从熊猫数据框中随机删除多个行，但有例外

Question

I'm attempting to remove x number of rows from a df with an exception of a certain row .

df :

                  Main             Ing 
0                  A              Apple            
1                  B              Bread            
2                  Z              Cheese            
3                  E              Egg            
4                  D              Dough           
5                  X              Pasta  
etc. 

I've attempted the following, with the intention of removing one row :

r = randint(0, df.shape[0])
df.drop(df.index[r])

However, it doesn't seem to do anything.

My goal is to randomly remove x number of rows from df, with the exception of a certain row , eg:

df.loc[df['Main'] == 'A']

---

Desired Output:

EG: If the number of rows to remove was 4 , with the exception of the row - df.loc[df['Main'] == 'A'] , the output would be:

                  Main             Ing 
0                  A              Apple                      
2                  Z              Cheese                                
etc. 

Answer 1

Use pd.DataFrame.sample

df.drop(df[df.Main != 'A'].sample(4).index)

  Main     Ing
0    A   Apple
2    Z  Cheese

Answer 2

Random pick index from 1 : n (PS: index = 0 is the row you want to keep)

import random
df.drop(random.sample(range(1, df.shape[0]), 4),0)

Out[212]: 
  Main    Ing
0    A  Apple
4    D  Dough