I can't say anything about your data that
you're not telling me. But if you have 229
different partners in total, then Stata needs 229
ways of representing them, which is what
-graph pie- is telling you. The structure
of your data is not really the issue:
it is how many slices need to be explained
in a graph legend.
What you can do is draw 10 separate graphs,
one for each year, and then use -graph
combine- to put them together. But then
the legends will differ and all hope of
comparability disappears.
Having two or more time series does not
rule out a time series graph. Check out
-tsline- or -xtline-.
Nick
[email protected]
[email protected]
> In a first stage I had dropped all the partners but the ten
> main partners for each year that is why there is nothing in
> the syntax to identify these partners.
> I wonder if the problem is not that the ten first partners
> are not the same for each year? And even though the ten first
> main partners are not the same why stata cannot, for each
> year, apply the command? Isn't there something to do with the
> long or wide format of the data?
>
> By the way, a time series graph could be used to show the
> evolution of one particuliar partner but not of the structure
> contrary to a serie of pie charts which could, I think, both
> represent the distribution of the pie and the evolution in
> the size of the pie...
>
> Anyway thank you for your answer,
> I have three ideas here.
>
> 1. The variable -partenaires- evidently
> has 229 categories, and Stata will be struggling
> to cope.
>
> Quite possibly all you will see is a legend and the
> charts themselves will be out of sight.
>
> 2. I can't see how your syntax corresponds to
> identifying the ten main partners.
>
> 3. Although you want a series of pie charts
> it is difficult for me to see how they will convey
> the structure of your data at all well. A time series
> graph appears more natural here. Stata does supply
> pie charts -- largely so nobody can say "But you
> can't get a pie chart in Stata!" -- but that doesn't
> make them an effective method for showing comparative
> structure over time.
>
> Nick
> [email protected]
>
>
> *
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>
*
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