index  country   value1   value2   value3
  0      USA      6         5        4
  1      USA      4         7        3
  2      USA      3         2        1
  3      CAN      4         5        7
  4      CAN      10        8        6

index   USA     CAN
   0      6       4
   1      4       10
   2      3       NaN

column = ['USA', 'CAN']
df_value1 = pd.DataFrame(columns=column)
temp = df['value1'].where(df['country']=='USA').dropna()
df_value1['USA'] = temp
temp = df['value1'].where(df['country']=='CAN').dropna()
pd.concat([df_value1, temp], axis=1, ignore_index=True)