How graphs can represent all the details through charts.

1. GreyB Research
Data Visualization By
Different Charts
Graphical Representation
Tushar saini

2. There are different types of charts to represent different type of date or in other
words there are different methods of data visualizations by graphs. The data may be
of any type, it may discrete, quantitative, continuous or categorical. The graphs are
used to represent various assumptions and data, which are discus below:
RANKING
This shows how two or more values compare
to each other in relative magnitude. Example:
Historic weather patterns, ranked from the
hottest months to the coldest.
TIME-SERIES
This tracks changes in values of a consistent
metric over time. Example: Monthly sales.
DEVIATION & CORRELATION
This examines how data points relate to each
other, particularly how far any given data point
differs from the mean. Example: Amusement
park tickets sold on a rainy day vs. a regular day.
This is data with two or more variables that may
demonstrate a positive or negative correlation to
each other. Example: Salaries according to
education level.

3. DISTRIBUTION
This shows data distribution, often around a central
value. Example: Heights of players on a basketball
team.
PART-TO-WHOLE RELATIONSHIPS
This shows a subset of data compared to the
larger whole. Example: Percentage of customers
purchasing specific products.
NOMINAL COMPARISON
This is a simple comparison of the quantitative
values of subcategories. Example: Number of
visitors to various websites.

4. Bar Charts:
They are used to show changes over the
time, for comparisons b/w different
categories.
VERTICAL
(COLUMN CHART)
Best used for chronological data
(time-series should always run left to
right), or when visualizing negative values
below the x-axis
HORIZONTAL
Best used for data with long category
labels.
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5. STACKED
Best used when there is a need to compare
multiple part-to-whole relationships. These can
use discrete or continuous data, oriented either
vertically or horizontally.
100% STACKED
Best used when the total value of each
Category is unimportant and percentage
distribution of subcategories is the primary
message
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6. Pie Charts:
Pie charts are best used for making part-to-whole comparisons with discrete
or continuous data. They are most impactful with a small data set.
STANDARD
Used to show part-to-whole relationships.
DONUT
Stylistic variation that enables the
inclusion of a total value or design
element in the center.
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7. Line Chart:
Line charts are used to show time-series relationships with continuous data. They
help show trend, acceleration, deceleration, and volatility.
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8. Area Chart:
Area charts depict a time-series relationship, but they are different than line charts
in that they can represent volume.
VARIATIONS OF AREA CHARTS
AREA CHART
Best used to show or
compare a quantitative
progression over time.
STACKED AREA
Best used to visualize part-to-
whole relationships, helping
show how each category
contributes to the cumulative
total.
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9. 100% STACKED AREA
Best used to show distribution of
categories as part of a whole,
where the cumulative total is
unimportant.
Scatter Plot:
Scatter plots show the relationship between items based on two sets of variables.
They are best used to show correlation in a large amount of data.
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10. Bubble Chart:
Bubble charts are good for displaying nominal comparisons or ranking relationships.
BUBBLE PLOT
This is a scatter plot with bubbles, best used to display an additional variable.
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11. We can use Bar graphs or infographic to represent the data.

13. Spatial/Axis Design