A DataSeries is a one-dimensional data container, similar to a one-dimensional Array, but whose entries can be referenced by "labels", as well as by position.

A related two-dimensional data container, known as a DataFrame is also available.

You can access the elements of a DataSeries similar to the way in which you access Array elements, by indexing the DataSeries by position. If ds is a DataSeries, then ds[ i ] evaluates to the ith element of ds. However, the elements of a DataSeries are also associated with symbolic names, and you can use these names to refer to DataSeries elements as well.

ds := DataSeries( [ sin( x ), cos( x ), tan( x ) ], 'labels' = [ 's', 'c', 't' ] );

$\mathrm{ds}≔\left[\begin{array}{cc}s& \sin \left(x\right)\\ c& \cos \left(x\right)\\ t& \tan \left(x\right)\end{array}\right]$

ds[ 2 ];

$\cos \left(x\right)$

ds[ 'c' ];

$\cos \left(x\right)$

To select a range of entries in a DataSeries, returning the result as a DataSeries, use a range of indices or labels.

ds[ 1 .. 2 ];

$\left[\begin{array}{cc}s& \sin \left(x\right)\\ c& \cos \left(x\right)\end{array}\right]$

ds[ 'c' .. 't' ];

$\left[\begin{array}{cc}c& \cos \left(x\right)\\ t& \tan \left(x\right)\end{array}\right]$

Note that indices and labels can be used together:

ds[ 'c' .. -1 ];

$\left[\begin{array}{cc}c& \cos \left(x\right)\\ t& \tan \left(x\right)\end{array}\right]$

You can select non-contiguous entries by enclosing the desired indices in a list.

ds[ [ 's', 't' ] ];

$\left[\begin{array}{cc}s& \sin \left(x\right)\\ t& \tan \left(x\right)\end{array}\right]$

One particular application for this kind of index is to re-order the given DataSeries.

ds2 := ds[ [ 2, 3, 1 ] ];

$\mathrm{ds2}≔\left[\begin{array}{cc}c& \cos \left(x\right)\\ t& \tan \left(x\right)\\ s& \sin \left(x\right)\end{array}\right]$

$\mathrm{ds}≔\mathrm{DataSeries}\left(\left[4\,5\,6\right]\,'\mathrm{labels}'=\left['a'\,'b'\,'c'\right]\right)$

$\mathrm{ds}≔\left[\begin{array}{cc}a& 4\\ b& 5\\ c& 6\end{array}\right]$

$\mathrm{type}\left(\mathrm{ds}\,\mathrm{DataSeries}\right)$

$\mathrm{true}$

$\mathrm{type}\left(\mathrm{ds}\,'\mathrm{Array}'\right)$

$\mathrm{false}$

$\mathrm{ds}\left[1\right]$

$4$

$\mathrm{ds}\left[b\right]$

$5$

ds >~ 4;

$\left[\begin{array}{cc}a& \mathrm{false}\\ b& \mathrm{true}\\ c& \mathrm{true}\end{array}\right]$

ds[ ds >~ 4 ];

$\left[\begin{array}{cc}b& 5\\ c& 6\end{array}\right]$

$\mathrm{oct27\_28}≔\mathrm{DataSeries}\left(\mathrm{map}\left(\mathrm{Temperature}\,\left[11\,12\,13\,12\,11\,10\,9\,8\,7\,7\,7\,7\,7\,7\,7\,7\,7\,8\,8\,8\,7\,8\,9\,10\right]\,'\mathrm{degC}'\right)\,'\mathrm{labels}'=\left[''12:00''\,''13:00''\,''14:00''\,''15:00''\,''16:00''\,''17:00''\,''18:00''\,''19:00''\,''20:00''\,''21:00''\,''22:00''\,''23:00''\,''00:00''\,''01:00''\,''02:00''\,''03:00''\,''04:00''\,''05:00''\,''06:00''\,''07:00''\,''08:00''\,''09:00''\,''10:00''\,''11:00''\right]\right)$

$\mathrm{avg}≔\frac{\mathrm{add}\left(\mathrm{oct27\_28}\right)}{\mathrm{numelems}\left(\mathrm{oct27\_28}\right)}$

$\mathrm{avg}≔\frac{69}{8}⟦\mathrm{\°C}⟧$

$\mathrm{Value}\left(\mathrm{avg}\right)$

$\frac{69}{8}$

$\mathrm{convert}\left(\mathrm{oct27\_28}\,'\mathrm{list}'\right)$

$\left[11⟦\mathrm{\°C}⟧\,12⟦\mathrm{\°C}⟧\,13⟦\mathrm{\°C}⟧\,12⟦\mathrm{\°C}⟧\,11⟦\mathrm{\°C}⟧\,10⟦\mathrm{\°C}⟧\,9⟦\mathrm{\°C}⟧\,8⟦\mathrm{\°C}⟧\,7⟦\mathrm{\°C}⟧\,7⟦\mathrm{\°C}⟧\,7⟦\mathrm{\°C}⟧\,7⟦\mathrm{\°C}⟧\,7⟦\mathrm{\°C}⟧\,7⟦\mathrm{\°C}⟧\,7⟦\mathrm{\°C}⟧\,7⟦\mathrm{\°C}⟧\,7⟦\mathrm{\°C}⟧\,8⟦\mathrm{\°C}⟧\,8⟦\mathrm{\°C}⟧\,8⟦\mathrm{\°C}⟧\,7⟦\mathrm{\°C}⟧\,8⟦\mathrm{\°C}⟧\,9⟦\mathrm{\°C}⟧\,10⟦\mathrm{\°C}⟧\right]$

$\mathrm{convert}\left(\mathrm{oct27\_28}\,'\mathrm{set}'\right)$

$\left\{8⟦\mathrm{\°C}⟧\,7⟦\mathrm{\°C}⟧\,9⟦\mathrm{\°C}⟧\,10⟦\mathrm{\°C}⟧\,13⟦\mathrm{\°C}⟧\,12⟦\mathrm{\°C}⟧\,11⟦\mathrm{\°C}⟧\right\}$

$\mathrm{convert}\left(\mathrm{oct27\_28}\,'\mathrm{table}'\right)$

$table\left(\left[''18:00''=9⟦\mathrm{\°C}⟧\,''09:00''=8⟦\mathrm{\°C}⟧\,''19:00''=8⟦\mathrm{\°C}⟧\,''08:00''=7⟦\mathrm{\°C}⟧\,''20:00''=7⟦\mathrm{\°C}⟧\,''13:00''=12⟦\mathrm{\°C}⟧\,''07:00''=8⟦\mathrm{\°C}⟧\,''12:00''=11⟦\mathrm{\°C}⟧\,''21:00''=7⟦\mathrm{\°C}⟧\,''06:00''=8⟦\mathrm{\°C}⟧\,''05:00''=8⟦\mathrm{\°C}⟧\,''22:00''=7⟦\mathrm{\°C}⟧\,''15:00''=12⟦\mathrm{\°C}⟧\,''04:00''=7⟦\mathrm{\°C}⟧\,''14:00''=13⟦\mathrm{\°C}⟧\,''23:00''=7⟦\mathrm{\°C}⟧\,''10:00''=9⟦\mathrm{\°C}⟧\,''03:00''=7⟦\mathrm{\°C}⟧\,''00:00''=7⟦\mathrm{\°C}⟧\,''17:00''=10⟦\mathrm{\°C}⟧\,''02:00''=7⟦\mathrm{\°C}⟧\,''11:00''=10⟦\mathrm{\°C}⟧\,''16:00''=11⟦\mathrm{\°C}⟧\,''01:00''=7⟦\mathrm{\°C}⟧\right]\right)$