{ "cells": [ { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [], "source": [ "result = pd.read_csv(\"./onto-test/bi_lstm.csv\")\n", "result.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The RESULTS\n", "The top 20 subsidary groups are:" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | company1 | \n", "company2 | \n", "is_parent | \n", "
---|---|---|---|
4045 | \n", "UniCredit | \n", "HypoVereinsbank | \n", "0.999999 | \n", "
239 | \n", "Dropcam | \n", "0.999999 | \n", "|
5923 | \n", "Volkswagen_Group | \n", "Lamborghini | \n", "0.999999 | \n", "
6101 | \n", "Pfizer | \n", "Allergan | \n", "0.999999 | \n", "
7128 | \n", "AT&T | \n", "Time_Warner | \n", "0.999997 | \n", "
6960 | \n", "Takeda_Pharmaceutical_Company | \n", "ARIAD_Pharmaceuticals | \n", "0.999997 | \n", "
13628 | \n", "British_American_Tobacco | \n", "Reynolds_American | \n", "0.999997 | \n", "
3005 | \n", "AT&T | \n", "Time_Warner | \n", "0.999996 | \n", "
16988 | \n", "Bank_of_America | \n", "Jefferies_Group | \n", "0.999996 | \n", "
16434 | \n", "Warner_Bros. | \n", "0.999995 | \n", "|
7086 | \n", "Tesco | \n", "Ben_&_Jerry's | \n", "0.999995 | \n", "
12854 | \n", "Amazon.com | \n", "Warner_Bros. | \n", "0.999994 | \n", "
15946 | \n", "Verizon_Communications | \n", "Tumblr | \n", "0.999993 | \n", "
13977 | \n", "Volkswagen_Group | \n", "Lamborghini | \n", "0.999993 | \n", "
907 | \n", "AT&T | \n", "Time_Warner | \n", "0.999993 | \n", "
17078 | \n", "Berkshire_Hathaway | \n", "NV_Energy | \n", "0.999992 | \n", "
11874 | \n", "Id_Software | \n", "0.999991 | \n", "|
8109 | \n", "Oracle_Corporation | \n", "NetSuite | \n", "0.999990 | \n", "
8954 | \n", "Alexa_Internet | \n", "0.999989 | \n", "|
4331 | \n", "Molson_Coors_Brewing_Company | \n", "SABMiller | \n", "0.999988 | \n", "