Passing list-likes to .loc or [] with any missing label will raise KeyError in the future, you can use .reindex() as an alternative.

[greenelab]

Passing list-likes to .loc or [] with any missing label will raise KeyError in the future, you can use .reindex() as an alternative.

[gwaybio]

nice catch @yagmuronay - although I am not sure that your solution will work. It is possible that the underlying data the notebook loads has changed in some way.

response = requests.get('http://oncokb.org/api/v1/genes')
oncokb_df = pd.read_json(response.content)
oncokb_df.to_csv(oncokb_out_file, sep='\t')

# Integrate copy number, oncokb gene-type, and mutation status to define status matrix
oncogenes_df = oncokb_df[oncokb_df['oncogene']]
tsg_df = oncokb_df[oncokb_df['tsg']]

# Subset copy gains by oncogenes and copy losses by tumor suppressors (tsg)
status_gain = copy_gain_df.loc[:, oncogenes_df['hugoSymbol']]
status_loss = copy_loss_df.loc[:, tsg_df['hugoSymbol']]
copy_status = pd.concat([status_gain, status_loss], axis=1)

what does tsg_df look like?

[yagmuronay]

Dear Dr. Greg (@gwaygenomics),

thank you so much for your quick reply. The parameters tsg_df and oncogenes_df indeed have a column named "hugoSymbol". I found out later that the output was written as expected. Previousy, I looked into the wrong path, which was for raw data. All in all, these were only some warnings. Thank you so much for your time!