python进行数据分析----线性回归，,线性回归分析：方法：

python进行数据分析----线性回归，,线性回归分析：方法：

线性回归分析：

方法：    import statsmodels.api as smimport pandas as pdfrom patsy.highlevel  import dmatrices  ----2.7里面是 from patsy import dmatriceshg =‘D:/hg.csv‘df=pd.read_csv(hg)vars=[‘rkzzl‘,‘zrs‘,‘rjgdp‘]df=df[vars]y,X=dmatrices(‘ rkzzl ~ zrs + rjgdp ‘,data=df,return_type=‘dataframe‘)mod=sm.OLS(y,X)res=mod.fit()print res.summary()

所有代码：

import statsmodels.api as smimport pandas as pdimport numpy as npfrom patsy.highlevel import dmatricesfrom common.util.my_sqlalchemy import sqlalchemy_engineimport mathsql = "select Q1R3, Q1R5, Q1R6, Q1R7 from db2017091115412316222027656281_1;"df = pd.read_sql(sql, sqlalchemy_engine)df_dropna = df.dropna()y,X=dmatrices(‘ Q1R3 ~ Q1R5 + Q1R6 + Q1R7‘,data=df_dropna,return_type=‘dataframe‘)mod=sm.OLS(y,X)res=mod.fit()result = res.summary()print(result)model = {                ‘n‘: int(res.nobs),                ‘df‘: res.df_model,                ‘r‘: math.sqrt(res.rsquared),                ‘r_squared‘:res.rsquared,                ‘r_squared_adj‘: res.rsquared_adj,                ‘f_statistic‘: res.fvalue,                ‘prob_f_statistic‘: res.f_pvalue,              }coefficient = {         ‘coefficient‘:list(res.params),         ‘std‘: list(np.diag(np.sqrt(res.cov_params()))),         ‘t‘: list(res.tvalues),         ‘sig‘: [i for i in map(lambda x:float(x),("".join("{:.4f},"*len(res.pvalues)).format(*list(res.pvalues))).rstrip(",").split(","))]      }returnValue = {‘model‘: model, ‘coefficient‘: coefficient}print(returnValue)

{    ‘model‘: {            ‘df‘: 3.0,             ‘n‘: 665,             ‘prob_f_statistic‘: 1.185607423551511e-17,             ‘r_squared_adj‘: 0.11247707470462853,             ‘f_statistic‘: 29.049896130483212,             ‘r_squared‘: 0.11648696743939679,             ‘r‘: 0.3413018714267427},     ‘coefficient‘: {            ‘std‘: [0.30170364007280126, 0.049972399035516278, 0.051623405028706125, 0.047659986606566104],             ‘sig‘: [0.0, 0.0, 0.0, 0.0312],             ‘t‘: [5.4578212730306044, 5.3469744215460269, 4.3810228293129168, 2.1587543885465008],             ‘coefficient‘: [1.6466445449401035, 0.26720113942619689, 0.22616331595762876, 0.10288620524499202]}}

python进行数据分析----线性回归