python - 为多列绘制多个条形图

Question

我有一个与下表大致相似的数据集。
我需要为每列创建一个条形图 TS1至 TS5计算该列中每个项目的数量。这些项目是以下之一:NOT_SEEN NOT_ABLE HIGH_BAR和 110 之间的数值和 140由 2 分隔(所以 110 、 112 、 114 等)。
我找到了一种方法可以很好地做到这一点，但我要问的是是否有办法创建循环或其他东西，这样我就不必将相同的代码复制粘贴 5 次(对于 5 列)？
这是我尝试过和工作的:

num_range = list(range(110,140, 2))
OUTCOMES = ['NOT_SEEN', 'NOT_ABLE', 'HIGH_BAR']
OUTCOMES.extend([str(num) for num in num_range])
OUTCOMES = CategoricalDtype(OUTCOMES, ordered = True)

fig, ax =plt.subplots(2, 3, sharey=True)
fig.tight_layout(pad=3)

下面是我复制了 5 次并且只更改了标题( Testing 1 、 Testing 2 等)和 TS1 的内容TS2 ..(在第一行)。

df["outcomes"] = df["TS1"].astype(OUTCOMES)
bpt=sns.countplot(x= "outcomes", data=df, palette='GnBu', ax=ax[0,0])
plt.setp(bpt.get_xticklabels(), rotation=60, size=6, ha='right')
bpt.set(xlabel='')
bpt.set_title('Testing 1')

然后下面的代码在上面的“5”个实例下面。

ax[1,2].set_visible(False)
plt.show()

我相信有一种方法可以更好地做到这一点，但我对这一切都不熟悉。
另外，我需要确保条形图的条形按从左到右的顺序排列为:NOT_SEEN NOT_ABLE HIGH_BAR和 110 , 112 , 114等等
使用python 2.7(不幸的是不是我的选择)和pandas 0.24.2。

+----+------+------+----------+----------+----------+----------+----------+
| ID | VIEW | YEAR | TS1      | TS2      | TS3      | TS4      | TS5      |
+----+------+------+----------+----------+----------+----------+----------+
| AA | NO   | 2005 |          | 134      |          | HIGH_BAR |          |
+----+------+------+----------+----------+----------+----------+----------+
| AB | YES  | 2015 |          |          | NOT_SEEN |          |          |
+----+------+------+----------+----------+----------+----------+----------+
| AB | YES  | 2010 | 118      |          |          |          | NOT_ABLE |
+----+------+------+----------+----------+----------+----------+----------+
| BB | NO   | 2020 |          |          |          |          |          |
+----+------+------+----------+----------+----------+----------+----------+
| BA | YES  | 2020 |          |          |          | NOT_SEEN |          |
+----+------+------+----------+----------+----------+----------+----------+
| AA | NO   | 2010 |          |          |          |          |          |
+----+------+------+----------+----------+----------+----------+----------+
| BA | NO   | 2015 |          |          |          |          | 132      |
+----+------+------+----------+----------+----------+----------+----------+
| BB | YES  | 2010 |          | HIGH_BAR |          | 140      | NOT_ABLE |
+----+------+------+----------+----------+----------+----------+----------+
| AA | YES  | 2020 |          |          |          |          |          |
+----+------+------+----------+----------+----------+----------+----------+
| AB | NO   | 2010 |          |          |          | 112      |          |
+----+------+------+----------+----------+----------+----------+----------+
| AB | YES  | 2015 |          |          | NOT_ABLE |          | HIGH_BAR |
+----+------+------+----------+----------+----------+----------+----------+
| BB | NO   | 2020 |          |          |          | 145      |          |
+----+------+------+----------+----------+----------+----------+----------+
| BA | NO   | 2015 |          | 110      |          |          |          |
+----+------+------+----------+----------+----------+----------+----------+
| AA | YES  | 2010 | HIGH_BAR |          |          | NOT_SEEN |          |
+----+------+------+----------+----------+----------+----------+----------+
| BA | YES  | 2015 |          |          |          |          |          |
+----+------+------+----------+----------+----------+----------+----------+
| AA | NO   | 2020 |          |          |          | 118      |          |
+----+------+------+----------+----------+----------+----------+----------+
| BA | YES  | 2015 |          | 180      | NOT_ABLE |          |          |
+----+------+------+----------+----------+----------+----------+----------+
| BB | YES  | 2020 |          | NOT_SEEN |          |          | 126      |
+----+------+------+----------+----------+----------+----------+----------+

Answer 1

您可以将绘图线放在一个函数中，并在 for 循环中调用它，在每次迭代中自动更改列、标题和轴:

fig, axes =plt.subplots(2, 3, sharey=True)
fig.tight_layout(pad=3)

def plotting(column, title, ax):
    df["outcomes"] = df[column].astype(OUTCOMES)
    bpt=sns.countplot(x= "outcomes", data=df, palette='GnBu', ax=ax)
    plt.setp(bpt.get_xticklabels(), rotation=60, size=6, ha='right')
    bpt.set(xlabel='')
    bpt.set_title(title)

columns = ['TS1', 'TS2', 'TS3', 'TS4', 'TS5']
titles = ['Testing 1', 'Testing 2', 'Testing 3', 'Testing 4', 'Testing 5']

for column, title, ax in zip(columns, titles, axes.flatten()):
    plotting(column, title, ax)

axes[1,2].set_visible(False)

plt.show()