class HeatMapChart(base_chart.BaseChart):
chart = None
zaxis_name = None
data_x = []
data_y = []
heat_map = []
max_value = 0
min_value = 0
def __init__(self, title, xaxis_name, yaxis_name, zaxis_name):
base_chart.BaseChart.__init__(self, title, xaxis_name, yaxis_name)
self.zaxis_name = zaxis_name
def clear(self):
self.data_x.clear()
self.data_y.clear()
self.heat_map.clear()
def set_data(self, **data):
if ('x' in data) & ('y' in data) & ('map' in data):
self.data_x = data['x']
self.data_y = data['y']
self.to_echarts_map(data['map'])
return self
def show(self):
return self.chart
def to_echarts_map(self, map) -> []:
self.max_value = map[0][0]
self.min_value = map[0][0]
for i in range(len(map)):
for j in range(len(map[i])):
if self.max_value < map[i][j]:
self.max_value = map[i][j]
if self.min_value > map[i][j]:
self.min_value = map[i][j]
self.heat_map.append([j, i, map[i][j]])
return self.heat_map
def plot(self):
self.chart = HeatMap(init_opts=opts.InitOpts(page_title=self.title))
# load data
self.chart.add_xaxis(self.data_x)
self.chart.add_yaxis(self.zaxis_name, self.data_y, self.heat_map)
self.chart.set_global_opts(
title_opts=opts.TitleOpts(title=self.title),
xaxis_opts=opts.AxisOpts(name=self.xaxis_name,
name_location='end',
name_gap=15),
yaxis_opts=opts.AxisOpts(name=self.yaxis_name,
name_location='end',
name_gap=15),
visualmap_opts=opts.VisualMapOpts(max_=self.max_value,
min_=self.min_value))
return self
def heat_map(data: List[dict],
x_label: List[str] = None,
y_label: List[str] = None,
title: str = "热力图",
width: str = "900px",
height: str = "680px") -> HeatMap:
"""绘制热力图
:param data: 用于绘制热力图的数据，示例如下
[{'x': '0hour', 'y': '0day', 'heat': 11},
{'x': '0hour', 'y': '1day', 'heat': 40},
{'x': '0hour', 'y': '2day', 'heat': 38},
{'x': '0hour', 'y': '3day', 'heat': 36},
{'x': '0hour', 'y': '4day', 'heat': 11}]
:param x_label: x轴标签
:param y_label: y轴标签
:param title: 图表标题
:param width: 图表宽度
:param height: 图表高度
:return: 图表
"""
value = [[s['x'], s['y'], s['heat']] for s in data]
heat = [s['heat'] for s in data]
if not x_label:
x_label = sorted(list(set([s['x'] for s in data])))
if not y_label:
y_label = sorted(list(set([s['y'] for s in data])))
vis_map_opts = opts.VisualMapOpts(pos_left="90%", pos_top="20%", min_=min(heat), max_=max(heat))
title_opts = opts.TitleOpts(title=title)
init_opts = opts.InitOpts(page_title=title, width=width, height=height)
dz_inside = opts.DataZoomOpts(False, "inside", xaxis_index=[0], range_start=80, range_end=100)
dz_slider = opts.DataZoomOpts(True, "slider", xaxis_index=[0], pos_top="96%", pos_bottom="0%",
range_start=80, range_end=100)
legend_opts = opts.LegendOpts(is_show=False)
hm = HeatMap(init_opts=init_opts)
hm.add_xaxis(x_label)
hm.add_yaxis("heat", y_label, value, label_opts=opts.LabelOpts(is_show=True, position="inside"))
hm.set_global_opts(title_opts=title_opts, visualmap_opts=vis_map_opts, legend_opts=legend_opts,
xaxis_opts=opts.AxisOpts(grid_index=0), datazoom_opts=[dz_inside, dz_slider])
return hm
def v_correlation(self, end=yesterdayobj(), vopts=None):
"""
各基金净值的相关程度热力图可视化
:param end: string or object of date, the end date of the line
:returns: pyecharts.charts.Heatmap.render_notebook object
"""
ctable = self.correlation_table(end)
x_axis = list(ctable.columns)
data = [[i, j, ctable.iloc[i, j]] for i in range(len(ctable))
for j in range(len(ctable))]
heatmap = HeatMap()
heatmap.add_xaxis(x_axis)
heatmap.add_yaxis(series_name="相关性", yaxis_data=x_axis, value=data)
if vopts is None:
vopts = heatmap_opts
heatmap.set_global_opts(**vopts)
return heatmap.render_notebook()
]
parallel_data = [[12.99, 100, 82, "Good"], [9.99, 80, 77, "OK"],
[20, 120, 60, "Excellent"]]
# init_opts=opts.InitOpts(width="800px",height="300px")
parallel = Parallel(init_opts=opts.InitOpts(width="800px", height="300px"))
parallel.add_schema(parallel_axis)
parallel.add(series_name="Related Indexes",
data=parallel_data,
linestyle_opts=opts.LineStyleOpts(width=4, opacity=0.5))
liquid = Liquid(init_opts=opts.InitOpts(width="300px", height="300px"))
liquid.add("liquid", [0.6, 0.7, 0.3])
liquid.set_global_opts(title_opts=opts.TitleOpts(title="Basic Example"))
heatmap_data = [[i, j, random.randint(0, 50)] for i in range(7)
for j in range(7)]
heatmap = HeatMap()
heatmap.add_xaxis(Faker.week)
heatmap.add_yaxis(
"相关表",
Faker.week,
heatmap_data,
label_opts=opts.LabelOpts(is_show=True, position="inside"),
)
heatmap.set_global_opts(
title_opts=opts.TitleOpts(title="HeatMap-Label 显示"),
visualmap_opts=opts.VisualMapOpts(),
)
for i in range(4, 10):
kw_counts_by_score[i] = pd.read_csv(r'.\data_set\{0}_movie_keywords.csv'.format(i))
kw_percentage_df = pd.DataFrame([], columns=list(range(4, 10)), index=kw_counts_by_score[9]['kw'][:10])
# 将数据写入空表
for i in range(4, 10):
kw_df = kw_counts_by_score[i]
kw_df = kw_df[kw_df['kw'].isin(kw_percentage_df.index)]
kw_percentage_df[i] = pd.Series(list(kw_df['percentage']), index=kw_df['kw'])
# 用0替换NAN，否则无法计算
kw_percentage_df.fillna(0, inplace=True)
# 建立有三个元素的列表，作为绘制的数据
data = []
i = 0
for index in kw_percentage_df.index:
j = 0
for column in kw_percentage_df.columns:
data.append([j, i, kw_percentage_df[column][index] * 100])
j += 1
i += 1
# 绘制热力图
heatmap = HeatMap()
heatmap.add_xaxis(list(kw_percentage_df.columns))
heatmap.add_yaxis('电影评论关键词热力图', list(kw_percentage_df.index), data)
heatmap.set_global_opts(visualmap_opts=opts.VisualMapOpts(min_=0, max_=10, orient='horizontal'))
heatmap.render('comment_heatmap.html')
# -*- coding: utf-8 -*-
"""
Created on Sun Dec 13 22:17:48 2020
@author: Administrator
"""
import pandas as pd
import numpy as np
from sklearn.preprocessing import StandardScaler
from pyecharts.charts import HeatMap
from pyecharts import options as opts
s = StandardScaler()
data = pd.read_excel('info_movies.xls')[['rank','year','score','comment']]
column = data.columns.tolist()
data1 = s.fit_transform(data)
corr = abs(np.corrcoef(data1.T))
value = [[i, j, corr[i,j]] for i in range(4) for j in range(4)]
heatmap = HeatMap()
heatmap.add_xaxis(column)
heatmap.add_yaxis("相关性热力学图", column, value)
heatmap.set_global_opts(
title_opts=opts.TitleOpts(title="豆瓣电影排行数据分析结果"),
visualmap_opts=opts.VisualMapOpts(max_=1),
)
heatmap.render('templates/corr.html')
