{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from IPython.core.interactiveshell import InteractiveShell\n", "InteractiveShell.ast_node_interactivity = \"all\"" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from pathlib import Path\n", "proj_dir = Path.cwd().parent\n", "proj_dir" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "pycharm": { "is_executing": true } }, "outputs": [], "source": [ "import kangas as kg\n", "from datasets import load_dataset\n", "\n", "# dataset = load_dataset(\"beans\", split=\"train\")\n", "# dg = kg.DataGrid(dataset)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from pathlib import Path\n", "proj_dir = Path.cwd().parent\n", "\n", "import kangas as kg\n", "from datasets import load_dataset\n", "\n", "dataset_repo = 'beans'\n", "dataset = load_dataset(dataset_repo, split=\"train\")\n", "dg = kg.DataGrid(dataset)\n", "dg_file_name = dataset_repo.replace('/', '__') + '.datagrid' + '.2'\n", "dg.save(proj_dir / 'datagrids' / dg_file_name)\n", "kg.show()" ] }, { "cell_type": "code", "execution_count": null, "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": "3.9.16" } }, "nbformat": 4, "nbformat_minor": 1 }