Tax-Calculator Data

Tax-Calculator Data#

Tax-Calculator Data

taxcalc.data#

class taxcalc.data.Data(data, start_year, gfactors=None, weights=None, weights_scale=0.01)[source]#

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.

Parameters:

  • 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.

  • weights_scale (float) – specifies the weights scaling factor used to convert contents of weights file into the s006 variable. PUF and CPS input data generated in the taxdata repository use a weights_scale of 0.01, while TMD input data generated in the tax-microdata repository use a 1.0 weights_scale value.

Raises:

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.

Returns:

class instance

Return type:

Data

_extrapolate(year)[source]#

Apply to data variables the growth factor values for specified year.

_read_data(data)[source]#

Read data from file or use specified DataFrame as data.

_read_var_info()[source]#

Read Data variables metadata from JSON file and specifies static variable name sets listed above.

_read_weights(weights)[source]#

Read sample weights from file or use specified DataFrame as weights or create empty DataFrame if None.

increment_year()[source]#

Add one to current year; and also does extrapolation & reweighting for new current year if aged_data is True.

zero_out_changing_calculated_vars()[source]#

Set to zero all variables in the self.CHANGING_CALCULATED_VARS set.