2020-06-29 01:08:07 +02:00
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[build-system]
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build-backend = "poetry.masonry.api"
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requires = ["poetry>=0.12"]
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2018-09-02 23:25:41 +02:00
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[tool.black]
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line-length = 79
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2020-06-29 01:08:07 +02:00
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[tool.poetry]
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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"
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homepage = "https://github.com/webartifex/ames-housing"
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keywords = [
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"data-science",
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"data-cleaning",
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"house-price-prediction",
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"machine-learning",
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"prediction",
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"predictive-analytics",
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]
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license = "MIT"
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name = "ames-housing"
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readme = "README.md"
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repository = "https://github.com/webartifex/ames-housing"
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version = "0.1.0"
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[tool.poetry.dependencies]
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jupyterlab = "^2.1.5"
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matplotlib = "^3.2.2"
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missingno = "^0.4.2"
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numpy = "^1.19.0"
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pandas = "^1.0.5"
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python = "^3.7"
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requests = "^2.24.0"
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seaborn = "^0.10.1"
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sklearn = "^0.0"
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statsmodels = "^0.11.1"
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tabulate = "^0.8.7"
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tqdm = "^4.47.0"
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xlrd = "^1.2.0"
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xlwt = "^1.3.0"
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[tool.poetry.dev-dependencies]
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black = "^19.10b0"
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pylint = "^2.5.3"
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