<jupyter_start><jupyter_text>for i in range (1,301):    dir_path = "{}{}{}".format('weather_data',i,'.csv')    a = pd.read_csv(dir_path, sep = ",", encoding = "utf-8")    a = a.tail(1)    a.to_csv(dir_path, sep = ",", encoding = "utf-8")<jupyter_code># merging the files
joined_files = os.path.join("weather*.csv")
  
# A list of all joined files is returned
joined_list = glob.glob(joined_files)
  
# Finally, the files are joined
df = pd.concat(map(pd.read_csv, joined_list), ignore_index=True)
#print(df.shape())
df.shape
df.to_csv("test_submission2.csv", sep = ',', encoding = "utf-8")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1841680129240711, 'fraction_numerical': 0.014539579967689823, 'mean_word_length': 5.138613861386139, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '29481', 'license': 'BSD-3-Clause', 'n_tokens_mistral': 246, 'n_tokens_neox': 240, 'n_words': 48, 'path': 'Compile_predictions.ipynb', 'repo_name': 'sandeepkogge/ShellAIHackathon_DG', 'size': '619'}