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蟒蛇3:如何打印groupby.last()?

python-3.7 group-by dataframe pandas python

0

AG1 · 技术社区 · 6 年前

$ cat n2.txt
apn,date
3704-156,11/04/2019
3704-156,11/22/2019
5515-004,10/23/2019
3732-231,10/07/2019
3732-231,11/15/2019

$ python3
Python 3.7.5 (default, Oct 25 2019, 10:52:18) 
[Clang 4.0.1 (tags/RELEASE_401/final)] :: Anaconda, Inc. on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import pandas as pd 
>>> df = pd.read_csv("n2.txt")
>>> df
        apn        date
0  3704-156  11/04/2019
1  3704-156  11/22/2019
2  5515-004  10/23/2019
3  3732-231  10/07/2019
4  3732-231  11/15/2019
>>> g = df.groupby('apn')
>>> g.last()
                date
apn                 
3704-156  11/22/2019
3732-231  11/15/2019
5515-004  10/23/2019
>>> f = g.last()

>>> for r in f.itertuples(index=True, name='Pandas'):
...     print(getattr(r,'apn'), getattr(r,'date'))
... 
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
AttributeError: 'Pandas' object has no attribute 'apn'

>>> for r in f.itertuples(index=True, name='Pandas'):
...     print(getattr(r,"apn"), getattr(r,"date"))
... 
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
AttributeError: 'Pandas' object has no attribute 'apn'

如何正确地将此打印到文件中?

apn, date
3704-156,11/22/2019
3732-231,11/15/2019
5515-004,10/23/2019

1 回复 | 直到 6 年前

1

Travis 6 年前

df = pd.read_csv("n2.txt")
g = df.groupby('apn').last()
print(g.to_csv())

如果你打字 g.to_csv() 'apn,data,\r\n...' . 以及 print 函数在遇到时将开始一个新行 '\r\n' ,最终输出如您所愿。

2

0

jezrael 6 年前

您的代码应该更改:

df = pd.read_csv("n2.txt")
g = df.groupby('apn')
f = g.last()

使用 Series.to_csv 因为 f 是熊猫吗 Series :

f.to_csv(file)

或使用 DataFrame.to_csv 带转换 index DataFrame :

f.reset_index().to_csv(file, index=False)

或使用溶液 DataFrame.drop_duplicates

df = pd.read_csv("n2.txt")
df = df.drop_duplicates('apn', keep='last')
df.to_csv(file, index=False)

在您的解决方案中使用 Index 选择属于 :

for r in f.itertuples(index=True, name='Pandas'):
    print(getattr(r,'Index'), getattr(r,'date'))
3704-156 11/22/2019
3732-231 11/15/2019
5515-004 10/23/2019