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Data visualization   data sources   data types
String values - text = name, city
Number (Integer) values
Date values
Date & Time values
Boolean values
Geographic values = City, state, pincode
Data types:
Connect to data in tableau
On opening Tableau, you will get the start page showing various data sources. Under the header “Connect”,
you have options to choose a file or server or saved data source.
Under Files, choose excel.
Then navigate to the file “Sample – Superstore.xls” as mentioned above.
The excel file has three sheets named Orders, People and Returns. Choose Orders.
Data visualization   data sources   data types
Assignment 1 - Superstore Sales Dashboard
Due Date - 12 October 2021
Objective:
To identify the number of customers, in the province region .
To analyse the number of sales, product-wise. Identify the number of packages by various ship-mode and
priority province-wise.
To Analyse the various modes of transport used in the superstore.
The display the priority of the order including customers Name by Order ID for taking the further action.
Derive one meaningful insight on your own.
Changing data type of a field in Data Source page
Changing data type of a field from Data pane
Changing the data type of a field in the View
Dimensions and Measures, Blue and Green
● Dimensions contain qualitative values (such as names, dates, or geographical data). You can use
dimensions to categorize, segment, and reveal the details in your data. Dimensions affect the level of
detail in the view.
● Measures contain numeric, quantitative values that you can measure. Measures can be aggregated.
When you drag a measure into the view, Tableau applies an aggregation to that measure (by
default).
● data.world
● Data is Plural
● UN Data
● Data.gov
● Kaggle
● NOAA
● Reddit
● World Fact Book
● UN Environmental Data Explorer
● World Health Organization
● Pitney Bowes
Portals For Data:
Visual Design Basics
Visual design aims to improve a design’s/product’s aesthetic appeal and usability with suitable
images, typography, space, layout and color. Visual design is about more than aesthetics. Designers
place elements carefully to create interfaces that optimize user experience and drive conversion.
Actually, you use visual design to create and organize elements to
A) lead the user’s eye to an item’s functionality, and
B) make the aesthetics consistent.
Elements and Principles of visual design:
1. Lines (straight/curved/geometric/organic) – use these to create divisions, textures and
shapes.
2. Shapes – use lines, different colors, etc. to create enclosed/self-contained areas.
3. Negative space/whitespace – use the blank area around a “positive” shape to create a
figure/ground effect or calm the design overall.
4. Volume – use this to show the rich fullness of all three dimensions of elements on
two-dimensional screens.
5. Value – use this to set the relationship between lightness and darkness, typically through a
light source to create shadows and highlights.
6. Color – use this to set the theme/tone and attract attention.
7. Texture – use this to define an object’s surface.
Data visualization   data sources   data types
Elements and Principles of visual design:
1. Unity – use this to establish harmony between page elements, so they
appear to belong together and users aren’t distracted by chaotic (e.g.,
misaligned) layouts.
2. Hierarchy – use placement, font, etc. to show importance.
3. Balance – use this to distribute elements evenly.
4. Contrast – use differences in color, etc. to accentuate elements.
5. Scale – use this to emphasize elements to establish importance or depth.
6. Dominance/Emphasis – use an object’s size, color, etc. to make it stand out.
Unity
Hierarchy
Balance
Contrast
Contrast
Scale
Dominance / Emphasis
Data visualization   data sources   data types
Position, color, size,
shape, and orientation are
variables applied to
individual graphic elements.
Graphic elements are the
units of information that go
into making a figure, slide,
or poster. These include
photos, icons, paragraphs
of text, and titles.
Contrast: Elements have noticeably
different visual characteristics then
others in the composition. Created using
the variables of color, size, shape,
orientation.
Repetition: Elements have consistent
visual characteristics within the
composition. Created using color, size,
shape, and orientation.
Alignment: Elements have been arranged
to create an imaginary line within the
composition. Uses the variable of
position.
Proximity: Elements are close together
within the space of a composition. Uses
the variable of position.
Hierarchy: A dominant-subordinate
relationship among elements.
Grouping: A relationship that specifies
the elements to be associated together.
Sequence: A relationship among
elements that specifies first, second,
third…
Data visualization   data sources   data types
Data visualization   data sources   data types
Color is perception. Our eyes see something (the sky, for example), and data sent from our eyes to our brains
tells us it’s a certain color (blue). Objects reflect light in different combinations of wavelengths. Our brains
pick up on those wavelength combinations and translate them into the phenomenon we call color.
In color theory, colors are organized on a color wheel and grouped into 3 categories: primary colors,
secondary colors and tertiary colors.
Colors:
Data visualization   data sources   data types
Data visualization   data sources   data types
Warm colors are
generally
associated with
energy,
brightness, and
action, whereas
cool colors are
often identified
with calm, peace,
and serenity.
Data visualization   data sources   data types
Data visualization   data sources   data types
Complementary colors
Complementary colors are opposites on the color wheel—red
and green, for example.
Because there’s a sharp contrast
between the two colors, they
can really make imagery pop,
but overusing them can get
tiresome. Think any shopping
mall in December. That being
said, using a complementary
color scheme in your business
marketing offers sharp contrast
and clear differentiation
between images.
Analogous colors
Analogous colors sit next to one
another on the color wheel—red,
orange and yellow, for example.
When creating an analogous color
scheme, one color will dominate, one
will support. In business, analogous
color schemes are not only pleasing
to the eye, but can effectively
instruct the consumer where and
how to take action.
Triadic colors
Triadic colors are evenly spaced
around the color wheel and tend to
be very bright and dynamic.
Using a triadic color scheme in
your marketing creates visual
contrast and harmony
simultaneously, making each item
stand out while making the overall
image pop.
Burger King uses this color scheme
quite successfully. Hey, is it
lunchtime yet?
Scatter Plot:
Scatter plots' primary uses are to observe and show relationships between two numeric variables.
Scatter Plot Applications and Uses:
1. Demonstration of the relationship between two variables.
2. Identification of correlational relationships.
3. Identification of data patterns.
Line Chart:
A line chart (aka line plot, line graph) uses points connected by line segments from left to right to
demonstrate changes in value.
1. To see changes of a variable over time.
2. To identify trends and spot spikes and dips.
3. To compare patterns of multiple sections.
Pie Chart:
The pie chart comprises of a circle that is divided into sectors, each representing a proportion of the
summation of all values in a dataset. The chart is useful in depicting the share of constituents as part of the
whole.
Pie charts are best to use when you are trying to compare parts of a whole. They do not show changes over
time.
Two primary use cases for a pie chart:
1) If you want your audience to have a general sense of the part-to-whole relationship in your data and
comparing the precise sizes of the slices is less important.
2) To convey that one segment of the total is relatively small or large.
Bar Charts:
If the variable we want to show on the horizontal axis is not numeric or ordered, but instead categorical, then
we need to use a bar chart instead of a line chart.
The bars in a bar chart are usually separated by small gaps, which help to emphasize the discrete nature of
the categories plotted.
These bars can be displayed horizontally or vertically. A bar graph will always have two axis. One axis will
generally have numerical values, and the other will describe the types of categories being compared.

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Data visualization data sources data types

  • 2. String values - text = name, city Number (Integer) values Date values Date & Time values Boolean values Geographic values = City, state, pincode Data types:
  • 3. Connect to data in tableau On opening Tableau, you will get the start page showing various data sources. Under the header “Connect”, you have options to choose a file or server or saved data source. Under Files, choose excel. Then navigate to the file “Sample – Superstore.xls” as mentioned above. The excel file has three sheets named Orders, People and Returns. Choose Orders.
  • 5. Assignment 1 - Superstore Sales Dashboard Due Date - 12 October 2021 Objective: To identify the number of customers, in the province region . To analyse the number of sales, product-wise. Identify the number of packages by various ship-mode and priority province-wise. To Analyse the various modes of transport used in the superstore. The display the priority of the order including customers Name by Order ID for taking the further action. Derive one meaningful insight on your own.
  • 6. Changing data type of a field in Data Source page
  • 7. Changing data type of a field from Data pane
  • 8. Changing the data type of a field in the View
  • 9. Dimensions and Measures, Blue and Green ● Dimensions contain qualitative values (such as names, dates, or geographical data). You can use dimensions to categorize, segment, and reveal the details in your data. Dimensions affect the level of detail in the view. ● Measures contain numeric, quantitative values that you can measure. Measures can be aggregated. When you drag a measure into the view, Tableau applies an aggregation to that measure (by default).
  • 10. ● data.world ● Data is Plural ● UN Data ● Data.gov ● Kaggle ● NOAA ● Reddit ● World Fact Book ● UN Environmental Data Explorer ● World Health Organization ● Pitney Bowes Portals For Data:
  • 11. Visual Design Basics Visual design aims to improve a design’s/product’s aesthetic appeal and usability with suitable images, typography, space, layout and color. Visual design is about more than aesthetics. Designers place elements carefully to create interfaces that optimize user experience and drive conversion. Actually, you use visual design to create and organize elements to A) lead the user’s eye to an item’s functionality, and B) make the aesthetics consistent.
  • 12. Elements and Principles of visual design: 1. Lines (straight/curved/geometric/organic) – use these to create divisions, textures and shapes. 2. Shapes – use lines, different colors, etc. to create enclosed/self-contained areas. 3. Negative space/whitespace – use the blank area around a “positive” shape to create a figure/ground effect or calm the design overall. 4. Volume – use this to show the rich fullness of all three dimensions of elements on two-dimensional screens. 5. Value – use this to set the relationship between lightness and darkness, typically through a light source to create shadows and highlights. 6. Color – use this to set the theme/tone and attract attention. 7. Texture – use this to define an object’s surface.
  • 14. Elements and Principles of visual design: 1. Unity – use this to establish harmony between page elements, so they appear to belong together and users aren’t distracted by chaotic (e.g., misaligned) layouts. 2. Hierarchy – use placement, font, etc. to show importance. 3. Balance – use this to distribute elements evenly. 4. Contrast – use differences in color, etc. to accentuate elements. 5. Scale – use this to emphasize elements to establish importance or depth. 6. Dominance/Emphasis – use an object’s size, color, etc. to make it stand out.
  • 15. Unity
  • 20. Scale
  • 23. Position, color, size, shape, and orientation are variables applied to individual graphic elements. Graphic elements are the units of information that go into making a figure, slide, or poster. These include photos, icons, paragraphs of text, and titles.
  • 24. Contrast: Elements have noticeably different visual characteristics then others in the composition. Created using the variables of color, size, shape, orientation. Repetition: Elements have consistent visual characteristics within the composition. Created using color, size, shape, and orientation. Alignment: Elements have been arranged to create an imaginary line within the composition. Uses the variable of position. Proximity: Elements are close together within the space of a composition. Uses the variable of position.
  • 25. Hierarchy: A dominant-subordinate relationship among elements. Grouping: A relationship that specifies the elements to be associated together. Sequence: A relationship among elements that specifies first, second, third…
  • 28. Color is perception. Our eyes see something (the sky, for example), and data sent from our eyes to our brains tells us it’s a certain color (blue). Objects reflect light in different combinations of wavelengths. Our brains pick up on those wavelength combinations and translate them into the phenomenon we call color. In color theory, colors are organized on a color wheel and grouped into 3 categories: primary colors, secondary colors and tertiary colors. Colors:
  • 31. Warm colors are generally associated with energy, brightness, and action, whereas cool colors are often identified with calm, peace, and serenity.
  • 34. Complementary colors Complementary colors are opposites on the color wheel—red and green, for example. Because there’s a sharp contrast between the two colors, they can really make imagery pop, but overusing them can get tiresome. Think any shopping mall in December. That being said, using a complementary color scheme in your business marketing offers sharp contrast and clear differentiation between images.
  • 35. Analogous colors Analogous colors sit next to one another on the color wheel—red, orange and yellow, for example. When creating an analogous color scheme, one color will dominate, one will support. In business, analogous color schemes are not only pleasing to the eye, but can effectively instruct the consumer where and how to take action.
  • 36. Triadic colors Triadic colors are evenly spaced around the color wheel and tend to be very bright and dynamic. Using a triadic color scheme in your marketing creates visual contrast and harmony simultaneously, making each item stand out while making the overall image pop. Burger King uses this color scheme quite successfully. Hey, is it lunchtime yet?
  • 37. Scatter Plot: Scatter plots' primary uses are to observe and show relationships between two numeric variables. Scatter Plot Applications and Uses: 1. Demonstration of the relationship between two variables. 2. Identification of correlational relationships. 3. Identification of data patterns.
  • 38. Line Chart: A line chart (aka line plot, line graph) uses points connected by line segments from left to right to demonstrate changes in value. 1. To see changes of a variable over time. 2. To identify trends and spot spikes and dips. 3. To compare patterns of multiple sections.
  • 39. Pie Chart: The pie chart comprises of a circle that is divided into sectors, each representing a proportion of the summation of all values in a dataset. The chart is useful in depicting the share of constituents as part of the whole. Pie charts are best to use when you are trying to compare parts of a whole. They do not show changes over time. Two primary use cases for a pie chart: 1) If you want your audience to have a general sense of the part-to-whole relationship in your data and comparing the precise sizes of the slices is less important. 2) To convey that one segment of the total is relatively small or large.
  • 40. Bar Charts: If the variable we want to show on the horizontal axis is not numeric or ordered, but instead categorical, then we need to use a bar chart instead of a line chart. The bars in a bar chart are usually separated by small gaps, which help to emphasize the discrete nature of the categories plotted. These bars can be displayed horizontally or vertically. A bar graph will always have two axis. One axis will generally have numerical values, and the other will describe the types of categories being compared.