我有以下输入文件:
"Name",97.7,0A,0A,65M,0A,100M,5M,75M,100M,90M,90M,99M,90M,0#,0N#,
我正在阅读:
#!/usr/bin/env python
import pandas as pd
import sys
import numpy as np
filename = sys.argv[1]
df = pd.read_csv(filename,header=None)
for col in df.columns[2:]:
df[col] = df[col].str.extract(r'(\d+\.*\d*)').astype(np.float)
print df
然而,我收到错误
df[col] = df[col].str.extract(r'(\d+\.*\d*)').astype(np.float)
File "/usr/local/lib/python2.7/dist-packages/pandas/core/generic.py", line 2241, in __getattr__
return object.__getattribute__(self, name)
File "/usr/local/lib/python2.7/dist-packages/pandas/core/base.py", line 188, in __get__
return self.construct_accessor(instance)
File "/usr/local/lib/python2.7/dist-packages/pandas/core/base.py", line 528, in _make_str_accessor
raise AttributeError("Can only use .str accessor with string "
AttributeError: Can only use .str accessor with string values, which use np.object_ dtype in pandas
这在pandas 0.14中运行正常但在pandas 0.17.0中不起作用。
答案 0 :(得分:13)
这种情况正在发生,因为您的上一列是空的,因此转换为NaN
:
In [417]:
t="""'Name',97.7,0A,0A,65M,0A,100M,5M,75M,100M,90M,90M,99M,90M,0#,0N#,"""
df = pd.read_csv(io.StringIO(t), header=None)
df
Out[417]:
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 \
0 'Name' 97.7 0A 0A 65M 0A 100M 5M 75M 100M 90M 90M 99M 90M 0#
15 16
0 0N# NaN
如果您将范围切割到最后一行,那么它可以正常工作:
In [421]:
for col in df.columns[2:-1]:
df[col] = df[col].str.extract(r'(\d+\.*\d*)').astype(np.float)
df
Out[421]:
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
0 'Name' 97.7 0 0 65 0 100 5 75 100 90 90 99 90 0 0 NaN
或者你可以选择object
dtype的cols并运行代码(跳过第一个col,因为这是'Name'条目):
In [428]:
for col in df.select_dtypes([np.object]).columns[1:]:
df[col] = df[col].str.extract(r'(\d+\.*\d*)').astype(np.float)
df
Out[428]:
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
0 'Name' 97.7 0 0 65 0 100 5 75 100 90 90 99 90 0 0 NaN
答案 1 :(得分:0)
在Eclipse中工作时出现此错误。事实证明,项目解释器以某种方式(我相信是在更新之后)重置为Python 2.7。将其重新设置为Python 3.6可解决此问题。所有这些都导致了几次崩溃,重新启动和警告。经过几分钟的麻烦,现在看来已经解决了。
虽然我知道这不能解决这里提出的问题,但我认为它可能对其他人有用,因为我在搜索此错误后来到了此页面。
答案 2 :(得分:0)
在这种情况下,我们必须在该系列上使用str.replace()
方法,但是首先我们必须将其转换为str
类型:
df1.Patient = 's125','s45',s588','s244','s125','s123'
df1 = pd.read_csv("C:\\Users\\Gangwar\\Desktop\\competitions\\cancer prediction\\kaggle_to_students.csv")
df1.Patient = df1.Patient.astype(str)
df1['Patient'] = df1['Patient'].str.replace('s','').astype(int)