dz_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 350,
   "id": "413cf38b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "pd.options.mode.chained_assignment = None"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9591d3da",
   "metadata": {},
   "source": [
    "# №1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "id": "fc90f71b",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_names_1 = []\n",
    "for i in range(10):\n",
    "    file_names_1.append(\"/home/nogaromo/Data/Students_info_\"+str(i)+\".csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "id": "7c5f3e46",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_all_1 = pd.concat((pd.read_csv(i) for i in file_names_1)).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "id": "e70349ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_names_2 = []\n",
    "for i in range(10):\n",
    "    file_names_2.append(\"/home/nogaromo/Data/Students_marks_\"+str(i)+\".csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "id": "241bad69",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_all_2 = pd.concat((pd.read_csv(i) for i in file_names_2)).reset_index(drop=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "id": "5fa1580d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>index</th>\n",
       "      <th>gender</th>\n",
       "      <th>race/ethnicity</th>\n",
       "      <th>parental level of education</th>\n",
       "      <th>lunch</th>\n",
       "      <th>test preparation course</th>\n",
       "      <th>group</th>\n",
       "      <th>index</th>\n",
       "      <th>math score</th>\n",
       "      <th>reading score</th>\n",
       "      <th>writing score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>0</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>group1</td>\n",
       "      <td>1</td>\n",
       "      <td>69</td>\n",
       "      <td>90</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>master's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>2</td>\n",
       "      <td>90</td>\n",
       "      <td>95</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>group A</td>\n",
       "      <td>associate's degree</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>3</td>\n",
       "      <td>47</td>\n",
       "      <td>57</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>4</td>\n",
       "      <td>76</td>\n",
       "      <td>78</td>\n",
       "      <td>75</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>995</td>\n",
       "      <td>female</td>\n",
       "      <td>group E</td>\n",
       "      <td>master's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>group10</td>\n",
       "      <td>995</td>\n",
       "      <td>88</td>\n",
       "      <td>99</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>996</td>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>high school</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>group10</td>\n",
       "      <td>996</td>\n",
       "      <td>62</td>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>997</td>\n",
       "      <td>female</td>\n",
       "      <td>group C</td>\n",
       "      <td>high school</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>completed</td>\n",
       "      <td>group10</td>\n",
       "      <td>997</td>\n",
       "      <td>59</td>\n",
       "      <td>71</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>998</td>\n",
       "      <td>female</td>\n",
       "      <td>group D</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>group10</td>\n",
       "      <td>998</td>\n",
       "      <td>68</td>\n",
       "      <td>78</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>999</td>\n",
       "      <td>female</td>\n",
       "      <td>group D</td>\n",
       "      <td>some college</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>group10</td>\n",
       "      <td>999</td>\n",
       "      <td>77</td>\n",
       "      <td>86</td>\n",
       "      <td>86</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index  gender race/ethnicity parental level of education         lunch  \\\n",
       "0        0  female        group B           bachelor's degree      standard   \n",
       "1        1  female        group C                some college      standard   \n",
       "2        2  female        group B             master's degree      standard   \n",
       "3        3    male        group A          associate's degree  free/reduced   \n",
       "4        4    male        group C                some college      standard   \n",
       "..     ...     ...            ...                         ...           ...   \n",
       "995    995  female        group E             master's degree      standard   \n",
       "996    996    male        group C                 high school  free/reduced   \n",
       "997    997  female        group C                 high school  free/reduced   \n",
       "998    998  female        group D                some college      standard   \n",
       "999    999  female        group D                some college  free/reduced   \n",
       "\n",
       "    test preparation course    group  index  math score  reading score  \\\n",
       "0                      none   group1      0          72             72   \n",
       "1                 completed   group1      1          69             90   \n",
       "2                      none   group1      2          90             95   \n",
       "3                      none   group1      3          47             57   \n",
       "4                      none   group1      4          76             78   \n",
       "..                      ...      ...    ...         ...            ...   \n",
       "995               completed  group10    995          88             99   \n",
       "996                    none  group10    996          62             55   \n",
       "997               completed  group10    997          59             71   \n",
       "998               completed  group10    998          68             78   \n",
       "999                    none  group10    999          77             86   \n",
       "\n",
       "     writing score  \n",
       "0               74  \n",
       "1               88  \n",
       "2               93  \n",
       "3               44  \n",
       "4               75  \n",
       "..             ...  \n",
       "995             95  \n",
       "996             55  \n",
       "997             65  \n",
       "998             77  \n",
       "999             86  \n",
       "\n",
       "[1000 rows x 11 columns]"
      ]
     },
     "execution_count": 355,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat([data_all_1, data_all_2], axis=1)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03f9c489",
   "metadata": {},
   "source": [
    "# №2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "id": "c391a656",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop('index', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "id": "82dbeb82",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gender</th>\n",
       "      <th>race/ethnicity</th>\n",
       "      <th>parental level of education</th>\n",
       "      <th>lunch</th>\n",
       "      <th>test preparation course</th>\n",
       "      <th>group</th>\n",
       "      <th>math score</th>\n",
       "      <th>reading score</th>\n",
       "      <th>writing score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>female</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>group1</td>\n",
       "      <td>69</td>\n",
       "      <td>90</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>master's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>90</td>\n",
       "      <td>95</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>male</td>\n",
       "      <td>group A</td>\n",
       "      <td>associate's degree</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>47</td>\n",
       "      <td>57</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>76</td>\n",
       "      <td>78</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>associate's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>71</td>\n",
       "      <td>83</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>group1</td>\n",
       "      <td>88</td>\n",
       "      <td>95</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>male</td>\n",
       "      <td>group B</td>\n",
       "      <td>some college</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>40</td>\n",
       "      <td>43</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>male</td>\n",
       "      <td>group D</td>\n",
       "      <td>high school</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>completed</td>\n",
       "      <td>group1</td>\n",
       "      <td>64</td>\n",
       "      <td>64</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>high school</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>38</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender race/ethnicity parental level of education         lunch  \\\n",
       "0  female        group B           bachelor's degree      standard   \n",
       "1  female        group C                some college      standard   \n",
       "2  female        group B             master's degree      standard   \n",
       "3    male        group A          associate's degree  free/reduced   \n",
       "4    male        group C                some college      standard   \n",
       "5  female        group B          associate's degree      standard   \n",
       "6  female        group B                some college      standard   \n",
       "7    male        group B                some college  free/reduced   \n",
       "8    male        group D                 high school  free/reduced   \n",
       "9  female        group B                 high school  free/reduced   \n",
       "\n",
       "  test preparation course   group  math score  reading score  writing score  \n",
       "0                    none  group1          72             72             74  \n",
       "1               completed  group1          69             90             88  \n",
       "2                    none  group1          90             95             93  \n",
       "3                    none  group1          47             57             44  \n",
       "4                    none  group1          76             78             75  \n",
       "5                    none  group1          71             83             78  \n",
       "6               completed  group1          88             95             92  \n",
       "7                    none  group1          40             43             39  \n",
       "8               completed  group1          64             64             67  \n",
       "9                    none  group1          38             60             50  "
      ]
     },
     "execution_count": 357,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d68698b5",
   "metadata": {},
   "source": [
    "# №3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "id": "b6a6b13d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1000, 9)"
      ]
     },
     "execution_count": 358,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1846aeb6",
   "metadata": {},
   "source": [
    "# №4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "id": "9c4ebe28",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>math score</th>\n",
       "      <th>reading score</th>\n",
       "      <th>writing score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.00000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>66.08900</td>\n",
       "      <td>69.169000</td>\n",
       "      <td>68.054000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>15.16308</td>\n",
       "      <td>14.600192</td>\n",
       "      <td>15.195657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>57.00000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>57.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>66.00000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>69.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>77.00000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>79.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>100.00000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       math score  reading score  writing score\n",
       "count  1000.00000    1000.000000    1000.000000\n",
       "mean     66.08900      69.169000      68.054000\n",
       "std      15.16308      14.600192      15.195657\n",
       "min       0.00000      17.000000      10.000000\n",
       "25%      57.00000      59.000000      57.750000\n",
       "50%      66.00000      70.000000      69.000000\n",
       "75%      77.00000      79.000000      79.000000\n",
       "max     100.00000     100.000000     100.000000"
      ]
     },
     "execution_count": 359,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42a0ecd0",
   "metadata": {},
   "source": [
    "# №5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "id": "57f912ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 360,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae752d3f",
   "metadata": {},
   "source": [
    "# №6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "id": "f04435bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " mean math score: 66.089 \n",
      " mean reading score: 69.169 \n",
      " mean writing score: 68.054\n"
     ]
    }
   ],
   "source": [
    "print(' mean math score: '+str(df['math score'].mean()),'\\n',\n",
    "    'mean reading score: '+str(df['reading score'].mean()),'\\n',\n",
    "    'mean writing score: '+str(df['writing score'].mean()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc545973",
   "metadata": {},
   "source": [
    "# №7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "id": "e290ee75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "math score       64.077882\n",
       "reading score    66.534268\n",
       "writing score    64.504673\n",
       "dtype: float64"
      ]
     },
     "execution_count": 362,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['test preparation course']=='none'].mean(numeric_only=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 363,
   "id": "34ec5610",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "math score       69.695531\n",
       "reading score    73.893855\n",
       "writing score    74.418994\n",
       "dtype: float64"
      ]
     },
     "execution_count": 363,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['test preparation course']=='completed'].mean(numeric_only=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d38fc9b2",
   "metadata": {},
   "source": [
    "# №8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "id": "8be44a15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['standard', 'free/reduced'], dtype=object)"
      ]
     },
     "execution_count": 364,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['lunch'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fcae785",
   "metadata": {},
   "source": [
    "# №9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 365,
   "id": "b7a2f3eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.rename(columns={\"parental level of education\": \"education\", \"test preparation course\": \"test preparation\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 388,
   "id": "13ef598b",
   "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>gender</th>\n",
       "      <th>race/ethnicity</th>\n",
       "      <th>education</th>\n",
       "      <th>lunch</th>\n",
       "      <th>test preparation</th>\n",
       "      <th>group</th>\n",
       "      <th>math score</th>\n",
       "      <th>reading score</th>\n",
       "      <th>writing score</th>\n",
       "      <th>math_PassStatus</th>\n",
       "      <th>reading_PassStatus</th>\n",
       "      <th>writing_PassStatus</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>74</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>female</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>group1</td>\n",
       "      <td>69</td>\n",
       "      <td>90</td>\n",
       "      <td>88</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>master's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>90</td>\n",
       "      <td>95</td>\n",
       "      <td>93</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>male</td>\n",
       "      <td>group A</td>\n",
       "      <td>associate's degree</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>47</td>\n",
       "      <td>57</td>\n",
       "      <td>44</td>\n",
       "      <td>F</td>\n",
       "      <td>P</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>76</td>\n",
       "      <td>78</td>\n",
       "      <td>75</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender race/ethnicity           education         lunch test preparation  \\\n",
       "0  female        group B   bachelor's degree      standard             none   \n",
       "1  female        group C        some college      standard        completed   \n",
       "2  female        group B     master's degree      standard             none   \n",
       "3    male        group A  associate's degree  free/reduced             none   \n",
       "4    male        group C        some college      standard             none   \n",
       "\n",
       "    group  math score  reading score  writing score math_PassStatus  \\\n",
       "0  group1          72             72             74               P   \n",
       "1  group1          69             90             88               P   \n",
       "2  group1          90             95             93               P   \n",
       "3  group1          47             57             44               F   \n",
       "4  group1          76             78             75               P   \n",
       "\n",
       "  reading_PassStatus writing_PassStatus  \n",
       "0                  P                  P  \n",
       "1                  P                  P  \n",
       "2                  P                  P  \n",
       "3                  P                  F  \n",
       "4                  P                  P  "
      ]
     },
     "execution_count": 388,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "029ef9d8",
   "metadata": {},
   "source": [
    "# №10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 367,
   "id": "114e693a",
   "metadata": {},
   "outputs": [],
   "source": [
    "passmark = 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "id": "fc194722",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.865"
      ]
     },
     "execution_count": 368,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['math score'] >= passmark].shape[0] / df['math score'].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 369,
   "id": "771c8944",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.33"
      ]
     },
     "execution_count": 369,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['math score'] >= passmark) & (df['test preparation'] == 'completed')].shape[0] / df['math score'].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 370,
   "id": "6d0ece75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.264"
      ]
     },
     "execution_count": 370,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['math score'] >= passmark) & (df['test preparation'] == 'none') & (df['gender'] == 'female')].shape[0] / df['math score'].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec40742d",
   "metadata": {},
   "source": [
    "# №11"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 371,
   "id": "e4e2489f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.26 ms, sys: 0 ns, total: 1.26 ms\n",
      "Wall time: 1.12 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "race/ethnicity\n",
       "group A    64.674157\n",
       "group B    67.352632\n",
       "group C    69.103448\n",
       "group D    70.030534\n",
       "group E    73.028571\n",
       "Name: reading score, dtype: float64"
      ]
     },
     "execution_count": 371,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "df.groupby(['race/ethnicity']).mean()['reading score']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 372,
   "id": "c01a7123",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 4.79 ms, sys: 0 ns, total: 4.79 ms\n",
      "Wall time: 4.6 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "education\n",
       "associate's degree    35\n",
       "bachelor's degree     38\n",
       "high school           15\n",
       "master's degree       46\n",
       "some college          19\n",
       "some high school      10\n",
       "Name: writing score, dtype: int64"
      ]
     },
     "execution_count": 372,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "df.groupby(['education']).min()['writing score']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "702f8184",
   "metadata": {},
   "source": [
    "# №12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 519,
   "id": "857ef182",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "64.67415730337079 67.35263157894737 69.10344827586206 70.03053435114504 73.02857142857142\n",
      "CPU times: user 1.16 ms, sys: 2 ms, total: 3.16 ms\n",
      "Wall time: 2.95 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "group_a = np.array(df[(df['race/ethnicity']=='group A')]['reading score'])\n",
    "group_b = np.array(df[(df['race/ethnicity']=='group B')]['reading score'])\n",
    "group_c = np.array(df[(df['race/ethnicity']=='group C')]['reading score'])\n",
    "group_d = np.array(df[(df['race/ethnicity']=='group D')]['reading score'])\n",
    "group_e = np.array(df[(df['race/ethnicity']=='group E')]['reading score'])\n",
    "mean_a = 0\n",
    "mean_b = 0\n",
    "mean_c = 0\n",
    "mean_d = 0\n",
    "mean_e = 0\n",
    "for i in range(len(group_a)):\n",
    "    mean_a += group_a[i]\n",
    "mean_a = mean_a / len(group_a)\n",
    "\n",
    "for i in range(len(group_b)):\n",
    "    mean_b += group_b[i]\n",
    "mean_b = mean_b / len(group_b)\n",
    "\n",
    "for i in range(len(group_c)):\n",
    "    mean_c += group_c[i]\n",
    "mean_c = mean_c / len(group_c)\n",
    "\n",
    "for i in range(len(group_d)):\n",
    "    mean_d += group_d[i]\n",
    "mean_d = mean_d / len(group_d)\n",
    "\n",
    "for i in range(len(group_e)):\n",
    "    mean_e += group_e[i]\n",
    "mean_e = mean_e / len(group_e)\n",
    "print(mean_a, mean_b, mean_c, mean_d, mean_e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 520,
   "id": "1b6c9504",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "35 38 15 46 19 10\n",
      "CPU times: user 3.14 ms, sys: 45 µs, total: 3.18 ms\n",
      "Wall time: 3.3 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "group_1 = np.array(df[(df['education']==\"associate's degree\")]['writing score'])\n",
    "group_2 = np.array(df[(df['education']==\"bachelor's degree\")]['writing score'])\n",
    "group_3 = np.array(df[(df['education']==\"high school\")]['writing score'])\n",
    "group_4 = np.array(df[(df['education']==\"master's degree\")]['writing score'])\n",
    "group_5 = np.array(df[(df['education']==\"some college\")]['writing score'])\n",
    "group_6 = np.array(df[(df['education']==\"some high school\")]['writing score'])\n",
    "print(min(group_1), min(group_2), min(group_3), min(group_4), min(group_5), min(group_6))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ccb9be96",
   "metadata": {},
   "source": [
    "# №13"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 374,
   "id": "3102ac3e",
   "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></th>\n",
       "      <th>math score</th>\n",
       "      <th>reading score</th>\n",
       "      <th>writing score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gender</th>\n",
       "      <th>education</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">female</th>\n",
       "      <th>associate's degree</th>\n",
       "      <td>65.250000</td>\n",
       "      <td>74.120690</td>\n",
       "      <td>74.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bachelor's degree</th>\n",
       "      <td>68.349206</td>\n",
       "      <td>77.285714</td>\n",
       "      <td>78.380952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>high school</th>\n",
       "      <td>59.351064</td>\n",
       "      <td>68.202128</td>\n",
       "      <td>66.691489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>master's degree</th>\n",
       "      <td>66.500000</td>\n",
       "      <td>76.805556</td>\n",
       "      <td>77.638889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>some college</th>\n",
       "      <td>65.406780</td>\n",
       "      <td>73.550847</td>\n",
       "      <td>74.050847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>some high school</th>\n",
       "      <td>59.296703</td>\n",
       "      <td>69.109890</td>\n",
       "      <td>68.285714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">male</th>\n",
       "      <th>associate's degree</th>\n",
       "      <td>70.764151</td>\n",
       "      <td>67.433962</td>\n",
       "      <td>65.405660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bachelor's degree</th>\n",
       "      <td>70.581818</td>\n",
       "      <td>68.090909</td>\n",
       "      <td>67.654545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>high school</th>\n",
       "      <td>64.705882</td>\n",
       "      <td>61.480392</td>\n",
       "      <td>58.539216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>master's degree</th>\n",
       "      <td>74.826087</td>\n",
       "      <td>73.130435</td>\n",
       "      <td>72.608696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>some college</th>\n",
       "      <td>69.009259</td>\n",
       "      <td>64.990741</td>\n",
       "      <td>63.148148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>some high school</th>\n",
       "      <td>67.840909</td>\n",
       "      <td>64.693182</td>\n",
       "      <td>61.375000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           math score  reading score  writing score\n",
       "gender education                                                   \n",
       "female associate's degree   65.250000      74.120690      74.000000\n",
       "       bachelor's degree    68.349206      77.285714      78.380952\n",
       "       high school          59.351064      68.202128      66.691489\n",
       "       master's degree      66.500000      76.805556      77.638889\n",
       "       some college         65.406780      73.550847      74.050847\n",
       "       some high school     59.296703      69.109890      68.285714\n",
       "male   associate's degree   70.764151      67.433962      65.405660\n",
       "       bachelor's degree    70.581818      68.090909      67.654545\n",
       "       high school          64.705882      61.480392      58.539216\n",
       "       master's degree      74.826087      73.130435      72.608696\n",
       "       some college         69.009259      64.990741      63.148148\n",
       "       some high school     67.840909      64.693182      61.375000"
      ]
     },
     "execution_count": 374,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = pd.pivot_table(data=df, index=['gender', 'education'], aggfunc={'math score': np.mean,\n",
    "                                                                        'reading score': np.mean,\n",
    "                                                                        'writing score': np.mean})\n",
    "grouped"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec3ff32b",
   "metadata": {},
   "source": [
    "# №14 and №15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 459,
   "id": "3d30e694",
   "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>gender</th>\n",
       "      <th>race/ethnicity</th>\n",
       "      <th>education</th>\n",
       "      <th>lunch</th>\n",
       "      <th>test preparation</th>\n",
       "      <th>group</th>\n",
       "      <th>math score</th>\n",
       "      <th>reading score</th>\n",
       "      <th>writing score</th>\n",
       "      <th>math_PassStatus</th>\n",
       "      <th>reading_PassStatus</th>\n",
       "      <th>writing_PassStatus</th>\n",
       "      <th>OverAll_PassStatus</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>74</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>female</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>group1</td>\n",
       "      <td>69</td>\n",
       "      <td>90</td>\n",
       "      <td>88</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>master's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>90</td>\n",
       "      <td>95</td>\n",
       "      <td>93</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>male</td>\n",
       "      <td>group A</td>\n",
       "      <td>associate's degree</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>47</td>\n",
       "      <td>57</td>\n",
       "      <td>44</td>\n",
       "      <td>F</td>\n",
       "      <td>P</td>\n",
       "      <td>F</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>76</td>\n",
       "      <td>78</td>\n",
       "      <td>75</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender race/ethnicity           education         lunch test preparation  \\\n",
       "0  female        group B   bachelor's degree      standard             none   \n",
       "1  female        group C        some college      standard        completed   \n",
       "2  female        group B     master's degree      standard             none   \n",
       "3    male        group A  associate's degree  free/reduced             none   \n",
       "4    male        group C        some college      standard             none   \n",
       "\n",
       "    group  math score  reading score  writing score math_PassStatus  \\\n",
       "0  group1          72             72             74               P   \n",
       "1  group1          69             90             88               P   \n",
       "2  group1          90             95             93               P   \n",
       "3  group1          47             57             44               F   \n",
       "4  group1          76             78             75               P   \n",
       "\n",
       "  reading_PassStatus writing_PassStatus OverAll_PassStatus  \n",
       "0                  P                  P                  P  \n",
       "1                  P                  P                  P  \n",
       "2                  P                  P                  P  \n",
       "3                  P                  F                  F  \n",
       "4                  P                  P                  P  "
      ]
     },
     "execution_count": 459,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def func_14_15(a, df, passmark):\n",
    "    df[a+'_PassStatus'] = np.zeros(df.shape[0])\n",
    "    for i in range(df.shape[0]):\n",
    "        if df[a +' score'][i] < passmark:\n",
    "            df[a +'_PassStatus'][i] = 'F'\n",
    "            df['OverAll_PassStatus'][i] = 'F'\n",
    "        else:\n",
    "            df[a +'_PassStatus'][i] = 'P'\n",
    "    return df[a +'_PassStatus']\n",
    "\n",
    "\n",
    "df['OverAll_PassStatus'] = 'P'\n",
    "func_14_15('math', df, passmark)\n",
    "func_14_15('reading', df, passmark)\n",
    "func_14_15('writing', df, passmark)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 460,
   "id": "7f956ba6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "math test passed: 865 \n",
      " reading test passed: 910 \n",
      " writing test passed: 886 \n",
      "\n",
      "math test not passed: 135 \n",
      " reading test not passed: 90 \n",
      " writing test not passed: 114 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('math test passed: '+ str(df[df['math_PassStatus']=='P'].shape[0]), '\\n',\n",
    "      'reading test passed: '+ str(df[df['reading_PassStatus']=='P'].shape[0]), '\\n',\n",
    "      'writing test passed: '+ str(df[df['writing_PassStatus']=='P'].shape[0]), '\\n'\n",
    "     )\n",
    "print('math test not passed: '+ str(df.shape[0]-df[df['math_PassStatus']=='P'].shape[0]), '\\n',\n",
    "     'reading test not passed: '+ str(df.shape[0]-df[df['reading_PassStatus']=='P'].shape[0]), '\\n',\n",
    "      'writing test not passed: '+ str(df.shape[0]-df[df['writing_PassStatus']=='P'].shape[0]), '\\n'\n",
    "     )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65c73237",
   "metadata": {},
   "source": [
    "# №15(print)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 461,
   "id": "bc884264",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "passed all tests: 812\n"
     ]
    }
   ],
   "source": [
    "print('passed all tests: ' + str(df[df['OverAll_PassStatus']=='P'].shape[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5639a143",
   "metadata": {},
   "source": [
    "# №16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 493,
   "id": "8ad450f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "C          261\n",
       "D          256\n",
       "E          182\n",
       "B          146\n",
       "F(Fail)    103\n",
       "A           52\n",
       "Name: Grade, dtype: int64"
      ]
     },
     "execution_count": 493,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def GetGrade(average_grade):\n",
    "    for i in range(average_grade.shape[0]):\n",
    "        if average_grade[i] >= 90:\n",
    "            df['Grade'][i] = 'A'\n",
    "        if average_grade[i] < 90 and average_grade[i]>= 80:\n",
    "            df['Grade'][i] = 'B'\n",
    "        if average_grade[i] < 80 and average_grade[i]>= 70:\n",
    "            df['Grade'][i] = 'C'\n",
    "        if average_grade[i] < 70 and average_grade[i]>= 60:\n",
    "            df['Grade'][i] = 'D'\n",
    "        if average_grade[i] < 60 and average_grade[i]>= 50:\n",
    "            df['Grade'][i] = 'E'\n",
    "        if average_grade[i] < 50:\n",
    "            df['Grade'][i] = 'F(Fail)'\n",
    "    return df['Grade']\n",
    "\n",
    "df['Grade'] = ''\n",
    "average_grade = (df['math score'] + df['reading score'] + df['writing score']) / 3\n",
    "GetGrade(average_grade)\n",
    "df['Grade'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 521,
   "id": "5671aca4",
   "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>gender</th>\n",
       "      <th>race/ethnicity</th>\n",
       "      <th>education</th>\n",
       "      <th>lunch</th>\n",
       "      <th>test preparation</th>\n",
       "      <th>group</th>\n",
       "      <th>math score</th>\n",
       "      <th>reading score</th>\n",
       "      <th>writing score</th>\n",
       "      <th>math_PassStatus</th>\n",
       "      <th>reading_PassStatus</th>\n",
       "      <th>writing_PassStatus</th>\n",
       "      <th>OverAll_PassStatus</th>\n",
       "      <th>Grade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>bachelor's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>72</td>\n",
       "      <td>72</td>\n",
       "      <td>74</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>female</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>completed</td>\n",
       "      <td>group1</td>\n",
       "      <td>69</td>\n",
       "      <td>90</td>\n",
       "      <td>88</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>female</td>\n",
       "      <td>group B</td>\n",
       "      <td>master's degree</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>90</td>\n",
       "      <td>95</td>\n",
       "      <td>93</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>male</td>\n",
       "      <td>group A</td>\n",
       "      <td>associate's degree</td>\n",
       "      <td>free/reduced</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>47</td>\n",
       "      <td>57</td>\n",
       "      <td>44</td>\n",
       "      <td>F</td>\n",
       "      <td>P</td>\n",
       "      <td>F</td>\n",
       "      <td>F</td>\n",
       "      <td>F(Fail)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>male</td>\n",
       "      <td>group C</td>\n",
       "      <td>some college</td>\n",
       "      <td>standard</td>\n",
       "      <td>none</td>\n",
       "      <td>group1</td>\n",
       "      <td>76</td>\n",
       "      <td>78</td>\n",
       "      <td>75</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>P</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   gender race/ethnicity           education         lunch test preparation  \\\n",
       "0  female        group B   bachelor's degree      standard             none   \n",
       "1  female        group C        some college      standard        completed   \n",
       "2  female        group B     master's degree      standard             none   \n",
       "3    male        group A  associate's degree  free/reduced             none   \n",
       "4    male        group C        some college      standard             none   \n",
       "\n",
       "    group  math score  reading score  writing score math_PassStatus  \\\n",
       "0  group1          72             72             74               P   \n",
       "1  group1          69             90             88               P   \n",
       "2  group1          90             95             93               P   \n",
       "3  group1          47             57             44               F   \n",
       "4  group1          76             78             75               P   \n",
       "\n",
       "  reading_PassStatus writing_PassStatus OverAll_PassStatus    Grade  \n",
       "0                  P                  P                  P        C  \n",
       "1                  P                  P                  P        B  \n",
       "2                  P                  P                  P        A  \n",
       "3                  P                  F                  F  F(Fail)  \n",
       "4                  P                  P                  P        C  "
      ]
     },
     "execution_count": 521,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "44420aea",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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