diff --git a/fa24-team-a/Midpoint_update.md b/fa24-team-a/Midpoint_update.md
new file mode 100644
index 00000000..e72753d0
--- /dev/null
+++ b/fa24-team-a/Midpoint_update.md
@@ -0,0 +1,8 @@
+# Project Midpoint Update
+
+The relevant notebooks are present in the _Population and Displacement_ folder with work on 3 submetrics -
+
+1. Population by Race and Ethnicity
+2. Population by Age (% over 65)
+3. Population in Poverty (poverty rate)
+
diff --git a/fa24-team-a/Population and Displacement/Population - % over 65.ipynb b/fa24-team-a/Population and Displacement/Population - % over 65.ipynb
new file mode 100644
index 00000000..6d4f77c4
--- /dev/null
+++ b/fa24-team-a/Population and Displacement/Population - % over 65.ipynb
@@ -0,0 +1,2484 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "5ab6e735",
+ "metadata": {},
+ "source": [
+ "### Population and Displacement - % over 65\n",
+ "\n",
+ "This notebook investigates Population Displacement Metrics with a specific focus on the percentage of the population aged 65 and over. Using census data from 2014 to 2023, this analysis seeks to understand how the demographics of older adults have shifted over nearly a decade.\n",
+ "\n",
+ "*The primary objective of this analysis is to examine trends in the percentage of individuals aged 65 and older across different regions.*\n",
+ "\n",
+ "The dataset analyzed here consists of census data collected from 2014 to 2023, focusing on the population distribution by age. By examining these trends over time, we aim to gain a clearer understanding of how aging populations may be affected by demographic shifts and displacement risks."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "6d2cf9f0",
+ "metadata": {},
+ "source": [
+ "#### Importing libraries and performing Exploratory Data Analysis"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "e60db1a3-4869-4145-bad1-81d31a354f7a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "a = ['0806.01', '0104.03', '0707.00', '0103.00', '9811.00', '1202.01', '9803.00', '0104.04', '0104.05', \n",
+ " '0801.00', '1203.01', '0711.01', '0913.00', '0105.00', '1101.05', '0102.06', '0813.01', '0813.02', \n",
+ " '0705.02', '0821.00', '0106.00', '0706.00', '0803.00', '0804.01', '0805.00', '0808.01', '0809.00', \n",
+ " '0814.00', '0815.00', '0817.00', '0818.00', '0819.00', '0820.00', '0901.00', '0902.00', '0903.00', \n",
+ " '0904.00', '0906.00', '0907.00', '0914.00', '0924.00', '0709.02', '0708.02', '0708.01', '0709.01']"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "25ab8096-4364-49c3-83a5-c430be6f8baa",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['0102.06', '0103.00', '0104.03', '0104.04', '0104.05', '0105.00', '0106.00', '0705.02', '0706.00', '0707.00', '0708.01', '0708.02', '0709.01', '0709.02', '0711.01', '0801.00', '0803.00', '0804.01', '0805.00', '0806.01', '0808.01', '0809.00', '0813.01', '0813.02', '0814.00', '0815.00', '0817.00', '0818.00', '0819.00', '0820.00', '0821.00', '0901.00', '0902.00', '0903.00', '0904.00', '0906.00', '0907.00', '0913.00', '0914.00', '0924.00', '1101.05', '1202.01', '1203.01', '9803.00', '9811.00']\n",
+ "45\n"
+ ]
+ }
+ ],
+ "source": [
+ "sorted_a = sorted(a, key=float)\n",
+ "print(sorted_a)\n",
+ "print(len(a))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 225,
+ "id": "8745de7a-e06c-4d0c-a59f-1f3685418b74",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pandas as pd\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "import seaborn as sns"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 79,
+ "id": "dccb8ba1-46a4-44d3-b5d3-f2d2f260d5b6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df1 = pd.read_csv('Demographics(2023-2019).csv')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 81,
+ "id": "7ec8ac66-872c-4f5d-a22a-990761261aa0",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Label (Grouping) | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2022 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2021 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2020 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2019 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " SEX AND AGE | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " Total population | \n",
+ " 652,442 | \n",
+ " 649,768 | \n",
+ " NaN | \n",
+ " 654,281 | \n",
+ " NaN | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 694,295 | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Male | \n",
+ " 48.1% | \n",
+ " 48.5% | \n",
+ " NaN | \n",
+ " 48.2% | \n",
+ " NaN | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 47.8% | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Female | \n",
+ " 51.9% | \n",
+ " 51.5% | \n",
+ " NaN | \n",
+ " 51.8% | \n",
+ " NaN | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 52.2% | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " Sex ratio (males per 100 females) | \n",
+ " 92.8 | \n",
+ " 94.1 | \n",
+ " NaN | \n",
+ " 92.9 | \n",
+ " NaN | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 91.7 | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ "
\n",
+ " \n",
+ " 94 | \n",
+ " Total housing units | \n",
+ " 313,752 | \n",
+ " 307,836 | \n",
+ " * | \n",
+ " 307,025 | \n",
+ " * | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 303,791 | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 95 | \n",
+ " CITIZEN, VOTING AGE POPULATION | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 96 | \n",
+ " Citizen, 18 and over population | \n",
+ " 478,610 | \n",
+ " 479,717 | \n",
+ " NaN | \n",
+ " 475,111 | \n",
+ " NaN | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 496,231 | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 97 | \n",
+ " Male | \n",
+ " 46.7% | \n",
+ " 46.7% | \n",
+ " NaN | \n",
+ " 47.1% | \n",
+ " NaN | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 46.6% | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 98 | \n",
+ " Female | \n",
+ " 53.3% | \n",
+ " 53.3% | \n",
+ " NaN | \n",
+ " 52.9% | \n",
+ " NaN | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 53.4% | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
99 rows × 10 columns
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Label (Grouping) \\\n",
+ "0 SEX AND AGE \n",
+ "1 Total population \n",
+ "2 Male \n",
+ "3 Female \n",
+ "4 Sex ratio (males per 100 females) \n",
+ ".. ... \n",
+ "94 Total housing units \n",
+ "95 CITIZEN, VOTING AGE POPULATION \n",
+ "96 Citizen, 18 and over population \n",
+ "97 Male \n",
+ "98 Female \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 Estimate \\\n",
+ "0 NaN \n",
+ "1 652,442 \n",
+ "2 48.1% \n",
+ "3 51.9% \n",
+ "4 92.8 \n",
+ ".. ... \n",
+ "94 313,752 \n",
+ "95 NaN \n",
+ "96 478,610 \n",
+ "97 46.7% \n",
+ "98 53.3% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2022 Estimate \\\n",
+ "0 NaN \n",
+ "1 649,768 \n",
+ "2 48.5% \n",
+ "3 51.5% \n",
+ "4 94.1 \n",
+ ".. ... \n",
+ "94 307,836 \n",
+ "95 NaN \n",
+ "96 479,717 \n",
+ "97 46.7% \n",
+ "98 53.3% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance \\\n",
+ "0 NaN \n",
+ "1 NaN \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "4 NaN \n",
+ ".. ... \n",
+ "94 * \n",
+ "95 NaN \n",
+ "96 NaN \n",
+ "97 NaN \n",
+ "98 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2021 Estimate \\\n",
+ "0 NaN \n",
+ "1 654,281 \n",
+ "2 48.2% \n",
+ "3 51.8% \n",
+ "4 92.9 \n",
+ ".. ... \n",
+ "94 307,025 \n",
+ "95 NaN \n",
+ "96 475,111 \n",
+ "97 47.1% \n",
+ "98 52.9% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance \\\n",
+ "0 NaN \n",
+ "1 NaN \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "4 NaN \n",
+ ".. ... \n",
+ "94 * \n",
+ "95 NaN \n",
+ "96 NaN \n",
+ "97 NaN \n",
+ "98 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2020 Estimate \\\n",
+ "0 NaN \n",
+ "1 (X) \n",
+ "2 (X) \n",
+ "3 (X) \n",
+ "4 (X) \n",
+ ".. ... \n",
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+ "95 NaN \n",
+ "96 (X) \n",
+ "97 (X) \n",
+ "98 (X) \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance \\\n",
+ "0 NaN \n",
+ "1 NaN \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "4 NaN \n",
+ ".. ... \n",
+ "94 NaN \n",
+ "95 NaN \n",
+ "96 NaN \n",
+ "97 NaN \n",
+ "98 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2019 Estimate \\\n",
+ "0 NaN \n",
+ "1 694,295 \n",
+ "2 47.8% \n",
+ "3 52.2% \n",
+ "4 91.7 \n",
+ ".. ... \n",
+ "94 303,791 \n",
+ "95 NaN \n",
+ "96 496,231 \n",
+ "97 46.6% \n",
+ "98 53.4% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance \n",
+ "0 NaN \n",
+ "1 * \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "4 NaN \n",
+ ".. ... \n",
+ "94 * \n",
+ "95 NaN \n",
+ "96 * \n",
+ "97 NaN \n",
+ "98 NaN \n",
+ "\n",
+ "[99 rows x 10 columns]"
+ ]
+ },
+ "execution_count": 81,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 83,
+ "id": "9cb313b3-ea9f-4636-b3c6-eef06a9d1378",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0 SEX AND AGE\n",
+ "1 Total population\n",
+ "2 Male\n",
+ "3 Female\n",
+ "4 Sex ratio (males per 100 females)\n",
+ " ... \n",
+ "94 Total housing units\n",
+ "95 CITIZEN, VOTING AGE POPULATION\n",
+ "96 Citizen, 18 and over population\n",
+ "97 Male\n",
+ "98 Female\n",
+ "Name: Label (Grouping), Length: 99, dtype: object\n"
+ ]
+ }
+ ],
+ "source": [
+ "df1[\"Label (Grouping)\"] = df1[\"Label (Grouping)\"].str.replace('\\xa0', ' ').str.strip()\n",
+ "print(df1[\"Label (Grouping)\"])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 89,
+ "id": "2a32044f-a198-44e5-8fe7-32f5f5a86870",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "over65_a = df1[df1[\"Label (Grouping)\"] == \"65 years and over\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 91,
+ "id": "aca93106-1963-4c7a-b6ef-62ba0146ea80",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Label (Grouping) | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2022 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2021 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2020 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2019 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 24 | \n",
+ " 65 years and over | \n",
+ " 13.4% | \n",
+ " 12.9% | \n",
+ " * | \n",
+ " 12.7% | \n",
+ " * | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 12.0% | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 29 | \n",
+ " 65 years and over | \n",
+ " 87,610 | \n",
+ " 83,638 | \n",
+ " * | \n",
+ " 83,078 | \n",
+ " * | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 83,656 | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ "
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+ "
"
+ ],
+ "text/plain": [
+ " Label (Grouping) \\\n",
+ "24 65 years and over \n",
+ "29 65 years and over \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 Estimate \\\n",
+ "24 13.4% \n",
+ "29 87,610 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2022 Estimate \\\n",
+ "24 12.9% \n",
+ "29 83,638 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance \\\n",
+ "24 * \n",
+ "29 * \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2021 Estimate \\\n",
+ "24 12.7% \n",
+ "29 83,078 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance \\\n",
+ "24 * \n",
+ "29 * \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2020 Estimate \\\n",
+ "24 (X) \n",
+ "29 (X) \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance \\\n",
+ "24 NaN \n",
+ "29 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2019 Estimate \\\n",
+ "24 12.0% \n",
+ "29 83,656 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance \n",
+ "24 * \n",
+ "29 * "
+ ]
+ },
+ "execution_count": 91,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "over65_a"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 143,
+ "id": "8ad46e88-379d-4803-b89b-e5dd9591a568",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
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+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Label (Grouping) | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2022 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2021 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2020 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2019 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 30 | \n",
+ " Male | \n",
+ " 43.5% | \n",
+ " 43.5% | \n",
+ " NaN | \n",
+ " 43.3% | \n",
+ " NaN | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 41.6% | \n",
+ " * | \n",
+ "
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+ " \n",
+ "
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+ ],
+ "text/plain": [
+ " Label (Grouping) Boston city, Suffolk County, Massachusetts!!2023 Estimate \\\n",
+ "30 Male 43.5% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2022 Estimate \\\n",
+ "30 43.5% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance \\\n",
+ "30 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2021 Estimate \\\n",
+ "30 43.3% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance \\\n",
+ "30 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2020 Estimate \\\n",
+ "30 (X) \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance \\\n",
+ "30 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2019 Estimate \\\n",
+ "30 41.6% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance \n",
+ "30 * "
+ ]
+ },
+ "execution_count": 143,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "row_30a = df1.iloc[[30]]\n",
+ "row_30a"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 145,
+ "id": "7298c0a2-74d2-46b5-9e9d-d2de3fd3dda1",
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+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Label (Grouping) | \n",
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+ " Boston city, Suffolk County, Massachusetts!!2022 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2021 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2020 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2019 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 31 | \n",
+ " Female | \n",
+ " 56.5% | \n",
+ " 56.5% | \n",
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+ " 56.7% | \n",
+ " NaN | \n",
+ " (X) | \n",
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+ ],
+ "text/plain": [
+ " Label (Grouping) Boston city, Suffolk County, Massachusetts!!2023 Estimate \\\n",
+ "31 Female 56.5% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2022 Estimate \\\n",
+ "31 56.5% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance \\\n",
+ "31 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2021 Estimate \\\n",
+ "31 56.7% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance \\\n",
+ "31 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2020 Estimate \\\n",
+ "31 (X) \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance \\\n",
+ "31 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2019 Estimate \\\n",
+ "31 58.4% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance \n",
+ "31 * "
+ ]
+ },
+ "execution_count": 145,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "row_31a = df1.iloc[[31]]\n",
+ "row_31a"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 149,
+ "id": "e8170401-0a5f-41be-92c9-ed1cecb54e8a",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Label (Grouping) | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2022 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2021 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2020 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2019 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 65 years and over | \n",
+ " 13.4% | \n",
+ " 12.9% | \n",
+ " * | \n",
+ " 12.7% | \n",
+ " * | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 12.0% | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 65 years and over | \n",
+ " 87,610 | \n",
+ " 83,638 | \n",
+ " * | \n",
+ " 83,078 | \n",
+ " * | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 83,656 | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Male | \n",
+ " 43.5% | \n",
+ " 43.5% | \n",
+ " NaN | \n",
+ " 43.3% | \n",
+ " NaN | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 41.6% | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Female | \n",
+ " 56.5% | \n",
+ " 56.5% | \n",
+ " NaN | \n",
+ " 56.7% | \n",
+ " NaN | \n",
+ " (X) | \n",
+ " NaN | \n",
+ " 58.4% | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Label (Grouping) \\\n",
+ "0 65 years and over \n",
+ "1 65 years and over \n",
+ "2 Male \n",
+ "3 Female \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 Estimate \\\n",
+ "0 13.4% \n",
+ "1 87,610 \n",
+ "2 43.5% \n",
+ "3 56.5% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2022 Estimate \\\n",
+ "0 12.9% \n",
+ "1 83,638 \n",
+ "2 43.5% \n",
+ "3 56.5% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance \\\n",
+ "0 * \n",
+ "1 * \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2021 Estimate \\\n",
+ "0 12.7% \n",
+ "1 83,078 \n",
+ "2 43.3% \n",
+ "3 56.7% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance \\\n",
+ "0 * \n",
+ "1 * \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2020 Estimate \\\n",
+ "0 (X) \n",
+ "1 (X) \n",
+ "2 (X) \n",
+ "3 (X) \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance \\\n",
+ "0 NaN \n",
+ "1 NaN \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2019 Estimate \\\n",
+ "0 12.0% \n",
+ "1 83,656 \n",
+ "2 41.6% \n",
+ "3 58.4% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance \n",
+ "0 * \n",
+ "1 * \n",
+ "2 * \n",
+ "3 * "
+ ]
+ },
+ "execution_count": 149,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "combined_df1 = pd.concat([over65_a, row_30a, row_31a], ignore_index=True)\n",
+ "combined_df1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 151,
+ "id": "e063f874-23de-44c1-8c18-0476e13fad03",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Index(['Label (Grouping)',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2023 Estimate',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2022 Estimate',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2021 Estimate',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2020 Estimate',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2019 Estimate',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance'],\n",
+ " dtype='object')"
+ ]
+ },
+ "execution_count": 151,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "combined_df1.columns"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 153,
+ "id": "1d6352db-9b6e-4c69-863c-3d6407bfb541",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "combined_df1 = combined_df1.drop(columns=['Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2020 Estimate',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 155,
+ "id": "00e58463-e510-477f-92ed-0990b78e4df9",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Label (Grouping) | \n",
+ " Boston city, Suffolk County, Massachusetts!!2023 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2022 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2021 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2019 Estimate | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 65 years and over | \n",
+ " 13.4% | \n",
+ " 12.9% | \n",
+ " 12.7% | \n",
+ " 12.0% | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 65 years and over | \n",
+ " 87,610 | \n",
+ " 83,638 | \n",
+ " 83,078 | \n",
+ " 83,656 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Male | \n",
+ " 43.5% | \n",
+ " 43.5% | \n",
+ " 43.3% | \n",
+ " 41.6% | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Female | \n",
+ " 56.5% | \n",
+ " 56.5% | \n",
+ " 56.7% | \n",
+ " 58.4% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Label (Grouping) \\\n",
+ "0 65 years and over \n",
+ "1 65 years and over \n",
+ "2 Male \n",
+ "3 Female \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2023 Estimate \\\n",
+ "0 13.4% \n",
+ "1 87,610 \n",
+ "2 43.5% \n",
+ "3 56.5% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2022 Estimate \\\n",
+ "0 12.9% \n",
+ "1 83,638 \n",
+ "2 43.5% \n",
+ "3 56.5% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2021 Estimate \\\n",
+ "0 12.7% \n",
+ "1 83,078 \n",
+ "2 43.3% \n",
+ "3 56.7% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2019 Estimate \n",
+ "0 12.0% \n",
+ "1 83,656 \n",
+ "2 41.6% \n",
+ "3 58.4% "
+ ]
+ },
+ "execution_count": 155,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "combined_df1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 157,
+ "id": "70f7a17d-618a-46d6-96b7-abeb0153c8e3",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " NaN 2023 2022 2021 2019\n",
+ "0 65 years and over 13.4% 12.9% 12.7% 12.0%\n",
+ "1 65 years and over 87,610 83,638 83,078 83,656\n",
+ "2 Male 43.5% 43.5% 43.3% 41.6%\n",
+ "3 Female 56.5% 56.5% 56.7% 58.4%\n"
+ ]
+ }
+ ],
+ "source": [
+ "combined_df1.columns = combined_df1.columns.str.extract(r'(\\d{4})', expand=False)\n",
+ "print(combined_df1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 159,
+ "id": "a4be4e1b-3f5c-4c05-8947-bc8779bf88bf",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "combined_df1.rename(columns={np.nan: 'Labels'}, inplace=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 161,
+ "id": "4398f0fa-9e62-4fa1-9aca-6f4864d37d0b",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Labels | \n",
+ " 2023 | \n",
+ " 2022 | \n",
+ " 2021 | \n",
+ " 2019 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 65 years and over | \n",
+ " 13.4% | \n",
+ " 12.9% | \n",
+ " 12.7% | \n",
+ " 12.0% | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 65 years and over | \n",
+ " 87,610 | \n",
+ " 83,638 | \n",
+ " 83,078 | \n",
+ " 83,656 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Male | \n",
+ " 43.5% | \n",
+ " 43.5% | \n",
+ " 43.3% | \n",
+ " 41.6% | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Female | \n",
+ " 56.5% | \n",
+ " 56.5% | \n",
+ " 56.7% | \n",
+ " 58.4% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Labels 2023 2022 2021 2019\n",
+ "0 65 years and over 13.4% 12.9% 12.7% 12.0%\n",
+ "1 65 years and over 87,610 83,638 83,078 83,656\n",
+ "2 Male 43.5% 43.5% 43.3% 41.6%\n",
+ "3 Female 56.5% 56.5% 56.7% 58.4%"
+ ]
+ },
+ "execution_count": 161,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "combined_df1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 171,
+ "id": "94731a93-f0c6-4b2e-a139-bc2b2232abb5",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df2 = pd.read_csv('Demographics(2018-2014).csv')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 173,
+ "id": "c5a67b34-e741-4abb-b7ed-e1026bedb46d",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Label (Grouping) | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2017 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2017 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2016 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2016 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2015 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2015 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2014 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2014 Statistical Significance | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " SEX AND AGE | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " Total population | \n",
+ " 695,926 | \n",
+ " 683,015 | \n",
+ " * | \n",
+ " 672,840 | \n",
+ " * | \n",
+ " 669,469 | \n",
+ " * | \n",
+ " 656,051 | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Male | \n",
+ " 48.0% | \n",
+ " 48.3% | \n",
+ " NaN | \n",
+ " 48.0% | \n",
+ " NaN | \n",
+ " 48.1% | \n",
+ " NaN | \n",
+ " 48.2% | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Female | \n",
+ " 52.0% | \n",
+ " 51.7% | \n",
+ " NaN | \n",
+ " 52.0% | \n",
+ " NaN | \n",
+ " 51.9% | \n",
+ " NaN | \n",
+ " 51.8% | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " Sex ratio (males per 100 females) | \n",
+ " 92.2 | \n",
+ " 93.4 | \n",
+ " NaN | \n",
+ " 92.4 | \n",
+ " NaN | \n",
+ " 92.8 | \n",
+ " NaN | \n",
+ " 93.0 | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ "
\n",
+ " \n",
+ " 89 | \n",
+ " Total housing units | \n",
+ " 299,472 | \n",
+ " 293,538 | \n",
+ " * | \n",
+ " 288,716 | \n",
+ " * | \n",
+ " 286,120 | \n",
+ " * | \n",
+ " 274,459 | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 90 | \n",
+ " CITIZEN, VOTING AGE POPULATION | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 91 | \n",
+ " Citizen, 18 and over population | \n",
+ " 496,326 | \n",
+ " 483,314 | \n",
+ " * | \n",
+ " 466,415 | \n",
+ " * | \n",
+ " 468,296 | \n",
+ " * | \n",
+ " 462,504 | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 92 | \n",
+ " Male | \n",
+ " 46.6% | \n",
+ " 47.5% | \n",
+ " * | \n",
+ " 47.3% | \n",
+ " NaN | \n",
+ " 46.8% | \n",
+ " NaN | \n",
+ " 47.0% | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 93 | \n",
+ " Female | \n",
+ " 53.4% | \n",
+ " 52.5% | \n",
+ " * | \n",
+ " 52.7% | \n",
+ " NaN | \n",
+ " 53.2% | \n",
+ " NaN | \n",
+ " 53.0% | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
94 rows × 10 columns
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Label (Grouping) \\\n",
+ "0 SEX AND AGE \n",
+ "1 Total population \n",
+ "2 Male \n",
+ "3 Female \n",
+ "4 Sex ratio (males per 100 females) \n",
+ ".. ... \n",
+ "89 Total housing units \n",
+ "90 CITIZEN, VOTING AGE POPULATION \n",
+ "91 Citizen, 18 and over population \n",
+ "92 Male \n",
+ "93 Female \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 Estimate \\\n",
+ "0 NaN \n",
+ "1 695,926 \n",
+ "2 48.0% \n",
+ "3 52.0% \n",
+ "4 92.2 \n",
+ ".. ... \n",
+ "89 299,472 \n",
+ "90 NaN \n",
+ "91 496,326 \n",
+ "92 46.6% \n",
+ "93 53.4% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2017 Estimate \\\n",
+ "0 NaN \n",
+ "1 683,015 \n",
+ "2 48.3% \n",
+ "3 51.7% \n",
+ "4 93.4 \n",
+ ".. ... \n",
+ "89 293,538 \n",
+ "90 NaN \n",
+ "91 483,314 \n",
+ "92 47.5% \n",
+ "93 52.5% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2017 Statistical Significance \\\n",
+ "0 NaN \n",
+ "1 * \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "4 NaN \n",
+ ".. ... \n",
+ "89 * \n",
+ "90 NaN \n",
+ "91 * \n",
+ "92 * \n",
+ "93 * \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2016 Estimate \\\n",
+ "0 NaN \n",
+ "1 672,840 \n",
+ "2 48.0% \n",
+ "3 52.0% \n",
+ "4 92.4 \n",
+ ".. ... \n",
+ "89 288,716 \n",
+ "90 NaN \n",
+ "91 466,415 \n",
+ "92 47.3% \n",
+ "93 52.7% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2016 Statistical Significance \\\n",
+ "0 NaN \n",
+ "1 * \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "4 NaN \n",
+ ".. ... \n",
+ "89 * \n",
+ "90 NaN \n",
+ "91 * \n",
+ "92 NaN \n",
+ "93 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2015 Estimate \\\n",
+ "0 NaN \n",
+ "1 669,469 \n",
+ "2 48.1% \n",
+ "3 51.9% \n",
+ "4 92.8 \n",
+ ".. ... \n",
+ "89 286,120 \n",
+ "90 NaN \n",
+ "91 468,296 \n",
+ "92 46.8% \n",
+ "93 53.2% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2015 Statistical Significance \\\n",
+ "0 NaN \n",
+ "1 * \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "4 NaN \n",
+ ".. ... \n",
+ "89 * \n",
+ "90 NaN \n",
+ "91 * \n",
+ "92 NaN \n",
+ "93 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2014 Estimate \\\n",
+ "0 NaN \n",
+ "1 656,051 \n",
+ "2 48.2% \n",
+ "3 51.8% \n",
+ "4 93.0 \n",
+ ".. ... \n",
+ "89 274,459 \n",
+ "90 NaN \n",
+ "91 462,504 \n",
+ "92 47.0% \n",
+ "93 53.0% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2014 Statistical Significance \n",
+ "0 NaN \n",
+ "1 * \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "4 NaN \n",
+ ".. ... \n",
+ "89 * \n",
+ "90 NaN \n",
+ "91 * \n",
+ "92 NaN \n",
+ "93 NaN \n",
+ "\n",
+ "[94 rows x 10 columns]"
+ ]
+ },
+ "execution_count": 173,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 175,
+ "id": "aa6e12d5-fe02-44b5-b18c-99594fbdce10",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0 SEX AND AGE\n",
+ "1 Total population\n",
+ "2 Male\n",
+ "3 Female\n",
+ "4 Sex ratio (males per 100 females)\n",
+ " ... \n",
+ "89 Total housing units\n",
+ "90 CITIZEN, VOTING AGE POPULATION\n",
+ "91 Citizen, 18 and over population\n",
+ "92 Male\n",
+ "93 Female\n",
+ "Name: Label (Grouping), Length: 94, dtype: object\n"
+ ]
+ }
+ ],
+ "source": [
+ "df2[\"Label (Grouping)\"] = df2[\"Label (Grouping)\"].str.replace('\\xa0', ' ').str.strip()\n",
+ "print(df2[\"Label (Grouping)\"])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 177,
+ "id": "9f1f97a4-3ca7-495e-a1ca-c6dbdfa23e0e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Label (Grouping) | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2017 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2017 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2016 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2016 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2015 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2015 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2014 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2014 Statistical Significance | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 24 | \n",
+ " 65 years and over | \n",
+ " 11.8% | \n",
+ " 11.7% | \n",
+ " NaN | \n",
+ " 11.0% | \n",
+ " * | \n",
+ " 10.6% | \n",
+ " * | \n",
+ " 10.3% | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 29 | \n",
+ " 65 years and over | \n",
+ " 82,414 | \n",
+ " 79,984 | \n",
+ " NaN | \n",
+ " 74,266 | \n",
+ " * | \n",
+ " 70,871 | \n",
+ " * | \n",
+ " 67,857 | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Label (Grouping) \\\n",
+ "24 65 years and over \n",
+ "29 65 years and over \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 Estimate \\\n",
+ "24 11.8% \n",
+ "29 82,414 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2017 Estimate \\\n",
+ "24 11.7% \n",
+ "29 79,984 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2017 Statistical Significance \\\n",
+ "24 NaN \n",
+ "29 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2016 Estimate \\\n",
+ "24 11.0% \n",
+ "29 74,266 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2016 Statistical Significance \\\n",
+ "24 * \n",
+ "29 * \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2015 Estimate \\\n",
+ "24 10.6% \n",
+ "29 70,871 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2015 Statistical Significance \\\n",
+ "24 * \n",
+ "29 * \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2014 Estimate \\\n",
+ "24 10.3% \n",
+ "29 67,857 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2014 Statistical Significance \n",
+ "24 * \n",
+ "29 * "
+ ]
+ },
+ "execution_count": 177,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "over65_b = df2[df2[\"Label (Grouping)\"] == \"65 years and over\"]\n",
+ "over65_b"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 179,
+ "id": "7428e689-994d-4391-8a99-b7681e6dd6a4",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "row_30b = df2.iloc[[30]]\n",
+ "row_31b = df2.iloc[[31]]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 181,
+ "id": "386a1732-6f0c-4b4f-a523-cb5fc476985b",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Label (Grouping) | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2017 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2017 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2016 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2016 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2015 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2015 Statistical Significance | \n",
+ " Boston city, Suffolk County, Massachusetts!!2014 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2014 Statistical Significance | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 65 years and over | \n",
+ " 11.8% | \n",
+ " 11.7% | \n",
+ " NaN | \n",
+ " 11.0% | \n",
+ " * | \n",
+ " 10.6% | \n",
+ " * | \n",
+ " 10.3% | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 65 years and over | \n",
+ " 82,414 | \n",
+ " 79,984 | \n",
+ " NaN | \n",
+ " 74,266 | \n",
+ " * | \n",
+ " 70,871 | \n",
+ " * | \n",
+ " 67,857 | \n",
+ " * | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Male | \n",
+ " 42.7% | \n",
+ " 42.3% | \n",
+ " NaN | \n",
+ " 41.4% | \n",
+ " NaN | \n",
+ " 41.7% | \n",
+ " NaN | \n",
+ " 41.8% | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Female | \n",
+ " 57.3% | \n",
+ " 57.7% | \n",
+ " NaN | \n",
+ " 58.6% | \n",
+ " NaN | \n",
+ " 58.3% | \n",
+ " NaN | \n",
+ " 58.2% | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Label (Grouping) \\\n",
+ "0 65 years and over \n",
+ "1 65 years and over \n",
+ "2 Male \n",
+ "3 Female \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 Estimate \\\n",
+ "0 11.8% \n",
+ "1 82,414 \n",
+ "2 42.7% \n",
+ "3 57.3% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2017 Estimate \\\n",
+ "0 11.7% \n",
+ "1 79,984 \n",
+ "2 42.3% \n",
+ "3 57.7% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2017 Statistical Significance \\\n",
+ "0 NaN \n",
+ "1 NaN \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2016 Estimate \\\n",
+ "0 11.0% \n",
+ "1 74,266 \n",
+ "2 41.4% \n",
+ "3 58.6% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2016 Statistical Significance \\\n",
+ "0 * \n",
+ "1 * \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2015 Estimate \\\n",
+ "0 10.6% \n",
+ "1 70,871 \n",
+ "2 41.7% \n",
+ "3 58.3% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2015 Statistical Significance \\\n",
+ "0 * \n",
+ "1 * \n",
+ "2 NaN \n",
+ "3 NaN \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2014 Estimate \\\n",
+ "0 10.3% \n",
+ "1 67,857 \n",
+ "2 41.8% \n",
+ "3 58.2% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 - 2014 Statistical Significance \n",
+ "0 * \n",
+ "1 * \n",
+ "2 NaN \n",
+ "3 NaN "
+ ]
+ },
+ "execution_count": 181,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "combined_df2 = pd.concat([over65_b, row_30b, row_31b], ignore_index=True)\n",
+ "combined_df2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 185,
+ "id": "5f175d77-3a2a-4e24-9bf3-6cdc26622bd0",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "combined_df2 = combined_df2.drop(columns=['Boston city, Suffolk County, Massachusetts!!2018 - 2017 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2018 - 2016 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2018 - 2015 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2018 - 2014 Statistical Significance'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 187,
+ "id": "87bf3358-0247-421b-b76e-1c57f4fed259",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Label (Grouping) | \n",
+ " Boston city, Suffolk County, Massachusetts!!2018 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2017 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2016 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2015 Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!2014 Estimate | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 65 years and over | \n",
+ " 11.8% | \n",
+ " 11.7% | \n",
+ " 11.0% | \n",
+ " 10.6% | \n",
+ " 10.3% | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 65 years and over | \n",
+ " 82,414 | \n",
+ " 79,984 | \n",
+ " 74,266 | \n",
+ " 70,871 | \n",
+ " 67,857 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Male | \n",
+ " 42.7% | \n",
+ " 42.3% | \n",
+ " 41.4% | \n",
+ " 41.7% | \n",
+ " 41.8% | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Female | \n",
+ " 57.3% | \n",
+ " 57.7% | \n",
+ " 58.6% | \n",
+ " 58.3% | \n",
+ " 58.2% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Label (Grouping) \\\n",
+ "0 65 years and over \n",
+ "1 65 years and over \n",
+ "2 Male \n",
+ "3 Female \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2018 Estimate \\\n",
+ "0 11.8% \n",
+ "1 82,414 \n",
+ "2 42.7% \n",
+ "3 57.3% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2017 Estimate \\\n",
+ "0 11.7% \n",
+ "1 79,984 \n",
+ "2 42.3% \n",
+ "3 57.7% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2016 Estimate \\\n",
+ "0 11.0% \n",
+ "1 74,266 \n",
+ "2 41.4% \n",
+ "3 58.6% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2015 Estimate \\\n",
+ "0 10.6% \n",
+ "1 70,871 \n",
+ "2 41.7% \n",
+ "3 58.3% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!2014 Estimate \n",
+ "0 10.3% \n",
+ "1 67,857 \n",
+ "2 41.8% \n",
+ "3 58.2% "
+ ]
+ },
+ "execution_count": 187,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "combined_df2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 207,
+ "id": "1a1f5617-c601-4c64-8312-ace24396a3c8",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " NaN | \n",
+ " 2018 | \n",
+ " 2017 | \n",
+ " 2016 | \n",
+ " 2015 | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 65 years and over | \n",
+ " 11.8% | \n",
+ " 11.7% | \n",
+ " 11.0% | \n",
+ " 10.6% | \n",
+ " 10.3% | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 65 years and over | \n",
+ " 82,414 | \n",
+ " 79,984 | \n",
+ " 74,266 | \n",
+ " 70,871 | \n",
+ " 67,857 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Male | \n",
+ " 42.7% | \n",
+ " 42.3% | \n",
+ " 41.4% | \n",
+ " 41.7% | \n",
+ " 41.8% | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Female | \n",
+ " 57.3% | \n",
+ " 57.7% | \n",
+ " 58.6% | \n",
+ " 58.3% | \n",
+ " 58.2% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " NaN 2018 2017 2016 2015 2014\n",
+ "0 65 years and over 11.8% 11.7% 11.0% 10.6% 10.3%\n",
+ "1 65 years and over 82,414 79,984 74,266 70,871 67,857\n",
+ "2 Male 42.7% 42.3% 41.4% 41.7% 41.8%\n",
+ "3 Female 57.3% 57.7% 58.6% 58.3% 58.2%"
+ ]
+ },
+ "execution_count": 207,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "combined_df2.columns = combined_df2.columns.str.extract(r'(\\d{4})', expand=False)\n",
+ "combined_df2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 215,
+ "id": "83ce9719-afde-427d-a12b-b391b55816db",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "combined_df2.rename(columns={np.nan: 'Labels'}, inplace=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 217,
+ "id": "549c9a44-3cc6-4b00-81a6-ac2683276970",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Labels | \n",
+ " 2018 | \n",
+ " 2017 | \n",
+ " 2016 | \n",
+ " 2015 | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 65 years and over | \n",
+ " 11.8% | \n",
+ " 11.7% | \n",
+ " 11.0% | \n",
+ " 10.6% | \n",
+ " 10.3% | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 65 years and over | \n",
+ " 82,414 | \n",
+ " 79,984 | \n",
+ " 74,266 | \n",
+ " 70,871 | \n",
+ " 67,857 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Male | \n",
+ " 42.7% | \n",
+ " 42.3% | \n",
+ " 41.4% | \n",
+ " 41.7% | \n",
+ " 41.8% | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Female | \n",
+ " 57.3% | \n",
+ " 57.7% | \n",
+ " 58.6% | \n",
+ " 58.3% | \n",
+ " 58.2% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Labels 2018 2017 2016 2015 2014\n",
+ "0 65 years and over 11.8% 11.7% 11.0% 10.6% 10.3%\n",
+ "1 65 years and over 82,414 79,984 74,266 70,871 67,857\n",
+ "2 Male 42.7% 42.3% 41.4% 41.7% 41.8%\n",
+ "3 Female 57.3% 57.7% 58.6% 58.3% 58.2%"
+ ]
+ },
+ "execution_count": 217,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "combined_df2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 219,
+ "id": "8f4e30bf-0a40-4495-833f-e2b96fcb07bc",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "combined_df2 = combined_df2.drop(columns=['Labels'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 243,
+ "id": "6db5cbf6-dea1-4d16-8370-a85c9d1a6c32",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "over65 = pd.concat([combined_df1, combined_df2], axis=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 245,
+ "id": "78038198-f2d7-47ce-b9c1-ad424e75e43d",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Labels | \n",
+ " 2023 | \n",
+ " 2022 | \n",
+ " 2021 | \n",
+ " 2019 | \n",
+ " 2018 | \n",
+ " 2017 | \n",
+ " 2016 | \n",
+ " 2015 | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " 65 years and over | \n",
+ " 13.4% | \n",
+ " 12.9% | \n",
+ " 12.7% | \n",
+ " 12.0% | \n",
+ " 11.8% | \n",
+ " 11.7% | \n",
+ " 11.0% | \n",
+ " 10.6% | \n",
+ " 10.3% | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " 65 years and over | \n",
+ " 87,610 | \n",
+ " 83,638 | \n",
+ " 83,078 | \n",
+ " 83,656 | \n",
+ " 82,414 | \n",
+ " 79,984 | \n",
+ " 74,266 | \n",
+ " 70,871 | \n",
+ " 67,857 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Male | \n",
+ " 43.5% | \n",
+ " 43.5% | \n",
+ " 43.3% | \n",
+ " 41.6% | \n",
+ " 42.7% | \n",
+ " 42.3% | \n",
+ " 41.4% | \n",
+ " 41.7% | \n",
+ " 41.8% | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Female | \n",
+ " 56.5% | \n",
+ " 56.5% | \n",
+ " 56.7% | \n",
+ " 58.4% | \n",
+ " 57.3% | \n",
+ " 57.7% | \n",
+ " 58.6% | \n",
+ " 58.3% | \n",
+ " 58.2% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Labels 2023 2022 2021 2019 2018 2017 2016 \\\n",
+ "0 65 years and over 13.4% 12.9% 12.7% 12.0% 11.8% 11.7% 11.0% \n",
+ "1 65 years and over 87,610 83,638 83,078 83,656 82,414 79,984 74,266 \n",
+ "2 Male 43.5% 43.5% 43.3% 41.6% 42.7% 42.3% 41.4% \n",
+ "3 Female 56.5% 56.5% 56.7% 58.4% 57.3% 57.7% 58.6% \n",
+ "\n",
+ " 2015 2014 \n",
+ "0 10.6% 10.3% \n",
+ "1 70,871 67,857 \n",
+ "2 41.7% 41.8% \n",
+ "3 58.3% 58.2% "
+ ]
+ },
+ "execution_count": 245,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "over65"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 229,
+ "id": "62fed11a-f636-44e5-b4d3-a73937e90866",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "file_name = 'over65.csv'\n",
+ "over65.to_csv(file_name, index=False)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "42b9c1be",
+ "metadata": {},
+ "source": [
+ "#### Plotting the trends for total population over 65 along with a gender-wise distribution "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 253,
+ "id": "791ef26a-2d15-4751-a809-4091110f020a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "percentage_data = over65.iloc[[0, 2, 3]].copy()\n",
+ "\n",
+ "# Remove the '%' sign and convert to numeric values\n",
+ "for col in percentage_data.columns[1:]:\n",
+ " percentage_data[col] = percentage_data[col].str.rstrip('%').astype(float)\n",
+ "\n",
+ "# Set the labels as the index\n",
+ "percentage_data.set_index('Labels', inplace=True)\n",
+ "\n",
+ "# Transpose the dataframe for plotting\n",
+ "percentage_data = percentage_data.T"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 285,
+ "id": "1e39ea86-6f15-4739-adb1-395ae4f92ee2",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Reordering the columns to display the years in ascending order\n",
+ "percentage_data = percentage_data.sort_index(ascending=True)\n",
+ "\n",
+ "# Plot for '65 years and over' (Total Population)\n",
+ "plt.figure(figsize=(8, 5))\n",
+ "sns.lineplot(data=percentage_data['65 years and over'], marker='o', color='green')\n",
+ "plt.title('Trend of Total Population 65 Years and Over (Percentage)')\n",
+ "plt.xlabel('Year')\n",
+ "plt.ylabel('Percentage (Total)')\n",
+ "plt.xticks(rotation=45)\n",
+ "plt.grid(True)\n",
+ "plt.tight_layout()\n",
+ "plt.show()\n",
+ "\n",
+ "last_two_columns = percentage_data.iloc[:, -2:]\n",
+ "\n",
+ "plt.figure(figsize=(8, 5))\n",
+ "for column in last_two_columns.columns:\n",
+ " plt.plot(last_two_columns.index, last_two_columns[column], marker='o', label=column)\n",
+ "\n",
+ "# Add titles and labels\n",
+ "plt.title('Trend for Last Two Columns')\n",
+ "plt.xlabel('Index')\n",
+ "plt.ylabel('Values')\n",
+ "plt.legend(title='Columns')\n",
+ "plt.grid(True)\n",
+ "plt.xticks(rotation=45)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "4c530edb-869d-404e-b317-4ed32033c0a4",
+ "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": "3.12.7"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/fa24-team-a/Population and Displacement/Population - Race.ipynb b/fa24-team-a/Population and Displacement/Population - Race.ipynb
new file mode 100644
index 00000000..8496449c
--- /dev/null
+++ b/fa24-team-a/Population and Displacement/Population - Race.ipynb
@@ -0,0 +1,1924 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "f8359f74",
+ "metadata": {},
+ "source": [
+ "## Population and Displacement - Race ethnicity (% of different populations)\n",
+ "\n",
+ "In this analysis, we explore Population Displacement Metrics with a focus on changes in demographics over time across various racial and ethnic groups. Using census data from 2014 to 2023, this notebook examines Population by Race and Ethnicity: Understanding the percentage distribution of different racial and ethnic populations helps identify groups disproportionately affected by housing, socioeconomic, and policy changes over time.\n",
+ "\n",
+ "\n",
+ "*The primary objective of this analysis is to identify the trends in population changes across various racial/ethnic groups.*\n",
+ "\n",
+ "\n",
+ "The dataset used in this analysis is derived from census data collected from 2014 to 2023. This dataset includes key demographic metrics, enabling a comprehensive view of population displacement trends over nearly a decade."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e62344b5",
+ "metadata": {},
+ "source": [
+ "#### Importing libraries and performing Exploratory Data Analysis"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 105,
+ "id": "8745de7a-e06c-4d0c-a59f-1f3685418b74",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pandas as pd\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "import seaborn as sns"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 273,
+ "id": "dccb8ba1-46a4-44d3-b5d3-f2d2f260d5b6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df1 = pd.read_csv('Demographics(2023-2019).csv')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 275,
+ "id": "af139386-1cc4-4618-9f02-fa73f618b62c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df2 = pd.read_csv('Demographics(2018-2014).csv')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 277,
+ "id": "9d735d1e-5cdc-46a8-9ab3-535f3ad1ff5e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df1[\"Label (Grouping)\"] = df1[\"Label (Grouping)\"].str.replace('\\xa0', ' ').str.strip()\n",
+ "df2[\"Label (Grouping)\"] = df2[\"Label (Grouping)\"].str.replace('\\xa0', ' ').str.strip()\n",
+ "\n",
+ "df1 = df1.drop(columns=['Boston city, Suffolk County, Massachusetts!!2023 - 2022 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2023 - 2021 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2020 Estimate',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2023 - 2020 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2023 - 2019 Statistical Significance'])\n",
+ "\n",
+ "df2 = df2.drop(columns=['Boston city, Suffolk County, Massachusetts!!2018 - 2017 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2018 - 2016 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2018 - 2015 Statistical Significance',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!2018 - 2014 Statistical Significance'])\n",
+ "\n",
+ "df1.columns = df1.columns.str.extract(r'(\\d{4})', expand=False)\n",
+ "df2.columns = df2.columns.str.extract(r'(\\d{4})', expand=False)\n",
+ "\n",
+ "df1.rename(columns={np.nan: 'Labels'}, inplace=True)\n",
+ "df2.rename(columns={np.nan: 'Labels'}, inplace=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 281,
+ "id": "4487c3ae-56e2-4271-8266-dac8e7b0daaf",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df2_race = df2.drop(columns=['Labels'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 447,
+ "id": "fa8a4050-1a6b-44ed-9b02-2d2b29e50350",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "race = pd.concat([df1, df2_race], axis=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 285,
+ "id": "49204bed-ccf7-49cc-b674-1eab673956bc",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Labels | \n",
+ " 2023 | \n",
+ " 2022 | \n",
+ " 2021 | \n",
+ " 2019 | \n",
+ " 2018 | \n",
+ " 2017 | \n",
+ " 2016 | \n",
+ " 2015 | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " SEX AND AGE | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " Total population | \n",
+ " 652,442 | \n",
+ " 649,768 | \n",
+ " 654,281 | \n",
+ " 694,295 | \n",
+ " 695,926 | \n",
+ " 683,015 | \n",
+ " 672,840 | \n",
+ " 669,469 | \n",
+ " 656,051 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Male | \n",
+ " 48.1% | \n",
+ " 48.5% | \n",
+ " 48.2% | \n",
+ " 47.8% | \n",
+ " 48.0% | \n",
+ " 48.3% | \n",
+ " 48.0% | \n",
+ " 48.1% | \n",
+ " 48.2% | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Female | \n",
+ " 51.9% | \n",
+ " 51.5% | \n",
+ " 51.8% | \n",
+ " 52.2% | \n",
+ " 52.0% | \n",
+ " 51.7% | \n",
+ " 52.0% | \n",
+ " 51.9% | \n",
+ " 51.8% | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " Sex ratio (males per 100 females) | \n",
+ " 92.8 | \n",
+ " 94.1 | \n",
+ " 92.9 | \n",
+ " 91.7 | \n",
+ " 92.2 | \n",
+ " 93.4 | \n",
+ " 92.4 | \n",
+ " 92.8 | \n",
+ " 93.0 | \n",
+ "
\n",
+ " \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ "
\n",
+ " \n",
+ " 94 | \n",
+ " Total housing units | \n",
+ " 313,752 | \n",
+ " 307,836 | \n",
+ " 307,025 | \n",
+ " 303,791 | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 95 | \n",
+ " CITIZEN, VOTING AGE POPULATION | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 96 | \n",
+ " Citizen, 18 and over population | \n",
+ " 478,610 | \n",
+ " 479,717 | \n",
+ " 475,111 | \n",
+ " 496,231 | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 97 | \n",
+ " Male | \n",
+ " 46.7% | \n",
+ " 46.7% | \n",
+ " 47.1% | \n",
+ " 46.6% | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 98 | \n",
+ " Female | \n",
+ " 53.3% | \n",
+ " 53.3% | \n",
+ " 52.9% | \n",
+ " 53.4% | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
99 rows × 10 columns
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Labels 2023 2022 2021 2019 \\\n",
+ "0 SEX AND AGE NaN NaN NaN NaN \n",
+ "1 Total population 652,442 649,768 654,281 694,295 \n",
+ "2 Male 48.1% 48.5% 48.2% 47.8% \n",
+ "3 Female 51.9% 51.5% 51.8% 52.2% \n",
+ "4 Sex ratio (males per 100 females) 92.8 94.1 92.9 91.7 \n",
+ ".. ... ... ... ... ... \n",
+ "94 Total housing units 313,752 307,836 307,025 303,791 \n",
+ "95 CITIZEN, VOTING AGE POPULATION NaN NaN NaN NaN \n",
+ "96 Citizen, 18 and over population 478,610 479,717 475,111 496,231 \n",
+ "97 Male 46.7% 46.7% 47.1% 46.6% \n",
+ "98 Female 53.3% 53.3% 52.9% 53.4% \n",
+ "\n",
+ " 2018 2017 2016 2015 2014 \n",
+ "0 NaN NaN NaN NaN NaN \n",
+ "1 695,926 683,015 672,840 669,469 656,051 \n",
+ "2 48.0% 48.3% 48.0% 48.1% 48.2% \n",
+ "3 52.0% 51.7% 52.0% 51.9% 51.8% \n",
+ "4 92.2 93.4 92.4 92.8 93.0 \n",
+ ".. ... ... ... ... ... \n",
+ "94 NaN NaN NaN NaN NaN \n",
+ "95 NaN NaN NaN NaN NaN \n",
+ "96 NaN NaN NaN NaN NaN \n",
+ "97 NaN NaN NaN NaN NaN \n",
+ "98 NaN NaN NaN NaN NaN \n",
+ "\n",
+ "[99 rows x 10 columns]"
+ ]
+ },
+ "execution_count": 285,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "race"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 139,
+ "id": "2a32044f-a198-44e5-8fe7-32f5f5a86870",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "r1 = race.iloc[34:37]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 141,
+ "id": "aca93106-1963-4c7a-b6ef-62ba0146ea80",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Labels | \n",
+ " 2023 | \n",
+ " 2022 | \n",
+ " 2021 | \n",
+ " 2019 | \n",
+ " 2018 | \n",
+ " 2017 | \n",
+ " 2016 | \n",
+ " 2015 | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 34 | \n",
+ " Total population | \n",
+ " 652,442 | \n",
+ " 649,768 | \n",
+ " 654,281 | \n",
+ " 694,295 | \n",
+ " 695,926 | \n",
+ " 683,015 | \n",
+ " 672,840 | \n",
+ " 669,469 | \n",
+ " 656,051 | \n",
+ "
\n",
+ " \n",
+ " 35 | \n",
+ " One race | \n",
+ " 85.8% | \n",
+ " 84.5% | \n",
+ " 83.0% | \n",
+ " 93.7% | \n",
+ " 94.2% | \n",
+ " 95.9% | \n",
+ " 94.3% | \n",
+ " 95.5% | \n",
+ " 95.2% | \n",
+ "
\n",
+ " \n",
+ " 36 | \n",
+ " Two or More Races | \n",
+ " 14.2% | \n",
+ " 15.5% | \n",
+ " 17.0% | \n",
+ " 6.3% | \n",
+ " 5.8% | \n",
+ " 4.1% | \n",
+ " 5.7% | \n",
+ " 4.5% | \n",
+ " 4.8% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Labels 2023 2022 2021 2019 2018 2017 \\\n",
+ "34 Total population 652,442 649,768 654,281 694,295 695,926 683,015 \n",
+ "35 One race 85.8% 84.5% 83.0% 93.7% 94.2% 95.9% \n",
+ "36 Two or More Races 14.2% 15.5% 17.0% 6.3% 5.8% 4.1% \n",
+ "\n",
+ " 2016 2015 2014 \n",
+ "34 672,840 669,469 656,051 \n",
+ "35 94.3% 95.5% 95.2% \n",
+ "36 5.7% 4.5% 4.8% "
+ ]
+ },
+ "execution_count": 141,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "r1"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "81442210",
+ "metadata": {},
+ "source": [
+ "#### Plotting trend of population on race"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 487,
+ "id": "8ad46e88-379d-4803-b89b-e5dd9591a568",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "g1 = r1.iloc[[1, 2]].copy()\n",
+ "\n",
+ "# Remove the '%' sign and convert to numeric values\n",
+ "for col in g1.columns[1:]:\n",
+ " g1[col] = g1[col].str.rstrip('%').astype(float)\n",
+ "\n",
+ "# Set the labels as the index\n",
+ "g1.set_index('Labels', inplace=True)\n",
+ "\n",
+ "# Transpose the dataframe for plotting\n",
+ "g1 = g1.T\n",
+ "\n",
+ "g1 = g1.sort_index(ascending=True)\n",
+ "\n",
+ "# Plot the trends using seaborn and matplotlib\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.lineplot(data=g1, markers=True, dashes=False)\n",
+ "\n",
+ "# Add plot labels and title\n",
+ "plt.title('Trend of Population on Race')\n",
+ "plt.xlabel('Year')\n",
+ "plt.ylabel('Percentage (Total)')\n",
+ "plt.xticks(rotation=45)\n",
+ "plt.legend(title='Category')\n",
+ "plt.grid(True)\n",
+ "\n",
+ "# Display the plot\n",
+ "plt.tight_layout()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 207,
+ "id": "428584da-f0f8-4b11-8f64-787f4074f5b7",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "r2 = race.iloc[38:41]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 209,
+ "id": "5ab8c2d3-076d-4df4-baca-271229b60684",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Labels | \n",
+ " 2023 | \n",
+ " 2022 | \n",
+ " 2021 | \n",
+ " 2019 | \n",
+ " 2018 | \n",
+ " 2017 | \n",
+ " 2016 | \n",
+ " 2015 | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 38 | \n",
+ " White | \n",
+ " 46.1% | \n",
+ " 45.2% | \n",
+ " 45.6% | \n",
+ " 53.2% | \n",
+ " 52.5% | \n",
+ " 52.8% | \n",
+ " 53.2% | \n",
+ " 52.7% | \n",
+ " 53.0% | \n",
+ "
\n",
+ " \n",
+ " 39 | \n",
+ " Black or African American | \n",
+ " 20.3% | \n",
+ " 21.2% | \n",
+ " 20.0% | \n",
+ " 24.9% | \n",
+ " 24.5% | \n",
+ " 25.9% | \n",
+ " 25.8% | \n",
+ " 25.3% | \n",
+ " 24.5% | \n",
+ "
\n",
+ " \n",
+ " 40 | \n",
+ " American Indian and Alaska Native | \n",
+ " 0.2% | \n",
+ " 0.6% | \n",
+ " 0.2% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.2% | \n",
+ " 0.4% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Labels 2023 2022 2021 2019 2018 \\\n",
+ "38 White 46.1% 45.2% 45.6% 53.2% 52.5% \n",
+ "39 Black or African American 20.3% 21.2% 20.0% 24.9% 24.5% \n",
+ "40 American Indian and Alaska Native 0.2% 0.6% 0.2% 0.3% 0.3% \n",
+ "\n",
+ " 2017 2016 2015 2014 \n",
+ "38 52.8% 53.2% 52.7% 53.0% \n",
+ "39 25.9% 25.8% 25.3% 24.5% \n",
+ "40 0.3% 0.3% 0.2% 0.4% "
+ ]
+ },
+ "execution_count": 209,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "r2"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "4b8f1289",
+ "metadata": {},
+ "source": [
+ "#### Plotting trend of particular population race over the years"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 451,
+ "id": "72856aea-e5e9-4cd8-815a-89f1dfa61103",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "asian1 = df1.iloc[49:56]\n",
+ "asian2 = df2.iloc[46:53]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 453,
+ "id": "684fc2a4-d73a-47fc-b552-028e8f4eb578",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Labels | \n",
+ " 2023 | \n",
+ " 2022 | \n",
+ " 2021 | \n",
+ " 2019 | \n",
+ " 2018 | \n",
+ " 2017 | \n",
+ " 2016 | \n",
+ " 2015 | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " Asian Indian | \n",
+ " 1.7% | \n",
+ " 1.7% | \n",
+ " 1.3% | \n",
+ " 1.7% | \n",
+ " 1.5% | \n",
+ " 1.4% | \n",
+ " 1.8% | \n",
+ " 1.2% | \n",
+ " 1.1% | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " Chinese | \n",
+ " 4.5% | \n",
+ " 4.4% | \n",
+ " 4.7% | \n",
+ " 5.3% | \n",
+ " 4.7% | \n",
+ " 4.7% | \n",
+ " 4.8% | \n",
+ " 4.9% | \n",
+ " 4.9% | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Filipino | \n",
+ " 0.5% | \n",
+ " 0.2% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.2% | \n",
+ " 0.2% | \n",
+ " 0.2% | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Japanese | \n",
+ " 0.1% | \n",
+ " 0.0% | \n",
+ " 0.3% | \n",
+ " 0.2% | \n",
+ " 0.2% | \n",
+ " 0.3% | \n",
+ " 0.2% | \n",
+ " 0.1% | \n",
+ " 0.2% | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " Korean | \n",
+ " 0.7% | \n",
+ " 0.8% | \n",
+ " 0.6% | \n",
+ " 0.5% | \n",
+ " 0.4% | \n",
+ " 0.5% | \n",
+ " 0.4% | \n",
+ " 0.7% | \n",
+ " 0.4% | \n",
+ "
\n",
+ " \n",
+ " 5 | \n",
+ " Vietnamese | \n",
+ " 1.8% | \n",
+ " 1.6% | \n",
+ " 1.7% | \n",
+ " 1.2% | \n",
+ " 1.6% | \n",
+ " 1.8% | \n",
+ " 1.7% | \n",
+ " 2.0% | \n",
+ " 1.8% | \n",
+ "
\n",
+ " \n",
+ " 6 | \n",
+ " Other Asian | \n",
+ " 1.1% | \n",
+ " 1.1% | \n",
+ " 0.7% | \n",
+ " 0.5% | \n",
+ " 0.7% | \n",
+ " 0.6% | \n",
+ " 0.7% | \n",
+ " 0.5% | \n",
+ " 1.0% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Labels 2023 2022 2021 2019 2018 2017 2016 2015 2014\n",
+ "0 Asian Indian 1.7% 1.7% 1.3% 1.7% 1.5% 1.4% 1.8% 1.2% 1.1%\n",
+ "1 Chinese 4.5% 4.4% 4.7% 5.3% 4.7% 4.7% 4.8% 4.9% 4.9%\n",
+ "2 Filipino 0.5% 0.2% 0.3% 0.3% 0.3% 0.3% 0.2% 0.2% 0.2%\n",
+ "3 Japanese 0.1% 0.0% 0.3% 0.2% 0.2% 0.3% 0.2% 0.1% 0.2%\n",
+ "4 Korean 0.7% 0.8% 0.6% 0.5% 0.4% 0.5% 0.4% 0.7% 0.4%\n",
+ "5 Vietnamese 1.8% 1.6% 1.7% 1.2% 1.6% 1.8% 1.7% 2.0% 1.8%\n",
+ "6 Other Asian 1.1% 1.1% 0.7% 0.5% 0.7% 0.6% 0.7% 0.5% 1.0%"
+ ]
+ },
+ "execution_count": 453,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "asian = pd.merge(asian1, asian2, on='Labels')\n",
+ "asian"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 455,
+ "id": "461bde29-1de7-44f6-aaf8-e3cf14916045",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/var/folders/9x/vzd90kdj3r31m970q9mvrq6w0000gn/T/ipykernel_10256/4127604266.py:3: SettingWithCopyWarning: \n",
+ "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+ "Try using .loc[row_indexer,col_indexer] = value instead\n",
+ "\n",
+ "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+ " other2['Labels'] = other2['Labels'].replace('Some other race', 'Some Other Race')\n"
+ ]
+ }
+ ],
+ "source": [
+ "other1 = df1.iloc[[61]]\n",
+ "other2 = df2.iloc[[58]]\n",
+ "other2['Labels'] = other2['Labels'].replace('Some other race', 'Some Other Race')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 457,
+ "id": "a18d5732-c86b-4384-94bd-f826bb9a3744",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Labels | \n",
+ " 2023 | \n",
+ " 2022 | \n",
+ " 2021 | \n",
+ " 2019 | \n",
+ " 2018 | \n",
+ " 2017 | \n",
+ " 2016 | \n",
+ " 2015 | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " Some Other Race | \n",
+ " 8.6% | \n",
+ " 7.6% | \n",
+ " 7.5% | \n",
+ " 5.4% | \n",
+ " 7.3% | \n",
+ " 7.2% | \n",
+ " 5.2% | \n",
+ " 7.8% | \n",
+ " 7.5% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Labels 2023 2022 2021 2019 2018 2017 2016 2015 2014\n",
+ "0 Some Other Race 8.6% 7.6% 7.5% 5.4% 7.3% 7.2% 5.2% 7.8% 7.5%"
+ ]
+ },
+ "execution_count": 457,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "other = pd.merge(other1, other2, on='Labels')\n",
+ "other"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 459,
+ "id": "819dd371-1a33-47a5-8474-9080c8685c42",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "one_race = pd.concat([r2, asian, other], ignore_index=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 461,
+ "id": "836450ea-ccef-42fd-b18d-d8938855ceca",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Labels | \n",
+ " 2023 | \n",
+ " 2022 | \n",
+ " 2021 | \n",
+ " 2019 | \n",
+ " 2018 | \n",
+ " 2017 | \n",
+ " 2016 | \n",
+ " 2015 | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " White | \n",
+ " 46.1% | \n",
+ " 45.2% | \n",
+ " 45.6% | \n",
+ " 53.2% | \n",
+ " 52.5% | \n",
+ " 52.8% | \n",
+ " 53.2% | \n",
+ " 52.7% | \n",
+ " 53.0% | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " Black or African American | \n",
+ " 20.3% | \n",
+ " 21.2% | \n",
+ " 20.0% | \n",
+ " 24.9% | \n",
+ " 24.5% | \n",
+ " 25.9% | \n",
+ " 25.8% | \n",
+ " 25.3% | \n",
+ " 24.5% | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " American Indian and Alaska Native | \n",
+ " 0.2% | \n",
+ " 0.6% | \n",
+ " 0.2% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.2% | \n",
+ " 0.4% | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Asian Indian | \n",
+ " 1.7% | \n",
+ " 1.7% | \n",
+ " 1.3% | \n",
+ " 1.7% | \n",
+ " 1.5% | \n",
+ " 1.4% | \n",
+ " 1.8% | \n",
+ " 1.2% | \n",
+ " 1.1% | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " Chinese | \n",
+ " 4.5% | \n",
+ " 4.4% | \n",
+ " 4.7% | \n",
+ " 5.3% | \n",
+ " 4.7% | \n",
+ " 4.7% | \n",
+ " 4.8% | \n",
+ " 4.9% | \n",
+ " 4.9% | \n",
+ "
\n",
+ " \n",
+ " 5 | \n",
+ " Filipino | \n",
+ " 0.5% | \n",
+ " 0.2% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.2% | \n",
+ " 0.2% | \n",
+ " 0.2% | \n",
+ "
\n",
+ " \n",
+ " 6 | \n",
+ " Japanese | \n",
+ " 0.1% | \n",
+ " 0.0% | \n",
+ " 0.3% | \n",
+ " 0.2% | \n",
+ " 0.2% | \n",
+ " 0.3% | \n",
+ " 0.2% | \n",
+ " 0.1% | \n",
+ " 0.2% | \n",
+ "
\n",
+ " \n",
+ " 7 | \n",
+ " Korean | \n",
+ " 0.7% | \n",
+ " 0.8% | \n",
+ " 0.6% | \n",
+ " 0.5% | \n",
+ " 0.4% | \n",
+ " 0.5% | \n",
+ " 0.4% | \n",
+ " 0.7% | \n",
+ " 0.4% | \n",
+ "
\n",
+ " \n",
+ " 8 | \n",
+ " Vietnamese | \n",
+ " 1.8% | \n",
+ " 1.6% | \n",
+ " 1.7% | \n",
+ " 1.2% | \n",
+ " 1.6% | \n",
+ " 1.8% | \n",
+ " 1.7% | \n",
+ " 2.0% | \n",
+ " 1.8% | \n",
+ "
\n",
+ " \n",
+ " 9 | \n",
+ " Other Asian | \n",
+ " 1.1% | \n",
+ " 1.1% | \n",
+ " 0.7% | \n",
+ " 0.5% | \n",
+ " 0.7% | \n",
+ " 0.6% | \n",
+ " 0.7% | \n",
+ " 0.5% | \n",
+ " 1.0% | \n",
+ "
\n",
+ " \n",
+ " 10 | \n",
+ " Some Other Race | \n",
+ " 8.6% | \n",
+ " 7.6% | \n",
+ " 7.5% | \n",
+ " 5.4% | \n",
+ " 7.3% | \n",
+ " 7.2% | \n",
+ " 5.2% | \n",
+ " 7.8% | \n",
+ " 7.5% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Labels 2023 2022 2021 2019 2018 \\\n",
+ "0 White 46.1% 45.2% 45.6% 53.2% 52.5% \n",
+ "1 Black or African American 20.3% 21.2% 20.0% 24.9% 24.5% \n",
+ "2 American Indian and Alaska Native 0.2% 0.6% 0.2% 0.3% 0.3% \n",
+ "3 Asian Indian 1.7% 1.7% 1.3% 1.7% 1.5% \n",
+ "4 Chinese 4.5% 4.4% 4.7% 5.3% 4.7% \n",
+ "5 Filipino 0.5% 0.2% 0.3% 0.3% 0.3% \n",
+ "6 Japanese 0.1% 0.0% 0.3% 0.2% 0.2% \n",
+ "7 Korean 0.7% 0.8% 0.6% 0.5% 0.4% \n",
+ "8 Vietnamese 1.8% 1.6% 1.7% 1.2% 1.6% \n",
+ "9 Other Asian 1.1% 1.1% 0.7% 0.5% 0.7% \n",
+ "10 Some Other Race 8.6% 7.6% 7.5% 5.4% 7.3% \n",
+ "\n",
+ " 2017 2016 2015 2014 \n",
+ "0 52.8% 53.2% 52.7% 53.0% \n",
+ "1 25.9% 25.8% 25.3% 24.5% \n",
+ "2 0.3% 0.3% 0.2% 0.4% \n",
+ "3 1.4% 1.8% 1.2% 1.1% \n",
+ "4 4.7% 4.8% 4.9% 4.9% \n",
+ "5 0.3% 0.2% 0.2% 0.2% \n",
+ "6 0.3% 0.2% 0.1% 0.2% \n",
+ "7 0.5% 0.4% 0.7% 0.4% \n",
+ "8 1.8% 1.7% 2.0% 1.8% \n",
+ "9 0.6% 0.7% 0.5% 1.0% \n",
+ "10 7.2% 5.2% 7.8% 7.5% "
+ ]
+ },
+ "execution_count": 461,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "one_race"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 489,
+ "id": "4d8903f5-0304-4af0-978b-7e9bd5071dc8",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "g2 = one_race.copy()\n",
+ "\n",
+ "# Remove the '%' sign and convert to numeric values\n",
+ "for col in g2.columns[1:]:\n",
+ " g2[col] = g2[col].str.rstrip('%').astype(float)\n",
+ "\n",
+ "# Set the labels as the index\n",
+ "g2.set_index('Labels', inplace=True)\n",
+ "\n",
+ "# Transpose the dataframe for plotting\n",
+ "g2 = g2.T\n",
+ "\n",
+ "g2 = g2.sort_index(ascending=True)\n",
+ "\n",
+ "\n",
+ "# Plot the trends using seaborn and matplotlib\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.lineplot(data=g2, markers=True, dashes=False)\n",
+ "\n",
+ "# Add plot labels and title\n",
+ "plt.title('Trend of One Race Population')\n",
+ "plt.xlabel('Year')\n",
+ "plt.ylabel('Percentage (Total)')\n",
+ "plt.xticks(rotation=45)\n",
+ "plt.legend(title='Category')\n",
+ "plt.grid(True)\n",
+ "\n",
+ "# Display the plot\n",
+ "plt.tight_layout()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 525,
+ "id": "d432c4af-bb3d-4fa0-818c-ffea15c85614",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.figure(figsize=(20, 6))\n",
+ "sns.barplot(data=g2)\n",
+ "\n",
+ "plt.title('Barplot of kinds of One Race')\n",
+ "plt.ylabel('Values')\n",
+ "plt.xticks(rotation=20)\n",
+ "plt.grid(True)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0926e558",
+ "metadata": {},
+ "source": [
+ "#### Plotting the trend of Asian Population"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 493,
+ "id": "ec9932ec-b925-44c5-a34e-f0a45c2b2d57",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "g3 = asian.copy()\n",
+ "\n",
+ "# Remove the '%' sign and convert to numeric values\n",
+ "for col in g3.columns[1:]:\n",
+ " g3[col] = g3[col].str.rstrip('%').astype(float)\n",
+ "\n",
+ "# Set the labels as the index\n",
+ "g3.set_index('Labels', inplace=True)\n",
+ "\n",
+ "# Transpose the dataframe for plotting\n",
+ "g3 = g3.T\n",
+ "\n",
+ "g3 = g3.sort_index(ascending=True)\n",
+ "\n",
+ "\n",
+ "# Plot the trends using seaborn and matplotlib\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.lineplot(data=g3, markers=True, dashes=False)\n",
+ "\n",
+ "# Add plot labels and title\n",
+ "plt.title('Trend of Asian Population')\n",
+ "plt.xlabel('Year')\n",
+ "plt.ylabel('Percentage (Total)')\n",
+ "plt.xticks(rotation=45)\n",
+ "plt.legend(title='Category')\n",
+ "plt.grid(True)\n",
+ "\n",
+ "# Display the plot\n",
+ "plt.tight_layout()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0817876d",
+ "metadata": {},
+ "source": [
+ "#### Plotting the trend of two or more races together over the years"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 501,
+ "id": "6c7ee239-b513-4e5c-932a-fcdde1f672cb",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "extra1 = df1.iloc[63:66]\n",
+ "extra2 = df1.iloc[[67]]\n",
+ "two_or_more1 = pd.concat([extra1, extra2], ignore_index=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 503,
+ "id": "739758b1-20f7-4ea5-89a5-03d2839f59fe",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "two_or_more2 = df2.iloc[60:64]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 505,
+ "id": "9a77100e-23c9-4224-9f93-6c3cbbb71726",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Labels | \n",
+ " 2023 | \n",
+ " 2022 | \n",
+ " 2021 | \n",
+ " 2019 | \n",
+ " 2018 | \n",
+ " 2017 | \n",
+ " 2016 | \n",
+ " 2015 | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " White and Black or African American | \n",
+ " 1.4% | \n",
+ " 1.2% | \n",
+ " 1.0% | \n",
+ " 3.6% | \n",
+ " 3.1% | \n",
+ " 2.4% | \n",
+ " 3.7% | \n",
+ " 2.2% | \n",
+ " 2.5% | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " White and American Indian and Alaska Native | \n",
+ " 0.4% | \n",
+ " 0.2% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.2% | \n",
+ " 0.2% | \n",
+ " 0.2% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " White and Asian | \n",
+ " 1.0% | \n",
+ " 1.0% | \n",
+ " 1.0% | \n",
+ " 0.9% | \n",
+ " 0.9% | \n",
+ " 0.7% | \n",
+ " 0.6% | \n",
+ " 0.7% | \n",
+ " 0.6% | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Black or African American and American Indian ... | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.3% | \n",
+ " 0.1% | \n",
+ " 0.2% | \n",
+ " 0.3% | \n",
+ " 0.1% | \n",
+ " 0.1% | \n",
+ " 0.1% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Labels 2023 2022 2021 2019 \\\n",
+ "0 White and Black or African American 1.4% 1.2% 1.0% 3.6% \n",
+ "1 White and American Indian and Alaska Native 0.4% 0.2% 0.3% 0.3% \n",
+ "2 White and Asian 1.0% 1.0% 1.0% 0.9% \n",
+ "3 Black or African American and American Indian ... 0.3% 0.3% 0.3% 0.1% \n",
+ "\n",
+ " 2018 2017 2016 2015 2014 \n",
+ "0 3.1% 2.4% 3.7% 2.2% 2.5% \n",
+ "1 0.2% 0.2% 0.2% 0.3% 0.3% \n",
+ "2 0.9% 0.7% 0.6% 0.7% 0.6% \n",
+ "3 0.2% 0.3% 0.1% 0.1% 0.1% "
+ ]
+ },
+ "execution_count": 505,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "two_or_more = pd.merge(two_or_more1, two_or_more2, on='Labels')\n",
+ "two_or_more"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 507,
+ "id": "5aa96373-e6af-4a75-a434-21fa712a8c4d",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "g4 = two_or_more.copy()\n",
+ "\n",
+ "# Remove the '%' sign and convert to numeric values\n",
+ "for col in g4.columns[1:]:\n",
+ " g4[col] = g4[col].str.rstrip('%').astype(float)\n",
+ "\n",
+ "# Set the labels as the index\n",
+ "g4.set_index('Labels', inplace=True)\n",
+ "\n",
+ "# Transpose the dataframe for plotting\n",
+ "g4 = g4.T\n",
+ "\n",
+ "g4 = g4.sort_index(ascending=True)\n",
+ "\n",
+ "\n",
+ "# Plot the trends using seaborn and matplotlib\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.lineplot(data=g4, markers=True, dashes=False)\n",
+ "\n",
+ "# Add plot labels and title\n",
+ "plt.title('Trend of Two or More Race Kind Population')\n",
+ "plt.xlabel('Year')\n",
+ "plt.ylabel('Percentage (Total)')\n",
+ "plt.xticks(rotation=45)\n",
+ "plt.legend(title='Category')\n",
+ "plt.grid(True)\n",
+ "\n",
+ "# Display the plot\n",
+ "plt.tight_layout()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 477,
+ "id": "f4a61fab-c7f0-46ef-ae38-bcde5912abf0",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "one_and_more1 = df1.iloc[71:77]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 479,
+ "id": "a3cd4bb9-13c7-4d8e-9d0c-50884ddd4d75",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/var/folders/9x/vzd90kdj3r31m970q9mvrq6w0000gn/T/ipykernel_10256/3090201655.py:2: SettingWithCopyWarning: \n",
+ "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+ "Try using .loc[row_indexer,col_indexer] = value instead\n",
+ "\n",
+ "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+ " one_and_more2['Labels'] = one_and_more2['Labels'].replace('Some other race', 'Some Other Race')\n"
+ ]
+ }
+ ],
+ "source": [
+ "one_and_more2 = df2.iloc[66:72]\n",
+ "one_and_more2['Labels'] = one_and_more2['Labels'].replace('Some other race', 'Some Other Race')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 483,
+ "id": "9f22c3e9-b029-4c01-af72-f689bcb9b6f6",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Labels | \n",
+ " 2023 | \n",
+ " 2022 | \n",
+ " 2021 | \n",
+ " 2019 | \n",
+ " 2018 | \n",
+ " 2017 | \n",
+ " 2016 | \n",
+ " 2015 | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " White | \n",
+ " 56.6% | \n",
+ " 55.8% | \n",
+ " 58.0% | \n",
+ " 58.6% | \n",
+ " 57.4% | \n",
+ " 56.5% | \n",
+ " 58.3% | \n",
+ " 56.5% | \n",
+ " 57.2% | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " Black or African American | \n",
+ " 26.6% | \n",
+ " 28.8% | \n",
+ " 28.8% | \n",
+ " 29.4% | \n",
+ " 28.6% | \n",
+ " 28.8% | \n",
+ " 30.2% | \n",
+ " 28.3% | \n",
+ " 27.6% | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " American Indian and Alaska Native | \n",
+ " 1.4% | \n",
+ " 1.5% | \n",
+ " 1.5% | \n",
+ " 0.9% | \n",
+ " 0.9% | \n",
+ " 0.9% | \n",
+ " 0.9% | \n",
+ " 0.8% | \n",
+ " 0.8% | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Asian | \n",
+ " 12.1% | \n",
+ " 11.2% | \n",
+ " 11.0% | \n",
+ " 11.1% | \n",
+ " 10.8% | \n",
+ " 10.6% | \n",
+ " 10.8% | \n",
+ " 10.5% | \n",
+ " 10.8% | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " Native Hawaiian and Other Pacific Islander | \n",
+ " 0.3% | \n",
+ " 0.1% | \n",
+ " 0.1% | \n",
+ " 0.3% | \n",
+ " 0.1% | \n",
+ " 0.1% | \n",
+ " 0.1% | \n",
+ " 0.1% | \n",
+ " 0.3% | \n",
+ "
\n",
+ " \n",
+ " 5 | \n",
+ " Some Other Race | \n",
+ " 19.3% | \n",
+ " 20.0% | \n",
+ " 21.3% | \n",
+ " 6.3% | \n",
+ " 8.4% | \n",
+ " 7.5% | \n",
+ " 5.7% | \n",
+ " 8.6% | \n",
+ " 8.5% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Labels 2023 2022 2021 2019 \\\n",
+ "0 White 56.6% 55.8% 58.0% 58.6% \n",
+ "1 Black or African American 26.6% 28.8% 28.8% 29.4% \n",
+ "2 American Indian and Alaska Native 1.4% 1.5% 1.5% 0.9% \n",
+ "3 Asian 12.1% 11.2% 11.0% 11.1% \n",
+ "4 Native Hawaiian and Other Pacific Islander 0.3% 0.1% 0.1% 0.3% \n",
+ "5 Some Other Race 19.3% 20.0% 21.3% 6.3% \n",
+ "\n",
+ " 2018 2017 2016 2015 2014 \n",
+ "0 57.4% 56.5% 58.3% 56.5% 57.2% \n",
+ "1 28.6% 28.8% 30.2% 28.3% 27.6% \n",
+ "2 0.9% 0.9% 0.9% 0.8% 0.8% \n",
+ "3 10.8% 10.6% 10.8% 10.5% 10.8% \n",
+ "4 0.1% 0.1% 0.1% 0.1% 0.3% \n",
+ "5 8.4% 7.5% 5.7% 8.6% 8.5% "
+ ]
+ },
+ "execution_count": 483,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "one_and_more = pd.merge(one_and_more1, one_and_more2, on='Labels')\n",
+ "one_and_more"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 509,
+ "id": "5ebdd6bf-a3d9-4be3-ae5d-39a1944ff5a3",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "g5 = one_and_more.copy()\n",
+ "\n",
+ "# Remove the '%' sign and convert to numeric values\n",
+ "for col in g5.columns[1:]:\n",
+ " g5[col] = g5[col].str.rstrip('%').astype(float)\n",
+ "\n",
+ "# Set the labels as the index\n",
+ "g5.set_index('Labels', inplace=True)\n",
+ "\n",
+ "# Transpose the dataframe for plotting\n",
+ "g5 = g5.T\n",
+ "\n",
+ "g5 = g5.sort_index(ascending=True)\n",
+ "\n",
+ "\n",
+ "# Plot the trends using seaborn and matplotlib\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.lineplot(data=g5, markers=True, dashes=False)\n",
+ "\n",
+ "# Add plot labels and title\n",
+ "plt.title('Trend of One and More Race Kind Population')\n",
+ "plt.xlabel('Year')\n",
+ "plt.ylabel('Percentage (Total)')\n",
+ "plt.xticks(rotation=45)\n",
+ "plt.legend(title='Category')\n",
+ "plt.grid(True)\n",
+ "\n",
+ "# Display the plot\n",
+ "plt.tight_layout()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "c394c6e3",
+ "metadata": {},
+ "source": [
+ "#### Plotting the trend of Latino population"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 513,
+ "id": "ca4419bf-8015-4c7b-b4e3-66e71edc5a79",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "latino1 = df1.iloc[80:84]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 515,
+ "id": "09ae2f13-5af6-451f-9183-7f5e1df58b8d",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "latino2 = df2.iloc[75:79]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 521,
+ "id": "8d45ad91-18b1-4832-aea5-d1c8f509e9a9",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Labels | \n",
+ " 2023 | \n",
+ " 2022 | \n",
+ " 2021 | \n",
+ " 2019 | \n",
+ " 2018 | \n",
+ " 2017 | \n",
+ " 2016 | \n",
+ " 2015 | \n",
+ " 2014 | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " Mexican | \n",
+ " 1.4% | \n",
+ " 1.3% | \n",
+ " 1.1% | \n",
+ " 1.3% | \n",
+ " 1.3% | \n",
+ " 1.0% | \n",
+ " 1.1% | \n",
+ " 1.0% | \n",
+ " 1.0% | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " Puerto Rican | \n",
+ " 4.4% | \n",
+ " 4.0% | \n",
+ " 4.6% | \n",
+ " 4.8% | \n",
+ " 4.7% | \n",
+ " 6.2% | \n",
+ " 4.8% | \n",
+ " 5.6% | \n",
+ " 5.0% | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Cuban | \n",
+ " 0.3% | \n",
+ " 0.2% | \n",
+ " 0.3% | \n",
+ " 0.7% | \n",
+ " 0.5% | \n",
+ " 0.4% | \n",
+ " 0.4% | \n",
+ " 0.4% | \n",
+ " 0.3% | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Other Hispanic or Latino | \n",
+ " 13.3% | \n",
+ " 14.5% | \n",
+ " 14.4% | \n",
+ " 12.9% | \n",
+ " 13.5% | \n",
+ " 12.9% | \n",
+ " 12.8% | \n",
+ " 12.5% | \n",
+ " 12.3% | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Labels 2023 2022 2021 2019 2018 2017 2016 \\\n",
+ "0 Mexican 1.4% 1.3% 1.1% 1.3% 1.3% 1.0% 1.1% \n",
+ "1 Puerto Rican 4.4% 4.0% 4.6% 4.8% 4.7% 6.2% 4.8% \n",
+ "2 Cuban 0.3% 0.2% 0.3% 0.7% 0.5% 0.4% 0.4% \n",
+ "3 Other Hispanic or Latino 13.3% 14.5% 14.4% 12.9% 13.5% 12.9% 12.8% \n",
+ "\n",
+ " 2015 2014 \n",
+ "0 1.0% 1.0% \n",
+ "1 5.6% 5.0% \n",
+ "2 0.4% 0.3% \n",
+ "3 12.5% 12.3% "
+ ]
+ },
+ "execution_count": 521,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "latino = pd.merge(latino1, latino2, on='Labels')\n",
+ "latino"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 523,
+ "id": "6bb0ca1e-166d-471d-94bf-9c6c797acc0e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "g6 = latino.copy()\n",
+ "\n",
+ "# Remove the '%' sign and convert to numeric values\n",
+ "for col in g6.columns[1:]:\n",
+ " g6[col] = g6[col].str.rstrip('%').astype(float)\n",
+ "\n",
+ "# Set the labels as the index\n",
+ "g6.set_index('Labels', inplace=True)\n",
+ "\n",
+ "# Transpose the dataframe for plotting\n",
+ "g6 = g6.T\n",
+ "\n",
+ "g6 = g6.sort_index(ascending=True)\n",
+ "\n",
+ "\n",
+ "# Plot the trends using seaborn and matplotlib\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.lineplot(data=g6, markers=True, dashes=False)\n",
+ "\n",
+ "# Add plot labels and title\n",
+ "plt.title('Trend of Latino Population')\n",
+ "plt.xlabel('Year')\n",
+ "plt.ylabel('Percentage (Total)')\n",
+ "plt.xticks(rotation=45)\n",
+ "plt.legend(title='Category')\n",
+ "plt.grid(True)\n",
+ "\n",
+ "# Display the plot\n",
+ "plt.tight_layout()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "b81b04ea-f99a-4016-b7d8-0ccaea465a77",
+ "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": "3.12.7"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/fa24-team-a/Population and Displacement/poverty_analysis.ipynb b/fa24-team-a/Population and Displacement/poverty_analysis.ipynb
new file mode 100644
index 00000000..f566e83e
--- /dev/null
+++ b/fa24-team-a/Population and Displacement/poverty_analysis.ipynb
@@ -0,0 +1,1161 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 141,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import seaborn as sns\n",
+ "import pandas as pd\n",
+ "import matplotlib.pyplot as plt\n",
+ "import geopandas as gpd"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Importing dataset for 2013-2023 and combining the dataset to visualize the trends. Combined_df used for the merged datasets"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 144,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import glob\n",
+ "\n",
+ "# path to the files \n",
+ "path = \"poverty_*.csv\"\n",
+ "files = glob.glob(path)\n",
+ "\n",
+ "# Extract year from filename and add it as a column\n",
+ "df_list = []\n",
+ "for file in files:\n",
+ " year = int(file.split('_')[-1].split('.')[0]) \n",
+ " df = pd.read_csv(file)\n",
+ " df['year'] = year\n",
+ " df_list.append(df)\n",
+ "\n",
+ "combined_df = pd.concat(df_list, ignore_index=True)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 146,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "RangeIndex: 655 entries, 0 to 654\n",
+ "Data columns (total 8 columns):\n",
+ " # Column Non-Null Count Dtype \n",
+ "--- ------ -------------- ----- \n",
+ " 0 Label (Grouping) 655 non-null object\n",
+ " 1 Boston city, Suffolk County, Massachusetts!!Total!!Estimate 583 non-null object\n",
+ " 2 Boston city, Suffolk County, Massachusetts!!Total!!Margin of Error 583 non-null object\n",
+ " 3 Boston city, Suffolk County, Massachusetts!!Below poverty level!!Estimate 583 non-null object\n",
+ " 4 Boston city, Suffolk County, Massachusetts!!Below poverty level!!Margin of Error 583 non-null object\n",
+ " 5 Boston city, Suffolk County, Massachusetts!!Percent below poverty level!!Estimate 583 non-null object\n",
+ " 6 Boston city, Suffolk County, Massachusetts!!Percent below poverty level!!Margin of Error 583 non-null object\n",
+ " 7 year 655 non-null int64 \n",
+ "dtypes: int64(1), object(7)\n",
+ "memory usage: 41.1+ KB\n",
+ "None\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(combined_df.info())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 148,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " Label (Grouping) | \n",
+ " Boston city, Suffolk County, Massachusetts!!Total!!Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!Total!!Margin of Error | \n",
+ " Boston city, Suffolk County, Massachusetts!!Below poverty level!!Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!Below poverty level!!Margin of Error | \n",
+ " Boston city, Suffolk County, Massachusetts!!Percent below poverty level!!Estimate | \n",
+ " Boston city, Suffolk County, Massachusetts!!Percent below poverty level!!Margin of Error | \n",
+ " year | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " Population for whom poverty status is determined | \n",
+ " 651,689 | \n",
+ " ±5,184 | \n",
+ " 111,442 | \n",
+ " ±8,138 | \n",
+ " 17.1% | \n",
+ " ±1.2 | \n",
+ " 2019 | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " AGE | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " 2019 | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " Under 18 years | \n",
+ " 104,108 | \n",
+ " ±3,210 | \n",
+ " 25,043 | \n",
+ " ±4,676 | \n",
+ " 24.1% | \n",
+ " ±4.4 | \n",
+ " 2019 | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " Under 5 years | \n",
+ " 31,264 | \n",
+ " ±2,040 | \n",
+ " 5,210 | \n",
+ " ±1,759 | \n",
+ " 16.7% | \n",
+ " ±5.5 | \n",
+ " 2019 | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " 5 to 17 years | \n",
+ " 72,844 | \n",
+ " ±2,636 | \n",
+ " 19,833 | \n",
+ " ±3,973 | \n",
+ " 27.2% | \n",
+ " ±5.3 | \n",
+ " 2019 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " Label (Grouping) \\\n",
+ "0 Population for whom poverty status is determined \n",
+ "1 AGE \n",
+ "2 Under 18 years \n",
+ "3 Under 5 years \n",
+ "4 5 to 17 years \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!Total!!Estimate \\\n",
+ "0 651,689 \n",
+ "1 NaN \n",
+ "2 104,108 \n",
+ "3 31,264 \n",
+ "4 72,844 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!Total!!Margin of Error \\\n",
+ "0 ±5,184 \n",
+ "1 NaN \n",
+ "2 ±3,210 \n",
+ "3 ±2,040 \n",
+ "4 ±2,636 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!Below poverty level!!Estimate \\\n",
+ "0 111,442 \n",
+ "1 NaN \n",
+ "2 25,043 \n",
+ "3 5,210 \n",
+ "4 19,833 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!Below poverty level!!Margin of Error \\\n",
+ "0 ±8,138 \n",
+ "1 NaN \n",
+ "2 ±4,676 \n",
+ "3 ±1,759 \n",
+ "4 ±3,973 \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!Percent below poverty level!!Estimate \\\n",
+ "0 17.1% \n",
+ "1 NaN \n",
+ "2 24.1% \n",
+ "3 16.7% \n",
+ "4 27.2% \n",
+ "\n",
+ " Boston city, Suffolk County, Massachusetts!!Percent below poverty level!!Margin of Error \\\n",
+ "0 ±1.2 \n",
+ "1 NaN \n",
+ "2 ±4.4 \n",
+ "3 ±5.5 \n",
+ "4 ±5.3 \n",
+ "\n",
+ " year \n",
+ "0 2019 \n",
+ "1 2019 \n",
+ "2 2019 \n",
+ "3 2019 \n",
+ "4 2019 "
+ ]
+ },
+ "execution_count": 148,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "combined_df.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 150,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[2019 2018 2021 2023 2022 2013 2015 2014 2016 2017]\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(combined_df['year'].unique())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 152,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[2013 2014 2015 2016 2017 2018 2019 2021 2022 2023]\n",
+ "Index(['Label (Grouping)',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!Total!!Estimate',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!Total!!Margin of Error',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!Below poverty level!!Estimate',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!Below poverty level!!Margin of Error',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!Percent below poverty level!!Estimate',\n",
+ " 'Boston city, Suffolk County, Massachusetts!!Percent below poverty level!!Margin of Error',\n",
+ " 'year'],\n",
+ " dtype='object')\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Sort the DataFrame by the 'year' column\n",
+ "combined_df.sort_values(by='year', inplace=True)\n",
+ "\n",
+ "# Reset the index \n",
+ "combined_df.reset_index(drop=True, inplace=True)\n",
+ "print(combined_df['year'].unique())\n",
+ "\n",
+ "print(combined_df.columns)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 154,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "combined_df.columns = [\n",
+ " \"label\", \"total_estimate\", \"total_margin_error\", \n",
+ " \"below_poverty_estimate\", \"below_poverty_margin_error\",\n",
+ " \"percent_below_poverty_estimate\", \"percent_below_poverty_margin_error\", \"year\"\n",
+ "]\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 156,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['Worked full-time, year-round in the past 12 months' 'SEX'\n",
+ " '65 years and over' '18 to 64 years' 'Related children under 18 years'\n",
+ " 'Under 18 years' 'AGE' 'Population for whom poverty status is determined'\n",
+ " 'Worked part-time or part-year in the past 12 months' 'Did not work'\n",
+ " 'All Individuals below:' '50 percent of poverty level' 'Male'\n",
+ " '125 percent of poverty level' '185 percent of poverty level'\n",
+ " '200 percent of poverty level'\n",
+ " 'Unrelated individuals for whom poverty status is determined' 'Female'\n",
+ " 'Mean income deficit for unrelated individuals (dollars)'\n",
+ " 'Worked less than full-time, year-round in the past 12 months'\n",
+ " 'PERCENT IMPUTED' 'Poverty status for individuals'\n",
+ " '150 percent of poverty level' 'Population 16 years and over' 'One race'\n",
+ " 'WORK EXPERIENCE' 'Unemployed' 'Employed'\n",
+ " 'Civilian labor force 16 years and over' 'EMPLOYMENT STATUS'\n",
+ " \"Bachelor's degree or higher\" \"Some college, associate's degree\"\n",
+ " 'High school graduate (includes equivalency)'\n",
+ " 'RACE AND HISPANIC OR LATINO ORIGIN' 'Population 25 years and over'\n",
+ " 'EDUCATIONAL ATTAINMENT' 'White alone, not Hispanic or Latino'\n",
+ " 'Hispanic or Latino origin (of any race)' 'Two or more races'\n",
+ " 'Some other race' 'Native Hawaiian and Other Pacific Islander' 'Asian'\n",
+ " 'American Indian and Alaska Native' 'Black or African American' 'White'\n",
+ " 'Less than high school graduate' '75 years and over' '65 to 74 years'\n",
+ " '15 years' '45 to 54 years' '55 to 64 years' 'Some other race alone'\n",
+ " 'Native Hawaiian and Other Pacific Islander alone' 'Asian alone'\n",
+ " 'American Indian and Alaska Native alone'\n",
+ " 'Black or African American alone' 'White alone' '60 years and over'\n",
+ " '35 to 64 years' '18 to 34 years'\n",
+ " 'Related children of householder under 18 years' '5 to 17 years'\n",
+ " 'Under 5 years' '35 to 44 years' '25 to 34 years' '18 to 24 years'\n",
+ " '16 to 17 years'\n",
+ " 'UNRELATED INDIVIDUALS FOR WHOM POVERTY STATUS IS DETERMINED'\n",
+ " '400 percent of poverty level' '300 percent of poverty level'\n",
+ " '500 percent of poverty level'\n",
+ " 'ALL INDIVIDUALS WITH INCOME BELOW THE FOLLOWING POVERTY RATIOS'\n",
+ " 'Population in housing units for whom poverty status is determined']\n"
+ ]
+ }
+ ],
+ "source": [
+ "def clean_string_columns(df):\n",
+ " for col in df.select_dtypes(include=['object']).columns:\n",
+ " df[col] = df[col].str.replace('\\xa0', '', regex=False).str.strip()\n",
+ " return df\n",
+ "\n",
+ "# Clean the entire DataFrame\n",
+ "combined_df = clean_string_columns(combined_df)\n",
+ "\n",
+ "# Verify the cleaned data\n",
+ "print(combined_df['label'].unique())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 158,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " label total_estimate \\\n",
+ "0 Worked full-time, year-round in the past 12 mo... 225,670 \n",
+ "1 SEX NaN \n",
+ "2 65 years and over 65,127 \n",
+ "3 18 to 64 years 432,336 \n",
+ "4 Related children under 18 years 104,877 \n",
+ "\n",
+ " total_margin_error below_poverty_estimate below_poverty_margin_error \\\n",
+ "0 ±5,704 4,245 ±1,703 \n",
+ "1 NaN NaN NaN \n",
+ "2 ±1,930 11,903 ±1,440 \n",
+ "3 ±3,386 86,576 ±5,543 \n",
+ "4 ±2,588 31,272 ±4,001 \n",
+ "\n",
+ " percent_below_poverty_estimate percent_below_poverty_margin_error year \n",
+ "0 1.9% ±0.7 2013 \n",
+ "1 NaN NaN 2013 \n",
+ "2 18.3% ±2.2 2013 \n",
+ "3 20.0% ±1.2 2013 \n",
+ "4 29.8% ±3.7 2013 \n"
+ ]
+ }
+ ],
+ "source": [
+ "print(combined_df.head())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Visualizing total population vs below poverty line population over the years"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 161,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Population Trend DataFrame:\n",
+ " year total_population below_poverty_population\n",
+ "7 2013 602704.0 130115.0\n",
+ "76 2014 612873.0 138625.0\n",
+ "142 2015 626152.0 128385.0\n",
+ "188 2016 628333.0 131871.0\n",
+ "286 2017 642003.0 119925.0\n",
+ "370 2018 653169.0 118946.0\n",
+ "380 2019 651689.0 111442.0\n",
+ "495 2021 610081.0 114198.0\n",
+ "576 2022 608933.0 103901.0\n",
+ "586 2023 608599.0 95207.0\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/var/folders/nz/yglwkh0d003_mjjfnfrm07y40000gn/T/ipykernel_1331/1741151318.py:15: SettingWithCopyWarning: \n",
+ "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+ "Try using .loc[row_indexer,col_indexer] = value instead\n",
+ "\n",
+ "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+ " total_population['total_estimate'] = total_population['total_estimate'].str.replace(',', '').astype(float)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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