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Copy file name to clipboardExpand all lines: _posts/2016-12-11-r-geojson-srt.md
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@@ -56,7 +56,7 @@ The first thing you can do is plot the data, and the `plot` command makes that e
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plot(data_json)
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{% endhighlight %}
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Unfortunately, this plot is not very helpful because it simply plots the points without any context. So we use the `ggmap` and `ggplot2` package to give us some context. First, we download from Google the right map.
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print(mapImage + geom_point(aes(lon, lat), data = data_df))
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{% endhighlight %}
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It may be helpful to add labels based on the name of the location, given in the 'title' field:
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Copy file name to clipboardExpand all lines: _posts/2016-12-16-r-geojson-gardens.md
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plot(data_park)
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{% endhighlight %}
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While this was easy to do, it doesn't give very much context. However, it does give the boundaries of the different parks. As before, we use the `ggmap` and `ggplot2` package to give us some context. First, we download from Google the right map.
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colour = "green"))
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{% endhighlight %}
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Note the use of the `group=` option in the `geom_polygon` function above. This tells `geom_polygon` that there are many polygons rather than just one. Without that option, you get a big mess:
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print(mapImage + geom_polygon(aes(long, lat), data = data_park_df, colour = "green"))
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{% endhighlight %}
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## Mashup of parking convenient to Swamp Rabbit Trail and city parks
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Next, we use the layering feature of `ggplot2` to draw the map:
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Then we can do this analysis within each speech to find out what distinguishes them from other speeches. The `for` loop below can be used to print multiple pages of faceted graphs, good for when you are using RStudio or the R gui to explore.
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}
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{% endhighlight %}
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It's pretty interesting that Speech 26 is unlike nearly all the others. This was William Henry Harrison discussing something about the Roman aristocracy, something other presidents have not felt the need to do very much.
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{% highlight text %}
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## [1] Cluster 1
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## [1]government people citizens time country nation
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## [7]own <NA> <NA> <NA> <NA> <NA>
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## [1] people government country owncitizens time
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## [7]nation <NA> <NA> <NA> <NA> <NA>
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## [13] <NA> <NA> <NA> <NA> <NA> <NA>
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## [19] <NA> <NA>
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## [1] Cluster 2
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## [1] government people citizens countryown nation
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## [7]time <NA> <NA> <NA> <NA> <NA>
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## [1] government people citizens timecountry nation
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## [7]own <NA> <NA> <NA> <NA> <NA>
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## [13] <NA> <NA> <NA> <NA> <NA> <NA>
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## [19] <NA> <NA>
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## [1] Cluster 3
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## [13] <NA> <NA> <NA> <NA> <NA> <NA>
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## [19] <NA> <NA>
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## [1] Cluster 5
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## [1] people government country own citizens time
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## [7]nation <NA> <NA> <NA> <NA> <NA>
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## [1]government people citizens country own nation
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