Day 18 - 50 Days of  Data Analysis .ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "371676ca",
   "metadata": {},
   "source": [
    "## 1.\n",
    "\n",
    "#### Import the running_data using pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f88197e1",
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "        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>Name</th>\n",
       "      <th>Distance (km)</th>\n",
       "      <th>Time (hours)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Wendy</td>\n",
       "      <td>9.10</td>\n",
       "      <td>4.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Yara</td>\n",
       "      <td>8.61</td>\n",
       "      <td>4.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Grace</td>\n",
       "      <td>7.17</td>\n",
       "      <td>2.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Grace</td>\n",
       "      <td>6.36</td>\n",
       "      <td>2.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>David</td>\n",
       "      <td>7.96</td>\n",
       "      <td>3.46</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Name  Distance (km)  Time (hours)\n",
       "0  Wendy           9.10          4.24\n",
       "1   Yara           8.61          4.16\n",
       "2  Grace           7.17          2.94\n",
       "3  Grace           6.36          2.78\n",
       "4  David           7.96          3.46"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv(\"running_data.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d56c714",
   "metadata": {},
   "source": [
    "## 2. \n",
    "\n",
    "#### Create a copy of the DataFrame. Add another column to the DataFrame that will convert the kilometers run into miles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0de75b49",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Distance (km)</th>\n",
       "      <th>Time (hours)</th>\n",
       "      <th>Distance (Mi)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Wendy</td>\n",
       "      <td>9.10</td>\n",
       "      <td>4.24</td>\n",
       "      <td>5.654492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Yara</td>\n",
       "      <td>8.61</td>\n",
       "      <td>4.16</td>\n",
       "      <td>5.350019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Grace</td>\n",
       "      <td>7.17</td>\n",
       "      <td>2.94</td>\n",
       "      <td>4.455243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Grace</td>\n",
       "      <td>6.36</td>\n",
       "      <td>2.78</td>\n",
       "      <td>3.951931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>David</td>\n",
       "      <td>7.96</td>\n",
       "      <td>3.46</td>\n",
       "      <td>4.946127</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "    Name  Distance (km)  Time (hours)  Distance (Mi)\n",
       "0  Wendy           9.10          4.24       5.654492\n",
       "1   Yara           8.61          4.16       5.350019\n",
       "2  Grace           7.17          2.94       4.455243\n",
       "3  Grace           6.36          2.78       3.951931\n",
       "4  David           7.96          3.46       4.946127"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating a copy of the DataFrame\n",
    "df_copy = df.copy()\n",
    "\n",
    "# Converting kms to miles and creating a new column\n",
    "df_copy[\"Distance (Mi)\"] = df_copy[\"Distance (km)\"] / 1.60934\n",
    "df_copy.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d426f8c",
   "metadata": {},
   "source": [
    "## 3. \n",
    "\n",
    "#### Add another column to the DataFrame to calculate the speed per hour in kilometers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "73994cfb",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Distance (km)</th>\n",
       "      <th>Time (hours)</th>\n",
       "      <th>Distance (Mi)</th>\n",
       "      <th>speed_in_kms(hr)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Wendy</td>\n",
       "      <td>9.10</td>\n",
       "      <td>4.24</td>\n",
       "      <td>5.654492</td>\n",
       "      <td>2.146226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Yara</td>\n",
       "      <td>8.61</td>\n",
       "      <td>4.16</td>\n",
       "      <td>5.350019</td>\n",
       "      <td>2.069712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Grace</td>\n",
       "      <td>7.17</td>\n",
       "      <td>2.94</td>\n",
       "      <td>4.455243</td>\n",
       "      <td>2.438776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Grace</td>\n",
       "      <td>6.36</td>\n",
       "      <td>2.78</td>\n",
       "      <td>3.951931</td>\n",
       "      <td>2.287770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>David</td>\n",
       "      <td>7.96</td>\n",
       "      <td>3.46</td>\n",
       "      <td>4.946127</td>\n",
       "      <td>2.300578</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Name  Distance (km)  Time (hours)  Distance (Mi)  speed_in_kms(hr)\n",
       "0  Wendy           9.10          4.24       5.654492          2.146226\n",
       "1   Yara           8.61          4.16       5.350019          2.069712\n",
       "2  Grace           7.17          2.94       4.455243          2.438776\n",
       "3  Grace           6.36          2.78       3.951931          2.287770\n",
       "4  David           7.96          3.46       4.946127          2.300578"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculating the speed in kms\n",
    "df_copy[\"speed_in_kms(hr)\"] = df_copy[\"Distance (km)\"] / df_copy[\"Time (hours)\"]\n",
    "df_copy.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7114bdfb",
   "metadata": {},
   "source": [
    "## 4. \n",
    "\n",
    "#### \tYou have come across some more information to be added to the DataFrame. Some runners stopped for some rests. This information is saved in a CSV dataset called \"runner_rest\"\n",
    "\n",
    "#### Merge this dataset to your DataFrame above. Use the pandas merge() method. Ensure to drop the \"Runners\" column since you already have the \"Names\" column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7c04d6b7",
   "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>Runners</th>\n",
       "      <th>Rest Time (Mins)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Grace</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Chris</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Frank</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Alice</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Noah</td>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Runners  Rest Time (Mins)\n",
       "0   Grace                45\n",
       "1   Chris                25\n",
       "2   Frank                58\n",
       "3   Alice                47\n",
       "4    Noah               105"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.read_csv(\"runner_rest.csv\")\n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "01122fc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Distance (km)</th>\n",
       "      <th>Time (hours)</th>\n",
       "      <th>Distance (Mi)</th>\n",
       "      <th>speed_in_kms(hr)</th>\n",
       "      <th>Rest Time (Mins)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Wendy</td>\n",
       "      <td>9.10</td>\n",
       "      <td>4.24</td>\n",
       "      <td>5.654492</td>\n",
       "      <td>2.146226</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Yara</td>\n",
       "      <td>8.61</td>\n",
       "      <td>4.16</td>\n",
       "      <td>5.350019</td>\n",
       "      <td>2.069712</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Grace</td>\n",
       "      <td>7.17</td>\n",
       "      <td>2.94</td>\n",
       "      <td>4.455243</td>\n",
       "      <td>2.438776</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Grace</td>\n",
       "      <td>6.36</td>\n",
       "      <td>2.78</td>\n",
       "      <td>3.951931</td>\n",
       "      <td>2.287770</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>David</td>\n",
       "      <td>7.96</td>\n",
       "      <td>3.46</td>\n",
       "      <td>4.946127</td>\n",
       "      <td>2.300578</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Name  Distance (km)  Time (hours)  Distance (Mi)  speed_in_kms(hr)   \n",
       "0  Wendy           9.10          4.24       5.654492          2.146226  \\\n",
       "1   Yara           8.61          4.16       5.350019          2.069712   \n",
       "2  Grace           7.17          2.94       4.455243          2.438776   \n",
       "3  Grace           6.36          2.78       3.951931          2.287770   \n",
       "4  David           7.96          3.46       4.946127          2.300578   \n",
       "\n",
       "   Rest Time (Mins)  \n",
       "0              38.0  \n",
       "1               NaN  \n",
       "2              45.0  \n",
       "3              45.0  \n",
       "4               NaN  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# New available information\n",
    "df2 = pd.read_csv(\"runner_rest.csv\")\n",
    "\n",
    "# Merge the two DataFrames \n",
    "df_merged = df_copy.merge(df2, left_on=\"Name\", \n",
    "                          right_on=\"Runners\", \n",
    "                          how=\"left\").drop(columns=[\"Runners\"])\n",
    "\n",
    "df_merged.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f420ca4",
   "metadata": {},
   "source": [
    "## 5.\n",
    "\n",
    "#### Convert the \"rest time in min\" column into hours using the apply function. Add a new column called \"rest time in hours\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cedcf997",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Distance (km)</th>\n",
       "      <th>Time (hours)</th>\n",
       "      <th>Distance (Mi)</th>\n",
       "      <th>speed_in_kms(hr)</th>\n",
       "      <th>Rest Time (Mins)</th>\n",
       "      <th>Rest Time(Hrs)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Wendy</td>\n",
       "      <td>9.10</td>\n",
       "      <td>4.24</td>\n",
       "      <td>5.654492</td>\n",
       "      <td>2.146226</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Yara</td>\n",
       "      <td>8.61</td>\n",
       "      <td>4.16</td>\n",
       "      <td>5.350019</td>\n",
       "      <td>2.069712</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Grace</td>\n",
       "      <td>7.17</td>\n",
       "      <td>2.94</td>\n",
       "      <td>4.455243</td>\n",
       "      <td>2.438776</td>\n",
       "      <td>45.0</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Grace</td>\n",
       "      <td>6.36</td>\n",
       "      <td>2.78</td>\n",
       "      <td>3.951931</td>\n",
       "      <td>2.287770</td>\n",
       "      <td>45.0</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>David</td>\n",
       "      <td>7.96</td>\n",
       "      <td>3.46</td>\n",
       "      <td>4.946127</td>\n",
       "      <td>2.300578</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Name  Distance (km)  Time (hours)  Distance (Mi)  speed_in_kms(hr)   \n",
       "0  Wendy           9.10          4.24       5.654492          2.146226  \\\n",
       "1   Yara           8.61          4.16       5.350019          2.069712   \n",
       "2  Grace           7.17          2.94       4.455243          2.438776   \n",
       "3  Grace           6.36          2.78       3.951931          2.287770   \n",
       "4  David           7.96          3.46       4.946127          2.300578   \n",
       "\n",
       "   Rest Time (Mins)  Rest Time(Hrs)  \n",
       "0              38.0        0.633333  \n",
       "1               NaN             NaN  \n",
       "2              45.0        0.750000  \n",
       "3              45.0        0.750000  \n",
       "4               NaN             NaN  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Converting mins to hrs and adding a new column\n",
    "df_merged[\"Rest Time(Hrs)\"] = df_merged[\"Rest Time (Mins)\"].apply(lambda x:\n",
    "                                                      x/60 if x is not None else None) \n",
    "                                                                  \n",
    "df_merged.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae453251",
   "metadata": {},
   "source": [
    "## 6\n",
    "\n",
    "#### Using the pandas map series, create a subset of the DataFrame with runners that covered over 5 miles. Reset the index of the resulting Dataframe. Which runner covered the most distance?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "940c3af0",
   "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>Name</th>\n",
       "      <th>Distance (km)</th>\n",
       "      <th>Time (hours)</th>\n",
       "      <th>Distance (Mi)</th>\n",
       "      <th>speed_in_kms(hr)</th>\n",
       "      <th>Rest Time (Mins)</th>\n",
       "      <th>Rest Time(Hrs)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Wendy</td>\n",
       "      <td>9.10</td>\n",
       "      <td>4.24</td>\n",
       "      <td>5.654492</td>\n",
       "      <td>2.146226</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.633333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Yara</td>\n",
       "      <td>8.61</td>\n",
       "      <td>4.16</td>\n",
       "      <td>5.350019</td>\n",
       "      <td>2.069712</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Noah</td>\n",
       "      <td>8.95</td>\n",
       "      <td>3.51</td>\n",
       "      <td>5.561286</td>\n",
       "      <td>2.549858</td>\n",
       "      <td>105.0</td>\n",
       "      <td>1.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Uma</td>\n",
       "      <td>8.12</td>\n",
       "      <td>3.15</td>\n",
       "      <td>5.045547</td>\n",
       "      <td>2.577778</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Xander</td>\n",
       "      <td>9.36</td>\n",
       "      <td>2.71</td>\n",
       "      <td>5.816049</td>\n",
       "      <td>3.453875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Name  Distance (km)  Time (hours)  Distance (Mi)  speed_in_kms(hr)   \n",
       "0   Wendy           9.10          4.24       5.654492          2.146226  \\\n",
       "1    Yara           8.61          4.16       5.350019          2.069712   \n",
       "2    Noah           8.95          3.51       5.561286          2.549858   \n",
       "3     Uma           8.12          3.15       5.045547          2.577778   \n",
       "4  Xander           9.36          2.71       5.816049          3.453875   \n",
       "\n",
       "   Rest Time (Mins)  Rest Time(Hrs)  \n",
       "0              38.0        0.633333  \n",
       "1               NaN             NaN  \n",
       "2             105.0        1.750000  \n",
       "3               NaN             NaN  \n",
       "4               NaN             NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "over_5_miles_run = df_merged[df_merged[\"Distance (Mi)\"]\n",
    "                             .map(lambda x: x) > 5].reset_index(drop=True)\n",
    "over_5_miles_run.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3c4e2976",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The longest distance was achieved by Bob\n"
     ]
    }
   ],
   "source": [
    "# retrieving the index with max miles\n",
    "max_distance_index = over_5_miles_run[\"Distance (Mi)\"].idxmax()\n",
    "\n",
    "# Using index to retrieve name with max miles\n",
    "name = over_5_miles_run[\"Name\"][max_distance_index]\n",
    "print(\"The longest distance was achieved by\", name)"
   ]
  }
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