<jupyter_start><jupyter_text>This is wordsthese are also words<jupyter_code>print type(arr.keys()[0])
print arr.keys()[2]
#create array key first that maps the indexes of grades.csv rows to rows of folders from os.walk(topdown=True)
for dirpath, dirnames, filenames in os.walk('.'):
    dirname = dirpath.split(os.path.sep)[-1]
    print dirname
for item in os.listdir('.'):
    print item
currDir = '.'
dirs = [ name for name in os.listdir(currDir) if os.path.isdir(os.path.join(currDir, name)) ]
print dirs
print os.walk('.').next()[1]
print arr
print arr.shape[0]
#Key for directories to studentID
arr2 = np.empty((2, arr.shape[0]), dtype=str)
print arr2
arr = pd.read_csv('gradebook_submit10.csv', quotechar='"', skipinitialspace=True)
print arr
print arr.shape[0]
arr2 = np.empty((2, arr.shape[0]), dtype=object)
print arr2
print arr.xs(arr.keys()[0],axis=1)
#StudentIDs
print arr.as_matrix().T[0]<jupyter_output>['<EMAIL>' '<EMAIL>' '<EMAIL>' '<EMAIL>']
{'fraction_non_alphanumeric': 0.1678832116788321, 'fraction_numerical': 0.01981230448383733, 'mean_word_length': 5.530612244897959, 'pattern_counts': {'":': 0, '<': 8, '<?xml version=': 0, '>': 8, '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': '330240', 'license': 'BSD-3-Clause', 'n_tokens_mistral': 362, 'n_tokens_neox': 356, 'n_words': 93, 'path': 'testcode/PHY161autoGrader/gradeCheckerTest.ipynb', 'repo_name': 'mtesseracted/TestBed', 'size': '987'}