Interval Filtering not working for EventTime column of type 'datetime'

[Timm638]

Describe the bug

The filter()-method of Interval Filtering doesn't filtering, if the EventTime-column is of the type datetime.
filter() fails at the last line, where the internal pandas dataframe is converted into a PySpark dataframe.

To Reproduce

1. Download example data
   Example data:
   Actual Generation per Production Type_2024-2025.csv

2. execute following code

from rtdip_sdk.pipelines.data_wranglers import NormalizationMean, NormalizationZScore, NormalizationMinMax, Denormalization, DuplicateDetection
from rtdip_sdk.pipelines.data_wranglers import KSigmaAnomalyDetection, IntervalFiltering
import pandas as pd
import matplotlib.pyplot as plt
from pyspark.sql import SparkSession

spark_session = SparkSession.builder.master("local[2]").appName("test").getOrCreate()

source_df = pd.read_csv('./Actual Generation per Production Type_2024-2025.csv')
df = source_df
df['MTU-Start'] = pd.to_datetime(df['MTU'].apply(lambda x: x.split('-')[0]), dayfirst=True)
df['Solar  - Actual Aggregated [MW]'] = pd.to_numeric(df['Solar  - Actual Aggregated [MW]'], errors='coerce')
df = df.set_index('MTU-Start')

april_2_week = pd.to_datetime('07.04.2024', dayfirst=True)
april_mid = pd.to_datetime('14.04.2024', dayfirst=True)

april_df = df[april_2_week:april_mid]
intf_april_df = april_df.copy(deep=True)
intf_april_df = intf_april_df['Solar  - Actual Aggregated [MW]'].to_frame()
intf_april_df['EventTime'] = pd.to_datetime(april_df.index)
# comment out to make it work
# intf_april_df['EventTime'] = pd.Series(intf_april_df['EventTime'], dtype="string")


intf_ps_df = spark_session.createDataFrame(intf_april_df, ['Solar  - Actual Aggregated [MW]', 'EventTime'])
output_intf_df = IntervalFiltering(spark_session, df=intf_ps_df, interval=6, interval_unit='hours', time_stamp_column_name='EventTime').filter().toPandas()

3. Receive the error message

Expected behavior

Receiving an output from the component

Installation Setup (please complete the following information):

• Pyspark Version: 3.5.3
• Python Version: 3.11.8

Additional context

Add any other context about the problem here.