Apache spark 通过获取现有列的比率在Pyspark DataFrame中创建新列
我在PySpark数据框中有两列,我想在填充空值(不是就地)后取这两列的比率。目前,我的数据框架如下所示:Apache spark 通过获取现有列的比率在Pyspark DataFrame中创建新列,apache-spark,pyspark,apache-spark-sql,pyspark-dataframes,fillna,Apache Spark,Pyspark,Apache Spark Sql,Pyspark Dataframes,Fillna,我在PySpark数据框中有两列,我想在填充空值(不是就地)后取这两列的比率。目前,我的数据框架如下所示: +----+----+---+----+----+----+----+ |Acct| M1D|M1C| M2D| M2C| M3D| M3C| +----+----+---+----+----+----+----+ | B| 10|200|null|null| 20|null| | C|1000|100| 10|null|null|null| | A| 100|200|
+----+----+---+----+----+----+----+
|Acct| M1D|M1C| M2D| M2C| M3D| M3C|
+----+----+---+----+----+----+----+
| B| 10|200|null|null| 20|null|
| C|1000|100| 10|null|null|null|
| A| 100|200| 200| 200| 300| 10|
+----+----+---+----+----+----+----+
+------+------+-----+------+------+------+------+-------+
| Acct | M1D | M1C | M2D | M2C | M3D | M3C | Ratio |
+------+------+-----+------+------+------+------+-------+
| B | 10 | 200 | null | null | 20 | null | 0 |
| C | 1000 | 100 | 10 | null | null | null | 10 |
| A | 100 | 200 | 200 | 200 | 300 | 10 | 20 |
+------+------+-----+------+------+------+------+-------+
我期望的输出如下所示:
+----+----+---+----+----+----+----+
|Acct| M1D|M1C| M2D| M2C| M3D| M3C|
+----+----+---+----+----+----+----+
| B| 10|200|null|null| 20|null|
| C|1000|100| 10|null|null|null|
| A| 100|200| 200| 200| 300| 10|
+----+----+---+----+----+----+----+
+------+------+-----+------+------+------+------+-------+
| Acct | M1D | M1C | M2D | M2C | M3D | M3C | Ratio |
+------+------+-----+------+------+------+------+-------+
| B | 10 | 200 | null | null | 20 | null | 0 |
| C | 1000 | 100 | 10 | null | null | null | 10 |
| A | 100 | 200 | 200 | 200 | 300 | 10 | 20 |
+------+------+-----+------+------+------+------+-------+
我想用M3C
获取M2D
的比率,以创建新列ratio
。在计算比率之前,我想用0
填充M2D
,用1
填充M3C
,这将动态执行,以避免出现空值,并避免替换原位值
我试着使用下面的代码来实现这一点
df = df.withColumn('Ratio', col('M2D').fillna(0, subset=['M2D']) / col('M3C').fillna(1, subset=['M3C']))
上面的代码给了我以下错误
TypeError: 'Column' object is not callable
如上错误所述,为了避免TypeError,我尝试了以下代码行。我现在使用的是DataFrame,而不是column
df = df.withColumn('Ratio', df.select('M2D').fillna(0, subset=['M2D']) / df.select('M3C').fillna(1, subset=['M3C']))
上述代码导致以下错误
TypeError: unsupported operand type(s) for /: 'DataFrame' and 'DataFrame'
如何实现所需的输出?在计算比率之前,应先填充空值,如下所示:
df = df.fillna(0, subset=['M2D'])\
.fillna(1, subset=['M3C'])\
.withColumn('Ratio', col('M2D') / col('M3C'))
或者更简单,如果您只想在计算中避免空值,请按如下所示使用coalesce
:
df = df.withColumn('Ratio', coalesce(col('M2D'), lit(0)) / coalesce(col('M3C'), lit(1)))
在计算比率之前,应填写空值,如下所示:
df = df.fillna(0, subset=['M2D'])\
.fillna(1, subset=['M3C'])\
.withColumn('Ratio', col('M2D') / col('M3C'))
或者更简单,如果您只想在计算中避免空值,请按如下所示使用coalesce
:
df = df.withColumn('Ratio', coalesce(col('M2D'), lit(0)) / coalesce(col('M3C'), lit(1)))