44 lines
1.1 KiB
Python
44 lines
1.1 KiB
Python
from typing import Any, Dict
|
|
from io import StringIO
|
|
import pandas as pd
|
|
|
|
|
|
class PandasAsInt:
|
|
"""
|
|
Converts all cells in a pandas DataFrame to integer type.
|
|
|
|
category: Data type conversion
|
|
"""
|
|
|
|
@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", {})
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES: tuple = ("DATAFRAME",)
|
|
FUNCTION: str = "f"
|
|
CATEGORY: str = "Data Analysis"
|
|
|
|
def f(self, dataframe: pd.DataFrame) -> tuple:
|
|
"""
|
|
Converts all cells in the DataFrame to integer type.
|
|
|
|
Args:
|
|
dataframe (DataFrame): The DataFrame.
|
|
|
|
Returns:
|
|
tuple: A tuple containing the DataFrame with all values as integers.
|
|
"""
|
|
# Convert all values to integer, non-numeric values become NaN
|
|
df = dataframe.apply(pd.to_numeric, errors='coerce').astype('Int64')
|
|
return (df,)
|