我正在databricks上运行以下代码:
dataToShow = jDataJoined.\
withColumn('id', monotonically_increasing_id()).\
filter(
(jDataJoined.containerNumber == 'SUDU8108536')).\
select(col('id'), col('returnTemperature'), col('supplyTemperature'))
这将给我类似表格数据
现在,我想显示一个以returnTemperature和supplyTemperature作为类别的折线图。
据我了解,databricks中的方法display
希望将类别作为第二个参数,因此基本上我应该拥有类似的东西
id - temperatureCategory - value
1 - returnTemperature - 25.0
1 - supplyTemperature - 27.0
2 - returnTemperature - 24.0
2 - supplyTemperature - 28.0
如何以这种方式转换数据框?
答案 0 :(得分:1)
我不知道您的格式是否是显示方法所期望的格式,但是您可以使用sql函数create_map和explode进行此转换:
#creates a example df
from pyspark.sql import functions as F
l1 = [(1,25.0,27.0),(2,24.0,28.0)]
df = spark.createDataFrame(l1,['id','returnTemperature','supplyTemperature'])
#creates a map column which contains the values of the returnTemperature and supplyTemperature
df = df.withColumn('mapCol', F.create_map(
F.lit('returnTemperature'),df.returnTemperature
,F.lit('supplyTemperature'),df.supplyTemperature
)
)
#The explode function creates a new row for each element of the map
df = df.select('id',F.explode(df.mapCol).alias('temperatureCategory','value'))
df.show()
输出:
+---+-------------------+-----+
| id|temperatureCategory|value|
+---+-------------------+-----+
| 1 | returnTemperature| 25.0|
| 1 | supplyTemperature| 27.0|
| 2 | returnTemperature| 24.0|
| 2 | supplyTemperature| 28.0|
+---+-------------------+-----+