◆ Data preparation overview
The help topics in this section describe how you can prepare data within the dashboard after importing to enable appropriate visualizations and extended analysis.
Timestamp Data Preparation
When raw data is imported, date-time attributes are likely to be first recognized as numeric or text data. Data preparation steps can convert these data to timestamp attributes for correct and effective analysis in Keshif.
Parsing timestamp data from categorical data
- Learn how to convert categorical (text) values of dates to timestamp data.
Parsing timestamp data from numeric data
- Learn how to convert numeric values (such as year) to timestamp data.
Extracting time components (month, year, weekday,...) from timestamp data
Categorical Data Preparation
Splitting multi-categories in an attribute
- If the data source include multiple categories stored in a single column, learn how to easily split the categories.
Changing category labels
- If the data source codes each category by a different value (e.g. M for Male), learn how to easily change labels.
Converting from numeric to categorical attribute
- If the data source codes categories by a numeric numeric value, or if you wish to have a categorical visualization for numeric options, learn how to change the data type from numeric to categorical.
Numeric Data Preparation
Setting unit name of numeric data
- Learn how to set unit names ("kg", "m" and "$") for numeric data.
Removing non-positive values from numeric data
Controlling aggregation options for a numeric attribute
- Learn how to fine-tune measurement options by selecting how a numeric attribute can be used for aggregation.