Bar#

import hvplot.xarray  # noqa
import xarray as xr

Introduction#

A bar plot represents categorical data with rectangular bars with heights proportional to the numerical values that they represent. The x-axis represents the categories and the y axis represents the numerical value scale. The bars are of equal width which allows for instant comparison of data.

Data#

Let’s load some data.

ds = xr.tutorial.open_dataset('air_temperature').load()
air = ds.air
air1d = air.sel(lon=285.,lat=40.).groupby('time.month').mean()
air1d
<xarray.DataArray 'air' (month: 12)> Size: 96B
array([272.57443548, 272.86397321, 275.4216129 , 282.50516667,
       288.4616129 , 293.99958333, 296.62262097, 295.09346774,
       292.44054167, 288.14100806, 279.71479167, 276.71915323])
Coordinates:
    lat      float32 4B 40.0
    lon      float32 4B 285.0
  * month    (month) int64 96B 1 2 3 4 5 6 7 8 9 10 11 12
Attributes:
    long_name:     4xDaily Air temperature at sigma level 995
    units:         degK
    precision:     2
    GRIB_id:       11
    GRIB_name:     TMP
    var_desc:      Air temperature
    dataset:       NMC Reanalysis
    level_desc:    Surface
    statistic:     Individual Obs
    parent_stat:   Other
    actual_range:  [185.16 322.1 ]

Basic Bar Plots#

air1d.hvplot.bar(y='air', height=500, title="Air Temperature by Month")
This web page was generated from a Jupyter notebook and not all interactivity will work on this website.