How best to convert from azure blob csv format to pandas dataframe while running notebook in azure ml

Question

I have a number of large csv (tab delimited) data stored as azure blobs, and I want to create a pandas dataframe from these. I can do this locally as follows:

Answer 1

The accepted answer will not work in the latest Azure Storage SDK. MS has rewritten the SDK completely. It's kind of annoying if you are using the old version and update it. The below code should work in the new version.

from azure.storage.blob import ContainerClient
from io import StringIO
import pandas as pd

conn_str = ""
container = ""
blob_name = ""

container_client = ContainerClient.from_connection_string(
    conn_str=conn_str, 
    container_name=container
    )
# Download blob as StorageStreamDownloader object (stored in memory)
downloaded_blob = container_client.download_blob(blob_name)

df = pd.read_csv(StringIO(downloaded_blob.content_as_text()))