44 lines
1.1 KiB
Python
44 lines
1.1 KiB
Python
from typing import Any, Dict
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import pandas as pd
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import numpy as np
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class PandasLog:
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"""
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Applying the natural logarithm function to a pandas DataFrame and converting non-numeric values to NaN.
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category: Math
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"""
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@classmethod
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def INPUT_TYPES(cls) -> Dict[str, Any]:
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"""
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Defines the input types for the function.
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Returns:
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Dict[str, Any]: A dictionary specifying required input types.
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"""
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return {
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"required": {
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"dataframe": ("DATAFRAME", {})
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}
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}
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RETURN_TYPES: tuple = ("DATAFRAME",)
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FUNCTION: str = "f"
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CATEGORY: str = "Data Analysis"
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def f(self, dataframe: pd.DataFrame) -> tuple:
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"""
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Converts non-numeric values to NaN and applies the natural logarithm function to the DataFrame.
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Args:
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dataframe (DataFrame): The DataFrame.
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Returns:
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tuple: A tuple containing the processed DataFrame.
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"""
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dataframe = dataframe.apply(pd.to_numeric, errors='coerce')
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dataframe = np.log(dataframe)
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return (dataframe,)
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