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diff --git a/module-3/Data-Cleaning-Challenge/Lab_data_cleaning_Iris.ipynb b/module-3/Data-Cleaning-Challenge/Lab_data_cleaning_Iris.ipynb
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@@ -0,0 +1,818 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "iris = pd.read_csv(\"iris-data.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "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>sepal_length_cm</th>\n",
+       "      <th>sepal_width_cm</th>\n",
+       "      <th>petal_length_cm</th>\n",
+       "      <th>petal_width_cm</th>\n",
+       "      <th>class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>5.1</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4.9</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>4.7</td>\n",
+       "      <td>3.2</td>\n",
+       "      <td>1.3</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4.6</td>\n",
+       "      <td>3.1</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5.0</td>\n",
+       "      <td>3.6</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.2</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   sepal_length_cm  sepal_width_cm  petal_length_cm  petal_width_cm  \\\n",
+       "0              5.1             3.5              1.4             0.2   \n",
+       "1              4.9             3.0              1.4             0.2   \n",
+       "2              4.7             3.2              1.3             0.2   \n",
+       "3              4.6             3.1              1.5             0.2   \n",
+       "4              5.0             3.6              1.4             0.2   \n",
+       "\n",
+       "         class  \n",
+       "0  Iris-setosa  \n",
+       "1  Iris-setosa  \n",
+       "2  Iris-setosa  \n",
+       "3  Iris-setosa  \n",
+       "4  Iris-setosa  "
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "sepal_length_cm    0\n",
+       "sepal_width_cm     0\n",
+       "petal_length_cm    0\n",
+       "petal_width_cm     5\n",
+       "class              0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris.isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "sepal_length_cm    float64\n",
+       "sepal_width_cm     float64\n",
+       "petal_length_cm    float64\n",
+       "petal_width_cm     float64\n",
+       "class               object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "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>sepal_length_cm</th>\n",
+       "      <th>sepal_width_cm</th>\n",
+       "      <th>petal_length_cm</th>\n",
+       "      <th>petal_width_cm</th>\n",
+       "      <th>class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>5.0</td>\n",
+       "      <td>3.4</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>4.4</td>\n",
+       "      <td>2.9</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>4.9</td>\n",
+       "      <td>3.1</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>5.4</td>\n",
+       "      <td>3.7</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>4.8</td>\n",
+       "      <td>3.4</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    sepal_length_cm  sepal_width_cm  petal_length_cm  petal_width_cm  \\\n",
+       "7               5.0             3.4              1.5             NaN   \n",
+       "8               4.4             2.9              1.4             NaN   \n",
+       "9               4.9             3.1              1.5             NaN   \n",
+       "10              5.4             3.7              1.5             NaN   \n",
+       "11              4.8             3.4              1.6             NaN   \n",
+       "\n",
+       "          class  \n",
+       "7   Iris-setosa  \n",
+       "8   Iris-setosa  \n",
+       "9   Iris-setosa  \n",
+       "10  Iris-setosa  \n",
+       "11  Iris-setosa  "
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris[iris.isnull().any(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.25"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris[iris[\"class\"]==\"Iris-setosa\"].mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "iris[\"petal_width_cm\"] = iris[\"petal_width_cm\"].fillna(iris[\"petal_width_cm\"][iris[\"class\"]==\"Iris-setosa\"].mean())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Iris-setosa\n",
+      "Iris-setossa\n",
+      "Iris-versicolor\n",
+      "versicolor\n",
+      "Iris-virginica\n"
+     ]
+    }
+   ],
+   "source": [
+    "lista = []\n",
+    "for flower in iris[\"class\"].unique(): \n",
+    "    print(flower)\n",
+    "    temporary_df = iris[iris[\"class\"] == flower]\n",
+    "    lista.append(temporary_df.fillna(temporary_df[\"petal_width_cm\"].mean()))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "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>sepal_length_cm</th>\n",
+       "      <th>sepal_width_cm</th>\n",
+       "      <th>petal_length_cm</th>\n",
+       "      <th>petal_width_cm</th>\n",
+       "      <th>class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>5.1</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4.9</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>4.7</td>\n",
+       "      <td>3.2</td>\n",
+       "      <td>1.3</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4.6</td>\n",
+       "      <td>3.1</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5.0</td>\n",
+       "      <td>3.6</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>5.4</td>\n",
+       "      <td>3.9</td>\n",
+       "      <td>1.7</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>4.6</td>\n",
+       "      <td>3.4</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>5.0</td>\n",
+       "      <td>3.4</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>4.4</td>\n",
+       "      <td>2.9</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>4.9</td>\n",
+       "      <td>3.1</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>5.4</td>\n",
+       "      <td>3.7</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>4.8</td>\n",
+       "      <td>3.4</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>4.8</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.10</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>5.7</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.1</td>\n",
+       "      <td>0.10</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>5.8</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.2</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    sepal_length_cm  sepal_width_cm  petal_length_cm  petal_width_cm  \\\n",
+       "0               5.1             3.5              1.4            0.20   \n",
+       "1               4.9             3.0              1.4            0.20   \n",
+       "2               4.7             3.2              1.3            0.20   \n",
+       "3               4.6             3.1              1.5            0.20   \n",
+       "4               5.0             3.6              1.4            0.20   \n",
+       "5               5.4             3.9              1.7            0.40   \n",
+       "6               4.6             3.4              1.4            0.30   \n",
+       "7               5.0             3.4              1.5            0.25   \n",
+       "8               4.4             2.9              1.4            0.25   \n",
+       "9               4.9             3.1              1.5            0.25   \n",
+       "10              5.4             3.7              1.5            0.25   \n",
+       "11              4.8             3.4              1.6            0.25   \n",
+       "12              4.8             3.0              1.4            0.10   \n",
+       "13              5.7             3.0              1.1            0.10   \n",
+       "14              5.8             4.0              1.2            0.20   \n",
+       "\n",
+       "          class  \n",
+       "0   Iris-setosa  \n",
+       "1   Iris-setosa  \n",
+       "2   Iris-setosa  \n",
+       "3   Iris-setosa  \n",
+       "4   Iris-setosa  \n",
+       "5   Iris-setosa  \n",
+       "6   Iris-setosa  \n",
+       "7   Iris-setosa  \n",
+       "8   Iris-setosa  \n",
+       "9   Iris-setosa  \n",
+       "10  Iris-setosa  \n",
+       "11  Iris-setosa  \n",
+       "12  Iris-setosa  \n",
+       "13  Iris-setosa  \n",
+       "14  Iris-setosa  "
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris2 = pd.concat(lista)\n",
+    "iris2.head(15)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "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>sepal_length_cm</th>\n",
+       "      <th>sepal_width_cm</th>\n",
+       "      <th>petal_length_cm</th>\n",
+       "      <th>petal_width_cm</th>\n",
+       "      <th>class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>5.1</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4.9</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>4.7</td>\n",
+       "      <td>3.2</td>\n",
+       "      <td>1.3</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4.6</td>\n",
+       "      <td>3.1</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5.0</td>\n",
+       "      <td>3.6</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>5.4</td>\n",
+       "      <td>3.9</td>\n",
+       "      <td>1.7</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>4.6</td>\n",
+       "      <td>3.4</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>5.0</td>\n",
+       "      <td>3.4</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>4.4</td>\n",
+       "      <td>2.9</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>4.9</td>\n",
+       "      <td>3.1</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>5.4</td>\n",
+       "      <td>3.7</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>4.8</td>\n",
+       "      <td>3.4</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>4.8</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>0.10</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>5.7</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.1</td>\n",
+       "      <td>0.10</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>5.8</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.2</td>\n",
+       "      <td>0.20</td>\n",
+       "      <td>Iris-setosa</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    sepal_length_cm  sepal_width_cm  petal_length_cm  petal_width_cm  \\\n",
+       "0               5.1             3.5              1.4            0.20   \n",
+       "1               4.9             3.0              1.4            0.20   \n",
+       "2               4.7             3.2              1.3            0.20   \n",
+       "3               4.6             3.1              1.5            0.20   \n",
+       "4               5.0             3.6              1.4            0.20   \n",
+       "5               5.4             3.9              1.7            0.40   \n",
+       "6               4.6             3.4              1.4            0.30   \n",
+       "7               5.0             3.4              1.5            0.25   \n",
+       "8               4.4             2.9              1.4            0.25   \n",
+       "9               4.9             3.1              1.5            0.25   \n",
+       "10              5.4             3.7              1.5            0.25   \n",
+       "11              4.8             3.4              1.6            0.25   \n",
+       "12              4.8             3.0              1.4            0.10   \n",
+       "13              5.7             3.0              1.1            0.10   \n",
+       "14              5.8             4.0              1.2            0.20   \n",
+       "\n",
+       "          class  \n",
+       "0   Iris-setosa  \n",
+       "1   Iris-setosa  \n",
+       "2   Iris-setosa  \n",
+       "3   Iris-setosa  \n",
+       "4   Iris-setosa  \n",
+       "5   Iris-setosa  \n",
+       "6   Iris-setosa  \n",
+       "7   Iris-setosa  \n",
+       "8   Iris-setosa  \n",
+       "9   Iris-setosa  \n",
+       "10  Iris-setosa  \n",
+       "11  Iris-setosa  \n",
+       "12  Iris-setosa  \n",
+       "13  Iris-setosa  \n",
+       "14  Iris-setosa  "
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "iris.head(15)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/anaconda3/lib/python3.8/site-packages/seaborn/distributions.py:283: UserWarning: Data must have variance to compute a kernel density estimate.\n",
+      "  warnings.warn(msg, UserWarning)\n",
+      "/opt/anaconda3/lib/python3.8/site-packages/seaborn/distributions.py:369: UserWarning: Default bandwidth for data is 0; skipping density estimation.\n",
+      "  warnings.warn(msg, UserWarning)\n",
+      "/opt/anaconda3/lib/python3.8/site-packages/seaborn/distributions.py:283: UserWarning: Data must have variance to compute a kernel density estimate.\n",
+      "  warnings.warn(msg, UserWarning)\n",
+      "/opt/anaconda3/lib/python3.8/site-packages/seaborn/distributions.py:283: UserWarning: Data must have variance to compute a kernel density estimate.\n",
+      "  warnings.warn(msg, UserWarning)\n",
+      "/opt/anaconda3/lib/python3.8/site-packages/seaborn/distributions.py:283: UserWarning: Data must have variance to compute a kernel density estimate.\n",
+      "  warnings.warn(msg, UserWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.PairGrid at 0x7fbc33d64d60>"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 823.25x720 with 20 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "import matplotlib as plt\n",
+    "\n",
+    "sns.pairplot(iris, hue = 'class')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.8.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/module-3/Data-Cleaning-Challenge/iris_data_corrected.csv b/module-3/Data-Cleaning-Challenge/iris_data_corrected.csv
new file mode 100644
index 00000000..a43226fc
--- /dev/null
+++ b/module-3/Data-Cleaning-Challenge/iris_data_corrected.csv
@@ -0,0 +1,151 @@
+,sepal_length_cm,sepal_width_cm,petal_length_cm,petal_width_cm,class
+0,5.1,3.5,1.4,0.2,Iris-setosa
+1,4.9,3.0,1.4,0.2,Iris-setosa
+2,4.7,3.2,1.3,0.2,Iris-setosa
+3,4.6,3.1,1.5,0.2,Iris-setosa
+4,5.0,3.6,1.4,0.2,Iris-setosa
+5,5.4,3.9,1.7,0.4,Iris-setosa
+6,4.6,3.4,1.4,0.3,Iris-setosa
+7,5.0,3.4,1.5,0.25,Iris-setosa
+8,4.4,2.9,1.4,0.25,Iris-setosa
+9,4.9,3.1,1.5,0.25,Iris-setosa
+10,5.4,3.7,1.5,0.25,Iris-setosa
+11,4.8,3.4,1.6,0.25,Iris-setosa
+12,4.8,3.0,1.4,0.1,Iris-setosa
+13,5.7,3.0,1.1,0.1,Iris-setosa
+14,5.8,4.0,1.2,0.2,Iris-setosa
+15,5.7,4.4,1.5,0.4,Iris-setosa
+16,5.4,3.9,1.3,0.4,Iris-setosa
+17,5.1,3.5,1.4,0.3,Iris-setosa
+19,5.1,3.8,1.5,0.3,Iris-setosa
+20,5.4,3.4,1.7,0.2,Iris-setosa
+21,5.1,3.7,1.5,0.4,Iris-setosa
+22,4.6,3.6,1.0,0.2,Iris-setosa
+23,5.1,3.3,1.7,0.5,Iris-setosa
+24,4.8,3.4,1.9,0.2,Iris-setosa
+25,5.0,3.0,1.6,0.2,Iris-setosa
+26,5.0,3.4,1.6,0.4,Iris-setosa
+27,5.2,3.5,1.5,0.2,Iris-setosa
+28,5.2,3.4,1.4,0.2,Iris-setosa
+29,4.7,3.2,1.6,0.2,Iris-setosa
+30,4.8,3.1,1.6,0.2,Iris-setosa
+31,5.4,3.4,1.5,0.4,Iris-setosa
+32,5.2,4.1,1.5,0.1,Iris-setosa
+33,5.5,4.2,1.4,0.2,Iris-setosa
+34,4.9,3.1,1.5,0.1,Iris-setosa
+35,5.0,3.2,1.2,0.2,Iris-setosa
+36,5.5,3.5,1.3,0.2,Iris-setosa
+37,4.9,3.1,1.5,0.1,Iris-setosa
+38,4.4,3.0,1.3,0.2,Iris-setosa
+39,5.1,3.4,1.5,0.2,Iris-setosa
+40,5.0,3.5,1.3,0.3,Iris-setosa
+41,4.5,2.3,1.3,0.3,Iris-setosa
+42,4.4,3.2,1.3,0.2,Iris-setosa
+43,5.0,3.5,1.6,0.6,Iris-setosa
+44,5.1,3.8,1.9,0.4,Iris-setosa
+45,4.8,3.0,1.4,0.3,Iris-setosa
+46,5.1,3.8,1.6,0.2,Iris-setosa
+47,4.6,3.2,1.4,0.2,Iris-setosa
+48,5.3,3.7,1.5,0.2,Iris-setosa
+49,5.0,3.3,1.4,0.2,Iris-setosa
+18,5.7,3.8,1.7,0.3,Iris-setossa
+50,7.0,3.2,4.7,1.4,Iris-versicolor
+51,6.4,3.2,4.5,1.5,Iris-versicolor
+52,6.9,3.1,4.9,1.5,Iris-versicolor
+53,5.5,2.3,4.0,1.3,Iris-versicolor
+54,6.5,2.8,4.6,1.5,Iris-versicolor
+55,5.7,2.8,4.5,1.3,Iris-versicolor
+56,6.3,3.3,4.7,1.6,Iris-versicolor
+57,4.9,2.4,3.3,1.0,Iris-versicolor
+58,6.6,2.9,4.6,1.3,Iris-versicolor
+59,5.2,2.7,3.9,1.4,Iris-versicolor
+60,5.0,2.0,3.5,1.0,Iris-versicolor
+61,5.9,3.0,4.2,1.5,Iris-versicolor
+62,6.0,2.2,4.0,1.0,Iris-versicolor
+63,6.1,2.9,4.7,1.4,Iris-versicolor
+64,5.6,2.9,3.6,1.3,Iris-versicolor
+65,6.7,3.1,4.4,1.4,Iris-versicolor
+66,5.6,3.0,4.5,1.5,Iris-versicolor
+67,5.8,2.7,4.1,1.0,Iris-versicolor
+68,6.2,2.2,4.5,1.5,Iris-versicolor
+69,5.6,2.5,3.9,1.1,Iris-versicolor
+70,5.9,3.2,4.8,1.8,Iris-versicolor
+71,6.1,2.8,4.0,1.3,Iris-versicolor
+72,6.3,2.5,4.9,1.5,Iris-versicolor
+73,6.1,2.8,4.7,1.2,Iris-versicolor
+74,6.4,2.9,4.3,1.3,Iris-versicolor
+75,6.6,3.0,4.4,1.4,Iris-versicolor
+76,6.8,2.8,4.8,1.4,Iris-versicolor
+77,0.067,3.0,5.0,1.7,Iris-versicolor
+78,0.06,2.9,4.5,1.5,Iris-versicolor
+79,0.057,2.6,3.5,1.0,Iris-versicolor
+80,0.055,2.4,3.8,1.1,Iris-versicolor
+81,0.055,2.4,3.7,1.0,Iris-versicolor
+82,5.8,2.7,3.9,1.2,Iris-versicolor
+83,6.0,2.8,5.1,1.6,Iris-versicolor
+84,5.4,3.0,4.5,1.5,Iris-versicolor
+85,6.0,3.4,4.5,1.6,Iris-versicolor
+86,6.7,3.1,4.7,1.5,Iris-versicolor
+87,6.3,2.3,4.4,1.3,Iris-versicolor
+88,5.6,3.0,4.1,1.3,Iris-versicolor
+89,5.5,2.5,4.0,1.3,Iris-versicolor
+90,5.5,2.6,4.4,1.2,Iris-versicolor
+91,6.1,3.0,4.6,1.4,Iris-versicolor
+92,5.8,2.6,4.0,1.2,Iris-versicolor
+93,5.0,2.3,3.3,1.0,Iris-versicolor
+94,5.6,2.7,4.2,1.3,Iris-versicolor
+95,5.7,3.0,4.2,1.2,versicolor
+96,5.7,2.9,4.2,1.3,versicolor
+97,6.2,2.9,4.3,1.3,versicolor
+98,5.1,2.5,3.0,1.1,versicolor
+99,5.7,2.8,4.1,1.3,versicolor
+100,6.3,3.3,6.0,2.5,Iris-virginica
+101,5.8,2.7,5.1,1.9,Iris-virginica
+102,7.1,3.0,5.9,2.1,Iris-virginica
+103,6.3,2.9,5.6,1.8,Iris-virginica
+104,6.5,3.0,5.8,2.2,Iris-virginica
+105,7.6,3.0,6.6,2.1,Iris-virginica
+106,4.9,2.5,4.5,1.7,Iris-virginica
+107,7.3,2.9,6.3,1.8,Iris-virginica
+108,6.7,2.5,5.8,1.8,Iris-virginica
+109,7.2,3.6,6.1,2.5,Iris-virginica
+110,6.5,3.2,5.1,2.0,Iris-virginica
+111,6.4,2.7,5.3,1.9,Iris-virginica
+112,6.8,3.0,5.5,2.1,Iris-virginica
+113,5.7,2.5,5.0,2.0,Iris-virginica
+114,5.8,2.8,5.1,2.4,Iris-virginica
+115,6.4,3.2,5.3,2.3,Iris-virginica
+116,6.5,3.0,5.5,1.8,Iris-virginica
+117,7.7,3.8,6.7,2.2,Iris-virginica
+118,7.7,2.6,6.9,2.3,Iris-virginica
+119,6.0,2.2,5.0,1.5,Iris-virginica
+120,6.9,3.2,5.7,2.3,Iris-virginica
+121,5.6,2.8,4.9,2.0,Iris-virginica
+122,5.6,2.8,6.7,2.0,Iris-virginica
+123,6.3,2.7,4.9,1.8,Iris-virginica
+124,6.7,3.3,5.7,2.1,Iris-virginica
+125,7.2,3.2,6.0,1.8,Iris-virginica
+126,6.2,2.8,4.8,1.8,Iris-virginica
+127,6.1,3.0,4.9,1.8,Iris-virginica
+128,6.4,2.8,5.6,2.1,Iris-virginica
+129,7.2,3.0,5.8,1.6,Iris-virginica
+130,7.4,2.8,6.1,1.9,Iris-virginica
+131,7.9,3.8,6.4,2.0,Iris-virginica
+132,6.4,2.8,5.6,2.2,Iris-virginica
+133,6.3,2.8,5.1,1.5,Iris-virginica
+134,6.1,2.6,5.6,1.4,Iris-virginica
+135,7.7,3.0,6.1,2.3,Iris-virginica
+136,6.3,3.4,5.6,2.4,Iris-virginica
+137,6.4,3.1,5.5,1.8,Iris-virginica
+138,6.0,3.0,4.8,1.8,Iris-virginica
+139,6.9,3.1,5.4,2.1,Iris-virginica
+140,6.7,3.1,5.6,2.4,Iris-virginica
+141,6.9,3.1,5.1,2.3,Iris-virginica
+142,5.8,2.7,5.1,1.9,Iris-virginica
+143,6.8,3.2,5.9,2.3,Iris-virginica
+144,6.7,3.3,5.7,2.5,Iris-virginica
+145,6.7,3.0,5.2,2.3,Iris-virginica
+146,6.3,2.5,5.0,2.3,Iris-virginica
+147,6.5,3.0,5.2,2.0,Iris-virginica
+148,6.2,3.4,5.4,2.3,Iris-virginica
+149,5.9,3.0,5.1,1.8,Iris-virginica