如何使用Xarray将csv文件转换为网格？

Question

我有一个包含许多列的csv文件。我想将纬度，经度和时间列定义为维度，并将其他列设置为Xarray数据集中的变量。在每个点（拉丁对Lon和隆对）之间，相距10公里。在下面的代码中，我无法在数据框中定义像素大小。有可能吗？

示例文件：https://www.dropbox.com/s/5lwzrkiqn2rxxrp/file_2018-01-01_01.csv?dl=0

代码

import os
import pandas as pd
import glob
import xarray

path = r'/path/file' # use your path
all_files = glob.glob(os.path.join(path, "*.csv"))

colnames = ['time','Lat','Lon','Alt','Temperature', 'Relative Humidity', 'Wind speed', 'Wind direction', 'Short-wave irradiation']
for filename in all_files:
    namecsv = os.path.splitext(os.path.basename(filename))[0]
    df = pd.read_csv(filename, header=0, error_bad_lines=False, names = colnames, sep=',')
    df["time"]= pd.to_datetime(df["time"]) 

    xr = df.set_index(['Lat', 'Lon', 'time']).to_xarray()

    # add variable attribute metadata
    #xr['time'].attrs={'units':'hours since 2018-01-01'}
    xr['Lat'].attrs={'units':'degrees', 'long_name':'Latitude'}
    xr['Lon'].attrs={'units':'degrees', 'long_name':'Longitude'}
    xr['Alt'].attrs={'units':'m', 'long_name':'depth'}
    xr['Temperature'].attrs={'units':'k', 'long_name':'Air Temperature'}
    xr['Relative Humidity'].attrs={'units':'%', 'long_name':'Air Relative Humidity'}
    xr['Wind speed'].attrs={'units':'m/s', 'long_name':'Wind speed'}
    xr['Wind direction'].attrs={'units':'deg', 'long_name':'Wind direction'}
    xr['Short-wave irradiation'].attrs={'units':'Wh/m2', 'long_name':'Short-wave irradiation'}

    # Save NetCDF file
    xr.to_netcdf('/path/to/save/' + namecsv + '.nc')
    del namecsv, df, xr

情节

import xarray as xr
da = xr.open_dataset('/home/file_2018-01-01_01.csv.nc').load()

da.Temperature[0].plot(yincrease=False)

结果

我想要什么：