从 pyspark 数据框字符串列中获取第一个数值到新列中
get first numeric values from pyspark dataframe string column into new column
我有一个 pyspark 数据框，就像下面的输入数据一样。我想创建一个新列 product1_num，将 productname 列中每条记录的第一个数字解析到一个新列中。我在下面有示例输出数据。就字符串拆分和正则表达式匹配而言，我不确定 pyspark 中有什么可用的。谁能建议如何用 pyspark 做到这一点？
输入数据：
+------+-------------------+
|id |productname |
+------+-------------------+
|234832|EXTREME BERRY SAUCE|
|419836|BLUE KOSHER SAUCE |
|350022|GUAVA (1G) |
|123213|GUAVA 1G |
+------+-------------------+
输出：
+------+-------------------+-------------+
|id |productname |product1_num |
+------+-------------------+-------------+
|234832|EXTREME BERRY SAUCE| |
|419836|BLUE KOSHER SAUCE | |
|350022|GUAVA (1G) |1 |
|123213|GUAVA G5 |5 |
|125513|3GULA G5 |3 |
|127143|GUAVA G50 |50 |
|124513|LAAVA C2L5 |2 |
+------+-------------------+-------------+
您可以使用 regexp_extract:
from pyspark.sql import functions as F
df.withColumn("product1_num", F.regexp_extract("productname", "([0-9]+)",1)).show()
+------+-------------------+------------+
| id| productname|product1_num|
+------+-------------------+------------+
|234832|EXTREME BERRY SAUCE| |
|419836| BLUE KOSHER SAUCE| |
|350022| GUAVA (1G)| 1|
|123213| GUAVA G5| 5|
|125513| 3GULA G5| 3|
|127143| GUAVA G50| 50|
|124513| LAAVA C2L5| 2|
+------+-------------------+------------+
我有一个 pyspark 数据框，就像下面的输入数据一样。我想创建一个新列 product1_num，将 productname 列中每条记录的第一个数字解析到一个新列中。我在下面有示例输出数据。就字符串拆分和正则表达式匹配而言，我不确定 pyspark 中有什么可用的。谁能建议如何用 pyspark 做到这一点？
输入数据：
+------+-------------------+
|id |productname |
+------+-------------------+
|234832|EXTREME BERRY SAUCE|
|419836|BLUE KOSHER SAUCE |
|350022|GUAVA (1G) |
|123213|GUAVA 1G |
+------+-------------------+
输出：
+------+-------------------+-------------+
|id |productname |product1_num |
+------+-------------------+-------------+
|234832|EXTREME BERRY SAUCE| |
|419836|BLUE KOSHER SAUCE | |
|350022|GUAVA (1G) |1 |
|123213|GUAVA G5 |5 |
|125513|3GULA G5 |3 |
|127143|GUAVA G50 |50 |
|124513|LAAVA C2L5 |2 |
+------+-------------------+-------------+
您可以使用 regexp_extract:
from pyspark.sql import functions as F
df.withColumn("product1_num", F.regexp_extract("productname", "([0-9]+)",1)).show()
+------+-------------------+------------+
| id| productname|product1_num|
+------+-------------------+------------+
|234832|EXTREME BERRY SAUCE| |
|419836| BLUE KOSHER SAUCE| |
|350022| GUAVA (1G)| 1|
|123213| GUAVA G5| 5|
|125513| 3GULA G5| 3|
|127143| GUAVA G50| 50|
|124513| LAAVA C2L5| 2|
+------+-------------------+------------+