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数据可视化的最基本信息,对入门的数据分析人员很有帮助(Data_Visualization 101 How to Design Charts and Graphs.ppt)
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DATA VISUALIZATION 101:
HOW TO DESIGN CHARTS
AND GRAPHS
TABLE OF
CONTENTS
INTRO
Bar Chart
Pie Chart
Line Chart
Area Chart
Scatter Plot
Bubble Chart
Heat Map
6
9
11
13
15
17
19
1
FINDING THE STORY IN
YOUR DATA
KNOW YOUR DATA
GUIDE TO CHART TYPES
10 DATA DESIGN
DO’S AND DONT’S
2
3
5
21
If your data is misrepresented or presented
ineectively, key insights and understanding
are lost, which hurts both your message and
your reputation. The good news is that you
don’t need a PhD in statistics to crack the data
visualization code. This guide will walk you
through the most common charts and
visualizations, help you choose the right
presentation for your data, and give you
practical design tips and tricks to make sure
you avoid rookie mistakes. It’s everything you
need to help your data make a big impact.
What’s the ideal distance
between columns in a bar chart?
Your data is only as good as
your ability to understand and
communicate it, which is why
choosing the right visualization
is essential.
You’re about to nd out.
1
FINDING THE STORY
IN YOUR DATA
Information can be visualized in a number of ways, each of which can
provide a specific insight. When you start to work with your data, it’s
important to identify and understand the story you are trying to tell and
the relationship you are looking to show. Knowing this information will
help you select the proper visualization to best deliver your message.
When analyzing data, search for patterns or interesting insights that can
be a good starting place for finding your story, such as:
TRENDS
CORRELATIONS
OUTLIERS
Example:
Ice cream sales
over time
Example:
Ice cream sales vs.
temperature
Example:
Ice cream sales in an
unusual region
2
CONTINUOUS
DISCRETE
CATEGORICAL
QUANTITATIVE
Before understanding visualizations, you
must understand the types of data that
can be visualized and their relationships
to each other. Here are some of the most
common you are likely to encounter.
Data that can be sorted according to group or
category. Example: Types of products sold.
Numerical data that has a finite number of
possible values. Example: Number of
employees in the oce.
Data that is measured and has a value within a
range. Example: Rainfall in a year.
Data that can be counted or measured;
all values are numerical.
KNOW YOUR
DATA
DATA TYPES
3
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- 帅气地沉迷于学习无法自拔2020-02-25呵呵,不言而喻,这叫ppt?????????
胡晓帆
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