pandas 笔记： interpolate

一个用于填充 NaN 值的工具

1 基本用法

DataFrame.interpolate(
    method='linear', 
    *, 
    axis=0, 
    limit=None, 
    inplace=False, 
    limit_direction=None, 
    limit_area=None, 
    downcast=_NoDefault.no_default, 
    **kwargs)

2 主要参数

2 举例

2.1 基本用法

import pandas as pd
import numpy as np
 
s = pd.Series([4,np.nan, np.nan, 3, np.nan, np.nan, 6, np.nan, np.nan,10])
 
 
s.interpolate(method='linear')
'''
0     4.000000
1     3.666667
2     3.333333
3     3.000000
4     4.000000
5     5.000000
6     6.000000
7     7.333333
8     8.666667
9    10.000000
dtype: float64
'''

2.2 limit

import pandas as pd
import numpy as np
 
s = pd.Series([1, np.nan, np.nan, np.nan, 5])
 
s.interpolate(method='linear', limit=2)
'''
0    1.0
1    2.0
2    3.0
3    NaN
4    5.0
dtype: float64
'''

2.3  limit_direction

import pandas as pd
import numpy as np
 
s = pd.Series([1, np.nan, np.nan, np.nan, 5])
 
s.interpolate(method='linear', limit=1, limit_direction='forward')
'''
0    1.0
1    2.0
2    NaN
3    NaN
4    5.0
dtype: float64
'''
 
 
s.interpolate(method='linear', limit=1, limit_direction='backward')
'''
0    1.0
1    NaN
2    NaN
3    4.0
4    5.0
dtype: float64
'''
 
s.interpolate(method='linear', limit_area=None)
'''
0    NaN
1    NaN
2    3.0
3    4.0
4    5.0
5    6.0
6    6.0
7    6.0
dtype: float64
'''