Pandas 过滤特定年份的数据框行
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/46878156/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Pandas filter dataframe rows with a specific year
提问by user3494047
I have a dataframe dfand it has a Datecolumn. I want to create two new data frames. One which contains all of the rows from dfwhere the year equals some_yearand another data frame which contains all of the rows of dfwhere the year does not equal some_year. I know you can do df.ix['2000-1-1' : '2001-1-1']but in order to get all of the rows which are not in 2000 requires creating 2 extra data frames and then concatenating/joining them.
我有一个数据框df，它有一Date列。我想创建两个新的数据框。一个包含df年份等于的所有行some_year，另一个数据框包含df年份不等于的所有行some_year。我知道你可以这样做，df.ix['2000-1-1' : '2001-1-1']但为了获得所有不在 2000 年的行，需要创建 2 个额外的数据帧，然后连接/加入它们。
Is there some way like this?
有这样的方法吗？
include = df[df.Date.year == year]
exclude = df[df['Date'].year != year]
This code doesn't work, but is there any similar sort of way?
这段代码不起作用，但有没有类似的方法？
回答by Vaishali
You can use datetime accesor.
您可以使用日期时间访问器。
import datetime as dt
df['Date'] = pd.to_datetime(df['Date'])
include = df[df['Date'].dt.year == year]
exclude = df[df['Date'].dt.year != year]
回答by jezrael
You can simplify it by inverting mask by ~and for condition use Series.dt.yearwith intfor cast string year:
您可以通过反向掩码简化它~和条件使用Series.dt.year与int流延字符串year：
mask = df['Date'].dt.year == int(year)
include = df[mask]
exclude = df[~mask]
