Pandas Exercises-3.ipynb

{
 "cells": [
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   "source": [
    "# Pandas - Filtering and Sorting Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 1. Import the necessary libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 2. Import the dataset from this [address](https://raw.githubusercontent.com/justmarkham/DAT8/master/data/chipotle.tsv). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 3. Assign it to a variable called chipo."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://raw.githubusercontent.com/justmarkham/DAT8/master/data/chipotle.tsv'\n",
    "    \n",
    "chipo = pd.read_csv(url, sep = '\\t')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 4. How many products cost more than $10.00?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prices = [float(value[1 : -1]) for value in chipo.item_price]\n",
    "chipo.item_price = prices\n",
    "chipo_filtered = chipo.drop_duplicates(['item_name','quantity'])\n",
    "chipo_one_prod = chipo_filtered[chipo_filtered.quantity == 1]\n",
    "chipo_one_prod[chipo_one_prod['item_price']>10].item_name.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 5. What is the price of each item? \n",
    "###### print a data frame with only two columns item_name and item_price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>item_name</th>\n",
       "      <th>item_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>606</th>\n",
       "      <td>Steak Salad Bowl</td>\n",
       "      <td>11.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1229</th>\n",
       "      <td>Barbacoa Salad Bowl</td>\n",
       "      <td>11.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1132</th>\n",
       "      <td>Carnitas Salad Bowl</td>\n",
       "      <td>11.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Steak Burrito</td>\n",
       "      <td>11.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>Barbacoa Crispy Tacos</td>\n",
       "      <td>11.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Barbacoa Bowl</td>\n",
       "      <td>11.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>738</th>\n",
       "      <td>Veggie Soft Tacos</td>\n",
       "      <td>11.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>Veggie Salad Bowl</td>\n",
       "      <td>11.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Veggie Bowl</td>\n",
       "      <td>11.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Veggie Burrito</td>\n",
       "      <td>11.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>Chicken Salad</td>\n",
       "      <td>10.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Chicken Bowl</td>\n",
       "      <td>10.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Steak Soft Tacos</td>\n",
       "      <td>9.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>554</th>\n",
       "      <td>Carnitas Crispy Tacos</td>\n",
       "      <td>9.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>Carnitas Soft Tacos</td>\n",
       "      <td>9.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Barbacoa Soft Tacos</td>\n",
       "      <td>9.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>Steak Crispy Tacos</td>\n",
       "      <td>9.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>664</th>\n",
       "      <td>Steak Salad</td>\n",
       "      <td>8.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>Steak Bowl</td>\n",
       "      <td>8.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3750</th>\n",
       "      <td>Carnitas Salad</td>\n",
       "      <td>8.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  item_name  item_price\n",
       "606        Steak Salad Bowl       11.89\n",
       "1229    Barbacoa Salad Bowl       11.89\n",
       "1132    Carnitas Salad Bowl       11.89\n",
       "7             Steak Burrito       11.75\n",
       "168   Barbacoa Crispy Tacos       11.75\n",
       "39            Barbacoa Bowl       11.75\n",
       "738       Veggie Soft Tacos       11.25\n",
       "186       Veggie Salad Bowl       11.25\n",
       "62              Veggie Bowl       11.25\n",
       "57           Veggie Burrito       11.25\n",
       "250           Chicken Salad       10.98\n",
       "5              Chicken Bowl       10.98\n",
       "8          Steak Soft Tacos        9.25\n",
       "554   Carnitas Crispy Tacos        9.25\n",
       "237     Carnitas Soft Tacos        9.25\n",
       "56      Barbacoa Soft Tacos        9.25\n",
       "92       Steak Crispy Tacos        9.25\n",
       "664             Steak Salad        8.99\n",
       "54               Steak Bowl        8.99\n",
       "3750         Carnitas Salad        8.99"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chipo_filtered = chipo.drop_duplicates(['item_name','quantity'])\n",
    "chipo_one_prod = chipo_filtered[chipo_filtered.quantity == 1]\n",
    "price_per_item = chipo_one_prod[['item_name', 'item_price']]\n",
    "price_per_item.sort_values(by = \"item_price\", ascending = False).head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 6. Sort by the name of the item"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3389    6 Pack Soft Drink\n",
       "341     6 Pack Soft Drink\n",
       "1849    6 Pack Soft Drink\n",
       "1860    6 Pack Soft Drink\n",
       "2713    6 Pack Soft Drink\n",
       "3422    6 Pack Soft Drink\n",
       "553     6 Pack Soft Drink\n",
       "1916    6 Pack Soft Drink\n",
       "1922    6 Pack Soft Drink\n",
       "1937    6 Pack Soft Drink\n",
       "3836    6 Pack Soft Drink\n",
       "298     6 Pack Soft Drink\n",
       "1976    6 Pack Soft Drink\n",
       "1167    6 Pack Soft Drink\n",
       "3875    6 Pack Soft Drink\n",
       "1124    6 Pack Soft Drink\n",
       "3886    6 Pack Soft Drink\n",
       "2108    6 Pack Soft Drink\n",
       "3010    6 Pack Soft Drink\n",
       "4535    6 Pack Soft Drink\n",
       "4169    6 Pack Soft Drink\n",
       "4174    6 Pack Soft Drink\n",
       "4527    6 Pack Soft Drink\n",
       "4522    6 Pack Soft Drink\n",
       "3806    6 Pack Soft Drink\n",
       "2389    6 Pack Soft Drink\n",
       "3132    6 Pack Soft Drink\n",
       "3141    6 Pack Soft Drink\n",
       "639     6 Pack Soft Drink\n",
       "1026    6 Pack Soft Drink\n",
       "              ...        \n",
       "2996         Veggie Salad\n",
       "3163         Veggie Salad\n",
       "4084         Veggie Salad\n",
       "1694         Veggie Salad\n",
       "2756         Veggie Salad\n",
       "4201    Veggie Salad Bowl\n",
       "1884    Veggie Salad Bowl\n",
       "455     Veggie Salad Bowl\n",
       "3223    Veggie Salad Bowl\n",
       "2223    Veggie Salad Bowl\n",
       "2269    Veggie Salad Bowl\n",
       "4541    Veggie Salad Bowl\n",
       "3293    Veggie Salad Bowl\n",
       "186     Veggie Salad Bowl\n",
       "960     Veggie Salad Bowl\n",
       "1316    Veggie Salad Bowl\n",
       "2156    Veggie Salad Bowl\n",
       "4261    Veggie Salad Bowl\n",
       "295     Veggie Salad Bowl\n",
       "4573    Veggie Salad Bowl\n",
       "2683    Veggie Salad Bowl\n",
       "496     Veggie Salad Bowl\n",
       "4109    Veggie Salad Bowl\n",
       "738     Veggie Soft Tacos\n",
       "3889    Veggie Soft Tacos\n",
       "2384    Veggie Soft Tacos\n",
       "781     Veggie Soft Tacos\n",
       "2851    Veggie Soft Tacos\n",
       "1699    Veggie Soft Tacos\n",
       "1395    Veggie Soft Tacos\n",
       "Name: item_name, Length: 4622, dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chipo.item_name.sort_values()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 7. What was the quantity of the most expensive item ordered?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>order_id</th>\n",
       "      <th>quantity</th>\n",
       "      <th>item_name</th>\n",
       "      <th>choice_description</th>\n",
       "      <th>item_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3598</th>\n",
       "      <td>1443</td>\n",
       "      <td>15</td>\n",
       "      <td>Chips and Fresh Tomato Salsa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      order_id  quantity                     item_name choice_description  \\\n",
       "3598      1443        15  Chips and Fresh Tomato Salsa                NaN   \n",
       "\n",
       "      item_price  \n",
       "3598       44.25  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chipo.sort_values(by = \"item_price\", ascending = False).head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 8. How many times were a Veggie Salad Bowl ordered?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chipo_salad = chipo[chipo.item_name == \"Veggie Salad Bowl\"]\n",
    "\n",
    "len(chipo_salad)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 9. How many times people orderd more than one Canned Soda?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chipo_drink_steak_bowl = chipo[(chipo.item_name == \"Canned Soda\") & (chipo.quantity > 1)]\n",
    "len(chipo_drink_steak_bowl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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