Most of the Data Science working hours are spent on Data Wrangling. But, there is no UI tool that is designed for those who analyze data.
Exploratory’s ‘Step’ based UI experience makes it easy to clean up and transform data in an iterative and a fully reproducible way so that you can spend more time on discovering new insights.
Reproducible Data Wrangling Steps
All the data wrangling operations are recorded in the Step pane (right-hand side) so that you can quickly move to any step to see how the data changes. You can automatically reproduce all the steps at any time so no more of the repetitive data wrangling woks!
You can create multiple data frames from the same data to experiment with various scenarios.
Independently Managed Step
All the steps are managed together in a reproducible way. But they can function independently. This means that you can create charts to different steps, cache or disable some of the steps, move the steps around. Just works as you would expect!
You can create custom calculations by accessing hundreds of R functions natively integrated.
You can summarize (aggregate) your data quickly with a simple UI.
Summarize - Custom Calculation
By using the custom function support, you can add various calculations in a very flexible way.
You can transform your data into a Pivot format so that you can apply other calculations or apply analytics algorithms on top of the Pivot data.
You can assign new values for existing data. You can also group multiple values into a single value.
Text Data Wrangling
Cleaning up text data is cumbersome and can be scary with all the regular expressions. With Exploratory’s Text Data Wrangling UI makes it more intuitive and fun to work with text data with various useful methods.
Text Data Wrangling - Convert
You can convert between uppercase and lowercase, country name and IP address, state name and code, or anonymize your data with Text Convert UI.
Join with another data frame to bring additional columns or filter the data based on the data from another data frame.
Merge multiple data frames to add extra rows such as various months, locations, products, etc.
You can tokenize text sentences so that you can visualize which words are more frequently used or analyze the similarities of words, for example.
Wide to Long
Transform data from the wide format to the long format.
Long to Wide
Transform data from the long format to the wide format.
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