Location Extraction.ipynb

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   "source": [
    "<h1><center>Location extraction from text and visualizing it on map</center></h1>"
   ]
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   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import spacy\n",
    "import folium\n",
    "import requests\n",
    "import pandas as pd"
   ]
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   "execution_count": null,
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   "source": [
    "nlp = spacy.load('en_core_web_sm')  #load the language model\n",
    "text = input()\n",
    "doc = nlp(text)\n",
    "location = []\n",
    "for ent in doc.ents:\n",
    "    if ent.label_ == 'GPE':\n",
    "        location.append(ent.text)\n",
    "print(location)"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('countries.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_countries(countries):\n",
    "    loc_dic = {}\n",
    "    for country in countries:\n",
    "            try:\n",
    "                loc_dic[country] = [float(df[df['Country']==country]['Latitude']),float(df[df['Country']==country]['Longitude'])]\n",
    "            except:\n",
    "                pass\n",
    "    return loc_dic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "countries = get_countries(location)\n",
    "print(countries)\n",
    "m = folium.Map(\n",
    "    location=[10,15],\n",
    "    zoom_start=2,\n",
    "    tiles='Stamen Terrain'\n",
    ")\n",
    "for country,location in countries.items():\n",
    "    folium.Marker(location, popup=country).add_to(m)\n",
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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