PyCitySchools_practice.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "529dedf1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add the Pandas dependency.\n",
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2d08a59d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Files to load\n",
    "school_data_to_load = os.path.join(\"Resources\", \"schools_complete.csv\")\n",
    "student_data_to_load = os.path.join(\"Resources\", \"students_complete.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bd8bcf4e",
   "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>School ID</th>\n",
       "      <th>school_name</th>\n",
       "      <th>type</th>\n",
       "      <th>size</th>\n",
       "      <th>budget</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>District</td>\n",
       "      <td>2917</td>\n",
       "      <td>1910635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Figueroa High School</td>\n",
       "      <td>District</td>\n",
       "      <td>2949</td>\n",
       "      <td>1884411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Shelton High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1761</td>\n",
       "      <td>1056600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Hernandez High School</td>\n",
       "      <td>District</td>\n",
       "      <td>4635</td>\n",
       "      <td>3022020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Griffin High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1468</td>\n",
       "      <td>917500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>Wilson High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>2283</td>\n",
       "      <td>1319574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>Cabrera High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1858</td>\n",
       "      <td>1081356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>Bailey High School</td>\n",
       "      <td>District</td>\n",
       "      <td>4976</td>\n",
       "      <td>3124928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>Holden High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>427</td>\n",
       "      <td>248087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>Pena High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>962</td>\n",
       "      <td>585858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>Wright High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1800</td>\n",
       "      <td>1049400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>Rodriguez High School</td>\n",
       "      <td>District</td>\n",
       "      <td>3999</td>\n",
       "      <td>2547363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>Johnson High School</td>\n",
       "      <td>District</td>\n",
       "      <td>4761</td>\n",
       "      <td>3094650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>Ford High School</td>\n",
       "      <td>District</td>\n",
       "      <td>2739</td>\n",
       "      <td>1763916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>Thomas High School</td>\n",
       "      <td>Charter</td>\n",
       "      <td>1635</td>\n",
       "      <td>1043130</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    School ID            school_name      type  size   budget\n",
       "0           0      Huang High School  District  2917  1910635\n",
       "1           1   Figueroa High School  District  2949  1884411\n",
       "2           2    Shelton High School   Charter  1761  1056600\n",
       "3           3  Hernandez High School  District  4635  3022020\n",
       "4           4    Griffin High School   Charter  1468   917500\n",
       "5           5     Wilson High School   Charter  2283  1319574\n",
       "6           6    Cabrera High School   Charter  1858  1081356\n",
       "7           7     Bailey High School  District  4976  3124928\n",
       "8           8     Holden High School   Charter   427   248087\n",
       "9           9       Pena High School   Charter   962   585858\n",
       "10         10     Wright High School   Charter  1800  1049400\n",
       "11         11  Rodriguez High School  District  3999  2547363\n",
       "12         12    Johnson High School  District  4761  3094650\n",
       "13         13       Ford High School  District  2739  1763916\n",
       "14         14     Thomas High School   Charter  1635  1043130"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the school data file and store it in a Pandas DataFrame.\n",
    "school_data_df = pd.read_csv(school_data_to_load)\n",
    "school_data_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "badbe5fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Student ID</th>\n",
       "      <th>student_name</th>\n",
       "      <th>gender</th>\n",
       "      <th>grade</th>\n",
       "      <th>school_name</th>\n",
       "      <th>reading_score</th>\n",
       "      <th>math_score</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Paul Bradley</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>66</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Victor Smith</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>94</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Kevin Rodriguez</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>90</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Richard Scott</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>67</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Bonnie Ray</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>97</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   Student ID     student_name gender grade        school_name  reading_score  \\\n",
       "0           0     Paul Bradley      M   9th  Huang High School             66   \n",
       "1           1     Victor Smith      M  12th  Huang High School             94   \n",
       "2           2  Kevin Rodriguez      M  12th  Huang High School             90   \n",
       "3           3    Richard Scott      M  12th  Huang High School             67   \n",
       "4           4       Bonnie Ray      F   9th  Huang High School             97   \n",
       "\n",
       "   math_score  \n",
       "0          79  \n",
       "1          61  \n",
       "2          60  \n",
       "3          58  \n",
       "4          84  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the student data file and store it in a Pandas DataFrame.\n",
    "student_data_df = pd.read_csv(student_data_to_load)\n",
    "student_data_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "104a3b22",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Determine if there are any missing values in the school data.\n",
    "# school_data_df.count()\n",
    "\n",
    "# Determine if there are any missing values in the school data.\n",
    "# school_data_df.isnull()\n",
    "\n",
    "# Determine if there are not any missing values in the school data.\n",
    "# school_data_df.notnull()\n",
    "\n",
    "# Determine if there are not any missing values in the student data.\n",
    "# student_data_df.notnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1d8adeef",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Determine if there are any missing values in the student data.\n",
    "# student_data_df.count()\n",
    "\n",
    "# Determine if there are any missing values in the student data.\n",
    "# student_data_df.isnull()\n",
    "\n",
    "# Determine if there are any missing values in the student data.\n",
    "# student_data_df.isnull().sum()\n",
    "\n",
    "# Determine if there are not any missing values in the student data.\n",
    "# student_data_df.notnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "611e2317",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Determine data types for the school DataFrame.\n",
    "# school_data_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "662071e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Determine data types for the student DataFrame.\n",
    "# student_data_df.dtypes\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0a6fd6cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add each prefix and suffix to remove to a list.\n",
    "prefixes_suffixes = [\"Dr. \", \"Mr. \",\"Ms. \", \"Mrs. \", \"Miss \", \" MD\", \" DDS\", \" DVM\", \" PhD\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9b2aeebd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/dv/ftpldl3d4gl2lk3hb5gz96b00000gn/T/ipykernel_36577/3790455543.py:3: FutureWarning: The default value of regex will change from True to False in a future version.\n",
      "  student_data_df[\"student_name\"] = student_data_df[\"student_name\"].str.replace(word,\"\")\n"
     ]
    }
   ],
   "source": [
    "# Iterate through the words in the \"prefixes_suffixes\" list and replace them with an empty space, \"\".\n",
    "for word in prefixes_suffixes:\n",
    "    student_data_df[\"student_name\"] = student_data_df[\"student_name\"].str.replace(word,\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "18226194",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Student ID</th>\n",
       "      <th>student_name</th>\n",
       "      <th>gender</th>\n",
       "      <th>grade</th>\n",
       "      <th>school_name</th>\n",
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       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Paul Bradley</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>66</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Victor Smith</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>94</td>\n",
       "      <td>61</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Kevin Rodriguez</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>90</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Richard Scott</td>\n",
       "      <td>M</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>67</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Bonnie Ray</td>\n",
       "      <td>F</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>97</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>Bryan Miranda</td>\n",
       "      <td>M</td>\n",
       "      <td>9th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>Sheena Carter</td>\n",
       "      <td>F</td>\n",
       "      <td>11th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>82</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>Nicole Baker</td>\n",
       "      <td>F</td>\n",
       "      <td>12th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>96</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>Michael Roth</td>\n",
       "      <td>M</td>\n",
       "      <td>10th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>95</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>Matthew Greene</td>\n",
       "      <td>M</td>\n",
       "      <td>10th</td>\n",
       "      <td>Huang High School</td>\n",
       "      <td>96</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Student ID     student_name gender grade        school_name  reading_score  \\\n",
       "0           0     Paul Bradley      M   9th  Huang High School             66   \n",
       "1           1     Victor Smith      M  12th  Huang High School             94   \n",
       "2           2  Kevin Rodriguez      M  12th  Huang High School             90   \n",
       "3           3    Richard Scott      M  12th  Huang High School             67   \n",
       "4           4       Bonnie Ray      F   9th  Huang High School             97   \n",
       "5           5    Bryan Miranda      M   9th  Huang High School             94   \n",
       "6           6    Sheena Carter      F  11th  Huang High School             82   \n",
       "7           7     Nicole Baker      F  12th  Huang High School             96   \n",
       "8           8     Michael Roth      M  10th  Huang High School             95   \n",
       "9           9   Matthew Greene      M  10th  Huang High School             96   \n",
       "\n",
       "   math_score  \n",
       "0          79  \n",
       "1          61  \n",
       "2          60  \n",
       "3          58  \n",
       "4          84  \n",
       "5          94  \n",
       "6          80  \n",
       "7          69  \n",
       "8          87  \n",
       "9          84  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "student_data_df.head(10)\n"
   ]
  }
 ],
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