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        "author": "JuanCorp",
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            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering :: Artificial Intelligence"
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        "description": "# pysimilarity\n\nPysimilarity is a library that contains several methods for determining similarities between groups. Currently, it supports calculating similarities using distances, and a classifier.\n\n## Install\n\n```\npip install pysimilarity\n```\n\n## Usage\n\n```\nfrom sklearn.datasets import load_iris\nfrom pysimilarity import DistanceSimilarity\nimport pandas as pd\n\niris_dataset = load_iris()\niris_df = pd.DataFrame(iris_dataset['data'],columns=iris_dataset['feature_names']\n                      )\niris_df['species'] = pd.Series(iris_dataset['target']).replace({0:'setosa', 1:'versicolor', 2:'virginica'})\n\n\ndist_similarity = DistanceSimilarity()\nsetosa_data = iris_df.loc[iris_df.species == 'setosa']\nsetosa_similarity = dist_similarity.fit_transform(setosa_data.drop('species',axis=1)\n                                                  ,iris_df.drop('species',axis=1))\nprint(setosa_similarity) # Array of shape n_rows of iris_df.\n```",
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        "keywords": "similarity data machine learning",
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        "name": "pysimilarity",
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        "summary": "Determine similarity between datasets",
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