问题描述
对于以下数据框
df=spark.createDataFrame(data=[('Alice',4.300),('Bob',7.677)],schema=['name','High'])
当我尝试查找min&最高我只会在输出中获得最小值.
When I try to find min & max I am only getting min value in output.
df.agg({'High':'max','High':'min'}).show()
+-----------+
|min(High) |
+-----------+
| 2094900|
+-----------+
为什么agg()不能同时给出max&像在熊猫里一样吗?
Why can't agg() give both max & min like in Pandas?
推荐答案
您可以看到此处:
计算汇总并以DataFrame的形式返回结果.
Compute aggregates and returns the result as a DataFrame.
可用的汇总函数是avg，max，min，sum，count.
The available aggregate functions are avg, max, min, sum, count.
如果exprs是从字符串到字符串的单个dict映射，则键是要对其执行聚合的列，而值是聚合函数.
If exprs is a single dict mapping from string to string, then the key is the column to perform aggregation on, and the value is the aggregate function.
或者，exprs也可以是聚合列表达式的列表.
Alternatively, exprs can also be a list of aggregate Column expressions.
参数: exprs –从列名(字符串)到聚合函数(字符串)或列列表的字典映射.
Parameters: exprs – a dict mapping from column name (string) to aggregate functions (string), or a list of Column.
您可以使用列列表，并在每列上应用所需的功能，如下所示:
You can use a list of column and apply the function that you need on every column, like this:
>>> from pyspark.sql import functions as F
>>> df.agg(F.min(df.High),F.max(df.High),F.avg(df.High),F.sum(df.High)).show()
+---------+---------+---------+---------+
|min(High)|max(High)|avg(High)|sum(High)|
+---------+---------+---------+---------+
| 4.3| 7.677| 5.9885| 11.977|
+---------+---------+---------+---------+
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