import xarray as xr
import numpy as np
import pandas as pd

# Create synthetic temperature data
temperature = np.random.rand(365, 50, 50) * 20 + 10

# Create time, latitude, and longitude coordinate arrays
times = pd.date_range('2023-01-01', periods=365, freq='D')
latitudes = np.linspace(-90, 90, 50)
longitudes = np.linspace(-180, 180, 50)

# Create an Xarray dataset
ds = xr.Dataset(
    {
        'temperature': (['time', 'latitude', 'longitude'], temperature),
    },
    coords={
        'time': times,
        'latitude': latitudes,
        'longitude': longitudes,
    }
)

# Perform statistical analysis on the temperature data
mean_temperature = ds['temperature'].mean(dim='time')
max_temperature = ds['temperature'].max(dim='time')
min_temperature = ds['temperature'].min(dim='time')

# Print values 
print(f"mean temperature:n {mean_temperature}n")
print(f"max temperature:n {max_temperature}n")
print(f"min temperature:n {min_temperature}n")

>>>

mean temperature:
 <xarray.DataArray 'temperature' (latitude: 50, longitude: 50)>
array([[19.99931701, 20.36395016, 20.04110699, ..., 19.98811842,
        20.08895803, 19.86064693],
       [19.84016491, 19.87077812, 20.27445405, ..., 19.8071972 ,
        19.62665953, 19.58231185],
       [19.63911165, 19.62051976, 19.61247548, ..., 19.85043831,
        20.13086891, 19.80267099],
       ...,
       [20.18590514, 20.05931149, 20.17133483, ..., 20.52858247,
        19.83882433, 20.66808513],
       [19.56455575, 19.90091128, 20.32566232, ..., 19.88689221,
        19.78811145, 19.91205212],
       [19.82268297, 20.14242279, 19.60842148, ..., 19.68290006,
        20.00327294, 19.68955107]])
Coordinates:
  * latitude   (latitude) float64 -90.0 -86.33 -82.65 ... 82.65 86.33 90.0
  * longitude  (longitude) float64 -180.0 -172.7 -165.3 ... 165.3 172.7 180.0

max temperature:
 <xarray.DataArray 'temperature' (latitude: 50, longitude: 50)>
array([[29.98465531, 29.97609171, 29.96821276, ..., 29.86639343,
        29.95069558, 29.98807808],
       [29.91802049, 29.92870312, 29.87625447, ..., 29.92519055,
        29.9964299 , 29.99792388],
       [29.96647016, 29.7934891 , 29.89731136, ..., 29.99174546,
        29.97267052, 29.96058079],
       ...,
       [29.91699117, 29.98920555, 29.83798369, ..., 29.90271746,
        29.93747041, 29.97244906],
       [29.99171911, 29.99051943, 29.92706773, ..., 29.90578739,
        29.99433847, 29.94506567],
       [29.99438621, 29.98798699, 29.97664488, ..., 29.98669576,
        29.91296382, 29.93100249]])
Coordinates:
  * latitude   (latitude) float64 -90.0 -86.33 -82.65 ... 82.65 86.33 90.0
  * longitude  (longitude) float64 -180.0 -172.7 -165.3 ... 165.3 172.7 180.0

min temperature:
 <xarray.DataArray 'temperature' (latitude: 50, longitude: 50)>
array([[10.0326431 , 10.07666029, 10.02795524, ..., 10.17215336,
        10.00264909, 10.05387097],
       [10.00355858, 10.00610942, 10.02567816, ..., 10.29100316,
        10.00861792, 10.16955806],
       [10.01636216, 10.02856619, 10.00389027, ..., 10.0929342 ,
        10.01504103, 10.06219179],
       ...,
       [10.00477003, 10.0303088 , 10.04494723, ..., 10.05720692,
        10.122994  , 10.04947012],
       [10.00422182, 10.0211205 , 10.00183528, ..., 10.03818058,
        10.02632697, 10.06722953],
       [10.10994581, 10.12445222, 10.03002468, ..., 10.06937041,
        10.04924046, 10.00645499]])
Coordinates:
  * latitude   (latitude) float64 -90.0 -86.33 -82.65 ... 82.65 86.33 90.0
  * longitude  (longitude) float64 -180.0 -172.7 -165.3 ... 165.3 172.7 180.0