Chart Types

Querri supports a comprehensive set of chart types for visualizing your data. This reference provides complete details on each chart type, when to use it, and how to request it.

Overview

Querri uses industry-standard charting libraries (Plotly.js, Chart.js) to render interactive visualizations. Charts can be created through natural language requests and customized as needed.

Line Charts

Description

Line charts connect data points with lines, ideal for showing trends and changes over time.

Best Used For

Time series data
Trends and patterns
Continuous data
Comparing multiple series over time
Showing progression or evolution

Variants

Single Line Chart

Use Case: Track one metric over time

Example Requests:

“Show monthly revenue as a line chart”
“Plot temperature over the past week”
“Create a line chart of daily active users”

Configuration:

X-axis: Typically time or sequential values
Y-axis: Metric being tracked
Single data series

Multi-Line Chart

Use Case: Compare multiple metrics or categories over time

Example Requests:

“Plot revenue and costs over time on the same chart”
“Show sales for each region as separate lines”
“Compare 2023 and 2024 revenue by month”

Configuration:

Multiple data series on same axes
Different colors for each line
Legend to identify series

Area Line Chart

Use Case: Emphasize volume or magnitude of change

Example Requests:

“Create a line chart with filled area below”
“Show cumulative sales with area shading”

Configuration:

Area below line filled with color
Semi-transparent fill
Useful for single or stacked series

When NOT to Use

Comparing unrelated categories
Too many series (>5-7 lines becomes cluttered)
Discrete, non-sequential data

Bar Charts

Description

Bar charts use rectangular bars to represent values, with bar length proportional to the value.

Best Used For

Comparing values across categories
Showing discrete data
Ranking items
Part-to-whole comparisons
Before/after comparisons

Variants

Vertical Bar Chart

Use Case: Standard category comparison

Example Requests:

“Make a bar chart of sales by product category”
“Show revenue by region as bars”
“Create a bar chart of top 10 customers”

Configuration:

X-axis: Categories
Y-axis: Values
Vertical orientation (default)

Horizontal Bar Chart

Use Case: Long category names or many categories

Example Requests:

“Create a horizontal bar chart of sales by customer”
“Show product names with horizontal bars”
“Make a bar chart with horizontal orientation”

Configuration:

X-axis: Values
Y-axis: Categories
Easier to read long labels

Grouped Bar Chart

Use Case: Compare multiple metrics across categories

Example Requests:

“Show revenue and costs side by side for each month”
“Compare 2023 and 2024 sales by quarter in grouped bars”
“Create grouped bars for actual vs budget by department”

Configuration:

Multiple bars per category
Bars grouped together
Different colors per metric

Stacked Bar Chart

Use Case: Show part-to-whole relationship while comparing totals

Example Requests:

“Create a stacked bar chart of revenue by product over time”
“Show revenue breakdown by category for each region”
“Stack sales by salesperson for each month”

Configuration:

Multiple data series stacked vertically
Total height shows sum
Each segment shows contribution

When NOT to Use

Continuous time series (use line chart)
Too many categories (>20 bars)
Precise value comparison (numbers too close)

Scatter Plots

Description

Scatter plots show individual data points on two axes, revealing relationships between variables.

Best Used For

Showing correlation between two variables
Identifying patterns and clusters
Spotting outliers
Distribution across two dimensions
Regression analysis

Variants

Basic Scatter Plot

Use Case: Show relationship between two variables

Example Requests:

“Create a scatter plot of marketing spend vs revenue”
“Plot price against units sold”
“Show age vs purchase frequency as a scatter plot”

Configuration:

X-axis: Independent variable
Y-axis: Dependent variable
Each point represents one observation

Scatter Plot with Regression Line

Use Case: Show correlation and trend

Example Requests:

“Plot marketing spend vs sales with a trend line”
“Show correlation between price and demand with regression line”
“Add a line of best fit to the scatter plot”

Configuration:

Data points plus fitted line
Shows correlation strength
Helps predict values

Bubble Chart

Use Case: Add a third dimension (size) to scatter plot

Example Requests:

“Create a bubble chart with revenue on x, profit on y, and size by customer count”
“Plot price vs quantity with bubble size representing market share”

Configuration:

X and Y positions
Bubble size represents third variable
Optional color for fourth dimension

Colored Scatter Plot

Use Case: Show categories or groups within scatter

Example Requests:

“Scatter plot of price vs demand, colored by region”
“Plot sales vs profit with different colors for each product category”

Configuration:

Different colors for different groups
Legend shows categories
Reveals group patterns

When NOT to Use

Few data points (<10)
No relationship between variables
Categorical data only
Time series (use line chart)

Pie Charts

Description

Pie charts show proportions of a whole as slices of a circle.

Best Used For

Showing percentage breakdown
Part-to-whole relationships
Composition at a single point in time
Simple proportional comparisons
Market share or distribution

Variants

Standard Pie Chart

Use Case: Show proportional breakdown

Example Requests:

“Make a pie chart of revenue share by product line”
“Show market share as a pie chart”
“Display customer distribution by region”

Configuration:

Slices sized by percentage
Labels show category and value/percentage
Works best with 3-7 slices

Donut Chart

Use Case: Same as pie, with space for center annotation

Example Requests:

“Create a donut chart of sales by category”
“Make a pie chart with a hole in the middle”

Configuration:

Same as pie chart with hollow center
Center can display total or summary
More modern appearance

When NOT to Use

Too many categories (>7 slices)
Comparing exact values (use bar chart)
Showing change over time (use line/area chart)
When slices are similar sizes
Multiple pie charts for comparison (use grouped bars instead)

Area Charts

Description

Area charts are like line charts but with the area below the line filled in, emphasizing volume.

Best Used For

Cumulative values over time
Volume or magnitude visualization
Part-to-whole over time
Multiple series showing composition
Emphasizing total quantity

Variants

Simple Area Chart

Use Case: Show volume of single metric over time

Example Requests:

“Create an area chart of monthly revenue”
“Show website traffic as an area chart”

Configuration:

X-axis: Time
Y-axis: Value
Area below line filled
Single data series

Stacked Area Chart

Use Case: Show composition changing over time

Example Requests:

“Create a stacked area chart of revenue by product category over time”
“Show traffic sources as stacked areas”
“Display sales composition by region over quarters”

Configuration:

Multiple series stacked
Total height shows sum
Each layer shows contribution
Colors identify series

Overlapping Area Chart

Use Case: Compare multiple series while showing individual volumes

Example Requests:

“Show overlapping area charts for each product line”
“Create area chart with semi-transparent overlays”

Configuration:

Multiple series drawn independently
Semi-transparent fills allow overlap visibility
Can identify individual and combined peaks

When NOT to Use

Discrete categories (use bar chart)
Exact value comparison needed
Too many series (becomes unreadable)

Histograms

Description

Histograms show distribution of values by grouping them into bins and counting frequency.

Best Used For

Frequency distributions
Understanding data distribution shape
Identifying patterns in value ranges
Finding outliers and anomalies
Statistical analysis

Variants

Standard Histogram

Use Case: Show distribution of continuous variable

Example Requests:

“Create a histogram of order values”
“Show the distribution of customer ages”
“Plot a histogram of transaction amounts”

Configuration:

X-axis: Value ranges (bins)
Y-axis: Frequency count
Automatic bin sizing (or manual)
Shows distribution shape

Histogram with Custom Bins

Use Case: Control grouping granularity

Example Requests:

“Make a histogram with 20 bins”
“Create a histogram grouping by $100 increments”
“Show distribution with bins of 10 units”

Configuration:

Specify number of bins or bin width
Affects granularity of distribution
Adjust to reveal patterns

When NOT to Use

Discrete categories (use bar chart)
Time series (use line chart)
Comparing groups (use box plot)

Heatmaps

Description

Heatmaps use color intensity to represent values across two dimensions.

Best Used For

Showing patterns across two dimensions
Time-of-day or day-of-week patterns
Correlation matrices
Intensity or density visualization
Complex multi-dimensional data

Variants

Standard Heatmap

Use Case: Show intensity across two categorical dimensions

Example Requests:

“Create a heatmap of sales by day of week and hour”
“Show activity by location and time as a heatmap”
“Display performance by product and region as heatmap”

Configuration:

X-axis: First dimension
Y-axis: Second dimension
Color intensity: Value magnitude
Color scale indicator (legend)

Correlation Matrix

Use Case: Show correlations between multiple variables

Example Requests:

“Show correlation matrix as a heatmap”
“Create a heatmap of variable correlations”
“Display relationships between metrics as heatmap”

Configuration:

Both axes show same variables
Cell color shows correlation strength
Diagonal typically shows perfect correlation (1.0)
Symmetrical matrix

When NOT to Use

Simple category comparison (use bar chart)
Time series trend (use line chart)
Too many categories (becomes unreadable)

Box Plots

Description

Box plots (box-and-whisker plots) show statistical distribution of data including median, quartiles, and outliers.

Best Used For

Statistical summaries
Comparing distributions across groups
Identifying outliers
Understanding data spread
Quality control analysis

Variants

Single Box Plot

Use Case: Show statistical distribution of one variable

Example Requests:

“Create a box plot of revenue”
“Show distribution of customer ages as box plot”

Configuration:

Box shows quartiles (Q1, median, Q3)
Whiskers show data range or 1.5×IQR
Outliers shown as individual points

Grouped Box Plots

Use Case: Compare distributions across categories

Example Requests:

“Create box plots of revenue by quarter”
“Show distribution of prices across categories”
“Compare sales performance by sales rep with box plots”

Configuration:

Multiple boxes side by side
Each box represents a group
Easy comparison of medians and spreads

Box Plot Components

Box: Middle 50% of data (Q1 to Q3)
Line in box: Median value
Whiskers: Extend to min/max or 1.5×IQR
Dots: Outliers beyond whiskers

When NOT to Use

Small datasets (<10 values)
When exact values needed
Time series trends

Network Graphs

Description

Network graphs show relationships between entities as nodes and connecting edges.

Best Used For

Relationship mapping
Social network analysis
Organizational structures
Dependency visualization
Connection patterns

Variants

Node-Link Diagram

Use Case: Show connections between entities

Example Requests:

“Create a network graph of customer relationships”
“Show connections between products and categories”
“Visualize organization structure as network”

Configuration:

Nodes: Entities (circles/shapes)
Edges: Relationships (lines)
Size/color: Additional attributes
Layout: Force-directed or hierarchical

When NOT to Use

Simple hierarchies (use tree diagram)
No relationship data
Too many nodes (>100 becomes cluttered)

Geospatial Maps

Description

Maps plot data on geographic coordinates to show spatial patterns and distributions.

Best Used For

Location-based data
Regional comparisons
Geographic distributions
Route visualization
Spatial patterns

Variants

Point Map

Use Case: Show locations of individual points

Example Requests:

“Map customer locations”
“Show store locations on a map”
“Plot sales by city on a map”

Configuration:

Points at lat/long coordinates
Size/color by metric value
Interactive zoom and pan

Choropleth Map

Use Case: Show values by region with color intensity

Example Requests:

“Create a map showing sales by state”
“Color regions by revenue on a map”
“Show population density by country”

Configuration:

Regions colored by value
Color scale shows intensity
Useful for regional comparisons

Heat Map (Geographic)

Use Case: Show density or intensity across geography

Example Requests:

“Create a heat map of customer locations”
“Show activity density on a map”

Configuration:

Color intensity shows density
Useful for clustering visualization
Requires lat/long coordinates

When NOT to Use

No geographic component
Simple regional comparison (bar chart may be clearer)
Precise value comparison needed

How to Request Charts

Basic Requests

Simply state the chart type and data:

"Show sales by month as a line chart"
"Make a bar chart of revenue by region"
"Create a scatter plot of price vs demand"

Specifying Details

Add specifics about axes, grouping, or styling:

"Create a line chart with month on x-axis and revenue on y-axis"
"Make a grouped bar chart of actual vs budget by department"
"Plot sales vs profit colored by product category"

Modifying Existing Charts

Update charts after creation:

"Change that to a bar chart"
"Add a trend line"
"Only show top 10 values"
"Use different colors"

Chart Configuration Options

Common Options Across Chart Types

Colors:

Automatic color assignment
Request specific colors: “use blue for revenue”
Category-based coloring

Labels:

Axis labels automatically generated
Data point labels: “add labels to bars”
Custom titles: “title it ‘Q4 Performance’”

Sorting:

“Sort bars by value descending”
“Order by date ascending”
“Arrange by category alphabetically”

Filtering:

“Only show top 10”
“Exclude values below 100”
“Filter to 2024 data”

Scales:

“Use logarithmic scale”
“Start y-axis at zero”
“Set maximum to 100”

Legends:

Automatic for multi-series
Position: “move legend to bottom”
Hide: “remove the legend”

Chart Selection Guide

Data Type	Recommended Chart	Alternative
Time series (single metric)	Line chart	Area chart
Time series (multiple metrics)	Multi-line chart	Stacked area
Category comparison	Bar chart	Horizontal bar
Part-to-whole	Pie chart	Stacked bar
Distribution	Histogram	Box plot
Correlation	Scatter plot	-
Geographic	Map	Choropleth
Two dimensions	Heatmap	Grouped bar
Statistical summary	Box plot	-
Relationships	Network graph	-

Best Practices

Choosing Chart Types

Match to data structure: Time series → line, categories → bar, proportions → pie
Consider audience: Familiar formats communicate faster
Emphasize the message: Choose type that highlights key insight
Avoid complexity: Simpler is often better

Chart Design

Keep it simple: Remove unnecessary elements
Label clearly: Axes, legends, and titles should be obvious
Use color purposefully: Differentiate series, show intensity
Ensure readability: Large enough text, sufficient contrast

Common Mistakes to Avoid

Too many series: >5-7 lines/groups becomes cluttered
Wrong chart type: Pie charts for time series, line charts for categories
Missing context: No labels, title, or units
Misleading scales: Truncated axes, inconsistent intervals
3D effects: Usually add confusion, not clarity

Next Steps

Learn about data types to prepare data for visualization
Explore creating visualizations in the user guide
Review dashboard configuration for combining charts