为多列数据绘制多个条形图

Question

我有一个类似下面表格的数据集。我需要为每个列 TS1 到TS5 创建一个条形图，计算该列中每个项的数量。这些项是以下之一：NOT_SEEN NOT_ABLE HIGH_BAR 和介于110和140之间的数字值，以2为间隔（因此为110，112，114等）。

我已经找到了一种行之有效的方法，但我的问题是是否有一种创建循环或其他东西的方法，这样我就不必复制并粘贴相同的代码5次（对于这5个列）？

这是我尝试过且有效的：

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)

以下是我复制了5次并仅更改标题（Testing 1，Testing 2等）和第一行中的TS1、TS2等的内容。

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')

接下来的代码位于上述"5"个实例之后。

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

我相信有更好的方法来做这件事，但我对这些都很陌生。

同时，我需要确保 barplot 的柱按照以下顺序从左到右排列：NOT_SEEN NOT_ABLE HIGH_BAR 以及 110、112、114 等等。

使用 Python 2.7（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      |
+----+------+------+----------+----------+----------+----------+----------+

- getting it

Answer 1

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

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()

- Zephyr