123 lines
3.4 KiB
Plaintext
123 lines
3.4 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 64,
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"id": "8b07c9a5-e5cf-4cf9-a6d9-e784eb109fef",
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"metadata": {},
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"outputs": [],
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"source": [
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"import re"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 65,
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"id": "fce94c21-6792-4938-bf2c-3f46ecf2f954",
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"metadata": {},
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"outputs": [],
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"source": [
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"states = ['Alabama', 'Alaska', 'Arizona', 'Arkansas', 'California', 'Colorado', 'Connecticut', 'Delaware', 'Florida', 'Georgia', \n",
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" 'Hawaii', 'Idaho', 'Illinois', 'Indiana', 'Kansas', 'Kentucky', 'Louisiana', 'Maine', 'Maryland', \n",
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" 'Massachusetts', 'Michigan', 'Minnesota', 'Mississippi', 'Missouri', 'Nebraska', 'Nevada', 'New Hampshire', 'New Jersey', \n",
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" 'New Mexico', 'New York', 'North Carolina', 'North Dakota', 'Ohio', 'Oklahoma', 'Pennsylvania', 'Rhode Island', 'South Carolina', \n",
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" 'South Dakota', 'Tennessee', 'Texas', 'Vermont', 'Virginia', 'Washington', 'West Virginia', 'Wisconsin', 'Wyoming']"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 66,
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"id": "eb1815f2-1876-4437-833a-ff22de81685e",
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"metadata": {},
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"outputs": [],
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"source": [
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"def counter(text_in, query):\n",
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" pattern = re.compile(query)\n",
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" return len(pattern.findall(text_in, re.IGNORECASE))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 67,
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"id": "8729062d-87b8-4111-a216-8500334f54b6",
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"metadata": {},
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"outputs": [],
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"source": [
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"def state_prediction(text_in):\n",
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" state_dict = {}\n",
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" for state in states:\n",
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" state_dict[state.replace(\" \", \"_\")] = counter(text_in, state) \n",
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" return max(state_dict, key=state_dict.get)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 68,
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"id": "ea8069f7-de8e-454c-8eac-9fb7cc0df626",
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"metadata": {},
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"outputs": [],
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"source": [
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"def jurisdiction(path_in, path_out): \n",
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" with open(path_in, 'r', encoding='utf8') as file:\n",
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" lines = file.readlines()\n",
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" with open(path_out, 'wt')as file_out:\n",
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" for i in lines:\n",
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" file_out.write(\"jurisdiction=\"+str(state_prediction(i))+'\\n') \n",
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" file_out.close()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 69,
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"id": "ade45bfb-9eaa-4b2b-bba1-6cfcaf0a9ce6",
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"metadata": {},
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"outputs": [],
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"source": [
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"jurisdiction('dev-0/in.tsv', 'dev-0/out.tsv')\n",
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"jurisdiction('train/in.tsv', 'train/out.tsv')\n",
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"jurisdiction('test-A/in.tsv', 'test-A/out.tsv')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 63,
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"id": "594a25a9-a0ce-4de9-82c8-df50a4ecac39",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[NbConvertApp] Converting notebook run.ipynb to script\n",
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"[NbConvertApp] Writing 1605 bytes to run.py\n"
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]
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}
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],
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"source": [
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"!jupyter nbconvert --to script run.ipynb"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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