<jupyter_start><jupyter_text>*New Steps Begin Here*<jupyter_code>!ls *.txt
!head edge_distance.txt
tx = g.begin()
with open('edge_distance.txt') as f_in:
    for line in f_in:
        edge_list = line.rstrip().split(',')
        city1_name = edge_list[0]
        city2_name = edge_list[1]
        city1_node = result_set.where(name=city1_name)
        city2_node = result_set.where(name=city2_name)
        city_pair = Relationship(city1_node, "FLIGHT_BETWEEN", city2_node)
        city_pair["distance"] = edge_list[2]
        tx.create(city_pair)
tx.commit()
g.relationship_types
import pandas as pd
flight_list = list()
for cities in g.match(rel_type="FLIGHT_BETWEEN"):
    city1_name = cities.nodes()[0]['name']
    city2_name = cities.nodes()[1]['name']
    distance = cities['distance']
    flight_list.append([city1_name, city2_name, distance])
type(flight_list)
flight_list[0]
flight_df = pd.DataFrame(flight_list)
flight_df<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.13007284079084286, 'fraction_numerical': 0.018730489073881373, 'mean_word_length': 4.5606936416184976, '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': '126492', 'license': 'MIT', 'n_tokens_mistral': 362, 'n_tokens_neox': 351, 'n_words': 60, 'path': 'Become a Data Engineer - Mastering the Concepts/8. Advanced NoSQL for Data Science/Graph Database - Neo4J/Load_Neo4j.ipynb', 'repo_name': 'jrderek/Big_Data_Engineering_Portfolio', 'size': '961'}