Wrangler is an interactive tool for cleaning data and transforming it. It helps the analyzers to spend minimum time formatting hence gives more time to analyze the data. Wrangler combines direct manipulation of visualized data with automatic inference of relevant transforms, enabling analysts to iteratively explore the space of applicable operations and preview their effects. Interactive histories support review, refinement, and annotation of transformation scripts. Wrangler significantly reduces specification time and promotes the use of robust, auditable transforms instead of manual editing.
The data wrangling results in a script which is written in a declarative transformation language. The script gives the description of the all transformations and hence enables analyzers to later inspect, reuse, and modify the data. By exporting, the analyst can either save the transformed data or generate runnable code implementing the transformation.
Transformation description table:
Cut | Remove selected text from cells in specified columns. |
Delete | Remove rows that match given indices or predicates. |
Drop | Remove specified columns from the table. |
Edit | Edit the text in each cell of the specified columns. |
Extract | Copy text from cells in a column into a new column. |
Fill | Fill empty cells using values from adjacent cells. |
Fold | Reshape a table into columns of key-value sets; selected rows map to keys, selected columns to values. |
Merge | Concatenate multiple columns into a single column. |
Promote | Promote row values to be the column names. |
Split | Split a column into multiple columns by delimiters. |
Translate | Shift the position of cell values by a given offset. |
Transpose | Transpose the rows and columns of the table. |
Unfold | Reshape a table by mapping key-value sets to a collection of new columns, one per unique key |
DATA USED:
The data which we would be using for our final demo/tutorial is the house crime data from the U.S. Bureau of Justice Statistics. This data is available as a sample data in the wrangler program. The data were downloaded as a CSV (comma-separated values) file, but are not immediately usable by other tools because the data contains empty lines, U.S. states are organized in disjoint matrices and the state names are embedded in other text. We would demonstrate how data wrangler can be used to interactively transform this difficult to use data into an easily usable format.
BUSINESS VALUE OF USING DATA WRANGLER:
· A lot of time is spent while reading the data needed to be manipulated by the analysis and visualization tools. Wrangler helps to speed up this process. Hence it helps managers to spend more time analyzing and learning from their data rather than spending much of the time just rearranging it.
· Data Wrangler allows interactive transformation of messy, real-world data into the data tables analysis tools expect. Export data for use in Excel, R, Tableau, Protovis etc.
LIMITATION:
Because this tool is still in its development stages, a major limitation right now is that data containing more than 40 columns and 1000 rows cannot be wrangled. In such a scenario the tool throws an exception and takes into consideration the first 40 columns and rows.
