def vtradevolume(cftable, freq="D"):
"""
aid function on visualization of trade summary
:param cftable: cftable (pandas.DataFrame) with at least date and cash columns
:param freq: one character string, frequency label, now supporting D for date,
W for week and M for month, namely the trade volume is shown based on the time unit
:returns: the Bar object
"""
### WARN: datazoom and time conflict, sliding till 1970..., need further look into pyeacharts
### very unsatisfied about current visualize effect, and it seems the order of add and set option matters a lot
if freq == "D":
datedata = [d.to_pydatetime() for d in cftable["date"]]
selldata = [
[row["date"].to_pydatetime(), row["cash"]]
for _, row in cftable.iterrows()
if row["cash"] > 0
]
buydata = [
[row["date"].to_pydatetime(), row["cash"]]
for _, row in cftable.iterrows()
if row["cash"] < 0
]
elif freq == "W":
cfmerge = cftable.groupby([cftable["date"].dt.year, cftable["date"].dt.week])[
"cash"
].sum()
datedata = [
dt.datetime.strptime(str(a) + "4", "(%Y, %W)%w")
for a, _ in cfmerge.iteritems()
]
selldata = [
[dt.datetime.strptime(str(a) + "4", "(%Y, %W)%w"), b]
for a, b in cfmerge.iteritems()
if b > 0
]
buydata = [
[dt.datetime.strptime(str(a) + "4", "(%Y, %W)%w"), b]
for a, b in cfmerge.iteritems()
if b < 0
]
elif freq == "M":
cfmerge = cftable.groupby([cftable["date"].dt.year, cftable["date"].dt.month])[
"cash"
].sum()
datedata = [
dt.datetime.strptime(str(a) + "15", "(%Y, %m)%d")
for a, _ in cfmerge.iteritems()
]
selldata = [
[dt.datetime.strptime(str(a) + "15", "(%Y, %m)%d"), b]
for a, b in cfmerge.iteritems()
if b > 0
]
buydata = [
[dt.datetime.strptime(str(a) + "15", "(%Y, %m)%d"), b]
for a, b in cfmerge.iteritems()
if b < 0
]
else:
raise ParserFailure("no such freq tag supporting")
bar = Bar()
bar.add_xaxis(datedata)
bar.add_yaxis(series_name="卖出", yaxis_data=selldata, category_gap="90%")
bar.add_yaxis(series_name="买入", yaxis_data=buydata, category_gap="90%")
bar.set_global_opts(
xaxis_opts=AxisOpts(type_="time"),
datazoom_opts=[DataZoomOpts(range_start=99, range_end=100)],
)
return bar.render_notebook()
"2021-12-24",
],
}
connection_errors = (
HttpStatusError,
ConnectionResetError,
requests.exceptions.RequestException,
requests.exceptions.ConnectionError,
requests.exceptions.SSLError,
JSONDecodeError,
)
line_opts = {
"datazoom_opts": [
DataZoomOpts(is_show=True, type_="slider", range_start=50, range_end=100),
DataZoomOpts(
is_show=True,
type_="slider",
orient="vertical",
range_start=50,
range_end=100,
),
],
"tooltip_opts": TooltipOpts(
is_show=True, trigger="axis", trigger_on="mousemove", axis_pointer_type="cross"
),
}
heatmap_opts = {
"visualmap_opts": VisualMapOpts(
def total_trend(day,shdeath,shcured,shsum,shpending) -> Line:
line = (
Line(init_opts=InitOpts())
.add_xaxis(day)
# .add_yaxis("全国死亡",y_axis=death,is_connect_nones=True,is_smooth=True)
.add_yaxis(
'死亡',shdeath,symbol_size=10,color='black',
itemstyle_opts=ItemStyleOpts(color='black'),
label_opts=LabelOpts(is_show=False),
areastyle_opts=AreaStyleOpts(opacity=0.5,color='black'),
stack=1,is_connect_nones=True,is_smooth=True
)
.add_yaxis(
'治愈',shcured,symbol_size=10,color='LimeGreen',
itemstyle_opts=ItemStyleOpts(color='LimeGreen'),
label_opts=LabelOpts(font_size=15,color='ForestGreen'),
areastyle_opts=AreaStyleOpts(opacity=0.5,color='LimeGreen'),
stack=1,is_connect_nones=True,is_smooth=True
)
.add_yaxis(
'确诊',shsum,symbol_size=10,color='Orange',
itemstyle_opts=ItemStyleOpts(color='Orange'),
label_opts=LabelOpts(font_size=15,color='DarkOrange',font_weight='bold'),
areastyle_opts=AreaStyleOpts(opacity=0.5,color='Orange'),
stack=1,is_connect_nones=True,is_smooth=True
)
.add_yaxis(
'疑似',shpending,symbol_size=10,color='LightSkyBlue',
itemstyle_opts=ItemStyleOpts(color='LightSkyBlue'),
label_opts=LabelOpts(font_size=15,color='DarkBlue'),
areastyle_opts=AreaStyleOpts(opacity=0.5,color='LightSkyBlue'),
stack=1,is_connect_nones=True,is_smooth=True
)
.set_global_opts(
title_opts=TitleOpts(
# title=title,
# pos_left='10%',
# pos_top='-10%',
),
# tooltip_opts=TooltipOpts(formatter="{b} {a}\n {c}人"),
datazoom_opts=[
DataZoomOpts(range_start=40,range_end=100,xaxis_index=[0, 1],),
DataZoomOpts(range_start=40,range_end=100,xaxis_index=[0, 1],type_='inside'),
],
xaxis_opts=AxisOpts(name_gap=50),
legend_opts=LegendOpts(
pos_top='top',pos_left='10%',
textstyle_opts=TextStyleOpts(font_size=30),
orient='horizontal',legend_icon='rect'
),
tooltip_opts=TooltipOpts(textstyle_opts=TextStyleOpts(font_size=30)),
graphic_opts=GraphicGroup(
graphic_item=GraphicItem(left="12%",top="11%"),
children=[
GraphicRect(
graphic_item=GraphicItem(z=0,left="center",top="middle"),
graphic_shape_opts=GraphicShapeOpts(width=150, height=90),
graphic_basicstyle_opts=GraphicBasicStyleOpts(
fill="#fff",
stroke="black",
line_width=3,
)
),
GraphicText(
graphic_item=GraphicItem(left="center",top="middle",z=0),
graphic_textstyle_opts=GraphicTextStyleOpts(
text=f"确诊{shsum[-1]}人\n\n疑似{shpending[-1]}人",
font="bolder 20px sans-serif",
graphic_basicstyle_opts=GraphicBasicStyleOpts(fill="#333")
)
)
]
)
)
)
# line.overlap(bar)
return line