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Sean R. Owen commented on SPARK-39895: -------------------------------------- Not a big deal, but the example doesn't make sense to me. It's multiple cols in one string, not multiple strings or cols. Right? that doesn't seem like the right example > pyspark drop doesn't accept *cols > ---------------------------------- > > Key: SPARK-39895 > URL: https://issues.apache.org/jira/browse/SPARK-39895 > Project: Spark > Issue Type: Bug > Components: PySpark > Affects Versions: 3.0.3, 3.3.0, 3.2.2 > Reporter: Santosh Pingale > Assignee: Santosh Pingale > Priority: Minor > Fix For: 3.4.0 > > > Pyspark dataframe drop has following signature: > {color:#4c9aff}{{def drop(self, *cols: "ColumnOrName") -> > "DataFrame":}}{color} > However when we try to pass multiple Column types to drop function it raises > TypeError > {{each col in the param list should be a string}} > *Minimal reproducible example:* > {color:#4c9aff}values = [("id_1", 5, 9), ("id_2", 5, 1), ("id_3", 4, 3), > ("id_1", 3, 3), ("id_2", 4, 3)]{color} > {color:#4c9aff}df = spark.createDataFrame(values, "id string, point int, > count int"){color} > |– id: string (nullable = true)| > |– point: integer (nullable = true)| > |– count: integer (nullable = true)| > {color:#4c9aff}{{df.drop(df.point, df.count)}}{color} > {quote}{color:#505f79}/spark/python/lib/pyspark.zip/pyspark/sql/dataframe.py > in drop(self, *cols){color} > {color:#505f79}2537 for col in cols:{color} > {color:#505f79}2538 if not isinstance(col, str):{color} > {color:#505f79}-> 2539 raise TypeError("each col in the param list should be > a string"){color} > {color:#505f79}2540 jdf = self._jdf.drop(self._jseq(cols)){color} > {color:#505f79}2541{color} > {color:#505f79}TypeError: each col in the param list should be a string{color} > {quote} -- This message was sent by Atlassian Jira (v8.20.10#820010) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org