python-3.x - 如何使用 matplotlib.pyplot 在条形图和数据表之间创建空间？

Question

我一直在寻找如何使用 matplotlib.pyplot 在条形图和表格之间添加空间的几个小时，但我还没有找到关于如何正确显示布局的解决方案。目前表格顶部与条形图 x 轴标题相冲突，表格底部超出图形。figsize我尝试使用bbox,使数字变大subplots_adjust，plt.tight_layout()但没有任何效果。任何帮助表示赞赏。

def plot_bar(df, *args):
    df = pd.DataFrame([{'OPEN': 4, 'CLOSED': 139, 'DATE': '2019-01-01'}, {'OPEN': 0, 'CLOSED': 139, 'DATE': '2019-02-01'}, {'OPEN': 1, 'CLOSED': 124, 'DATE': '2019-03-01'}, {'OPEN': 4, 'CLOSED': 127, 'DATE': '2019-04-01'}, {'OPEN': 1, 'CLOSED': 84, 'DATE': '2019-05-01'}, {'OPEN': 6, 'CLOSED': 113, 'DATE': '2019-06-01'}, {'OPEN': 0, 'CLOSED': 123, 'DATE': '2019-07-01'}, {'OPEN': 2, 'CLOSED': 109, 'DATE': '2019-08-01'}, {'OPEN': 0, 'CLOSED': 107, 'DATE': '2019-09-01'}, {'OPEN': 7, 'CLOSED': 119, 'DATE': '2019-10-01'}, {'OPEN': 2, 'CLOSED': 82, 'DATE': '2019-11-01'}, {'OPEN': 4, 'CLOSED': 83, 'DATE': '2019-12-01'}, {'OPEN': 12, 'CLOSED': 112, 'DATE': '2020-01-01'}, {'OPEN': 10, 'CLOSED': 89, 'DATE': '2020-02-01'}, {'OPEN': 31, 'CLOSED': 64, 'DATE': '2020-03-01'}])
    df["DATE"] = pd.to_datetime(df["DATE"])
    df['DATE'] = df['DATE'].apply(lambda x: [x.month, x.year])
    df['DATE'] = df['DATE'].apply(lambda x: f'{calendar.month_abbr[x[0]]}-{x[1]}')

    ax = df.plot.bar(x=args[0]['x'], y=args[0]['y'], figsize=(15, 7))
    for i, v in enumerate(df['OPEN']):
        ax.text(i - .20, v + 1, str(v), color='blue', fontweight='bold')
    for i, v in enumerate(df['CLOSED']):
        ax.text(i - .20, v + 1, str(v), color='orange', fontweight='bold')

    plt.title('Open vs Closed Tickets')
    plt.xlabel('Time')
    plt.ylabel('Tickets')

    table_columns = df['DATE'].values.tolist()
    open = df['OPEN'].values.tolist()
    closed = df['CLOSED'].values.tolist()
    table_data = [open, closed]
    table_rows = df.columns.values.tolist()[0:2]
    plt.table(cellText=table_data, rowLabels=table_rows, colLabels=table_columns, loc='bottom',
              bbox=[0, -0.250, 1, 0.2])

    plt.tight_layout()

    plt.show()

    return

回答 Diziet Asahi：我进行了这 2 项更改，但不知何故我的桌子仍然被切成两半，这太令人沮丧了。

标签： python-3.xmatplotlib

Answer 1

一个可能的问题是您必须使用after（否则，tight_layout 将撤消您对 subplots_adjust 所做的操作）。这将改变绘图的大小并为下表腾出更多空间。增加值以满足您的需要，该值以图形的分数给出，因此将图的底部定位在图形高度的 20% 处。plt.subplots_adjust(bottom=xxx) tight_layout()xxxbottom=0.2

另一个问题是您正在使用plt.table()它来让桌子“粘”在轴上。如果将表格放在轴下方，则基本上应该替换 x 轴标签。但是您必须在使用loc=（自动放置）或bbox=（手动放置）之间进行选择。您不能同时使用两者。

这是做这两件事的结果：

import calendar
df = pd.DataFrame([{'OPEN': 4, 'CLOSED': 139, 'DATE': '2019-01-01'}, {'OPEN': 0, 'CLOSED': 139, 'DATE': '2019-02-01'}, {'OPEN': 1, 'CLOSED': 124, 'DATE': '2019-03-01'}, {'OPEN': 4, 'CLOSED': 127, 'DATE': '2019-04-01'}, {'OPEN': 1, 'CLOSED': 84, 'DATE': '2019-05-01'}, {'OPEN': 6, 'CLOSED': 113, 'DATE': '2019-06-01'}, {'OPEN': 0, 'CLOSED': 123, 'DATE': '2019-07-01'}, {'OPEN': 2, 'CLOSED': 109, 'DATE': '2019-08-01'}, {'OPEN': 0, 'CLOSED': 107, 'DATE': '2019-09-01'}, {'OPEN': 7, 'CLOSED': 119, 'DATE': '2019-10-01'}, {'OPEN': 2, 'CLOSED': 82, 'DATE': '2019-11-01'}, {'OPEN': 4, 'CLOSED': 83, 'DATE': '2019-12-01'}, {'OPEN': 12, 'CLOSED': 112, 'DATE': '2020-01-01'}, {'OPEN': 10, 'CLOSED': 89, 'DATE': '2020-02-01'}, {'OPEN': 31, 'CLOSED': 64, 'DATE': '2020-03-01'}])
df["DATE"] = pd.to_datetime(df["DATE"])
df['DATE'] = df['DATE'].apply(lambda x: [x.month, x.year])
df['DATE'] = df['DATE'].apply(lambda x: f'{calendar.month_abbr[x[0]]}-{x[1]}')

ax = df.plot.bar(x='DATE', y=['OPEN','CLOSED'], figsize=(15, 7))
for i, v in enumerate(df['OPEN']):
    ax.text(i - .20, v + 1, str(v), color='blue', fontweight='bold')
for i, v in enumerate(df['CLOSED']):
    ax.text(i - .20, v + 1, str(v), color='orange', fontweight='bold')

plt.title('Open vs Closed Tickets')
plt.ylabel('Tickets')

#remove all x-labels since the table will be used instead
plt.xlabel('')
plt.xticks([])


table_columns = df['DATE'].values.tolist()
open = df['OPEN'].values.tolist()
closed = df['CLOSED'].values.tolist()
table_data = [open, closed]
table_rows = df.columns.values.tolist()[0:2]
plt.table(cellText=table_data, rowLabels=table_rows, colLabels=table_columns, loc='bottom')

plt.tight_layout()
plt.subplots_adjust(bottom=0.1)

plt.show()