rows : {list,Array,Vector}, labels to use for the rows of data

columns : {list,Array,Vector}, labels to use for the columns of data

datatypes : list(type), types for the columns of data

The DataFrame constructor produces a DataFrame data container, from the input data in various forms.

The input data (L) may be a list of columns for the resulting DataFrame. The individual columns in L may be specified as lists, one-dimensional rtables (Arrays, Vectors), or DataSeries objects.

You can also specify the data as a two-dimensional rtable (Matrix or Array) L, in which case the rows and columns of L are used respectively as the rows and columns of data for the DataFrame.

A sequence ds1, ds2, ... of DataSeries objects may be passed, and these are used as the columns of the resulting DataFrame.

A sequence of equations of the form label = ds can be passed to simultaneously specify the columns of data, from the DataSeries ds, and corresponding column labels label.

If the input T is a table, then the indices of T are used as the column labels, while the entries of T are used as the data items for the corresponding columns. Note that in this case, there is no pre-determined order for the columns.

The input L may be an existing DataFrame, in which case you can use the constructor to produce a new DataFrame with different (compatible) data types, or to re-label the data items.

$\mathrm{DataFrame}\left(⟨⟨⟨1\|2\|3⟩\,⟨4\|5\|6⟩⟩⟩\right)$

$\left[\begin{array}{cccc}& 1& 2& 3\\ 1& 1& 2& 3\\ 2& 4& 5& 6\end{array}\right]$

$\mathrm{df}≔\mathrm{DataFrame}\left(⟨⟨⟨1\|2\|3⟩\,⟨4\|5\|6⟩⟩⟩\,\'\mathrm{rows}\'\=\left[\'a\'\,\'b\'\right]\,\'\mathrm{columns}\'\=\left[\'A\'\,\'B\'\,\'C\'\right]\right)$

$\mathrm{df}≔\left[\begin{array}{cccc}& A& B& C\\ a& 1& 2& 3\\ b& 4& 5& 6\end{array}\right]$

${\mathrm{df}}_{\'A\'}$

$\left[\begin{array}{cc}a& 1\\ b& 4\end{array}\right]$

$\mathrm{type}\left({\mathrm{df}}_{\'A\'}\,\mathrm{DataSeries}\right)$

$\mathrm{true}$

$\mathrm{DataFrame}\left(⟨⟨⟨1\|2\|3⟩\,⟨4\|5\|6⟩⟩⟩\,\'\mathrm{rows}\'\=\left[\'a\'\,\'b\'\right]\,\'\mathrm{columns}\'\=\left[\'A\'\,\'B\'\,\'C\'\right]\,\'\mathrm{datatypes}\'\=\left[{\'\mathrm{integer}\'}_4\,{\'\mathrm{integer}\'}_4\,{\'\mathrm{integer}\'}_2\right]\right)$

$\left[\begin{array}{cccc}& A& B& C\\ a& 1& 2& 3\\ b& 4& 5& 6\end{array}\right]$

$\mathrm{DataFrame}\left(\left[\left[1\,2\,3\right]\,\left[4\,5\,6\right]\right]\right)$

$\left[\begin{array}{ccc}& 1& 2\\ 1& 1& 4\\ 2& 2& 5\\ 3& 3& 6\end{array}\right]$

$\mathrm{DataFrame}\left(\left[\left[1\,2\right]\,\left[3\,4\right]\,\left[5\,6\right]\right]\right)$

$\left[\begin{array}{cccc}& 1& 2& 3\\ 1& 1& 3& 5\\ 2& 2& 4& 6\end{array}\right]$

$\mathrm{DataFrame}\left(\left[\left[1\,2\right]\,\left[3\,4\,5\right]\right]\right)$

Error, (in DataFrame:-ModuleCopy) every column must have equally many data points, but received {2, 3}

$\mathrm{DataFrame}\left(\mathrm{df}\,\'\mathrm{rows}\'\=\left[\'c\'\,\'d\'\right]\right)$

$\left[\begin{array}{cccc}& A& B& C\\ c& 1& 2& 3\\ d& 4& 5& 6\end{array}\right]$

$\mathrm{DataFrame}\left(\mathrm{df}\,\'\mathrm{columns}\'\=\left[\'\mathrm{First}\'\,\'\mathrm{Second}\'\,\'\mathrm{Third}\'\right]\right)$

$\left[\begin{array}{cccc}& \mathrm{First}& \mathrm{Second}& \mathrm{Third}\\ a& 1& 2& 3\\ b& 4& 5& 6\end{array}\right]$

$\mathrm{DataFrame}\left(\mathrm{df}\,\'\mathrm{rows}\'\=\left[\'\mathrm{above}\'\,\'\mathrm{below}\'\right]\,\'\mathrm{columns}\'\=\left[\'\mathrm{First}\'\,\'\mathrm{Second}\'\,\'\mathrm{Third}\'\right]\right)$

$\left[\begin{array}{cccc}& \mathrm{First}& \mathrm{Second}& \mathrm{Third}\\ \mathrm{above}& 1& 2& 3\\ \mathrm{below}& 4& 5& 6\end{array}\right]$

$\mathrm{ds1}≔\mathrm{DataSeries}\left(\left[1\,2\,3\right]\right)$

$\mathrm{ds1}≔\left[\begin{array}{cc}1& 1\\ 2& 2\\ 3& 3\end{array}\right]$

$\mathrm{ds2}≔\mathrm{DataSeries}\left(\left[4\,5\,6\right]\right)$

$\mathrm{ds2}≔\left[\begin{array}{cc}1& 4\\ 2& 5\\ 3& 6\end{array}\right]$

$\mathrm{DataFrame}\left(\mathrm{ds1}\,\mathrm{ds2}\right)$

$\left[\begin{array}{ccc}& 1& 2\\ 1& 1& 4\\ 2& 2& 5\\ 3& 3& 6\end{array}\right]$

$\mathrm{DataFrame}\left(\left[\mathrm{ds1}\,\mathrm{ds2}\right]\right)$

$\left[\begin{array}{ccc}& 1& 2\\ 1& 1& 4\\ 2& 2& 5\\ 3& 3& 6\end{array}\right]$

$\mathrm{DataFrame}\left(\mathrm{ds1}\,\mathrm{ds2}\,\'\mathrm{columns}\'\=\left[\'A\'\,\'B\'\right]\right)$

$\left[\begin{array}{ccc}& A& B\\ 1& 1& 4\\ 2& 2& 5\\ 3& 3& 6\end{array}\right]$

The DataFrame command was introduced in Maple 2016.

For more information on Maple 2016 changes, see Updates in Maple 2016.