The **Histogram** chart is the default display for numeric features. It "buckets" numeric feature values into equal-sized ranges to show frequency distribution of the variable&mdash;the target observation (left Y-axis) plotted against the frequency of the value (X-axis). The height of each bar represents the number of rows with values in that range.

??? note "Histogram display variations"
    The display differs depending on whether the [data quality](quality-check#interpret-the-histogram-tab) issue "Outliers" was found.

    Without data quality issues:

    ![](images/histogram.png)

    With data quality issues:

    ![](images/histogram-outlier.png)

Initially, the display shows the bucketed data:

![](images/dq-8.png)

Select the **Show outliers** checkbox to calculate and display outliers:

![](images/dq-10.png)

The traditional box plot above the chart (shown in gold) highlights the middle quartiles for the data to help you determine whether the distribution is skewed. To determine whisker length, DataRobot uses [Ueda's algorithm](https://jsdajournal.springeropen.com/articles/10.1186/s40488-015-0031-y){ target=_blank } to identify the outlier points&mdash;the whiskers depict the full range for the lowest and highest data points in the dataset excluding those outliers. This is useful for helping to determine whether a distribution is skewed and/or whether the dataset contains a problematic number of outliers.

Note the change in the X-axis scale and compression of the box plot to allow for outlier display. Because there tend to be fewer rows recording an outlier value (it's what makes them outliers), the blue bar may not display. Hover on that column to display a tooltip with the actual row count.

After EDA2 completes, the histogram also displays an [average target value](histogram#average-target-values) overlay.
