Hyukjin Kwon created SPARK-61023:
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Summary: Take the arguments of dropna, na.drop, fillna, describe,
corr and approxQuantile in the Python client as PySpark does
Key: SPARK-61023
URL: https://issues.apache.org/jira/browse/SPARK-61023
Project: Spark
Issue Type: Bug
Components: Connect
Affects Versions: connect-rust-4.3.0
Reporter: Hyukjin Kwon
In PySpark, the {{subset}} of {{df.dropna(how, thresh, subset)}} and
{{df.na.drop}} is a column name or a list or tuple of them, and {{how}} is
"any" or "all", else {{VALUE_NOT_ALLOWED}}. {{df.fillna(value, subset)}} takes
a bool, a dict, a float, an int or a string as the value, else
{{NOT_EXPECTED_TYPE}}. {{df.describe(*cols)}} takes column names or a list of
them. {{df.corr(col1, col2, method)}} takes only the method "pearson", else
{{VALUE_NOT_ALLOWED}}. {{df.approxQuantile(col, probabilities, relativeError)}}
raises {{NEGATIVE_VALUE}} for a negative relativeError.
The Rust-backed Python client's {{df.dropna(subset="x")}} and
{{df.na.drop(subset="x")}} raise {{TypeError: argument 'subset': Can't extract
`str` to `Vec`}}. {{df.dropna(how="bogus")}} is accepted, {{df.fillna([1])}}
fills the string 'List([Long(1)])', and {{df.describe(["x", "v"])}} raises a
TypeError. {{df.corr("x", "v", "kendall")}} returns the Pearson correlation,
and {{df.approxQuantile("v", [0.5], -1.0)}} fails on the server with an
IllegalArgumentException. Take the arguments as PySpark does.
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