Wind is what we have to worry about

From the previous post, we were talking about observational astronomy. Specifically, we talked about 'seeing' and how weather can affect the ability for the astronomers to do observation. In this post, I want to talk specifically about wind.

You might be wondering how is wind has an effect on the telescope. The answer is a strong wind can  literally shake the telescope and have a damage on the telescope itself. The criterion for a strong wind is 35 mph (56 km/h). Therefore, every time the wind gets stronger, a telescope operator (a person who is responsible for moving the telescope and dome) will shut down the dome to protect the telescope from the wind and an astronomer can just sit there waiting for the wind to stop. If you think sitting and waiting for cloud to go away is bad, waiting for the wind to stop is even worse simple because you can literally see a clear night sky outside your dome, but you simply cannot do the observation.

A wind chart from 3/17-6/17

Average Seeing on Magellan Telescope in the past 4 months

It has been awhile since I wrote my last blog post. I am not sure why. Maybe I felt like 'blogging' was no longer exciting and novel, or maybe I just spent too much time consuming media and did not create anything. Then, someone commented on one of my old data visualization works that I did several years ago about Bangkok. Thank you to that person since it made me want to write a new one again.

Enough about excuses. Today, we will discuss about something that is near and dear to my heart, which is observational astronomy. During my PhD study, I got a chance to visit Magellan Telescope in northern part of Chile (I mentioned a little bit at the end of my last post). However, coming to the telescope is not enough for this kind of works. Weather also plays a huge role in this kind of works. And as we all know, we cannot really control weather. More often than not, astronomers travel to the top of the mountains, sit quietly inside the dome, and wait for the cloud to disappear. But, how often? 

To answer this question, we have to pick a specific place and time to get a finite answer. Naturally, I picked Magellan Telescope and within the last 4 months as a starting point. I put the method and all the resources that I used in the note below.

Seeing at Magellan Telescope from 3/17-6/17

2nd Post: Population Density in Bangkok

I want to continue the series of my post about the population of people in Bangkok, Thailand. Last time, I looked at the total number of people within different Khwangs (which is a finer division than districts). It was also the last post that we mentioned a possible misunderstanding from the previous plot because of the different in areas for each region which are vastly different. Therefore, we should look into the population density instead of the total number of population for each Khwang. I used the 'shape_area' that is calculated within the data file for the information about the area, but there is no obvious information about the unit of the area, so the number of population density, presented here, will not give a much insight into the actual number. However, the relationship between different region for the population density is still valid and required further discussion to make sense out of it.

Where do People Live in Bangkok?

Bangkok, the capitol of Thailand, is the center of everything that you can think of about one country. It is the location for the Grand Palace where the King lives, a large financial distinct in the center of Bangkok, several markets and shopping malls for everyone to buy something, and hundred of Buddhist temples scattering around Bangkok. The Siam Paragon (สยามพารากอน)—a massive shopping complex, movie theater and aquarium in Bangkok–often ranked the most-Instagrammed places for several years. And we also said that Bangkok is the first step to come to South-East Asia because of our enormous airport, Suvarnabhumi Airport.

But where do people actually live in Bangkok? We often saw an ordinary scene of bad traffic in the morning when people are rushing to go to work from different places, students are trying to get to school before 8 am and locals are opening up their stores for another day. Have you ever wondered where do they live? And how far they have to drive to come to work or study in the center of the city?

As a picture is worth a thousand words, I would say that a map is worth a thousand picture. But I could not find any online map showing the details of population of people who live in Bangkok, so I decided to make my own. Fortunately, it is not too difficult to find this data online. Specially, I found the data for the boundary of different khwaengs (แขวง)–an administrative subdivision used in the 50 distrincts of Bangkok and also population within each khwaeng from the Ministry of Transport of Thailand (MOT). In this map, I showed the population for different khwaengs in Bangkok. You could see where people tend to live in Bangkok. I also put in some public transportation like subway train and express ways to see whether there is a correlation between the number of available modes of transit and the population of people.

Which Region do you live in Bangkok?

If you live in Bangkok, you might have heard that Bangkok is divided into 3 main regions based on the location of each district. If you are not sure which region you actually live, here is the list of all 50 districts with its region (the data is from a Pantip forum).

1) Inner City (เขตชั้นใน - blue) including 21 districts: PHRA NAKHON (พระนคร), POM PRAP SATTRU PHAI (ป้อมปราบศัตรูพ่าย), SAMPHANTHAWONG (สัมพันธวงศ์), PATHUM WAN (ปทุมวัน), BANG RAK (บางรัก), YAN NAWA (ยานนาวา), SATHON (สาทร), BANG KHO LAEM (บางคอแหลม), DUSIT (ดุสิต), BANG SUE (บางซื่อ), PHAYA THAI (พญาไท), RATCHATHEWI (ราชเทวี), ห้วยขวาง (HUAI KHWANG), KHLONG TOEI (คลองเตย), CHATUCHAK (จตุจักร), ธนบุรี (THON BURI), KHLONG SAN (คลองสาน), BANGKOK NOI (บางกอกน้อย), BANGKOK YAI (บางกอกใหญ่), DIN DAENG (ดินแดง), WATTHANA (วัฒนา).

Books about US Politics: Network Visualization

Network of books about US politics with its frequent copurchasing of books by the same buyer.

Now, I am working on the project at the Knowledge Lab about books and its political spectrum from conservative to liberal. And I found this publicly available dataset online, so I think it would be good for me to try to visualize this network and see the relationship between books and its copurchase.

I got this dataset from Prof. Mark Newman's personal website page of Network data (If you are interested, you can check his website as well.) He is a physics professor at University of Michigan, conducting research on the structure and function of social and information networks. According to Prof. Newmann's website, this dataset contains

A network of books about US politics published around the time of the 2004 presidential election and sold by the online bookseller Amazon.com. Edges between books represent frequent copurchasing of books by the same buyers. The network was compiled by V. Krebs and is unpublished. 

Wealth Inequality Around the World

income inequality | Create Infographics

One morning, I found a youtube video about Wealth Inequality in America. I started to wonder whether the distribution like in my home country, Thailand, and other parts of the world. I searched for it in the internet for a while, but it seems like I could not find any graphs or chart on this similar topic. So, I decided to do some research on this topic.

Then, I found the data that I want from World Development Indicator which is the one of many database of World Bank. But I just do not like the chart that it had on its web interface, so I designed to create my own chart, called 'Income Inequality', about this topic using Infogr.am. I found that using this type of method is a good way to convey the information to other people.

I want this post to be all about how I get to make this infograph, so if I did not put any of my interpretation in this post since we should separate between facts and opinion. Nevertheless, others still argue that by displaying numbers like this infographics, a creator intended to persuade readers to a certain direction which is already an interpretation of a creator.

Note: If you want to learn more about infographics, you can learn more about it from Cool Infographics Blog by Randy Krum

Facebook Social Graph using Netvizz & Gephi

   
     Since I used Wolframalpha to analyze my facebook data (by just typing 'facebook' into it) in a minute back in 2012, I found it is really fascinating to make my own social graph using data from my own facebook account and see the connection that I have on facebook. Then, I found a blog called 'Persuasion' by Sarah Joy with a page called 'Using Netvizz & Gephi to Analyze a Facebook Network' about how to easily make a social graph using only two softwares: Netvizz and Gephi.

    - Netvizz allowed you to quickly download (if you do not have that many friends) your facebook data from the website as a gdf file.
    - Gephi will let you visualize gdf file easily with many options to change your own graph.

    I will not go into detail of how exactly to do this because you can find it extensively at the page I mentioned above. But I will tell you of what I found in my own social graph. It made me realize many friends that I used to keep in touch with and how those people are very far in connection with people that I am with now.

Social Graph for Me from Facebook Data