esoreader.py
def to_frame(self, search, key=None, frequency='TimeStep', index=None, use_key_for_columns=True):
        """
        creates a pandas DataFrame objects with a column for every variable
        that matches the search pattern and key. An None key matches all keys.
        NOTE: The frequency *has* to be the same for all variables selected.
        (uses find_variable to select the variables)
        """
        from pandas import DataFrame
        variables = self.find_variable(search, key=key, frequency=frequency)
        if use_key_for_columns:
            data = {v[1]: self.data[self.dd.index[v]] for v in variables}
        else:
            # use variable name as column name
            data = {v[2]: self.data[self.dd.index[v]] for v in variables}
        df = DataFrame(data)
        if index is not None:
            df.index = index
        return df

        creates a pandas DataFrame objects with a column for every variable
        that matches the search pattern and key. An None key matches all keys.
        NOTE: The frequency *has* to be the same for all variables selected.
        (uses find_variable to select the variables)
        
creates a pandas DataFrame objects with a column for every variable
that matches the search pattern and key. An None key matches all keys.
NOTE: The frequency *has* to be the same for all variables selected.
(uses find_variable to select the variables)
creates a pandas DataFrame objects with a column for every variable that matches the search pattern and key . An None key matches all keys . NOTE : The frequency * has * to be the same for all variables selected . ( uses find_variable to select the variables )
def to_frame(self, search, key=None, frequency='TimeStep', index=None, use_key_for_columns=True):
        from pandas import DataFrame
        variables = self.find_variable(search, key=key, frequency=frequency)
        if use_key_for_columns:
            data = {v[1]: self.data[self.dd.index[v]] for v in variables}
        else:
            data = {v[2]: self.data[self.dd.index[v]] for v in variables}
        df = DataFrame(data)
        if index is not None:
            df.index = index
        return df
def to_frame ( self , search , key = None , frequency = 'TimeStep' , index = None , use_key_for_columns = True ) : from pandas import DataFrame variables = self . find_variable ( search , key = key , frequency = frequency ) if use_key_for_columns : data = { v [ 1 ] : self . data [ self . dd . index [ v ] ] for v in variables } else : data = { v [ 2 ] : self . data [ self . dd . index [ v ] ] for v in variables } df = DataFrame ( data ) if index is not None : df . index = index return df
creates a pandas DataFrame objects with a column for every variable
that matches the search pattern and key.
creates a pandas DataFrame objects with a column for every variable that matches the search pattern and key .
"""
        creates a pandas DataFrame objects with a column for every variable
        that matches the search pattern and key. An None key matches all keys.
        NOTE: The frequency *has* to be the same for all variables selected.
        (uses find_variable to select the variables)
        """ # use variable name as column name

self
search
key
frequency
index
use_key_for_columns