Plot matplotlib中两个日期之间的线段

Question

给定以下数据：

dt = pd.DataFrame.from_dict(
    {
        "thing": {0: "A", 1: "B", 2: "C"},
        "min": {
            0: "2021-11-01 00:00:00+00:00",
            1: "2021-11-01 00:00:00+00:00",
            2: "2021-11-01 00:00:00+00:00",
        },
        "max": {
            0: "2021-11-02 00:00:00+00:00",
            1: "2021-11-05 00:00:00+00:00",
            2: "2021-11-07 00:00:00+00:00",
        },
    }
).assign(
    min=lambda x: pd.to_datetime(x["min"]),
    max=lambda x: pd.to_datetime(x["max"]),
)

看起来像：

|    | thing   | min                       | max                       |
|---:|:--------|:--------------------------|:--------------------------|
|  0 | A       | 2021-11-01 00:00:00+00:00 | 2021-11-02 00:00:00+00:00 |
|  1 | B       | 2021-11-01 00:00:00+00:00 | 2021-11-05 00:00:00+00:00 |
|  2 | C       | 2021-11-01 00:00:00+00:00 | 2021-11-07 00:00:00+00:00 |

我想创建一个 plot，它在 y 轴上有thing ，每条线代表 x 轴上的最小值/最大值。

例如：

所以 x 轴是日期，y 轴代表每个“事物”。

Answer 1

一个选项首先用melt重塑：

import matplotlib.pyplot as plt

ax = plt.subplot()
for k, g in dt.reset_index().melt(['index', 'thing']).groupby('thing'):
    g.plot(x='value', y='index', ax=ax, label=k, marker='s')

labels = dt['thing'].unique()

ax.set_yticks(range(len(labels)), labels)
ax.invert_yaxis()

Output：

替代seaborn

import seaborn as sns

g = sns.relplot(data=dt.reset_index().melt(['index', 'thing']),
                x='value', y='index', hue='thing',
                kind='line', marker='s')
labels = dt['thing'].unique()

g.ax.set_yticks(range(len(labels)), labels)
g.ax.invert_yaxis()

g.set_xticklabels(rotation=30)

Output：

纯matplotlib

ax = plt.subplot()
for row in dt.itertuples():
    ax.plot((row.min, row.max), (row.Index,)*2, label=row.thing, marker='s')

ax.set_yticks(range(len(dt)), dt['thing'])

ax.invert_yaxis()

如果要保留行的原始顺序：

for row in dt.reset_index(drop=True).itertuples():
    ax.plot((row.min, row.max), (row.Index,)*2, label=row.thing, marker='s')

# OR

for i, row in enumerate(dt.itertuples()):
    ax.plot((row.min, row.max), (i,)*2, label=row.thing, marker='s')