How to apply style.applymap to a DataFrame based on condition in another DataFrame

Question

I have two dataframes the same size (3 by 3), one is Logical (True/False) and the other is numerical:

Logical df Numerical df

My script allows the user to input a specific coordinate from the Logical Matrix in order to change it from False to True (if it is already True, just ignores the command). After that, I want to apply the style.applymap function to color the elements in my numerical df corresponding to the True values.

style.applymap(func, subset=((row), [columns])

Thus, my approach was to save the indexes of the True values and add them to the subset using my numerical df. However, I cannot add my specific indexes on the subset field nor add more than one row in the subset parameter. So far, my code goes like this:

Occupato = pd.DataFrame(np.zeros(shape = (3, 3)))
for i in range(3):
    Occupato = Occupato.astype({i: bool})

normale = pd.DataFrame(np.random.randint(0,10,size=(3, 3)), columns=list('ABC')) 


def colore(v, colore):
    # if v:
        return f"background-color: {colore};" 

idx = ('Insert coordinates as [x, y]: ')
Occupato.iloc[idx[0], idx[1]]
normale.style.applymap(colore, colore='blue', subset = (row), [columns])

Now, I find it weird to see the syntax for the subset, using parenthesis () for rows -and only accepting one integer- whereas for columns, square brackets[] and allowing multiple values. Thanks in advance.

I tried:

mydf.style.applymap(colore, colore='blue', subset = (rows), [columns])

I expected to obtain the list elements specified on the subset and colored blue. Instead I obtained:

KeyError: "None of [Index([(1, 2)], dtype='object')] are in the [index]"

Timeless · Accepted Answer · 2023-05-08 10:40:16Z

0

I would do it this way :

def colore(_, o, colore): #the white color is optional
    d_map = {True: f"background-color: {colore};color: white", False: ""}
    return o.replace(d_map)

normale.style.apply(colore, o=occupato, colore="blue", axis=None)

Output :

Inputs used :

print(occupato)

       A      B      C
0  False   True   True
1   True  False  False
2   True  False   True

print(normale)

    A  B  C
0   1  5  3
1   7  6  5
2  11  3  4

edited May 8, 2023 at 10:40

answered May 8, 2023 at 7:53

Timeless

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1 Comment

Carlos Alfonzo Over a year ago

Thanks it worked. 100% The key was to add the .replace() function and changing applymap -> apply.

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