diff --git a/lab-list-comprehensions/your-code/main.ipynb b/lab-list-comprehensions/your-code/main.ipynb
index c5931c4..34d8199 100644
--- a/lab-list-comprehensions/your-code/main.ipynb
+++ b/lab-list-comprehensions/your-code/main.ipynb
@@ -11,13 +11,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 85,
    "metadata": {},
    "outputs": [],
    "source": [
     "import os\n",
     "import numpy as np\n",
-    "import pandas as pd"
+    "import pandas as pd\n",
+    "from operator import itemgetter\n",
+    "import os\n",
+    "import glob"
    ]
   },
   {
@@ -29,10 +32,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": "[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]\n"
+    }
+   ],
+   "source": [
+    "consecutive_integers = list(map(lambda x:x,range(1,51)))\n",
+    "print(consecutive_integers)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -43,10 +55,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": "[2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50, 52, 54, 56, 58, 60, 62, 64, 66, 68, 70, 72, 74, 76, 78, 80, 82, 84, 86, 88, 90, 92, 94, 96, 98, 100, 102, 104, 106, 108, 110, 112, 114, 116, 118, 120, 122, 124, 126, 128, 130, 132, 134, 136, 138, 140, 142, 144, 146, 148, 150, 152, 154, 156, 158, 160, 162, 164, 166, 168, 170, 172, 174, 176, 178, 180, 182, 184, 186, 188, 190, 192, 194, 196, 198, 200]\n"
+    }
+   ],
+   "source": [
+    "even_numbers = list(map(lambda x:x*2,range(1,101)))\n",
+    "print(even_numbers)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -57,7 +78,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -75,10 +96,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 29,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": "[[0.84062117, 0.48006452, 0.7876326, 0.77109654],\n [0.44409793, 0.09014516, 0.81835917, 0.87645456],\n [0.7066597, 0.09610873, 0.41247947, 0.57433389],\n [0.29960807, 0.42315023, 0.34452557, 0.4751035],\n [0.17003563, 0.46843998, 0.92796258, 0.69814654],\n [0.41290051, 0.19561071, 0.16284783, 0.97016248],\n [0.71725408, 0.87702738, 0.31244595, 0.76615487],\n [0.20754036, 0.57871812, 0.07214068, 0.40356048],\n [0.12149553, 0.53222417, 0.9976855, 0.12536346],\n [0.80930099, 0.50962849, 0.94555126, 0.33364763]]"
+     },
+     "metadata": {},
+     "execution_count": 29
+    }
+   ],
+   "source": [
+    "a.tolist()"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -89,10 +121,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 28,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": "array([0.84062117, 0.7876326 , 0.77109654, 0.81835917, 0.87645456,\n       0.7066597 , 0.57433389, 0.92796258, 0.69814654, 0.97016248,\n       0.71725408, 0.87702738, 0.76615487, 0.57871812, 0.53222417,\n       0.9976855 , 0.80930099, 0.50962849, 0.94555126])"
+     },
+     "metadata": {},
+     "execution_count": 28
+    }
+   ],
+   "source": [
+    "a[a>=0.5]\n",
+    "    "
+   ]
   },
   {
    "cell_type": "markdown",
@@ -103,7 +147,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 53,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -125,10 +169,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 58,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": "[[[0.55867166, 0.06210792, 0.08147297], [0.82579068, 0.91512478, 0.06833034]], [[0.05440634, 0.65857693, 0.30296619], [0.06769833, 0.96031863, 0.51293743]], [[0.09143215, 0.71893382, 0.45850679], [0.58256464, 0.59005654, 0.56266457]], [[0.71600294, 0.87392666, 0.11434044], [0.8694668, 0.65669313, 0.10708681]], [[0.07529684, 0.46470767, 0.47984544], [0.65368638, 0.14901286, 0.23760688]]]\n"
+    }
+   ],
+   "source": [
+    "b_list = b.tolist()\n",
+    "print(b_list)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -139,10 +192,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 79,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": "[0.06833034, 0.10708681, 0.23760688]\n"
+    }
+   ],
+   "source": [
+    "def Extract(b): \n",
+    "    return [item[1][-1] for item in b]\n",
+    "\n",
+    "list_value = list(Extract(b))\n",
+    "last_value = []\n",
+    "\n",
+    "for i in list_value:\n",
+    "    if i <= 0.5:\n",
+    "        last_value.append(i)\n",
+    "print(last_value)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -153,10 +223,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 83,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": "['sample_file_1.csv', 'sample_file_0.csv', 'sample_file_2.csv', 'sample_file_3.csv', 'sample_file_7.csv', 'sample_file_6.csv', 'sample_file_4.csv', 'sample_file_5.csv', 'sample_file_8.csv', 'sample_file_9.csv']\n"
+    }
+   ],
+   "source": [
+    "files = [f for f in os.listdir('/Users/alejandropalacios/Desktop/Ironhack/Data Analytics Bootcamp/Labs/Lab-list-comprehension/Lab-list-comprehension/lab-list-comprehensions/data') if f.endswith('.csv')]\n",
+    "\n",
+    "print(files)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -167,10 +247,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 93,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": "          0         1         2         3         4         5         6  \\\n0  0.215190  0.155352  0.160848  0.807736  0.363587  0.899832  0.146754   \n1  0.895544  0.955196  0.089925  0.827555  0.089071  0.642883  0.996052   \n2  0.413752  0.693052  0.789796  0.929164  0.536191  0.439769  0.773474   \n3  0.728001  0.348156  0.935787  0.851163  0.444573  0.715080  0.988408   \n4  0.134942  0.875931  0.273505  0.207588  0.080696  0.717396  0.033930   \n\n          7         8         9        10        11        12        13  \\\n0  0.094802  0.705133  0.882762  0.773320  0.687745  0.016789  0.340725   \n1  0.879020  0.421837  0.412141  0.858513  0.217091  0.176157  0.551236   \n2  0.982074  0.876955  0.633154  0.279005  0.483317  0.908288  0.756172   \n3  0.210332  0.732133  0.892383  0.216893  0.367595  0.846208  0.240111   \n4  0.646837  0.888722  0.922742  0.176593  0.861333  0.389451  0.695244   \n\n         14        15        16        17        18        19  \n0  0.984182  0.985461  0.412044  0.867894  0.113432  0.349845  \n1  0.834378  0.419535  0.041431  0.602258  0.984628  0.516899  \n2  0.462130  0.289892  0.145233  0.076819  0.797836  0.197592  \n3  0.471880  0.399721  0.758196  0.665568  0.931542  0.448124  \n4  0.129955  0.364114  0.428224  0.365442  0.847818  0.588319  ",
+      "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>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>4</th>\n      <th>5</th>\n      <th>6</th>\n      <th>7</th>\n      <th>8</th>\n      <th>9</th>\n      <th>10</th>\n      <th>11</th>\n      <th>12</th>\n      <th>13</th>\n      <th>14</th>\n      <th>15</th>\n      <th>16</th>\n      <th>17</th>\n      <th>18</th>\n      <th>19</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.215190</td>\n      <td>0.155352</td>\n      <td>0.160848</td>\n      <td>0.807736</td>\n      <td>0.363587</td>\n      <td>0.899832</td>\n      <td>0.146754</td>\n      <td>0.094802</td>\n      <td>0.705133</td>\n      <td>0.882762</td>\n      <td>0.773320</td>\n      <td>0.687745</td>\n      <td>0.016789</td>\n      <td>0.340725</td>\n      <td>0.984182</td>\n      <td>0.985461</td>\n      <td>0.412044</td>\n      <td>0.867894</td>\n      <td>0.113432</td>\n      <td>0.349845</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0.895544</td>\n      <td>0.955196</td>\n      <td>0.089925</td>\n      <td>0.827555</td>\n      <td>0.089071</td>\n      <td>0.642883</td>\n      <td>0.996052</td>\n      <td>0.879020</td>\n      <td>0.421837</td>\n      <td>0.412141</td>\n      <td>0.858513</td>\n      <td>0.217091</td>\n      <td>0.176157</td>\n      <td>0.551236</td>\n      <td>0.834378</td>\n      <td>0.419535</td>\n      <td>0.041431</td>\n      <td>0.602258</td>\n      <td>0.984628</td>\n      <td>0.516899</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.413752</td>\n      <td>0.693052</td>\n      <td>0.789796</td>\n      <td>0.929164</td>\n      <td>0.536191</td>\n      <td>0.439769</td>\n      <td>0.773474</td>\n      <td>0.982074</td>\n      <td>0.876955</td>\n      <td>0.633154</td>\n      <td>0.279005</td>\n      <td>0.483317</td>\n      <td>0.908288</td>\n      <td>0.756172</td>\n      <td>0.462130</td>\n      <td>0.289892</td>\n      <td>0.145233</td>\n      <td>0.076819</td>\n      <td>0.797836</td>\n      <td>0.197592</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0.728001</td>\n      <td>0.348156</td>\n      <td>0.935787</td>\n      <td>0.851163</td>\n      <td>0.444573</td>\n      <td>0.715080</td>\n      <td>0.988408</td>\n      <td>0.210332</td>\n      <td>0.732133</td>\n      <td>0.892383</td>\n      <td>0.216893</td>\n      <td>0.367595</td>\n      <td>0.846208</td>\n      <td>0.240111</td>\n      <td>0.471880</td>\n      <td>0.399721</td>\n      <td>0.758196</td>\n      <td>0.665568</td>\n      <td>0.931542</td>\n      <td>0.448124</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0.134942</td>\n      <td>0.875931</td>\n      <td>0.273505</td>\n      <td>0.207588</td>\n      <td>0.080696</td>\n      <td>0.717396</td>\n      <td>0.033930</td>\n      <td>0.646837</td>\n      <td>0.888722</td>\n      <td>0.922742</td>\n      <td>0.176593</td>\n      <td>0.861333</td>\n      <td>0.389451</td>\n      <td>0.695244</td>\n      <td>0.129955</td>\n      <td>0.364114</td>\n      <td>0.428224</td>\n      <td>0.365442</td>\n      <td>0.847818</td>\n      <td>0.588319</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
+     },
+     "metadata": {},
+     "execution_count": 93
+    }
+   ],
+   "source": [
+    "path = r'/Users/alejandropalacios/Desktop/Ironhack/Data Analytics Bootcamp/Labs/Lab-list-comprehension/Lab-list-comprehension/lab-list-comprehensions/data'\n",
+    "all_files = glob.glob(path + \"/*.csv\")\n",
+    "\n",
+    "li = []\n",
+    "\n",
+    "for filename in all_files:\n",
+    "    df = pd.read_csv(filename, index_col = None, header = 0)\n",
+    "    li.append(df)\n",
+    "\n",
+    "frame = pd.concat(li, axis = 0, ignore_index = True)\n",
+    "\n",
+    "df.head(10)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -217,9 +320,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3.7.6 64-bit ('anaconda3': virtualenv)",
    "language": "python",
-   "name": "python3"
+   "name": "python37664bitanaconda3virtualenv0697af1ee67a458e9253591065064715"
   },
   "language_info": {
    "codemirror_mode": {
@@ -231,9 +334,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.0"
+   "version": "3.7.6-final"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}
\ No newline at end of file