a3a38e85d2
AI-powered tool that generates publication-quality SVG charts matching PIMCO's InDesign style. Upload Excel/CSV data, write a plain-English brief, then iterate with natural language edits until the chart is exactly right. - Claude Opus 4.6 interprets briefs into structured ChartSpec JSON - Deterministic SVG renderer via drawsvg (no visual hallucinations) - Roboto/Roboto Condensed fonts base64-embedded in SVG - FastAPI + HTMX web frontend with live preview - Conversational refinement: "make lines thicker", "change title", etc. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
"""Excel/CSV data loading and parsing."""
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from __future__ import annotations
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from pathlib import Path
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import pandas as pd
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def load_file(filepath: str | Path) -> dict[str, pd.DataFrame]:
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"""Load an Excel or CSV file into a dict of DataFrames.
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Returns:
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Dict mapping sheet names (or "_default" for CSV) to DataFrames.
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"""
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filepath = Path(filepath)
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if filepath.suffix.lower() in (".xlsx", ".xls"):
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return _load_excel(filepath)
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elif filepath.suffix.lower() == ".csv":
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df = pd.read_csv(filepath)
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return {"_default": df}
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else:
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raise ValueError(f"Unsupported file type: {filepath.suffix}")
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def _load_excel(filepath: Path) -> dict[str, pd.DataFrame]:
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"""Load all sheets from an Excel file."""
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xls = pd.ExcelFile(filepath)
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result = {}
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for sheet_name in xls.sheet_names:
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try:
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df = pd.read_excel(xls, sheet_name=sheet_name)
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# Skip empty or tiny sheets
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if df.empty or (df.shape[0] < 2 and df.shape[1] < 2):
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continue
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# Clean up: drop fully empty rows/columns
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df = df.dropna(how="all").dropna(axis=1, how="all")
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if not df.empty:
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result[sheet_name] = df
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except Exception:
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continue
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return result
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