Add column to pyspark dataframe based on a condition

Question

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 |

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 |

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

Solution

Try something like this:

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