{
"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
}