An easy to understand primer about the "split-apply-combine" concept popularized by Hadley Wickham applied to data visualization. Following that I go through a simple introduction to the perceptual variables available for data visualization and some common mistakes.
"Sparse Binary Zero-Sum Games". David Auger, Jialin Liu, Sylvie Ruette, David L. St-Pierre and Olivier Teytaud. The 6th Asian Conference on Machine Learning (ACML), 2014.
Second Quarter Group F Math Peta - Special Products (Sq. of Bi, Sq. of Tri, S...GroupFMathPeta
Commenting and Liking our Slideshow will help us a lot! Please support us by doing so.
This slideshow will show you how to perform Special Products using:
* Square of a Binomial
* Square of a Trinomial
* Product of Sum and Difference of Two Terms
* Product of a Binomial and Trinomial
* Cube of a Binomial
DDA algorithm examples, solved examples, computer graphics, pixel calculation, line drawing algorithm, line drawing solved, 2D line drawing calculation, extra examples on DDA algorithm, Hearn and Baker book on computer graphics
Slides from our PacificVis 2015 presentation.
The paper tackles the problems of the “giant hairballs”, the dense and tangled structures often resulting from visualiza- tion of large social graphs. Proposed is a high-dimensional rotation technique called AGI3D, combined with an ability to filter elements based on social centrality values. AGI3D is targeted for a high-dimensional embedding of a social graph and its projection onto 3D space. It allows the user to ro- tate the social graph layout in the high-dimensional space by mouse dragging of a vertex. Its high-dimensional rotation effects give the user an illusion that he/she is destructively reshaping the social graph layout but in reality, it assists the user to find a preferred positioning and direction in the high- dimensional space to look at the internal structure of the social graph layout, keeping it unmodified. A prototype im- plementation of the proposal called Social Viewpoint Finder is tested with about 70 social graphs and this paper reports four of the analysis results.
From smart phones to tablets to apps, business travelers have access to new tools that are helping them streamline their trips. Travel managers are faced with the challenge of corralling new technology and information while at the same time keeping travelers informed and compliant. This keynote dives deep into mobile trends and traveler behaviors, and offers insights into best practices on how mobile technology can be utilized in a travel program.
"Sparse Binary Zero-Sum Games". David Auger, Jialin Liu, Sylvie Ruette, David L. St-Pierre and Olivier Teytaud. The 6th Asian Conference on Machine Learning (ACML), 2014.
Second Quarter Group F Math Peta - Special Products (Sq. of Bi, Sq. of Tri, S...GroupFMathPeta
Commenting and Liking our Slideshow will help us a lot! Please support us by doing so.
This slideshow will show you how to perform Special Products using:
* Square of a Binomial
* Square of a Trinomial
* Product of Sum and Difference of Two Terms
* Product of a Binomial and Trinomial
* Cube of a Binomial
DDA algorithm examples, solved examples, computer graphics, pixel calculation, line drawing algorithm, line drawing solved, 2D line drawing calculation, extra examples on DDA algorithm, Hearn and Baker book on computer graphics
Slides from our PacificVis 2015 presentation.
The paper tackles the problems of the “giant hairballs”, the dense and tangled structures often resulting from visualiza- tion of large social graphs. Proposed is a high-dimensional rotation technique called AGI3D, combined with an ability to filter elements based on social centrality values. AGI3D is targeted for a high-dimensional embedding of a social graph and its projection onto 3D space. It allows the user to ro- tate the social graph layout in the high-dimensional space by mouse dragging of a vertex. Its high-dimensional rotation effects give the user an illusion that he/she is destructively reshaping the social graph layout but in reality, it assists the user to find a preferred positioning and direction in the high- dimensional space to look at the internal structure of the social graph layout, keeping it unmodified. A prototype im- plementation of the proposal called Social Viewpoint Finder is tested with about 70 social graphs and this paper reports four of the analysis results.
From smart phones to tablets to apps, business travelers have access to new tools that are helping them streamline their trips. Travel managers are faced with the challenge of corralling new technology and information while at the same time keeping travelers informed and compliant. This keynote dives deep into mobile trends and traveler behaviors, and offers insights into best practices on how mobile technology can be utilized in a travel program.
The SlideShare 101 is a quick start guide if you want to walk through the main features that the platform offers. This will keep getting updated as new features are launched.
The SlideShare 101 replaces the earlier "SlideShare Quick Tour".
Record linkage, a real use case with spark ml - Paris Spark meetup Dec 2015Modern Data Stack France
Record Linkage, un cas d’utilisation en Spark ML par Alexis Seigneurin
Le Record Linkage est le process qui consiste à trouver, dans un data set, les enregistrements qui représentent la même entité. Cette opération est particulièrement compliquée quand, comme nous, vous travaillez avec des données anonymisées. C’est là que le Machine Learning vient en renfort ! Nous avons implémenté un algorithme de Record Linkage en Spark SQL (DataFrames) et Spark ML plutôt que d’utiliser des règles statiques. Nous verrons le process de Feature Engineering, pourquoi nous avons dû étendre Spark DataFrames pour préserver des méta-données au travers du pipeline de traitement, et comment nous avons utilisé le Machine Learning pour réconcilier les enregistrements. Nous verrons enfin comment nous avons industrialisé cette application.
Alexis Seigneurin : Développeur depuis 15 ans, j'attache beaucoup d'importance aux problématiques de traitement, d'analyse et de stockage de la donnée.Chez Ippon, j'interviens principalement sur des missions de conseil et d'architecture autour de technologies big data. Par ailleurs, j'anime la formation Spark chez Ippon.
OLAP Basics and Fundamentals by Bharat Kalia Bharat Kalia
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Advanced Analytics: Analytic Platforms Should Be Columnar OrientationDATAVERSITY
A columnar database is an implementation of the relational theory, but with a twist. The data storage layer does not contain records. It contains a grouping of columns.
Due to the variable column lengths within a row, a small column with low cardinality, or variability of values, may reside completely within one block while another column with high cardinality and longer length may take a thousand blocks. In columnar, all the same data — your data — is there. It’s just organized differently (automatically, by the DBMS).
The main reason why you would want to utilize a columnar approach is simply to speed up the native performance of analytic queries.
Learn about the columnar orientation and how it can be effective for your needs. This is the native orientation of many databases and several others that have optional column-oriented storage layers.
There is also the equivalent in the cloud storage world, which is open format Parquet.
Modern query optimisation features in MySQL 8.Mydbops
MySQL 8 (a huge leap forward), indexing capabilities, execution plan enhancements, optimizer improvements, and many other current query tweak features are covered in the slides.
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Most PHP developers focus on writing code. But creating Web applications is about much more than just wrting PHP. Take a step outside the PHP cocoon and into the big PHP ecosphere to find out how small code changes can make a world of difference on servers and network. This talk is an eye-opener for developers who spend over 80% of their time coding, debugging and testing.
Beyond php - it's not (just) about the codeWim Godden
Most PHP developers focus on writing code. But creating Web applications is about much more than just wrting PHP. Take a step outside the PHP cocoon and into the big PHP ecosphere to find out how small code changes can make a world of difference on servers and network. This talk is an eye-opener for developers who spend over 80% of their time coding, debugging and testing.
2014-04-09, Data mining demo for astronomy researchersSamuel Harrold
This presentation is a demonstration of data mining and data management for astronomy researchers. The motivation is to help researchers who need to manage data but don't know how.
I give a step-by-step example of how I mined astronomy data using Python, MySQL, KNIME and other tools. The use-case for this example was to create a list of unobserved white dwarf stars that probably pulsate.
This presentation was given on Apr 9, 2014 for University of Texas at Austin, Astronomy Department, Stellar Seminar.
7 Alternatives to Bullet Points in PowerPointAlvis Oh
So you tried all the ways to beautify your bullet points on your pitch deck but it just got way uglier. These points are supposed to be memorable and leave a lasting impression on your audience. With these tips, you'll no longer have to spend so much time thinking how you should present your pointers.
Hello everyone! I am thrilled to present my latest portfolio on LinkedIn, marking the culmination of my architectural journey thus far. Over the span of five years, I've been fortunate to acquire a wealth of knowledge under the guidance of esteemed professors and industry mentors. From rigorous academic pursuits to practical engagements, each experience has contributed to my growth and refinement as an architecture student. This portfolio not only showcases my projects but also underscores my attention to detail and to innovative architecture as a profession.
Transforming Brand Perception and Boosting Profitabilityaaryangarg12
In today's digital era, the dynamics of brand perception, consumer behavior, and profitability have been profoundly reshaped by the synergy of branding, social media, and website design. This research paper investigates the transformative power of these elements in influencing how individuals perceive brands and products and how this transformation can be harnessed to drive sales and profitability for businesses.
Through an exploration of brand psychology and consumer behavior, this study sheds light on the intricate ways in which effective branding strategies, strategic social media engagement, and user-centric website design contribute to altering consumers' perceptions. We delve into the principles that underlie successful brand transformations, examining how visual identity, messaging, and storytelling can captivate and resonate with target audiences.
Methodologically, this research employs a comprehensive approach, combining qualitative and quantitative analyses. Real-world case studies illustrate the impact of branding, social media campaigns, and website redesigns on consumer perception, sales figures, and profitability. We assess the various metrics, including brand awareness, customer engagement, conversion rates, and revenue growth, to measure the effectiveness of these strategies.
The results underscore the pivotal role of cohesive branding, social media influence, and website usability in shaping positive brand perceptions, influencing consumer decisions, and ultimately bolstering sales and profitability. This paper provides actionable insights and strategic recommendations for businesses seeking to leverage branding, social media, and website design as potent tools to enhance their market position and financial success.
Dive into the innovative world of smart garages with our insightful presentation, "Exploring the Future of Smart Garages." This comprehensive guide covers the latest advancements in garage technology, including automated systems, smart security features, energy efficiency solutions, and seamless integration with smart home ecosystems. Learn how these technologies are transforming traditional garages into high-tech, efficient spaces that enhance convenience, safety, and sustainability.
Ideal for homeowners, tech enthusiasts, and industry professionals, this presentation provides valuable insights into the trends, benefits, and future developments in smart garage technology. Stay ahead of the curve with our expert analysis and practical tips on implementing smart garage solutions.
You could be a professional graphic designer and still make mistakes. There is always the possibility of human error. On the other hand if you’re not a designer, the chances of making some common graphic design mistakes are even higher. Because you don’t know what you don’t know. That’s where this blog comes in. To make your job easier and help you create better designs, we have put together a list of common graphic design mistakes that you need to avoid.
Expert Accessory Dwelling Unit (ADU) Drafting ServicesResDraft
Whether you’re looking to create a guest house, a rental unit, or a private retreat, our experienced team will design a space that complements your existing home and maximizes your investment. We provide personalized, comprehensive expert accessory dwelling unit (ADU)drafting solutions tailored to your needs, ensuring a seamless process from concept to completion.
Between Filth and Fortune- Urban Cattle Foraging Realities by Devi S Nair, An...Mansi Shah
This study examines cattle rearing in urban and rural settings, focusing on milk production and consumption. By exploring a case in Ahmedabad, it highlights the challenges and processes in dairy farming across different environments, emphasising the need for sustainable practices and the essential role of milk in daily consumption.
3. Men of great rank, or active business, can only
pay attention to particulars of use […] it is hoped
that with the assistance of these Charts,
information will be got, without the fatigue and
trouble of studying the particulars [...]
William Playfair - Commercial and Political Atlas, 1786
4. Data visualization is the art of
*reducing information in a data set while
preserving the knowledge contained in it.
*we can talk about what “reducing information” means in this case...
5. Data Preparation Data Visualization
Discovery of
knowledge
Conceptual data analysis workflow
6. Hadley Wickham popularized a concept called
split-apply-combine
as a way of thinking about data querying.
http://www.jstatsoft.org/v40/i01/paper
7. For the four most revenue generating
countries, what are the top three most
revenue generating categories?
Country Venue Type Sum Revenue
United States Fast Food $16
Street $10
Restaurant $9
France Cafe $18
Pub $12
Restaurant $2
Canada Cafe $10
Fast Food $4
Street $3
Japan Street $5
Fast Food $4
Pub $1
8. apply: Sum Revenue
Canada
United States
Germany
France
Japan
split by country
combine: sort descending by
Sum Revenue, limit 4
Country Sum Revenue
United States
France
Canada
Japan
$ 83
$ 42
$ 36
$ 18
data
Sum Revenue =
$ 36
Sum Revenue =
$ 83
Sum Revenue =
$ 8
Sum Revenue =
$ 42
Sum Revenue =
$ 18
The basics of split-apply-combine
9. Canada
United States
Germany
France
Japan
data
bus stop
fastfood
park
...
restaurant
hair saloon
pub
...
restaurant
street
cafe
...
park
pub
street
Country Sum Revenue
United States
France
Canada
Japan
$ 16
$ 10
$ 9
$ 18
$ 12
$ 2
$ 10
$ 4
$ 3
$ 5
$ 4
$ 1
Venue type
fastfood
street
restaurant
cafe
pub
restaurant
cafe
fastfood
park
street
fastfood
pub
...
The basics of split-apply-combine
10. Country Sum Revenue
United States
France
Canada
Japan
split by country,
combine by sorting
desc. on Sum
Revenue,
map to the vertical
axis using an ordinal
scale.
add labels
apply: sum revenue,
call it Sum Revenue,
plot rectangles and map
length to the horizontal
axis using a linear scale,
Color with #45808E.
Use `Country` as label
Split-apply-combine thinking translates to visualizations
11. 1. split on state
apply sum population
combine: sort desc. by population; limit 6
Nested split-apply-combine underpins more complex visualizations
2. split on age (bin by 5 year)
combine: sort by age
apply sum population
12. Data Visualization can be thought as a
visual mapping function applied
during the *Apply and Combine steps.
*although it can be thought as applied exclusively during the combine step…
15. Types of data
ID Timestamp Location Name Operation Lines Pass Test?
0000001 11-05-2013 10.45 am San Francisco Vadim Added 100 Yes
0000002 11-05-2013 11.12 am San Bruno Luca Removed 34 Yes
0000003 11-05-2013 11.30 am San Francisco Vadim Added 65 Yes
0000004 11-05-2013 11.34 am San Francisco Vadim Removed 5 Yes
0000005 11-05-2013 11.43 am San Bruno Luca Added 24 No
0000006 11-05-2013 11.45 am San Francisco Vadim Removed 71 Yes
0000007 11-05-2013 12.51 pm San Francisco Luca Removed 45 Yes
0000008 11-05-2013 12.55 pm San Francisco Vadim Added 7 No
... ... ... ... ... ... ...
Categorical # Discrete
# Continuous# Discrete
Boolean
16. There are other ways to classify data,
but this one will get you very far.
pick up a good statistics book and just start reading...
17. Types of variables
1. Independent
a. a variable that isn't changed by the other
variables you are trying to measure. It
usually goes on the x axis.
2. Dependent
a. It is a variable that changes depending on
other variable(s). It usually goes on the y
axis.
19. Variables of a visualization
1. Position (x,y)
2. Size (big, small…)
3. Value (bright, dark…)
4. Texture (hatched, dotted…)
5. Color (blue, red…)
6. Orientation (degree)
7. Shape (triangle, circle…)
y
x
20. # Discrete # Continuous Categorical Boolean
y
x
y
x
y
x
y
x
Optimal mappings by type
21. -960
LucaVadim
1531
-321
739
0
1k
2k
-2k
-1k
AddedRemoved
Name Operation Lines
Vadim Added 100
Luca Removed 34
Vadim Added 65
Vadim Removed 5
Luca Added 24
Vadim Removed 71
Luca Removed 45
Vadim Added 7
... ... ...
Split on Name
Split on Operation
Apply Sum(Added)
Apply Sum(Removed)
Combine -Removed map to
Red, value to size
Combine Added map to
Green, value to size
Combine Name map to x axis
22. Apply the minimum number of mappings
that illustrates the underlying question
you are trying to answer.
24. 1. Label your axes
2. Include measurement units
3. Explain your encodings (add a legend)
4. Remove redundant information
5. Don’t fuck with distort the axis, especially with time series
Golden rules - Part 1
25. Golden rules - Part 2
1. If you are trying to visualize rate of change, then do it
2. Remove outliers, but know they are there
3. Tools have their own biases and quirks, know them.
4. The solution to 80% of your problems are bar charts and
histograms
5. Data Tables are visualizations too
...there are thousands of good rules, but the best one is still “keep it simple”