文章目录
一、简介
二、代码
三、资料样例的展示
四、效果展示
1、主档案
2、数据库使用档案
3、ui设计模块
4、资料处理模块
Python实作股票资料分析的可视化
一、简介
我们知道在购买股票的时候,可以使用历史资料来对当前的股票的走势进行预测,这就需要对股票的资料进行获取并且进行一定的分析,当然了,人们是比较喜欢图形化的界面的,因此,我们在这里采用一种可视化的方法来实作股票资料的分析,
二、代码
1、主档案
from work1 import get_datafrom work1 import read_datafrom work1 import plot_dataimport pymysqlfrom uitest import MyFrame1import wxfrom database1 import write_to_baseimport timeclass CalcFrame(MyFrame1): def __init__(self, parent): MyFrame1.__init__(self, parent) # Virtual event handlers, overide them in your derived class def get_data(self, event): """ 获取资料 :param event: 点击 :return: 空 """ get_data() time.sleep(2) dlg = wx.MessageDialog(None, '已经成功获取资料', '获取资料') result = dlg.ShowModal() dlg.Destroy() event.Skip() def store_data(self, event): """ 存盘资料 :param event: 点击 :return: 空 """ write_to_base() dlg = wx.MessageDialog(None, '已经成功存盘资料', '存盘资料') result = dlg.ShowModal() dlg.Destroy() event.Skip() def read_data(self, event): """ 读取资料 :param event: 点击 :return: 空 """ df0 = read_data() dlg = wx.MessageDialog(None, '已经成功读取资料', '读取资料') result = dlg.ShowModal() dlg.Destroy() event.Skip() def show_data(self, event): """ 展示资料 :param event: 点击 :return: 空 """ df0 = read_data() plot_data(df0) event.Skip()if __name__ == '__main__': """ 主函式 """ app = wx.App(False) frame = CalcFrame(None) frame.Show(True) # start the applications app.MainLoop()
2、数据库使用档案
import pymysqlimport pandas as pddef write_to_base():
# pass
"""
写入数据库
:return:空
"""
df0 = pd.read_csv('./data.csv')
df0[['ts_code']] = df0[['ts_code']].astype(str)
df0[['trade_date']] = df0[['trade_date']].astype(str)
df0[['open']] = df0[['open']].astype(str)
df0[['high']] = df0[['high']].astype(str)
df0[['low']] = df0[['low']].astype(str)
df0[['close']] = df0[['close']].astype(str)
df0[['pre_close']] = df0[['pre_close']].astype(str)
df0[['change']] = df0[['change']].astype(str)
df0[['pct_chg']] = df0[['pct_chg']].astype(str)
df0[['vol']] = df0[['vol']].astype(str)
df0[['amount']] = df0[['amount']].astype(str)
# df0[['pre_close']] = df0[['pre_close']].astype(str)
# df0[['ts_code']] = df0[['ts_code']].astype(str)
# 打开数据库连接
# print(data)
# data = tuple(data)
db = pymysql.connect(host="localhost",
user="root",
password="671513",
db="base1")
# 使用cursor()方法获取操作游标
cursor = db.cursor()
# db.commit()
# db.ping(reconnect=True)
db.ping(reconnect=True)
cursor.execute("use base1")
db.commit()
cursor.execute("truncate table tb")
db.commit()
sql = "INSERT INTO tb(ts_code,trdae_date,open,high,low,close,pre_close,changed,pct_chg,vol,amount) \
VALUES ('%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s')" # ('%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s')"
# ('000001.SZ','20210716','21.41','21.82','21.3','21.34','21.62','-0.28','-1.2951','573002.61','1230180.813')
# ('%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s')
for i in range(220):
db.ping(reconnect=True)
# 执行sql陈述句
cursor.execute(sql %\ (df0.iloc[i, 1], df0.iloc[i, 2], df0.iloc[i, 3], df0.iloc[i, 4],
df0.iloc[i, 5], df0.iloc[i, 6], df0.iloc[i, 7], df0.iloc[i, 8],
df0.iloc[i, 9], df0.iloc[i, 10], df0.iloc[i, 11]))
# 执行sql陈述句
db.commit()
# 关闭数据库连接
db.close()3、ui设计模块
# -*- coding: utf-8 -*-############################################################################# Python code generated with wxFormBuilder (version Jun 17 2015)## http://www.wxformbuilder.org/#### PLEASE DO "NOT" EDIT THIS FILE!###########################################################################import wximport wx.xrc############################################################################# Class MyFrame1###########################################################################class MyFrame1(wx.Frame): def __init__(self, parent): wx.Frame.__init__(self, parent, id=wx.ID_ANY, title=u"股票资料分析", pos=wx.DefaultPosition, size=wx.Size(309, 300), style=wx.DEFAULT_FRAME_STYLE | wx.TAB_TRAVERSAL) self.SetSizeHintsSz(wx.DefaultSize, wx.DefaultSize) bSizer1 = wx.BoxSizer(wx.VERTICAL) self.m_button1 = wx.Button(self, wx.ID_ANY, u"获取资料", wx.DefaultPosition, wx.DefaultSize, 0) bSizer1.Add(self.m_button1, 1, wx.ALL | wx.EXPAND, 5) self.m_button2 = wx.Button(self, wx.ID_ANY, u"存盘资料", wx.DefaultPosition, wx.DefaultSize, 0) bSizer1.Add(self.m_button2, 1, wx.ALL | wx.EXPAND, 5) self.m_button3 = wx.Button(self, wx.ID_ANY, u"读取资料", wx.DefaultPosition, wx.DefaultSize, 0) bSizer1.Add(self.m_button3, 1, wx.ALL | wx.EXPAND, 5) self.m_button4 = wx.Button(self, wx.ID_ANY, u"展示曲线", wx.DefaultPosition, wx.DefaultSize, 0) bSizer1.Add(self.m_button4, 1, wx.ALL | wx.EXPAND, 5) self.SetSizer(bSizer1) self.Layout() self.Centre(wx.BOTH) # Connect Events self.m_button1.Bind(wx.EVT_BUTTON, self.get_data) self.m_button2.Bind(wx.EVT_BUTTON, self.store_data) self.m_button3.Bind(wx.EVT_BUTTON, self.read_data) self.m_button4.Bind(wx.EVT_BUTTON, self.show_data) def __del__(self): pass # Virtual event handlers, overide them in your derived class def get_data(self, event): event.Skip() def store_data(self, event): event.Skip() def read_data(self, event): event.Skip() def show_data(self, event): event.Skip()### class CalcFrame(MyFrame1):# def __init__(self, parent):# MyFrame1.__init__(self, parent)### app = wx.App(False)## frame = CalcFrame(None)## frame.Show(True)## # start the applications# app.MainLoop()
4、资料处理模块
import numpy as npimport tushare as tsimport matplotlib.pyplot as pltimport pandas as pddef get_data():
"""
获取资料
:return: 空
"""
# 获取股票的资料
pro = ts.pro_api('c62ba9195fa8b54ff78a38cab1cec01b15def7f47c32f91fb273ee3a')
df = pro.daily(ts_code='000001.SZ', start_date='20200101', end_date='20201130')
# 存盘资料到一个档案中
df.to_csv('./data.csv')
print(df)def read_data():
"""
读取资料
:return: 空
"""
# 读取资料
df = pd.read_csv('./data.csv')
# 洗掉不需要的行
df = df.drop(['Unnamed: 0'], axis=1)
df = df.drop(['ts_code'], axis=1)
# 反转行使得时间是从前到后的
df = df.iloc[::-1, :]
# 将时间由数字转为字符串
for i in range(220):
df.iloc[i, 0] = str(df.iloc[i, 0])
# 将字符串转为时间型别的资料
df['trade_date'] = pd.to_datetime(df['trade_date'])
# 将时间设定为索引
df = df.set_index(['trade_date'])
df = df.iloc[:, :]
print(df)
return dfdef plot_data(df):
"""
展示资料
:param df: 一个DataFrame
:return: 空
"""
ma5 = (df['close'].rolling(5).mean()).iloc[30:]
ma10 = (df['close'].rolling(10).mean()).iloc[30:]
ma20 = (df['close'].rolling(20).mean()).iloc[30:]
plt.figure(figsize=(16, 9))
l1, = plt.plot(ma5, label="ma5")
l2, = plt.plot(ma10, label="ma10")
l3, = plt.plot(ma20, label="ma20")
l4, = plt.plot(df['close'].iloc[30:], label="close")
plt.legend(handles=[l1, l2, l3, l4], labels=["ma5", "ma10", "ma20", "close"])
plt.show()
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