I am having a PySpark DataFrame. How can I chop off/remove last 5 characters from the column name
below -
from pyspark.sql.functions import subs
You can use expr function
>>> from pyspark.sql.functions import substring, length, col, expr
>>> df = df.withColumn("flower",expr("substring(name, 1, length(name)-5)"))
>>> df.show()
+--------------+----+---------+
| name|year| flower|
+--------------+----+---------+
| rose_2012|2012| rose|
| jasmine_2013|2013| jasmine|
| lily_2014|2014| lily|
| daffodil_2017|2017| daffodil|
|sunflower_2016|2016|sunflower|
+--------------+----+---------+
In this case, since we want to extract alphabetical characters, so REGEX will also work.
from pyspark.sql.functions import regexp_extract
df = df.withColumn("flower",regexp_extract(df['name'], '[a-zA-Z]+',0))
df.show()
+--------------+----+---------+
| name|year| flower|
+--------------+----+---------+
| rose_2012|2012| rose|
| jasmine_2013|2013| jasmine|
| lily_2014|2014| lily|
| daffodil_2017|2017| daffodil|
|sunflower_2016|2016|sunflower|
+--------------+----+---------+
You can use split
function. this code does what you want:
import pyspark.sql.functions as f
newDF = df.withColumn("year", f.split(df['name'], '\_')[1]).\
withColumn("flower", f.split(df['name'], '\_')[0])
newDF.show()
+--------------+----+---------+
| name|year| flower|
+--------------+----+---------+
| rose_2012|2012| rose|
| jasmine_2013|2013| jasmine|
| lily_2014|2014| lily|
| daffodil_2017|2017| daffodil|
|sunflower_2016|2016|sunflower|
+--------------+----+---------+
Adding little tweak to avoid hard coding and identify column length dynamically through location of underscore('_') using instr
function.
df = spark.createDataFrame([('rose_2012',),('jasmine_2013',),('lily_2014',),('daffodil_2017',),('sunflower_2016',)],['name'])
df.withColumn("flower",expr("substr(name, 1, (instr(name,'_')-1) )")).\
withColumn("year",expr("substr(name, (instr(name,'_')+1),length(name))")).show()