ValueError:< something>的石斑鱼不是一维的 [英] ValueError: Grouper for <something> not 1-dimensional
问题描述
我有以下代码，这些代码通过seaborn创建了一个表和一个barplot.
I'm have the following code which creates a table and a barplot via seaborn.
#Building a dataframe grouped by the # of Engagement Types
sales_type = sales.groupby('# of Engagement Types').sum()
#Calculating the % of people who bought the course by # engagement types
sales_type['% Sales per Participants'] = round(100*(sales_type['Sales'] / sales_type['Had an Engagement']), 2)
#Calculating the # of people who didn't have any engagements
sales_type.set_value(index=0, col='Had an Engagement', value=sales[sales['Had an Engagement']==0].count()['Sales'])
#Calculating the % of sales for those who didn't have any engagements
sales_type.set_value(index=0, col='% Sales per Participants',
value=round(100 * (sales_type.ix[0, 'Sales'] /
sales[sales['Had an Engagement']==0].count()['Sales']),2))
#Setting the graph image
fig, (ax1) = plt.subplots(nrows=1, ncols=1, figsize=(12,4))
sns.set_style("whitegrid")
# Ploting the histagram for the % of total prospects
ax1 = sns.barplot(x=sales_type.index,y='% Sales per Participants', data=sales_type ,ax=ax1)
ax1.set(ylabel = '%')
ax1.set_title('% Sales per Participants By # of Engagement Types')
#present the table
sales_type.xs(['Had an Engagement', 'Sales','% Sales per Participants'],axis=1).transpose()
#sales_type
我对其他参数使用相同的代码概念，没有问题.但是，对于一个参数，我得到一个错误:行代码为"ValueError:不是"一维的"Grouper":
I'm using the same code concept for other parameters I have with no issue. However, for one parameter I get an error: "ValueError: Grouper for '' not 1-dimensional" for the line code:
ax1 = sns.barplot(x=sales_type.index,y='% Sales per Participants', data=sales_type ,ax=ax1)
尽管数据框的维数不止一个，但仍会发生此错误.
This error occurs although the dataframe doesn't have more than one dimension.
这是表格的标题:
Sales Pre-Ordered / Ordered Book \
# of Engagement Types
0 1.0 0.0
1 20.0 496.0
2 51.0 434.0
3 82.0 248.0
4 71.0 153.0
5 49.0 97.0
6 5.0 24.0
Opted In For / Clicked to Kindle Viewed PLC \
# of Engagement Types
0 0.0 0
1 27034.0 5920
2 6953.0 6022
3 1990.0 1958
4 714.0 746
5 196.0 204
6 24.0 24
# of PLC Engagement Viewed Webinar \
# of Engagement Types
0 0.0 0
1 6434.0 1484
2 7469.0 1521
3 2940.0 1450
4 1381.0 724
5 463.0 198
6 54.0 24
# of Webinars (Live/Replay) \
# of Engagement Types
0 0.0
1 1613.0
2 1730.0
3 1768.0
4 1018.0
5 355.0
6 45.0
OCCC Facebook Group Member Engaged in Cart-Open \
# of Engagement Types
0 0.0 0
1 148.0 160
2 498.0 1206
3 443.0 967
4 356.0 511
5 168.0 177
6 24.0 24
# of Engagement at Cart Open Had an Engagement \
# of Engagement Types
0 0.0 3387
1 189.0 35242
2 1398.0 8317
3 1192.0 2352
4 735.0 801
5 269.0 208
6 40.0 24
Total # of Engagements % Sales per Participants
# of Engagement Types
0 0.0 0.03
1 35914.0 0.06
2 18482.0 0.61
3 8581.0 3.49
4 4357.0 8.86
5 1548.0 23.56
6 211.0 20.83
这是完整的错误:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-211-f0185fe64c1a> in <module>()
12 sns.set_style("whitegrid")
13 # Ploting the histagram for the % of total prospects
---> 14 ax1 = sns.barplot(x=sales_type.index,y='% Sales per Participants', data=sales_type ,ax=ax1)
15 ax1.set(ylabel = '%')
16 ax1.set_title('% Sales per Participants By # of Engagement Types')
ValueError: Grouper for '<class 'pandas.core.frame.DataFrame'>' not 1-dimensional
我试图在Internet和Stack Overflow上搜索此错误，但是没有结果.有谁知道发生了什么事?
I've tried to search the internet and Stack Overflow for this error, but got no results. Does anyone has an idea what's going on?
推荐答案
简化的问题
我也遇到了这个问题，找到了问题的原因和明显的解决方法
Simplified problem
I also ran into this problem, and found the cause of it and the obvious solution
要重新创建它:
df = pd.DataFrame({"foo": [1,2,3], "bar": [1,2,3]})
df.rename(columns={'foo': 'bar'}, inplace=True)
bar bar
0 1 1
1 2 2
2 3 3
df.groupby('bar')
ValueError: Grouper for 'bar' not 1-dimensional
就像许多神秘的熊猫错误一样，这也是源于具有相同名称的两列.
Just like a lot of cryptic pandas errors, this one too stems from having two columns with the same name.
找出要使用的哪一个，重命名或删除另一列，然后重做该操作.
Figure out which one you want to use, rename or drop the other column and redo the operation.
重命名这样的列
df.columns = ['foo', 'bar']
foo bar
0 1 1
1 2 2
2 3 3
df.groupby('bar')
<pandas.core.groupby.DataFrameGroupBy object at 0x1066dd950>
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