Python Pandas - 当多索引中的任何级别为 NaN 时删除该值
要在多索引中的任何级别为NaN时删除该值，请使用该方法。使用值any设置参数how。multiIndex.dropna()
首先，导入所需的库——
import pandas as pd import numpy as np
创建具有一些NaN值的多索引。names参数设置索引中级别的名称-
multiIndex = pd.MultiIndex.from_arrays([[5, 10], [np.nan, 20], [25, np.nan], [35, 40]],names=['a', 'b', 'c', 'd'])
当多索引中的任何级别为NaN时，删除该值。即使只有一个NaN值，dropna()也会删除所有值。的“how”参数dropna()与值“any”一起使用-
print("\nDropping the value when any level is NaN...\n",multiIndex.dropna(how='any'))示例
以下是代码-
import pandas as pd
import numpy as np
#Createamulti-indexwithsomeNaNvalues
#Thenamesparametersetsthenamesforthelevelsintheindex
multiIndex = pd.MultiIndex.from_arrays([[5, 10], [np.nan, 20], [25, np.nan], [35, 40]],names=['a', 'b', 'c', 'd'])
#displaythemulti-index
print("Multi-index...\n", multiIndex)
#DropthevaluewhenanylevelisNaNinaMulti-index
#EvenwithasingleNaNvalue,thedropna()willdropallthevalues
# The "how" parameter of the dropna() is used with the value "any" for this
print("\nDropping the value when any level is NaN...\n",multiIndex.dropna(how='any'))输出结果这将产生以下输出-
Multi-index... MultiIndex([( 5, nan, 25.0, 35),(10, 20.0, nan, 40)],names=['a', 'b', 'c', 'd']) Dropping the value when any level is NaN... MultiIndex([], names=['a', 'b', 'c', 'd'])