Extracting the data from pandas data frame

Question

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]

df[((df.LAT==30.75) & (df.LON==76.25))] this would work – iamklaus Feb 28 '19 at 08:52 — iamklaus, Feb 28 '19 at 08:52

score 1 · Accepted Answer · answered Feb 28 '19 at 08:52

1

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

answered Feb 28 '19 at 08:52

Chris

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Extracting the data from pandas data frame

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