Olympic medalist Research Paper

Anonymous
timer Asked: Oct 20th, 2018
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Question Description

Olympic Medalist Research Paper

You can, of course, repeat this exercise on any subject of your choice but here is an additional dataset about some contrasting Olympic medallist data.

This exercise involves you working with an already acquired dataset to undertake the remaining three key steps of examining, transforming and exploring your data to develop a deep familiarisation with its properties and qualities. Complete the "Olympic Medalists" exercise located at the following link:

Working With Data

Provide at least a 10-page paper and a 10-15 slide presentation of your findings.

For each dataset:

Examination: Articulate the meaning of the data (its representativeness and phenomenon) and thoroughly examine the physical properties (type, size, condition) noting down your descriptions in each case. Compare what the datasets offer and contrast their differences.

Transformation: What could you do/would you need to do to clean or modify the existing data? What other data could you imagine would be valuable to consolidate the existing data?

Exploration: Use a tool of your choice (common recommendations would be Excel, Tableau, R) to visually explore the two datasets separately in order to deepen your appreciation of their physical properties and their discoverable qualities (insights) to help you cement your understanding of their respective value.

1. Make the data stand out. The focus here is on revealing the structure of the data. It includes discussion of how to fill the data region, transform data, choose an appropriate scale for an axis, eliminate chart junk and other superfluous material, and avoid having graph elements interfere with data, which includes topics such as over plotting, jittering, and transparency.

2. Add information. In addition to the usual conveyance of the importance of labeling axes and using legends, we also discuss how to: use color and plotting symbols to convey additional information; add context with reference markers and labels; and write comprehensive captions that are self-contained, describe the important features, and summarize the conclusions drawn from the graph.

3. Key Questions and Interpretations of Data Analysis...

No.

Question

Interpretation

1

What is the message?

Get past the presentation to the facts

2

Is the source reliable?

Think about the information’s quality.

3

How strong is the evidence overall?

Understand how this information fits with other evidence.

4

Does the information matter?

Determine whether the information changes your thinking and leads you to respond.

5

What do the numbers mean?

Remember that understanding the importance of risk requires that you understand the numbers.

6

How does the risk compare to others?

Put the risk into context.

7

What actions can be taken to reduce risk?

Identify the ways you can mitigate the risk to improve your situation.

8

What are the trade-offs?

Make sure you can live with the trade-offs associated with different actions.

9

What else do I need to know?

Focus on identifying the information that would help you make a better decision.

10

Where can I get more information?

Find the information you need to make a better d

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Athletics Athletics Athletics Athletics Athletics Athletics Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing 400m Hurdles Women 400m Men 400m Men 400m Men 400m Women 400m Women 400m Women 4x100m Relay Men 4x100m Relay Men 4x100m Relay Men 4x100m Relay Women 4x100m Relay Women 4x100m Relay Women 4x400m Relay Men 4x400m Relay Men 4x400m Relay Men 4x400m Relay Women 4x400m Relay Women 4x400m Relay Women 5000m Men 5000m Men 5000m Men 5000m Women 5000m Women 5000m Women 50km Walk Men 50km Walk Men 50km Walk Men 800m Men 800m Men 800m Men 800m Women 800m Women 800m Women Marathon Men Marathon Men Marathon Men Marathon Women Marathon Women Marathon Women C1 1000m Canadian Singles Men C1 1000m Canadian Singles Men C1 1000m Canadian Singles Men C1 200m Canadian Singles Men C1 200m Canadian Singles Men C1 200m Canadian Singles Men C2 1000m Canadian Pairs Men C2 1000m Canadian Pairs Men 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 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K2 200m Kayak Pairs Men K2 200m Kayak Pairs Men K2 500m Kayak Pairs Women K2 500m Kayak Pairs Women K2 500m Kayak Pairs Women K4 1000m Kayak Fours Men K4 1000m Kayak Fours Men K4 1000m Kayak Fours Men K4 500m Kayak Fours Women K4 500m Kayak Fours Women K4 500m Kayak Fours Women Coxless Fours Men Coxless Fours Men Coxless Fours Men Coxless Pairs Men Coxless Pairs Men Coxless Pairs Men Coxless Pairs Women Coxless Pairs Women Coxless Pairs Women Double Sculls Men Double Sculls Men Double Sculls Men Double Sculls Women Double Sculls Women Double Sculls Women Eights Men Eights Men Eights Men Eights Women Eights Women 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing Rowing 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100m Breaststroke Women 100m Breaststroke Women 100m Butterfly Men 100m Butterfly Men 100m Butterfly Men 100m Butterfly Women 100m Butterfly Women 100m Butterfly Women 100m Freestyle Men 100m Freestyle Men 100m Freestyle Men 100m Freestyle Women 100m Freestyle Women 100m Freestyle Women 10km Marathon Men 10km Marathon Men 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming 10km Marathon Men 10km Marathon Women 10km Marathon Women 10km Marathon Women 1500m Freestyle Men 1500m Freestyle Men 1500m Freestyle Men 200m Backstroke Men 200m Backstroke Men 200m Backstroke Men 200m Backstroke Women 200m Backstroke Women 200m Backstroke Women 200m Breaststroke Men 200m Breaststroke Men 200m Breaststroke Men 200m Breaststroke Women 200m Breaststroke Women 200m Breaststroke Women 200m Butterfly Men 200m Butterfly Men 200m Butterfly Men 200m Butterfly Women 200m Butterfly Women 200m Butterfly Women 200m Freestyle Men 200m Freestyle Men 200m Freestyle Men 200m Freestyle Women 200m Freestyle Women 200m Freestyle Women 200m Individual Medley Men 200m Individual Medley Men 200m Individual Medley Men 200m Individual Medley Women 200m Individual Medley Women 200m Individual Medley Women 400m Freestyle Men 400m Freestyle Men 400m Freestyle Men 400m Freestyle Women 400m Freestyle Women 400m Freestyle Women 400m Individual Medley Men 400m Individual Medley Men 400m Individual Medley Men 400m Individual Medley Women 400m Individual Medley Women 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2012 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics 400m Individual Medley Women 4x100m Freestyle Relay Men 4x100m Freestyle Relay Men 4x100m Freestyle Relay Men 4x100m Freestyle Relay Women 4x100m Freestyle Relay Women 4x100m Freestyle Relay Women 4x100m Medley Relay Men 4x100m Medley Relay Men 4x100m Medley Relay Men 4x100m Medley Relay Women 4x100m Medley Relay Women 4x100m Medley Relay Women 4x200m Freestyle Relay Men 4x200m Freestyle Relay Men 4x200m Freestyle Relay Men 4x200m Freestyle Relay Women 4x200m Freestyle Relay Women 4x200m Freestyle Relay Women 50m Freestyle Men 50m Freestyle Men 50m Freestyle Men 50m Freestyle Women 50m Freestyle Women 50m Freestyle Women 800m Freestyle Women 800m Freestyle Women 800m Freestyle Women 10000m Men 10000m Men 10000m Men 10000m Women 10000m Women 10000m Women 100m Hurdles Women 100m Hurdles Women 100m Hurdles Women 100m Men 100m Men 100m Men 100m Women 100m Women 100m Women 110m Hurdles Men 110m Hurdles Men 110m Hurdles Men 1500m Men 1500m Men 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics 1500m Men 1500m Women 1500m Women 1500m Women 200m Men 200m Men 200m Men 200m Women 200m Women 200m Women 20km Walk Men 20km Walk Men 20km Walk Men 20km Walk Women 20km Walk Women 20km Walk Women 3000m Steeplechase Men 3000m Steeplechase Men 3000m Steeplechase Men 400m Hurdles Men 400m Hurdles Men 400m Hurdles Men 400m Hurdles Women 400m Hurdles Women 400m Hurdles Women 400m Men 400m Men 400m Men 400m Women 400m Women 400m Women 4x100m Relay Men 4x100m Relay Men 4x100m Relay Men 4x100m Relay Women 4x100m Relay Women 4x100m Relay Women 4x400m Relay Men 4x400m Relay Men 4x400m Relay Men 4x400m Relay Women 4x400m Relay Women 4x400m Relay Women 5000m Men 5000m Men 5000m Men 5000m Women 5000m Women 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing Canoeing 5000m Women 50km Walk Men 50km Walk Men 50km Walk Men 800m Men 800m Men 800m Men 800m Women 800m Women 800m Women Marathon Men Marathon Men Marathon Men Marathon Women Marathon Women Marathon Women C1 1000m Canadian Singles Men C1 1000m Canadian Singles Men C1 1000m Canadian Singles Men C1 500m Canadian Singles Men C1 500m Canadian Singles Men C1 500m Canadian Singles Men C2 1000m Canadian Pairs Men C2 1000m Canadian Pairs Men C2 1000m Canadian Pairs Men C2 500m Canadian Pairs Men C2 500m Canadian Pairs Men C2 500m Canadian Pairs Men K1 1000m Kayak Singles Men K1 1000m Kayak Singles Men K1 1000m Kayak Singles Men K1 500m Kayak Singles Men K1 500m Kayak Singles Men K1 500m Kayak Singles Men K1 500m Kayak Singles Women K1 500m Kayak Singles Women K1 500m Kayak Singles Women K2 1000m Kayak Pairs Men K2 1000m Kayak Pairs Men K2 1000m Kayak Pairs Men K2 500m Kayak Pairs Men K2 500m Kayak Pairs Men K2 500m Kayak Pairs Men K2 500m Kayak Pairs Women K2 500m Kayak Pairs Women K2 500m Kayak Pairs Women K4 1000m Kayak Fours Men K4 1000m Kayak Fours Men 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 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Lightweight Coxless Fours Men Lightweight Double Sculls Men Lightweight Double Sculls Men Lightweight Double Sculls Men Lightweight Double Sculls Women Lightweight Double Sculls Women Lightweight Double Sculls Women Quadruple Sculls Men Quadruple Sculls Men Quadruple Sculls Men Quadruple Sculls Women Quadruple Sculls Women Quadruple Sculls Women Single Sculls Men Single Sculls Men Single Sculls Men Single Sculls Women Single Sculls Women Single Sculls Women 100m Backstroke Men 100m Backstroke Men 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming 100m Backstroke Men 100m Backstroke Men 100m Backstroke Women 100m Backstroke Women 100m Backstroke Women 100m Breaststroke Men 100m Breaststroke Men 100m Breaststroke Men 100m Breaststroke Women 100m Breaststroke Women 100m Breaststroke Women 100m Butterfly Men 100m Butterfly Men 100m Butterfly Men 100m Butterfly Women 100m Butterfly Women 100m Butterfly Women 100m Freestyle Men 100m Freestyle Men 100m Freestyle Men 100m Freestyle Men 100m Freestyle Women 100m Freestyle Women 100m Freestyle Women 1500m Freestyle Men 1500m Freestyle Men 1500m Freestyle Men 200m Backstroke Men 200m Backstroke Men 200m Backstroke Men 200m Backstroke Women 200m Backstroke Women 200m Backstroke Women 200m Breaststroke Men 200m Breaststroke Men 200m Breaststroke Men 200m Breaststroke Women 200m Breaststroke Women 200m Breaststroke Women 200m Butterfly Men 200m Butterfly Men 200m Butterfly Men 200m Butterfly Women 200m Butterfly Women 200m Butterfly Women 200m Freestyle Men 200m Freestyle Men 200m Freestyle Men 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming Swimming 200m Freestyle Women 200m Freestyle Women 200m Freestyle Women 200m Individual Medley Men 200m Individual Medley Men 200m Individual Medley Men 200m Individual Medley Women 200m Individual Medley Women 200m Individual Medley Women 400m Freestyle Men 400m Freestyle Men 400m Freestyle Men 400m Freestyle Women 400m Freestyle Women 400m Freestyle Women 400m Individual Medley Men 400m Individual Medley Men 400m Individual Medley Men 400m Individual Medley Women 400m Individual Medley Women 400m Individual Medley Women 4x100m Freestyle Relay Men 4x100m Freestyle Relay Men 4x100m Freestyle Relay Men 4x100m Freestyle Relay Women 4x100m Freestyle Relay Women 4x100m Freestyle Relay Women 4x100m Medley Relay Men 4x100m Medley Relay Men 4x100m Medley Relay Men 4x100m Medley Relay Women 4x100m Medley Relay Women 4x100m Medley Relay Women 4x200m Freestyle Relay Men 4x200m Freestyle Relay Men 4x200m Freestyle Relay Men 4x200m Freestyle Relay Women 4x200m Freestyle Relay Women 4x200m Freestyle Relay Women 50m Freestyle Men 50m Freestyle Men 50m Freestyle Men 50m Freestyle Women 50m Freestyle Women 50m Freestyle Women 800m Freestyle Women 800m Freestyle Women 800m Freestyle Women 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics 10000m Men 10000m Men 10000m Men 10000m Women 10000m Women 10000m Women 100m Hurdles Women 100m Hurdles Women 100m Hurdles Women 100m Men 100m Men 100m Men 100m Women 100m Women 100m Women 110m Hurdles Men 110m Hurdles Men 110m Hurdles Men 1500m Men 1500m Men 1500m Men 1500m Women 1500m Women 1500m Women 200m Men 200m Men 200m Men 200m Women 200m Women 200m Women 20km Walk Men 20km Walk Men 20km Walk Men 20km Walk Women 20km Walk Women 20km Walk Women 3000m Steeplechase Men 3000m Steeplechase Men 3000m Steeplechase Men 400m Hurdles Men 400m Hurdles Men 400m Hurdles Men 400m Hurdles Women 400m Hurdles Women 400m Hurdles Women 400m Men 400m Men 400m Men 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 2004 Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athletics Athleti ...
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Tutor Answer

Tutorwilly
School: University of Maryland

Attached.

Olympic Medalist Research
Name of Student
Institution Affiliation

Date

DATA ACQUISITION
I would need to do some research to better acquaint myself with what data was
actually available, from where it might come and what kind of method would I
need to get access to it. I also knew that my curiosity was going to be framed
around hand-picked movie stars, not all actors. I would therefore need to do
some work to determine now my reason for selecting certain Athletes and
establish the process for acquiring the data.
RESEARCH

I was aware of several movie-related websites that would most likely hold the
type of data I was seeking. A quick scan through each of the sites, and several
others besides, already revealed that the data I was likely to be seeking would be
available but the collection methods and curating duties would involve a fair
amount of work: there were no singular origins to easily export all my data in one
place. Additionally, just from Olympic medalist data I had unearthed quite a few
inconsistencies between sites in the data they held.

RESEARCH
To help my focus and assessment of each site’s offering I established a ‘shopping list’
of the data I would ideally seek to gather:

Athlete name
Gender (I wanted to cover a balance of both male and female athlete stars)
Athlete DOB (to derive their age at the time of participation)
Race title (The US release title for consistency)

Athlete completion dates (The US release date for consistency)
Athlete events
Athlete score (critics and audiences)
Athlete finances (budget, gross, US domestic and worldwide, ideally)
Medals/career milestones for the athlete

RESEARCH
I then visited Olympic medalist data to determine the completeness and
accuracy of the data they held. My approach was to pick a single athlete–
someone whose career data would potentially span many decades and diverse
athlete characteristics and therefore really test the quality and depth of data
held – and one of his or her athletics to help me establish the scope of my data
gathering task. I identified Mo FARAH as a perfect candidate for this, not least
because he was one of the original names associated with my trigger curiosity. I
knew he offered a long career with a nice mix of well-rated and poorly-rated
events, as well as very high takings and very low takings. To assess the caliber
and coverage of data held on individual races, I picked one of Mo FARAH most
recent hits, Inception, as a further test value with which to assess site’s offering.

RESEARCH

The table below shows a summary of the data
that was available from each source about Mo
FARAH and about Inception



What you can see here is the inconsistency of availability, quality and format
across these sources. In particular, I found some key gaps in reliability:



Data about seemed to diminish in quality and completeness (come on kids
managing these Olympic medalist data,



The most consistent financial measure appeared to be worldwide gross.
Budget information was rarely available and when it was appeared to be only
in the form of broad estimates



Race was wildly inconsistent and often very wide-ranging. I knew that if the
range of categories here exceeded .I would not be interested in using it due
to the limitations of colour associations.



My initial intention would have been to ignore the critics’ ratings and make
this analysis purely about audience-led figures (looking at their ratings vs.
their box office spend felt like a pure enquiry of cinema goers views not
grumpy narrow-minded critics). However, a compromise was required due to
the far more complete and seemingly robust data available for critics reviews
compared to audience reviews.



My initial expectation that rating would be the best source of data was not
necessarily supported by going through this process. Additionally, there were
restrictions in data access and I was also somewhat impeded by the
complicated (for me, at least) nature of the API offered for extracting data.



Deciding on which source would be my best option to provide me with the
data was a far more frustrating proposition than I had anticipated from the
outset. This reinforces the point I make in the book about the often hidden
but excessive demands on your time and effort this stage frequently causes
and the importance of doing your research to help reduce wasted.



I finally established a list of 60 individuals, organized by 6 classifying groups:
Contemporary, Veterans, and ‘assorted’ others (which basically comprised 5
directors and 5 comedy actors). I really wanted to include this ‘assorted’
others group so that I could include analysis about how and why Olympic
medallist data was still being allowed to run races.

COLLECTION METHOD
I used the web-scraping tool Import.io to extract my data from the two main
origin sites that is the Olympic medallist data. The process involved customizing
and training the tool how to identify the data components of interest from the
typical page layouts on each site I was extracting from. After defining what I
wanted from an individual page, I then expressed my criteria for how the tool
should ‘crawl’ around and across each site (that is. “Go to these athletes’ pages
and pull off all their filmography data from these parts of the site, then repeat
for… etc.”). Once you’ve set the mechanism in motion you just leave it alone to
go fetch your data, make a cup of tea, then come back in a short while to see
how it has performed.

The final compiled data was available for export into either Excel or CSV format.
My first attempt at an export was into Excel but I immediately noticed how it had
lost some of the date value formatting, whereas exporting the data using CSV
and then opening it in Excel (a small but important distinction) managed to
preserve all the date values.
(TIP: The moment of taking data from a system, regardless of its nature, is one
of the most risky stages for compromising the quality and state of your data,
especially with content like date items.)
As I mentioned above, I knew I would also need to reinforce the data from
Olympic medallist data and The Numbers with data items for the actors’ gender
and DOB. The gender I could identify easily myself but the DOB’s were manually
gathered from a range of places including actors’ Wikipedia pages.

DATA EXAMINATION
I used Excel to pull together the original downloadable datasets and to quickly
assess the physical properties (type, size and condition) of the data. The table
below summarizes the initial examination (click on the image to view a higher
resolution version).



From this initial assessment I was able to identify several key
tran...

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Review

Anonymous
Good stuff. Would use again.

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