actually remove Python notebooks
This commit is contained in:
avimallu
@@ -1,86 +0,0 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "4f76fe31-46f7-4252-8a57-f6689d2ab9c7",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import polars as pl\n",
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"data = pl.from_repr(\"\"\"\n",
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"┌─────────────────────┬─────────────────────┬─────┐\n",
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"│ arrival_time ┆ departure_time ┆ ID │\n",
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"│ --- ┆ --- ┆ --- │\n",
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"│ datetime[μs] ┆ datetime[μs] ┆ str │\n",
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"╞═════════════════════╪═════════════════════╪═════╡\n",
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"│ 2023-01-01 06:23:47 ┆ 2023-01-01 06:25:08 ┆ A1 │\n",
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"│ 2023-01-01 06:26:42 ┆ 2023-01-01 06:28:02 ┆ A1 │\n",
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"│ 2023-01-01 06:30:20 ┆ 2023-01-01 06:35:01 ┆ A5 │\n",
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"│ 2023-01-01 06:32:06 ┆ 2023-01-01 06:33:48 ┆ A6 │\n",
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"│ 2023-01-01 06:33:09 ┆ 2023-01-01 06:36:01 ┆ B3 │\n",
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"│ 2023-01-01 06:34:08 ┆ 2023-01-01 06:39:49 ┆ C3 │\n",
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"│ 2023-01-01 06:36:40 ┆ 2023-01-01 06:38:34 ┆ A6 │\n",
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"│ 2023-01-01 06:37:43 ┆ 2023-01-01 06:40:48 ┆ A5 │\n",
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"│ 2023-01-01 06:39:48 ┆ 2023-01-01 06:46:10 ┆ A6 │\n",
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"└─────────────────────┴─────────────────────┴─────┘\n",
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"\"\"\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "a98af5f2-3dfb-405e-9654-62e8c623e683",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['A1', 'A1', 'A5', 'A6', 'B3', 'C3', 'A6', 'A5', 'A6']\n"
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]
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}
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],
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"source": [
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"print(data.to_series(2).cast(pl.Utf8).to_list())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "218be411-1e32-4374-8e73-0d9c40f133fe",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"df = pl.DataFrame({'a': [1,2,3], 'b': [4,5,6] , \"c\" : [6,7,8]})"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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204
Untitled1.ipynb
204
Untitled1.ipynb
@@ -1,204 +0,0 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "5be6be9d-cb59-4833-b5d2-d485b48ab605",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import polars as pl\n",
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"df = pl.DataFrame({'a': [1,2,3], 'b': [4,5,6] , \"c\" : [6,7,8]})"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "cbeac661-6bf5-4736-ac47-018b89ce178e",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div><style>\n",
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".dataframe > thead > tr > th,\n",
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".dataframe > tbody > tr > td {\n",
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" text-align: right;\n",
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"}\n",
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"</style>\n",
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"<small>shape: (3, 1)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>sum</th></tr><tr><td>i64</td></tr></thead><tbody><tr><td>11</td></tr><tr><td>14</td></tr><tr><td>17</td></tr></tbody></table></div>"
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],
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"text/plain": [
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"shape: (3, 1)\n",
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"┌─────┐\n",
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"│ sum │\n",
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"│ --- │\n",
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"│ i64 │\n",
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"╞═════╡\n",
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"│ 11 │\n",
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"│ 14 │\n",
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"│ 17 │\n",
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"└─────┘"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"df.select(pl.sum(df))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "23533f07-b063-4e0b-b429-3b822b7f8da3",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div><style>\n",
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".dataframe > thead > tr > th,\n",
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".dataframe > tbody > tr > td {\n",
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" text-align: right;\n",
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"}\n",
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"</style>\n",
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"<small>shape: (1, 3)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>a</th><th>b</th><th>c</th></tr><tr><td>list[i64]</td><td>list[i64]</td><td>list[i64]</td></tr></thead><tbody><tr><td>[1, 2, 3]</td><td>[4, 5, 6]</td><td>[6, 7, 8]</td></tr></tbody></table></div>"
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],
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"text/plain": [
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"shape: (1, 3)\n",
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"┌───────────┬───────────┬───────────┐\n",
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"│ a ┆ b ┆ c │\n",
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"│ --- ┆ --- ┆ --- │\n",
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"│ list[i64] ┆ list[i64] ┆ list[i64] │\n",
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"╞═══════════╪═══════════╪═══════════╡\n",
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"│ [1, 2, 3] ┆ [4, 5, 6] ┆ [6, 7, 8] │\n",
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"└───────────┴───────────┴───────────┘"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"df.select(pl.implode(df.columns))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "6132a9de-bbfe-4dea-a38c-321ec96ba7f9",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"shape: (3,)\n",
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"Series: '' [o][object]\n",
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"[\n",
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"\t{'a': '0', 'b': 0}\n",
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"\t{'a': '1', 'b': 1}\n",
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"\t{'a': '2', 'b': 2}\n",
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"]\n"
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]
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}
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],
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"source": [
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"import polars as pl\n",
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"# force use object here for demo, custom object in real production\n",
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"s=pl.Series([0,1,2], dtype=pl.Object) \n",
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"\n",
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"print(s.apply(lambda x: {\"a\":str(x), \"b\":x}, return_dtype=pl.Object))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "e3380d33-34a4-48ba-a1ee-aa2682d5e678",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"data = pl.DataFrame(\n",
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" {'geo': [\"[[-99.134,19.401],[-98.234,16.403],[-99.432,19.401]]\",\n",
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" \"[[-99.1962,19.401],[-95.196,19.345]]\",\n",
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" \"[[-93.196,19.401],[-94.196,19.401],[-99.196,19.401],[-99.196,19.401]]\"]})"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"id": "07a4e50f-e763-478d-a017-72cd00d74302",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div><style>\n",
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".dataframe > thead > tr > th,\n",
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".dataframe > tbody > tr > td {\n",
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" text-align: right;\n",
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"}\n",
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"</style>\n",
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"<small>shape: (3, 1)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>geo</th></tr><tr><td>list[str]</td></tr></thead><tbody><tr><td>["[[-99.134", "19.401]", … "19.401]]"]</td></tr><tr><td>["[[-99.1962", "19.401]", … "19.345]]"]</td></tr><tr><td>["[[-93.196", "19.401]", … "19.401]]"]</td></tr></tbody></table></div>"
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],
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"text/plain": [
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"shape: (3, 1)\n",
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"┌───────────────────────────────────┐\n",
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"│ geo │\n",
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"│ --- │\n",
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"│ list[str] │\n",
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"╞═══════════════════════════════════╡\n",
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"│ [\"[[-99.134\", \"19.401]\", … \"19.4… │\n",
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"│ [\"[[-99.1962\", \"19.401]\", … \"19.… │\n",
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"│ [\"[[-93.196\", \"19.401]\", … \"19.4… │\n",
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"└───────────────────────────────────┘"
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]
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},
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"execution_count": 19,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"data.with_columns(pl.col(\"geo\").str.split(\",\").list.eval(pl.element().str.split(\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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