pyspark error returned when checking if a df column contains values in broadcast.value.values() - pyspark

Question

i have below code
import pyspark
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName('SparkByExamples.com').getOrCreate()
states = {"NY":"New York", "CA":"California", "FL":"Florida"}
broadcastStates = spark.sparkContext.broadcast(states)
data = [("James","Smith","USA","CA"),
("Michael","Rose","USA","NY"),
("Robert","Williams","USA","CA"),
("Maria","Jones","USA","FL")
]
columns = ["firstname","lastname","country","state"]
df = spark.createDataFrame(data = data, schema = columns)
df.printSchema()
df.show(truncate=False)
def state_convert(code):
return broadcastStates.value[code]
result = df.rdd.map(lambda x: (x[0],x[1],x[2],state_convert(x[3]))).toDF(columns)
result.show(truncate=False)
dfFilter = result.where(result.state.isin(broadcastStates.value.values())
dfFilter.display()
When I run above code in notebook, I failed at below line
dfFilter = result.where(result.state.isin(broadcastStates.value.values())
The error is
Unsupported literal type class java.util.HashMap {FL=Florida, NY=New York, CA=California}
Then I check the type of broadcastStates.value.values by
print(type(broadcastStates.value.values()))
the type of returned value is <class 'dict_values'>
How should I covert the dict_values to a list that can passed to isin() function.