Load test data in PySpark.py

# Databricks notebook source
# DBTITLE 1,List of States (single dimensional)
states:list = [
    'Colorado',
    'New York',
    'Georgia',
    'Tennessee',
    'Utah'
] 

# COMMAND ----------

from pyspark.sql.types import StringType

states_df = spark.createDataFrame(states, schema=StringType()).toDF('State_Name')

states_df.printSchema()
display(states_df)

# COMMAND ----------

# DBTITLE 1,Data as Key-Value pair
states_JSONs:list = [
    {'CA': 'Colorado'},
    {'NY': 'New York'},
    {'GA': 'Georgia'},
    {'TN': 'Tennessee'},
    {'UT': 'Utah'}
] 

# COMMAND ----------

from pyspark.sql.types import StructType, StructField, MapType

# abbreviation_type = StructType(
#     [
#         StructField("Code", StringType(), False)
#     ]
# )
# state_name_type = StructType(
#     [
#         StructField("State_Name", StringType(), False)
#     ]
# )
# states_dict_schema = MapType(keyType=abbreviation_type, valueType=state_name_type, valueContainsNull=False)
states_dict_schema = MapType(keyType=StringType(), valueType=StringType(), valueContainsNull=False)

states_json_df = spark.createDataFrame(data=states_JSONs, schema=states_dict_schema)

states_json_df.printSchema()
display(states_json_df)

# COMMAND ----------

# DBTITLE 1,States info JSON
states_key_values:list = [
    {'Code': 'CA', 'State_Name': 'Colorado', 'Airport': 'DEN'},
    {'Code': 'NY', 'State_Name': 'New York', 'Airport': 'JFK'},
    {'Code': 'GA', 'State_Name': 'Georgia', 'Airport': 'ALT'},
    {'Code': 'TN', 'State_Name': 'Tennessee', 'Airport': 'BNA'},
    {'Code': 'UT', 'State_Name': 'Utah', 'Airport': 'SLC'}
] 

# COMMAND ----------

states_and_abbreviations_df = spark.createDataFrame(data=states_key_values)

states_and_abbreviations_df.printSchema()
display(states_and_abbreviations_df)

# COMMAND ----------

# DBTITLE 1,List of States and their Capitals (Map type yet with explicit schema)
state_and_capital_list:list = [
    ['Colorado', 'Denver'],
    ['New York', 'Albany'],
    ['Georgia', 'Atlanta'],
    ['Tennessee', 'Nashville'],
    ['Utah', 'Salt Lake City']
] 

# COMMAND ----------

from pyspark.sql.types import StringType, StructType, StructField

simple_tuple_schema = StructType (
    [
        StructField("State", StringType(), nullable=False),
        StructField("Capital", StringType(), nullable=False)
    ]
)

state_and_capital_df = spark.createDataFrame(state_and_capital_list, schema=simple_tuple_schema)

state_and_capital_df.printSchema()
display(state_and_capital_df)