溫馨提示×
您好，登錄后才能下訂單哦！
點擊 登錄注冊 即表示同意《億速云用戶服務條款》
您好，登錄后才能下訂單哦！
這篇文章主要為大家展示了“如何使用Python實現股票數據分析的可視化”，內容簡而易懂，條理清晰，希望能夠幫助大家解決疑惑，下面讓小編帶領大家一起研究并學習一下“如何使用Python實現股票數據分析的可視化”這篇文章吧。
我們知道在購買股票的時候，可以使用歷史數據來對當前的股票的走勢進行預測，這就需要對股票的數據進行獲取并且進行一定的分析，當然了，人們是比較喜歡圖形化的界面的，因此，我們在這里采用一種可視化的方法來實現股票數據的分析。
from work1 import get_data from work1 import read_data from work1 import plot_data import pymysql from uitest import MyFrame1 import wx from database1 import write_to_base import time class CalcFrame(MyFrame1): def __init__(self, parent): MyFrame1.__init__(self, parent) # Virtual event handlers, overide them in your derived class def get_data(self, event): """ 獲取數據 :param event: 點擊 :return: 空 """ get_data() time.sleep(2) dlg = wx.MessageDialog(None, '已經成功獲取數據', '獲取數據') result = dlg.ShowModal() dlg.Destroy() event.Skip() def store_data(self, event): """ 存儲數據 :param event: 點擊 :return: 空 """ write_to_base() dlg = wx.MessageDialog(None, '已經成功存儲數據', '存儲數據') result = dlg.ShowModal() dlg.Destroy() event.Skip() def read_data(self, event): """ 讀取數據 :param event: 點擊 :return: 空 """ df0 = read_data() dlg = wx.MessageDialog(None, '已經成功讀取數據', '讀取數據') result = dlg.ShowModal() dlg.Destroy() event.Skip() def show_data(self, event): """ 展示數據 :param event: 點擊 :return: 空 """ df0 = read_data() plot_data(df0) event.Skip() if __name__ == '__main__': """ 主函數 """ app = wx.App(False) frame = CalcFrame(None) frame.Show(True) # start the applications app.MainLoop()
import pymysql
import pandas as pd
def write_to_base():
# pass
"""
寫入數據庫
: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)
# 打開數據庫連接
# print(data)
# data = tuple(data)
db = pymysql.connect(host="localhost",
user="root",
password="671513",
db="base1")
# 使用cursor()方法獲取操作游標
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)
# 執行sql語句
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]))
# 執行sql語句
db.commit()
# 關閉數據庫連接
db.close()# -*- coding: utf-8 -*- ########################################################################### ## Python code generated with wxFormBuilder (version Jun 17 2015) ## http://www.wxformbuilder.org/ ## ## PLEASE DO "NOT" EDIT THIS FILE! ########################################################################### import wx import wx.xrc ########################################################################### ## Class MyFrame1 ########################################################################### class MyFrame1(wx.Frame): def __init__(self, parent): wx.Frame.__init__(self, parent, id=wx.ID_ANY, title=u"股票數據分析", 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"獲取數據", 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"存儲數據", 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"讀取數據", 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"展示曲線", 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()
import numpy as np
import tushare as ts
import matplotlib.pyplot as plt
import pandas as pd
def get_data():
"""
獲取數據
:return: 空
"""
# 獲取股票的數據
pro = ts.pro_api('c62ba9195fa8b54ff78a38cab1cec01b15def7f47c32f91fb273ee3a')
df = pro.daily(ts_code='000001.SZ', start_date='20200101', end_date='20201130')
# 存儲數據到一個文件中
df.to_csv('./data.csv')
print(df)
def read_data():
"""
讀取數據
:return: 空
"""
# 讀取數據
df = pd.read_csv('./data.csv')
# 刪除不需要的行
df = df.drop(['Unnamed: 0'], axis=1)
df = df.drop(['ts_code'], axis=1)
# 反轉行使得時間是從前到后的
df = df.iloc[::-1, :]
# 將時間由數字轉為字符串
for i in range(220):
df.iloc[i, 0] = str(df.iloc[i, 0])
# 將字符串轉為時間類型的數據
df['trade_date'] = pd.to_datetime(df['trade_date'])
# 將時間設置為索引
df = df.set_index(['trade_date'])
df = df.iloc[:, :]
print(df)
return df
def plot_data(df):
"""
展示數據
:param df: 一個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(),ts_code,trade_date,open,high,low,close,pre_close,change,pct_chg,vol,amount 0,000001.SZ,20201130,19.9,20.88,19.59,19.74,19.7,0.04,0.203,1581441.28,3213680.47 1,000001.SZ,20201127,20.0,20.0,19.38,19.7,19.5,0.2,1.0256,753773.74,1479430.635 2,000001.SZ,20201126,19.05,19.61,19.03,19.5,19.06,0.44,2.3085,639657.89,1240074.378 3,000001.SZ,20201125,19.48,19.7,19.05,19.06,19.36,-0.3,-1.5496,552585.01,1068352.014 4,000001.SZ,20201124,19.62,19.68,19.17,19.36,19.62,-0.26,-1.3252,678543.23,1313496.136 5,000001.SZ,20201123,18.85,19.62,18.8,19.62,18.86,0.76,4.0297,1165858.26,2252290.578 6,000001.SZ,20201120,18.83,18.99,18.52,18.86,18.85,0.01,0.0531,673919.22,1265262.915 7,000001.SZ,20201119,18.59,18.98,18.3,18.85,18.46,0.39,2.1127,1211740.62,2270476.474 8,000001.SZ,20201118,17.78,18.5,17.75,18.46,17.83,0.63,3.5334,1373400.72,2508632.642 9,000001.SZ,20201117,17.38,17.93,17.25,17.83,17.37,0.46,2.6482,852930.51,1509511.577 10,000001.SZ,20201116,17.08,17.43,16.9,17.37,17.18,0.19,1.1059,759856.93,1308190.459 11,000001.SZ,20201113,17.42,17.47,16.69,17.18,17.66,-0.48,-2.718,1289189.23,2191492.021 12,000001.SZ,20201112,17.81,17.94,17.45,17.66,17.81,-0.15,-0.8422,677258.48,1197284.181 13,000001.SZ,20201111,18.2,18.3,17.6,17.81,18.11,-0.3,-1.6565,940130.07,1677811.478 14,000001.SZ,20201110,18.0,18.5,17.93,18.11,17.84,0.27,1.5135,1021062.81,1854142.808 15,000001.SZ,20201109,17.67,18.0,17.54,17.84,17.64,0.2,1.1338,951424.32,1688807.401 16,000001.SZ,20201106,17.71,17.75,17.22,17.64,17.7,-0.06,-0.339,848781.53,1486492.208 17,000001.SZ,20201105,18.37,18.5,17.54,17.7,18.32,-0.62,-3.3843,1429469.44,2558562.453 18,000001.SZ,20201104,18.35,18.48,17.96,18.32,17.96,0.36,2.0045,1247636.4,2275824.963 19,000001.SZ,20201103,17.71,18.34,17.7,17.96,17.63,0.33,1.8718,957868.63,1727488.481 20,000001.SZ,20201102,17.65,18.05,17.33,17.63,17.75,-0.12,-0.6761,968452.77,1702741.437 21,000001.SZ,20201030,17.74,18.36,17.6,17.75,17.77,-0.02,-0.1125,1007803.83,1813064.343 22,000001.SZ,20201029,17.54,17.93,17.35,17.77,17.63,0.14,0.7941,846603.62,1498040.947 23,000001.SZ,20201028,17.76,17.9,17.29,17.63,17.76,-0.13,-0.732,1205823.86,2125604.541 24,000001.SZ,20201027,18.0,18.0,17.5,17.76,17.7,0.06,0.339,1034865.04,1839243.224 25,000001.SZ,20201026,18.2,18.29,17.45,17.7,18.13,-0.43,-2.3718,1175598.65,2085800.598 26,000001.SZ,20201023,17.53,18.78,17.53,18.13,17.56,0.57,3.246,1698501.68,3105623.948 27,000001.SZ,20201022,17.94,18.5,17.3,17.56,17.91,-0.35,-1.9542,1890519.05,3342069.01 28,000001.SZ,20201021,17.64,18.0,17.33,17.91,17.54,0.37,2.1095,1244560.18,2204040.364 29,000001.SZ,20201020,17.48,17.6,17.25,17.54,17.48,0.06,0.3432,960071.95,1673173.355 30,000001.SZ,20201019,17.3,18.1,17.3,17.48,17.1,0.38,2.2222,2016105.52,3571336.006 31,000001.SZ,20201016,16.56,17.37,16.54,17.1,16.56,0.54,3.2609,2095614.19,3589229.558 32,000001.SZ,20201015,16.2,16.92,16.15,16.56,16.03,0.53,3.3063,1600062.32,2654379.585 33,000001.SZ,20201014,16.04,16.12,15.8,16.03,16.06,-0.03,-0.1868,662562.36,1057937.816 34,000001.SZ,20201013,15.9,16.11,15.77,16.06,15.9,0.16,1.0063,908819.48,1453986.337 35,000001.SZ,20201012,15.22,16.05,15.21,15.9,15.18,0.72,4.7431,1591347.15,2509002.885 36,000001.SZ,20201009,15.3,15.55,15.13,15.18,15.17,0.01,0.0659,900425.93,1376995.906 37,000001.SZ,20200930,14.8,15.27,14.8,15.17,14.8,0.37,2.5,1217064.82,1838547.595 38,000001.SZ,20200929,15.39,15.41,14.76,14.8,15.31,-0.51,-3.3312,1182374.4,1766848.544 39,000001.SZ,20200928,15.19,15.37,14.98,15.31,15.19,0.12,0.79,612711.11,932800.766 40,000001.SZ,20200925,15.2,15.31,15.11,15.19,15.12,0.07,0.463,614087.0,933035.044 41,000001.SZ,20200924,15.59,15.61,15.12,15.12,15.63,-0.51,-3.263,1061011.24,1623376.2 42,000001.SZ,20200923,15.59,15.83,15.51,15.63,15.57,0.06,0.3854,599200.47,939763.265 43,000001.SZ,20200922,15.67,15.84,15.39,15.57,15.86,-0.29,-1.8285,867756.31,1354536.272 44,000001.SZ,20200921,16.0,16.05,15.71,15.86,16.07,-0.21,-1.3068,896161.65,1418370.973 45,000001.SZ,20200918,15.62,16.09,15.52,16.07,15.57,0.5,3.2113,1373193.3,2186759.087 46,000001.SZ,20200917,15.54,15.72,15.4,15.57,15.44,0.13,0.842,988215.63,1543414.501 47,000001.SZ,20200916,15.32,15.54,15.21,15.44,15.35,0.09,0.5863,722414.75,1114667.832 48,000001.SZ,20200915,15.2,15.48,15.15,15.35,15.3,0.05,0.3268,657132.67,1007999.044 49,000001.SZ,20200914,15.01,15.3,14.92,15.3,15.01,0.29,1.932,680251.05,1027508.108 50,000001.SZ,20200911,15.18,15.3,14.82,15.01,15.34,-0.33,-2.1512,954236.25,1431844.02 51,000001.SZ,20200910,15.32,15.48,15.2,15.34,15.21,0.13,0.8547,957092.39,1469402.768 52,000001.SZ,20200909,15.26,15.56,15.13,15.21,15.43,-0.22,-1.4258,1013572.47,1554005.575 53,000001.SZ,20200908,15.0,15.43,15.0,15.43,14.94,0.49,3.2798,1407601.66,2154220.778 54,000001.SZ,20200907,14.88,15.24,14.83,14.94,14.96,-0.02,-0.1337,1031376.81,1551971.38 55,000001.SZ,20200904,14.73,15.06,14.6,14.96,14.9,0.06,0.4027,909889.99,1353550.808 56,000001.SZ,20200903,15.32,15.33,14.84,14.9,15.32,-0.42,-2.7415,1279841.59,1919266.726 57,000001.SZ,20200902,15.01,15.53,15.01,15.32,15.14,0.18,1.1889,1679382.97,2575966.637 58,000001.SZ,20200901,14.96,15.23,14.88,15.14,15.08,0.06,0.3979,813642.58,1228342.741 59,000001.SZ,20200831,15.3,15.68,14.99,15.08,15.13,-0.05,-0.3305,1797129.54,2760350.322 60,000001.SZ,20200828,14.26,15.18,14.26,15.13,14.46,0.67,4.6335,2410400.02,3599035.694 61,000001.SZ,20200827,14.4,14.46,14.11,14.46,14.37,0.09,0.6263,626666.77,895618.648 62,000001.SZ,20200826,14.6,14.61,14.28,14.37,14.6,-0.23,-1.5753,734117.72,1057274.169 63,000001.SZ,20200825,14.56,14.69,14.46,14.6,14.46,0.14,0.9682,748320.22,1090756.854 64,000001.SZ,20200824,14.5,14.71,14.41,14.46,14.45,0.01,0.0692,919448.86,1338031.969 65,000001.SZ,20200821,14.71,14.71,14.32,14.45,14.59,-0.14,-0.9596,1234517.33,1787278.581 66,000001.SZ,20200820,15.01,15.14,14.53,14.59,15.1,-0.51,-3.3775,1333801.62,1962605.013 67,000001.SZ,20200819,15.11,15.35,14.96,15.1,15.15,-0.05,-0.33,1420928.11,2154215.097 68,000001.SZ,20200818,15.2,15.3,14.91,15.15,15.19,-0.04,-0.2633,1350261.07,2033477.707 69,000001.SZ,20200817,14.6,15.35,14.55,15.19,14.47,0.72,4.9758,3268027.8,4923669.137 70,000001.SZ,20200814,14.1,14.51,14.06,14.47,14.18,0.29,2.0451,1103215.82,1578543.607 71,000001.SZ,20200813,14.4,14.46,14.14,14.18,14.38,-0.2,-1.3908,837261.75,1190139.725 72,000001.SZ,20200812,14.21,14.5,14.15,14.38,14.13,0.25,1.7693,1596811.7,2287731.088 73,000001.SZ,20200811,13.97,14.66,13.97,14.13,13.95,0.18,1.2903,2603307.89,3748036.828 74,000001.SZ,20200810,13.67,14.02,13.62,13.95,13.7,0.25,1.8248,1587710.35,2208568.316 75,000001.SZ,20200807,13.8,13.9,13.62,13.7,13.9,-0.2,-1.4388,988678.37,1356305.781 76,000001.SZ,20200806,13.82,13.96,13.65,13.9,13.76,0.14,1.0174,1352510.68,1868047.342 77,000001.SZ,20200805,13.82,13.85,13.62,13.76,14.04,-0.28,-1.9943,1440203.13,1980352.978 78,000001.SZ,20200804,13.66,14.15,13.48,14.04,13.59,0.45,3.3113,2445663.25,3388510.059 79,000001.SZ,20200803,13.47,13.62,13.43,13.59,13.34,0.25,1.8741,1445096.16,1954607.257 80,000001.SZ,20200731,13.28,13.53,13.25,13.34,13.37,-0.03,-0.2244,1165821.91,1559068.291 81,000001.SZ,20200730,13.5,13.51,13.37,13.37,13.54,-0.17,-1.2555,964067.63,1294444.933 82,000001.SZ,20200729,13.35,13.63,13.21,13.54,13.34,0.2,1.4993,1519580.25,2043847.472 83,000001.SZ,20200728,13.34,13.43,13.18,13.34,13.24,0.1,0.7553,1217005.99,1618089.558 84,000001.SZ,20200727,13.67,13.68,13.1,13.24,13.5,-0.26,-1.9259,1880653.35,2497551.472 85,000001.SZ,20200724,13.97,13.99,13.42,13.5,14.01,-0.51,-3.6403,1830881.83,2504647.111 86,000001.SZ,20200723,14.24,14.29,13.81,14.01,14.41,-0.4,-2.7759,2027525.87,2838535.21 87,000001.SZ,20200722,14.49,14.65,14.27,14.41,14.49,-0.08,-0.5521,1312951.59,1895447.229 88,000001.SZ,20200721,14.68,14.68,14.4,14.49,14.73,-0.24,-1.6293,1252865.69,1815570.3 89,000001.SZ,20200720,14.23,14.77,14.1,14.73,14.14,0.59,4.1726,1979632.0,2872758.056 90,000001.SZ,20200717,14.17,14.28,13.95,14.14,14.15,-0.01,-0.0707,1291346.77,1821043.927 91,000001.SZ,20200716,14.3,14.55,14.12,14.15,14.27,-0.12,-0.8409,1930891.29,2771496.391 92,000001.SZ,20200715,14.78,14.86,14.23,14.27,14.68,-0.41,-2.7929,2042562.83,2947173.149 93,000001.SZ,20200714,14.9,15.19,14.55,14.68,14.89,-0.21,-1.4103,1953566.27,2891773.817 94,000001.SZ,20200713,14.7,15.08,14.5,14.89,14.86,0.03,0.2019,1937160.12,2871414.844 95,000001.SZ,20200710,15.35,15.48,14.76,14.86,15.53,-0.67,-4.3142,2158773.26,3254272.377 96,000001.SZ,20200709,15.66,15.66,15.31,15.53,15.76,-0.23,-1.4594,2243994.4,3469517.329 97,000001.SZ,20200708,15.23,16.0,15.23,15.76,15.48,0.28,1.8088,2631339.16,4095447.757 98,000001.SZ,20200707,16.3,16.63,15.03,15.48,15.68,-0.2,-1.2755,3964427.47,6267919.683 99,000001.SZ,20200706,14.6,15.68,14.59,15.68,14.25,1.43,10.0351,4711460.78,7168653.356 100,000001.SZ,20200703,13.57,14.32,13.56,14.25,13.43,0.82,6.1057,3768333.63,5280918.011 101,000001.SZ,20200702,13.08,13.49,12.97,13.43,13.12,0.31,2.3628,2590501.19,3433511.084 102,000001.SZ,20200701,12.79,13.15,12.74,13.12,12.8,0.32,2.5,1697390.01,2202800.843 103,000001.SZ,20200630,12.83,12.88,12.72,12.8,12.8,0.0,0.0,937940.22,1199181.601 104,000001.SZ,20200629,12.92,12.97,12.71,12.8,12.8,0.0,0.0,1038480.06,1330678.288 105,000001.SZ,20200624,12.64,12.88,12.6,12.8,12.6,0.2,1.5873,1523220.48,1946329.095 106,000001.SZ,20200623,12.65,12.69,12.52,12.6,12.64,-0.04,-0.3165,990806.73,1248046.646 107,000001.SZ,20200622,12.74,12.76,12.62,12.64,12.8,-0.16,-1.25,1319079.79,1671023.278 108,000001.SZ,20200619,12.73,12.84,12.61,12.8,12.76,0.04,0.3135,1539521.78,1954584.919 109,000001.SZ,20200618,12.76,12.8,12.59,12.76,12.85,-0.09,-0.7004,1119647.8,1419972.017 110,000001.SZ,20200617,12.89,12.92,12.76,12.85,12.89,-0.04,-0.3103,716468.24,918251.153 111,000001.SZ,20200616,12.9,12.99,12.86,12.89,12.82,0.07,0.546,718059.1,927043.687 112,000001.SZ,20200615,12.85,12.97,12.8,12.82,12.99,-0.17,-1.3087,660313.07,850767.506 113,000001.SZ,20200612,12.9,13.02,12.87,12.99,13.08,-0.09,-0.6881,1030550.57,1331618.728 114,000001.SZ,20200611,13.38,13.39,13.0,13.08,13.49,-0.41,-3.0393,1349039.82,1774199.978 115,000001.SZ,20200610,13.71,13.71,13.4,13.49,13.67,-0.18,-1.3168,580476.2,781995.749 116,000001.SZ,20200609,13.64,13.73,13.53,13.67,13.62,0.05,0.3671,474300.07,646895.834 117,000001.SZ,20200608,13.68,13.85,13.58,13.62,13.59,0.03,0.2208,585971.9,802115.792 118,000001.SZ,20200605,13.6,13.62,13.43,13.59,13.57,0.02,0.1474,383026.9,517232.135 119,000001.SZ,20200604,13.53,13.64,13.41,13.57,13.54,0.03,0.2216,583066.33,788707.63 120,000001.SZ,20200603,13.64,13.88,13.5,13.54,13.55,-0.01,-0.0738,956803.08,1308782.294 121,000001.SZ,20200602,13.29,13.63,13.28,13.55,13.32,0.23,1.7267,883458.88,1194375.822 122,000001.SZ,20200601,13.1,13.39,13.08,13.32,13.0,0.32,2.4615,882960.55,1173619.006 123,000001.SZ,20200529,13.01,13.04,12.92,13.0,13.07,-0.07,-0.5356,457808.22,594502.123 124,000001.SZ,20200528,12.87,13.18,12.81,13.07,12.78,0.29,2.2692,960760.31,1255226.999 125,000001.SZ,20200527,13.05,13.19,12.96,13.0,13.04,-0.04,-0.3067,482962.94,630305.864 126,000001.SZ,20200526,13.02,13.07,12.94,13.04,12.96,0.08,0.6173,396212.4,515451.849 127,000001.SZ,20200525,12.97,12.98,12.76,12.96,12.92,0.04,0.3096,410170.78,528769.352 128,000001.SZ,20200522,13.33,13.34,12.92,12.92,13.4,-0.48,-3.5821,856237.33,1119433.491 129,000001.SZ,20200521,13.52,13.57,13.36,13.4,13.51,-0.11,-0.8142,552312.0,742797.057 130,000001.SZ,20200520,13.38,13.62,13.27,13.51,13.36,0.15,1.1228,690851.07,929928.885 131,000001.SZ,20200519,13.41,13.45,13.27,13.36,13.2,0.16,1.2121,600368.64,801755.671 132,000001.SZ,20200518,13.2,13.34,13.12,13.2,13.23,-0.03,-0.2268,637208.57,843479.669 133,000001.SZ,20200515,13.39,13.43,13.14,13.23,13.3,-0.07,-0.5263,756794.47,1004313.267 134,000001.SZ,20200514,13.55,13.59,13.22,13.3,13.63,-0.33,-2.4211,944672.09,1259440.848 135,000001.SZ,20200513,13.75,13.78,13.53,13.63,13.79,-0.16,-1.1603,640358.79,871062.043 136,000001.SZ,20200512,13.95,14.05,13.72,13.79,14.0,-0.21,-1.5,558511.14,772109.502 137,000001.SZ,20200511,13.92,14.13,13.9,14.0,13.95,0.05,0.3584,612862.29,859156.594 138,000001.SZ,20200508,13.76,14.02,13.68,13.95,13.69,0.26,1.8992,934781.7,1297924.588 139,000001.SZ,20200507,13.76,13.76,13.6,13.69,13.77,-0.08,-0.581,662749.23,904349.531 140,000001.SZ,20200506,13.76,13.89,13.61,13.77,13.93,-0.16,-1.1486,1008998.02,1382727.481 141,000001.SZ,20200430,14.02,14.32,13.88,13.93,14.02,-0.09,-0.6419,819540.43,1155968.238 142,000001.SZ,20200429,13.48,14.1,13.45,14.02,13.52,0.5,3.6982,1108722.39,1541638.203 143,000001.SZ,20200428,13.45,13.56,13.27,13.52,13.5,0.02,0.1481,771564.17,1038718.08 144,000001.SZ,20200427,13.3,13.64,13.25,13.5,13.24,0.26,1.9637,936829.9,1263809.737 145,000001.SZ,20200424,13.17,13.28,13.11,13.24,13.23,0.01,0.0756,566001.61,747473.77 146,000001.SZ,20200423,13.23,13.31,13.11,13.23,13.23,0.0,0.0,646989.63,855052.11 147,000001.SZ,20200422,13.37,13.42,13.16,13.23,13.45,-0.22,-1.6357,1032802.74,1368222.854 148,000001.SZ,20200421,13.3,13.7,13.3,13.45,12.99,0.46,3.5412,2122448.34,2861879.086 149,000001.SZ,20200420,12.86,13.05,12.77,12.99,12.89,0.1,0.7758,818455.83,1058524.019 150,000001.SZ,20200417,12.77,13.04,12.65,12.89,12.68,0.21,1.6562,1331164.77,1713215.766 151,000001.SZ,20200416,12.79,12.79,12.54,12.68,12.87,-0.19,-1.4763,789154.98,997623.816 152,000001.SZ,20200415,12.86,12.93,12.78,12.87,12.86,0.01,0.0778,656396.4,843649.273 153,000001.SZ,20200414,12.65,12.86,12.57,12.86,12.59,0.27,2.1446,686086.87,874856.562 154,000001.SZ,20200413,12.67,12.71,12.47,12.59,12.79,-0.2,-1.5637,446214.4,562008.05 155,000001.SZ,20200410,12.76,12.98,12.65,12.79,12.74,0.05,0.3925,666674.95,853689.95 156,000001.SZ,20200409,12.88,12.89,12.72,12.74,12.78,-0.04,-0.313,408553.77,522027.888 157,000001.SZ,20200408,12.88,12.92,12.72,12.78,12.88,-0.1,-0.7764,528716.14,676604.872 158,000001.SZ,20200407,12.89,12.94,12.81,12.88,12.61,0.27,2.1412,870313.71,1121200.115 159,000001.SZ,20200403,12.82,12.89,12.55,12.61,12.97,-0.36,-2.7756,825348.14,1047282.4 160,000001.SZ,20200402,12.75,12.97,12.66,12.97,12.89,0.08,0.6206,518365.04,663197.628 161,000001.SZ,20200401,12.86,13.13,12.82,12.89,12.8,0.09,0.7031,520836.04,676070.117 162,000001.SZ,20200331,13.05,13.09,12.78,12.8,12.94,-0.14,-1.0819,513370.3,662915.471 163,000001.SZ,20200330,12.85,13.04,12.76,12.94,13.15,-0.21,-1.597,661738.79,852956.24 164,000001.SZ,20200327,13.25,13.38,13.08,13.15,13.06,0.09,0.6891,653018.88,861618.663 165,000001.SZ,20200326,12.78,13.34,12.72,13.06,12.87,0.19,1.4763,1075192.43,1408651.057 166,000001.SZ,20200325,12.88,13.07,12.7,12.87,12.61,0.26,2.0619,1136957.74,1467534.956 167,000001.SZ,20200324,12.4,12.68,12.27,12.61,12.15,0.46,3.786,1180200.26,1472909.399 168,000001.SZ,20200323,12.0,12.35,11.93,12.15,12.52,-0.37,-2.9553,1071113.64,1300469.494 169,000001.SZ,20200320,12.4,12.68,12.26,12.52,12.23,0.29,2.3712,1578352.96,1967487.818 170,000001.SZ,20200319,12.68,12.74,11.91,12.23,12.71,-0.48,-3.7766,1891457.13,2313863.663 171,000001.SZ,20200318,13.41,13.55,12.65,12.71,13.41,-0.7,-5.22,1384784.37,1816836.893 172,000001.SZ,20200317,13.75,13.97,13.13,13.41,13.75,-0.34,-2.4727,1177849.06,1582506.075 173,000001.SZ,20200316,14.45,14.46,13.75,13.75,14.52,-0.77,-5.303,1406202.18,1975824.191 174,000001.SZ,20200313,13.9,14.58,13.9,14.52,14.68,-0.16,-1.0899,1169765.8,1669009.835 175,000001.SZ,20200312,14.65,14.84,14.53,14.68,14.69,-0.01,-0.0681,986497.11,1447436.641 176,000001.SZ,20200311,14.77,14.88,14.62,14.69,14.76,-0.07,-0.4743,814381.64,1201250.682 177,000001.SZ,20200310,14.38,14.85,14.38,14.76,14.45,0.31,2.1453,1167864.97,1709084.565 178,000001.SZ,20200309,14.71,14.73,14.42,14.45,15.03,-0.58,-3.8589,1665793.54,2420392.13 179,000001.SZ,20200306,15.18,15.27,15.02,15.03,15.39,-0.36,-2.3392,1228531.03,1858691.259 180,000001.SZ,20200305,14.8,15.64,14.73,15.39,14.69,0.7,4.7651,2686602.34,4089493.523 181,000001.SZ,20200304,14.68,14.78,14.51,14.69,14.72,-0.03,-0.2038,862595.23,1261123.063 182,000001.SZ,20200303,14.96,14.99,14.63,14.72,14.79,-0.07,-0.4733,1153584.32,1705816.271 183,000001.SZ,20200302,14.55,14.95,14.46,14.79,14.5,0.29,2.0,1116580.66,1647432.269 184,000001.SZ,20200228,14.85,15.04,14.46,14.5,15.11,-0.61,-4.0371,1300644.45,1906892.413 185,000001.SZ,20200227,14.96,15.15,14.89,15.11,14.99,0.12,0.8005,975270.9,1464605.739 186,000001.SZ,20200226,14.77,15.27,14.7,14.99,15.04,-0.05,-0.3324,1176599.15,1769612.245 187,000001.SZ,20200225,15.0,15.13,14.78,15.04,15.23,-0.19,-1.2475,1144575.02,1710369.786 188,000001.SZ,20200224,15.46,15.46,15.15,15.23,15.58,-0.35,-2.2465,1191794.5,1820183.854 189,000001.SZ,20200221,15.49,15.72,15.45,15.58,15.59,-0.01,-0.0641,995071.02,1546692.93 190,000001.SZ,20200220,15.27,15.62,15.1,15.59,15.24,0.35,2.2966,1235444.34,1897923.029 191,000001.SZ,20200219,15.1,15.37,15.08,15.24,15.2,0.04,0.2632,874106.93,1333730.218 192,000001.SZ,20200218,15.33,15.33,15.01,15.2,15.37,-0.17,-1.1061,973612.35,1478274.222 193,000001.SZ,20200217,15.04,15.37,14.93,15.37,15.03,0.34,2.2621,1543696.01,2337993.586 194,000001.SZ,20200214,14.75,15.14,14.7,15.03,14.65,0.38,2.5939,1512434.73,2253906.452 195,000001.SZ,20200213,14.71,14.88,14.61,14.65,14.77,-0.12,-0.8125,1013205.28,1491327.713 196,000001.SZ,20200212,14.79,14.82,14.6,14.77,14.79,-0.02,-0.1352,1070503.21,1573229.042 197,000001.SZ,20200211,14.6,14.94,14.56,14.79,14.5,0.29,2.0,1407507.44,2077194.138 198,000001.SZ,20200210,14.51,14.53,14.3,14.5,14.62,-0.12,-0.8208,1339495.24,1931983.482 199,000001.SZ,20200207,14.6,14.69,14.41,14.62,14.77,-0.15,-1.0156,924852.96,1345053.255 200,000001.SZ,20200206,14.81,14.87,14.51,14.77,14.63,0.14,0.9569,1185815.72,1740107.625 201,000001.SZ,20200205,14.59,14.89,14.32,14.63,14.6,0.03,0.2055,1491380.21,2177632.043 202,000001.SZ,20200204,14.05,14.66,14.02,14.6,13.99,0.61,4.3603,1706172.07,2442932.842 203,000001.SZ,20200203,13.99,14.7,13.99,13.99,15.54,-1.55,-9.9743,2259194.83,3201454.164 204,000001.SZ,20200123,15.92,15.92,15.39,15.54,16.09,-0.55,-3.4183,1100592.07,1723394.336 205,000001.SZ,20200122,15.92,16.16,15.71,16.09,16.0,0.09,0.5625,719464.91,1150933.398 206,000001.SZ,20200121,16.34,16.34,15.93,16.0,16.45,-0.45,-2.7356,896603.1,1442171.431 207,000001.SZ,20200120,16.43,16.61,16.35,16.45,16.39,0.06,0.3661,746074.75,1226464.649 208,000001.SZ,20200117,16.38,16.55,16.35,16.39,16.33,0.06,0.3674,605436.69,995909.007 209,000001.SZ,20200116,16.52,16.57,16.2,16.33,16.52,-0.19,-1.1501,1028104.67,1678888.507 210,000001.SZ,20200115,16.79,16.86,16.45,16.52,16.76,-0.24,-1.432,859439.12,1424889.228 211,000001.SZ,20200114,16.99,17.27,16.76,16.76,16.99,-0.23,-1.3537,1304493.66,2217608.852 212,000001.SZ,20200113,16.75,17.03,16.61,16.99,16.69,0.3,1.7975,872133.36,1468271.683 213,000001.SZ,20200110,16.79,16.81,16.52,16.69,16.79,-0.1,-0.5956,585548.45,975154.818 214,000001.SZ,20200109,16.81,16.93,16.53,16.79,16.66,0.13,0.7803,1031636.65,1725326.806 215,000001.SZ,20200108,17.0,17.05,16.63,16.66,17.15,-0.49,-2.8571,847824.12,1423608.811 216,000001.SZ,20200107,17.13,17.28,16.95,17.15,17.07,0.08,0.4687,728607.56,1247047.135 217,000001.SZ,20200106,17.01,17.34,16.91,17.07,17.18,-0.11,-0.6403,862083.5,1477930.193 218,000001.SZ,20200103,16.94,17.31,16.92,17.18,16.87,0.31,1.8376,1116194.81,1914495.474 219,000001.SZ,20200102,16.65,16.95,16.55,16.87,16.45,0.42,2.5532,1530231.87,2571196.482
以上是“如何使用Python實現股票數據分析的可視化”這篇文章的所有內容，感謝各位的閱讀！相信大家都有了一定的了解，希望分享的內容對大家有所幫助，如果還想學習更多知識，歡迎關注億速云行業資訊頻道！
免責聲明：本站發布的內容（圖片、視頻和文字）以原創、轉載和分享為主，文章觀點不代表本網站立場，如果涉及侵權請聯系站長郵箱：is@yisu.com進行舉報，并提供相關證據，一經查實，將立刻刪除涉嫌侵權內容。
