SparkSession.createDataFrame, requires an RDD of Row/tuple/list, unless schema with DataType is provided. I would suggest you convert float to tuple like this:
from pyspark.sql import Row
row = Row("val") # Or some other column name
myFloatRdd.map(row).toDF()
To create a DataFrame from a list of scalars, you'll have to use SparkSession.createDataFrame directly and provide a schema:
from pyspark.sql.types import FloatType
df = spark.createDataFrame([1.0, 2.0, 3.0], FloatType())
df.show()
## +-----+
## |value|
## +-----+
## | 1.0|
## | 2.0|
## | 3.0|
## +-----+
If you want to know more about Spark, then do check out this awesome video tutorial: