Pandas replace row values with consecutive rows

Question

I have a pandas DF:-

    start end   ent
        0   2   O
        3   6   O
        7   10  O
        11  17  ABC
        18  20  O
        21  24  O
        25  29  O
        30  32  O
        33  37  XYZ
        38  41  XYZ
        42  46  XYZ
        47  50  O
        51  55  O
        56  59  O
        60  64  O
        65  67  O
        68  72  O
        72  75  O
        76  79  O
        79  82  O
        82  85  O

The goal is to compare 'end' value of a row with 'start' value of row+1 and if they are equal the above would result into:-

    start end   ent
        0   2   O
        3   6   O
        7   10  O
        11  17  ABC
        18  20  O
        21  24  O
        25  29  O
        30  32  O
        33  37  XYZ
        38  41  XYZ
        42  46  XYZ
        47  50  O
        51  55  O
        56  59  O
        60  64  O
        65  67  O
        68  75  O
        76  85  O

Last 5 rows of original df have changed.

Would really appreciate any inputs, Thank you.

Not a downvoter but probably you should detail your effort towards solving your problem and where you got stuck. — Quang Hoang
– Quang Hoang, Commented Sep 14, 2020 at 15:33

Quang Hoang · Accepted Answer · 2020-09-14 15:36:08Z

2

To get the previous values, we can use shift(). And the common technique to identify these blocks is cumsum on the negated condition, then groupby:

mask = df['start'] != df['end'].shift()

df.groupby(mask.cumsum()).agg({'start':'first', 'end':'last', 'ent':'first'})

Output:

    start  end  ent
1       0    2    O
2       3    6    O
3       7   10    O
4      11   17  ABC
5      18   20    O
6      21   24    O
7      25   29    O
8      30   32    O
9      33   37  XYZ
10     38   41  XYZ
11     42   46  XYZ
12     47   50    O
13     51   55    O
14     56   59    O
15     60   64    O
16     65   67    O
17     68   75    O
18     76   85    O

answered Sep 14, 2020 at 15:36

Quang Hoang

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