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I have a data frame like the following:

 LAT LON YEAR MO DY PREC T_MAX T_MIN WS 30.75 76.25 1981 1 3 5.40 22.08 11.22 3.95 30.75 76.75 1981 1 3 3.94 19.25 9.29 3.69 30.75 77.25 1981 1 3 3.28 14.25 6.29 2.87 30.75 77.75 1981 1 3 2.96 10.57 3.23 2.10 30.75 78.25 1981 1 3 2.78 7.62 -0.41 1.51 30.75 78.75 1981 1 3 2.77 1.02 -6.66 1.22 30.75 79.25 1981 1 3 2.47 -3.92 -12.18 1.74 31.25 76.25 1981 1 3 5.97 20.72 10.59 3.77 31.25 76.75 1981 1 3 4.17 15.05 6.70 3.22 31.25 77.25 1981 1 3 3.64 7.47 1.62 2.31

I need to extract the rows which have lat=30.75 and lon 76.25, for that I used:

data.where(data.LAT==30.75 & data.LON==76.25)

But this is showing this error:

cannot compare a dtyped [float64] array with a scalar of type [bool]
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    df[((df.LAT==30.75) & (df.LON==76.25))] this would work Commented Feb 28, 2019 at 8:52

1 Answer 1

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You don't need where:

data[(data.LAT==30.75) & (data.LON==76.25)] LAT LON YEAR MO DY PREC T_MAX T_MIN WS 0 30.75 76.25 1981 1 3 5.4 22.08 11.22 3.95
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