如何按WeekDay与WeekNo绘制月度发生次数折线图？

嘿，这需求很清晰，我用Python的pandas处理数据，seaborn+matplotlib来绘图，完全能满足你的要求！下面是一步步的实现方案：

步骤1：数据准备与预处理 #

首先我们把你的数据整理成DataFrame，并且统一星期几的格式并指定顺序——这很重要，不然x轴的星期会乱序显示。比如把缩写的Wed、Thursd等补全，然后设置成有序的类别：

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# 模拟你的数据（如果是真实数据，直接用pd.read_csv读取即可）
data = [
    ["2018-01-01", 214.0, "Monday", 1, 2018, 1],
    ["2018-01-02", 232.0, "Tuesday", 1, 2018, 1],
    ["2018-01-03", 147.0, "Wed", 1, 2018, 1],
    ["2018-01-04", 257.0, "Thursd", 1, 2018, 1],
    ["2018-01-05", 164.0, "Friday", 1, 2018, 1],
    ["2018-01-06", 187.0, "Saturd", 1, 2018, 1],
    ["2018-01-07", 201.0, "Sunday", 1, 2018, 1],
    ["2018-01-08", 141.0, "Monday", 2, 2018, 1],
    ["2018-01-09", 152.0, "Tuesday", 2, 2018, 1],
    ["2018-01-10", 167.0, "Wednesd", 2, 2018, 1],
    ["2018-01-15", 113.0, "Monday", 3, 2018, 1],
    ["2018-01-16", 139.0, "Tuesday", 3, 2018, 1],
    ["2018-01-17", 159.0, "Wednesd", 3, 2018, 1],
    ["2018-01-18", 202.0, "Thursd", 3, 2018, 1],
    ["2018-01-19", 207.0, "Friday", 3, 2018, 1]
]

df = pd.DataFrame(data, columns=["date", "value", "WeekDay", "WeekNo", "Year", "Month"])

# 统一星期几的名称，避免缩写导致的混乱
weekday_map = {
    "Monday": "Monday",
    "Tuesday": "Tuesday",
    "Wed": "Wednesday",
    "Wednesd": "Wednesday",
    "Thursd": "Thursday",
    "Friday": "Friday",
    "Saturd": "Saturday",
    "Sunday": "Sunday"
}
df["WeekDay"] = df["WeekDay"].map(weekday_map)

# 设置星期的顺序，确保x轴从周一到周日排列
weekday_order = ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]
df["WeekDay"] = pd.Categorical(df["WeekDay"], categories=weekday_order, ordered=True)

步骤2：绘制折线图 #

用seaborn.lineplot可以轻松实现按WeekNo区分颜色的折线，自动生成图例，代码非常简洁：

# 设置绘图风格
sns.set_style("whitegrid")

# 创建画布
plt.figure(figsize=(10, 6))

# 绘制折线图：x轴是WeekDay，y轴是value，按WeekNo区分颜色
sns.lineplot(
    data=df,
    x="WeekDay",
    y="value",
    hue="WeekNo",  # 按周数区分颜色
    marker="o",    # 显示每个数据点
    linewidth=2    # 设置折线宽度
)

# 添加标题和轴标签
plt.title("2018年1月各周每日发生次数变化", fontsize=14)
plt.xlabel("星期", fontsize=12)
plt.ylabel("发生次数", fontsize=12)

# 调整图例位置，避免遮挡图形
plt.legend(title="周数", bbox_to_anchor=(1.05, 1), loc="upper left")

# 自动调整布局，防止标签被截断
plt.tight_layout()

# 显示图形
plt.show()

效果说明 #

• 不同的WeekNo会用不同颜色的折线表示，图例里会标注对应的周数
• x轴严格按照周一到周日的顺序排列，不会出现乱序
• 每个数据点用圆形标记，方便查看具体数值位置
• 如果你的数据里有缺失的日期（比如1月11-14日），对应的位置不会有折线连接，完全符合实际数据情况

内容的提问来源于stack exchange，提问作者J.Doe