Pandas DataFrame.isnull()和 notnull()函数
Minahil Noor
2023年1月30日
Pandas
Pandas DataFrame
-
pandas.DataFrame.isnull()和pandas.DataFrame.notnull()语法 -
示例代码：
DataFrame.isnull()方法检查空值 -
示例代码：
DataFrame.notnull()方法检查非空值
Python Pandas DataFrame.annull() 函数检测对象的缺失值，DataFrame.notnull() 函数检测对象的非缺失值。
pandas.DataFrame.isnull() 和 pandas.DataFrame.notnull() 语法
DataFrame.isnull()
DataFrame.notnull()
返回
对于标量输入，两个函数都返回标量布尔值。对于数组输入，两个函数都返回一个布尔数组，表示每个对应的元素是否有效。
示例代码：DataFrame.isnull() 方法检查空值
import pandas as pd
import numpy as np
dataframe=pd.DataFrame({'Attendance': {0: 60, 1: np.nan, 2: 80,3: 78,4: 95},
'Name': {0: 'Olivia', 1: 'John', 2: 'Laura',3: 'Ben',4: 'Kevin'},
'Obtained Marks': {0: np.nan, 1: 75, 2: 82, 3: np.nan, 4: 45}})
print("The Original Data frame is: \n")
print(dataframe)
dataframe1 = dataframe.isnull()
print("The output is: \n")
print(dataframe1)
输出：
The Original Data frame is:
Attendance Name Obtained Marks
0 60.0 Olivia NaN
1 NaN John 75.0
2 80.0 Laura 82.0
3 78.0 Ben NaN
4 95.0 Kevin 45.0
The output is:
Attendance Name Obtained Marks
0 False False True
1 True False False
2 False False False
3 False False True
4 False False False
对于空值，该函数返回 True。
示例代码：DataFrame.notnull() 方法检查非空值
import pandas as pd
import numpy as np
dataframe=pd.DataFrame({'Attendance': {0: 60, 1: np.nan, 2: 80,3: 78,4: 95},
'Name': {0: 'Olivia', 1: 'John', 2: 'Laura',3: 'Ben',4: 'Kevin'},
'Obtained Marks': {0: np.nan, 1: 75, 2: 82, 3: np.nan, 4: 45}})
print("The Original Data frame is: \n")
print(dataframe)
dataframe1 = dataframe.notnull()
print("The output is: \n")
print(dataframe1)
输出：
The Original Data frame is:
Attendance Name Obtained Marks
0 60.0 Olivia NaN
1 NaN John 75.0
2 80.0 Laura 82.0
3 78.0 Ben NaN
4 95.0 Kevin 45.0
The output is:
Attendance Name Obtained Marks
0 True True False
1 False True True
2 True True True
3 True True False
4 True True True
该函数对非空值返回 True。
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