如何在 Pandas 数据框中的列上应用格式

Question

I have a pandas data frame with 90 columns and I want to apply a format to each column. Each column has its own format and the function with the format has the same name as the name of the column. I want to apply the format to each column on the data frame.

For example, let's say dv, dw are two columns of my dataframe df:

dv 
1
2
1
1
5
5

dw
2
2
1
3
2
3

def dv(dv):      
    if dv==1:
       return 1
    else:
       return 0

def dw(dw):
    if dw==2:
       return 1
    else:
       return 0

I am using the command below :

df['dv']=df['dv'].apply(dv)

df['dw']=df['dw'].apply(dw)

output :

dv 
1
0
1
1
0
0


dw
1
1
0
0
1
0

Problem statement: I don't want to write a .apply method for every column since I have 90 columns and want to reduce lines of code.

Answer 1

You can use a dictionary with the names of the columns you want to modify along with their corresponding condition and values to do the replacements. Then, use the apply function to replace the values according to the dictionary like this:

data = [
    [1, 2],
    [2, 2],
    [1, 1],
    [1, 3],
    [5, 2],
    [5, 3]
]

df = pd.DataFrame(data, columns = ["dv", "dw"])

dict_ = {
    "dv": {
        "condition": 1,
        "x": 1,
        "y": 0
    },
    "dw": {
        "condition": 2,
        "x": 1,
        "y": 0
    }
}

def func(x):
    column = x.name
    
    return np.where(x == dict_[column]["condition"], dict_[column]["x"], dict_[column]["y"])

df[dict_.keys()].apply(func)

Example:

Input:

   dv  dw
0   1   2
1   2   2
2   1   1
3   1   3
4   5   2
5   5   3

Output:

   dv  dw
0   1   1
1   0   1
2   1   0
3   1   0
4   0   1
5   0   0