`plotnine` 中的 KeyError（python 的 ggplot 包装器）

Question

我正在尝试使用 plotnine 构建图表，但当我只想绘制 x-axis 时，我一直遇到相同的 KeyError 问题。请参阅下面的回溯错误。我的数据样本是：

       WORD  TAG  TOPIC Value      
0       hey  aa      1  234 
1   working  bb      1  123 
2   lullaby  cc      2  32
3     Doggy  cc      2  63
4  document  aa      3  84

我的代码示例：

from plotnine import *
import pandas as pd

inFile = 'infile.csv'
df = pd.read_csv(inFile, names = ['WORD', 'TAG','TOPIC','VALUE'], header=0,sep='\t')
df.sort_values('value',ascending=False)
sortedDf = df[:5]

plot1 = ggplot(sortedDf) + aes(x='TOPIC') + geom_histogram(binwidth=3)

最终目标是在直方图中绘制每个主题的 count。我不确定缺少哪些数据会引发以下 key 错误，因为不需要 weight 因为我只对绘制该特定变量的计数感兴趣，即。主题 1 = 2，主题 2 = 2，主题 3 = 1。

有没有人有 link 更详细的 plotline 文档或任何使用图书馆的经验来帮助我更详细地了解我所缺少的东西。

Traceback Error:


    ---------------------------------------------------------------------------
    KeyError                                  Traceback (most recent call last)
    <ipython-input-112-71707b4cf21a> in <module>()
          1 plot2 = ggplot(sortedDf) + aes(x='TOPIC') + geom_histogram(binwidth=3)
    ----> 2 print plot2

    /Users/anaconda/lib/python2.7/site-packages/plotnine/ggplot.pyc in __repr__(self)
         82         Print/show the plot
         83         """
    ---> 84         self.draw()
         85         plt.show()
         86         return '<ggplot: (%d)>' % self.__hash__()

    /Users/anaconda/lib/python2.7/site-packages/plotnine/ggplot.pyc in draw(self)
        139         # assign a default theme
        140         self = deepcopy(self)
    --> 141         self._build()
        142 
        143         # If no theme we use the default

    /Users/anaconda/lib/python2.7/site-packages/plotnine/ggplot.pyc in _build(self)
        235 
        236         # Apply and map statistics
    --> 237         layers.compute_statistic(layout)
        238         layers.map_statistic(self)
        239 

    /Users/anaconda/lib/python2.7/site-packages/plotnine/layer.pyc in compute_statistic(self, layout)
         92     def compute_statistic(self, layout):
         93         for l in self:
    ---> 94             l.compute_statistic(layout)
         95 
         96     def map_statistic(self, plot):

    /Users/anaconda/lib/python2.7/site-packages/plotnine/layer.pyc in compute_statistic(self, layout)
        369         data = self.stat.use_defaults(data)
        370         data = self.stat.setup_data(data)
    --> 371         data = self.stat.compute_layer(data, params, layout)
        372         self.data = data
        373 

    /Users/anaconda/lib/python2.7/site-packages/plotnine/stats/stat.pyc in compute_layer(cls, data, params, layout)
        194             return cls.compute_panel(pdata, pscales, **params)
        195 
    --> 196         return groupby_apply(data, 'PANEL', fn)
        197 
        198     @classmethod

    /Users/anaconda/lib/python2.7/site-packages/plotnine/utils.pyc in groupby_apply(df, cols, func, *args, **kwargs)
        615         # do not mark d as a slice of df i.e no SettingWithCopyWarning
        616         d.is_copy = None
    --> 617         lst.append(func(d, *args, **kwargs))
        618     return pd.concat(lst, axis=axis, ignore_index=True)
        619 

    /Users/anaconda/lib/python2.7/site-packages/plotnine/stats/stat.pyc in fn(pdata)
        192                 return pdata
        193             pscales = layout.get_scales(pdata['PANEL'].iat[0])
    --> 194             return cls.compute_panel(pdata, pscales, **params)
        195 
        196         return groupby_apply(data, 'PANEL', fn)

    /Users/anaconda/lib/python2.7/site-packages/plotnine/stats/stat.pyc in compute_panel(cls, data, scales, **params)
        221         for _, old in data.groupby('group'):
        222             old.is_copy = None
    --> 223             new = cls.compute_group(old, scales, **params)
        224             unique = uniquecols(old)
        225             missing = unique.columns.difference(new.columns)

    /Users/anaconda/lib/python2.7/site-packages/plotnine/stats/stat_bin.pyc in compute_group(cls, data, scales, **params)
        107         new_data = assign_bins(
        108             data['x'], breaks, data.get('weight'),
    --> 109             params['pad'], params['closed'])
        110         return new_data

    /Users/anaconda/lib/python2.7/site-packages/plotnine/stats/binning.pyc in assign_bins(x, breaks, weight, pad, closed)
        163     df = pd.DataFrame({'bin_idx': bin_idx, 'weight': weight})
        164     wftable = df.pivot_table(
    --> 165         'weight', index=['bin_idx'], aggfunc=np.sum)['weight']
        166 
        167     # Empty bins get no value in the computed frequency table.

    /Users/anaconda/lib/python2.7/site-packages/pandas/core/series.pyc in __getitem__(self, key)
        601             result = self.index.get_value(self, key)
        602 
    --> 603             if not is_scalar(result):
        604                 if is_list_like(result) and not isinstance(result, Series):
        605 

    /Users/anaconda/lib/python2.7/site-packages/pandas/indexes/base.pyc in get_value(self, series, key)

    pandas/index.pyx in pandas.index.IndexEngine.get_value (pandas/index.c:3557)()

    pandas/index.pyx in pandas.index.IndexEngine.get_value (pandas/index.c:3240)()

    pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:4363)()

    KeyError: 'weight'

Answer 1

像在 R 中那样在 ggplot 中嵌套 aes 可能会解决您的问题：

plot1 = ggplot(sortedDf, aes(x='TOPIC')) + geom_histogram(binwidth=3)

`plotnine` 中的 KeyError（python 的 ggplot 包装器）

KeyError in `plotnine` (ggplot wrapper for python)

python

keyerror

python-ggplot

plotnine