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reformat with black; looks better

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Viktor Barzin 2025-05-31 23:50:43 +00:00
parent 1122f5a96f
commit 0b9d50af47
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GPG key ID: 4056458DBDBF8863
11 changed files with 240 additions and 244 deletions
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12
crawler/csv_exporter.py
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@ -12,9 +12,9 @@ async def export_to_csv(
ds = await asyncio.gather(*[listing.dict_nicely() for listing in listings])
df = pd.DataFrame(ds)
# read decisions on file
decisions_path = 'data/decisions.json'
decisions_path = "data/decisions.json"
decisions = pd.read_json(decisions_path)
df.loc[:, 'decision'] = df.identifier.apply(lambda x: decisions.get(x))
df.loc[:, "decision"] = df.identifier.apply(lambda x: decisions.get(x))
# remove all entries where we didnt calculate transit time (probably due to a too far distance)
# df2 = df[df.travel_time_fastest.notna()]
@ -26,9 +26,9 @@ async def export_to_csv(
# s1 = df2
# fill in gap values for service charge and lease left. This is for excel so we can use filters better there
df2.loc[:, 'service_charge'] = df2.service_charge.fillna(-1)
df2.loc[:, 'lease_left'] = df2.lease_left.fillna(-1)
df2.loc[:, 'sqm_ocr'] = df2.sqm_ocr.fillna(-1)
df2.loc[:, "service_charge"] = df2.service_charge.fillna(-1)
df2.loc[:, "lease_left"] = df2.lease_left.fillna(-1)
df2.loc[:, "sqm_ocr"] = df2.sqm_ocr.fillna(-1)
df3 = df2
# df3 = pd.concat([df2.drop(['travel_time_fastest', 'travel_time_second'], axis=1), s1], axis=1)
@ -37,5 +37,5 @@ async def export_to_csv(
df4 = df3
df5 = df4[columns]
df6 = df5.sort_values(by=['price_per_sqm'], ascending=True)
df6 = df5.sort_values(by=["price_per_sqm"], ascending=True)
df6.to_csv(str(output_file), index=False)