pandas 缺失值處理，插值

 

import pandas as pd
d = pd.DataFrame()

d['date'] = ['2019-01-01', '2019-01-02', '2019-01-04', '2019-01-07', '2019-01-09', '2019-01-11']
d['val'] = [10, 20, 30, 40, 50, 30]
d['date'] = pd.to_datetime(d['date'])

helper = pd.DataFrame({'date': pd.date_range(d['date'].min(), d['date'].max())})

d = pd.merge(d, helper, on='date', how='outer').sort_values('date')

d['val'] = d['val'].interpolate(method='linear')



    插值選擇方法不止有線性（linear），還可以是

    nearest：最鄰近插值法

    zero：階梯插值

    slinear、linear：線性插值

    quadratic、cubic：2、3階B樣條曲線插值（詳情請參考官方文檔）

 

Python Pandas

https://www.cnblogs.com/zhenyauntg/p/13188221.html