api_data_wrangling_mini_project_CZ.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This exercise will require you to pull some data from the Qunadl API. Qaundl is currently the most widely used aggregator of financial market data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a first step, you will need to register a free account on the http://www.quandl.com website."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After you register, you will be provided with a unique API key, that you should store:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Store the API key as a string - according to PEP8, constants are always named in all upper case\n",
    "API_KEY = 'r_o1kSfsxGYH6jAtsbmK'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Qaundl has a large number of data sources, but, unfortunately, most of them require a Premium subscription. Still, there are also a good number of free datasets."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this mini project, we will focus on equities data from the Frankfurt Stock Exhange (FSE), which is available for free. We'll try and analyze the stock prices of a company called Carl Zeiss Meditec, which manufactures tools for eye examinations, as well as medical lasers for laser eye surgery: https://www.zeiss.com/meditec/int/home.html. The company is listed under the stock ticker AFX_X."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can find the detailed Quandl API instructions here: https://docs.quandl.com/docs/time-series"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While there is a dedicated Python package for connecting to the Quandl API, we would prefer that you use the *requests* package, which can be easily downloaded using *pip* or *conda*. You can find the documentation for the package here: http://docs.python-requests.org/en/master/ "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, apart from the *requests* package, you are encouraged to not use any third party Python packages, such as *pandas*, and instead focus on what's available in the Python Standard Library (the *collections* module might come in handy: https://pymotw.com/3/collections/ ).\n",
    "Also, since you won't have access to DataFrames, you are encouraged to us Python's native data structures - preferably dictionaries, though some questions can also be answered using lists.\n",
    "You can read more on these data structures here: https://docs.python.org/3/tutorial/datastructures.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Keep in mind that the JSON responses you will be getting from the API map almost one-to-one to Python's dictionaries. Unfortunately, they can be very nested, so make sure you read up on indexing dictionaries in the documentation provided above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# First, import the relevant modules\n",
    "import requests\n",
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now, call the Quandl API and pull out a small sample of the data (only one day) to get a glimpse\n",
    "# into the JSON structure that will be returned\n",
    "r = requests.get('https://www.quandl.com/api/v3/datasets/FSE/AFX_X.json?start_date=2019-01-02&end_date=2019-01-02&api_key=r_o1kSfsxGYH6jAtsbmK')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'dataset': {'id': 10095370, 'dataset_code': 'AFX_X', 'database_code': 'FSE', 'name': 'Carl Zeiss Meditec (AFX_X)', 'description': 'Stock Prices for Carl Zeiss Meditec (AFX) from the Frankfurt Stock Exchange.<br><br>Trading System: Xetra<br><br>ISIN: DE0005313704', 'refreshed_at': '2019-05-10T22:30:38.681Z', 'newest_available_date': '2019-05-10', 'oldest_available_date': '2000-06-07', 'column_names': ['Date', 'Open', 'High', 'Low', 'Close', 'Change', 'Traded Volume', 'Turnover', 'Last Price of the Day', 'Daily Traded Units', 'Daily Turnover'], 'frequency': 'daily', 'type': 'Time Series', 'premium': False, 'limit': None, 'transform': None, 'column_index': None, 'start_date': '2019-01-02', 'end_date': '2019-01-02', 'data': [['2019-01-02', None, 70.85, 68.25, 69.85, None, None, None, None, None, None]], 'collapse': None, 'order': None, 'database_id': 6129}}\n"
     ]
    }
   ],
   "source": [
    "# Inspect the JSON structure of the object you created, and take note of how nested it is,\n",
    "# as well as the overall structure\n",
    "print(r.json())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These are your tasks for this mini project:\n",
    "\n",
    "1. Collect data from the Franfurt Stock Exchange, for the ticker AFX_X, for the whole year 2017 (keep in mind that the date format is YYYY-MM-DD).\n",
    "2. Convert the returned JSON object into a Python dictionary.\n",
    "3. Calculate what the highest and lowest opening prices were for the stock in this period.\n",
    "4. What was the largest change in any one day (based on High and Low price)?\n",
    "5. What was the largest change between any two days (based on Closing Price)?\n",
    "6. What was the average daily trading volume during this year?\n",
    "7. (Optional) What was the median trading volume during this year. (Note: you may need to implement your own function for calculating the median.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'dataset': {'id': 10095370, 'dataset_code': 'AFX_X', 'database_code': 'FSE', 'name': 'Carl Zeiss Meditec (AFX_X)', 'description': 'Stock Prices for Carl Zeiss Meditec (AFX) from the Frankfurt Stock Exchange.<br><br>Trading System: Xetra<br><br>ISIN: DE0005313704', 'refreshed_at': '2019-05-10T22:30:38.681Z', 'newest_available_date': '2019-05-10', 'oldest_available_date': '2000-06-07', 'column_names': ['Date', 'Open', 'High', 'Low', 'Close', 'Change', 'Traded Volume', 'Turnover', 'Last Price of the Day', 'Daily Traded Units', 'Daily Turnover'], 'frequency': 'daily', 'type': 'Time Series', 'premium': False, 'limit': None, 'transform': None, 'column_index': None, 'start_date': '2017-01-01', 'end_date': '2017-12-31', 'data': [['2017-12-29', 51.76, 51.94, 51.45, 51.76, None, 34640.0, 1792304.0, None, None, None], ['2017-12-28', 51.65, 51.82, 51.43, 51.6, None, 40660.0, 2099024.0, None, None, None], ['2017-12-27', 51.45, 51.89, 50.76, 51.82, None, 57452.0, 2957018.0, None, None, None], ['2017-12-22', 51.05, 51.5, 50.92, 51.32, None, 71165.0, 3641949.0, None, None, None], ['2017-12-21', 51.16, 51.52, 50.9, 51.4, None, 120649.0, 6179433.0, None, None, None], ['2017-12-20', 51.88, 52.04, 51.2, 51.27, None, 50587.0, 2610258.0, None, None, None], ['2017-12-19', 52.73, 52.73, 51.07, 51.66, None, 137313.0, 7102361.0, None, None, None], ['2017-12-18', 52.37, 52.75, 51.61, 52.62, None, 129733.0, 6770499.0, None, None, None], ['2017-12-15', 52.7, 52.7, 51.64, 52.01, None, 204080.0, 10596319.0, None, None, None], ['2017-12-14', 53.11, 53.54, 52.15, 52.67, None, 132981.0, 7016953.0, None, None, None], ['2017-12-13', 52.64, 53.35, 52.48, 53.09, None, 128434.0, 6801159.0, None, None, None], ['2017-12-12', 52.29, 53.1, 51.82, 52.43, None, 87911.0, 4615924.0, None, None, None], ['2017-12-11', 52.28, 52.45, 51.26, 52.14, None, 71817.0, 3724193.0, None, None, None], ['2017-12-08', 51.5, 52.83, 51.28, 52.12, None, 109157.0, 5690648.0, None, None, None], ['2017-12-07', 50.89, 51.47, 50.81, 51.47, None, 48123.0, 2463848.0, None, None, None], ['2017-12-06', 50.8, 51.11, 50.39, 50.89, None, 88730.0, 4504075.0, None, None, None], ['2017-12-05', 51.21, 51.38, 50.4, 51.25, None, 83023.0, 4231971.0, None, None, None], ['2017-12-04', 49.5, 51.23, 49.5, 51.14, None, 94385.0, 4800027.0, None, None, None], ['2017-12-01', 49.52, 50.49, 49.17, 49.86, None, 101733.0, 5065932.0, None, None, None], ['2017-11-30', 48.64, 49.84, 48.28, 49.7, None, 123019.0, 6085171.0, None, None, None], ['2017-11-29', 49.64, 49.64, 48.7, 48.75, None, 67342.0, 3292223.0, None, None, None], ['2017-11-28', 49.09, 49.89, 49.03, 49.25, None, 42669.0, 2107358.0, None, None, None], ['2017-11-27', 49.13, 49.73, 48.96, 49.2, None, 102180.0, 5055762.0, None, None, None], ['2017-11-24', 49.11, 49.41, 48.87, 49.11, None, 50350.0, 2472842.0, None, None, None], ['2017-11-23', 48.8, 49.46, 48.45, 49.2, None, 38834.0, 1909352.0, None, None, None], ['2017-11-22', 48.4, 49.61, 48.39, 48.8, None, 91142.0, 4478093.0, None, None, None], ['2017-11-21', 47.25, 48.59, 46.78, 48.39, None, 78502.0, 3782098.0, None, None, None], ['2017-11-20', 46.57, 47.38, 46.54, 47.04, None, 97252.0, 4563515.0, None, None, None], ['2017-11-17', 47.03, 47.15, 46.8, 46.84, None, 54107.0, 2540820.0, None, None, None], ['2017-11-16', 47.09, 47.23, 46.55, 47.03, None, 89373.0, 4195732.0, None, None, None], ['2017-11-15', 47.98, 48.01, 46.75, 47.05, None, 67593.0, 3188321.0, None, None, None], ['2017-11-14', 48.4, 48.9, 47.84, 48.0, None, 67672.0, 3259979.0, None, None, None], ['2017-11-13', 48.38, 48.61, 47.76, 48.34, None, 76286.0, 3681337.0, None, None, None], ['2017-11-10', 47.3, 48.89, 47.16, 48.34, None, 90245.0, 4361552.0, None, None, None], ['2017-11-09', 47.65, 48.06, 47.09, 47.21, None, 120268.0, 5712034.0, None, None, None], ['2017-11-08', 46.42, 47.72, 46.42, 47.47, None, 94195.0, 4463935.0, None, None, None], ['2017-11-07', 46.16, 46.33, 45.84, 46.26, None, 48152.0, 2224221.0, None, None, None], ['2017-11-06', 45.81, 46.09, 45.76, 45.99, None, 60716.0, 2789220.0, None, None, None], ['2017-11-03', 45.0, 46.04, 44.83, 45.97, None, 56911.0, 2603498.0, None, None, None], ['2017-11-02', 45.88, 46.06, 45.18, 45.27, None, 37958.0, 1724840.0, None, None, None], ['2017-11-01', 46.29, 46.55, 45.97, 46.04, None, 56319.0, 2603859.0, None, None, None], ['2017-10-30', 46.53, 46.65, 45.61, 45.76, None, 56245.0, 2585397.0, None, None, None], ['2017-10-27', 45.48, 46.42, 45.46, 46.41, None, 74472.0, 3434087.0, None, None, None], ['2017-10-26', 45.2, 45.41, 44.91, 45.41, None, 56319.0, 2548078.0, None, None, None], ['2017-10-25', 45.01, 45.06, 44.7, 45.0, None, 47730.0, 2145697.0, None, None, None], ['2017-10-24', 45.16, 45.27, 44.75, 44.85, None, 43042.0, 1937616.0, None, None, None], ['2017-10-23', 44.9, 45.34, 44.89, 45.0, None, 43375.0, 1952918.0, None, None, None], ['2017-10-20', 45.08, 45.34, 44.76, 44.87, None, 55707.0, 2503853.0, None, None, None], ['2017-10-19', 45.72, 45.85, 44.79, 45.0, None, 59991.0, 2703085.0, None, None, None], ['2017-10-18', 46.01, 46.2, 45.61, 45.77, None, 45263.0, 2076951.0, None, None, None], ['2017-10-17', 45.8, 46.06, 45.37, 45.96, None, 65837.0, 3014080.0, None, None, None], ['2017-10-16', 45.61, 45.75, 45.3, 45.55, None, 49246.0, 2243129.0, None, None, None], ['2017-10-13', 45.5, 45.7, 45.37, 45.4, None, 43362.0, 1971801.0, None, None, None], ['2017-10-12', 45.58, 45.58, 45.17, 45.43, None, 49180.0, 2233481.0, None, None, None], ['2017-10-11', 45.97, 45.97, 45.25, 45.29, None, 69455.0, 3158321.0, None, None, None], ['2017-10-10', 45.64, 46.04, 45.57, 45.84, None, 65860.0, 3016658.0, None, None, None], ['2017-10-09', 46.2, 46.2, 45.6, 45.74, None, 44059.0, 2015453.0, None, None, None], ['2017-10-06', 46.19, 46.19, 45.69, 46.0, None, 66760.0, 3066198.0, None, None, None], ['2017-10-05', 46.01, 46.09, 45.63, 46.05, None, 94804.0, 4352002.0, None, None, None], ['2017-10-04', 45.36, 46.17, 45.22, 46.11, None, 115706.0, 5313199.0, None, None, None], ['2017-10-02', 44.51, 44.98, 44.18, 44.98, None, 95313.0, 4265024.0, None, None, None], ['2017-09-29', 43.58, 44.17, 43.3, 44.17, None, 99821.0, 4384796.0, None, None, None], ['2017-09-28', 42.0, 43.56, 42.0, 43.56, None, 157234.0, 6775569.0, None, None, None], ['2017-09-27', 42.35, 42.49, 41.78, 42.04, None, 76600.0, 3219861.0, None, None, None], ['2017-09-26', 42.3, 42.57, 42.11, 42.37, None, 51321.0, 2175381.0, None, None, None], ['2017-09-25', 42.3, 42.3, 41.96, 42.07, None, 56224.0, 2366453.0, None, None, None], ['2017-09-22', 41.48, 42.38, 41.48, 42.06, None, 79955.0, 3362517.0, None, None, None], ['2017-09-21', 42.29, 42.29, 41.39, 41.46, None, 105194.0, 4378409.0, None, None, None], ['2017-09-20', 42.54, 42.54, 41.99, 41.99, None, 57838.0, 2440557.0, None, None, None], ['2017-09-19', 42.65, 42.65, 42.13, 42.44, None, 65546.0, 2777065.0, None, None, None], ['2017-09-18', 42.5, 42.63, 42.23, 42.27, None, 44037.0, 1864954.0, None, None, None], ['2017-09-15', 42.29, 42.81, 42.25, 42.42, None, 107144.0, 4555791.0, None, None, None], ['2017-09-14', 42.35, 42.8, 42.35, 42.52, None, 65157.0, 2770696.0, None, None, None], ['2017-09-13', 42.49, 42.69, 42.22, 42.45, None, 68801.0, 2921240.0, None, None, None], ['2017-09-12', 43.21, 43.34, 42.62, 42.73, None, 52828.0, 2259924.0, None, None, None], ['2017-09-11', 42.81, 42.89, 42.56, 42.85, None, 103273.0, 4415614.0, None, None, None], ['2017-09-08', 42.7, 42.75, 42.56, 42.67, None, 59881.0, 2553977.0, None, None, None], ['2017-09-07', 43.0, 43.02, 42.67, 42.77, None, 64320.0, 2751388.0, None, None, None], ['2017-09-06', 42.66, 42.71, 42.34, 42.55, None, 71006.0, 3020229.0, None, None, None], ['2017-09-05', 43.0, 43.19, 42.55, 42.62, None, 66351.0, 2846115.0, None, None, None], ['2017-09-04', 42.38, 42.75, 41.95, 42.6, None, 105288.0, 4471634.0, None, None, None], ['2017-09-01', 42.16, 43.06, 42.07, 42.41, None, 151474.0, 6453558.0, None, None, None], ['2017-08-31', 42.0, 42.08, 41.12, 41.9, None, 157888.0, 6580200.0, None, None, None], ['2017-08-30', 42.0, 42.2, 41.49, 41.94, None, 97804.0, 4090262.0, None, None, None], ['2017-08-29', 41.71, 41.98, 41.33, 41.85, None, 98156.0, 4094452.0, None, None, None], ['2017-08-28', 42.11, 42.25, 41.86, 41.91, None, 47130.0, 1978704.0, None, None, None], ['2017-08-25', 42.64, 42.64, 42.05, 42.14, None, 69734.0, 2948016.0, None, None, None], ['2017-08-24', 42.72, 43.05, 42.63, 42.69, None, 65213.0, 2792319.0, None, None, None], ['2017-08-23', 42.82, 43.17, 42.6, 42.71, None, 70269.0, 3011578.0, None, None, None], ['2017-08-22', 42.46, 42.96, 42.4, 42.71, None, 95376.0, 4075646.0, None, None, None], ['2017-08-21', 42.42, 42.76, 42.2, 42.26, None, 68812.0, 2922972.0, None, None, None], ['2017-08-18', 42.28, 42.6, 42.01, 42.41, None, 72886.0, 3092377.0, None, None, None], ['2017-08-17', 41.88, 43.01, 41.76, 42.5, None, 131361.0, 5583704.0, None, None, None], ['2017-08-16', 42.4, 42.62, 41.98, 42.05, None, 104676.0, 4408312.0, None, None, None], ['2017-08-15', 42.53, 42.53, 42.2, 42.28, None, 64334.0, 2721852.0, None, None, None], ['2017-08-14', 42.12, 42.69, 42.01, 42.3, None, 127682.0, 5416963.0, None, None, None], ['2017-08-11', 41.3, 41.94, 40.96, 41.94, None, 183412.0, 7604144.0, None, None, None], ['2017-08-10', 41.73, 41.99, 41.14, 41.68, None, 175161.0, 7303562.0, None, None, None], ['2017-08-09', 43.5, 43.5, 41.64, 41.81, None, 355857.0, 15003956.0, None, None, None], ['2017-08-08', 44.9, 45.09, 44.15, 44.37, None, 156168.0, 6941408.0, None, None, None], ['2017-08-07', 45.85, 46.34, 44.02, 44.96, None, 164543.0, 7378816.0, None, None, None], ['2017-08-04', 45.13, 45.13, 44.36, 45.07, None, 96202.0, 4306911.0, None, None, None], ['2017-08-03', 45.34, 45.54, 44.91, 44.97, None, 77854.0, 3517146.0, None, None, None], ['2017-08-02', 45.25, 45.77, 44.9, 45.56, None, 187468.0, 8528548.0, None, None, None], ['2017-08-01', 45.24, 45.54, 45.1, 45.45, None, 74975.0, 3399891.0, None, None, None], ['2017-07-31', 44.94, 45.75, 44.94, 45.3, None, 62672.0, 2844210.0, None, None, None], ['2017-07-28', 45.26, 45.29, 44.75, 44.97, None, 114006.0, 5127247.0, None, None, None], ['2017-07-27', 45.16, 45.45, 45.15, 45.25, None, 50557.0, 2290284.0, None, None, None], ['2017-07-26', 44.91, 45.33, 44.46, 45.16, None, 81970.0, 3688510.0, None, None, None], ['2017-07-25', 44.7, 45.04, 44.63, 44.82, None, 112224.0, 5033312.0, None, None, None], ['2017-07-24', 45.31, 45.31, 44.49, 44.61, None, 104282.0, 4661866.0, None, None, None], ['2017-07-21', 45.57, 45.88, 45.04, 45.44, None, 73422.0, 3334695.0, None, None, None], ['2017-07-20', 45.74, 45.96, 45.23, 45.66, None, 87399.0, 3986488.0, None, None, None], ['2017-07-19', 45.06, 45.72, 44.94, 45.57, None, 71971.0, 3273001.0, None, None, None], ['2017-07-18', 45.5, 45.55, 44.7, 45.0, None, 104003.0, 4684627.0, None, None, None], ['2017-07-17', 45.6, 46.23, 45.29, 45.6, None, 104995.0, 4801806.0, None, None, None], ['2017-07-14', 45.07, 45.56, 44.83, 45.53, None, 67375.0, 3054060.0, None, None, None], ['2017-07-13', 44.67, 45.18, 44.67, 44.95, None, 82745.0, 3718928.0, None, None, None], ['2017-07-12', 44.29, 45.05, 43.89, 44.95, None, 115705.0, 5133971.0, None, None, None], ['2017-07-11', 44.94, 44.94, 44.08, 44.2, None, 90538.0, 4010457.0, None, None, None], ['2017-07-10', 44.64, 45.18, 44.51, 44.7, None, 71868.0, 3221218.0, None, None, None], ['2017-07-07', 44.79, 44.79, 44.25, 44.53, None, 47999.0, 2136578.0, None, None, None], ['2017-07-06', 45.5, 45.5, 44.15, 44.62, None, 66116.0, 2952605.0, None, None, None], ['2017-07-05', 44.67, 45.36, 44.44, 45.19, None, 48706.0, 2189436.0, None, None, None], ['2017-07-04', 45.83, 45.83, 44.74, 44.8, None, 50549.0, 2273551.0, None, None, None], ['2017-07-03', 45.29, 45.83, 45.06, 45.75, None, 71381.0, 3251502.0, None, None, None], ['2017-06-30', 45.01, 45.74, 45.0, 45.44, None, 136112.0, 6187148.0, None, None, None], ['2017-06-29', 45.73, 45.81, 45.11, 45.2, None, 134965.0, 6132452.0, None, None, None], ['2017-06-28', 46.68, 46.68, 45.41, 45.68, None, 117165.0, 5381488.0, None, None, None], ['2017-06-27', 47.23, 47.33, 46.39, 46.83, None, 82492.0, 3866344.0, None, None, None], ['2017-06-26', 46.95, 47.63, 46.91, 47.21, None, 73322.0, 3465639.0, None, None, None], ['2017-06-23', 47.29, 47.4, 46.79, 46.99, None, 80586.0, 3792498.0, None, None, None], ['2017-06-22', 47.03, 47.4, 46.75, 47.29, None, 56071.0, 2640508.0, None, None, None], ['2017-06-21', 47.46, 47.48, 46.53, 46.99, None, 89752.0, 4206563.0, None, None, None], ['2017-06-20', 46.48, 47.43, 46.27, 47.37, None, 108334.0, 5109730.0, None, None, None], ['2017-06-19', 46.9, 46.9, 46.25, 46.64, None, 70056.0, 3260381.0, None, None, None], ['2017-06-16', 45.66, 46.8, 45.66, 46.63, None, 202214.0, 9411695.0, None, None, None], ['2017-06-15', 46.34, 46.34, 45.21, 45.67, None, 101733.0, 4635593.0, None, None, None], ['2017-06-14', 46.52, 46.86, 46.05, 46.33, None, 83741.0, 3881453.0, None, None, None], ['2017-06-13', 46.5, 46.51, 46.03, 46.32, None, 107644.0, 4981185.0, None, None, None], ['2017-06-12', 47.31, 47.43, 45.89, 46.31, None, 112942.0, 5238390.0, None, None, None], ['2017-06-09', 46.77, 47.44, 46.55, 47.44, None, 99674.0, 4702170.0, None, None, None], ['2017-06-08', 47.8, 47.8, 46.27, 46.27, None, 1945.0, 90599.0, None, None, None], ['2017-06-07', 47.01, 47.43, 47.01, 47.43, None, 1081.0, 51021.0, None, None, None], ['2017-06-06', 47.12, 47.45, 46.21, 47.43, None, 686.0, 32083.0, None, None, None], ['2017-06-02', 46.8, 46.99, 46.72, 46.99, None, 290.0, 13584.0, None, None, None], ['2017-06-01', 46.12, 46.52, 45.89, 46.52, None, 106513.0, 4930686.0, None, None, None], ['2017-05-31', 45.22, 46.26, 45.22, 45.86, None, 522.0, 24044.0, None, None, None], ['2017-05-30', 45.05, 46.02, 45.05, 46.02, None, 587.0, 26792.0, None, None, None], ['2017-05-29', 45.61, 45.61, 45.24, 45.32, None, 112.0, 5089.0, None, None, None], ['2017-05-26', 44.8, 45.36, 44.71, 45.3, None, 74453.0, 3360707.0, None, None, None], ['2017-05-25', 44.8, 44.87, 44.29, 44.78, None, 49970.0, 2231857.0, None, None, None], ['2017-05-24', 43.92, 44.67, 43.92, 44.53, None, 111923.0, 4971343.0, None, None, None], ['2017-05-23', 43.67, 44.13, 43.55, 43.9, None, 38308.0, 1681904.0, None, None, None], ['2017-05-22', 44.16, 44.22, 43.44, 43.84, None, 70856.0, 3103013.0, None, None, None], ['2017-05-19', 43.74, 44.12, 43.74, 44.12, None, 45.0, 1980.0, None, None, None], ['2017-05-18', 44.0, 44.3, 43.29, 43.98, None, 166160.0, 7277314.0, None, None, None], ['2017-05-17', 45.06, 45.34, 44.01, 44.19, None, 149515.0, 6664744.0, None, None, None], ['2017-05-16', 45.15, 45.36, 44.56, 45.31, None, 101476.0, 4567885.0, None, None, None], ['2017-05-15', 45.09, 45.78, 44.31, 45.14, None, 193702.0, 8734286.0, None, None, None], ['2017-05-12', 45.18, 45.18, 44.16, 44.99, None, 159495.0, 7113519.0, None, None, None], ['2017-05-11', 43.4, 46.06, 43.25, 45.0, None, 189125.0, 8496322.0, None, None, None], ['2017-05-10', 43.5, 43.6, 42.53, 43.28, None, 91858.0, 3958630.0, None, None, None], ['2017-05-09', 41.83, 43.55, 41.82, 43.3, None, 151439.0, 6538516.0, None, None, None], ['2017-05-08', 43.0, 43.0, 42.04, 42.24, None, 97456.0, 4128048.0, None, None, None], ['2017-05-05', 42.52, 42.91, 42.38, 42.75, None, 78512.0, 3353971.0, None, None, None], ['2017-05-04', 41.86, 42.5, 41.71, 42.5, None, 82058.0, 3465505.0, None, None, None], ['2017-05-03', 42.2, 42.29, 41.78, 41.9, None, 65266.0, 2738394.0, None, None, None], ['2017-05-02', 41.89, 42.23, 41.76, 42.15, None, 86559.0, 3636583.0, None, None, None], ['2017-05-01', None, 42.245, 41.655, 41.72, -0.44, 86348.0, 3606589.0, None, None, None], ['2017-04-28', 42.17, 42.25, 41.66, 41.72, None, 86348.0, 3606589.0, None, None, None], ['2017-04-27', 41.51, 42.24, 41.51, 42.16, None, 151683.0, 6380639.0, None, None, None], ['2017-04-26', 41.88, 41.94, 41.4, 41.5, None, 65847.0, 2743109.0, None, None, None], ['2017-04-25', 41.93, 42.18, 41.66, 41.89, None, 85973.0, 3604204.0, None, None, None], ['2017-04-24', 42.01, 42.02, 41.23, 41.81, None, 102084.0, 4247032.0, None, None, None], ['2017-04-21', 41.97, 42.14, 41.01, 41.32, None, 186784.0, 7728103.0, None, None, None], ['2017-04-20', 42.5, 42.64, 41.52, 41.93, None, 223621.0, 9418192.0, None, None, None], ['2017-04-19', 41.94, 42.61, 41.94, 42.61, None, 92722.0, 3930856.0, None, None, None], ['2017-04-18', 42.24, 42.4, 41.54, 42.0, None, 133057.0, 5587565.0, None, None, None], ['2017-04-17', None, 42.48, 41.985, 42.2, None, 88416.0, 3734717.0, None, None, None], ['2017-04-14', None, 42.48, 41.985, 42.2, None, 88416.0, 3734717.0, None, None, None], ['2017-04-13', 42.06, 42.48, 41.99, 42.2, None, 88416.0, 3734717.0, None, None, None], ['2017-04-12', 42.02, 42.45, 41.84, 42.2, None, 158278.0, 6672547.0, None, None, None], ['2017-04-11', 41.62, 42.03, 41.53, 41.75, None, 107817.0, 4501109.0, None, None, None], ['2017-04-10', 41.46, 41.68, 41.31, 41.68, None, 62297.0, 2585922.0, None, None, None], ['2017-04-07', 40.9, 41.42, 40.84, 41.42, None, 81255.0, 3344628.0, None, None, None], ['2017-04-06', 40.96, 41.25, 40.83, 41.05, None, 96794.0, 3968681.0, None, None, None], ['2017-04-05', 41.1, 41.34, 40.79, 41.1, None, 156005.0, 6404780.0, None, None, None], ['2017-04-04', 39.5, 40.88, 39.48, 40.81, None, 193156.0, 7822665.0, None, None, None], ['2017-04-03', 40.15, 40.15, 39.54, 39.64, None, 127973.0, 5081376.0, None, None, None], ['2017-03-31', 39.77, 40.07, 39.42, 39.98, None, 95382.0, 3795061.0, None, None, None], ['2017-03-30', 40.02, 40.14, 39.42, 39.75, None, 189201.0, 7541354.0, None, None, None], ['2017-03-29', 39.39, 40.01, 39.05, 40.01, None, 335406.0, 13349426.0, None, None, None], ['2017-03-28', 38.95, 39.35, 38.79, 39.22, None, 115075.0, 4505494.0, None, None, None], ['2017-03-27', 38.73, 39.1, 38.53, 38.85, None, 191515.0, 7446952.0, None, None, None], ['2017-03-24', 38.94, 39.02, 38.6, 38.94, None, 210926.0, 8205507.0, None, None, None], ['2017-03-23', 39.01, 39.25, 38.63, 38.96, None, 169971.0, 6621807.0, None, None, None], ['2017-03-22', 38.25, 39.02, 37.53, 38.94, None, 670349.0, 25910543.0, None, None, None], ['2017-03-21', 41.8, 41.83, 40.97, 40.98, None, 56906.0, 2349965.0, None, None, None], ['2017-03-20', 41.26, 42.17, 41.26, 41.97, None, 97572.0, 4074891.0, None, None, None], ['2017-03-17', 41.47, 41.59, 41.16, 41.34, None, 90109.0, 3734232.0, None, None, None], ['2017-03-16', 41.4, 41.57, 41.09, 41.46, None, 55799.0, 2308423.0, None, None, None], ['2017-03-15', 41.4, 41.5, 40.91, 41.25, None, 60324.0, 2488650.0, None, None, None], ['2017-03-14', 41.2, 41.5, 41.2, 41.3, None, 60420.0, 2498025.0, None, None, None], ['2017-03-13', 41.4, 41.46, 41.08, 41.3, None, 44803.0, 1850251.0, None, None, None], ['2017-03-10', 41.53, 41.53, 41.16, 41.4, None, 38518.0, 1592270.0, None, None, None], ['2017-03-09', 41.61, 41.61, 41.16, 41.4, None, 43988.0, 1819182.0, None, None, None], ['2017-03-08', 41.13, 41.71, 40.95, 41.68, None, 45111.0, 1870935.0, None, None, None], ['2017-03-07', 41.5, 41.8, 41.25, 41.42, None, 61925.0, 2569608.0, None, None, None], ['2017-03-06', 41.25, 41.4, 40.81, 41.4, None, 46510.0, 1916799.0, None, None, None], ['2017-03-03', 41.12, 41.22, 40.84, 41.18, None, 40800.0, 1675587.0, None, None, None], ['2017-03-02', 41.38, 41.39, 40.76, 41.17, None, 49863.0, 2048153.0, None, None, None], ['2017-03-01', 41.19, 41.57, 40.9, 41.2, None, 86753.0, 3569796.0, None, None, None], ['2017-02-28', 40.38, 40.95, 40.38, 40.84, None, 67440.0, 2747011.0, None, None, None], ['2017-02-27', 39.75, 40.64, 39.75, 40.39, None, 62655.0, 2520260.0, None, None, None], ['2017-02-24', 39.77, 40.14, 38.91, 39.74, None, 101294.0, 4015150.0, None, None, None], ['2017-02-23', 39.72, 39.98, 39.38, 39.79, None, 81945.0, 3260642.0, None, None, None], ['2017-02-22', 39.6, 39.75, 39.27, 39.7, None, 77619.0, 3066894.0, None, None, None], ['2017-02-21', 38.85, 39.57, 38.85, 39.45, None, 46070.0, 1808350.0, None, None, None], ['2017-02-20', 39.25, 39.25, 38.81, 38.98, None, 37014.0, 1444138.0, None, None, None], ['2017-02-17', 38.8, 39.03, 38.48, 39.02, None, 60583.0, 2352961.0, None, None, None], ['2017-02-16', 38.8, 39.2, 38.25, 38.71, None, 84682.0, 3282322.0, None, None, None], ['2017-02-15', 38.5, 38.93, 38.4, 38.72, None, 77420.0, 2996861.0, None, None, None], ['2017-02-14', 38.81, 38.86, 38.0, 38.37, None, 82601.0, 3163898.0, None, None, None], ['2017-02-13', 37.37, 39.36, 37.35, 38.53, None, 177171.0, 6804028.0, None, None, None], ['2017-02-10', 36.65, 37.5, 36.57, 37.06, None, 115843.0, 4291017.0, None, None, None], ['2017-02-09', 36.2, 36.25, 35.77, 36.25, None, 67781.0, 2445428.0, None, None, None], ['2017-02-08', 35.98, 36.14, 35.84, 36.05, None, 39731.0, 1431205.0, None, None, None], ['2017-02-07', 35.56, 36.05, 35.36, 35.89, None, 67410.0, 2410818.0, None, None, None], ['2017-02-06', 36.06, 36.15, 35.6, 35.64, None, 41911.0, 1496794.0, None, None, None], ['2017-02-03', 36.02, 36.2, 35.73, 36.1, None, 40705.0, 1464712.0, None, None, None], ['2017-02-02', 35.95, 36.2, 35.7, 36.07, None, 54279.0, 1953176.0, None, None, None], ['2017-02-01', 34.75, 36.0, 34.75, 35.94, None, 85137.0, 3038172.0, None, None, None], ['2017-01-31', 35.24, 35.24, 34.56, 34.56, None, 63371.0, 2199583.0, None, None, None], ['2017-01-30', 35.38, 35.59, 34.95, 35.15, None, 69603.0, 2457762.0, None, None, None], ['2017-01-27', 34.83, 35.43, 34.81, 35.3, None, 69657.0, 2444913.0, None, None, None], ['2017-01-26', 35.07, 35.58, 34.8, 34.89, None, 64103.0, 2249375.0, None, None, None], ['2017-01-25', 34.42, 34.86, 34.03, 34.83, None, 56240.0, 1947147.0, None, None, None], ['2017-01-24', 34.0, 34.35, 33.85, 34.22, None, 48797.0, 1666086.0, None, None, None], ['2017-01-23', 34.04, 34.12, 33.62, 34.06, None, 55333.0, 1877957.0, None, None, None], ['2017-01-20', 34.54, 34.59, 34.05, 34.17, None, 80246.0, 2743474.0, None, None, None], ['2017-01-19', 35.04, 35.04, 34.42, 34.5, None, 73105.0, 2526731.0, None, None, None], ['2017-01-18', 35.04, 35.51, 34.8, 34.9, None, 65931.0, 2311608.0, None, None, None], ['2017-01-17', 35.06, 35.19, 34.79, 34.99, None, 39195.0, 1369857.0, None, None, None], ['2017-01-16', 34.85, 35.24, 34.56, 35.07, None, 47879.0, 1678679.0, None, None, None], ['2017-01-13', 34.98, 34.98, 34.6, 34.85, None, 59367.0, 2065534.0, None, None, None], ['2017-01-12', 35.38, 35.38, 34.31, 34.9, None, 163860.0, 5703427.0, None, None, None], ['2017-01-11', 34.95, 36.0, 34.84, 35.42, None, 123530.0, 4369079.0, None, None, None], ['2017-01-10', 34.8, 34.98, 34.46, 34.91, None, 43976.0, 1528055.0, None, None, None], ['2017-01-09', 35.29, 35.35, 34.43, 34.67, None, 62225.0, 2157182.0, None, None, None], ['2017-01-06', 34.91, 35.21, 34.91, 35.04, None, 27507.0, 964046.0, None, None, None], ['2017-01-05', 35.02, 35.2, 34.73, 35.06, None, 48412.0, 1692326.0, None, None, None], ['2017-01-04', 35.48, 35.51, 34.75, 35.19, None, 54408.0, 1906810.0, None, None, None], ['2017-01-03', 35.9, 35.93, 35.34, 35.48, None, 70618.0, 2515473.0, None, None, None], ['2017-01-02', 34.99, 35.94, 34.99, 35.8, None, 44700.0, 1590561.0, None, None, None]], 'collapse': None, 'order': None, 'database_id': 6129}}\n"
     ]
    }
   ],
   "source": [
    "# question 1\n",
    "r_2017 = requests.get('https://www.quandl.com/api/v3/datasets/FSE/AFX_X.json?start_date=2017-01-01&end_date=2017-12-31&api_key=r_o1kSfsxGYH6jAtsbmK')\n",
    "print(r_2017.json())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "# question 2 \n",
    "r_dict = r_2017.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "# preparation\n",
    "\n",
    "r_dict_opening = []\n",
    "r_dict_high = []\n",
    "r_dict_low = []\n",
    "r_dict_close = []\n",
    "r_dict_change_day = []\n",
    "r_dict_volume = []\n",
    "\n",
    "r_dict_change = [0]\n",
    "\n",
    "for i in range(len(r_dict['dataset']['data'])):\n",
    "\n",
    "    opening = r_dict['dataset']['data'][i][1] \n",
    "    close = r_dict['dataset']['data'][i][4]\n",
    "    high = r_dict['dataset']['data'][i][2] \n",
    "    low = r_dict['dataset']['data'][i][3]    \n",
    "    t_vol = r_dict['dataset']['data'][i][6]\n",
    "    \n",
    "    if isinstance(opening,float):\n",
    "        r_dict_opening.append(opening)\n",
    "    if isinstance(close,float):\n",
    "        r_dict_close.append(close)\n",
    "    if isinstance(high,float) and isinstance(low,float):    \n",
    "        change_day = high - low\n",
    "        r_dict_change_day.append(change_day)\n",
    "        \n",
    "    if i != 0 : \n",
    "        change = r_dict_close[i] - r_dict_close[i-1]\n",
    "        r_dict_change.append(change)\n",
    "           \n",
    "    if isinstance(t_vol,float):\n",
    "        r_dict_volume.append(t_vol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "53.11\n",
      "34.0\n"
     ]
    }
   ],
   "source": [
    "# question 3: the highest and lowest opening prices were for the stock in this period\n",
    "print(max(r_dict_opening))\n",
    "print(min(r_dict_opening))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.8100000000000023\n"
     ]
    }
   ],
   "source": [
    "# question 4: the largest change in any one day (based on High and Low price)\n",
    "print(max(r_dict_change_day))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.559999999999995\n"
     ]
    }
   ],
   "source": [
    "# question 5: the largest change between any two days (based on Closing Price)\n",
    "print(max(r_dict_change))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "89124.33725490196\n"
     ]
    }
   ],
   "source": [
    "# question 6: the average daily trading volume during this year\n",
    "average_v = sum(r_dict_volume)/len(r_dict_volume)\n",
    "print(average_v)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}