Skipping over a number/range of values in a single row in a dataframe-CodePudding

I have a long row that contains all numbers. The data are all associated with a week so Week 1 has a data point, Week 2 has a point and so on. I need to take the average of the data every 3 weeks, skip 2 weeks and then continue taking the average. This is a short sample of my original list:

import pandas as pd
import numpy as np

data = {'Name': ['Week 1',  'Week 2',   'Week 3',   'Week 4',   'Week 5',   
                 'Week 6',  'Week 7',   'Week 8',   'Week 9',   'Week 10',  'Week 11',  'Week 12'],
        'Value': [1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1,2]
            }

df = pd.DataFrame(data)

avg_goodweeks = np.mean(np.concatenate((df.values[1:3], df.values[4:6], df.values[7:9],
                                        df.values[10:12])))

avg_badweeks = np.mean(np.concatenate((df.values[3], df.values[6], df.values[9],
                                        df.values[12])))

So the average of this would ideally be the values of week 1, 2, 3, 6, 7, 8, 11, 12, but I would like to be able to set up either a range or block of 2 weeks or something of that order to read through the row and repeat the 3 weeks on 2 weeks off pattern. I will take the average of all the skipped weeks as well, but I figured that would be the same code. I realize the .values[1:3] is not correct, that is old code from when I hard coded data from an excel sheet. The point of this code is to remove hard coded data from excel, have all data on python and automatically sort through using a user defined pattern/range to average values while skipping others. Any help or ideas will be very useful.

CodePudding user response：

IIUC, you can use iloc here and get the mean of Value column:

bad = df.iloc[3::3]['Value']
print(bad.mean())
1.6666666666666667

good = df.drop(bad.index)['Value']
print(good.mean())
1.4444444444444444

CodePudding user response：

avg_goodweeks = np.array([df.values[::3, 1],
                          df.values[1::3, 1]]).mean(axis=0)
avg_badweeks = df.values[2::3, 1].mean()