diff --git a/Assignment1/Assignment1.ipynb b/Assignment1/Assignment1.ipynb
index a6212ef..003fbb9 100644
--- a/Assignment1/Assignment1.ipynb
+++ b/Assignment1/Assignment1.ipynb
@@ -22,7 +22,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 31,
    "id": "fcf3beb9",
    "metadata": {},
    "outputs": [],
@@ -34,7 +34,8 @@
     "import seaborn as sns\n",
     "import matplotlib.pyplot as plt\n",
     "import bokeh\n",
-    "import ftfy"
+    "import ftfy\n",
+    "import matplotlib as mpl"
    ]
   },
   {
@@ -51,7 +52,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "id": "a0af6847",
    "metadata": {},
    "outputs": [
@@ -61,7 +62,7 @@
        "('Ü', 'sloppy-windows-1252')"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -73,7 +74,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "id": "22ce9426",
    "metadata": {},
    "outputs": [
@@ -270,7 +271,7 @@
        "4  2016-03-31 00:00:00             0       60437  2016-04-06 10:17:21  "
       ]
      },
-     "execution_count": 3,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -283,7 +284,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "a332b6a5",
    "metadata": {},
    "outputs": [
@@ -296,23 +297,23 @@
        " 'offerType': ['str'],\n",
        " 'price': ['int64'],\n",
        " 'abtest': ['str'],\n",
-       " 'vehicleType': ['nan', 'str'],\n",
+       " 'vehicleType': ['str', 'nan'],\n",
        " 'yearOfRegistration': ['int64'],\n",
-       " 'gearbox': ['nan', 'str'],\n",
+       " 'gearbox': ['str', 'nan'],\n",
        " 'powerPS': ['int64'],\n",
-       " 'model': ['nan', 'str'],\n",
+       " 'model': ['str', 'nan'],\n",
        " 'kilometer': ['int64'],\n",
        " 'monthOfRegistration': ['int64'],\n",
-       " 'fuelType': ['nan', 'str'],\n",
+       " 'fuelType': ['str', 'nan'],\n",
        " 'brand': ['str'],\n",
-       " 'notRepairedDamage': ['nan', 'str'],\n",
+       " 'notRepairedDamage': ['str', 'nan'],\n",
        " 'dateCreated': ['str'],\n",
        " 'nrOfPictures': ['int64'],\n",
        " 'postalCode': ['int64'],\n",
        " 'lastSeen': ['str']}"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -330,7 +331,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "id": "11bfa9a2",
    "metadata": {},
    "outputs": [
@@ -371,7 +372,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "id": "f1c539c4",
    "metadata": {},
    "outputs": [
@@ -412,7 +413,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "id": "86074e70",
    "metadata": {},
    "outputs": [
@@ -609,7 +610,7 @@
        "4  2016-03-31 00:00:00             0       60437  2016-04-06 10:17:21  "
       ]
      },
-     "execution_count": 7,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -652,7 +653,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "id": "8b6f9ce3",
    "metadata": {},
    "outputs": [
@@ -682,7 +683,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "id": "98f8d101",
    "metadata": {},
    "outputs": [
@@ -707,7 +708,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "id": "f300f49d",
    "metadata": {},
    "outputs": [
@@ -726,7 +727,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "id": "923c5354",
    "metadata": {},
    "outputs": [],
@@ -737,7 +738,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "id": "4b847b1f",
    "metadata": {},
    "outputs": [],
@@ -748,7 +749,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "id": "bf1f417d",
    "metadata": {},
    "outputs": [
@@ -778,7 +779,7 @@
        "dtype: int64"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -790,7 +791,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "id": "919e692f",
    "metadata": {},
    "outputs": [],
@@ -835,7 +836,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "id": "7cc5c90f",
    "metadata": {},
    "outputs": [
@@ -887,27 +888,25 @@
    "metadata": {},
    "source": [
     "### 2.2\n",
-    "\n"
+    "\n",
+    "To compare the range of prices between car brands, I choose to plot the distribution of car prices for each car brand. To achieve this, I choose to use a variant of the box plot called boxen plot, which ditches whiskers in favour of showing octiles, 16-tiles and so on with coloured rectangles similar to the inner quartiles with exponentially smaller heights.\n",
+    "\n",
+    "From the plot we can see that the `mercedes_benz` car type has the highest median price, and it also has the most right skewed price distribution out of all car brands. `volvo` has the second-highest average and also a skewed price distribution. Both `lancia` and `fiat` are instead more uniformly distributed towards lower prices, while `alfa_romeo` has a similar distribution however with some skewing towards the expensive side. [`trabant`](https://www.youtube.com/watch?v=npMKIUTa3uI) is the cheapest car type.\n",
+    "\n",
+    "I choose to use a box-plot style graph as it is an effective representation to show some salient characterististics for one-dimensional distributions, such as the median and the quartiles (25% percentile, 75% percentile). I choose a `boxenplot` in particular to better capture the right-skewedness of some distributions with the additional percentiles considered by the octiles (87.5%), 16-tiles (93.75%) and so on exponentially."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 32,
    "id": "ca97e7c8",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
-     ]
-    },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
-       "<Figure size 1500x800 with 1 Axes>"
+       "<Figure size 1800x800 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -915,27 +914,25 @@
     }
    ],
    "source": [
-    "brands = ['mercedes_benz', 'fiat', 'volvo', 'alfa_romeo', 'lancia']\n",
+    "brands = ['mercedes_benz', 'fiat', 'volvo', 'alfa_romeo', 'lancia', 'trabant']\n",
     "\n",
     "df_price = df_used \\\n",
-    "    .loc[df_used.brand.isin(brands), ['brand', 'price']]\n",
+    "    .loc[df_used.brand.isin(brands), ['brand', 'price']] \\\n",
+    "    .sort_values('brand', ascending=True)\n",
     "\n",
     "sns.set_theme(palette=\"hls\")\n",
     "\n",
     "# Initialize the matplotlib figure\n",
-    "f, ax = plt.subplots(figsize=(15, 8))\n",
+    "f, ax = plt.subplots(figsize=(18, 8))\n",
     "\n",
-    "import matplotlib as mpl\n",
     "mkfunc = lambda x, pos: '%1.0fk' % (x * 1e-3)\n",
     "mkformatter = mpl.ticker.FuncFormatter(mkfunc)\n",
     "ax.xaxis.set_major_formatter(mkformatter)\n",
     "\n",
-    "ax.legend(ncol=2, loc=\"lower right\", frameon=True)\n",
-    "\n",
     "# Draw a nested boxplot to show bills by day and time\n",
     "sns.boxenplot(y=\"brand\", x=\"price\", data=df_price)\n",
     "\n",
-    "ax.set(ylabel=\"\", xlim=[0, 100000], xticks=range(0, 100001, 5000),\n",
+    "ax.set(ylabel=\"\", xlim=[0, 100000], xticks=range(0, 105001, 5000),\n",
     "       xlabel=\"Distribution of prices per vehicle type and fuel type\")\n",
     "       \n",
     "sns.despine(offset=10, trim=True)"
@@ -967,11 +964,75 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 130,
    "id": "eb956ed4",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "df_m = pd.read_csv(\"./datasets/market_value_decline.csv\").rename(columns={\n",
+    "       'Unnamed: 0': 'bank',\n",
+    "       'market_value_2007': '2007',\n",
+    "       'market_value_2009': '2009'\n",
+    "})\n",
+    "\n",
+    "df_mkt = df_m\n",
+    "df_mkt[\"diff\"] = 100 * (df_mkt['2009'] - df_mkt['2007']) / df_mkt['2007']\n",
+    "df_mkt = df_mkt.sort_values(['diff'], ascending=False)\n",
+    "\n",
+    "# sort source DF according to new order by diff\n",
+    "df_m = df_m.reindex(df_mkt.index)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 131,
+   "id": "4a29684b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_mval = pd.melt(df_m.loc[:, ['bank', '2007', '2009']], id_vars=['bank'], var_name='year', value_name='market_value')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 136,
+   "id": "d3d58d25",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1500x800 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.set_theme(palette=\"hls\")\n",
+    "\n",
+    "# Initialize the matplotlib figure\n",
+    "f, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 8), sharey=True)\n",
+    "\n",
+    "ax2.xaxis.set_major_formatter(mpl.ticker.FuncFormatter(lambda x, pos: '%.0fB' % (x)))\n",
+    "ax1.xaxis.set_major_formatter(mpl.ticker.FuncFormatter(lambda x, pos: '%.0f%%' % (x)))\n",
+    "\n",
+    "sns.barplot(y=\"bank\", x=\"diff\", data=df_mkt, ax=ax1, color=sns.xkcd_rgb[\"purplish red\"])\n",
+    "sns.barplot(\n",
+    "    data=df_mval, ax=ax2,\n",
+    "    x=\"market_value\", y=\"bank\", hue=\"year\",\n",
+    "    palette=[sns.xkcd_rgb[\"prussian blue\"], sns.xkcd_rgb[\"sienna\"]]\n",
+    ")\n",
+    "\n",
+    "# Add a legend and informative axis label\n",
+    "ax2.set(ylabel=\"Institution\", xlim=[0, 300],\n",
+    "       xlabel=\"Market value\")\n",
+    "ax1.set(ylabel=\"Institution\", xlim=[-1, 0], xticks=range(-100, 1, 10),\n",
+    "       xlabel=\"Market value decrease\")\n",
+    "sns.despine(left=True, bottom=True)"
+   ]
   },
   {
    "attachments": {},
@@ -996,11 +1057,371 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 62,
    "id": "b4fde7e4",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>airport_name</th>\n",
+       "      <th>city</th>\n",
+       "      <th>country</th>\n",
+       "      <th>IATA</th>\n",
+       "      <th>ICAO</th>\n",
+       "      <th>latitude</th>\n",
+       "      <th>longitude</th>\n",
+       "      <th>altitude</th>\n",
+       "      <th>timezone</th>\n",
+       "      <th>DST</th>\n",
+       "      <th>tz_database_timezone</th>\n",
+       "      <th>type</th>\n",
+       "      <th>source</th>\n",
+       "      <th>flights_planned</th>\n",
+       "      <th>flights_cancelled</th>\n",
+       "      <th>flights_delayed</th>\n",
+       "      <th>delay_duration</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1600</th>\n",
+       "      <td>Bar Yehuda Airfield</td>\n",
+       "      <td>Metzada</td>\n",
+       "      <td>Israel</td>\n",
+       "      <td>MTZ</td>\n",
+       "      <td>LLMZ</td>\n",
+       "      <td>31.328199</td>\n",
+       "      <td>35.388599</td>\n",
+       "      <td>-1266</td>\n",
+       "      <td>2</td>\n",
+       "      <td>E</td>\n",
+       "      <td>Asia/Jerusalem</td>\n",
+       "      <td>airport</td>\n",
+       "      <td>OurAirports</td>\n",
+       "      <td>62</td>\n",
+       "      <td>0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>32.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1595</th>\n",
+       "      <td>Ein Yahav Airfield</td>\n",
+       "      <td>Eyn-yahav</td>\n",
+       "      <td>Israel</td>\n",
+       "      <td>EIY</td>\n",
+       "      <td>LLEY</td>\n",
+       "      <td>30.621700</td>\n",
+       "      <td>35.203300</td>\n",
+       "      <td>-164</td>\n",
+       "      <td>2</td>\n",
+       "      <td>E</td>\n",
+       "      <td>Asia/Jerusalem</td>\n",
+       "      <td>airport</td>\n",
+       "      <td>OurAirports</td>\n",
+       "      <td>56</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>24.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7646</th>\n",
+       "      <td>Jacqueline Cochran Regional Airport</td>\n",
+       "      <td>Palm Springs</td>\n",
+       "      <td>United States</td>\n",
+       "      <td>TRM</td>\n",
+       "      <td>KTRM</td>\n",
+       "      <td>33.626701</td>\n",
+       "      <td>-116.160004</td>\n",
+       "      <td>-115</td>\n",
+       "      <td>-8</td>\n",
+       "      <td>A</td>\n",
+       "      <td>America/Los_Angeles</td>\n",
+       "      <td>airport</td>\n",
+       "      <td>OurAirports</td>\n",
+       "      <td>60</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>28.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4357</th>\n",
+       "      <td>Atyrau Airport</td>\n",
+       "      <td>Atyrau</td>\n",
+       "      <td>Kazakhstan</td>\n",
+       "      <td>GUW</td>\n",
+       "      <td>UATG</td>\n",
+       "      <td>47.121899</td>\n",
+       "      <td>51.821400</td>\n",
+       "      <td>-72</td>\n",
+       "      <td>5</td>\n",
+       "      <td>U</td>\n",
+       "      <td>Asia/Oral</td>\n",
+       "      <td>airport</td>\n",
+       "      <td>OurAirports</td>\n",
+       "      <td>71</td>\n",
+       "      <td>0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>35.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2151</th>\n",
+       "      <td>Ramsar Airport</td>\n",
+       "      <td>Ramsar</td>\n",
+       "      <td>Iran</td>\n",
+       "      <td>RZR</td>\n",
+       "      <td>OINR</td>\n",
+       "      <td>36.909901</td>\n",
+       "      <td>50.679600</td>\n",
+       "      <td>-70</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>E</td>\n",
+       "      <td>Asia/Tehran</td>\n",
+       "      <td>airport</td>\n",
+       "      <td>OurAirports</td>\n",
+       "      <td>62</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>47.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3039</th>\n",
+       "      <td>Lengpui Airport</td>\n",
+       "      <td>Aizwal</td>\n",
+       "      <td>India</td>\n",
+       "      <td>AJL</td>\n",
+       "      <td>VELP</td>\n",
+       "      <td>23.840599</td>\n",
+       "      <td>92.619698</td>\n",
+       "      <td>1398</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>N</td>\n",
+       "      <td>Asia/Calcutta</td>\n",
+       "      <td>airport</td>\n",
+       "      <td>OurAirports</td>\n",
+       "      <td>118</td>\n",
+       "      <td>0</td>\n",
+       "      <td>23</td>\n",
+       "      <td>38.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1670</th>\n",
+       "      <td>Emmen Air Base</td>\n",
+       "      <td>Emmen</td>\n",
+       "      <td>Switzerland</td>\n",
+       "      <td>EML</td>\n",
+       "      <td>LSME</td>\n",
+       "      <td>47.092444</td>\n",
+       "      <td>8.305184</td>\n",
+       "      <td>1400</td>\n",
+       "      <td>1</td>\n",
+       "      <td>E</td>\n",
+       "      <td>Europe/Zurich</td>\n",
+       "      <td>airport</td>\n",
+       "      <td>OurAirports</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>19</td>\n",
+       "      <td>38.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6215</th>\n",
+       "      <td>Long Lellang Airport</td>\n",
+       "      <td>Long Datih</td>\n",
+       "      <td>Malaysia</td>\n",
+       "      <td>LGL</td>\n",
+       "      <td>WBGF</td>\n",
+       "      <td>3.421000</td>\n",
+       "      <td>115.153999</td>\n",
+       "      <td>1400</td>\n",
+       "      <td>8</td>\n",
+       "      <td>N</td>\n",
+       "      <td>Asia/Kuala_Lumpur</td>\n",
+       "      <td>airport</td>\n",
+       "      <td>OurAirports</td>\n",
+       "      <td>126</td>\n",
+       "      <td>0</td>\n",
+       "      <td>18</td>\n",
+       "      <td>32.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7375</th>\n",
+       "      <td>Minaçu Airport</td>\n",
+       "      <td>Minacu</td>\n",
+       "      <td>Brazil</td>\n",
+       "      <td>MQH</td>\n",
+       "      <td>SBMC</td>\n",
+       "      <td>-13.549100</td>\n",
+       "      <td>-48.195301</td>\n",
+       "      <td>1401</td>\n",
+       "      <td>-3</td>\n",
+       "      <td>S</td>\n",
+       "      <td>America/Sao_Paulo</td>\n",
+       "      <td>airport</td>\n",
+       "      <td>OurAirports</td>\n",
+       "      <td>119</td>\n",
+       "      <td>1</td>\n",
+       "      <td>25</td>\n",
+       "      <td>48.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9253</th>\n",
+       "      <td>Bubovice Airport</td>\n",
+       "      <td>Bubovice</td>\n",
+       "      <td>Czech Republic</td>\n",
+       "      <td>\\N</td>\n",
+       "      <td>LKBU</td>\n",
+       "      <td>49.974400</td>\n",
+       "      <td>14.178100</td>\n",
+       "      <td>1401</td>\n",
+       "      <td>1</td>\n",
+       "      <td>E</td>\n",
+       "      <td>Europe/Prague</td>\n",
+       "      <td>airport</td>\n",
+       "      <td>OurAirports</td>\n",
+       "      <td>128</td>\n",
+       "      <td>0</td>\n",
+       "      <td>15</td>\n",
+       "      <td>32.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>6029 rows × 17 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                             airport_name          city         country IATA  \\\n",
+       "ID                                                                             \n",
+       "1600                  Bar Yehuda Airfield       Metzada          Israel  MTZ   \n",
+       "1595                   Ein Yahav Airfield     Eyn-yahav          Israel  EIY   \n",
+       "7646  Jacqueline Cochran Regional Airport  Palm Springs   United States  TRM   \n",
+       "4357                       Atyrau Airport        Atyrau      Kazakhstan  GUW   \n",
+       "2151                       Ramsar Airport        Ramsar            Iran  RZR   \n",
+       "...                                   ...           ...             ...  ...   \n",
+       "3039                      Lengpui Airport        Aizwal           India  AJL   \n",
+       "1670                       Emmen Air Base         Emmen     Switzerland  EML   \n",
+       "6215                 Long Lellang Airport    Long Datih        Malaysia  LGL   \n",
+       "7375                       Minaçu Airport        Minacu          Brazil  MQH   \n",
+       "9253                     Bubovice Airport      Bubovice  Czech Republic   \\N   \n",
+       "\n",
+       "      ICAO   latitude   longitude  altitude timezone DST tz_database_timezone  \\\n",
+       "ID                                                                              \n",
+       "1600  LLMZ  31.328199   35.388599     -1266        2   E       Asia/Jerusalem   \n",
+       "1595  LLEY  30.621700   35.203300      -164        2   E       Asia/Jerusalem   \n",
+       "7646  KTRM  33.626701 -116.160004      -115       -8   A  America/Los_Angeles   \n",
+       "4357  UATG  47.121899   51.821400       -72        5   U            Asia/Oral   \n",
+       "2151  OINR  36.909901   50.679600       -70      3.5   E          Asia/Tehran   \n",
+       "...    ...        ...         ...       ...      ...  ..                  ...   \n",
+       "3039  VELP  23.840599   92.619698      1398      5.5   N        Asia/Calcutta   \n",
+       "1670  LSME  47.092444    8.305184      1400        1   E        Europe/Zurich   \n",
+       "6215  WBGF   3.421000  115.153999      1400        8   N    Asia/Kuala_Lumpur   \n",
+       "7375  SBMC -13.549100  -48.195301      1401       -3   S    America/Sao_Paulo   \n",
+       "9253  LKBU  49.974400   14.178100      1401        1   E        Europe/Prague   \n",
+       "\n",
+       "         type       source  flights_planned  flights_cancelled  \\\n",
+       "ID                                                               \n",
+       "1600  airport  OurAirports               62                  0   \n",
+       "1595  airport  OurAirports               56                  0   \n",
+       "7646  airport  OurAirports               60                  0   \n",
+       "4357  airport  OurAirports               71                  0   \n",
+       "2151  airport  OurAirports               62                  1   \n",
+       "...       ...          ...              ...                ...   \n",
+       "3039  airport  OurAirports              118                  0   \n",
+       "1670  airport  OurAirports              124                  0   \n",
+       "6215  airport  OurAirports              126                  0   \n",
+       "7375  airport  OurAirports              119                  1   \n",
+       "9253  airport  OurAirports              128                  0   \n",
+       "\n",
+       "      flights_delayed  delay_duration  \n",
+       "ID                                     \n",
+       "1600                9            32.0  \n",
+       "1595                7            24.0  \n",
+       "7646                7            28.0  \n",
+       "4357                9            35.0  \n",
+       "2151                6            47.0  \n",
+       "...               ...             ...  \n",
+       "3039               23            38.0  \n",
+       "1670               19            38.0  \n",
+       "6215               18            32.0  \n",
+       "7375               25            48.0  \n",
+       "9253               15            32.0  \n",
+       "\n",
+       "[6029 rows x 17 columns]"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_air = pd.read_csv(\"./datasets/airports.csv\", index_col='ID')\n",
+    "df_del = pd.read_csv(\"./datasets/airports-delays.csv\", index_col='ID', sep=\";\")\n",
+    "\n",
+    "df_del\n",
+    "#pd.cut(df_del.flights_delayed, range(0, df_del.flights_delayed.max(), 25))\n",
+    "\n",
+    "#df_bycountry = df_del.loc[:, ['country', 'flights_delayed']].groupby('country').sum().sort_values('flights_delayed', ascending=False)\n",
+    "#df_bycountry\n"
+   ]
   },
   {
    "cell_type": "markdown",
diff --git a/Assignment1/datasets/market_value_decline.csv b/Assignment1/datasets/market_value_decline.csv
new file mode 100644
index 0000000..5219bc1
--- /dev/null
+++ b/Assignment1/datasets/market_value_decline.csv
@@ -0,0 +1,16 @@
+,market_value_2007,market_value_2009
+Morgan Stanley,49,16.0
+RBS,120,4.6
+Deutsche Bank,76,10.3
+Credit Agricole,67,17.0
+Societe Generale,80,26.0
+Barclays,91,7.4
+BNP Paribas,108,32.5
+Unicredit,93,26.0
+UBS,116,35.0
+Credit Suisse,75,27.0
+Goldman Sachs,100,35.0
+Santander,116,64.0
+Citigroup,255,19.0
+JP Morgan,165,85.0
+HSBC,215,97.0