On 4/6/2020 11:05 PM, Luca wrote:
On 4/6/2020 8:51 PM, Reto wrote:
out = df.to_csv(None)
new = pd.read_csv(io.StringIO(out), index_col=0)
Thank you, brother. It works
BTW, a little gotcha (I write this in case someone gets here in the
future through Google or something)
"""
import pandas
On 4/6/2020 8:51 PM, Reto wrote:
out = df.to_csv(None)
new = pd.read_csv(io.StringIO(out), index_col=0)
Thank you, brother. It works
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On Mon, Apr 06, 2020 at 06:29:01PM -0400, Luca wrote:
> so, given a dataframe, how do I make it print itself out as CSV?
read the docs of to_csv...
> And given CSV data in my clipboard, how do I paste it into a Jupiter cell
> (possibly along with a line or two of code) that will create a datafram
On 4/6/2020 3:03 PM, Christian Gollwitzer wrote:
CSV is the most sensible option here. It is widely supported by
spreadsheets etc. and easily copy/pasteable.
Thank you Christian.
so, given a dataframe, how do I make it print itself out as CSV?
And given CSV data in my clipboard, how do I
Am 06.04.20 um 17:17 schrieb Luca:
On 4/6/2020 4:08 AM, Reto wrote:
Does this help?
Thank you, but not really. What I am trying to achieve is to have a way
to copy and paste small yet complete dataframes (which may be the result
of previous calculations) between a document (TXT, Word, Google
On 4/6/2020 4:08 AM, Reto wrote:
Does this help?
Thank you, but not really. What I am trying to achieve is to have a way
to copy and paste small yet complete dataframes (which may be the result
of previous calculations) between a document (TXT, Word, GoogleDoc) and
Jupiter/IPython.
Did I m
On Sat, Apr 04, 2020 at 07:00:23PM -0400, Luca wrote:
> dframe.to_string
>
> gives:
>
> 0 a0 b0 c0 d0
> 1 a1 b1 c1 d1
> 2 a2 b2 c2 d2
> 3 a3 b3 c3 d3>
That's not the output of to_string.
to_string is a method, not an attribute which is apparent by the
>
comment in your output
possibly a stupid question. Let's say I have a (small) dataframe:
import pandas as pd
dframe = pd.DataFrame({'A': ['a0','a1','a2','a3'],
'B': ['b0','b1','b2','b3'],
'C': ['c0','c1','c2','c3'],
'D': ['d0','d1','d2','d3']}, i
