text_plain_output_1.png
from tqdm import tqdm

import pandas as pd

import spacy

path = '../input/CORD-19-research-challenge/'
all_sources = pd.read_csv(path + 'metadata.csv')

all_sources.isna().sum()

nlp = spacy.load('en_core_web_sm')
sent_vecs = {}
docs = []
for i in tqdm(all_sources['title'].fillna('unknown')[:1000]):
    doc = nlp(i)
    docs.append(doc)
    sent_vecs.update({i: doc.vector})