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92 changes: 92 additions & 0 deletions data-preparation.ipynb
Original file line number Diff line number Diff line change
@@ -0,0 +1,92 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "eda9759b",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"original = pd.read_csv(\"data/smoker_train.csv\")\n",
"\n",
"# Number of Rows\n",
"# Original: 38984\n",
"# Ohne Duplikate: 33467\n",
"# Ohne Nullwerte: 33467\n",
"# Real. Blutdruck: 33467 \n",
"# Cholesterin: 33344\n",
"# BMI: 33340\n",
"# Anderes: 33302"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "94a8e555",
"metadata": {},
"outputs": [],
"source": [
"def clean_up(df):\n",
" # Duplikate Löschen\n",
" x = df.drop_duplicates()\n",
" \n",
" # Delete rows with null values\n",
" x = x.dropna()\n",
" \n",
" # Delete rows with impossible blood pressure values\n",
" x = x[x[\"systolic\"] > x[\"relaxation\"]]\n",
" \n",
" # Cholesterin\n",
" x = x[abs(x[\"Cholesterol\"] - x[\"HDL\"] - x[\"LDL\"] - x[\"triglyceride\"] / 5) < 30]\n",
" \n",
" # BMI > 16\n",
" x = x[(x[\"weight(kg)\"] / ((x[\"height(cm)\"] / 100) ** 2)) >= 15]\n",
" \n",
" # Anderes -> 10-facher Normbereich\n",
" x = x[x[\"AST\"] < 500] # 8 Werte\n",
" x = x[x[\"ALT\"] < 500] # 4 Werte\n",
" x = x[x[\"Gtp\"] < 660] # 26 Werte\n",
" x = x[x[\"hemoglobin\"] < 180] # 0 Werte\n",
" x = x[x[\"serum creatinine\"] < 12] # 0 Werte\n",
" x = x[x[\"fasting blood sugar\"] < 1000] # 0 Werte\n",
" \n",
" return x \n",
"\n",
"print(len(clean_up(original)))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "19704c5b",
"metadata": {},
"outputs": [],
"source": [
"y = original[\"fasting blood sugar\"].sort_values()\n",
"y.tail(30)"
]
}
],
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"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
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"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.4"
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