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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "markdown", | ||
"id": "76784523-1230-4c92-8cac-753cc0f8613e", | ||
"metadata": {}, | ||
"source": [ | ||
"# D-Tale: A Seamless Data Exploration Tool for Python\n", | ||
"\n", | ||
"D-Tale, born out of a SAS to Python conversion, transforms the data exploration process into a breeze. Originally a Perl script wrapper for SAS's insight function, it has evolved into a lightweight web client seamlessly integrated with Pandas data structures.\n", | ||
"\n", | ||
"Built on a Flask back-end and a React front-end, D-Tale offers a straightforward method to view and analyze Pandas data structures. Its seamless integration with Jupyter notebooks and Python/IPython terminals makes it a versatile tool. Currently, it supports various Pandas objects, including DataFrame, Series, MultiIndex, DatetimeIndex, and RangeIndex.\n", | ||
"\n", | ||
"D-Tale is a solution that simplifies data exploration. Acting as a lightweight web client over Pandas data structures, D-Tale offers an intuitive user interface for performing various data exploration tasks without the need to write any code.\n", | ||
"\n", | ||
"\n", | ||
"![](dtale.png)\n", | ||
"\n", | ||
"![](dtale-menu.png)\n", | ||
"\n", | ||
"![](dtale-2.png)\n", | ||
"\n", | ||
"## Installation:" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"id": "c1a92ee3-40b7-4a8c-b51b-4e007efe6593", | ||
"metadata": { | ||
"tags": [] | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"%%capture\n", | ||
"! pip install -r requirements.txt\n", | ||
"! pip install -U dtale" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "7b7fffba-5e2e-4381-973b-6da1a9dc1bb2", | ||
"metadata": {}, | ||
"source": [ | ||
"## Usage:" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"id": "31bec97e-6100-43ba-b41e-68fb3f837116", | ||
"metadata": { | ||
"tags": [] | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"import dtale\n", | ||
"import pandas as pd\n", | ||
"from ydata_profiling.utils.cache import cache_file\n", | ||
"\n", | ||
"# Fetching Pokemon dataset\n", | ||
"file_name = cache_file(\n", | ||
" \"pokemon.csv\",\n", | ||
" \"https://raw.githubusercontent.com/bryanpaget/html/main/pokemon.csv\"\n", | ||
")\n", | ||
"\n", | ||
"# Reading dataset using Pandas\n", | ||
"pokemon_df = pd.read_csv(file_name)\n", | ||
"\n", | ||
"# Displaying dataset with D-Tale\n", | ||
"dtale.show(pokemon_df)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "863aff9f-8be9-4231-ade4-21377856b1a0", | ||
"metadata": {}, | ||
"source": [ | ||
"D-Tale comes to the rescue by providing a user-friendly interface for essential data exploration tasks, eliminating the need for repetitive code and saving valuable time in the process.\n" | ||
] | ||
} | ||
], | ||
"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": "3.10.12" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 5 | ||
} |
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