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        "description": "K-means++ in Pandas\n===================\n\nAn implementation of the [k-means++ clustering algorithm](http://en.wikipedia.org/wiki/K-means%2B%2B) using [Pandas](http://pandas.pydata.org/).\n\nIMPORTANT NOTE\n--------------\n\n**This package should not be used in production.** The implementation of k-means++ contained therein is much slower than [that of scikit-learn](http://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html). Use that instead.\n\nThe only reason why I wrote any of this is to teach myself Pandas.\n\nPrerequisites\n-------------\n\n* Python 2.7 or lower; this is not Python 3 compatible (yet).\n* [Pandas](http://pandas.pydata.org/) (obviously).\n* [NumPy](http://numpy.org)\n\nInstallation\n------------\n\nIf you have [pip](http://www.pip-installer.org/en/latest/installing.html), then just do\n\n\tpip install k-means-plus-plus\n\nOtherwise,\n\n* Clone the repository:\n\n\t\tgit clone https://github.com/jackmaney/k-means-plus-plus-pandas.git\n\n* Enter the newly-created folder containing the repo\n\n\t\tcd k-means-plus-plus-pandas\n\n* And run the installation manually:\n\n\t\tpython setup.py install\n\n\n\nUsage\n-----\n\nHere are the constructor arguments:\n\n* `data_frame`: A Pandas data frame representing the data that you wish to cluster. Rows represent observations, and columns represent variables.\n\n* `k`: The number of clusters that you want.\n\n* `columns=None`: A list of column names upon which you wish to cluster your data. If this argument isn't provided, then all of the columns are selected. **Note:** Columns upon which you want to cluster must be numeric and have no `numpy.nan` values.\n\n* `max_iterations=None`: The maximum number of times that you wish to iterate k-means. If no value is provided, then the iterations continue until stability is reached (ie the cluster assignments don't change between one iteration and the next).\n\n* `appended_column_name=None`: If this value is set with a string, then a column will be appended to your data with the given name that contains the cluster assignments (which are integers from 0 to `k-1`). If this argument is not set, then you still have access to the clusters via the `clusters` attribute.\n\nOnce you've constructed a `KMeansPlusPlus` object, then just call the `cluster` method, and everything else should happen automagically. Take a look at the `examples` folder.\n\nTODO:\n----\n\n* Add on features that take iterations of k-means++ clusters and compares them via, eg, concordance matrices, Jaccard indices, etc.\n\n* Given a data frame, implement the so-called [Elbow Method](http://en.wikipedia.org/wiki/Determining_the_number_of_clusters_in_a_data_set#The_Elbow_Method) to take a stab at an optimal value for `k`.\n\n* ~~Make this into a proper Python module that can be installed via pip.~~\n\n* Python 3 compatibility (probably via six).",
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