population_distribution.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e08402df-29b3-42a9-a541-3b46ff7b0e5c",
   "metadata": {},
   "source": [
    "## This notebook presents the `distribution of population` and `distribution of population density` across US counties."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5dd82bb6-8aa7-43a3-9141-df6cc1371690",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filename where it is read from: must be used the file from readable_data_table.ipynp processing\n",
    "filename = \"data/vax_cases_deaths.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "539785af-9ee0-4d50-8f32-62f8fb62adb6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Imports\n",
    "import pandas as pd\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3d8d4094-67ff-4c4c-8708-f18edf04c9cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(filename)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b9c2925-a0db-46a6-b71c-d3e280a84abd",
   "metadata": {},
   "source": [
    "## Population distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d1f9f8cf-d930-472c-8855-80959303f4ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Minimum population:  86\n",
      "Maximum population:  10039107\n"
     ]
    }
   ],
   "source": [
    "print('Minimum population: ', df['Population'].min())\n",
    "print('Maximum population: ', df['Population'].max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "36e411d2-d7ba-4ac9-b66c-31a70c4644f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f55acdd4cd0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(df, x=\"Population\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1e695978-c8a5-4155-b396-7945d3b7fd85",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Population', ylabel='Count'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_smaller_2mln =  df[ df['Population'] < 2000000]\n",
    "sns.histplot(df_smaller_2mln, x=\"Population\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0d7d0bd0-9e4a-402b-af73-c84692701c1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Population', ylabel='Count'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_smaller_1mln =  df[ df['Population'] < 1000000] \n",
    "sns.histplot(df_smaller_1mln, x=\"Population\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "235eb68f-eac2-4e99-b1e0-88b531a5f8fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Population', ylabel='Count'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_smaller_500k =  df[ df['Population'] < 500000] \n",
    "sns.histplot(df_smaller_500k, x=\"Population\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5333e0e8-51f1-45bf-8ca4-e1cd2e944a84",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-10-3575010572de>:4: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  g.set_xticklabels(xlabels)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[Text(-25000.0, 0, '-25k'),\n",
       " Text(0.0, 0, '0k'),\n",
       " Text(25000.0, 0, '25k'),\n",
       " Text(50000.0, 0, '50k'),\n",
       " Text(75000.0, 0, '75k'),\n",
       " Text(100000.0, 0, '100k'),\n",
       " Text(125000.0, 0, '125k'),\n",
       " Text(150000.0, 0, '150k'),\n",
       " Text(175000.0, 0, '175k'),\n",
       " Text(200000.0, 0, '200k'),\n",
       " Text(225000.0, 0, '225k')]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_smaller_200k =  df[ df['Population'] < 200000] \n",
    "g = sns.histplot(df_smaller_200k, x=\"Population\")\n",
    "xlabels = ['{:,.0f}'.format(x) + 'k' for x in g.get_xticks()/1000]\n",
    "g.set_xticklabels(xlabels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b4d12922-767a-4ed7-968a-a5c9482d0abe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Counties above 200k inhabitants:  336\n",
      "Counties below 200k inhabitants:  2806\n"
     ]
    }
   ],
   "source": [
    "print(\"Counties above 200k inhabitants: \", len(df[ df['Population'] > 200000] ))\n",
    "print(\"Counties below 200k inhabitants: \", len(df[ df['Population'] < 200000] ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "090f5571-fe63-4b79-92db-2f333062f80f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Counties above 25k inhabitants:  1604\n",
      "Counties below 25k inhabitants:  1538\n"
     ]
    }
   ],
   "source": [
    "print(\"Counties above 25k inhabitants: \", len(df[ df['Population'] > 25000] ))\n",
    "print(\"Counties below 25k inhabitants: \", len(df[ df['Population'] < 25000] ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d2b6af7c-5c7d-481e-81f5-153e56533a66",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Counties above 5k inhabitants:  2827\n",
      "Counties below 5k inhabitants:  315\n"
     ]
    }
   ],
   "source": [
    "print(\"Counties above 5k inhabitants: \", len(df[ df['Population'] > 5000] ))\n",
    "print(\"Counties below 5k inhabitants: \", len(df[ df['Population'] < 5000] ))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36e6d5f7-0759-437c-abb8-f26949b2cd98",
   "metadata": {},
   "source": [
    "## Population density distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "51ee8e16-75b6-4ba2-bb8f-a39e6fa0aa64",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Minimum population density:  0.04\n",
      "Maximum population density:  71340.6\n"
     ]
    }
   ],
   "source": [
    "print('Minimum population density: ', round(df['Population Density'].min(),2))\n",
    "print('Maximum population density: ', round(df['Population Density'].max(),2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "70e05926-88ad-4f48-b9f5-582e8bf1f85a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7ff4fc58dfd0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(df, x=\"Population Density\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "719cc67c-9590-4374-9d8d-e4b30765afe9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Population Density', ylabel='Count'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_smaller_10k =  df[ df['Population Density'] < 10000] \n",
    "sns.histplot(df_smaller_10k, x=\"Population Density\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8016b3f0-c5cc-47d8-9fbb-92ddd93c404a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Population Density', ylabel='Count'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_smaller_2k =  df[ df['Population Density'] < 2000] \n",
    "sns.histplot(df_smaller_2k, x=\"Population Density\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8e367423-1921-4234-81bc-07f41cbcbf2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Population Density', ylabel='Count'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_smaller_500 =  df[ df['Population Density'] < 500] \n",
    "sns.histplot(df_smaller_500, x=\"Population Density\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3d8ee60b-a974-4326-b3d8-ca498c167cc0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Counties with density above 500 inhabitants per square mile:  268\n",
      "Counties with density above 500 inhabitants per square mile:  2874\n"
     ]
    }
   ],
   "source": [
    "print(\"Counties with density above 500 inhabitants per square mile: \", len(df[ df['Population Density'] > 500] ))\n",
    "print(\"Counties with density above 500 inhabitants per square mile: \", len(df[ df['Population Density'] < 500] ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a05386e7-b783-4baf-a42e-88febefca181",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Population Density', ylabel='Count'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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TLZK06ExaKHwRWJ3k1CQPAtYBW8ZckyQtGhN1+Kiq9iV5FfAxYAnwnqra0dPL3e9DUD2a1Nqsa/4mtTbrmp9JrQuOcG0TdaJZkjRek3b4SJI0RoaCJKmzKENhUobSSLIyydVJbkmyI8mrW/vrk3wzyQ3t53ljqO3rSb7UXn9bazshyVVJbmu3x4+hrscO7ZcbknwnycXj2GdJ3pNkb5Kbh9pm3EdJLm3vuVuTnDPiuv5zkq8kuSnJFUl+qrWvSvKDof32zr7qmqW2GX93Y95nHxqq6etJbmjtI9tns3xG9Pc+q6pF9cPgBPZXgccADwJuBE4bUy3LgCe05YcDf89geI/XA7875v30deDEKW3/CbikLV8CvGkCfpf/B/jpcewz4JnAE4CbD7eP2u/1RuBY4NT2Hlwywrp+GTimLb9pqK5Vw+uNaZ9N+7sb9z6b8vh/Af5g1Ptsls+I3t5ni7GnMDFDaVTVnqq6ri1/F7gFWD6OWuZoLbCpLW8CzhtfKQCcDXy1qr4xjhevqk8B/zCleaZ9tBa4vKrurarbgZ0M3osjqauqPl5V+9rdzzO4BmjkZthnMxnrPjsgg4kUXgx8sI/Xns0snxG9vc8WYygsB4anQ9rFBHwQJ1kFnAl8oTW9qnX13zOOwzQMriT/eJLtbWgRgJOrag8M3qzASWOoa9g6Dv6POu59BjPvo0l63/0W8LdD909Ncn2STyZ5xphqmu53Nyn77BnAXVV121DbyPfZlM+I3t5nizEUDjuUxqgleRjwl8DFVfUd4B3APwHOAPYw6LqO2tOq6gkMRqy9KMkzx1DDjNrFjS8APtyaJmGfzWYi3ndJLgP2Ae9vTXuAU6rqTOC1wAeSPGLEZc30u5uIfQa8lIP/+Bj5PpvmM2LGVadpm9c+W4yhMFFDaSR5IINf9vur6iMAVXVXVe2vqh8D76KnLvNsqmp3u90LXNFquCvJslb3MmDvqOsa8lzguqq6CyZjnzUz7aOxv++SrAeeD7ys2gHodpjhnra8ncEx6J8dZV2z/O4mYZ8dA/wq8KEDbaPeZ9N9RtDj+2wxhsLEDKXRjlX+GXBLVb15qH3Z0GovBG6eum3PdT00ycMPLDM4SXkzg/20vq22HrhylHVNcdBfb+PeZ0Nm2kdbgHVJjk1yKrAauHZURSU5F/h94AVV9f2h9qUZzGNCkse0ur42qrra6870uxvrPmt+CfhKVe060DDKfTbTZwR9vs9GcQZ90n6A5zE4i/9V4LIx1vF0Bl27m4Ab2s/zgPcBX2rtW4BlI67rMQy+wXAjsOPAPgIeBWwFbmu3J4xpvz0EuAd45FDbyPcZg1DaA/yIwV9oF8y2j4DL2nvuVuC5I65rJ4NjzQfeZ+9s6/5a+x3fCFwH/LMx7LMZf3fj3Get/b3AK6esO7J9NstnRG/vM4e5kCR1FuPhI0nSDAwFSVLHUJAkdQwFSVLHUJAkdQwFTbwk+9tolDcn+XCShxzh578myawTn2cwEutDhu7/zYGRRu/naw+PEHpbko8kOe3+Pu80r/PZdrsqyT8/0s+vo4ehoIXgB1V1RlU9Dvgh8Mox1HAxg+sjAKiq51XVt4/Qc7+l/ftWM7hy9hNJlh6h5wagqp7aFlcBhoJmZChoofk08DNtPPn/2QZR+3ySx0P3l/f7knyi/eX9itb+rCQfPfAkSf5bkt+c+uRJ3pFkWxu7/g2t7d8AjwauTnJ1a/t6khPb8mtbL+bmJBe3tlVtDPx3tef6eJIHH+4fV1UfAj5O++BO8sQ26Nr2JB8bGtrgmiRvSnJtkr8/MChbktNb2w1t36xu7d9rL/FG4Bnt8dck+XSSM4b+/Z85sC+1OBkKWjDaODTPZXD16xuA66vq8cDrgL8YWvXxwK8ATwH+IMmj5/Eyl1XVmvYc/zTJ46vqbQzGj3l2VT17Sk1PBP4F8IvAk4FXJDmzPbwa+JOqOh34NoMrYefiOuDn2pg3fwy8qKqeCLwH2DC03jFVdRaDXswftrZXAv+1qs4A1jC4OnfYJcCnW8/kLcC7gd9s/5afBY6tqpvmWKeOQoaCFoIHZzDr1TbgDgZjwTydwfAIVNUngEcleWRb/8qq+kFVfQu4mvkNjvfiJNcB1wOnM5i0ZDZPB66oqn+squ8BH2Ew1DLA7VV1Q1vezuDQzVwcGOnyscDjgKvav//fc/A8CAcGRxt+7s8Br0vy+8BPV9UPDvNaHwae3wLotxgM66BF7JhxFyDNwQ/aX76dNlDYVDXldrh9Hwf/EXTc1I3bAGK/Czypqv5vkvdOt97UzWZ57N6h5f3AYQ8fNWcyCMAAO6rqKYd5/v20/8tV9YEkX2DQU/pYkt9uoTmtqvp+kqsYTM7yYga9Cy1i9hS0UH0KeBkMzhcA36qfjDO/NslxSR4FPIvByLjfAE5ro0c+ksGsbVM9AvhH4P8lOZnBoaoDvstgOsTp6jgvyUPaiLIvZHDe4z5J8msMRqX9IIMBzZYmeUp77IFJTj/M9o8BvtYOeW1hcBhs2HT/jncDbwO+WFVznRVNRyl7ClqoXg/8eZKbgO/zk2GEYTBU8F8DpwD/sdrcEEk2Mxht8jYGh4cOUlU3JrmewQiYXwM+M/TwRuBvk+wZPq9QVde1HsWB4YnfXVXXZzBL1ly9JsnLgYcyGDb6OVV1d6v5RcDbWpAdA7y11TeTlwAvT/IjBvNX/4cpj98E7EtyI/DeqnpLVW1P8h3gz+dRs45SjpKqo0qS1wPfq6o/GnctC0U7EX8N8HM1mOhGi5iHj6RFLMlvMJjz9zIDQWBPQZI0xJ6CJKljKEiSOoaCJKljKEiSOoaCJKnz/wE51P2TIHq7dQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_smaller_200 =  df[ df['Population Density'] < 200] \n",
    "sns.histplot(df_smaller_200, x=\"Population Density\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f5431c93-a194-4e9e-a093-47580106ca3d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Counties with density above 100 inhabitants per square mile:  892\n",
      "Counties with density below 100 inhabitants per square mile:  2250\n"
     ]
    }
   ],
   "source": [
    "print(\"Counties with density above 100 inhabitants per square mile: \", len(df[ df['Population Density'] > 100] ))\n",
    "print(\"Counties with density below 100 inhabitants per square mile: \", len(df[ df['Population Density'] < 100] ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e49b1c5d-99ff-4bae-8205-ef1168c8b564",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}