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
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()
^^^^ seems ok
intercept, slope = model.params << I don't think this is quite right
plt.plot(merged2[:-1].lastqu,merged2[:-1].Units, 'bo')
plt.hold(True)
^^^^^ 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()
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
Edit:
I found I could do:
fig = plt.figure(figsize=(12,8))
fig = sm.graphics.plot_regress_exog(model, "lastqu", fig=fig)
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!
See Question&Answers more detail:
os 与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…