ames-housing/pyproject.toml

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[build-system]
requires = ["poetry-core"]
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build-backend = "poetry.core.masonry.api"
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[tool.poetry]
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name = "ames-housing"
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version = "0.2.0.dev0"
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authors = [
"Alexander Hess <alexander@webartifex.biz>",
]
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description = "A case study on predicting house prices in Ames, Iowa"
keywords = [
"data-science",
"data-cleaning",
"house-price-prediction",
"machine-learning",
"prediction",
"predictive-analytics",
]
license = "MIT"
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readme = "README.md"
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homepage = "https://github.com/webartifex/ames-housing"
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repository = "https://github.com/webartifex/ames-housing"
package-mode = false
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[tool.poetry.dependencies]
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python = "^3.9"
jupyterlab = "^4.2"
matplotlib = "^3.9"
missingno = "^0.5"
numpy = "^2.0"
pandas = "^2.2"
requests = "^2.32"
scikit-learn = "^1.5"
seaborn = "^0.13"
statsmodels = "^0.14"
tabulate = "^0.9"
tqdm = "^4.66"
xlrd = "^2.0"
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[tool.poetry.group.dev.dependencies]
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black = {extras = ["jupyter"], version = "^24.4"}
pylint = "^3.2"