def renderScatter(self, xname, yname, ax, ay, times, path, op):
for i in range(times):
sc = Scatter(width=450, height=450, is_animation=False)
if op == 0:
sc.add(xname,
ax[i],
ay[i],
xaxis_name=xname,
yaxis_name=yname,
is_legend_show=False,
is_toolbox_show=False)
elif op == -1:
sc.add(xname,
ax[i],
ay,
xaxis_name=xname,
yaxis_name=yname,
is_legend_show=False,
is_toolbox_show=False)
else:
sc.add(xname,
ax,
ay[i],
xaxis_name=xname,
yaxis_name=yname,
is_legend_show=False,
is_toolbox_show=False)
sc.render("data/" + path + str(i) + ".html")
def test_scatter():
# scatter_0
v1 = [10, 20, 30, 40, 50, 60]
v2 = [10, 20, 30, 40, 50, 60]
scatter = Scatter("散点图示例")
scatter.add("A", v1, v2)
scatter.add("B", v1[::-1], v2)
scatter.show_config()
scatter.render()
# scatter_1
scatter = Scatter("散点图示例")
v1, v2 = scatter.draw("../images/pyecharts-0.png")
scatter.add("pyecharts", v1, v2, is_random=True)
scatter.show_config()
scatter.render()
# scatter_2
scatter = Scatter("散点图示例", width=800, height=480)
v1, v2 = scatter.draw("../images/love.png")
scatter.add("Love", v1, v2)
scatter.render()
# scatter_3
scatter = Scatter("散点图示例", width=1000, height=480)
v1, v2 = scatter.draw("../images/cup.png")
scatter.add("Cup", v1, v2)
scatter.render()
# scatter_4
scatter = Scatter("散点图示例", width=1000, height=480)
v1, v2 = scatter.draw("../images/cup.png")
scatter.add("Cup", v1, v2, label_color=["#000"])
scatter.render()
def test_scatter_multi_dimension():
data = [
[28604, 77, 17096869],
[31163, 77.4, 27662440],
[1516, 68, 1154605773],
[13670, 74.7, 10582082],
[28599, 75, 4986705],
[29476, 77.1, 56943299],
[31476, 75.4, 78958237],
[28666, 78.1, 254830],
[1777, 57.7, 870601776],
[29550, 79.1, 122249285],
[2076, 67.9, 20194354],
[12087, 72, 42972254],
[24021, 75.4, 3397534],
[43296, 76.8, 4240375],
[10088, 70.8, 38195258],
[19349, 69.6, 147568552],
[10670, 67.3, 53994605],
[26424, 75.7, 57110117],
[37062, 75.4, 252847810]
]
x_lst = [v[0] for v in data]
y_lst = [v[1] for v in data]
extra_data = [v[2] for v in data]
sc = Scatter()
sc.add("scatter", x_lst, y_lst, extra_data=extra_data, is_visualmap=True,
visual_dimension=2, visual_orient='horizontal',
visual_type='size', visual_range=[254830, 1154605773],
visual_text_color='#000')
sc.render()
def sandiandayinziti():
'''散点打印字体'''
scatter = Scatter("散点图示例")
v1, v2 = scatter.draw("./img.PNG")
scatter.add("散点图打印文字", v1, v2, is_random=True)
scatter.render('./info/散点图打印文字.html')
def test_scatter_multi_dimension():
data = [[28604, 77, 17096869], [31163, 77.4, 27662440],
[1516, 68, 1154605773], [13670, 74.7, 10582082],
[28599, 75, 4986705], [29476, 77.1, 56943299],
[31476, 75.4, 78958237], [28666, 78.1, 254830],
[1777, 57.7, 870601776], [29550, 79.1, 122249285],
[2076, 67.9, 20194354], [12087, 72, 42972254],
[24021, 75.4, 3397534], [43296, 76.8, 4240375],
[10088, 70.8, 38195258], [19349, 69.6, 147568552],
[10670, 67.3, 53994605], [26424, 75.7, 57110117],
[37062, 75.4, 252847810]]
x_lst = [v[0] for v in data]
y_lst = [v[1] for v in data]
extra_data = [v[2] for v in data]
sc = Scatter()
sc.add("scatter",
x_lst,
y_lst,
extra_data=extra_data,
is_visualmap=True,
visual_dimension=2,
visual_orient='horizontal',
visual_type='size',
visual_range=[254830, 1154605773],
visual_text_color='#000')
sc.render()
def test_scatter():
# scatter_0
v1 = [10, 20, 30, 40, 50, 60]
v2 = [10, 20, 30, 40, 50, 60]
scatter = Scatter("散点图示例")
scatter.add("A", v1, v2)
scatter.add("B", v1[::-1], v2)
scatter.show_config()
scatter.render()
# scatter_1
scatter = Scatter("散点图示例")
v1, v2 = scatter.draw("../images/pyecharts-0.png")
scatter.add("pyecharts", v1, v2, is_random=True)
scatter.show_config()
scatter.render()
# scatter_2
scatter = Scatter("散点图示例", width=800, height=480)
v1, v2 = scatter.draw("../images/love.png")
scatter.add("Love", v1, v2)
scatter.render()
# scatter_3
scatter = Scatter("散点图示例", width=1000, height=480)
v1, v2 = scatter.draw("../images/cup.png")
scatter.add("Cup", v1, v2)
scatter.render()
# scatter_4
scatter = Scatter("散点图示例", width=1000, height=480)
v1, v2 = scatter.draw("../images/cup.png")
scatter.add("Cup", v1, v2, label_color=["#000"])
scatter.render()
def draw(generation):
s = []
for i in generation:
s.append(i[1])
scatter = Scatter('牛顿法')
# 因为牛顿法收敛很快，所以用横坐标表示不明显，故用次数表示
scatter.add('', list(range(len(s))), s)
scatter.render('牛顿法.html')
def DrawScatter(title, data, savepath='./results'):
if not os.path.exists(savepath):
os.mkdir(savepath)
scatter = Scatter(title)
attrs = [i for i, j in data.items()]
values = [j for i, j in data.items()]
scatter.add('', attrs, values, is_visualmap=True)
scatter.render(os.path.join(savepath, '%s.html' % title))
def sandiantu():
'''散点图'''
v1 = [10, 20, 30, 40, 50, 60]
v2 = [10, 20, 30, 40, 50, 60]
scatter = Scatter("散点图示例")
scatter.add("A", v1, v2)
scatter.add("B", v1[::-1], v2)
scatter.render('./info/散点图.html')
def DraScatter(self, title, data, savepath='./result'):
if (os.path.exists(savepath) is None):
os.mkdir(savepath)
scatter = Scatter(title)
attrs = [data[i][0] for i in range(len(data))]
vals = [data[i][1] for i in range(len(data))]
scatter.add('', attrs, vals, is_visualmap=True)
scatter.render(os.path.join(savepath, '%s.html' % title))
def draw(generation):
s1 = []
s2 = []
for i in generation:
s1.append(i[0])
s2.append(i[1])
scatter = Scatter('弦截法')
scatter.add('', s1, s2)
scatter.render('弦截法.html')
def draw(generator, name):
scatter = Scatter(name)
s1 = []
s2 = []
for i in generator:
s1.append(i[0])
s2.append(i[1])
scatter.add('', s1, s2)
scatter.render(name + '.html')
def draw(generation):
scatter = Scatter('定点法')
s = []
s1 = []
for i in generation:
s.append(i[0])
s1.append(i[1])
scatter.add('', s, s1)
scatter.render('定点迭代法.html')
def test_scatter_visualmap_type_size():
scatter = Scatter("散点图示例")
scatter.add("B",
v1[::-1],
v2,
is_visualmap=True,
visual_type='size',
visual_range_size=[20, 80])
scatter.render()
def tmp():
es = Scatter()
x = []
y = []
for item in data:
x.append(item[2])
y.append(item[3])
es.add('', x, y)
es.render('1.html')
return render_template('1.html')
def drawlog(dic):
"""
:param his: keras fit返回的的history对象字典
:return:
"""
line = Scatter("log")
for label, value in dic.items():
line.add(label, [i for i in range(len(value))], value, symbol_size=3)
line.render(path="output/temp.html")
def test_scatter_visualmap_type_size():
scatter = Scatter("散点图示例")
scatter.add(
"B",
v1[::-1],
v2,
is_visualmap=True,
visual_type="size",
visual_range_size=[20, 80],
)
scatter.render()
def show(self, class_key: dict, title: str, image_name):
# print(self.show_coordinates)
scatter = Scatter(title=title, background_color='#ffe')
for i in range(0, self.show_coordinates.shape[0]):
point = self.show_coordinates.iloc[i]['point']
# print(point, class_key[point])
coordinates = self.show_coordinates.iloc[i]['vector']
# print(type(coordinates), type(class_key[point]))
scatter.add(class_key[point], [coordinates[0]], [coordinates[1]])
temp_path = 'html/render.html'
scatter.render(path=temp_path)
make_a_snapshot(temp_path, image_name)
def scatter_demo(self):
# 散点图
from pyecharts import Scatter
scatter = Scatter('散点图', '一年的降水量与蒸发量')
# xais_name是设置横坐标名称，这里由于显示问题，还需要将y轴名称与y轴的距离进行设置
scatter.add("降水量与蒸发量的散点分布",
self.data1,
self.data2,
xaxis_name="降水量",
yaxis_name="蒸发量",
yaxis_name_gap=40)
scatter.render('sactter.html')
def scatter(self):
cmtnum = []
likenum = []
timeS = []
for item in self.data:
cmtnum.append(item[0])
likenum.append(item[1])
d = datetime.fromtimestamp(item[2])
timeS.append(d.year + d.month / 12)
y_min = datetime.fromtimestamp(self.createtime_min).year
y_max = datetime.fromtimestamp(self.createtime_max).year
scatter = Scatter('本人说说点赞数与评论数的时间序列（二维）')
scatter.add('评论数',
timeS,
cmtnum,
extra_data=cmtnum,
xaxis_max=y_max,
xaxis_min=y_min,
is_datazoom_extra_show=True,
datazoom_extra_type='inside',
legend_pos='right',
xaxis_name='年份',
is_visualmap=True,
visual_dimension=2,
visual_orient="horizontal",
visual_type="size",
visual_range=[0, 205],
visual_range_size=[5, 20],
visual_text_color="#000")
scatter.add('点赞数',
timeS,
likenum,
extra_data=likenum,
xaxis_max=y_max,
xaxis_min=y_min,
is_datazoom_extra_show=True,
datazoom_extra_type='inside',
legend_pos='right',
xaxis_name='年份',
is_visualmap=True,
visual_dimension=2,
visual_orient="horizontal",
visual_type="size",
visual_range=[0, 205],
visual_range_size=[5, 20],
visual_text_color="#000")
scatter.render(self.path + 'scatter2d_' + str(int(time.time())) +
'.html')
webbrowser.open_new_tab(self.path + 'scatter2d_' +
str(int(time.time())) + '.html')
self.ins.analysis_pb['value'] = 100
self.ins.analysis_lb.configure(text='完毕')
def scatter_echar_AvgArea_price(self):
x, y = self.getPriceInterval_avg()
scatter = Scatter("广州市租房平均面积与平均价格关系图")
scatter.add(
"平均面积-平均价格",
x,
y,
yaxis_name="平均价格(元)",
xaxis_name="平均面积(平米)",
yaxis_name_gap=50,
)
scatter.render('scatter_avgAreaPrice.html')
def create_scatter(df):
"""
三维度散点图
"""
# 生成数据列表
data = [list(i) for i in zip(df['videos'], df['fans'], df['likes'])]
print(data)
# 生成散点图
x_lst = [v[0] for v in data]
y_lst = [v[1] for v in data]
extra_data = [v[2] for v in data]
sc = Scatter("抖音大V视频数粉丝数点赞数三维度", title_pos='center', title_top='5', width=800, height=400)
sc.add("", x_lst, y_lst, extra_data=extra_data, is_visualmap=True, visual_dimension=2, visual_orient="horizontal", visual_type="size", visual_range=[0, 500000000], visual_text_color="#000", visual_range_size=[5, 30])
sc.render('抖音大V视频数粉丝数点赞数三维度.html')
def drawPicture(self, file):
df = pd.read_excel(file)
df = pd.DataFrame(df)
df.fillna(0, inplace=True)
df['曹操'] = df['曹操'] + df['丞相'] + df['操大怒'] + df['曹丞相'] + df['操大喜']
df['诸葛亮'] = df['诸葛亮'] + df['孔明曰'] + df['孔明笑'] + df['孔明']
df['刘备'] = df['刘备'] + df['玄德'] + df['玄德曰'] + df['主公'] + df['刘皇叔'] + \
df['刘玄德'] + df['玄德大'] + df['玄德问'] + df['刘豫州'] + df['玄德闻'] + df['玄德乃']
df['关云长'] = df['关云长'] + df['云长'] + df['关公']
df['赵云'] = df['赵子龙'] + df['子龙'] + df['赵云']
df['司马懿'] = df['司马懿'] + df['仲达'] + df['司马']
df['周瑜'] = df['公瑾'] + df['周瑜']
df['张飞'] = df['张飞'] + df['翼德']
del ([
df['丞相'], df['操大怒'], df['曹丞相'], df['操大喜'], df['孔明曰'], df['孔明笑'],
df['孔明'], df['玄德'], df['玄德曰'], df['主公'], df['刘皇叔'], df['刘玄德'],
df['玄德大'], df['玄德问'], df['刘豫州'], df['玄德闻'], df['玄德乃'], df['云长'],
df['关公'], df['赵子龙'], df['子龙'], df['仲达'], df['司马'], df['公瑾'],
df['翼德']
])
data = pd.DataFrame(df)
kings = ['曹操', '刘备', '孙权', '司马懿']
shuGuo = ['刘备', '关云长', '张飞', '诸葛亮']
x = [i for i in range(120)]
s = Scatter('四位当权者活跃回')
for king in kings:
s.add('{}'.format(king),
x,
data[king],
xaxis_rotate=60,
symbol_size=4)
s.show_config()
s.render('四位当权者活跃回.html')
nameS = Line('蜀国')
for name in shuGuo:
nameS.add('{}'.format(name),
x,
data[name],
xaxis_rotate=60,
symbol_size=0,
area_opacity=0.6)
nameS.show_config()
nameS.render('蜀国.html')
def tsen_plot(name,weight,label):
print("T-SNE start")
# 使用T-SNE算法，对权重进行降维，准确度比PCA算法高，但是耗时长
tsne = TSNE(n_components=2)
decomposition_data = tsne.fit_transform(weight)
x = []
y = []
for i in decomposition_data:
x.append(i[0])
y.append(i[1])
scatter = Scatter(title=name,title_top='bottom',title_pos='center')
for i in range(len(x)):
scatter.add(str(label[i]),[x[i]],[y[i]],symbol_size=5,is_datazoom_show=True)
scatter.render(name+".html")
def scores_of_bread(data):
star = data['Star'].mean()
taste = data['Taste'].mean()
environ = data['Environment'].mean()
service = data['Service'].mean()
ave = (taste + environ + service) / 3
result_show = [star, taste, environ, service, ave]
config_info = [('星级', 50), ('口味', 10), ('环境', 10), ('服务', 10), ('综合', 10)]
scores_fig1 = Radar('综合评分情况')
scores_fig1.config(config_info)
scores_fig1.add('', [result_show])
scores_fig1.render(os.path.join(data_out, 'scores1_of_bread.html'))
result = pd.DataFrame(columns=data.columns)
for index, item in enumerate(data['Taste']):
if item == data['Taste'].max():
# print('口味最好：\n', data.loc[index])
# print(data.loc[index].info())
result = result.append(data.loc[index])
for index, item in enumerate(data['Environment']):
if item == data['Environment'].max():
# print('环境最佳：\n', data.loc[index])
result = result.append(data.loc[index])
for index, item in enumerate(data['Service']):
if item == data['Service'].max():
# print('服务最棒：\n', data.loc[index])
result = result.append(data.loc[index])
result.to_csv(os.path.join(data_out, 'result_of_best.csv'),
encoding='utf-8-sig')
print(
'最昂贵的菜系：%s' %
data.groupby('Cuisine')['Per_Consumption'].mean().idxmax(),
'人均：%.2f元' % data.groupby('Cuisine')['Per_Consumption'].mean().max())
print('最受欢迎的菜系：%s' % data.groupby('Cuisine')['Comments'].mean().idxmax(),
'平均有：%d条评论' % data.groupby('Cuisine')['Comments'].mean().max())
data['ave'] = round(
(data['Taste'] + data['Environment'] + data['Service']) / 3, 2)
scores_fig2 = Scatter('综合评分与餐厅星级关系')
scores_fig2.add('综合评分', data['Star'].values, data['ave'].values)
scores_fig2.render(os.path.join(data_out, 'scores2_of_bread.html'))
def test_scatter_visualmap():
# visual type 'color'
v1 = [10, 20, 30, 40, 50, 60]
v2 = [10, 20, 30, 40, 50, 60]
scatter = Scatter("散点图示例")
scatter.add("A", v1, v2)
scatter.add("B", v1[::-1], v2, is_visualmap=True)
scatter.render()
# visual type 'size'
scatter = Scatter("散点图示例")
# scatter.add("A", v1, v2)
scatter.add("B",
v1[::-1],
v2,
is_visualmap=True,
visual_type='size',
visual_range_size=[20, 80])
scatter.render()
def scatterXY(self):
cmtnum = []
likenum = []
shuoshuo = []
for item in self.data:
cmtnum.append(item[0])
likenum.append(item[1])
shuoshuo.append(item[3])
regr = linear_model.LinearRegression()
# Train the model using the training sets
regr.fit(np.array(likenum)[:-5].reshape(-1, 1), np.array(cmtnum)[:-5])
pred = regr.predict(np.array(likenum)[-5:].reshape(-1, 1))
# The coefficients
print('Coefficients: \n', regr.coef_)
print('Intercept:\n', regr.intercept_)
# Explained variance score: 1 is perfect prediction
r2 = r2_score(np.array(cmtnum)[-5:], pred)
print('Variance score: %.2f' % r2)
scatter = Scatter(
'本人说说点赞数与评论数关系', '评论数 = ' + str(regr.coef_[0]) + ' * 点赞数 + ' +
str(regr.intercept_) + ' r2 = ' + str(r2))
scatter.add('说说',
likenum,
cmtnum,
extra_data=shuoshuo,
symbol_size=5,
is_label_show=False,
is_label_emphasis=True,
label_formatter='{c}',
label_emphasis_textcolor='#000',
is_datazoom_show=False,
is_datazoom_extra_show=False,
legend_pos='right',
xaxis_name='点赞数',
yaxis_name='评论数')
scatter.render(self.path + 'regression_' + str(int(time.time())) +
'.html')
webbrowser.open_new_tab(self.path + 'regression_' +
str(int(time.time())) + '.html')
self.ins.analysis_pb['value'] = 100
self.ins.analysis_lb.configure(text='完毕')
def MFE(path_name):
with open(path_name, 'r', encoding="utf-8") as json_file:
date_dict = json.loads(json_file.read())
# =============================================================================
# 从掘金回撤文件中获取净值-浮动盈亏
# =============================================================================
nav_fpnl = []
for date in range(len(date_dict["indicatorDuration"])):
if date != 0:
nav_fpnl.append((date_dict["indicatorDuration"][date]["nav"],date_dict["indicatorDuration"][date]["fpnl"]))
#止损能避免的损失-止损金额
stopprofit_stoplose = []
for index in range(len(nav_fpnl) - 1):
if nav_fpnl[index][1]<0:
stopprofit_stoplose.append((nav_fpnl[index][0] - (nav_fpnl[index+1][0] - nav_fpnl[index+1][1])
,nav_fpnl[index][1]))
temp = np.array([item[1] for item in stopprofit_stoplose]).min()
x_total = [item[1]/temp for item in stopprofit_stoplose]
temp = np.array([item[0] for item in stopprofit_stoplose]).max()
y_total = [item[0]/temp for item in stopprofit_stoplose]
x_y = list(zip(x_total,y_total))
x_y.sort(reverse=True)
x_y = x_y[1:161]
x_y.sort()
# =============================================================================
# 绘制MFE
# =============================================================================
from pyecharts import Scatter
scatter = Scatter("MFE")
y1 = [item[0]*10 for item in x_y if item[1]<0]
x1 = [abs(item[1])*5 for item in x_y if item[1]<0]
y2 = [item[0]*10 for item in x_y if item[1]>0]
x2 = [item[1]*5 for item in x_y if item[1]>0]
scatter.add("lose", x2, y2, symbol_size=5)
scatter.add("win", x1, y1, symbol_size=5,
xaxis_name="Run-up%",yaxis_name="Prfit(lose) in %",yaxis_name_gap=35)
scatter.render("MFE.html")
def test_scatter_xaxis_type():
# xAxis type 'value'
v1 = [10, 20, 30, 40, 50, 60]
v2 = [10, 20, 30, 40, 50, 60]
scatter = Scatter("散点图示例")
scatter.add("A", v1, v2)
scatter.add("B", v1[::-1], v2)
assert '"type": "value"' in scatter._repr_html_()
assert '"type": "category"' not in scatter._repr_html_()
scatter.render()
# xAxis type 'category'
scatter = Scatter("散点图示例")
scatter.add("A", ["a", "b", "c", "d", "e", "f"], v2)
scatter.add("B", ["a", "b", "c", "d", "e", "f"],
v1[::-1],
xaxis_type="category")
assert '"type": "category"' in scatter._repr_html_()
scatter.render()
def scanter():
v1, v2 = [], []
with open("C:\\Temp\\fund\\257020_detail.json", "r") as f:
data = json.load(f)
for year in data["0.05"]:
for item in data["0.05"][year]:
if len(item) != 1:
r = str(item).split(",")
print(r)
v1.append(float(r[2].replace(" ", "")))
v1.append(float(r[3].replace(" ", "")))
v2.append(int(r[4].replace("'", "")))
v2.append(int(r[5][:-1].replace("'", "")))
print(v1)
print(v2)
# v1 = [10, 20, 30, 40, 50, 60]
# v2 = [10, 20, 30, 40, 50, 60]
fund_scanter = Scatter("Fund")
fund_scanter.add("A", v2, v1, xaxis_min=2000000, xaxis_max=20200000)
# fund_scanter.add("B", v1[::-1], v2)
fund_scanter.render()
def scatter_map(chartname):
plot_data_er = np.loadtxt(open(
"static/res/charts-map/charts-data/plot_data_er2.csv", "rb"),
delimiter=",",
skiprows=0)
plot_data_mr = np.loadtxt(open(
"static/res/charts-map/charts-data/plot_data_mr2.csv", "rb"),
delimiter=",",
skiprows=0)
if (chartname == 'erangel'):
chartdata = plot_data_er
else:
chartdata = plot_data_mr
x_lst = [v[0] for v in chartdata]
y_lst = [v[1] for v in chartdata]
extra_data = [v[2] for v in chartdata]
sc = Scatter()
sc.add(
"scatter",
x_lst,
y_lst,
symbol_size=5,
extra_data=extra_data,
is_visualmap=True,
is_yaxis_inverse=True,
is_xaxis_show=False,
is_yaxis_show=False,
is_splitline_show=False,
visual_dimension=2,
visual_orient="horizontal",
# visual_type="size",
visual_range=[1500, 2200],
visual_text_color="#000",
)
sc.render()
return sc
def test_scatter_draw_picture():
# draw pyecharts
scatter = Scatter("散点图示例")
v1, v2 = scatter.draw("../images/pyecharts-0.png")
scatter.add("pyecharts", v1, v2, is_random=True)
scatter.render()
# draw love
scatter = Scatter("散点图示例", width=800, height=480)
v1, v2 = scatter.draw("../images/love.png")
scatter.add("Love", v1, v2)
scatter.render()
# draw a hot red bra
scatter = Scatter("散点图示例", width=1000, height=480)
v1, v2 = scatter.draw("../images/cup.png")
scatter.add("Cup", v1, v2)
scatter.render()
# draw a sexy black bra
scatter = Scatter("散点图示例", width=1000, height=480)
v1, v2 = scatter.draw("../images/cup.png")
scatter.add("Cup", v1, v2, label_color=["#000"])
scatter.render()
def test_scatter_draw_love():
scatter = Scatter("散点图示例", width=800, height=480)
v1, v2 = scatter.draw("../images/love.png")
scatter.add("Love", v1, v2)
scatter.render()
def test_scatter_visualmap_default():
scatter = Scatter("散点图示例")
scatter.add("A", v1, v2)
scatter.add("B", v1[::-1], v2, is_visualmap=True)
scatter.render()
def test_grid():
# grid_0
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, is_grid=True)
bar.add("商家A", attr, v1, is_stack=True, grid_bottom="60%")
bar.add("商家B", attr, v2, is_stack=True, grid_bottom="60%")
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%")
bar.grid(line.get_series(), grid_top="60%")
bar.show_config()
bar.render()
# grid_1
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter(width=1200, is_grid=True)
scatter.add("散点图示例", v1, v2, grid_left="60%", legend_pos="70%")
es = EffectScatter()
es.add("动态散点图示例", [11, 11, 15, 13, 12, 13, 10], [1, -2, 2, 5, 3, 2, 0],
effect_scale=6, legend_pos="20%")
scatter.grid(es.get_series(), grid_right="60%")
scatter.show_config()
scatter.render()
# 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%", is_grid=True)
bar.add("商家A", attr, v1, is_stack=True, grid_bottom="60%", grid_left="60%")
bar.add("商家B", attr, v2, is_stack=True, grid_bottom="60%", grid_left="60%", 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%")
bar.grid(line.get_series(), grid_bottom="60%", grid_right="60%")
bar.grid(scatter.get_series(), grid_top="60%", grid_left="60%")
bar.grid(es.get_series(), grid_top="60%", grid_right="60%")
bar.show_config()
bar.render()
# grid_3
line = Line("折线图示例", width=1200, is_grid=True)
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"], grid_right="65%")
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="45%")
pie.add("", attr, v1, radius=[30, 55], legend_pos="65%", legend_orient='vertical')
line.grid(pie.get_series(), grid_left="60%")
line.show_config()
line.render()
# grid_4
line = Line("折线图示例", width=1200, is_grid=True)
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"], grid_right="60%")
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"],
mark_line=["average"], legend_pos="20%", grid_right="60%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
value = [20, 40, 60, 80, 100, 120]
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%")
line.grid(kline.get_series(), grid_left="55%")
line.show_config()
line.render()
# grid_5
import random
x_axis = ["12a", "1a", "2a", "3a", "4a", "5a", "6a", "7a", "8a", "9a", "10a", "11a",
"12p", "1p", "2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p", "10p", "11p"]
y_aixs = ["Saturday", "Friday", "Thursday", "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", height=700, is_grid=True)
heatmap.add("热力图直角坐标系", x_axis, y_aixs, data, is_visualmap=True, visual_top="45%",
visual_text_color="#000", visual_orient='horizontal', grid_bottom="60%")
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%")
heatmap.grid(bar.get_series(), grid_top="60%")
heatmap.show_config()
heatmap.render()
import pandas as pd
dfboy = pd.DataFrame()
dfboy['weight'] = [56,67,65,70,57,60,80,85,76,64]
dfboy['height'] = [162,170,168,172,168,172,180,176,178,170]
dfgirl = pd.DataFrame()
dfgirl['weight'] = [50,62,60,70,57,45,62,65,70,56]
dfgirl['height'] = [155,162,165,170,166,158,160,170,172,165]
scatter = Scatter(title = "体格数据",width = 600,height = 420)
scatter.add(name = "boy", x_axis = dfboy['weight'], y_axis = dfboy['height'])
scatter.add(name = "girl", x_axis = dfgirl['weight'], y_axis = dfgirl['height'],
yaxis_min = 130,yaxis_max = 200,xaxis_min = 30,xaxis_max = 100)
scatter.render("result.散点图示范.html")
scatter
#当样本属性维度多于2个时，散点图可以使用点的颜色或大小等方式来表达更多属性维度。下面示范使用点的大小表示第3个维度。
def custom_formatter(params):
return (params.value[3] + ':' +
str(params.value[0]) +','
+str(params.value[1]) + ','
+str(params.value[2]))
df = pd.DataFrame()
df['country'] = ["中国",'美国','德国','法国','英国','日本','俄罗斯','印度','澳大利亚','加拿大']
df['life-expectancy'] = [76.9,79.1,81.1,81.9,81.4,83.5,73.13,66.8,81.8,81.7]
def test_scatter_draw_sexy_black_bra():
scatter = Scatter("散点图示例", width=1000, height=480)
v1, v2 = scatter.draw("../images/cup.png")
scatter.add("Cup", v1, v2, label_color=["#000"])
scatter.render()
def test_scatter_draw_pyecharts():
scatter = Scatter("散点图示例")
v1, v2 = scatter.draw("../images/pyecharts-0.png")
scatter.add("pyecharts", v1, v2, is_random=True)
scatter.render()
def test_grid():
# grid_0
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, is_grid=True)
bar.add("商家A", attr, v1, is_stack=True, grid_bottom="60%")
bar.add("商家B", attr, v2, is_stack=True, grid_bottom="60%")
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%")
bar.grid(line.get_series(), grid_top="60%")
bar.show_config()
bar.render()
# grid_1
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter(width=1200, is_grid=True)
scatter.add("散点图示例", v1, v2, grid_left="60%", legend_pos="70%")
es = EffectScatter()
es.add("动态散点图示例", [11, 11, 15, 13, 12, 13, 10], [1, -2, 2, 5, 3, 2, 0],
effect_scale=6,
legend_pos="20%")
scatter.grid(es.get_series(), grid_right="60%")
scatter.show_config()
scatter.render()
# 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%", is_grid=True)
bar.add("商家A", attr, v1, is_stack=True, grid_bottom="60%", grid_left="60%")
bar.add("商家B",
attr,
v2,
is_stack=True,
grid_bottom="60%",
grid_left="60%",
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%")
bar.grid(line.get_series(), grid_bottom="60%", grid_right="60%")
bar.grid(scatter.get_series(), grid_top="60%", grid_left="60%")
bar.grid(es.get_series(), grid_top="60%", grid_right="60%")
bar.show_config()
bar.render()
# grid_3
line = Line("折线图示例", width=1200, is_grid=True)
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"],
grid_right="65%")
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="45%")
pie.add("",
attr,
v1,
radius=[30, 55],
legend_pos="65%",
legend_orient='vertical')
line.grid(pie.get_series(), grid_left="60%")
line.show_config()
line.render()
# grid_4
line = Line("折线图示例", width=1200, is_grid=True)
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"],
grid_right="60%")
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%",
grid_right="60%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
value = [20, 40, 60, 80, 100, 120]
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%")
line.grid(kline.get_series(), grid_left="55%")
line.show_config()
line.render()
# grid_5
import random
x_axis = [
"12a", "1a", "2a", "3a", "4a", "5a", "6a", "7a", "8a", "9a", "10a",
"11a", "12p", "1p", "2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p",
"10p", "11p"
]
y_aixs = [
"Saturday", "Friday", "Thursday", "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", height=700, is_grid=True)
heatmap.add("热力图直角坐标系",
x_axis,
y_aixs,
data,
is_visualmap=True,
visual_top="45%",
visual_text_color="#000",
visual_orient='horizontal',
grid_bottom="60%")
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%")
heatmap.grid(bar.get_series(), grid_top="60%")
heatmap.show_config()
heatmap.render()
def test_scatter_draw__hot_red_bra():
scatter = Scatter("散点图示例", width=1000, height=480)
v1, v2 = scatter.draw("../images/cup.png")
scatter.add("Cup", v1, v2)
scatter.render()
