# Path: gbdt/_libgbdt.py



from ._libgbdt import libgbdt
            import pandas
            import numpy
            import pandas

        return pandas.DataFrame(dict([(k, list(v)) for k, v in self.items()]))

    def __repr__(self):
        return self._data_store.__repr__()

class DataLoader:
    @staticmethod
    def from_tsvs(tsvs, bucketized_float_cols=[], string_cols=[], raw_float_cols=[]):
        """Loads data from tsvs.
           Inputs:
             tsvs: Blocks of tsvs, among which only the first contains header.
             bucketized_float_cols: Float columns that will be bucketized. All features will be bucketized.
             string_cols: String cols.
             raw_float_cols: Float columns that are loaded raw. Target columns are usually not bucketized.
        """
        d = libgbdt.DataStore()
        d.load_tsv(tsvs,
                   bucketized_float_cols=bucketized_float_cols,
                   string_cols=string_cols,
                   raw_float_cols=raw_float_cols)
        return DataStore(d)

    @staticmethod
    def from_dict(bucketized_float_cols={}, string_cols={}, raw_float_cols={}):
        """Loads data from dict of columns.
             bucketized_float_cols: Float columns that will be bucketized. All features will be bucketized.
             string_cols: String cols.
             raw_float_cols: Float columns that are loaded raw. Target columns are usually not bucketized.
        """

# Path: gbdt/_libgbdt.py



# Path: gbdt/_data_store.py
from ._libgbdt import libgbdt
            import pandas
            import numpy
            import pandas


        return pandas.DataFrame(dict([(k, list(v)) for k, v in self.items()]))

    def __repr__(self):
        return self._data_store.__repr__()

class DataLoader:
    @staticmethod
    def from_tsvs(tsvs, bucketized_float_cols=[], string_cols=[], raw_float_cols=[]):
        """Loads data from tsvs.
           Inputs:
             tsvs: Blocks of tsvs, among which only the first contains header.
             bucketized_float_cols: Float columns that will be bucketized. All features will be bucketized.
             string_cols: String cols.
             raw_float_cols: Float columns that are loaded raw. Target columns are usually not bucketized.
        """
        d = libgbdt.DataStore()
        d.load_tsv(tsvs,
                   bucketized_float_cols=bucketized_float_cols,
                   string_cols=string_cols,
                   raw_float_cols=raw_float_cols)
        return DataStore(d)

    @staticmethod
    def from_dict(bucketized_float_cols={}, string_cols={}, raw_float_cols={}):
        """Loads data from dict of columns.
             bucketized_float_cols: Float columns that will be bucketized. All features will be bucketized.
             string_cols: String cols.
             raw_float_cols: Float columns that are loaded raw. Target columns are usually not bucketized.
        """

        d = libgbdt.DataStore()