【发布时间】:2014-01-31 14:33:37
【问题描述】:
在新版本 0.13.0 的 pandas 中,数据帧 df 打印在一长串数字中,使用
df
或
print df
而不是像以前那样的概述,现在只能使用
df.info()
是否可以将默认的“df”或“print df”命令更改为显示:
In [12]: df.info()
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 4319 entries, 2010-02-18 00:00:00 to 2010-03-13 23:15:00
Data columns (total 2 columns):
QInt 4319 non-null values
QHea 4319 non-null values
dtypes: float32(2)
再次代替:
In [11]: df
Out[11]:
QInt QHea
2010-02-18 00:00:00 169.666672 0.000000
2010-02-18 00:15:00 152.000000 -0.000000
2010-02-18 00:15:00 152.000000 -0.000000
2010-02-18 00:30:00 155.000000 -0.000000
2010-02-18 00:30:04 155.063950 -0.000000
2010-02-18 00:30:04 155.063950 -1136.823364
2010-02-18 00:45:00 169.666672 4587.430176
2010-02-18 01:00:00 137.333328 4532.890137
2010-02-18 01:00:00 137.333328 4532.890137
2010-02-18 01:15:00 177.000000 4464.479980
2010-02-18 01:15:00 177.000000 4464.479980
2010-02-18 01:30:00 169.666672 4391.839844
2010-02-18 01:30:00 169.666672 4391.839844
2010-02-18 01:45:00 155.000000 4313.049805
2010-02-18 01:45:00 155.000000 4313.049805
2010-02-18 02:00:00 144.666672 4230.100098
2010-02-18 02:15:00 162.333328 4144.819824
2010-02-18 02:15:00 162.333328 4144.819824
2010-02-18 02:30:00 177.000000 4059.689941
2010-02-18 02:45:00 144.666672 3987.149902
2010-02-18 02:45:00 144.666672 3987.149902
2010-02-18 03:00:00 155.000000 3924.629883
2010-02-18 03:00:00 155.000000 3924.629883
2010-02-18 03:15:00 162.333328 3865.129883
2010-02-18 03:15:00 162.333328 3865.129883
2010-02-18 03:30:00 162.333328 3811.050049
2010-02-18 03:30:00 162.333328 3811.050049
2010-02-18 03:45:00 152.000000 3765.590088
2010-02-18 03:45:00 152.000000 3765.590088
2010-02-18 04:00:00 162.333328 3735.080078
2010-02-18 04:15:00 162.333328 3703.169922
2010-02-18 04:15:00 162.333328 3703.169922
2010-02-18 04:30:00 144.666672 3673.139893
2010-02-18 04:45:00 169.666672 3647.100098
2010-02-18 04:45:00 169.666672 3647.100098
2010-02-18 05:00:00 162.333328 3622.129883
2010-02-18 05:15:00 155.000000 3594.159912
2010-02-18 05:15:00 155.000000 3594.159912
2010-02-18 05:30:00 159.333328 3569.699951
2010-02-18 05:30:00 159.333328 3569.699951
2010-02-18 05:45:00 147.666672 3551.179932
2010-02-18 05:45:00 147.666672 3551.179932
2010-02-18 06:00:00 177.000000 3531.669922
2010-02-18 06:00:00 177.000000 3531.669922
2010-02-18 06:15:00 159.333328 3514.679932
2010-02-18 06:15:00 159.333328 3514.679932
2010-02-18 06:30:00 155.000000 3499.669922
2010-02-18 06:30:00 155.000000 3499.669922
2010-02-18 06:45:00 155.000000 3485.320068
2010-02-18 06:45:00 155.000000 3485.320068
2010-02-18 06:59:54.750000 162.291245 19.999992
2010-02-18 06:59:54.750000 162.291245 0.000000
2010-02-18 07:00:00 162.333328 0.000000
2010-02-18 07:00:00 162.333328 0.000000
2010-02-18 07:15:00 166.666672 0.000000
2010-02-18 07:15:00 166.666672 0.000000
2010-02-18 07:30:00 155.000000 0.000000
2010-02-18 07:30:00 155.000000 0.000000
2010-02-18 07:45:00 155.000000 0.000000
2010-02-18 07:45:00 155.000000 0.000000
... ...
[4319 rows x 2 columns]
【问题讨论】:
-
你可以编写一个自定义的
__str__方法。或者从原始类派生一个类,并覆盖__str__方法。