从 pandas 回归获得回归线以进行绘图 [英] Getting the regression line to plot from a Pandas regression

问题描述

我已经尝试使用(pandas)pd.ols和(statsmodels)sm.ols来获得回归散点图和回归线，我可以得到散点图，但是我可以似乎没有获得参数来绘制回归线.很明显，我在这里做了一些剪切和粘贴编码:-((使用它作为指导:

I have tried with both the (pandas)pd.ols and the (statsmodels)sm.ols to get a regression scatter plot with the regression line, I can get the scatter plot but I can't seem to get the parameters to get the regression line to plot. It is probably obvious that I am doing some cut and paste coding here :-( (using this as a guide: http://nbviewer.ipython.org/github/weecology/progbio/blob/master/ipynbs/statistics.ipynb

我的数据在pandas DataFrame中，并且x列已合并2 [:-1] .lastqu 并且y数据列合并为2 [:-1].单位 我的代码现在如下: 得到回归:

My data is in a pandas DataFrame and the x column is merged2[:-1].lastqu and the y data column is merged2[:-1].Units My code is now as follows: to get the regression:

def fit_line2(x, y):
    X = sm.add_constant(x, prepend=True) #Add a column of ones to allow the calculation of the intercept
    model = sm.OLS(y, X,missing='drop').fit()
    """Return slope, intercept of best fit line."""
    X = sm.add_constant(x)
    return model
model=fit_line2(merged2[:-1].lastqu,merged2[:-1].Units)
print fit.summary()

^^^^似乎还可以

intercept, slope = model.params  << I don't think this is quite right
plt.plot(merged2[:-1].lastqu,merged2[:-1].Units, 'bo')
plt.hold(True)

^^^^^这样就完成了散点图 ****并且下面没有给我回归线

^^^^^ this gets the scatter plot done ****and the below does not get me a regression line

x = np.array([min(merged2[:-1].lastqu), max(merged2[:-1].lastqu)])
y = intercept + slope * x
plt.plot(x, y, 'r-')
plt.show()

Dataframe的摘要:[:-1]从数据中消除当前时间段，该数据随后将成为投影

A snippit of the Dataframe: the [:-1] eliminates the current period from the data which will subsequently be a projection

Units   lastqu  Uperchg lqperchg    fcast   errpercent  nfcast
date                            
2000-12-31   7177    NaN     NaN     NaN     NaN     NaN     NaN
2001-12-31   10694   2195.000000     0.490038    NaN     10658.719019    1.003310    NaN
2002-12-31   11725   2469.000000

我发现我可以做到:

fig = plt.figure(figsize=(12,8))
fig = sm.graphics.plot_regress_exog(model, "lastqu", fig=fig)

(如 Statsmodels文档中所述) 似乎得到了我想要的主要信息(以及更多)，我仍然想知道在先前的代码中哪里出错了！

as described here in the Statsmodels doc which seems to get the main thing I wanted (and more) I'd still like to know where I went wrong in the prior code!

推荐答案

检查数组和变量中的值.

Check what values you have in your arrays and variables.

我的猜测是您的x只是nans，因为您使用Python的min和max.至少在我当前打开的Pandas版本中会发生这种情况.

My guess is that your x is just nans, because you use Python's min and max. At least that happens with the version of Pandas that I have currently open.

最小和最大方法应该起作用，因为它们知道如何处理nan或缺少值

The min and max methods should work, since they know how to handle nans or missing values

>>> x = pd.Series([np.nan,2], index=['const','slope'])
>>> x
const   NaN
slope     2
dtype: float64

>>> min(x)
nan
>>> max(x)
nan

>>> x.min()
2.0
>>> x.max()
2.0

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