如何修复 AttributeError: 'DataFrame' 对象没有属性 'assign' 而不更新 Pandas？
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How to fix AttributeError: 'DataFrame' object has no attribute 'assign' with out updating Pandas?
提问by user1703276
I am trying merge multiple files based on a key ('r_id') and rename the column names in the output with the name of the files. I could able to do every thing except renaming the output with the file names. I have the following error probably caused by the old version of Pandas. Does any one know how to fix this with out updating pandas to new version?
我正在尝试根据键 ('r_id') 合并多个文件，并使用文件名重命名输出中的列名。除了使用文件名重命名输出之外，我可以做所有事情。我有以下错误可能是由旧版本的 Pandas 引起的。有谁知道如何在不将Pandas更新到新版本的情况下解决这个问题？
Error
错误
Traceback (most recent call last):
File "multijoin_2.py", line 19, in <module>
result = merge_files(files).reset_index()
File "multijoin_2.py", line 11, in merge_files
pd.read_csv(f, sep='\t', usecols=['r_id', 'exp'])
File "/users/xxx/anaconda/lib/python2.7/site-packages/pandas/core/frame.py", line 2007, in __getattr__
(type(self).__name__, name))
AttributeError: 'DataFrame' object has no attribute 'assign'
Input
输入
$ cat test1
$猫测试1
r_id g_id exp
r1 g1 20
r2 g1 30
r3 g1 1
r4 g1 3
$ cat test2
$猫测试2
r_id gid exp
r1 g2 20
r2 g2 30
r3 g2 1
r4 g2 3
$ cat test3
$猫测试3
r_id g_id exp
r1 g3 30
r2 g3 40
r3 g3 11
r4 g3 32
Desired Ouput
期望输出
r_id test3 test2 test1
0 r1 30 20 20
1 r2 40 30 30
2 r3 11 1 1
3 r4 32 3 3
Working code (except column naming)
工作代码（列命名除外）
import os
import glob
import pandas as pd
files = glob.glob(r'/path/test*')
def merge_files(files, **kwargs):
dfs = []
for f in files:
dfs.append(
pd.read_csv(f, sep='\t', usecols=['r_id', 'exp'])
#.assign(col=0)
.rename(columns={'col_name':os.path.splitext(os.path.basename(f))[0]})
.set_index(['repeat_id'])
)
return pd.concat(dfs, axis=1)
result = merge_files(files).reset_index()
print(result)
采纳答案by jezrael
You need change expas column name for rename:
您需要更改exp为重命名的列名：
def merge_files(files, **kwargs):
dfs = []
for f in files:
dfs.append(
pd.read_csv(f, sep='\t', usecols=['r_id', 'exp'], index_col=['r_id'])
.rename(columns={'exp':os.path.splitext(os.path.basename(f))[0]})
)
return pd.concat(dfs, axis=1)
result = merge_files(files).reset_index()
print(result)
r_id test1 test2 test3
0 r1 20 20 30
1 r2 30 30 40
2 r3 1 1 11
3 r4 3 3 32
