如何使用 Python 调用小红书笔记评论 API 时进行数据可视化？

pip install requests matplotlib pandas

import requests
import matplotlib.pyplot as plt
import time

# ===================== 配置 =====================
ACCESS_TOKEN = "你的token"
NOTE_ID = "笔记ID"
# =================================================

def get_xhs_comments(note_id, cursor=""):
    """获取评论"""
    url = f"https://api.xiaohongshu.com/v2/notes/{note_id}/comments"
    headers = {"Authorization": f"Bearer {ACCESS_TOKEN}"}
    params = {"cursor": cursor, "page_size": 50, "sort": "time"}
    resp = requests.get(url, headers=headers, params=params)
    return resp.json()

def parse_comments(json_data):
    """解析评论数据"""
    comments = json_data.get("data", {}).get("comments", [])
    result = []
    for c in comments:
        result.append({
            "like": c.get("like_count", 0),
            "time": c.get("create_time", 0),
            "content_len": len(c.get("content", "")),
            "username": c.get("user", {}).get("nickname", "")
        })
    return result

# 获取并解析
data = get_xhs_comments(NOTE_ID)
comment_list = parse_comments(data)

# 提取数据用于画图
likes = [c["like"] for c in comment_list]
times = [c["time"] for c in comment_list]
lengths = [c["content_len"] for c in comment_list]

# ===================== 可视化 =====================
plt.rcParams["font.sans-serif"] = ["SimHei"]  # 显示中文
plt.rcParams["axes.unicode_minus"] = False

# 1. 点赞数分布柱状图
plt.figure(figsize=(12,5))
plt.subplot(1,3,1)
plt.bar(range(len(likes)), likes, color="#ff5c5c")
plt.title("评论点赞数")
plt.xlabel("评论序号")
plt.ylabel("点赞数")

# 2. 评论长度分布
plt.subplot(1,3,2)
plt.hist(lengths, bins=10, color="#5ac8fa")
plt.title("评论长度分布")
plt.xlabel("字数")
plt.ylabel("条数")

# 3. 评论时间折线（时间戳转时间）
time_str = [time.strftime("%m-%d %H:%M", time.localtime(t)) for t in times]
plt.subplot(1,3,3)
plt.plot(time_str, likes, marker="o", color="#34c759")
plt.title("点赞-时间趋势")
plt.xticks(rotation=45)

plt.tight_layout()
plt.show()

pip install wordcloud jieba

from wordcloud import WordCloud
import jieba

# 拼接所有评论内容
contents = [c.get("content", "") for c in json_data["data"]["comments"]]
text = " ".join(contents)
words = " ".join(jieba.lcut(text))

wc = WordCloud(
    font_path="msyh.ttc",  # Windows
    # font_path="PingFang.ttc"  # Mac
    width=800, height=400, background_color="white"
)
wc.generate(words)
wc.to_file("xhs_wordcloud.png")

plt.imshow(wc)
plt.axis("off")
plt.show()