The Chart tab shows a graphical representation of your data. It is also a quick and easy way to apply filter on your data.
According to the data type or semantic type that you select, the graphical representation of the distribution of values in the tab will be different:
- Vertical bar charts for numerical data
- Horizontal bar charts for text data
- World map for Continent and Continent Code, Country, Country Code ISO2 and Country Code ISO3
- Map of North America for North American state and North American state code
- US map for US State and US State Code
- Map of Mexico for MX Estado and MX Estado Code
- Map of Canada for CA Province Territory and CA Province Territory Code
- Map of France for FR Departement, FR Region and FR Region Legacy
This example uses a dataset with typical customer information, such as their names, gender, email or the country they live in.
Select a column containing text data you want to filter,
FIRST_NAME for instance.
The horizontal bar chart showing the most common occurrences of first names is displayed in the chart tab.
Click the top bar to apply a filter on the most common first name.
The preparation now only displays the rows with this first name.
You can also use Ctrl + Click or Shift + Click to select multiple values at the same time and apply a more complex filter.
Select the ISO2_COUNTRY_CODE column.
This time, the data is displayed in the form of a world map. The more occurrences of a country there is, the darkest this country will be on the map.
You can alternate between the world map view and the usual bar chart view by clicking the icons on the top right of the chart tab.
Click the Unites States directly on the map to add this filter to the previous
The grid now only displays the data corresponding to those two filters.
- In the Functions panel, click a function to execute it on the data you filtered, Delete these Filtered Rows for example.
- In the filter bar, click the cross in each individual filter or click the garbage bin icon to clear the filters and display the whole dataset again.