How to sum the last 7 days in Pandas between two dates - python-3.x

Question

Here is my raw data
Raw Data
Here is the data (including types) after I add on the column 'Date_2wks_Ago' within Pandas
enter image description here
I would like to add on a new column 'Rainfall_Last7Days' that calculates, for each day, the total amount of rainfall for the last week.
So (ignoring the other columns that aren't relevant) it would look a little like this...
Ideal Dataset
Anyone know how to do this in Pandas?
My data is about 1000 observations long, so not huge.

Answer 1

I think what you are looking for is the rolling() function.
This section recreates a simplified version of table
import pandas as pd
import numpy as np
# Create df
rainfall_from_9am=[4.6
,0.4
,3.6
,3.5
,3.2
,5.5
,2.2
,1.3
,0
,0
,0.04
,0
,0
,0
,0.04
,0.4]
date=['2019-02-03'
,'2019-02-04'
,'2019-02-05'
,'2019-02-06'
,'2019-02-07'
,'2019-02-08'
,'2019-02-09'
,'2019-02-10'
,'2019-02-11'
,'2019-02-12'
,'2019-02-13'
,'2019-02-14'
,'2019-02-15'
,'2019-02-16'
,'2019-02-17'
,'2019-02-18'
]
# Create df from list
df=pd.DataFrame({'rainfall_from_9am':rainfall_from_9am
,'date':date
})
This part calculates the rolling sum of rainfall for the current and previous 6 records.
df['rain_last7days']=df['rainfall_from_9am'].rolling(7).sum()
print(df)
Output:
date rainfall_from_9am rain_last7days
0 2019-02-03 4.60 NaN
1 2019-02-04 0.40 NaN
2 2019-02-05 3.60 NaN
3 2019-02-06 3.50 NaN
4 2019-02-07 3.20 NaN
5 2019-02-08 5.50 NaN
6 2019-02-09 2.20 23.00
7 2019-02-10 1.30 19.70
8 2019-02-11 0.00 19.30
9 2019-02-12 0.00 15.70
10 2019-02-13 0.04 12.24
11 2019-02-14 0.00 9.04
12 2019-02-15 0.00 3.54
13 2019-02-16 0.00 1.34
14 2019-02-17 0.04 0.08
15 2019-02-18 0.40 0.48
Conscious that this output does not match exactly with the example in your original question. Can you please help verify the correct logic you are after?