62 lines
2.1 KiB
Python
62 lines
2.1 KiB
Python
from typing import Any, Dict
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import pandas as pd
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import ast
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class PandasReplaceAdvanced:
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"""
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Replaces strings in a DataFrame cell using a mapping specified in a dictionary.
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For example, if you want to replace "cat" with "dog" and replace "mountain" with "ocean", specify the mapping in Python dict format:
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```
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{"cat":"dog", "mountain":"ocean"}
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```
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category: Data cleansing
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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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"replacement_dict": ("STRING", {"default": "{}", "multiline":True})
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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, replacement_dict: str) -> tuple:
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"""
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Replaces part or all of a string in each DataFrame cell with a specified string using a wildcard for matching.
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Args:
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dataframe (DataFrame): The target DataFrame.
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replacement_dict (str): A dict containing the mapping.
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Returns:
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tuple: A tuple containing the DataFrame.
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"""
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d = ast.literal_eval(replacement_dict)
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if isinstance(d, dict) is False:
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raise ValueError('You need to specify the mapping in Python dict format such as {"cat":"dog", "mountain":"ocean"}')
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# check values
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for k, v in d.items():
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if (isinstance(k, str) is False and
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isinstance(k, float) is False and
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isinstance(k, int) is False):
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raise ValueError("You need to specify a string or a number for source values.")
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if (isinstance(v, str) is False and
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isinstance(v, float) is False and
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isinstance(v, int) is False):
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raise ValueError("You need to specify a string or a number for target values.")
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df2 = dataframe.replace(to_replace=d)
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return (df2,)
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