Tableau prep tableau desktop pro#
Tableau prep tableau desktop free#

I was able to split the вЂњPlayerвЂќ field from Pro Football Reference, which was comprised of the playerвЂ™s name and a player ID, into two fields. The clean step also works like the transformation functions that can be performed on a data source on Tableau DesktopвЂ™s Data Source page. For example, some players were listed as вЂњLBвЂќ (linebacker) when they should have been listed as вЂњILBвЂќ (Inside Linebacker), which is a more specific position.

In my flow, I used the clean step to group up mismatched positions in SporTracвЂ™s 2018 player salary data. The resulting diagram shows the workflow IвЂ™m creating to transform and join my data. Tableau PrepвЂ™s Clean step allows me to change field names, filter out or replace values, split columns,В and group data by selecting a column in the profile pane, then selecting the action I want to perform from the list at the top of the pane.ДЄs you can see at the top of the workspace above, the cleaning function is represented by a new step connected to my data source. Enter Tableau Prep.ДЄfter opening Tableau Prep, I connect to the Excel workbook containing my data and drag the first table onto the canvas to get started. Correcting them all manually would take hours. Though small, these discrepancies would generate mismatches if we simply joined the data in Desktop. Some of the dimensions in the data sources contain slight differences (e.g. The draft data is drawn from a few different sources, including Pro Football Reference and SporTrac. Given each teamвЂ™s set of picks, where could they potentially replace a player on a market-priced contract with a similarly productive player on a rookie contract? By comparing the value of rookie contracts to those of existing players I hope to see the positions where each team might create value with their draft selection. This means that a team with the number one overall pick will pay the same salary to any player they select, whether he is a quarterback (typically thought of as the most important position on the field) or a punter (a position that gets on the field about five plays per game). In the NFL, draft position determines the value of first year contracts. With so much talk about the NFL Draft this year, I decided to look at the money being paid to each player being drafted. When the NFL Draft season arrived, I couldnвЂ™t help but to look at some NFL Draft data to analyze the incoming draft class against active NFL players.

Tableau prep tableau desktop free#

As a self-proclaimed sports nerd, when I have free time, I like to dive into sports data sets. Prep makes it easy to clean your data and to complete many data transformations that would be tedious or even impossible in Desktop or in the data source. Tableau PrepВ is a new visual data preparation tool that integrates with Tableau Desktop.