Esercizio4.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "01948bc9-076b-475f-9b77-88054168d9b3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib as plt\n",
    "pd.set_option(\"display.max_columns\", None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e8ec2a17-cceb-48ab-b20c-7e30092277b8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "df = pd.read_excel(\"./Datasets4/CRM data.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "18dfd308-bd8a-4333-852e-923dcdb96e29",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\tnon sono presenti duplicati\n"
     ]
    }
   ],
   "source": [
    "if len(df[\"client_code\"].unique()) < len(df.index):\n",
    "    df.drop_duplicates(\"client_code\", keep=\"first\")\n",
    "    print(\"\\tnuovo dataset:\", len(df))\n",
    "else:\n",
    "    print(\"\\tnon sono presenti duplicati\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "eebdf3e4-065f-4dcf-845c-fda6d33811e9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>client_code</th>\n",
       "      <th>installment</th>\n",
       "      <th>first_amount_spent</th>\n",
       "      <th>number_of_products</th>\n",
       "      <th>Y</th>\n",
       "      <th>center</th>\n",
       "      <th>age51_89</th>\n",
       "      <th>age36_50</th>\n",
       "      <th>dim_big</th>\n",
       "      <th>dim_medium</th>\n",
       "      <th>age15_35</th>\n",
       "      <th>sex</th>\n",
       "      <th>north</th>\n",
       "      <th>south_and_islands</th>\n",
       "      <th>dim_small</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10500561</td>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10502394</td>\n",
       "      <td>1</td>\n",
       "      <td>1484000</td>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
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       "      <td>2459000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1052312E</td>\n",
       "      <td>0</td>\n",
       "      <td>3389000</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10579494</td>\n",
       "      <td>1</td>\n",
       "      <td>3823000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  client_code  installment  first_amount_spent  number_of_products  Y  center  \\\n",
       "0    10500561            0              520000                   0  0       0   \n",
       "1    10502394            1             1484000                   2  0       0   \n",
       "2    10521224            0             2459000                   1  0       0   \n",
       "3    1052312E            0             3389000                   0  0       1   \n",
       "4    10579494            1             3823000                   2  0       0   \n",
       "\n",
       "   age51_89  age36_50  dim_big  dim_medium  age15_35  sex  north  \\\n",
       "0         0         0        0           1         1    0    0.0   \n",
       "1         0         1        0           0         0    1    0.0   \n",
       "2         1         0        0           1         0    1    0.0   \n",
       "3         0         1        1           0         0    1    0.0   \n",
       "4         0         0        0           0         1    1    0.0   \n",
       "\n",
       "   south_and_islands  dim_small  \n",
       "0                1.0        0.0  \n",
       "1                1.0        1.0  \n",
       "2                1.0        0.0  \n",
       "3                0.0        0.0  \n",
       "4                1.0        1.0  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6bb391f7-17d3-441d-b072-6efd3bc95288",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age51_89</th>\n",
       "      <th>age36_50</th>\n",
       "      <th>age15_35</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2465</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2466</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2467</th>\n",
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       "      <th>2468</th>\n",
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       "      <th>2469</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2470 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age51_89  age36_50  age15_35\n",
       "0            0         0         1\n",
       "1            0         1         0\n",
       "2            1         0         0\n",
       "3            0         1         0\n",
       "4            0         0         1\n",
       "...        ...       ...       ...\n",
       "2465         1         0         0\n",
       "2466         1         0         0\n",
       "2467         1         0         0\n",
       "2468         0         1         0\n",
       "2469         1         0         0\n",
       "\n",
       "[2470 rows x 3 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[:,[6,7,10]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "e91d910b-a95c-4d10-b7a1-955a1a686347",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def drop_inconsistent_rows(dataframe,column1,column2,column3):\n",
    "    dataframe.drop(dataframe[dataframe.iloc[:,[column1,column2,column3]].sum(axis=1) != 1].index, inplace=True)\n",
    "    \n",
    "    print(\"rimozione inconsistenze, numero righe: \", len(dataframe))\n",
    "    \n",
    "    return df\n",
    "\n",
    "    #questa istruzione sopra siignifica, droppo tutte le tuple che risultano avere dei valori inconsistenti, ad esempio \n",
    "    #tramite la funzione iloc vado a selezionare [tutte le righe, [colonne che mi interessano]] in quanto i valori di queste colonne\n",
    "    #si escludono tra loro, solo una tra le colonne 6 7 e 10 possono assumere un valore 1 per una stessa tupla.\n",
    "    #eseguiamo questo processo per tutte le colonne che tra loro si escludono.\n",
    "\n",
    "    \n",
    "    \n",
    "def remove_unrelated_features(dataframe,treshold):\n",
    "    correlation_matrix = dataframe.corr()   #calcoliamo la matrice di correlazione\n",
    "    #una matrice di correlazione serve per trovare la correlazione tra gli elementi delle colonne di un dataframe \n",
    "    \n",
    "    corr_target = abs(correlation_matrix[\"Y\"])   #andiamo a farne il modulo\n",
    "    #l'operazione abs va a svolgere il modulo di un determinato dato che vi è stato inserito\n",
    "    #in questo caso radice quadrata della somma dei quadrati della matrice di correlazione nella colonna Y.\n",
    "    \n",
    "    relevant_features = corr_target[corr_target>threshold] #correlazione del target maggiore di una soglia (threshold = soglia)\n",
    "    print(\"\\nFeatures correl date maggiore della soglia:\")\n",
    "    relevant_features\n",
    "    \n",
    "    relevant_features_col = relevant_features.iloc[:,0]\n",
    "    new_df = dataframe.loc[:,relevant_features_col]\n",
    "    return new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "50b15b3f-1f6e-459b-8e10-3eb835c7ad8d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "verifica inconsistenze età:\n",
      "rimozione inconsistenze, numero righe:  2452\n",
      "verifica inconsistenze dim:\n",
      "rimozione inconsistenze, numero righe:  2452\n",
      "verifica inconsistenze regione:\n",
      "rimozione inconsistenze, numero righe:  2452\n"
     ]
    }
   ],
   "source": [
    "print(\"verifica inconsistenze età:\")\n",
    "df = drop_inconsistent_rows(df,6,7,10)\n",
    "\n",
    "print(\"verifica inconsistenze dim:\")\n",
    "df = drop_inconsistent_rows(df,8,9,14)\n",
    "\n",
    "print(\"verifica inconsistenze regione:\")\n",
    "df = drop_inconsistent_rows(df,5,12,13)\n",
    "\n",
    "#faccio la verifica delle inconsistenze per queste colonne che ho messo tra parentesi (i numeri interi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "79f885f3-4e10-4a1b-8ef3-a74461b8f259",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "client_code           0\n",
       "installment           0\n",
       "first_amount_spent    0\n",
       "number_of_products    0\n",
       "Y                     0\n",
       "center                0\n",
       "age51_89              0\n",
       "age36_50              0\n",
       "dim_big               0\n",
       "dim_medium            0\n",
       "age15_35              0\n",
       "sex                   0\n",
       "north                 1\n",
       "south_and_islands     1\n",
       "dim_small             1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum() #il metodo isna va a verificare dove sono i valori null all'interno del mio dataframe.\n",
    "#con il metodo sum li vado a sommare per ogni singola colonna che sto analizzando"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "2a21d8f9-df82-469f-922e-769e312a5334",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "boxplot = sns.boxplot(df[\"first_amount_spent\"]) #quì vado a creare un boxplot con seaborn per andare a vedere l'andamento\n",
    "#della colonna first amount spent del mio dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "5e806cdb-1c52-4e39-b232-b36bdf61d6ae",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Verifica valori variabile target:\n",
      "Conteggio valori variabile target\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    1446\n",
       "1    1006\n",
       "Name: Y, dtype: int64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Verifica valori variabile target:\")\n",
    "df[\"Y\"].unique() #con questa istruzione verifico quali sono i valori unici presenti nel mio dataframe sotto la colonna Y\n",
    "\n",
    "\n",
    "print(\"Conteggio valori variabile target\")\n",
    "df[\"Y\"].value_counts() #con questa unita alla funzione precedente, non solo vedo quali sono i valori unici del dataframe\n",
    "#in più vado a vedere quanti elementi sono 1 e quanti elementi sono 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "0c5a7548-679d-4eb5-af94-caac28dfb43a",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "df.to_excel(\"DataFrameRipu0litoEsercizio4.xlsx\") #con questa istruzione vado ad esportare i miei dati\n",
    "#per far si che io abbia raggiunto una sorta di checkpoint grazie al quale salvo quanto fatto fin ora."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "587508b2-6a4e-4c56-a3a9-2bec144cf385",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\renat\\AppData\\Local\\Temp\\ipykernel_12632\\1932409509.py:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  matrice_correlazione = df.corr() #vado a rigenerare la matrice di correlazione\n"
     ]
    }
   ],
   "source": [
    "matrice_correlazione = df.corr() #vado a rigenerare la matrice di correlazione\n",
    "#che posso successivamente rappresentare graficamente tramite una heatmap di seaborn."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "5544aa5b-771c-4600-84f3-062815b6e66d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#vado a generare una \"mappa di calore\" per capire l'andamento dei miei dati all'interno del DF\n",
    "\n",
    "\n",
    "plot = sns.heatmap(matrice_correlazione, vmax = 1, square = False,annot = True, fmt=\".1f\",cmap=\"GnBu\", robust=True)\n",
    "#genero una heatmap di seaborn immetteno alcuni parametri:\n",
    "#il primo indica dove sono allocati i dati sul quale il mio grafico si deve basare\n",
    "#il secondo (opzionale) indica il numero massimo che i miei valori assumono all'interno del grafico (se lo modifichi cambia la barra a destra e i colori all'interno del grafico)\n",
    "#il terzo (opzionale) se ha un valore true setta le Axes aspect to equal, così che le celle abbiano una forma di un quadrato\n",
    "#il quarto (opzionale) se ha un valore true scrive il valore del dato in ogni cella, se provi a toglierlo infatti eliminerà i valori e resteranno solo i colori\n",
    "#il quinto (opzionale) indica il numero di elementi dopo la virgola che visualizzi all'interno della heatmap\n",
    "#il sesto (opzionale) setta i colori della heatmap ad un particolare tono di colori\n",
    "#il settimo (opzionale) se ha un valore true e vmin/vmax sono assenti, la colormap range è calcolata in quantili e non in valori extreme (?)"
   ]
  }
 ],
 "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": "3.11.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}