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    <title>Reproducible Journalism</title>
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      <title>Mapping Sinclair Broadcast&#39;s reach</title>
      <link>/posts/2018-07-17-sf-sinclair-map/map/</link>
      <pubDate>Wed, 18 Jul 2018 21:13:14 -0500</pubDate>
      
      <guid>/posts/2018-07-17-sf-sinclair-map/map/</guid>
      <description>We’re going to recreate the graphic from The Washington Post story: As big chains gobble up small TV stations, merged newsrooms are creating a uniformity of news coverage.
 The work was done by graphics editor Chris Alcantara, who used a mix of R, Excel, QGIS, and Illustrator to create this map.
We’re going to try to stick to R exclusively with the help of some packages like jsonlite, tigris, dplyr, ggplot2, sf, ggrepel, and shadowtext.</description>
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      <title>How to copy and paste data into RStudio</title>
      <link>/posts/2018-06-07-datapasta/datapasta/</link>
      <pubDate>Thu, 07 Jun 2018 21:13:14 -0500</pubDate>
      
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      <description>Getting data into R can be quite difficult if it doesn’t come in a pre-made format.
I’m talking specifically about data in tables on websites, but this also applies to Excel spreadsheets with odd formatting structures or on PDFs.
Being a disciplined documenter of the process requires that all the steps taken to scrape data from a website or to import data from Excel or a PDF be clearly listed step by step, as well as what it took to transform the data workable dataframe.</description>
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    <item>
      <title>Recreating Quartz charts</title>
      <link>/posts/2018-06-07-hamilton-data/hamilton/</link>
      <pubDate>Thu, 07 Jun 2018 21:13:14 -0500</pubDate>
      
      <guid>/posts/2018-06-07-hamilton-data/hamilton/</guid>
      <description>Visualizing Hamilton and musicals data Let’s play around with this data set from the Quartz article about race in musicals and plays on Broadway.
Bring in the data.
broadway &amp;lt;- read.csv(&amp;quot;data/broadway.csv&amp;quot;, stringsAsFactors=F) Let’s see if we can replicate this chart.
Quarts chart 1
 We’ll use ggplot2, dplyr, and the scales package.
library(ggplot2) library(scales) library(dplyr) ## ## Attaching package: &amp;#39;dplyr&amp;#39; ## The following objects are masked from &amp;#39;package:stats&amp;#39;: ## ## filter, lag ## The following objects are masked from &amp;#39;package:base&amp;#39;: ## ## intersect, setdiff, setequal, union library(forcats) ggplot(broadway, aes(x=year, y=actors, fill=ethnicity)) + geom_bar(position=&amp;quot;fill&amp;quot;, stat=&amp;quot;identity&amp;quot;) + scale_y_continuous(labels=percent_format()) Close.</description>
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      <title>Investigating crime stats</title>
      <link>/posts/2018-06-07-crime-data/homicides/</link>
      <pubDate>Sun, 29 Jan 2017 21:13:14 -0500</pubDate>
      
      <guid>/posts/2018-06-07-crime-data/homicides/</guid>
      <description>Importing different data sets, calculations
Goal: Dealing with Excel files, analyzing data, adjusting for population.
Donald Trump promised to save America from the hellish wave of crime and disorder in his inaugural address.
“The crime and the gangs and the drugs that have stolen too many lives and robbed our country of so much unrealized potential,” said President Trump. “This American carnage stops right here and stops right now.</description>
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    <item>
      <title>The Problem We All Live With</title>
      <link>/posts/2018-06-07-schools-disparity/schools-disparity/</link>
      <pubDate>Sat, 28 Jan 2017 21:13:14 -0500</pubDate>
      
      <guid>/posts/2018-06-07-schools-disparity/schools-disparity/</guid>
      <description>Case Study Exploration This analysis is meant to accompany the story The Problem We All Live With from episode 562 of This American Life.
We’ll be exploring the test score gaps between black and white students and their relationship with socioeconomic factors such as income and population. The data used in this analysis comes from the Stanford Education Data Archive.
 Downloading and loading the data #if(!</description>
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