Python Data Science Handbook, 2nd Edition von Jake VanderPlas

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CLUSTER-LENSING: A PYTHON PACKAGE FOR GALAXY CLUSTERS AND MISCENTERING von Ford, Jes, VanderPlas, Jake

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SNANA: A Public Software Package for Supernova Analysis von Kessler, Richard, Bernstein, Joseph P., Cinabro, David, Dilday, Benjamin, Frieman, Joshua A., Jha, Saurabh, Kuhlmann, Stephen, Miknaitis, Gajus, Sako, Masao, Taylor, Matt, Vanderplas, Jake

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Python Data Science Handbook von Jake VanderPlas

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Python数据科学手册 von Jake VanderPlas

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A Whirlwind Tour of Python von Jake VanderPlas

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Python Data Science Handbook, 2. Auflage von Jake VanderPlas

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Python Data Science von Jake VanderPlas

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What Is Python? von Matthew Harrison, Jake VanderPlas

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Tests of modified gravity with dwarf galaxies von Jain, Bhuvnesh, VanderPlas, Jake

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Python Data Science Handbook: Essential Tools for Working with Data von VanderPlas, Jake

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A fast template periodogram von Hoffman, John, VanderPlas, Jake, Hartman, Joel, Bakos, Gáspár

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Python data science handbook: essential tools for working with data von VanderPlas, Jake

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Scikit-learn: Machine Learning in Python von Pedregosa, Fabian, Varoquaux, Gaël, Gramfort, Alexandre, Michel, Vincent, Thirion, Bertrand, Grisel, Olivier, Blondel, Mathieu, Prettenhofer, Peter, Weiss, Ron, Dubourg, Vincent, Vanderplas, Jake, Passos, Alexandre, Cournapeau, David, Brucher, Matthieu, Perrot, Matthieu, Duchesnay, Edouard

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Pythonデータサイエンスハンドブック ―Jupyter、NumPy、pandas、Matplotlib、scikit-learnを使ったデータ分析、機械学習 von Jake VanderPlas, 菊池 彰

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Data Science mit Python: Das Handbuch für den Einsatz von IPython, Jupyter, NumPy, Pandas, Matplotlib und Scikit-Learn von VanderPlas, Jake

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mst_clustering: Clustering via Euclidean Minimum Spanning Trees von VanderPlas, Jake

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Reducing the Dimensionality of Data: Locally Linear Embedding of Sloan Galaxy Spectra von Vanderplas, Jake, Connolly, Andrew

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First-Year Sloan Digital Sky Survey-II Supernova Results: Hubble Diagram and Cosmological Parameters von Kessler, Richard, Becker, Andrew C, Cinabro, David, Vanderplas, Jake, Frieman, Joshua A, Marriner, John, Davis, Tamara M, Dilday, Benjamin, Holtzman, Jon, Jha, Saurabh W, Lampeitl, Hubert, Sako, Masao, Smith, Mathew, Zheng, Chen, Nichol, Robert C, Bassett, Bruce, Bender, Ralf, Depoy, Darren L, Doi, Mamoru, Elson, Ed, Filippenko, Alexei V, Foley, Ryan J, Garnavich, Peter M, Hopp, Ulrich, Ihara, Yutaka, Ketzeback, William, Kollatschny, W, Konishi, Kohki, Marshall, Jennifer L, McMillan, Russet J, Miknaitis, Gajus, Morokuma, Tomoki, Mörtsell, Edvard, Pan, Kaike, Prieto, Jose Luis, Richmond, Michael W, Riess, Adam G, Romani, Roger, Schneider, Donald P, Sollerman, Jesper, Takanashi, Naohiro, Tokita, Kouichi, van der Heyden, Kurt, Wheeler, J. C, Yasuda, Naoki, York, Donald

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approxposterior: Approximate Posterior Distributions in Python von P. Fleming, David, VanderPlas, Jake

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