Quadmesh

import hvplot.xarray  # noqa

import xarray as xr

ds = xr.tutorial.open_dataset('rasm')
ds

<xarray.Dataset> Size: 17MB
Dimensions:  (time: 36, y: 205, x: 275)
Coordinates:
  * time     (time) object 288B 1980-09-16 12:00:00 ... 1983-08-17 00:00:00
    xc       (y, x) float64 451kB ...
    yc       (y, x) float64 451kB ...
Dimensions without coordinates: y, x
Data variables:
    Tair     (time, y, x) float64 16MB ...
Attributes:
    title:                     /workspace/jhamman/processed/R1002RBRxaaa01a/l...
    institution:               U.W.
    source:                    RACM R1002RBRxaaa01a
    output_frequency:          daily
    output_mode:               averaged
    convention:                CF-1.4
    references:                Based on the initial model of Liang et al., 19...
    comment:                   Output from the Variable Infiltration Capacity...
    nco_openmp_thread_number:  1
    NCO:                       netCDF Operators version 4.7.9 (Homepage = htt...
    history:                   Fri Aug  7 17:57:38 2020: ncatted -a bounds,,d...

xarray.Dataset

• Dimensions:
  • time: 36
  • y: 205
  • x: 275
• Coordinates: (3)
  • time
    (time)
    object
    1980-09-16 12:00:00 ... 1983-08-...

    long_name :

    time

    type_preferred :

    int

    array([cftime.DatetimeNoLeap(1980, 9, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1980, 10, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1980, 11, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1980, 12, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1981, 1, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1981, 2, 15, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1981, 3, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1981, 4, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1981, 5, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1981, 6, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1981, 7, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1981, 8, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1981, 9, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1981, 10, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1981, 11, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1981, 12, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1982, 1, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1982, 2, 15, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1982, 3, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1982, 4, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1982, 5, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1982, 6, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1982, 7, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1982, 8, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1982, 9, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1982, 10, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1982, 11, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1982, 12, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1983, 1, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1983, 2, 15, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1983, 3, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1983, 4, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1983, 5, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1983, 6, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1983, 7, 17, 0, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(1983, 8, 17, 0, 0, 0, 0, has_year_zero=True)],
          dtype=object)

  • xc
    (y, x)
    float64
    ...

    long_name :

    longitude of grid cell center

    units :

    degrees_east

    [56375 values with dtype=float64]

  • yc
    (y, x)
    float64
    ...

    long_name :

    latitude of grid cell center

    units :

    degrees_north

    [56375 values with dtype=float64]

• Data variables: (1)
  • Tair
    (time, y, x)
    float64
    ...

    units :

    C

    long_name :

    Surface air temperature

    type_preferred :

    double

    time_rep :

    instantaneous

    [2029500 values with dtype=float64]

• Indexes: (1)
  • time
    PandasIndex

    PandasIndex(CFTimeIndex([1980-09-16 12:00:00, 1980-10-17 00:00:00, 1980-11-16 12:00:00,
                 1980-12-17 00:00:00, 1981-01-17 00:00:00, 1981-02-15 12:00:00,
                 1981-03-17 00:00:00, 1981-04-16 12:00:00, 1981-05-17 00:00:00,
                 1981-06-16 12:00:00, 1981-07-17 00:00:00, 1981-08-17 00:00:00,
                 1981-09-16 12:00:00, 1981-10-17 00:00:00, 1981-11-16 12:00:00,
                 1981-12-17 00:00:00, 1982-01-17 00:00:00, 1982-02-15 12:00:00,
                 1982-03-17 00:00:00, 1982-04-16 12:00:00, 1982-05-17 00:00:00,
                 1982-06-16 12:00:00, 1982-07-17 00:00:00, 1982-08-17 00:00:00,
                 1982-09-16 12:00:00, 1982-10-17 00:00:00, 1982-11-16 12:00:00,
                 1982-12-17 00:00:00, 1983-01-17 00:00:00, 1983-02-15 12:00:00,
                 1983-03-17 00:00:00, 1983-04-16 12:00:00, 1983-05-17 00:00:00,
                 1983-06-16 12:00:00, 1983-07-17 00:00:00, 1983-08-17 00:00:00],
                dtype='object', length=36, calendar='noleap', freq=None))

• Attributes: (11)

  title :

  /workspace/jhamman/processed/R1002RBRxaaa01a/lnd/temp/R1002RBRxaaa01a.vic.ha.1979-09-01.nc

  institution :

  U.W.

  source :

  RACM R1002RBRxaaa01a

  output_frequency :

  daily

  output_mode :

  averaged

  convention :

  CF-1.4

  references :

  Based on the initial model of Liang et al., 1994, JGR, 99, 14,415- 14,429.

  comment :

  Output from the Variable Infiltration Capacity (VIC) model.

  nco_openmp_thread_number :

  1

  NCO :

  netCDF Operators version 4.7.9 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)

  history :

  Fri Aug 7 17:57:38 2020: ncatted -a bounds,,d,, rasm.nc Tue Dec 27 14:15:22 2016: ncatted -a dimensions,,d,, rasm.nc rasm.nc Tue Dec 27 13:38:40 2016: ncks -3 rasm.nc rasm.nc history deleted for brevity

quadmesh can be slower that image, but it allows you to plot values on an irregular grid by representing each value as a polygon.

ds.Tair.hvplot.quadmesh(x='xc', y='yc', geo=True, widget_location='bottom')