text_html_output_1.png
import pandas as pd

metadata_df = pd.read_csv('../input/CORD-19-research-challenge/metadata.csv', index_col='cord_uid')

example_df = pd.read_csv('../input/CORD-19-research-challenge/Kaggle/target_tables/2_relevant_factors/How does temperature and humidity affect the transmission of 2019-nCoV.csv')

example_shas = []
example_uids = []
for index, row in example_df.iterrows():
    study_title = row['Study']
    study_metadata = metadata_df[metadata_df['title'] == study_title]
    if len(study_metadata) != 0:
        sha = study_metadata.iloc[0]['sha']
        uid = study_metadata.iloc[0].name
        if str(sha) != 'nan':
            example_shas.append(sha)
            example_uids.append(uid)

unique_example_uids = set(example_uids)
len(unique_example_uids)