pandas count data in row with specific condition

We can sum to count values where equal to P or p on axis=1:

df['Total'] = (df.eq('P') | df.eq('p')).sum(axis=1)

Or with isin:

df['Total'] = df.isin(['P', 'p']).sum(axis=1)

If needed we can select specific columns first:

filtered = df[['c1', 'c3', 'c4']]
df['Total'] = (filtered.eq('P') | filtered.eq('p')).sum(axis=1)

Or:

filtered = df[['c1', 'c3', 'c4']]
df['Total'] = filtered.isin(['P', 'p']).sum(axis=1)

All options produce df:

          Data c1 c2 c3 c4  Total
0  ABCDEFG01AB  P     A  A      1
1  ABCDEFG02AB  A     P  P      2
2  ABCDEFG03AB  p     A  P      2
3  ABCDEFG04AB  P     P  p      3
4  ABCDEFG05AB  A     p  A      1
5  ABCDEFG06AB  A     A  A      0

DataFrame and imports:

import pandas as pd

df = pd.DataFrame({
    'Data': ['ABCDEFG01AB', 'ABCDEFG02AB', 'ABCDEFG03AB', 'ABCDEFG04AB',
             'ABCDEFG05AB', 'ABCDEFG06AB'],
    'c1': ['P', 'A', 'p', 'P', 'A', 'A'],
    'c2': ["", "", "", "", "", ""],
    'c3': ['A', 'P', 'A', 'P', 'p', 'A'], 'c4': ['A', 'P', 'P', 'p', 'A', 'A'],
    'Total': [0, 0, 0, 0, 0, 0]
})