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Is there another, more simple way to drop all table rows except the first one?

 df = df.drop([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, 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], axis = 0)
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  • You select the one row you're interested in? Something like df = df.loc[0, :]? I think this will result in a Series, but that makes sense for a single row. Commented May 8, 2021 at 7:25
  • 1
    df = df.loc[[0]] perhaps? Commented May 8, 2021 at 7:25
  • Make a new table with only that row? Commented May 8, 2021 at 8:28

2 Answers 2

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df.drop(df.index.to_list()[1:], axis=0)
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As Nick wrote: df = df.loc[[0]] works fine.

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