python实现股票历史数据可视化分析案例(数据可视化)

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")
)