need to replace duplicates in column market_offers with value that can be SUM for all entries that give main value.
but there is a case that there are different rank and country codes so
input
country_code rank store_id category_id offers market_offers
se 1 14582 1106 410 504860
se 1 1955 1294 2 504860
se 1 9831 1158 151 504860
se 2 666 11158 536 4000
se 2 6587 25863 6586 4000
se 2 6666 158 536 4000
se 5 65853 76722 1521 302
se 5 6587 25863 6586 302
expected result
country_code rank store_id category_id offers market_offers
se 1 14582 1106 410 168 286
se 1 1955 1294 2 168 286
se 1 9831 1158 151 168 286
se 2 666 11158 536 1333
se 2 6587 25863 6586 1333
se 2 6666 158 536 1333
se 5 65853 76722 1521 151
se 5 6587 25863 6586 151
Consider below
select * except(market_offers),
round(market_offers / count(1) over(partition by market_offers, rank), 2) as market_offers
from `project.dataset.table`
if applied to sample data in your question - output is
Related
I have a table like this
create table users(
user_id int not null auto_increment,
user_age date,
user_address varchar(255),
primary key(user_id)
)
user_id
user_age
user_address
1
2010-01-05
87 Polk St. Suite 5
2
2010-01-06
Carrera 52 con Ave. Bolivar #65-98 Liano Largo
3
2010-01-07
Ave. 5 de Mayo Porlamar
4
2010-01-08
89 Chiaroscuro Rd.
5
2010-01-09
Via Ludovico il Moro 22
6
2010-01-10
Rue JosephBens 532
7
2011-01-05
43 rue St. Laurent
8
2011-01-06
Heerstr. 22
9
2011-01-07
South House 300 Queensbridge
10
2011-01-08
Ing. Gustavo Moncaa 8585 Piso 20-A
11
2011-01-09
Obere Str. 57
12
2011-01-10
Avda. de la Constitución 2222
13
2012-01-05
Mataderos 2312
14
2012-01-06
120 Hanover Sq.
15
2012-01-07
Berguvsvägen 8
16
2012-01-08
Forsterstr. 57
And I'd like my table to be like this:
user_id
user_age
user_address
1
2010-01-05
87 Polk St. Suite 5
2
2010-01-06
Carrera 52 con Ave. Bolivar #65-98 Liano Largo
7
2011-01-05
43 rue St. Laurent
8
2011-01-06
Heerstr. 22
13
2012-01-05
Mataderos 2312
14
2012-01-06
120 Hanover Sq.
How can I make this happen with group by statement?
If your MySQL supports windows function try:
with cte as
(
SELECT *, ROW_NUMBER() OVER(partition by year(user_age) ORDER BY user_age) row_num
FROM users
)
select user_id,user_age,user_address
from cte
where row_num<=2;
Demo
my table look like following
id person counter
1 Ona 4946
2 Mayra 15077
3 Claire 496
4 Rita 13929
5 Demond 579
6 Winnifred 13580
7 Green 1734
8 Jacquelyn 19092
9 Aisha 5572
10 Kian 8826
11 Alexandrea 7514
12 Dalton 14151
13 Rossie 18403
14 Carson 19537
15 Mason 2022
16 Emie 2394
17 Jonatan 6655
18 June 5037
19 Jazmyn 10856
20 Mittie 18928
here is the fiddle
i would like to select the top 5 by counter and group by first character, here is the sql that i tried:
SELECT SUBSTR(person,1,1) AS Alpha, person, counter
FROM myTable
GROUP BY SUBSTR(person,1,1)
ORDER BY SUBSTR(person,1,1) ASC, counter DESC;
how to select desired result as following:
alpha person counter
a Arvid 9236
a Aisha 5572
a Alf 4000
a Ahmad 3500
a Alvin 2100
b Brandon 13000
b Ben 8230
b Bonny 7131
b Bella 4120
b Bun 1200
c Connie 9320
c Calvin 8310
c Camalia 6123
c Cimon 3419
c Clay 2515
im using mysql 8.0
You can do:
select *
from (
select *, row_number() over(partition by substr(person, 1, 1)
order by counter desc) as rn
from myTable
) x
where rn <= 5
order by substr(person, 1, 1), rn
Result:
id person counter rn
---- ---------- -------- --
153 Alf 19758 1
283 Alycia 19706 2
260 Abe 19463 3
223 Assunta 18808 4
300 Ari 18031 5
210 Bennie 18309 1
159 Barry 18281 2
128 Beulah 18080 3
314 Benny 16795 4
474 Barry 15789 5
342 Casandra 19656 1
14 Carson 19537 2
67 Chaim 19429 3
280 Colin 18507 4
500 Corbin 18433 5
380 Daphney 19138 1
234 Dejah 18781 2
241 Derrick 18722 3
49 Dasia 18562 4
312 Darrel 17903 5
163 Evalyn 19847 1
79 Ernestine 19523 2
344 Emilie 19520 3
371 Eva 19119 4
469 Emma 18403 5
140 Fiona 19522 1
216 Flo 18314 2
356 Frieda 16082 3
254 Floy 15942 4
54 Florencio 12739 5
447 Geoffrey 19858 1
327 Geoffrey 19223 2
335 Grant 19100 3
454 Giuseppe 16175 4
83 Gardner 15235 5
373 Hilario 19507 1
35 Hanna 19276 2
200 Halle 18150 3
491 Hailee 17521 4
411 Hermann 17018 5
21 Idella 7440 1
177 Izabella 5536 2
115 Isai 4164 3
412 Izabella 2112 4
275 Imani 573 5
195 Joannie 19374 1
8 Jacquelyn 19092 2
48 Jalon 18861 3
251 Jamie 18768 4
367 Joanny 17600 5
282 Kendra 19278 1
421 Kendra 19213 2
363 Kaylin 18977 3
96 Kaylie 18423 4
310 Katrine 17754 5
146 Lonzo 19778 1
194 Leonora 18258 2
399 Laurine 16847 3
137 Leslie 16718 4
190 Luther 16318 5
87 Maegan 19112 1
20 Mittie 18928 2
271 Mariana 18149 3
317 Mary 18043 4
305 Maybelle 17666 5
281 Noelia 19203 1
176 Nickolas 19047 2
408 Nelson 15901 3
142 Nasir 13700 4
366 Nicole 10694 5
423 Ova 19759 1
487 Osborne 19539 2
438 Ozella 18911 3
375 Ora 18270 4
414 Onie 17358 5
52 Pascale 19658 1
39 Pearlie 17621 2
364 Price 14177 3
161 Precious 10337 4
294 Paula 9162 5
70 Quincy 18343 1
73 Quincy 16631 2
192 Quentin 13578 3
131 Rodger 19776 1
231 Royal 19033 2
313 Rocky 19008 3
13 Rossie 18403 4
45 Rosanna 15992 5
418 Sydnee 19810 1
470 Sadie 19189 2
123 Shanna 18862 3
485 Savanah 18664 4
302 Steve 16412 5
406 Toney 18283 1
28 Tremaine 16400 2
98 Taurean 15911 3
278 Tremaine 14391 4
311 Treva 14026 5
239 Ubaldo 11630 1
78 Valentina 17736 1
458 Vita 17527 2
170 Vergie 16971 3
158 Vance 15089 4
272 Veronica 12027 5
102 Willis 18155 1
329 Ward 14919 2
156 Westley 14867 3
136 Winnifred 14315 4
6 Winnifred 13580 5
323 Yolanda 17920 1
155 Yesenia 6164 2
402 Zachary 19129 1
37 Zaria 5398 2
See running example at DB Fiddle.
How can get this : the last name (nom), first name (prenom) and age of competitors that participated at all competitons. I have difficulties with count and join.
my user table :
id
nom
prenom
login
age
1
Wehner
Einar
kleinviola
79
2
Beer
Cierra
earnestinelebsa
71
3
Gina
Lucien
cassindagmar
97
4
Maybelle
Delphine
haleypredovic
91
5
Upton
Elwyn
sstreich
63
6
Irwin
Prof.
christopframi
25
7
Ernser
Clint
cesar65
83
8
Bechtelar
Sheila
sofiasawayn
77
9
Simonis
Remington
christafahey
35
10
Parisian
Octavia
swiftsage
89
11
Predovic
Rory
bartolettisabri
78
12
Will
Sven
price66
20
13
O'Hara
Zoey
tiffanywillms
96
14
McGlynn
Julie
gkoss
74
15
Walter
Maximus
amandajenkins
63
16
Hahn
Andrew
drutherford
77
17
Kunze
Elinore
ziemanntheron
95
18
Ursula
Evelyne
collierodessa
64
19
Klein
Kirsten
darrellrunolfss
96
20
Chester
Lucien
jamey55
24
21
Darron
Antoine
justina27
60
22
Boyer
Harvey
hesseljameson
45
23
Jade
Lucien
kpagac
29
24
Eliane
Delphine
delphahessel
75
25
Lang
Shanna
sophia73
23
26
Wilderman
Fredrick
shaina75
34
27
Daniel
Emie
alene73
86
28
Daniel
Rhoda
foster22
63
29
Trantow
Tommie
boconner
40
30
Kerluke
Adolf
vstanton
74
31
Sehoubo
David
davidshbo
20
32
dfglskdsklj
dfvdvf
dfgdfg
0
my competitors table :
id_competitor
id_concours
1
1
2
1
3
1
4
1
5
1
6
1
7
1
8
1
31
1
9
2
10
2
11
2
12
2
13
2
14
2
15
2
16
2
17
2
18
2
31
2
1
3
2
3
3
3
4
3
5
3
19
3
20
3
31
3
2
4
4
4
6
4
8
4
10
4
12
4
14
4
16
4
18
4
20
4
1
5
3
5
5
5
7
5
9
5
11
5
13
5
15
5
17
5
19
5
my competitons table:
id
date_debut
date_fin
descriptif
theme
etat
1
2019-01-01 00:00:00
2019-03-01 00:00:00
Le premier concours de la plateforme
Les zinzins de l'espace
4
2
2018-01-01 00:00:00
2018-02-01 00:00:00
Le deuxième concours de la plateforme
Outils
4
3
2020-04-01 00:00:00
2020-05-01 00:00:00
Le troisième concours de la plateforme
Voiture sur autoroute
2
4
2018-07-01 00:00:00
2018-08-11 00:00:00
Le quatrième concours de la plateforme
Naruto Uzumaki
3
5
2018-10-01 00:00:00
2018-11-01 00:00:00
Le cinquième concours de la plateforme
Le grand peuple au dessus de la mer
4
This should return the name, first name and age of all users that participated in ALL competitions:
SELECT nom, prenom, age
FROM user
WHERE (SELECT count(DISTINCT id_concours) FROM competitors WHERE id_competitor = user.id) = (SELECT count(*) FROM competitons);
my code in MySQL workbench
SELECT
id,
user_id,
parent_id,
approved_time,
#new_approved_t:=IF(new_product_type != 'B', approved_time, #new_approved_t))AS new_approved_time
FROM p
my data frame look like this after I run the code:
id user_id parent_id product_type approved_time New_approved_time
30 11 NA A 8/4/2017 8/4/2017
31 11 30 B 12/1/2017 8/4/2017
54 5 NA A 5/5/2018 5/5/2018
322 5 54 B 7/22/2018 5/5/2018
21 5 NA C 8/1/2018 8/1/2018
13 5 NA C 8/2/2018 8/2/2018
2445 5 NA C 9/25/2018 9/25/2018
111 44 NA A 10/4/2018 10/4/2018
287 44 111 B 10/8/2018 10/4/2018
211 33 NA A 12/5/2018 12/5/2018
277 33 211 B 12/25/2018 12/5/2018
1120 33 NA C 1/1/2019 1/1/2019
1389 33 211 B 1/11/2019 1/1/2019
I would like all my product_type ending in 'B' and it's new_approved_time column to use the corresponding parent_id approved time. The result should look like in below:
id user_id parent_id product_type approved_time New_approved_time
30 11 NA A 8/4/2017 8/4/2017
31 11 30 B 12/1/2017 8/4/2017
54 5 NA A 5/5/2018 5/5/2018
322 5 54 B 7/22/2018 5/5/2018
21 5 NA C 8/1/2018 8/1/2018
13 5 NA C 8/2/2018 8/2/2018
2445 5 NA C 9/25/2018 9/25/2018
111 44 NA A 10/4/2018 10/4/2018
287 44 111 B 10/8/2018 10/4/2018
211 33 NA A 12/5/2018 12/5/2018
277 33 211 B 12/25/2018 12/5/2018
1120 33 NA C 1/1/2019 1/1/2019
1389 33 211 B 1/11/2019 12/5/2018 <-this is where I dont know how to write my code
Thank you!
Found a solution here with another column I didn't include in my example, but basically it's the reverse of parent_id column I listed above which only listed id in product_type A and rest of them is null.
But I got hint from Dan's code on COALESCE() function, thanks Dan.
CASE WHEN c.new_product_type IN ('A', 'B') THEN #new_approved_t:=IF(COALESCE(if((a.is_loc=1 AND b.ploc_RID IS NOT NULL), a.id, null)), a.approved_time, #new_approved_t)
ELSE a.approved_time END AS new_approved_time
Because the parent (pp) has its own value there needs to be a self join like this. Because of the join criteria pp.approved_time will be NULL for non-B products.
SELECT
p.id,
p.user_id,
p.parent_id,
p.approved_time,
COALESCE(pp.approved_time, p.approved_time) AS new_approved_time
FROM p
LEFT JOIN p AS pp ON p.new_product_type = 'B' AND p.parent_id = pp.id
I have the following csv structure:
'Country' '1960' '1961' '1962'
AUS 450 567 723
NZ 125 320
IND 350 375 395
SL
PAK 100 115 218
Using Python Pandas how do I convert(transpose) the above structure to the following?
'Country' 'Year' 'Value'
AUS 1960 450
AUS 1961 567
AUS 1962 723
NZ 1960
NZ 1961 125
...
My attempts at using pivot have been futile.
In [19]: df
Out[19]:
year 1960 1961 1962
Country
AUS 450 567 723
NZ NaN 125 320
IND 350 375 395
SL NaN NaN NaN
PAK 100 115 218
In [20]: df.stack().reset_index()
Out[20]:
Country year 0
0 AUS 1960 450
1 AUS 1961 567
2 AUS 1962 723
3 NZ 1961 125
4 NZ 1962 320
5 IND 1960 350
6 IND 1961 375
7 IND 1962 395
8 PAK 1960 100
9 PAK 1961 115
10 PAK 1962 218
Apparently NaN are dropped along the way.