{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "db1faab3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Päivitetty 2023-12-11 / Aki Taanila\n"
]
}
],
"source": [
"from datetime import datetime\n",
"print(f'Päivitetty {datetime.now().date()} / Aki Taanila')"
]
},
{
"cell_type": "markdown",
"id": "e4b6bd8e",
"metadata": {},
"source": [
"# Selittävä analytiikka - parhaat käytänteet\n",
"\n",
"Oletan, että muistion https://nbviewer.org/github/taanila/kuvaileva/blob/main/kuvaileva.ipynb sisältö on lukijalle tuttu.\n",
"\n",
"Menetelmät:\n",
"\n",
"* kategoriset muuttujat -> **ristiintaulukointi**\n",
"* kategorinen ja määrällinen muuttuja -> määrällisen muuttujan **luokittelu** ja sen jälkeen **ristiintaulukointi**\n",
"* kategorinen ja määrällinen muuttuja -> **tilastolliset tunnusluvut** kategorisen muuttujan määräämissä ryhmissä\n",
"* määrälliset muuttujat -> **hajontakaavio** ja **korrelaatiokerroin**.\n",
"\n",
"Tässä muistiossa käytän laskentaan seuraavia funktioita:\n",
"\n",
"* **crosstab** ristiintaulukointiin\n",
"* **cut** määrällisen muuttujan luokitteluun\n",
"* **groupby** ryhmittelyyn\n",
"* **describe** tilastollisten tunnuslukujen laskentaan\n",
"* **dropna** puuttuvia arvoja sisältävien rivien poistamiseen\n",
"* **corr** korrelaatiokertoimen laskemiseen.\n",
"\n",
"Tässä muistiossa käytän seuraavia funktioita kaavioiden luontiin:\n",
"\n",
"* **plot(kind='bar')** pystypylväskaavio\n",
"* **plot(kind='barh')** vaakapylväskaavio \n",
"* **histplot** seaborn-kirjaston histogrammi, joka esittää luokitellun jakauman\n",
"* **barplot** seaborn-kirjaston pylväskaavio, joka esittää oletuksena keskiarvot\n",
"* **boxplot** seaborn-kirjaston boxplot, joka esittää viiden luvun yhteenvedon\n",
"* **scatterplot** seaborn-kirjaston hajontakaavio\n",
"* **jointplot** seaborn-kirjaston hajontakaavio terästettynä reunajakaumilla\n",
"\n",
"\n",
"* **heatmap** seaborn-kirjaston värikartta korrelaatioiden visualisointiin\n",
"* **pairplot** seaborn-kirjaston usean hajontakaavion kokoelma\n",
"\n",
"\n",
"* **displot** seaborn-kirjaston usean kaavion kokoelma (histplot)\n",
"* **catplot** seaborn-kirjaston usean kaavion kokoelma (countplot, barplot, boxplot)\n",
"* **relplot** seaborn-kirjaston usean kaavion kokoelma (scatterplot).\n",
"\n",
"Tilastollisella merkitsevyystestauksella testaan onko otoksessa havaittu ero/riippuvuus tilastollisesti merkitsevää (yleistettävissä otoksesta laajempaan joukkoon, josta otos on poimittu). Tilastollisiin merkitsevyyden testauksiin käytän:\n",
"\n",
"* **chi2_contingency** khiin neliö -testi ristiintaulukoinnin testaamiseen\n",
"* **ttest_ind** riippumattomien otosten t-testi kahden ryhmän keskiarvojen vertaamiseen\n",
"* **f_oneway** F-testi useamman ryhmän keskiarvojen vertaamiseen\n",
"* **pearsonr** korrelaatiokertoimen testaamiseen\n",
"\n",
"Jos merkitsevyystestaus tuntuu käsittämättömältä, niin lue artikkelini p-arvosta https://tilastoapu.wordpress.com/2012/02/14/p-arvo/\n",
"\n",
"\n",
"## Alkuvalmistelut"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "4627deb2",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"sns.set_style('whitegrid')\n",
"\n",
"# Merkitsevyystestaukseen\n",
"from scipy.stats import chi2_contingency, ttest_ind, f_oneway, pearsonr\n",
"\n",
"# Kaavioiden prosenttiakselin muotoiluun\n",
"from matplotlib.ticker import PercentFormatter\n",
"ticks = PercentFormatter(xmax=100, decimals=0, symbol=' %')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "cc62f83d",
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
" nro sukup ikä perhe koulutus palveluv palkka johto työtov työymp \\\n",
"0 1 1 38 1 1.0 22.0 3587 3 3.0 3 \n",
"1 2 1 29 2 2.0 10.0 2963 1 5.0 2 \n",
"2 3 1 30 1 1.0 7.0 1989 3 4.0 1 \n",
"3 4 1 36 2 1.0 14.0 2144 3 3.0 3 \n",
"4 5 1 24 1 2.0 4.0 2183 2 3.0 2 \n",
".. ... ... ... ... ... ... ... ... ... ... \n",
"77 78 1 22 1 3.0 0.0 1598 4 4.0 4 \n",
"78 79 1 33 1 1.0 2.0 1638 1 3.0 2 \n",
"79 80 1 27 1 2.0 7.0 2612 3 4.0 3 \n",
"80 81 1 35 2 2.0 16.0 2808 3 4.0 3 \n",
"81 82 2 35 2 3.0 15.0 2183 3 4.0 4 \n",
"\n",
" palkkat työteht työterv lomaosa kuntosa hieroja \n",
"0 3 3 NaN NaN NaN NaN \n",
"1 1 3 NaN NaN NaN NaN \n",
"2 1 3 1.0 NaN NaN NaN \n",
"3 3 3 1.0 NaN NaN NaN \n",
"4 1 2 1.0 NaN NaN NaN \n",
".. ... ... ... ... ... ... \n",
"77 3 4 NaN 1.0 1.0 NaN \n",
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"79 3 3 1.0 NaN 1.0 NaN \n",
"80 3 3 NaN NaN NaN NaN \n",
"81 3 4 1.0 NaN NaN NaN \n",
"\n",
"[82 rows x 16 columns]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.read_excel('https://taanila.fi/data1.xlsx')\n",
"\n",
"# Muuttujien tekstimuotoisia arvoja\n",
"sukup = ['mies', 'nainen']\n",
"koulutus = ['peruskoulu', '2. aste', 'korkeakoulu', 'ylempi korkeakoulu']\n",
"tyytyväisyys = ['erittäin tyytymätön', 'tyytymätön', 'siltä väliltä', 'tyytyväinen', 'erittäin tyytyväinen']\n",
"\n",
"# Luokkarajat iän luokitteluun\n",
"bins = [20, 30, 40, 50, 60, 70]\n",
"\n",
"df"
]
},
{
"cell_type": "markdown",
"id": "9dafe8f6",
"metadata": {},
"source": [
"## Ristiintaulukointi (kategoriset muuttujat)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "8875fe74",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"text/plain": [
" mies nainen\n",
"tyytyväisyys johtoon \n",
"erittäin tyytymätön 7 0\n",
"tyytymätön 15 1\n",
"siltä väliltä 23 7\n",
"tyytyväinen 15 8\n",
"erittäin tyytyväinen 3 3"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Ristiintaulukointi lukumäärinä\n",
"df1 = pd.crosstab(df['johto'], df['sukup'])\n",
"\n",
"df1.index = tyytyväisyys\n",
"df1.index.name = 'tyytyväisyys johtoon'\n",
"df1.columns = sukup\n",
"df1"
]
},
{
"cell_type": "markdown",
"id": "e9bee980",
"metadata": {},
"source": [
"### Khiin neliö -testi\n",
"\n",
"https://docs.scipy.org/doc//scipy-1.2.1/reference/generated/scipy.stats.chi2_contingency.html"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "4329bb0c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"p-arvo 0.065\n"
]
}
],
"source": [
"# khiin neliö -testi lasketaan aina lukumäärätaulukosta!\n",
"p = chi2_contingency(df1)[1]\n",
"print(f'p-arvo {p:.3f}')"
]
},
{
"cell_type": "markdown",
"id": "336df3b5",
"metadata": {},
"source": [
"Khiin neliö -testin p-arvo on 0.065, joten riippuvuus ei ole merkitsevää."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "122c27e2",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Ristiintaulukointi pylväinä\n",
"df1.plot(kind='bar', width=0.8, rot=45)\n",
"\n",
"plt.ylabel('lukumäärä')\n",
"plt.grid(axis='x')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "4cb3d1b1",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
" \n",
" \n",
" | \n",
" mies, n = 63 | \n",
" nainen, n = 19 | \n",
"
\n",
" \n",
" tyytyväisyys johtoon | \n",
" | \n",
" | \n",
"
\n",
" \n",
" \n",
" \n",
" erittäin tyytymätön | \n",
" 11.1 % | \n",
" 0.0 % | \n",
"
\n",
" \n",
" tyytymätön | \n",
" 23.8 % | \n",
" 5.3 % | \n",
"
\n",
" \n",
" siltä väliltä | \n",
" 36.5 % | \n",
" 36.8 % | \n",
"
\n",
" \n",
" tyytyväinen | \n",
" 23.8 % | \n",
" 42.1 % | \n",
"
\n",
" \n",
" erittäin tyytyväinen | \n",
" 4.8 % | \n",
" 15.8 % | \n",
"
\n",
" \n",
"
\n"
],
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Ristiintaulukointi prosentteina (mieti tarkkaan, haluatko prosentit sarakkeiden summista vai rivien summista!)\n",
"df2 = pd.crosstab(df['johto'], df['sukup'], normalize='columns')*100\n",
"\n",
"df2.index = tyytyväisyys\n",
"df2.index.name = 'tyytyväisyys johtoon'\n",
"df2.columns = sukup\n",
"\n",
"# Lukumäärätaulukosta (df1) n-arvot sarakeotsikoihin\n",
"for sarake in df2.columns:\n",
" df2 = df2.rename(columns={sarake:f'{sarake}, n = {df1[sarake].sum()}'})\n",
"\n",
"# Ulkoasun viimeistely\n",
"df2.style.format('{:.1f} %').background_gradient(cmap='Reds')"
]
},
{
"cell_type": "markdown",
"id": "06c55d9e",
"metadata": {},
"source": [
"Värikarttoja https://matplotlib.org/stable/tutorials/colors/colormaps.html"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "ea60ebc3",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Edellinen 100 % pinottuina vaakapylväinä\n",
"# T vaihtaa taulukon rivit ja sarakkeet (kaavion arvosarjat ja kategoriat) päittäin\n",
"# alpha-parametrilla hieman läpinäkyvyyttä väreihin\n",
"df2.T.plot(kind='barh', stacked=True, width=0.8, cmap='Reds', alpha=0.8, figsize=(6, 3))\n",
"\n",
"plt.xlabel('Prosenttia sukupuolesta')\n",
"plt.grid(axis='y')\n",
"plt.gca().xaxis.set_major_formatter(ticks) # x-akselin prosenttimuotoilu\n",
"plt.legend(loc=(1, 0.5)) # Selitteen sijoittelu"
]
},
{
"cell_type": "markdown",
"id": "e4d7fb85",
"metadata": {},
"source": [
"Usean kaavion kokonaisuuksia saan seabornin **catplot** toiminnolla (countplot). Usean kaavion kokonaisuuksien hienosäätö vaatii jonkin verran perehtymistä.\n",
"\n",
"kind-parametrin arvo **count** tarkoittaa countplot-kaaviolajia.\n",
"\n",
"catplotin kuten muidenkin yhdistelmäkaavioiden koon määrittämiseen käytetään **height**- ja **aspect**-parametreja (kokeile eri arvoja)."
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "85611579",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Koulutuksen jakauma sukupuolen ja perhesuhteen mukaan\n",
"g = sns.catplot(data=df, x='koulutus', col='perhe', row='sukup', kind='count', \n",
" height=3, aspect=1.5)\n",
"\n",
"g.set_xticklabels(koulutus)\n",
"g.set_ylabels('lukumäärä')\n",
"\n",
"# Seuraavassa määritän kaavioiden otsikot\n",
"titles = ['mies, perheetön','mies, perheellinen', 'nainen, perheetön', 'mies, perheellinen']\n",
"for ax, title in zip(g.axes.flatten(), titles):\n",
" ax.set_title(title)"
]
},
{
"cell_type": "markdown",
"id": "50e85343",
"metadata": {},
"source": [
"## Ristiintaulukointi (kategorinen ja määrällinen muuttuja)\n",
"\n",
"Ennen ristiintaulukointia määrällinen muuttuja täytyy luokitella."
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "773e1d65",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" mies | \n",
" nainen | \n",
"
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" \n",
" ikäluokka | \n",
" | \n",
" | \n",
"
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" \n",
" \n",
" \n",
" [20, 30) | \n",
" 16 | \n",
" 1 | \n",
"
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" \n",
" [30, 40) | \n",
" 23 | \n",
" 7 | \n",
"
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" \n",
" [40, 50) | \n",
" 16 | \n",
" 7 | \n",
"
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" \n",
" [50, 60) | \n",
" 7 | \n",
" 4 | \n",
"
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" \n",
" [60, 70) | \n",
" 1 | \n",
" 0 | \n",
"
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" \n",
"
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"
"
],
"text/plain": [
" mies nainen\n",
"ikäluokka \n",
"[20, 30) 16 1\n",
"[30, 40) 23 7\n",
"[40, 50) 16 7\n",
"[50, 60) 7 4\n",
"[60, 70) 1 0"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Iän luokittelu\n",
"df['ikäluokka'] = pd.cut(df['ikä'], bins=bins, right=False)\n",
"\n",
"df3 = pd.crosstab(df['ikäluokka'], df['sukup'])\n",
"df3.columns = sukup\n",
"df3"
]
},
{
"cell_type": "markdown",
"id": "461f1885",
"metadata": {},
"source": [
"Usean kaavion kokonaisuuksia saan seabornin **displot** toiminnoilla (histplot). Usean kaavion kokonaisuuksien hienosäätö vaatii jonkin verran perehtymistä.\n",
"\n",
"Kind-parametrin arvo **hist** tarkoittaa histplot-kaaviolajia."
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "c5b533c2",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Ikäjakauma sukupuolen mukaan\n",
"g = sns.displot(data=df, x='ikä', col='sukup', kind='hist', bins=bins, height=3, aspect=1)\n",
"\n",
"g.set_ylabels('lukumäärä')\n",
"\n",
"# Kaavioiden otsikot sukup-listasta\n",
"for ax, title in zip(g.axes.flatten(), sukup):\n",
" ax.set_title(title)"
]
},
{
"cell_type": "markdown",
"id": "b26b306a",
"metadata": {},
"source": [
"## Tilastollisia tunnuslukuja (kategorinen ja määrällinen muuttuja)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "816bafe5",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
" \n",
" \n",
" | \n",
" count | \n",
" mean | \n",
" std | \n",
" min | \n",
" 25% | \n",
" 50% | \n",
" 75% | \n",
" max | \n",
"
\n",
" \n",
" \n",
" \n",
" peruskoulu | \n",
" 27 | \n",
" 2310 | \n",
" 473 | \n",
" 1638 | \n",
" 2008 | \n",
" 2144 | \n",
" 2534 | \n",
" 3587 | \n",
"
\n",
" \n",
" 2. aste | \n",
" 30 | \n",
" 2403 | \n",
" 534 | \n",
" 1521 | \n",
" 2008 | \n",
" 2378 | \n",
" 2729 | \n",
" 3510 | \n",
"
\n",
" \n",
" korkeakoulu | \n",
" 22 | \n",
" 2887 | \n",
" 1108 | \n",
" 1559 | \n",
" 2222 | \n",
" 2710 | \n",
" 2925 | \n",
" 6278 | \n",
"
\n",
" \n",
" ylempi korkeakoulu | \n",
" 2 | \n",
" 5147 | \n",
" 110 | \n",
" 5069 | \n",
" 5108 | \n",
" 5147 | \n",
" 5186 | \n",
" 5225 | \n",
"
\n",
" \n",
"
\n"
],
"text/plain": [
""
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Palkan tunnusluvut koulutuksen mukaan\n",
"df4 = df.groupby('koulutus')['palkka'].describe()\n",
"\n",
"df4.index = koulutus\n",
"\n",
"df4.style.format('{:.0f}')"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "9f572998",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, 'palkkakeskiarvo')"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Palkkakeskiarvot koulutuksen mukaan; näkyvillä myös virhemarginaalit (musta viiva)\n",
"sns.barplot(data=df, x='koulutus', y='palkka')\n",
"\n",
"# Pientä kikkailua n-arvojen saamiseksi kaavioon\n",
"n_koulutus = []\n",
"for i in range(4):\n",
" # \\n on rivinvaihdon merkki \n",
" n_koulutus.append(f'{koulutus[i]}\\n n = {int(df4.iloc[i, 0])}')\n",
"plt.xticks(ticks=[0, 1, 2, 3], labels=n_koulutus)\n",
"\n",
"plt.ylabel('palkkakeskiarvo')"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "cf97b14b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Palkkakeskiarvot koulutuksen ja sukupuolen mukaan\n",
"ax = sns.barplot(data=df, x='koulutus', y='palkka', hue='sukup')\n",
"\n",
"plt.xticks(ticks=[0, 1, 2, 3], labels=koulutus)\n",
"plt.ylabel('Palkkakeskiarvo')\n",
"\n",
"# Selitteeseen tekstimuotoiset nimet\n",
"handles, labels = ax.get_legend_handles_labels()\n",
"ax.legend(handles, sukup)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "934f37fb",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"([,\n",
" ,\n",
" ,\n",
" ],\n",
" [Text(0, 0, 'peruskoulu\\n n = 27'),\n",
" Text(1, 0, '2. aste\\n n = 30'),\n",
" Text(2, 0, 'korkeakoulu\\n n = 22'),\n",
" Text(3, 0, 'ylempi korkeakoulu\\n n = 2')])"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Palkka koulutuksen mukaan boxplottina\n",
"\n",
"sns.boxplot(data=df, x='koulutus', y='palkka')\n",
"\n",
"# n_koulutus-lista määritelty edellä palkkakeskiarvoja kuvaavan barplotin yhteydessä\n",
"plt.xticks(ticks=[0, 1, 2, 3], labels=n_koulutus)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "90f34d19",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Palkka koulutuksen ja sukupuolen mukaan\n",
"\n",
"ax = sns.boxplot(data=df, x='koulutus', y='palkka', hue='sukup')\n",
"\n",
"plt.xticks(ticks=[0, 1, 2, 3], labels=koulutus)\n",
"\n",
"handles, _ = ax.get_legend_handles_labels()\n",
"ax.legend(handles, sukup)"
]
},
{
"cell_type": "markdown",
"id": "b39e571a",
"metadata": {},
"source": [
"Usean kaavion kokonaisuuksia saan seabornin **catplot**-toiminnolla (barplot, boxplot)."
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "a27bc679",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Tyytyväisyys johtoon sukupuolen mukaan\n",
"\n",
"g = sns.catplot(data=df, x='johto', y='palkka', col='sukup', kind='bar', height=3, aspect=1)\n",
"\n",
"for ax, title in zip(g.axes.flatten(), sukup):\n",
" ax.set_title(title)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "31ba39f2",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Palkka sukupuolen ja koulutuksen mukaan\n",
"\n",
"g = sns.catplot(data=df, x='sukup', y='palkka', col='koulutus', kind='box', height=3, aspect=0.8)\n",
"\n",
"g.set_xlabels('')\n",
"g.set_xticklabels(sukup)\n",
"\n",
"for ax, title in zip(g.axes.flatten(), koulutus):\n",
" ax.set_title(title)"
]
},
{
"cell_type": "markdown",
"id": "75f02ed6",
"metadata": {},
"source": [
"### Kahden riippumattoman otoksen t-testi\n",
"\n",
"https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.ttest_ind.html"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "5ceb7571",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"p-arvo 0.003\n"
]
}
],
"source": [
"# Riippumattomien otosten t-testi\n",
"\n",
"# Vertailtavien ryhmien muodostaminen\n",
"s1 = df['palkka'][df['sukup']==1] # miehet\n",
"s2 = df['palkka'][df['sukup']==2] # naiset\n",
"\n",
"# Kahden riippumattoman (ind) otoksen t-testi\n",
"\n",
"p = ttest_ind(s1, s2, equal_var=False, nan_policy='omit')[1]\n",
"print(f'p-arvo {p:.3f}')"
]
},
{
"cell_type": "markdown",
"id": "0b89a6f0",
"metadata": {},
"source": [
"Kahden riippumattoman otoksen t-testin p-arvo on 0.003, joten miesten ja naisten palkkakeskiarvo poikkeavat merkitsevästi toisistaan."
]
},
{
"cell_type": "markdown",
"id": "b26dd71b",
"metadata": {},
"source": [
"### Yksisuuntainen anova f-testi\n",
"\n",
"https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.f_oneway.html"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "d17aa079",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"p-arvo 0.000\n"
]
}
],
"source": [
"# F-testi useamman ryhmän vertailuun\n",
"\n",
"# Data, josta on poistettu mahdolliset palkan puuttuvia arvoja sisältävät rivit\n",
"df_dropna = df.dropna(subset=['palkka'])\n",
"\n",
"# Vertailtavien ryhmien muodostaminen\n",
"k1 = df_dropna['palkka'][df_dropna['koulutus']==1] # peruskoulu\n",
"k2 = df_dropna['palkka'][df_dropna['koulutus']==2] # 2. aste\n",
"k3 = df_dropna['palkka'][df_dropna['koulutus']==3] # korkeakoulu\n",
"k4 = df_dropna['palkka'][df_dropna['koulutus']==4] # ylempi korkeakoulu\n",
"\n",
"# F-testi\n",
"p = f_oneway(k1, k2, k3, k4)[1]\n",
"print(f'p-arvo {p:.3f}')"
]
},
{
"cell_type": "markdown",
"id": "d317c3ec",
"metadata": {},
"source": [
"F-testin p-arvo on pienempi kuin 0.001, joten koulutusten välillä esiintyy merkiseviä eroja palkkakeskiarvojen välillä."
]
},
{
"cell_type": "markdown",
"id": "93cba1c0",
"metadata": {},
"source": [
"## Korrelaatioita ja hajontakaavioita (määrälliset muuttujat)\n",
"\n",
"Määrällisten muuttujien välisiä riippuvuuksia tarkastelen korrelaatioiden ja hajontakaavioiden avulla."
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "e70fc0a5",
"metadata": {},
"outputs": [
{
"data": {
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" 1 | \n",
" 3 | \n",
"
\n",
" \n",
" 97 | \n",
" 98 | \n",
" 2.0 | \n",
" 2.8 | \n",
" 5.2 | \n",
" 5.0 | \n",
" 2.4 | \n",
" 2.7 | \n",
" 8.4 | \n",
" 3.7 | \n",
" 1 | \n",
" 38 | \n",
" 0 | \n",
" 1 | \n",
"
\n",
" \n",
" 98 | \n",
" 99 | \n",
" 3.1 | \n",
" 2.2 | \n",
" 6.7 | \n",
" 6.8 | \n",
" 2.6 | \n",
" 2.9 | \n",
" 8.4 | \n",
" 4.3 | \n",
" 1 | \n",
" 42 | \n",
" 0 | \n",
" 1 | \n",
"
\n",
" \n",
" 99 | \n",
" 100 | \n",
" 2.5 | \n",
" 1.8 | \n",
" 9.0 | \n",
" 5.0 | \n",
" 2.2 | \n",
" 3.0 | \n",
" 6.0 | \n",
" 4.4 | \n",
" 0 | \n",
" 33 | \n",
" 0 | \n",
" 1 | \n",
"
\n",
" \n",
"
\n",
"
100 rows × 13 columns
\n",
"
"
],
"text/plain": [
" id Delivery Speed Price Level Price Flexibility Manufacturer Image \\\n",
"0 1 4.1 0.6 6.9 4.7 \n",
"1 2 1.8 3.0 6.3 6.6 \n",
"2 3 3.4 5.2 5.7 6.0 \n",
"3 4 2.7 1.0 7.1 5.9 \n",
"4 5 6.0 0.9 9.6 7.8 \n",
".. ... ... ... ... ... \n",
"95 96 0.6 1.6 6.4 5.0 \n",
"96 97 6.1 0.5 9.2 4.8 \n",
"97 98 2.0 2.8 5.2 5.0 \n",
"98 99 3.1 2.2 6.7 6.8 \n",
"99 100 2.5 1.8 9.0 5.0 \n",
"\n",
" Service Salesforce Image Product Quality Satisfaction Level Firm size \\\n",
"0 2.4 2.3 5.2 4.2 0 \n",
"1 2.5 4.0 8.4 4.3 1 \n",
"2 4.3 2.7 8.2 5.2 1 \n",
"3 1.8 2.3 7.8 3.9 1 \n",
"4 3.4 4.6 4.5 6.8 0 \n",
".. ... ... ... ... ... \n",
"95 0.7 2.1 8.4 3.4 1 \n",
"96 3.3 2.8 7.1 5.2 0 \n",
"97 2.4 2.7 8.4 3.7 1 \n",
"98 2.6 2.9 8.4 4.3 1 \n",
"99 2.2 3.0 6.0 4.4 0 \n",
"\n",
" Usage level % Industry type Buying situation \n",
"0 32 1 1 \n",
"1 43 0 1 \n",
"2 48 1 2 \n",
"3 32 1 1 \n",
"4 58 1 3 \n",
".. ... ... ... \n",
"95 25 1 1 \n",
"96 60 1 3 \n",
"97 38 0 1 \n",
"98 42 0 1 \n",
"99 33 0 1 \n",
"\n",
"[100 rows x 13 columns]"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Avaan toisen datan, jossa asteikolla 0-10 mitattuja mielikuvia\n",
"hatco = pd.read_excel('https://taanila.fi/hatco.xlsx')\n",
"hatco"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "f69fd3ca",
"metadata": {},
"outputs": [],
"source": [
"# Muodostan datan, jossa ainoastaan mielikuvamuuttujat\n",
"hatco1 = hatco.loc[:, 'Delivery Speed':'Satisfaction Level']"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "384b99ab",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
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" \n",
" \n",
" | \n",
" Delivery Speed | \n",
" Price Level | \n",
" Price Flexibility | \n",
" Manufacturer Image | \n",
" Service | \n",
" Salesforce Image | \n",
" Product Quality | \n",
" Satisfaction Level | \n",
"
\n",
" \n",
" \n",
" \n",
" Delivery Speed | \n",
" 1.000000 | \n",
" -0.349225 | \n",
" 0.509295 | \n",
" 0.050414 | \n",
" 0.611901 | \n",
" 0.077115 | \n",
" -0.482631 | \n",
" 0.650632 | \n",
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\n",
" \n",
" Price Level | \n",
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" 1.000000 | \n",
" -0.487213 | \n",
" 0.272187 | \n",
" 0.512981 | \n",
" 0.186243 | \n",
" 0.469746 | \n",
" 0.028395 | \n",
"
\n",
" \n",
" Price Flexibility | \n",
" 0.509295 | \n",
" -0.487213 | \n",
" 1.000000 | \n",
" -0.116104 | \n",
" 0.066617 | \n",
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" 0.524814 | \n",
"
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" \n",
" Manufacturer Image | \n",
" 0.050414 | \n",
" 0.272187 | \n",
" -0.116104 | \n",
" 1.000000 | \n",
" 0.298677 | \n",
" 0.788225 | \n",
" 0.199981 | \n",
" 0.475934 | \n",
"
\n",
" \n",
" Service | \n",
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" 0.298677 | \n",
" 1.000000 | \n",
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" -0.055161 | \n",
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"
\n",
" \n",
" Salesforce Image | \n",
" 0.077115 | \n",
" 0.186243 | \n",
" -0.034316 | \n",
" 0.788225 | \n",
" 0.240808 | \n",
" 1.000000 | \n",
" 0.177294 | \n",
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"
\n",
" \n",
" Product Quality | \n",
" -0.482631 | \n",
" 0.469746 | \n",
" -0.448112 | \n",
" 0.199981 | \n",
" -0.055161 | \n",
" 0.177294 | \n",
" 1.000000 | \n",
" -0.283340 | \n",
"
\n",
" \n",
" Satisfaction Level | \n",
" 0.650632 | \n",
" 0.028395 | \n",
" 0.524814 | \n",
" 0.475934 | \n",
" 0.631233 | \n",
" 0.340909 | \n",
" -0.283340 | \n",
" 1.000000 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" Delivery Speed Price Level Price Flexibility \\\n",
"Delivery Speed 1.000000 -0.349225 0.509295 \n",
"Price Level -0.349225 1.000000 -0.487213 \n",
"Price Flexibility 0.509295 -0.487213 1.000000 \n",
"Manufacturer Image 0.050414 0.272187 -0.116104 \n",
"Service 0.611901 0.512981 0.066617 \n",
"Salesforce Image 0.077115 0.186243 -0.034316 \n",
"Product Quality -0.482631 0.469746 -0.448112 \n",
"Satisfaction Level 0.650632 0.028395 0.524814 \n",
"\n",
" Manufacturer Image Service Salesforce Image \\\n",
"Delivery Speed 0.050414 0.611901 0.077115 \n",
"Price Level 0.272187 0.512981 0.186243 \n",
"Price Flexibility -0.116104 0.066617 -0.034316 \n",
"Manufacturer Image 1.000000 0.298677 0.788225 \n",
"Service 0.298677 1.000000 0.240808 \n",
"Salesforce Image 0.788225 0.240808 1.000000 \n",
"Product Quality 0.199981 -0.055161 0.177294 \n",
"Satisfaction Level 0.475934 0.631233 0.340909 \n",
"\n",
" Product Quality Satisfaction Level \n",
"Delivery Speed -0.482631 0.650632 \n",
"Price Level 0.469746 0.028395 \n",
"Price Flexibility -0.448112 0.524814 \n",
"Manufacturer Image 0.199981 0.475934 \n",
"Service -0.055161 0.631233 \n",
"Salesforce Image 0.177294 0.340909 \n",
"Product Quality 1.000000 -0.283340 \n",
"Satisfaction Level -0.283340 1.000000 "
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Mielikuvamuuttujien korrelaatiokertoimet\n",
"korrelaatiot = hatco1.corr()\n",
"korrelaatiot"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "29d91347",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
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