<jupyter_start><jupyter_text>GraphDDP<jupyter_code>target_fname = 'data/myeloid/partition_my.csv'
data_fname = 'data/myeloid/fdata_my.csv'
target_fname = 'data/intestine/partition_ADULT.csv'
data_fname = 'data/intestine/fdata_ADULT.csv'
from graph_embed import pre_process
res = pre_process(data_fname,
                  target_fname,
                  correlation_transformation=True,
                  normalization=True,
                  feature_selection=True,
                  min_threshold=5)
data_matrix, target, target_dict = res
from display import interactive_widget
w = interactive_widget(data_matrix, target_dict, target)
from IPython.display import display
display(w)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.0800561797752809, 'fraction_numerical': 0.0014044943820224719, 'mean_word_length': 3.8835616438356166, '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': '209892', 'license': 'MIT', 'n_tokens_mistral': 233, 'n_tokens_neox': 224, 'n_words': 36, 'path': 'interactive_graph_layout.ipynb', 'repo_name': 'smautner/GraphEmbed', 'size': '712'}