我写了一段代码，在按月汇总的数据中为每年的净值创建8个子图。我尝试使用两个for循环优化代码，但我不知道如何将查询部分捆绑在pd df中。有没有办法以更好的方式重写它或优化这段长代码？
VF_data只是一个Pandas Dataframe ，其中包含每年每个月聚合的数值正值和负值。其他列是月、年、日期。
提前感谢你们！！

def plot_MTY(df, aggregate_col='NET'):   


plt.subplot(2, 4, 1)

VF_data=df.query("(YEAR == '2015')")

aggregated_target = aggregate_data(VF_data, 'DATES', aggregate_col)

plt.plot(aggregated_target, label = 'df', linestyle="-")

plt.axhline(y=0, color='b', linestyle='-')

locs, labels = plt.xticks()

plt.setp(labels, rotation=90)


plt.subplot(2, 4, 2)

VF_data=df.query("(YEAR == '2016')")

aggregated_target = aggregate_data(VF_data, 'DATES', aggregate_col)

plt.plot(aggregated_target, label = 'df', linestyle="-")

plt.axhline(y=0, color='b', linestyle='-')

locs, labels = plt.xticks()

plt.setp(labels, rotation=90)


plt.subplot(2, 4, 3)

VF_data=df.query("(YEAR == '2017')")

aggregated_target = aggregate_data(VF_data, 'DATES', aggregate_col)

plt.plot(aggregated_target, label = 'df', linestyle="-")

plt.axhline(y=0, color='b', linestyle='-')

locs, labels = plt.xticks()

plt.setp(labels, rotation=90)


plt.subplot(2, 4, 4)

VF_data=df.query("(YEAR == '2018')")

aggregated_target = aggregate_data(VF_data, 'DATES', aggregate_col)

plt.plot(aggregated_target, label = 'df', linestyle="-")

plt.axhline(y=0, color='b', linestyle='-')

locs, labels = plt.xticks()

plt.setp(labels, rotation=90)


plt.subplot(2, 4, 5)

VF_data=df.query("(YEAR == '2019')")

aggregated_target = aggregate_data(VF_data, 'DATES', aggregate_col)

plt.plot(aggregated_target, label = 'df', linestyle="-")

plt.axhline(y=0, color='b', linestyle='-')

locs, labels = plt.xticks()

plt.setp(labels, rotation=90)


plt.subplot(2, 4, 6)

VF_data=df.query("(YEAR == '2020')")

aggregated_target = aggregate_data(VF_data, 'DATES', aggregate_col)

plt.plot(aggregated_target, label = 'df', linestyle="-")

plt.axhline(y=0, color='b', linestyle='-')

locs, labels = plt.xticks()

plt.setp(labels, rotation=90)


plt.subplot(2, 4, 7)

VF_data=df.query("(YEAR == '2021')")

aggregated_target = aggregate_data(VF_data, 'DATES', aggregate_col)

plt.plot(aggregated_target, label = 'df', linestyle="-")

plt.axhline(y=0, color='b', linestyle='-')

locs, labels = plt.xticks()

plt.setp(labels, rotation=90)


plt.subplot(2, 4, 8)

VF_data=df.query("(YEAR == '2022')")

aggregated_target = aggregate_data(VF_data, 'DATES', aggregate_col)

plt.plot(aggregated_target, label = 'df', linestyle="-")

plt.axhline(y=0, color='b', linestyle='-')

locs, labels = plt.xticks()

plt.setp(labels, rotation=90)


plt.gcf().set_size_inches(15, 8)

plt.show()