50 lines
1.5 KiB
Python
50 lines
1.5 KiB
Python
from typing import Any, Dict
|
|
import pandas as pd
|
|
|
|
|
|
class PandasVerticalSplit:
|
|
"""
|
|
Vertically splits a Pandas DataFrame into two pandas DataFrames.
|
|
|
|
category: Transformation
|
|
"""
|
|
|
|
@classmethod
|
|
def INPUT_TYPES(cls) -> Dict[str, Any]:
|
|
"""
|
|
Defines the input types for the function.
|
|
|
|
Returns:
|
|
Dict[str, Any]: A dictionary specifying required input types.
|
|
"""
|
|
return {
|
|
"required": {
|
|
"dataframe": ("DATAFRAME", {}),
|
|
"row_integer_position": ("INT", {"default": 0, "min": -1, "max": 2**31})
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES: tuple = ("DATAFRAME", "DATAFRAME")
|
|
RETURN_NAMES: tuple = ("Top DataFrame", "Bottom DataFrame")
|
|
|
|
FUNCTION: str = "f"
|
|
CATEGORY: str = "Data Analysis"
|
|
|
|
def f(self, dataframe: pd.DataFrame, row_integer_position: int) -> tuple:
|
|
"""
|
|
Vertically splits a Pandas DataFrame into two pandas DataFrames.
|
|
|
|
Args:
|
|
dataframe (pd.DataFrame): The DataFrame to split.
|
|
row_integer_position (int): The row integer position where the split occurs.
|
|
The top DataFrame contains rows [0, row_integer_position-1],
|
|
and the bottom DataFrame contains rows [row_integer_position, end].
|
|
|
|
Returns:
|
|
tuple: A tuple containing the top and bottom DataFrames.
|
|
"""
|
|
df_top = dataframe.iloc[:row_integer_position]
|
|
df_bottom = dataframe.iloc[row_integer_position:]
|
|
|
|
return (df_top, df_bottom)
|