Python Pandas - 用索引对象中的指定值填充 NaN 值

要使用Index对象中的指定值填充NaN值，请使用Pandas中的方法。首先，导入所需的库-index.fillna()

import pandas as pd import numpy as np

使用一些NaN值创建Pandas索引-

index = pd.Index([50, 10, 70, np.nan, 90, 50, np.nan, np.nan, 30])

显示熊猫指数-

print("Pandas Index...\n",index)

用一些特定的值填充NaN-

print("\nIndex object after filling NaN value...\n",index.fillna(Amit))

示例

以下是代码-

import pandas as pd import numpy as np #还使用一些NaN值创建Pandas索引 index = pd.Index([50, 10, 70, np.nan, 90, 50, np.nan, np.nan, 30]) #显示Pandas索引 print("Pandas Index...\n",index) #返回索引中的元素数 print("\nNumber of elements in the index...\n",index.size) #返回数据的dtype print("\nThe dtype object...\n",index.dtype) #用一些特定的值填充NaN print("\nIndex object after filling NaN value...\n",index.fillna(Amit))输出结果

这将产生以下输出-

Pandas Index... Float64Index([50.0, 10.0, 70.0, nan, 90.0, 50.0, nan, nan, 30.0], dtype=float64) Number of elements in the index... 9 The dtype object... float64 Index object after filling NaN value... Index([50.0, 10.0, 70.0, Amit, 90.0, 50.0, Amit, Amit, 30.0], dtype=object)