Data Visualization 101: How to Choose the proper Chart or Graph for the Data
Sorts of Charts to Use for Your Data
- Column Chart
- Bar Graph
- Line Graph
- Dual Axis Chart
- Area Chart
- Stacked Bar Graph
- Mekko Chart
- Pie Chart
- Scatter Plot Chart
- Bubble Chart
- Waterfall Chart
- Funnel Chart
- Bullet Chart
- Heat Map
You and I sift through a lot of data for our jobs. Data about website performance, sales performance, product adoption, customer service, marketing campaign results… the list goes on.
When you manage multiple content assets , such as social media or a blog, with several sources of data, it can obtain overwhelming. What should you be monitoring? What actually matters? How can you visualize and analyze the data so you can extract insights plus actionable information?
Meters ore importantly, how will you make reporting more efficient giving up cigarettes busy working on multiple tasks at once?
One of the struggles that slows down my own reporting plus analysis is understanding what types of graphs to use — plus why. That’s because selecting the wrong visual aid or perhaps defaulting to the most common kind of data visualization could cause dilemma with the viewer or lead to mistaken data interpretation.
To generate charts that clarify and offer the right canvas for analysis, you should first understand the reasons why you might need a chart. In this post, I’ll cover five answers to find when choosing a chart for your data.
Then, I’ll provide an overview of 14 various kinds of charts you have at your disposal.
five Questions to Ask Whenever Deciding Which Type of Chart to Use
1 . Do you want to compare values?
Charts are perfect for comparing one or many value sets, and they can easily show the low plus high values in the information sets. To create a comparison chart, use these types of graphs:
- Scatter Plot
2 . Do you want to show the composition of some thing?
Use this type of chart to exhibit how individual parts make up the whole of something, like the device type used for cellular visitors to your website or complete sales broken down by sales rep.
To show composition, use these types of charts:
- Stacked Bar
- Stacked Column
a few. Do you want to understand the distribution of the data?
Distribution charts enable you to understand outliers, the normal tendency, and the range of information within your values.
Use these graphs to show distribution:
- Scatter Plot
4. Are you interested in analyzing trends in your data set?
If you want to know more details about how a data set performed during a specific time period, there are specific chart types that do extremely well.
You should choose a:
- Dual-Axis Series
5. Do you want to better be familiar with relationship between value sets?
Relationship charts are suited to showing how one adjustable relates to one or numerous various variables. You could use this to show how something positively results, has no effect, or negatively effects another variable.
When trying to establish the relationship between things, use these charts:
- Scatter Plot
14 Various kinds of Graphs and Charts regarding Presenting Data
To better realize each chart and how they could be used, here’s an overview of each type of chart.
1 . Column Chart
A column chart is used to show a comparison amongst different items, or it can show a comparison of products over time. You could use this format to see the revenue per squeeze page or customers by near date.
Design Guidelines for Column Charts:
- Use consistent colors throughout the chart, selecting accessory colors to highlight meaningful data points or modifications over time.
- Use horizontal labels to improve readability.
- Start the particular y-axis at 0 to appropriately reveal the values in your chart.
2 . Bar Graph
A bar graph, basically a horizontal column chart, should be utilized to avoid clutter when one particular data label is lengthy or if you have more than ten items to compare. This type of visualization can also be used to display negative figures.
Design Best Practices just for Bar Graphs:
- Use constant colors through the chart, selecting accent colors to highlight meaningful data points or changes as time passes.
- Use horizontal labels to improve legibility.
- Start the y-axis at 0 to appropriately reflect the values in your graph.
3. Line Graph
A line chart reveals trends or progress over time and can be used to demonstrate many different categories of data. You should utilize it when you chart a consistent data set.
Style Best Practices for Line Charts:
- Use solid lines just.
- Don’t plot more than four lines to avoid visual interruptions.
- Use the right elevation so the ranges take up roughly 2/3 of the y-axis’ height.
4. Dual Axis Chart
A dual axis chart allows you to plot data using two y-axes and also a shared x-axis. It’s combined with three data sets, one of which is based on a continuous set of data and another which is better suited to being grouped by category. This should be used to visualize a correlation or the lack thereof between these three data models.
Design Best Practices designed for Dual Axis Charts:
- Use the y-axis on the left aspect for the primary variable because brains are naturally inclined to look left first.
- Use different graphing styles to illustrate the two data sets, as illustrated above.
- Choose contrasting shades for the 2 data sets.
5. Area Chart
An area chart is basically the line chart, but the space between the x-axis and the range is filled with a colour or pattern. It is helpful for showing part-to-whole relations, such as showing individual sales reps’ contribution to total sales for the year. It helps you evaluate both overall and individual trend information.
Design Best Practices for Area Graphs:
- Use transparent colors so information isn’t really obscured in the background.
- Don’t display more than four categories to prevent clutter.
- Organize extremely variable data at the top of the particular chart to make it easy to read.
6. Stacked Bar Chart
This will be used to compare many different items and show the composition of each item being compared.
Design Best Practices for Stacked Bar Graphs:
- Best utilized to illustrate part-to-whole relationships.
- Use contrasting colors designed for greater clarity.
- Make chart scale large enough to view group sizes pertaining to one another.
7. Mekko Graph
Also known as a marimekko graph, this type of graph can evaluate values, measure each a person’s composition, and show how your computer data is distributed across each one of these.
It’s similar to a stacked bar, except the mekko’s x-axis is used to capture another dimension of your beliefs — rather than period progression, like column graphs often do. In the graphic below, the particular x-axis compares each city to one another.
Image via Mekko Graphics
Design Best Practices for Mekko Charts:
- Vary you bar heights when the portion size is an important stage of comparison.
- May include too many composite values within every bar. you might want to reevaluate the right way to present your data if you have a lot.
- Order your own bars through left to right in such a way that exposes a relevant tendency or message.
8. Pie Graph
A pie chart displays a static number and exactly how categories represent part of an entire — the composition associated with something. A pie graph represents numbers in percentages, and the total sum of all of the segments needs to equal totally.
Design Best Practices regarding Pie Charts:
- Don’t demonstrate too many categories to ensure differentiation between pieces.
- Ensure that the slice beliefs add up to fully.
- Order slices according to their size.
9. Scatter Plot Chart
A scatter plot or scattergram chart will show the relationship between two different variables or it can expose the distribution trends. It must be used when there are many different information points, and you want to emphasize similarities in the data set. This is useful when looking for outliers or for understanding the distribution of your data.
Style Best Practices for Scatter And building plots:
- Include more variables , such as different sizes, to incorporate more data.
- Start y-axis at 0 to represent data accurately.
- If you use trend lines , just use a maximum of two to generate your plot easy to understand.
10. Bubble Chart
A bubble chart is similar to a scatter story in that it can show submission or relationship. There is a 3rd data set, which is indicated by the size of the bubble or circle.
Style Best Practices for Bubble Graphs:
- Scale bubbles according to area , not diameter.
- Make sure labels are usually clear and visible.
- Use rounded shapes just.
11. Waterfall Chart
The waterfall chart should be used to show how an initial value is affected by intermediate values — either positive or even negative — and resulted in a final value. This should be applied to reveal the structure of a number. An example of this could be to showcase how overall company revenue is inspired by different departments plus leads to a specific profit quantity.
Chart via Baans Consulting
Design Best Practices just for Waterfall Charts :
- Use contrasting colours to emphasize differences in data sets.
- Choose warm colors to indicate increases and cool colors to point decreases.
12. Funnel Chart
A funnel chart shows a number of steps and the completion rate for each step. This can be utilized to track the sales process or the conversion rate throughout a series of pages or tips.
Design Best Practices intended for Funnel Charts:
- Scale the size of each section to accurately reflect the size of the data set.
- Use contrasting colors or one color in gradating hues, from darkest to lightest because the size of the funnel decreases.
13. Bullet Graph
A topic graph reveals progress toward a goal, compares this to another measure, and provides context by means of a rating or performance.
Design Best Practices pertaining to Bullet Graphs:
- Use contrasting colors in order to highlight how the data is certainly progressing.
- Use one color in various shades to gauge progress.
fourteen. Heat Map
A temperature map shows the relationship among two items and provides ranking information, such as high in order to low or poor in order to excellent. The rating details is displayed using various colors or saturation.
Design Best Practices for Temperature Map:
- Use a basic plus clear map outline to avoid distracting from your data.
- Use a single color in varying colors to show changes in data.
- Avoid using multiple patterns.
The post Data Visualization 101: How to Choose the proper Chart or Graph for the Data appeared first on Social Media Ding.