{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Associazione tra Variabili\n", "\n", "Utilizzeremo come esempio nuovamente il dataset Titanic:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
PassengerId
103Braund, Mr. Owen Harrismale22.010A/5 211717.2500NaNS
211Cumings, Mrs. John Bradley (Florence Briggs Th...female38.010PC 1759971.2833C85C
313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250NaNS
411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000C123S
503Allen, Mr. William Henrymale35.0003734508.0500NaNS
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" ], "text/plain": [ " Survived Pclass \\\n", "PassengerId \n", "1 0 3 \n", "2 1 1 \n", "3 1 3 \n", "4 1 1 \n", "5 0 3 \n", "\n", " Name Sex Age \\\n", "PassengerId \n", "1 Braund, Mr. Owen Harris male 22.0 \n", "2 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 \n", "3 Heikkinen, Miss. Laina female 26.0 \n", "4 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 \n", "5 Allen, Mr. William Henry male 35.0 \n", "\n", " SibSp Parch Ticket Fare Cabin Embarked \n", "PassengerId \n", "1 1 0 A/5 21171 7.2500 NaN S \n", "2 1 0 PC 17599 71.2833 C85 C \n", "3 0 0 STON/O2. 3101282 7.9250 NaN S \n", "4 1 0 113803 53.1000 C123 S \n", "5 0 0 373450 8.0500 NaN S " ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "titanic = pd.read_csv('https://raw.githubusercontent.com/agconti/kaggle-titanic/master/data/train.csv',\n", " index_col='PassengerId')\n", "titanic.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Dato il dataset sopra, potremmo chiederci se delle variabili influenzano i valori di altre. Ad esempio, trovarsi in prima, seconda o terza classe (variabile `Pclass`) influenza in qualche modo la probabilità di sopravvivere (variabile `Survived`)?, o ancora, l'età (variabile `Age`) o il prezzo pagato (`Fare`) influenza in qualche modo la probabilità di salvarsi (`Survived`)?\n", "\n", "In questa lezione, vedremo diversi modi per riassumere le distribuzioni di due variabili e verificare eventuali associazioni (o correlazioni) tra le variabili." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Riassumere la Distribuzione di due Variabili Discrete\n", "\n", "Se entrambe le variabili che stiamo studiando sono discrete, possiamo enumerare tutte le possibili combinazioni di valori e riassumerle in una tabella di contingenza che indica i valori di una variabile sulle righe e quelli dell'altra variabile sulle colonne. Ogni cella indicherà il numero di volte in cui osserviamo una data coppia di valori.\n", "\n", "### Tabelle di Contingenza\n", "Costruiamo la tabella di contingenza per le variabili `Sex` e `Pclass`. Per farlo utilizzeremo la funzione `crosstab` di Pandas:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Pclass123
Sex
female9476144
male122108347
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" ], "text/plain": [ "Pclass 1 2 3\n", "Sex \n", "female 94 76 144\n", "male 122 108 347" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.crosstab(titanic['Sex'], titanic['Pclass'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "La tabella sopra indica ad esempio che $94$ passeggeri in classe $1$ erano di sesso femminile. Specificando `margins=True` possiamo ottenere le somme per righe e colonne, che indicheranno le frequenze assolute di ciascuna variabile:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Pclass123All
Sex
female9476144314
male122108347577
All216184491891
\n", "
" ], "text/plain": [ "Pclass 1 2 3 All\n", "Sex \n", "female 94 76 144 314\n", "male 122 108 347 577\n", "All 216 184 491 891" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.crosstab(titanic['Sex'], titanic['Pclass'],margins=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Distribuzioni di Frequenze Relative Congiunte\n", "\n", "Possiamo ottenere la tabella delle frequenze relative congiunte passando `normalize=True` alla funzione crosstab:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Pclass123
Sex
female0.1054990.0852970.161616
male0.1369250.1212120.389450
\n", "
" ], "text/plain": [ "Pclass 1 2 3\n", "Sex \n", "female 0.105499 0.085297 0.161616\n", "male 0.136925 0.121212 0.389450" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.crosstab(titanic['Sex'], titanic['Pclass'], normalize=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Distribuzioni di Frequenze Relative Marginali\n", "\n", "Otteniamo i marginali passando `margins=True`:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Pclass123All
Sex
female0.1054990.0852970.1616160.352413
male0.1369250.1212120.3894500.647587
All0.2424240.2065100.5510661.000000
\n", "
" ], "text/plain": [ "Pclass 1 2 3 All\n", "Sex \n", "female 0.105499 0.085297 0.161616 0.352413\n", "male 0.136925 0.121212 0.389450 0.647587\n", "All 0.242424 0.206510 0.551066 1.000000" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.crosstab(titanic['Sex'], titanic['Pclass'], normalize=True, margins=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Va notato che le frequenze relative marginali ottenute, sono identiche alle frequenze relative dei campioni univariati:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "male 0.647587\n", "female 0.352413\n", "Name: Sex, dtype: float64" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "titanic['Sex'].value_counts(normalize=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Che sono esattamente i valori nell'ultima colonna della tabella precedente. Analogamente:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3 0.551066\n", "1 0.242424\n", "2 0.206510\n", "Name: Pclass, dtype: float64" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "titanic['Pclass'].value_counts(normalize=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Che sono i valori nell'ultima riga della tabella precedente." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Distribuzioni di Frequenze Relative Condizionali\n", "\n", "È possibile ottenere le frequenze condizionate relative normalizzando per la riga opportuna. Se voglio condizionare rispetto alla variabile X, normalizzerò per righe:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Pclass123
Sex
female0.2993630.2420380.458599
male0.2114380.1871750.601386
\n", "
" ], "text/plain": [ "Pclass 1 2 3\n", "Sex \n", "female 0.299363 0.242038 0.458599\n", "male 0.211438 0.187175 0.601386" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#normalize=0 indica di condizionare rispetto alla prima variabile\n", "pd.crosstab(titanic['Sex'], titanic['Pclass'], normalize=0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Dalla tabella sopra, ad esempio, posso evincere:\n", "\n", "* $f(Pclass=1|Sex=female) = 0.290363$\n", "* $f(Pclass=2|Sex=female) = 0.242038$\n", "* $f(Pclass=3|Sex=female) = 0.458599$\n", "\n", "Queste sono le frequenze delle donne nelle tre classi. Analogamente, la seconda riga rappresenta le frequenze condizionate rispetto a `Sex=male`. Dalla tabella, notiamo che la distribuzione dei passeggeri cambia nelle tre classi. In particolare, tra gli uomini, la terza classe è più frequente che tra le donne. \n", "\n", "Possiamo ottenere la prospettiva complementare condizionando su classe invece:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Pclass123
Sex
female0.4351850.4130430.293279
male0.5648150.5869570.706721
\n", "
" ], "text/plain": [ "Pclass 1 2 3\n", "Sex \n", "female 0.435185 0.413043 0.293279\n", "male 0.564815 0.586957 0.706721" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#normalize=1 indica di condizionare rispetto alla prima variabile\n", "pd.crosstab(titanic['Sex'], titanic['Pclass'], normalize=1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In questo caso, ogni colonna sarà una distribuzione di probabilità. Ad esempio:\n", "\n", "* $P(Sex=female|Pclass=1) = 0.435185$\n", "* $P(Sex=male|Pclass=1) = 0.564815$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notiamo che le proporzione tra uomini e donne cambiano nelle tre classi e in particolare nella terza classe ci sono molti più uomini che donne." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Rappresentazioni Grafiche\n", "Possiamo facilmente ottenere rappresentazioni grafiche delle relazioni tra due variabili mediante grafici a barre, direttamente dalle tabelle di contingenza.\n", "\n", "Possiamo confrontare le frequenze assolute di passeggeri e sessi nelle tre classi come segue:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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YXImSpN21X38dktwMnASMT9IFXAGclKSDnimXJ4GPAlTVqiTLgEeBLcCFVbV1WCrXkDt66dEjer1HFj4yoteTRpN+w72qzumj+YZd9F8MLB5MUZKkwfEOVUlqIMNdkhrIcJekBjLcJamBDHdJaiDDXZIayHCXpAYy3CWpgQx3SWogw12SGshwl6QG6vfZMpL2DZMvvW3ErvXk1X8xYtfSnnHkLkkNZLhLUgMZ7pLUQIa7JDWQ4S5JDWS4S1IDGe6S1ECGuyQ1kDcxSdp9V75mZK835fUje70G6HfknuTGJM8mWdmr7dAkdyV5vPV6SK99lyVZk2R1knnDVbgkaecGMi1zE3D6dm2XAvdU1VTgntY2SaYDC4AZrWO+lGTMkFUrSRqQfsO9qn4CPL9d8xnA0tb7pcD7erXfUlWbquoJYA0wZ2hKlSQN1J7+QvW1VbUOoPV6eKv9CGBtr35drTZJ0gga6tUy6aOt+uyYXJBkeZLl3d3dQ1yGJI1uexruzySZCNB6fbbV3gUc2avfJODpvk5QVUuqqrOqOidMmLCHZUiS+rKn4X4rsLD1fiHwvV7tC5Lsn2QKMBV4YHAlSpJ2V7/r3JPcDJwEjE/SBVwBXA0sS7II+BVwFkBVrUqyDHgU2AJcWFVbh6n2ETeSX4YAfiGCpD3Xb7hX1Tk72XXqTvovBhYPpihJ0uD4+AFJaiDDXZIayHCXpAYy3CWpgQx3SWogw12SGshwl6QGMtwlqYEMd0lqIL9mb2/mV5lJ2kOO3CWpgQx3SWogw12SGshwl6QGMtwlqYEMd0lqIMNdkhrIcJekBjLcJamBDHdJaiDDXZIaaFDPlknyJLAR2ApsqarOJIcC3wImA08CZ1fVvwyuTEnS7hiKkfvJVdVRVZ2t7UuBe6pqKnBPa1uSNIKGY1rmDGBp6/1S4H3DcA1J0i4MNtwL+F9JHkxyQavttVW1DqD1enhfBya5IMnyJMu7u7sHWYYkqbfBPs/9hKp6OsnhwF1Jfj7QA6tqCbAEoLOzswZZhySpl0GN3Kvq6dbrs8DfA3OAZ5JMBGi9PjvYIiVJu2ePwz3JHyc5aNt74M+BlcCtwMJWt4XA9wZbpCRp9wxmWua1wN8n2Xae/15VdyT5J2BZkkXAr4CzBl+mJGl37HG4V9Uvgdl9tK8HTh1MUZKkwfEOVUlqIMNdkhrIcJekBjLcJamBDHdJaiDDXZIayHCXpAYy3CWpgQx3SWogw12SGshwl6QGMtwlqYEMd0lqIMNdkhrIcJekBjLcJamBDHdJaiDDXZIayHCXpAYy3CWpgQx3SWqgYQv3JKcnWZ1kTZJLh+s6kqQdDUu4JxkD/C3wLmA6cE6S6cNxLUnSjoZr5D4HWFNVv6yq3wG3AGcM07UkSdvZb5jOewSwttd2FzC3d4ckFwAXtDZfSLJ6mGrZZ2XPDx0PPLf7h63c8yvugZw3iE+otvLP5l7jDTvbMVzh3td/mXrFRtUSYMkwXX9US7K8qjrbXYe0Pf9sjpzhmpbpAo7stT0JeHqYriVJ2s5whfs/AVOTTEnyR8AC4NZhupYkaTvDMi1TVVuSXATcCYwBbqyqVcNxLfXJ6S7trfyzOUJSVf33kiTtU7xDVZIayHCXpAYy3CWpgQx3ScMuyQFJ3tzuOkYTw70BkrwpyT1JVra2ZyW5vN11SQBJ/hJYAdzR2u5I4tLoYWa4N8P1wGXAZoCqepieewukvcGV9DxvagNAVa0AJretmlHCcG+GV1fVA9u1bWlLJdKOtlTVr9tdxGgzXM+W0ch6LskbaT2/J8kHgHXtLUl62cokHwTGJJkKXAz8Q5trajxvYmqAJEfRc+ffvwb+BXgC+KuqerKddUkASV4NfBr4c3oeKngn8NmqeqmthTWc4d4gSf4YeFVVbWx3LZLay3DfhyW5ZFf7q+pzI1WLtL0k/5PtHvXdW1W9dwTLGXWcc9+3HdTuAqRduKbdBYxmjtwlqYEcuTdAknHAImAGMG5be1Wd37aipJbWCpn/CEznlX8+j2pbUaOA69yb4evA64B5wI/p+eYrf6mqvcV/A75Mz70XJwNfo+fPrIaR0zINkOShqjomycNVNSvJWODOqjql3bVJSR6squOSPFJVR7fa/ndVvb3dtTWZ0zLNsLn1uiHJTOD/4e3d2nu8lORVwOOtb2h7Cji8zTU1ntMyzbAkySHAv6Pnu2ofBf5Te0uSXvYJ4NX03Jl6HPBXwIfbWdBo4LSMpGGVpJOeO1TfAIxtNVdVzWpfVc1nuDdAkoPpGQlNptdUW1Vd3KaSpJclWQ18EngE+P229qr657YVNQo4594MtwP/yHZ/eaS9RHdV+fz2EebIvQGS/Kyqjm13HVJfkpwKnAPcA2za1l5V32lbUaOA4d4ASf4aeAH4Pq/8y/N824qSWpJ8A3gLsIo//J9leZPd8HJaphl+B/xnen5pte1f6wK8A1B7g9nb1rdr5BjuzXAJ8K+q6rl2FyL14R+TTK+qR9tdyGhiuDfDKuC37S5C2okTgYVJnqBn2jC4FHLYGe7NsBVYkeSHvHLO3aWQ2huc3u4CRiPDvRm+2/qR9jquZ28PV8s0RJIDgNdX1ep21yKp/Xy2TAMk+UtgBXBHa7sjiTeNSKOY4d4MVwJzgA0AVbUCmNK+ciS1m+HeDFuq6tfbtTnfJo1i/kK1GVYm+SAwpvWVZhcD/9DmmiS1kSP3fViSbV9V9gt6vj91E3Az8Bt6nqEtaZRytcw+LMmjwLvo+YKOk7ff77NlpNHLaZl923X0rJA5Cljeqz34bBlpVHPk3gBJvlxV/7bddUjaexjuktRA/kJVkhrIcJekBjLcNeol+XSSVUkeTrIiydx21yQNlqtlNKolOR54D3BsVW1KMh74ozaXJQ2aI3eNdhOB56pqE0BVPVdVTyc5LsmPkzyY5M4kE5O8JsnqJG8GSHJzko+0tXppJ1wto1EtyYHAT4FXA3cD36Ln0Q0/Bs6oqu4k/waYV1XnJzkNuAr4InBeVflFFNorOS2jUa2qXkhyHPB2eu7y/RbwH4CZwF1JAMYA61r970pyFvC3wOy2FC0NgCN3qZckHwAuBMZV1fF97H8VPaP6KcC7q+rhES5RGhDn3DWqJXlz60ma23QAjwETWr9sJcnYJDNa+/+6tf8c4MYkY0eyXmmgHLlrVGtNyfxX4GBgC7AGuACYBPwX4DX0TF9+gZ4R+/eAOVW1McnngI1VdcXIVy7tmuEuSQ3ktIwkNZDhLkkNZLhLUgMZ7pLUQIa7JDWQ4S5JDWS4S1IDGe6S1ED/H8o+Z88GVCaNAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pd.crosstab(titanic['Sex'], titanic['Pclass']).plot.bar()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Da qui notiamo che molti passeggeri sono uomini e in terza classe. In questi casi, può essere a volte utile uno stacked plot:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pd.crosstab(titanic['Sex'], titanic['Pclass']).plot.bar(stacked=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "È spesso utile visualizzare le distribuzioni condizionate. Ad esempio, il grafico che segue ci permette di confrontare le distribuzioni di passeggeri nelle tre classi, suddividendo in due gruppi sulla base del sesso:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pd.crosstab(titanic['Sex'], titanic['Pclass'], normalize=0).plot.bar()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Possiamo ottenere il grafico delle frequenze condizionate rispetto alle classi per una vista complementare. In questo caso, per avere un grafico significativo, dobbiamo trasporre la tabella di contingenza con un `.T`:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#normalize=1 indica di condizionare rispetto alla prima variabile\n", "pd.crosstab(titanic['Sex'], titanic['Pclass'], normalize=1).T.plot.bar()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Misure di Associazione tra due Variabili Discrete" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Statistica $\\mathcal{X}^2$ di Pearson\n", "Possiamo calcolare la statistica $\\mathcal{X}^2$ di Pearson come segue:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Chi2ContingencyResult(statistic=102.88898875696056, pvalue=4.549251711298793e-23, dof=2, expected_freq=array([[133.09090909, 82.90909091],\n", " [113.37373737, 70.62626263],\n", " [302.53535354, 188.46464646]]))" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from scipy.stats import chi2_contingency\n", "contingency = pd.crosstab(titanic['Pclass'], titanic['Survived'])\n", "chi2_contingency(contingency)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "La funzione `chi2_contingency` restituisce:\n", "* Il valore della statistica;\n", "* il p-value (lo vedremo meglio in seguito);\n", "* i gradi di libertà della distirbuzione $\\chi^2$ (vedremo meglio anche questo in seguito);\n", "* Le occorrenze attese in caso di indipendenza.\n", "\n", "Possiamo confrontare queste occorrenze con quelle reali:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Survived01
Pclass
180136
29787
3372119
\n", "
" ], "text/plain": [ "Survived 0 1\n", "Pclass \n", "1 80 136\n", "2 97 87\n", "3 372 119" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "contingency" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Statistica $V$ di Cramer\n", "È possibile calcolare la statistica V di Cramer come segue:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.33981738800531175" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from scipy.stats.contingency import association\n", "\n", "association(pd.crosstab(titanic['Pclass'], titanic['Survived']))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Rischio Relativo e Odds Ratio\n", "\n", "Consideriamo questa matrice di contingenza:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
ExposedNon Exposed
Diseased206
Healthy380594
\n", "
" ], "text/plain": [ " Exposed Non Exposed\n", "Diseased 20 6\n", "Healthy 380 594" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "contingency = pd.DataFrame({\n", " \"Exposed\": [20, 380],\n", " \"Non Exposed\": [6,594]\n", "}, index=[\"Diseased\", \"Healthy\"])\n", "contingency" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Possiamo calcolare il rischio relativo come segue:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "RelativeRiskResult(relative_risk=5.0, exposed_cases=20, exposed_total=400, control_cases=6, control_total=600)" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from scipy.stats.contingency import relative_risk\n", "relative_risk(contingency['Exposed']['Diseased'],contingency['Exposed'].sum(),contingency['Non Exposed']['Diseased'], contingency['Non Exposed'].sum())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "La funzione richiede che vengano passati i vari valori necessari piuttoto che la matrice di contingenza per evitare ambiguità." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "L'odds ratio si calcola così:" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "OddsRatioResult(statistic=5.202179487843056)" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from scipy.stats.contingency import odds_ratio\n", "odds_ratio(contingency)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Associazioni tra Variabili Continue" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Per studiare le associazioni tra variabili continue, considereremo il dataset delle iris di fisher come dataset di esempio. Carichiamo il dataset mediante la libreria `seaborn` e visualizziamone informazioni e prime righe:" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 150 entries, 0 to 149\n", "Data columns (total 5 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 sepal_length 150 non-null float64\n", " 1 sepal_width 150 non-null float64\n", " 2 petal_length 150 non-null float64\n", " 3 petal_width 150 non-null float64\n", " 4 species 150 non-null object \n", "dtypes: float64(4), object(1)\n", "memory usage: 6.0+ KB\n" ] }, { "data": { "text/html": [ "
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sepal_lengthsepal_widthpetal_lengthpetal_widthspecies
05.13.51.40.2setosa
14.93.01.40.2setosa
24.73.21.30.2setosa
34.63.11.50.2setosa
45.03.61.40.2setosa
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" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width species\n", "0 5.1 3.5 1.4 0.2 setosa\n", "1 4.9 3.0 1.4 0.2 setosa\n", "2 4.7 3.2 1.3 0.2 setosa\n", "3 4.6 3.1 1.5 0.2 setosa\n", "4 5.0 3.6 1.4 0.2 setosa" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import seaborn as sns\n", "iris = sns.load_dataset('iris')\n", "iris.info()\n", "iris.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Il dataset contiene $150$ osservazioni riportanti le misure di 4 grandezze (lunghezza e larghezza di sepalo e petalo) per $150$ esemplari di iris appartenenti a tre specie diverse: Iris setosa, Iris virginica e Iris versicolor. \n", "\n", "Tutte le variabili sono numeriche, eccetto `species` che è categorica. Visualizziamone i valori univoci:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['setosa', 'versicolor', 'virginica'], dtype=object)" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "iris['species'].unique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Esploriamo i dati calcolando i principali indicatori statistici mediante `describe`:" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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sepal_lengthsepal_widthpetal_lengthpetal_width
count150.000000150.000000150.000000150.000000
mean5.8433333.0573333.7580001.199333
std0.8280660.4358661.7652980.762238
min4.3000002.0000001.0000000.100000
25%5.1000002.8000001.6000000.300000
50%5.8000003.0000004.3500001.300000
75%6.4000003.3000005.1000001.800000
max7.9000004.4000006.9000002.500000
\n", "
" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width\n", "count 150.000000 150.000000 150.000000 150.000000\n", "mean 5.843333 3.057333 3.758000 1.199333\n", "std 0.828066 0.435866 1.765298 0.762238\n", "min 4.300000 2.000000 1.000000 0.100000\n", "25% 5.100000 2.800000 1.600000 0.300000\n", "50% 5.800000 3.000000 4.350000 1.300000\n", "75% 6.400000 3.300000 5.100000 1.800000\n", "max 7.900000 4.400000 6.900000 2.500000" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "iris.describe()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> **🙋‍♂️ Domanda 1**\n", ">\n", "> La variabile `species` non è stata inclusa nel sommario. Perché?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Confrontiamo le diverse variabili mediante boxplot:" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": 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v11A7Hst2rX8+L3L06uPaUtBGxEaaIfuxUsptSy1TSpkEJgGGhoZKXb+r6Pcwu8/g4CB9fX0MDw+f6t/s7CyDg4P2cq0cnGnLY9mW9a9N96Xn9PDj2spexwFMAXOllN/OL0laWxMTE4yOjjI7O8uJEyeYnZ1ldHSUiYmJTpcmqQe08on2SuCXgS9HxEPVeb9ZSvl0WlXSGlrY4Wn37t3Mzc0xODjIvn373BFKUlu0stfxISDaUIuUZufOnezcudOpf0lt55GhJElKZNBKkpTIX++RpB532d67OHrsePo4q/1py1adv2kjD19/TeoYq2HQSlKPO3rsePpvLrdj/4jsIF8tp44lSUpk0EqSlMiglSQpkUErSVIig1aSpEQGrSRJifx6j6Q10bavVhzM/y6mtJYMWkkvWvZ3MBcMjM+0bSxprTh1LElSIoNWkqREBq0kSYkMWkmSEhm0kiQlMmglSUpk0EqSlMiglSQpkUErSVIijwwlST1u6+A4lx4Yzx/oQO7Nbx0EWH9HDjNoJanHPTu3P/3Qlo1Gg+Hh4dQx2na87RVy6liSpEQGrSRJiQxaSZISGbSSJCUyaCVJSmTQSpKUaNmgjYibIuJbEfFoOwqSJKlOWvlEezNwbXIdkiTV0rJBW0q5B/jLNtQiSVLtuI1WkqREa3YIxogYA8YA+vv7aTQaa3XT68r8/Hxt71svsH/rx66Dz63qeis9zN7N125e1Ti9Jnu9aNe6tx7X7zUL2lLKJDAJMDQ0VLKPadkp7Thep/LYv/XjyPDKr2P/khycSX9c29K7NtyP1XDqWJKkRK18vWca+ALw6oh4JiJG88uSJKkelp06LqXsbEchkiTVkVPHkiQlMmglSUpk0EqSlMiglSQpkUErSVIig1aSpEQGrSRJiQxaSZISGbSSJCUyaCVJSmTQSpKUyKCVJCmRQStJUiKDVpKkRAatJEmJDFpJkhIZtJIkJTJoJUlKZNBKkpTIoJUkKZFBK0lSog2dLkCS1HkD4zP5gxzMHeP8TRtTb3+1DFpJ6nFH9u9IH2NgfKYt46xHTh1LkpTIoJUkKZFBK0lSIoNWkqREBq0kSYkMWkmSErX09Z6IuBb4ENAHfKSUsj+1KknSuraa792u5jp1+ErQskEbEX3AfwZ+DngGuC8iPlVKeTy7OEnS+rTSAGw0GgwPD+cUs861MnV8OfDVUsqTpZQfALcAv5RbliRJ9dBK0F4MPL3o72eq8yRJ0jJa2UYbS5xXXrBQxBgwBtDf30+j0Xhxla1T8/Pztb1vvcD+dTf71716uXetBO0zwE8u+vvlwDdOX6iUMglMAgwNDZW6zsX38naGOrB/3c3+da9e7l0rU8f3Aa+KiFdGxEuBtwGfyi1LkqR6WPYTbSnlRET8GvAZml/vuamU8lh6ZZIk1UBL36MtpXwa+HRyLZIk1Y5HhpIkKZFBK0lSIoNWkqREBq0kSYkMWkmSEhm0kiQlilJecDTFF3+jEd8GnlrzG14fLgS+0+kitGr2r7vZv+5V99797VLKRUtdkBK0dRYRh0spQ52uQ6tj/7qb/etevdw7p44lSUpk0EqSlMigXbnJThegF8X+dTf71716tnduo5UkKZGfaCVJSmTQSpKUyKA9TUQMR8SdZ7l8V0R8OGHcXRHxE4v+PhIRF671OL1iuT62cP2hiPjdM1x2JCIujIgLIuIdazVmXZ3+3D7LcjdHxFvOcnkjItb06yH2sHVr1ccWrv/vIuLqJc4/1Zvq9OvXasxsBu36sQtY9kms9iilHC6lvGuZxS4A3rHMMlrfz+0LsIet2kUb+lhKeV8p5c+WWWwYeP0yy6wbXRm0EbE5ImYi4uGIeDQi3hoRr42I/xER90fEZyLix6tlGxHxOxHx+WrZy6vzL6/Oe7D6/9WrqOOiiPhkRNxX/buyOv/9EXFTNfaTEfGuRdf5rYh4IiLujojpiLiueic2BHwsIh6KiE3V4rsj4oGI+HJE/MyLfuDWmU72sXpML4im70bEv6rO/+OIuPq0d88vi4i7qjH+AIjqZvYDP1317D9W522JiFurHn8sIuKFo3e3iBio7t+BiHikur/nLtW7pZ7bEfG+an15NCImV/MYRcQ1EfGFav34RERsqc4/EhF7T19vqnX17ur8P4iIp6I5Y9STPYTO9LFaX2+rTv9SRByLiJdGxDkR8WR1/qlPpxFxbVXjIeCfLtQNvB349aqWf1jd/Buq14AnY719ui2ldN0/4J8Bf7jo7/OBzwMXVX+/FbipOt1YWBZ4A/Bodfo8YEN1+mrgk9XpYeDOs4y9C/hwdfpPgO3V6VcAc9Xp91f1/AjNw459F9hI84n6ELAJ2Ap8BbhuUZ1Di8Y5AuyuTr8D+EinH/ea9fH3gR3ANuC+Rbf9FWDL4usDvwu8rzq9AyhVXwcW6lg05lHg5TTfxH5h4flRp3/V/S7AldXfNwH/dpneLX5u/9ii038M/GJ1+mbgLWcZt1GtQxcC9wCbq/P3LOrPkusN8GHgvdXpa3u9h53qI7AB+Ivq9Aerde9K4B8B04uvD5wDPA28iuab248vWiffT/Xaueg6n6h6dgnw1U4/vov/baA7fRn4YETcCNwJfI/mC+bd1ZuqPuCbi5afBiil3BMR50XEBTSD7kBEvIrmk23jKuq4Grhk0Ru58yJia3V6ppTyfeD7EfEtoB/YDvzXUsoxgIj402Vu/7bq//up3s3VTCf7+Fmagf0U8HvAWERcDPxlKWX+tDfnb6B6/EspMxHxvbPc7pdKKc8ARMRDNF/MDrVYUzd5upTyuer0R4Hf5Oy9W2wkIn4DOBf4MeAxYLl1YbHX0Xwx/Vw11ktpBuKCpdab7cCbAUopB+3hKW3tYynlRER8NSIGgcuB36a5fvXRXCcX+xmaofwVgIj4KDB2lpu/o5Ty/4DHI6L/bHW0W1cGbSnlzyPitcDPAzcAdwOPlVKuONNVlvj73wOzpZQ3V1MRjVWU8hLgioXgXFA9Qb+/6KyTNB/rlU5BLdzGwvVrpcN9vAd4J82ZiAmaL8Jv4YUr+5nGPpOl+l5Hpz8ez3L23gEQEecA/4XmJ6OnI+L9ND+5rEQAd5dSdp7h8qXWm5Wse73SQ+hMHz8LvBE4DvwZzU+jfcB1LdR3Nov7tq6m+7t1G+1PAH9TSvkozemHfwBcFBFXVJdvjIi/t+gqb63O3w4cLaUcpTlN+fXq8l2rLOUu4NcW1fWaZZY/BPxitT1iC81pyAXP0vx01jM62cdSytM0pw5fVUp5kmZvrmPpoL0H+BfV2G8EfrQ6v+d6tsgrFvoE7AS+yJl7t/hxWngx/k61DqxmW9oXgSsj4u9UY50bEX93mescAv55tfw12MMFnejjPcB7gC+UUr4NvIzmp9fHTlvuCeCVEfHTi+pb0FV968qgBS4FvlRN60wA76PZ6Bsj4mGa20EX75H2vYj4PM3tcqPVef8BuCEiPkfz3dRqvAsYqnYkeJzmBvozKqXcB3wKeJjm9NZhmtuDoPmu7vfj+TtD1V2n+3gv8OfV6c8CF7P0FOFemjtaPABcA3wNoJTyXZrTl4/GD3ek6RVzwK9ExCM0pw3/E2fu3c1Uz22anzr+kOZmgztobqNbkerFeRcwXY3/RZov1GezF7im6uEbaU6HPtvjPYTO9PFempvS7qn+fgR4pFQbWxeUUv4vzanimWpnqMU/vfqnwJtP2xlq3ar9IRgjokFzo/nhTtcCEBFbqm2A59J8oo2VUh7odF3r3XrrYy+rpujvLKVs63QtrYqIHwFOVtsIrwB+r5Tymg6X1VHd2MduVedtD+vVZERcQnPq5YAhK7XFK4CPR8RLgB8A/7rD9aiH1P4T7WpFxK8C7z7t7M+VUt7ZiXq0Ovax+0TE7cArTzt7TynlM52oR6tjH3/IoJUkKVG37gwlSVJXMGglSUpk0EqSlMiglSQpkUErSVKi/w8PzhiC+aPClQAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from matplotlib import pyplot as plt\n", "iris.plot.box(figsize=(8,6))\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Scatter Plot\n", "\n", "Possiamo mostrare uno scatterplot in seaborn come segue:" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from matplotlib import pyplot as plt\n", "plt.figure(figsize=(8,6))\n", "sns.scatterplot(x=iris['sepal_width'], y=iris['sepal_length'])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In alternativa, possiamo usare Pandas:" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "image/png": 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+1pazTPIZ5CymIgZ9/JZenknqq2iuDTEGEBH30KzDZBlnmeQzyFlMRQz6+C29PAGCiNgxadMLXexL36tblknZJR0OlM6Y8+JXJ1lMC+fNYfGCuTPu36rMMiOp1O39ZdWXZ5J6h6TXAyFpAfA+sttNdkCREg1VlGoytPHwk4zvO/BbceORJ6dtJyb+DL34aCZ1WqehLu8v6w95riAuAd4NrKS5lOi67LFNsvTwhZx49JK+/c87tnucyzdvZ8/e/ewa38eevfu5bPP2rl9JDI/sOugHN8D133l0yt/yJ/o1vi94bu8LjO+LGfuVt41+0O/vL+sfHQeIiHgiIn49IlZExC9GxNv8qep6qmoJEK/TYJbWjLeYJH2Kaa7lI+J9Xe2R9VxVS4B4nQaztDq5gmgAW6f5mpakJZJulPQjST+UtH7S85J0taRhSdslnZR/GNZNVS0BknKdBjMr8EG5Kb+R9KmIeG+b7Z8BtkTEddnk9uKIeLrl+XOB9wLnAqcCn4yIU6drq6oflJtQl1IIRcpmVLXURuOhMW5/4Ak2rl3G0LFLOzqmqlKVZrH6KbPUxkw2tOnMS2lZszoifs7By5YCXABcH81IdWd2xXFURDzexb4lU6eMmbLLZkzIU26iSButx2za8mBfl6dwqQ1LKdfnIAp4FTAKfFrS3ZKuy5YobbWSZqXYCTuzbX2njhkznUqR+VSkjVQZWSnUaSzWH8oOEPOAk4BrIuJ1wM+A35m0T7t1Iw+57yXpYkkNSY3R0dHu97QLBjljJkXmU4pFiaqsTmOx/tDNANHuB/1OYGdEfDd7fCPNgDF5n6NbHq8CHpv8jSJiU0QMRcTQ8uXLu9HfrhvkjJkUmU8pFiWqsjqNxfpDNwPEJydviIif0PwE9nHZprOA+ybt9mXgoiyb6TTgmX6dfxjkjJkUmU+zWZRowVyxcN4cFsxVqeUpyixP4lIbltqMWUyS/o7pPwdx/gzHrwOuo7mGxIPA24G3ZsdeK0nA/wXeCDwHvD0ipk1RchZTdaXIsMnbRqrEgVQTyM5isqLyZjF1EiD+w3TPR8Q/dtpYt1Q9QFh1DI/s4uxP3H7I9r//4MauBm+v1WD9oOtprr0IAGbdMl3iQDcDxMQE8h4OBIiJCWQHCOtXHX8OQtJa4I+A44FFE9sj4lUl9MusK1IlDngC2eoozyT1p4FrgH3ALwPXA58to1Nm3ZIqccATyFZHHZfayO5dnSzp3og4Idu2JSJOL7WHbXgOIo0ik6HfvO8n3HrfCG84fgVnHX9kae3klSpxwBPI1eNzckCZpTb2SJoDPCDpPcCPgV/M20HrD0Uyct7wiW/xLyM/A+CvGzs5bsVhfP2DZ3S9nSLylPOYjbzlSaxcLk0yO3luMX0AWExzJbmTgd8A/ksJfbIeK1LS4Zv3/eTF4DDh/pGf8c37ftLVdsw65ffX7OVZMOh7EbEbeBZ4X0T8akTcWV7XrFeKlHS49b6RXNuLtmPWKb+/Zq/jACFpSNK9wHbgXkn3SDq5vK5ZrxTJyHnD8StybS/ajlmn/P6avTy3mP4CeFdErI6I1TTXo/50Kb2yUnRaBmIiI2fhvDksXjCXhfNmzsg56/gjOW7FwYV6j1tx2LQT1a3tTHx1kvlTpJxFmSUwrDiXJskn9fs4zyT1rojYMvEgIr4tqf51rGsi72RdTPwZYppKKwf5+gfPyJ3F1Hj4Scb3Hfgtr/HIk9P2a7brQXiisjpSnJfz161kw5pltchi6sX7OE+a6ydoTlLfQPMnxluBp4DNABFxV0l9PITTXPPJWwYiVdmIvGUwivTLJTCqyecln269XmWmua7L/v7wpO2vpxkwzszxvSyhvGUgUpWNyFsGo0i/XAKjmnxe8unV69VxgIiIXy6tF1aqvJN1qSb38pbBGPT1IOrE5yWfXr1eebKYVkj6c0m3ZI+Pl/TfyuuadUveybpUk3t5y2DMZj2IOk1U1oHPSz69er3yzEHcQjNr6X9ExImS5gF3T5TdSMlzEMXkLTdRpERBkWMaD41x+wNPsHHtMoaOXTrj/kXKZuRtw9JwGYx8Zvt6dX09iJZv/L2I+HeS7s7Wl0bStohYl7uXs+QAkV+KDIgUGUZF2ki1YJBZ1eUNEHk+B/EzSUvJch4nlgfN2T/rgRQlB4q0kfeYIm0Mj+w6KDgAXP+dRxkecYa22UzyBIhLaa4f/UuS7qBZ7vu9pfTKuipFyYEibeQ9pkgb02VKmdn08gSIXwLOoZnW+nXgAfKlyVqPpMiASJFhVKSNVAsGmdVRngDxPyPiWeBlwNnAJpoLCE1L0sOS7pW0TdIhEweSzpD0TPb8NklX5OhTLRT5+PzwyC5ubOzo6FbJgZIWYvH8uSycp66XtEiRYVSkjVQLBlWdS42Uq66vb54rgBeyv98EXBsRfyvpf3V47C9HxBPTPL8lIs7L0ZfaSDXp2kxFEIisfEb3+1WkrEHeY4q0ceUFJ3DRaauTLBhURS41Uq46v755spi+QnORoLNprgfxPPDPEXHiDMc9DAxNFSAknQF8KE+AqEsWU5GPz+ctT1GkHZdBqA+fy3L12+tbZhbTf6Y59/DGiHgaeDnw2x0cF8CtkrZKuniKfdZn5cNvkfTqdjtIulhSQ1JjdHQ0R7erK9Wka4rJYKsmn8ty1f31zVNq4zngiy2PHwce7+DQDRHxmKRfBL4h6UcR0for8F3AMRGxW9K5wE3A2jbtb6I578HQ0FBnlz0Vl2rStaqlNqx8Ppflqvvrm+cKopCIeCz7+6fAl4BTJj3/bLZSHRFxMzBf0rKy+1UFqSZdq1pqw8rnc1muur++Hc9BFPrm0mHAnIjYlf37G8CVEfG1ln2OBEYiIiSdAtxI84piyo7VZQ5iQpGPzxcpN5G3nTqVQajTWFKc+yJStFFk7Cn0y/urzHLfRawAviRpoq3PRcTXJF0CEBHXAm8B3ilpH82J7wunCw51tPTwhbnfVGtWHJH7P0jedor0q4rqlGVStGxI2ecyxWtc5ZIpdfm/MlmpVxBlqdsVhJWn37JMplMkgy2FFK9xVcfeb8rMYjLrO3XKMqlq2ZAUr3FVx153DhBWa3XKMqlq2ZAUr3FVx153DhBWa3XKMqlq2ZCipVzyqOrY687F9qz2ipTnqKqqlg3JW8qliKqOvc48SW1ms1KnRIC68yS1mSVVp0QAO5gDhJnNSp0SAexgDhBmNit1SgSwg3mS2rqqX0oO9LMir3HZ56VOiQDg9/EEBwjrmjqVtKiqIq9xqvNSl3ITfh8f4FtM1hVju8e5fPN29uzdz67xfezZu5/LNm+v3RKMvVTkNfZ5ycev18EcIKwrnMlSviKvsc9LPn69DuYAYV3hTJbyFXmNfV7y8et1MAeIATK2e5x7djxdyuWyM1mKyXNOipS0OHDMnBe/yjovRd5fjYfG+Pit99N4aKzr/SnC7+ODeZJ6QKSYeKtbJkvZipyTIiUtGg8/yfi+A78VNx55suvnvshY3nbdnXx7uBkYrr5tmNPXLOWz7zitq/0qwu/jA3wFMQBSTrwtPXwhJx69ZKD/U3ViNhPO4/v289zPX2B838zHDI/sOmiRHYDrv/MowyO7ejqWxkNjLwaHCVuGxyp1JeH3sQPEQPDEW/WkmnBOsY5CkX7d/sATubZbbzhADABPvFVPqgnnFOsoFOnXxrXLcm233ig9QEh6WNK9krZJOqQEq5quljQsabukk8ru06DxxFv1FDknRY5JsY5CkX4NHbuU09csPWjb6WuWMnTs0imOsF4ovdy3pIeBoYhoe+0o6VzgvcC5wKnAJyPi1Om+Z9Fy31X9+HyqflV1/ClU9TUeHtmVe32DxkNj3P7AE2xcu6zjH6jfvO8n3HrfCG84fgVnHX/kjPunKudRZCxWXN5y31UIEH8KfCsibsge3w+cERGPT/U9iwSIqn58vqr9qpNUr3Hedor064qb7j1o0vmi9a/kygtO6Ooxfk/WVxXXgwjgVklbJV3c5vmVwI6WxzuzbV1T1Y/PV7VfdZLqNc7bTpF+FclIynuM35PWKkWA2BARJwHnAO+WtHHS8+2SuQ+5rJF0saSGpMbo6GiuDlQ1i6eq/aqTVK9x3nZSZSTlPcbvSWtVeoCIiMeyv38KfAk4ZdIuO4GjWx6vAh5r8302RcRQRAwtX748Vx+qmsVT1X7VSarXOG87qTKS8h7j96S1KjVASDpM0hET/wbeAHx/0m5fBi7KsplOA56Zbv6hiKpm8cymX0XKGpRZaqOqWktNLF4wN1epieGRXdzY2NHRh8rynstUGUl5jylSzsPqq+xSGyuAL0maaOtzEfE1SZcARMS1wM00M5iGgeeAt5fRkap+fL5Iv6q8JkAVxcSfIdrcvWyryGRw3nNZ5NxfecEJXHTa6lyZT3mPKVLOw+qp9CymMhRNc62Dsd3jbPjIbezZe+A2wKL5c7jj8jOn/AFT5Ji6KDL24ZFdnP2J2w/Z/vcf3NjVzw9U0SC/VwZBFbOYrIu8JkA+VS1PUVWD/F6xQzlA9BmvCZBPVctTVNUgv1fsUA4QfSZViYa6qGp5iqoa5PeKHcpzEH0qVSmEuihS0qGqZSCKlOfIa5DfK3VWuVIbZXCAsDyKZCRVNeuryFjMJniS2qxFkfIUVS03kWLxH7NWDhBWa0UykqqayTPI2VXWGw4QVmtFMpKqmskzyNlV1hsOEFZrRTKSZpPJk6c8R16DnF1lveFJahsIRTJ/8mbypJpATpHFZPWUd5K67FpMZpWwZsURuX+YLj18YccpnlNNIF902uqu/xAvMhazInyLyawLPIFsdeQAYdYFnkC2OnKAMOsCTyBbHXkOwmwKeSepr7zgBM5/7StKL8+RogyGS20YOECYtTXbRZk2bXmwlPIcKUqAVLXMiKXnW0xmkxQptZGiPEdd2rD+4QBhNklVF2WqSxvWPxwgzCap6qJMdWnD+keSACFprqS7JX2lzXNnSHpG0rbs64oUfaqSsd3j3LPjaV/GV0RVF2WqSxvWP5KU2pB0KTAEvDQizpv03BnAhyZvn06dSm14QrC6qrooU13asPQqV2pD0irgTcAfApeW3V4/aZ0Q3EPzsv6yzdvZsGaZ/1NWQJ5SG7M5Jq+6tGHVl+IW01XAZcD+afZZL+keSbdIenW7HSRdLKkhqTE6OlpGP5PzhKCZVVmpAULSecBPI2LrNLvdBRwTEScCnwJuardTRGyKiKGIGFq+fHn3O9sDnhA0syor+wpiA3C+pIeBzwNnSvrL1h0i4tmI2J39+2ZgvqRlJferEjwhaGZVVuocRET8LvC7cNBk9Nta95F0JDASESHpFJpBa6zMflXJ+etWsmHNMk8I5lDVyeOU7Zil0JNSG5IuAYiIa4G3AO+UtA94Hrgw+nEVo1nwhGDnZlsCo8xMMWekWd14RTnrG2O7x9nwkdvYs/fAvM2i+XO44/IzpwywRY5J1Tez1PKmufqT1NY3qloCI2U7Zik5QFjfqGoJjJTtmKXkAGF9YzYlMBbOm8PiBXNZOK+cTDFnpFkdeT0I6ytFsr5i4s/Qi4+q0jezKnOAsL6TJ+tropzJ+L4AXgDKLWfijDSrE99islrz5LFZcQ4QVmuePDYrzgHCas2Tx2bFeQ7Cas+Tx2bFOEDYQPDksVl+vsVkZmZtOUCYmVlbDhBmZtaWA4SZmbXlAGFmZm315XoQkkaBRwoevgx4oovd6TeDPP5BHjsM9vg99qZjImJ5pwf2ZYCYDUmNPAtm1M0gj3+Qxw6DPX6PvdjYfYvJzMzacoAwM7O2BjFAbOp1B3pskMc/yGOHwR6/x17AwM1BmJlZZwbxCsLMzDrgAGFmZm3VMkBIOlrSP0j6oaQfSHp/m30k6WpJw5K2SzqpF33ttg7HfoakZyRty76u6EVfyyBpkaR/lnRPNv7fb7NPXc99J2Ov7bkHkDRX0t2SvtLmuVqe91YzjD/3ua9rue99wG9FxF2SjgC2SvpGRNzXss85wNrs61TgmuzvftfJ2AG2RMR5Pehf2caBMyNit6T5wLcl3RIRd7bsU9dz38nYob7nHuD9wA+Bl7Z5rq7nvdV044ec576WVxAR8XhE3JX9exfNF2zlpN0uAK6PpjuBJZKOStzVrutw7LWVnc/d2cP52dfkTIy6nvtOxl5bklYBbwKum2KXWp73CR2MP7daBohWklYDrwO+O+mplcCOlsc7qdkP0mnGDrA+uxVxi6RXp+1ZubLL7G3AT4FvRMTAnPsOxg71PfdXAZcB+6d4vrbnPXMV048fcp77WgcISYcDm4EPRMSzk59uc0htftuaYex30azJciLwKeCmxN0rVUS8EBHrgFXAKZJeM2mX2p77DsZey3Mv6TzgpxGxdbrd2myrxXnvcPy5z31tA0R2D3Yz8FcR8cU2u+wEjm55vAp4LEXfyjbT2CPi2YlbERFxMzBf0rLE3SxdRDwNfAt446SnanvuJ0w19hqf+w3A+ZIeBj4PnCnpLyftU+fzPuP4i5z7WgYISQL+HPhhRHx8it2+DFyUZTacBjwTEY8n62RJOhm7pCOz/ZB0Cs33wVi6XpZH0nJJS7J/vwQ4G/jRpN3qeu5nHHtdz31E/G5ErIqI1cCFwG0R8bZJu9XyvENn4y9y7uuaxbQB+A3g3ux+LMDvAa8EiIhrgZuBc4Fh4Dng7em7WYpOxv4W4J2S9gHPAxdGfT5SfxTwGUlzaf4H+JuI+IqkS6D2576Tsdf53B9iQM77lGZ77l1qw8zM2qrlLSYzM5s9BwgzM2vLAcLMzNpygDAzs7YcIMzMrC0HCDMza8sBwqyArHTyISWVcxw/JOnqKZ57WNIySUskvatbbZrl5QBh1gMR0YiI982w2xLgXTPsY1YaBwirLUmHSfpqVr3y+5LeKulkSf8oaaukr0+Ue5b0LUlXSfqnbN9Tsu2nZNvuzv4+rsO2782uACRpTNJF2fbPSjq79WpA0lJJt2Zt/CkHisr9MfBLai7u8ifZtsMl3SjpR5L+aqJ0glkZHCCszt4IPBYRJ0bEa4Cv0axi+ZaIOBn4C+APW/Y/LCJeT/O39r/Itv0I2BgRrwOuAP53h23fQbPsyauBB4HTs+2nAZMX8Pkw8O2sjS+TlUUBfgf414hYFxG/nW17HfAB4HjgVVkbZqWoay0mM4B7gY9J+gjwFeAp4DXAN7JfvOcCrcXabgCIiNslvTQrfHcEzfpGa2mWhp7fYdtbgI3AIzRXLrtY0krgyWzFt9Z9NwK/mrX9VUlPTfN9/zkidgJktbZWA9/usE9mufgKwmorIv4FOJlmoPgj4M3AD7LfyNdFxAkR8YbWQyZ/C+APgH/IrkD+E7Cow+Zvp3nVcDrNstujNIulbZmqux1+3/GWf7+Af8mzEjlAWG1JegXwXET8JfAxmusPL5e0Pnt+vg5eVeut2fZ/T7MU9DPALwA/zp7/zU7bjogdwDJgbUQ8SPO3/A/RPkDcDvx61vY5wMuy7btoXsGY9YR/+7A6OwH4E0n7gb3AO4F9wNWSfoHm+/8q4AfZ/k9J+ieaC77/12zbR2neYroUuC1n+9+leRsLmoHhj2h/O+j3gRsk3QX8I/AoQESMSbpD0veBW4Cv5mzfbFZc7tuMZhYT8KGIaPS6L2ZV4VtMZmbWlq8gzGZB0tuB90/afEdEvLsX/THrJgcIMzNry7eYzMysLQcIMzNrywHCzMzacoAwM7O2/j+PlvlMYjr0+gAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "iris.plot.scatter(x='sepal_width',y='sepal_length')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Con seabord, possiamo facilmente colorare i punti in maniera diversa a seconda dell'appartenenza alle diverse classi di iris utilizzando il parametro `hue`:" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8,6))\n", "sns.scatterplot(x=iris['sepal_width'], y=iris['sepal_length'], hue=iris['species'])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> **🙋‍♂️ Domanda 2**\n", "> \n", "> Cosa apprendiamo dal plot? La coppia di variabili considerata costituisce un fattore discriminante per l'appartenenza alle diverse classi?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Lo scatterplot può essere effettuato con diverse coppie di variabili. Consideriamo la coppia (`sepal_length`, `petal_length`):" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8,6))\n", "sns.scatterplot(x=iris['petal_length'], y=iris['sepal_length'], hue=iris['species'])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> **🙋‍♂️ Domanda 3**\n", "> \n", "> Si confronti l'ultimo scatterplot visualizzato con lo scatterplot visto in precedenza. La nuova coppia di variabili costituisce un fattore discriminante per l'appartenenza alle diverse classi?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Come possiamo notare dai due plot, ogni coppia di variabili ci permette di vedere \"una parte\" delle possibili interazioni tra le diverse variabili. Per avere un quadro più completo, in pratica si visualizzano gli scatter plot di tutte le coppie possibili. Questo plot prende il nome di scatter matrix. Possiamo ottenere una scatter matrix con `seaborn` come segue:" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.pairplot(iris)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> **🙋‍♂️ Domanda 4**\n", "> \n", "> Perché sulla diagonale principale vengono mostrati degli istogrammi al posto di scatter plot? Si mostrino gli scatterplot corrispondenti alle coppie di variabili sulla diagonale principale." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Possiamo evidenziare i punti per classe specificando una variabile sulla base della quale colorare i punti:" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.pairplot(iris, hue='species')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> **🙋‍♂️ Domanda 5**\n", "> \n", "> Esiste una coppia di variabili che individua uno spazio nel quale le osservazioni appartenenti alle diverse classi sono maggiormente distinte? Esiste una unica variabile che presenta distribuzioni particolarmente diverse a seconda dell'appartenenza alle tre classi?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Medie e Covarianze\n", "\n", "Nel caso **multivariato**, la **media** viene calcolata in maniera del tutto analoga al caso **univariato** come **media di vettori**. Possiamo banalmente calcolare la media dei nostri dati multivariati mediante il metodo `mean`:" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "sepal_length 5.843333\n", "sepal_width 3.057333\n", "petal_length 3.758000\n", "petal_width 1.199333\n", "dtype: float64\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/cs/p62_d78d49n3ddj0xlfh1h7r0000gn/T/ipykernel_34355/769219605.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n", " print(iris.mean())\n" ] } ], "source": [ "print(iris.mean()) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Il risultato sarà un vettore (una serie di Pandas) che individua un punto nello spazio a quattro dimensioni che rappresenta la media delle osservazioni. Vediamo un semplice esempio a due dimensioni, considerando solo alcune variabili:" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "iris2d = iris[['sepal_length','sepal_width']]\n", "mean_point = iris2d.mean()\n", "plt.scatter(iris2d['sepal_length'],iris2d['sepal_width'])\n", "plt.plot(mean_point.iloc[0], mean_point.iloc[1],'rx')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "La croce rossa rappresenta il punto medio del dataset bidimensionale considerato." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Posso ottenre la matrice di covarianza mediante il metodo `cov`:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width\n", "sepal_length 0.685694 -0.042434 1.274315 0.516271\n", "sepal_width -0.042434 0.189979 -0.329656 -0.121639\n", "petal_length 1.274315 -0.329656 3.116278 1.295609\n", "petal_width 0.516271 -0.121639 1.295609 0.581006" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "iris.drop(\"species\", axis=1).cov()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> **🙋‍♂️ Domanda 6**\n", "> \n", "> A cosa serve il codice `drop(\"species\", axis=1)` inserito sopra?\n", "> \n", "> Che cosa rappresentano i valori sulla diagonale principale?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> **🙋‍♂️ Domanda 7**\n", "> \n", "> Ci sono coppie di variabili che presentano covarianze fortemente positive? Si confrontino i valori della matrice di covarianza con i relativi plot dello scatterplot. I due indicatori ci dicono la stessa cosa?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Indici di Correlazione\n", "\n", "Posso calcolare la matrice di correlazione con l'indice di correlazione di Pearson mediante il metodo `corr`:" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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petal_length0.871754-0.4284401.0000000.962865
petal_width0.817941-0.3661260.9628651.000000
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" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width\n", "sepal_length 1.000000 -0.117570 0.871754 0.817941\n", "sepal_width -0.117570 1.000000 -0.428440 -0.366126\n", "petal_length 0.871754 -0.428440 1.000000 0.962865\n", "petal_width 0.817941 -0.366126 0.962865 1.000000" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "iris.corr()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> **🙋‍♂️ Domanda 8**\n", "> \n", "> Ci sono coppie di variabili che presentano correlazioni fortemente positive? Si confrontino i valori della matrice di covarianza con i relativi plot dello scatterplot. I due indicatori ci dicono la stessa cosa?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "È possibile specificare l'utilizzo di un indice di correlazione diverso passando un parametro al metodo `corr`:" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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sepal_lengthsepal_widthpetal_lengthpetal_width
sepal_length1.000000-0.1667780.8818980.834289
sepal_width-0.1667781.000000-0.309635-0.289032
petal_length0.881898-0.3096351.0000000.937667
petal_width0.834289-0.2890320.9376671.000000
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" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width\n", "sepal_length 1.000000 -0.166778 0.881898 0.834289\n", "sepal_width -0.166778 1.000000 -0.309635 -0.289032\n", "petal_length 0.881898 -0.309635 1.000000 0.937667\n", "petal_width 0.834289 -0.289032 0.937667 1.000000" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "iris.corr(method='spearman')" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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sepal_lengthsepal_widthpetal_lengthpetal_width
sepal_length1.000000-0.0769970.7185160.655309
sepal_width-0.0769971.000000-0.185994-0.157126
petal_length0.718516-0.1859941.0000000.806891
petal_width0.655309-0.1571260.8068911.000000
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" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width\n", "sepal_length 1.000000 -0.076997 0.718516 0.655309\n", "sepal_width -0.076997 1.000000 -0.185994 -0.157126\n", "petal_length 0.718516 -0.185994 1.000000 0.806891\n", "petal_width 0.655309 -0.157126 0.806891 1.000000" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "iris.corr(method='kendall')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Correlation Plot\n", "Possiamo facilmente ottenere un correlation plot in `Seaborn` come segue:" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.heatmap(iris.corr(), annot=True) #annot=True serve a stampare i valori di correlazione\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Esercizi\n", "\n", "> 🧑‍💻 Esercizio 1\n", "> \n", "> Considerando il dataset Titanic, si calcolino per ogni variabile la numerosità, la media, la deviazione standard, il minimo, il massimo, il valore mediano, il primo e il terzo quartile. Dopo aver calcolato i valori richiesti individualmente, si utilizzi il metodo `describe` per ottenere tali valori. Qual è la variabile più dispersa?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> 🧑‍💻 Esercizio 2\n", "> \n", "> Considerando il dataset Titanic, per ognuna delle tre classi, si calcolino medie e varianze delle età dei passeggeri. In quale classe le età sono meno disperse? Quale classe contiene i soggetti più giovani? Si completi l'analisi con dei grafici a barre." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> 🧑‍💻 Esercizio 3\n", "> \n", "> Si aggiunga al dataset Titanic una nuova colonna \"Old\" che assume valore pari a 1 per le osservazioni che presentano età superiore al valore medio e 0 altrimenti. Si calcoli dunque una crosstab che calcoli il numero di soggetti \"anziani\" (soggetti per i quali old è pari a 1) rispetto alle variabili Pclass e Sex. Si mostri un barplot a partire dalla tabella. In quale classe gli uomini tendono ad essere molto più anziani delle donne?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> 🧑‍💻 Esercizio 4\n", "> \n", "> Si carichi il dataset mpg mediante la libreria seaborn (usare l'istruzione `t=sns.load_dataset('mpg')`). Si visualizzi la scatter matrix differenziando i colori dei punti a seconda dei valori della variabile `origin`. Chi produce le macchine più pesanti? Esistono coppie di variabili che costituiscono un fattore decisivo per distinguere una delle origini dalle altre?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> 🧑‍💻 Esercizio 5\n", "> \n", "> Considerando il dataset `mpg`, si scelga un gruppo di variabili rispetto alle quali ottenere un diagramma a coordinate parallele. Che cosa possiamo inferire dal diagramma?" ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 3", "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": "3.9.12" } }, "nbformat": 4, "nbformat_minor": 1 }