python实现股票历史数据可视化分析案例

股票交易数据分析可直观股市走向，对于如何把握股票行情，快速解读股票交易数据有不可替代的作用，感兴趣的可以了解一下

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") )