49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
from typing import Any, Dict
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from io import StringIO
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import pandas as pd
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class PandasJoin:
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"""
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Merges two pandas DataFrames based on a common column.
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category: Transformation
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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 `join` 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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"left_dataframe": ("DATAFRAME", {}),
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"right_dataframe": ("DATAFRAME", {}),
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"on_column_name": ("STRING", {"default": ""}),
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"join_method":(("inner", "left", "right", "outer"),)
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}
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}
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RETURN_TYPES: tuple = ("DATAFRAME",)
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FUNCTION: str = "join_dataframes"
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CATEGORY: str = "Data Analysis"
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def join_dataframes(self, left_dataframe: pd.DataFrame, right_dataframe: pd.DataFrame, on_column_name: str, join_method: str) -> tuple:
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"""
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Merges two pandas DataFrames based on a common column using the specified join method.
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Args:
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left_dataframe (DataFrame): The left DataFrame.
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right_dataframe (DataFrame): The right DataFrame.
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on_column_name (str): The name of the column to join on.
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join_method (str): The type of join to perform ("inner", "left", "right", "outer").
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Returns:
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tuple: A tuple containing a JSON string of the merged DataFrame.
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"""
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df_out = pd.merge(left_dataframe, right_dataframe, on=on_column_name, how=join_method)
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return (df_out,)
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