Update __init__.py

concat expire warning handled
pull/117/head
troy-conte 2024-02-29 16:13:47 -05:00 committed by GitHub
parent ba3a16b228
commit 9a3dff3c0f
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1 changed files with 20 additions and 4 deletions

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@ -152,9 +152,15 @@ def scrape_jobs(
jobs_dfs.append(job_df)
if jobs_dfs:
jobs_df = pd.concat(jobs_dfs, ignore_index=True)
desired_order: list[str] = [
"job_url_hyper" if hyperlinks else "job_url",
# Step 1: Filter out all-NA columns from each DataFrame before concatenation
filtered_dfs = [df.dropna(axis=1, how='all') for df in jobs_dfs]
# Step 2: Concatenate the filtered DataFrames
jobs_df = pd.concat(filtered_dfs, ignore_index=True)
# Desired column order
desired_order = [
"job_url_hyper" if 'hyperlinks' in locals() or 'hyperlinks' in globals() else "job_url",
"site",
"title",
"company",
@ -172,6 +178,16 @@ def scrape_jobs(
"emails",
"description",
]
return jobs_df[desired_order].sort_values(by=['site', 'date_posted'], ascending=[True, False])
# Step 3: Ensure all desired columns are present, adding missing ones as empty
for column in desired_order:
if column not in jobs_df.columns:
jobs_df[column] = None # Add missing columns as empty
# Reorder the DataFrame according to the desired order
jobs_df = jobs_df[desired_order]
# Step 4: Sort the DataFrame as required
return jobs_df.sort_values(by=['site', 'date_posted'], ascending=[True, False])
else:
return pd.DataFrame()