[15w] -0 for ppt 최초 상장일.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c8390cb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import FinanceDataReader as fdr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d81a20ae",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████| 3429/3429 [00:05<00:00, 578.07it/s]\n"
     ]
    }
   ],
   "source": [
    "상장 = fdr.StockListing('NYSE')   # 뉴욕거래소 fdr.StockListing('KOSPI') # 코스피"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "389091f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sector</th>\n",
       "      <th>Industry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MMM</td>\n",
       "      <td>3M</td>\n",
       "      <td>Industrials</td>\n",
       "      <td>Industrial Conglomerates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AOS</td>\n",
       "      <td>A. O. Smith</td>\n",
       "      <td>Industrials</td>\n",
       "      <td>Building Products</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ABT</td>\n",
       "      <td>Abbott</td>\n",
       "      <td>Health Care</td>\n",
       "      <td>Health Care Equipment</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ABBV</td>\n",
       "      <td>AbbVie</td>\n",
       "      <td>Health Care</td>\n",
       "      <td>Pharmaceuticals</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ABMD</td>\n",
       "      <td>Abiomed</td>\n",
       "      <td>Health Care</td>\n",
       "      <td>Health Care Equipment</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>498</th>\n",
       "      <td>YUM</td>\n",
       "      <td>Yum! Brands</td>\n",
       "      <td>Consumer Discretionary</td>\n",
       "      <td>Restaurants</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>ZBRA</td>\n",
       "      <td>Zebra Technologies</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>Electronic Equipment &amp; Instruments</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>ZBH</td>\n",
       "      <td>Zimmer Biomet</td>\n",
       "      <td>Health Care</td>\n",
       "      <td>Health Care Equipment</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>ZION</td>\n",
       "      <td>Zions Bancorporation</td>\n",
       "      <td>Financials</td>\n",
       "      <td>Regional Banks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>ZTS</td>\n",
       "      <td>Zoetis</td>\n",
       "      <td>Health Care</td>\n",
       "      <td>Pharmaceuticals</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>503 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Symbol                  Name                  Sector  \\\n",
       "0      MMM                    3M             Industrials   \n",
       "1      AOS           A. O. Smith             Industrials   \n",
       "2      ABT                Abbott             Health Care   \n",
       "3     ABBV                AbbVie             Health Care   \n",
       "4     ABMD               Abiomed             Health Care   \n",
       "..     ...                   ...                     ...   \n",
       "498    YUM           Yum! Brands  Consumer Discretionary   \n",
       "499   ZBRA    Zebra Technologies  Information Technology   \n",
       "500    ZBH         Zimmer Biomet             Health Care   \n",
       "501   ZION  Zions Bancorporation              Financials   \n",
       "502    ZTS                Zoetis             Health Care   \n",
       "\n",
       "                               Industry  \n",
       "0              Industrial Conglomerates  \n",
       "1                     Building Products  \n",
       "2                 Health Care Equipment  \n",
       "3                       Pharmaceuticals  \n",
       "4                 Health Care Equipment  \n",
       "..                                  ...  \n",
       "498                         Restaurants  \n",
       "499  Electronic Equipment & Instruments  \n",
       "500               Health Care Equipment  \n",
       "501                      Regional Banks  \n",
       "502                     Pharmaceuticals  \n",
       "\n",
       "[503 rows x 4 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "상장"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "68d1d33a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Market</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sector</th>\n",
       "      <th>Industry</th>\n",
       "      <th>ListingDate</th>\n",
       "      <th>SettleMonth</th>\n",
       "      <th>Representative</th>\n",
       "      <th>HomePage</th>\n",
       "      <th>Region</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>000050</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>경방</td>\n",
       "      <td>종합 소매업</td>\n",
       "      <td>섬유류(면사,면혼방사,면직물,면혼방직물,화섬사,화섬직물) 제조,도매,수출입</td>\n",
       "      <td>1956-03-03</td>\n",
       "      <td>12월</td>\n",
       "      <td>김준, 김담</td>\n",
       "      <td>http://www.kyungbang.co.kr</td>\n",
       "      <td>서울특별시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5248</th>\n",
       "      <td>000700</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>유수홀딩스</td>\n",
       "      <td>회사 본부 및 경영 컨설팅 서비스업</td>\n",
       "      <td>지주사업</td>\n",
       "      <td>1956-03-03</td>\n",
       "      <td>12월</td>\n",
       "      <td>송영규</td>\n",
       "      <td>http://www.eusu-holdings.com</td>\n",
       "      <td>서울특별시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7676</th>\n",
       "      <td>003480</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>한진중공업홀딩스</td>\n",
       "      <td>연료용 가스 제조 및 배관공급업</td>\n",
       "      <td>지주회사</td>\n",
       "      <td>1956-03-03</td>\n",
       "      <td>12월</td>\n",
       "      <td>조남호, 조원국</td>\n",
       "      <td>http://www.hhic-holdings.com</td>\n",
       "      <td>경기도</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2601</th>\n",
       "      <td>000060</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>메리츠화재</td>\n",
       "      <td>보험업</td>\n",
       "      <td>손해보험(화재,해상,운송보험)</td>\n",
       "      <td>1956-07-02</td>\n",
       "      <td>12월</td>\n",
       "      <td>김용범</td>\n",
       "      <td>http://www.meritzfire.com</td>\n",
       "      <td>서울특별시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>000120</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>CJ대한통운</td>\n",
       "      <td>도로 화물 운송업</td>\n",
       "      <td>Contract Logistics, 포워딩, 항만하역, 해운, 택배국제특송, SCM...</td>\n",
       "      <td>1956-07-02</td>\n",
       "      <td>12월</td>\n",
       "      <td>강신호,민영학(각자대표)</td>\n",
       "      <td>http://www.cjlogistics.com</td>\n",
       "      <td>서울특별시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7769</th>\n",
       "      <td>008775</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>호텔신라우</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7817</th>\n",
       "      <td>000547</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>흥국화재2우B</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7818</th>\n",
       "      <td>000545</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>흥국화재우</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7821</th>\n",
       "      <td>419890</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>히어로즈 단기채권ESG액티브</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7822</th>\n",
       "      <td>429870</td>\n",
       "      <td>KOSPI</td>\n",
       "      <td>히어로즈 리츠이지스액티브</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6127 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Symbol Market             Name               Sector  \\\n",
       "2019  000050  KOSPI               경방               종합 소매업   \n",
       "5248  000700  KOSPI            유수홀딩스  회사 본부 및 경영 컨설팅 서비스업   \n",
       "7676  003480  KOSPI         한진중공업홀딩스    연료용 가스 제조 및 배관공급업   \n",
       "2601  000060  KOSPI            메리츠화재                  보험업   \n",
       "66    000120  KOSPI           CJ대한통운            도로 화물 운송업   \n",
       "...      ...    ...              ...                  ...   \n",
       "7769  008775  KOSPI            호텔신라우                  NaN   \n",
       "7817  000547  KOSPI          흥국화재2우B                  NaN   \n",
       "7818  000545  KOSPI            흥국화재우                  NaN   \n",
       "7821  419890  KOSPI  히어로즈 단기채권ESG액티브                  NaN   \n",
       "7822  429870  KOSPI    히어로즈 리츠이지스액티브                  NaN   \n",
       "\n",
       "                                               Industry ListingDate  \\\n",
       "2019          섬유류(면사,면혼방사,면직물,면혼방직물,화섬사,화섬직물) 제조,도매,수출입  1956-03-03   \n",
       "5248                                               지주사업  1956-03-03   \n",
       "7676                                               지주회사  1956-03-03   \n",
       "2601                                   손해보험(화재,해상,운송보험)  1956-07-02   \n",
       "66    Contract Logistics, 포워딩, 항만하역, 해운, 택배국제특송, SCM...  1956-07-02   \n",
       "...                                                 ...         ...   \n",
       "7769                                                NaN         NaT   \n",
       "7817                                                NaN         NaT   \n",
       "7818                                                NaN         NaT   \n",
       "7821                                                NaN         NaT   \n",
       "7822                                                NaN         NaT   \n",
       "\n",
       "     SettleMonth Representative                      HomePage Region  \n",
       "2019         12월         김준, 김담    http://www.kyungbang.co.kr  서울특별시  \n",
       "5248         12월            송영규  http://www.eusu-holdings.com  서울특별시  \n",
       "7676         12월       조남호, 조원국  http://www.hhic-holdings.com    경기도  \n",
       "2601         12월            김용범     http://www.meritzfire.com  서울특별시  \n",
       "66           12월  강신호,민영학(각자대표)    http://www.cjlogistics.com  서울특별시  \n",
       "...          ...            ...                           ...    ...  \n",
       "7769         NaN            NaN                           NaN    NaN  \n",
       "7817         NaN            NaN                           NaN    NaN  \n",
       "7818         NaN            NaN                           NaN    NaN  \n",
       "7821         NaN            NaN                           NaN    NaN  \n",
       "7822         NaN            NaN                           NaN    NaN  \n",
       "\n",
       "[6127 rows x 10 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "상장.sort_values(by = 'ListingDate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "762b50c1",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
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       "      <th>Date</th>\n",
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       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1998-04-20</th>\n",
       "      <td>1243</td>\n",
       "      <td>1269</td>\n",
       "      <td>1227</td>\n",
       "      <td>1262</td>\n",
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       "      <th>1998-04-21</th>\n",
       "      <td>1279</td>\n",
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       "      <td>1252</td>\n",
       "      <td>1294</td>\n",
       "      <td>310010</td>\n",
       "      <td>0.025357</td>\n",
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       "    <tr>\n",
       "      <th>1998-04-22</th>\n",
       "      <td>1294</td>\n",
       "      <td>1314</td>\n",
       "      <td>1276</td>\n",
       "      <td>1282</td>\n",
       "      <td>324140</td>\n",
       "      <td>-0.009274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998-04-23</th>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>1238</td>\n",
       "      <td>1271</td>\n",
       "      <td>212640</td>\n",
       "      <td>-0.008580</td>\n",
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       "    <tr>\n",
       "      <th>1998-04-24</th>\n",
       "      <td>1270</td>\n",
       "      <td>1288</td>\n",
       "      <td>1239</td>\n",
       "      <td>1240</td>\n",
       "      <td>381180</td>\n",
       "      <td>-0.024390</td>\n",
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       "    <tr>\n",
       "      <th>2022-06-16</th>\n",
       "      <td>61300</td>\n",
       "      <td>61800</td>\n",
       "      <td>60500</td>\n",
       "      <td>60900</td>\n",
       "      <td>23394895</td>\n",
       "      <td>0.003295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-17</th>\n",
       "      <td>59400</td>\n",
       "      <td>59900</td>\n",
       "      <td>59400</td>\n",
       "      <td>59800</td>\n",
       "      <td>29053450</td>\n",
       "      <td>-0.018062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-20</th>\n",
       "      <td>59800</td>\n",
       "      <td>59900</td>\n",
       "      <td>58100</td>\n",
       "      <td>58700</td>\n",
       "      <td>34111306</td>\n",
       "      <td>-0.018395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-21</th>\n",
       "      <td>58700</td>\n",
       "      <td>59200</td>\n",
       "      <td>58200</td>\n",
       "      <td>58500</td>\n",
       "      <td>25148109</td>\n",
       "      <td>-0.003407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-22</th>\n",
       "      <td>59000</td>\n",
       "      <td>59100</td>\n",
       "      <td>57600</td>\n",
       "      <td>57600</td>\n",
       "      <td>22906785</td>\n",
       "      <td>-0.015385</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6000 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open   High    Low  Close    Volume    Change\n",
       "Date                                                      \n",
       "1998-04-20   1243   1269   1227   1262    152470       NaN\n",
       "1998-04-21   1279   1318   1252   1294    310010  0.025357\n",
       "1998-04-22   1294   1314   1276   1282    324140 -0.009274\n",
       "1998-04-23   1279   1279   1238   1271    212640 -0.008580\n",
       "1998-04-24   1270   1288   1239   1240    381180 -0.024390\n",
       "...           ...    ...    ...    ...       ...       ...\n",
       "2022-06-16  61300  61800  60500  60900  23394895  0.003295\n",
       "2022-06-17  59400  59900  59400  59800  29053450 -0.018062\n",
       "2022-06-20  59800  59900  58100  58700  34111306 -0.018395\n",
       "2022-06-21  58700  59200  58200  58500  25148109 -0.003407\n",
       "2022-06-22  59000  59100  57600  57600  22906785 -0.015385\n",
       "\n",
       "[6000 rows x 6 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "start_date = '20210303'\n",
    "end_date = '20211231'\n",
    "\n",
    "fdr.DataReader('005930') # , start = start_date, end = end_date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "bded7ec4",
   "metadata": {},
   "outputs": [
    {
     "ename": "JSONDecodeError",
     "evalue": "Expecting value: line 1 column 1 (char 0)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mJSONDecodeError\u001b[0m                           Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_882563/4247733274.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mend_date\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'19601231'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mfdr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'KS11'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/package/anaconda3.8/lib/python3.8/site-packages/FinanceDataReader/data.py\u001b[0m in \u001b[0;36mDataReader\u001b[0;34m(symbol, start, end, exchange, data_source)\u001b[0m\n\u001b[1;32m     39\u001b[0m     \u001b[0;31m# Investing\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     40\u001b[0m     \u001b[0mreader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mInvestingDailyReader\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 41\u001b[0;31m     \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mreader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msymbol\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstart\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexchange\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata_source\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     42\u001b[0m     \u001b[0mend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_datetime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mend\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdatetime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtoday\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     43\u001b[0m     \u001b[0;32mwhile\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0mend\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# issues/30\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/package/anaconda3.8/lib/python3.8/site-packages/FinanceDataReader/investing/data.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     60\u001b[0m         \u001b[0mstart_date_str\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstart\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrftime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'%m/%d/%Y'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     61\u001b[0m         \u001b[0mend_date_str\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mend\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrftime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'%m/%d/%Y'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 62\u001b[0;31m         \u001b[0mcurr_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_currid_investing\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msymbol\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexchange\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata_source\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     63\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mcurr_id\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     64\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Symbol unsupported or not found\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/package/anaconda3.8/lib/python3.8/site-packages/FinanceDataReader/investing/data.py\u001b[0m in \u001b[0;36m_get_currid_investing\u001b[0;34m(self, symbol, exchange, data_source)\u001b[0m\n\u001b[1;32m     28\u001b[0m         }\n\u001b[1;32m     29\u001b[0m         \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrequests\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpost\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'search_text'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0msymbol\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 30\u001b[0;31m         \u001b[0mjo\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mjson\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloads\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     31\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjo\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'quotes'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     32\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Symbol('{symbol}') not found\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/package/anaconda3.8/lib/python3.8/json/__init__.py\u001b[0m in \u001b[0;36mloads\u001b[0;34m(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)\u001b[0m\n\u001b[1;32m    355\u001b[0m             \u001b[0mparse_int\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mparse_float\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mand\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    356\u001b[0m             parse_constant is None and object_pairs_hook is None and not kw):\n\u001b[0;32m--> 357\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_default_decoder\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    358\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mcls\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    359\u001b[0m         \u001b[0mcls\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mJSONDecoder\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/package/anaconda3.8/lib/python3.8/json/decoder.py\u001b[0m in \u001b[0;36mdecode\u001b[0;34m(self, s, _w)\u001b[0m\n\u001b[1;32m    335\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    336\u001b[0m         \"\"\"\n\u001b[0;32m--> 337\u001b[0;31m         \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraw_decode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0midx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0m_w\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    338\u001b[0m         \u001b[0mend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_w\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    339\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mend\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/package/anaconda3.8/lib/python3.8/json/decoder.py\u001b[0m in \u001b[0;36mraw_decode\u001b[0;34m(self, s, idx)\u001b[0m\n\u001b[1;32m    353\u001b[0m             \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscan_once\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0midx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    354\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 355\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mJSONDecodeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Expecting value\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    356\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mJSONDecodeError\u001b[0m: Expecting value: line 1 column 1 (char 0)"
     ]
    }
   ],
   "source": [
    "start_date = '19560303'\n",
    "end_date = '19601231'\n",
    "\n",
    "fdr.DataReader('KS11') # , start = start_date, end = end_date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9feb3ecc",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  }
 ],
 "metadata": {
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