我会承认,遇到常见错误ValueError: shapes *value* and *value* not aligned
时我经常感到困惑,并且使用Statsmodels库运行的一些最新代码使我再次感到困惑。
我运行smModel = smf.ols(formula='leads ~ sessions', data=trainingRegressionData).fit()
没问题,但是在print(smModel.summary())
时遇到以下错误:
ValueError: shapes (181,61) and (181,61) not aligned: 61 (dim 1) != 181 (dim 0)
现在trainingRegressionData
是<class 'pandas.core.frame.DataFrame'>
,形状是(181, 2)
,所以我不确定摘要如何吐出61列,但是即使这样,形状也一样那么为什么错误会说未对齐?
对于上述问题的任何帮助以及有关调试形状错误的解释,将不胜感激。
完全错误:
ValueError Traceback (most recent call last)
<ipython-input-14-6777963ed99f> in <module>()
----> 1 print(smModel.summary())
~/.pyenv/versions/3.6.5/lib/python3.6/site-packages/statsmodels/regression/linear_model.py in summary(self, yname, xname, title, alpha)
2374 top_left.append(('Covariance Type:', [self.cov_type]))
2375
-> 2376 top_right = [('R-squared:', ["%#8.3f" % self.rsquared]),
2377 ('Adj. R-squared:', ["%#8.3f" % self.rsquared_adj]),
2378 ('F-statistic:', ["%#8.4g" % self.fvalue]),
~/.pyenv/versions/3.6.5/lib/python3.6/site-packages/statsmodels/tools/decorators.py in __get__(self, obj, type)
95 if _cachedval is None:
96 # Call the "fget" function
---> 97 _cachedval = self.fget(obj)
98 # Set the attribute in obj
99 # print("Setting %s in cache to %s" % (name, _cachedval))
~/.pyenv/versions/3.6.5/lib/python3.6/site-packages/statsmodels/regression/linear_model.py in rsquared(self)
1541 def rsquared(self):
1542 if self.k_constant:
-> 1543 return 1 - self.ssr/self.centered_tss
1544 else:
1545 return 1 - self.ssr/self.uncentered_tss
~/.pyenv/versions/3.6.5/lib/python3.6/site-packages/statsmodels/tools/decorators.py in __get__(self, obj, type)
95 if _cachedval is None:
96 # Call the "fget" function
---> 97 _cachedval = self.fget(obj)
98 # Set the attribute in obj
99 # print("Setting %s in cache to %s" % (name, _cachedval))
~/.pyenv/versions/3.6.5/lib/python3.6/site-packages/statsmodels/regression/linear_model.py in ssr(self)
1513 def ssr(self):
1514 wresid = self.wresid
-> 1515 return np.dot(wresid, wresid)
1516
1517 @cache_readonly
ValueError: shapes (181,61) and (181,61) not aligned: 61 (dim 1) != 181 (dim 0)
trainingRegressionData
的头尾:
[181 rows x 2 columns]>
sessions leads
366 197 33
367 408 71
368 404 59
369 412 60
...
544 357 58
545 285 48
546 275 38
[181 rows x 2 columns]