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I've just started to experiment with AWS SageMaker and would like to load data from an S3 bucket into a pandas dataframe in my SageMaker python jupyter notebook for analysis.

I could use boto to grab the data from S3, but I'm wondering whether there is a more elegant method as part of the SageMaker framework to do this in my python code?

Thanks in advance for any advice.

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import boto3
import pandas as pd
from sagemaker import get_execution_role

role = get_execution_role()
bucket='my-bucket'
data_key = 'train.csv'
data_location = 's3://{}/{}'.format(bucket, data_key)

pd.read_csv(data_location)

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