Table blocks feature a lot of power β€” you can sort, filter, transform and run parallel explorations on datasets. Best of all, actions you take on tables are captured as code that can be re-used.
Table blocks are useful UI blocks to clean, explore and visualize data. They're baked with a ton of power for anything from basic sorting and filtering, to supporting complex groupings and maintaining several views of a dataframe.

Adding a table block

Actions you take on tables are capture as equivalent pandas code. After cleaning and exploring, you can click on Save as dataframe to capture the generated python code, and use it further in your analysis.

Add a source

Open the / menu and search for 'table' or type /table to add a table block. Use the source dropdown to select either a dataframe that's in memory, or a CSV that's been uploaded to your workspace. Learn more about uploading files.
The source popup shows dataframes that are in memory, as well as CSV files available in your workspace.

Column info & display

By default, Dolphyn gives you useful statistics about each column. Additionally, tables scroll and occupy the full screen-width.
Column stats for tables β€” varies by the type of data in each column.

Hiding columns

Often when working with large datasets it's common for there to be several columns. If you need to hide any for a more focused view, hover over the table and click on Columns to expose a popup where you can toggle on or off each column.
Adjust the toggle to hide / show a column.

Table-level options

You may want to adjust the table in various ways β€” for example wrap cells, change the number of rows per page or hide the columns stats. All of these settings and more are available in the ... menu available on table hover at the top right.
Click the more menu ... at the top right of the table for table level settings.

Column-level options

You may want to adjust columns in various ways β€” for example to change the column name, add a colored background, or each change its type. All of these settings are available by clicking on the column header.
Click on a column heading to adjust column level settings.