获取pandas列的所有非NaN值

import pandas as pd

# 创建一个包含NaN值的Series
s = pd.Series([1, 2, np.nan, 4, np.nan])

# 获取所有非NaN值
result = s.dropna()

print(result)

0    1.0
1    2.0
3    4.0
dtype: float64

import pandas as pd
import numpy as np

# 创建一个包含NaN值的DataFrame
df = pd.DataFrame({'A': [1, 2, np.nan, 4, np.nan],
                   'B': [np.nan, 2, 3, np.nan, 5]})

# 获取所有非NaN值的列
result = df.dropna(axis=1)

print(result)

Empty DataFrame
Columns: []
Index: [0, 1, 2, 3, 4]

import pandas as pd
import numpy as np

# 创建一个包含NaN值的Series
s = pd.Series([1, 2, np.nan, 4, np.nan])

# 获取所有非NaN值
result = s[s.notnull()]

print(result)

0    1.0
1    2.0
3    4.0
dtype: float64

import pandas as pd
import numpy as np

# 创建一个包含NaN值的DataFrame
df = pd.DataFrame({'A': [1, 2, np.nan, 4, np.nan],
                   'B': [np.nan, 2, 3, np.nan, 5]})

# 获取所有非NaN值的列
result = df[df.notnull()]

print(result)

     A    B
0  1.0  NaN
1  2.0  2.0
2  NaN  3.0
3  4.0  NaN
4  NaN  5.0