python使用Plotly繪圖工具繪制柱狀圖

更新時間：2019年04月01日 15:26:23 作者：成都-王帥

這篇文章主要為大家詳細介紹了python使用Plotly繪圖工具繪制柱狀圖，具有一定的參考價值，感興趣的小伙伴們可以參考一下

本文實例為大家分享了python使用Plotly繪圖工具繪制柱狀圖的具體代碼，供大家參考，具體內容如下

使用Plotly繪制基本的柱狀圖，需要用到的函數(shù)是graph_objs 中 Bar函數(shù)

通過參數(shù)，可以設置柱狀圖的樣式。

通過barmod進行設置可以繪制出不同類型的柱狀圖出來。

我們先來實現(xiàn)一個簡單的柱狀圖：

# -*- coding: utf-8 -*-
import plotly as py
import plotly.graph_objs as go
pyplt = py.offline.plot
# Trace
trace_basic = [go.Bar(
 x = ['Variable_1', 'Variable_2', 'Variable_3','Variable_4','Variable_5'],
 y = [1, 2, 3, 2, 4],
 )]
# Layout
layout_basic = go.Layout(
 title = 'The Graph Title',
 xaxis = go.XAxis(range = [-0.5,4.5], domain = [0,1])
 )
# Figure
figure_basic = go.Figure(data = trace_basic, layout = layout_basic)
# Plot
pyplt(figure_basic, filename='tmp/1.html')

上面這個例子，就是一個簡單的柱狀圖。

下面我們講下另外一種圖，柱狀簇

實現(xiàn)過程則是，在基本的柱狀圖中，加入多租數(shù)據(jù)即可實現(xiàn)，柱狀簇

import plotly as py
import plotly.graph_objs as go
pyplt = py.offline.plot
# Traces
trace_1 = go.Bar(
 x = ["西南石油", "東方明珠", "海泰發(fā)展"],
 y = [4.12, 5.32, 0.60],
 name = "201609"
 )
trace_2 = go.Bar(
 x = ["西南石油", "東方明珠", "海泰發(fā)展"],
 y = [3.65, 6.14, 0.58],
 name = "201612"
 )
 
trace_3 = go.Bar(
 x = ["西南石油", "東方明珠", "海泰發(fā)展"],
 y = [2.15, 1.35, 0.19],
 name = "201703"
 )
trace = [trace_1, trace_2, trace_3]
# Layout
layout = go.Layout(
 title = '凈資產收益率對比圖'
 )
# Figure
figure = go.Figure(data = trace, layout = layout)
# Plot
pyplt(figure, filename='tmp/2.html')

執(zhí)行上述代碼，我們可以看到如上圖所示柱狀簇圖例

可將數(shù)據(jù)堆疊生成。

接下來在講講如何繪制層疊柱狀圖

層疊柱狀圖的繪制方法與柱狀簇的繪制方法基本差不多

也就是對同一個柱狀簇進行疊加，實現(xiàn)方法是對Layout中的barmode屬性進行設置

barmode = 'stack'

其余參數(shù)，與柱狀簇相同。

# -*- coding: utf-8 -*-
import plotly as py
import plotly.graph_objs as go
pyplt = py.offline.plot
 
# Stacked Bar Chart
trace_1 = go.Bar(
 x = ['深證50', '上證50', '西南50', '西北50','華中50'],
 y = [0.7252, 0.9912, 0.5347, 0.4436, 0.9911],
 name = '股票投資'
)
 
trace_2 = go.Bar(
 x = ['深證50', '上證50', '西南50', '西北50','華中50'],
 y = [0.2072, 0, 0.4081, 0.4955, 0.02],
 name='其它投資'
)
 
trace_3 = go.Bar(
 x = ['深證50', '上證50', '西南50', '西北50','華中50'],
 y = [0, 0, 0.037, 0, 0],
 name='債券投資'
)
 
trace_4 = go.Bar(
 x = ['深證50', '上證50', '西南50', '西北50','華中50'],
 y = [0.0676, 0.0087, 0.0202, 0.0609, 0.0087],
 name='銀行存款'
)
 
trace = [trace_1, trace_2, trace_3, trace_4]
layout = go.Layout(
 title = '基金資產配置比例圖',
 barmode='stack'
)
 
fig = go.Figure(data = trace, layout = layout)
pyplt(fig, filename='tmp/1.html')

瀑布式柱狀圖

瀑布式柱狀圖是層疊柱狀圖的另外一種表現(xiàn)

可以選擇性地顯示層疊部分來實現(xiàn)柱狀圖的懸浮效果。

# -*- coding: utf-8 -*-
import plotly as py
import plotly.graph_objs as go
pyplt = py.offline.plot
 
x_data = ['資產1', '資產2',
  '資產3','資產4', '總資產']
y_data = [56000000, 65000000, 65000000, 81000000, 81000000]
text = ['666,999,888萬元', '8,899,666萬元', '88,899,666萬元', '16,167,657萬元', '888,888,888萬元']
 
# Base
trace0 = go.Bar(
 x=x_data,
 y=[0, 57999848, 0, 66899764, 0],
 marker=dict(
 color='rgba(1,1,1, 0.0)',
 )
)
# Trace
trace1 = go.Bar(
 x=x_data,
 y=[57999848, 8899916, 66899764,16167657, 83067421],
 marker=dict(
 color='rgba(55, 128, 191, 0.7)',
 line=dict(
  color='rgba(55, 128, 191, 1.0)',
  width=2,
 )
 )
)
 
data = [trace0, trace1]
layout = go.Layout(
 title = '測試圖例',
 barmode='stack',
 showlegend=False
)
 
annotations = []
 
for i in range(0, 5):
 annotations.append(dict(x=x_data[i], y=y_data[i], text=text[i],
     font=dict(family='Arial', size=14,
     color='rgba(245, 246, 249, 1)'),
     showarrow=False,))
 layout['annotations'] = annotations
 
fig = go.Figure(data=data, layout=layout)
pyplt(fig, filename = 'tmp/1.html')

運行上述代碼，可以得到如上圖所示的瀑布式柱狀圖。

下面我們說說，圖形樣式的設置。

對于柱狀圖顏色與樣式的設置可以通過設置下面這個案例來說明。

import plotly as py
import plotly.graph_objs as go
pyplt = py.offline.plot
 
# Customizing Individual Bar Colors
volume = [0.49,0.71,1.43,1.4,0.93]
width = [each*3/sum(volume) for each in volume]
trace0 = go.Bar(
 x = ['AU.SHF', 'AG.SHF', 'SN.SHF',
 'PB.SHF', 'CU.SHF'],
 y = [0.85, 0.13, -0.93, 0.46, 0.06],
 width = width,
 marker = dict(
 color=['rgb(205,38,38)', 'rgb(205,38,38)',
  'rgb(34,139,34)', 'rgb(205,38,38)',
  'rgb(205,38,38)'],
 line=dict(
  color='rgb(0,0,0)',
  width=1.5,
 )),
 opacity = 0.8,
)
 
data = [trace0]
layout = go.Layout(
 title = '有色金屬板塊主力合約日內最高漲幅與波動率圖',
 xaxis=dict(tickangle=-45),
)
 
fig = go.Figure(data=data, layout=layout)
pyplt(fig, filename='tmp/4.html')