From 2325f8d11e9468af0c35939ce6bd9022f24183b7 Mon Sep 17 00:00:00 2001 From: Angel Heredia Uscanga Date: Thu, 14 Jul 2022 12:27:00 -0600 Subject: [PATCH] Lab Resuelto, estuvo pesadon, tengo que repasar aun mas este tema sobre todo con documentos y pandas --- lab-list-comprehensions/your-code/main.ipynb | 605 +++++++++++++++++-- 1 file changed, 570 insertions(+), 35 deletions(-) diff --git a/lab-list-comprehensions/your-code/main.ipynb b/lab-list-comprehensions/your-code/main.ipynb index 9860215..e764bb1 100644 --- a/lab-list-comprehensions/your-code/main.ipynb +++ b/lab-list-comprehensions/your-code/main.ipynb @@ -11,7 +11,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -29,10 +29,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "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": [ + "lst = []\n", + "lst =[i for i in range(1,51)]\n", + "print(lst)" + ] }, { "cell_type": "markdown", @@ -43,10 +55,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "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": [ + "lst = []\n", + "lst = [i for i in range(2,201,2)]\n", + "print(lst)\n" + ] }, { "cell_type": "markdown", @@ -57,7 +81,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -75,10 +99,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.84062117, 0.48006452, 0.7876326, 0.77109654, 0.44409793, 0.09014516, 0.81835917, 0.87645456, 0.7066597, 0.09610873, 0.41247947, 0.57433389, 0.29960807, 0.42315023, 0.34452557, 0.4751035, 0.17003563, 0.46843998, 0.92796258, 0.69814654, 0.41290051, 0.19561071, 0.16284783, 0.97016248, 0.71725408, 0.87702738, 0.31244595, 0.76615487, 0.20754036, 0.57871812, 0.07214068, 0.40356048, 0.12149553, 0.53222417, 0.9976855, 0.12536346, 0.80930099, 0.50962849, 0.94555126, 0.33364763]\n" + ] + } + ], + "source": [ + "lst = []\n", + "lst = [y for x in a for y in x]\n", + "print(lst)" + ] }, { "cell_type": "markdown", @@ -89,10 +125,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.84062117, 0.7876326, 0.77109654, 0.81835917, 0.87645456, 0.7066597, 0.57433389, 0.92796258, 0.69814654, 0.97016248, 0.71725408, 0.87702738, 0.76615487, 0.57871812, 0.53222417, 0.9976855, 0.80930099, 0.50962849, 0.94555126]\n" + ] + } + ], + "source": [ + "lst = [y for x in a for y in x if y>=0.5]\n", + "print(lst)" + ] }, { "cell_type": "markdown", @@ -103,7 +150,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -125,10 +172,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "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": [ + "lst = []\n", + "lst = [z for x in b for y in x for z in y]\n", + "print(lst)" + ] }, { "cell_type": "markdown", @@ -139,10 +198,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.08147297, 0.06833034, 0.30296619, 0.51293743, 0.45850679, 0.11434044, 0.10708681, 0.47984544, 0.23760688]\n" + ] + } + ], + "source": [ + "lst=[]\n", + "lst = [y[-1] for x in b for y in x if (y<=0.5).any()]\n", + "print(lst)" + ] }, { "cell_type": "markdown", @@ -153,10 +224,35 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "['sample_file_0.csv',\n", + " 'sample_file_1.csv',\n", + " 'sample_file_2.csv',\n", + " 'sample_file_3.csv',\n", + " 'sample_file_4.csv',\n", + " 'sample_file_5.csv',\n", + " 'sample_file_6.csv',\n", + " 'sample_file_7.csv',\n", + " 'sample_file_8.csv',\n", + " 'sample_file_9.csv']" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "path = '../data'\n", + "lst=[]\n", + "lst = [i for i in os.listdir('../data') if i.endswith('.csv')]\n", + "lst" + ] }, { "cell_type": "markdown", @@ -167,10 +263,337 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
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Use a list comprehension to extract and print all values from the data set that are between 0.7 and 0.75." ] }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[0.7347510852128797,\n", + " 0.7343092314001137,\n", + " 0.7490680818183477,\n", + " 0.7390312927111312,\n", + " 0.7159290265157912,\n", + " 0.7356923324968598,\n", + " 0.7357618655811269,\n", + " 0.7306642125209889,\n", + " 0.7033930409580709,\n", + " 0.7013619954419494,\n", + " 0.7396561066717461,\n", + " 0.7045750112959754,\n", + " 0.7383982036983279,\n", + " 0.7178166705957928,\n", + " 0.7088042362916818,\n", + " 0.737444918174949,\n", + " 0.7264121114538001,\n", + " 0.7133695725698419,\n", + " 0.7476323136755818,\n", + " 0.726854508853197,\n", + " 0.7111584953876777,\n", + " 0.7008930873050235,\n", + " 0.7209375615129192,\n", + " 0.7303553716733908,\n", + " 0.7274869207330491,\n", + " 0.7025657075988269,\n", + " 0.7298115760258881,\n", + " 0.7294980584878026,\n", + " 0.7215147068185102,\n", + " 0.7130781095091867,\n", + " 0.7393833032570581,\n", + " 0.7258310816144985,\n", + " 0.7358941798147411,\n", + " 0.736029494090402,\n", + " 0.7085098152301276,\n", + " 0.7472962776291713,\n", + " 0.7329024831531535,\n", + " 0.7124169515124726,\n", + " 0.71223975981198,\n", + " 0.7365416322783028,\n", + " 0.7133690799930356,\n", + " 0.7078738356977186,\n", + " 0.7032248108904495,\n", + " 0.7196096371031628,\n", + " 0.7244863338885654,\n", + " 0.7321533684342264,\n", + " 0.7376946446827494,\n", + " 0.7132714209987683,\n", + " 0.7023481768180954,\n", + " 0.7051334608870933,\n", + " 0.7280006345208285,\n", + " 0.7150799992177622,\n", + " 0.7321333453970806,\n", + " 0.7173964318670598]" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lst6 = [y for x in data_frames.values for y in x if y < 0.75 and y > 0.7]\n", + "lst6" + ] + }, { "cell_type": "code", "execution_count": null, @@ -217,7 +752,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -231,7 +766,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.7" + "version": "3.9.12" } }, "nbformat": 4,