2016-07-14 453 views

回答

3

這應該做到這一點:

import numpy as np 
import pandas as pd 

df = pd.DataFrame(np.random.rand(100, 5), pd.date_range('2012-01-01', periods=100)) 

def trend(df): 
    df = df.copy().sort_index() 
    dates = df.index.to_julian_date().values[:, None] 
    x = np.concatenate([np.ones_like(dates), dates], axis=1) 
    y = df.values 
    return pd.DataFrame(np.linalg.pinv(x.T.dot(x)).dot(x.T).dot(y).T, 
         df.columns, ['Constant', 'Trend']) 


trend(df) 

enter image description here

使用上述用於它的索引相同df

df_sample = pd.DataFrame((df.index.to_julian_date()* 10 + 2)+ np.random.rand(100)* 1e3, df.index)

coef = trend(df_sample) 
df_sample['trend'] = (coef.iloc[0, 1] * df_sample.index.to_julian_date() + coef.iloc[0, 0]) 
df_sample.plot(style=['.', '-']) 

enter image description here