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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 90,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\"\"\"\n",
+ "Name: Anand Panchdari\n",
+ "Roll No.: C013\n",
+ "Aim: Implement K means clustering and analyse the effect of varying the number of clusters.\n",
+ "\"\"\"\n",
+ "\n",
+ "import pandas as pd\n",
+ "import numpy as np\n",
+ "from sklearn.cluster import KMeans\n",
+ "from sklearn.preprocessing import LabelEncoder\n",
+ "from sklearn.preprocessing import MinMaxScaler\n",
+ "import seaborn as sns\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "df = pd.read_csv(\"datasets/facebook_live_sellers_thailand.csv\")\n",
+ "df.drop(['Column1', 'Column2', 'Column3', 'Column4'], axis=1, inplace=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 91,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Shape is \n",
+ "(7050, 12)\n",
+ "\n",
+ "Info is \n",
+ "<class 'pandas.core.frame.DataFrame'>\n",
+ "RangeIndex: 7050 entries, 0 to 7049\n",
+ "Data columns (total 12 columns):\n",
+ " # Column Non-Null Count Dtype \n",
+ "--- ------ -------------- ----- \n",
+ " 0 status_id 7050 non-null object\n",
+ " 1 status_type 7050 non-null object\n",
+ " 2 status_published 7050 non-null object\n",
+ " 3 num_reactions 7050 non-null int64 \n",
+ " 4 num_comments 7050 non-null int64 \n",
+ " 5 num_shares 7050 non-null int64 \n",
+ " 6 num_likes 7050 non-null int64 \n",
+ " 7 num_loves 7050 non-null int64 \n",
+ " 8 num_wows 7050 non-null int64 \n",
+ " 9 num_hahas 7050 non-null int64 \n",
+ " 10 num_sads 7050 non-null int64 \n",
+ " 11 num_angrys 7050 non-null int64 \n",
+ "dtypes: int64(9), object(3)\n",
+ "memory usage: 661.1+ KB\n",
+ "None\n",
+ "\n",
+ "Head is \n"
+ ]
+ },
+ {
+ "data": {
+ "application/vnd.microsoft.datawrangler.viewer.v0+json": {
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+ "rawType": "object",
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+ "rawType": "int64",
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+ "name": "num_comments",
+ "rawType": "int64",
+ "type": "integer"
+ },
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+ "name": "num_shares",
+ "rawType": "int64",
+ "type": "integer"
+ },
+ {
+ "name": "num_likes",
+ "rawType": "int64",
+ "type": "integer"
+ },
+ {
+ "name": "num_loves",
+ "rawType": "int64",
+ "type": "integer"
+ },
+ {
+ "name": "num_wows",
+ "rawType": "int64",
+ "type": "integer"
+ },
+ {
+ "name": "num_hahas",
+ "rawType": "int64",
+ "type": "integer"
+ },
+ {
+ "name": "num_sads",
+ "rawType": "int64",
+ "type": "integer"
+ },
+ {
+ "name": "num_angrys",
+ "rawType": "int64",
+ "type": "integer"
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+ "shape": {
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+ "rows": 5
+ }
+ },
+ "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",
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+ " .dataframe thead th {\n",
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+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>status_id</th>\n",
+ " <th>status_type</th>\n",
+ " <th>status_published</th>\n",
+ " <th>num_reactions</th>\n",
+ " <th>num_comments</th>\n",
+ " <th>num_shares</th>\n",
+ " <th>num_likes</th>\n",
+ " <th>num_loves</th>\n",
+ " <th>num_wows</th>\n",
+ " <th>num_hahas</th>\n",
+ " <th>num_sads</th>\n",
+ " <th>num_angrys</th>\n",
+ " </tr>\n",
+ " </thead>\n",
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+ " <td>1</td>\n",
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+ " <th>2</th>\n",
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+ " <td>4/21/2018 6:17</td>\n",
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+ " <td>0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>246675545449582_1648576705259452</td>\n",
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+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>246675545449582_1645700502213739</td>\n",
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+ " <td>204</td>\n",
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+ " <td>0</td>\n",
+ " <td>0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " status_id status_type status_published \\\n",
+ "0 246675545449582_1649696485147474 video 4/22/2018 6:00 \n",
+ "1 246675545449582_1649426988507757 photo 4/21/2018 22:45 \n",
+ "2 246675545449582_1648730588577397 video 4/21/2018 6:17 \n",
+ "3 246675545449582_1648576705259452 photo 4/21/2018 2:29 \n",
+ "4 246675545449582_1645700502213739 photo 4/18/2018 3:22 \n",
+ "\n",
+ " num_reactions num_comments num_shares num_likes num_loves num_wows \\\n",
+ "0 529 512 262 432 92 3 \n",
+ "1 150 0 0 150 0 0 \n",
+ "2 227 236 57 204 21 1 \n",
+ "3 111 0 0 111 0 0 \n",
+ "4 213 0 0 204 9 0 \n",
+ "\n",
+ " num_hahas num_sads num_angrys \n",
+ "0 1 1 0 \n",
+ "1 0 0 0 \n",
+ "2 1 0 0 \n",
+ "3 0 0 0 \n",
+ "4 0 0 0 "
+ ]
+ },
+ "execution_count": 91,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "print(f\"Shape is \\n{df.shape}\")\n",
+ "print(f\"\\nInfo is \")\n",
+ "print(df.info())\n",
+ "print(f\"\\nHead is \")\n",
+ "df.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 92,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.microsoft.datawrangler.viewer.v0+json": {
+ "columns": [
+ {
+ "name": "index",
+ "rawType": "object",
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+ "name": "num_reactions",
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+ "type": "float"
+ },
+ {
+ "name": "num_comments",
+ "rawType": "float64",
+ "type": "float"
+ },
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+ "name": "num_shares",
+ "rawType": "float64",
+ "type": "float"
+ },
+ {
+ "name": "num_likes",
+ "rawType": "float64",
+ "type": "float"
+ },
+ {
+ "name": "num_loves",
+ "rawType": "float64",
+ "type": "float"
+ },
+ {
+ "name": "num_wows",
+ "rawType": "float64",
+ "type": "float"
+ },
+ {
+ "name": "num_hahas",
+ "rawType": "float64",
+ "type": "float"
+ },
+ {
+ "name": "num_sads",
+ "rawType": "float64",
+ "type": "float"
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+ }
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+ "count",
+ "7050.0",
+ "7050.0",
+ "7050.0",
+ "7050.0",
+ "7050.0",
+ "7050.0",
+ "7050.0",
+ "7050.0",
+ "7050.0"
+ ],
+ [
+ "mean",
+ "230.11716312056737",
+ "224.3560283687943",
+ "40.022553191489365",
+ "215.0431205673759",
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+ "0.6964539007092199",
+ "0.24368794326241136",
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+ ],
+ [
+ "std",
+ "462.6253091352333",
+ "889.6368195190058",
+ "131.59996549017612",
+ "449.47235705614156",
+ "39.97293010859566",
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+ "17.0",
+ "0.0",
+ "0.0",
+ "0.0",
+ "0.0",
+ "0.0"
+ ],
+ [
+ "50%",
+ "59.5",
+ "4.0",
+ "0.0",
+ "58.0",
+ "0.0",
+ "0.0",
+ "0.0",
+ "0.0",
+ "0.0"
+ ],
+ [
+ "75%",
+ "219.0",
+ "23.0",
+ "4.0",
+ "184.75",
+ "3.0",
+ "0.0",
+ "0.0",
+ "0.0",
+ "0.0"
+ ],
+ [
+ "max",
+ "4710.0",
+ "20990.0",
+ "3424.0",
+ "4710.0",
+ "657.0",
+ "278.0",
+ "157.0",
+ "51.0",
+ "31.0"
+ ]
+ ],
+ "shape": {
+ "columns": 9,
+ "rows": 8
+ }
+ },
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
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+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
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+ " .dataframe thead th {\n",
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+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>num_reactions</th>\n",
+ " <th>num_comments</th>\n",
+ " <th>num_shares</th>\n",
+ " <th>num_likes</th>\n",
+ " <th>num_loves</th>\n",
+ " <th>num_wows</th>\n",
+ " <th>num_hahas</th>\n",
+ " <th>num_sads</th>\n",
+ " <th>num_angrys</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>count</th>\n",
+ " <td>7050.000000</td>\n",
+ " <td>7050.000000</td>\n",
+ " <td>7050.000000</td>\n",
+ " <td>7050.000000</td>\n",
+ " <td>7050.000000</td>\n",
+ " <td>7050.000000</td>\n",
+ " <td>7050.000000</td>\n",
+ " <td>7050.000000</td>\n",
+ " <td>7050.000000</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>mean</th>\n",
+ " <td>230.117163</td>\n",
+ " <td>224.356028</td>\n",
+ " <td>40.022553</td>\n",
+ " <td>215.043121</td>\n",
+ " <td>12.728652</td>\n",
+ " <td>1.289362</td>\n",
+ " <td>0.696454</td>\n",
+ " <td>0.243688</td>\n",
+ " <td>0.113191</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>std</th>\n",
+ " <td>462.625309</td>\n",
+ " <td>889.636820</td>\n",
+ " <td>131.599965</td>\n",
+ " <td>449.472357</td>\n",
+ " <td>39.972930</td>\n",
+ " <td>8.719650</td>\n",
+ " <td>3.957183</td>\n",
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+ " <td>0.000000</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>25%</th>\n",
+ " <td>17.000000</td>\n",
+ " <td>0.000000</td>\n",
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+ " </tr>\n",
+ " <tr>\n",
+ " <th>75%</th>\n",
+ " <td>219.000000</td>\n",
+ " <td>23.000000</td>\n",
+ " <td>4.000000</td>\n",
+ " <td>184.750000</td>\n",
+ " <td>3.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>max</th>\n",
+ " <td>4710.000000</td>\n",
+ " <td>20990.000000</td>\n",
+ " <td>3424.000000</td>\n",
+ " <td>4710.000000</td>\n",
+ " <td>657.000000</td>\n",
+ " <td>278.000000</td>\n",
+ " <td>157.000000</td>\n",
+ " <td>51.000000</td>\n",
+ " <td>31.000000</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " num_reactions num_comments num_shares num_likes num_loves \\\n",
+ "count 7050.000000 7050.000000 7050.000000 7050.000000 7050.000000 \n",
+ "mean 230.117163 224.356028 40.022553 215.043121 12.728652 \n",
+ "std 462.625309 889.636820 131.599965 449.472357 39.972930 \n",
+ "min 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
+ "25% 17.000000 0.000000 0.000000 17.000000 0.000000 \n",
+ "50% 59.500000 4.000000 0.000000 58.000000 0.000000 \n",
+ "75% 219.000000 23.000000 4.000000 184.750000 3.000000 \n",
+ "max 4710.000000 20990.000000 3424.000000 4710.000000 657.000000 \n",
+ "\n",
+ " num_wows num_hahas num_sads num_angrys \n",
+ "count 7050.000000 7050.000000 7050.000000 7050.000000 \n",
+ "mean 1.289362 0.696454 0.243688 0.113191 \n",
+ "std 8.719650 3.957183 1.597156 0.726812 \n",
+ "min 0.000000 0.000000 0.000000 0.000000 \n",
+ "25% 0.000000 0.000000 0.000000 0.000000 \n",
+ "50% 0.000000 0.000000 0.000000 0.000000 \n",
+ "75% 0.000000 0.000000 0.000000 0.000000 \n",
+ "max 278.000000 157.000000 51.000000 31.000000 "
+ ]
+ },
+ "execution_count": 92,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df.describe()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 93,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Status id 6997\n",
+ "Status published 6913\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(f\"Status id {len(df['status_id'].unique())}\")\n",
+ "print(f\"Status published {len(df['status_published'].unique())}\")\n",
+ "df.drop(['status_id', 'status_published'], axis=1, inplace=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 94,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<class 'pandas.core.frame.DataFrame'>\n",
+ "RangeIndex: 7050 entries, 0 to 7049\n",
+ "Data columns (total 10 columns):\n",
+ " # Column Non-Null Count Dtype \n",
+ "--- ------ -------------- ----- \n",
+ " 0 status_type 7050 non-null object\n",
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+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " status_type num_reactions num_comments num_shares num_likes num_loves \\\n",
+ "0 1.000000 0.112314 0.024393 0.076519 0.091720 0.140030 \n",
+ "1 0.333333 0.031847 0.000000 0.000000 0.031847 0.000000 \n",
+ "2 1.000000 0.048195 0.011243 0.016647 0.043312 0.031963 \n",
+ "3 0.333333 0.023567 0.000000 0.000000 0.023567 0.000000 \n",
+ "4 0.333333 0.045223 0.000000 0.000000 0.043312 0.013699 \n",
+ "\n",
+ " num_wows num_hahas num_sads num_angrys \n",
+ "0 0.010791 0.006369 0.019608 0.0 \n",
+ "1 0.000000 0.000000 0.000000 0.0 \n",
+ "2 0.003597 0.006369 0.000000 0.0 \n",
+ "3 0.000000 0.000000 0.000000 0.0 \n",
+ "4 0.000000 0.000000 0.000000 0.0 "
+ ]
+ },
+ "execution_count": 97,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "column = X.columns\n",
+ "minmax = MinMaxScaler()\n",
+ "X = minmax.fit_transform(X)\n",
+ "X = pd.DataFrame(X, columns=[column])\n",
+ "X.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def doKMEAN(n):\n",
+ " kmean = KMeans(n_clusters=n, random_state=0)\n",
+ " kmean.fit(X)\n",
+ " labels = kmean.labels_\n",
+ " correct_labels = sum(y==labels)\n",
+ " accuracy =correct_labels/float(y.size)\n",
+ " return correct_labels, accuracy"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "For k=1, the results are\n",
+ "63 out of 7050 were correctly labeled\n",
+ "Accuracy score: 0.01\n",
+ "\n",
+ "\n",
+ "For k=2, the results are\n",
+ "4288 out of 7050 were correctly labeled\n",
+ "Accuracy score: 0.61\n",
+ "\n",
+ "\n",
+ "For k=3, the results are\n",
+ "4066 out of 7050 were correctly labeled\n",
+ "Accuracy score: 0.58\n",
+ "\n",
+ "\n",
+ "For k=4, the results are\n",
+ "4112 out of 7050 were correctly labeled\n",
+ "Accuracy score: 0.58\n",
+ "\n",
+ "\n",
+ "For k=5, the results are\n",
+ "4080 out of 7050 were correctly labeled\n",
+ "Accuracy score: 0.58\n",
+ "\n",
+ "\n",
+ "For k=6, the results are\n",
+ "4014 out of 7050 were correctly labeled\n",
+ "Accuracy score: 0.57\n",
+ "\n",
+ "\n",
+ "For k=7, the results are\n",
+ "3965 out of 7050 were correctly labeled\n",
+ "Accuracy score: 0.56\n",
+ "\n",
+ "\n",
+ "For k=8, the results are\n",
+ "4074 out of 7050 were correctly labeled\n",
+ "Accuracy score: 0.58\n",
+ "\n",
+ "\n",
+ "For k=9, the results are\n",
+ "4074 out of 7050 were correctly labeled\n",
+ "Accuracy score: 0.58\n",
+ "\n",
+ "\n",
+ "For k=10, the results are\n",
+ "4009 out of 7050 were correctly labeled\n",
+ "Accuracy score: 0.57\n",
+ "\n",
+ "\n",
+ "The best value of k in range 1 to 10 is 2, with a value of 0.61\n"
+ ]
+ }
+ ],
+ "source": [
+ "accs=dict()\n",
+ "for i in range(1,11):\n",
+ " print(f\"For k={i}, the results are\")\n",
+ " correct_labels, accuracy = doKMEAN(i)\n",
+ " print(f\"{correct_labels} out of {y.size} were correctly labeled\")\n",
+ " print(f'Accuracy score: {correct_labels/float(y.size):.2f}')\n",
+ " print('\\n')\n",
+ " accs[i]=accuracy\n",
+ "bestk = max(accs, key=accs.get)\n",
+ "print(f\"The best value of k in range 1 to 10 is {bestk}, with a value of {accs[bestk]:.2f}\")"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "venv",
+ "language": "python",
+ "name": "venv"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.9"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
generated by cgit v1.2.3 (git 2.46.0) at 2026-04-06 23:22:31 +0000