Question

我有下表：

+----------+----------+--------------------+--------------------+--------------------+--------------------+--------------------+
    |  _created|  _updated|                name|         description|          indication|                name|      patents_patent|
    +----------+----------+--------------------+--------------------+--------------------+--------------------+--------------------+
    |2005-06-13|2016-08-17|           Lepirudin|Lepirudin is iden...|For the treatment...|           Lepirudin|1|
    |2005-06-13|2017-04-27|           Cetuximab|Cetuximab is an e...|Cetuximab, used i...|           Cetuximab|1|
    |2005-06-13|2017-06-14|        Dornase alfa|Dornase alfa is a...|Used as adjunct t...|        Dornase alfa|1|
    |2005-06-13|2017-03-10|          Etanercept|Dimeric fusion pr...|Etanercept is ind...|          Etanercept|1|
    |2005-06-13|2017-07-06|         Bivalirudin|Bivalirudin is a ...|For treatment of ...|         Bivalirudin|1|
    |2005-06-13|2017-07-05|          Leuprolide|Leuprolide belong...|For treatment of ...|          Leuprolide|1|
    |2005-06-13|2017-06-16|Peginterferon alf...|Peginterferon alf...|Peginterferon alf...|Peginterferon alf...|1|
    |

理想情况下，我需要派生2个表：

table_one我将过滤掉patent_patent不为NULL的表格，并将专利专利中的字符串替换为1：

    +----------+----------+--------------------+--------------------+--------------------+--------------------+--------------------+
   |  _created|  _updated|                name|         description|          indication|                name|      patents_patent|
    +----------+----------+--------------------+--------------------+--------------------+--------------------+------------------
   |2005-06-13|2016-08-17| Denileukin diftitox|A recombinant DNA...|For treatment of ...| Denileukin diftitox|                0|

    |2005-06-13|2017-06-08|           Alteplase|Human tissue plas...|For management of...|           Alteplase|                0|
    |2005-06-13|2016-12-08|          Sermorelin|Sermorelin acetat...|For the treatment...|          Sermorelin|                0|
    |2005-06-13|2016-08-17|  Interferon alfa-n1|Purified, natural...|For treatment of ...|  Interferon alfa-n1|                0|

table_two =过滤掉个表，其中patents_patent为null并将null替换为0

from pyspark.sql.functions import col, expr, when

data = table.where(col("patents_patent").isNull())

data = table.filter("patents_patent is not NULL")

我试过了：

root
 |-- _created: string (nullable = true)
 |-- _updated: string (nullable = true)
 |-- name: string (nullable = true)
 |-- description: string (nullable = true)
 |-- indication: string (nullable = true)
 |-- patents_patent: string (nullable = true)

结果错误或空：！

@media (min-width: 1920px) and (max-width: 2560px)  {
    //insert styles here...
}

感谢您的帮助！

Answer 1

table_one我将过滤掉patent_patent不为NULL的表格，并将专利专利中的字符串替换为1：

对于第一种情况，你应该做

data_not_null = table.filter((table['patents_patent'] != "NULL")).withColumn('patents_patent', f.lit("1"))

table_two =过滤掉个表，其中patents_patent为null并将null替换为0

对于第二个，您应该执行以下操作

data_null = table.where(f.col("patents_patent").isNull() | (table['patents_patent'] == "NULL")).withColumn('patents_patent', f.lit("0"))

我将导入为

from pyspark.sql import functions as f

当然f.col("patents_patent")和table['patents_patent']表示相同

PySpark：用数值替换字符串

1 个答案: