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deuxieme essai
2023-05-04 13:42:53 +02:00
{
"cells": [
{
"cell_type": "code",
modification
2023-05-04 13:53:50 +02:00
"execution_count": 2,
deuxieme essai
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"id": "c6b75e30-ce16-46c4-ab91-9ec69b3a5a9a",
modification
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"metadata": {
"tags": []
},
deuxieme essai
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"outputs": [],
"source": [
"url = \"https://archive.ics.uci.edu/ml/machine-learning-databases/heart-disease/processed.cleveland.data\""
]
},
{
"cell_type": "code",
modification
2023-05-04 13:53:50 +02:00
"execution_count": 3,
deuxieme essai
2023-05-04 13:42:53 +02:00
"id": "617f1d2a-49ab-4a1b-840c-73ca28e70ae1",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"#Importation des données \n",
"import pandas as pd\n",
modification
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"import seaborn as sns\n",
deuxieme essai
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"data = pd.io.parsers.read_csv(url)"
]
},
{
"cell_type": "code",
modification
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"execution_count": 4,
deuxieme essai
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"id": "ec96f94d-f855-42c0-b056-0520af40a8f5",
"metadata": {
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deuxieme essai
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" 0 1 2 3 4 5 \\\n",
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"metadata": {},
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"id": "de75f7d4-dad0-451d-bdf8-5b2f32b7d34a",
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{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data[1].value_counts().plot.bar()"
]
},
{
"cell_type": "code",
modification
2023-05-04 13:53:50 +02:00
"execution_count": 7,
deuxieme essai
2023-05-04 13:42:53 +02:00
"id": "973dcd7c-4c13-4992-bd5a-21419c245e11",
modification
2023-05-04 13:53:50 +02:00
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: >"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data)"
]
deuxieme essai
2023-05-04 13:42:53 +02:00
},
{
"cell_type": "code",
"execution_count": null,
"id": "b13946d0-7731-459d-b1bd-e2a89752df0e",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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