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LLCAXCHZF-61/handles cases where CKAN type guessing is disabled #14

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merged 3 commits into from
Oct 10, 2024
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LLCAXCHZF-61/handles cases where CKAN type guessing is disabled #14

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LLCAXCHZF-61/handles cases where CKAN type guessing is disabled
TomeCirun Oct 10, 2024
a74add6
LLCAXCHZF-61/typo
TomeCirun Oct 10, 2024
9a84bc7
LLCAXCHZF-61/perform date conversion before applying numeric operations
TomeCirun Oct 10, 2024
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17 changes: 10 additions & 7 deletions ckanext/charts/fetchers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -73,14 +73,17 @@ def fetch_data(self) -> pd.DataFrame:
get_read_engine(),
).drop(columns=["_id", "_full_text"])

# Identify columns that are not datetime
non_datetime_cols = df.select_dtypes(exclude=['datetime']).columns
# Apply numeric conversion only to non-datetime columns
df[non_datetime_cols] = df[non_datetime_cols].apply(pd.to_numeric, errors='ignore').fillna(0)

if "date_time" in df.columns:
# Convert the 'date_time' column to string format in ISO 8601
df['date_time'] = df['date_time'].dt.strftime("%Y-%m-%dT%H:%M:%S")
try:
df['date_time'] = pd.to_datetime(df['date_time'])
# Convert valid dates to ISO format
df['date_time'] = df['date_time'].dt.strftime("%Y-%m-%dT%H:%M:%S")
except (ValueError, TypeError, AttributeError) as e:
# Log the warning and keep the original values if conversion fails
log.warning(f"Warning: Could not convert date_time column: {e}")

# Apply numeric conversion to all columns - it will safely ignore non-numeric values
df = df.apply(pd.to_numeric, errors='ignore').fillna(0)

except (ProgrammingError, UndefinedTable) as e:
raise exception.DataFetchError(
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