（5）所有角色数据分析页面的构建-5

弦之森2023-08-15 21:41

所有角色数据分析页面，包括一个时间轴柱状图、六个散点图、六个柱状图(每个属性角色的生命值/防御力/攻击力的max与min的对比)。

python 复制代码 
"""绘图"""
from pyecharts.charts import Timeline
from find_type import FindType
import pandas as pd
from pyecharts.charts import Bar, Page
from pyecharts import options as opts
from pyecharts.charts import Scatter


# 全部角色
def x():
    tl = Timeline()
    for i in ["火", "水", "冰", "风", "雷", "岩"]:
        role_things = pd.read_excel("C:/Users/YHT/Desktop/项目/原神各属性角色信息.xlsx", header=0, index_col=0)
        role_things = role_things.fillna(axis=0, method="ffill")
        things_list = role_things.groupby("属性").groups
        print(role_things.loc[things_list[i]]["角色"])
        bar = (
            Bar()
            .add_xaxis(list(role_things.loc[things_list[i]]["角色"]))
            .add_yaxis("生命值", list(role_things.loc[things_list[i]]["生命值"]))
            .add_yaxis("防御力", list(role_things.loc[things_list[i]]["防御力"]))
            .add_yaxis("攻击力", list(role_things.loc[things_list[i]]["攻击力"]))
            .set_global_opts(title_opts=opts.TitleOpts())
        )
        tl.add(bar, f"{i}属性")
    return tl


# 火
def y():
    return_things = FindType("火").find_type()
    df = return_things.drop(["属性", "突破加成"], axis=1)
    list_source = [["produce", "max", "min"]]
    print(df)
    list_source = list_source + [["生命值"] + list(df[df["生命值"] == df["生命值"].max()]["生命值"]) + list(
        df[df["生命值"] == df["生命值"].max()]["生命值"])] + [
                      ["防御力"] + list(df[df["防御力"] == df["防御力"].max()]["防御力"]) + list(
                          df[df["防御力"] == df["防御力"].max()]["防御力"])] + [
                      ["攻击力"] + list(df[df["攻击力"] == df["攻击力"].max()]["攻击力"]) + list(
                          df[df["攻击力"] == df["攻击力"].max()]["攻击力"])]
    c = (
        Bar()
        .add_dataset(
            source=list_source
        )
        .add_yaxis(series_name="max", y_axis=[])
        .add_yaxis(series_name="min", y_axis=[])
        .set_global_opts(
            title_opts=opts.TitleOpts(title="火属性"),
            xaxis_opts=opts.AxisOpts(type_="category"),
        )
    )
    return c



# 水
def z():
    return_things = FindType("水").find_type()
    df = return_things.drop(["属性", "突破加成"], axis=1)
    list_source = [["produce", "max", "min"]]
    print(df)
    list_source = list_source + [["生命值"] + list(df[df["生命值"] == df["生命值"].max()]["生命值"]) + list(
        df[df["生命值"] == df["生命值"].max()]["生命值"])] + [
                      ["防御力"] + list(df[df["防御力"] == df["防御力"].max()]["防御力"]) + list(
                          df[df["防御力"] == df["防御力"].max()]["防御力"])] + [
                      ["攻击力"] + list(df[df["攻击力"] == df["攻击力"].max()]["攻击力"]) + list(
                          df[df["攻击力"] == df["攻击力"].max()]["攻击力"])]
    c = (
        Bar()
        .add_dataset(
            source=list_source
        )
        .add_yaxis(series_name="max", y_axis=[])
        .add_yaxis(series_name="min", y_axis=[])
        .set_global_opts(
            title_opts=opts.TitleOpts(title="水属性"),
            xaxis_opts=opts.AxisOpts(type_="category"),
        )
    )
    return c



# 冰
def a():
    return_things = FindType("冰").find_type()
    df = return_things.drop(["属性", "突破加成"], axis=1)
    list_source = [["produce", "max", "min"]]
    print(df)
    list_source = list_source + [["生命值"] + list(df[df["生命值"] == df["生命值"].max()]["生命值"]) + list(
        df[df["生命值"] == df["生命值"].max()]["生命值"])] + [
                      ["防御力"] + list(df[df["防御力"] == df["防御力"].max()]["防御力"]) + list(
                          df[df["防御力"] == df["防御力"].max()]["防御力"])] + [
                      ["攻击力"] + list(df[df["攻击力"] == df["攻击力"].max()]["攻击力"]) + list(
                          df[df["攻击力"] == df["攻击力"].max()]["攻击力"])]
    c = (
        Bar()
        .add_dataset(
            source=list_source
        )
        .add_yaxis(series_name="max", y_axis=[])
        .add_yaxis(series_name="min", y_axis=[])
        .set_global_opts(
            title_opts=opts.TitleOpts(title="冰属性"),
            xaxis_opts=opts.AxisOpts(type_="category"),
        )
    )
    return c



# 风
def b():
    return_things = FindType("风").find_type()
    df = return_things.drop(["属性", "突破加成"], axis=1)
    list_source = [["produce", "max", "min"]]
    print(df)
    list_source = list_source + [["生命值"] + list(df[df["生命值"] == df["生命值"].max()]["生命值"]) + list(
        df[df["生命值"] == df["生命值"].max()]["生命值"])] + [
                      ["防御力"] + list(df[df["防御力"] == df["防御力"].max()]["防御力"]) + list(
                          df[df["防御力"] == df["防御力"].max()]["防御力"])] + [
                      ["攻击力"] + list(df[df["攻击力"] == df["攻击力"].max()]["攻击力"]) + list(
                          df[df["攻击力"] == df["攻击力"].max()]["攻击力"])]
    c = (
        Bar()
        .add_dataset(
            source=list_source
        )
        .add_yaxis(series_name="max", y_axis=[])
        .add_yaxis(series_name="min", y_axis=[])
        .set_global_opts(
            title_opts=opts.TitleOpts(title="风属性"),
            xaxis_opts=opts.AxisOpts(type_="category"),
        )
    )
    return c



# 雷
def c():
    return_things = FindType("雷").find_type()
    df = return_things.drop(["属性", "突破加成"], axis=1)
    list_source = [["produce", "max", "min"]]
    print(df)
    list_source = list_source + [["生命值"] + list(df[df["生命值"] == df["生命值"].max()]["生命值"]) + list(
        df[df["生命值"] == df["生命值"].max()]["生命值"])] + [
                      ["防御力"] + list(df[df["防御力"] == df["防御力"].max()]["防御力"]) + list(
                          df[df["防御力"] == df["防御力"].max()]["防御力"])] + [
                      ["攻击力"] + list(df[df["攻击力"] == df["攻击力"].max()]["攻击力"]) + list(
                          df[df["攻击力"] == df["攻击力"].max()]["攻击力"])]
    c = (
        Bar()
        .add_dataset(
            source=list_source
        )
        .add_yaxis(series_name="max", y_axis=[])
        .add_yaxis(series_name="min", y_axis=[])
        .set_global_opts(
            title_opts=opts.TitleOpts(title="雷属性"),
            xaxis_opts=opts.AxisOpts(type_="category"),
        )
    )
    return c


# 岩
def d():
    return_things = FindType("岩").find_type()
    df = return_things.drop(["属性", "突破加成"], axis=1)
    list_source = [["produce", "max", "min"]]
    print(df)
    list_source = list_source + [["生命值"] + list(df[df["生命值"] == df["生命值"].max()]["生命值"]) + list(
        df[df["生命值"] == df["生命值"].max()]["生命值"])] + [
                      ["防御力"] + list(df[df["防御力"] == df["防御力"].max()]["防御力"]) + list(
                          df[df["防御力"] == df["防御力"].max()]["防御力"])] + [
                      ["攻击力"] + list(df[df["攻击力"] == df["攻击力"].max()]["攻击力"]) + list(
                          df[df["攻击力"] == df["攻击力"].max()]["攻击力"])]
    c = (
        Bar()
        .add_dataset(
            source=list_source
        )
        .add_yaxis(series_name="max", y_axis=[])
        .add_yaxis(series_name="min", y_axis=[])
        .set_global_opts(
            title_opts=opts.TitleOpts(title="岩属性"),
            xaxis_opts=opts.AxisOpts(type_="category"),
        )
    )
    return c



def e():
    role_things = pd.read_excel("C:/Users/YHT/Desktop/项目/原神各属性角色信息.xlsx", header=0, index_col=0)
    role_things = role_things.fillna(axis=0, method="ffill")
    print(role_things)
    return_things = FindType("岩").find_type()
    df = return_things.drop(["属性", "突破加成"], axis=1)
    Name = df["角色"]
    Hp = df["生命值"]
    Def = df["防御力"]
    Atk = df["攻击力"]
    c = (
        Scatter()
        .add_xaxis(list(Name))
        .add_yaxis("生命值", list(Hp))
        .add_yaxis("防御力", list(Def))
        .add_yaxis("攻击力", list(Atk))
        .set_global_opts(
            title_opts=opts.TitleOpts(title="岩属性"),
            visualmap_opts=opts.VisualMapOpts(type_="size", max_=150, min_=20),
            xaxis_opts=opts.AxisOpts(axislabel_opts={"rotate": 45})
        )
    )
    return c


def f():
    role_things = pd.read_excel("C:/Users/YHT/Desktop/项目/原神各属性角色信息.xlsx", header=0, index_col=0)
    role_things = role_things.fillna(axis=0, method="ffill")
    print(role_things)
    return_things = FindType("火").find_type()
    df = return_things.drop(["属性", "突破加成"], axis=1)
    Name = df["角色"]
    Hp = df["生命值"]
    Def = df["防御力"]
    Atk = df["攻击力"]
    c = (
        Scatter()
        .add_xaxis(list(Name))
        .add_yaxis("生命值", list(Hp))
        .add_yaxis("防御力", list(Def))
        .add_yaxis("攻击力", list(Atk))
        .set_global_opts(
            title_opts=opts.TitleOpts(title="火属性"),
            visualmap_opts=opts.VisualMapOpts(type_="size", max_=150, min_=20),
            xaxis_opts=opts.AxisOpts(axislabel_opts={"rotate": 45})
        )
    )
    return c


def g():
    role_things = pd.read_excel("C:/Users/YHT/Desktop/项目/原神各属性角色信息.xlsx", header=0, index_col=0)
    role_things = role_things.fillna(axis=0, method="ffill")
    print(role_things)
    return_things = FindType("水").find_type()
    df = return_things.drop(["属性", "突破加成"], axis=1)
    Name = df["角色"]
    Hp = df["生命值"]
    Def = df["防御力"]
    Atk = df["攻击力"]
    c = (
        Scatter()
        .add_xaxis(list(Name))
        .add_yaxis("生命值", list(Hp))
        .add_yaxis("防御力", list(Def))
        .add_yaxis("攻击力", list(Atk))
        .set_global_opts(
            title_opts=opts.TitleOpts(title="水属性"),
            visualmap_opts=opts.VisualMapOpts(type_="size", max_=150, min_=20),
            xaxis_opts=opts.AxisOpts(axislabel_opts={"rotate": 45})
        )
    )
    return c


def h():
    role_things = pd.read_excel("C:/Users/YHT/Desktop/项目/原神各属性角色信息.xlsx", header=0, index_col=0)
    role_things = role_things.fillna(axis=0, method="ffill")
    print(role_things)
    return_things = FindType("冰").find_type()
    df = return_things.drop(["属性", "突破加成"], axis=1)
    Name = df["角色"]
    Hp = df["生命值"]
    Def = df["防御力"]
    Atk = df["攻击力"]
    c = (
        Scatter()
        .add_xaxis(list(Name))
        .add_yaxis("生命值", list(Hp))
        .add_yaxis("防御力", list(Def))
        .add_yaxis("攻击力", list(Atk))
        .set_global_opts(
            title_opts=opts.TitleOpts(title="冰属性"),
            visualmap_opts=opts.VisualMapOpts(type_="size", max_=150, min_=20),
            xaxis_opts=opts.AxisOpts(axislabel_opts={"rotate": 45})
        )
    )
    return c


def I():
    role_things = pd.read_excel("C:/Users/YHT/Desktop/项目/原神各属性角色信息.xlsx", header=0, index_col=0)
    role_things = role_things.fillna(axis=0, method="ffill")
    print(role_things)
    return_things = FindType("风").find_type()
    df = return_things.drop(["属性", "突破加成"], axis=1)
    Name = df["角色"]
    Hp = df["生命值"]
    Def = df["防御力"]
    Atk = df["攻击力"]
    c = (
        Scatter()
        .add_xaxis(list(Name))
        .add_yaxis("生命值", list(Hp))
        .add_yaxis("防御力", list(Def))
        .add_yaxis("攻击力", list(Atk))
        .set_global_opts(
            title_opts=opts.TitleOpts(title="风属性"),
            visualmap_opts=opts.VisualMapOpts(type_="size", max_=150, min_=20),
            xaxis_opts=opts.AxisOpts(axislabel_opts={"rotate": 45})
        )
    )
    return c


def K():
    role_things = pd.read_excel("C:/Users/YHT/Desktop/项目/原神各属性角色信息.xlsx", header=0, index_col=0)
    role_things = role_things.fillna(axis=0, method="ffill")
    print(role_things)
    return_things = FindType("雷").find_type()
    df = return_things.drop(["属性", "突破加成"], axis=1)
    Name = df["角色"]
    Hp = df["生命值"]
    Def = df["防御力"]
    Atk = df["攻击力"]
    c = (
        Scatter()
        .add_xaxis(list(Name))
        .add_yaxis("生命值", list(Hp))
        .add_yaxis("防御力", list(Def))
        .add_yaxis("攻击力", list(Atk))
        .set_global_opts(
            title_opts=opts.TitleOpts(title="雷属性"),
            visualmap_opts=opts.VisualMapOpts(type_="size", max_=150, min_=20),
            xaxis_opts=opts.AxisOpts(axislabel_opts={"rotate": 45})
        )
    )
    return c


page = Page(layout=Page.DraggablePageLayout)
page.add(a(), b(), c(), d(), x(), y(), z(), e(), f(), g(), h(), I(), K())
# page.render(".html")
# Page.save_resize_html(".html", cfg_file="chaonfig.json", dest="./templates/无.html")

运行结果：

相关推荐
会编程的土豆9 分钟前
01背包与完全背包详解
开发语言·数据结构·c++·算法
lbb 小魔仙14 分钟前
Python_多模态大模型实战指南
开发语言·python
编码者卢布17 分钟前
【Azure Developer】IIS w3wp.exe 的 -m 参数：一个未被记录的管道模式标识
microsoft·flask·azure
XDHCOM29 分钟前
Python os.system() 和 subprocess 怎么选？运行系统命令哪个更好用？
开发语言·网络·python
雨墨✘39 分钟前
golang如何实现设备指纹识别_golang设备指纹识别实现详解
jvm·数据库·python
yfndsb1 小时前
从入门到落地：OpenClaw 全面介绍与全平台本地部署保姆级教程
人工智能·python·ai
qq_283720051 小时前
Python Web 开发：Flask 快速入门教程
python·flask·web
加勒比海带661 小时前
目标检测算法——低空智能实验室开放数据集汇总附下载链接【点赞+收藏】
大数据·图像处理·人工智能·python·深度学习·目标检测·计算机视觉
xixixi777771 小时前
AI自主挖洞 + 通信网络扩散：全域风险指数级放大，如何构建密码-沙箱-终端联动闭环？
开发语言·网络·人工智能·ai·大模型·php·通信
小碗羊肉2 小时前
【从零开始学Java | 第三十五篇】IO流-字节流
java·开发语言
热门推荐
012026年4月技术前沿：AI大模型爆发、智能体革命与量子安全新纪元02GitHub 镜像站点03一周AI热点速览（2026.03.31-04.06）：GPT-6曝光、谷歌开源Gemma 4、资本狂飙与模型军备竞赛04GPT-6核心能力解析及与现有主流大模型对比05基于 Docker 部署 Hermes Agent 并接入飞书机器人的完整指南06零成本！Ollama本地部署国产大模型全指南（支持Kimi-K2.5/GLM-5/Qwen，新手秒上手）07免费！不限量！用opencode接入英伟达（NVIDIA）大模型，轻松打造你的 AI 编程助手08从限购到畅通：GLM-5.1 Coding Plan接入攻略09AI Weekly | 2026年4月第二周 · GitHub热门项目与AI发展趋势深度解析10CodeBuddy与WorkBuddy深度对比：腾讯两款AI工具差异及实操指南