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In a data-driven world, businesses must make good use of the data they produce to remain competitive in any market. This involves predicting trends and making data-driven decisions. Stakeholders and decision-makers must analyze and interpret complex data quickly. This is where data visualization tools play a crucial role.
A chart comparison (histogram vs. bar chart) is a great tool for visualizing data. Although they may have some similarities — in fact, the histogram is a subclass of the bar chart — they’re quite different. In this article, you’ll learn the differences between the histogram and bar chart, and when to use them. You will also learn different bar graphing methods that help create more transparent and impactful data displays.
A histogram is a type of bar chart with connected bars that show the frequency and distribution of continuous data, using bins or intervals on the x-axis and values on the y-axis. Examples include average Instagram followers by age, website visit duration, or hotel counts by price range. Histograms are used to analyze data distributions, identify patterns, and simplify large datasets for statistical insights.
You should use a histogram to analyze continuous numerical data and detect changes in distribution. It shows particular patterns when analyzing distributions through central tendency measurements, as well as skewness and variability evaluation, if you have an analysis of test scores, website visit durations, and income brackets. The benefits of a histogram are that it shows the frequency distribution of values. This makes it ideal for understanding histogram data distribution across various datasets.
Here are a few histogram features mentioned below:
Let’s explore some comparison examples to highlight how histograms and bar charts can be applied to different kinds of data
A high school coach wants to evaluate players’ weights using bins like 50–60, 60–70, etc. The x-axis shows weight ranges, and the y-axis shows the number of players in each range. For example, if ten players weigh 90–100 lbs, the corresponding bar reaches 10 on the y-axis. A histogram in statistics displays how continuous data spreads across intervals.
Below is an example data set you can visualize using a histogram. A high school football coach wants to evaluate his players’ weight. Using a high school grading system, the coach is able to group the weight of his players. For example, the x-axis could include bins for players weights between 50-60, 60-70, and so forth. The y-axis will display the number of players with weights in the predefined range. If ten players’ weights fall between, the 90 – 100 bin bar will stop at the point marked “10” on the y-axis, as seen below.
A bar chart visualizes categorized data, making it easy to compare categories. Double bar charts compare two related data sets. Examples include students per course, properties per state, and yearly sales. Bar charts clearly show value differences, trends, and patterns across categories.
The following kinds of bar graphs exist for different data visualization requirements:
Users can tailor their data through a dynamic and interactive bar chart because FusionCharts supports every chart variation, offering flexibility when comparing histogram vs bar chart visualizations.
When different categories need comparison of their corresponding values, you should use a bar chart. This chart type serves to display survey results, product sales, and region-based population data. The use of bar graphing enables users to view which categories achieve better performance results.
Here are some of the bar chart characteristics listed below:
Knowledge about bar chart uses enables better assessment of situations that suit this data representation method despite its known limitations.
Read In-depth: Bar Charts: An easy guide for beginners
A developer community wants to compare users across programming languages. The x-axis shows the number of users, and the y-axis lists the languages. For instance, if Java has 60k+ users, its bar reaches the 60–70k mark. Bar charts compare distinct categories rather than continuous ranges.
Here’s a guide on preparing bar charts in Excel
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Below’s an example data set you can visualize using a histogram.
A high school football coach wants to evaluate his players’ weight. Using a high school grading system, the coach is able to group the weight of his players. For example, the x-axis could include bins for players weights between 50-60, 60-70, and so forth. The y-axis will display the number of players with weights in the predefined range. If ten players’ weights fall between, the 90 – 100 bin bar will stop at the point marked “10” on the y-axis, as seen below.
Here’s an example data type that requires a bar chart:
A global developer community wants to compare the number of users for various programming languages. Unlike the histogram example above, the x-axis would include the number of users of the various programming languages, with each language serving as a category. The y-axis will display the programming languages. If Java has around 60k+ users, the bar will stop between 60k – 70k, as seen in the chart below.
Here’s a guide on preparing bar charts. –>
Histograms and bar charts are both effective tools for representing large data sets. While they may share similarities, such as the number of axes and the use of bars, they display different data types and tell different stories. Below is a histogram vs. bar chart table describing their differences.
Histogram | Bar Chart |
| Histogram represents quantitative data by grouping them into bins. Bins can sometimes be referred to as intervals, classes, or buckets. | The bar chart plots datasets with data values divided into different non-numerical categories. |
| Histograms organize data in increasing order. The bins from left to right must be plotted from lowest to highest. | Bar charts have no strict organizational rules. What category comes first is at your discretion. However, some experts recommend using an alphabetical order of organization. Others recommend organization by size, for example, from smallest to largest or vice versa. |
| Histograms can determine the distribution or frequency of data values — for example, average income per age group. | A bar chart can determine the relationships between predefined categories — for example, product sales in different store locations. |
| There are no gaps between bins; therefore, no spaces between the bars of a histogram. However, if bins have zero value, they’re left empty and may appear as spaces between bars. | Bar charts have spaces between each category. |
| The bar widths of a histogram depend on the data it represents. It must be proportional to the data. Most importantly, the bar widths must equal the percentages used. | While the height of the columns of a bar chart is proportional to the data value of the y-axis, the bars’ widths are mostly similar. |
When selecting the best way to represent your data accurately, it’s essential to understand the difference between a bar graph and a histogram. Although both look similar, each serves a unique purpose based on the data type and structure.
| The x-axis of a histogram plots bins, numerical values, or range categories. The y-axis plots the data value of the bins or ranges. | The x-axis of a bar chart plots the various categories in the data set. The y-axis plots values representing the bars’ size in each category. |
| The variables plotted on a histogram are non-discrete variables. These are continuous variables whose values are determined through measurement. | The variables plotted on a bar chart are discrete variables. These are variables whose values are determined through counting. |
| Histograms group different x-axis elements or data values into bins or ranges. | Bar charts recognize each element, data value, or item as an individual entity. |
| Histograms can be used to identify trends and patterns. Its design and data type representation allows users to identify trends and predict future behavior or occurrences. | While bar charts allow you to determine which category performs best, it doesn’t display the details of why such category performs best or which element in a category is responsible for the high performance. Therefore, you can’t identify trends and patterns with a simple bar chart. However, there are classes of bar charts that display trends and patterns. providing more data visualization examples for comprehensive analysis. |
| Histograms do not display exact values; rather, they plot data in bins and ranges. | Bar charts display actual data values. |
| Since the columns of a histogram cannot be rearranged, skewness (i.e., data asymmetry or distribution) applies to histograms. | Bar charts allow for fluid column arrangement; therefore, skewness does not apply to bar charts. |
Read: Know the difference between bar charts and pie charts
Histograms and bar charts serve different purposes based on your data. Use histograms for frequency or distribution of continuous values, and bar charts for categorized data. If unsure, plot both to see which best represents your data. FusionCharts makes it easy to create and visualize your insights effectively. You can download a trial to see for yourself.
These are some of the use cases that show the difference between the histogram and bar chart. Knowing how histograms and bar charts differ from one another enables users to make proper decisions about their selection.
The histogram vs bar chart comparison is made easier with FusionCharts, which lets you make both charts at once to identify which visualization best communicates your data story.
Here are some of the common mistakes that appear when using these charts:
Histograms and bar charts are essential visualization tools for different data types. Use histograms for continuous data distributions and bar charts for category comparisons. Both kinds of visualizing examples can be easily created on platforms like FusionCharts, making data insights clear and actionable. Download a trial today to get started.
Both use bars along two axes, but bar charts show categories while histograms display continuous data.
Use histograms for continuous data distribution and bar charts for comparing distinct categories.
Choose histograms for trends and distributions, and bar charts for category comparisons; FusionCharts allows testing both.
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