diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..82f7da1
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,2 @@
+local
+node_modules
diff --git a/README.md b/README.md
index d817de8..5204362 100644
--- a/README.md
+++ b/README.md
@@ -1,2 +1,30 @@
 # open-data-portal
 Publishing data of civic interest that may not be available elsewhere
+
+## Scripts To Get And Clean Data
+Scripts contained in the scripts folder provide some code to clean Government Employees Demographic data that is downloaded from the data.Nashville.gov.  Because the scripts are written in javascript, and intended to be run in a nodejs environment, if you want to run the scripts, be sure to install the needed packages using the following command:
+
+<code>npm install</code>
+
+### get-data.js
+To execute the get-data script, change to the scripts directory, and use the following
+command:
+
+<code>cd scripts</code>
+
+<code>node clean-data.js --outputFile=test.csv</code>
+
+Where <code>--outputFile</code> is set equal to a file name that will be created in the
+local directory for use by the clean-data script.  There is an optional parameter
+<code>--url=</code> that can be used to specify the url of the api, if not specified
+the code will use the default value of https://data.nashville.gov/resource/4ibi-mxs4.csv
+
+### clean-data.js
+To execute the clean-data script, change to the scripts directors, and use the following command:
+
+<code>cd scripts</code>
+
+<code>node clean-data.js --templateFile=2020-08.csv
+--downloadedFile=General_Government_Employees_Demographics.csv --outputFile=2021-01.csv</code>
+
+Where <code>--templateFile=</code> is set equal to an already cleaned data file from the past that the script can use as a template; <code>--downloadedFile=</code> is set equal to the name of the file downloaded from data.nashville.gov (note: the script expects this file to be saved in the <code>../local</code> directory); and the <code>--outputFile=</code> is set equal to the name of the file that should be created to be stored in this open data portal.
diff --git a/package-lock.json b/package-lock.json
new file mode 100644
index 0000000..402a094
--- /dev/null
+++ b/package-lock.json
@@ -0,0 +1,477 @@
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+}
diff --git a/package.json b/package.json
new file mode 100644
index 0000000..083ce8f
--- /dev/null
+++ b/package.json
@@ -0,0 +1,16 @@
+{
+  "name": "open-data-portal",
+  "version": "1.0.0",
+  "description": "Publishing data of civic interest that may not be available elsewhere",
+  "main": "./scripts/main.js",
+  "scripts": {
+    "test": "test"
+  },
+  "author": "",
+  "license": "ISC",
+  "dependencies": {
+    "data-forge": "^1.8.15",
+    "data-forge-fs": "0.0.9",
+    "request": "^2.88.2"
+  }
+}
diff --git a/scripts/clean-data.js b/scripts/clean-data.js
new file mode 100644
index 0000000..02ef836
--- /dev/null
+++ b/scripts/clean-data.js
@@ -0,0 +1,131 @@
+// 
+// example useage from the command prompt:
+// node clean-data.js --templateFile=2020-08.csv --downloadedFile=General_Government_Employees_Demographics.csv --outputFile=2021-01.csv
+// 
+const df = require('data-forge');
+require('data-forge-fs');
+const hf = require('./helperFunctions.js');
+
+let args = require('minimist')(process.argv.slice(2));
+
+const destPath = '../nashville/metro-general-government-employees-demographic-data/renamed-csv/';
+const templateFile = args['templateFile'];
+
+const originPath = '../local/';
+const newFile = args['downloadedFile'];
+const outFileName = args['outputFile'];
+
+// load some existing data to use as a template
+//
+let currentData = hf.getFile(destPath + templateFile);
+console.log('Previous data file loaded, to use as template ...');
+                
+// extract the job categories with their codes into a new data frame
+// these are the job categories that exist in the current data
+// and add a category of 'Unknown'
+// 
+let jobCategories = hf.getCategory(currentData, 'EEO Job Category', 'EEO Job Category Description')
+                        .concat(new df.DataFrame([{
+                            'EEO Job Category': '99',
+                            'EEO Job Category Description': 'Unknown'
+                        }]));
+console.log('\nJob categories: \n', jobCategories.toCSV());
+
+// extract the ethnicities along wiht their ethnic codes into a new data frame
+// these are the ethnic codes that exist in the current data
+// 
+let ethnicCategories = hf.getCategory(currentData, 'Ethnic Code', 'Ethnic Code Description');
+console.log('\nEthnic categories: \n', ethnicCategories.toCSV());
+
+// load the new data
+// and replace any missing ethnic descriptions with 'Two or More Races'
+// and replace any missing job descriptions with 'Unknown'
+//
+let newData = hf.getFile(originPath + newFile)
+                .select(row => {
+                    if (row['Ethnic Code Description'].trim() === '' || row['Ethnic Code Description'] === null) {
+                        row['Ethnic Code Description'] = 'Two or More Races';
+                    };
+
+                    if (row['EEO Job Category Description'].trim() === '' || row['EEO Job Category Description'] === null) {
+                        row['EEO Job Category Description'] = 'Unknown'
+                    };
+
+                    return row;
+                });
+// join jobCategories and ethnicCategories to the newly loaded data
+// to make sure the job codes, and ethnic codes are consistent with
+// previous data.
+//
+let combined = newData
+    .join(
+        jobCategories,
+        left => left["EEO Job Category Description"],
+        right => right["EEO Job Category Description"],
+        (left, right) => {
+            return {
+                'Pay Grade / Step': left['Pay Grade / Step'],
+                'Annual Salary': left['Annual Salary'],
+                'Class': left['Class'],
+                'Title': left['Title'],
+                'Current Department': left['Current Department'],
+                'Employment Status': left['Employment Status'],
+                'EEO Job Category': right['EEO Job Category'],
+                'EEO Job Category Description': left['EEO Job Category Description'],
+                'Gender': left['Gender'],
+                'Ethnic Code Description': left['Ethnic Code Description'],
+                'Year of Birth': left['Year of Birth'],
+                'Date Started': left['Date Started'],
+                'FLSA Exempt?': left['FLSA Exempt?'],
+                'County': left['County']
+            }
+        }
+    )
+    .join(
+        ethnicCategories,
+        left => left["Ethnic Code Description"],
+        right => right["Ethnic Code Description"],
+        (left, right) => {
+            return {
+                'Pay Grade / Step': left['Pay Grade / Step'],
+                'Annual Salary': left['Annual Salary'],
+                'Class': left['Class'],
+                'Title': left['Title'],
+                'Current Department': left['Current Department'],
+                'Employment Status': left['Employment Status'],
+                'EEO Job Category': left['EEO Job Category'],
+                'EEO Job Category Description': left['EEO Job Category Description'],
+                'Gender': left['Gender'],
+                'Ethnic Code': right['Ethnic Code'],
+                'Ethnic Code Description': left['Ethnic Code Description'],
+                'Year of Birth': left['Year of Birth'],
+                'Date Started': left['Date Started'],
+                'FLSA Exempt?': left['FLSA Exempt?'],
+                'County': left['County']
+            }
+        }
+    );
+
+// check if the columns in the template data and the newly loaded and
+// adjusted data, are the same and in the same order.
+// if they are, then write the new file to renamed-csv folder
+// if they are not, then display some information about the columns, and 
+// exit the application.
+//
+if (currentData.getColumnNames().every((v, i) => v === combined.getColumnNames()[i])) {
+    console.log('\nCols in new data match all cols in current data.');
+    console.log('new, num rows: ', newData.count());
+    console.log('combined, new rows: ', combined.count());
+
+    combined.asCSV().writeFileSync(destPath + outFileName);
+    console.log('\nNew file ', outFileName, ' written to ', destPath, ' directory\n');
+} else {
+    console.log("Cols in current data: ",currentData.getColumnNames());
+    console.log("Cols in new combined data: ", combined.getColumnNames());
+
+    console.log('current, num cols: ', currentData.getColumnNames().length);
+    console.log('combined, num cols: ', combined.getColumnNames().length);
+    console.log(combined.head(10).toStrings("Date Started", "MM/DD/YYYY").toCSV());
+
+    process.exitCode = 1;
+}
diff --git a/scripts/get-data.js b/scripts/get-data.js
new file mode 100644
index 0000000..1244f96
--- /dev/null
+++ b/scripts/get-data.js
@@ -0,0 +1,59 @@
+// 
+// This script loads the government employees data from the data.nashville.gov
+// open data portal, and saves the results as a local csv file.
+// 
+// example useage from the command prompt:
+// node get-data.js --outputFile=test.csv
+//    or
+// node get-data.js --outputFile=test.csv --url=https://data.nashville.gov/resource/4ibi-mxs4.csv
+// url paramater is optional, the default value is https://data.nashville.gov/resource/4ibi-mxs4.csv
+//
+var request = require('request');
+var fs = require('fs');
+
+let args = require('minimist')(process.argv.slice(2));
+
+const apiUrl = args['url'] || 'https://data.nashville.gov/resource/4ibi-mxs4.csv';
+const destPath = '../local/';
+const outputFile = args['outputFile']
+
+const options = {
+  'method': 'GET',
+  'url': apiUrl,
+  'headers': {
+  }
+};
+request(options, function (error, response) {
+  if (error) throw new Error(error);
+  let lines = response.body.split("\n");
+  // previous files were downloaded as excel workbooks, and those
+  // had sligtly different column titles.
+  // the below object is used to translate the titles provided by the api
+  // into the same titles as were previously used for the excel versions
+  // of the files.
+  //
+  const titleTranslate = {
+    "pay_grade_step": "Pay Grade / Step",
+    "annual_salary": "Annual Salary",
+    "class": "Class",
+    "title": "Title",
+    "current_dept_description": "Current Department",
+    "employment_status": "Employment Status",
+    "eeo_job_cat_desc": "EEO Job Category Description",
+    "gender": "Gender",
+    "ethnic_code_description": "Ethnic Code Description",
+    "year_of_birth": "Year of Birth",
+    "date_started": "Date Started",
+    "flsa_exempt_y_n": "FLSA Exempt?",
+    "county": "County"
+  };
+
+  for (const apiTitle in titleTranslate) {
+    lines[0] = lines[0].replace(apiTitle, titleTranslate[apiTitle]);
+  };
+
+  const result = lines.join('\n');
+
+  fs.writeFileSync(destPath + outputFile, result);
+  console.log(`File ${destPath + outputFile} written.`);
+});
diff --git a/scripts/helperFunctions.js b/scripts/helperFunctions.js
new file mode 100644
index 0000000..7aea49c
--- /dev/null
+++ b/scripts/helperFunctions.js
@@ -0,0 +1,20 @@
+const df = require('data-forge');
+require('data-forge-fs');
+
+exports.getFile = function getFile(filename) {
+    return result = df.readFileSync(filename)
+                        .parseCSV();
+};
+
+exports.getCategory = function getCategory(data, categoryIdColumn, categoryDescColumn) {
+    return data
+            .groupBy(row => row[categoryIdColumn])
+            .select(group => {
+                return {
+                    [categoryIdColumn]: group.first()[categoryIdColumn],
+                    [categoryDescColumn]: group.deflate(row => row[categoryDescColumn]).first()
+                };
+            })
+            .orderBy(row => row[categoryIdColumn])
+            .inflate();
+};