1. Advisor
  2. modin
  3. functions
  4. modin.data_management.functions.MapReduceFunction.register
View all modin analysis

How to use the modin.data_management.functions.MapReduceFunction.register function in modin

To help you get started, we’ve selected a few modin examples, based on popular ways it is used in public projects.

Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately.

github modin-project / modin / modin / backends / pandas / query_compiler.py View on Github external
def transpose(self, *args, **kwargs):
        """Transposes this QueryCompiler.

        Returns:
            Transposed new QueryCompiler.
        """
        # Switch the index and columns and transpose the data within the blocks.
        return self.__constructor__(self._modin_frame.transpose())

    # END Transpose

    # MapReduce operations

    count = MapReduceFunction.register(pandas.DataFrame.count, pandas.DataFrame.sum)
    max = MapReduceFunction.register(pandas.DataFrame.max, pandas.DataFrame.max)
    min = MapReduceFunction.register(pandas.DataFrame.min, pandas.DataFrame.min)
    sum = MapReduceFunction.register(pandas.DataFrame.sum, pandas.DataFrame.sum)
    prod = MapReduceFunction.register(pandas.DataFrame.prod, pandas.DataFrame.prod)
    any = MapReduceFunction.register(pandas.DataFrame.any, pandas.DataFrame.any)
    all = MapReduceFunction.register(pandas.DataFrame.all, pandas.DataFrame.all)
    memory_usage = MapReduceFunction.register(
        pandas.DataFrame.memory_usage,
        lambda x, *args, **kwargs: pandas.DataFrame.sum(x),
        axis=0,
    )

    # END MapReduce operations

    # Reduction operations
    idxmax = ReductionFunction.register(pandas.DataFrame.idxmax)
    idxmin = ReductionFunction.register(pandas.DataFrame.idxmin)
github modin-project / modin / modin / backends / pandas / query_compiler.py View on Github external
# for simplicity of implementation.

    def transpose(self, *args, **kwargs):
        """Transposes this QueryCompiler.

        Returns:
            Transposed new QueryCompiler.
        """
        # Switch the index and columns and transpose the data within the blocks.
        return self.__constructor__(self._modin_frame.transpose())

    # END Transpose

    # MapReduce operations

    count = MapReduceFunction.register(pandas.DataFrame.count, pandas.DataFrame.sum)
    max = MapReduceFunction.register(pandas.DataFrame.max, pandas.DataFrame.max)
    min = MapReduceFunction.register(pandas.DataFrame.min, pandas.DataFrame.min)
    sum = MapReduceFunction.register(pandas.DataFrame.sum, pandas.DataFrame.sum)
    prod = MapReduceFunction.register(pandas.DataFrame.prod, pandas.DataFrame.prod)
    any = MapReduceFunction.register(pandas.DataFrame.any, pandas.DataFrame.any)
    all = MapReduceFunction.register(pandas.DataFrame.all, pandas.DataFrame.all)
    memory_usage = MapReduceFunction.register(
        pandas.DataFrame.memory_usage,
        lambda x, *args, **kwargs: pandas.DataFrame.sum(x),
        axis=0,
    )

    # END MapReduce operations

    # Reduction operations
    idxmax = ReductionFunction.register(pandas.DataFrame.idxmax)
github modin-project / modin / modin / backends / pandas / query_compiler.py View on Github external
def transpose(self, *args, **kwargs):
        """Transposes this QueryCompiler.

        Returns:
            Transposed new QueryCompiler.
        """
        # Switch the index and columns and transpose the data within the blocks.
        return self.__constructor__(self._modin_frame.transpose())

    # END Transpose

    # MapReduce operations

    count = MapReduceFunction.register(pandas.DataFrame.count, pandas.DataFrame.sum)
    max = MapReduceFunction.register(pandas.DataFrame.max, pandas.DataFrame.max)
    min = MapReduceFunction.register(pandas.DataFrame.min, pandas.DataFrame.min)
    sum = MapReduceFunction.register(pandas.DataFrame.sum, pandas.DataFrame.sum)
    prod = MapReduceFunction.register(pandas.DataFrame.prod, pandas.DataFrame.prod)
    any = MapReduceFunction.register(pandas.DataFrame.any, pandas.DataFrame.any)
    all = MapReduceFunction.register(pandas.DataFrame.all, pandas.DataFrame.all)
    memory_usage = MapReduceFunction.register(
        pandas.DataFrame.memory_usage,
        lambda x, *args, **kwargs: pandas.DataFrame.sum(x),
        axis=0,
    )

    # END MapReduce operations

    # Reduction operations
    idxmax = ReductionFunction.register(pandas.DataFrame.idxmax)
    idxmin = ReductionFunction.register(pandas.DataFrame.idxmin)
    median = ReductionFunction.register(pandas.DataFrame.median)
github modin-project / modin / modin / backends / pandas / query_compiler.py View on Github external
Transposed new QueryCompiler.
        """
        # Switch the index and columns and transpose the data within the blocks.
        return self.__constructor__(self._modin_frame.transpose())

    # END Transpose

    # MapReduce operations

    count = MapReduceFunction.register(pandas.DataFrame.count, pandas.DataFrame.sum)
    max = MapReduceFunction.register(pandas.DataFrame.max, pandas.DataFrame.max)
    min = MapReduceFunction.register(pandas.DataFrame.min, pandas.DataFrame.min)
    sum = MapReduceFunction.register(pandas.DataFrame.sum, pandas.DataFrame.sum)
    prod = MapReduceFunction.register(pandas.DataFrame.prod, pandas.DataFrame.prod)
    any = MapReduceFunction.register(pandas.DataFrame.any, pandas.DataFrame.any)
    all = MapReduceFunction.register(pandas.DataFrame.all, pandas.DataFrame.all)
    memory_usage = MapReduceFunction.register(
        pandas.DataFrame.memory_usage,
        lambda x, *args, **kwargs: pandas.DataFrame.sum(x),
        axis=0,
    )

    # END MapReduce operations

    # Reduction operations
    idxmax = ReductionFunction.register(pandas.DataFrame.idxmax)
    idxmin = ReductionFunction.register(pandas.DataFrame.idxmin)
    median = ReductionFunction.register(pandas.DataFrame.median)
    nunique = ReductionFunction.register(pandas.DataFrame.nunique)
    skew = ReductionFunction.register(pandas.DataFrame.skew)
    std = ReductionFunction.register(pandas.DataFrame.std)
    var = ReductionFunction.register(pandas.DataFrame.var)
github modin-project / modin / modin / backends / pandas / query_compiler.py View on Github external
Returns:
            Transposed new QueryCompiler.
        """
        # Switch the index and columns and transpose the data within the blocks.
        return self.__constructor__(self._modin_frame.transpose())

    # END Transpose

    # MapReduce operations

    count = MapReduceFunction.register(pandas.DataFrame.count, pandas.DataFrame.sum)
    max = MapReduceFunction.register(pandas.DataFrame.max, pandas.DataFrame.max)
    min = MapReduceFunction.register(pandas.DataFrame.min, pandas.DataFrame.min)
    sum = MapReduceFunction.register(pandas.DataFrame.sum, pandas.DataFrame.sum)
    prod = MapReduceFunction.register(pandas.DataFrame.prod, pandas.DataFrame.prod)
    any = MapReduceFunction.register(pandas.DataFrame.any, pandas.DataFrame.any)
    all = MapReduceFunction.register(pandas.DataFrame.all, pandas.DataFrame.all)
    memory_usage = MapReduceFunction.register(
        pandas.DataFrame.memory_usage,
        lambda x, *args, **kwargs: pandas.DataFrame.sum(x),
        axis=0,
    )

    # END MapReduce operations

    # Reduction operations
    idxmax = ReductionFunction.register(pandas.DataFrame.idxmax)
    idxmin = ReductionFunction.register(pandas.DataFrame.idxmin)
    median = ReductionFunction.register(pandas.DataFrame.median)
    nunique = ReductionFunction.register(pandas.DataFrame.nunique)
    skew = ReductionFunction.register(pandas.DataFrame.skew)
    std = ReductionFunction.register(pandas.DataFrame.std)
github modin-project / modin / modin / backends / pandas / query_compiler.py View on Github external
"""Transposes this QueryCompiler.

        Returns:
            Transposed new QueryCompiler.
        """
        # Switch the index and columns and transpose the data within the blocks.
        return self.__constructor__(self._modin_frame.transpose())

    # END Transpose

    # MapReduce operations

    count = MapReduceFunction.register(pandas.DataFrame.count, pandas.DataFrame.sum)
    max = MapReduceFunction.register(pandas.DataFrame.max, pandas.DataFrame.max)
    min = MapReduceFunction.register(pandas.DataFrame.min, pandas.DataFrame.min)
    sum = MapReduceFunction.register(pandas.DataFrame.sum, pandas.DataFrame.sum)
    prod = MapReduceFunction.register(pandas.DataFrame.prod, pandas.DataFrame.prod)
    any = MapReduceFunction.register(pandas.DataFrame.any, pandas.DataFrame.any)
    all = MapReduceFunction.register(pandas.DataFrame.all, pandas.DataFrame.all)
    memory_usage = MapReduceFunction.register(
        pandas.DataFrame.memory_usage,
        lambda x, *args, **kwargs: pandas.DataFrame.sum(x),
        axis=0,
    )

    # END MapReduce operations

    # Reduction operations
    idxmax = ReductionFunction.register(pandas.DataFrame.idxmax)
    idxmin = ReductionFunction.register(pandas.DataFrame.idxmin)
    median = ReductionFunction.register(pandas.DataFrame.median)
    nunique = ReductionFunction.register(pandas.DataFrame.nunique)
github modin-project / modin / modin / backends / pandas / query_compiler.py View on Github external
Returns:
            Transposed new QueryCompiler.
        """
        # Switch the index and columns and transpose the data within the blocks.
        return self.__constructor__(self._modin_frame.transpose())

    # END Transpose

    # MapReduce operations

    count = MapReduceFunction.register(pandas.DataFrame.count, pandas.DataFrame.sum)
    max = MapReduceFunction.register(pandas.DataFrame.max, pandas.DataFrame.max)
    min = MapReduceFunction.register(pandas.DataFrame.min, pandas.DataFrame.min)
    sum = MapReduceFunction.register(pandas.DataFrame.sum, pandas.DataFrame.sum)
    prod = MapReduceFunction.register(pandas.DataFrame.prod, pandas.DataFrame.prod)
    any = MapReduceFunction.register(pandas.DataFrame.any, pandas.DataFrame.any)
    all = MapReduceFunction.register(pandas.DataFrame.all, pandas.DataFrame.all)
    memory_usage = MapReduceFunction.register(
        pandas.DataFrame.memory_usage,
        lambda x, *args, **kwargs: pandas.DataFrame.sum(x),
        axis=0,
    )

    # END MapReduce operations

    # Reduction operations
    idxmax = ReductionFunction.register(pandas.DataFrame.idxmax)
    idxmin = ReductionFunction.register(pandas.DataFrame.idxmin)
    median = ReductionFunction.register(pandas.DataFrame.median)
    nunique = ReductionFunction.register(pandas.DataFrame.nunique)
    skew = ReductionFunction.register(pandas.DataFrame.skew)
github modin-project / modin / modin / backends / pandas / query_compiler.py View on Github external
"""
        # Switch the index and columns and transpose the data within the blocks.
        return self.__constructor__(self._modin_frame.transpose())

    # END Transpose

    # MapReduce operations

    count = MapReduceFunction.register(pandas.DataFrame.count, pandas.DataFrame.sum)
    max = MapReduceFunction.register(pandas.DataFrame.max, pandas.DataFrame.max)
    min = MapReduceFunction.register(pandas.DataFrame.min, pandas.DataFrame.min)
    sum = MapReduceFunction.register(pandas.DataFrame.sum, pandas.DataFrame.sum)
    prod = MapReduceFunction.register(pandas.DataFrame.prod, pandas.DataFrame.prod)
    any = MapReduceFunction.register(pandas.DataFrame.any, pandas.DataFrame.any)
    all = MapReduceFunction.register(pandas.DataFrame.all, pandas.DataFrame.all)
    memory_usage = MapReduceFunction.register(
        pandas.DataFrame.memory_usage,
        lambda x, *args, **kwargs: pandas.DataFrame.sum(x),
        axis=0,
    )

    # END MapReduce operations

    # Reduction operations
    idxmax = ReductionFunction.register(pandas.DataFrame.idxmax)
    idxmin = ReductionFunction.register(pandas.DataFrame.idxmin)
    median = ReductionFunction.register(pandas.DataFrame.median)
    nunique = ReductionFunction.register(pandas.DataFrame.nunique)
    skew = ReductionFunction.register(pandas.DataFrame.skew)
    std = ReductionFunction.register(pandas.DataFrame.std)
    var = ReductionFunction.register(pandas.DataFrame.var)
    sum_min_count = ReductionFunction.register(pandas.DataFrame.sum)

modin

Modin: Make your pandas code run faster by changing one line of code.

GitHub
Apache-2.0
Latest version published 2 months ago

Package Health Score

94 / 100
Full package analysis

Popular modin functions

Similar packages