Question

我在弄清楚如何使用xarray DataArrays和DataSet以及执行代数运算时遇到了麻烦；特别是当维度具有不同级别并且我的多维数据集具有不同粒度时。如果有人可以向我建议一些文档或给我一些建议，我将不胜感激。

在下面的示例中，我试图计算父母（PFS）下每个孩子（SKU）的贡献。我发现要获取正确的值，我需要将多维数据集切片转换为熊猫数据框。否则，Xarray将复制我正在使用的尺寸。

import pandas as pd
import numpy as np
import xarray as xr
from itertools import product

# Create hierachies

usage_type_entities = (('Regular',), ('Sample',),
                       ('Tender',), ('Clinic Trial',))

usage_type_tree = pd.MultiIndex.from_tuples(
    usage_type_entities, names=('Usage_Type',))

product_tree_hierarchy = (("PF1", "PFS1", "SKU1"),
                          ("PF1", "PFS1", "SKU2"),
                          ("PF1", "PFS2", "SKU3"),
                          ("PF1", "PFS2", "SKU4"),
                          ("PF2", "PFS3", "SKU5"))

product_tree_entities = ("PF", "PFS", "SKU")

product_tree = pd.MultiIndex.from_tuples(product_tree_hierarchy,
                                         names=product_tree_entities)

market_tree_hierarchy = (("Group1", "Region1", "Market1"),
                         ("Group1", "Region1", "Market2"),
                         ("Group1", "Region2", "Market3"),
                         ("Group1", "Region2", "Market4"),
                         ("Group2", "Region3", "Market5"))

market_tree_entities = ("Groups", "Regions", "Markets")

market_tree = pd.MultiIndex.from_tuples(market_tree_hierarchy,
                                        names=market_tree_entities)

time_tree_hierarchy = [(y, y+q) for y, q in product([str(2013+x) for x in range(6)],
                                                    ["Q"+str(int(q)) for q in np.arange(1, 4.1, 1)])][0:22]

time_entities = ("Year", "Quarter")

time_tree = pd.MultiIndex.from_tuples(time_tree_hierarchy, names=time_entities)

# Create X-array Dataset

x1 = np.random.randint(100, size=(len(usage_type_tree), len(
    product_tree), len(market_tree), len(time_tree)))

xda = xr.DataArray(x1, coords=(usage_type_tree, product_tree, market_tree, time_tree),
                   dims=("Usage", "Product", "Market", "Time"))

# Operations - I need to convert my slice into a pandas df to get 
the right values. Converting to pandas df works ok. 

market = "Market1"
ut = "Regular"

(xda.sel(Markets=market, Usage_Type=ut)[:, 0].to_pandas() /
 xda.sel(Markets=market, Usage_Type=ut)[:, 0].to_pandas().groupby("PFS").sum(axis=0))

如果不将切片转换为df并将其保存为xarray数据集，则维度将重复。例如，下面的行会生成一个DatArray（Product：5，Time：22，PFS：3），当它应该只是（Product：5，Time：22）

(xda.sel(Markets=market, Usage_Type=ut)[:, 0] /
 xda.sel(Markets=market, Usage_Type=ut)[:, 0].groupby("PFS").sum(axis=0))

Xarray：具有不同粒度/级别相同的层次结构/多索引

0 个答案: