On Wednesday, October 31, 2012, wrote: > On Wed, Oct 31, 2012 at 8:59 PM, klo uo <klo...@gmail.com <javascript:;>> > wrote: > > Thanks for your reply > > > > I suppose, variable length signals are split on equal parts and dominant > > harmonic is extracted. Then scatter plot shows this pattern, which has > some > > low correlation, but I can't abstract what could be concluded from grid > > pattern, as I lack statistical knowledge. > > Maybe it's saying that data is quantized, which can't be easily seen from > > single sample bar chart, but perhaps scatter plot suggests that? That's > only > > my wild guess > > http://pandasplotting.blogspot.ca/2012/06/lag-plot.html > In general you would see a lag autocorrelation structure in the plot. > > My guess is that even if there is a pattern in your data we might not > see it because we don't see plots that are plotted on top of each > other. We only see the support of the y_t, y_{t+1} transition (points > that are at least once in the sample), but not the frequencies (or > conditional distribution). > > If that's the case, then > reduce alpha level so many points on top of each other are darker, or > colorcode the histogram for each y_t: bincount for each y_t and > normalize, or use np.histogram directly for each y_t, then assign to > each point a colorscale depending on it's frequency. > > Did you calculate the correlation? (But maybe linear correlation won't > show much.) > > Josef
The answer is hexbin() in matplotlib when you have many points laying on or near each other. Cheers! Ben Root
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