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author | hyukjinkwon <gurwls223@gmail.com> | 2016-07-06 10:45:51 -0700 |
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committer | Reynold Xin <rxin@databricks.com> | 2016-07-06 10:45:51 -0700 |
commit | 4e14199ff740ea186eb2cec2e5cf901b58c5f90e (patch) | |
tree | cfd7850c821e764c2243615a8fd8642d73323da1 /python/pyspark/sql/group.py | |
parent | b1310425b30cbd711e4834d65a0accb3c5a8403a (diff) | |
download | spark-4e14199ff740ea186eb2cec2e5cf901b58c5f90e.tar.gz spark-4e14199ff740ea186eb2cec2e5cf901b58c5f90e.tar.bz2 spark-4e14199ff740ea186eb2cec2e5cf901b58c5f90e.zip |
[MINOR][PYSPARK][DOC] Fix wrongly formatted examples in PySpark documentation
## What changes were proposed in this pull request?
This PR fixes wrongly formatted examples in PySpark documentation as below:
- **`SparkSession`**
- **Before**
![2016-07-06 11 34 41](https://cloud.githubusercontent.com/assets/6477701/16605847/ae939526-436d-11e6-8ab8-6ad578362425.png)
- **After**
![2016-07-06 11 33 56](https://cloud.githubusercontent.com/assets/6477701/16605845/ace9ee78-436d-11e6-8923-b76d4fc3e7c3.png)
- **`Builder`**
- **Before**
![2016-07-06 11 34 44](https://cloud.githubusercontent.com/assets/6477701/16605844/aba60dbc-436d-11e6-990a-c87bc0281c6b.png)
- **After**
![2016-07-06 1 26 37](https://cloud.githubusercontent.com/assets/6477701/16607562/586704c0-437d-11e6-9483-e0af93d8f74e.png)
This PR also fixes several similar instances across the documentation in `sql` PySpark module.
## How was this patch tested?
N/A
Author: hyukjinkwon <gurwls223@gmail.com>
Closes #14063 from HyukjinKwon/minor-pyspark-builder.
Diffstat (limited to 'python/pyspark/sql/group.py')
-rw-r--r-- | python/pyspark/sql/group.py | 2 |
1 files changed, 2 insertions, 0 deletions
diff --git a/python/pyspark/sql/group.py b/python/pyspark/sql/group.py index a423206554..f2092f9c63 100644 --- a/python/pyspark/sql/group.py +++ b/python/pyspark/sql/group.py @@ -179,10 +179,12 @@ class GroupedData(object): :param values: List of values that will be translated to columns in the output DataFrame. # Compute the sum of earnings for each year by course with each course as a separate column + >>> df4.groupBy("year").pivot("course", ["dotNET", "Java"]).sum("earnings").collect() [Row(year=2012, dotNET=15000, Java=20000), Row(year=2013, dotNET=48000, Java=30000)] # Or without specifying column values (less efficient) + >>> df4.groupBy("year").pivot("course").sum("earnings").collect() [Row(year=2012, Java=20000, dotNET=15000), Row(year=2013, Java=30000, dotNET=48000)] """ |