Data Science, Pyspark, Data Analytics, Machine Learning, Artificial Intelligence.
daily_return_percentages: price_series.append(price_series[-1] * j) return price_series trials_rdd = spark.sparkContext.parallelize(range(number_of_trials)) price_series_rdd = trials_rdd.map(simulate_trial) price_series_list = price_series_rdd.collect() for series in price_series_list: