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https://github.com/rodneyosodo/variational-quantum-classifier-on-heartattack.git
synced 2026-08-07 07:15:00 +00:00
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16307 lines
1.5 MiB
Plaintext
16307 lines
1.5 MiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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||
"outputs": [],
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"source": [
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||
"import pandas as pd\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns\n",
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"import pandas_profiling as pp\n",
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"from sklearn.datasets import load_wine, load_iris\n",
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"%matplotlib inline"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Constants\n",
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"CLEAN_DATA_PATH = \"../../Data/Processed/iris_csv.csv\""
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 1. DATA COLLECTION"
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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": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"raw_data = load_iris()"
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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": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" }\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>sepal length (cm)</th>\n",
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" <th>sepal width (cm)</th>\n",
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" <th>petal length (cm)</th>\n",
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||
" <th>petal width (cm)</th>\n",
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||
" <th>target</th>\n",
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||
" <th>class</th>\n",
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||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
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||
" <th>0</th>\n",
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||
" <td>5.1</td>\n",
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||
" <td>3.5</td>\n",
|
||
" <td>1.4</td>\n",
|
||
" <td>0.2</td>\n",
|
||
" <td>0</td>\n",
|
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" <td>setosa</td>\n",
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||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>4.9</td>\n",
|
||
" <td>3.0</td>\n",
|
||
" <td>1.4</td>\n",
|
||
" <td>0.2</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>setosa</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>4.7</td>\n",
|
||
" <td>3.2</td>\n",
|
||
" <td>1.3</td>\n",
|
||
" <td>0.2</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>setosa</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>4.6</td>\n",
|
||
" <td>3.1</td>\n",
|
||
" <td>1.5</td>\n",
|
||
" <td>0.2</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>setosa</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>5.0</td>\n",
|
||
" <td>3.6</td>\n",
|
||
" <td>1.4</td>\n",
|
||
" <td>0.2</td>\n",
|
||
" <td>0</td>\n",
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||
" <td>setosa</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
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||
"</table>\n",
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"</div>"
|
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],
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"text/plain": [
|
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" sepal length (cm) sepal width (cm) petal length (cm) petal width (cm) \\\n",
|
||
"0 5.1 3.5 1.4 0.2 \n",
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"1 4.9 3.0 1.4 0.2 \n",
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||
"2 4.7 3.2 1.3 0.2 \n",
|
||
"3 4.6 3.1 1.5 0.2 \n",
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"4 5.0 3.6 1.4 0.2 \n",
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"\n",
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||
" target class \n",
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"0 0 setosa \n",
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"1 0 setosa \n",
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"2 0 setosa \n",
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"3 0 setosa \n",
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"4 0 setosa "
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||
]
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||
},
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||
"execution_count": 4,
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||
"metadata": {},
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||
"output_type": "execute_result"
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||
}
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||
],
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||
"source": [
|
||
"features = pd.DataFrame(data=raw_data['data'],columns=raw_data['feature_names'])\n",
|
||
"data = features\n",
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||
"data['target']=raw_data['target']\n",
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||
"data['class']=data['target'].map(lambda ind: raw_data['target_names'][ind])\n",
|
||
"data.head()"
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||
]
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||
},
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||
{
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||
"cell_type": "markdown",
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||
"metadata": {},
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"source": [
|
||
"## 2. DATA EXPLORATION"
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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": 5,
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||
"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
|
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"(150, 6)"
|
||
]
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},
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||
"execution_count": 5,
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||
"metadata": {},
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||
"output_type": "execute_result"
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||
}
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||
],
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||
"source": [
|
||
"data.shape"
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||
]
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||
},
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{
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||
"cell_type": "markdown",
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||
"metadata": {},
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||
"source": [
|
||
"We have 294 rows of data with 14 columns"
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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": 6,
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||
"metadata": {},
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"outputs": [
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{
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||
"data": {
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||
"text/plain": [
|
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"Index(['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)',\n",
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" 'petal width (cm)', 'target', 'class'],\n",
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||
" dtype='object')"
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||
]
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||
},
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||
"execution_count": 6,
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||
"metadata": {},
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||
"output_type": "execute_result"
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||
}
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||
],
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||
"source": [
|
||
"data.columns"
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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": 7,
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||
"metadata": {},
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||
"outputs": [
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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"text": [
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".. _iris_dataset:\n",
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||
"\n",
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||
"Iris plants dataset\n",
|
||
"--------------------\n",
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||
"\n",
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||
"**Data Set Characteristics:**\n",
|
||
"\n",
|
||
" :Number of Instances: 150 (50 in each of three classes)\n",
|
||
" :Number of Attributes: 4 numeric, predictive attributes and the class\n",
|
||
" :Attribute Information:\n",
|
||
" - sepal length in cm\n",
|
||
" - sepal width in cm\n",
|
||
" - petal length in cm\n",
|
||
" - petal width in cm\n",
|
||
" - class:\n",
|
||
" - Iris-Setosa\n",
|
||
" - Iris-Versicolour\n",
|
||
" - Iris-Virginica\n",
|
||
" \n",
|
||
" :Summary Statistics:\n",
|
||
"\n",
|
||
" ============== ==== ==== ======= ===== ====================\n",
|
||
" Min Max Mean SD Class Correlation\n",
|
||
" ============== ==== ==== ======= ===== ====================\n",
|
||
" sepal length: 4.3 7.9 5.84 0.83 0.7826\n",
|
||
" sepal width: 2.0 4.4 3.05 0.43 -0.4194\n",
|
||
" petal length: 1.0 6.9 3.76 1.76 0.9490 (high!)\n",
|
||
" petal width: 0.1 2.5 1.20 0.76 0.9565 (high!)\n",
|
||
" ============== ==== ==== ======= ===== ====================\n",
|
||
"\n",
|
||
" :Missing Attribute Values: None\n",
|
||
" :Class Distribution: 33.3% for each of 3 classes.\n",
|
||
" :Creator: R.A. Fisher\n",
|
||
" :Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov)\n",
|
||
" :Date: July, 1988\n",
|
||
"\n",
|
||
"The famous Iris database, first used by Sir R.A. Fisher. The dataset is taken\n",
|
||
"from Fisher's paper. Note that it's the same as in R, but not as in the UCI\n",
|
||
"Machine Learning Repository, which has two wrong data points.\n",
|
||
"\n",
|
||
"This is perhaps the best known database to be found in the\n",
|
||
"pattern recognition literature. Fisher's paper is a classic in the field and\n",
|
||
"is referenced frequently to this day. (See Duda & Hart, for example.) The\n",
|
||
"data set contains 3 classes of 50 instances each, where each class refers to a\n",
|
||
"type of iris plant. One class is linearly separable from the other 2; the\n",
|
||
"latter are NOT linearly separable from each other.\n",
|
||
"\n",
|
||
".. topic:: References\n",
|
||
"\n",
|
||
" - Fisher, R.A. \"The use of multiple measurements in taxonomic problems\"\n",
|
||
" Annual Eugenics, 7, Part II, 179-188 (1936); also in \"Contributions to\n",
|
||
" Mathematical Statistics\" (John Wiley, NY, 1950).\n",
|
||
" - Duda, R.O., & Hart, P.E. (1973) Pattern Classification and Scene Analysis.\n",
|
||
" (Q327.D83) John Wiley & Sons. ISBN 0-471-22361-1. See page 218.\n",
|
||
" - Dasarathy, B.V. (1980) \"Nosing Around the Neighborhood: A New System\n",
|
||
" Structure and Classification Rule for Recognition in Partially Exposed\n",
|
||
" Environments\". IEEE Transactions on Pattern Analysis and Machine\n",
|
||
" Intelligence, Vol. PAMI-2, No. 1, 67-71.\n",
|
||
" - Gates, G.W. (1972) \"The Reduced Nearest Neighbor Rule\". IEEE Transactions\n",
|
||
" on Information Theory, May 1972, 431-433.\n",
|
||
" - See also: 1988 MLC Proceedings, 54-64. Cheeseman et al\"s AUTOCLASS II\n",
|
||
" conceptual clustering system finds 3 classes in the data.\n",
|
||
" - Many, many more ...\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(raw_data['DESCR'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 150 entries, 0 to 149\n",
|
||
"Data columns (total 6 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 sepal length (cm) 150 non-null float64\n",
|
||
" 1 sepal width (cm) 150 non-null float64\n",
|
||
" 2 petal length (cm) 150 non-null float64\n",
|
||
" 3 petal width (cm) 150 non-null float64\n",
|
||
" 4 target 150 non-null int64 \n",
|
||
" 5 class 150 non-null object \n",
|
||
"dtypes: float64(4), int64(1), object(1)\n",
|
||
"memory usage: 7.2+ KB\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"data.info()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"We have missing values which have `'?'` but they don't show as missing values.\n",
|
||
"Let's fix that"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
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"data": {
|
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"text/html": [
|
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
|
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" }\n",
|
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"\n",
|
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" .dataframe thead th {\n",
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" text-align: right;\n",
|
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" }\n",
|
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"</style>\n",
|
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"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>sepal length (cm)</th>\n",
|
||
" <th>sepal width (cm)</th>\n",
|
||
" <th>petal length (cm)</th>\n",
|
||
" <th>petal width (cm)</th>\n",
|
||
" <th>target</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>count</th>\n",
|
||
" <td>150.000000</td>\n",
|
||
" <td>150.000000</td>\n",
|
||
" <td>150.000000</td>\n",
|
||
" <td>150.000000</td>\n",
|
||
" <td>150.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>mean</th>\n",
|
||
" <td>5.843333</td>\n",
|
||
" <td>3.057333</td>\n",
|
||
" <td>3.758000</td>\n",
|
||
" <td>1.199333</td>\n",
|
||
" <td>1.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>std</th>\n",
|
||
" <td>0.828066</td>\n",
|
||
" <td>0.435866</td>\n",
|
||
" <td>1.765298</td>\n",
|
||
" <td>0.762238</td>\n",
|
||
" <td>0.819232</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>min</th>\n",
|
||
" <td>4.300000</td>\n",
|
||
" <td>2.000000</td>\n",
|
||
" <td>1.000000</td>\n",
|
||
" <td>0.100000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>25%</th>\n",
|
||
" <td>5.100000</td>\n",
|
||
" <td>2.800000</td>\n",
|
||
" <td>1.600000</td>\n",
|
||
" <td>0.300000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>50%</th>\n",
|
||
" <td>5.800000</td>\n",
|
||
" <td>3.000000</td>\n",
|
||
" <td>4.350000</td>\n",
|
||
" <td>1.300000</td>\n",
|
||
" <td>1.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>75%</th>\n",
|
||
" <td>6.400000</td>\n",
|
||
" <td>3.300000</td>\n",
|
||
" <td>5.100000</td>\n",
|
||
" <td>1.800000</td>\n",
|
||
" <td>2.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>max</th>\n",
|
||
" <td>7.900000</td>\n",
|
||
" <td>4.400000</td>\n",
|
||
" <td>6.900000</td>\n",
|
||
" <td>2.500000</td>\n",
|
||
" <td>2.000000</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" sepal length (cm) sepal width (cm) petal length (cm) \\\n",
|
||
"count 150.000000 150.000000 150.000000 \n",
|
||
"mean 5.843333 3.057333 3.758000 \n",
|
||
"std 0.828066 0.435866 1.765298 \n",
|
||
"min 4.300000 2.000000 1.000000 \n",
|
||
"25% 5.100000 2.800000 1.600000 \n",
|
||
"50% 5.800000 3.000000 4.350000 \n",
|
||
"75% 6.400000 3.300000 5.100000 \n",
|
||
"max 7.900000 4.400000 6.900000 \n",
|
||
"\n",
|
||
" petal width (cm) target \n",
|
||
"count 150.000000 150.000000 \n",
|
||
"mean 1.199333 1.000000 \n",
|
||
"std 0.762238 0.819232 \n",
|
||
"min 0.100000 0.000000 \n",
|
||
"25% 0.300000 0.000000 \n",
|
||
"50% 1.300000 1.000000 \n",
|
||
"75% 1.800000 2.000000 \n",
|
||
"max 2.500000 2.000000 "
|
||
]
|
||
},
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"data.describe()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"def check_unique(df):\n",
|
||
" \"\"\"\"\n",
|
||
" Checks the unique value in each column\n",
|
||
" :param df: The dataframe\n",
|
||
" \"\"\"\n",
|
||
" for col in df.columns:\n",
|
||
" unique = df[col].unique()\n",
|
||
" print(\"Column: {} has {} unique values\\n\".format(col, unique))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Column: sepal length (cm) has [5.1 4.9 4.7 4.6 5. 5.4 4.4 4.8 4.3 5.8 5.7 5.2 5.5 4.5 5.3 7. 6.4 6.9\n",
|
||
" 6.5 6.3 6.6 5.9 6. 6.1 5.6 6.7 6.2 6.8 7.1 7.6 7.3 7.2 7.7 7.4 7.9] unique values\n",
|
||
"\n",
|
||
"Column: sepal width (cm) has [3.5 3. 3.2 3.1 3.6 3.9 3.4 2.9 3.7 4. 4.4 3.8 3.3 4.1 4.2 2.3 2.8 2.4\n",
|
||
" 2.7 2. 2.2 2.5 2.6] unique values\n",
|
||
"\n",
|
||
"Column: petal length (cm) has [1.4 1.3 1.5 1.7 1.6 1.1 1.2 1. 1.9 4.7 4.5 4.9 4. 4.6 3.3 3.9 3.5 4.2\n",
|
||
" 3.6 4.4 4.1 4.8 4.3 5. 3.8 3.7 5.1 3. 6. 5.9 5.6 5.8 6.6 6.3 6.1 5.3\n",
|
||
" 5.5 6.7 6.9 5.7 6.4 5.4 5.2] unique values\n",
|
||
"\n",
|
||
"Column: petal width (cm) has [0.2 0.4 0.3 0.1 0.5 0.6 1.4 1.5 1.3 1.6 1. 1.1 1.8 1.2 1.7 2.5 1.9 2.1\n",
|
||
" 2.2 2. 2.4 2.3] unique values\n",
|
||
"\n",
|
||
"Column: target has [0 1 2] unique values\n",
|
||
"\n",
|
||
"Column: class has ['setosa' 'versicolor' 'virginica'] unique values\n",
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"check_unique(data)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"fig = plt.figure()\n",
|
||
"sns.countplot(x=\"target\", data=data, palette=\"gist_rainbow_r\")\n",
|
||
"plt.xlabel(\"Classes(0 = setosa, 1 = versicolor, 2 = verginica)\")\n",
|
||
"plt.title(\"Target distribution\")\n",
|
||
"plt.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 2. DATA CLEANING"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"data = data[data['class'] != 'virginica']"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Check duplicates"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"0"
|
||
]
|
||
},
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"data.duplicated().sum()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/r0x6f736f646f/Documents/VENVS/qosf/lib/python3.6/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
|
||
"A value is trying to be set on a copy of a slice from a DataFrame\n",
|
||
"\n",
|
||
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
|
||
" \"\"\"Entry point for launching an IPython kernel.\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"data.drop_duplicates(inplace=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 3. PROFILING"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<AxesSubplot:title={'center':'Correlation with target'}>"
|
||
]
|
||
},
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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||
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||
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||
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||
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||
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|
||
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|
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|
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|
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|
||
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|
||
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|
||
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|
||
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|
||
".freq:not(.mini) tr td:nth-child(1), .freq:not(.mini) tr th:nth-child(1){\n",
|
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|
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|
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|
||
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|
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|
||
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|
||
".freq:not(.mini) tr td:nth-child(2), .freq:not(.mini) tr td:nth-child(3), .freq:not(.mini) tr th:nth-child(2), .freq:not(.mini) tr th:nth-child(3){\n",
|
||
" width: 100px;\n",
|
||
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|
||
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|
||
".freq:not(.mini) tr td:nth-child(4), .freq:not(.mini) tr th:nth-child(4){\n",
|
||
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|
||
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|
||
"\n",
|
||
".freq .bar {\n",
|
||
" float: left;\n",
|
||
" width: 0;\n",
|
||
" height: 100%;\n",
|
||
" line-height: 20px;\n",
|
||
" color: #fff;\n",
|
||
" text-align: center;\n",
|
||
" background-color: #2c3e50;\n",
|
||
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|
||
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|
||
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|
||
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|
||
".other .bar {\n",
|
||
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|
||
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|
||
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|
||
".missing .bar {\n",
|
||
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|
||
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|
||
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|
||
".tooltip-inner {\n",
|
||
" width: 100%;\n",
|
||
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|
||
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|
||
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|
||
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|
||
".extrapadding {\n",
|
||
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|
||
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|
||
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|
||
".variable .h4 {\n",
|
||
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|
||
" display:inline-block;\n",
|
||
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|
||
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|
||
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|
||
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|
||
".variable.ignore .h4{\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
".img-responsive{\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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||
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|
||
".variable-description{\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
".named-list-item{\n",
|
||
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|
||
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|
||
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|
||
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|
||
"@media print {\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" page-break-before: avoid;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .nav-pills, .nav-tabs, button[data-toggle="collapse"], .mini, .col-sm-3 img {\n",
|
||
" display:none !important;\n",
|
||
" }\n",
|
||
"\n",
|
||
" a[download="config.yml"]:after {\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"\n",
|
||
".text-placeholder {\n",
|
||
" display: inline-block;\n",
|
||
" background-color: #444;\n",
|
||
" height: 12px;\n",
|
||
" border-radius: 100px;\n",
|
||
" margin: 5px 0;\n",
|
||
" min-width: 200px;\n",
|
||
" opacity: .1;\n",
|
||
"}</style></head><body><a class=anchor-pos id=top></a><nav class="navbar navbar-default navbar-fixed-top"><div class=container-fluid><div class=navbar-header><button type=button class="navbar-toggle collapsed" data-toggle=collapse data-target=#navbar aria-expanded=false aria-controls=navbar><span class=sr-only>Toggle navigation</span><span class=icon-bar></span><span class=icon-bar></span><span class=icon-bar></span></button><a class="navbar-brand anchor" href=#top>Pandas Profiling Report</a></div><div id=navbar class="navbar-collapse collapse"><ul class="nav navbar-nav navbar-right"><li><a class=anchor href=#overview>Overview</a></li><li><a class=anchor href=#variables>Variables</a></li><li><a class=anchor href=#interactions>Interactions</a></li><li><a class=anchor href=#correlations>Correlations</a></li><li><a class=anchor href=#missing>Missing values</a></li><li><a class=anchor href=#sample>Sample</a></li></ul></div></div></nav><div class=content><div class=container><div class="row header"><a class=anchor-pos id=overview></a><h1 class=page-header>Overview</h1></div><div class=section-items><div class="row spacing"><ul class="nav nav-pills" role=tablist><li role=presentation class=active><a href=#overview-dataset_overview aria-controls=overview-dataset_overview role=tab data-toggle=tab>Overview</a></li><li role=presentation><a href=#overview-warnings aria-controls=overview-warnings role=tab data-toggle=tab>Warnings <span class=badge>4</span></a></li><li role=presentation><a href=#overview-reproduction aria-controls=overview-reproduction role=tab data-toggle=tab>Reproduction</a></li></ul><div class=tab-content style="padding-top: 10px;"><div role=tabpanel class="tab-pane col-sm-12 active" id=overview-dataset_overview><div class=col-sm-6><p class=h4>Dataset statistics</p><table class="table table-condensed stats"><tbody><tr><th>Number of variables</th><td>6</td></tr><tr><th>Number of observations</th><td>100</td></tr><tr><th>Missing cells</th><td>0</td></tr><tr><th>Missing cells (%)</th><td>0.0%</td></tr><tr><th>Duplicate rows</th><td>0</td></tr><tr><th>Duplicate rows (%)</th><td>0.0%</td></tr><tr><th>Total size in memory</th><td>17.7 KiB</td></tr><tr><th>Average record size in memory</th><td>181.0 B</td></tr></tbody></table></div><div class=col-sm-6><p class=h4>Variable types</p><table class="table table-condensed stats"><tbody><tr><th>NUM</th><td>4</td></tr><tr><th>BOOL</th><td>1</td></tr><tr><th>CAT</th><td>1</td></tr></tbody></table></div></div><div role=tabpanel class="tab-pane col-sm-12" id=overview-warnings><table class="table table-condensed list-warnings"><p class=h4>Warnings</p><tr style=border-top:0><td><a class=anchor href=#pp_var_431248425830137136><code>petal width (cm)</code></a> is highly correlated with <code>petal length (cm)</code> and <abbr title="petal length (cm), target">1 other fields</abbr></td><td><span class="label label-default">High correlation</span></td></tr><tr><td><a class=anchor href=#pp_var_8684076095524020880><code>petal length (cm)</code></a> is highly correlated with <code>petal width (cm)</code> and <abbr title="petal width (cm), target">1 other fields</abbr></td><td><span class="label label-default">High correlation</span></td></tr><tr><td><a class=anchor href=#pp_var_1975489024884402091><code>target</code></a> is highly correlated with <code>petal length (cm)</code> and <abbr title="petal length (cm), petal width (cm)">1 other fields</abbr></td><td><span class="label label-default">High correlation</span></td></tr><tr><td><a class=anchor href=#pp_var_1329591615293691764><code>class</code></a> is uniformly distributed </td><td><span class="label label-primary">Uniform</span></td></tr></table></div><div role=tabpanel class="tab-pane col-sm-12" id=overview-reproduction><div class=col-sm-12><p class=h4>Reproduction</p><table class="table table-condensed stats"><tbody><tr><th>Analysis started</th><td>2021-01-07 10:25:37.464805</td></tr><tr><th>Analysis finished</th><td>2021-01-07 10:25:46.467916</td></tr><tr><th>Duration</th><td>9 seconds</td></tr><tr><th>Software version</th><td><a href=https://github.com/pandas-profiling/pandas-profiling>pandas-profiling v2.9.0</a></td></tr><tr><th>Download configuration</th><td><a download=config.yaml 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""/></g></g></g><defs><clippath id=pcc4e0469ba><rect height=239.724932 width=374.775 x=46.425 y=10.8 /></clippath></defs></svg><div class="caption text-center text-muted"><strong>Histogram with fixed size bins</strong> (bins=28) </div></div><div role=tabpanel class="tab-pane col-sm-12" id=-8786172757504012648bottom--8786172757504012648common_values><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=5>5</td><td>10</td><td>10.0%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=5.1>5.1</td><td>9</td><td>9.0%</td><td><div class=bar style=width:90.0%>&nbsp;</div></td></tr><tr class><td title=5.5>5.5</td><td>7</td><td>7.0%</td><td><div class=bar style=width:70.0%>&nbsp;</div></td></tr><tr class><td title=5.7>5.7</td><td>7</td><td>7.0%</td><td><div class=bar style=width:70.0%>&nbsp;</div></td></tr><tr class><td title=5.4>5.4</td><td>6</td><td>6.0%</td><td><div class=bar style=width:60.0%>&nbsp;</div></td></tr><tr class><td title=4.8>4.8</td><td>5</td><td>5.0%</td><td><div class=bar style=width:50.0%>&nbsp;</div></td></tr><tr class><td title=4.9>4.9</td><td>5</td><td>5.0%</td><td><div class=bar style=width:50.0%>&nbsp;</div></td></tr><tr class><td title=5.6>5.6</td><td>5</td><td>5.0%</td><td><div class=bar style=width:50.0%>&nbsp;</div></td></tr><tr class><td title=5.8>5.8</td><td>4</td><td>4.0%</td><td><div class=bar style=width:40.0%>&nbsp;</div></td></tr><tr class><td title=5.2>5.2</td><td>4</td><td>4.0%</td><td><div class=bar style=width:40.0%>&nbsp;</div></td></tr><tr class><td title=6>6</td><td>4</td><td>4.0%</td><td><div class=bar style=width:40.0%>&nbsp;</div></td></tr><tr class><td title=6.1>6.1</td><td>4</td><td>4.0%</td><td><div class=bar style=width:40.0%>&nbsp;</div></td></tr><tr class><td title=4.6>4.6</td><td>4</td><td>4.0%</td><td><div class=bar style=width:40.0%>&nbsp;</div></td></tr><tr class><td title=6.7>6.7</td><td>3</td><td>3.0%</td><td><div class=bar style=width:30.0%>&nbsp;</div></td></tr><tr class><td title=4.4>4.4</td><td>3</td><td>3.0%</td><td><div class=bar style=width:30.0%>&nbsp;</div></td></tr><tr class><td title=6.3>6.3</td><td>3</td><td>3.0%</td><td><div class=bar style=width:30.0%>&nbsp;</div></td></tr><tr class><td title=6.2>6.2</td><td>2</td><td>2.0%</td><td><div class=bar style=width:20.0%>&nbsp;</div></td></tr><tr class><td title=6.4>6.4</td><td>2</td><td>2.0%</td><td><div class=bar style=width:20.0%>&nbsp;</div></td></tr><tr class><td title=6.6>6.6</td><td>2</td><td>2.0%</td><td><div class=bar style=width:20.0%>&nbsp;</div></td></tr><tr class><td title=4.7>4.7</td><td>2</td><td>2.0%</td><td><div class=bar style=width:20.0%>&nbsp;</div></td></tr><tr class><td title=5.9>5.9</td><td>2</td><td>2.0%</td><td><div class=bar style=width:20.0%>&nbsp;</div></td></tr><tr class><td title=4.3>4.3</td><td>1</td><td>1.0%</td><td><div class=bar style=width:10.0%>&nbsp;</div></td></tr><tr class><td title=6.9>6.9</td><td>1</td><td>1.0%</td><td><div class=bar style=width:10.0%>&nbsp;</div></td></tr><tr class><td title=6.8>6.8</td><td>1</td><td>1.0%</td><td><div class=bar style=width:10.0%>&nbsp;</div></td></tr><tr class><td title=6.5>6.5</td><td>1</td><td>1.0%</td><td><div class=bar style=width:10.0%>&nbsp;</div></td></tr><tr class=other><td title="Other values (3)">Other values (3)</td><td>3</td><td>3.0%</td><td><div class=bar style=width:30.0%>&nbsp;</div></td></tr></tbody></table></div><div role=tabpanel class="tab-pane col-sm-12" id=-8786172757504012648bottom--8786172757504012648extreme_values><div class="row spacing"><ul class="nav nav-tabs" role=tablist><li role=presentation class=active><a href=#-8786172757504012648extreme_values--8786172757504012648firstn aria-controls=-8786172757504012648extreme_values--8786172757504012648firstn role=tab data-toggle=tab>Minimum 5 values</a></li><li role=presentation><a href=#-8786172757504012648extreme_values--8786172757504012648lastn aria-controls=-8786172757504012648extreme_values--8786172757504012648lastn role=tab data-toggle=tab>Maximum 5 values</a></li></ul><div class=tab-content><div role=tabpanel class="tab-pane col-sm-12 active" id=-8786172757504012648extreme_values--8786172757504012648firstn><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=4.3>4.3</td><td>1</td><td>1.0%</td><td><div class=bar style=width:10.0%>&nbsp;</div></td></tr><tr class><td title=4.4>4.4</td><td>3</td><td>3.0%</td><td><div class=bar style=width:30.0%>&nbsp;</div></td></tr><tr class><td title=4.5>4.5</td><td>1</td><td>1.0%</td><td><div class=bar style=width:10.0%>&nbsp;</div></td></tr><tr class><td title=4.6>4.6</td><td>4</td><td>4.0%</td><td><div class=bar style=width:40.0%>&nbsp;</div></td></tr><tr class><td title=4.7>4.7</td><td>2</td><td>2.0%</td><td><div class=bar style=width:20.0%>&nbsp;</div></td></tr><tr class><td title=4.8>4.8</td><td>5</td><td>5.0%</td><td><div class=bar style=width:50.0%>&nbsp;</div></td></tr><tr class><td title=4.9>4.9</td><td>5</td><td>5.0%</td><td><div class=bar style=width:50.0%>&nbsp;</div></td></tr><tr class><td title=5>5</td><td>10</td><td>10.0%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=5.1>5.1</td><td>9</td><td>9.0%</td><td><div class=bar style=width:90.0%>&nbsp;</div></td></tr><tr class><td title=5.2>5.2</td><td>4</td><td>4.0%</td><td><div class=bar style=width:40.0%>&nbsp;</div></td></tr></tbody></table></div><div role=tabpanel class="tab-pane col-sm-12" id=-8786172757504012648extreme_values--8786172757504012648lastn><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td 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title=3.1>3.1</td><td>7</td><td>7.0%</td><td><div class=bar style=width:50.0%>&nbsp;</div></td></tr><tr class><td title=3.5>3.5</td><td>6</td><td>6.0%</td><td><div class=bar style=width:42.9%>&nbsp;</div></td></tr><tr class><td title=2.8>2.8</td><td>6</td><td>6.0%</td><td><div class=bar style=width:42.9%>&nbsp;</div></td></tr><tr class><td title=2.7>2.7</td><td>5</td><td>5.0%</td><td><div class=bar style=width:35.7%>&nbsp;</div></td></tr><tr class><td title=2.3>2.3</td><td>4</td><td>4.0%</td><td><div class=bar style=width:28.6%>&nbsp;</div></td></tr><tr class><td title=2.5>2.5</td><td>4</td><td>4.0%</td><td><div class=bar style=width:28.6%>&nbsp;</div></td></tr><tr class><td title=3.8>3.8</td><td>4</td><td>4.0%</td><td><div class=bar style=width:28.6%>&nbsp;</div></td></tr><tr class><td title=3.7>3.7</td><td>3</td><td>3.0%</td><td><div class=bar style=width:21.4%>&nbsp;</div></td></tr><tr class><td title=2.4>2.4</td><td>3</td><td>3.0%</td><td><div class=bar style=width:21.4%>&nbsp;</div></td></tr><tr class><td title=2.6>2.6</td><td>3</td><td>3.0%</td><td><div class=bar style=width:21.4%>&nbsp;</div></td></tr><tr class><td title=3.3>3.3</td><td>3</td><td>3.0%</td><td><div class=bar style=width:21.4%>&nbsp;</div></td></tr><tr class><td title=3.6>3.6</td><td>3</td><td>3.0%</td><td><div class=bar style=width:21.4%>&nbsp;</div></td></tr><tr class><td title=2.2>2.2</td><td>2</td><td>2.0%</td><td><div class=bar style=width:14.3%>&nbsp;</div></td></tr><tr class><td title=3.9>3.9</td><td>2</td><td>2.0%</td><td><div class=bar style=width:14.3%>&nbsp;</div></td></tr><tr class><td title=4.2>4.2</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.1%>&nbsp;</div></td></tr><tr class><td title=4.4>4.4</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.1%>&nbsp;</div></td></tr><tr class><td title=2>2</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.1%>&nbsp;</div></td></tr><tr class><td title=4>4</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.1%>&nbsp;</div></td></tr><tr class><td title=4.1>4.1</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.1%>&nbsp;</div></td></tr></tbody></table></div><div role=tabpanel class="tab-pane col-sm-12" id=3637421707381282704bottom-3637421707381282704extreme_values><div class="row spacing"><ul class="nav nav-tabs" role=tablist><li role=presentation class=active><a href=#3637421707381282704extreme_values-3637421707381282704firstn aria-controls=3637421707381282704extreme_values-3637421707381282704firstn role=tab data-toggle=tab>Minimum 5 values</a></li><li role=presentation><a href=#3637421707381282704extreme_values-3637421707381282704lastn aria-controls=3637421707381282704extreme_values-3637421707381282704lastn role=tab data-toggle=tab>Maximum 5 values</a></li></ul><div class=tab-content><div role=tabpanel class="tab-pane col-sm-12 active" id=3637421707381282704extreme_values-3637421707381282704firstn><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=2>2</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.1%>&nbsp;</div></td></tr><tr class><td title=2.2>2.2</td><td>2</td><td>2.0%</td><td><div class=bar style=width:14.3%>&nbsp;</div></td></tr><tr class><td title=2.3>2.3</td><td>4</td><td>4.0%</td><td><div class=bar style=width:28.6%>&nbsp;</div></td></tr><tr class><td title=2.4>2.4</td><td>3</td><td>3.0%</td><td><div class=bar style=width:21.4%>&nbsp;</div></td></tr><tr class><td title=2.5>2.5</td><td>4</td><td>4.0%</td><td><div class=bar style=width:28.6%>&nbsp;</div></td></tr><tr class><td title=2.6>2.6</td><td>3</td><td>3.0%</td><td><div class=bar style=width:21.4%>&nbsp;</div></td></tr><tr class><td title=2.7>2.7</td><td>5</td><td>5.0%</td><td><div class=bar style=width:35.7%>&nbsp;</div></td></tr><tr class><td title=2.8>2.8</td><td>6</td><td>6.0%</td><td><div 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""/></g></g></g><defs><clippath id=pb24c8683b5><rect height=245.558563 width=366.4 x=54.8 y=10.8 /></clippath></defs></svg><div class="caption text-center text-muted"><strong>Histogram with fixed size bins</strong> (bins=28) </div></div><div role=tabpanel class="tab-pane col-sm-12" id=8684076095524020880bottom-8684076095524020880common_values><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=1.5>1.5</td><td>13</td><td>13.0%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=1.4>1.4</td><td>13</td><td>13.0%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=1.6>1.6</td><td>7</td><td>7.0%</td><td><div class=bar style=width:53.8%>&nbsp;</div></td></tr><tr class><td title=4.5>4.5</td><td>7</td><td>7.0%</td><td><div class=bar style=width:53.8%>&nbsp;</div></td></tr><tr class><td title=1.3>1.3</td><td>7</td><td>7.0%</td><td><div class=bar style=width:53.8%>&nbsp;</div></td></tr><tr class><td title=4>4</td><td>5</td><td>5.0%</td><td><div class=bar style=width:38.5%>&nbsp;</div></td></tr><tr class><td title=4.7>4.7</td><td>5</td><td>5.0%</td><td><div class=bar style=width:38.5%>&nbsp;</div></td></tr><tr class><td title=4.2>4.2</td><td>4</td><td>4.0%</td><td><div class=bar style=width:30.8%>&nbsp;</div></td></tr><tr class><td title=4.4>4.4</td><td>4</td><td>4.0%</td><td><div class=bar style=width:30.8%>&nbsp;</div></td></tr><tr class><td title=1.7>1.7</td><td>4</td><td>4.0%</td><td><div class=bar style=width:30.8%>&nbsp;</div></td></tr><tr class><td title=4.6>4.6</td><td>3</td><td>3.0%</td><td><div class=bar style=width:23.1%>&nbsp;</div></td></tr><tr class><td title=4.1>4.1</td><td>3</td><td>3.0%</td><td><div class=bar style=width:23.1%>&nbsp;</div></td></tr><tr class><td title=3.9>3.9</td><td>3</td><td>3.0%</td><td><div class=bar style=width:23.1%>&nbsp;</div></td></tr><tr class><td title=1.9>1.9</td><td>2</td><td>2.0%</td><td><div class=bar style=width:15.4%>&nbsp;</div></td></tr><tr class><td title=3.5>3.5</td><td>2</td><td>2.0%</td><td><div class=bar style=width:15.4%>&nbsp;</div></td></tr><tr class><td title=4.9>4.9</td><td>2</td><td>2.0%</td><td><div class=bar style=width:15.4%>&nbsp;</div></td></tr><tr class><td title=3.3>3.3</td><td>2</td><td>2.0%</td><td><div class=bar style=width:15.4%>&nbsp;</div></td></tr><tr class><td title=1.2>1.2</td><td>2</td><td>2.0%</td><td><div class=bar style=width:15.4%>&nbsp;</div></td></tr><tr class><td title=4.8>4.8</td><td>2</td><td>2.0%</td><td><div class=bar style=width:15.4%>&nbsp;</div></td></tr><tr class><td title=4.3>4.3</td><td>2</td><td>2.0%</td><td><div class=bar style=width:15.4%>&nbsp;</div></td></tr><tr class><td title=5.1>5.1</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.7%>&nbsp;</div></td></tr><tr class><td title=3>3</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.7%>&nbsp;</div></td></tr><tr class><td title=5>5</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.7%>&nbsp;</div></td></tr><tr class><td title=3.7>3.7</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.7%>&nbsp;</div></td></tr><tr class><td title=3.6>3.6</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.7%>&nbsp;</div></td></tr><tr class=other><td title="Other values (3)">Other values (3)</td><td>3</td><td>3.0%</td><td><div class=bar style=width:23.1%>&nbsp;</div></td></tr></tbody></table></div><div role=tabpanel class="tab-pane col-sm-12" id=8684076095524020880bottom-8684076095524020880extreme_values><div class="row spacing"><ul class="nav nav-tabs" role=tablist><li role=presentation class=active><a href=#8684076095524020880extreme_values-8684076095524020880firstn aria-controls=8684076095524020880extreme_values-8684076095524020880firstn role=tab data-toggle=tab>Minimum 5 values</a></li><li role=presentation><a href=#8684076095524020880extreme_values-8684076095524020880lastn aria-controls=8684076095524020880extreme_values-8684076095524020880lastn role=tab data-toggle=tab>Maximum 5 values</a></li></ul><div class=tab-content><div role=tabpanel class="tab-pane col-sm-12 active" id=8684076095524020880extreme_values-8684076095524020880firstn><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=1>1</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.7%>&nbsp;</div></td></tr><tr class><td title=1.1>1.1</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.7%>&nbsp;</div></td></tr><tr class><td title=1.2>1.2</td><td>2</td><td>2.0%</td><td><div class=bar style=width:15.4%>&nbsp;</div></td></tr><tr class><td title=1.3>1.3</td><td>7</td><td>7.0%</td><td><div class=bar style=width:53.8%>&nbsp;</div></td></tr><tr class><td title=1.4>1.4</td><td>13</td><td>13.0%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=1.5>1.5</td><td>13</td><td>13.0%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=1.6>1.6</td><td>7</td><td>7.0%</td><td><div class=bar style=width:53.8%>&nbsp;</div></td></tr><tr class><td title=1.7>1.7</td><td>4</td><td>4.0%</td><td><div class=bar style=width:30.8%>&nbsp;</div></td></tr><tr class><td title=1.9>1.9</td><td>2</td><td>2.0%</td><td><div class=bar style=width:15.4%>&nbsp;</div></td></tr><tr class><td title=3>3</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.7%>&nbsp;</div></td></tr></tbody></table></div><div role=tabpanel class="tab-pane col-sm-12" id=8684076095524020880extreme_values-8684076095524020880lastn><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td 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""/></g></g></g><defs><clippath id=pa1fb631a75><rect height=235.747457 width=374.775 x=46.425 y=10.8 /></clippath></defs></svg><div class="caption text-center text-muted"><strong>Histogram with fixed size bins</strong> (bins=15) </div></div><div role=tabpanel class="tab-pane col-sm-12" id=431248425830137136bottom-431248425830137136common_values><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=0.2>0.2</td><td>29</td><td>29.0%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=1.3>1.3</td><td>13</td><td>13.0%</td><td><div class=bar style=width:44.8%>&nbsp;</div></td></tr><tr class><td title=1.5>1.5</td><td>10</td><td>10.0%</td><td><div class=bar style=width:34.5%>&nbsp;</div></td></tr><tr class><td title=0.4>0.4</td><td>7</td><td>7.0%</td><td><div class=bar style=width:24.1%>&nbsp;</div></td></tr><tr class><td title=1.4>1.4</td><td>7</td><td>7.0%</td><td><div class=bar style=width:24.1%>&nbsp;</div></td></tr><tr class><td title=0.3>0.3</td><td>7</td><td>7.0%</td><td><div class=bar style=width:24.1%>&nbsp;</div></td></tr><tr class><td title=1>1</td><td>7</td><td>7.0%</td><td><div class=bar style=width:24.1%>&nbsp;</div></td></tr><tr class><td title=1.2>1.2</td><td>5</td><td>5.0%</td><td><div class=bar style=width:17.2%>&nbsp;</div></td></tr><tr class><td title=0.1>0.1</td><td>5</td><td>5.0%</td><td><div class=bar style=width:17.2%>&nbsp;</div></td></tr><tr class><td title=1.1>1.1</td><td>3</td><td>3.0%</td><td><div class=bar style=width:10.3%>&nbsp;</div></td></tr><tr class><td title=1.6>1.6</td><td>3</td><td>3.0%</td><td><div class=bar style=width:10.3%>&nbsp;</div></td></tr><tr class><td title=1.7>1.7</td><td>1</td><td>1.0%</td><td><div class=bar style=width:3.4%>&nbsp;</div></td></tr><tr class><td title=1.8>1.8</td><td>1</td><td>1.0%</td><td><div class=bar style=width:3.4%>&nbsp;</div></td></tr><tr class><td title=0.6>0.6</td><td>1</td><td>1.0%</td><td><div class=bar style=width:3.4%>&nbsp;</div></td></tr><tr class><td title=0.5>0.5</td><td>1</td><td>1.0%</td><td><div class=bar style=width:3.4%>&nbsp;</div></td></tr></tbody></table></div><div role=tabpanel class="tab-pane col-sm-12" id=431248425830137136bottom-431248425830137136extreme_values><div class="row spacing"><ul class="nav nav-tabs" role=tablist><li role=presentation class=active><a href=#431248425830137136extreme_values-431248425830137136firstn aria-controls=431248425830137136extreme_values-431248425830137136firstn role=tab data-toggle=tab>Minimum 5 values</a></li><li role=presentation><a href=#431248425830137136extreme_values-431248425830137136lastn aria-controls=431248425830137136extreme_values-431248425830137136lastn role=tab data-toggle=tab>Maximum 5 values</a></li></ul><div class=tab-content><div role=tabpanel class="tab-pane col-sm-12 active" id=431248425830137136extreme_values-431248425830137136firstn><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=0.1>0.1</td><td>5</td><td>5.0%</td><td><div class=bar style=width:17.2%>&nbsp;</div></td></tr><tr class><td title=0.2>0.2</td><td>29</td><td>29.0%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=0.3>0.3</td><td>7</td><td>7.0%</td><td><div class=bar style=width:24.1%>&nbsp;</div></td></tr><tr class><td title=0.4>0.4</td><td>7</td><td>7.0%</td><td><div class=bar style=width:24.1%>&nbsp;</div></td></tr><tr class><td title=0.5>0.5</td><td>1</td><td>1.0%</td><td><div class=bar style=width:3.4%>&nbsp;</div></td></tr><tr class><td title=0.6>0.6</td><td>1</td><td>1.0%</td><td><div class=bar style=width:3.4%>&nbsp;</div></td></tr><tr class><td title=1>1</td><td>7</td><td>7.0%</td><td><div class=bar style=width:24.1%>&nbsp;</div></td></tr><tr class><td title=1.1>1.1</td><td>3</td><td>3.0%</td><td><div class=bar style=width:10.3%>&nbsp;</div></td></tr><tr class><td title=1.2>1.2</td><td>5</td><td>5.0%</td><td><div class=bar style=width:17.2%>&nbsp;</div></td></tr><tr class><td title=1.3>1.3</td><td>13</td><td>13.0%</td><td><div class=bar style=width:44.8%>&nbsp;</div></td></tr></tbody></table></div><div role=tabpanel class="tab-pane col-sm-12" id=431248425830137136extreme_values-431248425830137136lastn><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=1.8>1.8</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.7%>&nbsp;</div></td></tr><tr class><td title=1.7>1.7</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.7%>&nbsp;</div></td></tr><tr class><td title=1.6>1.6</td><td>3</td><td>3.0%</td><td><div class=bar style=width:23.1%>&nbsp;</div></td></tr><tr class><td title=1.5>1.5</td><td>10</td><td>10.0%</td><td><div class=bar style=width:76.9%>&nbsp;</div></td></tr><tr class><td title=1.4>1.4</td><td>7</td><td>7.0%</td><td><div class=bar style=width:53.8%>&nbsp;</div></td></tr><tr class><td title=1.3>1.3</td><td>13</td><td>13.0%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=1.2>1.2</td><td>5</td><td>5.0%</td><td><div class=bar style=width:38.5%>&nbsp;</div></td></tr><tr class><td title=1.1>1.1</td><td>3</td><td>3.0%</td><td><div class=bar style=width:23.1%>&nbsp;</div></td></tr><tr class><td title=1>1</td><td>7</td><td>7.0%</td><td><div class=bar style=width:53.8%>&nbsp;</div></td></tr><tr class><td title=0.6>0.6</td><td>1</td><td>1.0%</td><td><div class=bar style=width:7.7%>&nbsp;</div></td></tr></tbody></table></div></div></div></div></div></div></div></div></div><div class="row spacing"><a class="anchor-pos anchor-pos-variable" id=pp_var_1975489024884402091></a><div class=variable><div class=col-sm-3><p class=h4 title=target><a href=#pp_var_1975489024884402091>target</a><br><small>Boolean</small></p><code><abbr title="This variable has a high correlation with 2 fields: petal length (cm), petal width (cm)">HIGH CORRELATION</abbr></code><br><p class=variable-description></p></div><div class=col-sm-3><table class="table table-condensed stats"><tbody><tr><th>Distinct</th><td>2</td></tr><tr><th>Distinct (%)</th><td>2.0%</td></tr><tr><th>Missing</th><td>0</td></tr><tr><th>Missing (%)</th><td>0.0%</td></tr><tr><th>Memory size</th><td>1.6 KiB</td></tr></tbody></table></div><div class=col-sm-6><div class="col-sm- collapse in" id=minifreqtable><table class="mini freq"><tr class><th width=50%> 1 </th><td width=50%><div class=bar style=width:100.0% data-toggle=tooltip data-placement=right data-html=true data-delay=500> 50&nbsp; </div></td></tr><tr class><th width=50%> 0 </th><td width=50%><div class=bar 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""/></g></g></g><defs><clippath id=pdba3874d18><rect height=235.835845 width=374.775 x=46.425 y=10.8 /></clippath></defs></svg><div class="caption text-center text-muted"> Histogram of lengths of the category </div></div><div class=col-sm-6><p class=h4>Length</p><table class="table table-condensed stats"><tbody><tr><th>Max length</th><td>10</td></tr><tr><th>Median length</th><td>8</td></tr><tr><th>Mean length</th><td>8</td></tr><tr><th>Min length</th><td>6</td></tr></tbody></table></div></div><div role=tabpanel class="tab-pane col-sm-12" id=1329591615293691764bottom-1329591615293691764unicode><div class="row spacing"><ul class="nav nav-tabs" role=tablist><li role=presentation class=active><a href=#1329591615293691764unicode-1329591615293691764character_overview aria-controls=1329591615293691764unicode-1329591615293691764character_overview role=tab data-toggle=tab>Overview</a></li><li role=presentation><a href=#1329591615293691764unicode-1329591615293691764characters aria-controls=1329591615293691764unicode-1329591615293691764characters role=tab data-toggle=tab>Characters</a></li><li role=presentation><a href=#1329591615293691764unicode-1329591615293691764categories aria-controls=1329591615293691764unicode-1329591615293691764categories role=tab data-toggle=tab>Categories</a></li><li role=presentation><a href=#1329591615293691764unicode-1329591615293691764scripts aria-controls=1329591615293691764unicode-1329591615293691764scripts role=tab data-toggle=tab>Scripts</a></li><li role=presentation><a href=#1329591615293691764unicode-1329591615293691764blocks aria-controls=1329591615293691764unicode-1329591615293691764blocks role=tab data-toggle=tab>Blocks</a></li></ul><div class=tab-content><div role=tabpanel class="tab-pane col-sm-12 active" id=1329591615293691764unicode-1329591615293691764character_overview><div class="row spacing"><p class=h4>Overview of Unicode Properties</p><table class="table table-condensed stats"><tbody><tr><th>Unique unicode characters</th><td>10</td></tr><tr><th>Unique unicode categories</th><td>1 <a title="Unicode categories (click for more information)" href=https://en.wikipedia.org/wiki/Unicode_character_property#General_Category target=_blank><span class="badge pull-right" style=color:#fff;background-color:#337ab7; title="Unicode categories (click for more information)">?</span></a></td></tr><tr><th>Unique unicode scripts</th><td>1 <a title="Unicode scripts (click for more information)" href=https://en.wikipedia.org/wiki/Script_(Unicode)#List_of_scripts_in_Unicode target=_blank><span class="badge pull-right" style=color:#fff;background-color:#337ab7; title="Unicode scripts (click for more information)">?</span></a></td></tr><tr><th>Unique unicode blocks</th><td>1 <a title="Unicode blocks (click for more information)" href=https://en.wikipedia.org/wiki/Unicode_block target=_blank><span class="badge pull-right" style=color:#fff;background-color:#337ab7; title="Unicode blocks (click for more information)">?</span></a></td></tr></tbody></table><div class="caption text-center text-muted"> The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables. </div></div></div><div role=tabpanel class="tab-pane col-sm-12" id=1329591615293691764unicode-1329591615293691764characters><div class="row named-list-item"><h4>Most occurring characters</h4><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=s>s</td><td>150</td><td>18.8%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=o>o</td><td>150</td><td>18.8%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=e>e</td><td>100</td><td>12.5%</td><td><div class=bar style=width:66.7%>&nbsp;</div></td></tr><tr class><td title=r>r</td><td>100</td><td>12.5%</td><td><div class=bar style=width:66.7%>&nbsp;</div></td></tr><tr class><td title=t>t</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=a>a</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=v>v</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=i>i</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=c>c</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=l>l</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr></tbody></table></div></div><div role=tabpanel class="tab-pane col-sm-12" id=1329591615293691764unicode-1329591615293691764categories><div class="row named-list-item"><h4>Most occurring categories</h4><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title="Lowercase Letter">Lowercase Letter</td><td>800</td><td>100.0%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr></tbody></table></div><div class="row named-list-item"><h4>Most frequent Lowercase Letter characters</h4><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=s>s</td><td>150</td><td>18.8%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=o>o</td><td>150</td><td>18.8%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=e>e</td><td>100</td><td>12.5%</td><td><div class=bar style=width:66.7%>&nbsp;</div></td></tr><tr class><td title=r>r</td><td>100</td><td>12.5%</td><td><div class=bar style=width:66.7%>&nbsp;</div></td></tr><tr class><td title=t>t</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=a>a</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=v>v</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=i>i</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=c>c</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=l>l</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr></tbody></table></div></div><div role=tabpanel class="tab-pane col-sm-12" id=1329591615293691764unicode-1329591615293691764scripts><div class="row named-list-item"><h4>Most occurring scripts</h4><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=Latin>Latin</td><td>800</td><td>100.0%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr></tbody></table></div><div class="row named-list-item"><h4>Most frequent Latin characters</h4><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=s>s</td><td>150</td><td>18.8%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=o>o</td><td>150</td><td>18.8%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=e>e</td><td>100</td><td>12.5%</td><td><div class=bar style=width:66.7%>&nbsp;</div></td></tr><tr class><td title=r>r</td><td>100</td><td>12.5%</td><td><div class=bar style=width:66.7%>&nbsp;</div></td></tr><tr class><td title=t>t</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=a>a</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=v>v</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=i>i</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=c>c</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=l>l</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr></tbody></table></div></div><div role=tabpanel class="tab-pane col-sm-12" id=1329591615293691764unicode-1329591615293691764blocks><div class="row named-list-item"><h4>Most occurring blocks</h4><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=ASCII>ASCII</td><td>800</td><td>100.0%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr></tbody></table></div><div class="row named-list-item"><h4>Most frequent ASCII characters</h4><table class="freq table table-hover table-striped"><thead><tr><td>Value</td><td>Count</td><td>Frequency (%)</td><td>&nbsp;</td></tr></thead><tbody><tr class><td title=s>s</td><td>150</td><td>18.8%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=o>o</td><td>150</td><td>18.8%</td><td><div class=bar style=width:100.0%>&nbsp;</div></td></tr><tr class><td title=e>e</td><td>100</td><td>12.5%</td><td><div class=bar style=width:66.7%>&nbsp;</div></td></tr><tr class><td title=r>r</td><td>100</td><td>12.5%</td><td><div class=bar style=width:66.7%>&nbsp;</div></td></tr><tr class><td title=t>t</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=a>a</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=v>v</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=i>i</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=c>c</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr><tr class><td title=l>l</td><td>50</td><td>6.2%</td><td><div class=bar style=width:33.3%>&nbsp;</div></td></tr></tbody></table></div></div></div></div></div></div></div></div></div></div></div><div class="row header"><a class=anchor-pos id=interactions></a><h1 class=page-header>Interactions</h1></div><div class=section-items><div class="row spacing"><ul class="nav nav-tabs" role=tablist><li role=presentation class=active><a href=#interactions-interactions_sepal_length_cm aria-controls=interactions-interactions_sepal_length_cm role=tab data-toggle=tab>sepal length (cm)</a></li><li role=presentation><a href=#interactions-interactions_sepal_width_cm aria-controls=interactions-interactions_sepal_width_cm role=tab data-toggle=tab>sepal width (cm)</a></li><li role=presentation><a href=#interactions-interactions_petal_length_cm aria-controls=interactions-interactions_petal_length_cm role=tab data-toggle=tab>petal length (cm)</a></li><li role=presentation><a href=#interactions-interactions_petal_width_cm aria-controls=interactions-interactions_petal_width_cm role=tab data-toggle=tab>petal width (cm)</a></li></ul><div class=tab-content><div role=tabpanel class="tab-pane col-sm-12 active" id=interactions-interactions_sepal_length_cm><div class="row spacing"><ul class="nav nav-tabs" role=tablist><li role=presentation class=active><a href=#interactions_sepal_length_cm-interactions_sepal_length_cm_sepal_length_cm aria-controls=interactions_sepal_length_cm-interactions_sepal_length_cm_sepal_length_cm role=tab data-toggle=tab>sepal length (cm)</a></li><li role=presentation><a href=#interactions_sepal_length_cm-interactions_sepal_length_cm_sepal_width_cm aria-controls=interactions_sepal_length_cm-interactions_sepal_length_cm_sepal_width_cm role=tab data-toggle=tab>sepal width (cm)</a></li><li role=presentation><a href=#interactions_sepal_length_cm-interactions_sepal_length_cm_petal_length_cm aria-controls=interactions_sepal_length_cm-interactions_sepal_length_cm_petal_length_cm role=tab data-toggle=tab>petal length (cm)</a></li><li role=presentation><a href=#interactions_sepal_length_cm-interactions_sepal_length_cm_petal_width_cm aria-controls=interactions_sepal_length_cm-interactions_sepal_length_cm_petal_width_cm role=tab data-toggle=tab>petal width (cm)</a></li></ul><div class=tab-content><div role=tabpanel class="tab-pane col-sm-12 active" id=interactions_sepal_length_cm-interactions_sepal_length_cm_sepal_length_cm><?xml version="1.0" encoding="utf-8" standalone="no"?><!DOCTYPE svg class="img-responsive center-img"PUBLIC "-//W3C//DTD SVG 1.1//EN"\n",
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|
||
"$(function () {\n",
|
||
" $('[data-toggle="tooltip"]').tooltip();\n",
|
||
"});\n",
|
||
"\n",
|
||
"$("a[href^='#'].anchor").on('click', function (e) {\n",
|
||
"\n",
|
||
" // prevent default anchor click behavior\n",
|
||
" e.preventDefault();\n",
|
||
"\n",
|
||
" // store hash\n",
|
||
" var hash = this.hash;\n",
|
||
"\n",
|
||
" // animate\n",
|
||
" $('html, body').animate({\n",
|
||
" scrollTop: $(hash).offset().top\n",
|
||
" }, 300, function () {\n",
|
||
"\n",
|
||
" // when done, add hash to url\n",
|
||
" // (default click behaviour)\n",
|
||
" window.location.hash = hash;\n",
|
||
" });\n",
|
||
"\n",
|
||
"}); </script></body></html>\" frameborder=\"0\" allowfullscreen></iframe>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
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|
||
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|
||
{
|
||
"data": {
|
||
"text/plain": []
|
||
},
|
||
"execution_count": 17,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"pp.ProfileReport(df=data, dark_mode=True, explorative=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>sepal length (cm)</th>\n",
|
||
" <th>sepal width (cm)</th>\n",
|
||
" <th>petal length (cm)</th>\n",
|
||
" <th>petal width (cm)</th>\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" <td>3.5</td>\n",
|
||
" <td>1.4</td>\n",
|
||
" <td>0.2</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>setosa</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>4.9</td>\n",
|
||
" <td>3.0</td>\n",
|
||
" <td>1.4</td>\n",
|
||
" <td>0.2</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>setosa</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>4.7</td>\n",
|
||
" <td>3.2</td>\n",
|
||
" <td>1.3</td>\n",
|
||
" <td>0.2</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>setosa</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>4.6</td>\n",
|
||
" <td>3.1</td>\n",
|
||
" <td>1.5</td>\n",
|
||
" <td>0.2</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>setosa</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>5.0</td>\n",
|
||
" <td>3.6</td>\n",
|
||
" <td>1.4</td>\n",
|
||
" <td>0.2</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>setosa</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>...</th>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>95</th>\n",
|
||
" <td>5.7</td>\n",
|
||
" <td>3.0</td>\n",
|
||
" <td>4.2</td>\n",
|
||
" <td>1.2</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>versicolor</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>96</th>\n",
|
||
" <td>5.7</td>\n",
|
||
" <td>2.9</td>\n",
|
||
" <td>4.2</td>\n",
|
||
" <td>1.3</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>versicolor</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>97</th>\n",
|
||
" <td>6.2</td>\n",
|
||
" <td>2.9</td>\n",
|
||
" <td>4.3</td>\n",
|
||
" <td>1.3</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>versicolor</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>98</th>\n",
|
||
" <td>5.1</td>\n",
|
||
" <td>2.5</td>\n",
|
||
" <td>3.0</td>\n",
|
||
" <td>1.1</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>versicolor</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>99</th>\n",
|
||
" <td>5.7</td>\n",
|
||
" <td>2.8</td>\n",
|
||
" <td>4.1</td>\n",
|
||
" <td>1.3</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>versicolor</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>100 rows × 6 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" sepal length (cm) sepal width (cm) petal length (cm) petal width (cm) \\\n",
|
||
"0 5.1 3.5 1.4 0.2 \n",
|
||
"1 4.9 3.0 1.4 0.2 \n",
|
||
"2 4.7 3.2 1.3 0.2 \n",
|
||
"3 4.6 3.1 1.5 0.2 \n",
|
||
"4 5.0 3.6 1.4 0.2 \n",
|
||
".. ... ... ... ... \n",
|
||
"95 5.7 3.0 4.2 1.2 \n",
|
||
"96 5.7 2.9 4.2 1.3 \n",
|
||
"97 6.2 2.9 4.3 1.3 \n",
|
||
"98 5.1 2.5 3.0 1.1 \n",
|
||
"99 5.7 2.8 4.1 1.3 \n",
|
||
"\n",
|
||
" target class \n",
|
||
"0 0 setosa \n",
|
||
"1 0 setosa \n",
|
||
"2 0 setosa \n",
|
||
"3 0 setosa \n",
|
||
"4 0 setosa \n",
|
||
".. ... ... \n",
|
||
"95 1 versicolor \n",
|
||
"96 1 versicolor \n",
|
||
"97 1 versicolor \n",
|
||
"98 1 versicolor \n",
|
||
"99 1 versicolor \n",
|
||
"\n",
|
||
"[100 rows x 6 columns]"
|
||
]
|
||
},
|
||
"execution_count": 18,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
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"source": [
|
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"data"
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]
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},
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{
|
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"cell_type": "code",
|
||
"execution_count": 19,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"data = data[['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)', 'petal width (cm)', 'target']]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"data.to_csv(CLEAN_DATA_PATH, index=False)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
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||
"metadata": {},
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"outputs": [],
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"source": []
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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",
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"language": "python",
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"name": "python3"
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.6.9"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 4
|
||
}
|