from io import StringIO

import pandas as pd

csv_buffer = StringIO()
df.to_csv(csv_buffer, chunksize=1000)
s3_resource = boto3.resource('s3')
s3_resource.Object(bucket, 'df.csv').put(Body=csv_buffer.getvalue())

>>> from io import StringIO
... from itertools import islice
... import sys
...
... import numpy as np
... import pandas as pd
...
... df = pd.DataFrame(np.arange(300).reshape(100, -1))
... csv_buffer = StringIO()
... df.to_csv(csv_buffer)
... csv_buffer.seek(0)
...
... # Account for indivisibility (scoop up a remainder on the final slice).
... chunksize = 33
... rowsize = df.shape[1]
... slices = [(0, chunksize)] * (rowsize - 1) + [(0, sys.maxsize)]
... chunks = (tuple(islice(csv_buffer, i, j)) for i, j in slices)
...

>>> next(chunks)
(',0,1,2n',
 '0,0,1,2n',
 '1,3,4,5n',
 '2,6,7,8n',
 '3,9,10,11n',
 '4,12,13,14n',
 '5,15,16,17n',
 '6,18,19,20n',
 '7,21,22,23n',
 '8,24,25,26n',
 '9,27,28,29n',
 '10,30,31,32n',
 '11,33,34,35n',
 '12,36,37,38n',
 '13,39,40,41n',
 '14,42,43,44n',
 '15,45,46,47n',
 '16,48,49,50n',
 '17,51,52,53n',
 '18,54,55,56n',
 '19,57,58,59n',
 '20,60,61,62n',
 '21,63,64,65n',
 '22,66,67,68n',
 '23,69,70,71n',
 '24,72,73,74n',
 '25,75,76,77n',
 '26,78,79,80n',
 '27,81,82,83n',
 '28,84,85,86n',
 '29,87,88,89n',
 '30,90,91,92n',
 '31,93,94,95n')