10.Distribusi-kategorisasi-average-transaction-amount.py

"""
Distribusi kategorisasi average transaction amount

Selanjutnya, akan melakukan visualisasi dari distribusi kategorisasi average transaction amount. 
Kategorisasi ini dilakukan dengan mengelompokkan rata-rata besar transaksi seperti yang diperlihatkan oleh tabel berikut:
"""

plt.clf()
# Kategorisasi rata-rata besar transaksi
def f(row):
    if (row['Average_Transaction_Amount'] >= 100000 and row['Average_Transaction_Amount'] <= 200000):
        val ='1. 100.000 - 250.000'
    elif (row['Average_Transaction_Amount'] > 250000 and row['Average_Transaction_Amount'] <= 500000):
        val ='2. >250.000 - 500.000'
    elif (row['Average_Transaction_Amount'] > 500000 and row['Average_Transaction_Amount'] <= 750000):
        val = '3. >500.000 - 750.000'
    elif (row['Average_Transaction_Amount'] > 750000 and row['Average_Transaction_Amount'] <= 1000000):
        val = '4. >750.000 - 1.000.000'
    elif (row['Average_Transaction_Amount'] > 1000000 and row['Average_Transaction_Amount'] <= 2500000):
        val = '5. >1.000.000 - 2.500.000'
    elif (row['Average_Transaction_Amount'] > 2500000 and row['Average_Transaction_Amount'] <= 5000000):
        val = '6. >2.500.000 - 5.000.000'
    elif (row['Average_Transaction_Amount'] > 5000000 and row['Average_Transaction_Amount'] <= 10000000):
        val = '7. >5.000.000 - 10.000.000'
    else:
        val = '8. >10.000.000'
    return val
# Tambahkan kolom baru
df['Average_Transaction_Amount_Group'] = df.apply(f, axis=1)

df_year = df.groupby(['Average_Transaction_Amount_Group'])['Customer_ID'].count()
df_year.plot(x='Average_Transaction_Amount_Group', y='Customer_ID', kind='bar', 
             title='Customer Distribution by Average Transaction Amount Group')
plt.xlabel('Average Transaction Amount Group')
plt.ylabel('Num of Customer')
plt.tight_layout()
#plt.savefig("averageTransaction.png", format='png')
plt.show()