如何使用 Altair 创建嵌套分组条形图？ - 添加了示例数据
How to create a nested Grouped Bar Chart using Altair? - Added sample data
<table class="table table-bordered table-hover table-condensed">
<thead><tr><th title="Field #1">year</th>
<th title="Field #2">primary_type</th>
<th title="Field #3">Number_of_Incidents</th>
<th title="Field #4">number_of_arrests</th>
<th title="Field #5">percent_arrest</th>
<th title="Field #6">rank</th>
</tr></thead>
<tbody><tr>
<td align="right">2018</td>
<td>THEFT</td>
<td align="right">57330</td>
<td align="right">5503</td>
<td align="right">9.6</td>
<td align="right">1</td>
</tr>
<tr>
<td align="right">2018</td>
<td>BATTERY</td>
<td align="right">44667</td>
<td align="right">8886</td>
<td align="right">19.89</td>
<td align="right">2</td>
</tr>
<tr>
<td align="right">2018</td>
<td>CRIMINAL DAMAGE</td>
<td align="right">24889</td>
<td align="right">1498</td>
<td align="right">6.02</td>
<td align="right">3</td>
</tr>
<tr>
<td align="right">2018</td>
<td>ASSAULT</td>
<td align="right">18229</td>
<td align="right">2931</td>
<td align="right">16.08</td>
<td align="right">4</td>
</tr>
<tr>
<td align="right">2018</td>
<td>DECEPTIVE PRACTICE</td>
<td align="right">15879</td>
<td align="right">713</td>
<td align="right">4.49</td>
<td align="right">5</td>
</tr>
<tr>
<td align="right">2017</td>
<td>THEFT</td>
<td align="right">64334</td>
<td align="right">6459</td>
<td align="right">10.04</td>
<td align="right">1</td>
</tr>
<tr>
<td align="right">2017</td>
<td>BATTERY</td>
<td align="right">49213</td>
<td align="right">10060</td>
<td align="right">20.44</td>
<td align="right">2</td>
</tr>
<tr>
<td align="right">2017</td>
<td>CRIMINAL DAMAGE</td>
<td align="right">29040</td>
<td align="right">1747</td>
<td align="right">6.02</td>
<td align="right">3</td>
</tr>
<tr>
<td align="right">2017</td>
<td>ASSAULT</td>
<td align="right">19298</td>
<td align="right">3455</td>
<td align="right">17.9</td>
<td align="right">4</td>
</tr>
<tr>
<td align="right">2017</td>
<td>DECEPTIVE PRACTICE</td>
<td align="right">18816</td>
<td align="right">805</td>
<td align="right">4.28</td>
<td align="right">5</td>
</tr>
<tr>
<td align="right">2016</td>
<td>THEFT</td>
<td align="right">61600</td>
<td align="right">6518</td>
<td align="right">10.58</td>
<td align="right">1</td>
</tr>
<tr>
<td align="right">2016</td>
<td>BATTERY</td>
<td align="right">50292</td>
<td align="right">10328</td>
<td align="right">20.54</td>
<td align="right">2</td>
</tr>
<tr>
<td align="right">2016</td>
<td>CRIMINAL DAMAGE</td>
<td align="right">31018</td>
<td align="right">1668</td>
<td align="right">5.38</td>
<td align="right">3</td>
</tr>
<tr>
<td align="right">2016</td>
<td>ASSAULT</td>
<td align="right">18738</td>
<td align="right">3490</td>
<td align="right">18.63</td>
<td align="right">4</td>
</tr>
<tr>
<td align="right">2016</td>
<td>DECEPTIVE PRACTICE</td>
<td align="right">18733</td>
<td align="right">815</td>
<td align="right">4.35</td>
<td align="right">5</td>
</tr>
<tr>
<td align="right">2015</td>
<td>THEFT</td>
<td align="right">57335</td>
<td align="right">6771</td>
<td align="right">11.81</td>
<td align="right">1</td>
</tr>
<tr>
<td align="right">2015</td>
<td>BATTERY</td>
<td align="right">48918</td>
<td align="right">11558</td>
<td align="right">23.63</td>
<td align="right">2</td>
</tr>
<tr>
<td align="right">2015</td>
<td>CRIMINAL DAMAGE</td>
<td align="right">28675</td>
<td align="right">1835</td>
<td align="right">6.4</td>
<td align="right">3</td>
</tr>
<tr>
<td align="right">2015</td>
<td>NARCOTICS</td>
<td align="right">23883</td>
<td align="right">23875</td>
<td align="right">99.97</td>
<td align="right">4</td>
</tr>
<tr>
<td align="right">2015</td>
<td>OTHER OFFENSE</td>
<td align="right">17552</td>
<td align="right">4795</td>
<td align="right">27.32</td>
<td align="right">5</td>
</tr>
<tr>
<td align="right">2014</td>
<td>THEFT</td>
<td align="right">61561</td>
<td align="right">7415</td>
<td align="right">12.04</td>
<td align="right">1</td>
</tr>
<tr>
<td align="right">2014</td>
<td>BATTERY</td>
<td align="right">49447</td>
<td align="right">12517</td>
<td align="right">25.31</td>
<td align="right">2</td>
</tr>
<tr>
<td align="right">2014</td>
<td>NARCOTICS</td>
<td align="right">29116</td>
<td align="right">29000</td>
<td align="right">99.6</td>
<td align="right">3</td>
</tr>
<tr>
<td align="right">2014</td>
<td>CRIMINAL DAMAGE</td>
<td align="right">27798</td>
<td align="right">2095</td>
<td align="right">7.54</td>
<td align="right">4</td>
</tr>
<tr>
<td align="right">2014</td>
<td>OTHER OFFENSE</td>
<td align="right">16979</td>
<td align="right">4159</td>
<td align="right">24.49</td>
<td align="right">5</td>
</tr>
<tr>
<td align="right">2013</td>
<td>THEFT</td>
<td align="right">71530</td>
<td align="right">7727</td>
<td align="right">10.8</td>
<td align="right">1</td>
</tr>
<tr>
<td align="right">2013</td>
<td>BATTERY</td>
<td align="right">54002</td>
<td align="right">12927</td>
<td align="right">23.94</td>
<td align="right">2</td>
</tr>
<tr>
<td align="right">2013</td>
<td>NARCOTICS</td>
<td align="right">34127</td>
<td align="right">33819</td>
<td align="right">99.1</td>
<td align="right">3</td>
</tr>
<tr>
<td align="right">2013</td>
<td>CRIMINAL DAMAGE</td>
<td align="right">30853</td>
<td align="right">2107</td>
<td align="right">6.83</td>
<td align="right">4</td>
</tr>
<tr>
<td align="right">2013</td>
<td>OTHER OFFENSE</td>
<td align="right">17993</td>
<td align="right">3400</td>
<td align="right">18.9</td>
<td align="right">5</td>
</tr>
</tbody></table>
我的情况很特殊。在我的数据中，我有年份，每年我有 5 个类别及其相应的计数。我能够为相应的年份创建这 5 个类别的堆积条形图。但是，我想在我的 x 轴上显示每年 5 个相邻的条形图。对于 y 轴，它应该显示每个条的相应总数。
这是我当前的可视化和代码：
import altair as alt
base = alt.Chart(q13a).encode(
alt.X('year:O',
axis=alt.Axis(format='%b', title='Year'),
scale=alt.Scale(zero=False)
),
tooltip = ['year']
)
bar = base.mark_bar().encode(
alt.Y('sum(Number_of_Incidents)',
axis=alt.Axis(title='sum(Number_of_Incidents)'))
,color=alt.Color('primary_type')
#tooltip = ['primary_type']
)
line = base.mark_line(color='red').encode(
#y='No_of_repos',
alt.Y('percent_arrest',
axis=alt.Axis(title='percent_arrest')),
)
alt.layer(
bar
).resolve_scale(
y='independent'
).properties(
height=500,
width=1200
)
我的问题是，我如何才能在 x 轴上为每年创建 5 个相邻的条形图而不是堆积条形图？
提前感谢您的帮助。
制作并排条形图的唯一方法是同时使用列编码和 x 编码。您可以在此处关注 Altair 示例库中的分组条形图示例：https://altair-viz.github.io/gallery/grouped_bar_chart.html
您的数据结果将如下所示：
import altair as alt
import pandas as pd
import numpy as np
q13a = pd.DataFrame({
'year': np.random.randint(2000, 2018, 100),
'Number_of_Incidents': np.random.randint(0, 20, 100),
'percent_arrest': np.random.rand(100),
'primary_type': np.random.choice(['a', 'b', 'c', 'd', 'e'], 100)
})
alt.Chart(q13a).mark_bar().encode(
x=alt.X('primary_type', scale=alt.Scale(rangeStep=8), title=None),
y=alt.Y('sum(Number_of_Incidents)', title='sum(Number_of_Incidents)'),
color='primary_type',
column='year',
tooltip=['year']
).configure_view(
stroke='transparent'
)
@jakevdp 已经回答了，但是为了回答你的最后一个问题（即使你有几个问题应该问几个问题），你可以用 alt.EncodingSortField.[=15 对条形进行排序=]
import altair as alt
alt.Chart(q13a).mark_bar().encode(
x=alt.X('primary_type:N',
scale=alt.Scale(rangeStep=8),
axis=None,
sort=alt.EncodingSortField(field='Number_of_Incident',
op='sum',
order='ascending')
),
y=alt.Y('sum(Number_of_Incidents):Q', title='sum(Number_of_Incidents)'),
color='primary_type:N',
tooltip=['primary_type:N',
'year:O',
alt.Tooltip('sum(Number_of_Incidents):Q',
title='Number of incidents')
]
).facet(
column=alt.Column('year:O',
header=alt.Header(title=None)),
).resolve_scale(
x='independent'
).configure_view(
stroke='transparent'
)
数据
import pandas as pd
from io import StringIO
q13a = pd.read_table(StringIO("""year primary_type Number_of_Incidents number_of_arrests percent_arrest rank
2018 THEFT 57330 5503 9.6 1
2018 BATTERY 44667 8886 19.89 2
2018 CRIMINAL DAMAGE 24889 1498 6.02 3
2018 ASSAULT 18229 2931 16.08 4
2018 DECEPTIVE PRACTICE 15879 713 4.49 5
2017 THEFT 64334 6459 10.04 1
2017 BATTERY 49213 10060 20.44 2
2017 CRIMINAL DAMAGE 29040 1747 6.02 3
2017 ASSAULT 19298 3455 17.9 4
2017 DECEPTIVE PRACTICE 18816 805 4.28 5
2016 THEFT 61600 6518 10.58 1
2016 BATTERY 50292 10328 20.54 2
2016 CRIMINAL DAMAGE 31018 1668 5.38 3
2016 ASSAULT 18738 3490 18.63 4
2016 DECEPTIVE PRACTICE 18733 815 4.35 5
2015 THEFT 57335 6771 11.81 1
2015 BATTERY 48918 11558 23.63 2
2015 CRIMINAL DAMAGE 28675 1835 6.4 3
2015 NARCOTICS 23883 23875 99.97 4
2015 OTHER OFFENSE 17552 4795 27.32 5
2014 THEFT 61561 7415 12.04 1
2014 BATTERY 49447 12517 25.31 2
2014 NARCOTICS 29116 29000 99.6 3
2014 CRIMINAL DAMAGE 27798 2095 7.54 4
2014 OTHER OFFENSE 16979 4159 24.49 5
2013 THEFT 71530 7727 10.8 1
2013 BATTERY 54002 12927 23.94 2
2013 NARCOTICS 34127 33819 99.1 3
2013 CRIMINAL DAMAGE 30853 2107 6.83 4
2013 OTHER OFFENSE 17993 3400 18.9 5"""))
于 2018-11-28 创建
<table class="table table-bordered table-hover table-condensed">
<thead><tr><th title="Field #1">year</th>
<th title="Field #2">primary_type</th>
<th title="Field #3">Number_of_Incidents</th>
<th title="Field #4">number_of_arrests</th>
<th title="Field #5">percent_arrest</th>
<th title="Field #6">rank</th>
</tr></thead>
<tbody><tr>
<td align="right">2018</td>
<td>THEFT</td>
<td align="right">57330</td>
<td align="right">5503</td>
<td align="right">9.6</td>
<td align="right">1</td>
</tr>
<tr>
<td align="right">2018</td>
<td>BATTERY</td>
<td align="right">44667</td>
<td align="right">8886</td>
<td align="right">19.89</td>
<td align="right">2</td>
</tr>
<tr>
<td align="right">2018</td>
<td>CRIMINAL DAMAGE</td>
<td align="right">24889</td>
<td align="right">1498</td>
<td align="right">6.02</td>
<td align="right">3</td>
</tr>
<tr>
<td align="right">2018</td>
<td>ASSAULT</td>
<td align="right">18229</td>
<td align="right">2931</td>
<td align="right">16.08</td>
<td align="right">4</td>
</tr>
<tr>
<td align="right">2018</td>
<td>DECEPTIVE PRACTICE</td>
<td align="right">15879</td>
<td align="right">713</td>
<td align="right">4.49</td>
<td align="right">5</td>
</tr>
<tr>
<td align="right">2017</td>
<td>THEFT</td>
<td align="right">64334</td>
<td align="right">6459</td>
<td align="right">10.04</td>
<td align="right">1</td>
</tr>
<tr>
<td align="right">2017</td>
<td>BATTERY</td>
<td align="right">49213</td>
<td align="right">10060</td>
<td align="right">20.44</td>
<td align="right">2</td>
</tr>
<tr>
<td align="right">2017</td>
<td>CRIMINAL DAMAGE</td>
<td align="right">29040</td>
<td align="right">1747</td>
<td align="right">6.02</td>
<td align="right">3</td>
</tr>
<tr>
<td align="right">2017</td>
<td>ASSAULT</td>
<td align="right">19298</td>
<td align="right">3455</td>
<td align="right">17.9</td>
<td align="right">4</td>
</tr>
<tr>
<td align="right">2017</td>
<td>DECEPTIVE PRACTICE</td>
<td align="right">18816</td>
<td align="right">805</td>
<td align="right">4.28</td>
<td align="right">5</td>
</tr>
<tr>
<td align="right">2016</td>
<td>THEFT</td>
<td align="right">61600</td>
<td align="right">6518</td>
<td align="right">10.58</td>
<td align="right">1</td>
</tr>
<tr>
<td align="right">2016</td>
<td>BATTERY</td>
<td align="right">50292</td>
<td align="right">10328</td>
<td align="right">20.54</td>
<td align="right">2</td>
</tr>
<tr>
<td align="right">2016</td>
<td>CRIMINAL DAMAGE</td>
<td align="right">31018</td>
<td align="right">1668</td>
<td align="right">5.38</td>
<td align="right">3</td>
</tr>
<tr>
<td align="right">2016</td>
<td>ASSAULT</td>
<td align="right">18738</td>
<td align="right">3490</td>
<td align="right">18.63</td>
<td align="right">4</td>
</tr>
<tr>
<td align="right">2016</td>
<td>DECEPTIVE PRACTICE</td>
<td align="right">18733</td>
<td align="right">815</td>
<td align="right">4.35</td>
<td align="right">5</td>
</tr>
<tr>
<td align="right">2015</td>
<td>THEFT</td>
<td align="right">57335</td>
<td align="right">6771</td>
<td align="right">11.81</td>
<td align="right">1</td>
</tr>
<tr>
<td align="right">2015</td>
<td>BATTERY</td>
<td align="right">48918</td>
<td align="right">11558</td>
<td align="right">23.63</td>
<td align="right">2</td>
</tr>
<tr>
<td align="right">2015</td>
<td>CRIMINAL DAMAGE</td>
<td align="right">28675</td>
<td align="right">1835</td>
<td align="right">6.4</td>
<td align="right">3</td>
</tr>
<tr>
<td align="right">2015</td>
<td>NARCOTICS</td>
<td align="right">23883</td>
<td align="right">23875</td>
<td align="right">99.97</td>
<td align="right">4</td>
</tr>
<tr>
<td align="right">2015</td>
<td>OTHER OFFENSE</td>
<td align="right">17552</td>
<td align="right">4795</td>
<td align="right">27.32</td>
<td align="right">5</td>
</tr>
<tr>
<td align="right">2014</td>
<td>THEFT</td>
<td align="right">61561</td>
<td align="right">7415</td>
<td align="right">12.04</td>
<td align="right">1</td>
</tr>
<tr>
<td align="right">2014</td>
<td>BATTERY</td>
<td align="right">49447</td>
<td align="right">12517</td>
<td align="right">25.31</td>
<td align="right">2</td>
</tr>
<tr>
<td align="right">2014</td>
<td>NARCOTICS</td>
<td align="right">29116</td>
<td align="right">29000</td>
<td align="right">99.6</td>
<td align="right">3</td>
</tr>
<tr>
<td align="right">2014</td>
<td>CRIMINAL DAMAGE</td>
<td align="right">27798</td>
<td align="right">2095</td>
<td align="right">7.54</td>
<td align="right">4</td>
</tr>
<tr>
<td align="right">2014</td>
<td>OTHER OFFENSE</td>
<td align="right">16979</td>
<td align="right">4159</td>
<td align="right">24.49</td>
<td align="right">5</td>
</tr>
<tr>
<td align="right">2013</td>
<td>THEFT</td>
<td align="right">71530</td>
<td align="right">7727</td>
<td align="right">10.8</td>
<td align="right">1</td>
</tr>
<tr>
<td align="right">2013</td>
<td>BATTERY</td>
<td align="right">54002</td>
<td align="right">12927</td>
<td align="right">23.94</td>
<td align="right">2</td>
</tr>
<tr>
<td align="right">2013</td>
<td>NARCOTICS</td>
<td align="right">34127</td>
<td align="right">33819</td>
<td align="right">99.1</td>
<td align="right">3</td>
</tr>
<tr>
<td align="right">2013</td>
<td>CRIMINAL DAMAGE</td>
<td align="right">30853</td>
<td align="right">2107</td>
<td align="right">6.83</td>
<td align="right">4</td>
</tr>
<tr>
<td align="right">2013</td>
<td>OTHER OFFENSE</td>
<td align="right">17993</td>
<td align="right">3400</td>
<td align="right">18.9</td>
<td align="right">5</td>
</tr>
</tbody></table>
我的情况很特殊。在我的数据中，我有年份，每年我有 5 个类别及其相应的计数。我能够为相应的年份创建这 5 个类别的堆积条形图。但是，我想在我的 x 轴上显示每年 5 个相邻的条形图。对于 y 轴，它应该显示每个条的相应总数。
这是我当前的可视化和代码：
import altair as alt
base = alt.Chart(q13a).encode(
alt.X('year:O',
axis=alt.Axis(format='%b', title='Year'),
scale=alt.Scale(zero=False)
),
tooltip = ['year']
)
bar = base.mark_bar().encode(
alt.Y('sum(Number_of_Incidents)',
axis=alt.Axis(title='sum(Number_of_Incidents)'))
,color=alt.Color('primary_type')
#tooltip = ['primary_type']
)
line = base.mark_line(color='red').encode(
#y='No_of_repos',
alt.Y('percent_arrest',
axis=alt.Axis(title='percent_arrest')),
)
alt.layer(
bar
).resolve_scale(
y='independent'
).properties(
height=500,
width=1200
)
我的问题是，我如何才能在 x 轴上为每年创建 5 个相邻的条形图而不是堆积条形图？
提前感谢您的帮助。
制作并排条形图的唯一方法是同时使用列编码和 x 编码。您可以在此处关注 Altair 示例库中的分组条形图示例：https://altair-viz.github.io/gallery/grouped_bar_chart.html
您的数据结果将如下所示：
import altair as alt
import pandas as pd
import numpy as np
q13a = pd.DataFrame({
'year': np.random.randint(2000, 2018, 100),
'Number_of_Incidents': np.random.randint(0, 20, 100),
'percent_arrest': np.random.rand(100),
'primary_type': np.random.choice(['a', 'b', 'c', 'd', 'e'], 100)
})
alt.Chart(q13a).mark_bar().encode(
x=alt.X('primary_type', scale=alt.Scale(rangeStep=8), title=None),
y=alt.Y('sum(Number_of_Incidents)', title='sum(Number_of_Incidents)'),
color='primary_type',
column='year',
tooltip=['year']
).configure_view(
stroke='transparent'
)
@jakevdp 已经回答了，但是为了回答你的最后一个问题（即使你有几个问题应该问几个问题），你可以用 alt.EncodingSortField.[=15 对条形进行排序=]
import altair as alt
alt.Chart(q13a).mark_bar().encode(
x=alt.X('primary_type:N',
scale=alt.Scale(rangeStep=8),
axis=None,
sort=alt.EncodingSortField(field='Number_of_Incident',
op='sum',
order='ascending')
),
y=alt.Y('sum(Number_of_Incidents):Q', title='sum(Number_of_Incidents)'),
color='primary_type:N',
tooltip=['primary_type:N',
'year:O',
alt.Tooltip('sum(Number_of_Incidents):Q',
title='Number of incidents')
]
).facet(
column=alt.Column('year:O',
header=alt.Header(title=None)),
).resolve_scale(
x='independent'
).configure_view(
stroke='transparent'
)
数据
import pandas as pd
from io import StringIO
q13a = pd.read_table(StringIO("""year primary_type Number_of_Incidents number_of_arrests percent_arrest rank
2018 THEFT 57330 5503 9.6 1
2018 BATTERY 44667 8886 19.89 2
2018 CRIMINAL DAMAGE 24889 1498 6.02 3
2018 ASSAULT 18229 2931 16.08 4
2018 DECEPTIVE PRACTICE 15879 713 4.49 5
2017 THEFT 64334 6459 10.04 1
2017 BATTERY 49213 10060 20.44 2
2017 CRIMINAL DAMAGE 29040 1747 6.02 3
2017 ASSAULT 19298 3455 17.9 4
2017 DECEPTIVE PRACTICE 18816 805 4.28 5
2016 THEFT 61600 6518 10.58 1
2016 BATTERY 50292 10328 20.54 2
2016 CRIMINAL DAMAGE 31018 1668 5.38 3
2016 ASSAULT 18738 3490 18.63 4
2016 DECEPTIVE PRACTICE 18733 815 4.35 5
2015 THEFT 57335 6771 11.81 1
2015 BATTERY 48918 11558 23.63 2
2015 CRIMINAL DAMAGE 28675 1835 6.4 3
2015 NARCOTICS 23883 23875 99.97 4
2015 OTHER OFFENSE 17552 4795 27.32 5
2014 THEFT 61561 7415 12.04 1
2014 BATTERY 49447 12517 25.31 2
2014 NARCOTICS 29116 29000 99.6 3
2014 CRIMINAL DAMAGE 27798 2095 7.54 4
2014 OTHER OFFENSE 16979 4159 24.49 5
2013 THEFT 71530 7727 10.8 1
2013 BATTERY 54002 12927 23.94 2
2013 NARCOTICS 34127 33819 99.1 3
2013 CRIMINAL DAMAGE 30853 2107 6.83 4
2013 OTHER OFFENSE 17993 3400 18.9 5"""))