python实现股票历史数据可视化分析案例

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1 数据预处理

1.1 股票历史数据csv文件读取

import pandas as pd
import csv

df = pd.read_csv("/home/kesci/input/maotai4154/maotai.csv")

1.2 关键数据――在csv文件中选择性提取“列”

df_high_low = df[["date","high","low"]]

1.3 数据类型转换

df_high_low_array = np.array(df_high_low)
df_high_low_list =df_high_low_array.tolist()

1.4 数据按列提取并累加性存入列表

price_dates, heigh_prices, low_prices = [], [], []
for content in zip(df_high_low_list):
    price_date = content[0][0]
    heigh_price = content[0][1]
    low_price = content[0][2]
    price_dates.append(price_date)
    heigh_prices.append(heigh_price)
    low_prices.append(low_price)

2 pyecharts实现数据可视化

2.1 导入库

import pyecharts.options as opts
from pyecharts.charts import Line

2.2 初始化画布

Line(init_opts=opts.InitOpts(width="1200px", height="600px"))

2.3 根据需要传入关键性数据并画图

    .add_yaxis(
        series_name="最低价",
        y_axis=low_prices,
        markpoint_opts=opts.MarkPointOpts(
            data=[opts.MarkPointItem(value=-2, name="周最低", x=1, y=-1.5)]
        ),
        markline_opts=opts.MarkLineOpts(
            data=[
                opts.MarkLineItem(type_="average", name="平均值"),
                opts.MarkLineItem(symbol="none", x="90%", y="max"),
                opts.MarkLineItem(symbol="circle", type_="max", name="最高点"),
            ]
        ),
    )

tooltip_opts=opts.TooltipOpts(trigger="axis"),
toolbox_opts=opts.ToolboxOpts(is_show=True),
xaxis_opts=opts.AxisOpts(type_="category", boundary_gap=True)

2.4 将生成的文件形成HTML代码并下载

.render("HTML名字填这里.html")

2.5 完整代码展示

import pyecharts.options as opts
from pyecharts.charts import Line
 
(
    Line(init_opts=opts.InitOpts(width="1200px", height="600px"))
    .add_xaxis(xaxis_data=price_dates)
    .add_yaxis(
        series_name="最高价",
        y_axis=heigh_prices,
        markpoint_opts=opts.MarkPointOpts(
            data=[
                opts.MarkPointItem(type_="max", name="最大值"),
                opts.MarkPointItem(type_="min", name="最小值"),
            ]
        ),
        markline_opts=opts.MarkLineOpts(
            data=[opts.MarkLineItem(type_="average", name="平均值")]
        ),
    )
    .add_yaxis(
        series_name="最低价",
        y_axis=low_prices,
        markpoint_opts=opts.MarkPointOpts(
            data=[opts.MarkPointItem(value=-2, name="周最低", x=1, y=-1.5)]
        ),
        markline_opts=opts.MarkLineOpts(
            data=[
                opts.MarkLineItem(type_="average", name="平均值"),
                opts.MarkLineItem(symbol="none", x="90%", y="max"),
                opts.MarkLineItem(symbol="circle", type_="max", name="最高点"),
            ]
        ),
    )
    .set_global_opts(
        title_opts=opts.TitleOpts(title="茅台股票历史数据可视化", subtitle="日期、最高价、最低价可视化"),
        tooltip_opts=opts.TooltipOpts(trigger="axis"),
        toolbox_opts=opts.ToolboxOpts(is_show=True),
        xaxis_opts=opts.AxisOpts(type_="category", boundary_gap=True),
    )
    .render("everyDayPrice_change_line_chart2.html")
)

3 结果展示

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原文链接：https://blog.csdn.net/IT_charge/article/details/113761938