Overview

Dataset statistics

Number of variables5
Number of observations1947
Missing cells0
Missing cells (%)0.0%
Duplicate rows13
Duplicate rows (%)0.7%
Total size in memory76.2 KiB
Average record size in memory40.1 B

Variable types

Text1
Categorical1
Boolean3

Dataset

Description전국 시장 점포에 온누리 상품권 사용여부에 대한 데이터로 온누리 종이 상품권 여부, 온누리 전자 상품권 여부, 온누리 모바일 상품권 여부 항목을 제공합니다.
Author소상공인시장진흥공단
URLhttps://www.data.go.kr/data/15091186/fileData.do

Alerts

온누리 전용시장 구(O_온누리, G_일반) has constant value ""Constant
Dataset has 13 (0.7%) duplicate rowsDuplicates
온누리종이상품권 여부 is highly imbalanced (76.9%)Imbalance
온누리전자상품권여부 is highly imbalanced (53.9%)Imbalance

Reproduction

Analysis started2023-12-12 22:02:26.595830
Analysis finished2023-12-12 22:02:27.397153
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시장명
Text

Distinct1917
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
2023-12-13T07:02:27.507187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length6.69132
Min length3

Characters and Unicode

Total characters13028
Distinct characters439
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1891 ?
Unique (%)97.1%

Sample

1st row남대문시장
2nd row삼익패션타운
3rd row서울중부시장
4th row신중부시장
5th row평화시장
ValueCountFrequency (%)
상점가 6
 
0.3%
동문시장 3
 
0.1%
덕산시장 3
 
0.1%
한솔동 3
 
0.1%
역전시장 3
 
0.1%
고투몰(강남터미널지하도상점가 3
 
0.1%
제일시장 3
 
0.1%
가야시장 3
 
0.1%
중앙시장 3
 
0.1%
신흥시장 2
 
0.1%
Other values (1982) 2007
98.4%
2023-12-13T07:02:27.850817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 1676
 
12.9%
시 1609
 
12.4%
상 475
 
3.6%
가 454
 
3.5%
동 287
 
2.2%
산 232
 
1.8%
전 213
 
1.6%
점 183
 
1.4%
중 173
 
1.3%
구 166
 
1.3%
Other values (429) 7560
58.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12524
96.1%
Open Punctuation 138
 
1.1%
Close Punctuation 138
 
1.1%
Decimal Number 114
 
0.9%
Space Separator 94
 
0.7%
Other Punctuation 7
 
0.1%
Uppercase Letter 7
 
0.1%
Math Symbol 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 1676
 
13.4%
시 1609
 
12.8%
상 475
 
3.8%
가 454
 
3.6%
동 287
 
2.3%
산 232
 
1.9%
전 213
 
1.7%
점 183
 
1.5%
중 173
 
1.4%
구 166
 
1.3%
Other values (406) 7056
56.3%
Decimal Number
ValueCountFrequency (%)
5 47
41.2%
1 25
21.9%
2 17
 
14.9%
3 11
 
9.6%
4 5
 
4.4%
6 4
 
3.5%
7 3
 
2.6%
0 1
 
0.9%
9 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
A 2
28.6%
B 2
28.6%
C 1
14.3%
D 1
14.3%
S 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
! 1
 
14.3%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 138
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12524
96.1%
Common 495
 
3.8%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 1676
 
13.4%
시 1609
 
12.8%
상 475
 
3.8%
가 454
 
3.6%
동 287
 
2.3%
산 232
 
1.9%
전 213
 
1.7%
점 183
 
1.5%
중 173
 
1.4%
구 166
 
1.3%
Other values (406) 7056
56.3%
Common
ValueCountFrequency (%)
( 138
27.9%
) 138
27.9%
94
19.0%
5 47
 
9.5%
1 25
 
5.1%
2 17
 
3.4%
3 11
 
2.2%
, 6
 
1.2%
4 5
 
1.0%
6 4
 
0.8%
Other values (6) 10
 
2.0%
Latin
ValueCountFrequency (%)
A 2
22.2%
B 2
22.2%
C 1
11.1%
k 1
11.1%
s 1
11.1%
D 1
11.1%
S 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12524
96.1%
ASCII 504
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 1676
 
13.4%
시 1609
 
12.8%
상 475
 
3.8%
가 454
 
3.6%
동 287
 
2.3%
산 232
 
1.9%
전 213
 
1.7%
점 183
 
1.5%
중 173
 
1.4%
구 166
 
1.3%
Other values (406) 7056
56.3%
ASCII
ValueCountFrequency (%)
( 138
27.4%
) 138
27.4%
94
18.7%
5 47
 
9.3%
1 25
 
5.0%
2 17
 
3.4%
3 11
 
2.2%
, 6
 
1.2%
4 5
 
1.0%
6 4
 
0.8%
Other values (13) 19
 
3.8%

온누리 전용시장 구(O_온누리, G_일반)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
O
1947 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowO
3rd rowO
4th rowO
5th rowO

Common Values

ValueCountFrequency (%)
O 1947
100.0%

Length

2023-12-13T07:02:27.964868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:02:28.051006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 1947
100.0%

온누리종이상품권 여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
True
1874 
False
 
73
ValueCountFrequency (%)
True 1874
96.3%
False 73
 
3.7%
2023-12-13T07:02:28.139615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

온누리전자상품권여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
True
1757 
False
190 
ValueCountFrequency (%)
True 1757
90.2%
False 190
 
9.8%
2023-12-13T07:02:28.228836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

온누리모바일상품권여부
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
True
1598 
False
349 
ValueCountFrequency (%)
True 1598
82.1%
False 349
 
17.9%
2023-12-13T07:02:28.306905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:02:28.365498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온누리종이상품권 여부온누리전자상품권여부온누리모바일상품권여부
온누리종이상품권 여부1.0000.0000.461
온누리전자상품권여부0.0001.0000.658
온누리모바일상품권여부0.4610.6581.000
2023-12-13T07:02:28.441502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온누리종이상품권 여부온누리전자상품권여부온누리모바일상품권여부
온누리종이상품권 여부1.0000.0000.305
온누리전자상품권여부0.0001.0000.457
온누리모바일상품권여부0.3050.4571.000
2023-12-13T07:02:28.527667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온누리종이상품권 여부온누리전자상품권여부온누리모바일상품권여부
온누리종이상품권 여부1.0000.0000.305
온누리전자상품권여부0.0001.0000.457
온누리모바일상품권여부0.3050.4571.000

Missing values

2023-12-13T07:02:27.267046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:02:27.358483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

시장명온누리 전용시장 구(O_온누리, G_일반)온누리종이상품권 여부온누리전자상품권여부온누리모바일상품권여부
0남대문시장OYYY
1삼익패션타운OYYY
2서울중부시장OYYY
3신중부시장OYYY
4평화시장OYYY
5서울중앙시장OYYY
6남평화시장OYYY
7청평화시장OYNY
8제일평화시장OYYY
9신당동중앙시장OYYY
시장명온누리 전용시장 구(O_온누리, G_일반)온누리종이상품권 여부온누리전자상품권여부온누리모바일상품권여부
1937오산원동상점가OYYY
1938홍제골목형상점가OYYY
1939양주가래비중앙로상점가OYYY
1940비래동 상점가OYYY
1941황학동주방거리상점가OYYY
1942동작구상권활성화구역OYYN
1943양주신산시장마을상점가OYYY
1944황계 골목형상점가OYNN
1945산정동골목형상점가OYYN
1946강진읍상권활성화구역OYYN

Duplicate rows

Most frequently occurring

시장명온누리 전용시장 구(O_온누리, G_일반)온누리종이상품권 여부온누리전자상품권여부온누리모바일상품권여부# duplicates
2동문시장OYYY3
10제일시장OYYY3
0강남시장OYYY2
1구암시장OYYY2
3동서시장OYYY2
4서부시장OYYY2
5신중앙시장OYYY2
6신평시장OYYY2
7신흥시장OYYY2
8역전시장OYYY2