如何根据特定列中的值对数据帧的行求平均？

Question

My dataframe has a column named "Zeroing" which is either True or False, and it alternates. It's False for 12 rows then True for 48 rows. I'd like to make a new data frame where it's False for 1 row and True for 4, with all other columns averaged accordingly. I know for sure that it's a 12/48 pattern, but would like to use the condition just to be certain.

Assume for brevity that it alternates True for 2 rows then False for 8 and I want to average every 2 rows. I would have:

>>> df
    Value1    Value2    Value3   Zeroing
0        1         2         0      True
1        2         4         5      True
2        3         6        10     False
3        4         8        15     False
4        5        10        20     False
5        6        12        25     False
6        7        14        30     False
7        8        16        35     False
8        9        18        40     False
9       10        20        45     False

I would like the output to be:

    >>> df
    Value1    Value2    Value3   Zeroing
0      1.5         3       2.5      True
1      3.5         7      12.5     False
2      5.5        11      22.5     False
3      7.5        15      32.5     False
4      9.5        19      42.5     False

Answer 1

For your example, you can use a groupby and then take the mean for every two rows. Translate this to your actual problem.

>>> df.groupby(df.index // 2).mean()

Which returns

   Value1  Value2  Value3  Zeroing
0     1.5     3.0     2.5     True
1     3.5     7.0    12.5    False
2     5.5    11.0    22.5    False
3     7.5    15.0    32.5    False
4     9.5    19.0    42.5    False