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A Pareto Chart is a special type of bar chart that sorts data from highest to lowest frequency, and it is used to identify the most significant factors in a process. A Histogram is a bar chart that shows the frequency of data in different groups or ranges. It is used to identify the shape of the data distribution and to identify outliers.
Two charts that look somewhat similar are pareto charts and histograms. However, these two charts are not the same and they’re each used in unique situations.
A pareto chart is a type of chart that displays quantitative or on the x-axis and uses bars ordered from highest to lowest frequency on the y-axis to visualize which values occur most often in a dataset.
A histogram is a type of chart that displays ranges of quantitative data on the x-axis and uses bars to represent the frequency of values in each range.
The following examples illustrate how to create and interpret each type of chart.
Example 1: Creating and Interpreting a Pareto Chart
Suppose we have the following dataset that shows the total sales of various products for a certain company:
We can create the following pareto chart to visualize which products contribute most to the total sales:
From this chart we can quickly see that product B has the highest total sales, followed by product A, followed by product F, etc.
The line in the chart also displays the percentage of cumulative sales by product. Note that the percentage of total sales is shown on the right axis.
For example:
- Product B accounts for roughly 25% of total sales
- Products B and A account for roughly 50% of total sales
- Products B, A, and F account for roughly 65% of total sales.
And so on.
Example 2: Creating and Interpreting a Histogram
Suppose we have the following dataset that shows the total number of points scored by various basketball players:
We can create the following histogram to visualize the distribution of points scored by the players:
From the histogram we can quickly gain an understanding of the distribution of points scored.
For example, we can see that most players score between 16 and 25 points, with very few scoring less than 5 and very few scoring 36 or more.
We can also see that the distribution is roughly “bell shaped” – indicating the the distribution of points scored is roughly .
Summary: Differences Between Pareto Charts & Histograms
Here’s a quick summary of the differences between pareto charts and histograms:
Difference #1: A pareto chart can use quantitative or qualitative data on the x-axis. Conversely, a histogram can only use quantitative data on the x-axis.
Difference #2: A pareto chart orders each bar from highest to lowest frequency. Conversely, a histogram places each bar in order from smallest to largest numerical values on the x-axis.
Difference #3: A pareto chart uses a line to represent cumulative frequencies of each bar. Conversely, a histogram does not use any such line.
Both pareto charts and histograms use bars to represent frequencies, but that’s about all they have in common.
The following tutorials offer additional information on pareto charts:
How to Create a Pareto Chart in Python
The following tutorials offer additional information on histograms: