Types of Data Visualization Charts: From Basic to Advanced
Data Visualization Charts is a method of presenting data in a visual way. In this guide we'll explore about the different types of data visualization charts in very detailed manner
Basic Charts for Data Visualization
These are the charts you'll face when starting with data visualization. They are simple to create easy to understand and help you start making sense of your data right away. we use Python libraries like Matplotlib and Seaborn to create these type of charts.
1. Bar Charts
Bar charts are one of the common visualization tool used to compare facts by showing square bars. A bar chart has X and Y Axis where the X Axis represents the types and the Y axis represents the price. There are various types of Bar charts like horizontal bar chart, Stacked bar chart, Grouped bar chart and Diverging bar Chart.
When to Use Bar Chart:
- Comparing Categories: Used to show differences between categories and understand relationships in the data.
- Ranking: When we got records with categories need to be arranged from highest to lowest we use bar charts.
- Relationship between categories: When you have a dataset with multiple specific variables it can help to display relationship between them to discover patterns and tendencies.
2. Line Charts
Line chart is a type of graph that displays information over time. It uses markers to represent data points and these dots are connected by lines to show how the values change over a period. This makes easy to see trends such as whether something is increasing, decreasing, or staying the same.
When to Use Line Chart:
- Line charts can be used to analyze developments over individual values.
- Line charts also are used in comparing trends among more than one facts series.
- Line chart is also used for time series information.
3. Pie Charts
A pie chart is a circular visualization divided into slices to show numerical percentages of a whole. Each slice represents a category and its size is proportional to the share it represents. They are only valid with small variety of categories. Simple Pie chart and Exploded Pie charts are distinctive varieties of Pie charts.
When to Use Pie Chart:
- To show how parts make up a whole.
- Useful in emphasizing a particular category by way of highlighting a dominant slice.
4. Scatter Chart (Plots)
A scatter chart is a tool that uses dots to represent data points showing the relationship between two numerical variables. The X-axis represents the independent variable and the Y-axis represents the dependent variable. Type of scatter chart consists of simple scatter chart, scatter chart with trendline and scatter chart with coloration coding. They are used for identifying outliers or unusual remark for your facts.
5. Histogram
A histogram shows the distribution of numerical data by dividing it into intervals (bins) and displaying the frequency of data points as bars. It helps visualize patterns like skewness, central tendency, and variability.
When to Use Histogram:
- Distribution Visualization: Histograms are best for visualizing the distribution of numerical information allow customers to recognize shape of the records.
- Data Exploration: It provides records exploration by using revealing patterns, trends, and outliers inside datasets.
Advanced Charts for Data Visualization
After learning basic charts Now let's move toward advanced charts It allow you to dive deeper into your data help to find detailed insights show multiple variables and find hidden patterns or relationships.
1. Heatmap
A heatmap visualizes statistics in a matrix layout the usage of colors to symbolize the values of person cells. It is good for figuring out patterns, correlation and variations within big datasets. Heatmaps are usually utilized in fields like in finance for portfolio analysis , in biology for gene expression analysis, and in advertising for customer segmentation.
When to Use heatmap:
- Identify Clusters: Heatmaps help us identify clusters or groups within datasets make it easier to segment the data.
- Correlation Analysis: They are useful for visualizing correlations between variables to discover relationships and traits.
- Risk Assessment: They are useful for assessing risk like identifying high-risk areas in financial portfolios or spotting unusual patterns in network traffic.
Area Chart
An area chart displays data trends over time by filling the area beneath lines. It’s similar to a line chart used for displaying time-series data, where data points are measured over a specific period.
When to Use Area charts:
- Tracking Trends: It shows how something changes over time like stock prices or temperatures.
- Comparative Analysis: They allow to compare multiple categories or variable at a time.
- Highlighting Patterns: Area charts useful for plotting spotting pattern such as seasonality or cyclical tendencies in time-collection facts.
3. Box Plot (Box-and-Whisker Plot)
A box plot summarizes the distribution of numerical data show quartiles, outliers, and the median. It helps to identify variability, skewness, and outliers in datasets and is commonly used in statistical analysis ,quality control and data exploration.
When to Use Box Plots:
- Identify Outliers: Box plots is used to identify outliers in datasets for data cleaning and anomaly detection.
- Compare Distributions: To compare distributions between different groups or categories.
- Visualize Spread: They visualize the spread and variability of information providing insights.
4. Bubble Chart
A bubble chart represents records points as bubbles in which the dimensions and color of every bubble deliver additional facts. It is powerful for visualizing three-dimensional facts and comparing more than one variables simultaneously. They are commonly used in finance for portfolio evaluation, in marketing for market segmentation, and in biology for gene expression evaluation.
When to Use bubble chart:
- Multivariate Analysis: Bubble charts allow you to compare three or more variables in a single visualization.
- Size and Color Encoding: They use size and coloration to deliver extra information such as fee or class.
- Relationship Visualization: Bubble charts help visualize relationships between variables and make easier to find pattern
5. Tree Map
A tree map displays hierarchical data using nested rectangles where each rectangle's size represents a quantitative value. It is useful for visualizing hierarchical structures and comparing proportions within the hierarchy.
When to Use Tree Map:
- Hierarchical Representation: Tree maps best at representing hierarchical records structures
- Proportion Comparison: It help to compare proportions within the hierarchy.
- Space Efficiency: They optimize area utilization by using packing rectangles efficiently so that you can visualize large datasets in a compact layout.
6. Parallel Coordinates
Parallel coordinates visualize multivariate statistics through representing every information point as a line connecting values across multiple variables. They are useful for exploring relationships among variables and figuring out styles or trends. Parallel coordinates are generally used in data evaluation, gadget learning, and sample popularity.
When to Use Parallel Coordinates:
- Multivariate Analysis: Parallel coordinates help you compare many variables at the same time to find patterns.
- Relationship Visualization: They help visualize relationships among variables such as correlations or clusters.
- Outlier Detection: They help us to find unusual data points that don't follow the common pattern
7. Choropleth Map
A choropleth map uses shade shading or styles to symbolize statistical records over geographic regions. It is generally used to visualize variations and identify geographic patterns. Choropleth maps are broadly used in fields which includes demography for populace density mapping, in economics for income distribution visualization, and in epidemiology for disease prevalence mapping.
When to Use Choropleth Map:
- Spatial Analysis: Choropleth maps are best for spatial analysis allow the visualization of variations in records.
- Geographic Patterns: They help to become aware of geographic styles which include clusters or gradients in datasets used in fashion analysis and decision-making.
- Comparison Across Regions: It allow for clean evaluation of information values throughout geographic regions and provide local evaluation.
8. Sankey Diagram
A Sankey diagram is a type of flow chart that shows how data or resources move between different points (called nodes) using arrows. The width of each arrow shows how much flow there is so thicker arrows represent more flow. They are helpful for understanding complex systems and finding patterns in data used in areas like energy flow analysis, supply chain management and web analytics.
When to Use Sankey Diagram:
- Flow Visualization: It show how information or resources move between different points and making it easier to understand complex processes or system.
- Bottleneck Identification: They help to spot bottlenecks or areas where the flow of resources slows down or becomes inefficient.
- Comparative Analysis: They are useful for comparing how flows change over time or in different scenario and help in evaluating performance and finding opportunities to improve efficiency.
9. Radar Chart (Spider Chart)
A radar chart shows multivariate information on a two-dimensional aircraft with a couple of axes emanating from a primary point. It is beneficial for comparing a couple of variables across distinct categories and identifying strengths and weaknesses. Radar charts are usually utilized in sports for overall performance analysis and in selection-making for multi-criteria decision evaluation.
When to Use Radar Chart:
- Multi-Criteria Comparison: Radar charts permit for the evaluation of more than one criteria or variables across extraordinary classes.
- Strengths and Weaknesses Analysis: They help to discover strengths and weaknesses within categories or variables and visualizing their relative overall performance.
- Pattern Recognition: Radar charts useful resource in pattern recognition ,highlighting similarities or variations between classes..
10. Network Graph
A network graph represents relationships between entities as nodes and edges. It is useful for visualizing complicated networks consisting of social networks, transportation networks, and organic networks. Network graphs are typically utilized in social network analysis for community detection and in biology for gene interaction analysis.
When to Use Network Graph:
- Relationship Visualization: Network graphs visualize relationships among entities which includes connections or interactions and make them valuable for network analysis
- Community Detection: They help to discover communities or clusters within networks by using visualizing node connections and densities.
- Path Analysis: It help in route analysis by showing the shortest paths or routes between points makes it easier to optimize routes and plan efficiently.
11. Donut or Doughnut chart
A donut chart is just like pie chart has a hole in the center make it look like a donut. This design makes the chart visually cleaner and more appealing especially when displaying multiple categories.
In a donut chart the outer ring represents 100% and each slice represents a category. The size of each slice shows how much each category contributes to the whole.
When to Use Donut Chart:
- It is useful for showing how different categories contribute to a total. For example showing market share or sales breakdowns.
- Donut charts are great for showing progress towards a goal like a percentage of a target achieved
- Best used for comparing few classes.
12. Gauge Chart
A Gauge chart used to display the progress of a single value, like a key performance indicator (KPI), toward a goal. It looks like a speedometer with a circular arc showing how close the value is to the target. There two different kinds of Gauge charts specifically Circular Gauge or Radial Gauge which resembles a speedometer and Linear Gauge.
When to Use Gauge Chart:
- It is useful in monitoring metrics like income or consumer satisfaction towards benchmark signs set.
- Used in KPI monitoring in tracking development towards a selected aim indicator.
- This Can be utilized in project control to music the fame of project progress against assignment timeline.
13. Sunburst Chart
A sunburst chart presents hierarchical records using nested rings in which each ring represents a degree within the hierarchy. It is beneficial for visualizing hierarchical structures with more than one tiers of aggregation. They allow customers to explore relationships and proportions inside complicated datasets in an interactive way.
When to use sunburst charts:
- Visualizing hierarchical data systems including organizational hierarchies or nested classes.
- To Explore relationships and proportions within multi-level datasets.
- To Communicate with complex records structures and dependencies in a visually attractive layout.
14. Hexbin Plot
A hexbin plot represents the distribution of dimensional facts by using binning records points into hexagonal cells and coloring each cellular based totally on the range of factors it contains. It is effective for visualizing density in scatter plots with a huge wide variety of information points. It provide insights into spatial patterns and concentrations within datasets.
When to use Hexbin Plot:
- To Visualize the density and distribution of statistics points in two-dimensional area.
- For Identifying clusters or concentrations of statistics inside a scatter plot.
- Handling massive datasets with overlapping data factors in a clear and informative way.
15. Violin Plot
A violin plot combines a box plot with a kernel density plot to show the distribution of statistics together with its summary statistics. It is useful for comparing the distribution of more than one organizations or categories. It provide insights into the shape, unfold, and important tendency of statistics distributions.
When to use Violin Plot:
- It Compare the distribution of continuous variables across distinctive groups or categories.
- Visualizing the shape and spread of information distributions, including skewness and multimodality.
- To Present precise information and outliers within information distributions in a visually appealing layout.
Visualization Charts for Textual and Symbolic data
Data visualization charts for textual and symbolic data represent information made up of words, symbols, or other non-numeric forms. These charts are helpful for displaying data that isn't numbers but still needs to be visualized. There are mainly of two types let's understand them:
1. Word Cloud
A word cloud is a visual representation of textual content records in which phrases are sized based totally on their frequency or significance inside the textual content. Common words seem larger and greater outstanding at the same time as less common phrases are smaller. Word clouds provide a short and intuitive manner to identify distinguished phrases or issues within a frame of textual content.
When to use Word Cloud:
- To Identify key themes or subjects within a massive corpus of text.
- Visualizing keyword frequency or distribution in textual facts.
- Highlight the giant terms or principles in qualitative evaluation or sentiment evaluation.
2. Pictogram Chart
A pictogram chart makes use of icons or symbols to represent information values wherein the size or amount of icons corresponds to the value they represent. It is an powerful way to deliver information in a visually appealing way mainly when coping with categorical or qualitative records.
When to use pictograph chart:
- To Present records in a visual format specially for non-numeric or qualitative records.
- Communicating information to audiences with various tiers of literacy or language talent.
- Emphasizing key statistics points or tendencies the usage of without difficulty recognizable symbols or icons.
Temporal and Trend Charts Data Visualization
Temporal and trend charts are used to show patterns and changes over time especially for time-series data where each data point is linked to a specific time. Let's understand them one by one:
1. Streamgraph
A streamgraph shows how the composition of a dataset changes over time using stacked areas along a baseline. It's great for visualizing trends and changes in data distribution over the years.
When to use streamplot:
- Analyze trends and changes in facts distribution over the years.
- Compare the relative contributions of different classes or organizations within a dataset.
- It Highlight patterns in facts through the years in a visually attractive manner.
2. Bullet Graph
A bullet graph is a variant of a bar chart but it includes markers and reference lines to show progress toward a goal. It's useful for tracking performance against a target.
When to use Bullet Graph:
- It display development toward goals or objectives in a concise and informative manner.
- Compare real performance in opposition to predefined benchmarks or thresholds.
- It Communicate overall performance metrics successfully in dashboards or reports.
3. Gantt Chart
A Gantt chart shows project tasks as horizontal bars along a time axis. It is beneficial for planning, scheduling, and monitoring progress in venture control. Gantt charts offer a visual evaluation of venture timelines, dependencies, and aid allocation.
When to use Gantt Chart:
- Do Planning and scheduling complicated tasks with multiple duties and dependencies.
- To Track progress and managing resources at some stage in the mission lifecycle.
- Communicating undertaking timelines and milestones to stakeholders and team participants.
4. Waterfall Chart
A waterfall chart visualizes the cumulative impact of sequential high-quality and negative values on an starting point. It is generally utilized in financial analysis to show adjustments in net price over time. They provide a clean visual representation of the way individual factors make contributions to the general alternate in a dataset.
When to use waterfall chart:
- To Analyze and visualize modifications in economic performance or budget allocations through the years.
- For Identify the sources of gains or losses within a dataset and their cumulative impact.
- To Present complicated statistics ameliorations or calculations in a clear and concise layout.
In this article we learned how different charts are used to show data in a simple way. Basic charts like bar charts and line charts help compare things while advanced charts like heatmaps and box plots show deeper details and Charts like word clouds and streamgraphs help display text data or data over time.
