line = Line("折线图示例", width = 1200)
attr_line = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"]
data1_line = [11, 11, 15, 13, 12, 13, 10]
data2_line = [1, -2, 2, 5, 3, 2, 0]
line.add("最高气温",
attr_line, data1_line,
mark_point = ["max", "min"],
mark_line = ["average"])
line.add("最低气温",
attr_line, data2_line,
mark_point = ["max", "min"],
mark_line = ["avergae"],
legend_pos = "20%")
# Pie
attr_pie = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
data_pie = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图示例", title_pos = "45%")
pie.add("",
attr_pie, data_pie,
radius = [30, 55],
legend_pos = "65%",
legend_orient = "horizonial")
# Grid
grid = Grid()
grid.add(line, grid_right = "65%")
grid.add(pie, grid_left = "60%")
grid.render("/home/wangzhefeng/project/DataVisualiztion/pyecharts/grid_test.html")
make_a_snapshot("grid_test.html", "grid_test.pdf")
def PL_draw_echarts(PL_df, PL_slices):
# 初始化一个画图的页面.每一种信号画一张图片
PL_page = Page()
PL_columns = PL_df.columns.values.tolist()
# 所有统计的信号种类
PL_signal_items = list(set(PL_df['signal_name'].tolist()))
PL_signal_items.sort()
# 所有的N[第n个bar]
PL_bar_nos = []
for PL_col in PL_columns:
if re.match('chg_pct_', PL_col):
# 获取当前统计的是第几根bar的收益
PL_bar_nos.append(PL_col.replace('chg_pct_', ''))
for PL_sig in PL_signal_items:
# 获取一种信号在M个bar内的收益统计
PL_bar = Bar(PL_sig + "收益分布", title_text_size=14, width='100%')
PL_sdf = PL_df[(PL_df['signal_name'] == PL_sig)]
if PL_sdf.empty:
continue
# 划分收益区间,从0开始往正负两端划分收益区间
# 计算每个收益区间的大小
PL_max_profit = 0
PL_min_profit = 0
for PL_no in PL_bar_nos:
PL_pcol = 'chg_pct_' + PL_no
PL_profits = PL_sdf[PL_pcol].tolist()
PL_max_profit = max(max(PL_profits), PL_max_profit)
PL_min_profit = min(min(PL_profits), PL_min_profit)
PL_intervals = []
if PL_min_profit < 0:
PL_unit = round(
max(PL_max_profit, abs(PL_min_profit)) / PL_slices, 4)
# 先划分小于0的区间
for i in range(0, int(math.ceil(abs(PL_min_profit) / PL_unit))):
PL_intervals.append(
[round(-(i + 1) * PL_unit, 4),
round(-i * PL_unit, 4)])
PL_intervals.reverse()
else:
PL_unit = PL_max_profit / PL_slices
for i in range(0, int(math.ceil(abs(PL_max_profit) / PL_unit))):
PL_intervals.append([i * PL_unit, (i + 1) * PL_unit])
# 显示收益区间之前先格式化成百分比。
PL_format_intervals = [
'%.2f%%~%.2f%%' % (i[0] * 100, i[1] * 100) for i in PL_intervals
]
for PL_no in PL_bar_nos:
# 计算第M个bar收益，落在某一个收益区间的概率
PL_win_ratios = []
PL_pcol = 'chg_pct_' + PL_no
for PL_interval in PL_intervals:
# 统计在收益落在某个收益区间的概率
PL_conf = (PL_sdf[PL_pcol] > PL_interval[0]) & (
PL_sdf[PL_pcol] <= PL_interval[1])
# 避免int类型直接除之后返回的还是int,这里*1.0
PL_win_ratios.append(
round(len(PL_sdf[PL_conf]) / (len(PL_sdf) * 1.0), 2))
PL_bar.add(
"第%s个bar" % PL_no,
PL_format_intervals,
PL_win_ratios,
xaxis_name='收益区间',
xaxis_name_pos='end',
xaxis_name_size=12,
xaxis_label_textsize=12,
xaxis_interval=1,
xaxis_rotate=45,
yaxis_name='概率',
yaxis_name_pos='end',
yaxis_name_size=12,
yaxis_label_textsize=12,
is_splitline_show=False,
# 默认为 X 轴，横向
is_datazoom_show=True,
datazoom_type="both",
datazoom_range=[40, 60],
# 额外的 dataZoom 控制条，纵向
# is_datazoom_extra_show=True,
# datazoom_extra_type="slider",
# datazoom_extra_range=[10, 25],
# is_toolbox_show=False,
)
PL_grid = Grid(width='100%')
PL_grid.add(PL_bar, grid_bottom=120)
PL_page.add(PL_grid)
PL_page.render()
from pyecharts import Bar, Grid
x = [
"名字很长的x轴1",
"名字很长的x轴2",
"名字很长的x轴3",
"名字很长的x轴4",
"名字很长的x轴5",
"名字很长的x轴6",
"名字很长的x轴7",
"名字很长的x轴8",
"名字很长的x轴9",
]
y = [10, 20, 30, 40, 50, 60, 70, 80, 90]
grid = Grid()
bar = Bar("利用 Grid 解决 dataZoom 与 X 轴标签重叠问题")
bar.add("", x, y, is_datazoom_show=True, xaxis_interval=0, xaxis_rotate=30)
# 把 bar 加入到 grid 中，并适当调整 grid_bottom 参数，使 bar 图整体上移
grid.add(bar, grid_bottom="25%")
grid.render()
def test_grid_multiple_datazoom_index():
line = Line("折线图示例", width=1200, height=700)
line.add(
"最高气温",
WEEK,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
WEEK,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
legend_top="50%",
mark_line=["average"],
is_datazoom_show=True,
datazoom_xaxis_index=[0, 1],
)
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", title_top="50%")
kline.add(
"日K",
["2017/7/{}".format(i + 1) for i in range(31)],
v1,
is_datazoom_show=True,
)
grid = Grid()
grid.add(line, grid_top="60%")
grid.add(kline, grid_bottom="60%")
grid.render()
"Wednesday",
"Tuesday",
"Monday",
"Sunday",
]
data = [[i, j, random.randint(0, 50)] for i in range(24) for j in range(7)]
heatmap = HeatMap("热力图示例")
heatmap.add(
"热力图直角坐标系",
x_axis,
y_axis,
data,
is_visualmap=True,
visual_top="45%",
visual_text_color="#000",
visual_orient="horizontal",
)
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", title_top="52%")
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True, legend_top="50%")
grid = Grid(height=700)
grid.add(heatmap, grid_bottom="60%")
grid.add(bar, grid_top="60%")
page.add(grid)
page.render('./grid01.html')
def bar_chart():
ggu = tableau_services.get_growthOfunit(**g.my_dict)
timestr = ggu['growth_of_unit']['xAxis']
timestr = [i[:-9] for i in timestr]
attr = timestr
vs = "v" + "s"
print(vs)
1 + 1 = 3
print(vs)
v1 = ggu['growth_of_unit']['series']['DEMOXYZ9'][1]
v2 = ggu['growth_of_unit']['series']['DEMOXYZ9'][2]
v3 = ggu['growth_of_unit']['series']['DEMOXYZ6'][1]
v4 = ggu['growth_of_unit']['series']['DEMOXYZ6'][2]
v5 = ggu['growth_of_unit']['series']['DEMOXYZ8'][1]
v6 = ggu['growth_of_unit']['series']['DEMOXYZ8'][2]
bar = Bar(" ")
bar.add("DEMOXYZ9",
attr,
v1,
is_convert=True,
legend_text_size=18,
is_datazoom_show=True,
datazoom_type="both")
bar.add("DEMOXYZ9",
attr,
v2,
is_convert=True,
legend_text_size=18,
is_datazoom_show=True,
datazoom_type="both")
bar.add("DEMOXYZ6",
attr,
v3,
is_convert=True,
legend_text_size=18,
is_datazoom_show=True,
datazoom_type="both")
bar.add("DEMOXYZ6",
attr,
v4,
is_convert=True,
legend_text_size=18,
is_datazoom_show=True,
datazoom_type="both")
bar.add("DEMOXYZ8",
attr,
v5,
is_convert=True,
legend_text_size=18,
is_datazoom_show=True,
datazoom_type="both")
bar.add("DEMOXYZ8",
attr,
v6,
is_convert=True,
legend_text_size=18,
is_datazoom_show=True,
datazoom_type="both")
line = Line(" ")
line.add("DEMOXYZ9",
timestr,
ggu['growth_of_unit']['series']['DEMOXYZ9'][1],
is_stack=True,
is_label_show=True,
legend_top="50%",
is_datazoom_show=True,
is_legend_show=False,
datazoom_type="both")
line.add("DEMOXYZ9",
timestr,
ggu['growth_of_unit']['series']['DEMOXYZ9'][2],
is_stack=True,
is_label_show=True,
legend_top="50%",
is_datazoom_show=True,
is_legend_show=False,
datazoom_type="both")
line.add("DEMOXYZ6",
timestr,
ggu['growth_of_unit']['series']['DEMOXYZ6'][1],
is_stack=True,
is_label_show=True,
legend_top="50%",
is_datazoom_show=True,
is_legend_show=False,
datazoom_type="both")
line.add("DEMOXYZ6",
timestr,
ggu['growth_of_unit']['series']['DEMOXYZ6'][2],
is_stack=True,
is_label_show=True,
legend_top="50%",
is_datazoom_show=True,
is_legend_show=False,
datazoom_type="both")
line.add("DEMOXYZ8",
timestr,
ggu['growth_of_unit']['series']['DEMOXYZ8'][1],
is_stack=True,
is_label_show=True,
legend_top="50%",
is_datazoom_show=True,
is_legend_show=False,
datazoom_type="both")
line.add("DEMOXYZ8",
timestr,
ggu['growth_of_unit']['series']['DEMOXYZ8'][2],
is_stack=True,
is_label_show=True,
legend_top="50%",
is_datazoom_show=True,
is_legend_show=False,
datazoom_type="both")
grid = Grid()
grid.add(bar, grid_right="50%")
grid.add(line, grid_left="60%")
return grid
bb_peoples = []
for i in bb_data:
bb_times.append(i[0])
j = json.dumps(i[1], cls=DecimalEncoder)
bb_peoples.append(j)
# 张思强组
zsq_times = []
zsq_peoples = []
for i in zsq_data:
zsq_times.append(i[0])
j = json.dumps(i[1], cls=DecimalEncoder)
zsq_peoples.append(j)
line_sound = Line("各部门开播主播趋势图", title_pos='50%')
line_sound.add("池珊组", cs_times, cs_peoples, mark_point=["max, min"], mark_line=['average'], legend_pos='70%')
line_sound.add("希文组", xw_times, xw_peoples, mark_point=["max, min"], mark_line=['average'], legend_pos='70%')
line_sound.add("北北组", bb_times, bb_peoples, mark_point=["max, min"], mark_line=['average'], legend_pos='70%')
line_sound.add("张思强组", zsq_times, zsq_peoples, mark_point=["max, min"], mark_line=['average'], legend_pos='70%')
grid = Grid(height=720, width=1500)
grid.add(line1, grid_top='60%', grid_right='60%')
grid.add(line_open, grid_top='60%', grid_left='60%')
grid.add(line2, grid_bottom='60%', grid_right='60%')
grid.add(line_sound, grid_bottom='60%', grid_left='60%')
grid.render('line01.html')
days0,
radius=[45, 65],
center=[20, 50],
is_label_show=True,
legend_orient='vertical',
legend_pos="40%",
label_text_size=10,
mark_point=['max'])
# bar.render(path = 'D:\\示例1.jpeg')
sheet1 = pd.read_excel("./data_resources/3.3各组出差费用密度.xls")
group1 = sheet1["组名"].values.tolist()
days1 = sheet1["各组出差成本的密度"].values.tolist()
pie1 = Pie('各组出差成本的密度', title_pos="55%")
pie1.add('组名',
group1,
days1,
radius=[45, 65],
center=[65, 50],
is_label_show=True,
legend_orient='vertical',
legend_pos="85%",
label_text_size=10,
mark_point=['max'])
# bar.render(path = 'D:\\示例1.jpeg')
grid = Grid(width=1200)
grid.add(pie0, grid_right="55%")
# grid.render("./all_charts/"+"各组出差天数费用0.xls"+".html")
grid.add(pie1, grid_left="50%")
grid.render("./all_charts/" + "3.1_3.3每个组的出差成本密度" + ".html")
class HKUFigure(object):
def __init__(self, width, height, num=1):
if num < 1:
self._num = 1
elif num > 4:
self._num = 4
else:
self._num = num
self._added_flag = [False, False, False, False]
self._grid = Grid(width=width, height=height)
self._width = width
self._height = height
self._axis_num = {}
self._axis_list = [None, None, None, None]
for i in range(self._num):
overlap = Overlap(width=width, height=height)
self._axis_num[overlap] = i
self._axis_list[i] = overlap
self._current_axis = 0
self._xaxis = None
self._label_color = []
def _repr_html_(self):
return self.get_grid()._repr_html_()
def get_current_axis(self):
return self._axis_list[self._current_axis]
def get_axis(self, pos):
return self._axis_list[pos]
def get_grid(self):
return self._grid
def set_xaxis(self, xaxis):
self._xaxis = xaxis
def get_xaxis(self):
return self._xaxis
def add_axis(self, axis):
if axis not in self._axis_num:
return
pos = self._axis_num[axis]
self._current_axis = pos
self._added_flag[pos] = True
self._flush()
return axis
def _flush(self):
self._grid = Grid(width=self._width, height=self._height)
for pos, axis in enumerate(self._axis_list):
if axis is None or axis.options is None \
or axis.options.get('yAxis') is None:
continue
if self._num == 1:
self._grid.add(axis, grid_top="8%")
elif self._num == 2:
if pos == 0:
self._grid.add(axis, grid_top="8%", grid_height='52%')
else:
self._grid.add(axis, grid_top="62%")
elif self._num == 3:
if pos == 0:
self._grid.add(axis, grid_top='8%', grid_height='40%')
elif pos == 1:
self._grid.add(axis, grid_top='50%', grid_height='19%')
else:
self._grid.add(axis, grid_bottom='10%', grid_height='19%')
else:
if pos == 0:
self._grid.add(axis, grid_top='8%', grid_height='30%')
elif pos == 1:
self._grid.add(axis, grid_top='40%', grid_height='18%')
elif pos == 2:
self._grid.add(axis, grid_top='60%', grid_height='15%')
else:
self._grid.add(axis, grid_top='77%', grid_height='15%')
def get_style(self, axis, **kwargs):
pos = self._axis_num[axis]
num = self._num
style = Style()
default_datazoom_type = 'both'
result = None
if num == 1:
result = style.add(legend_text_size='10',
legend_top='8%',
legend_pos='10%',
legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type)
elif num == 2:
if pos == 0:
result = style.add(legend_text_size='10',
legend_top='8%',
legend_pos='10%',
legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0, 1],
is_xaxis_show=False)
else:
result = style.add(
legend_text_size='10',
legend_top='62%',
legend_pos='10%',
#legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0, 1],
is_xaxis_show=True)
elif num == 3:
if pos == 0:
result = style.add(legend_text_size='10',
legend_top='8%',
legend_pos='10%',
legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0, 1, 2],
is_xaxis_show=False)
elif pos == 1:
result = style.add(
legend_text_size='10',
legend_top='50%',
legend_pos='10%',
#legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0, 1, 2],
is_xaxis_show=False)
else:
result = style.add(
legend_text_size='10',
legend_top='71%',
legend_pos='10%',
#legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0, 1, 2],
is_xaxis_show=True)
else:
if pos == 0:
result = style.add(legend_text_size='10',
legend_top='8%',
legend_pos='10%',
legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0, 1, 2, 3],
is_xaxis_show=False)
elif pos == 1:
result = style.add(
legend_text_size='10',
legend_top='40%',
legend_pos='10%',
#legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0, 1, 2, 3],
is_xaxis_show=False)
elif pos == 2:
result = style.add(
legend_text_size='10',
legend_top='60%',
legend_pos='10%',
#legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0, 1, 2, 3],
is_xaxis_show=False)
else:
result = style.add(
legend_text_size='10',
legend_top='77%',
legend_pos='10%',
#legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0, 1, 2, 3],
is_xaxis_show=True)
color_map = {
'r': '#CD0000',
'g': '#008B00',
'b': '#0000EE',
'c': '#40E0D0',
'm': '#CD00CD',
'y': '#EE9A00',
'k': '#000000',
'w': '#FFFFFF'
}
line_map = {'-': 'solid', '--': 'dashed', ':': 'dotted'}
for item in kwargs.items():
if 'color' == item[0]:
color = color_map[
item[1]] if item[1] in color_map else color_map['r']
result['line_color'] = color
self._label_color += [color]
result['label_color'] = self._label_color
elif 'linestyle' == item[0]:
result['line_type'] = line_map[
item[1]] if item[1] in line_map else line_map['-']
else:
result[item[0]] = item[1]
return result
attr_2=["周一", "周二", "周三", "周四", "周五", "周六", "周日"]
v3=[11, 11, 15, 13, 12, 13, 10]
v4=[1, -2, 2, 5, 3, 2, 0]
line=Line('折线图示例')
line.add('最高气温',attr_2,v3,mark_point=['max','min'],mark_line=['average'])
line.add('最低气温',attr_2,v4,mark_point=['max','min'],mark_line=['average'],legend_pos='20%')
scatter=Scatter('散点图示例',title_top="50%", title_pos="65%")
v1=[5, 20, 36, 10, 75, 90]
v2=[10, 25, 8, 60, 20, 80]
scatter.add('scatter',
v1,
v2,
legend_top="50%", legend_pos="80%")
effectscatter=EffectScatter('动态散点图示例',title_top="50%")
effectscatter.add('es',
[11, 11, 15, 13, 12, 13, 10],
[1, -2, 2, 5, 3, 2, 0],
effect_scale=6,
legend_top="50%",
legend_pos="20%",
)
grid=Grid(width=1200,height=720)
grid.add(bar,grid_bottom='60%',grid_left='60%')
grid.add(line,grid_bottom='60%',grid_right='60%')
grid.add(scatter,grid_top='60%',grid_left='60%')
grid.add(effectscatter,grid_top='60%',grid_right='60%')
grid.render()
def scatter(bq,output):
page=Page()
page.height=900
c=0
fc=18 #fontsize
if len(bq.keys())>4:
fig=plt.figure(figsize=(24,10))
else:
fig=plt.figure(figsize=(20,5))
#fig.subplots_adjust(wspace=0.5,hspace=0.5)
#iden the fig shape
#2 col situation
if len(bq.keys())%2==0 and len(bq.keys())%3!=0 and len(bq.keys())%4!=0:
all_col=2
elif len(bq.keys())%3==0:
all_col=3
elif len(bq.keys())%4==0:
all_col=4
#iden shape end
if int(len(bq.keys())%all_col)==0:
row=int(len(bq.keys())/all_col)
else:
row=int(len(bq.keys())/all_col)+1
for key1 in bq:
cp=[] #completeness
ct=[] #contamination
a=sorted(bq[key1]['completeness'].items(),key=lambda x:x[1],reverse=True) #sort keys according to their values
#c=0
for e in a:
cp.append(bq[key1]['completeness'][e[0]])
ct.append(bq[key1]['contamination'][e[0]])
c+=1
x=range(1,len(cp)+1)
##### literature figure part #####
#fig.subplots_adjust(wspace=0.3,hspace=0.6)
if max(ct)>100:
ax1=fig.add_subplot(row,all_col,c)
ax1.set_xlabel(key1,color='black',fontsize=fc)
ax1.set_ylabel('Completeness',fontsize=fc)
ax1.scatter(x,cp,color='black',label='Completeness')
ax2=ax1.twinx()
ax2.scatter(x,ct,color='red',label='Contamination')
ax2.set_ylabel('Contamination',color='black',fontsize=fc)
ax2.tick_params(axis='y',colors='red')
ax2.spines['right'].set_color('red')
if max(ct)%10==0:
max_10_ct=max(ct)
else:
max_10_ct=(10-max(ct)%10)+max(ct)
ax2.axis([min(x),max(x),0,max_10_ct])
ax1.axis([min(x),max(x),0,max_10_ct])
#ax2.axis([min(x),max(x),0,max(cp)])
else:
ax1=fig.add_subplot(row,all_col,c)
ax1.set_xlabel(key1,color='black',fontsize=fc)
ax1.set_ylabel('Completeness',fontsize=fc)
ax1.scatter(x,cp,color='black',label='Completeness')
ax2=ax1.twinx()
ax2.scatter(x,ct,color='red',label='Contamination')
ax2.set_ylabel('Contamination',color='black',fontsize=fc)
ax2.tick_params(axis='y',colors='red')
ax2.spines['right'].set_color('red')
ax2.axis([min(x),max(x),0,100])
#plt.savefig(output+'/3.scatter.png')
##### literature figure end #####
#x=range(1,len(cp)+1)
#grid=Grid()
#overlap = Overlap()
#scatter = Scatter()
#scatter2 = Scatter(key1)
if c%2==0:
#2
if c%4!=0:
overlap2 = Overlap()
scatter3 = Scatter()
scatter3.add("Completeness",x,cp,yaxis_label_textcolor='red',yaxis_line_color='red',xaxis_type='category',xaxis_max=max(x),legend_pos="40%",legend_orient="vertical")
scatter4 = Scatter(key1,title_pos="25%")
scatter4.add('Contamination',x,ct,xaxis_type='category',xaxis_max=max(x),legend_pos="40%",legend_orient="vertical")
overlap2.add(scatter4)
overlap2.add(scatter3)
#4
else:
overlap4 = Overlap()
scatter7 = Scatter()
scatter7.add("Completeness",x,cp,yaxis_label_textcolor='red',yaxis_line_color='red',xaxis_type='category',xaxis_max=max(x),legend_pos="90%",legend_orient="vertical")
scatter8 = Scatter(key1,title_pos="75%")
scatter8.add('Contamination',x,ct,xaxis_type='category',xaxis_max=max(x),legend_pos="90%",legend_orient="vertical")
overlap4.add(scatter8)
overlap4.add(scatter7)
#overlap2.render(output+'/3.scatter_o2.html')
else:
#1
if (c+1)%4!=0:
overlap = Overlap()
scatter = Scatter()
scatter.add("Completeness",x,cp,yaxis_label_textcolor='red',yaxis_line_color='red',xaxis_type='category',xaxis_max=max(x),legend_pos="15%",legend_orient="vertical")
scatter2 = Scatter(key1)
scatter2.add('Contamination',x,ct,xaxis_type='category',xaxis_max=max(x),legend_pos="15%",legend_orient="vertical")
overlap.add(scatter2)
overlap.add(scatter)
#3
else:
overlap3 = Overlap()
scatter5= Scatter()
scatter5.add("Completeness",x,cp,yaxis_label_textcolor='red',yaxis_line_color='red',xaxis_type='category',xaxis_max=max(x),legend_pos="65%",legend_orient="vertical")
scatter6= Scatter(key1,title_pos="50%")
scatter6.add('Contamination',x,ct,xaxis_type='category',xaxis_max=max(x),legend_pos="65%",legend_orient="vertical")
overlap3.add(scatter6)
overlap3.add(scatter5)
#overlap.render(output+'/3.scatter_o1.html')
'''
if c==len(bq.keys()) and c%2!=0:
grid=Grid()
grid.add(overlap,grid_left="60%")
page.add(grid)
continue
'''
if c%2==0:
#2
if c%4!=0:
grid.add(overlap2,grid_left="30%",grid_width=250)
#4
else:
grid.add(overlap4,grid_left="80%",grid_width=200)
page.add(grid)
#grid.render(output+'/3.scatter.html')
#page.render(output+'/3.scatter.html')
else:
#3
if (c+1)%4==0:
grid.add(overlap3, grid_left="55%",grid_width=250)
#1
else:
grid=Grid()
grid.width=1500
grid.height=300
grid.add(overlap,grid_left="5%",grid_width=250)
#grid.render(output+'/3.scatter.html')
#page.render(output+'/3.scatter.html')
#exit()
if c==len(bq.keys()) and c%4!=0:
page.add(grid)
page.render(output+'/3_scatter.html')
#fig.subplots_adjust(wspace=0.3,hspace=0.3)
#ax1.legend(loc='center', bbox_to_anchor=(-1.3, 3.8),ncol=5,fontsize=20)
fig.subplots_adjust(wspace=0.5)
plt.savefig(output+'/3.scatter.png')
attr = ['{}日'.format(i) for i in range(1, 32)]
line1.add("6月",
attr,
data3,
line_opacity=1.9,
is_symbol=True,
legend_pos='70%')
line1.add("7月", attr, data4, is_smooth=True, legend_pos='70%')
line1.add("8月",
attr,
data5,
line_opacity=1.9,
area_opacity=0.6,
is_symbol=True,
legend_pos='70%')
grid = Grid(width=900, height=600)
grid.add(line1, grid_top="60%", grid_left="15%")
grid.add(line, grid_bottom="60%", grid_left="15%")
grid.render(path='C:/Users/lenovo/Downloads/Active.png')
# #累计月活图
# f,ax = plt.subplots(figsize = (8,16),nrows=2)
# # ax[0].plot(data1,'g.-',label = 'Aug')
# ax[0].plot(data3,'y.-',label = 'Mar')
# ax[0].plot(data4,'b.-',label = 'Apr')
# ax[0].plot(data5,'r.-',label = 'May')
# ax[0].legend(loc = 'best')
# ax[0].set_title("Monthly live")
# # ax[0].set_xlabel('Time')
# ax[0].set_ylabel('Nums_consum')
# ticks = ax[0].set_xticks(range(0,31))
#增加RSI指标模型
#改正了BAR 与 line 横坐标不能共享的 bug
import xlrd
from xlrd import xldate_as_tuple
from datetime import datetime
from pyecharts import Kline, Line, Overlap, Grid, Bar, Page
grid = Grid()
#导入 开 收 低 高
def Import():
data = xlrd.open_workbook("Bitcoin - 比特币历史数据_历史行情,价格,走势图表.xlsx")
table = data.sheets()[0] #通过索引顺序获取
time = table.col_values(0) #获取日期指
time.reverse() #反转
time.pop() #去掉最后一个字符
#将日期转化为 %Y/%m/%d 形式
date = []
for i in range(len(time)):
date.append(
datetime(*xldate_as_tuple(time[i], 0)).strftime('%Y/%m/%d'))
print("导入时间：", date)
close = table.col_values(1)
close.reverse()
close.pop()
print("导入收盘价：", close)
# 先算出柱状图高度占比，下面有，得出间隔增量是25
bar1=Bar('餐饮类标签排名',title_top="0%")
bar2=Bar('景点类标签排名',title_top="25%")
bar3=Bar('娱乐类标签排名',title_top="50%")
bar4=Bar('购物类标签排名',title_top="75%")
# is_splitline_show 显示X轴的标尺线
# xaxis_rotate 未知
# legend_top 图例的顶部位置(可以用百分比)
# legend_pos 以控制图例的x轴位置,可以用百分比
# 图例的名字不同，则柱状图的颜色不同
bar1.add('餐饮游记',df1['城市'],df1['餐饮游记'],is_splitline_show=True,xaxis_rotate=30,legend_top="0%")
bar2.add('景点游记',df2['城市'],df2['景点游记'],is_splitline_show=True,xaxis_rotate=30,legend_top="25%")
bar3.add('娱乐游记',df3['城市'],df3['娱乐游记'],is_splitline_show=True,xaxis_rotate=30,legend_top="50%")
bar4.add('购物游记',df4['城市'],df4['购物游记'],is_splitline_show=True,xaxis_rotate=30,legend_top="75%")
grid=Grid(width=1280,height=700)
# grid_top grid组件离容器顶部距离
# grid_bottom grid组件离容器底部距离
# 也支持grid_left grid_right
# 100-(80+5)=15 容器的高度占比
grid.add(bar1,grid_top="5%",grid_bottom="80%")
# 四个柱状图高度占比:4*15=60
# 中间隔占比:100-60-5-5(第一5和最后5)=30,30/3=10
# 则间隔增量是：10(间隔占比)+15(柱状图高度占比)=25
grid.add(bar2,grid_top="30%",grid_bottom="55%")
grid.add(bar3,grid_top="55%",grid_bottom="30%")
grid.add(bar4,grid_top="80%",grid_bottom="5%")
'''
# 布局如图
——————————————
5
#encoding:utf-8
# 作者：孙亚楠
# 日期：2020/3/21 0021 18:41
# 工具：PyCharm
# Python版本：3.7.3
#此python文件完成功能：
from pyecharts import Grid,Line,Bar
# //设置行名
columns = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
# //设置数据
data1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]
data2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]
# //设置折线图标题位置
line = Line("折线图","一年的降水量与蒸发量",title_top="45%")
line.add("降水量", columns, data1, is_label_show=True)
line.add("蒸发量", columns, data2, is_label_show=True)
grid = Grid()
# //设置柱状图的主标题与副标题
bar = Bar("柱状图", "一年的降水量与蒸发量")
# //添加柱状图的数据及配置项
bar.add("降水量", columns, data1, mark_line=["average"], mark_point=["max", "min"])
bar.add("蒸发量", columns, data2, mark_line=["average"], mark_point=["max", "min"])
# //设置两个图表的相对位置
grid.add(bar, grid_bottom="60%")
grid.add(line, grid_top="60%")
grid.render()
# 将持仓和cci重叠在一个图中
cci_overlap = Overlap()
cci_overlap.add(cci_line)
cci_overlap.add(bar)
cci_overlap.render()
# 画出K线图
price = [[open, close, lowest,
highest] for open, close, lowest, highest in zip(
data['open'], data['close'], data['low'], data['high'])]
kline = Kline("贵州茅台", title_pos='center')
kline.add('日线',
x_axis=data['date'],
y_axis=price,
is_datazoom_show=True,
is_xaxislabel_align=True,
tooltip_tragger='axis',
yaxis_pos='left',
legend_top="20%",
legend_orient='vertical',
legend_pos='right',
is_toolbox_show=True,
tooltip_formatter=show_kline_data)
# 将cci折线图和K线图合并到一张图表中
grid = Grid()
grid.add(cci_overlap, grid_top="70%")
grid.add(kline, grid_bottom="40%")
grid.render()
df_fuwu=df.drop(df[df['服务']==0].index,inplace=False)
df_fuwu=df_fuwu.groupby(by='城市').agg({'服务':'mean'}).reset_index()
df_fuwu=df_fuwu.sort_values(by='服务',ascending=False)[0:20]
df_fuwu['服务']=df_fuwu['服务'].map(lambda x:round(x,2))
# 柱状图
bar1=Bar('小龙虾人气城市',title_top="10px",title_pos="5%")
bar2=Bar('人均消费排名',title_top="180px",title_pos="5%")
bar3=Bar('口味评分排名',title_top="350px",title_pos="5%")
bar4=Bar('环境评分排名',title_top="520px",title_pos="5%")
bar5=Bar('服务评分排名',title_top="690px",title_pos="5%")
# is_splitline_show 水平标线 xaxis_rotate 未知 legend_top 图例离页面顶部距离
bar1.add('点评',df_dianping['城市'],df_dianping['点评'],is_splitline_show=True,xaxis_rotate=30,legend_top="10px",legend_pos="50%")
bar2.add('人均消费',df_renjun['城市'],df_renjun['人均'],is_splitline_show=True,xaxis_rotate=30,legend_top="180px",legend_pos="50%")
bar3.add('评分',df_kouwei['城市'],df_kouwei['口味'],is_splitline_show=True,xaxis_rotate=30,legend_top="350px",legend_pos="50%")
bar4.add('评分',df_huanjing['城市'],df_huanjing['环境'],is_splitline_show=True,xaxis_rotate=30,legend_top="520px",legend_pos="50%")
bar5.add('评分',df_fuwu['城市'],df_fuwu['服务'],is_splitline_show=True,xaxis_rotate=30,legend_top="690px",legend_pos="50%")
grid = Grid(height=1200,width=1280)
# grid_bottom 图表底部离页面底部距离 grid_top 图表顶部离页面顶部距离
'''100%-(grid_bottom:80 + grid_top 5)=15%即为柱状图高的占比, 即4个图占60%空间,并留一些白'''
'''先填出第一个图(80,5)与最后一个图(5,80)的位置, 然后用(80-5)/(4-1)=25为增量间距'''
# grid.add(bar1,grid_bottom="80%",grid_top="6%" ,grid_left="5%",grid_right="55%")
grid.add(bar1,grid_top="50px",grid_bottom="1050px")
grid.add(bar2,grid_top="220px",grid_bottom="880px")
grid.add(bar3,grid_top="390px",grid_bottom="710px")
grid.add(bar4,grid_top="560px",grid_bottom="540px")
grid.add(bar5,grid_top="730px",grid_bottom="370px")
grid.render('小龙虾.html')
def test_page_grid_timeline_overlap():
# Grid
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=720, width=1200, title_pos="65%")
bar.add("商家A", CLOTHES, v1, is_stack=True)
bar.add("商家B", CLOTHES, v2, is_stack=True, legend_pos="80%")
line = Line("折线图示例")
line.add(
"最高气温",
WEEK,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
WEEK,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%",
)
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter("散点图示例", title_top="50%", title_pos="65%")
scatter.add("scatter", v1, v2, legend_top="50%", legend_pos="80%")
es = EffectScatter("动态散点图示例", title_top="50%")
es.add(
"es",
[11, 11, 15, 13, 12, 13, 10],
[1, -2, 2, 5, 3, 2, 0],
effect_scale=6,
legend_top="50%",
legend_pos="20%",
)
grid = Grid()
grid.add(bar, grid_bottom="60%", grid_left="60%")
grid.add(line, grid_bottom="60%", grid_right="60%")
grid.add(scatter, grid_top="60%", grid_left="60%")
grid.add(es, grid_top="60%", grid_right="60%")
# Timeline
bar_1 = Bar("2012 年销量", "数据纯属虚构")
bar_1.add("春季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_1.add("夏季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_1.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_1.add("冬季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_2 = Bar("2013 年销量", "数据纯属虚构")
bar_2.add("春季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_2.add("夏季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_2.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_2.add("冬季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_3 = Bar("2014 年销量", "数据纯属虚构")
bar_3.add("春季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_3.add("夏季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_3.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_3.add("冬季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_4 = Bar("2015 年销量", "数据纯属虚构")
bar_4.add("春季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_4.add("夏季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_4.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_4.add("冬季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_5 = Bar("2016 年销量", "数据纯属虚构", height=720, width=1200)
bar_5.add("春季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_5.add("夏季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_5.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_5.add(
"冬季",
CLOTHES,
[randint(10, 100) for _ in range(6)],
is_legend_show=True,
)
timeline = Timeline(is_auto_play=True, timeline_bottom=0)
timeline.add(bar_1, "2012 年")
timeline.add(bar_2, "2013 年")
timeline.add(bar_3, "2014 年")
timeline.add(bar_4, "2015 年")
timeline.add(bar_5, "2016 年")
# Overlap
attr = ["{}月".format(i) for i in range(1, 13)]
v1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]
v2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]
v3 = [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2]
bar = Bar(height=720, width=1200)
bar.add("蒸发量", attr, v1)
bar.add("降水量", attr, v2, yaxis_formatter=" ml", yaxis_max=250)
line = Line()
line.add("平均温度", attr, v3, yaxis_formatter=" °C")
overlap = Overlap()
overlap.add(bar)
overlap.add(line, yaxis_index=1, is_add_yaxis=True)
page = Page()
page.add(grid)
page.add(timeline)
page.add(overlap)
page.render()
# 设置折线图x轴标签
attr = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"]
# 分别设置折线图的两条线
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"])
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%")
# 准备饼图的标签
attr = ["机械", "曙光", "人艺", "冶金", "管理", "外语"]
# 准备饼图的数据
v1 = [11, 12, 13, 10, 10, 10]
# 设置饼图
pie = Pie("饼图", title_pos="55%")
# 设置属性
pie.add("",
attr,
v1,
radius=[45, 65],
center=[65, 50],
legend_pos="80%",
legend_orient="vertical")
grid = Grid()
grid.add(line, grid_right="55%")
grid.add(pie, grid_left="60%")
# 生成html，打开即可
grid.render()
def plot(df):
kl = df.copy()
kl['MID'] = (kl['HIGH'] + kl['LOW']) / 2
kl['AG13'] = kl['MID'].rolling(window=13).mean()
kl['AG8'] = kl['MID'].rolling(window=8).mean()
kl['AG5'] = kl['MID'].rolling(window=5).mean()
kl['SMA5'] = kl['MID'].rolling(window=5).mean()
kl['SMA34'] = kl['MID'].rolling(window=34).mean()
kl['AO'] = kl['SMA5'] - kl['SMA34']
kl['AC'] = (kl['AO'] -
kl['AO'].rolling(window=5).mean()).rolling(window=5).mean()
kl = kl[20:]
for i in range(2, len(kl['MID'])):
kl.ix[i, 'AG13'] = (kl.ix[i - 1, 'AG13'] * 12 +
(kl.ix[i, 'HIGH'] + kl.ix[i, 'LOW']) / 2) / 13
kl.ix[i, 'AG8'] = (kl.ix[i - 1, 'AG8'] * 7 +
(kl.ix[i, 'HIGH'] + kl.ix[i, 'LOW']) / 2) / 8
kl.ix[i, 'AG5'] = (kl.ix[i - 1, 'AG5'] * 4 +
(kl.ix[i, 'HIGH'] + kl.ix[i, 'LOW']) / 2) / 5
kl['AG13'] = kl['AG13'].shift(8)
kl['AG8'] = kl['AG8'].shift(5)
kl['AG5'] = kl['AG5'].shift(3)
kl = kl.where(kl.notnull(), 0)
kl['GTUP'] = abs(kl['AG13'] - kl['AG8'])
kl['GTDOWN'] = abs(kl['AG8'] - kl['AG5'])
kl['MUP'] = 0
kl['MDOWN'] = 0
markd = []
for i in range(2, len(kl['MID']) - 2):
if kl.ix[i, 'HIGH'] == max(kl.ix[i - 2, 'HIGH'], kl.ix[i - 1, 'HIGH'],
kl.ix[i, 'HIGH'], kl.ix[i + 1, 'HIGH'],
kl.ix[i + 2, 'HIGH']):
#kl.ix[i,'MUP']=1
markd.append({
"coord": [kl.index[i], kl.ix[i, 'HIGH']],
"name": "1"
})
if kl.ix[i, 'LOW'] == min(kl.ix[i - 2, 'LOW'], kl.ix[i - 1, 'LOW'],
kl.ix[i, 'LOW'], kl.ix[i + 1, 'LOW'],
kl.ix[i + 2, 'LOW']):
markd.append({
"coord": [kl.index[i], kl.ix[i, 'LOW']],
"name": "2"
})
page = Page(page_title='AC')
kline = Kline()
kline.add('',
list(kl.index), [
list(kl[['OPEN', 'CLOSE', 'LOW', 'HIGH']].iloc[i, ].values)
for i in range(len(kl))
],
is_datazoom_show=True,
datazoom_xaxis_index=[0, 1],
datazoom_type="both",
is_xaxislabel_align=True,
tooltip_axispointer_type="cross",
mark_point=markd,
mark_point_symbol='circle',
mark_point_symbolsize=10)
line = Line(' ')
line.add('JAW',
list(kl.index),
list(kl['AG13']),
line_color=['#0000ff'],
label_color=['#0000ff'])
line.add('TEETH',
list(kl.index),
list(kl['AG8']),
line_color=['#ff0000'],
label_color=['#ff0000'])
line.add('LIPS',
list(kl.index),
list(kl['AG5']),
line_color=['#00ff00'],
label_color=['#00ff00'])
overlap1 = Overlap()
overlap1.add(kline)
overlap1.add(line)
#gator
# bar1 = Bar(' ')
# bar2 = Bar(' ')
# up = list(kl['GTUP'])
# down = list(kl['GTDOWN'])
# redup = []
# greenup = []
# reddown = []
# greendown = []
# for i in range(len(up)):
# if (i == 0):
# greenup.append(up[i])
# redup.append(0)
# greendown.append(-down[i])
# reddown.append(0)
# continue
# if (up[i] > up[i - 1]):
# greenup.append(up[i])
# redup.append(0)
# else:
# greenup.append(0)
# redup.append(up[i])
# if (down[i] > down[i - 1]):
# greendown.append(-down[i])
# reddown.append(0)
# else:
# greendown.append(0)
# reddown.append(-down[i])
#
# # bar.add('MACDhist',klt,macd[2].tolist(),is_datazoom_show=True,legend_top='65%')
# bar1.add('GTREDUP', list(kl.index), redup, legend_top='65%', label_color=['#ff0000'])
# bar2.add('GTREDDOWN', list(kl.index), reddown, legend_top='65%', label_color=['#00ff00'])
# bar1.add('GTGREENUP', list(kl.index), greenup, legend_top='65%', label_color=['#ff0000'])
# bar2.add('GTGREENDOWN', list(kl.index), greendown, legend_top='65%', label_color=['#00ff00'])
bar1 = Bar(' ')
bar2 = Bar(' ')
ac = list(kl['AC'])
acr = []
acg = []
for i in range(len(ac)):
if (i == 0):
acr.append(ac[i])
acg.append(0)
continue
if ac[i] > ac[i - 1]:
acr.append(0)
acg.append(ac[i])
else:
acr.append(ac[i])
acg.append(0)
bar1.add('ACR',
list(kl.index),
acr,
legend_top='65%',
label_color=['#ff0000'])
bar2.add('ACG',
list(kl.index),
acg,
legend_top='65%',
label_color=['#00ff00'])
overlap2 = Overlap()
overlap2.add(bar1)
overlap2.add(bar2)
grid = Grid(width=1920, height=950)
grid.add(overlap1, grid_bottom='40%')
grid.add(overlap2, grid_top='70%')
# page.add(line)
# page.add(overlap)
page.add(grid)
path = os.path.abspath('.')
page.render(path + '\\plot\\AC.html')
line.add(
"最低气温",
attr,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%",
)
# ************************************************************************************
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter("散点图示例", title_top="50%", title_pos="65%")
scatter.add("scatter", v1, v2, legend_top="50%", legend_pos="80%")
# ************************************************************************************
es = EffectScatter("动态散点图示例", title_top="50%")
es.add(
"es",
[11, 11, 15, 13, 12, 13, 10],
[1, -2, 2, 5, 3, 2, 0],
effect_scale=6,
legend_top="50%",
legend_pos="20%",
)
# ************************************************************************************
grid = Grid(height=720, width=1500)
grid.add(bar, grid_bottom="60%", grid_left="60%")
grid.add(line, grid_bottom="60%", grid_right="60%")
grid.add(scatter, grid_top="60%", grid_left="60%")
grid.add(es, grid_top="60%", grid_right="60%")
grid.render(path='ht3.html')
bar = Bar("iPhone销售状况")
bar.add("iPhone销售额", years, ip_sales)
bar2 = Bar()
bar2.add("iPhone销量", years, ip_unit, bar_category_gap=25)
percent = ip_sales.astype('float') / net_sales.astype('float')
line = Line()
line.add("收入占比",
years,
percent,
line_width=3,
yaxis_margin=60,
yaxis_pos='left')
ol = Overlap()
ol.add(bar)
ol.add(bar2, is_add_yaxis=True, yaxis_index=1)
ol.add(line, is_add_yaxis=True, yaxis_index=2)
grid = Grid()
grid.add(ol, grid_left="15%")
grid.render()
cn_sales = data.loc['国行'].values
bar = Bar("国行销售状况")
bar.add("国行", years, cn_sales)
percent = cn_sales.astype('float') / net_sales.astype('float')
line = Line()
line.add("国行占比", years, percent, line_width=3)
ol = Overlap()
ol.add(bar)
ol.add(line, is_add_yaxis=True, yaxis_index=1)
ol.render()
def test_grid_four_direction():
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=720, width=1200, title_pos="65%")
bar.add("商家A", CLOTHES, v1, is_stack=True)
bar.add("商家B", CLOTHES, v2, is_stack=True, legend_pos="80%")
line = Line("折线图示例")
line.add(
"最高气温",
WEEK,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
WEEK,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%",
)
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter("散点图示例", title_top="50%", title_pos="65%")
scatter.add("scatter", v1, v2, legend_top="50%", legend_pos="80%")
es = EffectScatter("动态散点图示例", title_top="50%")
es.add(
"es",
[11, 11, 15, 13, 12, 13, 10],
[1, -2, 2, 5, 3, 2, 0],
effect_scale=6,
legend_top="50%",
legend_pos="20%",
)
grid = Grid()
grid.add(bar, grid_bottom="60%", grid_left="60%")
grid.add(line, grid_bottom="60%", grid_right="60%")
grid.add(scatter, grid_top="60%", grid_left="60%")
grid.add(es, grid_top="60%", grid_right="60%")
grid.render()
from pyecharts import Bar,Grid
import pandas as pd
sheet0 = pd.read_excel("./data_resources/出差省合同_2018拓展落实项目统计_柱状图.xls")
people0 = sheet0["合同省"][0:10].values.tolist()
days0 = sheet0["合同成本（万元）"][0:10].values.tolist()
# days0 = sheet0["对数值（取2位）"][0:10].values.tolist()
bar0 = Bar('2018拓展落实项目统计合同额度',title_pos="10%")
# bar0.add('出差省',people0,days0,xaxis_rotate = 40, yaxis_name = '合同成本Log10(万元）',yaxis_name_pos = 'middle',yaxis_name_gap = 40,legend_pos="35%",label_text_size = 10, is_label_show = True,label_pos= 'inside')
bar0.add('省名称',people0,days0,xaxis_rotate = 40, yaxis_name = '合同成本(万元）',yaxis_name_pos = 'middle',yaxis_name_gap = 50,legend_pos="35%",label_text_size = 12, is_label_show = True)
# bar.render(path = 'D:\\示例1.jpeg')
# bar.render("./all_charts/"+"个人出差人天成本比（补）"+".html")
# sheet1 = pd.read_excel("./data_resources/1.3出差城市与合同城市费用比值.xls")
# people1 = sheet1["合同市"][0:10].values.tolist()
# days1 = sheet1["合同/出差"][0:10].values.tolist()
# bar1 = Bar('出差城市与合同城市费用比值',title_pos="55%")
# bar1.add('合同市',people1,days1,xaxis_rotate = 40, yaxis_name = '成本比例（%）',yaxis_name_pos = 'middle',yaxis_name_gap = 40,legend_pos="80%",label_text_size = 8, is_label_show = True, label_pos= 'inside',mark_point = ['max'])
# # bar.render(path = 'D:\\示例1.jpeg')
grid = Grid(width=850)
grid.add(bar0, grid_right="10%")
# grid.add(bar0)
# # grid.render("./all_charts/"+"各组出差天数费用0.xls"+".html")
# grid.add(bar1, grid_left="50%")
grid.render("./all_charts/"+"1.2合同_2018"+".html")
def create_charts():
page = Page()
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=800, width=WIDTH)
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True)
line = Line("折线图示例", title_top="50%")
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"])
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_top="50%")
chart = Grid()
chart.add(bar, grid_bottom="60%")
chart.add(line, grid_top="60%")
page.add(chart)
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter("散点图示例", width=WIDTH, title_pos="55%")
scatter.add("scatter", v1, v2, legend_pos="70%")
es = EffectScatter("动态散点图示例")
es.add("effectScatter", [11, 11, 15, 13, 12, 13, 10],
[1, -2, 2, 5, 3, 2, 0],
effect_scale=6,
legend_pos="20%")
chart = Grid()
chart.add(scatter, grid_left="60%")
chart.add(es, grid_right="60%")
page.add(chart)
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=740, width=WIDTH, title_pos="65%")
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True, legend_pos="80%")
line = Line("折线图示例")
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"])
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%")
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter("散点图示例", title_top="50%", title_pos="65%")
scatter.add("scatter", v1, v2, legend_top="50%", legend_pos="80%")
es = EffectScatter("动态散点图示例", title_top="50%")
es.add("es", [11, 11, 15, 13, 12, 13, 10], [1, -2, 2, 5, 3, 2, 0],
effect_scale=6,
legend_top="50%",
legend_pos="20%")
chart = Grid()
chart.add(bar, grid_bottom="60%", grid_left="60%")
chart.add(line, grid_bottom="60%", grid_right="60%")
chart.add(scatter, grid_top="60%", grid_left="60%")
chart.add(es, grid_top="60%", grid_right="60%")
page.add(chart)
line = Line("折线图示例", width=WIDTH)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"])
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图示例", title_pos="55%")
pie.add("",
attr,
v1,
radius=[45, 65],
center=[70, 50],
legend_pos="85%",
legend_orient='vertical')
chart = Grid()
chart.add(line, grid_right="55%")
chart.add(pie, grid_left="60%")
page.add(chart)
line = Line("折线图示例", width=WIDTH)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"])
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%")
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", title_pos="60%")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
v1,
legend_pos="80%")
chart = Grid()
chart.add(line, grid_right="60%")
chart.add(kline, grid_left="55%")
page.add(chart)
data = [[i, j, random.randint(0, 50)] for i in range(24) for j in range(7)]
heatmap = HeatMap("热力图示例", width=WIDTH, height=700)
heatmap.add("热力图直角坐标系",
X_TIME,
Y_WEEK,
data,
is_visualmap=True,
visual_top="45%",
visual_text_color="#000",
visual_orient='horizontal')
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", title_top="52%")
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True, legend_top="50%")
chart = Grid()
chart.add(heatmap, grid_bottom="60%")
chart.add(bar, grid_top="60%")
page.add(chart)
line = Line("折线图示例", width=WIDTH, height=700)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"])
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
legend_top="50%",
mark_line=["average"],
is_datazoom_show=True,
datazoom_xaxis_index=[0, 1])
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", title_top="50%")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
v1,
is_datazoom_show=True)
chart = Grid()
chart.add(line, grid_top="60%")
chart.add(kline, grid_bottom="60%")
page.add(chart)
attr = ['{}天'.format(i) for i in range(1, 31)]
line_top = Line("折线图示例", width=WIDTH, height=700)
line_top.add("最高气温",
attr, [random.randint(20, 100) for i in range(30)],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos='38%')
line_bottom = Line()
line_bottom.add("最低气温",
attr, [random.randint(20, 100) for i in range(30)],
mark_point=["max", "min"],
mark_line=["average"],
is_yaxis_inverse=True,
xaxis_pos='top')
chart = Grid()
chart.add(line_top, grid_bottom='60%')
chart.add(line_bottom, grid_top='50%')
page.add(chart)
attr = ["{}月".format(i) for i in range(1, 13)]
v1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]
v2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]
v3 = [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2]
bar = Bar("Overlap+Grid 示例", title_pos="40%", width=1100, height=600)
bar.add("蒸发量", attr, v1)
bar.add("降水量",
attr,
v2,
yaxis_formatter=" ml",
yaxis_max=250,
legend_pos="85%",
legend_orient="vertical",
legend_top="45%")
line = Line()
line.add("平均温度", attr, v3, yaxis_formatter=" °C")
overlap = Overlap()
overlap.add(bar)
overlap.add(line, is_add_yaxis=True, yaxis_index=1)
chart = Grid()
chart.add(overlap, grid_right='20%')
page.add(chart)
return page
def render(self):
bar1, bar2, bar3 = self.get_data()
grid = Grid(height=800)
grid.add(bar1, grid_bottom="75%")
grid.add(bar2, grid_bottom="37.5%", grid_top="37.5%")
grid.add(bar3, grid_top="75%")
grid.render('城市分类标签.html')
self.city_base.sort_values('total_city_yj',
ascending=False,
inplace=True)
attr = self.city_base['city_name'][0:10]
v1 = self.city_base['total_city_yj'][0:10]
bar = Bar("游记总数量TOP10")
bar.add("游记总数", attr, v1, is_stack=True)
bar.render('游记总数量TOP10.html')
self.city_food.sort_values('food_count', ascending=False, inplace=True)
attr_food = self.city_food['food'][0:15]
# print(attr_food)
v1_food = self.city_food['food_count'][0:15]
bar_food = Bar('热门食物排名')
bar_food.add('热门食物',
attr_food,
v1_food,
is_stack=True,
interval=0,
xaxis_rotate=30,
yaxix_min=4.2,
is_splitline_show=False)
bar_food.render('热门食物.html')
self.city_jd.sort_values('jd_count', ascending=False, inplace=True)
attr_f = self.city_jd['jd'][0:15]
v1_f = self.city_jd['jd_count'][0:15]
bar_f = Bar('热门景点排名')
bar_f.add('热门景点',
attr_f,
v1_f,
is_stack=True,
interval=0,
xaxis_rotate=30,
yaxix_min=4.2,
is_splitline_show=False)
bar_f.render('热门景点.html')
# 按照各个城市游记数量获得全国旅行目的地热力图
# pycharts中的Geo绘制中国地图，在图中显示各个地区的旅游热度
data = [(self.city_base['city_name'][i],
self.city_base['total_city_yj'][i])
for i in range(0, self.city_base.shape[0])]
geo = Geo('全国城市旅游热力图',
title_color="#fff",
title_pos="center",
width=1200,
height=600,
background_color='#404a59')
while True:
try:
attr, value = geo.cast(data)
geo.add("",
attr,
value,
visual_range=[0, 15000],
visual_text_color="#fff",
symbol_size=15,
is_visualmap=True,
is_roam=False)
except ValueError as e:
e = str(e)
e = e.split("No coordinate is specified for ")[1] # 获取不支持的城市名
for i in range(0, len(data)):
if e in data[i]:
data.pop(i)
break
else:
break
geo.render('蚂蜂窝游记热力图.html')
# if __name__=='__main__':
# object=MaFengWoData()
# object.view_data()
def test_grid_2():
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=720, width=1200, title_pos="65%")
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True, legend_pos="80%")
line = Line("折线图示例")
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"])
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%")
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter("散点图示例", title_top="50%", title_pos="65%")
scatter.add("scatter", v1, v2, legend_top="50%", legend_pos="80%")
es = EffectScatter("动态散点图示例", title_top="50%")
es.add("es", [11, 11, 15, 13, 12, 13, 10], [1, -2, 2, 5, 3, 2, 0],
effect_scale=6,
legend_top="50%",
legend_pos="20%")
grid = Grid()
grid.add(bar, grid_bottom="60%", grid_left="60%")
grid.add(line, grid_bottom="60%", grid_right="60%")
grid.add(scatter, grid_top="60%", grid_left="60%")
grid.add(es, grid_top="60%", grid_right="60%")
grid.render()
[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', title_pos='60%')
kline.add('日k', ['2018/12/{}'.format(i + 1) for i in range(31)],
v1,
legend_pos='80%')
grid = Grid(width=1200)
grid.add(line, grid_right='60%')
grid.add(kline, grid_left='55%')
grid.render()
def kline_echarts(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.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']])
kline.add(ds.code[0], datetime, ohlc, mark_point=[
"max", "min"], is_datazoom_show=True, datazoom_orient='horizontal')
return kline
else:
data = []
axis = []
ds = self.select_code(code)
data = []
#axis = []
if self.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']])
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])
grid = Grid(width=1360, height=700, page_title='QUANTAXIS')
grid.add(bar, grid_top="80%")
grid.add(kline, grid_bottom="30%")
return grid
mark_line=["average"],
)
line.add(
"最低气温",
attr,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%",
)
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter("散点图示例", title_top="50%", title_pos="65%")
scatter.add("scatter", v1, v2, legend_top="50%", legend_pos="80%")
es = EffectScatter("动态散点图示例", title_top="50%")
es.add(
"es",
[11, 11, 15, 13, 12, 13, 10],
[1, -2, 2, 5, 3, 2, 0],
effect_scale=6,
legend_top="50%",
legend_pos="20%",
)
grid = Grid()
grid.add(bar, grid_bottom="60%", grid_left="60%")
grid.add(line, grid_bottom="60%", grid_right="60%")
grid.add(scatter, grid_top="60%", grid_left="60%")
grid.add(es, grid_top="60%", grid_right="60%")
grid.render(path="demo.base64", delay=3)