mirror of
https://github.com/deepseek-ai/DeepSeek-Coder
synced 2025-04-30 02:30:16 +00:00
apriori
This commit is contained in:
Orrm23
parent
50608e80e5
commit
5d2215c06c
730
Untitled13.ipynb
Normal file
730
Untitled13.ipynb
Normal file
@ -0,0 +1,730 @@
|
||||
{
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 0,
|
||||
"metadata": {
|
||||
"colab": {
|
||||
"provenance": [],
|
||||
"authorship_tag": "ABX9TyMJAMTJ2UxcPpBAc/ntokzp",
|
||||
"include_colab_link": true
|
||||
},
|
||||
"kernelspec": {
|
||||
"name": "python3",
|
||||
"display_name": "Python 3"
|
||||
},
|
||||
"language_info": {
|
||||
"name": "python"
|
||||
}
|
||||
},
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "view-in-github",
|
||||
"colab_type": "text"
|
||||
},
|
||||
"source": [
|
||||
"<a href=\"https://colab.research.google.com/github/Orrm23/DeepSeek-Coder/blob/main/Untitled13.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "iU_l3SQ9A65p"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
},
|
||||
{
|
||||
"source": [
|
||||
"#23_MarketBasketAnalysisusingAPIRIORI\n",
|
||||
"### Importing the basic libraries\n",
|
||||
"import numpy as np\n",
|
||||
"import pandas as pd\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"### Load Dataset from Local Directory\n",
|
||||
"from google.colab import files\n",
|
||||
"uploaded = files.upload()\n",
|
||||
"### Importing the dataset\n",
|
||||
"dataset = pd.read_csv('dataset.csv')\n",
|
||||
"print(dataset.shape)\n",
|
||||
"print(dataset.head(5))\n",
|
||||
"### Data Pre-Processing using vectorized operations\n",
|
||||
"# Extract the relevant columns (assuming first 20)\n",
|
||||
"transactions_df = dataset.iloc[:, :20]\n",
|
||||
"# Convert all values to strings\n",
|
||||
"transactions_df = transactions_df.astype(str)\n",
|
||||
"# Convert DataFrame to list of lists\n",
|
||||
"transactions = transactions_df.values.tolist()\n",
|
||||
"### Training APRIORI\n",
|
||||
"!pip install apyori\n",
|
||||
"from apyori import apriori\n",
|
||||
"rules = apriori(transactions = transactions, min_support = 0.003, min_confidence = 0.2, min_lift = 3, min_length = 2, max_length = 2)\n",
|
||||
"### Result\n",
|
||||
"results = list(rules)\n",
|
||||
"results\n",
|
||||
"### Results in Dataframe\n",
|
||||
"lhs = [tuple(result[2][0][0])[0] for result in results]\n",
|
||||
"rhs = [tuple(result[2][0][1])[0] for result in results]\n",
|
||||
"supports = [result[1] for result in results]\n",
|
||||
"confidences = [result[2][0][2] for result in results]\n",
|
||||
"lifts = [result[2][0][3] for result in results]\n",
|
||||
"resultsinDataFrame = pd.DataFrame(zip(lhs, rhs, supports, confidences, lifts), columns = ['Left Hand Side', 'Right Hand Side', 'Support', 'Confidence', 'Lift'])\n",
|
||||
"resultsinDataFrame"
|
||||
],
|
||||
"cell_type": "code",
|
||||
"metadata": {
|
||||
"id": "lFqrYPxIAk31",
|
||||
"colab": {
|
||||
"base_uri": "https://localhost:8080/",
|
||||
"height": 1291
|
||||
},
|
||||
"outputId": "dfb99183-e856-45ba-8a3d-9d4e58d67a90"
|
||||
},
|
||||
"execution_count": 1,
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "display_data",
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<IPython.core.display.HTML object>"
|
||||
],
|
||||
"text/html": [
|
||||
"\n",
|
||||
" <input type=\"file\" id=\"files-cd4b8c1e-81ca-47e9-afff-0523698ccd96\" name=\"files[]\" multiple disabled\n",
|
||||
" style=\"border:none\" />\n",
|
||||
" <output id=\"result-cd4b8c1e-81ca-47e9-afff-0523698ccd96\">\n",
|
||||
" Upload widget is only available when the cell has been executed in the\n",
|
||||
" current browser session. Please rerun this cell to enable.\n",
|
||||
" </output>\n",
|
||||
" <script>// Copyright 2017 Google LLC\n",
|
||||
"//\n",
|
||||
"// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
|
||||
"// you may not use this file except in compliance with the License.\n",
|
||||
"// You may obtain a copy of the License at\n",
|
||||
"//\n",
|
||||
"// http://www.apache.org/licenses/LICENSE-2.0\n",
|
||||
"//\n",
|
||||
"// Unless required by applicable law or agreed to in writing, software\n",
|
||||
"// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
|
||||
"// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
|
||||
"// See the License for the specific language governing permissions and\n",
|
||||
"// limitations under the License.\n",
|
||||
"\n",
|
||||
"/**\n",
|
||||
" * @fileoverview Helpers for google.colab Python module.\n",
|
||||
" */\n",
|
||||
"(function(scope) {\n",
|
||||
"function span(text, styleAttributes = {}) {\n",
|
||||
" const element = document.createElement('span');\n",
|
||||
" element.textContent = text;\n",
|
||||
" for (const key of Object.keys(styleAttributes)) {\n",
|
||||
" element.style[key] = styleAttributes[key];\n",
|
||||
" }\n",
|
||||
" return element;\n",
|
||||
"}\n",
|
||||
"\n",
|
||||
"// Max number of bytes which will be uploaded at a time.\n",
|
||||
"const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
|
||||
"\n",
|
||||
"function _uploadFiles(inputId, outputId) {\n",
|
||||
" const steps = uploadFilesStep(inputId, outputId);\n",
|
||||
" const outputElement = document.getElementById(outputId);\n",
|
||||
" // Cache steps on the outputElement to make it available for the next call\n",
|
||||
" // to uploadFilesContinue from Python.\n",
|
||||
" outputElement.steps = steps;\n",
|
||||
"\n",
|
||||
" return _uploadFilesContinue(outputId);\n",
|
||||
"}\n",
|
||||
"\n",
|
||||
"// This is roughly an async generator (not supported in the browser yet),\n",
|
||||
"// where there are multiple asynchronous steps and the Python side is going\n",
|
||||
"// to poll for completion of each step.\n",
|
||||
"// This uses a Promise to block the python side on completion of each step,\n",
|
||||
"// then passes the result of the previous step as the input to the next step.\n",
|
||||
"function _uploadFilesContinue(outputId) {\n",
|
||||
" const outputElement = document.getElementById(outputId);\n",
|
||||
" const steps = outputElement.steps;\n",
|
||||
"\n",
|
||||
" const next = steps.next(outputElement.lastPromiseValue);\n",
|
||||
" return Promise.resolve(next.value.promise).then((value) => {\n",
|
||||
" // Cache the last promise value to make it available to the next\n",
|
||||
" // step of the generator.\n",
|
||||
" outputElement.lastPromiseValue = value;\n",
|
||||
" return next.value.response;\n",
|
||||
" });\n",
|
||||
"}\n",
|
||||
"\n",
|
||||
"/**\n",
|
||||
" * Generator function which is called between each async step of the upload\n",
|
||||
" * process.\n",
|
||||
" * @param {string} inputId Element ID of the input file picker element.\n",
|
||||
" * @param {string} outputId Element ID of the output display.\n",
|
||||
" * @return {!Iterable<!Object>} Iterable of next steps.\n",
|
||||
" */\n",
|
||||
"function* uploadFilesStep(inputId, outputId) {\n",
|
||||
" const inputElement = document.getElementById(inputId);\n",
|
||||
" inputElement.disabled = false;\n",
|
||||
"\n",
|
||||
" const outputElement = document.getElementById(outputId);\n",
|
||||
" outputElement.innerHTML = '';\n",
|
||||
"\n",
|
||||
" const pickedPromise = new Promise((resolve) => {\n",
|
||||
" inputElement.addEventListener('change', (e) => {\n",
|
||||
" resolve(e.target.files);\n",
|
||||
" });\n",
|
||||
" });\n",
|
||||
"\n",
|
||||
" const cancel = document.createElement('button');\n",
|
||||
" inputElement.parentElement.appendChild(cancel);\n",
|
||||
" cancel.textContent = 'Cancel upload';\n",
|
||||
" const cancelPromise = new Promise((resolve) => {\n",
|
||||
" cancel.onclick = () => {\n",
|
||||
" resolve(null);\n",
|
||||
" };\n",
|
||||
" });\n",
|
||||
"\n",
|
||||
" // Wait for the user to pick the files.\n",
|
||||
" const files = yield {\n",
|
||||
" promise: Promise.race([pickedPromise, cancelPromise]),\n",
|
||||
" response: {\n",
|
||||
" action: 'starting',\n",
|
||||
" }\n",
|
||||
" };\n",
|
||||
"\n",
|
||||
" cancel.remove();\n",
|
||||
"\n",
|
||||
" // Disable the input element since further picks are not allowed.\n",
|
||||
" inputElement.disabled = true;\n",
|
||||
"\n",
|
||||
" if (!files) {\n",
|
||||
" return {\n",
|
||||
" response: {\n",
|
||||
" action: 'complete',\n",
|
||||
" }\n",
|
||||
" };\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" for (const file of files) {\n",
|
||||
" const li = document.createElement('li');\n",
|
||||
" li.append(span(file.name, {fontWeight: 'bold'}));\n",
|
||||
" li.append(span(\n",
|
||||
" `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
|
||||
" `last modified: ${\n",
|
||||
" file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
|
||||
" 'n/a'} - `));\n",
|
||||
" const percent = span('0% done');\n",
|
||||
" li.appendChild(percent);\n",
|
||||
"\n",
|
||||
" outputElement.appendChild(li);\n",
|
||||
"\n",
|
||||
" const fileDataPromise = new Promise((resolve) => {\n",
|
||||
" const reader = new FileReader();\n",
|
||||
" reader.onload = (e) => {\n",
|
||||
" resolve(e.target.result);\n",
|
||||
" };\n",
|
||||
" reader.readAsArrayBuffer(file);\n",
|
||||
" });\n",
|
||||
" // Wait for the data to be ready.\n",
|
||||
" let fileData = yield {\n",
|
||||
" promise: fileDataPromise,\n",
|
||||
" response: {\n",
|
||||
" action: 'continue',\n",
|
||||
" }\n",
|
||||
" };\n",
|
||||
"\n",
|
||||
" // Use a chunked sending to avoid message size limits. See b/62115660.\n",
|
||||
" let position = 0;\n",
|
||||
" do {\n",
|
||||
" const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
|
||||
" const chunk = new Uint8Array(fileData, position, length);\n",
|
||||
" position += length;\n",
|
||||
"\n",
|
||||
" const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
|
||||
" yield {\n",
|
||||
" response: {\n",
|
||||
" action: 'append',\n",
|
||||
" file: file.name,\n",
|
||||
" data: base64,\n",
|
||||
" },\n",
|
||||
" };\n",
|
||||
"\n",
|
||||
" let percentDone = fileData.byteLength === 0 ?\n",
|
||||
" 100 :\n",
|
||||
" Math.round((position / fileData.byteLength) * 100);\n",
|
||||
" percent.textContent = `${percentDone}% done`;\n",
|
||||
"\n",
|
||||
" } while (position < fileData.byteLength);\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" // All done.\n",
|
||||
" yield {\n",
|
||||
" response: {\n",
|
||||
" action: 'complete',\n",
|
||||
" }\n",
|
||||
" };\n",
|
||||
"}\n",
|
||||
"\n",
|
||||
"scope.google = scope.google || {};\n",
|
||||
"scope.google.colab = scope.google.colab || {};\n",
|
||||
"scope.google.colab._files = {\n",
|
||||
" _uploadFiles,\n",
|
||||
" _uploadFilesContinue,\n",
|
||||
"};\n",
|
||||
"})(self);\n",
|
||||
"</script> "
|
||||
]
|
||||
},
|
||||
"metadata": {}
|
||||
},
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"text": [
|
||||
"Saving dataset.csv to dataset.csv\n",
|
||||
"(7500, 20)\n",
|
||||
" shrimp almonds avocado vegetables mix green grapes \\\n",
|
||||
"0 burgers meatballs eggs NaN NaN \n",
|
||||
"1 chutney NaN NaN NaN NaN \n",
|
||||
"2 turkey avocado NaN NaN NaN \n",
|
||||
"3 mineral water milk energy bar whole wheat rice green tea \n",
|
||||
"4 low fat yogurt NaN NaN NaN NaN \n",
|
||||
"\n",
|
||||
" whole weat flour yams cottage cheese energy drink tomato juice \\\n",
|
||||
"0 NaN NaN NaN NaN NaN \n",
|
||||
"1 NaN NaN NaN NaN NaN \n",
|
||||
"2 NaN NaN NaN NaN NaN \n",
|
||||
"3 NaN NaN NaN NaN NaN \n",
|
||||
"4 NaN NaN NaN NaN NaN \n",
|
||||
"\n",
|
||||
" low fat yogurt green tea honey salad mineral water salmon antioxydant juice \\\n",
|
||||
"0 NaN NaN NaN NaN NaN NaN NaN \n",
|
||||
"1 NaN NaN NaN NaN NaN NaN NaN \n",
|
||||
"2 NaN NaN NaN NaN NaN NaN NaN \n",
|
||||
"3 NaN NaN NaN NaN NaN NaN NaN \n",
|
||||
"4 NaN NaN NaN NaN NaN NaN NaN \n",
|
||||
"\n",
|
||||
" frozen smoothie spinach olive oil \n",
|
||||
"0 NaN NaN NaN \n",
|
||||
"1 NaN NaN NaN \n",
|
||||
"2 NaN NaN NaN \n",
|
||||
"3 NaN NaN NaN \n",
|
||||
"4 NaN NaN NaN \n",
|
||||
"Collecting apyori\n",
|
||||
" Downloading apyori-1.1.2.tar.gz (8.6 kB)\n",
|
||||
" Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
|
||||
"Building wheels for collected packages: apyori\n",
|
||||
" Building wheel for apyori (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
|
||||
" Created wheel for apyori: filename=apyori-1.1.2-py3-none-any.whl size=5954 sha256=6f460bf2d21945572fd7d1a90d9524bf5c416704c59847856c42f2fb0d60d484\n",
|
||||
" Stored in directory: /root/.cache/pip/wheels/77/3d/a6/d317a6fb32be58a602b1e8c6b5d6f31f79322da554cad2a5ea\n",
|
||||
"Successfully built apyori\n",
|
||||
"Installing collected packages: apyori\n",
|
||||
"Successfully installed apyori-1.1.2\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"output_type": "execute_result",
|
||||
"data": {
|
||||
"text/plain": [
|
||||
" Left Hand Side Right Hand Side Support Confidence Lift\n",
|
||||
"0 light cream chicken 0.004533 0.290598 4.843305\n",
|
||||
"1 mushroom cream sauce escalope 0.005733 0.300699 3.790327\n",
|
||||
"2 pasta escalope 0.005867 0.372881 4.700185\n",
|
||||
"3 fromage blanc honey 0.003333 0.245098 5.178128\n",
|
||||
"4 herb & pepper ground beef 0.016000 0.323450 3.291555\n",
|
||||
"5 tomato sauce ground beef 0.005333 0.377358 3.840147\n",
|
||||
"6 light cream olive oil 0.003200 0.205128 3.120612\n",
|
||||
"7 whole wheat pasta olive oil 0.008000 0.271493 4.130221\n",
|
||||
"8 pasta shrimp 0.005067 0.322034 4.514494"
|
||||
],
|
||||
"text/html": [
|
||||
"\n",
|
||||
" <div id=\"df-008c783b-279a-40b9-a9e4-1b17fd994e2c\" class=\"colab-df-container\">\n",
|
||||
" <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>Left Hand Side</th>\n",
|
||||
" <th>Right Hand Side</th>\n",
|
||||
" <th>Support</th>\n",
|
||||
" <th>Confidence</th>\n",
|
||||
" <th>Lift</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>light cream</td>\n",
|
||||
" <td>chicken</td>\n",
|
||||
" <td>0.004533</td>\n",
|
||||
" <td>0.290598</td>\n",
|
||||
" <td>4.843305</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>mushroom cream sauce</td>\n",
|
||||
" <td>escalope</td>\n",
|
||||
" <td>0.005733</td>\n",
|
||||
" <td>0.300699</td>\n",
|
||||
" <td>3.790327</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>pasta</td>\n",
|
||||
" <td>escalope</td>\n",
|
||||
" <td>0.005867</td>\n",
|
||||
" <td>0.372881</td>\n",
|
||||
" <td>4.700185</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>fromage blanc</td>\n",
|
||||
" <td>honey</td>\n",
|
||||
" <td>0.003333</td>\n",
|
||||
" <td>0.245098</td>\n",
|
||||
" <td>5.178128</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>herb & pepper</td>\n",
|
||||
" <td>ground beef</td>\n",
|
||||
" <td>0.016000</td>\n",
|
||||
" <td>0.323450</td>\n",
|
||||
" <td>3.291555</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>5</th>\n",
|
||||
" <td>tomato sauce</td>\n",
|
||||
" <td>ground beef</td>\n",
|
||||
" <td>0.005333</td>\n",
|
||||
" <td>0.377358</td>\n",
|
||||
" <td>3.840147</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>6</th>\n",
|
||||
" <td>light cream</td>\n",
|
||||
" <td>olive oil</td>\n",
|
||||
" <td>0.003200</td>\n",
|
||||
" <td>0.205128</td>\n",
|
||||
" <td>3.120612</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>7</th>\n",
|
||||
" <td>whole wheat pasta</td>\n",
|
||||
" <td>olive oil</td>\n",
|
||||
" <td>0.008000</td>\n",
|
||||
" <td>0.271493</td>\n",
|
||||
" <td>4.130221</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>8</th>\n",
|
||||
" <td>pasta</td>\n",
|
||||
" <td>shrimp</td>\n",
|
||||
" <td>0.005067</td>\n",
|
||||
" <td>0.322034</td>\n",
|
||||
" <td>4.514494</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>\n",
|
||||
" <div class=\"colab-df-buttons\">\n",
|
||||
"\n",
|
||||
" <div class=\"colab-df-container\">\n",
|
||||
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-008c783b-279a-40b9-a9e4-1b17fd994e2c')\"\n",
|
||||
" title=\"Convert this dataframe to an interactive table.\"\n",
|
||||
" style=\"display:none;\">\n",
|
||||
"\n",
|
||||
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
|
||||
" <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
|
||||
" </svg>\n",
|
||||
" </button>\n",
|
||||
"\n",
|
||||
" <style>\n",
|
||||
" .colab-df-container {\n",
|
||||
" display:flex;\n",
|
||||
" gap: 12px;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .colab-df-convert {\n",
|
||||
" background-color: #E8F0FE;\n",
|
||||
" border: none;\n",
|
||||
" border-radius: 50%;\n",
|
||||
" cursor: pointer;\n",
|
||||
" display: none;\n",
|
||||
" fill: #1967D2;\n",
|
||||
" height: 32px;\n",
|
||||
" padding: 0 0 0 0;\n",
|
||||
" width: 32px;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .colab-df-convert:hover {\n",
|
||||
" background-color: #E2EBFA;\n",
|
||||
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
|
||||
" fill: #174EA6;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .colab-df-buttons div {\n",
|
||||
" margin-bottom: 4px;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" [theme=dark] .colab-df-convert {\n",
|
||||
" background-color: #3B4455;\n",
|
||||
" fill: #D2E3FC;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" [theme=dark] .colab-df-convert:hover {\n",
|
||||
" background-color: #434B5C;\n",
|
||||
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
|
||||
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
|
||||
" fill: #FFFFFF;\n",
|
||||
" }\n",
|
||||
" </style>\n",
|
||||
"\n",
|
||||
" <script>\n",
|
||||
" const buttonEl =\n",
|
||||
" document.querySelector('#df-008c783b-279a-40b9-a9e4-1b17fd994e2c button.colab-df-convert');\n",
|
||||
" buttonEl.style.display =\n",
|
||||
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
|
||||
"\n",
|
||||
" async function convertToInteractive(key) {\n",
|
||||
" const element = document.querySelector('#df-008c783b-279a-40b9-a9e4-1b17fd994e2c');\n",
|
||||
" const dataTable =\n",
|
||||
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
|
||||
" [key], {});\n",
|
||||
" if (!dataTable) return;\n",
|
||||
"\n",
|
||||
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
|
||||
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
|
||||
" + ' to learn more about interactive tables.';\n",
|
||||
" element.innerHTML = '';\n",
|
||||
" dataTable['output_type'] = 'display_data';\n",
|
||||
" await google.colab.output.renderOutput(dataTable, element);\n",
|
||||
" const docLink = document.createElement('div');\n",
|
||||
" docLink.innerHTML = docLinkHtml;\n",
|
||||
" element.appendChild(docLink);\n",
|
||||
" }\n",
|
||||
" </script>\n",
|
||||
" </div>\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"<div id=\"df-99413864-1e27-4eff-b893-b72424d2b6a1\">\n",
|
||||
" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-99413864-1e27-4eff-b893-b72424d2b6a1')\"\n",
|
||||
" title=\"Suggest charts\"\n",
|
||||
" style=\"display:none;\">\n",
|
||||
"\n",
|
||||
"<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
|
||||
" width=\"24px\">\n",
|
||||
" <g>\n",
|
||||
" <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
|
||||
" </g>\n",
|
||||
"</svg>\n",
|
||||
" </button>\n",
|
||||
"\n",
|
||||
"<style>\n",
|
||||
" .colab-df-quickchart {\n",
|
||||
" --bg-color: #E8F0FE;\n",
|
||||
" --fill-color: #1967D2;\n",
|
||||
" --hover-bg-color: #E2EBFA;\n",
|
||||
" --hover-fill-color: #174EA6;\n",
|
||||
" --disabled-fill-color: #AAA;\n",
|
||||
" --disabled-bg-color: #DDD;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" [theme=dark] .colab-df-quickchart {\n",
|
||||
" --bg-color: #3B4455;\n",
|
||||
" --fill-color: #D2E3FC;\n",
|
||||
" --hover-bg-color: #434B5C;\n",
|
||||
" --hover-fill-color: #FFFFFF;\n",
|
||||
" --disabled-bg-color: #3B4455;\n",
|
||||
" --disabled-fill-color: #666;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .colab-df-quickchart {\n",
|
||||
" background-color: var(--bg-color);\n",
|
||||
" border: none;\n",
|
||||
" border-radius: 50%;\n",
|
||||
" cursor: pointer;\n",
|
||||
" display: none;\n",
|
||||
" fill: var(--fill-color);\n",
|
||||
" height: 32px;\n",
|
||||
" padding: 0;\n",
|
||||
" width: 32px;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .colab-df-quickchart:hover {\n",
|
||||
" background-color: var(--hover-bg-color);\n",
|
||||
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
|
||||
" fill: var(--button-hover-fill-color);\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .colab-df-quickchart-complete:disabled,\n",
|
||||
" .colab-df-quickchart-complete:disabled:hover {\n",
|
||||
" background-color: var(--disabled-bg-color);\n",
|
||||
" fill: var(--disabled-fill-color);\n",
|
||||
" box-shadow: none;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .colab-df-spinner {\n",
|
||||
" border: 2px solid var(--fill-color);\n",
|
||||
" border-color: transparent;\n",
|
||||
" border-bottom-color: var(--fill-color);\n",
|
||||
" animation:\n",
|
||||
" spin 1s steps(1) infinite;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" @keyframes spin {\n",
|
||||
" 0% {\n",
|
||||
" border-color: transparent;\n",
|
||||
" border-bottom-color: var(--fill-color);\n",
|
||||
" border-left-color: var(--fill-color);\n",
|
||||
" }\n",
|
||||
" 20% {\n",
|
||||
" border-color: transparent;\n",
|
||||
" border-left-color: var(--fill-color);\n",
|
||||
" border-top-color: var(--fill-color);\n",
|
||||
" }\n",
|
||||
" 30% {\n",
|
||||
" border-color: transparent;\n",
|
||||
" border-left-color: var(--fill-color);\n",
|
||||
" border-top-color: var(--fill-color);\n",
|
||||
" border-right-color: var(--fill-color);\n",
|
||||
" }\n",
|
||||
" 40% {\n",
|
||||
" border-color: transparent;\n",
|
||||
" border-right-color: var(--fill-color);\n",
|
||||
" border-top-color: var(--fill-color);\n",
|
||||
" }\n",
|
||||
" 60% {\n",
|
||||
" border-color: transparent;\n",
|
||||
" border-right-color: var(--fill-color);\n",
|
||||
" }\n",
|
||||
" 80% {\n",
|
||||
" border-color: transparent;\n",
|
||||
" border-right-color: var(--fill-color);\n",
|
||||
" border-bottom-color: var(--fill-color);\n",
|
||||
" }\n",
|
||||
" 90% {\n",
|
||||
" border-color: transparent;\n",
|
||||
" border-bottom-color: var(--fill-color);\n",
|
||||
" }\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"\n",
|
||||
" <script>\n",
|
||||
" async function quickchart(key) {\n",
|
||||
" const quickchartButtonEl =\n",
|
||||
" document.querySelector('#' + key + ' button');\n",
|
||||
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
|
||||
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
|
||||
" try {\n",
|
||||
" const charts = await google.colab.kernel.invokeFunction(\n",
|
||||
" 'suggestCharts', [key], {});\n",
|
||||
" } catch (error) {\n",
|
||||
" console.error('Error during call to suggestCharts:', error);\n",
|
||||
" }\n",
|
||||
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
|
||||
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
|
||||
" }\n",
|
||||
" (() => {\n",
|
||||
" let quickchartButtonEl =\n",
|
||||
" document.querySelector('#df-99413864-1e27-4eff-b893-b72424d2b6a1 button');\n",
|
||||
" quickchartButtonEl.style.display =\n",
|
||||
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
|
||||
" })();\n",
|
||||
" </script>\n",
|
||||
"</div>\n",
|
||||
"\n",
|
||||
" <div id=\"id_608141c4-567b-4f50-88d6-7182c8a13969\">\n",
|
||||
" <style>\n",
|
||||
" .colab-df-generate {\n",
|
||||
" background-color: #E8F0FE;\n",
|
||||
" border: none;\n",
|
||||
" border-radius: 50%;\n",
|
||||
" cursor: pointer;\n",
|
||||
" display: none;\n",
|
||||
" fill: #1967D2;\n",
|
||||
" height: 32px;\n",
|
||||
" padding: 0 0 0 0;\n",
|
||||
" width: 32px;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .colab-df-generate:hover {\n",
|
||||
" background-color: #E2EBFA;\n",
|
||||
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
|
||||
" fill: #174EA6;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" [theme=dark] .colab-df-generate {\n",
|
||||
" background-color: #3B4455;\n",
|
||||
" fill: #D2E3FC;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" [theme=dark] .colab-df-generate:hover {\n",
|
||||
" background-color: #434B5C;\n",
|
||||
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
|
||||
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
|
||||
" fill: #FFFFFF;\n",
|
||||
" }\n",
|
||||
" </style>\n",
|
||||
" <button class=\"colab-df-generate\" onclick=\"generateWithVariable('resultsinDataFrame')\"\n",
|
||||
" title=\"Generate code using this dataframe.\"\n",
|
||||
" style=\"display:none;\">\n",
|
||||
"\n",
|
||||
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
|
||||
" width=\"24px\">\n",
|
||||
" <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
|
||||
" </svg>\n",
|
||||
" </button>\n",
|
||||
" <script>\n",
|
||||
" (() => {\n",
|
||||
" const buttonEl =\n",
|
||||
" document.querySelector('#id_608141c4-567b-4f50-88d6-7182c8a13969 button.colab-df-generate');\n",
|
||||
" buttonEl.style.display =\n",
|
||||
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
|
||||
"\n",
|
||||
" buttonEl.onclick = () => {\n",
|
||||
" google.colab.notebook.generateWithVariable('resultsinDataFrame');\n",
|
||||
" }\n",
|
||||
" })();\n",
|
||||
" </script>\n",
|
||||
" </div>\n",
|
||||
"\n",
|
||||
" </div>\n",
|
||||
" </div>\n"
|
||||
],
|
||||
"application/vnd.google.colaboratory.intrinsic+json": {
|
||||
"type": "dataframe",
|
||||
"variable_name": "resultsinDataFrame",
|
||||
"summary": "{\n \"name\": \"resultsinDataFrame\",\n \"rows\": 9,\n \"fields\": [\n {\n \"column\": \"Left Hand Side\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"light cream\",\n \"mushroom cream sauce\",\n \"tomato sauce\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Right Hand Side\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"chicken\",\n \"escalope\",\n \"shrimp\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Support\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.003896500487537852,\n \"min\": 0.0032,\n \"max\": 0.016,\n \"num_unique_values\": 9,\n \"samples\": [\n 0.008,\n 0.005733333333333333,\n 0.005333333333333333\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Confidence\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.056168653549259547,\n \"min\": 0.20512820512820515,\n \"max\": 0.37735849056603776,\n \"num_unique_values\": 9,\n \"samples\": [\n 0.2714932126696833,\n 0.30069930069930073,\n 0.37735849056603776\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Lift\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.7066844698506499,\n \"min\": 3.120611639881417,\n \"max\": 5.178127589063795,\n \"num_unique_values\": 9,\n \"samples\": [\n 4.130221288078346,\n 3.7903273197390845,\n 3.840147461662528\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
|
||||
}
|
||||
},
|
||||
"metadata": {},
|
||||
"execution_count": 1
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [],
|
||||
"metadata": {
|
||||
"id": "rj5duez_ERkd"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
}
|
||||
]
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user