Scientific mode
Scientific mode in Python plugin provides support for interactive scientific computing and data visualization.
To enable the Scientific mode use one of the following ways
Go to .
In your code, add an import statement for
numpy. IntelliJ IDEA shows the banner that suggests that you enable the Scientific mode:
Click the Use scientific mode link on the banner.
User interface in the scientific mode
With this mode enabled, the following changes are introduced to the UI:
The SciView tool window appears. It has two tabs:
Data tab for viewing data from pandas DataFrames and numpy arrays.
Plots tab for viewing Matplotlib charts.
Python console is shown.
The Documentation tool window appears (a pinned version of the Quick Documentation popup), showing the inline documentation for the symbol at caret.
In the Scientific mode you can format your code as a set of executable cells to run each separately. To split your code into cells just add # %% lines where appropriate.
Analyzing data
When you preview variable in the Python Console, you can click DataFrame or Array links to view these types in the Data tab of the SciView tool window.
You can sort data in a table column by clicking a soring icon (
) on its header. You can also filter out data in the table by selecting a column name and typing a substring or an expression.
Set a value (for example, 8) or use a wildcard (for example, 8*):
Type an expression using x as a column value variable (for example, x > 20):
A column with an applied filter is marked with the filter icon (
). Hover over it to see the filter value.
Any table can be saved (
) or opened in a separate tab of the editor (
). You can also select any cells in the table and copy them to the clipboard (Control+C). The copied cells can be pasted into any file, for example, .csv.
Building matplotlib charts
In the Scientific mode, a graph opens in its own tab in the SciView window, allowing you to resize it, and to zoom it in and out.
When stopping on a breakpoint, a tab appears in the SciView with the graph being debugged. See the Debug section of the Scientific Mode tutorial.
Matplotlib is available also in console. See the Running in console section of the Scientific Mode tutorial. When starting a Python console (), one can import Matplotlib, and build graphs as required:
The Java console is accessible for further inputs.