hw2

def plot_pivot_table(pivot_table):
    plt.figure(figsize=(14, 11))
    sns.heatmap(pivot_table, cmap="YlGnBu", annot=True,
                fmt='.3g', annot_kws={"size": 14, "fontsize": 14})
    plt.xticks(fontsize=15)
    plt.yticks(rotation=0, fontsize=15)
    plt.xlabel('Bucket', size=18)
    plt.ylabel('Hour', fontsize=18)
    plt.title('Gender analysis per bucket and hour', fontsize=20)
    plt.show()

negative = transactions[transactions.amount<0].amount

transactions['amount_bucket'] = pd.cut(negative, 5, labels=['Very High', 'High', 'Middle', 'Low', 'Very Low'])
transactions

transactions['amount_bucket'] = transactions['amount_bucket'].cat.add_categories('Income').fillna('Income')

transactions['tr_hour'] = transactions['tr_datetime'].apply(lambda x: x.split()[1].split(':')[0])

tp = transactions.pivot_table(['gender'], index=['tr_hour'], columns=['amount_bucket'])

plot_pivot_table(tp)