added raw files and processed population

.gitattributes

@@ -16,7 +16,7 @@
 *.npz filter=lfs diff=lfs merge=lfs -text
 *.onnx filter=lfs diff=lfs merge=lfs -text
 *.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
+# *.parquet filter=lfs diff=lfs merge=lfs -text
 *.pb filter=lfs diff=lfs merge=lfs -text
 *.pickle filter=lfs diff=lfs merge=lfs -text
 *.pkl filter=lfs diff=lfs merge=lfs -text
@@ -31,7 +31,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.tgz filter=lfs diff=lfs merge=lfs -text
 *.wasm filter=lfs diff=lfs merge=lfs -text
 *.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
+# *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 # Audio files - uncompressed

.gitignore

@@ -0,0 +1,163 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# Mac
+.DS_Store

01_Data/01_Raw/county_fips.csv

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01_Data/01_Raw/state_abbreviations.csv

@@ -0,0 +1,52 @@
+"state","abbrev","code"
+"Alabama","Ala.","AL"
+"Alaska","Alaska","AK"
+"Arizona","Ariz.","AZ"
+"Arkansas","Ark.","AR"
+"California","Calif.","CA"
+"Colorado","Colo.","CO"
+"Connecticut","Conn.","CT"
+"Delaware","Del.","DE"
+"District of Columbia","D.C.","DC"
+"Florida","Fla.","FL"
+"Georgia","Ga.","GA"
+"Hawaii","Hawaii","HI"
+"Idaho","Idaho","ID"
+"Illinois","Ill.","IL"
+"Indiana","Ind.","IN"
+"Iowa","Iowa","IA"
+"Kansas","Kans.","KS"
+"Kentucky","Ky.","KY"
+"Louisiana","La.","LA"
+"Maine","Maine","ME"
+"Maryland","Md.","MD"
+"Massachusetts","Mass.","MA"
+"Michigan","Mich.","MI"
+"Minnesota","Minn.","MN"
+"Mississippi","Miss.","MS"
+"Missouri","Mo.","MO"
+"Montana","Mont.","MT"
+"Nebraska","Nebr.","NE"
+"Nevada","Nev.","NV"
+"New Hampshire","N.H.","NH"
+"New Jersey","N.J.","NJ"
+"New Mexico","N.M.","NM"
+"New York","N.Y.","NY"
+"North Carolina","N.C.","NC"
+"North Dakota","N.D.","ND"
+"Ohio","Ohio","OH"
+"Oklahoma","Okla.","OK"
+"Oregon","Ore.","OR"
+"Pennsylvania","Pa.","PA"
+"Rhode Island","R.I.","RI"
+"South Carolina","S.C.","SC"
+"South Dakota","S.D.","SD"
+"Tennessee","Tenn.","TN"
+"Texas","Tex.","TX"
+"Utah","Utah","UT"
+"Vermont","Vt.","VT"
+"Virginia","Va.","VA"
+"Washington","Wash.","WA"
+"West Virginia","W.Va.","WV"
+"Wisconsin","Wis.","WI"
+"Wyoming","Wyo.","WY"

02_Codes/01_population_eda.ipynb

@@ -0,0 +1,2263 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Importing required packages\n",
+    "import pandas as pd\n",
+    "\n",
+    "# setting default option\n",
+    "pd.set_option(\"mode.copy_on_write\", True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Notes</th>\n",
+       "      <th>State</th>\n",
+       "      <th>State Code</th>\n",
+       "      <th>County</th>\n",
+       "      <th>County Code</th>\n",
+       "      <th>Yearly July 1st Estimates</th>\n",
+       "      <th>Yearly July 1st Estimates Code</th>\n",
+       "      <th>Population</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>13280</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Kentucky</td>\n",
+       "      <td>21.0</td>\n",
+       "      <td>Christian County, KY</td>\n",
+       "      <td>21047.0</td>\n",
+       "      <td>2010.0</td>\n",
+       "      <td>2010.0</td>\n",
+       "      <td>74145</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12354</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Kansas</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>Marion County, KS</td>\n",
+       "      <td>20115.0</td>\n",
+       "      <td>2007.0</td>\n",
+       "      <td>2007.0</td>\n",
+       "      <td>12707</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21061</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Montana</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>Glacier County, MT</td>\n",
+       "      <td>30035.0</td>\n",
+       "      <td>2004.0</td>\n",
+       "      <td>2004.0</td>\n",
+       "      <td>13388</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5447</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Georgia</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>Cherokee County, GA</td>\n",
+       "      <td>13057.0</td>\n",
+       "      <td>2003.0</td>\n",
+       "      <td>2003.0</td>\n",
+       "      <td>165585</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17285</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Minnesota</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>Cass County, MN</td>\n",
+       "      <td>27021.0</td>\n",
+       "      <td>2011.0</td>\n",
+       "      <td>2011.0</td>\n",
+       "      <td>28383</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Notes      State  State Code                County  County Code  \\\n",
+       "13280   NaN   Kentucky        21.0  Christian County, KY      21047.0   \n",
+       "12354   NaN     Kansas        20.0     Marion County, KS      20115.0   \n",
+       "21061   NaN    Montana        30.0    Glacier County, MT      30035.0   \n",
+       "5447    NaN    Georgia        13.0   Cherokee County, GA      13057.0   \n",
+       "17285   NaN  Minnesota        27.0       Cass County, MN      27021.0   \n",
+       "\n",
+       "       Yearly July 1st Estimates  Yearly July 1st Estimates Code Population  \n",
+       "13280                     2010.0                          2010.0      74145  \n",
+       "12354                     2007.0                          2007.0      12707  \n",
+       "21061                     2004.0                          2004.0      13388  \n",
+       "5447                      2003.0                          2003.0     165585  \n",
+       "17285                     2011.0                          2011.0      28383  "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Load Raw Data File\n",
+    "df = pd.read_csv(\"../01_Data/01_Raw/raw_population.txt\", sep=\"\\t\")\n",
+    "df.sample(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 41037 entries, 0 to 41036\n",
+      "Data columns (total 8 columns):\n",
+      " #   Column                          Non-Null Count  Dtype  \n",
+      "---  ------                          --------------  -----  \n",
+      " 0   Notes                           100 non-null    object \n",
+      " 1   State                           40937 non-null  object \n",
+      " 2   State Code                      40937 non-null  float64\n",
+      " 3   County                          40937 non-null  object \n",
+      " 4   County Code                     40937 non-null  float64\n",
+      " 5   Yearly July 1st Estimates       40937 non-null  float64\n",
+      " 6   Yearly July 1st Estimates Code  40937 non-null  float64\n",
+      " 7   Population                      40937 non-null  object \n",
+      "dtypes: float64(4), object(4)\n",
+      "memory usage: 2.5+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Notes</th>\n",
+       "      <th>State</th>\n",
+       "      <th>State Code</th>\n",
+       "      <th>County</th>\n",
+       "      <th>County Code</th>\n",
+       "      <th>Yearly July 1st Estimates</th>\n",
+       "      <th>Yearly July 1st Estimates Code</th>\n",
+       "      <th>Population</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>40937</th>\n",
+       "      <td>---</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40938</th>\n",
+       "      <td>Dataset: Bridged-Race Population Estimates 199...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40939</th>\n",
+       "      <td>Query Parameters:</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40940</th>\n",
+       "      <td>Yearly July 1st Estimates: 2003; 2004; 2005; 2...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40941</th>\n",
+       "      <td>Group By: State; County; Yearly July 1st Estim...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41032</th>\n",
+       "      <td>City are available only for the years prior to...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41033</th>\n",
+       "      <td>1999 and 2000 due to the addition of population.</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41034</th>\n",
+       "      <td>20. South Boston City, Virginia (FIPS code 517...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41035</th>\n",
+       "      <td>June 30, 1995. This change was made retroactiv...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41036</th>\n",
+       "      <td>have been reported with Halifax County since y...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>100 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                   Notes State  State Code  \\\n",
+       "40937                                                ---   NaN         NaN   \n",
+       "40938  Dataset: Bridged-Race Population Estimates 199...   NaN         NaN   \n",
+       "40939                                  Query Parameters:   NaN         NaN   \n",
+       "40940  Yearly July 1st Estimates: 2003; 2004; 2005; 2...   NaN         NaN   \n",
+       "40941  Group By: State; County; Yearly July 1st Estim...   NaN         NaN   \n",
+       "...                                                  ...   ...         ...   \n",
+       "41032  City are available only for the years prior to...   NaN         NaN   \n",
+       "41033   1999 and 2000 due to the addition of population.   NaN         NaN   \n",
+       "41034  20. South Boston City, Virginia (FIPS code 517...   NaN         NaN   \n",
+       "41035  June 30, 1995. This change was made retroactiv...   NaN         NaN   \n",
+       "41036  have been reported with Halifax County since y...   NaN         NaN   \n",
+       "\n",
+       "      County  County Code  Yearly July 1st Estimates  \\\n",
+       "40937    NaN          NaN                        NaN   \n",
+       "40938    NaN          NaN                        NaN   \n",
+       "40939    NaN          NaN                        NaN   \n",
+       "40940    NaN          NaN                        NaN   \n",
+       "40941    NaN          NaN                        NaN   \n",
+       "...      ...          ...                        ...   \n",
+       "41032    NaN          NaN                        NaN   \n",
+       "41033    NaN          NaN                        NaN   \n",
+       "41034    NaN          NaN                        NaN   \n",
+       "41035    NaN          NaN                        NaN   \n",
+       "41036    NaN          NaN                        NaN   \n",
+       "\n",
+       "       Yearly July 1st Estimates Code Population  \n",
+       "40937                             NaN        NaN  \n",
+       "40938                             NaN        NaN  \n",
+       "40939                             NaN        NaN  \n",
+       "40940                             NaN        NaN  \n",
+       "40941                             NaN        NaN  \n",
+       "...                               ...        ...  \n",
+       "41032                             NaN        NaN  \n",
+       "41033                             NaN        NaN  \n",
+       "41034                             NaN        NaN  \n",
+       "41035                             NaN        NaN  \n",
+       "41036                             NaN        NaN  \n",
+       "\n",
+       "[100 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# View the rows which have text values in notes column\n",
+    "df[df[\"Notes\"].notnull()]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# droping notes column\n",
+    "df1 = df.drop(columns=[\"Notes\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# removing the rows with na values generated due to Notes, using state column for reference\n",
+    "df1 = df1.dropna(subset=[\"State\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# dropping alaska\n",
+    "df1 = df1[df1[\"State\"] != \"Alaska\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>State</th>\n",
+       "      <th>State Code</th>\n",
+       "      <th>County</th>\n",
+       "      <th>County Code</th>\n",
+       "      <th>Yearly July 1st Estimates</th>\n",
+       "      <th>Yearly July 1st Estimates Code</th>\n",
+       "      <th>Population</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>22685</th>\n",
+       "      <td>Nebraska</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>Thurston County, NE</td>\n",
+       "      <td>31173.0</td>\n",
+       "      <td>2003.0</td>\n",
+       "      <td>2003.0</td>\n",
+       "      <td>6987</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39888</th>\n",
+       "      <td>Wisconsin</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>Door County, WI</td>\n",
+       "      <td>55029.0</td>\n",
+       "      <td>2007.0</td>\n",
+       "      <td>2007.0</td>\n",
+       "      <td>27957</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4159</th>\n",
+       "      <td>Connecticut</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>Tolland County, CT</td>\n",
+       "      <td>9013.0</td>\n",
+       "      <td>2015.0</td>\n",
+       "      <td>2015.0</td>\n",
+       "      <td>151815</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20889</th>\n",
+       "      <td>Montana</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>Broadwater County, MT</td>\n",
+       "      <td>30007.0</td>\n",
+       "      <td>2014.0</td>\n",
+       "      <td>2014.0</td>\n",
+       "      <td>5657</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36855</th>\n",
+       "      <td>Virginia</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>Bland County, VA</td>\n",
+       "      <td>51021.0</td>\n",
+       "      <td>2003.0</td>\n",
+       "      <td>2003.0</td>\n",
+       "      <td>6913</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             State  State Code                 County  County Code  \\\n",
+       "22685     Nebraska        31.0    Thurston County, NE      31173.0   \n",
+       "39888    Wisconsin        55.0        Door County, WI      55029.0   \n",
+       "4159   Connecticut         9.0     Tolland County, CT       9013.0   \n",
+       "20889      Montana        30.0  Broadwater County, MT      30007.0   \n",
+       "36855     Virginia        51.0       Bland County, VA      51021.0   \n",
+       "\n",
+       "       Yearly July 1st Estimates  Yearly July 1st Estimates Code Population  \n",
+       "22685                     2003.0                          2003.0       6987  \n",
+       "39888                     2007.0                          2007.0      27957  \n",
+       "4159                      2015.0                          2015.0     151815  \n",
+       "20889                     2014.0                          2014.0       5657  \n",
+       "36855                     2003.0                          2003.0       6913  "
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df1.sample(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Index: 40495 entries, 0 to 40936\n",
+      "Data columns (total 7 columns):\n",
+      " #   Column                          Non-Null Count  Dtype  \n",
+      "---  ------                          --------------  -----  \n",
+      " 0   State                           40495 non-null  object \n",
+      " 1   State Code                      40495 non-null  float64\n",
+      " 2   County                          40495 non-null  object \n",
+      " 3   County Code                     40495 non-null  float64\n",
+      " 4   Yearly July 1st Estimates       40495 non-null  float64\n",
+      " 5   Yearly July 1st Estimates Code  40495 non-null  float64\n",
+      " 6   Population                      40495 non-null  object \n",
+      "dtypes: float64(4), object(3)\n",
+      "memory usage: 2.5+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df1.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# validate if yealry estimate and estimate code are same\n",
+    "df1[\"Yearly July 1st Estimates\"].equals(df1[\"Yearly July 1st Estimates Code\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Correcting Data Types\n",
+    "df2 = df1.copy()\n",
+    "\n",
+    "# Saving state code as padded string\n",
+    "df2[\"State Code\"] = df2[\"State Code\"].astype(int).astype(str).str.zfill(2)\n",
+    "\n",
+    "# Saving county code as padded string\n",
+    "df2[\"County Code\"] = df2[\"County Code\"].astype(int).astype(str).str.zfill(5)\n",
+    "\n",
+    "# Converting Year to Integer\n",
+    "df2[\"Yearly July 1st Estimates\"] = df2[\"Yearly July 1st Estimates\"].astype(int)\n",
+    "\n",
+    "# Converting Population to Integer\n",
+    "# replacing the missing values with 0 for now\n",
+    "df2[\"Population\"] = df2[\"Population\"].replace(\"Missing\", 0)\n",
+    "df2[\"Population\"] = df2[\"Population\"].astype(int)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>State</th>\n",
+       "      <th>State Code</th>\n",
+       "      <th>County</th>\n",
+       "      <th>County Code</th>\n",
+       "      <th>Yearly July 1st Estimates</th>\n",
+       "      <th>Yearly July 1st Estimates Code</th>\n",
+       "      <th>Population</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>9811</th>\n",
+       "      <td>Indiana</td>\n",
+       "      <td>18</td>\n",
+       "      <td>Monroe County, IN</td>\n",
+       "      <td>18105</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>2012.0</td>\n",
+       "      <td>141570</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30855</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Brule County, SD</td>\n",
+       "      <td>46015</td>\n",
+       "      <td>2009</td>\n",
+       "      <td>2009.0</td>\n",
+       "      <td>5184</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38764</th>\n",
+       "      <td>Washington</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Lincoln County, WA</td>\n",
+       "      <td>53043</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>2014.0</td>\n",
+       "      <td>10224</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34257</th>\n",
+       "      <td>Texas</td>\n",
+       "      <td>48</td>\n",
+       "      <td>Hidalgo County, TX</td>\n",
+       "      <td>48215</td>\n",
+       "      <td>2005</td>\n",
+       "      <td>2005.0</td>\n",
+       "      <td>674982</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14148</th>\n",
+       "      <td>Kentucky</td>\n",
+       "      <td>21</td>\n",
+       "      <td>Nicholas County, KY</td>\n",
+       "      <td>21181</td>\n",
+       "      <td>2007</td>\n",
+       "      <td>2007.0</td>\n",
+       "      <td>7143</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              State State Code               County County Code  \\\n",
+       "9811        Indiana         18    Monroe County, IN       18105   \n",
+       "30855  South Dakota         46     Brule County, SD       46015   \n",
+       "38764    Washington         53   Lincoln County, WA       53043   \n",
+       "34257         Texas         48   Hidalgo County, TX       48215   \n",
+       "14148      Kentucky         21  Nicholas County, KY       21181   \n",
+       "\n",
+       "       Yearly July 1st Estimates  Yearly July 1st Estimates Code  Population  \n",
+       "9811                        2012                          2012.0      141570  \n",
+       "30855                       2009                          2009.0        5184  \n",
+       "38764                       2014                          2014.0       10224  \n",
+       "34257                       2005                          2005.0      674982  \n",
+       "14148                       2007                          2007.0        7143  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df2.sample(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Index: 40495 entries, 0 to 40936\n",
+      "Data columns (total 7 columns):\n",
+      " #   Column                          Non-Null Count  Dtype  \n",
+      "---  ------                          --------------  -----  \n",
+      " 0   State                           40495 non-null  object \n",
+      " 1   State Code                      40495 non-null  object \n",
+      " 2   County                          40495 non-null  object \n",
+      " 3   County Code                     40495 non-null  object \n",
+      " 4   Yearly July 1st Estimates       40495 non-null  int64  \n",
+      " 5   Yearly July 1st Estimates Code  40495 non-null  float64\n",
+      " 6   Population                      40495 non-null  int64  \n",
+      "dtypes: float64(1), int64(2), object(4)\n",
+      "memory usage: 2.5+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df2.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df3 = df2.copy()\n",
+    "\n",
+    "# rename columns\n",
+    "df3 = df3.rename(\n",
+    "    columns={\n",
+    "        \"Yearly July 1st Estimates\": \"Year\",\n",
+    "        \"State Code\": \"State_Code\",\n",
+    "        \"County Code\": \"County_Code\",\n",
+    "    }\n",
+    ")\n",
+    "\n",
+    "# reorder columns\n",
+    "df3 = df3[\n",
+    "    [\n",
+    "        \"State\",\n",
+    "        \"State_Code\",\n",
+    "        \"County\",\n",
+    "        \"County_Code\",\n",
+    "        \"Year\",\n",
+    "        \"Population\",\n",
+    "    ]\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>State</th>\n",
+       "      <th>State_Code</th>\n",
+       "      <th>County</th>\n",
+       "      <th>County_Code</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Population</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>14210</th>\n",
+       "      <td>Kentucky</td>\n",
+       "      <td>21</td>\n",
+       "      <td>Pendleton County, KY</td>\n",
+       "      <td>21191</td>\n",
+       "      <td>2004</td>\n",
+       "      <td>14809</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30045</th>\n",
+       "      <td>Pennsylvania</td>\n",
+       "      <td>42</td>\n",
+       "      <td>Washington County, PA</td>\n",
+       "      <td>42125</td>\n",
+       "      <td>2005</td>\n",
+       "      <td>205359</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31810</th>\n",
+       "      <td>Tennessee</td>\n",
+       "      <td>47</td>\n",
+       "      <td>Clay County, TN</td>\n",
+       "      <td>47027</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>7668</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25762</th>\n",
+       "      <td>North Carolina</td>\n",
+       "      <td>37</td>\n",
+       "      <td>Swain County, NC</td>\n",
+       "      <td>37173</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>14054</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20357</th>\n",
+       "      <td>Missouri</td>\n",
+       "      <td>29</td>\n",
+       "      <td>Pemiscot County, MO</td>\n",
+       "      <td>29155</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>17427</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                State State_Code                 County County_Code  Year  \\\n",
+       "14210        Kentucky         21   Pendleton County, KY       21191  2004   \n",
+       "30045    Pennsylvania         42  Washington County, PA       42125  2005   \n",
+       "31810       Tennessee         47        Clay County, TN       47027  2015   \n",
+       "25762  North Carolina         37       Swain County, NC       37173  2012   \n",
+       "20357        Missouri         29    Pemiscot County, MO       29155  2015   \n",
+       "\n",
+       "       Population  \n",
+       "14210       14809  \n",
+       "30045      205359  \n",
+       "31810        7668  \n",
+       "25762       14054  \n",
+       "20357       17427  "
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3.sample(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>BUYER_COUNTY</th>\n",
+       "      <th>BUYER_STATE</th>\n",
+       "      <th>countyfips</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1937</th>\n",
+       "      <td>JONES</td>\n",
+       "      <td>NC</td>\n",
+       "      <td>37103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3083</th>\n",
+       "      <td>MARQUETTE</td>\n",
+       "      <td>WI</td>\n",
+       "      <td>55077</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>564</th>\n",
+       "      <td>CLEARWATER</td>\n",
+       "      <td>ID</td>\n",
+       "      <td>16035</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>722</th>\n",
+       "      <td>HANCOCK</td>\n",
+       "      <td>IN</td>\n",
+       "      <td>18059</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1229</th>\n",
+       "      <td>ALLEGAN</td>\n",
+       "      <td>MI</td>\n",
+       "      <td>26005</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     BUYER_COUNTY BUYER_STATE  countyfips\n",
+       "1937        JONES          NC       37103\n",
+       "3083    MARQUETTE          WI       55077\n",
+       "564    CLEARWATER          ID       16035\n",
+       "722       HANCOCK          IN       18059\n",
+       "1229      ALLEGAN          MI       26005"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# maps with fips for proper county names\n",
+    "fips = pd.read_csv(\"../01_Data/01_Raw/county_fips.csv\")\n",
+    "fips.sample(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# padding fips to have consistency\n",
+    "fips[\"countyfips\"] = fips[\"countyfips\"].astype(str).str.zfill(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# performing left join to get the county names\n",
+    "df4 = pd.merge(\n",
+    "    df3,\n",
+    "    fips,\n",
+    "    how=\"left\",\n",
+    "    left_on=\"County_Code\",\n",
+    "    right_on=\"countyfips\",\n",
+    "    validate=\"m:1\",\n",
+    "    indicator=True,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "_merge\n",
+       "both          40456\n",
+       "left_only        39\n",
+       "right_only        0\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# validate match for all rows\n",
+    "df4[\"_merge\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>State</th>\n",
+       "      <th>State_Code</th>\n",
+       "      <th>County</th>\n",
+       "      <th>County_Code</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Population</th>\n",
+       "      <th>BUYER_COUNTY</th>\n",
+       "      <th>BUYER_STATE</th>\n",
+       "      <th>countyfips</th>\n",
+       "      <th>_merge</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1690</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2003</td>\n",
+       "      <td>9239</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1691</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2004</td>\n",
+       "      <td>9334</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1692</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2005</td>\n",
+       "      <td>9358</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1693</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2006</td>\n",
+       "      <td>9437</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1694</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2007</td>\n",
+       "      <td>9478</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1695</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>9573</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1696</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2009</td>\n",
+       "      <td>9490</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1697</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>9515</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1698</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>9404</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1699</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>9344</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1700</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>9254</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1701</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>9163</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1702</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>05</td>\n",
+       "      <td>Montgomery County, AR</td>\n",
+       "      <td>05097</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>9029</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6747</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2003</td>\n",
+       "      <td>127</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6748</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2004</td>\n",
+       "      <td>117</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6749</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2005</td>\n",
+       "      <td>114</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6750</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2006</td>\n",
+       "      <td>109</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6751</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2007</td>\n",
+       "      <td>105</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6752</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>99</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6753</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2009</td>\n",
+       "      <td>93</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6754</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>90</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6755</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>90</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6756</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>89</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6757</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>89</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6758</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>89</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6759</th>\n",
+       "      <td>Hawaii</td>\n",
+       "      <td>15</td>\n",
+       "      <td>Kalawao County, HI</td>\n",
+       "      <td>15005</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>88</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30979</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2003</td>\n",
+       "      <td>12993</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30980</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2004</td>\n",
+       "      <td>12983</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30981</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2005</td>\n",
+       "      <td>13150</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30982</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2006</td>\n",
+       "      <td>13404</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30983</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2007</td>\n",
+       "      <td>13345</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30984</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>13368</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30985</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2009</td>\n",
+       "      <td>13425</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30986</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>13636</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30987</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>13897</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30988</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>14041</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30989</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2013</td>\n",
+       "      <td>14130</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30990</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>14217</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30991</th>\n",
+       "      <td>South Dakota</td>\n",
+       "      <td>46</td>\n",
+       "      <td>Oglala Lakota County, SD</td>\n",
+       "      <td>46102</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>14364</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>left_only</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              State State_Code                    County County_Code  Year  \\\n",
+       "1690       Arkansas         05     Montgomery County, AR       05097  2003   \n",
+       "1691       Arkansas         05     Montgomery County, AR       05097  2004   \n",
+       "1692       Arkansas         05     Montgomery County, AR       05097  2005   \n",
+       "1693       Arkansas         05     Montgomery County, AR       05097  2006   \n",
+       "1694       Arkansas         05     Montgomery County, AR       05097  2007   \n",
+       "1695       Arkansas         05     Montgomery County, AR       05097  2008   \n",
+       "1696       Arkansas         05     Montgomery County, AR       05097  2009   \n",
+       "1697       Arkansas         05     Montgomery County, AR       05097  2010   \n",
+       "1698       Arkansas         05     Montgomery County, AR       05097  2011   \n",
+       "1699       Arkansas         05     Montgomery County, AR       05097  2012   \n",
+       "1700       Arkansas         05     Montgomery County, AR       05097  2013   \n",
+       "1701       Arkansas         05     Montgomery County, AR       05097  2014   \n",
+       "1702       Arkansas         05     Montgomery County, AR       05097  2015   \n",
+       "6747         Hawaii         15        Kalawao County, HI       15005  2003   \n",
+       "6748         Hawaii         15        Kalawao County, HI       15005  2004   \n",
+       "6749         Hawaii         15        Kalawao County, HI       15005  2005   \n",
+       "6750         Hawaii         15        Kalawao County, HI       15005  2006   \n",
+       "6751         Hawaii         15        Kalawao County, HI       15005  2007   \n",
+       "6752         Hawaii         15        Kalawao County, HI       15005  2008   \n",
+       "6753         Hawaii         15        Kalawao County, HI       15005  2009   \n",
+       "6754         Hawaii         15        Kalawao County, HI       15005  2010   \n",
+       "6755         Hawaii         15        Kalawao County, HI       15005  2011   \n",
+       "6756         Hawaii         15        Kalawao County, HI       15005  2012   \n",
+       "6757         Hawaii         15        Kalawao County, HI       15005  2013   \n",
+       "6758         Hawaii         15        Kalawao County, HI       15005  2014   \n",
+       "6759         Hawaii         15        Kalawao County, HI       15005  2015   \n",
+       "30979  South Dakota         46  Oglala Lakota County, SD       46102  2003   \n",
+       "30980  South Dakota         46  Oglala Lakota County, SD       46102  2004   \n",
+       "30981  South Dakota         46  Oglala Lakota County, SD       46102  2005   \n",
+       "30982  South Dakota         46  Oglala Lakota County, SD       46102  2006   \n",
+       "30983  South Dakota         46  Oglala Lakota County, SD       46102  2007   \n",
+       "30984  South Dakota         46  Oglala Lakota County, SD       46102  2008   \n",
+       "30985  South Dakota         46  Oglala Lakota County, SD       46102  2009   \n",
+       "30986  South Dakota         46  Oglala Lakota County, SD       46102  2010   \n",
+       "30987  South Dakota         46  Oglala Lakota County, SD       46102  2011   \n",
+       "30988  South Dakota         46  Oglala Lakota County, SD       46102  2012   \n",
+       "30989  South Dakota         46  Oglala Lakota County, SD       46102  2013   \n",
+       "30990  South Dakota         46  Oglala Lakota County, SD       46102  2014   \n",
+       "30991  South Dakota         46  Oglala Lakota County, SD       46102  2015   \n",
+       "\n",
+       "       Population BUYER_COUNTY BUYER_STATE countyfips     _merge  \n",
+       "1690         9239          NaN         NaN        NaN  left_only  \n",
+       "1691         9334          NaN         NaN        NaN  left_only  \n",
+       "1692         9358          NaN         NaN        NaN  left_only  \n",
+       "1693         9437          NaN         NaN        NaN  left_only  \n",
+       "1694         9478          NaN         NaN        NaN  left_only  \n",
+       "1695         9573          NaN         NaN        NaN  left_only  \n",
+       "1696         9490          NaN         NaN        NaN  left_only  \n",
+       "1697         9515          NaN         NaN        NaN  left_only  \n",
+       "1698         9404          NaN         NaN        NaN  left_only  \n",
+       "1699         9344          NaN         NaN        NaN  left_only  \n",
+       "1700         9254          NaN         NaN        NaN  left_only  \n",
+       "1701         9163          NaN         NaN        NaN  left_only  \n",
+       "1702         9029          NaN         NaN        NaN  left_only  \n",
+       "6747          127          NaN         NaN        NaN  left_only  \n",
+       "6748          117          NaN         NaN        NaN  left_only  \n",
+       "6749          114          NaN         NaN        NaN  left_only  \n",
+       "6750          109          NaN         NaN        NaN  left_only  \n",
+       "6751          105          NaN         NaN        NaN  left_only  \n",
+       "6752           99          NaN         NaN        NaN  left_only  \n",
+       "6753           93          NaN         NaN        NaN  left_only  \n",
+       "6754           90          NaN         NaN        NaN  left_only  \n",
+       "6755           90          NaN         NaN        NaN  left_only  \n",
+       "6756           89          NaN         NaN        NaN  left_only  \n",
+       "6757           89          NaN         NaN        NaN  left_only  \n",
+       "6758           89          NaN         NaN        NaN  left_only  \n",
+       "6759           88          NaN         NaN        NaN  left_only  \n",
+       "30979       12993          NaN         NaN        NaN  left_only  \n",
+       "30980       12983          NaN         NaN        NaN  left_only  \n",
+       "30981       13150          NaN         NaN        NaN  left_only  \n",
+       "30982       13404          NaN         NaN        NaN  left_only  \n",
+       "30983       13345          NaN         NaN        NaN  left_only  \n",
+       "30984       13368          NaN         NaN        NaN  left_only  \n",
+       "30985       13425          NaN         NaN        NaN  left_only  \n",
+       "30986       13636          NaN         NaN        NaN  left_only  \n",
+       "30987       13897          NaN         NaN        NaN  left_only  \n",
+       "30988       14041          NaN         NaN        NaN  left_only  \n",
+       "30989       14130          NaN         NaN        NaN  left_only  \n",
+       "30990       14217          NaN         NaN        NaN  left_only  \n",
+       "30991       14364          NaN         NaN        NaN  left_only  "
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Check for unmatched rows\n",
+    "df4[(df4[\"_merge\"] == \"left_only\")]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['Montgomery County, AR', 'Kalawao County, HI',\n",
+       "       'Oglala Lakota County, SD'], dtype=object)"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df4[(df4[\"_merge\"] == \"left_only\")][\"County\"].unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Manual Correction\n",
+    "df4.loc[df4[\"County\"] == \"Montgomery County, AR\", \"BUYER_COUNTY\"] = \"MONTGOMERY\"\n",
+    "df4.loc[df4[\"County\"] == \"Kalawao County, HI\", \"BUYER_COUNTY\"] = \"KALAWAO\"\n",
+    "df4.loc[df4[\"County\"] == \"Oglala Lakota County, SD\", \"BUYER_COUNTY\"] = \"OGLALA LAKOTA\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>State</th>\n",
+       "      <th>State_Code</th>\n",
+       "      <th>County</th>\n",
+       "      <th>County_Code</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Population</th>\n",
+       "      <th>BUYER_COUNTY</th>\n",
+       "      <th>BUYER_STATE</th>\n",
+       "      <th>countyfips</th>\n",
+       "      <th>_merge</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>13500</th>\n",
+       "      <td>Kentucky</td>\n",
+       "      <td>21</td>\n",
+       "      <td>McLean County, KY</td>\n",
+       "      <td>21149</td>\n",
+       "      <td>2009</td>\n",
+       "      <td>9566</td>\n",
+       "      <td>MCLEAN</td>\n",
+       "      <td>KY</td>\n",
+       "      <td>21149</td>\n",
+       "      <td>both</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28137</th>\n",
+       "      <td>Oklahoma</td>\n",
+       "      <td>40</td>\n",
+       "      <td>Pottawatomie County, OK</td>\n",
+       "      <td>40125</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>68752</td>\n",
+       "      <td>POTTAWATOMIE</td>\n",
+       "      <td>OK</td>\n",
+       "      <td>40125</td>\n",
+       "      <td>both</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26396</th>\n",
+       "      <td>Ohio</td>\n",
+       "      <td>39</td>\n",
+       "      <td>Crawford County, OH</td>\n",
+       "      <td>39033</td>\n",
+       "      <td>2009</td>\n",
+       "      <td>43921</td>\n",
+       "      <td>CRAWFORD</td>\n",
+       "      <td>OH</td>\n",
+       "      <td>39033</td>\n",
+       "      <td>both</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26602</th>\n",
+       "      <td>Ohio</td>\n",
+       "      <td>39</td>\n",
+       "      <td>Hardin County, OH</td>\n",
+       "      <td>39065</td>\n",
+       "      <td>2007</td>\n",
+       "      <td>32132</td>\n",
+       "      <td>HARDIN</td>\n",
+       "      <td>OH</td>\n",
+       "      <td>39065</td>\n",
+       "      <td>both</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20230</th>\n",
+       "      <td>Missouri</td>\n",
+       "      <td>29</td>\n",
+       "      <td>Stoddard County, MO</td>\n",
+       "      <td>29207</td>\n",
+       "      <td>2005</td>\n",
+       "      <td>30240</td>\n",
+       "      <td>STODDARD</td>\n",
+       "      <td>MO</td>\n",
+       "      <td>29207</td>\n",
+       "      <td>both</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          State State_Code                   County County_Code  Year  \\\n",
+       "13500  Kentucky         21        McLean County, KY       21149  2009   \n",
+       "28137  Oklahoma         40  Pottawatomie County, OK       40125  2008   \n",
+       "26396      Ohio         39      Crawford County, OH       39033  2009   \n",
+       "26602      Ohio         39        Hardin County, OH       39065  2007   \n",
+       "20230  Missouri         29      Stoddard County, MO       29207  2005   \n",
+       "\n",
+       "       Population  BUYER_COUNTY BUYER_STATE countyfips _merge  \n",
+       "13500        9566        MCLEAN          KY      21149   both  \n",
+       "28137       68752  POTTAWATOMIE          OK      40125   both  \n",
+       "26396       43921      CRAWFORD          OH      39033   both  \n",
+       "26602       32132        HARDIN          OH      39065   both  \n",
+       "20230       30240      STODDARD          MO      29207   both  "
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df4.sample(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 40495 entries, 0 to 40494\n",
+      "Data columns (total 10 columns):\n",
+      " #   Column        Non-Null Count  Dtype   \n",
+      "---  ------        --------------  -----   \n",
+      " 0   State         40495 non-null  object  \n",
+      " 1   State_Code    40495 non-null  object  \n",
+      " 2   County        40495 non-null  object  \n",
+      " 3   County_Code   40495 non-null  object  \n",
+      " 4   Year          40495 non-null  int64   \n",
+      " 5   Population    40495 non-null  int64   \n",
+      " 6   BUYER_COUNTY  40495 non-null  object  \n",
+      " 7   BUYER_STATE   40456 non-null  object  \n",
+      " 8   countyfips    40456 non-null  object  \n",
+      " 9   _merge        40495 non-null  category\n",
+      "dtypes: category(1), int64(2), object(7)\n",
+      "memory usage: 2.8+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Final Verification\n",
+    "df4.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>state</th>\n",
+       "      <th>abbrev</th>\n",
+       "      <th>code</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>Minnesota</td>\n",
+       "      <td>Minn.</td>\n",
+       "      <td>MN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>New Jersey</td>\n",
+       "      <td>N.J.</td>\n",
+       "      <td>NJ</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Arkansas</td>\n",
+       "      <td>Ark.</td>\n",
+       "      <td>AR</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>Nevada</td>\n",
+       "      <td>Nev.</td>\n",
+       "      <td>NV</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>Louisiana</td>\n",
+       "      <td>La.</td>\n",
+       "      <td>LA</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         state abbrev code\n",
+       "23   Minnesota  Minn.   MN\n",
+       "30  New Jersey   N.J.   NJ\n",
+       "3     Arkansas   Ark.   AR\n",
+       "28      Nevada   Nev.   NV\n",
+       "18   Louisiana    La.   LA"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "abbreviations = pd.read_csv(\"../01_Data/01_Raw/state_abbreviations.csv\")\n",
+    "abbreviations.sample(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# rename colums to match with the main dataframe\n",
+    "abbreviations = abbreviations.rename(\n",
+    "    columns={\n",
+    "        \"state\": \"State\",\n",
+    "        \"code\": \"State_Code\",\n",
+    "    }\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>State</th>\n",
+       "      <th>BUYER_COUNTY</th>\n",
+       "      <th>County_Code</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Population</th>\n",
+       "      <th>State_Code</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>33041</th>\n",
+       "      <td>Texas</td>\n",
+       "      <td>CONCHO</td>\n",
+       "      <td>48095</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>4121</td>\n",
+       "      <td>TX</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9306</th>\n",
+       "      <td>Indiana</td>\n",
+       "      <td>MADISON</td>\n",
+       "      <td>18095</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>129773</td>\n",
+       "      <td>IN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27074</th>\n",
+       "      <td>Ohio</td>\n",
+       "      <td>PUTNAM</td>\n",
+       "      <td>39137</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>34386</td>\n",
+       "      <td>OH</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39655</th>\n",
+       "      <td>Wisconsin</td>\n",
+       "      <td>KEWAUNEE</td>\n",
+       "      <td>55061</td>\n",
+       "      <td>2008</td>\n",
+       "      <td>20636</td>\n",
+       "      <td>WI</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28895</th>\n",
+       "      <td>Pennsylvania</td>\n",
+       "      <td>BRADFORD</td>\n",
+       "      <td>42015</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>63005</td>\n",
+       "      <td>PA</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              State BUYER_COUNTY County_Code  Year  Population State_Code\n",
+       "33041         Texas       CONCHO       48095  2011        4121         TX\n",
+       "9306        Indiana      MADISON       18095  2014      129773         IN\n",
+       "27074          Ohio       PUTNAM       39137  2011       34386         OH\n",
+       "39655     Wisconsin     KEWAUNEE       55061  2008       20636         WI\n",
+       "28895  Pennsylvania     BRADFORD       42015  2012       63005         PA"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# select required columns\n",
+    "df5 = pd.merge(\n",
+    "    df4[[\"State\", \"BUYER_COUNTY\", \"County_Code\", \"Year\", \"Population\"]],\n",
+    "    abbreviations[[\"State\", \"State_Code\"]],\n",
+    "    how=\"left\",\n",
+    "    left_on=\"State\",\n",
+    "    right_on=\"State\",\n",
+    "    validate=\"m:1\",\n",
+    ")\n",
+    "df5.sample(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>State</th>\n",
+       "      <th>State_Code</th>\n",
+       "      <th>County</th>\n",
+       "      <th>County_Code</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Population</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>38099</th>\n",
+       "      <td>Washington</td>\n",
+       "      <td>WA</td>\n",
+       "      <td>CLALLAM</td>\n",
+       "      <td>53009</td>\n",
+       "      <td>2012</td>\n",
+       "      <td>71791</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31623</th>\n",
+       "      <td>Tennessee</td>\n",
+       "      <td>TN</td>\n",
+       "      <td>HANCOCK</td>\n",
+       "      <td>47067</td>\n",
+       "      <td>2010</td>\n",
+       "      <td>6796</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19983</th>\n",
+       "      <td>Missouri</td>\n",
+       "      <td>MO</td>\n",
+       "      <td>POLK</td>\n",
+       "      <td>29167</td>\n",
+       "      <td>2005</td>\n",
+       "      <td>29308</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33149</th>\n",
+       "      <td>Texas</td>\n",
+       "      <td>TX</td>\n",
+       "      <td>DALLAM</td>\n",
+       "      <td>48111</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>7301</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12855</th>\n",
+       "      <td>Kentucky</td>\n",
+       "      <td>KY</td>\n",
+       "      <td>CLARK</td>\n",
+       "      <td>21049</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>35643</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            State State_Code   County County_Code  Year  Population\n",
+       "38099  Washington         WA  CLALLAM       53009  2012       71791\n",
+       "31623   Tennessee         TN  HANCOCK       47067  2010        6796\n",
+       "19983    Missouri         MO     POLK       29167  2005       29308\n",
+       "33149       Texas         TX   DALLAM       48111  2015        7301\n",
+       "12855    Kentucky         KY    CLARK       21049  2014       35643"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# rename columns\n",
+    "df5 = df5.rename(\n",
+    "    columns={\n",
+    "        \"BUYER_COUNTY\": \"County\",\n",
+    "    }\n",
+    ")\n",
+    "\n",
+    "# reorder columns\n",
+    "df5 = df5[\n",
+    "    [\n",
+    "        \"State\",\n",
+    "        \"State_Code\",\n",
+    "        \"County\",\n",
+    "        \"County_Code\",\n",
+    "        \"Year\",\n",
+    "        \"Population\",\n",
+    "    ]\n",
+    "]\n",
+    "\n",
+    "df5.sample(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 40495 entries, 0 to 40494\n",
+      "Data columns (total 6 columns):\n",
+      " #   Column       Non-Null Count  Dtype \n",
+      "---  ------       --------------  ----- \n",
+      " 0   State        40495 non-null  object\n",
+      " 1   State_Code   40495 non-null  object\n",
+      " 2   County       40495 non-null  object\n",
+      " 3   County_Code  40495 non-null  object\n",
+      " 4   Year         40495 non-null  int64 \n",
+      " 5   Population   40495 non-null  int64 \n",
+      "dtypes: int64(2), object(4)\n",
+      "memory usage: 1.9+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df5.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

02_Codes/02_population_script.py

@@ -0,0 +1,136 @@
+# importing pandas and setting default option
+import pandas as pd
+
+pd.set_option("mode.copy_on_write", True)
+
+# reading the raw files
+df = pd.read_csv("01_Data/01_Raw/raw_population.txt", sep="\t")
+fips = pd.read_csv("01_Data/01_Raw/county_fips.csv")
+abbreviations = pd.read_csv("01_Data/01_Raw/state_abbreviations.csv")
+
+# ------------------------------------------
+# dropping the unnecessary columns
+df1 = df.drop(columns=["Notes"])
+
+# Dropping unnecessary rows
+# 1.  removing the rows with na values generated due to Notes, using state column for reference
+df1 = df1.dropna(subset=["State"])
+
+# 2. Removing Alaska
+df1 = df1[df1["State"] != "Alaska"]
+
+
+# ------------------------------------------
+# Correcting Data Types for columns
+df2 = df1.copy()
+
+# 1. Saving state code as padded string
+df2["State Code"] = df2["State Code"].astype(int).astype(str).str.zfill(2)
+
+# 2. Saving county code as padded string
+df2["County Code"] = df2["County Code"].astype(int).astype(str).str.zfill(5)
+
+# padding fips to have consistency
+fips["countyfips"] = fips["countyfips"].astype(str).str.zfill(5)
+
+# 3. Converting Year to Integer
+df2["Yearly July 1st Estimates"] = df2["Yearly July 1st Estimates"].astype(int)
+
+# 4. Converting Population to Integer
+# replacing the missing values with 0 for now <-------------------Change this later if required
+df2["Population"] = df2["Population"].replace("Missing", 0)
+df2["Population"] = df2["Population"].astype(int)
+
+# ------------------------------------------
+
+# creating subset of data for analysis
+df3 = df2.copy()
+
+# rename columns
+df3 = df3.rename(
+    columns={
+        "Yearly July 1st Estimates": "Year",
+        "State Code": "State_Code",
+        "County Code": "County_Code",
+    }
+)
+
+# reorder columns
+df3 = df3[
+    [
+        "State",
+        "State_Code",
+        "County",
+        "County_Code",
+        "Year",
+        "Population",
+    ]
+]
+
+# ------------------------------------------
+
+# mapping with fips for proper county names
+df4 = pd.merge(
+    df3,
+    fips,
+    how="left",
+    left_on="County_Code",
+    right_on="countyfips",
+    validate="m:1",
+    indicator=True,
+)
+
+# ------------------------------------------
+
+# correcting the county names where fips mapping failed
+df4.loc[df4["County"] == "Montgomery County, AR", "BUYER_COUNTY"] = "MONTGOMERY"
+df4.loc[df4["County"] == "Kalawao County, HI", "BUYER_COUNTY"] = "KALAWAO"
+df4.loc[df4["County"] == "Oglala Lakota County, SD", "BUYER_COUNTY"] = "OGLALA LAKOTA"
+
+# ------------------------------------------
+
+# creating final dataframe
+# ------------------------------------------
+# mapping state names to abbreviations
+# rename abbreviations columns to match with the main dataframe
+abbreviations = abbreviations.rename(
+    columns={
+        "state": "State",
+        "code": "State_Code",
+    }
+)
+
+# merge the dataframes
+df5 = pd.merge(
+    df4[["State", "BUYER_COUNTY", "County_Code", "Year", "Population"]],
+    abbreviations[["State", "State_Code"]],
+    how="left",
+    left_on="State",
+    right_on="State",
+    validate="m:1",
+)
+
+
+# rename columns
+df5 = df5.rename(
+    columns={
+        "BUYER_COUNTY": "County",
+    }
+)
+
+# reorder columns
+df5 = df5[
+    [
+        "State",
+        "State_Code",
+        "County",
+        "County_Code",
+        "Year",
+        "Population",
+    ]
+]
+
+# ------------------------------------------
+
+# Writing to Parquet
+df5.to_parquet("01_Data/02_processed/01_Population.parquet", index=False)