station       Lat      Lon     sum_from_May1_to_May7
 USC00397992  44.26  -99.44       2.5 (for instance)
  .             .       .           .
  .             .       .           .

  .  

Answer 1

First filter your data frame

df2 = df.loc[(df.date >= '1999-05-01') & (df.date <= '1999-05-07)]

Then just straightforwardly

df2.groupby('station').prcp.sum()

If you don't want different Lat and Lon grouped together, then

df2.groupby(['station', 'Lat', 'Lon']).prcp.sum()

Answer 2

If you dont want to groupby with respect to lat long:

df[(df['date']>pd.Timestamp(1995,5,1)) & (df['date']<pd.Timestamp(1995,5,7))]\
     .groupby('station').agg({'prcp':'sum', 'Lat' :'first', 'Lon' :'first'})