{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Your Student ID:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# your student ID\n", "6304640748" ] }, { "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": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "time.struct_time(tm_year=2022, tm_mon=8, tm_mday=23, tm_hour=10, tm_min=35, tm_sec=11, tm_wday=1, tm_yday=235, tm_isdst=0)" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import time as t\n", "t.localtime()\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": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[1, 3, 1, 2, 9, 4, 5, 6, 10, 4]\n" ] } ], "source": [ "x = [1,3,1,2,9,4,5,6,10,4]\n", "print(x)\n" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "ename": "NameError", "evalue": "name 'numpy' is not defined", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", "Input \u001b[1;32mIn [17]\u001b[0m, in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mnumpy\u001b[49m\u001b[38;5;241m.\u001b[39mstd(x)\n", "\u001b[1;31mNameError\u001b[0m: name 'numpy' is not defined" ] } ], "source": [ "numpy.std(x)" ] }, { "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": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[8, 11, 2, 5, 6, 4, 3, 2, 10, 11, 12]\n" ] } ], "source": [ "add_data =[8,11,2,5,6,4,3,2]\n", "y =[10,11,12]\n", "add_data.extend(y)\n", "print(add_data)" ] }, { "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": "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": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'Year': '2021', 'transactional data': {'transaction_id': 1000001, 'source_country': 'United Kingdom', 'target_country': 'Italy', 'send_currency': 'GBP', 'send_amount': 'GBP1000.00', 'target_currency': 'EUR', 'fx_rate EUR/GBP': 1.1648674, 'fee_pct': 0.5, 'platform': 'mobile'}}\n" ] } ], "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'}}\n", "print(data)" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "ename": "KeyError", "evalue": "'fx_rate EUR/GBP'", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)", "Input \u001b[1;32mIn [20]\u001b[0m, in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# your code here -- notice the comment!\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m \u001b[43mdata\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfx_rate EUR/GBP\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[0;32m 3\u001b[0m \u001b[38;5;28mprint\u001b[39m[data]\n", "\u001b[1;31mKeyError\u001b[0m: 'fx_rate EUR/GBP'" ] } ], "source": [ "# your code here -- notice the comment!\n", "data ['fx_rate EUR/GBP']\n", "print[data]" ] }, { "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!" ] } ], "metadata": { "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" } }, "nbformat": 4, "nbformat_minor": 4 }