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author | WeichenXu <WeichenXu123@outlook.com> | 2016-07-14 22:55:49 -0700 |
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committer | Reynold Xin <rxin@databricks.com> | 2016-07-14 22:55:49 -0700 |
commit | 1832423827fd518853b63f91c321e4568a39107d (patch) | |
tree | 1ba1f0973010ac852de22a9f94ebac714bb0ebb7 /python/pyspark | |
parent | 2e4075e2ece9574100c79558cab054485e25c2ee (diff) | |
download | spark-1832423827fd518853b63f91c321e4568a39107d.tar.gz spark-1832423827fd518853b63f91c321e4568a39107d.tar.bz2 spark-1832423827fd518853b63f91c321e4568a39107d.zip |
[SPARK-16546][SQL][PYSPARK] update python dataframe.drop
## What changes were proposed in this pull request?
Make `dataframe.drop` API in python support multi-columns parameters,
so that it is the same with scala API.
## How was this patch tested?
The doc test.
Author: WeichenXu <WeichenXu123@outlook.com>
Closes #14203 from WeichenXu123/drop_python_api.
Diffstat (limited to 'python/pyspark')
-rw-r--r-- | python/pyspark/sql/dataframe.py | 27 |
1 files changed, 19 insertions, 8 deletions
diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py index ab41e88620..adf549dd02 100644 --- a/python/pyspark/sql/dataframe.py +++ b/python/pyspark/sql/dataframe.py @@ -1399,11 +1399,11 @@ class DataFrame(object): @since(1.4) @ignore_unicode_prefix - def drop(self, col): + def drop(self, *cols): """Returns a new :class:`DataFrame` that drops the specified column. - :param col: a string name of the column to drop, or a - :class:`Column` to drop. + :param cols: a string name of the column to drop, or a + :class:`Column` to drop, or a list of string name of the columns to drop. >>> df.drop('age').collect() [Row(name=u'Alice'), Row(name=u'Bob')] @@ -1416,13 +1416,24 @@ class DataFrame(object): >>> df.join(df2, df.name == df2.name, 'inner').drop(df2.name).collect() [Row(age=5, name=u'Bob', height=85)] + + >>> df.join(df2, 'name', 'inner').drop('age', 'height').collect() + [Row(name=u'Bob')] """ - if isinstance(col, basestring): - jdf = self._jdf.drop(col) - elif isinstance(col, Column): - jdf = self._jdf.drop(col._jc) + if len(cols) == 1: + col = cols[0] + if isinstance(col, basestring): + jdf = self._jdf.drop(col) + elif isinstance(col, Column): + jdf = self._jdf.drop(col._jc) + else: + raise TypeError("col should be a string or a Column") else: - raise TypeError("col should be a string or a Column") + for col in cols: + if not isinstance(col, basestring): + raise TypeError("each col in the param list should be a string") + jdf = self._jdf.drop(self._jseq(cols)) + return DataFrame(jdf, self.sql_ctx) @ignore_unicode_prefix |