{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Päivitetty 2024-04-15 / Aki Taanila\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "print(f'Päivitetty {datetime.now().date()} / Aki Taanila')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dataan tutustuminen\n",
    "\n",
    "Datan avaamisen jälkeen kannattaa ensimmäiseksi tutustua dataan. Tähän muistioon olen koonnut mielestäni keskeisimmät pandas-kirjaston funktiot ja ominaisuudet, joita voit käyttää dataan tutustuttaessa."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tuon data-analytiikan peruspaketin\n",
    "import pandas as pd\n",
    "\n",
    "# Luen datan dataframeen\n",
    "df = pd.read_excel('https://taanila.fi/data1.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(82, 16)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Datan rivien ja sarakkeiden lukumäärät\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nro</th>\n",
       "      <th>sukup</th>\n",
       "      <th>ikä</th>\n",
       "      <th>perhe</th>\n",
       "      <th>koulutus</th>\n",
       "      <th>palveluv</th>\n",
       "      <th>palkka</th>\n",
       "      <th>johto</th>\n",
       "      <th>työtov</th>\n",
       "      <th>työymp</th>\n",
       "      <th>palkkat</th>\n",
       "      <th>työteht</th>\n",
       "      <th>työterv</th>\n",
       "      <th>lomaosa</th>\n",
       "      <th>kuntosa</th>\n",
       "      <th>hieroja</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
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       "      <td>1</td>\n",
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       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2963</td>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1989</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>36</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2144</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2183</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>78</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1598</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>79</td>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1638</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2612</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>35</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2808</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>82</td>\n",
       "      <td>2</td>\n",
       "      <td>35</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2183</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>82 rows × 16 columns</p>\n",
       "</div>"
      ],
      "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",
       "78        1        2      1.0      NaN      NaN      NaN  \n",
       "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": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df\n",
    "# Huomaa että vain datan ensimmäiset ja viimeiset rivit näytetään"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Huomautus**: **työtov**-muuttujan arvot ovat desimaalimuodossa (3.0, 5.0, jne.), koska työtov-muuttujalla on puuttuvia arvoja. Kokonaislukutyyppinen muuttuja ei voi sisältää puuttuvia arvoja ja sen vuoksi Python on muuttanut tietotyypiksi liukuluvun (desimaaliluku)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Kategorinen vai määrällinen muuttuja\n",
    "\n",
    "* **nro** Tämä muuttuja on keinotekoinen järjestysnumero eikä muuttujan tyypillä ole merkitystä.\n",
    "* **sukup** Sukupuoli on kategorinen muuttuja. Tässä arvo 1 tarkoittaa miestä ja 2 naista.\n",
    "* **ika** Ikä on määrällinen muuttuja.\n",
    "* **perhe** Perhesuhde on kategorinen muuttuja. Tässä arvo 1 tarkoittaa perheetöntä ja 2 perheellistä.\n",
    "* **koulutus** Koulutus on kategorinen muuttuja (1 = peruskoulu, 2 = 2. aste, 3 = korkeakoulu, 4 = ylempi korkeakoulu).\n",
    "* **palveluv** Palvelusvuodet on määrällinen muuttuja.\n",
    "* **palkka** Palkka on määrällinen muuttuja.\n",
    "* **johto, työtov, työymp, palkkat, työteht** Nämä ovat tyytyväisyysmuuttujia, joiden arvo on välillä 1 = erittäin tyytymätön - 5 = erittäin tyytyväinen. Lähtökohtaisesti nämä ovat kategorisia muuttujia, mutta voidaan tulkita myös määrällisiksi muuttujiksi. Mielipideasteikot ovat usein rajatapauksia, joille voidaan käyttää sekä kategoristen että määrällisten muuttujien menetelmiä.\n",
    "* **työterv, lomaosa, kuntosa, hieroja** Nämä ovat kategorisia muuttujia, jotka kertovat onko vastaaja käyttänyt (**1**) kyseistä etua."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nro</th>\n",
       "      <th>sukup</th>\n",
       "      <th>ikä</th>\n",
       "      <th>perhe</th>\n",
       "      <th>koulutus</th>\n",
       "      <th>palveluv</th>\n",
       "      <th>palkka</th>\n",
       "      <th>johto</th>\n",
       "      <th>työtov</th>\n",
       "      <th>työymp</th>\n",
       "      <th>palkkat</th>\n",
       "      <th>työteht</th>\n",
       "      <th>työterv</th>\n",
       "      <th>lomaosa</th>\n",
       "      <th>kuntosa</th>\n",
       "      <th>hieroja</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>3587</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2963</td>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1989</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>36</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2144</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2183</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "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",
       "   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  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Datan alkupää. Voin myös määrittää näytettävien rivien määrän, esimerkiksi df.head(10)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nro</th>\n",
       "      <th>sukup</th>\n",
       "      <th>ikä</th>\n",
       "      <th>perhe</th>\n",
       "      <th>koulutus</th>\n",
       "      <th>palveluv</th>\n",
       "      <th>palkka</th>\n",
       "      <th>johto</th>\n",
       "      <th>työtov</th>\n",
       "      <th>työymp</th>\n",
       "      <th>palkkat</th>\n",
       "      <th>työteht</th>\n",
       "      <th>työterv</th>\n",
       "      <th>lomaosa</th>\n",
       "      <th>kuntosa</th>\n",
       "      <th>hieroja</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>78</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1598</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>79</td>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1638</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2612</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>81</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2808</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>82</td>\n",
       "      <td>2</td>\n",
       "      <td>35</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2183</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    nro  sukup  ikä  perhe  koulutus  palveluv  palkka  johto  työtov  työymp  \\\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",
       "77        3        4      NaN      1.0      1.0      NaN  \n",
       "78        1        2      1.0      NaN      NaN      NaN  \n",
       "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  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Datan loppupää \n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nro</th>\n",
       "      <th>sukup</th>\n",
       "      <th>ikä</th>\n",
       "      <th>perhe</th>\n",
       "      <th>koulutus</th>\n",
       "      <th>palveluv</th>\n",
       "      <th>palkka</th>\n",
       "      <th>johto</th>\n",
       "      <th>työtov</th>\n",
       "      <th>työymp</th>\n",
       "      <th>palkkat</th>\n",
       "      <th>työteht</th>\n",
       "      <th>työterv</th>\n",
       "      <th>lomaosa</th>\n",
       "      <th>kuntosa</th>\n",
       "      <th>hieroja</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>22.0</td>\n",
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       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>40</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2846</td>\n",
       "      <td>3</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2808</td>\n",
       "      <td>3</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>58</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>3587</td>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>53</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3393</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    nro  sukup  ikä  perhe  koulutus  palveluv  palkka  johto  työtov  työymp  \\\n",
       "10   11      1   39      2       1.0      22.0    2651      3     5.0       3   \n",
       "11   12      1   40      2       3.0      21.0    2846      3     5.0       3   \n",
       "12   13      1   35      2       3.0      15.0    2808      3     5.0       3   \n",
       "13   14      1   58      2       3.0      21.0    3587      4     5.0       4   \n",
       "14   15      1   53      2       3.0      12.0    3393      4     4.0       4   \n",
       "\n",
       "    palkkat  työteht  työterv  lomaosa  kuntosa  hieroja  \n",
       "10        1        3      NaN      NaN      NaN      NaN  \n",
       "11        1        2      NaN      1.0      NaN      1.0  \n",
       "12        1        4      NaN      1.0      NaN      NaN  \n",
       "13        1        3      NaN      NaN      NaN      NaN  \n",
       "14        4        4      NaN      1.0      NaN      NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Tietyt rivit (huomaa, että rivien numerointi alkaa nollasta)\n",
    "df[10:15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Jos haluan näyttää kaikki rivit, niin asetan max_rows arvoksi None\n",
    "# pd.options.display.max_rows = None\n",
    "\n",
    "# Jos haluan näyttää kaikki sarakkeet, niin asetan max_columns arvoksi None\n",
    "#pd.options.display.max_columns = None\n",
    "\n",
    "# df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Varoitus!** Edellisen solut komentoja kannattaa käyttää varoen. Kaikki näytetyt rivit ja sarakkeet tallentuvat muistion mukana, kasvattavat muistion tiedostokokoa ja hidastavat toimintaa."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nro         82\n",
       "sukup       82\n",
       "ikä         82\n",
       "perhe       82\n",
       "koulutus    81\n",
       "palveluv    80\n",
       "palkka      82\n",
       "johto       82\n",
       "työtov      81\n",
       "työymp      82\n",
       "palkkat     82\n",
       "työteht     82\n",
       "työterv     47\n",
       "lomaosa     20\n",
       "kuntosa      9\n",
       "hieroja     22\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sarakkeiden otsikot (muuttujien nimet) ja arvojen lukumäärät\n",
    "df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nro          0\n",
       "sukup        0\n",
       "ikä          0\n",
       "perhe        0\n",
       "koulutus     1\n",
       "palveluv     2\n",
       "palkka       0\n",
       "johto        0\n",
       "työtov       1\n",
       "työymp       0\n",
       "palkkat      0\n",
       "työteht      0\n",
       "työterv     35\n",
       "lomaosa     62\n",
       "kuntosa     73\n",
       "hieroja     60\n",
       "dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Puuttuvien arvojen lukumäärät\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 82 entries, 0 to 81\n",
      "Data columns (total 16 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   nro       82 non-null     int64  \n",
      " 1   sukup     82 non-null     int64  \n",
      " 2   ikä       82 non-null     int64  \n",
      " 3   perhe     82 non-null     int64  \n",
      " 4   koulutus  81 non-null     float64\n",
      " 5   palveluv  80 non-null     float64\n",
      " 6   palkka    82 non-null     int64  \n",
      " 7   johto     82 non-null     int64  \n",
      " 8   työtov    81 non-null     float64\n",
      " 9   työymp    82 non-null     int64  \n",
      " 10  palkkat   82 non-null     int64  \n",
      " 11  työteht   82 non-null     int64  \n",
      " 12  työterv   47 non-null     float64\n",
      " 13  lomaosa   20 non-null     float64\n",
      " 14  kuntosa   9 non-null      float64\n",
      " 15  hieroja   22 non-null     float64\n",
      "dtypes: float64(7), int64(9)\n",
      "memory usage: 10.4 KB\n"
     ]
    }
   ],
   "source": [
    "# Sarakkeiden otsikot, arvojen lukumäärät ja sarakkeiden tietotyypit\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pelkästään numeroarvoja sisältävät sarakkeet ovat kokonaislukuja (int) tai liukulukuja (float). Liukuluvun voit ajatella olevan käytännössä sama kuin desimaaliluku."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**unique**-funktion avulla on helppo huomata virheellisiä tai epäilyttäviä arvoja.\n",
    "\n",
    "Unique näyttää sarakkeen ainutkertaiset arvot listana. Esimerkiksi seuraavasta selviää, että 'työtov' (tyytyväisyys työtovereihin) sarakkeella on arvoja 2, 3, 4 ja 5 sekä yksi tai useampia puuttuvia arvoja (**nan**). Yksikään vastaajista ei siis ole ollut erittäin tyytymätön työtovereihin (arvo 1). \n",
    "\n",
    "Arvot tulostuvat siinä järjestyksessä kuin ne tulevat datassa vastaan."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 3.,  5.,  4.,  2., nan])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['työtov'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## for-silmukka\n",
    "\n",
    "**for**-silmukka on toistorakenne, joka osaa läpikäydä erilaisia luetteloja. Seuraavan solun for-silmukka käy läpi dataframen sarakkeet lukuun ottamatta nro-saraketta, joka poistetaan **drop**-funktiolla. Parametri **axis=1** määrittää läpi käytäväksi sarakkeet; ilman tätä parametria käytäisiin läpi dataframen rivit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sukup [1 2]\n",
      "ikä [38 29 30 36 24 31 49 55 40 33 39 35 58 53 42 26 47 44 43 56 21 45 59 37\n",
      " 28 50 32 51 22 34 27 41 25 61 20 52 46]\n",
      "perhe [1 2]\n",
      "koulutus [ 1.  2.  3.  4. nan]\n",
      "palveluv [22. 10.  7. 14.  4. 16.  0. 23. 21. 15. 12.  2. 17. 20. 13. 27.  1.  3.\n",
      " nan 24.  5.  9.  6. 35. 28. 18. 36. 19.  8.]\n",
      "palkka [3587 2963 1989 2144 2183 1910 2066 2768 2106 2651 2846 2808 3393 2691\n",
      " 5225 2729 2925 2457 4874 3510 4446 1521 2223 1949 2340 6278 1559 2027\n",
      " 2300 2534 1872 2261 2417 3119 2574 1715 5069 2495 3470 1598 1638 2612]\n",
      "johto [3 1 2 4 5]\n",
      "työtov [ 3.  5.  4.  2. nan]\n",
      "työymp [3 2 1 5 4]\n",
      "palkkat [3 1 2 4 5]\n",
      "työteht [3 2 4 1 5]\n",
      "työterv [nan  1.]\n",
      "lomaosa [nan  1.]\n",
      "kuntosa [nan  1.]\n",
      "hieroja [nan  1.]\n"
     ]
    }
   ],
   "source": [
    "# for-silmukalla käyn läpi kaikki sarakkeet paitsi 'nro'\n",
    "# drop poistaa oletuksena rivejä (axis=0), mutta haluan poistaa sarakkeita (axis=1)\n",
    "for sarake in df.drop('nro', axis=1):\n",
    "    print(sarake, df[sarake].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>koulutus</th>\n",
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       "      <th>työterv</th>\n",
       "      <th>lomaosa</th>\n",
       "      <th>kuntosa</th>\n",
       "      <th>hieroja</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6278</td>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5225</td>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>67</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5069</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    nro  sukup  ikä  perhe  koulutus  palveluv  palkka  johto  työtov  työymp  \\\n",
       "32   33      1   59      2       3.0      15.0    6278      4     4.0       5   \n",
       "16   17      1   26      1       4.0       2.0    5225      5     5.0       5   \n",
       "66   67      1   37      2       4.0       8.0    5069      3     4.0       3   \n",
       "\n",
       "    palkkat  työteht  työterv  lomaosa  kuntosa  hieroja  \n",
       "32        4        4      NaN      1.0      NaN      NaN  \n",
       "16        4        5      NaN      NaN      1.0      NaN  \n",
       "66        2        2      1.0      1.0      NaN      1.0  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# kolme riviä, joissa palkalla suurin arvo\n",
    "df.nlargest(3, 'palkka')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nro</th>\n",
       "      <th>sukup</th>\n",
       "      <th>ikä</th>\n",
       "      <th>perhe</th>\n",
       "      <th>koulutus</th>\n",
       "      <th>palveluv</th>\n",
       "      <th>palkka</th>\n",
       "      <th>johto</th>\n",
       "      <th>työtov</th>\n",
       "      <th>työymp</th>\n",
       "      <th>palkkat</th>\n",
       "      <th>työteht</th>\n",
       "      <th>työterv</th>\n",
       "      <th>lomaosa</th>\n",
       "      <th>kuntosa</th>\n",
       "      <th>hieroja</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1521</td>\n",
       "      <td>2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1559</td>\n",
       "      <td>2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>54</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1559</td>\n",
       "      <td>2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    nro  sukup  ikä  perhe  koulutus  palveluv  palkka  johto  työtov  työymp  \\\n",
       "25   26      1   26      1       2.0       3.0    1521      2     4.0       2   \n",
       "35   36      1   31      2       3.0       0.0    1559      2     4.0       3   \n",
       "53   54      1   25      1       2.0       1.0    1559      2     4.0       3   \n",
       "\n",
       "    palkkat  työteht  työterv  lomaosa  kuntosa  hieroja  \n",
       "25        1        3      1.0      NaN      1.0      1.0  \n",
       "35        1        3      1.0      NaN      NaN      NaN  \n",
       "53        1        2      1.0      NaN      NaN      NaN  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# kolme riviä, joissa palkalla pienin arvo \n",
    "df.nsmallest(3, 'palkka')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**value_counts**-funktio laskee ainutkertaisten arvojen frekvenssit eli esiintymiskertojen lukumäärät.\n",
    "\n",
    "Seuraavassa lasken frekvenssit kaikille muuttujille paitsi juoksevalle järjestysnumerolle, iälle ja palkalle. **sort_index()** järjestää arvot arvojen mukaiseen järjestykseen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sukup\n",
      "1    63\n",
      "2    19\n",
      "Name: count, dtype: int64\n",
      "perhe\n",
      "1    31\n",
      "2    51\n",
      "Name: count, dtype: int64\n",
      "koulutus\n",
      "1.0    27\n",
      "2.0    30\n",
      "3.0    22\n",
      "4.0     2\n",
      "Name: count, dtype: int64\n",
      "palveluv\n",
      "0.0     4\n",
      "1.0     9\n",
      "2.0     4\n",
      "3.0     3\n",
      "4.0     1\n",
      "5.0     1\n",
      "6.0     2\n",
      "7.0     7\n",
      "8.0     1\n",
      "9.0     1\n",
      "10.0    5\n",
      "12.0    2\n",
      "13.0    1\n",
      "14.0    3\n",
      "15.0    5\n",
      "16.0    4\n",
      "17.0    5\n",
      "18.0    2\n",
      "19.0    1\n",
      "20.0    3\n",
      "21.0    3\n",
      "22.0    4\n",
      "23.0    4\n",
      "24.0    1\n",
      "27.0    1\n",
      "28.0    1\n",
      "35.0    1\n",
      "36.0    1\n",
      "Name: count, dtype: int64\n",
      "johto\n",
      "1     7\n",
      "2    16\n",
      "3    30\n",
      "4    23\n",
      "5     6\n",
      "Name: count, dtype: int64\n",
      "työtov\n",
      "2.0     3\n",
      "3.0    16\n",
      "4.0    35\n",
      "5.0    27\n",
      "Name: count, dtype: int64\n",
      "työymp\n",
      "1     9\n",
      "2     9\n",
      "3    30\n",
      "4    23\n",
      "5    11\n",
      "Name: count, dtype: int64\n",
      "palkkat\n",
      "1    33\n",
      "2    19\n",
      "3    19\n",
      "4    10\n",
      "5     1\n",
      "Name: count, dtype: int64\n",
      "työteht\n",
      "1     5\n",
      "2    15\n",
      "3    29\n",
      "4    25\n",
      "5     8\n",
      "Name: count, dtype: int64\n",
      "työterv\n",
      "1.0    47\n",
      "Name: count, dtype: int64\n",
      "lomaosa\n",
      "1.0    20\n",
      "Name: count, dtype: int64\n",
      "kuntosa\n",
      "1.0    9\n",
      "Name: count, dtype: int64\n",
      "hieroja\n",
      "1.0    22\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "for muuttuja in df.drop(['nro', 'ikä', 'palkka'], axis=1):\n",
    "    print(df[muuttuja].value_counts().sort_index())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "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>nro</th>\n",
       "      <th>sukup</th>\n",
       "      <th>ikä</th>\n",
       "      <th>perhe</th>\n",
       "      <th>koulutus</th>\n",
       "      <th>palveluv</th>\n",
       "      <th>palkka</th>\n",
       "      <th>johto</th>\n",
       "      <th>työtov</th>\n",
       "      <th>työymp</th>\n",
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       "      <th>työterv</th>\n",
       "      <th>lomaosa</th>\n",
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       "      <th>hieroja</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>82.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>47.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>41.500000</td>\n",
       "      <td>1.231707</td>\n",
       "      <td>37.951220</td>\n",
       "      <td>1.621951</td>\n",
       "      <td>1.987654</td>\n",
       "      <td>12.175000</td>\n",
       "      <td>2563.878049</td>\n",
       "      <td>3.060976</td>\n",
       "      <td>4.061728</td>\n",
       "      <td>3.219512</td>\n",
       "      <td>2.109756</td>\n",
       "      <td>3.195122</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>23.815261</td>\n",
       "      <td>0.424519</td>\n",
       "      <td>9.773866</td>\n",
       "      <td>0.487884</td>\n",
       "      <td>0.844006</td>\n",
       "      <td>8.807038</td>\n",
       "      <td>849.350302</td>\n",
       "      <td>1.058155</td>\n",
       "      <td>0.826826</td>\n",
       "      <td>1.154961</td>\n",
       "      <td>1.111179</td>\n",
       "      <td>1.047502</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1521.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>21.250000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.750000</td>\n",
       "      <td>2027.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>41.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>37.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>2320.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>61.750000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>18.250000</td>\n",
       "      <td>2808.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>82.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>6278.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             nro      sukup        ikä      perhe   koulutus   palveluv  \\\n",
       "count  82.000000  82.000000  82.000000  82.000000  81.000000  80.000000   \n",
       "mean   41.500000   1.231707  37.951220   1.621951   1.987654  12.175000   \n",
       "std    23.815261   0.424519   9.773866   0.487884   0.844006   8.807038   \n",
       "min     1.000000   1.000000  20.000000   1.000000   1.000000   0.000000   \n",
       "25%    21.250000   1.000000  31.000000   1.000000   1.000000   3.750000   \n",
       "50%    41.500000   1.000000  37.500000   2.000000   2.000000  12.500000   \n",
       "75%    61.750000   1.000000  44.000000   2.000000   3.000000  18.250000   \n",
       "max    82.000000   2.000000  61.000000   2.000000   4.000000  36.000000   \n",
       "\n",
       "            palkka      johto     työtov     työymp    palkkat    työteht  \\\n",
       "count    82.000000  82.000000  81.000000  82.000000  82.000000  82.000000   \n",
       "mean   2563.878049   3.060976   4.061728   3.219512   2.109756   3.195122   \n",
       "std     849.350302   1.058155   0.826826   1.154961   1.111179   1.047502   \n",
       "min    1521.000000   1.000000   2.000000   1.000000   1.000000   1.000000   \n",
       "25%    2027.000000   2.000000   4.000000   3.000000   1.000000   3.000000   \n",
       "50%    2320.000000   3.000000   4.000000   3.000000   2.000000   3.000000   \n",
       "75%    2808.000000   4.000000   5.000000   4.000000   3.000000   4.000000   \n",
       "max    6278.000000   5.000000   5.000000   5.000000   5.000000   5.000000   \n",
       "\n",
       "       työterv  lomaosa  kuntosa  hieroja  \n",
       "count     47.0     20.0      9.0     22.0  \n",
       "mean       1.0      1.0      1.0      1.0  \n",
       "std        0.0      0.0      0.0      0.0  \n",
       "min        1.0      1.0      1.0      1.0  \n",
       "25%        1.0      1.0      1.0      1.0  \n",
       "50%        1.0      1.0      1.0      1.0  \n",
       "75%        1.0      1.0      1.0      1.0  \n",
       "max        1.0      1.0      1.0      1.0  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Tilastolliset tunnusluvut kannattaa myös vilkaista\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Luettelo muistiossa käytetyistä funktioista ja toiminnoista\n",
    "\n",
    "* **pd.read_excel()** datan lukeminen Excel-tiedostosta\n",
    "* **df.shape** datan rivien ja sarakkeiden lukumäärät\n",
    "* **pd.options.display.max_rows = None** dataframejen kaikkien rivien näyttäminen\n",
    "* **pd.options.display.max_columns = None** dataframejen kaikkien sarakkeiden näyttäminen\n",
    "* **df.head()** datan alkupää\n",
    "* **df.tail()** datan loppupää\n",
    "* **df.count()** sarakkeiden otsikot ja arvojen lukumäärät kussakin sarakkeessa\n",
    "* **df.isnull().sum()** puuttuvien arvojen lukumäärät kussakin sarakkeessa\n",
    "* **df.info()** sarakkeiden otsikot, arvojen lukumäärät ja sarakkeiden tietotyypit\n",
    "* **df['sarake'].unique()** nimetyn sarakkeen ainutkertaisten arvojen luettelo\n",
    "* **df.drop()** rivien tai sarakkeiden poistamiseen\n",
    "* **print()** näytölle tulostaminen\n",
    "* **df.nlargest()** n suurinta nimetyn sarakkeen suhteen\n",
    "* **df.nsmallest()** n pienintä nimetyn sarakkeen suhteen\n",
    "* **df['sarake'].value_counts()** arvojen esiintymiskertojen (frekvenssien) laskemiseen\n",
    "* **df.describe()** tilastolliset tunnusluvut\n",
    "\n",
    "\n",
    "* Lisäksi opittiin toistamaan samankaltaisia toimia **for**-silmukalla."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lisätietoa\n",
    "\n",
    "Data-analytiikka Pythonilla https://tilastoapu.wordpress.com/python/"
   ]
  }
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