Data(data, start_year, gfactors=None, weights=None)¶
Inherit from this class for Records and other collections of cross-sectional data that need to have growth factors and sample weights to age the data to years after the start_year.
data (string or Pandas DataFrame) –
string describes CSV file in which data reside; DataFrame already contains cross-sectional data for start_year. NOTE: data=None is allowed but the returned instance contains only
the data variable information in the specified VARINFO file.
NOTE: when using custom data, set this argument to a DataFrame.
start_year (integer) – specifies calendar year of the input data.
gfactors (None or GrowFactors class instance) – None implies empty growth factors DataFrame; instance contains data growth factors.
weights (None or string or Pandas DataFrame) – None creates empty sample weights DataFrame. string describes CSV file in which sample weights reside; DataFrame already contains sample weights. NOTE: when using custom weights, set this argument to a DataFrame. NOTE: assumes weights are integers that are 100 times the real weights.
ValueError: – if data is not a string or a DataFrame instance. if start_year is not an integer. if gfactors is not None or a GrowFactors class instance if weights is not None or a string or a DataFrame instance. if gfactors and weights are not consistent. if files cannot be found.
- Return type
Apply to dats variables the growth factor values for specified year.
Read data from file or use specified DataFrame as data.
Read Data variables metadata from JSON file and specifies static variable name sets listed above.
Read sample weights from file or use specified DataFrame as weights or create empty DataFrame if None. NOTE: assumes weights are integers equal to 100 times the real weight.
Add one to current year; and also does extrapolation & reweighting for new current year if aged_data is True.
Set to zero all variables in the self.CHANGING_CALCULATED_VARS set.