lecture_1_exercise_solution.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Class 1 in-class exercise solution\n",
    "\n",
    "## Step 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-18T21:43:13.164166Z",
     "iopub.status.busy": "2024-03-18T21:43:13.163653Z",
     "iopub.status.idle": "2024-03-18T21:43:13.577874Z",
     "shell.execute_reply": "2024-03-18T21:43:13.576993Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2024-03-18 17:43:13 URL:https://data.cityofnewyork.us/resource/m6nq-qud6.csv [136065] -> \"2021_yellow_taxi_trips.csv\" [1]\r\n"
     ]
    }
   ],
   "source": [
    "!wget -O 2021_yellow_taxi_trips.csv --no-verbose https://data.cityofnewyork.us/resource/m6nq-qud6.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-18T21:43:13.582348Z",
     "iopub.status.busy": "2024-03-18T21:43:13.582047Z",
     "iopub.status.idle": "2024-03-18T21:43:13.596595Z",
     "shell.execute_reply": "2024-03-18T21:43:13.596169Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "3.20\n",
      "3.80\n",
      "1.14\n",
      "7.30\n",
      "5.36\n",
      "1.60\n",
      "3.80\n",
      "4.98\n",
      "0.77\n",
      "1.96\n",
      "0.20\n",
      "0.51\n",
      "6.88\n",
      "1.76\n",
      "0.00\n",
      "0.00\n",
      "0.36\n",
      "7.24\n",
      "3.70\n",
      "0.00\n",
      "4.68\n",
      "1.10\n",
      "32.58\n",
      "2.10\n",
      "0.28\n",
      "0.28\n",
      "3.80\n",
      "3.30\n",
      "0.30\n",
      "3.30\n",
      "1.40\n",
      "0.76\n",
      "1.60\n",
      "0.00\n",
      "1.87\n",
      "0.53\n",
      "2.36\n",
      "1.73\n",
      "4.82\n",
      "0.46\n",
      "1.99\n",
      "3.36\n",
      "4.32\n",
      "1.53\n",
      "1.64\n",
      "0.79\n",
      "1.13\n",
      "0.00\n",
      "0.83\n",
      "4.71\n",
      "0.54\n",
      "3.67\n",
      "1.51\n",
      "0.96\n",
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      "0.60\n",
      "2.63\n",
      "2.06\n",
      "1.59\n",
      "2.30\n",
      "0.10\n",
      "1.64\n",
      "1.01\n",
      "2.65\n",
      "0.74\n",
      "1.13\n",
      "1.13\n",
      "2.84\n",
      "2.84\n",
      "1.52\n",
      "1.84\n",
      "1.08\n",
      "1.18\n",
      "1.69\n",
      "2.35\n",
      "6.09\n",
      "3.08\n",
      "0.05\n",
      "1.97\n",
      "1.30\n",
      "0.10\n",
      "1.40\n",
      "1.60\n",
      "2.31\n",
      "5.67\n",
      "4.64\n",
      "1.69\n",
      "2.47\n",
      "0.68\n",
      "1.85\n",
      "2.72\n",
      "3.10\n",
      "2.73\n",
      "0.68\n",
      "2.60\n",
      "4.70\n",
      "2.99\n",
      "11.15\n",
      "1.35\n",
      "0.76\n",
      "3.07\n",
      "3.17\n",
      "1.84\n",
      "1.60\n",
      "5.40\n",
      "0.90\n",
      "1.69\n",
      "2.49\n",
      "0.93\n",
      "3.52\n",
      "7.05\n",
      "2.39\n",
      "10.52\n",
      "1.99\n",
      "4.13\n",
      "8.16\n",
      "1.06\n",
      "4.80\n",
      "1.30\n",
      "5.50\n",
      "3.80\n",
      "0.03\n",
      "1.91\n",
      "1.98\n",
      "1.78\n",
      "1.15\n",
      "2.03\n",
      "10.82\n",
      "5.20\n",
      "2.00\n",
      "0.80\n",
      "11.64\n",
      "1.77\n",
      "1.70\n",
      "7.20\n",
      "5.60\n",
      "3.17\n",
      "1.80\n",
      "6.81\n",
      "3.86\n",
      "1.19\n",
      "1.79\n",
      "0.50\n",
      "9.08\n",
      "0.62\n",
      "21.17\n",
      "2.70\n",
      "1.65\n",
      "1.30\n",
      "12.40\n",
      "0.56\n",
      "3.67\n",
      "10.50\n",
      "2.34\n",
      "6.45\n",
      "11.78\n",
      "1.60\n",
      "0.41\n",
      "0.41\n",
      "1.67\n",
      "3.60\n",
      "0.70\n",
      "1.13\n",
      "0.89\n",
      "1.92\n",
      "2.15\n",
      "1.65\n",
      "2.25\n",
      "7.83\n",
      "9.61\n",
      "9.84\n",
      "2.30\n",
      "4.24\n",
      "2.60\n",
      "1.64\n",
      "2.24\n",
      "0.12\n",
      "7.28\n",
      "5.10\n",
      "4.30\n",
      "2.10\n",
      "2.59\n",
      "0.93\n",
      "0.61\n",
      "0.30\n",
      "6.10\n",
      "5.71\n",
      "3.58\n",
      "3.76\n",
      "1.90\n",
      "2.10\n",
      "1.60\n",
      "1.68\n",
      "6.33\n",
      "23.26\n",
      "4.72\n",
      "7.02\n",
      "3.05\n",
      "1.55\n",
      "3.40\n",
      "2.00\n",
      "6.50\n",
      "1.20\n",
      "3.96\n",
      "2.00\n",
      "1.90\n",
      "8.90\n",
      "4.51\n",
      "0.99\n",
      "2.79\n",
      "13.03\n",
      "2.35\n",
      "0.94\n",
      "2.50\n",
      "1.45\n",
      "2.36\n",
      "8.90\n",
      "3.06\n",
      "0.98\n",
      "2.19\n",
      "2.87\n",
      "0.47\n",
      "0.13\n",
      "1.13\n",
      "1.41\n",
      "1.38\n",
      "0.48\n",
      "3.60\n",
      "6.34\n",
      "6.34\n",
      "0.00\n",
      "9.34\n",
      "7.09\n",
      "8.75\n",
      "0.01\n",
      "0.80\n",
      "3.50\n",
      "4.39\n",
      "2.72\n",
      "2.21\n",
      "3.12\n",
      "4.45\n",
      "1.53\n",
      "3.85\n",
      "0.00\n",
      "0.50\n",
      "2.20\n",
      "3.10\n",
      "2.77\n",
      "2.01\n",
      "3.35\n",
      "3.35\n"
     ]
    }
   ],
   "source": [
    "import csv\n",
    "\n",
    "\n",
    "with open(\"2021_yellow_taxi_trips.csv\") as csvfile:\n",
    "    reader = csv.DictReader(csvfile)\n",
    "    for row in reader:\n",
    "        print(row[\"trip_distance\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-18T21:43:13.599275Z",
     "iopub.status.busy": "2024-03-18T21:43:13.599083Z",
     "iopub.status.idle": "2024-03-18T21:43:13.606891Z",
     "shell.execute_reply": "2024-03-18T21:43:13.606492Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.279060000000005\n"
     ]
    }
   ],
   "source": [
    "num_trips = 0\n",
    "miles = 0\n",
    "\n",
    "with open(\"2021_yellow_taxi_trips.csv\") as csvfile:\n",
    "    reader = csv.DictReader(csvfile)\n",
    "    for row in reader:\n",
    "        # convert from a string to a numeric type\n",
    "        dist = float(row[\"trip_distance\"])\n",
    "\n",
    "        # increment the counters\n",
    "        num_trips += 1\n",
    "        miles += dist\n",
    "\n",
    "print(miles / num_trips)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-18T21:43:13.609203Z",
     "iopub.status.busy": "2024-03-18T21:43:13.609021Z",
     "iopub.status.idle": "2024-03-18T21:43:13.615650Z",
     "shell.execute_reply": "2024-03-18T21:43:13.615320Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "59.0%\n"
     ]
    }
   ],
   "source": [
    "num_trips = 0\n",
    "num_paid_by_card = 0\n",
    "\n",
    "with open(\"2021_yellow_taxi_trips.csv\") as csvfile:\n",
    "    reader = csv.DictReader(csvfile)\n",
    "    for row in reader:\n",
    "        # increment the counters\n",
    "        num_trips += 1\n",
    "        if row[\"payment_type\"] == \"1\":\n",
    "            num_paid_by_card += 1\n",
    "\n",
    "pct = num_paid_by_card / num_trips\n",
    "print(f\"{pct * 100}%\")"
   ]
  }
 ],
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