- Histograms | Hands-On Data Visualization (2024)

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- Histograms

Histograms are best to show the distribution of raw data, by displaying the number of values that fall within defined ranges, often called buckets or bins. Creating a histogram can be a great way to better understand what your data looks like to inform your decision-making when designing more advanced visualizations, such as choropleth maps, as you’ll learn in Chapter 7. Although histograms may look similar to column charts, the two are different. First, histograms show continuous data, and usually you can adjust the bucket ranges to explore frequency patterns. For example, you can shift histogram buckets from 0-1, 1-2, 2-3, etc. to 0-2, 2-4, etc. By contrast, column charts show categorical data, such as the number of apples, bananas, carrots, etc. Second, histograms do not usually show spaces between buckets because these are continuous values, while column charts show spaces to separate each category.

In this section, you’ll create two types of histograms in Google Sheets: quick histograms using the Column stats menu versus regular histograms using the Chart menu, and the advantages of each method. For both tutorials we’ll use the same data: the average calorie supply per capita for 174 countries in 2017, compiled by the United Nations Food and Agriculture Organization, accessed through Our World In Data. Note that methods for measuring food supply vary across nations and over time, and estimate the amount of food availability, rather than actual consumption.

Quick Histograms with Google Sheets Column Stats

  1. Open the sample data on Average Daily Calorie Supply per capita by country 2017 in Google Sheets, log in with your account, and go to File > Make a Copy to create a version you can edit in your Google Drive.

  2. To create a quick histogram in Google Sheets, select any column, then go to Data > Column stats, and click the Distribution button in the sidebar to view a histogram for that column, as shown in Figure 6.27. The advantage is that this method is very fast, and you can quickly create histograms for other columns in the same sheet using the arrows near the top of the sidebar (< >). However, you cannot manually adjust the bucket ranges or make other edits to these quick histograms, and you cannot embed them on the web as you can with regular charts in Google Sheets.

- Histograms | Hands-On Data Visualization (1)

Figure 6.27: To create a quick histogram in a Google Sheet, select a column, then go to Data - Column stats - Distribution.

Histograms are designed to show broad patterns of data distribution, not individual values. The histogram in Figure 6.27 shows that while most nations have an average daily supply around 2,800 calories per capita, 8 nations have fewer than 2,000, and 11 nations have more than 3,500. Without annotations, histograms don’t tell us the names of those outlier countries. But they do offer a better sense of the shape of the data distribution.

Regular Histograms with Google Sheets Charts

Compare the quick histogram created with Column stats in Figure 6.27 with the regular histogram created with Charts in Figure 6.28. You’ll notice that in the regular histogram, you can define the bucket ranges, display dividers, and add titles and labels to provide more context to readers. Also, the interactive version of the regular histogram allows users to float their cursor to see underlying data on the count for each column.

Figure 6.28: Regular histogram chart: Explore the full-screen interactive version.

  1. To create a regular histogram in Google Sheets, open the sample data on Average Daily Calorie Supply per capita by country 2017 in Google Sheets, log in with your account, and go to File > Make a Copy to create a version you can edit in your Google Drive.

  2. Select only one column with numerical values as shown in Figure 6.29.

- Histograms | Hands-On Data Visualization (2)

Figure 6.29: Select only one column with values to create a histogram.

  1. Go to Insert > Chart. If Google Sheets does not automatically select Histogram chart as the Chart type in Chart editor, use the dropdown and select it manually, near the bottom of the list in the Other category, as shown in Figure 6.30

- Histograms | Hands-On Data Visualization (3)

Figure 6.30: If not shown automatically, go to the Chart Editor sidebar and select Setup - Chart type - Other - Histogram.

  1. You can manually set the range of each bucket and round the breakpoints to whole numbers (such as multiple of 1, 5, or 100), if this makes sense for the distribution of your data. In the Chart Editor, go to Customize > Histogram > Bucket size. Larger intervals will contain more data points and will appear wider, while smaller intervals will contain fewer points and appear narrower.

Note: Currently, Google Sheets does not allow users to remove decimal points in the x-axis label of a histogram, even when all of the breakpoints are integers.

  1. Optionally, you can break down the column into individual items (in our case, countries), which will appear as blocks with white boundaries. To do this, go to Customize > Histogram > Show item dividers.

  2. In the Chart Editor, customize further to add a Chart title, a subtitle to describe the source, and also vertical and horizontal axis titles to help readers interpret the chart.

Since the regular histogram is created using the Charts feature, you can choose to Publish it and copy the embed code for the interactive version, as you’ll learn in Chapter 9: Embed on the Web.

Now that you’ve learned how to create histograms to show the distribution of raw data, in the next section we’ll move on to other types of Google Sheets chart types, such as pie, line, and area charts.

- Histograms | Hands-On Data Visualization (2024)

FAQs

What is histogram data visualization? ›

A histogram is a graph used to represent the frequency distribution of a few data points of one variable. Histograms often classify data into various “bins” or “range groups” and count how many data points belong to each of those bins.

What are the alternatives to histograms? ›

Alternatives to histograms for visualizing height distribution include box plots, violin plots, density plots, and scatter plots. Each of these methods provides a different perspective on the data and can be useful depending on the specific requirements of the analysis.

Can you make a histogram in Google Sheets? ›

Double-click the “Insert” drop-down menu at the top of your Google Sheets and select “Chart.” The Chart editor panel will appear on the right. Click on “Chart type,” and a list of chart options will appear. Select “Histogram.”

How do you visualize multiple distributions at the same time? ›

The simplest approach to showing many distributions at once is to show their mean or median as points, with some indication of the variation around the mean or median shown by error bars.

What is the main purpose of a histogram? ›

The histogram is a popular graphing tool. It is used to summarize discrete or continuous data that are measured on an interval scale. It is often used to illustrate the major features of the distribution of the data in a convenient form.

What does a histogram tell you? ›

Histograms are visual representations of a data set which show how often each value in the data set occurs. The values are grouped into bins along the x-axis. The height of the bar indicates how many values of the data set fall into that bin.

What is the difference between a bar graph and a histogram? ›

Although histograms and bar charts use a column-based display, they serve different purposes. A bar graph is used to compare discrete or categorical variables in a graphical format whereas a histogram depicts the frequency distribution of variables in a dataset.

What is an example of a histogram? ›

For example, the histogram indicates that 40 of the 200 students received test scores greater than 90, with 100 being the highest score they could achieve. On the other hand, three students received scores of 50 or below, and 47 students received scores greater than 70 but lower than or equal to 80.

What is the best plot to show data distribution? ›

Box plots show distribution based on a statistical summary, while column histograms are great for finding the frequency of an occurrence. Scatter plots are best for showing distribution in large data sets.

What is the most appropriate option for visualizing distributions? ›

Boxplots, or box-and-whisker plots, provide a skeletal representation of a distribution. They are very well suited for showing distributions for multiple groups. There are many variations of boxplots: Most start with a box from the first to the third quartiles and divided by the median.

What is the best way to view the distribution of data? ›

A histogram is the most commonly used plot type for visualizing distribution. It shows the frequency of values in data by grouping it into equal-sized intervals or classes (so-called bins). In such a way, it gives you an idea about the approximate probability distribution of your quantitative data.

What is the histogram analysis used for? ›

Histogram analysis to visualize and graphically analyze the pixel frequencies in the image for each pixel or intensity value between 1 and 255. The histogram is very useful for the adversary to analyze the data distribution graphical view (cipher space).

What does a histogram visually represent? ›

A histogram is a statistical graph that represents the distribution of a continuous dataset through plotted bars, each representing a particular category or class interval. The bar height reflects the frequency or count of data points within each group.

How does a histogram help you analyze data? ›

Histograms show the shape of your data. The horizontal axis shows your data values, where each bar includes a range of values. The vertical axis shows how many points in your data have values in the specified range for the bar. In the histogram in Figure 1, the bars show the count of values in each range.

What is the difference between a histogram and a graph? ›

Although histograms and bar charts use a column-based display, they serve different purposes. A bar graph is used to compare discrete or categorical variables in a graphical format whereas a histogram depicts the frequency distribution of variables in a dataset.

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