PYF_Project_LearnerNotebook_FullCode_Reference.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Gc8x8QimJY_H"
   },
   "source": [
    "# Project Python Foundations: FoodHub Data Analysis"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {
    "id": "NqikjkWwJY_L"
   },
   "source": [
    "### Context\n",
    "\n",
    "The number of restaurants in New York is increasing day by day. Lots of students and busy professionals rely on those restaurants due to their hectic lifestyles. Online food delivery service is a great option for them. It provides them with good food from their favorite restaurants. A food aggregator company FoodHub offers access to multiple restaurants through a single smartphone app.\n",
    "\n",
    "The app allows the restaurants to receive a direct online order from a customer. The app assigns a delivery person from the company to pick up the order after it is confirmed by the restaurant. The delivery person then uses the map to reach the restaurant and waits for the food package. Once the food package is handed over to the delivery person, he/she confirms the pick-up in the app and travels to the customer's location to deliver the food. The delivery person confirms the drop-off in the app after delivering the food package to the customer. The customer can rate the order in the app. The food aggregator earns money by collecting a fixed margin of the delivery order from the restaurants.\n",
    "\n",
    "### Objective\n",
    "\n",
    "The food aggregator company has stored the data of the different orders made by the registered customers in their online portal. They want to analyze the data to get a fair idea about the demand of different restaurants which will help them in enhancing their customer experience. Suppose you are hired as a Data Scientist in this company and the Data Science team has shared some of the key questions that need to be answered. Perform the data analysis to find answers to these questions that will help the company to improve the business.\n",
    "\n",
    "### Data Description\n",
    "\n",
    "The data contains the different data related to a food order. The detailed data dictionary is given below.\n",
    "\n",
    "### Data Dictionary\n",
    "\n",
    "* order_id: Unique ID of the order\n",
    "* customer_id: ID of the customer who ordered the food\n",
    "* restaurant_name: Name of the restaurant\n",
    "* cuisine_type: Cuisine ordered by the customer\n",
    "* cost_of_the_order: Cost of the order\n",
    "* day_of_the_week: Indicates whether the order is placed on a weekday or weekend (The weekday is from Monday to Friday and the weekend is Saturday and Sunday)\n",
    "* rating: Rating given by the customer out of 5\n",
    "* food_preparation_time: Time (in minutes) taken by the restaurant to prepare the food. This is calculated by taking the difference between the timestamps of the restaurant's order confirmation and the delivery person's pick-up confirmation.\n",
    "* delivery_time: Time (in minutes) taken by the delivery person to deliver the food package. This is calculated by taking the difference between the timestamps of the delivery person's pick-up confirmation and drop-off information"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cEtNUxNAJY_M"
   },
   "source": [
    "### Let us start by importing the required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "_aG-ZzhYXs_1"
   },
   "outputs": [],
   "source": [
    "# Installing the libraries with the specified version.\n",
    "!pip install numpy==1.25.2 pandas==1.5.3 matplotlib==3.7.1 seaborn==0.13.1 -q --user"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7ueES9WOzI5X"
   },
   "source": [
    "**Note**: *After running the above cell, kindly restart the notebook kernel and run all cells sequentially from the start again.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "u6PlpJAPJY_N"
   },
   "outputs": [],
   "source": [
    "# import libraries for data manipulation\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# import libraries for data visualization\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "AdracY0HJY_O"
   },
   "source": [
    "### Understanding the structure of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "WBh2ZGB9kFhU"
   },
   "outputs": [],
   "source": [
    "# uncomment and run the following lines for Google Colab\n",
    "# from google.colab import drive\n",
    "# drive.mount('/content/drive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "GF01IZDbJY_O",
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Write your code here to read the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write your code here to view the first 5 rows"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "c3kenV4vJY_Q"
   },
   "source": [
    "### **Question 1:** How many rows and columns are present in the data? [0.5 mark]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "Yvz5i-PhJY_Q"
   },
   "outputs": [],
   "source": [
    "# Write your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UsTNy3unJY_R"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jRXakVrUJY_R"
   },
   "source": [
    "### **Question 2:** What are the datatypes of the different columns in the dataset? (The info() function can be used) [0.5 mark]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "Kp70Z0BNJY_R"
   },
   "outputs": [],
   "source": [
    "# Write your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WJes5GP2JY_S"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pF_92MN6JY_S"
   },
   "source": [
    "### **Question 3:** Are there any missing values in the data? If yes, treat them using an appropriate method. [1 mark]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "Zth-RR1PJY_S"
   },
   "outputs": [],
   "source": [
    "# Write your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jDHT3vD1JY_S"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MnJo7MWrJY_S"
   },
   "source": [
    "### **Question 4:** Check the statistical summary of the data. What is the minimum, average, and maximum time it takes for food to be prepared once an order is placed? [2 marks]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "WprQBgOSJY_T"
   },
   "outputs": [],
   "source": [
    "# Write your code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9YbSOR5wJY_T"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cw3l58z_JY_T"
   },
   "source": [
    "### **Question 5:** How many orders are not rated? [1 mark]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "hEzDUL9wgksi"
   },
   "outputs": [],
   "source": [
    "# Write the code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5E0O_oviJY_T"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7msIfXE-JY_T"
   },
   "source": [
    "### Exploratory Data Analysis (EDA)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-2xfI28YJY_T"
   },
   "source": [
    "### Univariate Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0RHZnugBJY_U"
   },
   "source": [
    "### **Question 6:** Explore all the variables and provide observations on their distributions. (Generally, histograms, boxplots, countplots, etc. are used for univariate exploration.) [9 marks]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "rU5ZqISjJY_U"
   },
   "outputs": [],
   "source": [
    "# Write the code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "K9CqA5H_JY_U"
   },
   "source": [
    "### **Question 7**: Which are the top 5 restaurants in terms of the number of orders received? [1 mark]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "PaJZ3wlOJY_U"
   },
   "outputs": [],
   "source": [
    "# Write the code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tnjhWgUfJY_U"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gWPMqGq0JY_U"
   },
   "source": [
    "### **Question 8**: Which is the most popular cuisine on weekends? [1 mark]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "c-Xnus3VJY_U"
   },
   "outputs": [],
   "source": [
    "# Write the code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bpQ270TUJY_U"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "88xgTqkxJY_U"
   },
   "source": [
    "### **Question 9**: What percentage of the orders cost more than 20 dollars? [2 marks]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "OTpHyTdzJY_U"
   },
   "outputs": [],
   "source": [
    "# Write the code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "77KNAC5zJY_U"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "HFyHn7hsJY_V"
   },
   "source": [
    "### **Question 10**: What is the mean order delivery time? [1 mark]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "cyFL13hNJY_V"
   },
   "outputs": [],
   "source": [
    "# Write the code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "F35SRV-HJY_V"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "48IjaOuDJY_V"
   },
   "source": [
    "### **Question 11:** The company has decided to give 20% discount vouchers to the top 3 most frequent customers. Find the IDs of these customers and the number of orders they placed. [1 mark]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "Hz8-DE4Zge0j"
   },
   "outputs": [],
   "source": [
    "# Write the code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9tWVwfX6JY_V"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "AfIc2jPaJY_V"
   },
   "source": [
    "### Multivariate Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iqiS0RT_JY_V"
   },
   "source": [
    "### **Question 12**: Perform a multivariate analysis to explore relationships between the important variables in the dataset. (It is a good idea to explore relations between numerical variables as well as relations between numerical and categorical variables) [10 marks]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "3qt4MCNTJY_V"
   },
   "outputs": [],
   "source": [
    "# Write the code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YLkMf09YJY_V"
   },
   "source": [
    "### **Question 13:** The company wants to provide a promotional offer in the advertisement of the restaurants. The condition to get the offer is that the restaurants must have a rating count of more than 50 and the average rating should be greater than 4. Find the restaurants fulfilling the criteria to get the promotional offer. [3 marks]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "0M_QDvbYJY_V"
   },
   "outputs": [],
   "source": [
    "# Write the code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "10uryUMhJY_V"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1gvWBkRUJY_V"
   },
   "source": [
    "### **Question 14:** The company charges the restaurant 25% on the orders having cost greater than 20 dollars and 15% on the orders having cost greater than 5 dollars. Find the net revenue generated by the company across all orders. [3 marks]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "rEjbnTNEJY_W"
   },
   "outputs": [],
   "source": [
    "# Write the code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "XHCEJgH0JY_W"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pRlVW-oeJY_W"
   },
   "source": [
    "### **Question 15:** The company wants to analyze the total time required to deliver the food. What percentage of orders take more than 60 minutes to get delivered from the time the order is placed? (The food has to be prepared and then delivered.) [2 marks]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "zxoTrxfLJY_W"
   },
   "outputs": [],
   "source": [
    "# Write the code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iqzBXn2yJY_W"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bUd6cYpPJY_W"
   },
   "source": [
    "### **Question 16:** The company wants to analyze the delivery time of the orders on weekdays and weekends. How does the mean delivery time vary during weekdays and weekends? [2 marks]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "pIU5xZZ6JY_W"
   },
   "outputs": [],
   "source": [
    "# Write the code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8H-ODxbVJY_W"
   },
   "source": [
    "#### Observations:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "17roJywaJY_W"
   },
   "source": [
    "### Conclusion and Recommendations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ZdX2Wz4FJY_W"
   },
   "source": [
    "### **Question 17:** What are your conclusions from the analysis? What recommendations would you like to share to help improve the business? (You can use cuisine type and feedback ratings to drive your business recommendations.) [6 marks]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VTugVsL4Ddz-"
   },
   "source": [
    "### Conclusions:\n",
    "*  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PWnsI0i_guWJ"
   },
   "source": [
    "### Recommendations:\n",
    "\n",
    "*  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tSoucKKbg9Hc"
   },
   "source": [
    "---"
   ]
  }
 ],
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