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[Montserrat Labrada] Lab-functional programming #67

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dbf241e
Completed lab-functional programming
MonVala Oct 16, 2022
89dee3e
completed q3
MonVala Oct 16, 2022
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97 changes: 79 additions & 18 deletions lab-functional-programming/your-code/Q3.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 1,
"metadata": {},
"outputs": [
{
Expand All @@ -22,7 +22,7 @@
"[2, 12, 30]"
]
},
"execution_count": 11,
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -44,7 +44,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 2,
"metadata": {},
"outputs": [
{
Expand All @@ -53,7 +53,7 @@
"[2, 12, 30]"
]
},
"execution_count": 10,
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
Expand Down Expand Up @@ -85,13 +85,24 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 3,
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1, 4, 5]\n"
]
}
],
"source": [
"numbers = [1, 4, -1, -100, 0, 5, -99]\n",
"\n",
"# Enter your code below"
"# Enter your code below\n",
"\n",
"positive_numbers=list(filter(lambda x: x>0, numbers))\n",
"print(positive_numbers)"
]
},
{
Expand All @@ -113,15 +124,53 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 4,
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: langdetect in c:\\users\\monla\\anaconda3\\lib\\site-packages (1.0.9)\n",
"Requirement already satisfied: six in c:\\users\\monla\\anaconda3\\lib\\site-packages (from langdetect) (1.16.0)\n",
"Note: you may need to restart the kernel to use updated packages.\n"
]
}
],
"source": [
"import langdetect\n",
"pip install langdetect\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['good morning', 'everyone']\n"
]
},
{
"data": {
"text/plain": [
"'good morning everyone'"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from langdetect import detect\n",
"from functools import reduce\n",
"words = ['good morning', '早上好', 'доброго', 'おはようございます', 'everyone', '大家', 'каждый', 'みんな']\n",
"\n",
"# Enter your code below"
"english_words=list(filter(lambda x: detect(x)=='en',words))\n",
"print(english_words)\n",
"' '.join(english_words)"
]
},
{
Expand All @@ -142,7 +191,7 @@
},
{
"cell_type": "code",
"execution_count": 80,
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -160,9 +209,21 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 7,
"metadata": {},
"outputs": [],
"outputs": [
{
"ename": "ImportError",
"evalue": "cannot import name 'stop_words' from 'sklearn.feature_extraction' (C:\\Users\\monla\\anaconda3\\lib\\site-packages\\sklearn\\feature_extraction\\__init__.py)",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mImportError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [7]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01msklearn\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mfeature_extraction\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m stop_words\n\u001b[0;32m 2\u001b[0m bow \u001b[38;5;241m=\u001b[39m get_bow_from_docs([\n\u001b[0;32m 3\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../../lab-bag-of-words/your-code/doc1.txt\u001b[39m\u001b[38;5;124m'\u001b[39m, \n\u001b[0;32m 4\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../../lab-bag-of-words/your-code/doc2.txt\u001b[39m\u001b[38;5;124m'\u001b[39m, \n\u001b[0;32m 5\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../../lab-bag-of-words/your-code/doc3.txt\u001b[39m\u001b[38;5;124m'\u001b[39m],\n\u001b[0;32m 6\u001b[0m stop_words\u001b[38;5;241m.\u001b[39mENGLISH_STOP_WORDS\n\u001b[0;32m 7\u001b[0m )\n\u001b[0;32m 9\u001b[0m \u001b[38;5;28mprint\u001b[39m(bow)\n",
"\u001b[1;31mImportError\u001b[0m: cannot import name 'stop_words' from 'sklearn.feature_extraction' (C:\\Users\\monla\\anaconda3\\lib\\site-packages\\sklearn\\feature_extraction\\__init__.py)"
]
}
],
"source": [
"from sklearn.feature_extraction import stop_words\n",
"bow = get_bow_from_docs([\n",
Expand All @@ -185,7 +246,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
Expand All @@ -199,9 +260,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.6"
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 2
"nbformat_minor": 4
}
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