We’ve appended these datasets together to create one stacked dataset. The other contains all of the superhero movies released in 2014. One contains all of the superhero movies released in 2013. Usually, when appending data, the datasets contain the same (or very similar) fields. To append two datasets is to stack them to create one larger dataset. We’ve merged these datasets to create one dataset that contains state, state, capital, and state population through data cleanup. Here we have two datasets one contains a column for state and a column for state capitol the other contains a column for state and a column for state population. When your data is scattered in multiple datasets, merging allows you to combine the relevant parts of those datasets to create a new file to work with. We’ve filtered the list down to just the metal elements. Here we have a list of elements and their element type. Filteringįiltering a dataset narrows it down to just a specific group of records: Aggregating the list gave us the total number of Peace Prize Winners from each country. Here we have a list of Nobel Peace Prize Winners that includes the country they hail from. AggregatingĪggregating is sorting data and then expressing the data in a summary form. Below, we’ve created a visual glossary to answer that question and explain some commonly used data cleanup operations. So we asked ourselves, “What does data cleanup look like?” in hopes that this might be another way to communicate the meaning of these terms in a less technical way. While we’ve defined these terms in both a technical and less technical way, it might still be hard to visualize what these terms are actually doing… See how we can help!ĭuring a recent data conference, a coworker and I realized that there is a bit of a language barrier between “data people” and “non-data people.” For us, this was most apparent when we tried to describe data cleanup operations - while there are technical terms for types of data cleanup, we’ve found that many of them can be described just as easily in plain English.
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