jupyter notebook/Functions.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<spacy.pipeline.entityruler.EntityRuler at 0x2af0d0e3900>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import jsonlines\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import re\n",
    "import spacy\n",
    "import warnings \n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "nlp = spacy.load('en_core_web_md')\n",
    "\n",
    "from spacy.pipeline import EntityRuler\n",
    "ruler = nlp.add_pipe(\"entity_ruler\", name=\"ruler\", before=\"ner\")\n",
    "ruler.from_disk(\"jz_skill_patterns.jsonl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def parse_skills(resume):\n",
    "    doc = nlp(resume)\n",
    "    myset = []\n",
    "    subset = []\n",
    "    for ent in doc.ents:\n",
    "        if ent.label_ == \"SKILL\":\n",
    "            subset.append(ent.text)\n",
    "    myset.append(subset)\n",
    "    subset = list(set(subset))\n",
    "    return subset\n",
    "\n",
    "def skills_to_doc(skills):\n",
    "    a = re.sub(r'\\'', '', skills)\n",
    "    b = re.sub(r'\\[|\\]', '',a)\n",
    "    c = re.split(r\"[,]\\s*\", b)\n",
    "    lst_of_string =  ' '.join(str(e) for e in c)\n",
    "    return lst_of_string\n",
    "\n",
    "\n",
    "def find_resumes(skills, resume, max_matches):\n",
    "    similarity_score= []\n",
    "    append_resume = resume\n",
    "    eg =  ' '.join(str(e) for e in skills)\n",
    "    for i in range(3677):\n",
    "        x = skills_to_doc(resume['skills'].loc[i])\n",
    "        nlp_score = nlp(x).similarity(nlp(eg))\n",
    "        similarity_score.append(nlp_score)\n",
    "    append_resume['Similarity'] = similarity_score\n",
    "    append_resume = append_resume.sort_values(by=['Similarity'], ascending=False)\n",
    "    append_resume = append_resume.drop(columns=['Resume'])\n",
    "    sample_row = pd.DataFrame({'ID':'Sample resume', 'Category':'Need to define', 'skills':eg},index =[0])\n",
    "    appended_resume = pd.concat([sample_row, append_resume])\n",
    "    return appended_resume.head(max_matches+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "    }\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>ID</th>\n",
       "      <th>Category</th>\n",
       "      <th>Resume</th>\n",
       "      <th>skills</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>HR</td>\n",
       "      <td>b'John H. Smith, P.H.R.\\n800-991-5187 | PO Box...</td>\n",
       "      <td>['Collaboration', 'security', 'Box', 'Data Man...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>HR</td>\n",
       "      <td>b'Name Surname\\nAddress\\nMobile No/Email\\nPERS...</td>\n",
       "      <td>['databases', 'business']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>HR</td>\n",
       "      <td>b'Anthony Brown\\nHR Assistant\\nAREAS OF EXPERT...</td>\n",
       "      <td>['support', 'first class', 'Business', 'commun...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>HR</td>\n",
       "      <td>b'www.downloadmela.com\\nSatheesh\\nEMAIL ID:\\nC...</td>\n",
       "      <td>['Testing', 'database', 'Multimedia', 'Java', ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>HR</td>\n",
       "      <td>b\"HUMAN RESOURCES DIRECTOR\\n\\xef\\x82\\xb7Expert...</td>\n",
       "      <td>['support', 'collaboration', 'Engineering', 'C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3672</th>\n",
       "      <td>99416532</td>\n",
       "      <td>AVIATION</td>\n",
       "      <td>RANK: SGT/E-5 NON- COMMISSIONED OFFIC...</td>\n",
       "      <td>['Engineering', 'material', 'Accounting']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3673</th>\n",
       "      <td>24589765</td>\n",
       "      <td>AVIATION</td>\n",
       "      <td>GOVERNMENT RELATIONS, COMMUNICATIONS ...</td>\n",
       "      <td>['design', 'support', 'Support', 'finance', 'c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3674</th>\n",
       "      <td>31605080</td>\n",
       "      <td>AVIATION</td>\n",
       "      <td>GEEK SQUAD AGENT         Professional...</td>\n",
       "      <td>['IOS', 'support', 'Software', 'Android', 'Win...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3675</th>\n",
       "      <td>21190805</td>\n",
       "      <td>AVIATION</td>\n",
       "      <td>PROGRAM DIRECTOR / OFFICE MANAGER    ...</td>\n",
       "      <td>['Twitter', 'support', 'design', 'Operating Sy...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3676</th>\n",
       "      <td>37473139</td>\n",
       "      <td>AVIATION</td>\n",
       "      <td>STOREKEEPER II       Professional Sum...</td>\n",
       "      <td>['support', 'Business', 'material', 'Windows',...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3677 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ID  Category                                             Resume  \\\n",
       "0            1        HR  b'John H. Smith, P.H.R.\\n800-991-5187 | PO Box...   \n",
       "1            2        HR  b'Name Surname\\nAddress\\nMobile No/Email\\nPERS...   \n",
       "2            3        HR  b'Anthony Brown\\nHR Assistant\\nAREAS OF EXPERT...   \n",
       "3            4        HR  b'www.downloadmela.com\\nSatheesh\\nEMAIL ID:\\nC...   \n",
       "4            5        HR  b\"HUMAN RESOURCES DIRECTOR\\n\\xef\\x82\\xb7Expert...   \n",
       "...        ...       ...                                                ...   \n",
       "3672  99416532  AVIATION           RANK: SGT/E-5 NON- COMMISSIONED OFFIC...   \n",
       "3673  24589765  AVIATION           GOVERNMENT RELATIONS, COMMUNICATIONS ...   \n",
       "3674  31605080  AVIATION           GEEK SQUAD AGENT         Professional...   \n",
       "3675  21190805  AVIATION           PROGRAM DIRECTOR / OFFICE MANAGER    ...   \n",
       "3676  37473139  AVIATION           STOREKEEPER II       Professional Sum...   \n",
       "\n",
       "                                                 skills  \n",
       "0     ['Collaboration', 'security', 'Box', 'Data Man...  \n",
       "1                             ['databases', 'business']  \n",
       "2     ['support', 'first class', 'Business', 'commun...  \n",
       "3     ['Testing', 'database', 'Multimedia', 'Java', ...  \n",
       "4     ['support', 'collaboration', 'Engineering', 'C...  \n",
       "...                                                 ...  \n",
       "3672          ['Engineering', 'material', 'Accounting']  \n",
       "3673  ['design', 'support', 'Support', 'finance', 'c...  \n",
       "3674  ['IOS', 'support', 'Software', 'Android', 'Win...  \n",
       "3675  ['Twitter', 'support', 'design', 'Operating Sy...  \n",
       "3676  ['support', 'Business', 'material', 'Windows',...  \n",
       "\n",
       "[3677 rows x 4 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resume = pd.read_csv ('Extract skills.csv')\n",
    "resume"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 0 ns\n",
      "DIGITAL-MEDIA\n"
     ]
    }
   ],
   "source": [
    "%time\n",
    "sample = resume['Resume'].loc[696]\n",
    "print(resume['Category'].loc[696])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n",
      "['wireless', 'business', 'Commerce', 'HTML', 'marketing', 'CSS', 'Android', 'functional testing', 'iOS', 'ecommerce', 'front end', 'Wordpress', 'design', 'mobile', 'support', 'Marketing', 'forums', 'email marketing']\n",
      "Wall time: 243 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "parsed_skills = parse_skills(sample)\n",
    "print(type(parsed_skills))\n",
    "print(parsed_skills)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 48.3 s\n"
     ]
    },
    {
     "data": {
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       "\n",
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       "    }\n",
       "\n",
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       "        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>ID</th>\n",
       "      <th>Category</th>\n",
       "      <th>skills</th>\n",
       "      <th>Similarity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sample resume</td>\n",
       "      <td>Need to define</td>\n",
       "      <td>wireless business Commerce HTML marketing CSS ...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>696</th>\n",
       "      <td>697</td>\n",
       "      <td>DIGITAL-MEDIA</td>\n",
       "      <td>['design', 'iOS', 'support', 'Commerce', 'emai...</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3498</th>\n",
       "      <td>22848179</td>\n",
       "      <td>ARTS</td>\n",
       "      <td>['Twitter', 'design', 'Finance', 'Communicatio...</td>\n",
       "      <td>0.953560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>88</td>\n",
       "      <td>DESIGNER</td>\n",
       "      <td>['big data', 'iOS', 'design', 'Content Managem...</td>\n",
       "      <td>0.951886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2485</th>\n",
       "      <td>16893572</td>\n",
       "      <td>DIGITAL-MEDIA</td>\n",
       "      <td>['Twitter', 'design', 'MARKETING', 'CSS', 'mar...</td>\n",
       "      <td>0.951464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3288</th>\n",
       "      <td>37375999</td>\n",
       "      <td>PUBLIC-RELATIONS</td>\n",
       "      <td>['chef', 'support', 'design', 'email marketing...</td>\n",
       "      <td>0.948040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2447</th>\n",
       "      <td>27419236</td>\n",
       "      <td>DIGITAL-MEDIA</td>\n",
       "      <td>['design', 'SQL', 'Box', 'data management', 'A...</td>\n",
       "      <td>0.945291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2523</th>\n",
       "      <td>12085736</td>\n",
       "      <td>DIGITAL-MEDIA</td>\n",
       "      <td>['Search Engine', 'design', 'SQL', 'material',...</td>\n",
       "      <td>0.940656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1857</th>\n",
       "      <td>12230301</td>\n",
       "      <td>BUSINESS-DEVELOPMENT</td>\n",
       "      <td>['design', 'MARKETING', 'search engines', 'BUS...</td>\n",
       "      <td>0.940603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1503</th>\n",
       "      <td>64017585</td>\n",
       "      <td>INFORMATION-TECHNOLOGY</td>\n",
       "      <td>['support', 'design', 'security', 'Computer Sc...</td>\n",
       "      <td>0.940569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3558</th>\n",
       "      <td>16887936</td>\n",
       "      <td>ARTS</td>\n",
       "      <td>['Twitter', 'design', 'Publishing', 'databases...</td>\n",
       "      <td>0.939565</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 ID                Category  \\\n",
       "0     Sample resume          Need to define   \n",
       "696             697           DIGITAL-MEDIA   \n",
       "3498       22848179                    ARTS   \n",
       "87               88                DESIGNER   \n",
       "2485       16893572           DIGITAL-MEDIA   \n",
       "3288       37375999        PUBLIC-RELATIONS   \n",
       "2447       27419236           DIGITAL-MEDIA   \n",
       "2523       12085736           DIGITAL-MEDIA   \n",
       "1857       12230301    BUSINESS-DEVELOPMENT   \n",
       "1503       64017585  INFORMATION-TECHNOLOGY   \n",
       "3558       16887936                    ARTS   \n",
       "\n",
       "                                                 skills  Similarity  \n",
       "0     wireless business Commerce HTML marketing CSS ...         NaN  \n",
       "696   ['design', 'iOS', 'support', 'Commerce', 'emai...    1.000000  \n",
       "3498  ['Twitter', 'design', 'Finance', 'Communicatio...    0.953560  \n",
       "87    ['big data', 'iOS', 'design', 'Content Managem...    0.951886  \n",
       "2485  ['Twitter', 'design', 'MARKETING', 'CSS', 'mar...    0.951464  \n",
       "3288  ['chef', 'support', 'design', 'email marketing...    0.948040  \n",
       "2447  ['design', 'SQL', 'Box', 'data management', 'A...    0.945291  \n",
       "2523  ['Search Engine', 'design', 'SQL', 'material',...    0.940656  \n",
       "1857  ['design', 'MARKETING', 'search engines', 'BUS...    0.940603  \n",
       "1503  ['support', 'design', 'security', 'Computer Sc...    0.940569  \n",
       "3558  ['Twitter', 'design', 'Publishing', 'databases...    0.939565  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "find_resumes(parsed_skills, resume, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 40.3 s\n"
     ]
    },
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Category</th>\n",
       "      <th>skills</th>\n",
       "      <th>Similarity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sample resume</td>\n",
       "      <td>Need to define</td>\n",
       "      <td>branding collateral competitive analysis data ...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2448</th>\n",
       "      <td>13328680</td>\n",
       "      <td>DIGITAL-MEDIA</td>\n",
       "      <td>['Search Engine', 'Languages', 'Business', 'da...</td>\n",
       "      <td>0.899977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2358</th>\n",
       "      <td>29770086</td>\n",
       "      <td>CONSULTANT</td>\n",
       "      <td>['Search Engine', 'Hubspot', 'Ecommerce', 'Ope...</td>\n",
       "      <td>0.883262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2480</th>\n",
       "      <td>39166680</td>\n",
       "      <td>DIGITAL-MEDIA</td>\n",
       "      <td>['SQL', 'Tableau', 'CRM', 'framework', 'Google...</td>\n",
       "      <td>0.877268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2506</th>\n",
       "      <td>20628003</td>\n",
       "      <td>DIGITAL-MEDIA</td>\n",
       "      <td>['Search Engine', 'support', 'MARKETING', 'mar...</td>\n",
       "      <td>0.868064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2511</th>\n",
       "      <td>80679862</td>\n",
       "      <td>DIGITAL-MEDIA</td>\n",
       "      <td>['Search Engine', 'design', 'MARKETING', 'New ...</td>\n",
       "      <td>0.866412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2249</th>\n",
       "      <td>12351749</td>\n",
       "      <td>SALES</td>\n",
       "      <td>['C++', 'support', 'business', 'Business', 'da...</td>\n",
       "      <td>0.862006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2522</th>\n",
       "      <td>16536141</td>\n",
       "      <td>DIGITAL-MEDIA</td>\n",
       "      <td>['Twitter', 'design', 'MARKETING', 'Telecommun...</td>\n",
       "      <td>0.857801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1828</th>\n",
       "      <td>79759716</td>\n",
       "      <td>BUSINESS-DEVELOPMENT</td>\n",
       "      <td>['Twitter', 'design', 'Business', 'HubSpot', '...</td>\n",
       "      <td>0.855590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>700</th>\n",
       "      <td>701</td>\n",
       "      <td>DIGITAL-MEDIA</td>\n",
       "      <td>['Twitter', 'amp', 'Buffer', 'Analytics', 'Goo...</td>\n",
       "      <td>0.854119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2433</th>\n",
       "      <td>13837784</td>\n",
       "      <td>DIGITAL-MEDIA</td>\n",
       "      <td>['Twitter', 'Software', 'Optimizely', 'search ...</td>\n",
       "      <td>0.853280</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 ID              Category  \\\n",
       "0     Sample resume        Need to define   \n",
       "2448       13328680         DIGITAL-MEDIA   \n",
       "2358       29770086            CONSULTANT   \n",
       "2480       39166680         DIGITAL-MEDIA   \n",
       "2506       20628003         DIGITAL-MEDIA   \n",
       "2511       80679862         DIGITAL-MEDIA   \n",
       "2249       12351749                 SALES   \n",
       "2522       16536141         DIGITAL-MEDIA   \n",
       "1828       79759716  BUSINESS-DEVELOPMENT   \n",
       "700             701         DIGITAL-MEDIA   \n",
       "2433       13837784         DIGITAL-MEDIA   \n",
       "\n",
       "                                                 skills  Similarity  \n",
       "0     branding collateral competitive analysis data ...         NaN  \n",
       "2448  ['Search Engine', 'Languages', 'Business', 'da...    0.899977  \n",
       "2358  ['Search Engine', 'Hubspot', 'Ecommerce', 'Ope...    0.883262  \n",
       "2480  ['SQL', 'Tableau', 'CRM', 'framework', 'Google...    0.877268  \n",
       "2506  ['Search Engine', 'support', 'MARKETING', 'mar...    0.868064  \n",
       "2511  ['Search Engine', 'design', 'MARKETING', 'New ...    0.866412  \n",
       "2249  ['C++', 'support', 'business', 'Business', 'da...    0.862006  \n",
       "2522  ['Twitter', 'design', 'MARKETING', 'Telecommun...    0.857801  \n",
       "1828  ['Twitter', 'design', 'Business', 'HubSpot', '...    0.855590  \n",
       "700   ['Twitter', 'amp', 'Buffer', 'Analytics', 'Goo...    0.854119  \n",
       "2433  ['Twitter', 'Software', 'Optimizely', 'search ...    0.853280  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "sample_1 =['branding','collateral','competitive analysis','data analytics','ecommerce']\n",
    "find_resumes(sample_1, resume, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def university_parser(doc):\n",
    "    tokenized_doc = nlp(doc)\n",
    "    ORG_list = [ent.text for ent in tokenized_doc.ents if ent.label_ == \"ORG\"]\n",
    "    lst = [\"university\",\"University\",\"UNIVERSITY\",\"institude\",\"Institude\",\"INSTITUDE\",\"college\",\"College\",\"COLLEGE\"]\n",
    "    university = []\n",
    "    for org in ORG_list:\n",
    "        for word in lst:\n",
    "            if word in org:\n",
    "                university.append(org)\n",
    "    return university"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Faulkner UniversityMontgomery']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "university_parser(resume['Resume'].loc[1982])"
   ]
  }
 ],
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