When you create a box plot, a result dataset with the input fields and output statistics will be added to the data pane. Outlier values are indicated on the box plot as circles linked by dottedĮach statistic or range in the box plot can be selected by clicking the chart. In Insights, the range for the lower and upper If there are no outliers, the whiskers will stretch to the minimum and maximum values in the dataset. Whiskers on a box plot represent the threshold beyond which values are considered outliers. Outliers are values that are much larger or smaller than the rest of the data. The Card info tab provides information about the data on the card and the Export data tab allows users to export the data from the card.Ī key feature for a box plot is the determination Use the Flip card button to view the back of the card. If the box plot includes a Group by field, the visualization can be changed to charts, such as a line graph or column chart. Use the Visualization type button to switch directly between a box plot and other visualizations, such as a graduated symbols map, summary table, or histogram. The Appearance tab changes the symbol color on the chart (single symbol only).To change the color associated with a value, click the symbol and choose a color from the palette or enter a hex value. You can use the legend to make selections on the chart. The pop out legend button displays the legend as a separate card on your page. If a group by field is used, side-by-side box plots are created, with each box plot representing the spread of data in each category. The Legend tab is available when a group by field is applied to the x-axis of the chart.The Layer options pane contains the following functions: The Layer options button opens the Layer options pane. Database datasets are available through database connections in Insights in ArcGIS Enterprise and Insights desktop. Box plots with fewer than five records are most likely to occur when grouping your box plot using a string field or applying a filter to your dataset or card. To create a box plot, complete the following steps:īox plots created from database datasets must have at least five records. The analyst may want to focus her analysis on those two regions to find out why there is such a variation in performance. In the Bay Area and Southern regions, the whiskers are a bit longer, which implies those regions have stores that are performing poorly, as well as stores that are performing well. However, the whiskers for the Northern and Central regions are slightly more compact than the Bay Area and Southern regions, which implies that those regions have more consistent performance than the others. The result is four individual box plots that can be compared to discern information about each region.īased on the box plots, the analyst can tell that there are few differences between regions the medians are consistent across the four box plots, the boxes are similar sizes, and all regions have outliers at both the minimum and maximum ends. She does this by changing the Group by field to Region. To delve deeper into the data, the analyst decides to create individual box plots for each region where the stores are located. There are also low and high outliers, which gives the analyst an indication of which stores are over- and underperforming. The distribution seems fairly even, with the median being in the middle of the box and the whiskers being a similar size. The box plot above shows the median sales amount is $1,111,378 (shown by hovering over the chart or using the Flip card button to flip the card over). A box plot of the annual revenue at each store can be used to determine the distribution of sales, including the minimum, maximum, and median values. Using a number or rate/ratio field on the y-axis.īox plots can answer questions about your data, such as: How is my data distributed? Are there any outliers in the dataset? What are the variations in the spread of several series in the dataset? ExamplesĪ market researcher is studying the performance of a retail chain. Outliers can reveal mistakes or unusual occurrences in data. They show the median, upper and lower quartiles, minimum and maximum Box plots provide a quick visual summary of the
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |