Python Pandas - 使用指定的 value 填充 Index 物件中的 NaN 值


若要使用指定的 value 填充 Index 物件中的 NaN 值,請在 Pandas 中使用 index.fillna() 方法。首先,匯入所需的庫-。

import pandas as pd
import numpy as np

建立具有 NaN 值的 Pandas 索引-。

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

顯示 Pandas 索引 -

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

使用特定值填充 NaN 值 -

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

示例

以下為程式碼 -

import pandas as pd
import numpy as np

# Creating Pandas index with some NaN values as well
index = pd.Index([50, 10, 70, np.nan, 90, 50, np.nan, np.nan, 30])

# Display the Pandas index
print("Pandas Index...\n",index)

# Return the number of elements in the Index
print("\nNumber of elements in the index...\n",index.size)

# Return the dtype of the data
print("\nThe dtype object...\n",index.dtype)

# Fill the NaN with some specific value
print("\nIndex object after filling NaN value...\n",index.fillna('Amit'))

輸出

這將生成以下輸出 -

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')

更新於: 13-Oct-2021

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