from pyspark.sql.functions import col, concat_ws, to_date

# Drop rows with missing values
df = org_df.na.drop()

# Convert columns "Date" and "Time" into new column "DateTime"
df = df.withColumn("Date", to_date(col("Date"),"d/M/y"))
df = df.withColumn("Date", df["Date"].cast("date"))
df = df.select(concat_ws(" ", to_date(col("Date"),"d/M/y"), col("Time")).alias("DateTime"), "*")
df = df.withColumn("DateTime", df["DateTime"].cast("timestamp"))

# Add time-related features
df = df.withColumn("year", year("DateTime"))
df = df.withColumn("month", month("DateTime"))
df = df.withColumn("week_num", weekofyear("DateTime"))
df = df.withColumn("hour", hour("DateTime"))