{"id":5035,"date":"2016-06-29T23:23:12","date_gmt":"2016-06-30T03:23:12","guid":{"rendered":"http:\/\/research.prattsils.org\/?p=5035"},"modified":"2016-06-29T23:23:12","modified_gmt":"2016-06-30T03:23:12","slug":"cartodb-lab-report-mining-data-map","status":"publish","type":"post","link":"https:\/\/studentwork.prattsi.org\/infovis\/visualization\/cartodb-lab-report-mining-data-map\/","title":{"rendered":"CartoDB Lab Report: Mining data map"},"content":{"rendered":"

Ratirat Osiri (Rey)<\/span><\/p>\n

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SU-LIS-658-01<\/span>: CartoDB Lab Report<\/span><\/p>\n

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Working with CartoDB has turned out harder than I thought it would be, not because of the program itself, but because of the difficulties searching the suitable dataset to work with. At first, I found a dataset that I think it could work, I chose tornado historic data from CartoDB data library. The data contain the information of historic tornado in the US since 1950, including their location and route. It worked perfectly fine on CartoDB, but quantitative data is not included in the dataset so I couldn\u2019t manipulate anything with this dataset except the color. The final result is shown in figure 1<\/span><\/p>\n

Figure 1
\n\"tornado_by_remyratio_06_29_2016_11_21_18\"<\/a><\/p>\n

I later managed to find the other dataset called Mineral mining data. This dataset also including shapefile and other detailed data so it is little easier to work with even though they don\u2019t include numerical data either. I downloaded\u00a0QGIS\u00a0to use with my computer, but the program unfortunately crashed every single time I tried to open a file so I just gave up and go with the dataset I have. I also used all the data storage from the account I created in class so I needed to create a new one. I think the data limit is a little frustrating, \u00a0especially when it doesn\u2019t allow you to delete any unused data. Anyway, I understand that it\u2019s the way convince their users to buy an upgrade. <\/span><\/p>\n

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From the dataset, I decided to separate the map into two layers, one is for types of minerals commonly found in each location, and the other is the quantity they found from each location. I tried to merge latitude and longitude together and then use the new column as location display on the map, but my data storage is not enough so I need to find other ways, by combining longitude and latitude together in georeference function. However, for some reasons, the newly combined longitude and latitude isn\u2019t appear in any layer option. I finally decided to move on with two simple layers, type and location. The first layer is the number of minerals produced from each location on the map. I picked torque template to displays the intensity of the data on the map. I picked blue color to associate with mineral and give it a heatmap feeling (in my opinion) Since the dataset also provide yearly data, I chose the play animated map that changed each year, as shown in figure 2. The other layer is type of mineral found in each location. I chose category template associated with the mineral data column as shown in figure 3. <\/span><\/p>\n

Figure 2
\n\"wqeweweqwe\"<\/a><\/p>\n

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Figure 3<\/p>\n

\"mrds_trim_1_by_ratiocide_06_29_2016_11_07_02\"<\/a><\/p>\n

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I found that CartoDB is fairly easy to work with, at least much easier than Gephi. The program itself offers so many options and functions to manipulate the map and data. The interface is also surprisingly easy to adjust anything. I think the layer function really comes in handy when the user wants to displays many data within one map, which I really wish to use on Tableau and Gephi. \u00a0I\u2019m not sure if all the difficulties I and other classmates had encountered are from the data incompatibility or the program\u2019s characteristic which requires a suitable suitable dataset, especially geographical data to works well. I feels that I need to learn a lot more about CartoDB to use this program at its full potential. At this time, I\u2019d still prefer tableau over CartoDB and Gephi, which is understandable since Tableau is the only \u2018full\u2019 program to use, compare to Gephi and CartoDB which is opensource and free version. However, I believe that CartoDB would suit better than Tableau for the data with more geographical oriented, which I wish I would have a chance to use it properly someday.<\/span><\/p>\n

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Ratirat Osiri (Rey)   SU-LIS-658-01: CartoDB Lab Report   Working with CartoDB has turned out harder than I thought it would be, not because of the program itself, but because of the difficulties searching the suitable dataset to work with. At first, I found a dataset that I think it could work, I chose tornado…<\/p>\n","protected":false},"author":357,"featured_media":5043,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"coauthors":[],"class_list":["post-5035","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-visualization"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/paBdcV-1jd","_links":{"self":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/5035","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/users\/357"}],"replies":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/comments?post=5035"}],"version-history":[{"count":0,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/5035\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/"}],"wp:attachment":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/media?parent=5035"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/categories?post=5035"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/tags?post=5035"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/coauthors?post=5035"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}