Python Pandas - 当多索引中的所有级别均为 NaN 时删除该值
要在Multi-index中的所有级别均为NaN时删除该值，请使用该方法。设置参数how与valueall。multiIndex.dropna()
首先，导入所需的库——
import pandas as pd import numpy as np
创建一个包含所有NaN值的多索引。names参数设置索引中级别的名称-
multiIndex = pd.MultiIndex.from_arrays([[np.nan, np.nan], [np.nan, np.nan]], names=['a', 'b'])
当Multi-index中的所有级别iareNaN时删除该值。对于所有NaN值，dropna()如果的“how”参数dropna()设置为“all”，则将删除所有值-
print("\nDropping the values when all levels are NaN...\n",multiIndex.dropna(how='all'))示例
以下是代码-
import pandas as pd
import numpy as np
#Createamulti-indexwithallNaNvalues
#Thenamesparametersetsthenamesforthelevelsintheindex
multiIndex = pd.MultiIndex.from_arrays([[np.nan, np.nan], [np.nan, np.nan]],
names=['a', 'b'])
#displaythemulti-index
print("Multi-index...\n", multiIndex)
#DropthevaluewhenalllevelsiareNaNinaMulti-index
#WithallNaNvalues,thedropna()willdropallthevalues,ifthe
# "how" parameter of the dropna() is set "all"
print("\nDropping the values when all levels are NaN...\n",multiIndex.dropna(how='all'))输出结果这将产生以下输出-
Multi-index... MultiIndex([(nan, nan),(nan, nan)],names=['a', 'b']) Dropping the values when all levels are NaN... MultiIndex([], names=['a', 'b'])