[FIXED] How to change index by row value?

Issue

My dataframe is like that:

And I want to change index by "video_second" value.

conditions=[(df['video_second'] == 612.00),
        (df['video_second'] == 612.05),
        (df['video_second'] == 612.10),
        (df['video_second'] == 612.15),
        (df['video_second'] == 612.20),
        (df['video_second'] == 612.25),
        (df['video_second'] == 612.30),
        (df['video_second'] == 612.35),
        (df['video_second'] == 612.40),
        (df['video_second'] == 612.45),
        (df['video_second'] == 612.50),
        (df['video_second'] == 612.55),
        (df['video_second'] == 612.60),
        (df['video_second'] == 612.65),
        (df['video_second'] == 612.70),
        (df['video_second'] == 612.75),
        (df['video_second'] == 612.80),
        (df['video_second'] == 612.85),
        (df['video_second'] == 612.90),
        (df['video_second'] == 612.95),
        (df['video_second'] == 613.00),
        (df['video_second'] == 613.05),
        (df['video_second'] == 613.10),
        (df['video_second'] == 613.15),
        (df['video_second'] == 613.20),
        (df['video_second'] == 613.25),
        (df['video_second'] == 613.30),
        (df['video_second'] == 613.35),
        (df['video_second'] == 613.40),
        (df['video_second'] == 613.45),
        (df['video_second'] == 613.50),
        (df['video_second'] == 613.55),
        (df['video_second'] == 613.60),
        (df['video_second'] == 613.65),
        (df['video_second'] == 613.70),
        (df['video_second'] == 613.75),
        (df['video_second'] == 613.80),
        (df['video_second'] == 613.85),
        (df['video_second'] == 613.90),
        (df['video_second'] == 613.95),
        (df['video_second'] == 614.00),
        (df['video_second'] == 614.05),
                  ..........
        (df['video_second'] == 617.45),
        (df['video_second'] == 617.50),
        (df['video_second'] == 617.55),
        (df['video_second'] == 617.60),
        (df['video_second'] == 617.65),
        (df['video_second'] == 617.70),
        (df['video_second'] == 617.75),
        (df['video_second'] == 617.80),
        (df['video_second'] == 617.85),
        (df['video_second'] == 617.90),
        (df['video_second'] == 617.95),
        (df['video_second'] == 618.00)]

choices = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 
23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 
46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 
69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 
92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 
112, 113, 114, 115, 116, 117, 118, 119, 120]
df['frame'] = np.select(conditions, choices)
df.index = df["frame"]
df.drop("frame", axis=1, inplace=True)
df=df.sort_index()

After that, it works and my dataframe looks like that:

But I want to automatize this work. Manually, it is easy to do but so much waste of time. And I should modify that long code for every other seconds. So, any easy/automatize way to do that?

Solution

video_seconds = np.arange(612.00, 618.05, 0.05)
choices = np.arange(len(video_seconds))

df.index = df['video_second'].replace(video_seconds, choices)

then you are sorting, which can also be done in-place:

df.sort_index(inplace=True)

Answered By - Vladimir Fokow