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in, df there is a column called Signal. What I want to do is calculate consequent 2's and add that number to the List.

example:

enter image description here

lst=[1,7,8.....]

1 means 1 consequent 2's, then 7 consequent 2's and so on.

Data:

{'Signal': {0: 2,
  1: 3,
  2: 2,
  3: 2,
  4: 2,
  5: 2,
  6: 2,
  7: 2,
  8: 2,
  9: 3,
  10: 3,
  11: 3,
  12: 3,
  13: 3,
  14: 3,
  15: 3,
  16: 3,
  17: 3,
  18: 3,
  19: 3,
  20: 3,
  21: 3,
  22: 3,
  23: 3,
  24: 2,
  25: 2,
  26: 2,
  27: 2,
  28: 2,
  29: 2,
  30: 2,
  31: 2,
  32: 3,
  33: 3,
  34: 3,
  35: 3,
  36: 3,
  37: 2,
  38: 2,
  39: 3,
  40: 3,
  41: 3,
  42: 3,
  43: 3,
  44: 3,
  45: 3,
  46: 3,
  47: 3,
  48: 3,
  49: 3}}

1 Answer 1

2

First compare by not equal 2, create consecutive groups, filter only 2 by invert mask and call Series.value_counts:

m = df['Signal'].ne(2)

lst = m.cumsum()[~m].value_counts().sort_index().tolist()
print (lst)
[1, 7, 8, 2]

Or use GroupBy.size for count consecutive 2:

m = df['Signal'].ne(2)

lst = df[~m].groupby(m.cumsum()).size().tolist()
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