Datasets:
common-pile
/
stackv2

Dataset card Data Studio Files
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1
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40
40
text
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9
10.5M
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stringdate
2024-11-18 17:53:22
2024-11-18 18:03:05
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2010-12-05 19:03:03
2023-09-03 17:46:41
metadata
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Parkinson's Disease - Hybrid Functional Petri Net (HFPN)\n", "This script has implemented the following blocks of the HFPN for PD:\n", "- [ ] Cholesterol homeostasis\n", "- [x] Calcium homeotasis\n", "- [ ] Energy met...
stackv2
2024-11-18T18:03:05.123876+00:00
2021-02-04T10:37:06
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 02 - Autoregressive Integrated Moving Average Models\n", "\n", "Based on [Alejandro Correa Bahnsen](albahnsen.com/)'s class notes for this course.\n", "\n", "version 2.0, July 2021\n", "\n", "## Part of the cl...
stackv2
2024-11-18T18:03:05.126300+00:00
2021-07-21T05:12:25
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{ "cells": [ { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "import tweepy\n", "from ibm_watson import PersonalityInsightsV3\n", "import json\n", "import pandas as pd\n", "import time" ] }, { "cell_type": "code", "execution_coun...
stackv2
2024-11-18T18:03:05.138653+00:00
2019-05-24T02:29:14
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{ "cells": [ { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "ename": "JSONDecodeError", "evalue": "Expecting value: line 1 column 1 (char 0)", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------...
stackv2
2024-11-18T18:03:05.144536+00:00
2019-11-27T23:38:07
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{ "metadata": { "name": "DTMC" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "code", "collapsed": false, "input": "%pylab inline", "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream"...
stackv2
2024-11-18T18:03:05.144649+00:00
2014-03-11T07:29:17
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "In this notebook we reconstruct the Stabilizer decomposition of the state $|H>^{\\otimes 6}$ of *Trading classical and quantum computational resources* (2016).\n", "\n", "Here $|H> = |0> + (1/\\sqrt 2-1)|1>$ is within local Cli...
stackv2
2024-11-18T18:03:05.144729+00:00
2023-08-18T15:32:57
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# P300 with muse - Cats & Dogs\n", "\n", "I was interested in knowing whether it was possible to observe a P300 with a Muse 2016 EEG headset.\n", "EEG channels on the Muse are not positioned ideally for P300. However, EEG p...
stackv2
2024-11-18T18:03:05.148454+00:00
2018-04-24T20:23:12
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d04610cbe701ff271e31e388c7783cc1906bcee0
{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Anlyse [`HiBench`](https://github.com/Intel-bigdata/HiBench) Measurements on [Gilgamesh](https://kb.hlrs.de/platforms/index.php/Urika_GX) (Cray URIKA GX)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ ...
stackv2
2024-11-18T18:03:05.163123+00:00
2021-07-16T14:03:19
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{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/sam/opt/anaconda3/envs/learn-env/lib/python3.6/site-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing ...
stackv2
2024-11-18T18:03:05.233362+00:00
2020-10-27T23:25:00
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "### Visualizing Data in Python\n", "#### Tables, Histograms, Boxplots, and Slicing for Statistics\n", "\n", "When working with a new dataset, one of the most useful things to do is to begin to visualize the data. By using t...
stackv2
2024-11-18T18:03:05.241919+00:00
2019-09-17T02:22:16
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{ "cells": [ { "cell_type": "markdown", "id": "dedicated-bahrain", "metadata": {}, "source": [ "# Yue - test suite code" ] }, { "cell_type": "code", "execution_count": 2, "id": "exterior-collective", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", ...
stackv2
2024-11-18T18:03:05.244740+00:00
2021-08-20T14:17:20
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Approximate and subdivide polygon chains\n", "\n", "This example shows how to approximate ([Douglas-Peucker algorithm](https://en.wikipedia.org/wiki/Ramer%E2%80%93Douglas%E2%80%93Peucker_algorithm)) and subdivide (B-Splines) ...
stackv2
2024-11-18T18:03:05.256301+00:00
2019-06-29T07:15:32
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{ "cells": [ { "cell_type": "code", "execution_count": 71, "metadata": { "ExecuteTime": { "end_time": "2020-05-02T10:01:51.863444Z", "start_time": "2020-05-02T10:01:51.670443Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "C:\\User...
stackv2
2024-11-18T18:03:05.261394+00:00
2020-05-25T07:49:37
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Merge and Data Preperation\n", "This Notebook is Merging different Dataframes containing features of patients together.\n", " " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outp...
stackv2
2024-11-18T18:03:05.338725+00:00
2021-02-27T15:48:08
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{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ {...
stackv2
2024-11-18T18:03:05.338842+00:00
2021-10-26T20:34:55
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{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "so...
stackv2
2024-11-18T18:03:05.346098+00:00
2023-07-15T10:35:53
{ "license": "MIT", "url": "https://raw.githubusercontent.com/mariushobbhahn/mariushobbhahn.github.io/b8884b91b0cb217c3e0bbb70a68520d1f5fca22a/img/Smoking/Costs and revenue of smoking.ipynb", "blob_id": "49e7d4fa22c6ef9d4e193d71b15d802e69f939d1", "directory_id": "d2f7467471d6ed170a695f5ab08a7dcee5407b0c", "pa...
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Load DataFrame and Buildup JS-useable table" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import os\n", "import pandas as pd\n", "from tqdm.auto impor...
stackv2
2024-11-18T18:03:05.377480+00:00
2021-01-17T06:30:24
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ebcf761f951eb8ee5bd659376ecbdd3c2aeb5e68
{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Customer Segmentation Analysis\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count...
stackv2
2024-11-18T18:03:05.377628+00:00
2019-03-12T06:29:32
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stackv2
2024-11-18T18:03:05.388468+00:00
2020-07-24T04:52:14
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fbd6fee0b3fc353ad47fd28297bbfcc59c00802e
{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Time delay-cosmography simulations\n", "\n", "This notebook requires standard python libraries and the publicly available packages on github:\n", "\n", "- lenstronomy (https://github.com/sibirrer/lenstronomy)\n", ...
stackv2
2024-11-18T18:03:05.390190+00:00
2019-07-17T21:09:44
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Prepare BOLD5000 data for input into a deep learning model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook takes the BOLD5000 dataset and prepares it for use in a deep learning model. S...
stackv2
2024-11-18T18:03:05.420822+00:00
2019-12-13T20:32:30
{ "license": "MIT", "url": "https://raw.githubusercontent.com/arashjamalian/fmriNet/a33ce002e46b4236e339ed0b6a4a35b696fa06eb/prep_data.ipynb", "blob_id": "b5c0a9561169e177f23b65c5f50db1dffd31ed2d", "directory_id": "38cf91461a11c8d240ace0015957f0841da8ab7f", "path": "/prep_data.ipynb", "content_id": "93cf008...
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{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "slideshow": { "slide_type": "skip" } }, "outputs": [], "source": [ "import numpy as np\n", "from scipy import stats\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import arv...
stackv2
2024-11-18T18:03:05.436453+00:00
2020-03-11T23:18:58
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{ "cells": [ { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "# U.S. College Majors - Data Analysis and Visualizations" ] }, { "cell_type": "markdown", "metadata": { "toc": true }, "source": [ "<h1>Table of Contents<span class=\"tocSkip\"></spa...
stackv2
2024-11-18T18:03:05.487368+00:00
2018-11-13T19:09:26
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{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "accelerator": "GPU", "colab": { "name": "AlphaFold2_with_ManualTemplates.ipynb", "provenance": [], "collapsed_sections": [], "include_colab_link": true }, "kernelspec": { "display_name": "Python 3", "name": "p...
stackv2
2024-11-18T18:03:05.519281+00:00
2021-09-12T17:32:14
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{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "name": "TPflashBenchmarkJava.ipynb", "provenance": [], "collapsed_sections": [], "toc_visible": true, "authorship_tag": "ABX9TyPwdx1uFKziJk1MvTRk9Imz", "include_colab_link": true }, "kernelspec": { ...
stackv2
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2023-08-24T14:23:50
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Base text classification" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Version 1\n", "# original: https://www.tensorflow.org/tutorials/keras/text_cla...
stackv2
2024-11-18T18:03:05.524704+00:00
2020-12-14T22:30:38
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Pandas Visualization" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n"...
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2020-12-17T19:37:46
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Analysis of Crowdfunding Projects\n", "\n", "### Data Description\n", "\n", "Kickstarter.com is a crowd funding website where creators post descriptions of projects they want to create, and individuals contribute some...
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