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Collapse and add argparse #18

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c26e02b
Collapse state specific scripts into one script that takes state code…
bcope Oct 6, 2019
0b4845d
Add new line to end of file
bcope Oct 6, 2019
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346 changes: 346 additions & 0 deletions chronam_issue_counts/ISO_3166-2:US.txt
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{
"ISO_3166-2:US": [
{
"code": "US-AL",
"short_code": "AL",
"subdivision_name": "Alabama",
"subdivision_category": "state"
},
{
"code": "US-AK",
"short_code": "AK",
"subdivision_name": "Alaska",
"subdivision_category": "state"
},
{
"code": "US-AZ",
"short_code": "AZ",
"subdivision_name": "Arizona",
"subdivision_category": "state"
},
{
"code": "US-AR",
"short_code": "AR",
"subdivision_name": "Arkansas",
"subdivision_category": "state"
},
{
"code": "US-CA",
"short_code": "CA",
"subdivision_name": "California",
"subdivision_category": "state"
},
{
"code": "US-CO",
"short_code": "CO",
"subdivision_name": "Colorado",
"subdivision_category": "state"
},
{
"code": "US-CT",
"short_code": "CT",
"subdivision_name": "Connecticut",
"subdivision_category": "state"
},
{
"code": "US-DE",
"short_code": "DE",
"subdivision_name": "Delaware",
"subdivision_category": "state"
},
{
"code": "US-FL",
"short_code": "FL",
"subdivision_name": "Florida",
"subdivision_category": "state"
},
{
"code": "US-GA",
"short_code": "GA",
"subdivision_name": "Georgia",
"subdivision_category": "state"
},
{
"code": "US-HI",
"short_code": "HI",
"subdivision_name": "Hawaii",
"subdivision_category": "state"
},
{
"code": "US-ID",
"short_code": "ID",
"subdivision_name": "Idaho",
"subdivision_category": "state"
},
{
"code": "US-IL",
"short_code": "IL",
"subdivision_name": "Illinois",
"subdivision_category": "state"
},
{
"code": "US-IN",
"short_code": "IN",
"subdivision_name": "Indiana",
"subdivision_category": "state"
},
{
"code": "US-IA",
"short_code": "IA",
"subdivision_name": "Iowa",
"subdivision_category": "state"
},
{
"code": "US-KS",
"short_code": "KS",
"subdivision_name": "Kansas",
"subdivision_category": "state"
},
{
"code": "US-KY",
"short_code": "KY",
"subdivision_name": "Kentucky",
"subdivision_category": "state"
},
{
"code": "US-LA",
"short_code": "LA",
"subdivision_name": "Louisiana",
"subdivision_category": "state"
},
{
"code": "US-ME",
"short_code": "ME",
"subdivision_name": "Maine",
"subdivision_category": "state"
},
{
"code": "US-MD",
"short_code": "MD",
"subdivision_name": "Maryland",
"subdivision_category": "state"
},
{
"code": "US-MA",
"short_code": "MA",
"subdivision_name": "Massachusetts",
"subdivision_category": "state"
},
{
"code": "US-MI",
"short_code": "MI",
"subdivision_name": "Michigan",
"subdivision_category": "state"
},
{
"code": "US-MN",
"short_code": "MN",
"subdivision_name": "Minnesota",
"subdivision_category": "state"
},
{
"code": "US-MS",
"short_code": "MS",
"subdivision_name": "Mississippi",
"subdivision_category": "state"
},
{
"code": "US-MO",
"short_code": "MO",
"subdivision_name": "Missouri",
"subdivision_category": "state"
},
{
"code": "US-MT",
"short_code": "MT",
"subdivision_name": "Montana",
"subdivision_category": "state"
},
{
"code": "US-NE",
"short_code": "NE",
"subdivision_name": "Nebraska",
"subdivision_category": "state"
},
{
"code": "US-NV",
"short_code": "NV",
"subdivision_name": "Nevada",
"subdivision_category": "state"
},
{
"code": "US-NH",
"short_code": "NH",
"subdivision_name": "New Hampshire",
"subdivision_category": "state"
},
{
"code": "US-NJ",
"short_code": "NJ",
"subdivision_name": "New Jersey",
"subdivision_category": "state"
},
{
"code": "US-NM",
"short_code": "NM",
"subdivision_name": "New Mexico",
"subdivision_category": "state"
},
{
"code": "US-NY",
"short_code": "NY",
"subdivision_name": "New York",
"subdivision_category": "state"
},
{
"code": "US-NC",
"short_code": "NC",
"subdivision_name": "North Carolina",
"subdivision_category": "state"
},
{
"code": "US-ND",
"short_code": "ND",
"subdivision_name": "North Dakota",
"subdivision_category": "state"
},
{
"code": "US-OH",
"short_code": "OH",
"subdivision_name": "Ohio",
"subdivision_category": "state"
},
{
"code": "US-OK",
"short_code": "OK",
"subdivision_name": "Oklahoma",
"subdivision_category": "state"
},
{
"code": "US-OR",
"short_code": "OR",
"subdivision_name": "Oregon",
"subdivision_category": "state"
},
{
"code": "US-PA",
"short_code": "PA",
"subdivision_name": "Pennsylvania",
"subdivision_category": "state"
},
{
"code": "US-RI",
"short_code": "RI",
"subdivision_name": "Rhode Island",
"subdivision_category": "state"
},
{
"code": "US-SC",
"short_code": "SC",
"subdivision_name": "South Carolina",
"subdivision_category": "state"
},
{
"code": "US-SD",
"short_code": "SD",
"subdivision_name": "South Dakota",
"subdivision_category": "state"
},
{
"code": "US-TN",
"short_code": "TN",
"subdivision_name": "Tennessee",
"subdivision_category": "state"
},
{
"code": "US-TX",
"short_code": "TX",
"subdivision_name": "Texas",
"subdivision_category": "state"
},
{
"code": "US-UT",
"short_code": "UT",
"subdivision_name": "Utah",
"subdivision_category": "state"
},
{
"code": "US-VT",
"short_code": "VT",
"subdivision_name": "Vermont",
"subdivision_category": "state"
},
{
"code": "US-VA",
"short_code": "VA",
"subdivision_name": "Virginia",
"subdivision_category": "state"
},
{
"code": "US-WA",
"short_code": "WA",
"subdivision_name": "Washington",
"subdivision_category": "state"
},
{
"code": "US-WV",
"short_code": "WV",
"subdivision_name": "West Virginia",
"subdivision_category": "state"
},
{
"code": "US-WI",
"short_code": "WI",
"subdivision_name": "Wisconsin",
"subdivision_category": "state"
},
{
"code": "US-WY",
"short_code": "WY",
"subdivision_name": "Wyoming",
"subdivision_category": "state"
},
{
"code": "US-DC",
"short_code": "DC",
"subdivision_name": "District of Columbia",
"subdivision_category": "district"
},
{
"code": "US-AS",
"short_code": "AS",
"subdivision_name": "American Samoa",
"subdivision_category": "outlying area"
},
{
"code": "US-GU",
"short_code": "GU",
"subdivision_name": "Guam",
"subdivision_category": "outlying area"
},
{
"code": "US-MP",
"short_code": "MP",
"subdivision_name": "Northern Mariana Islands",
"subdivision_category": "outlying area"
},
{
"code": "US-PR",
"short_code": "PR",
"subdivision_name": "Puerto Rico",
"subdivision_category": "outlying area"
},
{
"code": "US-UM",
"short_code": "UM",
"subdivision_name": "United States Minor Outlying Islands",
"subdivision_category": "outlying area"
},
{
"code": "US-VI",
"short_code": "VI",
"subdivision_name": "Virgin Islands, U.S.",
"subdivision_category": "outlying area"
}
]
}
25 changes: 13 additions & 12 deletions chronam_issue_counts/README.md
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<h1>Overview</h1>
<p>The scripts available here will calculate the number of digitized newspaper issues available year by year, state by state in Chronicling America, the Library of Congress’ database of historic American newspapers.</p>
<p>Each script is named “state_issues_year_2019_[state_abbreviation]” and will create a .csv file of the number of digitized issues available in Chronicling America for each year of digitized content from state partners that is available.</p>
<p>The scripts available here will calculate the number of digitized newspaper issues available year by year, state by state in Chronicling America, the Library of Congress’ database of historic American newspapers.</p>
<p>The primary script is named "state_issues.py" and will create a .csv file of the number of digitized issues available in Chronicling America for each year of digitized content from state partners that is available.</p>
<p>Please visit https://chroniclingamerica.loc.gov/about/api/ for background information about the various views of data available from Chronicling America.</p>

<h1>Output</h1>
<b>state_issues_year_2019_DC.py or other files with state/territory abbreviations</b>
<p>The output from this script is one .csv file named "District of Columbia_total.csv". Each row in the .csv contains the state name, year, and number of issues available in Chronicling America.</p>
<b>state_issues_year_2019_NOSTATE</b>
<p>Use find and replace for "STATE_NAME" with the state or territory name you want the script run for. The output from this script is one .csv file named "STATE_NAME_total.csv". Each row in the .csv contains the state name, year, and number of issues available in Chronicling America.</p>
<b>state_issues.py</b>
<p>The output from this script is one .csv file named "[state name]_total.csv". Each row in the .csv contains the state name, year, and number of issues available in Chronicling America.</p>

<h1>Dependencies</h1>
<p>To run this script, you'll need to have Python 3 installed. You will also need access to a command line interface such as Terminal on OS X, Anaconda on Windows, or other.</p>
<p>To run this script, you'll need to have Python 3 installed and the requests library downloaded. You will also need access to a command line interface such as Terminal on OS X, Anaconda on Windows, or other.</p>

<h1>Instructions</h1>
<p>Save the "state_issues_year_2019_[state_abbreviation]" file to a folder where you want the results file saved. Using the command line interface, navigate to the folder.</p>
<p>Save the "state_issues.py" and "ISO_3166-2:US.txt" files to a folder where you want the results file saved. Using the command line interface, navigate to the folder.</p>

<p>Run the script by typing: "python state_issues_year_2019_[state_abbreviation]"</p>
<p>Ex: python state_issues_year_2019_DC.py</p>
<p>Run the script by typing: <code>python state_issues.py [two letter state code or full state name]</code></p>
<p>Ex: <code>python state_issues.py TN</code></p>
<p>Ex: <code>python state_issues.py Tennessee</code></p>
<p>State names with multiple words should be wrapped in quotes.</p>
<p>Ex: <code>python state_issues.py "District of Columbia"</code></p>
<p>There is no indication printed to the console that the script is running. When the script is complete, "done" will be printed to the console.</p>
<p>Optionally, input validation can be skipped by adding the force flag.</p>
<p>Ex: <code>python state_issues.py Piedmont --force</code></p>

<h1>Customizations</h1>
<p>The scripts can be changed to run for any state. The template file is state_issues_year_2019_NOSTATE.py. To change the states issues being counted, use find for "NO STATE" and replace for the state or territory name you would like the script run on. There is an issue count script for each state and territory available in Chronicling America as of May 2019. As additional content from new state partners is added to Chronicling America, the state_issues_year_2019_NOSTATE.py file can be updated to add the state information by using find "STATE_NAME" and replace with the state/territory you would like to add.</p>

<h1>Implementation</h1>
<p>We used this script to pull data from Chronicling America to create data visualizations available at http://www.loc.gov/ndnp/data-visualizations/.</p>
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1 change: 1 addition & 0 deletions chronam_issue_counts/requirements.txt
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requests
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