diff --git "a/Network Science/Data/Archivo_s\303\255ntomas.ipynb" "b/Network Science/Data/Archivo_s\303\255ntomas.ipynb"
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index 0000000000000000000000000000000000000000..4441aacdd652cefe0c06a482208176a88af9ee00
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+++ "b/Network Science/Data/Archivo_s\303\255ntomas.ipynb"	
@@ -0,0 +1,123 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "d6b3c349-ae07-4be2-8e13-79fd26936534",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import seaborn as sns #este no sé para qué se usa -> creación de gráficos \n",
+    "import matplotlib.pyplot as plt\n",
+    "import networkx as nx\n",
+    "import csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "5daac64f-9764-4076-98a2-f83b8fcdc836",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cuis = pd.read_csv('cuis_stys.csv')\n",
+    "cuis.to_csv('cuis_stys.tsv', sep='\\t', index=False)\n",
+    "dse_sym = pd.read_csv('Links/dse_sym.tsv', sep=\"\\t\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "e3419cdc-7664-4614-ae50-2808ef2b9135",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#hago una lista con las enfermedades y otra con los síntomas del archivo cuis:\n",
+    "enfs = []\n",
+    "syms = []\n",
+    "syms_cui=[]\n",
+    "for i, sym in enumerate(cuis[\"TUI\"]):\n",
+    "    if sym == \"T184\":\n",
+    "        #syms.append(sym) #lista con los TUI de los síntomas\n",
+    "        syms_cui.append(cuis[\"CUI\"][i]) #lista con los CUI de los síntomas\n",
+    "    else:\n",
+    "        enfs.append(cuis[\"CUI\"][i]) #lista con los CUI de las enfermedades (las que no tienen el TUI correcto)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "e57fcada-20f1-4b90-982a-98445e0f8a4a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "syms_original=[]\n",
+    "enf_original=[]\n",
+    "for s1 in syms_cui:  # Recorrer la lista de síntomas\n",
+    "    for i, s2 in enumerate(dse_sym[\"sym\"]):  # Recorrer la columna de síntomas del archivo original\n",
+    "        if s1 == s2:  # Si uno de tus síntomas está en la columna de síntomas original\n",
+    "            enfermedad_cui = dse_sym[\"dse\"][i]  # Obtener el código CUI de la enfermedad\n",
+    "            if enfermedad_cui not in syms_cui:\n",
+    "                enf_original.append(enfermedad_cui)\n",
+    "                syms_original.append(s1)\n",
+    "                #print(str(enfermedad_cui) + \" es enfermedad y \" + str(s1) + \" es síntoma\")\n",
+    "                \n",
+    "#no hay posibilidad de relaciones enf - enf porque solo establecemos relaciones en el diccionario con los syms con TUI de síntoma."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "ce815fa0-610c-4a3e-b8d3-3ace87432d93",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#escribo el nombre de las columnas en el nuevo archivo\n",
+    "arch = pd.DataFrame({\"dse\": enf_original, \"sym\": syms_original})\n",
+    "dse_sym_limpio = \"dse_sym_limpio.csv\"\n",
+    "arch.to_csv(\"dse_sym_limpio.tsv\", sep =\"\\t\",index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "8f6fc9e2-748b-457a-87bd-59763f142dc9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dse_sym_limpio_f = pd.read_csv(\"dse_sym_limpio.tsv\", sep =\"\\t\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "11fdf2fd-f381-4752-b146-b9555d22fe2a",
+   "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": "3.11.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}