[Python] How to improve code performance ( using Google Translate API )

import time
start = time.time()
import pandas as pd
from deep_translator import GoogleTranslator

data = pd.read_excel(r"latestdata.xlsx")
translatedata = data['column']. fillna('novalue')

list = []
for i in translatedata:
finaldata = GoogleTranslator(source='auto', target='english').translate(i)
print(finaldata)
list.append(finaldata)

df = pd.DataFrame(list, columns=['Translated_values'])
df.to_csv(r"jobdone.csv", sep= ';')

end = time.time()

print(f"Runtime of the program is {end - start}")


I have data of 220k points and trying to translate a column data At first I tried to use pool method parallel program but got an error that I can not access API several time at once. My question is if there is other way to improve performance of code that I have right now.

# 4066.826668739319 with just 10000 data all together.
# 3809.4675991535187 computation time when I run in 2 batch's of 5000

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