Python 筛选数据帧或序列中的值

我试图从pandas数据帧中的列中筛选值，但我似乎接收的是布尔值，而不是实际值。 我正在尝试按月份和年份筛选我们的数据。 在下面的代码中，您将看到我仅按年份过滤，但我已以不同的方式尝试了月份和年份多次：

    In [1]: import requests

    In [2]: import pandas as pd # pandas

    In [3]: import datetime as dt # module for manipulating dates and times

    In [4]: url = "http://elections.huffingtonpost.com/pollster/2012-general-election-romney-vs-obama.csv"

    In [5]: source = requests.get(url).text

    In [6]: from io import StringIO, BytesIO

    In [7]: s = StringIO(source)

    In [8]: election_data = pd.DataFrame.from_csv(s, index_col=None).convert_objects(convert_dates="coerce", convert_numeric=True)


    In [9]: election_data.head(n=3)
    Out[9]:
                Pollster Start Date   End Date Entry Date/Time (ET)  \
    0  Politico/GWU/Battleground 2012-11-04 2012-11-05  2012-11-06 08:40:26
    1           YouGov/Economist 2012-11-03 2012-11-05  2012-11-26 15:31:23
    2           Gravis Marketing 2012-11-03 2012-11-05  2012-11-06 09:22:02

       Number of Observations     Population             Mode  Obama  Romney  \
    0                  1000.0  Likely Voters       Live Phone   47.0    47.0
    1                   740.0  Likely Voters         Internet   49.0    47.0
    2                   872.0  Likely Voters  Automated Phone   48.0    48.0

       Undecided  Other                                       Pollster URL  \
    0        6.0    NaN  http://elections.huffingtonpost.com/pollster/p...
    1        3.0    NaN  http://elections.huffingtonpost.com/pollster/p...
    2        4.0    NaN  http://elections.huffingtonpost.com/pollster/p...

                                              Source URL     Partisan Affiliation  \
    0  http://www.politico.com/news/stories/1112/8338...  Nonpartisan        None
    1  http://cdn.yougov.com/cumulus_uploads/document...  Nonpartisan        None
    2  http://www.gravispolls.com/2012/11/gravis-mark...  Nonpartisan        None

       Question Text  Question Iteration
    0            NaN                   1
    1            NaN                   1
    2            NaN                   1

    In [10]: start_date = pd.Series(election_data["Start Date"])
        ...: start_date.head(n=3)
        ...:
    Out[10]:
    0   2012-11-04
    1   2012-11-03
    2   2012-11-03
    Name: Start Date, dtype: datetime64[ns]

    In [11]: filtered = start_date.map(lambda x: x.year == 2012)

    In [12]: filtered
    Out[12]:
    0       True
    1       True
    2       True
    ...
    587    False
    588    False
    589    False
    Name: Start Date, dtype: bool

我认为您需要先使用

url

地址，然后使用和创建的掩码：

---

我认为您需要先使用

url

地址，然后使用和创建的掩码：

---

---

如果索引为

Start date

，则可以使用熊猫日期筛选

获取所有

2012

选举数据。设置索引（“开始日期”）['2012']

获取2012年1月的所有

选举数据。设置索引（“开始日期”）['2012-01']

在

2012年1月1日

和

2012年1月13日

选举数据。设置索引（“开始日期”）['2012-01-01'：'2012-01-13]

---

如果将

开始日期

作为索引，则可以使用熊猫日期筛选

获取所有

2012

选举数据。设置索引（“开始日期”）['2012']

获取2012年1月的所有

选举数据。设置索引（“开始日期”）['2012-01']

在

2012年1月1日

和

2012年1月13日

选举数据。设置索引（“开始日期”）['2012-01-01'：'2012-01-13]

---

谢谢！！成功了！我这个月也要试试，很高兴能帮到你！如果我的答案或其他答案有用，别忘了。谢谢，谢谢！！成功了！我这个月也要试试，很高兴能帮到你！如果我的答案或其他答案有用，别忘了。谢谢

election_data = pd.read_csv('http://elections.huffingtonpost.com/pollster/2012-general-election-romney-vs-obama.csv', parse_dates=[1,2,3])

print (election_data.head(3))
                    Pollster Start Date   End Date Entry Date/Time (ET)  \
0  Politico/GWU/Battleground 2012-11-04 2012-11-05  2012-11-06 08:40:26   
1           YouGov/Economist 2012-11-03 2012-11-05  2012-11-26 15:31:23   
2           Gravis Marketing 2012-11-03 2012-11-05  2012-11-06 09:22:02   

   Number of Observations     Population             Mode  Obama  Romney  \
0                  1000.0  Likely Voters       Live Phone   47.0    47.0   
1                   740.0  Likely Voters         Internet   49.0    47.0   
2                   872.0  Likely Voters  Automated Phone   48.0    48.0   

   Undecided  Other                                       Pollster URL  \
0        6.0    NaN  http://elections.huffingtonpost.com/pollster/p...   
1        3.0    NaN  http://elections.huffingtonpost.com/pollster/p...   
2        4.0    NaN  http://elections.huffingtonpost.com/pollster/p...   

                                          Source URL     Partisan Affiliation  \
0  http://www.politico.com/news/stories/1112/8338...  Nonpartisan        None   
1  http://cdn.yougov.com/cumulus_uploads/document...  Nonpartisan        None   
2  http://www.gravispolls.com/2012/11/gravis-mark...  Nonpartisan        None   

   Question Text  Question Iteration  
0            NaN                   1  
1            NaN                   1  
2            NaN                   1  

print (election_data.dtypes)
Pollster                          object
Start Date                datetime64[ns]
End Date                  datetime64[ns]
Entry Date/Time (ET)      datetime64[ns]
Number of Observations           float64
Population                        object
Mode                              object
Obama                            float64
Romney                           float64
Undecided                        float64
Other                            float64
Pollster URL                      object
Source URL                        object
Partisan                          object
Affiliation                       object
Question Text                    float64
Question Iteration                 int64
dtype: object


election_data[election_data["Start Date"].dt.year == 2012]

election_data[(election_data["Start Date"].dt.year == 2012) & (election_data["Start Date"].dt.month== 10)]