本文共 3481 字，大约阅读时间需要 11 分钟。

甘特图是一种常见的项目管理工具，用于直观地展示项目任务的时间分布和进度。在项目管理中，甘特图通过将任务按时间轴排列，便于团队成员了解各个任务的时间安排和完成情况。常用的绘制工具包括matplotlib和plotly，这两种工具各有特点，适用于不同的需求。

matplotlib是一种功能强大的绘图库，尤其适合制作静态的甘特图。以下是使用matplotlib绘制甘特图的示例代码：

import matplotlib.pyplot as plt
import pandas as pd
import matplotlib.dates as mdates
tasks = [
    {"Task": "Task A", "Start": "2024-01-01", "End": "2024-01-05"},
    {"Task": "Task B", "Start": "2024-01-02", "End": "2024-01-07"},
    {"Task": "Task C", "Start": "2024-01-08", "End": "2024-01-10"},
]
df = pd.DataFrame(tasks)
df["Start"] = pd.to_datetime(df["Start"])
df["End"] = pd.to_datetime(df["End"])
fig, ax = plt.subplots(figsize=(10, 6))
for index, row in df.iterrows():
    ax.barh(row["Task"], (row["End"] - row["Start"]).days, left=row["Start"], color="skyblue")
ax.xaxis.set_major_locator(mdates.DayLocator(interval=1))
ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m-%d"))
plt.title("Gantt Chart")
plt.xlabel("Date")
plt.ylabel("Tasks")
plt.show()

如上代码所示，matplotlib通过barh函数绘制水平条形图，Start和End字段用于确定任务的时间范围。日期轴通过DateLocator和DateFormatter设置为每天一个刻度，确保时间轴清晰易读。

如果需要更复杂的甘特图，例如带有不同的颜色来区分任务，可以在tasks数据结构中添加Color字段：

tasks = [
    {
        "Task": "Task A",
        "Start": "2024-01-01",
        "End": "2024-01-05",
        "Color": "skyblue"
    },
    {
        "Task": "Task B",
        "Start": "2024-01-02",
        "End": "2024-01-07",
        "Color": "lightgreen"
    },
    {
        "Task": "Task C",
        "Start": "2024-01-08",
        "End": "2024-01-10",
        "Color": "lightcoral"
    }
]

修改后的代码如下：

import matplotlib.pyplot as plt
import pandas as pd
import matplotlib.dates as mdates
tasks = [
    {
        "Task": "Task A",
        "Start": "2024-01-01",
        "End": "2024-01-05",
        "Color": "skyblue"
    },
    {
        "Task": "Task B",
        "Start": "2024-01-02",
        "End": "2024-01-07",
        "Color": "lightgreen"
    },
    {
        "Task": "Task C",
        "Start": "2024-01-08",
        "End": "2024-01-10",
        "Color": "lightcoral"
    }
]
df = pd.DataFrame(tasks)
df["Start"] = pd.to_datetime(df["Start"])
df["End"] = pd.to_datetime(df["End"])
fig, ax = plt.subplots(figsize=(10, 6))
for index, row in df.iterrows():
    ax.barh(row["Task"], (row["End"] - row["Start"]).days, left=row["Start"], color=row["Color"])
ax.xaxis.set_major_locator(mdates.DayLocator(interval=1))
ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m-%d"))
plt.title("Gantt Chart with Different Colors")
plt.xlabel("Date")
plt.ylabel("Tasks")
plt.show()

如果你想使用交互式的甘特图工具，plotly是一个更好的选择。plotly可以生成动态的交互式图表，适合在线展示。

以下是使用plotly绘制甘特图的示例代码：

import plotly.express as px
import pandas as pd
tasks = [
    {
        "Task": "Task A1",
        "Start": "2024-01-01",
        "Finish": "2024-01-05",
        "Group": "Group A"
    },
    {
        "Task": "Task A2",
        "Start": "2024-01-06",
        "Finish": "2024-01-10",
        "Group": "Group A"
    },
    {
        "Task": "Task B1",
        "Start": "2024-01-02",
        "Finish": "2024-01-07",
        "Group": "Group B"
    },
    {
        "Task": "Task B2",
        "Start": "2024-01-08",
        "Finish": "2024-01-12",
        "Group": "Group B"
    }
]
df = pd.DataFrame(tasks)
fig = px.timeline(df, x_start="Start", x_end="Finish", y="Task", color="Group", title="Gantt Chart with Groups")
fig.update_yaxes(categoryorder="total ascending")
fig.show()

如上代码所示，plotly通过px.timeline函数绘制交互式甘特图，color参数用于指定不同的组别颜色，categoryorder参数用于设置y轴的分类顺序。

通过以上代码示例，可以轻松创建出美观且功能完善的甘特图，满足不同项目管理需求。

转载地址：http://ehofk.baihongyu.com/