Python使用xarray从NETCDF文件中提取多个纬度/经度

Question

我有一个NC文件（时间，纬度，经度）Download from here，并且我试图提取多个测站的时间序列（纬度/经度Download from here）。因此，我尝试通过这种方式读取坐标并从NC文件中提取最接近的值：

import pandas as pd
import xarray as xr
nc_file = r"C:\Users\lab\Desktop\harvey\example.nc"
NC = xr.open_dataset(nc_file)
csv = r"C:\Users\lab\Desktop\harvey\stations.csv"
df = pd.read_csv(csv,delimiter=',')
Newdf = pd.DataFrame([])
# grid point lists
lat = df["Lat"]
lon = df["Lon"]
point_list = zip(lat,lon)
for i, j in point_list:
    dsloc = NC.sel(lat=i,lon=j,method='nearest')
    DT=dsloc.to_dataframe()
    Newdf=Newdf.append(DT,sort=True)

该代码可以正常工作并返回此：

                        EVP     lat      lon
time                                        
2019-01-01 19:00:00  0.0546  40.063  -88.313
2019-01-01 23:00:00  0.0049  40.063  -88.313
2019-01-01 19:00:00  0.0052  41.938  -93.688
2019-01-01 23:00:00  0.0029  41.938  -93.688
2019-01-01 19:00:00  0.0101  52.938 -124.938
2019-01-01 23:00:00  0.0200  52.938 -124.938
2019-01-01 19:00:00  0.1644  39.063  -79.438
2019-01-01 23:00:00 -0.0027  39.063  -79.438

但是，我需要为每个坐标关联台站ID（来自我的原始经/长文件），如下所示：

  Station-ID       Lat        Lon            time     EVP     lat      lon
0        Bo1  40.00620  -88.29040  1/1/2019 19:00  0.0546  40.063  -88.313
1                                  1/1/2019 23:00  0.0049  40.063  -88.313
2        Br1  41.97490  -93.69060  1/1/2019 19:00  0.0052  41.938  -93.688
3                                  1/1/2019 23:00  0.0029  41.938  -93.688
4        Brw  71.32250 -156.60917  1/1/2019 19:00  0.0101  52.938 -124.938
5                                  1/1/2019 23:00  0.0200  52.938 -124.938
6        CaV  39.06333  -79.42083  1/1/2019 19:00  0.1644  39.063  -79.438
7                                  1/1/2019 23:00 -0.0027  39.063  -79.438

任何想法都如何像提供的示例一样合并我的数据框？

Answer 1

如果您在zip命令中包含工作站名称，然后将ID插入到这样的pandas数据框行中（顺便说一句，我无法访问您的CSV文件，因此我用一个虚拟的示例略微简化了该示例，该怎么办？列表）。

import pandas as pd
import xarray as xr
nc_file = "example.nc"
NC = xr.open_dataset(nc_file)

#dummy locations and station id as I can't access the CSV
lat=[40,42,41]
lon=[-100,-105,-99]
name=["a","b","c"]

point_list = zip(lat,lon,name)
Newdf = pd.DataFrame([])
for i,j,id in point_list:
    dsloc = NC.sel(lat=i,lon=j,method='nearest')
    DT=dsloc.to_dataframe()

    # insert the name with your preferred column title:
    DT.insert(loc=0,column="station",value=id)
    Newdf=Newdf.append(DT,sort=True)

print(Newdf)

这给了我：

                        EVP     lat      lon station
time                                                
2019-01-01 19:00:00  0.0527  39.938  -99.938       a
2019-01-01 23:00:00  0.0232  39.938  -99.938       a
2019-01-01 19:00:00  0.0125  41.938 -104.938       b
2019-01-01 23:00:00  0.0055  41.938 -104.938       b
2019-01-01 19:00:00  0.0527  40.938  -98.938       c
2019-01-01 23:00:00  0.0184  40.938  -98.938       c