basic parsing working

04_Results_Aggregation.py

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+import marimo
+
+__generated_with = "0.18.3"
+app = marimo.App(width="medium")
+
+
+@app.cell
+def _():
+    import marimo as mo
+    import pandas as pd
+    from pathlib import Path
+
+    INPUT_DIR = Path("./data/processing/03_sentiment_analysis")
+    WORKING_DIR = Path('./data/processing/04_sentiment_aggregation')
+
+    if not WORKING_DIR.exists():
+        WORKING_DIR.mkdir(parents=True)
+    return INPUT_DIR, mo, pd
+
+
+@app.cell(hide_code=True)
+def _(mo):
+    mo.md(r"""
+    # Voices
+    """)
+    return
+
+
+@app.cell
+def _(INPUT_DIR, mo):
+    voice_csv_files = list(INPUT_DIR.glob("*voice*.csv"))
+    file_options = {f.stem: str(f) for f in voice_csv_files}
+
+    voice_multiselect = mo.ui.multiselect(options=file_options, label="Select Voice CSV Files for Aggregation")
+    voice_multiselect
+    return (voice_multiselect,)
+
+
+@app.cell
+def _(mo, voice_multiselect):
+    mo.hstack([voice_multiselect, mo.md(f"Has value: {voice_multiselect.value}")])
+    return
+
+
+@app.cell
+def _(pd, voice_multiselect):
+    # Load all voice CSV files and aggregate them so that each row-column pair is summed
+    KEY_COL = "_context"
+
+    def _read_voice_csv(path: str) -> pd.DataFrame:
+        df = pd.read_csv(path).set_index(KEY_COL)
+        df = df.apply(pd.to_numeric, errors="coerce")
+        return df
+
+    def aggregate_voice_data(files: list[str]) -> pd.DataFrame:
+        if not files:
+            return pd.DataFrame()
+
+        master = _read_voice_csv(files[0])
+        for path in files[1:]:
+            master = master.add(_read_voice_csv(path), fill_value=0)
+
+        return master.reset_index()
+
+    master_df = aggregate_voice_data(voice_multiselect.value)
+    master_df
+    return
+
+
+@app.cell(hide_code=True)
+def _(mo):
+    mo.md(r"""
+    # Characters
+    """)
+    return
+
+
+@app.cell
+def _(INPUT_DIR):
+    char_csv_files = list(INPUT_DIR.glob("*character*.csv"))
+    char_csv_files
+    return
+
+
+if __name__ == "__main__":
+    app.run()