# Read the CSV (with the first row as data)
df = spark.read.format("csv").option("header", "false").load("/path/to/csvfile")

# Extract the first row as the header
new_header = df.first()

# Create a new DataFrame without the first row
df_without_first_row = df.filter(df["_c0"] != new_header["_c0"])

# Rename columns to match the values from the first row (header)
new_column_names = [new_header[col] for col in df.columns]
df_with_new_header = df_without_first_row.toDF(*new_column_names)

df_with_new_header.show()