Line chart

The line chart connects data points with straight lines, allowing for a smooth representation of the data's progression. This chart type is commonly employed in various fields, including tracking stock prices, monitoring sales performance, analyzing temperature variations, and many other scenarios where understanding trends and changes over time is crucial.

The line chart is ideal for displaying trends and changes over time. It is widely used for visualizing continuous data series and highlighting patterns, fluctuations, and relationships. By utilizing line charts in Google Sheets, users can effectively visualize and analyze data to gain insights into long-term patterns and make informed decisions.

Smooth line chart

A smooth line chart in Google Sheets is a charting option that uses curved lines instead of straight lines to connect data points, providing a more visually polished representation of data trends compared to regular line charts. This type of chart is commonly utilized to track time-series data, analyze continuous data with reduced noise, facilitate comparative analysis between multiple data series or categories, and present forecasted data in a visually appealing manner.

This chart type is widely used in fields such as finance, sales analysis, scientific research, and marketing, where presenting data trends in a visually appealing and informative manner is crucial for effective decision-making and communication. By employing smooth lines, this charting style enhances the clarity and aesthetic appeal of data visualization in Google Sheets.

Bar chart

By representing data as vertical or horizontal bars, bar charts provide a clear visual comparison of the values associated with each category or group. The length or height of each bar directly corresponds to the data value it represents, making it easy to assess and compare magnitudes.

Bar charts are highly effective for comparing data across different categories or groups. Bar charts are commonly utilized in various domains, such as sales analysis, market research, and population studies. They are particularly useful for comparing sales figures, survey responses, population statistics, or any other data where categorical comparisons are required.

By leveraging bar charts in Google Sheets, users can gain valuable insights into the relative differences and trends across different categories, aiding decision-making and data-driven analysis.

Stacked bar chart

A stacked bar chart is a visual representation of multiple data series using horizontal bars stacked on top of each other. Each bar segment represents the contribution of a specific data series to the total for each category.

Stacked bar charts are commonly used to compare the total values and proportions of different categories, providing insights into data composition and distribution. Stacked bar charts offer a clear and concise way to analyze and compare data across various categories.

100% stacked bar chart

A 100% stacked bar chart is a chart that represents multiple data series as horizontal bars stacked on top of each other, with each bar segment normalized to 100%. It allows for easy comparison of the relative proportions or percentages of each data series within each category.

This chart type is useful for visualizing the composition and distribution of data across different categories, providing a clear overview of the relative contributions within each category. The 100% stacked bar chart simplifies the analysis and comparison of data by maintaining a consistent scale and highlighting proportional relationships.

Column chart

Column charts represent data as vertical columns, where the height of each column corresponds to the data value it represents. Column charts are widely used for comparing data across different categories or groups.

Commonly used in sales analysis, survey results, and population statistics, column charts provide a clear visual comparison of values and allow users to identify trends and variations across categories or groups. By leveraging column charts in Google Sheets, users can effectively analyze and present data in a concise and easily understandable format.

Stacked column chart

A stacked column chart in Google Sheets is a powerful visual tool that helps users analyze and interpret data comparisons. By representing multiple data series as stacked columns, this chart type allows users to easily understand the impact of distinct categories on the total value. Each column in the chart corresponds to a specific category, and its height represents the magnitude or value of that category.

This chart is especially beneficial for identifying patterns, trends, and proportions within the data. Whether you are comparing sales figures, survey responses, or any other data with distinct categories, the stacked column chart in Google Sheets provides an intuitive and effective way to visualize and gain insights from your data.

100% stacked column chart

A 100% stacked column chart represents multiple data series as vertical columns stacked on top of each other. The height of the stacked columns is normalized to 100%, reflecting the relative proportions or percentages of each data series within the total for each category.

This chart type is commonly used to compare the relative contributions of different categories to the whole while maintaining a consistent scale across all categories. It is particularly useful for illustrating market share, the composition of a portfolio, or the distribution of resources across various categories.

Pie chart

Pie charts are circular visualizations commonly used to represent categorical data. Each category is represented by a slice of the pie, and the size of each slice corresponds to the proportion or percentage it represents in relation to the whole.

Pie charts are ideal for displaying the distribution and relative importance of different categories within a dataset, making it easy to compare and interpret data at a glance. By leveraging pie charts in Google Sheets, users can effectively communicate and analyze categorical data, providing insights into the composition and proportions of various categories.

3D pie chart

Similar to a regular pie chart, each slice of the 3D pie chart represents a category or data series, and the size of the slice corresponds to the proportion or percentage it represents. 3D pie charts are used to visualize data distributions and compare relative proportions in a visually appealing manner.

However, it's worth noting that 3D pie charts can sometimes distort the perception of data due to the visual emphasis on depth and perspective. This can make accurate comparisons and interpretations more challenging.

Doughnut chart

A doughnut chart is similar to a pie chart, but the center of the chart is typically left empty, creating a "doughnut hole" in the middle. Additionally, doughnut charts can support multiple rings, allowing for hierarchical representation or nested categories.

Like a pie chart, doughnut charts are ideal for displaying the distribution and relative importance of different categories within a dataset, making it easy to compare and interpret data at a glance.

Area chart

Area charts in Google Sheets are effective visualizations for showcasing the cumulative and relative changes in data over time. They plot data points and connect them with filled-in areas, resulting in a visual representation that emphasizes the overall trend rather than individual data points.

Area charts are commonly used to demonstrate the progression of metrics such as sales figures, stock prices, or population growth over a specific period. By utilizing area charts in Google Sheets, users can gain insights into the overall patterns and fluctuations within their data, allowing for better analysis and communication of trends.

Stacked area chart

A stacked area chart displays multiple data series stacked on top of one another, using colored areas to represent the values. In this chart, each data series is represented by a colored area, and the cumulative total of all the series forms the complete stacked area. The chart emphasizes both the overall trend and the relative contribution of each component to the total at any given point.

Stacked area charts are particularly useful for illustrating how different components contribute to the total value over time or any other continuous axis.

100% stacked area chart

A 100% stacked area chart is a data visualization that represents multiple components as stacked areas, with the total height of the chart always equal to 100%.

It allows for easy comparison of relative proportions and distributions, making it useful for analyzing market share, resource allocation, survey results, sales by region, and portfolio composition. The chart provides a clear understanding of the relative contributions of different components within a whole, aiding in data analysis and decision-making processes.

Stepped area chart

A stepped area chart displays data points as connected horizontal and vertical lines, creating a stepped appearance. It is commonly used to represent data with discrete changes or intervals, such as stock prices, manufacturing processes, project timelines, inventory management, and event analysis.

The chart highlights abrupt changes and provides a clear view of trends, enabling users to analyze patterns and make informed decisions based on the displayed data.

Stacked stepped area chart

A stacked stepped area chart combines the features of stacked area charts and stepped area charts. It represents multiple components as stacked areas with stepped lines, allowing for visualization of both discrete changes and cumulative totals.

This chart type is useful for analyzing data with distinct intervals or milestones, such as cumulative sales by category or project progress. It provides a comprehensive view of both the cumulative and stepped aspects of the data, facilitating trend analysis and comparison of components.

100% stacked stepped area chart

A 100% stacked stepped area chart combines the features of a 100% stacked area chart and a stepped area chart. It represents multiple components as stacked areas with stepped lines, while also normalizing the areas to display percentages or proportions.

This chart type is useful for visualizing the relative distribution and changes of components over time, highlighting both the stepped nature of the data and the proportional contribution of each component within the total. It enables effective trend analysis and comparison of data.

Scatter chart

A scatter chart in Google Sheets is a valuable tool for visualizing the relationship between two variables. It displays individual data points as dots on a Cartesian coordinate grid, with one variable represented on the x-axis and the other on the y-axis. Scatter charts are commonly used to identify correlations, patterns, or trends in data.

By analyzing the positioning and distribution of the data points, users can gain insights into the relationship between the variables. Google Sheets offers the ability to create scatter charts easily, enabling users to effectively explore and understand the connections within their data.

Combo chart

A combo chart in Google Sheets is a powerful visualization tool that combines multiple chart types into a single chart. It allows users to present different data series with varying characteristics and scales, enabling comprehensive data analysis and comparison.

By leveraging combo charts, users can effectively display and interpret complex datasets, showcasing different data types and relationships within a unified visual representation. Google Sheets provides the flexibility to create customized combo charts, making it easier to convey insights and patterns from diverse data sources in a concise and informative manner.

Histogram chart

A histogram chart in Google Sheets is a visual representation of the distribution of numerical data. It divides the data into intervals or bins along the x-axis and displays the frequency or count of data points falling within each bin on the y-axis.

Histogram charts are valuable for understanding data distribution, identifying outliers, and detecting patterns or trends. By selecting the data range and customizing the chart options, users can create histogram charts in Google Sheets to effectively analyze and visualize the distribution of their numerical data, enabling them to gain insights and make data-driven decisions. This type of chart is commonly used in different statistical analyses.

Radar chart

A radar chart in Google Sheets is a type of chart that allows users to compare multiple variables by plotting data points on multiple axes emanating from a central point. It is useful for visualizing and comparing patterns, trends, and strengths across different dimensions of data.

Radar charts are commonly used in sports analysis, market research, and performance evaluations. By using radar charts, users can effectively assess and understand the relationships between variables in a visually engaging manner.

Bubble chart

A bubble chart in Google Sheets visually represents data points as bubbles on a two-dimensional grid. It is used to display relationships among three numeric variables. The position of the bubbles on the axes represents two variables, while the size of the bubbles represents a third variable.

Bubble charts are valuable for analyzing complex data sets and identifying patterns between variables. In Google Sheets, users can create bubble charts by selecting the data range and customizing the chart options. They provide insights into data relationships efficiently.

Geo chart

A geo chart, also known as a geographical chart or map chart, is a type of data visualization that displays data values on a geographic map. It represents data points or regions as colors or patterns on the map, providing a visual representation of the distribution or density of the data across different geographic areas.

Geo charts can be used to display various types of data, such as population density, sales by region, election results, or any other data that has a geographic component. The data values are typically assigned to specific regions, countries, states, or other geographical boundaries, and then visualized using color gradients or shading to represent different values or categories.

Geo charts are valuable tools for analyzing and presenting spatial data in an easily understandable format. They can help identify regional patterns, disparities, or correlations between data and geography. Geo charts are commonly utilized in fields such as demographics, market research, public policy, and social sciences to provide insights into geographic data and facilitate decision-making processes.

Geo chart with markers

A geo chart with markers combines a geographic map with individual markers to represent specific data points at their respective locations. It is a visual representation of data that provides information about the geographic distribution of points of interest.

This chart type is commonly used in applications such as logistics, real estate, and tracking data with a spatial component. It enables users to easily analyze and explore data within a geographical context, enhancing the understanding and interpretation of spatial information.

Waterfall chart

A waterfall chart is a type of data visualization that illustrates the cumulative effect of positive and negative changes on an initial value. It is commonly used to depict the flow of values, showing how different factors contribute to a final result. The chart starts with a baseline value and then represents each subsequent change as a bar that either increases or decreases from the previous value. The length and direction of the bars show the magnitude and direction of each change.

Waterfall charts are often utilized in financial analysis, project management, and other scenarios where it is important to understand the contributions of various factors to an overall outcome. They provide a clear visual representation of the sequential flow of values, aiding in understanding and analyzing the impact of different factors on the final result.

Gauge cart

A gauge chart, also known as a dial or speedometer chart, is a data visualization that represents a single value within a defined range using a circular or semi-circular gauge. It provides a visual indication of where the value falls on a scale, allowing for easy assessment and comparison.

Gauge charts are commonly used to monitor progress toward a goal, display performance metrics, or present key indicators. They offer a quick and intuitive way to interpret data and make informed decisions based on the value's position within the range.

Scorecard chart

A scorecard chart is a tabular data visualization that presents key performance indicators (KPIs) or metrics in a structured format. It consists of rows representing different KPIs and columns representing time periods or dimensions. Each cell contains the corresponding metric value, allowing for easy comparison and assessment.

Scorecard charts are widely used in various industries and sectors to track and analyze performance, enabling users to make informed decisions based on the displayed data.

Candlestick chart

A candlestick chart is a type of financial chart used to represent the price movement of an asset, typically within a specified time period. It provides a visual depiction of the opening, closing, and high, and low prices for each period. Each data point on the chart is represented by a rectangular "candlestick" shape, which consists of a body and "wicks" or "shadows" extending from it. The body represents the price range between the opening and closing prices, while the wicks indicate the range between the high and low prices.

Candlestick charts are commonly used in technical analysis to identify patterns, trends, and potential reversals in price movements, providing insights for trading decisions in financial markets.

Organizational chart

An organizational chart is a visual representation of the structure and hierarchy of an organization. It depicts the relationships, reporting lines, and roles of individuals or departments within the organization. Typically, an organizational chart uses a hierarchical format, with higher levels representing top management or executives and lower levels representing various departments, teams, or positions. The chart may include boxes or nodes for each individual or group, with lines or arrows indicating the reporting relationships and lines of authority.

Organizational charts are commonly used to illustrate the chain of command, communication channels, and overall structure of an organization, aiding in understanding roles, responsibilities, and decision-making processes within the company.

Treemap chart

A treemap chart is a data visualization that displays hierarchical data in a nested rectangular layout. It uses rectangles to represent different categories or groups, with the size of each rectangle representing a quantitative value, such as the proportion or magnitude of the data within that category. The larger the rectangle, the larger the value it represents. The treemap chart is divided into smaller rectangles, which are further divided based on the sub-categories or sub-groups within each category. The color or shading of the rectangles can also be used to represent additional data dimensions or attributes.

Treemap charts are commonly used to analyze and compare hierarchical data structures, such as market share by product categories, portfolio allocation by asset classes, or file sizes within different folders. They provide an intuitive and visual way to understand the composition and distribution of data within a hierarchy, allowing for easy identification of patterns, outliers, and relative proportions.

Timeline chart

A timeline chart is a type of data visualization that presents chronological information in a linear format. It displays a sequence of events or milestones along a horizontal axis, representing time. Each event or milestone is typically represented as a point or marker on the timeline, with additional information such as labels, descriptions, or durations. The timeline chart provides a visual representation of the temporal relationships between different events or milestones, allowing for easy comprehension of the sequence and duration of activities.

It is commonly used in project management, historical analysis, event planning, or any context where understanding the chronological order of events is crucial. The timeline chart facilitates tracking progress, identifying dependencies, and visualizing the overall timeline of a project or historical timeline.

Table chart

A table chart is a data visualization that presents information in a structured tabular format. It organizes data into rows and columns, where each row represents a distinct data entry or record, and each column represents a specific attribute or variable.

A table chart is commonly used to present and compare data across different categories or dimensions. It provides a clear and concise overview of the data, allowing for easy analysis, sorting, and filtering. Table charts are widely used in data analysis, reporting, and displaying data in a structured manner that is easily readable and accessible to users.

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