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fix: Resolve the issue of conflicts between columns added during the analysis process and the original data columns in the Spark version. #1518

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merged 3 commits into from
May 6, 2024
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fix: Resolve the issue of conflicts between columns added during the analysis process and the original data columns in the Spark version. #1518

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7fdc07a
Resolve the issue of conflicts between columns added during the analy…
Dec 9, 2023
925bcee
remove trailing whitespace
Dec 9, 2023
2d7f8bb
Merge branch 'develop' into fix/spark_column_conflict
fabclmnt May 6, 2024
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8 changes: 7 additions & 1 deletion src/ydata_profiling/model/spark/summary_spark.py
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Original file line number Diff line number Diff line change
Expand Up @@ -87,19 +87,25 @@ def multiprocess_1d(args: tuple) -> Tuple[str, dict]:
column, df = args
return column, describe_1d(config, df.select(column), summarizer, typeset)

# Rename the df column names to prevent potential conflicts
for col in df.columns:
df = df.withColumnRenamed(col, f"{col}_customer")

args = [(name, df) for name in df.columns]
with multiprocessing.pool.ThreadPool(12) as executor:
for i, (column, description) in enumerate(
executor.imap_unordered(multiprocess_1d, args)
):
if column.endswith("_customer"):
column = column[:-9]
pbar.set_postfix_str(f"Describe variable:{column}")

# summary clean up for spark
description.pop("value_counts")

series_description[column] = description
pbar.update()
series_description = {k: series_description[k] for k in df.columns}
series_description = {k[:-9]: series_description[k[:-9]] for k in df.columns}

# Mapping from column name to variable type
series_description = sort_column_names(series_description, config.sort)
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