{"id":12973,"date":"2024-10-10T15:43:53","date_gmt":"2024-10-10T21:43:53","guid":{"rendered":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/?p=12973"},"modified":"2024-10-17T09:21:32","modified_gmt":"2024-10-17T15:21:32","slug":"large-assignment-3-qinghong-shao","status":"publish","type":"post","link":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/2024\/10\/10\/large-assignment-3-qinghong-shao\/","title":{"rendered":"Large Assignment 3: Qinghong Shao"},"content":{"rendered":"\n

I choose the data of Electric Vehicle Population, it is popular to buy and drive electric vehicle in my country rencent years, but it is still common to drive oil vehicle in US. The first car I bought here is also the oil vehicle. It seems the price of gas is more cheap than other country, and there are a lot of oil reserves, although the electric vehicle could produce less air pollution. Therefore, it motivates me to search the reason and the history of the electric vehicle population in US.<\/p>\n\n\n\n

Data Clean<\/h2>\n\n\n\n

The data I choose it include many noise which will affect the other normal data, then I delete some lable of this dataset, for example the county, state, postal code and so on, because these seems difficult to visualize. In addition, I sorted the data in ascending order by time. Finally, I add the Normalization Function to scale all of these data, because many of them belong to different ranges.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Design Process<\/h2>\n\n\n\n

First step: I design data_parse(file, scale1, scale2) to reads the CSV file containing energy data, it also take the two scale from number slider so that we can control the scale of the visualized objcet.<\/p>\n\n\n\n

Second step: plot(data, offset=0, start=0, end=70)<\/code>: Each point\u2019s z<\/code> coordinate is determined by its index, and its x<\/code> coordinate comes from the third column.<\/p>\n\n\n\n

Third Step: normalization(data): This is useful to ensure that the data falls within a reasonable range for visualization, especially when scaling for 3D geometry.<\/p>\n\n\n\n

Forms<\/h2>\n\n\n\n
    \n
  1. the dataset of this forms begin from 01\/2013, and it include the 70 months after 01\/2013, it behaves the variation in primary energy imports.<\/li>\n<\/ol>\n\n\n\n
    \"\"<\/figure>\n\n\n\n

    2. the dataset of this forms begin from 01\/2013, and it include the 70 months after 01\/2013, it behaves the variation in total renewable energy consumption.<\/p>\n\n\n\n

    \"\"<\/figure>\n\n\n\n

    3. the dataset of this forms begin from 01\/2013 to 06\/2024, it behaves the variation in the variation in total primary energy production.<\/p>\n\n\n\n

    \"\"<\/figure>\n\n\n\n

    Analysis from the shape of form<\/strong>: As can be seen from the figure, Total Primary Energy Production has fluctuated overall but shows an upward trend. We can infer that the increase at the bottom may be due to the large-scale exploitation of shale gas by hydraulic fracturing technology in the United States in the early 2010s, which led to a significant increase in domestic natural gas and oil production.<\/p>\n\n\n\n

    During this period, the US government introduced some policies to promote energy production. For example, during the Obama administration, energy policies promoted the development of clean energy, but also retained support for traditional energy such as oil and natural gas. These factors may have worked together to cause the gradual increase in primary energy production and short-term fluctuations.<\/p>\n\n\n\n

    \"\"<\/figure>\n\n\n\n
    \"\"<\/figure>\n\n\n\n
    \"\"<\/figure>\n\n\n\n
    \"\"<\/figure>\n\n\n\n

    Challenges<\/h2>\n\n\n\n

    In general, I met two challenges when I do the printing work. The first is the input data is too large or too small. You can not compare them straightly. There are two ways I found to deal wtih, use the scale number slider or design the normalization function, so that you can control the scale or range of the inputed data.<\/p>\n\n\n\n

    The second challeng is that it seems the rendered object is not continus. I guess it is because I process too much rows of data, and i cut the data to 70 pieces, and it behave better. But why it will occur when i use the rs.AddRevSrf()? I will try to explor it in future.<\/p>\n\n\n\n

    \"\"<\/figure>\n\n\n\n

    When it prints to a high level it collapses because of the disconnected layers.<\/p>\n\n\n\n

    \"\"<\/figure>\n\n\n\n

    Dataset Link<\/h2>\n\n\n\n

    The original dataset: Electric Vehicle Population Data – Catalog<\/a> https:\/\/catalog.data.gov\/dataset\/electric-vehicle-population-data<\/a><\/p>\n\n\n\n

    The dataset after cleaning: https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-content\/uploads\/2024\/10\/cleaned-electric-vehicle-population-data-2.csv<\/a><\/p>\n\n\n\n

    Grasshopper Code<\/h2>\n\n\n\n

    Grasshopper code: https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-content\/uploads\/2024\/10\/QinghongShaoLA3.gh<\/a><\/p>\n\n\n\n

    Reflection<\/h2>\n\n\n\n

    Now, there are many ways to visualize the data, for example, you can use the library of python called Matplotlib, and it is also even common to use Excel to visualize the data. What is the meaning for using the printed work to demonstrate the static data? <\/p>\n\n\n\n

    In my opinion, the printed work it is real work, it looks like the paint, sculpture, we can even go back to ancient times, thousands of years ago with pottery, ceramics, or sites like Stonehenge. All of there I mention they could be carved with information and stored for a long time until our descendants could discover the work we produce and reconsider them. For example, there are some discovered printed objects that our descendants found it recorded the information that as cars became more popular around the world, their emissions had an impact on global temperatures in the 20th and 21st centuries. Just like today we are re-acquainting ourselves with the pottery, stone tools, murals, etc. left behind by our Neolithic ancestors thousands of years ago, we can learn a lot of their stories from them. On the contrary, all the data we save electronically seems to be deleted over time, and USB flash drives do not seem to be able to be preserved in the soil for too long, or their components will be damaged and lose the data they store.<\/p>\n","protected":false},"excerpt":{"rendered":"

    I choose the data of Electric Vehicle Population, it is popular to buy and drive electric vehicle in my country rencent years, but it is still common to drive oil vehicle in US. The first car I bought here is also the oil vehicle. It seems the price of gas is more cheap than other country, and there are a […]<\/p>\n","protected":false},"author":39,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[57,46],"tags":[],"class_list":["post-12973","post","type-post","status-publish","format-standard","hentry","category-large-assignment-3-data","category-studentwork24"],"_links":{"self":[{"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/posts\/12973","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/users\/39"}],"replies":[{"embeddable":true,"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/comments?post=12973"}],"version-history":[{"count":12,"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/posts\/12973\/revisions"}],"predecessor-version":[{"id":13138,"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/posts\/12973\/revisions\/13138"}],"wp:attachment":[{"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/media?parent=12973"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/categories?post=12973"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/tags?post=12973"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}