diff --git a/your-code/challenge-1.ipynb b/your-code/challenge-1.ipynb
index 9df5e53..7d7d76b 100644
--- a/your-code/challenge-1.ipynb
+++ b/your-code/challenge-1.ipynb
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -35,11 +35,401 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "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>Date</th>\n",
+       "      <th>Calorie burned</th>\n",
+       "      <th>Steps</th>\n",
+       "      <th>Distance</th>\n",
+       "      <th>Floors</th>\n",
+       "      <th>Minutes Sedentary</th>\n",
+       "      <th>Minutes Lightly Active</th>\n",
+       "      <th>Minutes Fairly Active</th>\n",
+       "      <th>Minutes Very Active</th>\n",
+       "      <th>Activity Calories</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Distance_miles</th>\n",
+       "      <th>Days</th>\n",
+       "      <th>Days_encoded</th>\n",
+       "      <th>Work_or_Weekend</th>\n",
+       "      <th>Hours Sleep</th>\n",
+       "      <th>Sleep efficiency</th>\n",
+       "      <th>Yesterday_sleep</th>\n",
+       "      <th>Yesterday_sleep_efficiency</th>\n",
+       "      <th>Months</th>\n",
+       "      <th>Months_encoded</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2015-05-08</td>\n",
+       "      <td>1934</td>\n",
+       "      <td>905</td>\n",
+       "      <td>0.65</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.355</td>\n",
+       "      <td>46</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1680</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.403891</td>\n",
+       "      <td>Friday</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.400000</td>\n",
+       "      <td>92.086331</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2015-05-09</td>\n",
+       "      <td>3631</td>\n",
+       "      <td>18925</td>\n",
+       "      <td>14.11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>611.000</td>\n",
+       "      <td>316</td>\n",
+       "      <td>61</td>\n",
+       "      <td>60</td>\n",
+       "      <td>2248</td>\n",
+       "      <td>...</td>\n",
+       "      <td>8.767545</td>\n",
+       "      <td>Saturday</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7.566667</td>\n",
+       "      <td>92.464358</td>\n",
+       "      <td>6.400000</td>\n",
+       "      <td>92.086331</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2015-05-10</td>\n",
+       "      <td>3204</td>\n",
+       "      <td>14228</td>\n",
+       "      <td>10.57</td>\n",
+       "      <td>1</td>\n",
+       "      <td>602.000</td>\n",
+       "      <td>226</td>\n",
+       "      <td>14</td>\n",
+       "      <td>77</td>\n",
+       "      <td>1719</td>\n",
+       "      <td>...</td>\n",
+       "      <td>6.567891</td>\n",
+       "      <td>Sunday</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6.450000</td>\n",
+       "      <td>88.761468</td>\n",
+       "      <td>7.566667</td>\n",
+       "      <td>92.464358</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2015-05-11</td>\n",
+       "      <td>2673</td>\n",
+       "      <td>6756</td>\n",
+       "      <td>5.02</td>\n",
+       "      <td>8</td>\n",
+       "      <td>749.000</td>\n",
+       "      <td>190</td>\n",
+       "      <td>23</td>\n",
+       "      <td>4</td>\n",
+       "      <td>9620</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.119282</td>\n",
+       "      <td>Monday</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.183333</td>\n",
+       "      <td>88.857143</td>\n",
+       "      <td>6.450000</td>\n",
+       "      <td>88.761468</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2015-05-12</td>\n",
+       "      <td>2495</td>\n",
+       "      <td>502</td>\n",
+       "      <td>3.73</td>\n",
+       "      <td>1</td>\n",
+       "      <td>876.000</td>\n",
+       "      <td>171</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7360</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.317714</td>\n",
+       "      <td>Tuesday</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.783333</td>\n",
+       "      <td>82.892057</td>\n",
+       "      <td>5.183333</td>\n",
+       "      <td>88.857143</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>362</th>\n",
+       "      <td>2016-05-03</td>\n",
+       "      <td>3796</td>\n",
+       "      <td>18588</td>\n",
+       "      <td>14.13</td>\n",
+       "      <td>16</td>\n",
+       "      <td>599.000</td>\n",
+       "      <td>275</td>\n",
+       "      <td>49</td>\n",
+       "      <td>79</td>\n",
+       "      <td>236</td>\n",
+       "      <td>...</td>\n",
+       "      <td>8.779972</td>\n",
+       "      <td>Tuesday</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.283333</td>\n",
+       "      <td>91.951220</td>\n",
+       "      <td>5.233333</td>\n",
+       "      <td>90.229885</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>363</th>\n",
+       "      <td>2016-05-04</td>\n",
+       "      <td>3525</td>\n",
+       "      <td>16382</td>\n",
+       "      <td>12.39</td>\n",
+       "      <td>16</td>\n",
+       "      <td>684.000</td>\n",
+       "      <td>333</td>\n",
+       "      <td>10</td>\n",
+       "      <td>55</td>\n",
+       "      <td>2075</td>\n",
+       "      <td>...</td>\n",
+       "      <td>7.698787</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.766667</td>\n",
+       "      <td>95.081967</td>\n",
+       "      <td>6.283333</td>\n",
+       "      <td>91.951220</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>364</th>\n",
+       "      <td>2016-05-05</td>\n",
+       "      <td>3649</td>\n",
+       "      <td>21913</td>\n",
+       "      <td>16.40</td>\n",
+       "      <td>19</td>\n",
+       "      <td>701.000</td>\n",
+       "      <td>287</td>\n",
+       "      <td>29</td>\n",
+       "      <td>90</td>\n",
+       "      <td>2249</td>\n",
+       "      <td>...</td>\n",
+       "      <td>10.190484</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.666667</td>\n",
+       "      <td>88.888889</td>\n",
+       "      <td>6.766667</td>\n",
+       "      <td>95.081967</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>365</th>\n",
+       "      <td>2016-05-06</td>\n",
+       "      <td>3539</td>\n",
+       "      <td>19023</td>\n",
+       "      <td>14.79</td>\n",
+       "      <td>15</td>\n",
+       "      <td>575.000</td>\n",
+       "      <td>298</td>\n",
+       "      <td>8</td>\n",
+       "      <td>85</td>\n",
+       "      <td>2112</td>\n",
+       "      <td>...</td>\n",
+       "      <td>9.190077</td>\n",
+       "      <td>Friday</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.166667</td>\n",
+       "      <td>89.805825</td>\n",
+       "      <td>4.666667</td>\n",
+       "      <td>88.888889</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>366</th>\n",
+       "      <td>2016-05-07</td>\n",
+       "      <td>304</td>\n",
+       "      <td>9526</td>\n",
+       "      <td>7.08</td>\n",
+       "      <td>2</td>\n",
+       "      <td>564.000</td>\n",
+       "      <td>370</td>\n",
+       "      <td>13</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.399307</td>\n",
+       "      <td>Saturday</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.366667</td>\n",
+       "      <td>89.165187</td>\n",
+       "      <td>6.166667</td>\n",
+       "      <td>89.805825</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>367 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           Date  Calorie burned  Steps  Distance  Floors  Minutes Sedentary  \\\n",
+       "0    2015-05-08            1934    905      0.65       0              1.355   \n",
+       "1    2015-05-09            3631  18925     14.11       4            611.000   \n",
+       "2    2015-05-10            3204  14228     10.57       1            602.000   \n",
+       "3    2015-05-11            2673   6756      5.02       8            749.000   \n",
+       "4    2015-05-12            2495    502      3.73       1            876.000   \n",
+       "..          ...             ...    ...       ...     ...                ...   \n",
+       "362  2016-05-03            3796  18588     14.13      16            599.000   \n",
+       "363  2016-05-04            3525  16382     12.39      16            684.000   \n",
+       "364  2016-05-05            3649  21913     16.40      19            701.000   \n",
+       "365  2016-05-06            3539  19023     14.79      15            575.000   \n",
+       "366  2016-05-07             304   9526      7.08       2            564.000   \n",
+       "\n",
+       "     Minutes Lightly Active  Minutes Fairly Active  Minutes Very Active  \\\n",
+       "0                        46                      0                    0   \n",
+       "1                       316                     61                   60   \n",
+       "2                       226                     14                   77   \n",
+       "3                       190                     23                    4   \n",
+       "4                       171                      0                    0   \n",
+       "..                      ...                    ...                  ...   \n",
+       "362                     275                     49                   79   \n",
+       "363                     333                     10                   55   \n",
+       "364                     287                     29                   90   \n",
+       "365                     298                      8                   85   \n",
+       "366                     370                     13                   10   \n",
+       "\n",
+       "     Activity Calories  ...  Distance_miles       Days  Days_encoded  \\\n",
+       "0                 1680  ...        0.403891     Friday           4.0   \n",
+       "1                 2248  ...        8.767545   Saturday           5.0   \n",
+       "2                 1719  ...        6.567891     Sunday           6.0   \n",
+       "3                 9620  ...        3.119282     Monday           0.0   \n",
+       "4                 7360  ...        2.317714    Tuesday           1.0   \n",
+       "..                 ...  ...             ...        ...           ...   \n",
+       "362                236  ...        8.779972    Tuesday           1.0   \n",
+       "363               2075  ...        7.698787  Wednesday           2.0   \n",
+       "364               2249  ...       10.190484   Thursday           3.0   \n",
+       "365               2112  ...        9.190077     Friday           4.0   \n",
+       "366               1604  ...        4.399307   Saturday           5.0   \n",
+       "\n",
+       "     Work_or_Weekend  Hours Sleep Sleep efficiency  Yesterday_sleep  \\\n",
+       "0                  1     6.400000        92.086331         0.000000   \n",
+       "1                  0     7.566667        92.464358         6.400000   \n",
+       "2                  0     6.450000        88.761468         7.566667   \n",
+       "3                  1     5.183333        88.857143         6.450000   \n",
+       "4                  1     6.783333        82.892057         5.183333   \n",
+       "..               ...          ...              ...              ...   \n",
+       "362                1     6.283333        91.951220         5.233333   \n",
+       "363                1     6.766667        95.081967         6.283333   \n",
+       "364                1     4.666667        88.888889         6.766667   \n",
+       "365                1     6.166667        89.805825         4.666667   \n",
+       "366                0     8.366667        89.165187         6.166667   \n",
+       "\n",
+       "     Yesterday_sleep_efficiency  Months  Months_encoded  \n",
+       "0                      0.000000     May               5  \n",
+       "1                     92.086331     May               5  \n",
+       "2                     92.464358     May               5  \n",
+       "3                     88.761468     May               5  \n",
+       "4                     88.857143     May               5  \n",
+       "..                          ...     ...             ...  \n",
+       "362                   90.229885     May               5  \n",
+       "363                   91.951220     May               5  \n",
+       "364                   95.081967     May               5  \n",
+       "365                   88.888889     May               5  \n",
+       "366                   89.805825     May               5  \n",
+       "\n",
+       "[367 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "# your code here\n",
+    "fitbit = pd.read_csv(\"../data/Fitbit2.csv\")\n",
+    "fitbit"
    ]
   },
   {
@@ -59,20 +449,62 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 42,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "def plot_steps():\n",
+    "    fitbit.groupby(\"Months_encoded\")[\"Steps\"].median().plot(kind=\"bar\", color=\"salmon\", title=\"Avg Steps\", figsize=(12,4))\n",
+    "    plt.xticks(rotation=0.5)\n",
+    "    plt.savefig(\"step.png\") \n",
+    "\n",
+    "plot_steps()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 51,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# your code here\n"
+    "!cd /Users/leonplaza/Desktop/ironhack/lab/lab-matplotlib-seaborn/figures\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# your code here\n",
+    "def plot_steps_wknd():\n",
+    "    fitbit.groupby(\"Work_or_Weekend\")[\"Steps\"].median().plot(kind=\"bar\", color=\"salmon\", title=\"Avg Steps\", figsize=(12,6))\n",
+    "    plt.xticks(rotation=0.5)\n",
+    "    plt.savefig(\"step.png\") \n",
+    "\n",
+    "plot_steps_wknd()"
    ]
   },
   {
@@ -88,9 +520,77 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 61,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def minutes_active_steps(a):\n",
+    "    sns.scatterplot(x=\"Steps\", y=a, data=fitbit,);\n",
+    "    \n",
+    "    \n",
+    "a = [\"Minutes Sedentary\", \"Minutes Lightly Active\", \"Minutes Very Active\"]\n",
+    "for i in minutes:\n",
+    "    minutes_active_steps(i)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.scatterplot(fitbit, x=\"Minutes Very Active\", y=\"Steps\");"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0       0\n",
+       "1      60\n",
+       "2      77\n",
+       "3       4\n",
+       "4       0\n",
+       "       ..\n",
+       "362    79\n",
+       "363    55\n",
+       "364    90\n",
+       "365    85\n",
+       "366    10\n",
+       "Name: Minutes Very Active, Length: 367, dtype: int64"
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": []
   }
  ],
@@ -111,7 +611,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.11.5"
   },
   "nbTranslate": {
    "displayLangs": [
diff --git a/your-code/challenge-2.ipynb b/your-code/challenge-2.ipynb
index d7465f0..76f404e 100644
--- a/your-code/challenge-2.ipynb
+++ b/your-code/challenge-2.ipynb
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -36,13 +36,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 56,
    "metadata": {
     "scrolled": true
    },
    "outputs": [],
    "source": [
-    "# your code here\n"
+    "# your code here\n",
+    "titanic = pd.read_csv(\"../data/titanic.csv\")"
    ]
   },
   {
@@ -52,13 +53,6 @@
     "#### Explore the titanic dataset using Pandas dtypes."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -74,6 +68,36 @@
    "outputs": [],
    "source": []
   },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['PassengerId',\n",
+       " 'Pclass',\n",
+       " 'SibSp',\n",
+       " 'Parch',\n",
+       " 'Name',\n",
+       " 'Gender',\n",
+       " 'Ticket',\n",
+       " 'Cabin',\n",
+       " 'Embarked']"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "categorical = [z for x in [list(titanic.select_dtypes(include=\"int\").columns),(list(titanic.select_dtypes(include=\"object\").columns))] for z in x]\n",
+    "numerical = list(titanic.select_dtypes(include=\"float\").columns)\n",
+    "categorical"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -84,11 +108,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# your code here\n"
+    "# your code here\n",
+    "sns.set_style(\"whitegrid\")"
    ]
   },
   {
@@ -100,11 +125,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "# your code here\n",
+    "sns.histplot(x=titanic.Age, bins=6);"
    ]
   },
   {
@@ -122,6 +159,11 @@
    "source": [
     "\"\"\"\n",
     "your comments here\n",
+    "\n",
+    "Bins have an interval of values, this range captures a set of values so bins represent the \n",
+    "frequency of the values within the range. The size of the bins affects the number of bins in \n",
+    "the plot, the bigger the range of the bin the smaller the total of bins present.\n",
+    "\n",
     "\"\"\""
    ]
   },
@@ -135,12 +177,111 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 67,
+   "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>PassengerId</th>\n",
+       "      <th>Survived</th>\n",
+       "      <th>Pclass</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Age</th>\n",
+       "      <th>SibSp</th>\n",
+       "      <th>Parch</th>\n",
+       "      <th>Ticket</th>\n",
+       "      <th>Fare</th>\n",
+       "      <th>Cabin</th>\n",
+       "      <th>Embarked</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Gender</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>female</th>\n",
+       "      <td>466</td>\n",
+       "      <td>314</td>\n",
+       "      <td>466</td>\n",
+       "      <td>466</td>\n",
+       "      <td>466</td>\n",
+       "      <td>466</td>\n",
+       "      <td>466</td>\n",
+       "      <td>466</td>\n",
+       "      <td>466</td>\n",
+       "      <td>466</td>\n",
+       "      <td>466</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>male</th>\n",
+       "      <td>843</td>\n",
+       "      <td>577</td>\n",
+       "      <td>843</td>\n",
+       "      <td>843</td>\n",
+       "      <td>843</td>\n",
+       "      <td>843</td>\n",
+       "      <td>843</td>\n",
+       "      <td>843</td>\n",
+       "      <td>843</td>\n",
+       "      <td>843</td>\n",
+       "      <td>843</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        PassengerId  Survived  Pclass  Name  Age  SibSp  Parch  Ticket  Fare  \\\n",
+       "Gender                                                                         \n",
+       "female          466       314     466   466  466    466    466     466   466   \n",
+       "male            843       577     843   843  843    843    843     843   843   \n",
+       "\n",
+       "        Cabin  Embarked  \n",
+       "Gender                   \n",
+       "female    466       466  \n",
+       "male      843       843  "
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Method 1 - matplotlib\n",
-    "# your code here"
+    "# your code here\n",
+    "titanic.groupby(by=\"Gender\").agg(\"count\")"
    ]
   },
   {
@@ -150,7 +291,8 @@
    "outputs": [],
    "source": [
     "# Method 2 - seaborn\n",
-    "# your code here"
+    "# your code here\n",
+    "sns.countplot(titanic, x=\"Gender\");"
    ]
   },
   {
@@ -318,7 +460,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.11.5"
   },
   "nbTranslate": {
    "displayLangs": [