CUSIP.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 20856,
     "status": "ok",
     "timestamp": 1634143372595,
     "user": {
      "displayName": "Garvit Khurana",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgHlZhTmguzgFW3jERCp5bXjeOziGW4ujHWyQzr=s64",
      "userId": "01087518626428062277"
     },
     "user_tz": 240
    },
    "id": "eITcQSopCScy",
    "outputId": "35a2f654-cb68-4f4e-974b-52dde983b32d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mounted at /content/drive/\n"
     ]
    }
   ],
   "source": [
    "from google.colab import drive\n",
    "drive.mount('/content/drive/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "vf8N83saCmWn"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "36BC8GTDDC9G"
   },
   "outputs": [],
   "source": [
    "data_path = '/content/drive/MyDrive/Data/data.csv'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 408
    },
    "executionInfo": {
     "elapsed": 1505,
     "status": "ok",
     "timestamp": 1634143374685,
     "user": {
      "displayName": "Garvit Khurana",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgHlZhTmguzgFW3jERCp5bXjeOziGW4ujHWyQzr=s64",
      "userId": "01087518626428062277"
     },
     "user_tz": 240
    },
    "id": "gqvC0-9GFazK",
    "outputId": "d280eb06-7339-4639-fe88-69b0752f3981"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Manager</th>\n",
       "      <th>NAME OF ISSUER</th>\n",
       "      <th>TITLE OF CLASS</th>\n",
       "      <th>CUSIP</th>\n",
       "      <th>VALUE (x$1000)</th>\n",
       "      <th>INVESTMENT DISCRETION</th>\n",
       "      <th>SHRS OR PRN AMT</th>\n",
       "      <th>SH/PRN</th>\n",
       "      <th>VOTING AUTHORITY SOLE</th>\n",
       "      <th>VOTING AUTHORITY SHARED</th>\n",
       "      <th>VOTING AUTHORITY NONE</th>\n",
       "      <th>OTHER MANAGER</th>\n",
       "      <th>PUT/CALL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4110</th>\n",
       "      <td>MILLENNIUM MANAGEMENT LLC</td>\n",
       "      <td>1   800  FLOWERS   COM    INC</td>\n",
       "      <td>CL      A</td>\n",
       "      <td>68243Q106</td>\n",
       "      <td>10424</td>\n",
       "      <td>SOLE</td>\n",
       "      <td>327089</td>\n",
       "      <td>SH</td>\n",
       "      <td>327089</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10561</th>\n",
       "      <td>TWO SIGMA INVESTMENTS, LP</td>\n",
       "      <td>1 800 FLOWERS COM INC</td>\n",
       "      <td>CL A</td>\n",
       "      <td>68243Q106</td>\n",
       "      <td>521</td>\n",
       "      <td>SOLE</td>\n",
       "      <td>16357</td>\n",
       "      <td>SH</td>\n",
       "      <td>16357</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>705</th>\n",
       "      <td>RENAISSANCE TECHNOLOGIES LLC</td>\n",
       "      <td>1 800 FLOWERS COM INC</td>\n",
       "      <td>CL A</td>\n",
       "      <td>68243Q106</td>\n",
       "      <td>15925</td>\n",
       "      <td>SOLE</td>\n",
       "      <td>499700</td>\n",
       "      <td>SH</td>\n",
       "      <td>469515</td>\n",
       "      <td>0</td>\n",
       "      <td>30185</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14815</th>\n",
       "      <td>AQR CAPITAL MANAGEMENT LLC</td>\n",
       "      <td>1 800 FLOWERS COM INC</td>\n",
       "      <td>CL A</td>\n",
       "      <td>68243Q106</td>\n",
       "      <td>781</td>\n",
       "      <td>DFND</td>\n",
       "      <td>24517</td>\n",
       "      <td>SH</td>\n",
       "      <td>24517</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4112</th>\n",
       "      <td>MILLENNIUM MANAGEMENT LLC</td>\n",
       "      <td>10X  CAPITAL     VENTURE       ACQU   COR</td>\n",
       "      <td>*W      EXP     10/29/202</td>\n",
       "      <td>88025V115</td>\n",
       "      <td>1916</td>\n",
       "      <td>SOLE</td>\n",
       "      <td>1088750</td>\n",
       "      <td>SH</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1088750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Call</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Manager  ... PUT/CALL\n",
       "4110      MILLENNIUM MANAGEMENT LLC  ...      NaN\n",
       "10561     TWO SIGMA INVESTMENTS, LP  ...      NaN\n",
       "705    RENAISSANCE TECHNOLOGIES LLC  ...      NaN\n",
       "14815    AQR CAPITAL MANAGEMENT LLC  ...      NaN\n",
       "4112      MILLENNIUM MANAGEMENT LLC  ...     Call\n",
       "\n",
       "[5 rows x 13 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv(data_path)\n",
    "df=df.sort_values('NAME OF ISSUER')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "S4bYypFgmp8S"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "RtWqfDBiYYDb"
   },
   "outputs": [],
   "source": [
    "df=df[['Manager','NAME OF ISSUER','VALUE (x$1000)']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "executionInfo": {
     "elapsed": 1360,
     "status": "ok",
     "timestamp": 1634146136901,
     "user": {
      "displayName": "Garvit Khurana",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgHlZhTmguzgFW3jERCp5bXjeOziGW4ujHWyQzr=s64",
      "userId": "01087518626428062277"
     },
     "user_tz": 240
    },
    "id": "oplOqUxwsu4r",
    "outputId": "5fa84f20-e604-42f8-a6f6-afffced03197"
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots(figsize=(20, 20))\n",
    "sns.barplot(x='VALUE (x$1000)',y='Manager',data=df, ax=ax1)\n",
    "sns.despine(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "executionInfo": {
     "elapsed": 245381,
     "status": "ok",
     "timestamp": 1634145057740,
     "user": {
      "displayName": "Garvit Khurana",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgHlZhTmguzgFW3jERCp5bXjeOziGW4ujHWyQzr=s64",
      "userId": "01087518626428062277"
     },
     "user_tz": 240
    },
    "id": "-i_BvpQ2YYKb",
    "outputId": "8c67dbdc-b048-4692-c72d-a19ee610b80d"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots(figsize=(20, 20))\n",
    "sns.barplot(x='NAME OF ISSUER',y='VALUE (x$1000)',data=df, ax=ax1)\n",
    "sns.despine(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "mYEs8pD4GorZ"
   },
   "outputs": [],
   "source": [
    "df_issuer=pd.DataFrame(set(df['NAME OF ISSUER']),columns=['NAME OF ISSUER'])\n",
    "df_issuer=df_issuer.sort_values('NAME OF ISSUER')\n",
    "df_issuer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "HJPuFTHSQPGv"
   },
   "outputs": [],
   "source": [
    "df_cusip=pd.DataFrame(pd.DataFrame(df_issuer['NAME OF ISSUER']).merge(df[['CUSIP','NAME OF ISSUER']])).drop_duplicates()\n",
    "df_cusip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "wVkiVYtVRCZE"
   },
   "outputs": [],
   "source": [
    "df_cusip.to_csv('/content/drive/MyDrive/Data/cusip.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "OwPNUDelW3yT"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "name": "CUSIP.ipynb",
   "provenance": []
  },
  "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": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}