Python資料分析可視化工具

開發環境：Ubuntu16.04+Python2.7+jupyter

pyecharts

可互動的餅圖工具

from sklearn import datasets
from pyecharts import  Pie

data = pd.DataFrame(datasets.load_iris().target)
attr = ["0", "1","2"]
pie = Pie('type')
pie.add("", attr, [int(i) for i in data[0].value_counts()] ,is_label_show=True)
pie
           

可互動柱狀圖資料堆疊示例

from pyecharts import Bar, Scatter3D
from pyecharts import Page

page = Page()  
attr = ["1", "2", "3", "4", "5", "6"]
v1 = [, , , , , ]
v2 = [, , , , , ]
bar = Bar("柱狀圖資料堆疊示例")
bar.add("A", attr, v1, is_stack=True)
bar.add("B", attr, v2, is_stack=True)
page.add(bar)
page
           

可互動3D散點圖示例

import random
data = [[random.randint(, ), random.randint(, ), random.randint(, )] for _ in range()]
range_color = ['#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',
               '#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026']
scatter3D = Scatter3D("3D 散點圖示例", width=, height=)
scatter3D.add("", data, is_visualmap=True, visual_range_color=range_color)
page.add(scatter3D) 
page