<commit_before>"""Tweet Analysis"""


# using PySpark on EC2 Spark cluster, SparkContext and SQLContext are loaded
from pyspark.sql import SQLContext
from pyspark.sql.functions import col
from pyspark import SparkContext

sqlContext = SQLContext(sc)
<commit_msg>Commit<commit_after>"""Tweet Analysis"""

# using PySpark on EC2 Spark cluster, SparkContext and SQLContext are loaded
from pyspark.sql import SQLContext
from pyspark.sql.functions import col
from pyspark import SparkContext

sqlContext = SQLContext(sc)

# reading the json-format tweet file for further analysis
tweet_load = sqlContext.read.json("tweets/cleaned_2012_01_0.json")

{'fraction_non_alphanumeric': 0.07009345794392523, 'fraction_numerical': 0.014018691588785047, 'mean_word_length': 6.306818181818182, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '3052472', 'n_tokens_mistral': 200, 'n_tokens_neox': 188, 'n_words': 64}