PySpark: multiple conditions in when clause

Question

I would like to modify the cell values of a dataframe column (Age) where currently it is blank and I would only do it if another column (Survived) has the value 0 for the c

Answer 1

You get SyntaxError error exception because Python has no && operator. It has and and & where the latter one is the correct choice to create boolean expressions on Column (| for a logical disjunction and ~ for logical negation).

Condition you created is also invalid because it doesn't consider operator precedence. & in Python has a higher precedence than == so expression has to be parenthesized.

(col("Age") == "") & (col("Survived") == "0")
## Column

On a side note when function is equivalent to case expression not WHEN clause. Still the same rules apply. Conjunction:

df.where((col("foo") > 0) & (col("bar") < 0))

Disjunction:

df.where((col("foo") > 0) | (col("bar") < 0))

You can of course define conditions separately to avoid brackets:

cond1 = col("Age") == "" 
cond2 = col("Survived") == "0"

cond1 & cond2