trade_plots_us.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd             # data package\n",
    "import matplotlib.pyplot as plt # graphics \n",
    "import datetime as dt\n",
    "import numpy as np\n",
    "\n",
    "import requests, io             # internet and input tools  \n",
    "import zipfile as zf            # zip file tools \n",
    "import os\n",
    "import geopandas as gpd # this is the main geopandas \n",
    "\n",
    "import pyarrow as pa\n",
    "import pyarrow.parquet as pq\n",
    " \n",
    "from bokeh.palettes import brewer, Spectral6\n",
    "from bokeh.io import show, output_file, curdoc\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.models import ColumnDataSource, HoverTool, Panel, Tabs, GeoJSONDataSource, LinearColorMapper\n",
    "from bokeh.models import ColorBar\n",
    "from bokeh.layouts import column, gridplot, row\n",
    "from bokeh.transform import factor_cmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "trade_type = \"imports\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "crl = [\"forestgreen\",\"darkslategray\",\"mediumblue\",\"crimson\"]\n",
    "\n",
    "background = \"#ffffff\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "trade_file = trade_type + \"_by_naics.csv\"\n",
    "\n",
    "df = pd.read_csv(\".//data//\" + trade_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"high_cat\"] = df.naics3.astype(str).str[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"time\"] = pd.to_datetime(df.time)\n",
    "\n",
    "df.set_index([\"time\",\"naics3\"],inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "naics_cat = list(df.loc[\"2018-01-01\"].high_cat.unique())\n",
    "\n",
    "color_map_naics = dict(zip(naics_cat,crl))\n",
    "\n",
    "name_map = dict(zip(naics_cat,[\"Agriculture\", \"Oil/Mining\",\"Manufacturing\", \"N/S\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"colors\"] = df.high_cat.map(color_map_naics)\n",
    "\n",
    "df[\"name\"] = df.high_cat.map(name_map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(mapper = {\"china_trade_y\":\"weight\"}, inplace = True, axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>tariff_trd_w_avg</th>\n",
       "      <th>total_trade</th>\n",
       "      <th>china_trade</th>\n",
       "      <th>high_cat</th>\n",
       "      <th>colors</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th>naics3</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2015-01-01</th>\n",
       "      <th>111</th>\n",
       "      <td>2.691070</td>\n",
       "      <td>3.237275e+09</td>\n",
       "      <td>63674530.0</td>\n",
       "      <td>1</td>\n",
       "      <td>forestgreen</td>\n",
       "      <td>Agriculture</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>0.016408</td>\n",
       "      <td>3.739969e+08</td>\n",
       "      <td>889946.0</td>\n",
       "      <td>1</td>\n",
       "      <td>forestgreen</td>\n",
       "      <td>Agriculture</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>1.016320</td>\n",
       "      <td>1.969950e+08</td>\n",
       "      <td>15953858.0</td>\n",
       "      <td>1</td>\n",
       "      <td>forestgreen</td>\n",
       "      <td>Agriculture</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>1.500939</td>\n",
       "      <td>1.440097e+09</td>\n",
       "      <td>285216144.0</td>\n",
       "      <td>1</td>\n",
       "      <td>forestgreen</td>\n",
       "      <td>Agriculture</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.232820e+10</td>\n",
       "      <td>75188.0</td>\n",
       "      <td>2</td>\n",
       "      <td>darkslategray</td>\n",
       "      <td>Oil/Mining</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   tariff_trd_w_avg   total_trade  china_trade high_cat  \\\n",
       "time       naics3                                                         \n",
       "2015-01-01 111             2.691070  3.237275e+09   63674530.0        1   \n",
       "           112             0.016408  3.739969e+08     889946.0        1   \n",
       "           113             1.016320  1.969950e+08   15953858.0        1   \n",
       "           114             1.500939  1.440097e+09  285216144.0        1   \n",
       "           211             0.000000  1.232820e+10      75188.0        2   \n",
       "\n",
       "                          colors         name  \n",
       "time       naics3                              \n",
       "2015-01-01 111       forestgreen  Agriculture  \n",
       "           112       forestgreen  Agriculture  \n",
       "           113       forestgreen  Agriculture  \n",
       "           114       forestgreen  Agriculture  \n",
       "           211     darkslategray   Oil/Mining  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df.set_index([\"time\",\"naics3\"],inplace = True)\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_map():\n",
    "    \n",
    "    map_projection = \"epsg:2163\"\n",
    "    \n",
    "    county_shape = \".\\\\shapefiles\\\\lake\\\\ne_10m_lakes.shx\"\n",
    "\n",
    "    lake_map = gpd.read_file(county_shape)\n",
    "\n",
    "    lake_map = lake_map.to_crs({'init': map_projection})\n",
    "    \n",
    "##########################################################################\n",
    "    \n",
    "    county_shape = \".\\\\shapefiles\\\\land\\\\ne_50m_land.shx\"\n",
    "\n",
    "    land_map = gpd.read_file(county_shape)\n",
    "\n",
    "    land_map = land_map.to_crs({'init': map_projection})\n",
    "\n",
    "    land_map = land_map.iloc[0:1200]\n",
    "    \n",
    "##########################################################################\n",
    "    \n",
    "    county_shape = \".\\\\shapefiles\\\\county\\\\tl_2017_us_county.shx\"\n",
    "\n",
    "    us_map = gpd.read_file(county_shape)\n",
    "\n",
    "    us_map = us_map.to_crs({'init': map_projection})\n",
    "    \n",
    "    us_map[\"geometry\"] = us_map[\"geometry\"].simplify(4000)\n",
    "    \n",
    "    us_map[\"area_fips\"] = (us_map.STATEFP.astype(str) + us_map.COUNTYFP.astype(str)).astype(int)\n",
    "\n",
    "    us_map.set_index(\"STATEFP\", inplace = True)\n",
    "\n",
    "    drop_list = [\"02\",\"15\",\"72\"]\n",
    "\n",
    "    us_map.drop(drop_list, inplace = True)\n",
    "    \n",
    "    us_map.reset_index(inplace = True)\n",
    "    \n",
    "##########################################################################\n",
    "    \n",
    "    state_shape = \".\\\\shapefiles\\\\state\\\\tl_2017_us_state.shx\"\n",
    "\n",
    "    state_map = gpd.read_file(state_shape)\n",
    "\n",
    "    state_map = state_map.to_crs({'init': map_projection})\n",
    "\n",
    "    state_map[\"geometry\"] = state_map[\"geometry\"].simplify(4000)\n",
    "\n",
    "    state_map.set_index(\"STATEFP\", inplace = True)\n",
    "\n",
    "    drop_list = [\"02\",\"15\",\"72\",\"78\",\"69\",\"66\",\"60\",]\n",
    "\n",
    "    state_map.drop(drop_list, inplace = True)\n",
    "    \n",
    "    state_map.reset_index(inplace = True)\n",
    "    \n",
    "    state_fp_dict = dict(zip(state_map.STATEFP, state_map.STUSPS))\n",
    "    \n",
    "    us_map[\"STSPS\"] = us_map[\"STATEFP\"].map(state_fp_dict)\n",
    "    \n",
    "    us_map[\"NAME\"] = us_map[\"NAME\"] + \" County, \" + us_map[\"STSPS\"]\n",
    "    \n",
    "##########################################################################\n",
    "    \n",
    "    us_map = gpd.overlay(us_map, land_map,  how='intersection')\n",
    "    \n",
    "    great_lakes = [\"Lake Superior\", \"Lake Michigan\", \"Lake Erie\",\"Lake Superior\"\"Lake Huron\"]\n",
    "\n",
    "    us_map = gpd.overlay(us_map, lake_map[lake_map.name.isin(great_lakes)],  how='difference')\n",
    "    \n",
    "    state_map = gpd.overlay(state_map, land_map,  how='intersection')\n",
    "\n",
    "    state_map = gpd.overlay(state_map, lake_map[lake_map.name.isin(great_lakes)],  how='difference')\n",
    "    \n",
    "    return us_map, state_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "##########################################################################\n",
    "def make_source(time):\n",
    "    \n",
    "    datasource = df.loc[time].copy()\n",
    "    \n",
    "    datasource.reset_index(inplace = True)\n",
    "    \n",
    "    datasource[\"position\"] = datasource.index.values\n",
    "    \n",
    "    source = ColumnDataSource(datasource)\n",
    "    \n",
    "    return source"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_tariff_source(time):\n",
    "    file = \".\\\\data\\\\\" + trade_type + \"_trade_data_2020.parquet\"\n",
    "    \n",
    "    df = pq.read_table(file).to_pandas()\n",
    "\n",
    "    df[\"time\"] = pd.to_datetime(df.time)\n",
    "\n",
    "    df.set_index([\"area_fips\", \"time\"],inplace = True)\n",
    "\n",
    "    tariff = df.xs(time, level=1).copy()\n",
    "\n",
    "    tariff[\"fips_code\"] = tariff.index\n",
    "\n",
    "    tariff[\"fips_code\"] = tariff[\"fips_code\"].astype(int)\n",
    "    \n",
    "    tariff[\"pop_label\"] = tariff[\"2017_population\"].map('{:,.0f}'.format)\n",
    "\n",
    "    tariff[\"tariff_label\"] = tariff[\"tariff\"].map('{:,.2f}'.format)\n",
    "    \n",
    "    return tariff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_map(time):\n",
    "    height = 520\n",
    "    width = 795\n",
    "    \n",
    "    tariff_df = make_tariff_source(time)\n",
    "    \n",
    "    timedt = dt.datetime.strptime(time, \"%Y-%m-%d\")\n",
    "    \n",
    "    month = timedt.strftime(\"%B\")\n",
    "    year = timedt.strftime(\"%Y\")\n",
    "    \n",
    "    tariff_df.tariff.fillna(0, inplace = True)\n",
    "    \n",
    "    var = [\"tariff\",\"fips_code\",\"pop_label\",\"tariff_label\"]\n",
    "    \n",
    "    us_map = us_map_fixed.merge(tariff_df[var], left_on='area_fips',\n",
    "                      right_on = \"fips_code\", how = \"inner\", indicator = True)\n",
    "    ################################################################################\n",
    "        \n",
    "    title = \"US Tariff Protection by County as of: \" + month + \" \" + year\n",
    "        \n",
    "    state_geosource = GeoJSONDataSource(geojson = state_map.to_json())\n",
    "\n",
    "    geosource = GeoJSONDataSource(geojson = us_map.to_json())\n",
    "    \n",
    "    palette = brewer['RdBu'][10]\n",
    "    \n",
    "    color_mapper = LinearColorMapper(palette = palette, low = 0, high = 10)\n",
    "\n",
    "    color_bar = ColorBar(color_mapper = color_mapper, \n",
    "                     label_standoff = 8,\n",
    "                     border_line_color = None,\n",
    "                     orientation = \"vertical\",\n",
    "                     location=(0,0))\n",
    "\n",
    "# Create figure object.\n",
    "    p = figure( \n",
    "           plot_height = height ,\n",
    "           plot_width = width, \n",
    "           toolbar_location = 'below',\n",
    "           tools = \"box_zoom, reset\",\n",
    "            title = title)\n",
    "    \n",
    "    p.xgrid.grid_line_color = None\n",
    "    p.ygrid.grid_line_color = None\n",
    "\n",
    "    states = p.patches('xs','ys', source = geosource,\n",
    "                   fill_color = {\"field\" :'tariff',\n",
    "                                 \"transform\" : color_mapper},\n",
    "                   line_color = \"gray\", \n",
    "                   line_width = 0.25, \n",
    "                   fill_alpha = 1)\n",
    "\n",
    "    state_line = p.multi_line('xs','ys', source = state_geosource,\n",
    "                   line_color = \"black\", \n",
    "                   line_width = 0.5)\n",
    "\n",
    "    p.axis.visible = False\n",
    "    p.background_fill_color = \"grey\"\n",
    "    p.background_fill_alpha = 0.25\n",
    "    \n",
    "    TOOLTIPS = \"\"\"\n",
    "    <div style=\"background-color:#F5F5F5; opacity: 0.65;\">\n",
    "        <div style = \"text-align:center;\">\n",
    "            <span style=\"font-size: 13px; font-weight:;\">@NAME (pop. @pop_label)\n",
    "        </div>\n",
    "        <div style = \"text-align:left;\">\n",
    "            <span style=\"font-size: 13px; font-weight:\">Tariff: <b>@tariff_label</b></span>\n",
    "        </div>\n",
    "    </div>\n",
    "    \"\"\"\n",
    "    p.add_tools(HoverTool(renderers = [states],\n",
    "                      tooltips = TOOLTIPS))\n",
    "    p.toolbar.autohide = True\n",
    "    p.add_layout(color_bar, \"left\")\n",
    "    p.border_fill_color = background\n",
    "    color_bar.background_fill_color = background\n",
    "    p.background_fill_color = background\n",
    "    p.background_fill_alpha = 1.0\n",
    "    p.outline_line_color = None\n",
    "    \n",
    "    p.sizing_mode= \"scale_both\"\n",
    "    p.max_height = height\n",
    "    p.max_width = width\n",
    "    \n",
    "    p.toolbar.active_drag = None\n",
    "    #show(p)\n",
    "    return p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_tradewar_fig(trade_war_time):\n",
    "\n",
    "    trade_war_time = trade_war_time\n",
    "    width = 600\n",
    "    height = 245\n",
    "##########################################################################\n",
    "#output_file(\"bars.html\")\n",
    "\n",
    "\n",
    "    p = figure(plot_height=height, plot_width = width, title=\"US Tariff Rate on Imports from China by NAICs Industry Code\",\n",
    "               toolbar_location = 'below',\n",
    "           tools = \"box_zoom, reset\")\n",
    "    \n",
    "    source = make_source(trade_war_time)\n",
    "\n",
    "    p.vbar(x = \"position\", top = \"tariff_trd_w_avg\", width = 0.9, color = \"colors\", alpha = 0.5,\n",
    "       hatch_pattern = \" \",hatch_alpha = 0.10,\n",
    "       source = source, legend_field=  \"name\")\n",
    "    \n",
    "    mfn_time = \"2018-01-01\"\n",
    "    source = make_source(mfn_time)\n",
    "    \n",
    "    if dt.datetime.strptime(\"2018-03-01\", \"%Y-%m-%d\") >= dt.datetime.strptime(trade_war_time, \"%Y-%m-%d\"):\n",
    "        alpha_tw = 0\n",
    "    else:\n",
    "        alpha_tw = 0.25\n",
    "\n",
    "    p.vbar(x = \"position\", top = \"tariff_trd_w_avg\", width = 0.9, alpha = alpha_tw,\n",
    "       hatch_pattern = \">\",hatch_alpha = 0.10,\n",
    "       source = source, color = \"colors\")\n",
    "##########################################################################33\n",
    "    TOOLTIPS = \"\"\"\n",
    "        <div style=\"background-color:#F5F5F5; opacity: 0.65;\">\n",
    "            <div style = \"text-align:left;\">\n",
    "                <span style=\"font-size: 13px; font-weight:;\">Industry Code: @naics3</span>\n",
    "            </div>\n",
    "            <div style = \"text-align:left;\">\n",
    "                <span style=\"font-size: 13px; font-weight:\">Tariff: <b>@tariff_trd_w_avg</b></span>\n",
    "            </div>\n",
    "        </div>\n",
    "    \"\"\"\n",
    "\n",
    "    p.add_tools(HoverTool(tooltips = TOOLTIPS))\n",
    "##########################################################################\n",
    "    p.xgrid.grid_line_color = None\n",
    "    p.y_range.start = 0\n",
    "    p.y_range.end = 45\n",
    "    p.x_range.start = -0.75\n",
    "    p.x_range.end = 30\n",
    "    p.toolbar.autohide = True\n",
    "\n",
    "    p.xaxis.major_tick_line_color = None  # turn off x-axis major ticks\n",
    "    p.xaxis.minor_tick_line_color = None  # turn off x-axis minor ticks\n",
    "    p.xaxis.major_label_text_font_size = '0pt'  # turn off x-axis tick labels\n",
    "    p.yaxis.minor_tick_line_color = None\n",
    "    \n",
    "    p.border_fill_color = background    \n",
    "    p.legend.orientation = \"horizontal\"\n",
    "    p.legend.background_fill_color = background\n",
    "    p.legend.background_fill_alpha = 0.10\n",
    "    p.legend.label_text_font_size = \"1em\"\n",
    "    p.legend.location = (130,130)\n",
    "    \n",
    "    p.background_fill_color = background \n",
    "    p.background_fill_alpha = 0.75\n",
    "    p.outline_line_color = None\n",
    "    \n",
    "    p.sizing_mode= \"scale_both\"\n",
    "    p.max_height = height\n",
    "    p.max_width = width\n",
    "    p.toolbar.active_drag = None\n",
    "##########################################################################\n",
    "    start = \"2017-08-01\"\n",
    "\n",
    "    tariffs_over_time = df.groupby([\"time\"]).agg({\"tariff_trd_w_avg\": \"mean\"})\n",
    "\n",
    "    source = ColumnDataSource(tariffs_over_time.loc[start:trade_war_time].reset_index())\n",
    "    \n",
    "    avgtar = str(round(tariffs_over_time.loc[start:trade_war_time].iloc[-1][0],2))\n",
    "    \n",
    "    ptime = figure(plot_height=height, plot_width = width, x_axis_type=\"datetime\", \n",
    "                   title=\"Average US Tariff Rate on Imports from China:\" + avgtar, toolbar_location = 'below',\n",
    "           tools = \"box_zoom, reset\")\n",
    "\n",
    "    ptime.line(x = \"time\", y = \"tariff_trd_w_avg\", line_width=3, color='darkblue',source = source)\n",
    "\n",
    "    source = ColumnDataSource(tariffs_over_time.loc[start:].reset_index())\n",
    "\n",
    "    ptime.line(x = \"time\", y = \"tariff_trd_w_avg\", line_width=3, color='gray',source = source, alpha = 0.20)\n",
    "\n",
    "    ptime.vbar(x = dt.datetime.strptime(\"2018-04-01\",\"%Y-%m-%d\"), \n",
    "           color='gray', top = 50, width = 0.1, alpha = 0.20)\n",
    "\n",
    "    ptime.vbar(x = dt.datetime.strptime(\"2018-07-01\",\"%Y-%m-%d\"), \n",
    "           color='gray', top = 50, width = 0.1, alpha = 0.20)\n",
    "\n",
    "    ptime.vbar(x = dt.datetime.strptime(\"2018-08-23\",\"%Y-%m-%d\"), \n",
    "           color='gray', top = 50, width = 0.1, alpha = 0.20)\n",
    "\n",
    "    ptime.vbar(x = dt.datetime.strptime(\"2018-09-24\",\"%Y-%m-%d\"), \n",
    "           color='darkgray', top = 50, width = 0.1, alpha = 0.20)\n",
    "##########################################################################\n",
    "\n",
    "    TIMETOOLTIPS = \"\"\"\n",
    "    <div style=\"background-color:#F5F5F5; opacity: 0.65; border: 0px 0px 0px 0px\">\n",
    "        <div style = \"text-align:left;\">\n",
    "            <span style=\"font-size: 13px; font-weight: bold\">Tariff: @tariff_trd_w_avg</span>\n",
    "        </div>\n",
    "    </div>\n",
    "    \"\"\"\n",
    "\n",
    "    ptime.add_tools(HoverTool(tooltips = TIMETOOLTIPS))\n",
    "\n",
    "    ptime.y_range.start = 0\n",
    "    ptime.y_range.end = 25\n",
    "    ptime.x_range.start = dt.datetime.strptime(start,\"%Y-%m-%d\")\n",
    "    ptime.x_range.end = dt.datetime.strptime(\"2020-03-01\",\"%Y-%m-%d\")\n",
    "    ptime.xaxis.major_label_text_font_size = '0.75em'\n",
    "    ptime.toolbar.autohide = True\n",
    "    ptime.yaxis.minor_tick_line_color = None  # turn off y-axis minor ticks\n",
    "    ptime.border_fill_color = background\n",
    "    \n",
    "    ptime.background_fill_color = background \n",
    "    ptime.background_fill_alpha = 0.75\n",
    "    ptime.outline_line_color = None\n",
    "    \n",
    "    ptime.min_border_bottom = 0\n",
    "    p.min_border_top = 0\n",
    "    \n",
    "    ptime.sizing_mode= \"scale_both\"\n",
    "    ptime.max_height = height\n",
    "    ptime.max_width = width\n",
    "    ptime.toolbar.active_drag = None\n",
    "##########################################################################\n",
    "\n",
    "    pmap = make_map(trade_war_time)\n",
    "\n",
    "##########################################################################\n",
    "    outfig = row(pmap, column(ptime, p, margin = (-0,0,-0,0)), sizing_mode = \"scale_both\")\n",
    "    #show(outfig)\n",
    "    return outfig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "us_map_fixed, state_map = load_map()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "#us_map_fixed, state_map = load_map()\n",
    "\n",
    "output_file('.\\\\docs\\\\' + trade_type + \"_trade_tracker.html\")\n",
    "\n",
    "tab1 = Panel(child= make_tradewar_fig(\"2018-03-01\"), title=\"Pre Trade War\")\n",
    "\n",
    "tab3 = Panel(child= make_tradewar_fig(\"2018-07-01\"), title=\"301 Retaliation, Phase 1\")\n",
    "\n",
    "tab4 = Panel(child= make_tradewar_fig(\"2018-09-01\"), title=\"Phase 2\")\n",
    "\n",
    "tab5 = Panel(child= make_tradewar_fig(\"2018-10-01\"), title=\"Phase 3\")\n",
    "\n",
    "tab6 = Panel(child= make_tradewar_fig(\"2019-06-01\"), title=\"Talks Fail\")\n",
    "\n",
    "tab7 = Panel(child= make_tradewar_fig(\"2019-09-01\"), title=\"More Tariffs\")\n",
    "\n",
    "tab8 = Panel(child= make_tradewar_fig(\"2020-03-01\"), title=\"Trade Agrement\")\n",
    "\n",
    "tabs = Tabs(tabs=[ tab1, tab3, tab4, tab5, tab6, tab7, tab8 ])\n",
    "\n",
    "show(tabs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "trade_file = trade_type + \"_by_naics.csv\"\n",
    "\n",
    "zipObj = zf.ZipFile('.\\\\data\\\\ustariffs-trade-tracker-data.zip', 'w')\n",
    " \n",
    "# Add multiple files to the zip\n",
    "zipObj.write(\".\\\\data\\\\\" + trade_file)\n",
    "\n",
    "file = \".\\\\data\\\\\" + trade_type + \"_trade_data_2020.parquet\"\n",
    "    \n",
    "outdf = pq.read_table(file).to_pandas()\n",
    "\n",
    "outdf.to_csv(\".\\\\data\\\\ustariffs-by-county.csv\")\n",
    "\n",
    "zipObj.write(\".\\\\data\\\\ustariffs-by-county.csv\")\n",
    "\n",
    " # close the Zip File\n",
    "zipObj.close()"
   ]
  }
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