{ "cells": [ { "cell_type": "markdown", "id": "bb85f8b2", "metadata": { "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", "papermill": { "duration": 0.019514, "end_time": "2021-07-13T06:21:48.291129", "exception": false, "start_time": "2021-07-13T06:21:48.271615", "status": "completed" }, "tags": [] }, "source": [ "
\n", "

DatatableTon

\n", " πŸ’― datatable exercises\n", "
\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
" ] }, { "cell_type": "markdown", "id": "d0754598", "metadata": { "papermill": { "duration": 0.017668, "end_time": "2021-07-13T06:21:48.327709", "exception": false, "start_time": "2021-07-13T06:21:48.310041", "status": "completed" }, "tags": [] }, "source": [ "
\n", " This is Set 3: Data Selection (Exercises 21-30) of DatatableTon: πŸ’― datatable exercises\n", "
\n", " You can find all the exercises and solutions on GitHub\n", "
" ] }, { "cell_type": "markdown", "id": "39ac5f92", "metadata": { "papermill": { "duration": 0.01749, "end_time": "2021-07-13T06:21:48.363013", "exception": false, "start_time": "2021-07-13T06:21:48.345523", "status": "completed" }, "tags": [] }, "source": [ "**Prerequisites**\n", "* The `datatable` package should be upgraded to the latest version (or v1.0.0+).\n", "* The sample dataset [datatableton_sample.csv](https://github.com/vopani/datatableton/blob/main/data/datatableton_sample.csv) will be used for the exercises." ] }, { "cell_type": "code", "execution_count": 1, "id": "75433678", "metadata": { "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-07-13T06:21:48.411941Z", "iopub.status.busy": "2021-07-13T06:21:48.411385Z", "iopub.status.idle": "2021-07-13T06:22:16.869865Z", "shell.execute_reply": "2021-07-13T06:22:16.869175Z", "shell.execute_reply.started": "2021-07-09T16:57:01.831667Z" }, "papermill": { "duration": 28.48944, "end_time": "2021-07-13T06:22:16.870003", "exception": false, "start_time": "2021-07-13T06:21:48.380563", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: pip in /opt/conda/lib/python3.7/site-packages (21.1.2)\r\n", "Collecting pip\r\n", " Downloading pip-21.1.3-py3-none-any.whl (1.5 MB)\r\n", "\u001b[K |β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1.5 MB 1.1 MB/s \r\n", "\u001b[?25hInstalling collected packages: pip\r\n", " Attempting uninstall: pip\r\n", " Found existing installation: pip 21.1.2\r\n", " Uninstalling pip-21.1.2:\r\n", " Successfully uninstalled pip-21.1.2\r\n", "Successfully installed pip-21.1.3\r\n", "\u001b[33mWARNING: Running pip as root will break packages and permissions. You should install packages reliably by using venv: https://pip.pypa.io/warnings/venv\u001b[0m\r\n", "Requirement already satisfied: datatable in /opt/conda/lib/python3.7/site-packages (1.0.0)\r\n", "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\r\n", "--2021-07-13 06:22:16-- https://raw.githubusercontent.com/vopani/datatableton/main/data/datatableton_sample.csv\r\n", "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.111.133, 185.199.109.133, ...\r\n", "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\r\n", "HTTP request sent, awaiting response... 200 OK\r\n", "Length: 940 [text/plain]\r\n", "Saving to: β€˜datatableton_sample.csv’\r\n", "\r\n", "datatableton_sample 100%[===================>] 940 --.-KB/s in 0s \r\n", "\r\n", "2021-07-13 06:22:16 (60.9 MB/s) - β€˜datatableton_sample.csv’ saved [940/940]\r\n", "\r\n" ] } ], "source": [ "!python3 -m pip install -U pip\n", "!python3 -m pip install -U datatable\n", "!wget https://raw.githubusercontent.com/vopani/datatableton/main/data/datatableton_sample.csv" ] }, { "cell_type": "code", "execution_count": 2, "id": "483e12a1", "metadata": { "execution": { "iopub.execute_input": "2021-07-13T06:22:16.922007Z", "iopub.status.busy": "2021-07-13T06:22:16.921187Z", "iopub.status.idle": "2021-07-13T06:22:17.075393Z", "shell.execute_reply": "2021-07-13T06:22:17.075906Z", "shell.execute_reply.started": "2021-07-09T16:57:11.178992Z" }, "papermill": { "duration": 0.183177, "end_time": "2021-07-13T06:22:17.076054", "exception": false, "start_time": "2021-07-13T06:22:16.892877", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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timestampuserageproductcategorypricequantity
▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪
02017-01-01T13:22:41U121EggsDairy2.32
12017-05-22T09:54:21U241BreadNA0.62
22018-11-09T15:00:01U3NABananaFruit0.71
32018-12-24T23:03:33U121WaterDrink0.21
42019-03-03T06:21:58U419EggsDairy2.32
52019-06-17T16:13:39U525GrapesFruit1.51
62019-07-28T21:03:11U525BreadNA0.61
72019-12-05T04:15:42U121BananaFruit0.72
82020-02-02T03:45:34U3NABananaFruit0.71
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142020-11-19T18:51:22U525WaterDrink0.21
152020-12-03T16:23:48U3NABananaFruit0.53
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20 rows × 7 columns
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\n" ], "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import datatable as dt\n", "\n", "data = dt.fread('datatableton_sample.csv')\n", "data" ] }, { "cell_type": "markdown", "id": "6ca4f445", "metadata": { "papermill": { "duration": 0.029309, "end_time": "2021-07-13T06:22:17.133745", "exception": false, "start_time": "2021-07-13T06:22:17.104436", "status": "completed" }, "tags": [] }, "source": [ "**Exercise 21: Select the columns `user`, `product` and `quantity` from `data` and assign it to `data_upq` and select the `user` column from `data_upq` and assign it to `data_u`**" ] }, { "cell_type": "code", "execution_count": null, "id": "8d19d727", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:47.347063Z", "iopub.status.busy": "2021-07-10T03:45:47.346303Z", "iopub.status.idle": "2021-07-10T03:45:47.349484Z", "shell.execute_reply": "2021-07-10T03:45:47.349981Z", "shell.execute_reply.started": "2021-07-09T16:57:11.398425Z" }, "papermill": { "duration": 0.029402, "end_time": "2021-07-13T06:22:17.186258", "exception": false, "start_time": "2021-07-13T06:22:17.156856", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "0db7a5a5", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:47.401297Z", "iopub.status.busy": "2021-07-10T03:45:47.400593Z", "iopub.status.idle": "2021-07-10T03:45:47.407143Z", "shell.execute_reply": "2021-07-10T03:45:47.406444Z", "shell.execute_reply.started": "2021-07-09T16:57:57.848188Z" }, "papermill": { "duration": 0.023768, "end_time": "2021-07-13T06:22:17.233672", "exception": false, "start_time": "2021-07-13T06:22:17.209904", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "42adcb4b", "metadata": { "papermill": { "duration": 0.027044, "end_time": "2021-07-13T06:22:17.286592", "exception": false, "start_time": "2021-07-13T06:22:17.259548", "status": "completed" }, "tags": [] }, "source": [ "**Exercise 22: Select columns 2nd to 4th using indices from `data` and assign it to `data_c234`**" ] }, { "cell_type": "code", "execution_count": null, "id": "e047af44", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:47.509214Z", "iopub.status.busy": "2021-07-10T03:45:47.508512Z", "iopub.status.idle": "2021-07-10T03:45:47.514814Z", "shell.execute_reply": "2021-07-10T03:45:47.514256Z", "shell.execute_reply.started": "2021-07-09T17:00:00.76353Z" }, "papermill": { "duration": 0.032678, "end_time": "2021-07-13T06:22:17.342630", "exception": false, "start_time": "2021-07-13T06:22:17.309952", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "c8b3f1a9", "metadata": { "papermill": { "duration": 0.023018, "end_time": "2021-07-13T06:22:17.396710", "exception": false, "start_time": "2021-07-13T06:22:17.373692", "status": "completed" }, "tags": [] }, "source": [ "**Exercise 23: Select all string columns from `data` and assign it to `data_str`**" ] }, { "cell_type": "code", "execution_count": null, "id": "94e62b84", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:47.618463Z", "iopub.status.busy": "2021-07-10T03:45:47.617378Z", "iopub.status.idle": "2021-07-10T03:45:47.621728Z", "shell.execute_reply": "2021-07-10T03:45:47.622194Z", "shell.execute_reply.started": "2021-07-09T17:00:19.482581Z" }, "papermill": { "duration": 0.023554, "end_time": "2021-07-13T06:22:17.443382", "exception": false, "start_time": "2021-07-13T06:22:17.419828", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "b2f3487d", "metadata": { "papermill": { "duration": 0.023222, "end_time": "2021-07-13T06:22:17.489740", "exception": false, "start_time": "2021-07-13T06:22:17.466518", "status": "completed" }, "tags": [] }, "source": [ "**Exercise 24: Select rows 4th and 1st from `data` and assign it to `data_r41`**" ] }, { "cell_type": "code", "execution_count": null, "id": "faab4ff1", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:47.731591Z", "iopub.status.busy": "2021-07-10T03:45:47.730805Z", "iopub.status.idle": "2021-07-10T03:45:47.735896Z", "shell.execute_reply": "2021-07-10T03:45:47.736415Z", "shell.execute_reply.started": "2021-07-09T17:01:05.089537Z" }, "papermill": { "duration": 0.023442, "end_time": "2021-07-13T06:22:17.536925", "exception": false, "start_time": "2021-07-13T06:22:17.513483", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "8c357f8d", "metadata": { "papermill": { "duration": 0.02343, "end_time": "2021-07-13T06:22:17.583628", "exception": false, "start_time": "2021-07-13T06:22:17.560198", "status": "completed" }, "tags": [] }, "source": [ "**Exercise 25: Select the element in the 4th row and 2nd column in `data` and assign it to `value_1` and select the 3rd element of `category` column in `data` and assign it to `value_2`**" ] }, { "cell_type": "code", "execution_count": null, "id": "610e1df0", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:47.858656Z", "iopub.status.busy": "2021-07-10T03:45:47.857945Z", "iopub.status.idle": "2021-07-10T03:45:47.860829Z", "shell.execute_reply": "2021-07-10T03:45:47.861512Z", "shell.execute_reply.started": "2021-07-09T17:01:50.345437Z" }, "papermill": { "duration": 0.023511, "end_time": "2021-07-13T06:22:17.630576", "exception": false, "start_time": "2021-07-13T06:22:17.607065", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "3c178def", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:47.917056Z", "iopub.status.busy": "2021-07-10T03:45:47.916253Z", "iopub.status.idle": "2021-07-10T03:45:47.921802Z", "shell.execute_reply": "2021-07-10T03:45:47.922322Z", "shell.execute_reply.started": "2021-07-09T17:01:52.359791Z" }, "papermill": { "duration": 0.023369, "end_time": "2021-07-13T06:22:17.678137", "exception": false, "start_time": "2021-07-13T06:22:17.654768", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "65e97f9d", "metadata": { "papermill": { "duration": 0.026019, "end_time": "2021-07-13T06:22:17.729176", "exception": false, "start_time": "2021-07-13T06:22:17.703157", "status": "completed" }, "tags": [] }, "source": [ "**Exercise 26: Select rows from `data` where `category` is `Fruit` and assign it to `data_fruit` and select rows from `data_fruit` where `product` is `Banana` and `quantity` is more than 1 and assign it to `data_multi_banana`**" ] }, { "cell_type": "code", "execution_count": null, "id": "7e99c7c3", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:48.033945Z", "iopub.status.busy": "2021-07-10T03:45:48.033214Z", "iopub.status.idle": "2021-07-10T03:45:48.041388Z", "shell.execute_reply": "2021-07-10T03:45:48.041888Z", "shell.execute_reply.started": "2021-07-09T17:03:50.613283Z" }, "papermill": { "duration": 0.024718, "end_time": "2021-07-13T06:22:17.779480", "exception": false, "start_time": "2021-07-13T06:22:17.754762", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "d4fc0d98", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:48.114482Z", "iopub.status.busy": "2021-07-10T03:45:48.113591Z", "iopub.status.idle": "2021-07-10T03:45:48.119539Z", "shell.execute_reply": "2021-07-10T03:45:48.120095Z", "shell.execute_reply.started": "2021-07-09T17:04:01.360049Z" }, "papermill": { "duration": 0.02281, "end_time": "2021-07-13T06:22:17.826157", "exception": false, "start_time": "2021-07-13T06:22:17.803347", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "2215f1ef", "metadata": { "papermill": { "duration": 0.02294, "end_time": "2021-07-13T06:22:17.872156", "exception": false, "start_time": "2021-07-13T06:22:17.849216", "status": "completed" }, "tags": [] }, "source": [ "**Exercise 27: Select columns from `data` that have no missing values and assign it to `data_nomissing_cols`**" ] }, { "cell_type": "code", "execution_count": null, "id": "9f7dfb28", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:48.248095Z", "iopub.status.busy": "2021-07-10T03:45:48.247204Z", "iopub.status.idle": "2021-07-10T03:45:48.252606Z", "shell.execute_reply": "2021-07-10T03:45:48.252004Z", "shell.execute_reply.started": "2021-07-09T17:04:53.636677Z" }, "papermill": { "duration": 0.022833, "end_time": "2021-07-13T06:22:17.918291", "exception": false, "start_time": "2021-07-13T06:22:17.895458", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "1578f433", "metadata": { "papermill": { "duration": 0.022816, "end_time": "2021-07-13T06:22:17.964547", "exception": false, "start_time": "2021-07-13T06:22:17.941731", "status": "completed" }, "tags": [] }, "source": [ "**Exercise 28: Select rows from `data` that have no missing values and assign it to `data_nomissing_rows`**" ] }, { "cell_type": "code", "execution_count": null, "id": "18945f43", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:48.373275Z", "iopub.status.busy": "2021-07-10T03:45:48.372562Z", "iopub.status.idle": "2021-07-10T03:45:48.381275Z", "shell.execute_reply": "2021-07-10T03:45:48.381812Z", "shell.execute_reply.started": "2021-07-09T17:05:04.266965Z" }, "papermill": { "duration": 0.023203, "end_time": "2021-07-13T06:22:18.010860", "exception": false, "start_time": "2021-07-13T06:22:17.987657", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "f9dcb5f8", "metadata": { "papermill": { "duration": 0.023177, "end_time": "2021-07-13T06:22:18.057433", "exception": false, "start_time": "2021-07-13T06:22:18.034256", "status": "completed" }, "tags": [] }, "source": [ "**Exercise 29: Select unique rows from `data` and assign it to `data_unique` and select unique `product` from `data_unique` and assign it to `product_unique`**" ] }, { "cell_type": "code", "execution_count": null, "id": "7bfb89f5", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:48.514123Z", "iopub.status.busy": "2021-07-10T03:45:48.513328Z", "iopub.status.idle": "2021-07-10T03:45:48.519147Z", "shell.execute_reply": "2021-07-10T03:45:48.519727Z", "shell.execute_reply.started": "2021-07-09T17:05:33.261595Z" }, "papermill": { "duration": 0.023427, "end_time": "2021-07-13T06:22:18.104261", "exception": false, "start_time": "2021-07-13T06:22:18.080834", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "e798ad2a", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:48.596327Z", "iopub.status.busy": "2021-07-10T03:45:48.59545Z", "iopub.status.idle": "2021-07-10T03:45:48.599235Z", "shell.execute_reply": "2021-07-10T03:45:48.596954Z", "shell.execute_reply.started": "2021-07-09T17:08:13.440725Z" }, "papermill": { "duration": 0.023788, "end_time": "2021-07-13T06:22:18.152138", "exception": false, "start_time": "2021-07-13T06:22:18.128350", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "598599ae", "metadata": { "papermill": { "duration": 0.023629, "end_time": "2021-07-13T06:22:18.199638", "exception": false, "start_time": "2021-07-13T06:22:18.176009", "status": "completed" }, "tags": [] }, "source": [ "**Exercise 30: Select first row of each user from `data` and assign it to `data_first`**" ] }, { "cell_type": "code", "execution_count": null, "id": "10f07cb6", "metadata": { "execution": { "iopub.execute_input": "2021-07-10T03:45:48.735644Z", "iopub.status.busy": "2021-07-10T03:45:48.734838Z", "iopub.status.idle": "2021-07-10T03:45:48.739981Z", "shell.execute_reply": "2021-07-10T03:45:48.740507Z", "shell.execute_reply.started": "2021-07-09T17:08:29.889451Z" }, "papermill": { "duration": 0.024686, "end_time": "2021-07-13T06:22:18.249236", "exception": false, "start_time": "2021-07-13T06:22:18.224550", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "630f3740", "metadata": { "papermill": { "duration": 0.024623, "end_time": "2021-07-13T06:22:18.297833", "exception": false, "start_time": "2021-07-13T06:22:18.273210", "status": "completed" }, "tags": [] }, "source": [ "βœ… This completes Set 3: Data Selection (Exercises 21-30) of **DatatableTon**: *πŸ’― datatable exercises*\n", "\n", "#### Set 04 β€’ Frame Operations β€’ Beginner β€’ Exercises 31-40\n", "\n", "| Style | Colab | Kaggle | Binder | GitHub |\n", "| ----- | ----- | ------ | ------ | ------ |\n", "| Exercises | [![Open in Colab](https://img.shields.io/static/v1?label=&message=Open%20in%20Colab&labelColor=grey&color=blue&logo=google-colab)](https://colab.research.google.com/github/vopani/datatableton/blob/main/notebooks/04_frame_operations_exercises.ipynb) | [![Open in Kaggle](https://img.shields.io/static/v1?label=&message=Open%20in%20Kaggle&labelColor=grey&color=blue&logo=kaggle)](https://www.kaggle.com/rohanrao/datatableton-frame-operations-exercises) | [![Open in Binder](https://img.shields.io/static/v1?label=&message=Open%20in%20Binder&labelColor=grey&color=blue&logo=data:image/png;base64,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)](https://mybinder.org/v2/gh/vopani/datatableton/main?filepath=notebooks%2F04_frame_operations_exercises.ipynb) | [![Open in GitHub](https://img.shields.io/static/v1?label=&message=Open%20in%20GitHub&labelColor=grey&color=blue&logo=github)](https://github.com/vopani/datatableton/blob/main/notebooks/04_frame_operations_exercises.ipynb) |\n", "| Solutions | [![Open in Colab](https://img.shields.io/static/v1?label=&message=Open%20in%20Colab&labelColor=grey&color=blue&logo=google-colab)](https://colab.research.google.com/github/vopani/datatableton/blob/main/notebooks/04_frame_operations_solutions.ipynb) | [![Open in Kaggle](https://img.shields.io/static/v1?label=&message=Open%20in%20Kaggle&labelColor=grey&color=blue&logo=kaggle)](https://www.kaggle.com/rohanrao/datatableton-frame-operations-solutions) | [![Open in Binder](https://img.shields.io/static/v1?label=&message=Open%20in%20Binder&labelColor=grey&color=blue&logo=data:image/png;base64,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)](https://mybinder.org/v2/gh/vopani/datatableton/main?filepath=notebooks%2F04_frame_operations_solutions.ipynb) | [![Open in GitHub](https://img.shields.io/static/v1?label=&message=Open%20in%20GitHub&labelColor=grey&color=blue&logo=github)](https://github.com/vopani/datatableton/blob/main/notebooks/04_frame_operations_solutions.ipynb) |\n", "\n", "You can find all the exercises and solutions on [GitHub](https://github.com/vopani/datatableton#exercises-)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.7.10" }, "papermill": { "default_parameters": {}, "duration": 37.378194, "end_time": "2021-07-13T06:22:18.842712", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2021-07-13T06:21:41.464518", "version": "2.3.3" } }, 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