pandas: how replace string value from column by multi if condition

I need help for my problem. I try replace "pe60" with "pe61" in column "level_2" if have ("pe60" in column "level_2" and "b" in column "level_1") and the same replace "pe70" with "pe71" in column "level_2" if have ("pe70" in column "level_2" and "b" in column "level_1").
my try but not work is:

import pandas as pd
data = {'Name': ['Tom','nick','krish','jack','bob'],
        'level_1': ['a', 'b', 'a', 'b','a'],
        'level_2': ['pe60', 'pe70', 'pe71', 'pe60','pe60'],
        'level_3': [-2, -1, 4, 6,-4],
        }

df = pd.DataFrame(data)

print(df)

def f(row):
    if (row['level_2'] == 'pe60') & (row['level_1'] == 'b'):
        val = (row['level_2'] == 'pe61')
    elif (row['level_2'] == 'pe70') & (row['level_1'] == 'b'):
        val = (row['level_2'] == 'pe71')
    else:
        val = row['level_2']
    return val
df['level_2'] = df.apply(f, axis=1)
print(df)

my solution must be:

data_sol = {'Name': ['Tom', 'nick', 'krish', 'jack','bob'],
        'level_1': ['a', 'b', 'a', 'b','a'],
        'level_2': ['pe60', 'pe71', 'pe71', 'pe61','pe60'],
        'level_3': [-2, -1, 4, 6,-4],
        }

df_solution = pd.DataFrame(data_sol)
print(df_solution)

how can solve my problem ?

There are many ways to do this. Here's one way.

def my_func(x):
     return [
              x[0],
              x[1],
              "pe61" if (x[1]=="b" and x[2]=="pe60") else ("pe71" if (x[1]=="b" and x[2]=="pe70") else x[2]),
              x[3]
            ]

fixed_df = df.apply(my_func, axis=1, raw=True)

The output:

    Name level_1 level_2 level_3
0    Tom       a    pe60      -2
1   nick       b    pe71      -1
2  krish       a    pe71       4
3   jack       b    pe61       6
4    bob       a    pe60      -4

Here's another way.

def my_func2(x):
     return "pe61" if (x[1]=="b" and x[2]=="pe60") else ("pe71" if (x[1]=="b" and x[2]=="pe70") else x[2])

df["level_2"] = df.apply(my_func2, axis=1, raw=True)

The new df:

    Name level_1 level_2  level_3
0    Tom       a    pe60       -2
1   nick       b    pe71       -1
2  krish       a    pe71        4
3   jack       b    pe61        6
4    bob       a    pe60       -4

You were really close! You want to return the value, not test for equality:

def f(row):
    if (row['level_2'] == 'pe60') & (row['level_1'] == 'b'):
        val = 'pe61'
    elif (row['level_2'] == 'pe70') & (row['level_1'] == 'b'):
        val = 'pe71'
    else:
        val = row['level_2']
    return val

You can use pandas built-in functions and a dictionary if you have multiple such mappings:

mappings = {'pe60': 'pe61', 
            'pe70': 'pe71'}
df.loc[(df['level_2'].isin(mappings.keys())) & (df['level_1'] == 'b'), 'level_2'] = df['level_2'].map(mappings)

#df

	Name	level_1	level_2	level_3
0	Tom	    a	    pe60	-2
1	nick	b	    pe71	-1
2	krish	a	    pe71	4
3	jack	b	    pe61	6
4	bob	    a	    pe60	-4

Please note that this check conditional value of 'level_1 against a constant value of 'b'. If this value is also dependent on the 'level_2', the solution will be slightly different.