User_NYC_TAXI_workbook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "A1cTcMelgzD1"
   },
   "source": [
    "# Import Statements\n",
    "Add libraries you like and look at already imported libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-07T15:17:07.032721Z",
     "iopub.status.busy": "2023-04-07T15:17:07.031699Z",
     "iopub.status.idle": "2023-04-07T15:17:07.053732Z",
     "shell.execute_reply": "2023-04-07T15:17:07.050733Z",
     "shell.execute_reply.started": "2023-04-07T15:17:07.032721Z"
    },
    "id": "VoI4Pi7dg51g",
    "tags": []
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "86FFIKjef9ZJ"
   },
   "source": [
    "# Milestone 1 -Data Exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VJE2yjlG9xDn"
   },
   "source": [
    "## Task 1 - Import Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MJ9JmlH-gZF5"
   },
   "source": [
    "Please do not perform any sort of analysis (it's the next step!)<br>\n",
    "(HINT: The file is csv and pandas is already imported)\n",
    "\n",
    "\n",
    "---\n",
    "\n",
    "<font size = \"4\"> Sanity Check\n",
    "\n",
    "The df.head() should look like this\n",
    "![Milestone1-task1.jpg](data:image/jpeg;base64,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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "vC6aoxs5ghI3"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bPRnbtgOgGs7"
   },
   "source": [
    "## Task 2 - Exploratory analysis on data\n",
    "<font size=\"3\">Use functions (such as describe, count, head) to understand the start data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "sF5NaVJbgF6Z"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "0Mmrbvpgh5d7"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multiple choice\n",
    "\n",
    "Of the 4 cleaning, which are the only two required? (Enter your answer as \"ab\" in the code cell below and run) <br />\n",
    "**a)** Remove non integer passenger count <br />\n",
    "**b)** Remove negative fare amounts <br />\n",
    "**c)** Remove longitudes outside NYC <br />\n",
    "**d)** Remove negative pickup_longitude <br />"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "cellView": "form",
    "id": "LM0K6lhrizjC"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TzSbWUE4jgq2"
   },
   "source": [
    "# Milestone 2 - Cleaning dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "nJ8Cm9Of-N-G"
   },
   "source": [
    "## Task - 3 Remove values in with negative or null data\n",
    "1. Values where fare amount < 0\n",
    "2. Passenger count <= 0\n",
    "3. Any field that has any value missing\n",
    "---\n",
    "\n",
    "### HINTS\n",
    "Documentation to drop null elements in pandas https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.dropna.html <br />\n",
    "Remember that most of the operations on dataframes are out of place! \n",
    "\n",
    "---\n",
    "### Sanity Check\n",
    "The length of the final dataset should be 12729\n",
    "\n",
    "---\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "2kasq4_-joh4"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "odyQyLE0mZ3l"
   },
   "source": [
    "# Milestone 3 - Removing data points which lie outside of NYC latitutes\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0ClBwrZuyW3W"
   },
   "source": [
    "## Task 4 - Corners of the area\n",
    "Find the minmum and maximum latitude and longitude points in the dataframe\n",
    "\n",
    "---\n",
    "\n",
    "HINT: \n",
    "The dataframe consists of two columns -- pickup and dropoff points <br/>\n",
    "\n",
    "---\n",
    "Sanity Check - maximum latitude is 401.08332\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "9FMV5kqzydGm",
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kWnkW0nWCKPE"
   },
   "source": [
    "## Task 5 - Dropping undesired location rows\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "eHrIve9Dz8-J"
   },
   "source": [
    "Given that the desired area of concern is within -74.5 < `longitude` < -72.8 and  40.5 < `latitude` < 41.8. Remove the latitudes and longitudes that lie outside this area. <br>\n",
    "Think if your above result provide any information to filter the dataframe by?\n",
    "---\n",
    "\n",
    "Sanity Check - you will be dropping 250 rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "FRR6QcbC1ebF",
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "veXPazJCmsWK"
   },
   "source": [
    "# Milestone 4 - Fare from anywhere to JFK"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "u0qwfWKtC7Kt"
   },
   "source": [
    "## Task 6 - Testing hypothesis\n",
    "\n",
    "A local Uber enthusiast claims that all travel to and from JFK (an airport at NYC) has the same cost. <br> Given that JFK is between (latitudes longitudes) (40.644633, -73.795537) and (40.645848, -73.771921) verify if their claim is correct or not? If it is not, plot the distribution of cost vs distance. <br> <br> HINT: Do not perform want inplace operations. <br> Did task 5 asked you to do something similar? <br> Take a sneek peak to the next sanity check question <br> Note that to convert latitudes and longitudes to actual distance, you can use this formula = `np.sqrt(((new_df['pickup_latitude'] - new_df['dropoff_latitude']) * 69)**2 + ((new_df['pickup_longitude'] - new_df['dropoff_longitude']) * 54.6) ** 2)`\n",
    "\n",
    "\n",
    "\n",
    "---\n",
    "\n",
    "Sanity check - a scatter plot should look like <br>\n",
    "![image.png](data:image/png;base64,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)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "8VbpBHvH2uPI"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "cellView": "form",
    "id": "iFtF7lfAQqEX"
   },
   "source": [
    "## Sanity check\n",
    "Think about how many unique fare amount values are there?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "YQjz7m4eUFqQ",
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Final\n",
    "Please run the commands below and follow the instructions carefully"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-07T15:17:07.143208Z",
     "iopub.status.busy": "2023-04-07T15:17:07.142205Z",
     "iopub.status.idle": "2023-04-07T15:17:07.161101Z",
     "shell.execute_reply": "2023-04-07T15:17:07.159924Z",
     "shell.execute_reply.started": "2023-04-07T15:17:07.143208Z"
    }
   },
   "outputs": [],
   "source": [
    "import codecs\n",
    "\n",
    "jupyter_file = codecs.open(\"User_NYC_TAXI_workbook.ipynb\", 'r')\n",
    "source_data = jupyter_file.read()\n",
    "\n",
    "f = open(\"submit.json\", \"w\")\n",
    "f.write(source_data)\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-07T15:17:07.163120Z",
     "iopub.status.busy": "2023-04-07T15:17:07.162109Z",
     "iopub.status.idle": "2023-04-07T15:17:07.176129Z",
     "shell.execute_reply": "2023-04-07T15:17:07.175129Z",
     "shell.execute_reply.started": "2023-04-07T15:17:07.163120Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "f = open(\"in_file.txt\", \"a\")\n",
    "for i in In:\n",
    "    f.write(i)\n",
    "    f.write('\\n')\n",
    "f.close()"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "history_visible": true,
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
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}