Histograms visually summarize the distribution of a continuous numeric variable by measuring the frequency at which certain values appear in the dataset. The x-axis in a histogram is a number line that has been split into number ranges, or bins. For each bin, a bar is drawn where the width of the bar represents the range of the bin, and the height of the bar represents the number of data points that fall into that range. Understanding the distribution of your data is an important step in the data exploration process.
Histograms require one continuous Number variable on the x-axis.
Some analytical methods require that data be normally distributed. When the data is skewed (the distribution is lopsided), you might want to transform the data to make it normal. Histograms allow you to explore the effects of logarithmic and square root transformations on the distribution of your data. For reference, you can add a normal distribution overlay to your histogram by checking the Show Normal distribution checkbox in the Chart properties pane.
The logarithmic transformation is often used where the data has a positively skewed distribution and there are a few very large values. If these large values are located in your dataset, the log transformation will help make the variances more constant and normalize your data.
For example, the positively skewed distribution in the chart on the left is transformed to a normal distribution using a logarithmic transformation in the chart on the right:
Logarithmic transformations can only be applied to numbers greater than zero.
Square root transformation
A square root transformation is similar to a logarithmic transformation in that it reduces right skewness of a dataset. Unlike logarithmic transformations, square root transformations can be applied to zero.
Square root transformations can only be applied to numbers greater than or equal to zero.
Number of bins
The number of bins defaults to the square root of the number of records in your dataset. This can be adjusted by changing the Number of bins in the Data tab of the Chart pane. Changing the number of bins allows you to see more or less detail in the structure of your data.
Some basic descriptive statistics are calculated and displayed on histograms. The mean and median are displayed with one line each, and one standard deviation above and below the mean is displayed using two lines. You can click on these items in the statistics table or chart legend to toggle them on or off.
Default y-axis bounds are set based on the range of data values represented on the y-axis. These values can be customized by typing in a new desired axis bound value. Setting axis bounds can be used as a way to keep the scale of your chart consistent for comparison. Clicking the reset icon will revert the axis bound back to the default value.
You can format the way an axis will display numeric values by specifying a number format category or by defining a custom format string. For example, $#,### can be used as a custom format string to display currency values.
Titles and description
Charts and axes are given default titles based on the variable names and chart type. These can be edited on the General tab in the Chart Properties pane. You can also provide a chart Description, which is a block of text that appears at the bottom of the chart window.
It is not possible to change color settings for histograms in this release.
Guide lines or ranges can be added to charts as a reference or way to highlight significant values. To add a new guide, navigate to the Guides tab in the Chart Properties pane and click Add guide. To draw a line, enter a Value where you would like the line to draw. To create a range, enter a to value. You can optionally add text to your guide by specifying a Label.
Create a histogram to visualize distribution of population density across Washington, D.C. census block groups.
- Number— Population Density