Python translate a column with multiple languages to english - python-3.x

Question

I have a dataset where there are multiple comments columns having multiple languages and I want to translate these columns into English and create new columns with all the english translations.
Accountability_COMMENT is the column which has multiple comments in different language in every row. I want to create a new column and translate all such comments to English.
I have tried the following code :
from googletrans import Translator
from textblob import TextBlob
translator = Translator()
data_merge['Accountability_COMMENT'] = data_merge['Accountability_COMMENT'].apply(lambda x:
TextBlob(x).translate(to='en'))
The error that I am getting is :
TypeError: The text argument passed to __init__(text) must be a string, not class 'float'
My column has objet format which is correct

Answer 1

You most probably have some comments that only consists of a float (i.e. a decimal number), that even if they are type: object according to pandas they are still interpreted as float by TextBlob. This leads to the error:
TypeError: The text argument passed to __init__(text) must be a string, not <class 'float'>
One solution is to make sure that the input x of TextBlob(x) is a string. You could do this by modifying the apply row like:
data_merge['Accountability_COMMENT'] = data_merge['Accountability_COMMENT'].apply(lambda x: TextBlob(str(x)).translate(to='en'))
Unfortunately this will probably also rais an error like:
raise NotTranslated('Translation API returned the input string unchanged.')
textblob.exceptions.NotTranslated: Translation API returned the input string unchanged.
This is due to the fact that when translating a number, the translation and the original text will be exactly the same, and apparently TextBlob doesn't like that.
What you can do to avoid this is to catch that exception NotTranslated and just return the untranslated TextBlob, like this:
from textblob import TextBlob
from textblob.exceptions import NotTranslated
def translate_comment(x):
try:
# Try to translate the string version of the comment
return TextBlob(str(x)).translate(to='en')
except NotTranslated:
# If the output is the same as the input just return the TextBlob version of the input
return TextBlob(str(x))
data_merge['Accountability_COMMENT'] = data_merge['Accountability_COMMENT'].apply(translate_comment)
EDIT:
If you get the HTTP error Too Many Requests it's probably because you are being kicked out by the Google Translate API. Instead of using apply, you can make your translation "extra-slow" by using a for loop with some sleep in-between cycles. In this case you should import another package (time) and substitute the last line:
from time import sleep
from textblob import TextBlob
from textblob.exceptions import NotTranslated
def translate_comment(x):
try:
# Try to translate the string version of the comment
return TextBlob(str(x)).translate(to='en')
except NotTranslated:
# If the output is the same as the input just return the TextBlob version of the input
return TextBlob(str(x))
for i in range(len(data_merge['Accountability_COMMENT'])):
# Translate one comment at a time
data_merge['Accountability_COMMENT'].iloc[i] = translate_comment(data_merge['Accountability_COMMENT'].iloc[i])
# Sleep for a quarter of second
sleep(0.25)
You can then experiment with different values for the sleep function. Of course the longer the sleep the slower the translation! N.B. sleep argument is in seconds.