def plot(self, code=None):
if code is None:
data=[]
axis=[]
for dates,row in self.data.iterrows():
open,high,low,close=row[1:5]
datas=[open,close,low,high]
axis.append(dates[0])
data.append(datas)
path_name='.\QA_'+self.type+'_'+self.code[0]+'_'+self.if_fq+'.html'
kline=Kline(self.code[0]+'__'+self.if_fq+'__'+self.type,width=1360,height=700)
kline.add(self.code[0],axis,data,mark_point=["max","min"], is_datazoom_show=True,datazoom_orient='horizontal')
kline.render(path_name)
QA_util_log_info('The Pic has been saved to your path: %s'%path_name)
else:
data=[]
axis=[]
for dates,row in self.select_code(code).data.iterrows():
open,high,low,close=row[1:5]
datas=[open,close,low,high]
axis.append(dates[0])
data.append(datas)
path_name='.\QA_'+self.type+'_'+code+'_'+self.if_fq+'.html'
kline=Kline(code+'__'+self.if_fq+'__'+self.type,width=1360,height=700)
kline.add(code,axis,data,mark_point=["max","min"], is_datazoom_show=True,datazoom_orient='horizontal')
kline.render(path_name)
QA_util_log_info('The Pic has been saved to your path: %s'%path_name)
def candLestick_mode():
v1 = [[2320.26, 2320.26, 2287.3,
2362.94], [2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58,
2440.38], [2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K 线图示例")
kline.add("日K", ["2019/1/{}".format(i + 1) for i in range(31)], v1)
kline.render('kline.html')
def draw_kline_pic(title: str,
labels: list,
data_package: list,
y_min: int = 0,
y_max: int = 100,
y_formatter: str = "元人民币",
path: str = './charts/k_line.html'):
"""
K线图
:param title: 画图标题
:param labels: 图例
:param data_package: 数据包
:param y_min: y轴最小值
:param y_max: y轴最大值
:param y_formatter: y轴的格式化
:param path: 保存的路径
"""
style = Style(title_top="#fff", title_pos="left", width=1920, height=900)
kline = Kline(title=title, renderer='svg', **style.init_style)
kline.add('日K',
labels,
data_package,
yaxis_min=y_min,
yaxis_max=y_max,
yaxis_formatter=y_formatter,
mark_line=["min", "max"],
mark_point=["min", "max"],
is_datazoom_show=True,
datazoom_type="both",
datazoom_range=[80, 100])
kline.render(path=path)
def draw(code):
import pandas as pd
stock = pd.read_csv(code + '.csv',
usecols=[0, 1, 2, 3, 4, 5, 6],
encoding='gbk')
stock.head()
stock_new = stock.iloc[:180, :]
stock_new_sorted = stock_new.sort_values('日期', ascending=True)
stock_new_sorted.head()
from pyecharts import Kline
stock_code = stock_new_sorted['股票代码'][0]
stock_name = stock_new_sorted['名称'][0]
index = stock_new_sorted['日期']
v = [[o, close, lowest, highest] for o, close, lowest, highest in zip(
stock_new_sorted['开盘价'], stock_new_sorted['收盘价'],
stock_new_sorted['最低价'], stock_new_sorted['最高价'])]
kline = Kline()
kline.add(stock_name + '(' + stock_code + ')' + '日K线图',
index,
v,
mark_point=["max"],
is_datazoom_show=True)
kline.render()
def test_kline_datazoom_horizontal():
kline = Kline("K 线图示例 - dataZoom 水平布局")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
data,
mark_point=["max"],
is_datazoom_show=True)
kline.render()
def test_kline_user_define_markline_style():
kline = Kline("K 线图-自定义标记点风格")
kline.add("日K", DATE, data, mark_point=["min", "max"],
mark_point_symbolsize=80,
datazoom_orient='vertical',
mark_line_valuedim=['lowest', 'highest'])
kline.show_config()
kline.render()
def test_kline_user_define_markline_style():
kline = Kline("K 线图示例 - 自定义标记线风格")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
data,
mark_line=["max"],
mark_line_symbolsize=0,
datazoom_orient='vertical',
mark_line_valuedim='close')
kline.render()
def plot(self, code=None):
'plot the market_data'
if code is None:
path_name = '.' + os.sep + 'QA_' + self.type + \
'_codepackage_' + self.if_fq + '.html'
kline = Kline('CodePackage_' + self.if_fq + '_' + self.type,
width=1360,
height=700,
page_title='QUANTAXIS')
data_splits = self.splits()
for i_ in range(len(data_splits)):
data = []
axis = []
for dates, row in data_splits[i_].data.iterrows():
open, high, low, close = row[1:5]
datas = [open, close, low, high]
axis.append(dates[0])
data.append(datas)
kline.add(self.code[i_],
axis,
data,
mark_point=["max", "min"],
is_datazoom_show=True,
datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info('The Pic has been saved to your path: %s' %
path_name)
else:
data = []
axis = []
for dates, row in self.select_code(code).data.iterrows():
open, high, low, close = row[1:5]
datas = [open, close, low, high]
axis.append(dates[0])
data.append(datas)
path_name = '.{}QA_{}_{}_{}.html'.format(os.sep, self.type, code,
self.if_fq)
kline = Kline('{}__{}__{}'.format(code, self.if_fq, self.type),
width=1360,
height=700,
page_title='QUANTAXIS')
kline.add(code,
axis,
data,
mark_point=["max", "min"],
is_datazoom_show=True,
datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info(
'The Pic has been saved to your path: {}'.format(path_name))
def plot_datastruct(__stock_hq_base, code=None):
if code is None:
path_name = '.' + os.sep + 'QA_' + __stock_hq_base.type + \
'_codepackage_' + __stock_hq_base.if_fq + '.html'
kline = Kline('CodePackage_' + __stock_hq_base.if_fq + '_' +
__stock_hq_base.type,
width=1360,
height=700,
page_title='QUANTAXIS')
data_splits = __stock_hq_base.splits()
for i_ in range(len(data_splits)):
data = []
axis = []
for dates, row in data_splits[i_].data.iterrows():
open, high, low, close = row[1:5]
datas = [open, close, low, high]
axis.append(dates[0])
data.append(datas)
kline.add(__stock_hq_base.code[i_],
axis,
data,
mark_point=["max", "min"],
is_datazoom_show=True,
datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info('The Pic has been saved to your path: %s' % path_name)
else:
data = []
axis = []
for dates, row in __stock_hq_base.select_code(code).data.iterrows():
open, high, low, close = row[1:5]
datas = [open, close, low, high]
axis.append(dates[0])
data.append(datas)
path_name = '.' + os.sep + 'QA_' + __stock_hq_base.type + \
'_' + code + '_' + __stock_hq_base.if_fq + '.html'
kline = Kline(code + '__' + __stock_hq_base.if_fq + '__' +
__stock_hq_base.type,
width=1360,
height=700,
page_title='QUANTAXIS')
kline.add(code,
axis,
data,
mark_point=["max", "min"],
is_datazoom_show=True,
datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info('The Pic has been saved to your path: %s' % path_name)
def test_kline_datazoom_vertical():
kline = Kline("K 线图-dataZoom 垂直布局")
kline.add(
"日K",
DATE,
data,
mark_line=["max"],
is_datazoom_show=True,
datazoom_orient="vertical",
)
kline.render()
def test_kline_datazoom_vertical():
kline = Kline("K 线图-dataZoom 垂直布局")
kline.add(
"日K",
DATE,
data,
mark_line=["max"],
is_datazoom_show=True,
datazoom_orient='vertical',
)
kline.render()
def test_kline_datazoom_vertical():
kline = Kline("K 线图示例 - dataZoom 垂直布局")
kline.add(
"日K",
["2017/7/{}".format(i + 1) for i in range(31)],
data,
mark_line=["max"],
is_datazoom_show=True,
datazoom_orient='vertical',
)
kline.render()
def test_kline_user_define_markline_style():
title = "K 线图-自定义标记点风格"
kline = Kline(title)
kline.add("日K",
DATE,
data,
mark_point=["min", "max"],
mark_point_symbolsize=80,
datazoom_orient='vertical',
mark_line_valuedim=['lowest', 'highest'])
kline.render()
actual_content = get_default_rendering_file_content()
assert 'lowest' in actual_content
assert 'highest' in actual_content
assert json.dumps(title) in actual_content
def create(self, code):
rsbasic = bs.query_stock_basic(code)
if len(rsbasic.data) > 0:
data_basic_list = []
while (rsbasic.error_code == '0') & rsbasic.next():
data_basic_list.append(rsbasic.get_row_data())
result_basic = pd.DataFrame(data_basic_list,
columns=rsbasic.fields)
# print(result_basic.code)
# print(result_basic.to_dict()['code_name'][0])
fields = "date,code,open,high,low,close"
rs = bs.query_history_k_data_plus(code,
fields,
start_date=self.start_date,
end_date=self.end_date,
frequency="d",
adjustflag="2")
# frequency="d"取日k线，adjustflag="3"默认不复权，
# 1：后复权；2：前复权
data_list = []
while (rs.error_code == '0') & rs.next():
# 获取一条记录，将记录合并在一起
data_list.append(rs.get_row_data())
result = pd.DataFrame(data_list, columns=rs.fields)
result.index = pd.to_datetime(result.date)
y = list(result.loc[:, ['open', 'close', 'low', 'high']].values)
x = list(result.index.strftime('%Y%m%d'))
kline = Kline(result_basic.to_dict()['code_name'][0],
title_text_size=15)
kline.add("",
x,
y,
is_datazoom_show=False,
mark_line=["average"],
mark_point=["max", "min"],
mark_point_symbolsize=60,
mark_line_valuedim=['highest', 'lowest'])
kline.render("baostock/%s.gif" % (code))
kline
else:
print("empty ----> " + rsbasic.code)
def test_kline_user_define_markline_style():
title = "K 线图-自定义标记点风格"
kline = Kline(title)
kline.add(
"日K",
DATE,
data,
mark_point=["min", "max"],
mark_point_symbolsize=80,
datazoom_orient="vertical",
mark_line_valuedim=["lowest", "highest"],
)
kline.render()
actual_content = get_default_rendering_file_content()
assert "lowest" in actual_content
assert "highest" in actual_content
assert json.dumps(title) in actual_content
def draw_kline(self, start, end, pro):
# 输入起始时间、终止时间绘制K线图，并将K线图保存到本地
if self.code == 'None':
return ''
elif len(start) != 8 or len(end) != 8:
return ''
elif int(end[0:4]) > 2020:
return ''
elif int(start[4:6]) > 12 or int(end[4:6]) > 12:
return ''
elif int(start[6:8]) > 31 or (
int(start[6:8]) > 30 and
(int(start[4:6]) == 2 or int(start[4:6]) == 4 or int(start[4:6])
== 6 or int(start[4:6]) == 9 or int(start[4:6]) == 11) or
(int(start[6:8]) > 28 and int(start[4:6]) == 2)):
return ''
elif int(start) > int(end):
return ''
price = self.get_price(start, end, pro)
price.index = pd.to_datetime(price.trade_date)
price = price.sort_index()
v1 = list(price.loc[:, ['open', 'close', 'low', 'high']].values)
v0 = list(price.index.strftime('%Y%m%d'))
kline = Kline(self.name + 'K线图', title_text_size=15)
kline.add("",
v0,
v1,
is_datazoom_show=True,
mark_line=["average"],
mark_point=["max", "min"],
mark_point_symbolsize=60,
mark_line_valuedim=['highest', 'lowest'])
# 将K线图保存到本地
root_path = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
#kline.render(os.path.join(root_path, 'static', 'klines', self.code + '-' + start + '-' + end + '.html'))
#尝试一下写到一个固定的临时文件，每次调用查看股票信息时删除，然后新建，以此来防止文件冲突和储存堆满
#临时文件为static/klines/temp_custom_date.html
target_file = os.path.join(root_path, 'static', 'klines',
'temp_custom' + '.html')
if os.path.exists(target_file):
os.remove(target_file)
kline.render(target_file)
return kline
def plot(self, code=None):
"""plot the market_data"""
if code is None:
path_name = '.' + os.sep + 'QA_' + self.type + \
'_codepackage_' + self.if_fq + '.html'
kline = Kline('CodePackage_' + self.if_fq + '_' + self.type,
width=1360, height=700, page_title='QUANTAXIS')
data_splits = self.splits()
for i_ in range(len(data_splits)):
data = []
axis = []
for dates, row in data_splits[i_].data.iterrows():
open, high, low, close = row[1:5]
datas = [open, close, low, high]
axis.append(dates[0])
data.append(datas)
kline.add(self.code[i_], axis, data, mark_point=[
"max", "min"], is_datazoom_show=True, datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info(
'The Pic has been saved to your path: %s' % path_name)
else:
data = []
axis = []
for dates, row in self.select_code(code).data.iterrows():
open, high, low, close = row[1:5]
datas = [open, close, low, high]
axis.append(dates[0])
data.append(datas)
path_name = '.{}QA_{}_{}_{}.html'.format(
os.sep, self.type, code, self.if_fq)
kline = Kline('{}__{}__{}'.format(code, self.if_fq, self.type),
width=1360, height=700, page_title='QUANTAXIS')
kline.add(code, axis, data, mark_point=[
"max", "min"], is_datazoom_show=True, datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info(
'The Pic has been saved to your path: {}'.format(path_name))
def plot_datastruct(_quotation_base, code=None):
if code is None:
path_name = '.' + os.sep + 'QA_' + _quotation_base.type + \
'_codepackage_' + _quotation_base.if_fq + '.html'
kline = Kline('CodePackage_' + _quotation_base.if_fq + '_' + _quotation_base.type,
width=1360, height=700, page_title='QUANTAXIS')
data_splits = _quotation_base.splits()
for i_ in range(len(data_splits)):
data = []
axis = []
for dates, row in data_splits[i_].data.iterrows():
open, high, low, close = row[1:5]
datas = [open, close, low, high]
axis.append(dates[0])
data.append(datas)
kline.add(_quotation_base.code[i_], axis, data, mark_point=[
"max", "min"], is_datazoom_show=True, datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info('The Pic has been saved to your path: %s' % path_name)
else:
data = []
axis = []
for dates, row in _quotation_base.select_code(code).data.iterrows():
open, high, low, close = row[1:5]
datas = [open, close, low, high]
axis.append(dates[0])
data.append(datas)
path_name = '.' + os.sep + 'QA_' + _quotation_base.type + \
'_' + code + '_' + _quotation_base.if_fq + '.html'
kline = Kline(code + '__' + _quotation_base.if_fq + '__' + _quotation_base.type,
width=1360, height=700, page_title='QUANTAXIS')
kline.add(code, axis, data, mark_point=[
"max", "min"], is_datazoom_show=True, datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info('The Pic has been saved to your path: %s' % path_name)
def view(code, start_, end_):
'''
使用pyecharts展示数据
:param code: 股票代码
:param start_: 开始时间（包含）格式为'2018-01-01'
:param end_: 结束时间（包含）格式为'2018-01-01'
:return:
'''
# 从数据库获取数据
th = get_data_from_db(code, start_, end_)
'''
官网网址：http://pyecharts.org/#/zh-cn/charts?id=klinecandlestick%ef%bc%88k%e7%ba%bf%e5%9b%be%ef%bc%89
Kline.add() 方法签名
add(name, x_axis, y_axis, **kwargs)
name -> str
图例名称
x_axis -> list
x 坐标轴数据
y_axis -> [list], 包含列表的列表
y 坐标轴数据。数据中，每一行是一个『数据项』，每一列属于一个『维度』。
数据项具体为 [open, close, lowest, highest] （即：[开盘值, 收盘值, 最低值, 最高值]）
'''
# 此处存放的是K线数组
v1 = th.values.tolist()
# 存放X轴横坐标数组，此处选用的是日期
v2 = [str(x.strftime('%Y-%m-%d')) for x in th.index]
kline = Kline("{0} K线图".format(code))
'''
is_datazoom_show:是否显示放大缩小
mark_point:标记最大最小值
'''
kline.add("日K", v2, v1, is_datazoom_show=True, mark_point=["min", "max"])
# 打印配置信息
kline.show_config()
try:
kline.render('股票[{0}]K线图.html'.format(code))
except Exception as e:
print('生成图形出错啦[{0}]'.format(e))
def create_view():
# open, close, lowest, highest]
v1 = []
kline = Kline("日K线图")
rows = SQLiteUtil.select_all()
down_flag = []
for row in rows:
down_flag.append(row[0])
v1.append([row[3], row[4], row[1], row[2]])
kline.add(
"日K",
down_flag,
v1,
mark_point=["max"],
is_datazoom_show=True,
)
kline.render(path="../view/day.html")
v1 = []
kline = Kline("7天K线图")
rows = SQLiteUtil.select_group_by_week()
down_flag = []
for row in rows:
down_flag.append(row.get("week_flag"))
v1.append([
row.get("first_price"),
row.get("last_price"),
row.get("min_price"),
row.get("max_price")
])
kline.add(
"周K",
down_flag,
v1,
mark_point=["max"],
is_datazoom_show=True,
)
kline.render(path="../view/week.html")
v1 = []
kline = Kline("30天K线图")
rows = SQLiteUtil.select_group_by_moon()
down_flag = []
for row in rows:
down_flag.append(row.get("moon_flag"))
v1.append([
row.get("first_price"),
row.get("last_price"),
row.get("min_price"),
row.get("max_price")
])
kline.add(
"月K",
down_flag,
v1,
mark_point=["max"],
is_datazoom_show=True,
)
kline.render(path="../view/moon.html")
def test_kline():
# kline_0
v1 = [[2320.26, 2320.26, 2287.3,
2362.94], [2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58,
2440.38], [2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K 线图示例")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)], v1)
kline.show_config()
kline.render()
# kline_1
kline = Kline("K 线图示例")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
v1,
mark_point=["max"],
is_datazoom_show=True)
kline.show_config()
kline.render()
# kline_2
kline = Kline("K 线图示例")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
v1,
mark_point=["max"],
is_datazoom_show=True,
datazoom_orient='vertical')
kline.show_config()
kline.render()
def test_kline():
# kline_0
v1 = [[2320.26, 2320.26, 2287.3, 2362.94],
[2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K 线图示例")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)], v1)
kline.show_config()
kline.render()
# kline_1
kline = Kline("K 线图示例")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)], v1, mark_point=["max"], is_datazoom_show=True)
kline.show_config()
kline.render()
# kline_2
kline = Kline("K 线图示例")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)], v1, mark_point=["max"],
is_datazoom_show=True, datazoom_orient='vertical')
kline.show_config()
kline.render()
#正常显示画图时出现的中文和负号
if __name__ == '__main__':
token = '8b09761b8473e73a0a57bafa07ea2766dfba5d3472d527c40e03d47b'
pro = ts.pro_api(token)
from pylab import mpl
mpl.rcParams['font.sans-serif'] = ['SimHei']
mpl.rcParams['axes.unicode_minus'] = False
# 获取平安银行日行情数据
pa = pro.daily(ts_code='000001.SZ',
start_date='20180101',
end_date='20190106')
# pa.head()
# K线图可视化
pa.index = pd.to_datetime(pa.trade_date)
pa = pa.sort_index()
v1 = list(pa.loc[:, ['open', 'close', 'low', 'high']].values)
t = pa.index
v0 = list(t.strftime('%Y%m%d'))
kline = Kline("平安银行K线图", title_text_size=15)
kline.add("",
v0,
v1,
is_datazoom_show=True,
mark_line=["average"],
mark_point=["max", "min"],
mark_point_symbolsize=60,
mark_line_valuedim=['highest', 'lowest'])
kline.render("上证指数图.html")
def test_kline_datazoom_horizontal():
kline = Kline("K 线图-dataZoom 水平布局")
kline.add("日K", DATE, data,
mark_point=["max"], is_datazoom_show=True)
kline.render()
def test_kline_default():
kline = Kline("K 线图-默认示例")
kline.add("日K", DATE, data)
kline.render()
#bs.logout()
result.info()
#将某些object转化numeric
result=result.apply(pd.to_numeric, errors='ignore')
result.info()
result.close.plot(figsize=(16,8))
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
#plt.show()
from pyecharts import Kline
y=list(result.loc[:,['open','close','low','high']].values)
x=list(result.index.strftime('%Y%m%d'))
kline = Kline("000831K线图",title_text_size=15)
kline.add("", x, y,is_datazoom_show=False,
mark_line=["average"],
mark_point=["max", "min"],
mark_point_symbolsize=60,
mark_line_valuedim=['highest', 'lowest'] )
kline.render("gif/000831_bao.gif")
kline
print()
import tushare as ts
import pandas as pd
ts.set_token('xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx')
pro = ts.pro_api()
df1 = pro.daily(ts_code='000938.SZ',
start_date='20150401',
end_date='20180930')
df = df1.sort_values(by=['trade_date'])
df.reset_index(level=0, inplace=True)
df.drop(['index'], axis=1, inplace=True)
print(df)
df.to_csv("aaa.csv")
date = df.trade_date.tolist()
data = []
for idx in df.index:
row = [
df.iloc[idx]['open'], df.iloc[idx]['close'], df.iloc[idx]['low'],
df.iloc[idx]['high']
]
data.append(row)
kline = Kline("K 线图示例")
kline.add(
"日K",
date,
data,
mark_point=["max"],
is_datazoom_show=True,
)
kline.render()
v1 = [[2320.26, 2320.26, 2287.3, 2362.94], [2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92], [2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89,
2383.76], [2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57,
2421.15], [2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42], [2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89], [2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43,
2444.8], [2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61,
2397.94], [2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76,
2330.88], [2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89,
2340.71], [2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92,
2366.16], [2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54], [2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6,
2351.44], [2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59,
2333.67], [2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83,
2333.29], [2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K线图示例")
kline.add("日K", ["2018/7/{}".format(i + 1) for i in range(31)], v1)
kline.render(path="kline.html")
def plot(self, code=None):
def kline_formater(param):
return param.name + ':' + vars(param)
"""plot the market_data"""
if code is None:
path_name = '.' + os.sep + 'QA_' + self.type + \
'_codepackage_' + self.if_fq + '.html'
kline = Kline('CodePackage_' + self.if_fq + '_' + self.type,
width=1360,
height=700,
page_title='QUANTAXIS')
bar = Bar()
data_splits = self.splits()
for ds in data_splits:
data = []
axis = []
if ds.data_type[-3:] == 'day':
datetime = np.array(ds.date.map(str))
else:
datetime = np.array(ds.datetime.map(str))
ohlc = np.array(ds.data.loc[:,
['open', 'close', 'low', 'high']])
#amount = np.array(ds.amount)
#vol = np.array(ds.volume)
kline.add(ds.code[0],
datetime,
ohlc,
mark_point=["max", "min"],
is_datazoom_show=False,
datazoom_orient='horizontal')
kline.render(path_name)
webbrowser.open(path_name)
QA_util_log_info('The Pic has been saved to your path: %s' %
path_name)
else:
data = []
axis = []
ds = self.select_code(code)
data = []
#axis = []
if self.data_type[-3:] == 'day':
datetime = np.array(ds.date.map(str))
else:
datetime = np.array(ds.datetime.map(str))
ohlc = np.array(ds.data.loc[:, ['open', 'close', 'low', 'high']])
#amount = np.array(ds.amount)
vol = np.array(ds.volume)
kline = Kline('{}__{}__{}'.format(code, self.if_fq, self.type),
width=1360,
height=700,
page_title='QUANTAXIS')
bar = Bar()
kline.add(
self.code,
datetime,
ohlc,
mark_point=["max", "min"],
# is_label_show=True,
is_datazoom_show=True,
is_xaxis_show=False,
# is_toolbox_show=True,
tooltip_formatter='{b}:{c}', # kline_formater,
# is_more_utils=True,
datazoom_orient='horizontal')
bar.add(self.code,
datetime,
vol,
is_datazoom_show=True,
datazoom_xaxis_index=[0, 1])
path_name = '.{}QA_{}_{}_{}.html'.format(os.sep, self.type, code,
self.if_fq)
# kline.add(code, axis, data, mark_point=[
# "max", "min"], is_datazoom_show=True, datazoom_orient='horizontal')
grid = Grid(width=1360, height=700, page_title='QUANTAXIS')
grid.add(bar, grid_top="80%")
grid.add(kline, grid_bottom="30%")
grid.render(path_name)
webbrowser.open(path_name)
QA_util_log_info(
'The Pic has been saved to your path: {}'.format(path_name))
basic = pro.stock_basic(list_status='L')
pa = pro.daily(ts_code='000831.SZ', start_date='20190101', end_date='20190220')
from pyecharts import Kline
#from pyecharts.engine import create_default_environment
pa.index = pd.to_datetime(pa.trade_date)
pa = pa.sort_index()
y = list(pa.loc[:, ['open', 'close', 'low', 'high']].values)
t = pa.index
x = list(t.strftime('%Y%m%d'))
kline = Kline("000831K线图", title_text_size=15)
kline.add("",
x,
y,
is_datazoom_show=False,
mark_line=["average"],
mark_point=["max", "min"],
mark_point_symbolsize=60,
mark_line_valuedim=['highest', 'lowest'])
# create_default_environment(filet_ype)
# file_type: 'html', 'svg', 'png', 'jpeg', 'gif' or 'pdf'
#env = create_default_environment('jpeg')
#env.render_chart_to_file(kline, path='line.jpeg')
kline.render("gif/000831.gif")
kline
def test_kline_default():
kline = Kline("K 线图示例 - 默认")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)], data)
kline.render()
#-*-coding:utf-8
from pyecharts import Kline
import pandas_datareader.data as web
import datetime
df_stockload = web.DataReader("000001.SS", "yahoo",
datetime.datetime(2018, 1, 1),
datetime.datetime(2019, 1, 1))
kline = Kline("行情显示图")
# 数据转换
ohlc = list(
zip(df_stockload.Open, df_stockload.Close, df_stockload.Low,
df_stockload.High))
dates = df_stockload.index.strftime('%Y-%m-%d')
kline.add("日K",
dates,
ohlc,
is_datazoom_show=True,
mark_line=["max"],
mark_point=["max"],
xaxis_rotate=30,
yaxis_min=0.9 * min(df_stockload["Low"]))
kline.show_config()
kline.render(r'k.html')
def test_custom():
# custom_0
attr = ['A', 'B', 'C', 'D', 'E', 'F']
v1 = [10, 20, 30, 40, 50, 60]
v2 = [15, 25, 35, 45, 55, 65]
v3 = [38, 28, 58, 48, 78, 68]
bar = Bar("Line - Bar 示例")
bar.add("bar", attr, v1)
line = Line()
line.add("line", v2, v3)
bar.custom(line.get_series())
bar.show_config()
bar.render()
# custom_1
v1 = [10, 20, 30, 40, 50, 60]
v2 = [30, 30, 30, 30, 30, 30]
v3 = [50, 50, 50, 50, 50, 50]
v4 = [10, 10, 10, 10, 10, 10]
es = EffectScatter("Scatter - EffectScatter 示例")
es.add("es", v1, v2)
scatter = Scatter()
scatter.add("scatter", v1, v3)
es.custom(scatter.get_series())
es_1 = EffectScatter()
es_1.add("es_1", v1, v4, symbol='pin', effect_scale=5)
es.custom(es_1.get_series())
es.show_config()
es.render()
# custom_2
import random
v1 = [[2320.26, 2320.26, 2287.3,
2362.94], [2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58,
2440.38], [2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
attr = ["2017/7/{}".format(i + 1) for i in range(31)]
kline = Kline("Kline - Line 示例")
kline.add("日K", attr, v1)
line_1 = Line()
line_1.add("line-1", attr, [random.randint(2400, 2500) for _ in range(31)])
line_2 = Line()
line_2.add("line-2", attr, [random.randint(2400, 2500) for _ in range(31)])
kline.custom(line_1.get_series())
kline.custom(line_2.get_series())
kline.show_config()
kline.render()
# ts.set_token(token)
pro = ts.pro_api(token)
# 获取当前上市的股票代码、简称、注册地、行业、上市时间等数据
basic = pro.stock_basic(list_status='L')
# 查看前五行数据
# basic.head(5)
# 获取日行情数据
pa = pro.daily(ts_code='000711.SZ', start_date='20180101', end_date='20190106')
# pa.head()
pa.index = pd.to_datetime(pa.trade_date)
pa = pa.sort_index()
v1 = list(pa.loc[:, ['open', 'close', 'low', 'high']].values)
t = pa.index
v0 = list(t.strftime('%Y%m%d'))
kline = Kline("K线图", title_text_size=15)
kline.add("",
v0,
v1,
is_datazoom_show=True,
mark_line=["average"],
mark_point=["max", "min"],
mark_point_symbolsize=60,
mark_line_valuedim=['highest', 'lowest'])
kline.render("K线图.html")
kline
