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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Your Student ID:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# your student ID"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Question 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# This task, you want to find out Today's date by using the library time\n",
    "\n",
    "Hint: Use time.FUNC_NAME.FUNC_NAME? (where FUNC_NAME is replaced with the function you found) to see information about that function and then call the function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time as t\n",
    "\n",
    "# your code here -- notice the comment!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Question  2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.1 What is the standard deviation of the data:\n",
    "\n",
    "Hint: Using the function std in library Numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = [1,3,1,2,9,4,5,6,10,4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# your code here -- notice the comment!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.2 Then, you have the additional data as shown below"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "add_data =[8,11,2,5,6,4,3,2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Add the new data to the original data, then re-calculate the standard deviation again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# your code here -- notice the comment!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Question 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Consider the below information:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "data ={'Year':'2021','transactional data':{\n",
    " 'transaction_id': 1000001,\n",
    " 'source_country': 'United Kingdom',\n",
    " 'target_country': 'Italy',\n",
    " 'send_currency': 'GBP',\n",
    " 'send_amount': 'GBP1000.00',\n",
    " 'target_currency': 'EUR',\n",
    " 'fx_rate EUR/GBP': 1.1648674,\n",
    " 'fee_pct': 0.50, \n",
    " 'platform': 'mobile'}}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3.1 Using the python code to pick up the foreign exchange rate  ('fx_rate EUR/GBP') from this dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# your code here -- notice the comment!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3.2 You now need to include the data for the \"fee_amount,\" which can be determined from the funds you send to the target country (send_amount) multiplied by the fee percentage (fee_pct). \n",
    "\n",
    "Create the new keyword \"fee_amount\" for this dataset, and then report its value.\n",
    "\n",
    "Hint: using replace() and float() to convert the 'send_amount' into a number.Then, multiply with fee percentage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# your code here -- notice the comment!"
   ]
  }
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