Change pandas 0.13.0 "print dataframe" to print data, as in previous versions

Question

In the new version 0.13.0 of pandas, the dataframe df is printed in one long list of numbers using

df 

or

 print df 

instead of the review, as before, which is now possible only with

 df.info() 

Is it possible to change the default command 'df' or 'print df' to display:

 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) 

again instead:

 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] 

Answer 1

Set

 pd.options.display.large_repr = 'info' 

The default default v.0.13 is "truncate".

 In [93]: df = pd.DataFrame(np.arange(4319*2).reshape(4319,2)) In [94]: pd.options.display.large_repr = 'info' In [95]: df Out[95]: <class 'pandas.core.frame.DataFrame'> Int64Index: 4319 entries, 0 to 4318 Data columns (total 2 columns): 0 4319 non-null int32 1 4319 non-null int32 dtypes: int32(2) 

---

I found this by searching for the string 'info()' in the output:

 In [65]: pd.set_option? 

---

To make this default behavior for interactive sessions:

If you have not set it yet, define the PYTHONSTARTUP environment variable for something like /home/user/bin/startup.py

Then edit / create /home/user/bin/startup.py to contain something like

 import pandas as pd pd.options.display.large_repr = 'info' 

Now, when you start an interactive Python session, the startup.py file will be executed, you will have access to pandas via the pd variable, and large_repr will default to 'info' .