workspace
stringclasses 1
value | channel
stringclasses 1
value | sentences
stringlengths 1
3.93k
| ts
stringlengths 26
26
| user
stringlengths 2
11
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stringlengths 44
53
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float64 1.5B
1.56B
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int64 0
106k
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|---|---|---|---|---|---|---|---|
pythondev
|
help
|
I have the json file c:\temp\nba\counties.json
|
2019-04-13T09:59:23.221100
|
Gia
|
pythondev_help_Gia_2019-04-13T09:59:23.221100
| 1,555,149,563.2211 | 18,521 |
pythondev
|
help
|
data=f.read()
|
2019-04-13T09:59:23.221200
|
Erika
|
pythondev_help_Erika_2019-04-13T09:59:23.221200
| 1,555,149,563.2212 | 18,522 |
pythondev
|
help
|
d=json.loads(data)
|
2019-04-13T09:59:32.221500
|
Erika
|
pythondev_help_Erika_2019-04-13T09:59:32.221500
| 1,555,149,572.2215 | 18,523 |
pythondev
|
help
|
Oh
|
2019-04-13T09:59:33.221700
|
Gia
|
pythondev_help_Gia_2019-04-13T09:59:33.221700
| 1,555,149,573.2217 | 18,524 |
pythondev
|
help
|
Let me try that
|
2019-04-13T09:59:40.222000
|
Gia
|
pythondev_help_Gia_2019-04-13T09:59:40.222000
| 1,555,149,580.222 | 18,525 |
pythondev
|
help
|
That is for Python
|
2019-04-13T09:59:46.222400
|
Gia
|
pythondev_help_Gia_2019-04-13T09:59:46.222400
| 1,555,149,586.2224 | 18,526 |
pythondev
|
help
|
df=pd.DataFrame(d)
|
2019-04-13T09:59:55.222700
|
Erika
|
pythondev_help_Erika_2019-04-13T09:59:55.222700
| 1,555,149,595.2227 | 18,527 |
pythondev
|
help
|
Or R
|
2019-04-13T09:59:55.222800
|
Gia
|
pythondev_help_Gia_2019-04-13T09:59:55.222800
| 1,555,149,595.2228 | 18,528 |
pythondev
|
help
|
that's python lol
|
2019-04-13T10:00:01.223000
|
Erika
|
pythondev_help_Erika_2019-04-13T10:00:01.223000
| 1,555,149,601.223 | 18,529 |
pythondev
|
help
|
Ok
|
2019-04-13T10:00:05.223300
|
Gia
|
pythondev_help_Gia_2019-04-13T10:00:05.223300
| 1,555,149,605.2233 | 18,530 |
pythondev
|
help
|
Did you see that counties.json file
|
2019-04-13T10:00:30.224000
|
Gia
|
pythondev_help_Gia_2019-04-13T10:00:30.224000
| 1,555,149,630.224 | 18,531 |
pythondev
|
help
|
here is the full code:
import pandas as pd
import json
with open('countries.jon,'r') as f:
data=f.read()
d=json.loads(data)
df=pd.DataFrame(d)
|
2019-04-13T10:00:52.224500
|
Erika
|
pythondev_help_Erika_2019-04-13T10:00:52.224500
| 1,555,149,652.2245 | 18,532 |
pythondev
|
help
|
depending on whether powerbi wants that in array or dataframe, jsut change the last step
|
2019-04-13T10:01:57.225000
|
Erika
|
pythondev_help_Erika_2019-04-13T10:01:57.225000
| 1,555,149,717.225 | 18,533 |
pythondev
|
help
|
It probably dataframe
|
2019-04-13T10:02:15.225600
|
Gia
|
pythondev_help_Gia_2019-04-13T10:02:15.225600
| 1,555,149,735.2256 | 18,534 |
pythondev
|
help
|
you want to paste that code in PowerQuery, just like you would paste SQL code in custom query
|
2019-04-13T10:02:23.225900
|
Erika
|
pythondev_help_Erika_2019-04-13T10:02:23.225900
| 1,555,149,743.2259 | 18,535 |
pythondev
|
help
|
is it hooked up to a SQL 2017 database? MSSQL?
|
2019-04-13T10:02:46.226500
|
Erika
|
pythondev_help_Erika_2019-04-13T10:02:46.226500
| 1,555,149,766.2265 | 18,536 |
pythondev
|
help
|
No
|
2019-04-13T10:03:50.227300
|
Gia
|
pythondev_help_Gia_2019-04-13T10:03:50.227300
| 1,555,149,830.2273 | 18,537 |
pythondev
|
help
|
anyway it would be better to rather make the ETL process run in native python, populate a table and then hidrate it
|
2019-04-13T10:03:55.227500
|
Erika
|
pythondev_help_Erika_2019-04-13T10:03:55.227500
| 1,555,149,835.2275 | 18,538 |
pythondev
|
help
|
Ahh yea
|
2019-04-13T10:04:06.227900
|
Gia
|
pythondev_help_Gia_2019-04-13T10:04:06.227900
| 1,555,149,846.2279 | 18,539 |
pythondev
|
help
|
I should create a sql table
|
2019-04-13T10:04:10.228100
|
Gia
|
pythondev_help_Gia_2019-04-13T10:04:10.228100
| 1,555,149,850.2281 | 18,540 |
pythondev
|
help
|
yeah :slightly_smiling_face:
|
2019-04-13T10:04:15.228400
|
Erika
|
pythondev_help_Erika_2019-04-13T10:04:15.228400
| 1,555,149,855.2284 | 18,541 |
pythondev
|
help
|
And use python native
|
2019-04-13T10:04:17.228600
|
Gia
|
pythondev_help_Gia_2019-04-13T10:04:17.228600
| 1,555,149,857.2286 | 18,542 |
pythondev
|
help
|
I do have psycharm on my laptop
|
2019-04-13T10:04:26.229000
|
Gia
|
pythondev_help_Gia_2019-04-13T10:04:26.229000
| 1,555,149,866.229 | 18,543 |
pythondev
|
help
|
I never done that before
|
2019-04-13T10:04:30.229300
|
Gia
|
pythondev_help_Gia_2019-04-13T10:04:30.229300
| 1,555,149,870.2293 | 18,544 |
pythondev
|
help
|
be careful of trying to hammer a nail with a saw
|
2019-04-13T10:04:33.229400
|
Erika
|
pythondev_help_Erika_2019-04-13T10:04:33.229400
| 1,555,149,873.2294 | 18,545 |
pythondev
|
help
|
Oh I see
|
2019-04-13T10:04:44.229800
|
Gia
|
pythondev_help_Gia_2019-04-13T10:04:44.229800
| 1,555,149,884.2298 | 18,546 |
pythondev
|
help
|
PowerBI is meant to be hooked up to a relational data soure
|
2019-04-13T10:05:01.230700
|
Erika
|
pythondev_help_Erika_2019-04-13T10:05:01.230700
| 1,555,149,901.2307 | 18,547 |
pythondev
|
help
|
*source
|
2019-04-13T10:05:03.230900
|
Erika
|
pythondev_help_Erika_2019-04-13T10:05:03.230900
| 1,555,149,903.2309 | 18,548 |
pythondev
|
help
|
This is only giving me counties names, can I use some fips code to match to a state
|
2019-04-13T10:05:12.231600
|
Gia
|
pythondev_help_Gia_2019-04-13T10:05:12.231600
| 1,555,149,912.2316 | 18,549 |
pythondev
|
help
|
Oh yea
|
2019-04-13T10:05:18.231900
|
Gia
|
pythondev_help_Gia_2019-04-13T10:05:18.231900
| 1,555,149,918.2319 | 18,550 |
pythondev
|
help
|
I noticed that I spent until 10 am last night
|
2019-04-13T10:05:25.232300
|
Gia
|
pythondev_help_Gia_2019-04-13T10:05:25.232300
| 1,555,149,925.2323 | 18,551 |
pythondev
|
help
|
Fighting with power bi
|
2019-04-13T10:05:30.232600
|
Gia
|
pythondev_help_Gia_2019-04-13T10:05:30.232600
| 1,555,149,930.2326 | 18,552 |
pythondev
|
help
|
trying to build a pipeline from non-relational straight to powerbi will provide too much of a technical debt
|
2019-04-13T10:05:30.232700
|
Erika
|
pythondev_help_Erika_2019-04-13T10:05:30.232700
| 1,555,149,930.2327 | 18,553 |
pythondev
|
help
|
And json
|
2019-04-13T10:05:31.232900
|
Gia
|
pythondev_help_Gia_2019-04-13T10:05:31.232900
| 1,555,149,931.2329 | 18,554 |
pythondev
|
help
|
and as soon as the json becomes nested, your pipeline fails
|
2019-04-13T10:05:49.233200
|
Erika
|
pythondev_help_Erika_2019-04-13T10:05:49.233200
| 1,555,149,949.2332 | 18,555 |
pythondev
|
help
|
Yea if you saw this file it is nested
|
2019-04-13T10:05:59.233500
|
Gia
|
pythondev_help_Gia_2019-04-13T10:05:59.233500
| 1,555,149,959.2335 | 18,556 |
pythondev
|
help
|
ah yeah then you don't want that
|
2019-04-13T10:06:12.233800
|
Erika
|
pythondev_help_Erika_2019-04-13T10:06:12.233800
| 1,555,149,972.2338 | 18,557 |
pythondev
|
help
|
you need an intermediary step to flatten
|
2019-04-13T10:06:22.234300
|
Erika
|
pythondev_help_Erika_2019-04-13T10:06:22.234300
| 1,555,149,982.2343 | 18,558 |
pythondev
|
help
|
Opening pycharm
|
2019-04-13T10:06:26.234600
|
Gia
|
pythondev_help_Gia_2019-04-13T10:06:26.234600
| 1,555,149,986.2346 | 18,559 |
pythondev
|
help
|
Can I have python create a csv file
|
2019-04-13T10:06:40.235300
|
Gia
|
pythondev_help_Gia_2019-04-13T10:06:40.235300
| 1,555,150,000.2353 | 18,560 |
pythondev
|
help
|
Oh I forgot I got sql express on this laptop
|
2019-04-13T10:06:56.235800
|
Gia
|
pythondev_help_Gia_2019-04-13T10:06:56.235800
| 1,555,150,016.2358 | 18,561 |
pythondev
|
help
|
if you don't have a db at hand, then unflatten into dataframe and save as csv's with df.to_csv('file.csv')
|
2019-04-13T10:07:02.236000
|
Erika
|
pythondev_help_Erika_2019-04-13T10:07:02.236000
| 1,555,150,022.236 | 18,562 |
pythondev
|
help
|
Cool
|
2019-04-13T10:07:22.236300
|
Gia
|
pythondev_help_Gia_2019-04-13T10:07:22.236300
| 1,555,150,042.2363 | 18,563 |
pythondev
|
help
|
but if you are planning to scale this, then you need a db
|
2019-04-13T10:07:28.236600
|
Erika
|
pythondev_help_Erika_2019-04-13T10:07:28.236600
| 1,555,150,048.2366 | 18,564 |
pythondev
|
help
|
I am opening up pycharm
|
2019-04-13T10:07:30.236900
|
Gia
|
pythondev_help_Gia_2019-04-13T10:07:30.236900
| 1,555,150,050.2369 | 18,565 |
pythondev
|
help
|
Na this is one time project
|
2019-04-13T10:07:39.237300
|
Gia
|
pythondev_help_Gia_2019-04-13T10:07:39.237300
| 1,555,150,059.2373 | 18,566 |
pythondev
|
help
|
but if i were you i would try and avoid powerbi without a db
|
2019-04-13T10:07:41.237500
|
Erika
|
pythondev_help_Erika_2019-04-13T10:07:41.237500
| 1,555,150,061.2375 | 18,567 |
pythondev
|
help
|
Okay I will use sql express
|
2019-04-13T10:07:59.237900
|
Gia
|
pythondev_help_Gia_2019-04-13T10:07:59.237900
| 1,555,150,079.2379 | 18,568 |
pythondev
|
help
|
what is your main goal?
|
2019-04-13T10:08:41.238700
|
Erika
|
pythondev_help_Erika_2019-04-13T10:08:41.238700
| 1,555,150,121.2387 | 18,569 |
pythondev
|
help
|
My main goal is this
|
2019-04-13T10:08:48.239100
|
Gia
|
pythondev_help_Gia_2019-04-13T10:08:48.239100
| 1,555,150,128.2391 | 18,570 |
pythondev
|
help
|
And also a map
|
2019-04-13T10:09:25.239600
|
Gia
|
pythondev_help_Gia_2019-04-13T10:09:25.239600
| 1,555,150,165.2396 | 18,571 |
pythondev
|
help
|
no more high level please
|
2019-04-13T10:09:39.239800
|
Erika
|
pythondev_help_Erika_2019-04-13T10:09:39.239800
| 1,555,150,179.2398 | 18,572 |
pythondev
|
help
|
like you would explain to your grandmother
|
2019-04-13T10:09:47.240200
|
Erika
|
pythondev_help_Erika_2019-04-13T10:09:47.240200
| 1,555,150,187.2402 | 18,573 |
pythondev
|
help
|
Okay
|
2019-04-13T10:09:53.240700
|
Gia
|
pythondev_help_Gia_2019-04-13T10:09:53.240700
| 1,555,150,193.2407 | 18,574 |
pythondev
|
help
|
then we can go low level from there
|
2019-04-13T10:09:54.240800
|
Erika
|
pythondev_help_Erika_2019-04-13T10:09:54.240800
| 1,555,150,194.2408 | 18,575 |
pythondev
|
help
|
My end goal is to be able to be able to tell how many knicks fans are in X county
|
2019-04-13T10:10:25.241600
|
Gia
|
pythondev_help_Gia_2019-04-13T10:10:25.241600
| 1,555,150,225.2416 | 18,576 |
pythondev
|
help
|
who is your audiance?
|
2019-04-13T10:10:50.242000
|
Erika
|
pythondev_help_Erika_2019-04-13T10:10:50.242000
| 1,555,150,250.242 | 18,577 |
pythondev
|
help
|
you or someone else?
|
2019-04-13T10:10:53.242300
|
Erika
|
pythondev_help_Erika_2019-04-13T10:10:53.242300
| 1,555,150,253.2423 | 18,578 |
pythondev
|
help
|
My manager
|
2019-04-13T10:10:59.242500
|
Gia
|
pythondev_help_Gia_2019-04-13T10:10:59.242500
| 1,555,150,259.2425 | 18,579 |
pythondev
|
help
|
It a proof of concept
|
2019-04-13T10:11:04.242800
|
Gia
|
pythondev_help_Gia_2019-04-13T10:11:04.242800
| 1,555,150,264.2428 | 18,580 |
pythondev
|
help
|
To show what powerbi can do
|
2019-04-13T10:11:10.243100
|
Gia
|
pythondev_help_Gia_2019-04-13T10:11:10.243100
| 1,555,150,270.2431 | 18,581 |
pythondev
|
help
|
While also probably solving a business thing
|
2019-04-13T10:11:25.243500
|
Gia
|
pythondev_help_Gia_2019-04-13T10:11:25.243500
| 1,555,150,285.2435 | 18,582 |
pythondev
|
help
|
apologies but I can only help if it is in a personal capacity
|
2019-04-13T10:12:16.244700
|
Erika
|
pythondev_help_Erika_2019-04-13T10:12:16.244700
| 1,555,150,336.2447 | 18,583 |
pythondev
|
help
|
Ahh yea sorry
|
2019-04-13T10:12:28.245200
|
Gia
|
pythondev_help_Gia_2019-04-13T10:12:28.245200
| 1,555,150,348.2452 | 18,584 |
pythondev
|
help
|
That fine I totally forgot the rules
|
2019-04-13T10:12:36.245700
|
Gia
|
pythondev_help_Gia_2019-04-13T10:12:36.245700
| 1,555,150,356.2457 | 18,585 |
pythondev
|
help
|
if it is for your work then we need to speak legalities
|
2019-04-13T10:12:36.245800
|
Erika
|
pythondev_help_Erika_2019-04-13T10:12:36.245800
| 1,555,150,356.2458 | 18,586 |
pythondev
|
help
|
Yea I can’t say much
|
2019-04-13T10:12:47.246100
|
Gia
|
pythondev_help_Gia_2019-04-13T10:12:47.246100
| 1,555,150,367.2461 | 18,587 |
pythondev
|
help
|
But I will use pycharm to flat it
|
2019-04-13T10:12:55.246600
|
Gia
|
pythondev_help_Gia_2019-04-13T10:12:55.246600
| 1,555,150,375.2466 | 18,588 |
pythondev
|
help
|
Thanks for the tips
|
2019-04-13T10:13:51.247200
|
Gia
|
pythondev_help_Gia_2019-04-13T10:13:51.247200
| 1,555,150,431.2472 | 18,589 |
pythondev
|
help
|
Sorry
|
2019-04-13T10:13:52.247300
|
Gia
|
pythondev_help_Gia_2019-04-13T10:13:52.247300
| 1,555,150,432.2473 | 18,590 |
pythondev
|
help
|
it's okay :slightly_smiling_face:
|
2019-04-13T10:14:01.247700
|
Erika
|
pythondev_help_Erika_2019-04-13T10:14:01.247700
| 1,555,150,441.2477 | 18,591 |
pythondev
|
help
|
and pleasure for the tips
|
2019-04-13T10:14:04.248100
|
Erika
|
pythondev_help_Erika_2019-04-13T10:14:04.248100
| 1,555,150,444.2481 | 18,592 |
pythondev
|
help
|
My Adhd Hyperactive mind forgets that I can’t mix work and personal
|
2019-04-13T10:14:17.248800
|
Gia
|
pythondev_help_Gia_2019-04-13T10:14:17.248800
| 1,555,150,457.2488 | 18,593 |
pythondev
|
help
|
Life
|
2019-04-13T10:14:18.248900
|
Gia
|
pythondev_help_Gia_2019-04-13T10:14:18.248900
| 1,555,150,458.2489 | 18,594 |
pythondev
|
help
|
Anyways I should go get my dry cleaning and breakfast and then come back home and just code
|
2019-04-13T10:15:09.249600
|
Gia
|
pythondev_help_Gia_2019-04-13T10:15:09.249600
| 1,555,150,509.2496 | 18,595 |
pythondev
|
help
|
Until I have a solution before monday
|
2019-04-13T10:15:16.249900
|
Gia
|
pythondev_help_Gia_2019-04-13T10:15:16.249900
| 1,555,150,516.2499 | 18,596 |
pythondev
|
help
|
Just one last quesiton none work realted
|
2019-04-13T10:15:39.250200
|
Gia
|
pythondev_help_Gia_2019-04-13T10:15:39.250200
| 1,555,150,539.2502 | 18,597 |
pythondev
|
help
|
Python support mssql right
|
2019-04-13T10:15:48.250600
|
Gia
|
pythondev_help_Gia_2019-04-13T10:15:48.250600
| 1,555,150,548.2506 | 18,598 |
pythondev
|
help
|
have you used sql server manager before?
|
2019-04-13T10:17:24.251200
|
Erika
|
pythondev_help_Erika_2019-04-13T10:17:24.251200
| 1,555,150,644.2512 | 18,599 |
pythondev
|
help
|
where you would say "select top 10 * from table with (nolock)" ?
|
2019-04-13T10:17:40.251800
|
Erika
|
pythondev_help_Erika_2019-04-13T10:17:40.251800
| 1,555,150,660.2518 | 18,600 |
pythondev
|
help
|
Yea I have
|
2019-04-13T10:17:50.252000
|
Gia
|
pythondev_help_Gia_2019-04-13T10:17:50.252000
| 1,555,150,670.252 | 18,601 |
pythondev
|
help
|
okay now when you execute it in sql server manager
|
2019-04-13T10:18:02.252300
|
Erika
|
pythondev_help_Erika_2019-04-13T10:18:02.252300
| 1,555,150,682.2523 | 18,602 |
pythondev
|
help
|
you automatically login to the db
|
2019-04-13T10:18:13.252700
|
Erika
|
pythondev_help_Erika_2019-04-13T10:18:13.252700
| 1,555,150,693.2527 | 18,603 |
pythondev
|
help
|
Yea
|
2019-04-13T10:18:17.253000
|
Gia
|
pythondev_help_Gia_2019-04-13T10:18:17.253000
| 1,555,150,697.253 | 18,604 |
pythondev
|
help
|
you parse a string to the server
|
2019-04-13T10:18:21.253300
|
Erika
|
pythondev_help_Erika_2019-04-13T10:18:21.253300
| 1,555,150,701.2533 | 18,605 |
pythondev
|
help
|
the server reads it and spits out the results
|
2019-04-13T10:18:29.253600
|
Erika
|
pythondev_help_Erika_2019-04-13T10:18:29.253600
| 1,555,150,709.2536 | 18,606 |
pythondev
|
help
|
Yea
|
2019-04-13T10:18:34.253900
|
Gia
|
pythondev_help_Gia_2019-04-13T10:18:34.253900
| 1,555,150,714.2539 | 18,607 |
pythondev
|
help
|
now in the same way, you can connect to ANY sql server from python
|
2019-04-13T10:18:48.254300
|
Erika
|
pythondev_help_Erika_2019-04-13T10:18:48.254300
| 1,555,150,728.2543 | 18,608 |
pythondev
|
help
|
and send a string to it
|
2019-04-13T10:18:55.254600
|
Erika
|
pythondev_help_Erika_2019-04-13T10:18:55.254600
| 1,555,150,735.2546 | 18,609 |
pythondev
|
help
|
the connection is called a *odbc* connection
|
2019-04-13T10:19:10.255000
|
Erika
|
pythondev_help_Erika_2019-04-13T10:19:10.255000
| 1,555,150,750.255 | 18,610 |
pythondev
|
help
|
you will need pyodbc
|
2019-04-13T10:19:17.255200
|
Erika
|
pythondev_help_Erika_2019-04-13T10:19:17.255200
| 1,555,150,757.2552 | 18,611 |
pythondev
|
help
|
and look at Microsoft docs on how to set up a odbc connection between your python environment and the SQL server
|
2019-04-13T10:19:52.256000
|
Erika
|
pythondev_help_Erika_2019-04-13T10:19:52.256000
| 1,555,150,792.256 | 18,612 |
pythondev
|
help
|
Ahh I see
|
2019-04-13T10:20:25.256200
|
Gia
|
pythondev_help_Gia_2019-04-13T10:20:25.256200
| 1,555,150,825.2562 | 18,613 |
pythondev
|
help
|
Thanks for the tip
|
2019-04-13T10:24:02.256800
|
Gia
|
pythondev_help_Gia_2019-04-13T10:24:02.256800
| 1,555,151,042.2568 | 18,614 |
pythondev
|
help
|
<#C5CAD2J67|editors> is probably your best bet
|
2019-04-13T11:13:16.257300
|
Cherish
|
pythondev_help_Cherish_2019-04-13T11:13:16.257300
| 1,555,153,996.2573 | 18,615 |
pythondev
|
help
|
Can someone help me out with a random coding problem? I swear this is easy and I'm just being stupid.
I have dates that are in this format:
`2013.500`
The portion to the left of the `.` is the year. This is good. The portion to the right of the `.` is the percentage into the year, by month. So for example this says we're `50`% through the year, so we'd figure out that that means month 6 of of 12, or June.
I need to write a method to convert that fractional value to the month,. where just the numerical representation of the month is great [1-12].
|
2019-04-13T11:13:51.257600
|
Cammie
|
pythondev_help_Cammie_2019-04-13T11:13:51.257600
| 1,555,154,031.2576 | 18,616 |
pythondev
|
help
|
Came up with:
```
def month_decimal_to_index(s: str):
"""Converts the weird encoding deciaml that this data set had to an actual month.
EX: '2013.250' -> 3, for March, the third month of the year
"""
DECIMAL_VALUE_PER_MONTH = 1.00/12
return float('.' + s.split('.')[1])//DECIMAL_VALUE_PER_MONTH + 1 # we reattach the '.' we split on, as it is a decimal and we want to use it
```
|
2019-04-13T11:16:18.257900
|
Cammie
|
pythondev_help_Cammie_2019-04-13T11:16:18.257900
| 1,555,154,178.2579 | 18,617 |
pythondev
|
help
|
In what way does your attempt not work?
|
2019-04-13T11:35:48.258500
|
Raven
|
pythondev_help_Raven_2019-04-13T11:35:48.258500
| 1,555,155,348.2585 | 18,618 |
pythondev
|
help
|
A handy trick is to use the modulus operator to get the fractional part of a float, so `(float(s) % 1) * 12` would give you the month.
|
2019-04-13T11:38:10.259700
|
Sasha
|
pythondev_help_Sasha_2019-04-13T11:38:10.259700
| 1,555,155,490.2597 | 18,619 |
pythondev
|
help
|
However, the representation is a little weird. If 0.500 is supposed to be June, how is December specified?
|
2019-04-13T11:38:44.260300
|
Sasha
|
pythondev_help_Sasha_2019-04-13T11:38:44.260300
| 1,555,155,524.2603 | 18,620 |
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