6_Parts_of_Speech_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d1b15dcf-f104-477b-a862-16f718d7fdcf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<spacy.lang.en.English at 0x20d9c158650>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import spacy\n",
    "spacy.load(\"en_core_web_sm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3996e7be-3317-4bc2-b483-00a0290b8098",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"news_story.txt\",\"r\") as f:\n",
    "    text = f.read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "af295d43-439c-4486-977a-75b6154ba76d",
   "metadata": {},
   "outputs": [],
   "source": [
    "doc = nlp(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "4ed5c149-42ca-45b8-a8ca-1ac14476e64d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[8.3, 8.1, 1982, 6.2, 6, â€, 0.3, 0.2, 0.6, 0.4, 0.1, 0.3, 2.6, 5.5, 2021, 1984, one, two, two, 2]\n",
      "[Inflation, climb, consumers, brink, expansion, consumer, price, index, measure, prices, goods, services, %, year, estimate, %, gain, ease, Marchâ€, ™, peak, level, summer, food, energy, prices, core, %, expectations, %, gain, hopes, inflation, month, month, gains, expectations, %, headline, %, estimate, %, increase, core, outlook, %, gain, price, gains, workers, ground, wages, inflation, %, month, increase, %, earnings, year, earnings, %, earnings, %, Inflation, threat, recovery, pandemic, economy, stage, year, growth, level, prices, pump, grocery, stores, problem, inflation, areas, housing, auto, sales, host, areas, officials, problem, interest, rate, hikes, year, pledges, inflation, %, goal, ™, data, job, Credits]\n"
     ]
    }
   ],
   "source": [
    "numeral_tokens = []\n",
    "noun_tokens = []\n",
    "\n",
    "for token in doc:\n",
    "    if token.pos_ == \"NOUN\":\n",
    "        noun_tokens.append(token)\n",
    "    if token.pos_ == \"NUM\":\n",
    "        numeral_tokens.append(token)\n",
    "\n",
    "print(numeral_tokens)\n",
    "print(noun_tokens)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "308cb61f-ba8e-4191-a72d-8b28b6372bd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{92: 98,\n",
       " 100: 27,\n",
       " 86: 15,\n",
       " 85: 39,\n",
       " 96: 17,\n",
       " 97: 32,\n",
       " 90: 34,\n",
       " 95: 4,\n",
       " 87: 13,\n",
       " 89: 10,\n",
       " 84: 23,\n",
       " 103: 7,\n",
       " 93: 20,\n",
       " 94: 4,\n",
       " 98: 8,\n",
       " 101: 1}"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count = doc.count_by(spacy.attrs.POS) # For attrs and POS in the attribute.\n",
    "count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "9924ed24-dd19-4d00-8ed3-0b5b3f1e75e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NOUN | 98\n",
      "VERB | 27\n",
      "ADV | 15\n",
      "ADP | 39\n",
      "PROPN | 17\n",
      "PUNCT | 32\n",
      "DET | 34\n",
      "PRON | 4\n",
      "AUX | 13\n",
      "CCONJ | 10\n",
      "ADJ | 23\n",
      "SPACE | 7\n",
      "NUM | 20\n",
      "PART | 4\n",
      "SCONJ | 8\n",
      "X | 1\n"
     ]
    }
   ],
   "source": [
    "for k,v in count.items():\n",
    "    print(doc.vocab[k].text, \"|\",v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32f9573e-1631-40d8-82e3-3574bc7e3f5a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}