Seaborn Catplot 在条形图上设置值

Seaborn Catplot set values over the bars(Seaborn Catplot 在条形图上设置值)

问题描述

我像这样在seaborn中绘制了一个catplot

将 seaborn 导入为 sns将熊猫导入为 pd数据= {'年':[2016、2013、2014、2015、2016、2013、2014、2015、2016、2013、2014、2015、2016、2013、2014、2015、2016、2013、2014、2015]geo_name': ['Michigan', 'Michigan', 'Michigan', 'Michigan', 'Washtenaw County, MI', 'Washtenaw County, MI', 'Washtenaw County, MI', 'Washtenaw County, MI', 'Ann密歇根州阿伯市"、密歇根州安娜堡"、密歇根州安娜堡"、密歇根州安娜堡"、宾夕法尼亚州费城"、宾夕法尼亚州费城"、宾夕法尼亚州费城"、宾夕法尼亚州费城"、'密歇根州安娜堡市都会区', '密歇根州安娜堡市都会区', '密歇根州安娜堡市都会区', '密歇根州安娜堡市都会区'], 'geo': ['04000US26', '04000US26','04000us26'，'04000us26'，'05000us26161'，'05000us26161'，'05000us26161'，'16000us2603000'，'16000us2603000'，'16000us2603000'，'16000us4260000'，'16000us4260000'，'16000US4260000'，'16000US4260000'，'16000US42600'，'16000US42600'，'16000US42600'，'16000US42600'，'16000US42600'，'16000US42600'，'16000US4260000''16000US4260000''，'16000US4260000'，'31000US11460'，'31000US11460'，'31000US11460'，'31000us11460'，'收入':[50803.0,48411.0,49087.0,49576.0,62484.0,59055.0,60805.0,61003.0,57697.0,59003.0,56835.0，55990.0,39770.0,37192.0,37460.0,38253.0,62484.0,59055.0,60805.0,61003.0]，收入_MOE":[162.0,163.0,192.0,186.0,984.0,985.0,958.0,901.0,2046.0,1688.0,1320.0,1259.0,567.0，424.0、430.0、511.0、984.0、985.0、958.0、901.0]}df = pd.DataFrame(数据)g = sns.catplot(x='year', y='income', data=df, kind='bar', hue='geo_name', legend=True)g.fig.set_size_inches(15,8)g.fig.subplots_adjust(top=0.81,right=0.86)

我得到如下所示的输出

我想在 K 表示的顶部添加每个条的值.例如在 2013 中，Michigan 的栏位于 48411 所以我想在上面添加值 48.4K酒吧.对于所有的酒吧也是如此.

更新至matplotlib v3.4.2

• 使用

  对于单个或多个地块

  g = sns.catplot(x='year', y='income', data=df, kind='bar', col='geo_name',col_wrap=3，图例=真)g.fig.set_size_inches(15, 8)g.fig.subplots_adjust(top=0.9)g.fig.suptitle('带注释的条形计数')# 遍历轴对于 g.axes.ravel() 中的 ax:# 添加注释对于 ax.containers 中的 c:标签 = [f'{(v.get_height()/1000):.1f}K' for v in c]ax.bar_label(c, 标签=标签, label_type='edge')ax.margins(y=0.2)plt.show()

  I plotted a catplot in seaborn like this

  import seaborn as sns
  import pandas as pd
  
  data  = {'year': [2016, 2013, 2014, 2015, 2016, 2013, 2014, 2015, 2016, 2013, 2014, 2015, 2016, 2013, 2014, 2015, 2016, 2013, 2014, 2015], 'geo_name': ['Michigan', 'Michigan', 'Michigan', 'Michigan', 'Washtenaw County, MI', 'Washtenaw County, MI', 'Washtenaw County, MI', 'Washtenaw County, MI', 'Ann Arbor, MI', 'Ann Arbor, MI', 'Ann Arbor, MI', 'Ann Arbor, MI', 'Philadelphia, PA', 'Philadelphia, PA', 'Philadelphia, PA', 'Philadelphia, PA', 'Ann Arbor, MI Metro Area', 'Ann Arbor, MI Metro Area', 'Ann Arbor, MI Metro Area', 'Ann Arbor, MI Metro Area'], 'geo': ['04000US26', '04000US26', '04000US26', '04000US26', '05000US26161', '05000US26161', '05000US26161', '05000US26161', '16000US2603000', '16000US2603000', '16000US2603000', '16000US2603000', '16000US4260000', '16000US4260000', '16000US4260000', '16000US4260000', '31000US11460', '31000US11460', '31000US11460', '31000US11460'], 'income': [50803.0, 48411.0, 49087.0, 49576.0, 62484.0, 59055.0, 60805.0, 61003.0, 57697.0, 55003.0, 56835.0, 55990.0, 39770.0, 37192.0, 37460.0, 38253.0, 62484.0, 59055.0, 60805.0, 61003.0], 'income_moe': [162.0, 163.0, 192.0, 186.0, 984.0, 985.0, 958.0, 901.0, 2046.0, 1688.0, 1320.0, 1259.0, 567.0, 424.0, 430.0, 511.0, 984.0, 985.0, 958.0, 901.0]}
  df = pd.DataFrame(data)
  
  g = sns.catplot(x='year', y='income', data=df, kind='bar', hue='geo_name', legend=True)
  g.fig.set_size_inches(15,8)
  g.fig.subplots_adjust(top=0.81,right=0.86)  
  

  I am getting an output like shown below

  I want to add the values of each bar on its top in K representation. For example in 2013 the bar for Michigan is at 48411 so I want to add the value 48.4K on top of that bar. Likewise for all the bars.

  解决方案

  Updated as of matplotlib v3.4.2

  • Use matplotlib.pyplot.bar_label
  • See the matplotlib: Bar Label Demo page for additional formatting options.
  • Tested with pandas v1.2.4, which is using matplotlib as the plot engine.
  • Use the fmt parameter for simple formats, and labels parameter for customized string formatting.
  • See Adding value labels on a matplotlib bar chart for other plotting options related to the new method.

  For single plot only

  g = sns.catplot(x='year', y='income', data=df, kind='bar', hue='geo_name', legend=True)
  g.fig.set_size_inches(15, 8)
  g.fig.subplots_adjust(top=0.81, right=0.86)
  
  # extract the matplotlib axes_subplot objects from the FacetGrid
  ax = g.facet_axis(0, 0)
  
  # iterate through the axes containers
  for c in ax.containers:
      labels = [f'{(v.get_height() / 1000):.1f}K' for v in c]
      ax.bar_label(c, labels=labels, label_type='edge')
  

  For single or multiple plots

  g = sns.catplot(x='year', y='income', data=df, kind='bar', col='geo_name', col_wrap=3, legend=True)
  g.fig.set_size_inches(15, 8)
  g.fig.subplots_adjust(top=0.9)
  
  g.fig.suptitle('Bar Count with Annotations')
  
  # iterate through axes
  for ax in g.axes.ravel():
      
      # add annotations
      for c in ax.containers:
          labels = [f'{(v.get_height() / 1000):.1f}K' for v in c]
          ax.bar_label(c, labels=labels, label_type='edge')
      ax.margins(y=0.2)
  
  plt.show()
  

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