combine_sector_results
Function
combine_sector_results(result_dict:dict = None, write_path:str = None, significance_stars: bool = False, round_results: int = None, latex_syntax: bool = True)
Description
Extract key result fields (coefficients, standard errors, and p-values) and combine them in a DataFrame. Has the option to write the data to a .csv file with or without extra value formatting options.
Arguments
- result_dict: Dict[statsmodels.genmod.generalized_linear_model.GLMResultsWrapper]
A dictionary of GLM fit objects as returned by gme.EsimationModel.estimate()
- write_path: (optional) str
A system location and file name in which to write a csv file containing the combined results.
- significance_stars: bool
If true, combined results are output with significance stars. \*\*\*<0.01, \*\*<0.05, and \*<0.10. Default is False.
- round_results: (optional) int
Rounds combined results to the desired decimal place.
- latex_syntax: bool
If True, reports aspects of results, such as significance stars, using standard latex syntax.
Returns
Returns: Pandas.DataFrame A DataFrame containing combined GLM results for all results in the supplied dictionary.
Examples
# Using a gme.EstimationModel named 'sample_model'.
>>> sample_results = sample_model.estimate()
# Return a dataframe of results
>>> result_df = combine_sector_results(sample_results)
>>> result_df.head(5)
all_coeff all_pvalue all_stderr
log_distance -0.739840 9.318804e-211 0.023879
agree_pta 0.334219 5.134355e-15 0.042719
common_language 0.128770 1.076932e-03 0.039383
contiguity 0.255161 5.857612e-08 0.047050
importer_year_fe_ARG2013 26.980367 0.000000e+00 0.361228
# Export table as a .csv file
>>> combine_sector_results(sample_results,
... round_results = 3,
... path = 'c:\\Documents\\combined_results_saved.csv')