pydata/pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

Joris Van den Bossche

@jorisvandenbossche

The failing build has

openssl 1.1.1d h7b6447c_0

while the non-failing build from defaults has

openssl 1.0.2s h7b6447c_0

so that seems to confirm what you posted in the issue

Loïc Estève

@lesteve

scikit-learn approach is pinning openssl=1.1.1c which seems reasonable

as a temporary work-around

Joris Van den Bossche

@jorisvandenbossche

Trying that for pandas as well, thanks

Kolmar Kafran

@kafran

Whats that site its a big white area where people copy and paste code live in the meetings?

PatrykJacak

@PatrykJacak

Hello

Someone is here? :)

I have a latest version Pandas: 0.25.0 and I have a problem with pandas.DataFrame.loc - I don't know why however i don't have that

Gabriel Corona

@randomstuff

What's your problem ?

londheshubham

@londheshubham

Whats the problem?

PatrykJacak

@PatrykJacak

I don't now why however my installation of Pandas have missing this function

For example :)

PatrykJacak

@PatrykJacak

Okay, however how I can use this?

Gabriel Corona

@randomstuff

Just try using it anyway

PatrykJacak

@PatrykJacak

Okay

I will try

PatrykJacak

@PatrykJacak

It works :) thank you

matrixbot

@matrixbot

Florian Hi there, can anyone help me with a seamingly simple task?

I have the following DataFrame:

   Participant  Time  Value
0            1     1      1
1            1     2      2
2            1     3      3
3            2     1      2
4            2     2      5
5            2     3      7

And now I want to subtract the Value at Time==1 from the Value at Time==2 and Time==3, such that the DataFrame becomes:

   Participant  Time  Value
0            1     1      0
1            1     2      1
2            1     3      2
3            2     1      0
4            2     2      3
5            2     3      5

I just cannot figure out how to do this :-)

matrixbot

@matrixbot

kir0ul > <@fladd:matrix.org> Hi there, can anyone help me with a seamingly simple task?

I have the following DataFrame:

   Participant  Time  Value
0            1     1      1
1            1     2      2
2            1     3      3
3            2     1      2
4            2     2      5
5            2     3      7

And now I want to subtract the Value at Time==1 from the Value at Time==2 and Time==3, such that the DataFrame becomes:

   Participant  Time  Value
0            1     1      0
1            1     2      1
2            1     3      2
3            2     1      0
4            2     2      3
5            2     3      5

I just cannot figure out how to do this :-)

Maybe this can help?
https://stackoverflow.com/questions/34855859/is-there-a-way-in-pandas-to-use-previous-row-value-in-dataframe-apply-when-previ

matrixbot

@matrixbot

Florian kir0ul: Thanks for the pointer. However, this does not seem to work. I do:

for i in range(1, len(data)):
    time = data.loc[i, "Time"]
    if time != 1:
        data.loc[i, "Time"] = data.loc[i, "Time"] - data.loc[i-time-1, "Time"]

But I get the error:

KeyError: 'the label [-2] is not in the [index]'

Florian ha, paranthesis error :-)

Florian but it still does not work. I creates the original data frame, instead of the subtracted one

matrixbot

@matrixbot

Florian got it to work now. Thanks!

Marc Garcia

@datapythonista

@WillAyd regarding the stale bot, this should be quite simple to implement with GitHub actions directly in the CI (see https://github.com/actions/stale). This is still beta, but when it's released, I see an advantage having it set up in a yaml in the repository, compared to having to integrate another third-party service.

I'm neutral on whether this is a good idea or not, I'd say that if there is interest, we can give it a try, and if it becomes annoying we remove it

Joris Van den Bossche

@jorisvandenbossche

@jreback @TomAugspurger @jbrockmendel now or in 2.5 hours?

Tom Augspurger

@TomAugspurger

I think now

Joris Van den Bossche

@jorisvandenbossche

Jeff just sent a mail to ask in two hours

Tom Augspurger

@TomAugspurger

https://meet.google.com/gvh-okpg-qux

Joris Van den Bossche

@jorisvandenbossche

as I said originally, for me either now or in 2.5 hours, but both are fine

Jeff Reback

@jreback

if u don’t mind can we reschedule for 2 (or 2.5) hours

or go ahead if i guys are already on the call

Tom Augspurger

@TomAugspurger

@jreback we had the call. Notes at https://docs.google.com/document/d/1k_E_1oSV9VNHgGzepdeCyFdju8ZaXDwI3CvDYkhOtQ8/edit?usp=sharing. Summary at the bottom is where I’d recommend focusing.

Jeff Reback

@jreback

onboard with the summary - i’d say go ahead with a PR

William Ayd

@WillAyd

@datapythonista cool thanks for the info. I am also on board with maybe try and if we don’t like can always revert

Where in what you showed me did you see the info around a stable release?

Marc Garcia

@datapythonista

GitHub actions itself is in beta, not sure when it'll be stable: https://github.com/features/actions

sabquat

@sabquat

I am having trouble with scatter plot. I have posted my problem in Stack Overflow-
https://stackoverflow.com/q/57988832/3862410
I need some hints on my mistake

I am not sure, if this is my mistake or some kind of bug

Chris

@0x5f3759df_gitlab

hi there.

i want to store a class or @dataclass as the values for one of my dataframe columns

i was just wondering if you can access member functions or attributes particularly like when you do the df filtering

like df[df['MYCLASSCOL'].attribute == 'helloworld']]

or df[df['MYCLASSCOL'].someBoolMethod(1,2,3)]

killerontherun1

@killerontherun1

When parsing a dictionary containing a list of datetime objects, pandas converts it to numpy.datetime64. Is this normal? Reproducable example:

>>>  from pandas import DataFrame as df
>>>  import datetime
>>>  inp = {'date':[datetime.datetime.now() for val in range(3)]}
>>>  inp_tbl = df(inp)
>>>  inp_tbl
                        date
0  2019-09-20 15:00:35.080488
1  2019-09-20 15:00:35.080525
2  2019-09-20 15:00:35.080527
>>>  inp_tbl.dtypes
date    datetime64[ns]
dtype: object
>>>  inp_tbl['date'].values[0]
numpy.datetime64('2019-09-20T15:00:35.080488000')

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