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| import gradio as gr | |
| import pandas as pd | |
| import statsmodels.formula.api as smf | |
| from linearmodels.iv import IV2SLS | |
| import warnings | |
| warnings.simplefilter(action='ignore', category=FutureWarning) | |
| def process_file(file): | |
| global df | |
| df = pd.read_csv(file.name) | |
| return df.columns.tolist() | |
| def run_2sls(dependent_var, endogenous_vars, instruments, exogenous_vars): | |
| if not all([dependent_var, endogenous_vars, instruments]): | |
| return "Error: Please select all required variables." | |
| endogenous_vars = endogenous_vars.split(",") | |
| instruments = instruments.split(",") | |
| exogenous_vars = exogenous_vars.split(",") if exogenous_vars else [] | |
| if len(instruments) < len(endogenous_vars): | |
| return "Error: The number of instruments must be at least equal to the number of endogenous variables." | |
| try: | |
| df_selected = df[[dependent_var] + endogenous_vars + instruments + exogenous_vars].dropna() | |
| # First stage | |
| predicted_vars = [] | |
| for var in endogenous_vars: | |
| first_stage_formula = f'{var} ~ ' + ' + '.join(instruments + exogenous_vars) | |
| first_stage = smf.ols(first_stage_formula, data=df_selected).fit() | |
| df_selected[f'{var}_hat'] = first_stage.fittedvalues | |
| predicted_vars.append(f'{var}_hat') | |
| # Second stage | |
| second_stage_formula = f'{dependent_var} ~ ' + ' + '.join(predicted_vars + exogenous_vars) | |
| second_stage = smf.ols(second_stage_formula, data=df_selected).fit() | |
| return second_stage.summary().as_text() | |
| except Exception as e: | |
| return f"Error: {str(e)}" | |
| with gr.Blocks() as app: | |
| gr.Markdown("## Two-Stage Least Squares Regression (2SLS)") | |
| file_input = gr.File(label="Upload CSV File") | |
| column_output = gr.Label(label="Available Columns") | |
| file_input.change(process_file, inputs=file_input, outputs=column_output) | |
| dependent_var = gr.Dropdown(label="Dependent Variable") | |
| endogenous_vars = gr.Textbox(label="Endogenous Variables (comma-separated)") | |
| instruments = gr.Textbox(label="Instruments (comma-separated)") | |
| exogenous_vars = gr.Textbox(label="Exogenous Variables (comma-separated, optional)") | |
| run_button = gr.Button("Run 2SLS Regression") | |
| output = gr.Textbox(label="Regression Output", lines=20) | |
| run_button.click(run_2sls, inputs=[dependent_var, endogenous_vars, instruments, exogenous_vars], outputs=output) | |
| app.launch() | |