Python中检查NaN值的几种方法

import math
x = float('nan')
print(math.isnan(x))  # 输出: True

def isNaN(num):
    return num != num

x = float('nan')
print(isNaN(x))  # 输出: True

import numpy as np
x = float('nan')
print(np.isnan(x))  # 输出: True

import pandas as pd
x = float('nan')
print(pd.isna(x))  # 输出: True

import math
import numpy as np
import pandas as pd

x = float('nan')

# 使用math.isnan()
print(f"math.isnan: {math.isnan(x)}")

# 利用NaN不等于自身的特性
def isNaN(num):
    return num != num
print(f"num != num: {isNaN(x)}")

# 使用numpy.isnan()
print(f"numpy.isnan: {np.isnan(x)}")

# 使用pandas.isna()
print(f"pandas.isna: {pd.isna(x)}")

import math
import numpy as np
import pandas as pd

values = [float('nan'), 55, "string"]

# 使用math.isnan()
math_result = [math.isnan(i) if isinstance(i, float) else False for i in values]
print(f"math.isnan: {math_result}")

# 利用NaN不等于自身的特性
custom_result = [i != i for i in values]
print(f"num != num: {custom_result}")

# 使用numpy.isnan()
np_result = np.isnan(np.array(values, dtype=float)) if all(isinstance(i, (int, float)) for i in values) else [False] * len(values)
print(f"numpy.isnan: {np_result}")

# 使用pandas.isna()
pd_result = pd.isna(pd.Series(values))
print(f"pandas.isna: {pd_result}")