Pandas - 根据条件更新行中的值 with.apply()

Question

Simplified, I would like to use a function to check a condition on a row and set the value accordingly:

def helper(row):
    if row["A"] == "TEST":
         row["B"] = "WOW"
     else:
         row["C"] = "NO_GO"


moddf = df.apply(helper, axis=1)

I can do this using iterrows() but.apply should be MUCH faster to iterate over 1M rows in a df.

Answer 1

You don't need (and shouldn't use) apply:

# toy data
df = pd.DataFrame({'A':['TEST','NO'],
              'B' : ['A','B'],
              'C' :list('12')})

s = df['A']=='TEST'

df.loc[s,'B'] = 'WOW'
df.loc[~s, 'C'] = 'NO_GO'

Output:

      A    B      C
0  TEST  WOW      1
1    NO    B  NO_GO