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Diffstat (limited to 'gems/ipynbdiff/spec/testdata/from.ipynb')
| -rw-r--r-- | gems/ipynbdiff/spec/testdata/from.ipynb | 197 |
1 files changed, 197 insertions, 0 deletions
diff --git a/gems/ipynbdiff/spec/testdata/from.ipynb b/gems/ipynbdiff/spec/testdata/from.ipynb new file mode 100644 index 00000000000..68a4b11cbbc --- /dev/null +++ b/gems/ipynbdiff/spec/testdata/from.ipynb @@ -0,0 +1,197 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "0aac5da7-745c-4eda-847a-3d0d07a1bb9b", + "metadata": { + "tags": [] + }, + "source": [ + "# This is a markdown cell\n", + "\n", + "This paragraph has\n", + "With\n", + "Many\n", + "Lines. How we will he handle MR notes?\n", + "\n", + "But I can add another paragraph" + ] + }, + { + "cell_type": "raw", + "id": "faecea5b-de0a-49fa-9a3a-61c2add652da", + "metadata": {}, + "source": [ + "This is a raw cell\n", + "With\n", + "Multiple lines" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "893ca2c0-ab75-4276-9dad-be1c40e16e8a", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0d707fb5-226f-46d6-80bd-489ebfb8905c", + "metadata": {}, + "outputs": [], + "source": [ + "np.random.seed(42)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "35467fcf-28b1-4c7b-bb09-4cb192c35293", + "metadata": { + "tags": [ + "senoid" + ] + }, "outputs": [ + { + "data": { + "text/plain": [ + "[<matplotlib.lines.Line2D at 0x123e39370>]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "some_invalid_base64_image_here\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = np.linspace(0, 4*np.pi,50)\n", + "y = np.sin(x)\n", + "\n", + "plt.plot(x, y)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "dc1178cd-c46d-4da3-9ab5-08f000699884", + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.DataFrame({\"x\": x, \"y\": y})" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "6e749b4f-b409-4700-870f-f68c39462490", + "metadata": { + "tags": [ + "some-table" + ] + }, + "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>x</th>\n", + " <th>y</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>0.000000</td>\n", + " <td>0.000000</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>0.256457</td>\n", + " <td>0.253655</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " x y\n", + "0 0.000000 0.000000\n", + "1 0.256457 0.253655" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df[:2]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0ddef5ef-94a3-4afd-9c70-ddee9694f512", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + }, + "toc-showtags": true + }, + "nbformat": 4, + "nbformat_minor": 5 +} |