df  Receiver Payer   Amount
0    0045    xx04     300
1    5400    zz03     600
2    5400    0045     100
3    xx04    5400     400

df1   ID     In_0    In_1    Out_0  Out_1
0    0045     0      300      100    0
1    5400    100     600       0    400
2    zz03     0       0       600    0
3    xx04    400      0       300    0

df.groupby(['Receiver', 'Payer'], as_index = False)['Amount'].sum()

df_out = df.rename(columns={'Receiver':'IN','Payer':'OUT'})

df_out['IN_TYPE'] = df_out['OUT'].str.contains(r'D').astype(int).astype(str)
df_out['OUT_TYPE'] = df_out['IN'].str.contains(r'D').astype(int).astype(str)

df_out = df_out.melt(['df','Amount','IN_TYPE','OUT_TYPE'], value_name='ID')

df_out['Cols'] = df_out['variable']+'_'+np.where(df_out['variable']=='IN',df_out['IN_TYPE'],df_out['OUT_TYPE'])

df_out = df_out.set_index(['ID','Cols'])['Amount'].unstack().fillna(0).reset_index()
print(df_out)

Cols    ID   IN_0   IN_1  OUT_0  OUT_1
0     0045    0.0  300.0  100.0    0.0
1     5400  100.0  600.0    0.0  400.0
2     xx04  400.0    0.0  300.0    0.0
3     zz03    0.0    0.0  600.0    0.0