3_visualizations/figure_9.ipynb

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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create Figure 9"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from plotly.subplots import make_subplots\n",
    "import plotly.graph_objects as go"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "csv_file_path = '../2_processing/7_weekly_survey_with_personality_no_nan_one_response_per_week.csv'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Read data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the CSV file into a DataFrame\n",
    "df_weekly = pd.read_csv(csv_file_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create Figure 9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
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          "Always",
          "Often",
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          "text": "Conscientiousness"
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   "source": [
    "# Define columns of interest\n",
    "helpful_column = 'The noise and/or temperature intervention messages were helpful to me in understanding how to improve my indoor environmental satisfaction.'\n",
    "change_location_column = 'Over the past week, I changed my location, adjusted the thermostat, fan etc. to feel thermally comfortable after receiving the temperature intervention messages.'\n",
    "\n",
    "# Filter 'No intervention messages received'\n",
    "#df_weekly = df_weekly[df_weekly[helpful_column]!='No intervention messages received']\n",
    "#df_weekly = df_weekly[df_weekly[change_location_column]!='No intervention messages received']\n",
    "\n",
    "\n",
    "# Order responses\n",
    "df_weekly[helpful_column] = df_weekly[helpful_column].astype(pd.CategoricalDtype(categories=['Strongly agree', 'Agree', 'Neutral', 'Disagree', 'Strongly disagree', 'No response'], ordered=True))\n",
    "df_weekly[change_location_column] = df_weekly[change_location_column].astype(pd.CategoricalDtype(categories=['Always', 'Often', 'Sometimes', 'Seldom', 'Never', 'No response'], ordered=True))\n",
    "\n",
    "# Create subplots with shared y-axis, add subplot titles, and reduce spacing\n",
    "fig = make_subplots(\n",
    "    rows=1, cols=2, \n",
    "    shared_yaxes=True, \n",
    "    subplot_titles=(\"\", \"\"),\n",
    "    horizontal_spacing=0.05  # Decreased horizontal spacing to bring the plots closer\n",
    ")\n",
    "\n",
    "# First box plot\n",
    "fig.add_trace(\n",
    "    go.Box(\n",
    "        y=df_weekly['Conscientiousness'],\n",
    "        x=df_weekly[helpful_column],\n",
    "        quartilemethod='inclusive', # exclusive, inclusive, linear\n",
    "        #color=\"Helpful Messages\",\n",
    "        #color_discrete_map=custom_colors,\n",
    "        #category_orders={\"Helpful Messages\": [\"Strongly Agree\", \"Agree\", \"Neutral\", \"Disagree\", \"Strongly Disagree\"]},\n",
    "    ),\n",
    "    row=1, col=1\n",
    ")\n",
    "fig['layout']['xaxis1'].update(\n",
    "    title_text='Intervention messages helpful?<br> ',\n",
    "    categoryorder=\"array\", \n",
    "    categoryarray=['Strongly agree', 'Agree', 'Neutral', 'Disagree', 'Strongly disagree', 'No response'],\n",
    "    tickvals=[0, 1, 2, 3, 4, 5],\n",
    "    ticktext=['Strongly<br>agree', 'Agree', 'Neutral', 'Disagree', 'Strongly<br>disagree', 'No<br>response'],\n",
    "    tickangle=0)\n",
    "fig['layout']['yaxis1'].update(\n",
    "    title_text='Conscientiousness',\n",
    "    range=[0, 7.5],\n",
    "    dtick=1)\n",
    "\n",
    "# Annotate number of responses (first plot)\n",
    "for response in df_weekly[helpful_column].cat.categories:\n",
    "    fig.add_annotation(\n",
    "        x=response, y=1.1,\n",
    "        xref='x1', yref='y domain',\n",
    "        showarrow=False,\n",
    "        text='N=' + str(df_weekly[helpful_column].value_counts()[response]),\n",
    "        font=dict(size=14),\n",
    "        row=1, col=1\n",
    "    )\n",
    "\n",
    "# Add highlighted median bar\n",
    "for i, response in enumerate(df_weekly[helpful_column].cat.categories):\n",
    "    y_median = df_weekly[df_weekly[helpful_column]==response]['Conscientiousness'].median()\n",
    "    fig.add_shape(\n",
    "        type='line',\n",
    "        x0=i-0.2,\n",
    "        y0=y_median,\n",
    "        x1=i+ 0.2,\n",
    "        y1=y_median,\n",
    "        line=dict(color='red', width=2),\n",
    "        row=1, col=1\n",
    "    )\n",
    "\n",
    "# Second box plot\n",
    "fig.add_trace(\n",
    "    go.Box(\n",
    "        y=df_weekly['Conscientiousness'],\n",
    "        x=df_weekly[change_location_column],\n",
    "        fillcolor='#A3ADF8',\n",
    "        line=dict(color='#636EFA'),\n",
    "        quartilemethod='inclusive',\n",
    "        #color_discrete_map=custom_colors,\n",
    "        #category_orders={\"Helpful Messages\": [\"Strongly Agree\", \"Agree\", \"Neutral\", \"Disagree\", \"Strongly Disagree\"]},\n",
    "    ), \n",
    "    row=1, col=2\n",
    ")\n",
    "fig['layout']['xaxis2'].update(\n",
    "    title_text='Changed location etc. to feel <br>thermally comfortable?')\n",
    "fig['layout']['xaxis2'].update(\n",
    "    categoryorder=\"array\", \n",
    "    categoryarray=['Always', 'Often', 'Sometimes', 'Seldom', 'Never', 'No response'],\n",
    "    tickvals=[0, 1, 2, 3, 4, 5],\n",
    "    ticktext=['Always', 'Often', 'Sometimes', 'Seldom', 'Never', 'No<br>response'])\n",
    "\n",
    "# Annotate number of responses (second plot)\n",
    "for response in df_weekly[change_location_column].cat.categories:\n",
    "    fig.add_annotation(\n",
    "        x=response, y=1.1,\n",
    "        xref='x2', yref='y domain',\n",
    "        showarrow=False,\n",
    "        text='N=' + str(df_weekly[change_location_column].value_counts()[response]),\n",
    "        font=dict(size=14),\n",
    "        row=1, col=2\n",
    "    )\n",
    "\n",
    "# Add highlighted median bar\n",
    "for i, response in enumerate(df_weekly[change_location_column].cat.categories):\n",
    "    y_median = df_weekly[df_weekly[change_location_column]==response]['Conscientiousness'].median()\n",
    "    fig.add_shape(\n",
    "        type='line',\n",
    "        x0=i-0.2,\n",
    "        y0=y_median,\n",
    "        x1=i+ 0.2,\n",
    "        y1=y_median,\n",
    "        line=dict(color='red', width=2),\n",
    "        row=1, col=2\n",
    "    )\n",
    "\n",
    "fig.update_traces(showlegend=False, width=0.4)  # Make the boxes thicker\n",
    "fig.update_layout(font=dict(color='#000000'), width=1000)\n",
    "fig.show()\n",
    "fig.write_image('./img/Figure_9.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Double checks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Fig 9: Remaining issues:\n",
    "  - Intervention messages helpful? - Agree, Q1\n",
    "     - Plotly: 4.75 (inclusive)\n",
    "     - Excel:  4.875\n",
    "     - Pandas: 4.875\n",
    "  - Changed location etc...? - Seldom, Q1\n",
    "     - Plotly: 3.75\n",
    "     - Excel:  3.875\n",
    "     - Pandas: 3.75\n",
    "\n",
    "     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weekly[df_weekly[helpful_column]=='Agree']['Conscientiousness'].quantile(0.25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.5"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weekly[df_weekly[change_location_column]=='Seldom']['Conscientiousness'].quantile(0.25, interpolation='midpoint')"
   ]
  }
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