{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "dc1cc1e4-7bea-474f-b192-96de7b9086e6",
   "metadata": {},
   "source": [
    "# Análisis final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4a5392a2-8aff-4133-8d4f-ab8d43ad3d05",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51ee57cb-38b3-4962-b9d0-0885595b5fd5",
   "metadata": {},
   "source": [
    "Lo primero que hemos hecho ha sido cargar todos los datos que hemos generado y guardado en csv en los pasos anteriores de formateo.\n",
    "\n",
    "En este primer paso lo que nos interesa es solamente los ficheros con los pagos, por ello filtramos aquellos que contengan la palabra 'payment' en el nombre ya que todos empiezan su nombre como `payment_`.\n",
    "\n",
    "Además de esto, hemos visto que hay varios ficheros que suman un total de 0EUR en movimientos, así que estos los descartamos ya que no nos interesan para nuestro estudio."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ce639766-b7b5-44cc-b56c-85f367d52be1",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_files_path = './input'\n",
    "files = os.listdir(input_files_path)\n",
    "\n",
    "df = pd.DataFrame(columns=['filename', 'amount'])\n",
    "\n",
    "for file in files:\n",
    "    if os.path.isfile(os.path.join(input_files_path, file)):\n",
    "        if 'payment' in file:\n",
    "            path = os.path.join(input_files_path, file)\n",
    "            entities = pd.read_csv(path)\n",
    "            amount = entities.amount.sum()\n",
    "            if amount != 0.0:\n",
    "                df = df.append({'filename': file, 'amount': amount}, ignore_index=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16116fe3-01b9-4ceb-81f1-c052984750ab",
   "metadata": {},
   "source": [
    "Después de tener los totales de cada fichero los ordenamos y le damos formato a las cantidades para una representación más cómoda."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5b1d6bd6-2f43-4b4f-b11e-bcb1a4491c2d",
   "metadata": {},
   "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",
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       "    }\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>filename</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>payment_trimloc2017-econ-ingr-importes_Estimac...</td>\n",
       "      <td>436847778.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>payment_trimloc2017-econ-ingr-importes_Estimac...</td>\n",
       "      <td>436813581.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>payment_trimloc2017-econ-gast-importes_Estimac...</td>\n",
       "      <td>378481403.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>payment_trimloc2017-econ-gast-importes_Estimac...</td>\n",
       "      <td>375702492.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>payment_trimloc2017-remt_ImporteEjercicioActua...</td>\n",
       "      <td>287242552.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>payment_trimloc2017-econ-ingr-importes_Derecho...</td>\n",
       "      <td>53977408.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>payment_trimloc2017-econ-ingr-importes_Recauda...</td>\n",
       "      <td>53811324.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>payment_trimloc2017-econ-gast-importes_Obligac...</td>\n",
       "      <td>25892861.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>payment_trimloc2017-econ-gast-importes_PagosRe...</td>\n",
       "      <td>25640767.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>payment_trimloc2017-econ-gast-importes_PagosLi...</td>\n",
       "      <td>19449643.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>payment_trimloc2017-econ-ingr-importes_Recauda...</td>\n",
       "      <td>897957.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>payment_trimloc2017-anexo5_Capitulo4.csv</td>\n",
       "      <td>875696.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>payment_trimloc2017-anexo5_Capitulo8.csv</td>\n",
       "      <td>95944.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>payment_trimloc2017-anexo5_Capitulo2.csv</td>\n",
       "      <td>1038.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>payment_trimloc2017-anexo5_Capitulo6.csv</td>\n",
       "      <td>113.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             filename       amount\n",
       "10  payment_trimloc2017-econ-ingr-importes_Estimac... 436847778.46\n",
       "11  payment_trimloc2017-econ-ingr-importes_Estimac... 436813581.23\n",
       "4   payment_trimloc2017-econ-gast-importes_Estimac... 378481403.26\n",
       "5   payment_trimloc2017-econ-gast-importes_Estimac... 375702492.11\n",
       "14  payment_trimloc2017-remt_ImporteEjercicioActua... 287242552.08\n",
       "9   payment_trimloc2017-econ-ingr-importes_Derecho...  53977408.64\n",
       "13  payment_trimloc2017-econ-ingr-importes_Recauda...  53811324.38\n",
       "6   payment_trimloc2017-econ-gast-importes_Obligac...  25892861.08\n",
       "8   payment_trimloc2017-econ-gast-importes_PagosRe...  25640767.79\n",
       "7   payment_trimloc2017-econ-gast-importes_PagosLi...  19449643.77\n",
       "12  payment_trimloc2017-econ-ingr-importes_Recauda...    897957.72\n",
       "1            payment_trimloc2017-anexo5_Capitulo4.csv    875696.53\n",
       "3            payment_trimloc2017-anexo5_Capitulo8.csv     95944.02\n",
       "0            payment_trimloc2017-anexo5_Capitulo2.csv      1038.14\n",
       "2            payment_trimloc2017-anexo5_Capitulo6.csv       113.50"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.options.display.float_format = '{:.2f}'.format\n",
    "df.sort_values(by='amount', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dea0fbee-5821-4f8f-a345-b04c8cd0218d",
   "metadata": {},
   "source": [
    "## Entidades\n",
    "\n",
    "En este punto cargamos las entidades y hacemos varios análisis exploratorios. Vemos que pinta tienen los datos, como podemos conectarlos, que sentido le podemos dar, etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "aa538111-e5cb-480b-a66e-e368658f60b7",
   "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>id</th>\n",
       "      <th>entity</th>\n",
       "      <th>period</th>\n",
       "      <th>explicit_member</th>\n",
       "      <th>typed_member</th>\n",
       "      <th>dimension</th>\n",
       "      <th>typed_member_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1049</td>\n",
       "      <td>1049</td>\n",
       "      <td>1049</td>\n",
       "      <td>738</td>\n",
       "      <td>310</td>\n",
       "      <td>1048</td>\n",
       "      <td>310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>1049</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>738</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>IdContextoDatosBasicos</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-econ-ingr-cuentas:EconomicaIngresos</td>\n",
       "      <td>trimloc2017-anexo5:Filasdimension</td>\n",
       "      <td>trimloc2017-econ-gast:Cuentasdimension</td>\n",
       "      <td>Primer aval</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>1</td>\n",
       "      <td>1049</td>\n",
       "      <td>1049</td>\n",
       "      <td>1</td>\n",
       "      <td>300</td>\n",
       "      <td>372</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            id                                    entity  \\\n",
       "count                     1049                                      1049   \n",
       "unique                    1049                                         1   \n",
       "top     IdContextoDatosBasicos  EXCMA.DIPUTACION PROVINCIAL TERUEL         \n",
       "freq                         1                                      1049   \n",
       "\n",
       "            period                                  explicit_member  \\\n",
       "count         1049                                              738   \n",
       "unique           1                                              738   \n",
       "top     2021-03-31  trimloc2017-econ-ingr-cuentas:EconomicaIngresos   \n",
       "freq          1049                                                1   \n",
       "\n",
       "                             typed_member  \\\n",
       "count                                 310   \n",
       "unique                                  5   \n",
       "top     trimloc2017-anexo5:Filasdimension   \n",
       "freq                                  300   \n",
       "\n",
       "                                     dimension typed_member_value  \n",
       "count                                     1048                310  \n",
       "unique                                      10                303  \n",
       "top     trimloc2017-econ-gast:Cuentasdimension        Primer aval  \n",
       "freq                                       372                  4  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entities = pd.read_csv('./input/entities.csv')\n",
    "entities.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "349a991f-88c6-4293-ac31-206e49f75a17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan,\n",
       "       'trimloc2017-anexo4:AvalesEjecutadosClasificacionEconomicaDeGastosDimensionDeFilas',\n",
       "       'trimloc2017-anexo4:AvalesReintegradosClasificacionEconomicaDeIngresosDimensionDeFilas',\n",
       "       'trimloc2017-anexo4:AvalesEjecutadosConceptosNoPresupuestariosDimensionDeFilas',\n",
       "       'trimloc2017-anexo4:AvalesReintegradosConceptosNoPresupuestariosDimensionDeFilas',\n",
       "       'trimloc2017-anexo5:Filasdimension'], dtype=object)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entities['typed_member'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8534bcdd-662e-4340-b901-13e20614190f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>decimals</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>IdContextosAnexo5_Transferencia1</td>\n",
       "      <td>euro</td>\n",
       "      <td>10.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>IdContextosAnexo5_Transferencia3</td>\n",
       "      <td>euro</td>\n",
       "      <td>776.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>IdContextosAnexo5_Transferencia6</td>\n",
       "      <td>euro</td>\n",
       "      <td>96.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>IdContextosAnexo5_Transferencia7</td>\n",
       "      <td>euro</td>\n",
       "      <td>154.54</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   decimals                         reference currency  amount\n",
       "0         0  IdContextosAnexo5_Transferencia1     euro   10.79\n",
       "2         0  IdContextosAnexo5_Transferencia3     euro  776.21\n",
       "5         0  IdContextosAnexo5_Transferencia6     euro   96.60\n",
       "6         0  IdContextosAnexo5_Transferencia7     euro  154.54"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "anexo5_Capitulo2 = pd.read_csv('./input/payment_trimloc2017-anexo5_Capitulo2.csv', index_col=0)\n",
    "anexo5_Capitulo2 = anexo5_Capitulo2[anexo5_Capitulo2.amount != 0.0]\n",
    "anexo5_Capitulo2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d3ce9286-8ea2-40f7-b5eb-62f3a1d7530e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4.00</td>\n",
       "      <td>4.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.00</td>\n",
       "      <td>259.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.00</td>\n",
       "      <td>349.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.00</td>\n",
       "      <td>10.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.00</td>\n",
       "      <td>75.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.00</td>\n",
       "      <td>125.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.00</td>\n",
       "      <td>309.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.00</td>\n",
       "      <td>776.21</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       decimals  amount\n",
       "count      4.00    4.00\n",
       "mean       0.00  259.54\n",
       "std        0.00  349.48\n",
       "min        0.00   10.79\n",
       "25%        0.00   75.15\n",
       "50%        0.00  125.57\n",
       "75%        0.00  309.96\n",
       "max        0.00  776.21"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "anexo5_Capitulo2.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b25b20ab-6253-4632-8055-9b338b3910db",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "      <td>IdContextosEconomicaGastos_OrganosDeGobiernoYP...</td>\n",
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       "      <td>993006.93</td>\n",
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       "      <th>1</th>\n",
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       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>IdContextosEconomicaGastos_OrganosDeGobiernoYP...</td>\n",
       "      <td>euro</td>\n",
       "      <td>993006.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>IdContextosEconomicaGastos_PersonalEventual_Re...</td>\n",
       "      <td>euro</td>\n",
       "      <td>101119.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>IdContextosEconomicaGastos_PersonalEventual_Re...</td>\n",
       "      <td>euro</td>\n",
       "      <td>156655.90</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   decimals                                          reference currency  \\\n",
       "0         2  IdContextosEconomicaGastos_OrganosDeGobiernoYP...     euro   \n",
       "1         2  IdContextosEconomicaGastos_RetribucionesBasica...     euro   \n",
       "2         2  IdContextosEconomicaGastos_OrganosDeGobiernoYP...     euro   \n",
       "3         2  IdContextosEconomicaGastos_PersonalEventual_Re...     euro   \n",
       "4         2  IdContextosEconomicaGastos_PersonalEventual_Re...     euro   \n",
       "\n",
       "     amount  \n",
       "0 993006.93  \n",
       "1 993006.93  \n",
       "2 993006.93  \n",
       "3 101119.27  \n",
       "4 156655.90  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EstimacionCreditosDefinitivosAFinEjercicioCorriente = pd.read_csv('./input/payment_trimloc2017-econ-gast-importes_EstimacionCreditosDefinitivosAFinEjercicioCorriente.csv', index_col=0)\n",
    "EstimacionCreditosDefinitivosAFinEjercicioCorriente = EstimacionCreditosDefinitivosAFinEjercicioCorriente[EstimacionCreditosDefinitivosAFinEjercicioCorriente.amount != 0.0]\n",
    "EstimacionCreditosDefinitivosAFinEjercicioCorriente.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2cb6544a-def1-4f1a-bc59-a9068620b88b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>amount</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>count</th>\n",
       "      <td>167.00</td>\n",
       "      <td>167.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.00</td>\n",
       "      <td>2266355.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.00</td>\n",
       "      <td>5809076.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.00</td>\n",
       "      <td>700.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.00</td>\n",
       "      <td>49489.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.00</td>\n",
       "      <td>213917.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.00</td>\n",
       "      <td>1074775.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.00</td>\n",
       "      <td>35330539.20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "       decimals      amount\n",
       "count    167.00      167.00\n",
       "mean       2.00  2266355.71\n",
       "std        0.00  5809076.31\n",
       "min        2.00      700.00\n",
       "25%        2.00    49489.85\n",
       "50%        2.00   213917.93\n",
       "75%        2.00  1074775.59\n",
       "max        2.00 35330539.20"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EstimacionCreditosDefinitivosAFinEjercicioCorriente.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e5b006d5-1ee1-4851-86fa-ea19bf0fa04a",
   "metadata": {},
   "outputs": [],
   "source": [
    "reference = EstimacionCreditosDefinitivosAFinEjercicioCorriente.reference[0]"
   ]
  },
  {
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   "execution_count": 11,
   "id": "b796ac92-ad62-4e16-84dc-15cfbdbcbd7d",
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   "outputs": [
    {
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       "                                                    id  \\\n",
       "573  IdContextosEconomicaGastos_OrganosDeGobiernoYP...   \n",
       "\n",
       "                                       entity      period  \\\n",
       "573  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "\n",
       "                                       explicit_member typed_member  \\\n",
       "573  trimloc2017-econ-gast-cuentas:OrganosDeGobiern...          NaN   \n",
       "\n",
       "                                  dimension typed_member_value  \n",
       "573  trimloc2017-econ-gast:Cuentasdimension                NaN  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "entities[entities.id == reference]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c481f763-2b23-49c5-9685-f21623f236e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>euro</td>\n",
       "      <td>993006.93</td>\n",
       "      <td>IdContextosEconomicaGastos_OrganosDeGobiernoYP...</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-econ-gast-cuentas:OrganosDeGobiern...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-econ-gast:Cuentasdimension</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
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       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>IdContextosEconomicaGastos_PersonalEventual_Re...</td>\n",
       "      <td>euro</td>\n",
       "      <td>101119.27</td>\n",
       "      <td>IdContextosEconomicaGastos_PersonalEventual_Re...</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-econ-gast-cuentas:PersonalEventual...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-econ-gast:Cuentasdimension</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>IdContextosEconomicaGastos_PersonalEventual_Re...</td>\n",
       "      <td>euro</td>\n",
       "      <td>156655.90</td>\n",
       "      <td>IdContextosEconomicaGastos_PersonalEventual_Re...</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-econ-gast-cuentas:PersonalEventual...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-econ-gast:Cuentasdimension</td>\n",
       "      <td>NaN</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   decimals                                          reference currency  \\\n",
       "0         2  IdContextosEconomicaGastos_OrganosDeGobiernoYP...     euro   \n",
       "1         2  IdContextosEconomicaGastos_RetribucionesBasica...     euro   \n",
       "2         2  IdContextosEconomicaGastos_OrganosDeGobiernoYP...     euro   \n",
       "3         2  IdContextosEconomicaGastos_PersonalEventual_Re...     euro   \n",
       "4         2  IdContextosEconomicaGastos_PersonalEventual_Re...     euro   \n",
       "\n",
       "     amount                                                 id  \\\n",
       "0 993006.93  IdContextosEconomicaGastos_OrganosDeGobiernoYP...   \n",
       "1 993006.93  IdContextosEconomicaGastos_RetribucionesBasica...   \n",
       "2 993006.93  IdContextosEconomicaGastos_OrganosDeGobiernoYP...   \n",
       "3 101119.27  IdContextosEconomicaGastos_PersonalEventual_Re...   \n",
       "4 156655.90  IdContextosEconomicaGastos_PersonalEventual_Re...   \n",
       "\n",
       "                                     entity      period  \\\n",
       "0  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "1  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "2  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "3  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "4  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "\n",
       "                                     explicit_member typed_member  \\\n",
       "0  trimloc2017-econ-gast-cuentas:OrganosDeGobiern...          NaN   \n",
       "1  trimloc2017-econ-gast-cuentas:RetribucionesBas...          NaN   \n",
       "2  trimloc2017-econ-gast-cuentas:OrganosDeGobiern...          NaN   \n",
       "3  trimloc2017-econ-gast-cuentas:PersonalEventual...          NaN   \n",
       "4  trimloc2017-econ-gast-cuentas:PersonalEventual...          NaN   \n",
       "\n",
       "                                dimension typed_member_value  \n",
       "0  trimloc2017-econ-gast:Cuentasdimension                NaN  \n",
       "1  trimloc2017-econ-gast:Cuentasdimension                NaN  \n",
       "2  trimloc2017-econ-gast:Cuentasdimension                NaN  \n",
       "3  trimloc2017-econ-gast:Cuentasdimension                NaN  \n",
       "4  trimloc2017-econ-gast:Cuentasdimension                NaN  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged = EstimacionCreditosDefinitivosAFinEjercicioCorriente.merge(entities, right_on='id', left_on='reference')\n",
    "merged.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e3a84ba-2717-4d4b-9003-ff89b7e40420",
   "metadata": {},
   "source": [
    "## Mezcla de datos\n",
    "\n",
    "Tras varias pruebas hemos visto que podemos unir los datos de los pagos con las entidades según la referencia que tengan estas y el ID de cada pago.  \n",
    "\n",
    "Para esto lo que hacemos es primeramente mezclar cada fichero de pagos con las entidades y con esta mezcla crear un dataset nuevo con todos los pagos y las entidades concatenadas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "360257ce-d2dd-4720-b1cb-5a3a53e645d5",
   "metadata": {},
   "outputs": [
    {
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       "      <td>IdContextosAnexo1_InteresesDeDepositosYFianzas</td>\n",
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       "      <td>2021-03-31</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>trimloc2017-anexo1:Conceptosdimension</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>IdContextosAnexo1_EjecucionDeAvales357</td>\n",
       "      <td>euro</td>\n",
       "      <td>0.00</td>\n",
       "      <td>IdContextosAnexo1_EjecucionDeAvales357</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-anexo1:EjecucionDeAvales357</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-anexo1:Conceptosdimension</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2</td>\n",
       "      <td>R42</td>\n",
       "      <td>euro</td>\n",
       "      <td>1776599.45</td>\n",
       "      <td>R42</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-remt:ExcesoDeFinanciacionAfectada</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-remt:FilasdeRemanentedeTesoreriadi...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2</td>\n",
       "      <td>R49t</td>\n",
       "      <td>euro</td>\n",
       "      <td>63588850.58</td>\n",
       "      <td>R49t</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-remt:RemanenteDeTesoreriaParaGasto...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-remt:FilasdeRemanentedeTesoreriadi...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2</td>\n",
       "      <td>R59t</td>\n",
       "      <td>euro</td>\n",
       "      <td>210410.12</td>\n",
       "      <td>R59t</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-remt:SaldoDeObligacionesPendientes...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-remt:FilasdeRemanentedeTesoreriadi...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2</td>\n",
       "      <td>R69t</td>\n",
       "      <td>euro</td>\n",
       "      <td>131.25</td>\n",
       "      <td>R69t</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-remt:SaldoDeObligacionesPorDevoluc...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-remt:FilasdeRemanentedeTesoreriadi...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2</td>\n",
       "      <td>R79</td>\n",
       "      <td>euro</td>\n",
       "      <td>63378309.21</td>\n",
       "      <td>R79</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-remt:RemanenteDeTesoreriaParaGasto...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-remt:FilasdeRemanentedeTesoreriadi...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1629 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    decimals                                          reference currency  \\\n",
       "0          2          IdContextosAnexo1_InteresesDeDeudaPublica     euro   \n",
       "1          2  IdContextosAnexo1_InteresesDePrestamosYOtrasOp...     euro   \n",
       "2          2     IdContextosAnexo1_InteresesDeDepositosYFianzas     euro   \n",
       "3          2            IdContextosAnexo1_OtrosIntereses352y358     euro   \n",
       "4          2             IdContextosAnexo1_EjecucionDeAvales357     euro   \n",
       "..       ...                                                ...      ...   \n",
       "14         2                                                R42     euro   \n",
       "15         2                                               R49t     euro   \n",
       "16         2                                               R59t     euro   \n",
       "17         2                                               R69t     euro   \n",
       "18         2                                                R79     euro   \n",
       "\n",
       "        amount                                                 id  \\\n",
       "0         0.00          IdContextosAnexo1_InteresesDeDeudaPublica   \n",
       "1         0.00  IdContextosAnexo1_InteresesDePrestamosYOtrasOp...   \n",
       "2         0.00     IdContextosAnexo1_InteresesDeDepositosYFianzas   \n",
       "3         0.00            IdContextosAnexo1_OtrosIntereses352y358   \n",
       "4         0.00             IdContextosAnexo1_EjecucionDeAvales357   \n",
       "..         ...                                                ...   \n",
       "14  1776599.45                                                R42   \n",
       "15 63588850.58                                               R49t   \n",
       "16   210410.12                                               R59t   \n",
       "17      131.25                                               R69t   \n",
       "18 63378309.21                                                R79   \n",
       "\n",
       "                                      entity      period  \\\n",
       "0   EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "1   EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "2   EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "3   EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "4   EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "..                                       ...         ...   \n",
       "14  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "15  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "16  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "17  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "18  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "\n",
       "                                      explicit_member typed_member  \\\n",
       "0          trimloc2017-anexo1:InteresesDeDeudaPublica          NaN   \n",
       "1   trimloc2017-anexo1:InteresesDePrestamosYOtrasO...          NaN   \n",
       "2     trimloc2017-anexo1:InteresesDeDepositosYFianzas          NaN   \n",
       "3            trimloc2017-anexo1:OtrosIntereses352y358          NaN   \n",
       "4             trimloc2017-anexo1:EjecucionDeAvales357          NaN   \n",
       "..                                                ...          ...   \n",
       "14      trimloc2017-remt:ExcesoDeFinanciacionAfectada          NaN   \n",
       "15  trimloc2017-remt:RemanenteDeTesoreriaParaGasto...          NaN   \n",
       "16  trimloc2017-remt:SaldoDeObligacionesPendientes...          NaN   \n",
       "17  trimloc2017-remt:SaldoDeObligacionesPorDevoluc...          NaN   \n",
       "18  trimloc2017-remt:RemanenteDeTesoreriaParaGasto...          NaN   \n",
       "\n",
       "                                            dimension typed_member_value  \n",
       "0               trimloc2017-anexo1:Conceptosdimension                NaN  \n",
       "1               trimloc2017-anexo1:Conceptosdimension                NaN  \n",
       "2               trimloc2017-anexo1:Conceptosdimension                NaN  \n",
       "3               trimloc2017-anexo1:Conceptosdimension                NaN  \n",
       "4               trimloc2017-anexo1:Conceptosdimension                NaN  \n",
       "..                                                ...                ...  \n",
       "14  trimloc2017-remt:FilasdeRemanentedeTesoreriadi...                NaN  \n",
       "15  trimloc2017-remt:FilasdeRemanentedeTesoreriadi...                NaN  \n",
       "16  trimloc2017-remt:FilasdeRemanentedeTesoreriadi...                NaN  \n",
       "17  trimloc2017-remt:FilasdeRemanentedeTesoreriadi...                NaN  \n",
       "18  trimloc2017-remt:FilasdeRemanentedeTesoreriadi...                NaN  \n",
       "\n",
       "[1629 rows x 11 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_payments = None\n",
    "for file in files:\n",
    "    if os.path.isfile(os.path.join(input_files_path, file)):\n",
    "        if 'payment_' in file:\n",
    "            path = os.path.join(input_files_path, file)\n",
    "            payments = pd.read_csv(path, index_col=0)\n",
    "            merged = payments.merge(entities, right_on='id', left_on='reference', how='left')\n",
    "\n",
    "            if all_payments is None:\n",
    "                all_payments = merged\n",
    "            else:\n",
    "                all_payments = pd.concat([all_payments, merged])\n",
    "\n",
    "all_payments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "79dac2ed-1184-4fdc-8049-77270b560204",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                                                  1629\n",
       "unique                                                  294\n",
       "top       IdContextosEconomicaGastos_TransferenciasCorri...\n",
       "freq                                                      6\n",
       "Name: id, dtype: object"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_payments.id.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "caea2533-3fb1-4359-aa5a-16f6eed1e69a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2095730562.7099998"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_payments.amount.sum()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "422ff225-5998-4eb2-89f5-422e8d4ef1e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_payments.to_csv('output/all_payments.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba03b4d4-3a6a-4f4b-9725-95bbd1c63c8a",
   "metadata": {},
   "source": [
    "## Agrupemos\n",
    "\n",
    "Ahora toca el turno de agrupar y visualizar. En esta parte nos hemos puesto a agrupar este dataset con todos los pagos y entidades por diferentes campos para ver si podemos llegar a alguna conclusión. Además, para que sea más fácil de comprender hemos pintado algunas gráficas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d43af4e4-b4c3-4862-9ea0-76e17bb81557",
   "metadata": {},
   "outputs": [],
   "source": [
    "group_payments = all_payments[all_payments.amount != 0.0] # remove before sum to avoid errors\n",
    "group_payments = group_payments.groupby('id').sum()\n",
    "group_payments = group_payments.sort_values(by='amount', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "de0ca7b5-75da-482e-9e38-087ef9d144a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "group_payments.to_csv('output/payments_group_by_id.csv', index_label='index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "49554dee-9aa1-49f7-b1ba-393a27147e58",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='amount', ylabel='id'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_10_payments = group_payments.head(10)\n",
    "sns.barplot(x=top_10_payments['amount'], y=top_10_payments.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "747b561b-867a-415b-ad5d-bd6a6277e0f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='amount', ylabel='id'>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "botton_10_payments = group_payments.tail(10)\n",
    "sns.barplot(x=botton_10_payments['amount'], y=botton_10_payments.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "43e1e10c-5c01-468a-b41a-63fbeba9c02b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(284, 2)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "group_payments_without_empties = group_payments[group_payments.amount != 0.0]\n",
    "group_payments_without_empties.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "95061f56-ced3-4ff9-bd63-84cf4309887e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='amount', ylabel='id'>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "botton_10_payments = group_payments_without_empties[:-2].tail(6)\n",
    "sns.barplot(x=botton_10_payments['amount'], y=botton_10_payments.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3bda6b9b-edf9-4760-9b0f-1cd3125247ee",
   "metadata": {},
   "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>decimals</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>IdContextosEconomicaIngresos_DerechoDeSuperficieConContraprestacionNoPeriodica</th>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdContextosEconomicaGastos_ProductosAlimenticios</th>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdContextosEconomicaGastos_EconomicaGastos_GastosFinancieros_InteresesDeDemoraYOtrosGastosFinancieros_InteresesDeDemora</th>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdContextosEconomicaIngresos_ParaGastosConFinanciacionAfectada</th>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdContextosEconomicaIngresos_ProductosDeConcesionesYAprovechamientosEspeciales</th>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdContextosEconomicaIngresos_TransferenciaCorrientes_DeEntidadesLocales_DeComarcas</th>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    decimals  amount\n",
       "id                                                                  \n",
       "IdContextosEconomicaIngresos_DerechoDeSuperfici...         4    0.01\n",
       "IdContextosEconomicaGastos_ProductosAlimenticios           4    0.01\n",
       "IdContextosEconomicaGastos_EconomicaGastos_Gast...         4    0.01\n",
       "IdContextosEconomicaIngresos_ParaGastosConFinan...         4    0.01\n",
       "IdContextosEconomicaIngresos_ProductosDeConcesi...         4    0.01\n",
       "IdContextosEconomicaIngresos_TransferenciaCorri...         4    0.01"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "botton_10_payments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "189b978d-dea0-44a4-a43a-2b2f2ed9a42a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='amount', ylabel='id'>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "botton_10_payments = group_payments_without_empties[:-9].tail(10)\n",
    "sns.barplot(x=botton_10_payments['amount'], y=botton_10_payments.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b6a70fc9-3682-436e-99d9-e6e8ac9716c6",
   "metadata": {},
   "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>decimals</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>IdContextosEconomicaIngresos_DerechoDeSuperficieConContraprestacionNoPeriodica</th>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdContextosEconomicaGastos_ProductosAlimenticios</th>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdContextosEconomicaGastos_EconomicaGastos_GastosFinancieros_InteresesDeDemoraYOtrosGastosFinancieros_InteresesDeDemora</th>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdContextosEconomicaIngresos_ParaGastosConFinanciacionAfectada</th>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdContextosEconomicaIngresos_ProductosDeConcesionesYAprovechamientosEspeciales</th>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdContextosEconomicaIngresos_TransferenciaCorrientes_DeEntidadesLocales_DeComarcas</th>\n",
       "      <td>4</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    decimals  amount\n",
       "id                                                                  \n",
       "IdContextosEconomicaIngresos_DerechoDeSuperfici...         4    0.01\n",
       "IdContextosEconomicaGastos_ProductosAlimenticios           4    0.01\n",
       "IdContextosEconomicaGastos_EconomicaGastos_Gast...         4    0.01\n",
       "IdContextosEconomicaIngresos_ParaGastosConFinan...         4    0.01\n",
       "IdContextosEconomicaIngresos_ProductosDeConcesi...         4    0.01\n",
       "IdContextosEconomicaIngresos_TransferenciaCorri...         4    0.01"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "group_payments_without_empties[group_payments_without_empties.amount == 0.01]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c48036d6-2368-490e-bbbb-8ad95e93d363",
   "metadata": {},
   "outputs": [
    {
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       "      <th>decimals</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>IdContextosAnexo1_InteresesDeDeudaPublica</td>\n",
       "      <td>euro</td>\n",
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       "      <td>IdContextosAnexo1_InteresesDePrestamosYOtrasOp...</td>\n",
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       "      <td>2</td>\n",
       "      <td>IdContextosAnexo1_InteresesDeDepositosYFianzas</td>\n",
       "      <td>euro</td>\n",
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       "      <td>IdContextosAnexo1_InteresesDeDepositosYFianzas</td>\n",
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       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-anexo1:InteresesDeDepositosYFianzas</td>\n",
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       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>IdContextosAnexo1_OtrosIntereses352y358</td>\n",
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       "      <td>IdContextosAnexo1_OtrosIntereses352y358</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>IdContextosAnexo1_EjecucionDeAvales357</td>\n",
       "      <td>euro</td>\n",
       "      <td>0.00</td>\n",
       "      <td>IdContextosAnexo1_EjecucionDeAvales357</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-anexo1:EjecucionDeAvales357</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-anexo1:Conceptosdimension</td>\n",
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       "    <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",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2</td>\n",
       "      <td>R42</td>\n",
       "      <td>euro</td>\n",
       "      <td>1776599.45</td>\n",
       "      <td>R42</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-remt:ExcesoDeFinanciacionAfectada</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-remt:FilasdeRemanentedeTesoreriadi...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2</td>\n",
       "      <td>R49t</td>\n",
       "      <td>euro</td>\n",
       "      <td>63588850.58</td>\n",
       "      <td>R49t</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-remt:RemanenteDeTesoreriaParaGasto...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-remt:FilasdeRemanentedeTesoreriadi...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2</td>\n",
       "      <td>R59t</td>\n",
       "      <td>euro</td>\n",
       "      <td>210410.12</td>\n",
       "      <td>R59t</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-remt:SaldoDeObligacionesPendientes...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-remt:FilasdeRemanentedeTesoreriadi...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2</td>\n",
       "      <td>R69t</td>\n",
       "      <td>euro</td>\n",
       "      <td>131.25</td>\n",
       "      <td>R69t</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-remt:SaldoDeObligacionesPorDevoluc...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-remt:FilasdeRemanentedeTesoreriadi...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2</td>\n",
       "      <td>R79</td>\n",
       "      <td>euro</td>\n",
       "      <td>63378309.21</td>\n",
       "      <td>R79</td>\n",
       "      <td>EXCMA.DIPUTACION PROVINCIAL TERUEL</td>\n",
       "      <td>2021-03-31</td>\n",
       "      <td>trimloc2017-remt:RemanenteDeTesoreriaParaGasto...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>trimloc2017-remt:FilasdeRemanentedeTesoreriadi...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1629 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    decimals                                          reference currency  \\\n",
       "0          2          IdContextosAnexo1_InteresesDeDeudaPublica     euro   \n",
       "1          2  IdContextosAnexo1_InteresesDePrestamosYOtrasOp...     euro   \n",
       "2          2     IdContextosAnexo1_InteresesDeDepositosYFianzas     euro   \n",
       "3          2            IdContextosAnexo1_OtrosIntereses352y358     euro   \n",
       "4          2             IdContextosAnexo1_EjecucionDeAvales357     euro   \n",
       "..       ...                                                ...      ...   \n",
       "14         2                                                R42     euro   \n",
       "15         2                                               R49t     euro   \n",
       "16         2                                               R59t     euro   \n",
       "17         2                                               R69t     euro   \n",
       "18         2                                                R79     euro   \n",
       "\n",
       "        amount                                                 id  \\\n",
       "0         0.00          IdContextosAnexo1_InteresesDeDeudaPublica   \n",
       "1         0.00  IdContextosAnexo1_InteresesDePrestamosYOtrasOp...   \n",
       "2         0.00     IdContextosAnexo1_InteresesDeDepositosYFianzas   \n",
       "3         0.00            IdContextosAnexo1_OtrosIntereses352y358   \n",
       "4         0.00             IdContextosAnexo1_EjecucionDeAvales357   \n",
       "..         ...                                                ...   \n",
       "14  1776599.45                                                R42   \n",
       "15 63588850.58                                               R49t   \n",
       "16   210410.12                                               R59t   \n",
       "17      131.25                                               R69t   \n",
       "18 63378309.21                                                R79   \n",
       "\n",
       "                                      entity      period  \\\n",
       "0   EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "1   EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "2   EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "3   EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "4   EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "..                                       ...         ...   \n",
       "14  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "15  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "16  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "17  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "18  EXCMA.DIPUTACION PROVINCIAL TERUEL        2021-03-31   \n",
       "\n",
       "                                      explicit_member typed_member  \\\n",
       "0          trimloc2017-anexo1:InteresesDeDeudaPublica          NaN   \n",
       "1   trimloc2017-anexo1:InteresesDePrestamosYOtrasO...          NaN   \n",
       "2     trimloc2017-anexo1:InteresesDeDepositosYFianzas          NaN   \n",
       "3            trimloc2017-anexo1:OtrosIntereses352y358          NaN   \n",
       "4             trimloc2017-anexo1:EjecucionDeAvales357          NaN   \n",
       "..                                                ...          ...   \n",
       "14      trimloc2017-remt:ExcesoDeFinanciacionAfectada          NaN   \n",
       "15  trimloc2017-remt:RemanenteDeTesoreriaParaGasto...          NaN   \n",
       "16  trimloc2017-remt:SaldoDeObligacionesPendientes...          NaN   \n",
       "17  trimloc2017-remt:SaldoDeObligacionesPorDevoluc...          NaN   \n",
       "18  trimloc2017-remt:RemanenteDeTesoreriaParaGasto...          NaN   \n",
       "\n",
       "                                            dimension typed_member_value  \n",
       "0               trimloc2017-anexo1:Conceptosdimension                NaN  \n",
       "1               trimloc2017-anexo1:Conceptosdimension                NaN  \n",
       "2               trimloc2017-anexo1:Conceptosdimension                NaN  \n",
       "3               trimloc2017-anexo1:Conceptosdimension                NaN  \n",
       "4               trimloc2017-anexo1:Conceptosdimension                NaN  \n",
       "..                                                ...                ...  \n",
       "14  trimloc2017-remt:FilasdeRemanentedeTesoreriadi...                NaN  \n",
       "15  trimloc2017-remt:FilasdeRemanentedeTesoreriadi...                NaN  \n",
       "16  trimloc2017-remt:FilasdeRemanentedeTesoreriadi...                NaN  \n",
       "17  trimloc2017-remt:FilasdeRemanentedeTesoreriadi...                NaN  \n",
       "18  trimloc2017-remt:FilasdeRemanentedeTesoreriadi...                NaN  \n",
       "\n",
       "[1629 rows x 11 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_payments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "207d586a-c054-4d15-bfb9-d6ed7aa775bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "group_payments_by_explicit_member = all_payments[all_payments.amount != 0.0] # remove before sum to avoid errors\n",
    "group_payments_by_explicit_member = group_payments_by_explicit_member.groupby('explicit_member').sum()\n",
    "group_payments_by_explicit_member = group_payments_by_explicit_member.drop('decimals', axis=1)\n",
    "group_payments_by_explicit_member = group_payments_by_explicit_member.sort_values(by='amount', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "07bb92d7-8f7d-4553-8873-a25935906909",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>trimloc2017-econ-ingr-cuentas:TransferenciasCorrientes</th>\n",
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       "      <td>123657224.34</td>\n",
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       "      <td>123657224.34</td>\n",
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       "    <tr>\n",
       "      <th>trimloc2017-econ-ingr-cuentas:EconomicaIngresos_ActivosFinancieros</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trimloc2017-econ-gast-cuentas:ProductosAlimenticios</th>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trimloc2017-econ-ingr-cuentas:ProductosDeConcesionesYAprovechamientosEspeciales</th>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trimloc2017-econ-ingr-cuentas:DerechoDeSuperficieConContraprestacionNoPeriodica</th>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trimloc2017-econ-ingr-cuentas:EconomicaIngresos_TasasPreciosPublicosYOtrosIngresos_OtrosIngresos_InteresesDeDemora</th>\n",
       "      <td>-95364.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trimloc2017-remt:PartidasPendientesDeAplicacion</th>\n",
       "      <td>-155416.81</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>276 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                         amount\n",
       "explicit_member                                                \n",
       "trimloc2017-econ-ingr-cuentas:TransferenciasCor... 129203875.85\n",
       "trimloc2017-econ-ingr-cuentas:TransferenciaCorr... 123757224.34\n",
       "trimloc2017-econ-ingr-cuentas:TransferenciaCorr... 123657224.34\n",
       "trimloc2017-econ-ingr-cuentas:FondoComplementar... 123657224.34\n",
       "trimloc2017-econ-ingr-cuentas:EconomicaIngresos...  73924826.67\n",
       "...                                                         ...\n",
       "trimloc2017-econ-gast-cuentas:ProductosAlimenti...         0.01\n",
       "trimloc2017-econ-ingr-cuentas:ProductosDeConces...         0.01\n",
       "trimloc2017-econ-ingr-cuentas:DerechoDeSuperfic...         0.01\n",
       "trimloc2017-econ-ingr-cuentas:EconomicaIngresos...    -95364.32\n",
       "trimloc2017-remt:PartidasPendientesDeAplicacion      -155416.81\n",
       "\n",
       "[276 rows x 1 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "group_payments_by_explicit_member"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "ffe08094-7798-4e77-b236-3c40999e00e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='amount', ylabel='explicit_member'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_10_explicit_member_payments = group_payments_by_explicit_member.head(10)\n",
    "sns.barplot(x=top_10_explicit_member_payments['amount'], y=top_10_explicit_member_payments.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "d5fa370b-b836-4235-869b-d128e30e4eac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='amount', ylabel='explicit_member'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "botton_10_explicit_member_payments = group_payments_by_explicit_member.tail(10)\n",
    "sns.barplot(x=botton_10_explicit_member_payments['amount'], y=botton_10_explicit_member_payments.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ad7e4b87-e807-49a7-898f-0f0c9bdea53e",
   "metadata": {},
   "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>amount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dimension</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>trimloc2017-econ-ingr:Cuentasdimension</th>\n",
       "      <td>982348050.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trimloc2017-econ-gast:Cuentasdimension</th>\n",
       "      <td>825167168.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trimloc2017-remt:FilasdeRemanentedeTesoreriadimension</th>\n",
       "      <td>287242552.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trimloc2017-anexo5:Filasdimension</th>\n",
       "      <td>972792.19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                         amount\n",
       "dimension                                                      \n",
       "trimloc2017-econ-ingr:Cuentasdimension             982348050.43\n",
       "trimloc2017-econ-gast:Cuentasdimension             825167168.01\n",
       "trimloc2017-remt:FilasdeRemanentedeTesoreriadim... 287242552.08\n",
       "trimloc2017-anexo5:Filasdimension                     972792.19"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dimension = all_payments[all_payments.amount != 0.0] # remove before sum to avoid errors\n",
    "dimension = dimension.groupby('dimension').sum()\n",
    "dimension = dimension.drop('decimals', axis=1)\n",
    "dimension = dimension.sort_values(by='amount', ascending=False)\n",
    "dimension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "d0695dce-2c29-480e-b654-b942727090ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='amount', ylabel='dimension'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=dimension['amount'], y=dimension.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b7707a3e-e792-49fb-994e-5930eadd968e",
   "metadata": {},
   "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>amount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>typed_member_value</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Transferencia2</th>\n",
       "      <td>849129.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transferencia4</th>\n",
       "      <td>95944.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transferencia8</th>\n",
       "      <td>26566.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transferencia3</th>\n",
       "      <td>776.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transferencia7</th>\n",
       "      <td>154.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transferencia5</th>\n",
       "      <td>113.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transferencia6</th>\n",
       "      <td>96.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Transferencia1</th>\n",
       "      <td>10.79</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      amount\n",
       "typed_member_value          \n",
       "Transferencia2     849129.68\n",
       "Transferencia4      95944.02\n",
       "Transferencia8      26566.85\n",
       "Transferencia3        776.21\n",
       "Transferencia7        154.54\n",
       "Transferencia5        113.50\n",
       "Transferencia6         96.60\n",
       "Transferencia1         10.79"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "typed_member = all_payments[all_payments.amount != 0.0] # remove before sum to avoid errors\n",
    "typed_member = typed_member.groupby('typed_member_value').sum()\n",
    "typed_member = typed_member.drop('decimals', axis=1)\n",
    "typed_member = typed_member.sort_values(by='amount', ascending=False)\n",
    "typed_member"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "e4f497cc-8a27-4b5c-a4da-e0ecf22d13f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='amount', ylabel='typed_member_value'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=typed_member['amount'], y=typed_member.index)"
   ]
  }
 ],
 "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": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}