conversations listlengths 2 3 | source stringclasses 1
value | stack stringclasses 1
value |
|---|---|---|
[
{
"from": "human",
"value": "Add in stub for Cython demo Jupyter notebook\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Cython Demo\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": ... | jupyter-notebook | chosen |
[
{
"from": "system",
"value": "Add command demo for reading object location/rotation.\n"
},
{
"from": "human",
"value": "version https://git-lfs.github.com/spec/v1\noid sha256:eef49fd96b60b5aa50e4ae498c57bd0249cf5221f6a37c9fa80542305d52b6df\nsize 680100\n"
},
{
"from": "gpt",
"value":... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Copy with only calculations (as best as possible) taken from the clean_copy and adding things from the original master\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {\n \"collap... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Test jupyter notebook within sphinx documentation.\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Try to incorporate jupyter notebook into sphinx\\n\",\n \"\\n\",\n \"1. I... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add an example notebook for testing.\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [],\n \"source\": [\n \"from oommffield impo... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add initial commit for 'Disentangled Representations for Manipulation of Sentiment in Text'\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Disentangled Representations for Manip... | jupyter-notebook | chosen |
[
{
"from": "system",
"value": "Add main idea for 'Fader Networks: Manipulating Images by Sliding Attributes'\n"
},
{
"from": "human",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Fader Networks: Manipulating Images by Sliding At... | jupyter-notebook | chosen |
[
{
"from": "system",
"value": "Fix the ASCII encoding issue with the clean script.\n"
},
{
"from": "human",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"- COCO (COmparing Continuous Optimisers): http://coco.gforge.inria.fr/\\n\",\... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add a basic test notebook for nbval testing\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"metadata\": {},\n \"outputs\": [\n {\n \"data\": {\n \"application/javascript\": [\n ... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Print Ones for every subject in Kampala\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [],\n \"source\": [\n \"import pandas ... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add an example of using db.py for filtering\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"metadata\": {\n \"collapsed\": false\n },\n \"outputs\": [\n ],\n \"source\": [\n \"# autom... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add a new directory for risk score learning.\n\nPiperOrigin-RevId: 325887256\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {\n \"colab_type\": \"text\",\n \"id\": \"FnylYBNKXI0t\"\n ... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add empty notebook for tutorials/phase so sphinx won't complain\n\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Empty example!\\n\",\n \"\\n\",\n \"Add an example here!\"... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Save list of users and numer of emails in csv\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 14,\n \"metadata\": {\n \"collapsed\": false\n },\n \"outputs\": [],\n \"source\": [\n \"from bigb... | jupyter-notebook | chosen |
[
{
"from": "system",
"value": "Fix the ASCII encoding issue with the clean script.\n"
},
{
"from": "human",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"- Iris data set: https://en.wikipedia.org/wiki/Iris_flower_data_set\\n\",\n ... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "chore: Create IPython file for code and tutorial\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# OpenCV Face Recognition\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"exe... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add a simple example for pytorch\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [],\n \"source\": [\n \"import torch\"\n ]\n ... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add minimal example using the Cython magic\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"%load_ext cythonmagic\"\n ]\n },\n {\... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add (empty) notebook about FFT\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Fast Fourier Transform (FFT)\\n\",\n \"\\n\",\n \"[back to main page](index.ipynb)\"\n ]\n ... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add global index for docs\n"
},
{
"from": "gpt",
"value": "{\n \"metadata\": {\n \"name\": \"\",\n \"signature\": \"sha256:90d45e817b951abdee1b2e0ee48a5d2d3c23c46848e36431ab6410b123c71436\"\n },\n \"nbformat\": 3,\n \"nbformat_minor\": 0,\n \"worksheets\": [\n {\n... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add global wind example notebook\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from ipyleaflet import Map, Velocity, TileLayer\\n\... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add simple IPyNotebook demonstrating execution times of algos.\n"
},
{
"from": "gpt",
"value": "{\n \"metadata\": {\n \"name\": \"\",\n \"signature\": \"sha256:5bf0d0467aaa6624c2fa9d0d73f2a53eb1b4364af2ab2f3f3b2f06849d609400\"\n },\n \"nbformat\": 3,\n \"nbformat_m... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add first stab at using ckan api\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from ckanapi import RemoteCKAN\"\n ]\n },\n {\n... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add the ability to specify whether a tensor you send is searchable publicly\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "DOC: Add annotations file for answer key.\n\nCurrently, just provide a way to render to some of the data extracted.\nIntended to have more thorough documentation of the spreadsheet,\nexplaining derivation/calculations in each sheet and column.\n"
},
{
"from": "gpt",
... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add (empty) notebook for Numba\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"http://numba.pydata.org/\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": nul... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add imports to demo notebook\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"metadata\": {},\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\":... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add another notebook about dates and time (this initial version is almost empty).\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Python date and time snippets\"\n ]\n },\n {... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add notebook for aromatic adjlists in thermo libraries\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {\n \"collapsed\": false\n },\n \"outputs\": [],\n \"source\": [\n ... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add a data download notebook\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"import matplotlib.pyplot as plt\\n\",\n \"import numpy ... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add notebook for simulations for Fig 3(b) with Nx=200.\n"
},
{
"from": "gpt",
"value": "{\n \"metadata\": {\n \"name\": \"fig3b_sim_nx200\"\n },\n \"nbformat\": 3,\n \"nbformat_minor\": 0,\n \"worksheets\": [\n {\n \"cells\": [\n {\n \"cell_type\": \"code\... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add notebook to test install\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"This notebook will test your system to check if Anaconda and Py-ART have been installed correctly. Sel... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add notebook with some CFFI experiments\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"these are just some random experiments ...\"\n ]\n },\n {\n \"cell_type\": \"code\",\n... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add a NB for testing/dev\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"A scratch notebook for testing and developing `simmy`.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n ... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add notebook for primitive generators\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Primitive generators\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add notebook with links to IR data\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Available Measurement Data\\n\",\n \"\\n\",\n \"[back to overview page](index.ipynb)\"\n ... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add an empty notebook for pandas\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Tools - pandas\\n\",\n \"*The `pandas` library provides high-performance, easy-to-use data str... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add rooter for this project\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"metadata\": {\n \"collapsed\": true\n },\n \"outputs\": [],\n \"source\": [\n \"import tensorflow\"\n ]\n ... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Test running python notebook from Github"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"metadata\": {\n \"collapsed\": false\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"o... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add Jupyter notebooks dir with example template\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Example Notebook for DFGMark\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add empty notebook for bacterial case\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n ... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add still empty tutorial ipython notebook\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# pymofa tutorial\\n\",\n \"last updated: 2016-09-02\\n\",\n \"\\n\",\n \"This no... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add notebook with a signal processing link\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Signal Processing\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\":... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add new chapter 10 notebook\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# ★ Trigonometric Interpolation And The FFT ★\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add another notebook about random numbers (this initial version is almost empty).\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Python random snippets\"\n ]\n },\n {\n \"... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add second notebook: get OECD metropolitan areas\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"metadata\": {\n \"collapsed\": false\n },\n \"outputs\": [],\n \"source\": [\n \"# -*- c... | jupyter-notebook | chosen |
[
{
"from": "human",
"value": "Add short blurb about testing\n"
},
{
"from": "gpt",
"value": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Testing\\n\",\n \"Several sets of test data were used to ensure the accuracy of each of the algor... | jupyter-notebook | chosen |
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