Working with outputs
When you execute a code cell, its output is shown below. You can save the results or clear the output.
You can manage the length of the notebook by expanding and collapsing cell outputs.
Click an arrow next to the cell counter:
Right-click the output and select Save As from the context menu.
If you are using a dark UI theme, the colors in charts are adapted for better readability by default. To change this behavior, perform the following steps:
Go to Languages & Frameworks | Jupyter in the IDE Settings (CtrlAlt0S)
Disable the Invert image outputs for dark themes checkbox
Restart the editor to apply the changes.
Move the mouse pointer to the bottom of the cell, so that the pointer becomes a double arrow.
Click and drag the cell border up or down to reach the desired size:
When data frames are built, they are displayed in the tabular form. To open a data frame in a separate editor tab, click in the upper-right corner of the output cell.

Right-click the column name to open the context menu:

To copy the column name to the clipboard, select Copy Column Name.
To hide a column, select Hide Column. Hide Other Columns will hide all columns except the selected one.
To display hidden columns, click Columns List CtrlF12. The hidden columns are shown strikethrough. Select a column and press Space to toggle its visibility. To search through the column list, start typing a column name in the Columns List window.
To sort the table data based on the column values, you can either click the column name or select Ascending or Descending from the context menu.
To assign a language to a column, use Set Highlighting Language. For more information, refer to Inject a language for a column.
You can browse table data in several modes: Table, Tree, Text, and Transpose. To switch between these modes, click
in the upper-right corner of the output cell and select the mode that you need.
For more information about viewing modes, refer to View data.
To configure the way DataSpell displays data in the Text mode, use the Data Extractors drop-down:
For more information, refer to Data extractors.
Run a code cell that produces a table output from a data frame.
In the cell output, hover over a column name. A popup with column statistics appears.
For non-numeric dataFor numeric data- Data type
Shows the data type the column belongs to
- Missing
Shows the number of
None
values in the column- Count
Shows the total number of items in a column
- Distinct
Shows the number of unique values
- Top
Shows the most popular value
- Frequency
Shows the number of times an element occurs
- Data type
Shows the data type the column belongs to
- Missing
Shows the number of
None
values in the column- Count
Shows the total number of items in a column
- Mean
Shows the average number of all values in the column
- Std. Deviation
Shows the standard deviation value
- Min
Shows the minimum value in the column
- Pctl
Shows values for 5th, 25th, 50th( Median) and 95th percentiles
- Max
Shows the maximum value in the column
note
Viewing column statistics in table outputs is equivalent to using the
describe()
method forSeries
. For more information, refer to pandas.Series.describe and polars.Series.describe.
Thanks for your feedback!