added some plots on initial article, theme alter
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32
config.toml
32
config.toml
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@ -1,6 +1,6 @@
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baseUrl = ""
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baseUrl = ""
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title = "Distill Hugo Theme"
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title = "Status Network Token Distribution Analysis"
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author = "Sanyam Kapoor"
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author = "Corey Petty"
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canonifyurls = true
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canonifyurls = true
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theme = "distillpub"
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theme = "distillpub"
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@ -8,41 +8,25 @@ theme = "distillpub"
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# TODO: Taxonomies?
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# TODO: Taxonomies?
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[params]
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[params]
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description = "Distill Hugo Theme Demo"
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description = "Status Network Token Distribution"
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keywords = ["hugo", "distill", "theme"]
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keywords = ["hugo", "distill", "theme"]
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sourcePrefix = "https://github.com/activatedgeek/distillpub/blob/master/exampleSite"
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sourcePrefix = "https://github.com/status-im/snt-distribution"
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color = "#0f2e3d"
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color = "#4360DF"
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[[params.social]]
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class = "fas fa-user-graduate"
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url = "https://scholar.google.com/citations?user=p0NMtgsAAAAJ"
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[[params.social]]
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[[params.social]]
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class = "fab fa-github"
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class = "fab fa-github"
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url = "https://github.com/activatedgeek"
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url = "https://github.com/status-im"
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[[params.social]]
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class = "fab fa-hacker-news"
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url = "https://news.ycombinator.com/user?id=activatedgeek"
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[[params.social]]
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class = "fab fa-linkedin"
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url = "https://linkedin.com/in/sanyamkapoor"
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[[params.social]]
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class = "fab fa-stack-overflow"
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url = "https://stackoverflow.com/users/2425365"
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[[params.social]]
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[[params.social]]
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class = "fab fa-twitter"
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class = "fab fa-twitter"
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url = "https://twitter.com/activatedgeek"
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url = "https://twitter.com/ethstatus"
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[menu]
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[menu]
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[[menu.main]]
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[[menu.main]]
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identifier = "about"
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identifier = "about"
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name = "About Hugo"
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name = "Corey Petty"
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title = "about"
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title = "about"
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url = "/about"
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url = "/about"
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weight = -10
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weight = -10
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@ -1,7 +1,8 @@
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### Contributions
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### Contributions
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Some text describing who did what.
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- Corey Petty performed the aggregation of data, labeling of addresses, data munging and transformation, plot visualization, and writing.
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- Jakub Sakolowski recommeneded the Hugo platform and assisted in platform familiarization, as well as various devOps questions.
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### Reviewers
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### Reviewers
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Some text with links describing who reviewed the article.
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The associated Status accounts were reviewed by Jarrad Hope and Carl Bennetts
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@ -1,7 +1,7 @@
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+++
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+++
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title = "Attention and Augmented Recurrent Neural Networks"
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title = "SNT Distribution Analysis: A visual article"
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description = "This is a demo article."
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description = "This is a demo article."
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date = "2017-01-10"
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date = "2020-10-15"
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thumbnail = ""
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thumbnail = ""
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categories = [
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categories = [
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"demo"
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"demo"
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@ -31,68 +31,35 @@ vega = true
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<p>This is the first paragraph of the article. Test a long — dash — here it is.</p>
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<p>This is the first paragraph of the article. Test a long — dash — here it is.</p>
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</d-abstract>
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</d-abstract>
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This is the first paragraph of the article. Test a long — dash — here it is
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This is an article that will discribe how SNT is distributed throughout its community. There was a previous analysis performed by the author {{<cite bib="pettyDistribution2017">}} directly after the Status.im ICO. This analysis attempted to look at who participated directly with the token distribution smart contract, and how they relate to each other. Since then, there has been a lot of development, a lot of movement of the SNT token, and adoption of several exchanges whcih drastically alters the distribution.
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Test for owner’s possessive. Test for "quoting a passage." And another sentence. Or two. Some flopping fins; for diving.
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Here we will create various plots that show, in as much detail as publicly possible, who holds what as it stands today and review is it looks any different than a naive view, or the snapshot given by the author directly after the ICO.
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Here’s a test of an inline equation {{<math>}}c = a^2 + b^2{{</math>}}. And then there’s a block equation:
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Here we have the initial SNT distribution seperation. It is most easily seperated into three seperate sections which each require further analysis:
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{{<math block="true">}}
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c = \pm \sqrt{ \sum_{i=0}^{n}{a^{222} + b^2}}
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{{</math>}}
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We can {{<cite bib="mercier2011humans">}} also cite {{<cite bib="gregor2015draw,mercier2011humans">}} external publications. {{<cite bib="dong2014image,dumoulin2016guide,mordvintsev2015inceptionism">}}.
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{{<vega id="viz-compare" spec="status-exchange-community-donut.vg.json" >}}
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We should also be testing footnotes{{<footnote>}}This will become a hoverable footnote. This will become a hoverable footnote. This will become a hoverable footnote. This will become a hoverable footnote. This will become a hoverable footnote. This will become a hoverable footnote. This will become a hoverable footnote. This will become a hoverable footnote.{{</footnote>}}. There are multiple footnotes, and they appear in the appendix{{<footnote>}}Given I have coded them right. Also, here’s math in a footnote: {{<math>}}c = \sum_0^i{x}{{</math>}}. Also, a citation. Box-ception {{<cite bib="gregor2015draw">}}! {{</footnote>}} as well.
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1. `Status`- contracts and accounts related to the Status Network. These don't necessarily need to be owned and operated by the Status Network GmbH, but certaily include those accounts.
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2. `Exchanges` - accounts that have been identified {{<cite bib="etherscan,f13endgist">}} as accounts used by exchanges to store funds.
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3. `Community` - accounts that cannot be attribute elsewhere that hold SNT, we consider this the "community."
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| **First** | **Second** | **Third** |
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An initial glance at this distribution combined with a naive understanding of the specifics of the Status related holdings will lead to the narrative that SNT is "centralized."
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|---|---|---|
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| 23 | 654 | 23 |
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| 14 | 54 | 34 |
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| 234 | 54 | 23 |
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## Displaying code snippets
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---
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## Plots of Status related addresses
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Some inline javascript: {{<code language="javascript">}}var x = 25;{{</code>}}
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---
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## Plots of Exchange addresses
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Here’s a javascript code block.
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{{<vega id="viz-exchange" spec="exchange-treemap.vg.json" >}}
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{{<code language="javascript" block="true">}}
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var x = 25;
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function(x){
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return x * x;
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}
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{{</code>}}
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We also support python.
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---
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{{<code language="python" block="true">}}
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## Plots of the Community distribution
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# Python 3: Fibonacci series up to n
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def fib(n):
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a, b = 0, 1
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while a < n:
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print(a, end=' ')
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a, b = b, a+b
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{{</code>}}
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And guess what! We also have Vega-Lite embedded graphs!
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Here we break up the community accounts into groups of "exponential value."{{<footnote>}}Note that this plot is not interactive, because it is a picture and I haven't had time to create the vega-lite version of it yet.{{</footnote>}} That is, we bucket each address based on what order of magnitude it is, as well as note how big that bucket is to show how many people control how much total value.
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{{<vega id="viz" spec="https://raw.githubusercontent.com/vega/vega/master/docs/examples/bar-chart.vg.json">}}
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That’s it for the example article!
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## Bringing it all together to get a real picture
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<table>
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Now that we have more insight into each of the sub-groups explained earlier, we can start to form a more informed picture of the total distribution of SNT across its various holders.
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<thead>
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<tr>
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<th>Address</th>
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<th>Balance</th>
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</tr>
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</thead>
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<tbody>
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{{ $url := "static/data_csv/holders.csv" }}
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{{ $sep := "," }}
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{{ range $i, $r := getCSV $sep $url }}
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<tr>
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<td>{{ index $r 0 }}</td>
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<td>{{ index $r 1 }}</td>
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</tr>
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{{ end }}
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</tbody>
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</table>
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@ -1,89 +1,18 @@
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@article{gregor2015draw,
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@misc{etherscan,
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title={DRAW: A recurrent neural network for image generation},
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title={Etherscan Blockchain Explorer},
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author={Gregor, Karol and Danihelka, Ivo and Graves, Alex and Rezende, Danilo Jimenez and Wierstra, Daan},
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author={Matthew Tann},
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journal={arXiv preprint arXiv:1502.04623},
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year={2015},
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year={2015},
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url ={https://arxiv.org/pdf/1502.04623.pdf}
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url={https://etherscan.io},
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}
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}
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@article{mercier2011humans,
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@misc{f13endgist,
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title={Why do humans reason? Arguments for an argumentative theory},
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title={Wallet Addresses Github Gist},
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author={Mercier, Hugo and Sperber, Dan},
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author={f13end},
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journal={Behavioral and brain sciences},
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year={2018},
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volume={34},
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url={https://gist.github.com/f13end/bf88acb162bed0b3dcf5e35f1fdb3c17},
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number={02},
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pages={57--74},
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year={2011},
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publisher={Cambridge Univ Press},
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doi={10.1017/S0140525X10000968}
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}
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}
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@article{dong2014image,
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@#article{pettyDistribution2017,
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title={Image super-resolution using deep convolutional networks},
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title={A Look at the Status.im ICO Token Distribution},
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author={Dong, Chao and Loy, Chen Change and He, Kaiming and Tang, Xiaoou},
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author={Corey Petty},
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journal={arXiv preprint arXiv:1501.00092},
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year={2017},
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year={2014},
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url={https://medium.com/the-bitcoin-podcast-blog/a-look-at-the-status-im-ico-token-distribution-f5bcf7f00907},
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url={https://arxiv.org/pdf/1501.00092.pdf}
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}
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@article{dumoulin2016adversarially,
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title={Adversarially Learned Inference},
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author={Dumoulin, Vincent and Belghazi, Ishmael and Poole, Ben and Lamb, Alex and Arjovsky, Martin and Mastropietro, Olivier and Courville, Aaron},
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journal={arXiv preprint arXiv:1606.00704},
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year={2016},
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url={https://arxiv.org/pdf/1606.00704.pdf}
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}
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@article{dumoulin2016guide,
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title={A guide to convolution arithmetic for deep learning},
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author={Dumoulin, Vincent and Visin, Francesco},
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journal={arXiv preprint arXiv:1603.07285},
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year={2016},
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url={https://arxiv.org/pdf/1603.07285.pdf}
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}
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@article{gauthier2014conditional,
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title={Conditional generative adversarial nets for convolutional face generation},
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author={Gauthier, Jon},
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journal={Class Project for Stanford CS231N: Convolutional Neural Networks for Visual Recognition, Winter semester},
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volume={2014},
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year={2014},
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url={http://www.foldl.me/uploads/papers/tr-cgans.pdf}
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}
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@article{johnson2016perceptual,
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title={Perceptual losses for real-time style transfer and super-resolution},
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author={Johnson, Justin and Alahi, Alexandre and Fei-Fei, Li},
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journal={arXiv preprint arXiv:1603.08155},
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year={2016},
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url={https://arxiv.org/pdf/1603.08155.pdf}
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}
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@article{mordvintsev2015inceptionism,
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title={Inceptionism: Going deeper into neural networks},
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author={Mordvintsev, Alexander and Olah, Christopher and Tyka, Mike},
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journal={Google Research Blog},
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year={2015},
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url={https://research.googleblog.com/2015/06/inceptionism-going-deeper-into-neural.html}
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}
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@misc{mordvintsev2016deepdreaming,
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title={DeepDreaming with TensorFlow},
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author={Mordvintsev, Alexander},
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year={2016},
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url={https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/tutorials/deepdream/deepdream.ipynb},
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}
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@article{radford2015unsupervised,
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title={Unsupervised representation learning with deep convolutional generative adversarial networks},
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author={Radford, Alec and Metz, Luke and Chintala, Soumith},
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journal={arXiv preprint arXiv:1511.06434},
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year={2015},
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url={https://arxiv.org/pdf/1511.06434.pdf}
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}
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@inproceedings{salimans2016improved,
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title={Improved techniques for training gans},
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author={Salimans, Tim and Goodfellow, Ian and Zaremba, Wojciech and Cheung, Vicki and Radford, Alec and Chen, Xi},
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booktitle={Advances in Neural Information Processing Systems},
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pages={2226--2234},
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year={2016},
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url={https://arxiv.org/pdf/1606.03498.pdf}
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}
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@article{shi2016deconvolution,
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title={Is the deconvolution layer the same as a convolutional layer?},
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author={Shi, Wenzhe and Caballero, Jose and Theis, Lucas and Huszar, Ferenc and Aitken, Andrew and Ledig, Christian and Wang, Zehan},
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journal={arXiv preprint arXiv:1609.07009},
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year={2016},
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url={https://arxiv.org/pdf/1609.07009.pdf}
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}
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}
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File diff suppressed because it is too large
Load Diff
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munge.py
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munge.py
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import pandas as pd
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import numpy as np
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snt_stats = {
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'total_supply': 6804870174.8781,
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}
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def lower(string):
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return string.lower()
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def label_exp_group(value):
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labels = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11']
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for label in labels:
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if value <= 10**float(label):
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return label
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# import known Status Addresses
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status = pd.read_csv('./data_csv/utility.csv')
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status['address'] = status['address'].apply(lower)
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status['isStatus'] = True
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# import holder accounts
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holders = pd.read_csv('./data_csv/holders.csv')
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holders['address'] = holders['address'].apply(lower)
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# import exchange accounts
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exchanges = pd.read_csv('./data_csv/exchanges.csv')
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exchanges['address'] = exchanges['address'].apply(lower)
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exchanges['isExchange'] = True
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# merge into single dataset
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holders = holders.merge(status, on="address", how="left")
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holders = holders.merge(exchanges, on="address", how="left")
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# clean up
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holders['name_x'].fillna('', inplace=True)
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holders['name_y'].fillna('', inplace=True)
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holders['name'] = holders['name_x'] + holders['name_y']
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# add additional columns
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holders['percent'] = holders['balance'] / snt_stats['total_supply'] * 100
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holders['exp_group'] = holders.balance.apply(label_exp_group)
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# clean up NaN
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holders['isContract'].fillna('False', inplace=True)
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holders['isExchange'].fillna('False', inplace=True)
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holders['isStatus'].fillna('False', inplace=True)
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# filter out what we want
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holders = holders[['address', 'balance', 'percent', 'exp_group', 'name', 'isContract', 'isExchange', 'isStatus']]
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holders.to_csv('./data_csv/holders_munged.csv')
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import pandas as pd
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import numpy as np
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import json
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snt_stats = {
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'total_supply': 6804870174.8781,
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}
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def lower(string):
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return string.lower()
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def label_exp_group(value):
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labels = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11']
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for label in labels:
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if value <= 10**float(label):
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return label
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# import known Status Addresses
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status = pd.read_csv('./data_csv/utility.csv')
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status['address'] = status['address'].apply(lower)
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status['isStatus'] = True
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# import holder accounts
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holders = pd.read_csv('./data_csv/holders.csv')
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holders['address'] = holders['address'].apply(lower)
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# import exchange accounts
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exchanges = pd.read_csv('./data_csv/exchanges.csv')
|
||||||
|
exchanges['address'] = exchanges['address'].apply(lower)
|
||||||
|
exchanges['isExchange'] = True
|
||||||
|
|
||||||
|
# merge into single dataset
|
||||||
|
holders = holders.merge(status, on="address", how="left")
|
||||||
|
holders = holders.merge(exchanges, on="address", how="left")
|
||||||
|
|
||||||
|
# clean up
|
||||||
|
holders['name_x'].fillna('', inplace=True)
|
||||||
|
holders['name_y'].fillna('', inplace=True)
|
||||||
|
holders['name'] = holders['name_x'] + holders['name_y']
|
||||||
|
|
||||||
|
# add additional columns
|
||||||
|
holders['percent'] = holders['balance'] / snt_stats['total_supply'] * 100
|
||||||
|
holders['exp_group'] = holders.balance.apply(label_exp_group)
|
||||||
|
|
||||||
|
# clean up NaN
|
||||||
|
holders['isContract'].fillna('False', inplace=True)
|
||||||
|
holders['isExchange'].fillna('False', inplace=True)
|
||||||
|
holders['isStatus'].fillna('False', inplace=True)
|
||||||
|
|
||||||
|
# filter out what we want
|
||||||
|
holders = holders[['address', 'balance', 'percent', 'exp_group', 'name', 'isContract', 'isExchange', 'isStatus']]
|
||||||
|
|
||||||
|
## Export holders CSV
|
||||||
|
holders.to_csv('./data_csv/holders_munged.csv')
|
||||||
|
|
||||||
|
##################### Plots creation
|
||||||
|
## Status vs Exchange vs Community
|
||||||
|
status_perc = holders[holders['isStatus'] == True].percent.sum()
|
||||||
|
exchange_perc = holders[holders['isExchange'] == True].percent.sum()
|
||||||
|
community_perc = 100 - status_perc - exchange_perc
|
||||||
|
vegaJson = {
|
||||||
|
"$schema": "https://vega.github.io/schema/vega/v5.json",
|
||||||
|
"description": "A basic bar chart example, with value labels shown upon mouse hover.",
|
||||||
|
"width": 400,
|
||||||
|
"height": 200,
|
||||||
|
"padding": 5,
|
||||||
|
|
||||||
|
"data": [
|
||||||
|
{
|
||||||
|
"name": "table",
|
||||||
|
"values": [
|
||||||
|
{"category": "Status", "amount": round(status_perc,2)},
|
||||||
|
{"category": "Exchanges", "amount": round(exchange_perc,2)},
|
||||||
|
{"category": "Community", "amount": round(community_perc,2)}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
|
||||||
|
"signals": [
|
||||||
|
{
|
||||||
|
"name": "tooltip",
|
||||||
|
"value": {},
|
||||||
|
"on": [
|
||||||
|
{"events": "rect:mouseover", "update": "datum"},
|
||||||
|
{"events": "rect:mouseout", "update": "{}"}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
|
||||||
|
"scales": [
|
||||||
|
{
|
||||||
|
"name": "xscale",
|
||||||
|
"type": "band",
|
||||||
|
"domain": {"data": "table", "field": "category"},
|
||||||
|
"range": "width",
|
||||||
|
"padding": 0.05,
|
||||||
|
"round": True
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "yscale",
|
||||||
|
"domain": {"data": "table", "field": "amount"},
|
||||||
|
"nice": True,
|
||||||
|
"range": "height"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
|
||||||
|
"axes": [
|
||||||
|
{ "orient": "bottom", "scale": "xscale" },
|
||||||
|
{ "orient": "left", "scale": "yscale" }
|
||||||
|
],
|
||||||
|
|
||||||
|
"marks": [
|
||||||
|
{
|
||||||
|
"type": "rect",
|
||||||
|
"from": {"data":"table"},
|
||||||
|
"encode": {
|
||||||
|
"enter": {
|
||||||
|
"x": {"scale": "xscale", "field": "category"},
|
||||||
|
"width": {"scale": "xscale", "band": 1},
|
||||||
|
"y": {"scale": "yscale", "field": "amount"},
|
||||||
|
"y2": {"scale": "yscale", "value": 0}
|
||||||
|
},
|
||||||
|
"update": {
|
||||||
|
"fill": {"value": "steelblue"}
|
||||||
|
},
|
||||||
|
"hover": {
|
||||||
|
"fill": {"value": "red"}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"type": "text",
|
||||||
|
"encode": {
|
||||||
|
"enter": {
|
||||||
|
"align": {"value": "center"},
|
||||||
|
"baseline": {"value": "bottom"},
|
||||||
|
"fill": {"value": "#333"}
|
||||||
|
},
|
||||||
|
"update": {
|
||||||
|
"x": {"scale": "xscale", "signal": "tooltip.category", "band": 0.5},
|
||||||
|
"y": {"scale": "yscale", "signal": "tooltip.amount", "offset": -2},
|
||||||
|
"text": {"signal": "tooltip.amount"},
|
||||||
|
"fillOpacity": [
|
||||||
|
{"test": "datum === tooltip", "value": 0},
|
||||||
|
{"value": 1}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
with open('./static/status-exchange-community-donut.vg.json', 'w') as plot_file:
|
||||||
|
json.dump(vegaJson, plot_file, ensure_ascii=False, indent=4, sort_keys=False)
|
||||||
|
|
||||||
|
## Exchange Treemap
|
||||||
|
exchangeBarJson = holders[holders['isExchange'] == True].groupby("name").sum().reset_index().reset_index().to_json(orient='records')
|
||||||
|
vegaJson ={
|
||||||
|
"$schema": "https://vega.github.io/schema/vega/v5.json",
|
||||||
|
"description": "A basic bar chart example, with value labels shown upon mouse hover.",
|
||||||
|
"width": 400,
|
||||||
|
"height": 200,
|
||||||
|
"padding": 5,
|
||||||
|
|
||||||
|
"data": [
|
||||||
|
{
|
||||||
|
"name": "table",
|
||||||
|
"values": json.loads(exchangeBarJson)
|
||||||
|
}
|
||||||
|
],
|
||||||
|
|
||||||
|
"signals": [
|
||||||
|
{
|
||||||
|
"name": "tooltip",
|
||||||
|
"value": {},
|
||||||
|
"on": [
|
||||||
|
{"events": "rect:mouseover", "update": "datum"},
|
||||||
|
{"events": "rect:mouseout", "update": "{}"}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
|
||||||
|
"scales": [
|
||||||
|
{
|
||||||
|
"name": "xscale",
|
||||||
|
"type": "band",
|
||||||
|
"domain": {"data": "table", "field": "name"},
|
||||||
|
"range": "width",
|
||||||
|
"padding": 0.05,
|
||||||
|
"round": True
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "yscale",
|
||||||
|
"domain": {"data": "table", "field": "percent"},
|
||||||
|
"nice": True,
|
||||||
|
"range": "height"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
|
||||||
|
"axes": [
|
||||||
|
{ "orient": "bottom", "scale": "xscale" },
|
||||||
|
{ "orient": "left", "scale": "yscale" }
|
||||||
|
],
|
||||||
|
|
||||||
|
"marks": [
|
||||||
|
{
|
||||||
|
"type": "rect",
|
||||||
|
"from": {"data":"table"},
|
||||||
|
"encode": {
|
||||||
|
"enter": {
|
||||||
|
"x": {"scale": "xscale", "field": "name"},
|
||||||
|
"width": {"scale": "xscale", "band": 1},
|
||||||
|
"y": {"scale": "yscale", "field": "percent"},
|
||||||
|
"y2": {"scale": "yscale", "value": 0}
|
||||||
|
},
|
||||||
|
"update": {
|
||||||
|
"fill": {"value": "steelblue"}
|
||||||
|
},
|
||||||
|
"hover": {
|
||||||
|
"fill": {"value": "red"}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"type": "text",
|
||||||
|
"encode": {
|
||||||
|
"enter": {
|
||||||
|
"align": {"value": "center"},
|
||||||
|
"baseline": {"value": "bottom"},
|
||||||
|
"fill": {"value": "#333"}
|
||||||
|
},
|
||||||
|
"update": {
|
||||||
|
"x": {"scale": "xscale", "signal": "tooltip.name", "band": 0.5},
|
||||||
|
"y": {"scale": "yscale", "signal": "tooltip.percent", "offset": -2},
|
||||||
|
"text": {"signal": "tooltip.percent"},
|
||||||
|
"fillOpacity": [
|
||||||
|
{"test": "datum === tooltip", "value": 0},
|
||||||
|
{"value": 1}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
with open('static/exchange-treemap.vg.json', 'w') as treemapPlot:
|
||||||
|
json.dump(vegaJson, treemapPlot, ensure_ascii=False, indent=4, sort_keys=False)
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
@ -0,0 +1,100 @@
|
||||||
|
{
|
||||||
|
"$schema": "https://vega.github.io/schema/vega/v5.json",
|
||||||
|
"description": "A basic bar chart example, with value labels shown upon mouse hover.",
|
||||||
|
"width": 400,
|
||||||
|
"height": 200,
|
||||||
|
"padding": 5,
|
||||||
|
|
||||||
|
"data": [
|
||||||
|
{
|
||||||
|
"name": "table",
|
||||||
|
"values": [
|
||||||
|
{
|
||||||
|
"category": "Status.im",
|
||||||
|
"amount": 46.520569484242756
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"category": "Exchanges",
|
||||||
|
"amount": 32.04532180329212
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"category": "Community",
|
||||||
|
"amount": 21.434108712465125
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
|
||||||
|
"signals": [
|
||||||
|
{
|
||||||
|
"name": "tooltip",
|
||||||
|
"value": {},
|
||||||
|
"on": [
|
||||||
|
{"events": "rect:mouseover", "update": "datum"},
|
||||||
|
{"events": "rect:mouseout", "update": "{}"}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
|
||||||
|
"scales": [
|
||||||
|
{
|
||||||
|
"name": "xscale",
|
||||||
|
"type": "band",
|
||||||
|
"domain": {"data": "table", "field": "category"},
|
||||||
|
"range": "width",
|
||||||
|
"padding": 0.05,
|
||||||
|
"round": true
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "yscale",
|
||||||
|
"domain": {"data": "table", "field": "amount"},
|
||||||
|
"nice": true,
|
||||||
|
"range": "height"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
|
||||||
|
"axes": [
|
||||||
|
{ "orient": "bottom", "scale": "xscale" },
|
||||||
|
{ "orient": "left", "scale": "yscale" }
|
||||||
|
],
|
||||||
|
|
||||||
|
"marks": [
|
||||||
|
{
|
||||||
|
"type": "rect",
|
||||||
|
"from": {"data":"table"},
|
||||||
|
"encode": {
|
||||||
|
"enter": {
|
||||||
|
"x": {"scale": "xscale", "field": "category"},
|
||||||
|
"width": {"scale": "xscale", "band": 1},
|
||||||
|
"y": {"scale": "yscale", "field": "amount"},
|
||||||
|
"y2": {"scale": "yscale", "value": 0}
|
||||||
|
},
|
||||||
|
"update": {
|
||||||
|
"fill": {"value": "steelblue"}
|
||||||
|
},
|
||||||
|
"hover": {
|
||||||
|
"fill": {"value": "red"}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"type": "text",
|
||||||
|
"encode": {
|
||||||
|
"enter": {
|
||||||
|
"align": {"value": "center"},
|
||||||
|
"baseline": {"value": "bottom"},
|
||||||
|
"fill": {"value": "#333"}
|
||||||
|
},
|
||||||
|
"update": {
|
||||||
|
"x": {"scale": "xscale", "signal": "tooltip.category", "band": 0.5},
|
||||||
|
"y": {"scale": "yscale", "signal": "tooltip.amount", "offset": -2},
|
||||||
|
"text": {"signal": "tooltip.amount"},
|
||||||
|
"fillOpacity": [
|
||||||
|
{"test": "datum === tooltip", "value": 0},
|
||||||
|
{"value": 1}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,194 @@
|
||||||
|
{
|
||||||
|
"$schema": "https://vega.github.io/schema/vega/v5.json",
|
||||||
|
"description": "A basic bar chart example, with value labels shown upon mouse hover.",
|
||||||
|
"width": 400,
|
||||||
|
"height": 200,
|
||||||
|
"padding": 5,
|
||||||
|
"data": [
|
||||||
|
{
|
||||||
|
"name": "table",
|
||||||
|
"values": [
|
||||||
|
{
|
||||||
|
"index": 0,
|
||||||
|
"name": "Binance",
|
||||||
|
"balance": 540477233.0112911,
|
||||||
|
"percent": 7.9425061628
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"index": 1,
|
||||||
|
"name": "Bitfinex",
|
||||||
|
"balance": 75644081.8606061,
|
||||||
|
"percent": 1.1116168261
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"index": 2,
|
||||||
|
"name": "Bitrex",
|
||||||
|
"balance": 1066272864.0312135,
|
||||||
|
"percent": 15.6692609356
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"index": 3,
|
||||||
|
"name": "Gate.io",
|
||||||
|
"balance": 108969051.66943823,
|
||||||
|
"percent": 1.6013391713
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"index": 4,
|
||||||
|
"name": "Huobi",
|
||||||
|
"balance": 197336263.422743,
|
||||||
|
"percent": 2.8999269398
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"index": 5,
|
||||||
|
"name": "Kucoin",
|
||||||
|
"balance": 47290553.264842294,
|
||||||
|
"percent": 0.6949515869
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"index": 6,
|
||||||
|
"name": "OKEx",
|
||||||
|
"balance": 122699341.4858642,
|
||||||
|
"percent": 1.8031106889
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"index": 7,
|
||||||
|
"name": "Peatio",
|
||||||
|
"balance": 15296368.661758801,
|
||||||
|
"percent": 0.224785606
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"index": 8,
|
||||||
|
"name": "Poloniex",
|
||||||
|
"balance": 6656788.42817715,
|
||||||
|
"percent": 0.0978238858
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"signals": [
|
||||||
|
{
|
||||||
|
"name": "tooltip",
|
||||||
|
"value": {},
|
||||||
|
"on": [
|
||||||
|
{
|
||||||
|
"events": "rect:mouseover",
|
||||||
|
"update": "datum"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"events": "rect:mouseout",
|
||||||
|
"update": "{}"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"scales": [
|
||||||
|
{
|
||||||
|
"name": "xscale",
|
||||||
|
"type": "band",
|
||||||
|
"domain": {
|
||||||
|
"data": "table",
|
||||||
|
"field": "name"
|
||||||
|
},
|
||||||
|
"range": "width",
|
||||||
|
"padding": 0.05,
|
||||||
|
"round": true
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "yscale",
|
||||||
|
"domain": {
|
||||||
|
"data": "table",
|
||||||
|
"field": "percent"
|
||||||
|
},
|
||||||
|
"nice": true,
|
||||||
|
"range": "height"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"axes": [
|
||||||
|
{
|
||||||
|
"orient": "bottom",
|
||||||
|
"scale": "xscale"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"orient": "left",
|
||||||
|
"scale": "yscale"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"marks": [
|
||||||
|
{
|
||||||
|
"type": "rect",
|
||||||
|
"from": {
|
||||||
|
"data": "table"
|
||||||
|
},
|
||||||
|
"encode": {
|
||||||
|
"enter": {
|
||||||
|
"x": {
|
||||||
|
"scale": "xscale",
|
||||||
|
"field": "name"
|
||||||
|
},
|
||||||
|
"width": {
|
||||||
|
"scale": "xscale",
|
||||||
|
"band": 1
|
||||||
|
},
|
||||||
|
"y": {
|
||||||
|
"scale": "yscale",
|
||||||
|
"field": "percent"
|
||||||
|
},
|
||||||
|
"y2": {
|
||||||
|
"scale": "yscale",
|
||||||
|
"value": 0
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"update": {
|
||||||
|
"fill": {
|
||||||
|
"value": "steelblue"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"hover": {
|
||||||
|
"fill": {
|
||||||
|
"value": "red"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"type": "text",
|
||||||
|
"encode": {
|
||||||
|
"enter": {
|
||||||
|
"align": {
|
||||||
|
"value": "center"
|
||||||
|
},
|
||||||
|
"baseline": {
|
||||||
|
"value": "bottom"
|
||||||
|
},
|
||||||
|
"fill": {
|
||||||
|
"value": "#333"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"update": {
|
||||||
|
"x": {
|
||||||
|
"scale": "xscale",
|
||||||
|
"signal": "tooltip.name",
|
||||||
|
"band": 0.5
|
||||||
|
},
|
||||||
|
"y": {
|
||||||
|
"scale": "yscale",
|
||||||
|
"signal": "tooltip.percent",
|
||||||
|
"offset": -2
|
||||||
|
},
|
||||||
|
"text": {
|
||||||
|
"signal": "tooltip.percent"
|
||||||
|
},
|
||||||
|
"fillOpacity": [
|
||||||
|
{
|
||||||
|
"test": "datum === tooltip",
|
||||||
|
"value": 0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"value": 1
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,88 @@
|
||||||
|
{
|
||||||
|
"$schema": "https://vega.github.io/schema/vega/v5.json",
|
||||||
|
"description": "A basic donut chart example.",
|
||||||
|
"width": 200,
|
||||||
|
"height": 200,
|
||||||
|
"autosize": "none",
|
||||||
|
|
||||||
|
"signals": [
|
||||||
|
{
|
||||||
|
"name": "startAngle", "value": 0,
|
||||||
|
"bind": {"input": "range", "min": 0, "max": 6.29, "step": 0.01}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "endAngle", "value": 6.29,
|
||||||
|
"bind": {"input": "range", "min": 0, "max": 6.29, "step": 0.01}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "padAngle", "value": 0,
|
||||||
|
"bind": {"input": "range", "min": 0, "max": 0.1}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "innerRadius", "value": 60,
|
||||||
|
"bind": {"input": "range", "min": 0, "max": 90, "step": 1}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "cornerRadius", "value": 0,
|
||||||
|
"bind": {"input": "range", "min": 0, "max": 10, "step": 0.5}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "sort", "value": false,
|
||||||
|
"bind": {"input": "checkbox"}
|
||||||
|
}
|
||||||
|
],
|
||||||
|
|
||||||
|
"data": [
|
||||||
|
{
|
||||||
|
"name": "table",
|
||||||
|
"values": [
|
||||||
|
{"id": 1, "field": 4},
|
||||||
|
{"id": 2, "field": 6},
|
||||||
|
{"id": 3, "field": 10},
|
||||||
|
{"id": 4, "field": 3},
|
||||||
|
{"id": 5, "field": 7},
|
||||||
|
{"id": 6, "field": 8}
|
||||||
|
],
|
||||||
|
"transform": [
|
||||||
|
{
|
||||||
|
"type": "pie",
|
||||||
|
"field": "field",
|
||||||
|
"startAngle": {"signal": "startAngle"},
|
||||||
|
"endAngle": {"signal": "endAngle"},
|
||||||
|
"sort": {"signal": "sort"}
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
|
||||||
|
"scales": [
|
||||||
|
{
|
||||||
|
"name": "color",
|
||||||
|
"type": "ordinal",
|
||||||
|
"domain": {"data": "table", "field": "id"},
|
||||||
|
"range": {"scheme": "category20"}
|
||||||
|
}
|
||||||
|
],
|
||||||
|
|
||||||
|
"marks": [
|
||||||
|
{
|
||||||
|
"type": "arc",
|
||||||
|
"from": {"data": "table"},
|
||||||
|
"encode": {
|
||||||
|
"enter": {
|
||||||
|
"fill": {"scale": "color", "field": "id"},
|
||||||
|
"x": {"signal": "width / 2"},
|
||||||
|
"y": {"signal": "height / 2"}
|
||||||
|
},
|
||||||
|
"update": {
|
||||||
|
"startAngle": {"field": "startAngle"},
|
||||||
|
"endAngle": {"field": "endAngle"},
|
||||||
|
"padAngle": {"signal": "padAngle"},
|
||||||
|
"innerRadius": {"signal": "innerRadius"},
|
||||||
|
"outerRadius": {"signal": "width / 2"},
|
||||||
|
"cornerRadius": {"signal": "cornerRadius"}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
Binary file not shown.
|
After Width: | Height: | Size: 8.4 KiB |
|
|
@ -0,0 +1,152 @@
|
||||||
|
{
|
||||||
|
"$schema": "https://vega.github.io/schema/vega/v5.json",
|
||||||
|
"description": "A basic bar chart example, with value labels shown upon mouse hover.",
|
||||||
|
"width": 400,
|
||||||
|
"height": 200,
|
||||||
|
"padding": 5,
|
||||||
|
"data": [
|
||||||
|
{
|
||||||
|
"name": "table",
|
||||||
|
"values": [
|
||||||
|
{
|
||||||
|
"category": "Status",
|
||||||
|
"amount": 46.52
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"category": "Exchanges",
|
||||||
|
"amount": 32.05
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"category": "Community",
|
||||||
|
"amount": 21.43
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"signals": [
|
||||||
|
{
|
||||||
|
"name": "tooltip",
|
||||||
|
"value": {},
|
||||||
|
"on": [
|
||||||
|
{
|
||||||
|
"events": "rect:mouseover",
|
||||||
|
"update": "datum"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"events": "rect:mouseout",
|
||||||
|
"update": "{}"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"scales": [
|
||||||
|
{
|
||||||
|
"name": "xscale",
|
||||||
|
"type": "band",
|
||||||
|
"domain": {
|
||||||
|
"data": "table",
|
||||||
|
"field": "category"
|
||||||
|
},
|
||||||
|
"range": "width",
|
||||||
|
"padding": 0.05,
|
||||||
|
"round": true
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "yscale",
|
||||||
|
"domain": {
|
||||||
|
"data": "table",
|
||||||
|
"field": "amount"
|
||||||
|
},
|
||||||
|
"nice": true,
|
||||||
|
"range": "height"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"axes": [
|
||||||
|
{
|
||||||
|
"orient": "bottom",
|
||||||
|
"scale": "xscale"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"orient": "left",
|
||||||
|
"scale": "yscale"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"marks": [
|
||||||
|
{
|
||||||
|
"type": "rect",
|
||||||
|
"from": {
|
||||||
|
"data": "table"
|
||||||
|
},
|
||||||
|
"encode": {
|
||||||
|
"enter": {
|
||||||
|
"x": {
|
||||||
|
"scale": "xscale",
|
||||||
|
"field": "category"
|
||||||
|
},
|
||||||
|
"width": {
|
||||||
|
"scale": "xscale",
|
||||||
|
"band": 1
|
||||||
|
},
|
||||||
|
"y": {
|
||||||
|
"scale": "yscale",
|
||||||
|
"field": "amount"
|
||||||
|
},
|
||||||
|
"y2": {
|
||||||
|
"scale": "yscale",
|
||||||
|
"value": 0
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"update": {
|
||||||
|
"fill": {
|
||||||
|
"value": "steelblue"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"hover": {
|
||||||
|
"fill": {
|
||||||
|
"value": "red"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"type": "text",
|
||||||
|
"encode": {
|
||||||
|
"enter": {
|
||||||
|
"align": {
|
||||||
|
"value": "center"
|
||||||
|
},
|
||||||
|
"baseline": {
|
||||||
|
"value": "bottom"
|
||||||
|
},
|
||||||
|
"fill": {
|
||||||
|
"value": "#333"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"update": {
|
||||||
|
"x": {
|
||||||
|
"scale": "xscale",
|
||||||
|
"signal": "tooltip.category",
|
||||||
|
"band": 0.5
|
||||||
|
},
|
||||||
|
"y": {
|
||||||
|
"scale": "yscale",
|
||||||
|
"signal": "tooltip.amount",
|
||||||
|
"offset": -2
|
||||||
|
},
|
||||||
|
"text": {
|
||||||
|
"signal": "tooltip.amount"
|
||||||
|
},
|
||||||
|
"fillOpacity": [
|
||||||
|
{
|
||||||
|
"test": "datum === tooltip",
|
||||||
|
"value": 0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"value": 1
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
Loading…
Reference in New Issue