问题
Say I have this dataframe
d = { 'Path' : ['abc', 'abc', 'ghi','ghi', 'jkl','jkl'],
'Detail' : ['foo', 'bar', 'bar','foo','foo','foo'],
'Program': ['prog1','prog1','prog1','prog2','prog3','prog3'],
'Value' : [30, 20, 10, 40, 40, 50],
'Field' : [50, 70, 10, 20, 30, 30] }
df = DataFrame(d)
df.set_index(['Path', 'Detail'], inplace=True)
df
Field Program Value
Path Detail
abc foo 50 prog1 30
bar 70 prog1 20
ghi bar 10 prog1 10
foo 20 prog2 40
jkl foo 30 prog3 40
foo 30 prog3 50
I can aggregate it no problem (if there's a better way to do this, by the way, I'd like to know!)
df_count = df.groupby('Program').count().sort(['Value'], ascending=False)[['Value']]
df_count
Program Value
prog1 3
prog3 2
prog2 1
df_mean = df.groupby('Program').mean().sort(['Value'], ascending=False)[['Value']]
df_mean
Program Value
prog3 45
prog2 40
prog1 20
I can plot it from Pandas no problem...
df_mean.plot(kind='bar')
But why do I get this error when I try it in seaborn?
sns.factorplot('Program',data=df_mean)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-26-23c2921627ec> in <module>()
----> 1 sns.factorplot('Program',data=df_mean)
C:\Anaconda3\lib\site-packages\seaborn\categorical.py in factorplot(x, y, hue, data, row, col, col_wrap, estimator, ci, n_boot, units, order, hue_order, row_order, col_order, kind, size, aspect, orient, color, palette, legend, legend_out, sharex, sharey, margin_titles, facet_kws, **kwargs)
2673 # facets to ensure representation of all data in the final plot
2674 p = _CategoricalPlotter()
-> 2675 p.establish_variables(x_, y_, hue, data, orient, order, hue_order)
2676 order = p.group_names
2677 hue_order = p.hue_names
C:\Anaconda3\lib\site-packages\seaborn\categorical.py in establish_variables(self, x, y, hue, data, orient, order, hue_order, units)
143 if isinstance(input, string_types):
144 err = "Could not interperet input '{}'".format(input)
--> 145 raise ValueError(err)
146
147 # Figure out the plotting orientation
ValueError: Could not interperet input 'Program'
回答1:
The reason for the exception you are getting is that Program becomes an index of the dataframes df_mean and df_count after your group_by operation.
If you wanted to get the factorplot from df_mean, an easy solution is to add the index as a column,
In [7]:
df_mean['Program'] = df_mean.index
In [8]:
%matplotlib inline
import seaborn as sns
sns.factorplot(x='Program', y='Value', data=df_mean)
However you could even more simply let factorplot do the calculations for you,
sns.factorplot(x='Program', y='Value', data=df)
You'll obtain the same result. Hope it helps.
EDIT after comments
Indeed you make a very good point about the parameter as_index; by default it is set to True, and in that case Program becomes part of the index, as in your question.
In [14]:
df_mean = df.groupby('Program', as_index=True).mean().sort(['Value'], ascending=False)[['Value']]
df_mean
Out[14]:
Value
Program
prog3 45
prog2 40
prog1 20
Just to be clear, this way Program is not column anymore, but it becomes the index. the trick df_mean['Program'] = df_mean.index actually keeps the index as it is, and adds a new column for the index, so that Program is duplicated now.
In [15]:
df_mean['Program'] = df_mean.index
df_mean
Out[15]:
Value Program
Program
prog3 45 prog3
prog2 40 prog2
prog1 20 prog1
However, if you set as_index to False, you get Program as a column, plus a new autoincrement index,
In [16]:
df_mean = df.groupby('Program', as_index=False).mean().sort(['Value'], ascending=False)[['Program', 'Value']]
df_mean
Out[16]:
Program Value
2 prog3 45
1 prog2 40
0 prog1 20
This way you could feed it directly to seaborn. Still, you could use df and get the same result.
Hope it helps.
来源：https://stackoverflow.com/questions/32908315/could-not-interpret-input-error-with-seaborn-when-plotting-groupbys