diff --git a/analise_resultados_muriki.ipynb b/analise_resultados_muriki.ipynb
index 2ad62a19ea61027fb525d7fad2bda3433df5397a..da43327c1733044ed1686db7b0b886a7455ab21c 100644
--- a/analise_resultados_muriki.ipynb
+++ b/analise_resultados_muriki.ipynb
@@ -2,9 +2,11 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 2,
"id": "e13d5b4a-95a3-404c-bf01-7b4b48b4d121",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"import numpy as np\n",
@@ -14,10 +16,11 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 8,
"id": "3ee220b5-c632-415e-8a0e-76e85f31b5f1",
"metadata": {
- "scrolled": true
+ "scrolled": true,
+ "tags": []
},
"outputs": [
{
@@ -121,7 +124,7 @@
"16 74158 0.066157 1.129997e-22 "
]
},
- "execution_count": 4,
+ "execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
@@ -150,9 +153,16 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 9,
"id": "ae5ebf5b-a2b3-4d87-af13-62fc187b3ecc",
- "metadata": {},
+ "metadata": {
+ "collapsed": true,
+ "jupyter": {
+ "outputs_hidden": true,
+ "source_hidden": true
+ },
+ "tags": []
+ },
"outputs": [
{
"name": "stdout",
@@ -581,6 +591,286 @@
" print(f'NOVAS COLUNAS: {name}')\n",
" print('\\n')"
]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 119,
+ "id": "81aa6d2b-582d-4982-ae36-35eb7ea3a004",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "2007\n",
+ "NUM_SALAS:\n",
+ " NUM_SALAS\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ " NUM_SALAS\n",
+ "NUM_COMPUTADPR_ALUNO:\n",
+ " NUM_COMPUTADPR_ALUNO\n",
+ "NUM_FUNCIONARIOS:\n",
+ " NUM_FUNCIONARIOS\n",
+ "NUM_COMPUTADOR_ADM:\n",
+ " NUM_COMPUTADOR_ADM\n",
+ "NUM_COMPUTADOR:\n",
+ " NUM_COMPUTADOR\n",
+ "NOVAS COLUNAS: []\n",
+ "2008\n",
+ "NUM_SALAS:\n",
+ " NUM_SALAS\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NUM_FUNCIONARIOS:\n",
+ " NUM_FUNCIONARIOS\n",
+ "NUM_COMPUTADPR_ALUNO:\n",
+ " NUM_COMPUTADPR_ALUNO\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ " NUM_SALAS\n",
+ "NUM_COMPUTADOR:\n",
+ " NUM_COMPUTADOR\n",
+ "NOVAS COLUNAS: []\n",
+ "2009\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ " NUM_SALAS\n",
+ "NUM_SALAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ " NUM_SALAS\n",
+ "NUM_COMPUTADOR_ADM:\n",
+ " NUM_COMPUTADOR_ADM\n",
+ "NUM_FUNCIONARIOS:\n",
+ " NUM_FUNCIONARIOS\n",
+ "NUM_COMPUTADOR:\n",
+ " NUM_COMPUTADOR\n",
+ "NUM_COMPUTADPR_ALUNO:\n",
+ " NUM_COMPUTADPR_ALUNO\n",
+ "NOVAS COLUNAS: []\n",
+ "2010\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ " NUM_SALAS\n",
+ "NUM_SALAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ " NUM_SALAS\n",
+ "NUM_FUNCIONARIOS:\n",
+ " NUM_FUNCIONARIOS\n",
+ "NUM_COMPUTADOR_ADM:\n",
+ " NUM_COMPUTADOR_ADM\n",
+ "NUM_COMPUTADPR_ALUNO:\n",
+ " NUM_COMPUTADPR_ALUNO\n",
+ "NUM_COMPUTADOR:\n",
+ " NUM_COMPUTADOR\n",
+ "NOVAS COLUNAS: []\n",
+ "2011\n",
+ "NUM_SALAS:\n",
+ " NUM_SALAS\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NUM_COMPUTADOR:\n",
+ " NUM_COMPUTADOR\n",
+ "NUM_COMPUTADPR_ALUNO:\n",
+ " NUM_COMPUTADPR_ALUNO\n",
+ "NUM_COMPUTADOR_ADM:\n",
+ " NUM_COMPUTADOR_ADM\n",
+ "NUM_FUNCIONARIOS:\n",
+ " NUM_FUNCIONARIOS\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ " NUM_SALAS\n",
+ "NOVAS COLUNAS: []\n",
+ "2012\n",
+ "NUM_COMPUTADOR_ADM:\n",
+ " NUM_COMPUTADOR_ADM\n",
+ "NUM_COMPUTADPR_ALUNO:\n",
+ " NUM_COMPUTADPR_ALUNO\n",
+ "NUM_FUNCIONARIOS:\n",
+ " NUM_FUNCIONARIOS\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NUM_SALAS:\n",
+ " NUM_SALAS\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NOVAS COLUNAS: []\n",
+ "2013\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ " NUM_SALAS\n",
+ "NUM_SALAS:\n",
+ " NUM_SALAS\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NUM_COMPUTADOR:\n",
+ " NUM_COMPUTADOR\n",
+ "NUM_SOM:\n",
+ " NUM_TV\n",
+ " NUM_SOM\n",
+ "NUM_FUNCIONARIOS:\n",
+ " NUM_FUNCIONARIOS\n",
+ "NUM_COMPUTADPR_ALUNO:\n",
+ " NUM_COMPUTADPR_ALUNO\n",
+ "NUM_DVD:\n",
+ " NUM_DVD\n",
+ "NUM_TV:\n",
+ " NUM_TV\n",
+ " NUM_SOM\n",
+ "NOVAS COLUNAS: ['NUM_DVD' 'NUM_SOM' 'NUM_TV']\n",
+ "2014\n",
+ "NUM_SALAS:\n",
+ " NUM_SALAS\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ " NUM_SALAS\n",
+ "NUM_FUNCIONARIOS:\n",
+ " NUM_FUNCIONARIOS\n",
+ "NUM_COMPUTADOR:\n",
+ " NUM_COMPUTADPR_ALUNO\n",
+ "NUM_SOM:\n",
+ " NUM_TV\n",
+ "NOVAS COLUNAS: ['NUM_TV']\n",
+ "2015\n",
+ "NUM_SOM:\n",
+ " NUM_SOM\n",
+ "NUM_SALAS:\n",
+ " NUM_SALAS\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NUM_DVD:\n",
+ " NUM_DVD\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NUM_FUNCIONARIOS:\n",
+ " NUM_FUNCIONARIOS\n",
+ "NUM_TV:\n",
+ " NUM_TV\n",
+ "NUM_COMPUTADPR_ALUNO:\n",
+ " NUM_COMPUTADPR_ALUNO\n",
+ "NUM_COMPUTADOR:\n",
+ " NUM_COMPUTADOR\n",
+ "NOVAS COLUNAS: ['NUM_DVD' 'NUM_SOM' 'NUM_TV']\n",
+ "2016\n",
+ "NUM_TV:\n",
+ " NUM_TV\n",
+ "NUM_SOM:\n",
+ " NUM_SOM\n",
+ " NUM_COMPUTADOR_ADM\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ " NUM_SALAS\n",
+ "NUM_FUNCIONARIOS:\n",
+ " NUM_FUNCIONARIOS\n",
+ "NUM_SALAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ " NUM_SALAS\n",
+ "NUM_COMPUTADOR:\n",
+ " NUM_COMPUTADOR\n",
+ "NUM_COMPUTADPR_ALUNO:\n",
+ " NUM_COMPUTADPR_ALUNO\n",
+ "NOVAS COLUNAS: ['NUM_SOM' 'NUM_TV']\n",
+ "2017\n",
+ "NUM_FUNCIONARIOS:\n",
+ " NUM_FUNCIONARIOS\n",
+ "NUM_SALAS:\n",
+ " NUM_SALAS\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ " NUM_SALAS\n",
+ "NOVAS COLUNAS: []\n",
+ "2018\n",
+ "NUM_SALAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NOVAS COLUNAS: []\n",
+ "2019\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NUM_SOM:\n",
+ " NUM_SOM\n",
+ "NUM_TV:\n",
+ " NUM_TV\n",
+ "NUM_DVD:\n",
+ " NUM_DVD\n",
+ "NOVAS COLUNAS: ['NUM_DVD' 'NUM_SOM' 'NUM_TV']\n",
+ "2020\n",
+ "NUM_SALAS_UTILIZADAS:\n",
+ " NUM_SALAS_UTILIZADAS\n",
+ "NUM_DVD:\n",
+ " NUM_DVD\n",
+ "NUM_TV:\n",
+ " NUM_TV\n",
+ "NUM_SOM:\n",
+ " NUM_SOM\n",
+ "NOVAS COLUNAS: ['NUM_DVD' 'NUM_SOM' 'NUM_TV']\n"
+ ]
+ }
+ ],
+ "source": [
+ "anos = df.ano_coluna1.unique()\n",
+ "threshold = 0.2\n",
+ "\n",
+ "# Itera sobre todos os anos\n",
+ "for ano in anos:\n",
+ " # Constroi dataframe do ano\n",
+ " ano_df = df[(df.ano_coluna1 == ano) & (df.estatistica_f < threshold)]\n",
+ " \n",
+ " # Estruturas\n",
+ " base_columns = ano_df.coluna1.unique() # Colunas que ja existiam na base\n",
+ " new_columns = ano_df.coluna2.unique() # Colunas do próximo ano\n",
+ " true_new_columns = np.setdiff1d(new_columns, base_columns) # Colunas que nao existiam na base\n",
+ " base_empty_columns = np.setdiff1d(base_columns, new_columns) # Colunas da base que nao receberam dados\n",
+ " all_columns = np.union1d(base_columns, new_columns) # Todas as colunas possiveis\n",
+ " resultados = [] # Resultados dos matches\n",
+ " \n",
+ " # Alterar para um dicionario\n",
+ " prev_col = [] # Colunas da base para match\n",
+ " next_col = [] # Colunas do proximo ano para match\n",
+ " \n",
+ " \n",
+ " # Itera sobre o dataframe\n",
+ " for col in base_columns:\n",
+ " top3 = ano_df[ano_df.coluna1 == col]\n",
+ " resultados.append(top3.iloc[:3,:].values)\n",
+ " \n",
+ " # Encontra colunas prev que deram match\n",
+ " all_match_columns = []\n",
+ " not_match_columns = [] \n",
+ "\n",
+ " for res in resultados:\n",
+ " for i in res:\n",
+ " next_col = np.union1d(next_col, i[2])\n",
+ " prev_col = np.union1d(prev_col, i[0])\n",
+ " \n",
+ " all_match_columns = np.union1d(next_col, prev_col)\n",
+ " not_match_columns = np.setdiff1d(all_columns, all_match_columns) \n",
+ " found_new_columns = np.setdiff1d(new_columns, next_columns)\n",
+ " \n",
+ " # Calcula acurácia\n",
+ " acuracia = 0\n",
+ " acertos = 0\n",
+ " for res in resultados:\n",
+ " for i in res:\n",
+ " if i[0] == i[2]:\n",
+ " acertos += 1\n",
+ " break\n",
+ " acuracia = acertos / len(base_columns) \n",
+ " \n",
+ " # Imprime resultados\n",
+ " print(ano)\n",
+ " for res in resultados:\n",
+ " print(f'{res[0][0]}:')\n",
+ " for i in res:\n",
+ " print(f' {i[2]}')\n",
+ " print(f'NOVAS COLUNAS: {found_new_columns}')\n",
+ " # print(f'{acuracia}\\n')\n",
+ " \n",
+ " "
+ ]
}
],
"metadata": {
@@ -599,7 +889,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.12.3"
+ "version": "3.11.4"
}
},
"nbformat": 4,