claim_text_extraction.ipynb df = pd.read_csv('./data/20k_G_and_H_publication_numbers.csv') workaround

[austinjhicks]

I had a hard time getting this bit of code to work:

df = pd.read_csv('./data/20k_G_and_H_publication_numbers.csv')

I went into jupyter labs, copied the file path of the 20k_G_and_H_publication_numbers.csv,
and then pasted the file path.
For me, the command looked like this:

df=pd.read_csv('GCS/20k_G_and_H_publication_numbers.csv')

I don't know that I'm doing that ^^ right, but it didn't work to load the dataframe.
I found this google-cloud-service-buckets workaround on stack overflow:

Store the file in a GCS bucket.

1.Upload your file to GCS.

2.In your Notebook, type the following code, replacing the bucket and file names accordingly:

import pandas as pd
from google.cloud import storage
from io import BytesIO
client = storage.Client()
bucket_name = "your-bucket"
file_name = "your_file.csv"
bucket = client.get_bucket(bucket_name)
blob = bucket.get_blob(file_name)
content = blob.download_as_string()
df = pd.read_csv(BytesIO(content))
print(df)

Credit to OP

^^ this workaround worked for me