Question

我正在为doc字符串中概述的编码类解决此问题。我将不胜感激任何有关优化我的代码的帮助，以及关于为什么我收到以下错误尽管重置索引的任何解释。

import pandas as pd
def beds_top_ten(df, facility_id):
    '''
    INPUT: DataFrame, int
    OUTPUT: date
    Write a pandas query that returns the ten census dates with the highest 
    number of available beds for the nursing home with the specified facility id
    REQUIREMENTS:
    Do a filter followed by a sort rather than a sort followed by a merge.
    '''
    df = pd.read_csv('beds.csv', low_memory= False)
    df['Bed Census Date'] = pd.to_datetime(df['Bed Census Date'])
    df = df.filter(items =['Facility ID', 'Bed Census Date','Available Residential Beds'])
    df = df.sort_values(by =[ 'Facility ID', 'Available Residential Beds'], ascending= False)
    df_group_by_ten = df.groupby('Facility ID').head(10).reset_index(drop=True)
    dates = df_group_by_ten.loc[df_group_by_ten['Facility ID']==facility_id, 'Bed Census Date']
    return dates

这是第一个groupby之后表格的样子：

Facility ID Bed Census Date Available Residential Beds
336 19  2011-01-05  29
339 19  2010-12-15  28
330 19  2011-02-23  27
332 19  2011-02-02  27
333 19  2011-01-26  27
334 19  2011-01-19  27
335 19  2011-01-12  27
338 19  2010-12-22  27
341 19  2010-12-01  27
331 19  2011-02-09  26
16  17  2013-04-10  22
87  17  2011-11-09  19
30  17  2013-01-02  17
37  17  2012-11-07  17
47  17  2012-08-29  17
31  17  2012-12-26  16
56  17  2012-06-20  16
10  17  2013-05-22  15
27  17  2013-01-23  15
61  17  2012-05-16  15

当我从command_line运行时：

In [15]: beds_top_ten('beds.csv',17)
Out[15]:
16   2013-04-10
87   2011-11-09
30   2013-01-02
37   2012-11-07
47   2012-08-29
31   2012-12-26
56   2012-06-20
10   2013-05-22
27   2013-01-23
61   2012-05-16
Name: Bed Census Date, dtype: datetime64[ns]

然而，当我在在线环境中运行相同的代码时，我收到以下错误：

/usr/local/lib/python2.7/unittest/suite.py:108: DtypeWarning: Columns (10,45) have mixed types. Specify dtype option on import or set low_memory=False.
  test(result)
E
======================================================================
ERROR: test_fourth_pandas (test_methods.Test)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/src/app/test_methods.py", line 25, in test_fourth_pandas
    all_equal = np.all(result == answer)
  File "/usr/local/lib/python2.7/site-packages/pandas/core/ops.py", line 812, in wrapper
    raise ValueError(msg)
ValueError: Can only compare identically-labeled Series objects

----------------------------------------------------------------------
Ran 1 test in 19.743s

FAILED (errors=1)

Answer 1

pd.to_datetime没有错。你可能错误的约会。请尝试指定格式，errors='coerce以便将无效格式转换为NaT。

df['Bed Census Date'] = pd.to_datetime(df['Bed Census Date'].str.strip(), 
                            format='%Y-%m-%d', errors='coerce')

现在，扩展我的comment，过滤，排序，并使用head获取前10个项目：

x = df[df['Facility ID'] == facility_id]\
      .sort_values('Available Residential Beds', ascending=False).head(10)
return x['Bed Census Date']

Answer 2

删除日期格式化行解决了上述错误。

 df = pd.read_csv('beds.csv', low_memory= False)
    #df['Bed Census Date'] = pd.to_datetime(df['Bed Census Date'])
    df = df.filter(items=['Facility ID', 'Bed Census Date','Available Residential Beds'])
    x = df[df['Facility ID'] == facility_id].sort_values('Available Residential Beds', ascending=False).head(10)
    return x['Bed Census Date']

Pandas查询使用过滤器和排序，导致无法解决的错误

2 个答案: