def __init__(self, data, **kwargs): """Initialize an instance of an IamDataFrame Parameters ---------- data: ixmp.TimeSeries, ixmp.Scenario, pd.DataFrame or data file an instance of an TimeSeries or Scenario (requires `ixmp`), or pd.DataFrame or data file with IAMC-format data columns. Special support is provided for data files downloaded directly from IIASA SSP and RCP databases. If you run into any problems loading data, please make an issue at: https://github.com/IAMconsortium/pyam/issues """ # import data from pd.DataFrame or read from source if isinstance(data, pd.DataFrame): self.data = format_data(data.copy()) elif has_ix and isinstance(data, ixmp.TimeSeries): self.data = read_ix(data, **kwargs) else: self.data = read_files(data, **kwargs) # define a dataframe for categorization and other metadata indicators self.meta = self.data[META_IDX].drop_duplicates().set_index(META_IDX) self.reset_exclude() # execute user-defined code if 'exec' in run_control(): self._execute_run_control()
def __init__(self, data, **kwargs): """Initialize an instance of an IamDataFrame Parameters ---------- data: ixmp.TimeSeries, ixmp.Scenario, pd.DataFrame or data file an instance of an TimeSeries or Scenario (requires `ixmp`), or pd.DataFrame or data file with IAMC-format data columns """ # import data from pd.DataFrame or read from source if isinstance(data, pd.DataFrame): self.data = format_data(data.copy()) elif has_ix and isinstance(data, ixmp.TimeSeries): self.data = read_ix(data, **kwargs) else: self.data = read_files(data, **kwargs) # define a dataframe for categorization and other metadata indicators self.meta = self.data[META_IDX].drop_duplicates().set_index(META_IDX) self.reset_exclude() # execute user-defined code if 'exec' in run_control(): self._execute_run_control()