PIT to Ticker Delta.ipynb

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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>tickers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1996-01-02</td>\n",
       "      <td>AAL,AAMRQ,AAPL,ABI,ABS,ABT,ABX,ACKH,ACV,ADM,AD...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1996-01-03</td>\n",
       "      <td>AAL,AAMRQ,AAPL,ABI,ABS,ABT,ABX,ACKH,ACV,ADM,AD...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1996-01-04</td>\n",
       "      <td>AAL,AAMRQ,AAPL,ABI,ABS,ABT,ABX,ACKH,ACV,ADM,AD...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1996-01-10</td>\n",
       "      <td>AAL,AAMRQ,AAPL,ABI,ABS,ABT,ABX,ACKH,ACV,ADM,AD...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1996-01-11</td>\n",
       "      <td>AAL,AAMRQ,AAPL,ABI,ABS,ABT,ABX,ACKH,ACV,ADM,AD...</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "        date                                            tickers\n",
       "0 1996-01-02  AAL,AAMRQ,AAPL,ABI,ABS,ABT,ABX,ACKH,ACV,ADM,AD...\n",
       "1 1996-01-03  AAL,AAMRQ,AAPL,ABI,ABS,ABT,ABX,ACKH,ACV,ADM,AD...\n",
       "2 1996-01-04  AAL,AAMRQ,AAPL,ABI,ABS,ABT,ABX,ACKH,ACV,ADM,AD...\n",
       "3 1996-01-10  AAL,AAMRQ,AAPL,ABI,ABS,ABT,ABX,ACKH,ACV,ADM,AD...\n",
       "4 1996-01-11  AAL,AAMRQ,AAPL,ABI,ABS,ABT,ABX,ACKH,ACV,ADM,AD..."
      ]
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     "execution_count": 1,
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   ],
   "source": [
    "import pandas as pd\n",
    "from tqdm import tqdm\n",
    "import json\n",
    "\n",
    "df = pd.read_csv(\"S&P 500 Historical Components & Changes(12-10-2024).csv\")\n",
    "df['date'] = pd.to_datetime(df['date'])\n",
    "df.head()"
   ]
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   "execution_count": 2,
   "id": "b1423720-3384-4d61-ae24-bca401d157d6",
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   "outputs": [],
   "source": [
    "# Get Unique Tickers\n",
    "unique_tickers = set()\n",
    "transformed_data = []\n",
    "for i, row in df.iterrows():\n",
    "    tickers = row['tickers'].split(',')\n",
    "    unique_tickers = unique_tickers.union(set(tickers))"
   ]
  },
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   "execution_count": 3,
   "id": "e6f3434e-7c64-48e8-8169-c6950f9dacaf",
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     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1172/1172 [05:11<00:00,  3.76it/s]\n"
     ]
    }
   ],
   "source": [
    "# Convert Point in Time to Ticker Start/End Records\n",
    "ticker_start_end_records = []\n",
    "for ticker in tqdm(unique_tickers):\n",
    "    ticker_record = None\n",
    "    for i, row in df.iterrows():\n",
    "        period_tickers = set(row['tickers'].split(','))\n",
    "        if ticker in period_tickers:\n",
    "            if ticker_record is None:\n",
    "                ticker_record = {\"ticker\": ticker, \"start_date\": row[\"date\"]}\n",
    "                continue\n",
    "        elif ticker_record is not None:\n",
    "            ticker_record.update({\"end_date\": row[\"date\"]})\n",
    "            ticker_start_end_records.append(ticker_record)\n",
    "            ticker_record = None\n",
    "\n",
    "    if ticker_record is not None:\n",
    "        ticker_start_end_records.append(ticker_record)"
   ]
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ticker</th>\n",
       "      <th>start_date</th>\n",
       "      <th>end_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PGL</td>\n",
       "      <td>1996-01-02</td>\n",
       "      <td>2007-02-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MEA</td>\n",
       "      <td>1996-01-02</td>\n",
       "      <td>2002-01-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>KLAC</td>\n",
       "      <td>1997-09-15</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>XL</td>\n",
       "      <td>2001-09-04</td>\n",
       "      <td>2018-09-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NVDA</td>\n",
       "      <td>2001-11-30</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "  ticker start_date   end_date\n",
       "0    PGL 1996-01-02 2007-02-22\n",
       "1    MEA 1996-01-02 2002-01-30\n",
       "2   KLAC 1997-09-15        NaT\n",
       "3     XL 2001-09-04 2018-09-12\n",
       "4   NVDA 2001-11-30        NaT"
      ]
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     "execution_count": 4,
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   ],
   "source": [
    "# Convert back to dataframe\n",
    "ticker_record_df = pd.DataFrame(ticker_start_end_records)\n",
    "ticker_record_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f4aed634-93c0-4c36-8907-3cdcd53af73c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ticker\n",
       "COV     3\n",
       "DELL    2\n",
       "CNC     2\n",
       "JBL     2\n",
       "CEG     2\n",
       "HP      2\n",
       "TMUS    2\n",
       "GGP     2\n",
       "PCG     2\n",
       "H       2\n",
       "MXIM    2\n",
       "IR      2\n",
       "CBE     2\n",
       "FL      2\n",
       "DXC     2\n",
       "Name: start_date, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Look at top tickers entering and leaving S&P 500\n",
    "(\n",
    "    ticker_record_df.groupby(\"ticker\")[\"start_date\"]\n",
    "    .count().sort_values(ascending=False)\n",
    "    .head(15)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "30739501-b01d-4840-a03d-975ab2791d31",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Record to CSV\n",
    "(\n",
    "    ticker_record_df.sort_values([\"ticker\", \"start_date\"])\n",
    "    .to_csv(\"sp500_ticker_start_end.csv\", index=False)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "31288233-b806-4c0d-9105-0ff87da3c772",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "1172"
      ]
     },
     "execution_count": 7,
     "metadata": {},
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   ],
   "source": [
    "ticker_record_df.ticker.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d1127e76-cc08-4146-98ad-e045ec431399",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1221"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ticker_record_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1b90c49b-0cb0-4772-89d3-1a3cbf7ef3a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Record list of tickers to JSON (Optional)\n",
    "# with open(\"sp_500_full.json\", \"w\") as f:\n",
    "#     json.dump(ticker_record_df.ticker.str.replace(\".\", \" \").to_list(), f)"
   ]
  }
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