The World Cup in football (soccer) is a quadrennial tournament of 32 men’s national teams that is organized by the Fédération Internationale de Football Association (FIFA). It determines the sport’s men’s world champion. It is likely the most popular sporting event in the world, drawing billions of television viewers every tournament.
The World Cup happens every four years in order to have enough time for the qualification tournaments and playoffs among national teams to take place. Additionally, four years provides the host country adequate time to plan the logistics of the tournament and how to best accommodate an influx of millions of fans.
Millions around the world stop their daily lives in order to watch the best football team their country can send to represent them on the field.
The World Cup started in 1930 in Uruguay and since then the explosion of football in the world has only increased.
Ever wondered what stadiums were used in each final or per stage?
Stadiums used at Final since 1930
How about Goals made at each final per world cup.
What about the attendance per elimination game since 1930?
Whenever, I go outside and see a beautiful sunset or sunrise, I often take out my phone and take a photo to capture the moment. Recently, I was walking and decided to take a picture of a beautiful sunset then I wonder how many times I have done this before?
Whenever, I go outside and see a beautiful sunset or sunrise, I often take out my phone and take a photo to capture the moment. Recently, I was walking and decided to take a picture of a beautiful sunset then I wonder how many times I have done this before?
This visualization is meant for people who are interested in learning more about my interaction with sunsets and sunrises. Also, people who have google drive and would like to see how i manually created a dataset with just the metadata.
Here is a bar graph which shows me the total amount of photos i took of Sunrises and Sunsets from April 2015 -> June 2020
Here is a line graph chart in which i manually categorized what photos are “actual sunsets/sunrises”
In the final data visual, I manually added in three variables such as “tress” and “buildings” in the background of each photo.
1. Your research question: Can we determine if noisy vehicles in different boroughs affect sleep patterns for the general populace?
This question was inspired by the loud noises we as New Yorkers randomly hear in the middle of the night. It is annoying and worst of all, it can possibly affect our health. Whenever, we hear a loud bang or music playing in the middle of the night, i often wonder if it’s only me who wishes that we can inform or stop it.
Your audience:
My audience will be aimed at the general populace who live in poorer areas in NYC. My hope is that this research can help answer or aid the question of sleeping pattern disturbances in NYC. It is a known fact that heart problems are rampant in poorer areas and irregular sleep patterns can be one of the key factors in the increase of these issues.
Line graph. Here you can see the amount of 311 noise complaint calls per hour in a workweek.
Here we can see that more calls are made right before late night.
Bar Graph. Here is a visualization of the amount of 311 noise complaints per borough
There is almost an equal amount of noise complaints per borough except Staten Island.
Bubble representation. Fun representation of types of noise complaints per boroughs in a colorful way
The size of the bubbles is important here as there is more complaints of Car music rather than honking or loud noises.
An explanation of the data and design decisions you made:
My source is the 311 complaint data portal: https://data.cityofnewyork.us/Social-Services/311-Service-Requests-from-2010-to-Present/erm2-nwe9/data The data is around 400-line items that were filtered to two categories. One being “Complaint Type: Noise – Vehicle” and the other is a time period from September 19, 2022 12:00AM until September 23, 2022 12:00 AM. While this dataset is extremely small for a proper study, we can see data in a randomize five-day workweek at the beginning of the school year. This dataset also includes columns that indicate borough, address and status of the complaint.
The three types of visualizations are three of the common forms of visualizing massive amounts of data. The Line graph was an excellent choice because we can clearly see that most of the calls were at night. The Bar graph can easily show us that the amount of noise complaints were similar per borough except the outlier of Staten Island. The third and final graph was a colorful bubble graph, here we can see out of three complaints, which one was the most called for.
Next steps:
This visualization can bring forth a possible new avenue of questions to pinpoint time and place. With some tooltips, researchers can further this study with precise moments when a call is made and compare them to hospital visits nearby and or long-term hospital visits.
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