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import pandas as pd |
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import requests |
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from io import BytesIO |
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import numpy as np |
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def analyze_excel(path_or_url: str) -> str: |
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"""Analysera Excel-fil och returnera detaljerad information""" |
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try: |
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if path_or_url.startswith("http"): |
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response = requests.get(path_or_url, timeout=10) |
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response.raise_for_status() |
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df = pd.read_excel(BytesIO(response.content)) |
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else: |
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df = pd.read_excel(path_or_url) |
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except Exception as e: |
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return f"Error reading Excel file: {e}" |
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analysis = [] |
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analysis.append(f"Rows: {df.shape[0]}, Columns: {df.shape[1]}") |
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analysis.append(f"Column names: {', '.join(df.columns)}") |
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numeric_cols = df.select_dtypes(include=[np.number]).columns.tolist() |
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if numeric_cols: |
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analysis.append(f"Numeric columns: {', '.join(numeric_cols)}") |
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for col in numeric_cols: |
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analysis.append(f"{col} - Sum: {df[col].sum():.2f}, Mean: {df[col].mean():.2f}, Max: {df[col].max():.2f}, Min: {df[col].min():.2f}") |
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text_cols = df.select_dtypes(include=['object']).columns.tolist() |
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if text_cols: |
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analysis.append(f"Text columns: {', '.join(text_cols)}") |
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for col in text_cols: |
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unique_values = df[col].nunique() |
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analysis.append(f"{col} - Unique values: {unique_values}") |
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if unique_values <= 10: |
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analysis.append(f"{col} values: {', '.join(map(str, df[col].unique()))}") |
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analysis.append("First 3 rows:") |
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analysis.append(df.head(3).to_string()) |
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return "\n".join(analysis) |