線性迴歸問題statsmodel

我有一個熊貓DF，看起來像這樣：線性迴歸問題statsmodel

broker-value-current broker-value-prior  consensus-after 
       590.00    510.00    462.55 
        32.74    31.98    30.72 
        33.00    30.00    30.04 

      pctch_broker  pctch_consensus pctch_frstrec_eps 
       15.686275    1.599051    1.421657 
       2.376485    0.195695   -82.098455 
       10.000000    0.805369   -82.098455 

     pctch_frstrec_rev 
       1.243782 
       -1.258936 
       -1.258936

其中最後幾列用創建：

data['pctch_broker'] = ((data['broker-value-current']-data['broker-value-prior'])/data['broker-value-prior'])*100 
data['pctch_consensus'] = ((data['consensus-after']-data['consensus-before'])/data['consensus-before'])*100 
data['pctch_frstrec_eps'] = ((data['frstrec_eps_announced']-data['frstrec_eps_forecast'])/data['frstrec_eps_forecast'])*100 
data['pctch_frstrec_rev'] = ((data['frstrec_rev_announced']-data['frstrec_rev_forecast'])/data['frstrec_rev_forecast'])*100

我還清楚NA這一行：

cleaned_data = data.dropna()

當使用SciPy的統計：

import statsmodels.formula.api as sm

然而，當我試圖迴歸「pctch_consensus」或「pctch_broker」與「pctch_frstrec_rev」或「pctch_frstrec_eps」與此代碼因變量的自變量：

reg1 = sm.ols(formula="pctch_consensus ~ pctch_frstrec_rev", data=cleaned_data).fit()

我收到此錯誤：

RuntimeWarning: invalid value encountered in greater return (S > tol).sum(axis=-1)

來源

2017-08-01 Graham Streich

哎呦，謝謝，我更新的問題，是的，我有我的進口產品，以及：進口statsmodels.formula.api爲SM –

發生此問題是因爲您的數據框中存在無窮無盡。創建新變量時，您可能會創建這些無窮大，除以零。

這應該修復它：

cleaned_data = data.replace([np.inf, -np.inf], np.nan)

來源

2017-08-01 21:06:12

線性迴歸問題statsmodel

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