Plot only specific categorical values / scatterplot

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Simon Schmidt
Simon Schmidt 2021-4-28
评论： Adam Danz 2021-4-29
Hello,
I want to create a scatterplot of selected values (in this case A, B, D; without C & E) of a categorical attribute (see image).
Unfortunately I have not found a solution for this-
Help is much appreciated!
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Simon Schmidt
Simon Schmidt 2021-4-28
Hi Adam,
im having trouble with the selection. As described above I only want to plot some specific values of shop_name ("A", "B", "D")

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Adam Danz
Adam Danz 2021-4-28
编辑：Adam Danz 2021-4-29
Ran in:
>I only want to plot some specific values of shop_name ("A", "B", "D")
Using idexing. But with categories you also need to set which categories should appear on the axes (last line in demo). Otherwise, even with indexing, all categories will display in the plot, even if they do not contain y-values due to indexing.
Demo 1
T = table(repelem(categorical(num2cell(char(65:70))),1,2)', randi(10,12,1),'VariableNames',{'Shop','Sales'})
T = 12×2 table
Shop Sales ____ _____ A 5 A 5 B 4 B 6 C 7 C 10 D 3 D 3 E 5 E 2 F 8 F 7
selection = categorical({'A','B','D'});
idx = ismember(T.Shop, selection);
scatter(T.Shop(idx), T.Sales(idx),90,'filled')
ax = gca();
ax.XAxis.Categories = selection; % Set which categories appear
Demo 2
After adding the answer, I realized that indexing isn't really required but if you have many data points, indexing might help to speed up the process and reduce the size of the figure in memory since it only plots the data you want rather than plotting all of the data and then making only some of it visible like this approach does below.
T = table(repelem(categorical(num2cell(char(65:70))),1,2)', randi(10,12,1),'VariableNames',{'Shop','Sales'})
scatter(T.Shop, T.Sales,90,'filled')
ax = gca();
ax.XAxis.Categories = categorical({'A','B','D'});
If you want to change the visible categories you don't need to reproduce the plot, you just need to call this last line again with the selected categories.
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Simon Schmidt
Simon Schmidt 2021-4-29
Its about 2,000,000 rows of data- so i think your first solution is more handy. Thanks again!

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