There's a bunch of ways that Mito and Visidata are different. The two largest probably being:
1) Mito is an extension to JupyterLab whereas Visidata is a CLI tool. As a result, Mito is a react frontend that is more of a traditional Excel-styled spreadsheet interface. You can use your mouse to perform point-and-click transformations, like writing configuring pivot tables or writing spreadsheet formulas.
2) Mito generates Python/pandas code for every edit the the user makes. So users are generating a script to manipulate their dataframes, running that script, and then continuing to use their dataframes throughout the analysis. People use Mito in a Jupyter notebook the way that they use pandas code, multiple times throughout their analysis, interspersed with graphing, ML, etc.
1) Mito is an extension to JupyterLab whereas Visidata is a CLI tool. As a result, Mito is a react frontend that is more of a traditional Excel-styled spreadsheet interface. You can use your mouse to perform point-and-click transformations, like writing configuring pivot tables or writing spreadsheet formulas.
2) Mito generates Python/pandas code for every edit the the user makes. So users are generating a script to manipulate their dataframes, running that script, and then continuing to use their dataframes throughout the analysis. People use Mito in a Jupyter notebook the way that they use pandas code, multiple times throughout their analysis, interspersed with graphing, ML, etc.