Spark Dataframe-Python

Question

In pandas, I can successfully run the following:

def car(t)
    if t in df_a:
       return df_a[t]/df_b[t]
    else:
       return 0

But how can I do the exact same thing with spark dataframe?Many thanks!
The data is like this

df_a
a 20
b 40
c 60

df_b
a 80
b 50
e 100

The result should be 0.25 when input car(a)

Answer 1

First you have to join both dataframes, then you have to filter by the letter you want and select the operation you need.

df_a = sc.parallelize([("a", 20), ("b", 40), ("c", 60)]).toDF(["key", "value"])
df_b = sc.parallelize([("a", 80), ("b", 50), ("e", 100)]).toDF(["key", "value"])

def car(c):
  return df_a.join(df_b, on=["key"]).where(df_a["key"] == c).select((df_a["value"] / df_b["value"]).alias("ratio")).head()

car("a")

# Row(ratio=0.25)