我有一个要转换为netCDF的空间数据的熊猫数据框。我找到了使用xarray的方法,并将数据框转换为xarray数据集:
# create xray Dataset from Pandas DataFrame
xr = xarray.Dataset.from_dataframe(df)
现在,我想将lon
和lat
变量设置为xarray数据集的坐标。我尝试过xarray.Dataset.assign_coords
,但似乎无法使其正常工作吗?
我的xarray数据集看起来像:
<xarray.Dataset>
Dimensions: (index: 58705)
Coordinates:
* index (index) int64 0 1 2 3 4 5 6 ... 58699 58700 58701 58702 58703 58704
Data variables:
x_km (index) float64 5.274e+03 5.273e+03 ... 2.873e+03 2.873e+03
y_km (index) float64 0.0 46.02 92.03 138.0 ... -75.23 -50.15 -25.07 -0.0
z_km (index) float64 3.575e+03 3.575e+03 ... 1.947e+03 1.947e+03
dv_v (index) float64 0.2407 0.1774 0.1786 ... -0.2163 -0.2035 -0.3197
rxy (index) float64 5.274e+03 5.273e+03 ... 2.873e+03 2.873e+03
lon (index) float64 0.0 0.5 1.0 1.5 2.0 ... -2.0 -1.5 -1.0 -0.5 -0.0
lat (index) float64 34.13 34.13 34.13 34.13 ... 34.11 34.12 34.12 34.13
rxyz (index) float64 6.371e+03 6.371e+03 ... 3.471e+03 3.471e+03
depth (index) float64 0.04665 0.04747 0.04766 ... 2.9e+03 2.9e+03 2.9e+03
Attributes:
Conventions: CF-1.6
title: Data
summary: Data generated
感谢您的任何帮助:D
从如下所示的名为Dataset
的ds
开始:
Dimensions: (index: 10)
Coordinates:
* index (index) int64 0 1 2 3 4 5 6 7 8 9
Data variables:
dv_v (index) int64 5 14 6 1 19 12 16 10 0 11
rxy (index) int64 15 8 6 2 0 1 4 16 7 19
lon (index) int64 15 7 9 17 18 1 12 2 6 8
lat (index) int64 6 8 5 17 15 16 9 19 11 14
rxyz (index) int64 15 17 18 5 14 13 16 2 10 9
depth (index) int64 11 18 5 19 3 14 7 17 0 4
您可以将lat
和lon
转换为带有ds.set_coordinates(("lat", "lon"))
的坐标。结果如下:
Dimensions: (index: 10)
Coordinates:
* index (index) int64 0 1 2 3 4 5 6 7 8 9
lon (index) int64 15 7 9 17 18 1 12 2 6 8
lat (index) int64 6 8 5 17 15 16 9 19 11 14
Data variables:
dv_v (index) int64 5 14 6 1 19 12 16 10 0 11
rxy (index) int64 15 8 6 2 0 1 4 16 7 19
rxyz (index) int64 15 17 18 5 14 13 16 2 10 9
depth (index) int64 11 18 5 19 3 14 7 17 0 4
[另一个类似(但不等同)的替代方法是使用ds.set_index(index=("lat", "lon"))
,它将index
修改为具有索引lat
和lon
的多级索引。输出如下:
Dimensions: (index: 10)
Coordinates:
* index (index) MultiIndex
- lat (index) int64 6 8 5 17 15 16 9 19 11 14
- lon (index) int64 15 7 9 17 18 1 12 2 6 8
Data variables:
dv_v (index) int64 5 14 6 1 19 12 16 10 0 11
rxy (index) int64 15 8 6 2 0 1 4 16 7 19
rxyz (index) int64 15 17 18 5 14 13 16 2 10 9
depth (index) int64 11 18 5 19 3 14 7 17 0 4