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"cells": [
{
"cell_type": "code",
"execution_count": 5,
"id": "34acba0a-8aab-46e7-a36a-12aff60da3d1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/home/skiredj.abderrahman/khalil/cleaning_data_semantic_model\n"
]
}
],
"source": [
"!pwd"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "059fcee7-dbf9-46d9-a501-d744e48b5a9c",
"metadata": {},
"outputs": [
{
"ename": "UnicodeDecodeError",
"evalue": "'utf-8' codec can't decode byte 0xd9 in position 56: unexpected end of data",
"output_type": "error",
"traceback": [
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
"\u001b[31mUnicodeDecodeError\u001b[39m Traceback (most recent call last)",
"\u001b[36mFile \u001b[39m\u001b[32mpandas/_libs/parsers.pyx:1067\u001b[39m, in \u001b[36mpandas._libs.parsers.TextReader._convert_tokens\u001b[39m\u001b[34m()\u001b[39m\n",
"\u001b[36mFile \u001b[39m\u001b[32mpandas/_libs/parsers.pyx:1227\u001b[39m, in \u001b[36mpandas._libs.parsers.TextReader._convert_with_dtype\u001b[39m\u001b[34m()\u001b[39m\n",
"\u001b[36mFile \u001b[39m\u001b[32mpandas/_libs/parsers.pyx:1240\u001b[39m, in \u001b[36mpandas._libs.parsers.TextReader._string_convert\u001b[39m\u001b[34m()\u001b[39m\n",
"\u001b[36mFile \u001b[39m\u001b[32mpandas/_libs/parsers.pyx:1527\u001b[39m, in \u001b[36mpandas._libs.parsers._string_box_utf8\u001b[39m\u001b[34m()\u001b[39m\n",
"\u001b[31mUnicodeDecodeError\u001b[39m: 'utf-8' codec can't decode byte 0xd9 in position 56: unexpected end of data",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[31mUnicodeDecodeError\u001b[39m Traceback (most recent call last)",
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[9]\u001b[39m\u001b[32m, line 3\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mpandas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mpd\u001b[39;00m\n\u001b[32m 2\u001b[39m dataset28_train = \u001b[33m'\u001b[39m\u001b[33m/home/skiredj.abderrahman/khalil/cleaning_data_semantic_model/train.csv\u001b[39m\u001b[33m'\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m3\u001b[39m ds28_train = \u001b[43mpd\u001b[49m\u001b[43m.\u001b[49m\u001b[43mread_csv\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdataset28_train\u001b[49m\u001b[43m,\u001b[49m\u001b[43mencoding\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mutf-8\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m 4\u001b[39m ds28_train\n",
"\u001b[36mFile \u001b[39m\u001b[32m~/.conda/envs/fatnaoui_jupyter/lib/python3.11/site-packages/pandas/io/parsers/readers.py:873\u001b[39m, in \u001b[36mread_csv\u001b[39m\u001b[34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, skip_blank_lines, parse_dates, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, low_memory, memory_map, float_precision, storage_options, dtype_backend)\u001b[39m\n\u001b[32m 861\u001b[39m kwds_defaults = _refine_defaults_read(\n\u001b[32m 862\u001b[39m dialect,\n\u001b[32m 863\u001b[39m delimiter,\n\u001b[32m (...)\u001b[39m\u001b[32m 869\u001b[39m dtype_backend=dtype_backend,\n\u001b[32m 870\u001b[39m )\n\u001b[32m 871\u001b[39m kwds.update(kwds_defaults)\n\u001b[32m--> \u001b[39m\u001b[32m873\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_read\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n",
"\u001b[36mFile \u001b[39m\u001b[32m~/.conda/envs/fatnaoui_jupyter/lib/python3.11/site-packages/pandas/io/parsers/readers.py:306\u001b[39m, in \u001b[36m_read\u001b[39m\u001b[34m(filepath_or_buffer, kwds)\u001b[39m\n\u001b[32m 303\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m parser\n\u001b[32m 305\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m parser:\n\u001b[32m--> \u001b[39m\u001b[32m306\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mparser\u001b[49m\u001b[43m.\u001b[49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnrows\u001b[49m\u001b[43m)\u001b[49m\n",
"\u001b[36mFile \u001b[39m\u001b[32m~/.conda/envs/fatnaoui_jupyter/lib/python3.11/site-packages/pandas/io/parsers/readers.py:1947\u001b[39m, in \u001b[36mTextFileReader.read\u001b[39m\u001b[34m(self, nrows)\u001b[39m\n\u001b[32m 1940\u001b[39m nrows = validate_integer(\u001b[33m\"\u001b[39m\u001b[33mnrows\u001b[39m\u001b[33m\"\u001b[39m, nrows)\n\u001b[32m 1941\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 1942\u001b[39m \u001b[38;5;66;03m# error: \"ParserBase\" has no attribute \"read\"\u001b[39;00m\n\u001b[32m 1943\u001b[39m (\n\u001b[32m 1944\u001b[39m index,\n\u001b[32m 1945\u001b[39m columns,\n\u001b[32m 1946\u001b[39m col_dict,\n\u001b[32m-> \u001b[39m\u001b[32m1947\u001b[39m ) = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_engine\u001b[49m\u001b[43m.\u001b[49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# type: ignore[attr-defined]\u001b[39;49;00m\n\u001b[32m 1948\u001b[39m \u001b[43m \u001b[49m\u001b[43mnrows\u001b[49m\n\u001b[32m 1949\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1950\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m:\n\u001b[32m 1951\u001b[39m \u001b[38;5;28mself\u001b[39m.close()\n",
"\u001b[36mFile \u001b[39m\u001b[32m~/.conda/envs/fatnaoui_jupyter/lib/python3.11/site-packages/pandas/io/parsers/c_parser_wrapper.py:215\u001b[39m, in \u001b[36mCParserWrapper.read\u001b[39m\u001b[34m(self, nrows)\u001b[39m\n\u001b[32m 213\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 214\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.low_memory:\n\u001b[32m--> \u001b[39m\u001b[32m215\u001b[39m chunks = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_reader\u001b[49m\u001b[43m.\u001b[49m\u001b[43mread_low_memory\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnrows\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 216\u001b[39m \u001b[38;5;66;03m# destructive to chunks\u001b[39;00m\n\u001b[32m 217\u001b[39m data = _concatenate_chunks(chunks, \u001b[38;5;28mself\u001b[39m.names)\n",
"\u001b[36mFile \u001b[39m\u001b[32mpandas/_libs/parsers.pyx:832\u001b[39m, in \u001b[36mpandas._libs.parsers.TextReader.read_low_memory\u001b[39m\u001b[34m()\u001b[39m\n",
"\u001b[36mFile \u001b[39m\u001b[32mpandas/_libs/parsers.pyx:911\u001b[39m, in \u001b[36mpandas._libs.parsers.TextReader._read_rows\u001b[39m\u001b[34m()\u001b[39m\n",
"\u001b[36mFile \u001b[39m\u001b[32mpandas/_libs/parsers.pyx:1009\u001b[39m, in \u001b[36mpandas._libs.parsers.TextReader._convert_column_data\u001b[39m\u001b[34m()\u001b[39m\n",
"\u001b[36mFile \u001b[39m\u001b[32mpandas/_libs/parsers.pyx:1078\u001b[39m, in \u001b[36mpandas._libs.parsers.TextReader._convert_tokens\u001b[39m\u001b[34m()\u001b[39m\n",
"\u001b[36mFile \u001b[39m\u001b[32mpandas/_libs/parsers.pyx:1227\u001b[39m, in \u001b[36mpandas._libs.parsers.TextReader._convert_with_dtype\u001b[39m\u001b[34m()\u001b[39m\n",
"\u001b[36mFile \u001b[39m\u001b[32mpandas/_libs/parsers.pyx:1240\u001b[39m, in \u001b[36mpandas._libs.parsers.TextReader._string_convert\u001b[39m\u001b[34m()\u001b[39m\n",
"\u001b[36mFile \u001b[39m\u001b[32mpandas/_libs/parsers.pyx:1527\u001b[39m, in \u001b[36mpandas._libs.parsers._string_box_utf8\u001b[39m\u001b[34m()\u001b[39m\n",
"\u001b[31mUnicodeDecodeError\u001b[39m: 'utf-8' codec can't decode byte 0xd9 in position 56: unexpected end of data"
]
}
],
"source": [
"import pandas as pd\n",
"dataset28_train = '/home/skiredj.abderrahman/khalil/cleaning_data_semantic_model/train.csv'\n",
"ds28_train = pd.read_csv(dataset28_train,encoding=\"utf-8\")\n",
"ds28_train"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "509e93c0-6e3e-4e95-a958-e6ae363582e3",
"metadata": {},
"outputs": [],
"source": [
"dataset28_val= dataset28_path/'dev.csv'\n",
"ds28_val = pd.read_csv(dataset28_val)\n",
"ds28_val"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4f4b5ea3-9968-4fda-a556-e5dff56069a7",
"metadata": {},
"outputs": [],
"source": [
"dataset28_test = dataset28_path/'test.csv'\n",
"ds28_test = pd.read_csv(dataset28_test)\n",
"ds28_test"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c4319545-d79a-42cf-a571-dbc5e77f3c79",
"metadata": {},
"outputs": [],
"source": [
"frames = [ds28_train,ds28_test, ds28_val]\n",
"ds28= pd.concat(frames)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ffc1f36b-5dcc-4e4a-9f52-25f61124c198",
"metadata": {},
"outputs": [],
"source": [
"ds28 = ds28[(ds28['label']==0)]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b9e7708b-08e6-41d8-9234-7ce1a606ab06",
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"source": []
},
{
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"id": "448b55fc-99ef-45ff-95f9-bf71b41b4142",
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{
"cell_type": "code",
"execution_count": null,
"id": "29396884-3b3c-409f-8dda-2a600c16a83b",
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{
"cell_type": "code",
"execution_count": null,
"id": "d27f0e50-0e88-4121-add5-d70cc11a5afc",
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{
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"id": "e20139b4-7ccc-48c4-bd95-26e483d9d4ee",
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{
"cell_type": "code",
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"id": "d19a5b00-23d3-49e7-bfc5-0d959ef87965",
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{
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"id": "7d9c2e1d-3c02-450f-bc00-08019e3a6c6c",
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{
"cell_type": "code",
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"id": "ce6734b0-0599-46ee-97d5-42b1c6840473",
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{
"cell_type": "code",
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"id": "9546364c-110f-4d6b-bbf9-881a2080ed51",
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{
"cell_type": "code",
"execution_count": null,
"id": "a6e04d90-6932-4dd6-8cd2-82618d41b23d",
"metadata": {},
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}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
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|