pandas python if语句字典与系列不兼容的索引器
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python if statement dictionary incompatible indexer with Series
提问by salim
This script :
这个脚本：
for x in df.index:
if df.loc[x,'medicament1'] in dicoprix:
df.loc[x,'coutmed1'] = dicoprix[df.loc[x,'medicament1']]
gives this error :
给出这个错误：
File "<ipython-input-35-097fdb2220b8>", line 3, in <module>
df.loc[x,'coutmed1'] = dicoprix[df.loc[x,'medicament1']]
File "//anaconda/lib/python2.7/site-packages/pandas/core/indexing.py", line 115, in __setitem__
self._setitem_with_indexer(indexer, value)
File "//anaconda/lib/python2.7/site-packages/pandas/core/indexing.py", line 346, in _setitem_with_indexer
value = self._align_series(indexer, value)
File "//anaconda/lib/python2.7/site-packages/pandas/core/indexing.py", line 613, in _align_series
raise ValueError('Incompatible indexer with Series')
ValueError: Incompatible indexer with Series
But the script is working, meaning df.loc[x,'coutmed1']takes the value that I want.
但是脚本正在运行，意思df.loc[x,'coutmed1']是我想要的值。
I don't understand what am I doing wrong ?
我不明白我做错了什么？
I think that the problem comes from this
我认为问题来自于此
dicoprix[df.loc[x,'medicament1']]
回答by salim
This problem occurs when a key in the dict refers to more than one value !
当字典中的一个键引用多个值时会出现此问题！
回答by ANKIT MORAL
Solution: Remove the duplicate indexes from the series (i.e. dicoprix) and keep them unique
解决方案：从系列中删除重复的索引（即dicoprix）并保持它们的唯一性
You got it, the problem is in dicoprix[df.loc[x,'medicament1']]
你明白了，问题出在 dicoprix[df.loc[x,'medicament1']]
There are duplicates in the indexes of the series dicoprix, which cannot be put as one value in the dataframe.
series 的索引中有重复项，dicoprix不能将其作为一个值放入数据框中。
Below is the demonstration:
下面是演示：
In [1]:
import pandas as pd
dum_ser = pd.Series(index=['a','b','b','c'], data=['apple', 'balloon', 'ball', 'cat' ])
[Out 1]
a apple
b balloon
b ball
c cat
dtype: object
In [2]:
df = pd.DataFrame({'letter':['a','b','c','d'], 'full_form':['aley', 'byue', 'case', 'cible']}, index=[0,1,2,3])
df
Out [2]:
letter full_form
0 a aley
1 b byue
2 c case
3 d cible
Following command will run fine as 'a' is not the duplicate index in
dum_serseries
以下命令将正常运行，因为“a”不是
dum_ser系列中的重复索引
In [3]:
df.loc[0,'full_form'] = dum_ser['a']
df
Out [3]:
letter full_form
0 a apple
1 b byue
2 c case
3 d apple
Error will occur when the command tries to insert two records from the series(as there are two records for the index
bindum_ser, to check run the commanddum_ser['b']) into one value-space of the DataFrame. Refer below
当命令中尝试从系列中插入两个记录将出现错误（因为有两个记录为索引
b中dum_ser，以检查运行命令dum_ser['b']）转换成数据帧的一个值空间。参考以下
In [4]:
df.loc[1,'full_form'] = dum_ser['b']
Out [4]:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-4-af11b9b3a776> in <module>()
----> 1 df.loc['b','full_form'] = dum_ser['b']
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in __setitem__(self, key, value)
187 key = com._apply_if_callable(key, self.obj)
188 indexer = self._get_setitem_indexer(key)
--> 189 self._setitem_with_indexer(indexer, value)
190
191 def _validate_key(self, key, axis):
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _setitem_with_indexer(self, indexer, value)
635 # setting for extensionarrays that store dicts. Need to decide
636 # if it's worth supporting that.
--> 637 value = self._align_series(indexer, Series(value))
638
639 elif isinstance(value, ABCDataFrame):
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _align_series(self, indexer, ser, multiindex_indexer)
775 return ser.reindex(ax)._values
776
--> 777 raise ValueError('Incompatible indexer with Series')
778
779 def _align_frame(self, indexer, df):
ValueError: Incompatible indexer with Series
The above-written line of the code is the one of the iteration from the
forloop i.e. for x=1
上面写的代码行是
for循环中的迭代之一，即 for x=1
Solution: Remove the duplicate indexes from the series (i.e. dum_serhere) and keep them unique
解决方案：从系列中删除重复的索引（即dum_ser这里）并保持它们的唯一性
回答by krish___na
Use indexing like this:
像这样使用索引：
dicoprix[df.loc[x,'medicament1']][0]
dicoprix[df.loc[x,'medicament1']] [0]
It did work for me.
它确实对我有用。
