def draw(df, xf, yf, tf, title='New Stock Chart'):
'''
Draw hight stock chart by pandas.DataFrame
Args:
df: dataFrame
xf: field name of dataFrame to x coordinate, the value of x must be unique datetime.
yf: field name of dataFrame to y coordinate.
tf: field name of dataFrame to line title.
'''
uniques = df[tf].unique()
# log.debug(str(uniques))
c = Highstock()
for unique in uniques:
sel_df = df[df[tf] == unique]
sel_df = sel_df.loc[:, [xf, yf]]
xyl = xy(sel_df)
c.add_data_set(xyl, series_type='line', name=unique)
options = {
'title': {
'text': title
},
}
c.set_dict_options(options)
c.save_file()
log.info('Successful completion of drawing.')
def plot(self, plt_type='all'):
self.getsecID(sec=1)
if not exist:
return self.etf + ' ceased trading'
#這邊廢code很多QQ
#為避免error，先創一堆空的dict（相信這邊有更好的寫法XD）
nav_data = dict()
price_data = dict()
volume_data = dict()
nav_data[self.etf] = dict()
price_data[self.etf] = dict()
volume_data[self.etf] = dict()
if plt_type == 'all':
nav_data = self.data(data_type='nav')
price_data = self.data(data_type='price')
volume_data = self.data(data_type='volume')
elif plt_type == 'nav':
nav_data = self.data(data_type='nav')
elif plt_type == 'price':
price_data = self.data(data_type='price')
else:
return 'Sorry, plt_type should be nav, price or all'
#用highchart裡的hichstock畫圖
H = Highstock()
nav_high_data = [[
datetime.strptime(i, "%Y-%m-%d"),
nav_data[list(nav_data.keys())[0]][i]
] for i in nav_data[list(nav_data.keys())[0]]]
price_high_data = [[
datetime.strptime(i, "%Y-%m-%d"),
price_data[list(price_data.keys())[0]][i]
] for i in price_data[list(price_data.keys())[0]]]
volume_high_data = [[
datetime.strptime(i, "%Y-%m-%d"),
volume_data[list(volume_data.keys())[0]][i]
] for i in volume_data[list(volume_data.keys())[0]]]
if plt_type == 'all':
H.add_data_set(price_high_data,
'line',
'price',
id='dataseries',
color='#969696',
tooltip={'valueDecimals': 4})
H.add_data_set(nav_high_data,
'line',
'nav',
id='dataseries',
tooltip={'valueDecimals': 4})
H.add_data_set(volume_high_data,
'column',
'Volume',
yAxis=1,
color='#969696')
elif plt_type == 'nav':
H.add_data_set(nav_high_data,
'line',
'nav',
id='dataseries',
tooltip={'valueDecimals': 4})
elif plt_type == 'price':
H.add_data_set(price_high_data,
'line',
'price',
id='dataseries',
color='#969696',
tooltip={'valueDecimals': 4})
options = {
'rangeSelector': {
'selected': 4
},
'title': {
'text': self.etf.upper()
},
'tooltip': {
'style': {
'width': '200px'
},
'shared':
True,
'pointFormat':
'<span style="color:{series.color}">{series.name}</span>: <b>{point.y}</b><br/>',
},
'yAxis': [{
'labels': {
'align': 'right',
'x': -3
},
'title': {
'text': 'USD'
},
'height': '60%',
'lineWidth': 0.5
}, {
'labels': {
'align': 'right',
'x': -3
},
'title': {
'text': 'Volume'
},
'top': '65%',
'height': '35%',
'offset': 0,
'lineWidth': 2
}],
#'plotOptions': {'series': {'compare': 'percent'}},
}
H.set_dict_options(options)
return H
H.add_data_set(data, 'line', 'USD to EUR', id='dataseries')
H.add_data_set(data2,
'flags',
onSeries='dataseries',
shape='circlepin',
width=16)
options = {
'rangeSelector': {
'selected': 0
},
'title': {
'text': 'USD to EUR exchange rate'
},
'tooltip': {
'style': {
'width': '200px'
},
'valueDecimals': 4,
'shared': True
},
'yAxis': {
'title': {
'text': 'Exchange rate'
}
},
}
H.set_dict_options(options)
H.htmlcontent
names = ["MSFT", "AAPL", "GOOG"]
for name in names:
data_url = "http://www.highcharts.com/samples/data/jsonp.php?filename=" + name.lower() + "-c.json&callback=?"
data = jsonp_loader(data_url, sub_d=r"(\/\*.*\*\/)")
H.add_data_set(data, "line", name)
options = {
"rangeSelector": {"selected": 4},
"yAxis": {
"labels": {
"formatter": "function () {\
return (this.value > 0 ? ' + ' : '') + this.value + '%';\
}"
},
"plotLines": [{"value": 0, "width": 2, "color": "silver"}],
},
"plotOptions": {"series": {"compare": "percent"}},
"tooltip": {
"pointFormat": '<span style="color:{series.color}">{series.name}</span>: <b>{point.y}</b> ({point.change}%)<br/>',
"valueDecimals": 2,
},
}
H.set_dict_options(options)
H.htmlcontent
def plot(self,
title=False,
width=600,
height=300,
load_js=None,
js_sources=[]):
chart_height = (height +
50) * self.number_of_candlestick_charts - 50 + 200
H = Highstock(width=width, height=chart_height)
groupingUnits = [
['hour', [60]],
]
with open(
os.path.join(os.path.dirname(os.path.abspath(__file__)),
"files/load.jinja")) as f:
load_tempate = jinja2.Template(f.read())
options = {
'rangeSelector': {
'buttons': [{
'type': 'minute',
'count': 180,
'text': '3h'
}, {
'type': 'minute',
'count': 360,
'text': '6h'
}, {
'type': 'minute',
'count': 720,
'text': '12h'
}, {
'type': 'minute',
'count': 60 * 24,
'text': '1d'
}, {
'type': 'minute',
'count': 60 * 48,
'text': '2d'
}, {
'type': 'second',
'count': 1,
'text': '1s'
}, {
'type': 'second',
'count': 10,
'text': '10s'
}],
'selected':
4,
'inputEnabled':
False
},
'plotOptions': {
'series': {
'turboThreshold:': 0,
'dataGrouping': {
'enabled': False,
},
'animation': False,
},
'scatter': {
'turboThreshold:': 0,
'marker': {
'radius': 5,
'symbol': 'circle',
'states': {
'hover': {
'enabled': True,
'lineColor': 'rgb(100,100,100)'
}
}
},
'tooltip': {
'pointFormat': '{series.name} x:{point.x}, y:{point.y}'
#'pointFormatter': """
#function () { debugger; }
#"""
},
'states': {
'hover': {
'marker': {
'enabled': False
}
}
},
},
},
'navigator': {
'enabled': True,
'height': 20
},
'chart': {
'animation': False,
},
'title': {
'text': '',
'style': {
'display': 'none'
}
},
'legend': {
'enabled': True,
},
'yAxis': []
}
if title:
options['title'] = {'text': title}
if load_js:
load_js = load_tempate.render(symbols=self.symbols)
options['event']['load'] = load_js
idx = -1
current_y = -height
for chart_type, symbol, data, is_new_chart in self.symbols:
if is_new_chart:
idx += 1
current_y += height + 50
options['yAxis'].append({
'labels': {
'align': 'right',
'x': -3
},
'title': {
'text': 'y'
},
'top': '%dpx' % (current_y),
'height': '%dpx' % (height),
'lineWidth': 2,
'offset': 0,
})
if chart_type == 'candlestick':
H.add_data_set(data,
chart_type,
symbol,
yAxis=idx,
dataGrouping={})
elif chart_type == 'line':
H.add_data_set(data,
chart_type,
symbol,
yAxis=idx,
dataGrouping={})
elif chart_type == 'scatter':
H.add_data_set(data,
chart_type,
symbol,
yAxis=idx,
dataGrouping={},
turboThreshold=0)
H.set_dict_options(options)
H.add_JSscript(self.theme, "head")
for js_source in js_sources:
H.add_JSsource(js_source)
return H
def plot(self,
title=False,
width=600,
height=300,
load_js=None,
js_sources=[]):
chart_height = (height + 50) * 1 - 50 + 200
H = Highstock(width=width, height=chart_height)
groupingUnits = [
['hour', [60]],
]
with open(
os.path.join(os.path.dirname(os.path.abspath(__file__)),
"files/load.jinja")) as f:
load_tempate = jinja2.Template(f.read())
options = {
'rangeSelector': {
'buttons': [{
'type': 'minute',
'count': 180,
'text': '3h'
}, {
'type': 'minute',
'count': 360,
'text': '6h'
}, {
'type': 'minute',
'count': 720,
'text': '12h'
}, {
'type': 'minute',
'count': 60 * 24,
'text': '1d'
}, {
'type': 'minute',
'count': 60 * 48,
'text': '2d'
}, {
'type': 'second',
'count': 1,
'text': '1s'
}, {
'type': 'second',
'count': 10,
'text': '10s'
}],
'selected':
4,
'inputEnabled':
False
},
'plotOptions': {
'series': {
'turboThreshold:': 0,
'dataGrouping': {
'enabled': False,
},
'animation': False
}
},
'navigator': {
'enabled': True,
'height': 20
},
'chart': {
'animation': False,
},
'legend': {
'enabled': True,
},
'yAxis': [],
'title': {
'text': '',
'style': {
'display': 'none'
}
},
}
if title:
options['title'] = {'text': title}
if load_js:
load_js = load_tempate.render(symbols=self.symbols)
options['event']['load'] = load_js
symbol_data = {}
for idx, (symbol, data) in enumerate(self.symbols):
symbol_data[symbol] = data
options['yAxis'].append({
'labels': {
'align': 'right',
'x': -3
},
'title': {
'text': 'y'
},
'lineWidth': 2,
'offset': 0,
})
H.add_data_set(data, 'line', symbol, dataGrouping={})
H.set_dict_options(options)
H.add_JSscript(self.theme, "head")
for js_source in js_sources:
H.add_JSsource(js_source)
return H
data = Load.FinData(dataset='TaiwanStockPrice',
select='2330',
date='2018-10-10')
print(' change type of dataframe to highcharts ')
data['date'] = date2millisecond(data['date'])
list_data = []
for i in range(len(data)):
tem = [
int(data.loc[i, 'date']),
float(data.loc[i, 'max']),
float(data.loc[i, 'min'])
]
list_data.append(tem)
chart.add_data_set(list_data, 'arearange', 'Temperatures')
options = {
'rangeSelector': {
'selected': 2
},
'title': {
'text': 'Temperature variation by day'
},
}
chart.set_dict_options(options)
# This will generate and save a .html file at the location you assign
chart.save_file()
def hc_candlestick_and_volume(data, title, theme=None):
H = Highstock()
ohlc = []
volume = []
groupingUnits = [['week', [1]], ['month', [1, 2, 3, 4, 6]]]
for i in range(len(data)):
ohlc.append([
data[i][0], # the date
data[i][1], # open
data[i][2], # high
data[i][3], # low
data[i][4] # close
])
volume.append([
data[i][0], # the date
data[i][5] # the volume
])
options = {
'rangeSelector': {
'selected': 1
},
'title': {
'text': title
},
'yAxis': [{
'labels': {
'align': 'right',
'x': -3
},
'title': {
'text': 'OHLC'
},
'height': '60%',
'lineWidth': 2
}, {
'labels': {
'align': 'right',
'x': -3
},
'title': {
'text': 'Volume'
},
'top': '65%',
'height': '35%',
'offset': 0,
'lineWidth': 2
}],
}
H.add_data_set(ohlc,
'candlestick',
'OHLC',
dataGrouping={'units': groupingUnits})
H.add_data_set(volume,
'column',
'Volume',
yAxis=1,
dataGrouping={'units': groupingUnits})
H.set_dict_options(options)
return hc_plot(H, title, theme)
def pplot_from_df(df, kind='line', stock=False, y_axes=None, debug=False, **kwargs):
"""
:param df: (pd.DataFrame): Column names become series names
:param kind: (str or list): Use list of same length as number of cols for multiple plot types
(e.g. ['line_w_col', 'column'])
:param stock:
:param y_axes:
:param debug: (bool): Pretty prints options json
:param kwargs: (): Plotting options such as resolution, labels, color, etc.
:return:
"""
# If series given instead of DataFrame, convert:
df = pd.DataFrame(df)
# If no columns, do nothing:
if df.shape[1] == 0:
print("nothing to plot...")
return
# Create a color list for each line to plot:
if 'colors' not in kwargs:
kwargs['colors'] = map(
lambda val: val.get_hex_l(),
list(Color('#1492FB').range_to(Color('#27662A'), df.shape[1]))
)
# Set y axis
if y_axes is None:
y_axes = [1] * df.shape[1]
else:
assert (len(y_axes) == df.shape[1]), "y_axes must be list of same length as dataframe columns"
# Should also assert something about the values in this list... later
# Create highcharts_df object:
# (Use height and width if provided):
if stock:
hc_visualization = Highstock(**{key: kwargs.pop(key) for key in ['width', 'height'] if key in kwargs})
else:
hc_visualization = Highchart(**{key: kwargs.pop(key) for key in ['width', 'height'] if key in kwargs})
# Set timeseries encoding automatically:
if df.index.is_all_dates:
# NOTE *** AFTER monthes, I finally figured out that certain types of option settings
# were the cause of time not encoding properly. Basically, customer jinja-js like {x.point} functions
# need to be created carefully with timestamps in mind. Also, data must be encoded as 32 bit datetime.
# (e.g. df.index.map(lambda dt: dt.to_datetime()), or [(datetime.datetime(2016,9,28), $val), ...]
hc_visualization.set_options('xAxis', {'type': 'datetime'})
# Set options (chart customization):
options = get_highchart_options(**kwargs)
if kind == 'line':
for col_idx, col in enumerate(df.columns):
hc_visualization = _highcharts_add_data_set(hc_visualization, df[col], col, kind, y_axes[col_idx])
elif kind == 'bar' or kind == 'column':
# Add bar categories (dataframe index):
options['xAxis']['categories'] = list(df.index)
# Add grouped column/bar data:
for col_idx, col in enumerate(df.columns):
hc_visualization = _highcharts_add_data_set(hc_visualization, df[col], col, kind, y_axes[col_idx])
elif isinstance(kind, list):
# Make sure the kind list is the right size:
assert len(kind) == df.shape[1], "list kind must be the same length as df"
# If columns in the list, map to line_w_col:
if 'bar' in kind or 'column' in kind:
kind = map(lambda a_kind: ("%s_w_col" % a_kind) if a_kind == 'line' else a_kind, kind)
# Add categories:
options['xAxis']['categories'] = list(df.index.values)
# Add grouped data:
for col_idx, col in enumerate(df.columns):
hc_visualization = _highcharts_add_data_set(hc_visualization, df[col], col, kind[col_idx], y_axes[col_idx])
# Set options:
hc_visualization.set_dict_options(options)
# Print options json if debug mode is on:
if debug:
pp = pprint.PrettyPrinter(indent=1)
pp.pprint(options)
return hc_visualization
def hc_candlestick_and_volume(data, title, theme=None):
H = Highstock()
ohlc = []
volume = []
groupingUnits = [
['week', [1]],
['month', [1, 2, 3, 4, 6]]
]
for i in range(len(data)):
ohlc.append(
[
data[i][0], # the date
data[i][1], # open
data[i][2], # high
data[i][3], # low
data[i][4] # close
]
)
volume.append(
[
data[i][0], # the date
data[i][5] # the volume
]
)
options = {
'rangeSelector': {
'selected': 1
},
'title': {
'text': title
},
'yAxis': [{
'labels': {
'align': 'right',
'x': -3
},
'title': {
'text': 'OHLC'
},
'height': '60%',
'lineWidth': 2
}, {
'labels': {
'align': 'right',
'x': -3
},
'title': {
'text': 'Volume'
},
'top': '65%',
'height': '35%',
'offset': 0,
'lineWidth': 2
}],
}
H.add_data_set(ohlc, 'candlestick', 'OHLC', dataGrouping = {
'units': groupingUnits
})
H.add_data_set(volume, 'column', 'Volume', yAxis = 1, dataGrouping = {
'units': groupingUnits
})
H.set_dict_options(options)
return hc_plot(H, title, theme)
def creatChart(klines, symbol):
filename = "%s_dayk" % symbol
ohlc = []
volume = []
for line in klines:
ohlc.append([
line[0],
#open
float(line[1]),
#high
float(line[2]),
# low
float(line[3]),
# close
float(line[4])
])
volume.append([line[0], float(line[5])])
H = Highstock()
groupingUnits = [['day', [1]]]
options = {
'rangeSelector': {
'selected': 4
},
'chart': {
'zoomType': 'x',
'reflow': True,
'height': 900
},
'title': {
'text': '%s' % (symbol)
},
'subtitle': {
'text': filename
},
'yAxis': [{
'labels': {
'align': 'right',
'x': -3
},
'title': {
'text': 'OHLC'
},
'height': '60%',
'lineWidth': 2
}, {
'labels': {
'align': 'right',
'x': -3
},
'title': {
'text': 'Volume'
},
'top': '65%',
'height': '35%',
'offset': 0,
'lineWidth': 2
}],
}
H.add_data_set(ohlc,
'candlestick',
symbol,
dataGrouping={'units': groupingUnits})
H.add_data_set(volume,
'column',
'Volume',
yAxis=1,
dataGrouping={'units': groupingUnits})
H.set_dict_options(options)
H.save_file(filename)
print("===--- Completed ---===")
def main(argv):
from highcharts import Highstock # 暂时这样避免其他脚本 import 出错
unittest()
opts, args = parse_options(argv)
#exchanges = ('binance', 'huobipro', 'okex', 'zb')
#symbol = 'qtum/btc'
#sdt = '2018-01-20 18-00-00'
#edt = '2018-01-20 18-59-00'
#folder = r'C:\Users\Eph\Desktop\CC\trade\ccxtbot\CCMarkets\data'
exchanges = args
symbol = opts.get('symbol')
sdt = opts.get('start')
edt = opts.get('stop')
folder = opts.get('folder')
prec = int(opts.get('prec', 8))
fname = opts.get('file', 'StockChart')
verbose = opts.get('verbose', False)
if not exchanges or not symbol or not sdt or not edt or not folder:
usage(argv[0])
return 2
options = {
'chart': {
'height': '50%', # default None
},
'title': {
'text': 'Price Difference',
},
"tooltip": {
"xDateFormat": "%Y-%m-%d %H:%M:%S %A", # NOTE: BUG, 设置不生效
'pointFormat': '<span style="color:{point.color}">' + '\\u25CF'.decode('unicode-escape') + \
'</span> {series.name}: <b>{point.y}</b><br/>',
'padding': 1, # default 8
},
"legend": {
"enabled": True
},
"xAxis": {
"type": "datetime"
},
'yAxis': {
'title': {
'text': '价格',
},
'opposite': True, # False 表示在左边显示，默认值为 True
},
# 这是K线图的属性，不画K线图的话不需要
"plotOptions": {
"candlestick": {
"color": "#d75442",
"upColor": "#6ba583"
}
},
"rangeSelector": {
"buttons": [
{
"type" : "hour",
"count" : 1,
"text" : "1h",
},
{
"type" : 'hour',
"count" : 3,
"text" : "3h"
},
{
"type" : "hour",
"count" : 6,
"text" : "6h"
},
{
"type" : "hour",
"count" : 12,
"text" : "12h"
},
{
"type" : "all",
"text" : "All"
}
],
#"selected": 2, # 默认选择的索引号，从0开始，默认值为 undefined
"inputEnabled": True,
"inputBoxWidth": 150, # default 90
'inputDateFormat': '%Y/%m/%d %H:%M:%S',
'inputEditDateFormat': '%Y/%m/%d %H:%M:%S',
},
}
chart = Highstock()
chart.set_options('global', {'timezoneOffset': -8 * 60})
chart.set_dict_options(options)
#chart.set_options('chart', {'height': None})
chart.set_options(
'tooltip',
{
#'pointFormat': '<span style="color:{point.color}">' + '\\u25CF'.decode('unicode-escape') + \
#'</span> {series.name}: <b>{point.y:.%df}</b><br/>' % prec,
'valueDecimals': prec,
'valueSuffix':
' ' + symbol.replace('/', '_').upper().split('_')[1],
})
ers = []
stats = {}
for exchange in exchanges:
inst = ExchangeRecords(exchange, symbol, sdt, edt, folder)
ers.append(inst)
stats[exchange] = {}
stats[exchange]['records_count'] = 0
chart.set_options('subtitle', {'text': ers[0].symbol.replace('_', '/')})
# 'binance': {'Buy': x, 'Sell': y}
all_records = {}
loop_count = 0
# 标记哪个交易所已经拿完数据了
# {exchange: True/False, ...}
ctl = {}
for inst in ers:
ctl[inst.exchange] = False
while True:
all_true = True
for v in ctl.itervalues():
if not v:
all_true = False
break
if ctl and all_true:
break
loop_count += 1
for inst in ers:
record = inst.get_one_record()
if record is None:
ctl[inst.exchange] = True
continue
records_dict = all_records.setdefault(inst.exchange, {})
if not record:
#ctl[inst.exchange] = True
continue
stats[inst.exchange]['records_count'] += 1
# 不需要小数点
t = int(int(float(record[0])) * 1000)
#t += 3600*1000*8 # GMT+8
buy = records_dict.setdefault('buy', [])
buy.append([t, float(record[1])])
sell = records_dict.setdefault('sell', [])
sell.append([t, float(record[2])])
last = records_dict.setdefault('last', [])
last.append([t, float(record[3])])
if verbose:
print('loop_count:', loop_count)
Log(json.dumps(stats, indent=4, sort_keys=True))
for exchange in exchanges:
records_dict = all_records[exchange]
chart.add_data_set(records_dict['buy'],
series_type='line',
name='%s buy' % exchange)
chart.add_data_set(records_dict['sell'],
series_type='line',
name='%s sell' % exchange)
chart.add_data_set(records_dict['last'],
series_type='line',
name='%s last' % exchange)
# 后缀名值 .html
chart.save_file(filename=fname)
Log('Successfully write to the file:', fname + '.html')
