根据条件将列添加到pyspark数据框 [英] Add column to pyspark dataframe based on a condition

问题描述

我的data.csv文件具有三列，如下所示.我已经将此文件转换为python spark数据框.

My data.csv file has three columns like given below. I have converted this file to python spark dataframe.

  A   B    C
| 1 | -3 | 4 |
| 2 | 0  | 5 |
| 6 | 6  | 6 |

我要基于以下条件在spark数据框中添加另一列D，其值为Yes或No:如果B列中的对应值大于0，则为Yes，否则为No.

I want to add another column D in spark dataframe with values as Yes or No based on the condition that if corresponding value in B column is greater than 0 then yes otherwise No.

  A   B    C   D
| 1 | -3 | 4 | No  |
| 2 | 0  | 5 | No  |
| 6 | 6  | 6 | Yes |

我无法通过PySpark数据框操作来实现此目的.

I am not able to implement this through PySpark dataframe operations.

推荐答案

尝试如下操作:

from pyspark.sql import functions as f
df.withColumn('D', f.when(f.col('B') > 0, "Yes").otherwise("No")).show()

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