<jupyter_start><jupyter_text>len(city_data)<jupyter_code>city_data_df = pd.DataFrame(city_data)
city_data_df.head()
new_column_order = ["City", "Country", "Date", "Lat", "Lng", "Max Temp", "Humidity", "Cloudiness", "Wind Speed", "Description"]
city_data_df = city_data_df[new_column_order]
city_data_df.head(10)
# Create the output file (CSV).
output_data_file = "weather_database/weatherpy_database.csv"
# Export the City_Data into a CSV.
city_data_df.to_csv(output_data_file, index_label="City_ID")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14150943396226415, 'fraction_numerical': 0.0037735849056603774, 'mean_word_length': 10.0625, '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': '548070', 'license': 'Apache-2.0', 'n_tokens_mistral': 210, 'n_tokens_neox': 201, 'n_words': 34, 'path': 'weather_database/Weather_Database.ipynb', 'repo_name': 'pascalegeday/World_Weather_Analysis', 'size': '530'}