pytubes4.py

# Find the matching rows (where the first column is True)
word_rows = one_grams[IS_WORD_COL]
# Create an empty array to hold the per-year % values 
word_counts = np.zeros(last_year+1)
# Iterate over each matching row (for a matching word, there should just be 1,000s of rows)
for _, year, count in one_grams[word_rows]:
    # Set the relevant word_counts row to the calculated value 
    word_counts[year] += (100*count) / year_totals[year]