Question

这是我的代码，

avg_data = dataset.groupby('Gender').mean()
print(avg_data)

输出：

            Height      Weight     Index
Gender                                  
Female  170.227451  105.698039  3.709804
Male    169.648980  106.314286  3.787755

我想使用countplot绘制这些数据。

sns.countplot(x='Gender',hue='Height',data=avg_data)

错误！

ValueError                                Traceback (most recent call 
last)
<ipython-input-54-59e9d525d88d> in <module>
----> 1 sns.countplot(x='Gender',hue='Height',data=avg_data)

/usr/local/lib/python3.6/dist-packages/seaborn/categorical.py in 
countplot(x, y, hue, data, order, hue_order, orient, color, palette, 
saturation, dodge, ax, **kwargs)
3551                           estimator, ci, n_boot, units,
3552                           orient, color, palette, saturation,
-> 3553                           errcolor, errwidth, capsize, dodge)
3554 
3555     plotter.value_label = "count"

/usr/local/lib/python3.6/dist-packages/seaborn/categorical.py in 
__init__(self, x, y, hue, data, order, hue_order, estimator, ci, 
n_boot, units, orient, color, palette, saturation, errcolor, errwidth, 
capsize, dodge)
1605         """Initialize the plotter."""
1606         self.establish_variables(x, y, hue, data, orient,
-> 1607                                  order, hue_order, units)
1608         self.establish_colors(color, palette, saturation)
1609         self.estimate_statistic(estimator, ci, n_boot)

/usr/local/lib/python3.6/dist-packages/seaborn/categorical.py in 
establish_variables(self, x, y, hue, data, orient, order, hue_order, 
units)
153                 if isinstance(input, string_types):
154                     err = "Could not interpret input 
'{}'".format(input)
--> 155                     raise ValueError(err)
156 
157             # Figure out the plotting orientation

ValueError: Could not interpret input 'Gender'

它检测到没有“性别”列。该如何解决？

Answer 1

现在，Gender是所得数据帧的索引。只需对此命令执行reset_index()：

avg_data = dataset.groupby('Gender').mean().reset_index()

OR

avg_data = dataset.groupby('Gender', as_index=False).mean()

这将创建Gender作为您可以在其上绘制数据框的列。

将列名称分配给DataFrame中的列

1 个答案: