[英]Plotting Pandas OLS linear regression results
对于从熊猫进行的线性回归,我如何绘制线性回归结果?
import pandas as pd
from pandas.stats.api import ols
df = pd.read_csv('Samples.csv', index_col=0)
control = ols(y=df['Control'], x=df['Day'])
one = ols(y=df['Sample1'], x=df['Day'])
two = ols(y=df['Sample2'], x=df['Day'])
我尝试了plot()
但是没有用。 我想在一个绘图上绘制所有三个样本,是否有任何熊猫代码或matplotlib代码以这些摘要的格式处理数据?
无论如何,结果看起来像这样:
控制
------------------------Summary of Regression Analysis-------------------------
Formula: Y ~ <x> + <intercept>
Number of Observations: 7
Number of Degrees of Freedom: 2
R-squared: 0.5642
Adj R-squared: 0.4770
Rmse: 4.6893
F-stat (1, 5): 6.4719, p-value: 0.0516
Degrees of Freedom: model 1, resid 5
-----------------------Summary of Estimated Coefficients------------------------
Variable Coef Std Err t-stat p-value CI 2.5% CI 97.5%
--------------------------------------------------------------------------------
x -0.4777 0.1878 -2.54 0.0516 -0.8457 -0.1097
intercept 41.4621 2.9518 14.05 0.0000 35.6766 47.2476
---------------------------------End of Summary---------------------------------
一
-------------------------Summary of Regression Analysis-------------------------
Formula: Y ~ <x> + <intercept>
Number of Observations: 6
Number of Degrees of Freedom: 2
R-squared: 0.8331
Adj R-squared: 0.7914
Rmse: 2.0540
F-stat (1, 4): 19.9712, p-value: 0.0111
Degrees of Freedom: model 1, resid 4
-----------------------Summary of Estimated Coefficients------------------------
Variable Coef Std Err t-stat p-value CI 2.5% CI 97.5%
--------------------------------------------------------------------------------
x -0.4379 0.0980 -4.47 0.0111 -0.6300 -0.2459
intercept 29.6731 1.6640 17.83 0.0001 26.4116 32.9345
---------------------------------End of Summary---------------------------------
二
-------------------------Summary of Regression Analysis-------------------------
Formula: Y ~ <x> + <intercept>
Number of Observations: 5
Number of Degrees of Freedom: 2
R-squared: 0.8788
Adj R-squared: 0.8384
Rmse: 1.0774
F-stat (1, 3): 21.7542, p-value: 0.0186
Degrees of Freedom: model 1, resid 3
-----------------------Summary of Estimated Coefficients------------------------
Variable Coef Std Err t-stat p-value CI 2.5% CI 97.5%
--------------------------------------------------------------------------------
x -0.2399 0.0514 -4.66 0.0186 -0.3407 -0.1391
intercept 24.0902 0.9009 26.74 0.0001 22.3246 25.8559
---------------------------------End of Summary---------------------------------
您可能会发现我的问题对您有所帮助从熊猫回归中绘制回归线
我试图找到一些与Pandas一起进行ols绘图的代码,但是却无法付诸实践,通常来说,使用Statsmodels可能会更好,因为它了解Pandas数据结构..因此过渡不是太难。 然后,我的回答和引用的示例将更有意义。
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