packages/vaex-core/vaex/dataframe.py
def to_pandas_df(self, column_names=None, selection=None, strings=True, virtual=False, index_name=None):
        """Return a pandas DataFrame containing the ndarray corresponding to the evaluated data

         If index is given, that column is used for the index of the dataframe.

         Example

         >>> df_pandas = df.to_pandas_df(["x", "y", "z"])
         >>> df_copy = vaex.from_pandas(df_pandas)

        :param column_names: list of column names, to export, when None DataFrame.get_column_names(strings=strings, virtual=virtual) is used
        :param selection: {selection}
        :param strings: argument passed to DataFrame.get_column_names when column_names is None
        :param virtual: argument passed to DataFrame.get_column_names when column_names is None
        :param index_column: if this column is given it is used for the index of the DataFrame
        :return: pandas.DataFrame object
        """
        import pandas as pd
        data = self.to_dict(column_names=column_names, selection=selection, strings=strings, virtual=virtual)
        if index_name is not None:
            if index_name in data:
                index = data.pop(index_name)
            else:
                index = self.evaluate(index_name, selection=selection)
        else:
            index = None
        df = pd.DataFrame(data=data, index=index)
        if index is not None:
            df.index.name = index_name
        return df
def to_pandas_df(self, column_names=None, selection=None, strings=True, virtual=False, index_name=None):
        import pandas as pd
        data = self.to_dict(column_names=column_names, selection=selection, strings=strings, virtual=virtual)
        if index_name is not None:
            if index_name in data:
                index = data.pop(index_name)
            else:
                index = self.evaluate(index_name, selection=selection)
        else:
            index = None
        df = pd.DataFrame(data=data, index=index)
        if index is not None:
            df.index.name = index_name
        return df
def to_pandas_df ( self , column_names = None , selection = None , strings = True , virtual = False , index_name = None ) : import pandas as pd data = self . to_dict ( column_names = column_names , selection = selection , strings = strings , virtual = virtual ) if index_name is not None : if index_name in data : index = data . pop ( index_name ) else : index = self . evaluate ( index_name , selection = selection ) else : index = None df = pd . DataFrame ( data = data , index = index ) if index is not None : df . index . name = index_name return df
Return a pandas DataFrame containing the ndarray corresponding to the evaluated data

         If index is given, that column is used for the index of the dataframe.

         Example

         >>> df_pandas = df.to_pandas_df(["x", "y", "z"])
         >>> df_copy = vaex.from_pandas(df_pandas)

        :param column_names: list of column names, to export, when None DataFrame.get_column_names(strings=strings, virtual=virtual) is used
        :param selection: {selection}
        :param strings: argument passed to DataFrame.get_column_names when column_names is None
        :param virtual: argument passed to DataFrame.get_column_names when column_names is None
        :param index_column: if this column is given it is used for the index of the DataFrame
        :return: pandas.DataFrame object
Return a pandas DataFrame containing the ndarray corresponding to the evaluated data