如何基于另一列的值应用熊猫函数？

Question

I have a pandas dataframe with two columns, one with some string values and another one with empty dicts:

ColA ColB
True  {}
False {}
True  {}
True  {}
False {}
False {}
True  {}

I have a function that updates a dict with some other values:

def update_dict(a):
    return a.update({"VAL":["yes"]})

How can I apply the above function to all the ColB cells that have "False" strings next to them in their ColA?:

ColA ColB
True  {}
False {"VAL":["yes"]}
True  {}
True  {}
False {"VAL":["yes"]}
False {"VAL":["yes"]}
True  {}

I know that in pandas you can use the apply function or applymap. However, I do not know how can I do it based on a previous column value.

Answer 1

It is possible but working with dict in values of columns is not recommended, because lost all vectorized functions:

def update_dict(a):
    a.update({"VAL":["yes"]})
    return a

df['ColB'] = [update_dict(j) if i == 'False' else j for i, j in zip(df['ColA'], df['ColB'])]
print (df)
    ColA              ColB
0   True                {}
1  False  {'VAL': ['yes']}
2   True                {}
3   True                {}
4  False  {'VAL': ['yes']}
5  False  {'VAL': ['yes']}
6   True                {}