how to replace list of columns with condition on one col by dict\df

Question

i like to change my the values in list of columns by condition on one col use dict\df i got df\dict the

Something like this

list_of_cols=["col1",.."col5"]
df[list_of_cols]=where[df["A"]==dict],dict

this is the data

data={"col1":[np.nan,3,4,5,9,2,6],
"col2":[4,2,4,6,0,1,5],
"col3":[7,6,0,11,3,6,7],
"col4":[14,11,22,8,6,np.nan,9],
"col5":[0,5,7,3,8,2,9],
"type":["A","A","C","A","B","A","E"],
"number":["one","two","two","one","one","two","two"]}
df=pd.DataFrame.from_dict(data)
df

this is my dict\df that i want to map the df["type"] with the dict so where the type==A, col1-col5 will be 0

my_dict={"A":0,"B":21,"C":14,"D":9}
my_dict=pd.DataFrame.from_dict(my_dict, orient='index')
my_dict

that what i like to get

data={"col1":[0,0,14,0,21,0,6],
      "col2":[0,0,14,0,21,0,5],
      "col3":[0,0,14,0,21,0,7],
      "col4":[0,0,14,0,21,0,0.9],
      "col5":[0,0,14,0,21,0,9],
      "type":["A","A","C","A","B","A","E"],
"number":["one","two","two","one","one","two","two"]}
df=pd.DataFrame.from_dict(data)
df

Answer 1

IIUC, use isin to filter out types, and then assign directly using apply and map :

m = df["type"].isin(my_dict)

df.loc[m, "col1":"col5"] = df.loc[m, "col1":"col5"].apply(lambda d: pd.Series.map(df["type"], my_dict))

print (df)

   col1  col2  col3  col4  col5 type number
0   0.0   0.0   0.0   0.0   0.0    A    one
1   0.0   0.0   0.0   0.0   0.0    A    two
2  14.0  14.0  14.0  14.0  14.0    C    two
3   0.0   0.0   0.0   0.0   0.0    A    one
4  21.0  21.0  21.0  21.0  21.0    B    one
5   0.0   0.0   0.0   0.0   0.0    A    two
6   6.0   5.0   7.0   9.0   9.0    E    two