diff --git a/SL/aufgaben/workshop3/devenv.nix b/SL/aufgaben/workshop3/devenv.nix
index a489fc9..d6838db 100644
--- a/SL/aufgaben/workshop3/devenv.nix
+++ b/SL/aufgaben/workshop3/devenv.nix
@@ -24,5 +24,6 @@
packages = [
pkgs.graphviz
pkgs.zsh
+ pkgs.zlib
];
}
diff --git a/SL/aufgaben/workshop3/src/ws2_feature_engineering.ipynb b/SL/aufgaben/workshop3/src/ws2_feature_engineering.ipynb
deleted file mode 100644
index 17ab6e2..0000000
--- a/SL/aufgaben/workshop3/src/ws2_feature_engineering.ipynb
+++ /dev/null
@@ -1,2023 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "id": "ebe6815d",
- "metadata": {},
- "source": [
- "# Workshop 2 – Feature Engineering & Datenaufbereitung\n",
- "\n",
- "Untersuchung des Melbourne Housing Datasets aus ML-Perspektive.\n",
- "\n",
- "**Punkte:**\n",
- "1. Ungeeignete Variablen identifizieren\n",
- "2. Missing Values – Strategien pro Variable\n",
- "3. Nicht-numerische Variablen – Encoding-Strategien\n",
- "4. Anomalien entdecken\n",
- "5. Empfehlungen formulieren"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "da07c895",
- "metadata": {},
- "source": [
- "## 1. Setup"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 25,
- "id": "c70c47e0",
- "metadata": {},
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import pandas as pd\n",
- "import matplotlib.pyplot as plt\n",
- "import seaborn as sns\n",
- "\n",
- "# plot inline\n",
- "%matplotlib inline\n",
- "\n",
- "# Display-Optionen\n",
- "pd.set_option('display.max_columns', None)\n",
- "pd.set_option('display.width', 200)\n",
- "pd.set_option('display.max_rows', 50)\n",
- "\n",
- "# Plot-Style\n",
- "sns.set_theme(style='whitegrid')\n",
- "plt.rcParams['figure.figsize'] = (10, 5)\n",
- "\n",
- "DATA_PATH = '../data/melb_data.csv'"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "9465aa14",
- "metadata": {},
- "source": [
- "## 2. Daten laden & erste Sichtung"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "id": "9a54f1a6",
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Shape: (18396, 22)\n"
- ]
- },
- {
- "data": {
- "text/html": [
- "
\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " Unnamed: 0 | \n",
- " Suburb | \n",
- " Address | \n",
- " Rooms | \n",
- " Type | \n",
- " Price | \n",
- " Method | \n",
- " SellerG | \n",
- " Date | \n",
- " Distance | \n",
- " Postcode | \n",
- " Bedroom2 | \n",
- " Bathroom | \n",
- " Car | \n",
- " Landsize | \n",
- " BuildingArea | \n",
- " YearBuilt | \n",
- " CouncilArea | \n",
- " Lattitude | \n",
- " Longtitude | \n",
- " Regionname | \n",
- " Propertycount | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " | 0 | \n",
- " 1 | \n",
- " Abbotsford | \n",
- " 85 Turner St | \n",
- " 2 | \n",
- " h | \n",
- " 1480000.0 | \n",
- " S | \n",
- " Biggin | \n",
- " 3/12/2016 | \n",
- " 2.5 | \n",
- " 3067.0 | \n",
- " 2.0 | \n",
- " 1.0 | \n",
- " 1.0 | \n",
- " 202.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " Yarra | \n",
- " -37.7996 | \n",
- " 144.9984 | \n",
- " Northern Metropolitan | \n",
- " 4019.0 | \n",
- "
\n",
- " \n",
- " | 1 | \n",
- " 2 | \n",
- " Abbotsford | \n",
- " 25 Bloomburg St | \n",
- " 2 | \n",
- " h | \n",
- " 1035000.0 | \n",
- " S | \n",
- " Biggin | \n",
- " 4/02/2016 | \n",
- " 2.5 | \n",
- " 3067.0 | \n",
- " 2.0 | \n",
- " 1.0 | \n",
- " 0.0 | \n",
- " 156.0 | \n",
- " 79.0 | \n",
- " 1900.0 | \n",
- " Yarra | \n",
- " -37.8079 | \n",
- " 144.9934 | \n",
- " Northern Metropolitan | \n",
- " 4019.0 | \n",
- "
\n",
- " \n",
- " | 2 | \n",
- " 4 | \n",
- " Abbotsford | \n",
- " 5 Charles St | \n",
- " 3 | \n",
- " h | \n",
- " 1465000.0 | \n",
- " SP | \n",
- " Biggin | \n",
- " 4/03/2017 | \n",
- " 2.5 | \n",
- " 3067.0 | \n",
- " 3.0 | \n",
- " 2.0 | \n",
- " 0.0 | \n",
- " 134.0 | \n",
- " 150.0 | \n",
- " 1900.0 | \n",
- " Yarra | \n",
- " -37.8093 | \n",
- " 144.9944 | \n",
- " Northern Metropolitan | \n",
- " 4019.0 | \n",
- "
\n",
- " \n",
- " | 3 | \n",
- " 5 | \n",
- " Abbotsford | \n",
- " 40 Federation La | \n",
- " 3 | \n",
- " h | \n",
- " 850000.0 | \n",
- " PI | \n",
- " Biggin | \n",
- " 4/03/2017 | \n",
- " 2.5 | \n",
- " 3067.0 | \n",
- " 3.0 | \n",
- " 2.0 | \n",
- " 1.0 | \n",
- " 94.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " Yarra | \n",
- " -37.7969 | \n",
- " 144.9969 | \n",
- " Northern Metropolitan | \n",
- " 4019.0 | \n",
- "
\n",
- " \n",
- " | 4 | \n",
- " 6 | \n",
- " Abbotsford | \n",
- " 55a Park St | \n",
- " 4 | \n",
- " h | \n",
- " 1600000.0 | \n",
- " VB | \n",
- " Nelson | \n",
- " 4/06/2016 | \n",
- " 2.5 | \n",
- " 3067.0 | \n",
- " 3.0 | \n",
- " 1.0 | \n",
- " 2.0 | \n",
- " 120.0 | \n",
- " 142.0 | \n",
- " 2014.0 | \n",
- " Yarra | \n",
- " -37.8072 | \n",
- " 144.9941 | \n",
- " Northern Metropolitan | \n",
- " 4019.0 | \n",
- "
\n",
- " \n",
- "
\n",
- "
"
- ],
- "text/plain": [
- " Unnamed: 0 Suburb Address Rooms Type Price Method SellerG Date Distance Postcode Bedroom2 Bathroom Car Landsize BuildingArea YearBuilt CouncilArea Lattitude \\\n",
- "0 1 Abbotsford 85 Turner St 2 h 1480000.0 S Biggin 3/12/2016 2.5 3067.0 2.0 1.0 1.0 202.0 NaN NaN Yarra -37.7996 \n",
- "1 2 Abbotsford 25 Bloomburg St 2 h 1035000.0 S Biggin 4/02/2016 2.5 3067.0 2.0 1.0 0.0 156.0 79.0 1900.0 Yarra -37.8079 \n",
- "2 4 Abbotsford 5 Charles St 3 h 1465000.0 SP Biggin 4/03/2017 2.5 3067.0 3.0 2.0 0.0 134.0 150.0 1900.0 Yarra -37.8093 \n",
- "3 5 Abbotsford 40 Federation La 3 h 850000.0 PI Biggin 4/03/2017 2.5 3067.0 3.0 2.0 1.0 94.0 NaN NaN Yarra -37.7969 \n",
- "4 6 Abbotsford 55a Park St 4 h 1600000.0 VB Nelson 4/06/2016 2.5 3067.0 3.0 1.0 2.0 120.0 142.0 2014.0 Yarra -37.8072 \n",
- "\n",
- " Longtitude Regionname Propertycount \n",
- "0 144.9984 Northern Metropolitan 4019.0 \n",
- "1 144.9934 Northern Metropolitan 4019.0 \n",
- "2 144.9944 Northern Metropolitan 4019.0 \n",
- "3 144.9969 Northern Metropolitan 4019.0 \n",
- "4 144.9941 Northern Metropolitan 4019.0 "
- ]
- },
- "execution_count": 2,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df = pd.read_csv(DATA_PATH)\n",
- "print(f'Shape: {df.shape}')\n",
- "df.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "id": "8f52d4e6",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\n",
- "RangeIndex: 18396 entries, 0 to 18395\n",
- "Data columns (total 22 columns):\n",
- " # Column Non-Null Count Dtype \n",
- "--- ------ -------------- ----- \n",
- " 0 Unnamed: 0 18396 non-null int64 \n",
- " 1 Suburb 18396 non-null object \n",
- " 2 Address 18396 non-null object \n",
- " 3 Rooms 18396 non-null int64 \n",
- " 4 Type 18396 non-null object \n",
- " 5 Price 18396 non-null float64\n",
- " 6 Method 18396 non-null object \n",
- " 7 SellerG 18396 non-null object \n",
- " 8 Date 18396 non-null object \n",
- " 9 Distance 18395 non-null float64\n",
- " 10 Postcode 18395 non-null float64\n",
- " 11 Bedroom2 14927 non-null float64\n",
- " 12 Bathroom 14925 non-null float64\n",
- " 13 Car 14820 non-null float64\n",
- " 14 Landsize 13603 non-null float64\n",
- " 15 BuildingArea 7762 non-null float64\n",
- " 16 YearBuilt 8958 non-null float64\n",
- " 17 CouncilArea 12233 non-null object \n",
- " 18 Lattitude 15064 non-null float64\n",
- " 19 Longtitude 15064 non-null float64\n",
- " 20 Regionname 18395 non-null object \n",
- " 21 Propertycount 18395 non-null float64\n",
- "dtypes: float64(12), int64(2), object(8)\n",
- "memory usage: 3.1+ MB\n"
- ]
- }
- ],
- "source": [
- "df.info()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "id": "284ec9d1",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- "
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- " \n",
- " \n",
- " | \n",
- " count | \n",
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- " top | \n",
- " freq | \n",
- " mean | \n",
- " std | \n",
- " min | \n",
- " 25% | \n",
- " 50% | \n",
- " 75% | \n",
- " max | \n",
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- " 330 | \n",
- " Reservoir | \n",
- " 541 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- "
\n",
- " \n",
- " | Address | \n",
- " 18396 | \n",
- " 18134 | \n",
- " 16 Smith St | \n",
- " 3 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- "
\n",
- " \n",
- " | Rooms | \n",
- " 18396.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 2.93504 | \n",
- " 0.958202 | \n",
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- " 3 | \n",
- " h | \n",
- " 12095 | \n",
- " NaN | \n",
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- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
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\n",
- " \n",
- " | Price | \n",
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- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
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- " \n",
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- " 18396 | \n",
- " 5 | \n",
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- " 12034 | \n",
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\n",
- " \n",
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- " 305 | \n",
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- " 2002 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- "
\n",
- " \n",
- " | Date | \n",
- " 18396 | \n",
- " 58 | \n",
- " 27/05/2017 | \n",
- " 610 | \n",
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- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- "
\n",
- " \n",
- " | Distance | \n",
- " 18395.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 10.389986 | \n",
- " 6.00905 | \n",
- " 0.0 | \n",
- " 6.3 | \n",
- " 9.7 | \n",
- " 13.3 | \n",
- " 48.1 | \n",
- "
\n",
- " \n",
- " | Postcode | \n",
- " 18395.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 3107.140147 | \n",
- " 95.000995 | \n",
- " 3000.0 | \n",
- " 3046.0 | \n",
- " 3085.0 | \n",
- " 3149.0 | \n",
- " 3978.0 | \n",
- "
\n",
- " \n",
- " | Bedroom2 | \n",
- " 14927.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 2.913043 | \n",
- " 0.964641 | \n",
- " 0.0 | \n",
- " 2.0 | \n",
- " 3.0 | \n",
- " 3.0 | \n",
- " 20.0 | \n",
- "
\n",
- " \n",
- " | Bathroom | \n",
- " 14925.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 1.538492 | \n",
- " 0.689311 | \n",
- " 0.0 | \n",
- " 1.0 | \n",
- " 1.0 | \n",
- " 2.0 | \n",
- " 8.0 | \n",
- "
\n",
- " \n",
- " | Car | \n",
- " 14820.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 1.61552 | \n",
- " 0.955916 | \n",
- " 0.0 | \n",
- " 1.0 | \n",
- " 2.0 | \n",
- " 2.0 | \n",
- " 10.0 | \n",
- "
\n",
- " \n",
- " | Landsize | \n",
- " 13603.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 558.116371 | \n",
- " 3987.326586 | \n",
- " 0.0 | \n",
- " 176.5 | \n",
- " 440.0 | \n",
- " 651.0 | \n",
- " 433014.0 | \n",
- "
\n",
- " \n",
- " | BuildingArea | \n",
- " 7762.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 151.220219 | \n",
- " 519.188596 | \n",
- " 0.0 | \n",
- " 93.0 | \n",
- " 126.0 | \n",
- " 174.0 | \n",
- " 44515.0 | \n",
- "
\n",
- " \n",
- " | YearBuilt | \n",
- " 8958.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 1965.879996 | \n",
- " 37.013261 | \n",
- " 1196.0 | \n",
- " 1950.0 | \n",
- " 1970.0 | \n",
- " 2000.0 | \n",
- " 2018.0 | \n",
- "
\n",
- " \n",
- " | CouncilArea | \n",
- " 12233 | \n",
- " 33 | \n",
- " Moreland | \n",
- " 1163 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- "
\n",
- " \n",
- " | Lattitude | \n",
- " 15064.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " -37.809849 | \n",
- " 0.081152 | \n",
- " -38.18255 | \n",
- " -37.8581 | \n",
- " -37.803625 | \n",
- " -37.75627 | \n",
- " -37.40853 | \n",
- "
\n",
- " \n",
- " | Longtitude | \n",
- " 15064.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 144.996338 | \n",
- " 0.106375 | \n",
- " 144.43181 | \n",
- " 144.931193 | \n",
- " 145.00092 | \n",
- " 145.06 | \n",
- " 145.52635 | \n",
- "
\n",
- " \n",
- " | Regionname | \n",
- " 18395 | \n",
- " 8 | \n",
- " Southern Metropolitan | \n",
- " 6343 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- "
\n",
- " \n",
- " | Propertycount | \n",
- " 18395.0 | \n",
- " NaN | \n",
- " NaN | \n",
- " NaN | \n",
- " 7517.975265 | \n",
- " 4488.416599 | \n",
- " 249.0 | \n",
- " 4294.0 | \n",
- " 6567.0 | \n",
- " 10331.0 | \n",
- " 21650.0 | \n",
- "
\n",
- " \n",
- "
\n",
- "
"
- ],
- "text/plain": [
- " count unique top freq mean std min 25% 50% 75% max\n",
- "Unnamed: 0 18396.0 NaN NaN NaN 11826.787073 6800.710448 1.0 5936.75 11820.5 17734.25 23546.0\n",
- "Suburb 18396 330 Reservoir 541 NaN NaN NaN NaN NaN NaN NaN\n",
- "Address 18396 18134 16 Smith St 3 NaN NaN NaN NaN NaN NaN NaN\n",
- "Rooms 18396.0 NaN NaN NaN 2.93504 0.958202 1.0 2.0 3.0 3.0 12.0\n",
- "Type 18396 3 h 12095 NaN NaN NaN NaN NaN NaN NaN\n",
- "Price 18396.0 NaN NaN NaN 1056697.460915 641921.66671 85000.0 633000.0 880000.0 1302000.0 9000000.0\n",
- "Method 18396 5 S 12034 NaN NaN NaN NaN NaN NaN NaN\n",
- "SellerG 18396 305 Nelson 2002 NaN NaN NaN NaN NaN NaN NaN\n",
- "Date 18396 58 27/05/2017 610 NaN NaN NaN NaN NaN NaN NaN\n",
- "Distance 18395.0 NaN NaN NaN 10.389986 6.00905 0.0 6.3 9.7 13.3 48.1\n",
- "Postcode 18395.0 NaN NaN NaN 3107.140147 95.000995 3000.0 3046.0 3085.0 3149.0 3978.0\n",
- "Bedroom2 14927.0 NaN NaN NaN 2.913043 0.964641 0.0 2.0 3.0 3.0 20.0\n",
- "Bathroom 14925.0 NaN NaN NaN 1.538492 0.689311 0.0 1.0 1.0 2.0 8.0\n",
- "Car 14820.0 NaN NaN NaN 1.61552 0.955916 0.0 1.0 2.0 2.0 10.0\n",
- "Landsize 13603.0 NaN NaN NaN 558.116371 3987.326586 0.0 176.5 440.0 651.0 433014.0\n",
- "BuildingArea 7762.0 NaN NaN NaN 151.220219 519.188596 0.0 93.0 126.0 174.0 44515.0\n",
- "YearBuilt 8958.0 NaN NaN NaN 1965.879996 37.013261 1196.0 1950.0 1970.0 2000.0 2018.0\n",
- "CouncilArea 12233 33 Moreland 1163 NaN NaN NaN NaN NaN NaN NaN\n",
- "Lattitude 15064.0 NaN NaN NaN -37.809849 0.081152 -38.18255 -37.8581 -37.803625 -37.75627 -37.40853\n",
- "Longtitude 15064.0 NaN NaN NaN 144.996338 0.106375 144.43181 144.931193 145.00092 145.06 145.52635\n",
- "Regionname 18395 8 Southern Metropolitan 6343 NaN NaN NaN NaN NaN NaN NaN\n",
- "Propertycount 18395.0 NaN NaN NaN 7517.975265 4488.416599 249.0 4294.0 6567.0 10331.0 21650.0"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df.describe(include='all').transpose()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "id": "8dc59d74",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Unnamed: 0 18396\n",
- "Address 18134\n",
- "Longtitude 8168\n",
- "Lattitude 7518\n",
- "Price 2470\n",
- "Landsize 1449\n",
- "BuildingArea 613\n",
- "Suburb 330\n",
- "Propertycount 324\n",
- "SellerG 305\n",
- "Distance 210\n",
- "Postcode 205\n",
- "YearBuilt 144\n",
- "Date 58\n",
- "CouncilArea 33\n",
- "Bedroom2 12\n",
- "Car 11\n",
- "Rooms 11\n",
- "Bathroom 9\n",
- "Regionname 8\n",
- "Method 5\n",
- "Type 3\n",
- "dtype: int64"
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Anzahl unique Werte pro Spalte – wichtig für Encoding-Entscheidungen\n",
- "df.nunique().sort_values(ascending=False)"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "7262acc9",
- "metadata": {},
- "source": [
- "## 3. Profiling-Report\n",
- "\n",
- "`ydata-profiling` generiert einen umfassenden HTML-Report.\n",
- "Bei ~13k Zeilen dauert das ein paar Sekunden."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "id": "90d4c058",
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/tmp/ipykernel_168904/2895230826.py:1: DeprecationWarning: \n",
- " `import ydata_profiling` is deprecated and will not receive more updates. \n",
- " Please install fg-data-profiling via `pip install fg-data-profiling` and use `import data_profiling` instead.\n",
- " \n",
- " from ydata_profiling import ProfileReport\n"
- ]
- },
- {
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- "model_id": "2c48579dacb347a39be9fc92c2918fe1",
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- "Summarize dataset: 0%| | 0/5 [00:00, ?it/s]"
- ]
- },
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- "output_type": "display_data"
- },
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- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\n",
- " 0%| | 0/22 [00:00, ?it/s]\u001b[A\n",
- " 5%|█████ | 1/22 [00:00<00:03, 5.62it/s]\u001b[A\n",
- " 41%|█████████████████████████████████████████████▊ | 9/22 [00:00<00:00, 32.49it/s]\u001b[A\n",
- "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████| 22/22 [00:00<00:00, 46.78it/s]\u001b[A\n"
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- "Generate report structure: 0%| | 0/1 [00:00, ?it/s]"
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- "Render HTML: 0%| | 0/1 [00:00, ?it/s]"
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- "