可视化神器Plotly(4)---条形图

2019-07-07 本文已影响0人惑也

一、导入包

# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import plotly.offline as py                    #保存图表，相当于plotly.plotly as py，同时增加了离线功能
py.init_notebook_mode(connected=True)          #离线绘图时，需要额外进行初始化
import plotly.graph_objs as go                 #创建各类图表
import plotly.figure_factory as ff             #创建table

二、参数说明

本文用到的部分参数说明如下，仅供参考，具体见官方文档；
barmode : 设置相同坐标的条形图位置。包括 : stack(叠加)、group(并列)、overlay(覆盖)、relative(相对)；
opacity : 设置跟踪的不透明度，default为1；
text : 设置跟踪文本；
textposition : 设置text的位置，包括 : "inside" | "outside" | "auto" | "none"；
tickangle : 设置刻度标签相对于水平线的角度；
base : 设置坐标位置基数；
tickfont : 设置刻度标签字体和颜色；
titlefont : 设置刻度标题字体和颜色；
bargroupgap : 设置相同位置条形图之间的间隙，范围：0-1；
bargap : 设置相邻位置条形图之间的间隙，范围：0-1；
layout.legend : 设置图例布局
bgcolor：设置图例背景颜色
bordercolor：设置图例边框颜色
borderwidth：设置图例的边框的宽度
front：设置图例文本设置
orientation：设置图例方向
x : 设置图例的x位置，范围：-2～3，y轴相同
traceorder：设置图例显示顺序，包括："reversed"，"grouped"，"reversed+grouped"，"normal"
<br> : 通过html标签可以对图例文本进行换行；
paper_bgcolor : 设置图表内容外的背景色；
plot_bgcolor : 设置图表背景色；
font : 设置悬停标签中使用的字体。family(HTML字体系列)、size、color等；
特别地，Plotly的图表中，trace / data / layout / iplot 等均可以采用字典的方式书写。

三、基本条形图

代码

trace = go.Bar(
    x = ['giraffes', 'orangutans', 'monkeys'],
    y = [15, 32, 26]
)
data = [trace]

py.iplot(data, filename='basic-bar')

效果

三、分组条形图

代码

trace1 = go.Bar(
     x = ['giraffes', 'orangutans', 'monkeys'],
     y = [20, 14, 23],
     name='SF Zoo'
)
trace2 = go.Bar(
     x = ['giraffes', 'orangutans', 'monkeys'],
     y = [12, 18, 29],
     name='LA Zoo'
)
data = [trace1, trace2]

# layout = go.Layout(barmode='relative')
# fig = go.Figure(data=data, layout=layout)
layout = dict(barmode='stack')
fig = dict(data=data, layout=layout)
py.iplot(fig, filename='grouped-bar')

效果

四、条形图与悬停文本

代码

trace = go.Bar(
    x = ['Product A', 'Product B', 'Product C'],
    y = [20, 14, 23],
    text=['27% market share', '24% market share', '19% market share'],
    marker=dict(color='rgb(158,202,225)', line=dict(color='rgb(8,48,107)', width=1.5)),
    opacity=0.6
)
data = [trace]

layout = dict(title='January 2013 Sales Report')
fig = dict(data=data, layout=layout)
py.iplot(fig, filename='text-hover-bar')

效果

五、带有直接标签的条形图

代码

x = ['Product A', 'Product B', 'Product C']
y = [20, 14, 23]

trace = go.Bar(
    x = x,
    y = y,
    text = y,
    textposition = 'outside',
    marker = dict(color = 'rgb(158,202,225)',
                  line = dict(color = 'rgb(8,48,107)',
                              width = 1.5)
    ),
    opacity = 0.6
)
data = [trace]

py.iplot(data, filename='bar-direct-labels')

效果

六、旋转条形图

代码

trace0 = go.Bar(
    x = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'],
    y = [20, 14, 25, 16, 18, 22, 19, 15, 12, 16, 14, 17],
    name = 'Primary Product',
    marker = dict(color='rgb(49,130,189)')
)
trace1 = go.Bar(
     x = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'],
     y = [19, 14, 22, 14, 16, 19, 15, 14, 10, 12, 12, 16],
     name = 'Secondary Product',
     marker = dict(color='rgb(204,204,204)')
)
data = [trace0, trace1]

layout = dict(xaxis = dict(tickangle = -60), barmode = 'group')
fig = dict(data = data, layout = layout)
py.iplot(fig, filename = 'angled-text-bar')

效果

七、自定义单个条形颜色

代码

trace0 = go.Bar(
     x = ['Feature A', 'Feature B', 'Feature C', 'Feature D', 'Feature E'],
     y = [20, 14, 23, 25, 22],
     marker = dict(color=['rgba(204,204,204,1)', 'rgba(222,45,38,0.8)',
                          'rgba(204,204,204,1)', 'rgba(204,204,204,1)',
                          'rgba(204,204,204,1)'])
)
data = [trace0]

layout = dict(title='Least Used Feature')
fig = dict(data=data, layout=layout)
py.iplot(fig, filename='color-bar')

效果

八、自定义单个条宽度

代码

trace0 = go.Bar(
     x = [1, 2, 3, 5.5, 10],
     y = [10, 8, 6, 4, 2],
     width = [0.8, 0.8, 0.8, 3.5, 5]
)

data = [trace0]

py.iplot(data, filename='width-bar')

效果

九、自定义坐标位置基数

代码

trace0 = go.Bar(
     x = ['2016','2017','2018'],
     y = [500,600,700],
     base = [-500,-600,-700],
     marker = dict(color = 'red'),
     name = 'expenses'
)
trace1 = go.Bar(
     x = ['2016','2017','2018'],
     y = [300,400,700],
     base = 0,
     marker = dict(color = 'blue'),
     name = 'revenue'
)
data = [trace0, trace1]

py.iplot(data)

效果

十、样式条形图

代码

trace1 = go.Bar(
     x = [1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003,
          2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012],
     y = [219, 146, 112, 127, 124, 180, 236, 207, 236, 263,
          350, 430, 474, 526, 488, 537, 500, 439],
     name = 'Rest of world',
     marker = dict(color='rgb(55, 83, 109)')
)
trace2 = go.Bar(
     x = [1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003,
          2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012],
     y = [16, 13, 10, 11, 28, 37, 43, 55, 56, 88, 105, 156, 270,
          299, 340, 403, 549, 499],
     name = 'China',
     marker = dict(color='rgb(26, 118, 255)')
)
data = [trace1, trace2]

layout = dict(title = 'US Export of Plastic Scrap',
              xaxis = dict(title = 'Month',
                           tickfont = dict(size = 16, color = 'rgb(55, 83, 109)'),
                           titlefont = dict(size = 13, color = 'rgb(26, 118, 255)')),
              yaxis = dict(title = 'USD (millions)',
                           tickfont = dict(size = 16, color = 'rgb(26, 118, 255)'),
                           titlefont = dict(size = 13, color = 'rgb(55, 83, 109)')),
              legend = dict(x = 0.03,
                            y = 1.03,
                            bgcolor = 'rgba(204,204,204,1)',
                            bordercolor = 'rgba(222,45,38,0.8)',
                            borderwidth = 2),
              barmode = 'group',
              bargap = 0.3,
              bargroupgap = 0.2)

fig = dict(data=data, layout=layout)
py.iplot(fig, filename='style-bar')

代码

十一、瀑布条形图

代码

x_data = ['Product<br>Revenue', 'Services<br>Revenue', 'Total<br>Revenue', 'Fixed<br>Costs',
          'Variable<br>Costs', 'Total<br>Costs', 'Total']
y_data = [400, 660, 660, 660, 450, 660, 350]
text = ['$430K', '$260K', '$690K', '$-120K', '$-200K', '$-320K', '$370K']

# Base
trace0 = go.Bar(
     x = x_data,
     y = [0, 430, 0, 570, 370, 370, 0],
     marker = dict(color='rgba(1,1,1, 0.0)')    #通过颜色设置，将trace0的bar都隐藏了
)
# Revenue
trace1 = go.Bar(
     x = x_data,
     y = [430, 260, 690, 0, 0, 0, 0],
     marker = dict(color='rgba(55, 128, 191, 0.7)',
                   line=dict(color='rgba(55, 128, 191, 1.0)', width=2))
)
# Costs
trace2 = go.Bar(
     x = x_data,
     y = [0, 0, 0, 120, 200, 320, 0],
    marker = dict(color = 'rgba(219, 64, 82, 0.7)',
                  line=dict(color='rgba(219, 64, 82, 1.0)', width=2))
)
# Profit
trace3 = go.Bar(
     x = x_data,
     y = [0, 0, 0, 0, 0, 0, 370],
     marker = dict(color='rgba(50, 171, 96, 0.7)',
                   line=dict(color='rgba(50, 171, 96, 1.0)', width=2))
)
data = [trace0, trace1, trace2, trace3]

layout = go.Layout(title='Annual Profit- 2015',
                   barmode='stack',
                   paper_bgcolor='rgba(204,204,204,1)',
                   plot_bgcolor='rgba(245, 246, 249, 1)',
                   showlegend=False)

"""
通过遍历，设置标记在图表中的位置：x 定位横轴、y 定位纵轴距离
"""
annotations = []
for i in range(0, 7):
    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 = dict(data=data, layout=layout)
py.iplot(fig)

效果

十二、相对堆叠的条形图

代码

trace1 = {
    'x': [1, 2, 3, 4],
    'y': [1, 4, 9, 16],
    'name': 'Trace1',
    'type': 'bar'
}
trace2 = {
    'x': [1, 2, 3, 4],
    'y': [6, -8, -4.5, 8],
    'name': 'Trace2',
    'type': 'bar'
}
trace3 = {
    'x': [1, 2, 3, 4],
    'y': [-15, -3, 4.5, -8],
    'name': 'Trace3',
    'type': 'bar'
}
trace4 = {
    'x': [1, 2, 3, 4],
    'y': [-1, 3, -3, -4],
    'name': 'Trace4',
    'type': 'bar'
}
data = [trace1, trace2, trace3, trace4]

layout = {
  'xaxis': {'title': '横轴'},
  'yaxis': {'title': '纵轴'},
  'barmode': 'relative',
  'title': '相对堆叠条形图'
};
py.iplot({'data': data, 'layout': layout}, filename='barmode-relative')

效果

可视化神器Plotly(4)---条形图

一、导入包

二、参数说明

三、基本条形图

三、分组条形图

四、条形图与悬停文本

五、带有直接标签的条形图

六、旋转条形图

七、自定义单个条形颜色

八、自定义单个条宽度

九、自定义坐标位置基数

十、样式条形图

十一、瀑布条形图

十二、相对堆叠的条形图

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