IntelliJ IDEA 2024.3 Help

Scientific mode

To perform scientific computing and data visualization, select the Python project type in the New Project wizard.

When choosing the Python project type, you need to ensure that you have conda installed. Once this is done, all you need is to specify the project name.

Note that to work with Matplotlib, Numpy, Plotly, or pandas, you need to install these packages on your Python interpreter.

Analyze data

View data structures

  • When viewing variables in the Python Console, you can click View as Array, View as DataFrame, or View as Series links to display the data in the Data View tool window.

    Viewing data frames
  • By default, the new table representation is used. Click Switch Between Table Representations Switch Between Table Representations to change the table interface.

  • Click Table Coloring Options to toggle and configure cell coloring.

    Switching the table interface
  • Use the Format field to adjust the data frame formatting.

    Adjusting the presentation of the data frame

Dataframes and series can be displayed in tabular or graphical form. By default, tables are shown. To toggle the view mode, use the corresponding icons in the upper left corner.

View dataframe as a table

Work with tables

  • To open the table search bar, click the table and press Ctrl+F.

  • To open the context menu, right-click the column name:

    Copying table headers
  • To copy the column name to the clipboard, select Copy Column Name.

  • To select the entire column, select Select Column.

  • 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 Ctrl+F12. 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 assign a language to a column, use Set Highlighting Language. For more information, refer to Inject a language for a column.

Sort data

  • To sort the table data based on the column values, you can either click the column name or select Ascending or Descending from the ORDER BY section in the context menu.

  • To add another column to sorting, you can either click the column name while pressing Alt or select Ascending or Descending from the Add to ORDER BY section in the context menu.

    The data will be sorted by selected columns.

    State

    Description

    No sorting

    Indicates that the data is not sorted in this column. The initial state of the sorting marker.

    Ascending order

    The data is sorted in the ascending order.

    Descending order

    The data is sorted in the descending order.

    Sorting level

    The number to the right of the marker (1 on the picture) is the sorting level. You can sort by more than one column. In such cases, different columns will have different sorting levels.

Filter data

  1. Click Open Filter View in the upper-right corner of the table.

  2. In the dialog that opens, select the column where you want to apply the filter and specify the filter criteria.

  3. If you want to use additional filters, click Add filter and specify the new filter criteria.

  4. Click Apply to filter data.

To remove or duplicate a filter, click Additional Filter ActionsAdditional Filter Actions and select the required option from the list.

View column statistics

By default, column statistics are turned off.

To change the default mode to Compact or Detailed, navigate to Settings | Languages & Frameworks | Tables.

The Compact mode includes only Missing and Count statistics:

Column statistics in a compact mode

For numeric data, histograms are plotted and shown together with statistics. Hover over the histogram to view detailed information about each bar.

To view detailed column statistics, do one of the following:

  1. Hover over a column name. A popup with column statistics appears.

  2. Click Show Column Statistics and select Detailed.

    The detailed statistics are shown above the columns.

Column statistics for non-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

Column statistics for 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

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

Work with charts

To view dataframes or series in a graphical form, click Show Chart.

The data will be displayed in the form of a chart. You can change the type of chart and configure additional settings.

Data displayed as a chart

Configure charts

  1. Click Show series settings Show series settings to change the initial settings of the chart.

  2. Select the chart type and configure the settings. You can choose one of the following chart types:

    • Bar

    • Pie

    • Area

    • Line

    • Scatter

    • Bubble

    • Stock

    • AreaRange

    • Histogram

    Change initial settings of the chart
  3. Click the Add new series link to add more series to the chart.

Save a chart as an image

  1. Click Export to PNG Export to PNG to save the generated chart in the .png format.

  2. Enter the filename and click Save.

View data visualizations

Data visualizations are displayed in the Plots tool window, allowing you to resize it and to zoom it in and out.

To save a plot, right-click the preview thumbnail and select Save as Image or Save All Plots from the context menu.

Matplotlib debugging

When stopping on a breakpoint, the plot being debugged appears in the Plots tool window. See the Debug section of the Data Science project tutorial.

Matplotlib and Plotly are also available in the console. See the Running in console section of the Data Science project tutorial. When starting a Python console (Tools | Python Console...), one can import required packages and build graphs as required:

Building graphs with matplotlib in Python console

The Java console is accessible for further inputs.

Last modified: 31 October 2024