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https://issues.apache.org/jira/browse/ARROW-3543?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16719488#comment-16719488
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Tanya Schlusser commented on ARROW-3543:
----------------------------------------

I can confirm this bug is still present. Most recent commit in my pull is

c0ac97f126c98fb29e81d6544adfea9d4ab74aff

 

For others, the R libraries needed to re-run Olaf's code (in addition to arrow) 
are readr, dplyr, and lubridate.

I will mess around but won't be hurt if a stronger R coder takes this before I 
finish.

 

 

> [R] Time zone adjustment issue when reading Feather file written by Python
> --------------------------------------------------------------------------
>
>                 Key: ARROW-3543
>                 URL: https://issues.apache.org/jira/browse/ARROW-3543
>             Project: Apache Arrow
>          Issue Type: Bug
>            Reporter: Olaf
>            Priority: Critical
>             Fix For: 0.12.0
>
>
> Hello the dream team,
> Pasting from [https://github.com/wesm/feather/issues/351]
> Thanks for this wonderful package. I was playing with feather and some 
> timestamps and I noticed some dangerous behavior. Maybe it is a bug.
> Consider this
>  
> {code:java}
> import pandas as pd
> import feather
> import numpy as np
> df = pd.DataFrame(
> {'string_time_utc' : [pd.to_datetime('2018-02-01 14:00:00.531'), 
> pd.to_datetime('2018-02-01 14:01:00.456'), pd.to_datetime('2018-03-05 
> 14:01:02.200')]}
> )
> df['timestamp_est'] = 
> pd.to_datetime(df.string_time_utc).dt.tz_localize('UTC').dt.tz_convert('US/Eastern').dt.tz_localize(None)
> df
>  Out[17]: 
>  string_time_utc timestamp_est
>  0 2018-02-01 14:00:00.531 2018-02-01 09:00:00.531
>  1 2018-02-01 14:01:00.456 2018-02-01 09:01:00.456
>  2 2018-03-05 14:01:02.200 2018-03-05 09:01:02.200
> {code}
> Here I create the corresponding `EST` timestamp of my original timestamps (in 
> `UTC` time).
> Now saving the dataframe to `csv` or to `feather` will generate two 
> completely different results.
>  
> {code:java}
> df.to_csv('P://testing.csv')
> df.to_feather('P://testing.feather')
> {code}
> Switching to R.
> Using the good old `csv` gives me something a bit annoying, but expected. R 
> thinks my timezone is `UTC` by default, and wrongly attached this timezone to 
> `timestamp_est`. No big deal, I can always use `with_tz` or even better: 
> import as character and process as timestamp while in R.
>  
> {code:java}
> > dataframe <- read_csv('P://testing.csv')
>  Parsed with column specification:
>  cols(
>  X1 = col_integer(),
>  string_time_utc = col_datetime(format = ""),
>  timestamp_est = col_datetime(format = "")
>  )
>  Warning message:
>  Missing column names filled in: 'X1' [1] 
>  > 
>  > dataframe %>% mutate(mytimezone = tz(timestamp_est))
> A tibble: 3 x 4
>  X1 string_time_utc timestamp_est 
>  <int> <dttm> <dttm> 
>  1 0 2018-02-01 14:00:00.530 2018-02-01 09:00:00.530
>  2 1 2018-02-01 14:01:00.456 2018-02-01 09:01:00.456
>  3 2 2018-03-05 14:01:02.200 2018-03-05 09:01:02.200
>  mytimezone
>  <chr> 
>  1 UTC 
>  2 UTC 
>  3 UTC  {code}
> {code:java}
> #Now look at what happens with feather:
>  
>  > dataframe <- read_feather('P://testing.feather')
>  > 
>  > dataframe %>% mutate(mytimezone = tz(timestamp_est))
> A tibble: 3 x 3
>  string_time_utc timestamp_est mytimezone
>  <dttm> <dttm> <chr> 
>  1 2018-02-01 09:00:00.531 2018-02-01 04:00:00.531 "" 
>  2 2018-02-01 09:01:00.456 2018-02-01 04:01:00.456 "" 
>  3 2018-03-05 09:01:02.200 2018-03-05 04:01:02.200 "" {code}
> My timestamps have been converted!!! pure insanity. 
>  Am I missing something here?
> Thanks!!



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