Choosing the Right Chart Type: A Technical Guide
Last Updated : 22 Jan, 2025
In Data Visualization we visualize data in a graphical format through charts and graphs. However selecting the right chart type can be challenging especially if you're new to data visualization. This guide will help you choose the best chart type for your data step by step.
Importance of Charts and Graphs in Data Visualization
Charts and Graphs help to:
- Identify trends and patterns: Data points is observed together and compared to see the increase/decrease in their data values with respect to specific parameters and help to identify trends & patterns in the values.
- Approximately predict values at future points: Multiple data points in a chart observed together and give a predictable correlational value for the next data point.
- Identify deviation: In continuation of the above point on actually putting the next data point it can be see and calculated from the chart how much its value deviates from the expected value.
- Compare between significant points: Two or more significant data points and their values can be compared to one another easily visually due to them being plotted in the same chart.
Understanding Your Data and Visualization Goals
Before choosing the right chart it's essential to understand the nature of your data and the message you want to convey. To understand consider the following questions:
- What is the primary purpose of the visualization?
- Are you comparing values, showing trends over time, illustrating relationships, or displaying the composition of data?
- What type of data are you working with?
- Is it categorical, numerical, or a mix of both?
- How many variables are you visualizing?
- Are you dealing with a single variable, two variables, or multiple variables?
- What is the volume of data points?
- Do you have a few data points or a large dataset?
Criteria for Selecting Chart Types
The right chart depends on your data type and the message you want to communicate. Different charts serve different purposes:
classification of chart based on data- Comparison: If you need to compare different categories like sales across different regions bar charts or column charts work well.
- Distribution: To show how data is spread out like test scores or income levels use a histogram.
- Composition: To show how parts contribute to a whole like the market share of products a pie chart is typically used.
- Trend: If you need to show how data changes over time like sales trends over months a line chart is best.
- Geographical: If you want to show the states and countries through visualization it can be with the help of geographical charts.
Now Let's understand them one by one in detail:
1. Comparison Charts
Comparison charts are used to show how different things are related or how they change. They help us see patterns trends and differences in data more easily. For example you can compare sales numbers for two months or see how one product performs against others. By looking at these charts you can quickly understand what’s going on with the data and find important insights. The charts used for comparison are:
Comparison Charts- Bar charts used to compare values across different categories with categories shown on the x-axis and values on the y-axis. It's best for comparing things like product sales or city populations.
- column chart is similar to a bar chart but uses vertical bars. It’s useful for comparing time-based data or hierarchical categories.
- Radar chart helps compare multiple variables across different categories displayed in a circular layout with each axis representing one variable. It’s ideal for comparing performance across areas like product ratings or team stats.
2. Trend Charts
Trend charts are used to show how data changes over time. They visually represent the movement of variables helping to identify patterns and trends. By displaying data points across a timeline trend charts provide an easy way to understand how something evolves like stock prices or temperature changes.
Trends Charts- Line chart is best for showing how data changes over time, with points connected by a line. It helps to identify trends and patterns over a period, like tracking sales over months.
- Area chart is similar to a line chart but highlights the total value over time by filling the area below the line. It’s useful for showing the cumulative value, like total revenue over several months.
- Waterfall chart helps understand how sequential values impact the overall result displaying increases and decreases over time. It’s great for showing how different factors contribute to a final value like profit changes.
3. Relationship Charts
Relationship charts are used to show a connection or correlation between two or more variables. By visually representing the interdependencies and associations relationship charts provide a clear and concise way to understand the relationship between the variables.
Relationship Charts- A scatter chart is a simple way to show how two things are connected. Each point on the chart represents a pair of values and it helps us see if there’s a pattern or correlation between them.
- Bubble chart takes the idea of a scatter plot and adds extra details. It uses the size and color of each bubble to show more variables making it easier to understand how different factors relate to each other.
- Heatmaps on the other hand use colors in a grid to represent data values. They’re great when you want to see patterns in relationships especially when dealing with non-numeric data or to visualize the density of numbers.
4. Distribution Charts
Distribution charts are used to show how data is spread out over time. They help to identify outliers and highlight trends. By showing where most data points fall distribution charts make it easier to understand patterns and spot anything that stands out.
Distribution Charts- A histogram shows how often data falls within specific ranges make it easy to see the distribution of values like how many times a score appears in a certain range.
- The box plot displays the spread of data showing the range median and any outliers helps to understand the distribution and identify any extreme values.
- KDE plot (Kernel Density Estimate) shows a smooth curve that represents how data is distributed and give a clearer view of the overall shape of the data and its density across different values.
- Violin plot compares numeric value distributions between groups by plotting a density curve for each group.
5. Composition Charts
Composition charts are helpful when you want to break down something into smaller parts and see how each part fits into the bigger picture. For example imagine you're looking at a company’s revenue over time. It can show you how different products or services contribute to the total revenue and how those contributions change each year or month.
Composition Charts- A pie chart shows how different parts make up a whole like slices of a pizza. It's best for small amounts of data helping you see each part’s share easily.
- stacked bar chart compares parts in different categories. Each bar shows a category and the sections within the bar show how much each part contributes.
- The treemap organizes data in boxes where each box represents a part of the whole. The size of the box shows how big that part is helping you understand how everything fits together.
6. Geographical Charts
When working with geographical data we often need charts that can represent regions and locations in a meaningful way. Choropleths and cartograms are two charts designed specifically for this purpose.
Geographical Charts- A choropleth map shows regions like countries, states, or districts with colors indicating how much of something (like population or income) each region has.
- A cartogram takes a different approach by changing the size of each region based on its data value like population or GDP. If a region has a large population it will appear larger on the map even if the actual geographical shape gets distorted.
To effectively share your data pick the right chart based on your goal and the data you have. Whether you’re comparing values, showing trends, or displaying parts of a whole the right chart helps make your message clear and easy to understand.
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