Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells181
Missing cells (%)0.5%
Duplicate rows29
Duplicate rows (%)0.3%
Total size in memory390.6 KiB
Average record size in memory40.0 B

Variable types

Text4

Dataset

Description전국 시장에 종이상품권가맹점에 대한 데이터로 점포가 속해있는 시장명, 가맹 점포명, 취급품목, 주소 등을 항목으로 제공합니다.
Author소상공인시장진흥공단
URLhttps://www.data.go.kr/data/15091227/fileData.do

Alerts

Dataset has 29 (0.3%) duplicate rowsDuplicates
취급품목 has 139 (1.4%) missing valuesMissing

Reproduction

Analysis started2024-04-21 03:26:52.935594
Analysis finished2024-04-21 03:26:55.578250
Duration2.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시장명
Text

Distinct1349
Distinct (%)13.5%
Missing14
Missing (%)0.1%
Memory size156.2 KiB
2024-04-21T12:26:56.207187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length7.4086721
Min length3

Characters and Unicode

Total characters73983
Distinct characters410
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

Unique235 ?
Unique (%)2.4%

Sample

1st row민속오일시장
2nd row제천중앙시장
3rd row평택통복시장
4th row순천원도심상점가
5th row경산시중앙상점가
ValueCountFrequency (%)
부산진시장 112
 
1.0%
중앙로지하상가 74
 
0.7%
민속오일시장 74
 
0.7%
평화시장 73
 
0.7%
고투몰(강남터미널지하도상점가 73
 
0.7%
남대문시장 71
 
0.7%
충주자유시장 70
 
0.6%
신평화패션타운 67
 
0.6%
대현프리몰 61
 
0.6%
르네시떼시장 55
 
0.5%
Other values (1406) 10151
93.3%
2024-04-21T12:26:57.183178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 8755
 
11.8%
시 8445
 
11.4%
상 2383
 
3.2%
가 2306
 
3.1%
산 1571
 
2.1%
동 1407
 
1.9%
전 1358
 
1.8%
중 1260
 
1.7%
부 1210
 
1.6%
통 1113
 
1.5%
Other values (400) 44175
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70068
94.7%
Close Punctuation 1098
 
1.5%
Open Punctuation 1098
 
1.5%
Space Separator 976
 
1.3%
Decimal Number 557
 
0.8%
Other Punctuation 129
 
0.2%
Control 35
 
< 0.1%
Lowercase Letter 12
 
< 0.1%
Math Symbol 7
 
< 0.1%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 8755
 
12.5%
시 8445
 
12.1%
상 2383
 
3.4%
가 2306
 
3.3%
산 1571
 
2.2%
동 1407
 
2.0%
전 1358
 
1.9%
중 1260
 
1.8%
부 1210
 
1.7%
통 1113
 
1.6%
Other values (379) 40260
57.5%
Decimal Number
ValueCountFrequency (%)
1 161
28.9%
5 155
27.8%
2 96
17.2%
3 75
13.5%
4 26
 
4.7%
7 17
 
3.1%
0 13
 
2.3%
9 9
 
1.6%
6 5
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
D 1
33.3%
C 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 108
83.7%
! 21
 
16.3%
Lowercase Letter
ValueCountFrequency (%)
k 6
50.0%
s 6
50.0%
Close Punctuation
ValueCountFrequency (%)
) 1098
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1098
100.0%
Space Separator
ValueCountFrequency (%)
976
100.0%
Control
ValueCountFrequency (%)
35
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70068
94.7%
Common 3900
 
5.3%
Latin 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 8755
 
12.5%
시 8445
 
12.1%
상 2383
 
3.4%
가 2306
 
3.3%
산 1571
 
2.2%
동 1407
 
2.0%
전 1358
 
1.9%
중 1260
 
1.8%
부 1210
 
1.7%
통 1113
 
1.6%
Other values (379) 40260
57.5%
Common
ValueCountFrequency (%)
) 1098
28.2%
( 1098
28.2%
976
25.0%
1 161
 
4.1%
5 155
 
4.0%
, 108
 
2.8%
2 96
 
2.5%
3 75
 
1.9%
35
 
0.9%
4 26
 
0.7%
Other values (6) 72
 
1.8%
Latin
ValueCountFrequency (%)
k 6
40.0%
s 6
40.0%
S 1
 
6.7%
D 1
 
6.7%
C 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70068
94.7%
ASCII 3915
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 8755
 
12.5%
시 8445
 
12.1%
상 2383
 
3.4%
가 2306
 
3.3%
산 1571
 
2.2%
동 1407
 
2.0%
전 1358
 
1.9%
중 1260
 
1.8%
부 1210
 
1.7%
통 1113
 
1.6%
Other values (379) 40260
57.5%
ASCII
ValueCountFrequency (%)
) 1098
28.0%
( 1098
28.0%
976
24.9%
1 161
 
4.1%
5 155
 
4.0%
, 108
 
2.8%
2 96
 
2.5%
3 75
 
1.9%
35
 
0.9%
4 26
 
0.7%
Other values (11) 87
 
2.2%

점포명
Text

Distinct9027
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T12:26:57.835681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length4.818
Min length1

Characters and Unicode

Total characters48180
Distinct characters1010
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8552 ?
Unique (%)85.5%

Sample

1st row노점
2nd rowI&U(아이앤유)
3rd row동우평택대리점
4th row위드유
5th row배가네찹쌀도너츠
ValueCountFrequency (%)
노점 284
 
2.7%
형제상회 12
 
0.1%
제일상회 9
 
0.1%
싱싱야채 8
 
0.1%
경북상회 8
 
0.1%
아리따움 8
 
0.1%
서울상회 8
 
0.1%
우리상회 8
 
0.1%
주식회사 7
 
0.1%
엄마손반찬 7
 
0.1%
Other values (9285) 10078
96.6%
2024-04-21T12:26:58.753137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 1075
 
2.2%
상 972
 
2.0%
이 893
 
1.9%
산 851
 
1.8%
회 849
 
1.8%
수 695
 
1.4%
리 660
 
1.4%
스 561
 
1.2%
식 543
 
1.1%
대 535
 
1.1%
Other values (1000) 40546
84.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45483
94.4%
Decimal Number 604
 
1.3%
Uppercase Letter 510
 
1.1%
Space Separator 456
 
0.9%
Open Punctuation 330
 
0.7%
Close Punctuation 321
 
0.7%
Lowercase Letter 252
 
0.5%
Other Punctuation 122
 
0.3%
Other Symbol 75
 
0.2%
Dash Punctuation 26
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1075
 
2.4%
상 972
 
2.1%
이 893
 
2.0%
산 851
 
1.9%
회 849
 
1.9%
수 695
 
1.5%
리 660
 
1.5%
스 561
 
1.2%
식 543
 
1.2%
대 535
 
1.2%
Other values (923) 37849
83.2%
Uppercase Letter
ValueCountFrequency (%)
C 45
 
8.8%
B 41
 
8.0%
A 37
 
7.3%
S 34
 
6.7%
T 32
 
6.3%
N 28
 
5.5%
D 27
 
5.3%
E 23
 
4.5%
O 22
 
4.3%
Y 22
 
4.3%
Other values (16) 199
39.0%
Lowercase Letter
ValueCountFrequency (%)
e 41
16.3%
o 30
 
11.9%
s 15
 
6.0%
a 15
 
6.0%
n 14
 
5.6%
i 13
 
5.2%
t 11
 
4.4%
r 11
 
4.4%
d 10
 
4.0%
c 10
 
4.0%
Other values (14) 82
32.5%
Other Punctuation
ValueCountFrequency (%)
. 41
33.6%
& 30
24.6%
, 23
18.9%
？ 10
 
8.2%
# 6
 
4.9%
? 4
 
3.3%
' 3
 
2.5%
: 2
 
1.6%
! 1
 
0.8%
; 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
1 128
21.2%
2 114
18.9%
3 80
13.2%
0 52
8.6%
5 51
 
8.4%
8 45
 
7.5%
4 39
 
6.5%
7 37
 
6.1%
9 33
 
5.5%
6 25
 
4.1%
Space Separator
ValueCountFrequency (%)
456
100.0%
Open Punctuation
ValueCountFrequency (%)
( 330
100.0%
Close Punctuation
ValueCountFrequency (%)
) 321
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Math Symbol
ValueCountFrequency (%)
× 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45557
94.6%
Common 1860
 
3.9%
Latin 762
 
1.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1075
 
2.4%
상 972
 
2.1%
이 893
 
2.0%
산 851
 
1.9%
회 849
 
1.9%
수 695
 
1.5%
리 660
 
1.4%
스 561
 
1.2%
식 543
 
1.2%
대 535
 
1.2%
Other values (923) 37923
83.2%
Latin
ValueCountFrequency (%)
C 45
 
5.9%
B 41
 
5.4%
e 41
 
5.4%
A 37
 
4.9%
S 34
 
4.5%
T 32
 
4.2%
o 30
 
3.9%
N 28
 
3.7%
D 27
 
3.5%
E 23
 
3.0%
Other values (40) 424
55.6%
Common
ValueCountFrequency (%)
456
24.5%
( 330
17.7%
) 321
17.3%
1 128
 
6.9%
2 114
 
6.1%
3 80
 
4.3%
0 52
 
2.8%
5 51
 
2.7%
8 45
 
2.4%
. 41
 
2.2%
Other values (16) 242
13.0%
Han
ValueCountFrequency (%)
李 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45482
94.4%
ASCII 2611
 
5.4%
None 86
 
0.2%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 1075
 
2.4%
상 972
 
2.1%
이 893
 
2.0%
산 851
 
1.9%
회 849
 
1.9%
수 695
 
1.5%
리 660
 
1.5%
스 561
 
1.2%
식 543
 
1.2%
대 535
 
1.2%
Other values (922) 37848
83.2%
ASCII
ValueCountFrequency (%)
456
17.5%
( 330
 
12.6%
) 321
 
12.3%
1 128
 
4.9%
2 114
 
4.4%
3 80
 
3.1%
0 52
 
2.0%
5 51
 
2.0%
8 45
 
1.7%
C 45
 
1.7%
Other values (64) 989
37.9%
None
ValueCountFrequency (%)
㈜ 75
87.2%
？ 10
 
11.6%
× 1
 
1.2%
CJK Compat Ideographs
ValueCountFrequency (%)
李 1
100.0%

취급품목
Text

MISSING 

Distinct2377
Distinct (%)24.1%
Missing139
Missing (%)1.4%
Memory size156.2 KiB
2024-04-21T12:26:59.727793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length29
Mean length4.191867
Min length1

Characters and Unicode

Total characters41336
Distinct characters484
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1729 ?
Unique (%)17.5%

Sample

1st row농산물
2nd row아동복
3rd row도매업(식육판매)
4th row의류
5th row도너츠
ValueCountFrequency (%)
의류 987
 
9.5%
한식 306
 
2.9%
수산물 291
 
2.8%
농산물 272
 
2.6%
음식점 268
 
2.6%
음식 242
 
2.3%
잡화 180
 
1.7%
야채 164
 
1.6%
과일 139
 
1.3%
건어물 136
 
1.3%
Other values (2205) 7412
71.3%
2024-04-21T12:27:00.973501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 2566
 
6.2%
( 2503
 
6.1%
) 2477
 
6.0%
소 2016
 
4.9%
매 2011
 
4.9%
의 1677
 
4.1%
류 1642
 
4.0%
음 1329
 
3.2%
물 1206
 
2.9%
업 1034
 
2.5%
Other values (474) 22875
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34896
84.4%
Open Punctuation 2504
 
6.1%
Close Punctuation 2479
 
6.0%
Other Punctuation 886
 
2.1%
Space Separator 548
 
1.3%
Uppercase Letter 14
 
< 0.1%
Lowercase Letter 4
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Connector Punctuation 1
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 2566
 
7.4%
소 2016
 
5.8%
매 2011
 
5.8%
의 1677
 
4.8%
류 1642
 
4.7%
음 1329
 
3.8%
물 1206
 
3.5%
업 1034
 
3.0%
산 991
 
2.8%
도 955
 
2.7%
Other values (449) 19469
55.8%
Uppercase Letter
ValueCountFrequency (%)
D 4
28.6%
C 3
21.4%
P 3
21.4%
Y 1
 
7.1%
I 1
 
7.1%
G 1
 
7.1%
L 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 845
95.4%
. 22
 
2.5%
/ 14
 
1.6%
? 3
 
0.3%
？ 2
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 2477
99.9%
} 1
 
< 0.1%
] 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
c 2
50.0%
v 1
25.0%
t 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 2503
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
548
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34897
84.4%
Common 6421
 
15.5%
Latin 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 2566
 
7.4%
소 2016
 
5.8%
매 2011
 
5.8%
의 1677
 
4.8%
류 1642
 
4.7%
음 1329
 
3.8%
물 1206
 
3.5%
업 1034
 
3.0%
산 991
 
2.8%
도 955
 
2.7%
Other values (450) 19470
55.8%
Common
ValueCountFrequency (%)
( 2503
39.0%
) 2477
38.6%
, 845
 
13.2%
548
 
8.5%
. 22
 
0.3%
/ 14
 
0.2%
? 3
 
< 0.1%
- 2
 
< 0.1%
？ 2
 
< 0.1%
_ 1
 
< 0.1%
Other values (4) 4
 
0.1%
Latin
ValueCountFrequency (%)
D 4
22.2%
C 3
16.7%
P 3
16.7%
c 2
11.1%
Y 1
 
5.6%
I 1
 
5.6%
v 1
 
5.6%
t 1
 
5.6%
G 1
 
5.6%
L 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34896
84.4%
ASCII 6437
 
15.6%
None 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 2566
 
7.4%
소 2016
 
5.8%
매 2011
 
5.8%
의 1677
 
4.8%
류 1642
 
4.7%
음 1329
 
3.8%
물 1206
 
3.5%
업 1034
 
3.0%
산 991
 
2.8%
도 955
 
2.7%
Other values (449) 19469
55.8%
ASCII
ValueCountFrequency (%)
( 2503
38.9%
) 2477
38.5%
, 845
 
13.1%
548
 
8.5%
. 22
 
0.3%
/ 14
 
0.2%
D 4
 
0.1%
C 3
 
< 0.1%
P 3
 
< 0.1%
? 3
 
< 0.1%
Other values (13) 15
 
0.2%
None
ValueCountFrequency (%)
？ 2
66.7%
㈜ 1
33.3%

주소
Text

Distinct8834
Distinct (%)88.6%
Missing28
Missing (%)0.3%
Memory size156.2 KiB
2024-04-21T12:27:02.151777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length52
Mean length20.601183
Min length3

Characters and Unicode

Total characters205435
Distinct characters497
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8339 ?
Unique (%)83.6%

Sample

1st row제주시 오일장서길 26
2nd row충북 제천시 풍양로 108 나동 99호
3rd row경기 평택시 중앙1로 27
4th row전라남도 순천시 시민로 58-3
5th row경북 경산시 중앙로16길 16
ValueCountFrequency (%)
중구 1161
 
2.5%
서울 926
 
2.0%
경기도 843
 
1.8%
부산광역시 768
 
1.6%
서울시 542
 
1.2%
강원도 522
 
1.1%
대구 507
 
1.1%
1층 498
 
1.1%
경남 482
 
1.0%
서울특별시 458
 
1.0%
Other values (9621) 40064
85.7%
2024-04-21T12:27:03.638711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37153
 
18.1%
1 9925
 
4.8%
시 8281
 
4.0%
구 7330
 
3.6%
2 6482
 
3.2%
로 6023
 
2.9%
동 5429
 
2.6%
3 4591
 
2.2%
길 4164
 
2.0%
- 3855
 
1.9%
Other values (487) 112202
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117064
57.0%
Decimal Number 42286
 
20.6%
Space Separator 37153
 
18.1%
Dash Punctuation 3855
 
1.9%
Other Punctuation 2116
 
1.0%
Open Punctuation 1180
 
0.6%
Close Punctuation 1179
 
0.6%
Uppercase Letter 540
 
0.3%
Math Symbol 48
 
< 0.1%
Lowercase Letter 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 8281
 
7.1%
구 7330
 
6.3%
로 6023
 
5.1%
동 5429
 
4.6%
길 4164
 
3.6%
산 3316
 
2.8%
서 2965
 
2.5%
남 2766
 
2.4%
경 2599
 
2.2%
중 2381
 
2.0%
Other values (442) 71810
61.3%
Uppercase Letter
ValueCountFrequency (%)
A 139
25.7%
B 130
24.1%
C 103
19.1%
D 73
13.5%
E 20
 
3.7%
F 17
 
3.1%
G 15
 
2.8%
I 9
 
1.7%
H 7
 
1.3%
L 6
 
1.1%
Other values (6) 21
 
3.9%
Decimal Number
ValueCountFrequency (%)
1 9925
23.5%
2 6482
15.3%
3 4591
10.9%
4 3766
 
8.9%
5 3384
 
8.0%
6 3238
 
7.7%
0 3061
 
7.2%
7 2923
 
6.9%
8 2601
 
6.2%
9 2315
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 1937
91.5%
. 79
 
3.7%
/ 76
 
3.6%
· 20
 
0.9%
？ 3
 
0.1%
: 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
c 5
41.7%
b 5
41.7%
a 1
 
8.3%
k 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 1179
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1178
99.9%
] 1
 
0.1%
Other Symbol
ValueCountFrequency (%)
㈜ 1
50.0%
┗ 1
50.0%
Space Separator
ValueCountFrequency (%)
37153
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3855
100.0%
Math Symbol
ValueCountFrequency (%)
~ 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117065
57.0%
Common 87818
42.7%
Latin 552
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 8281
 
7.1%
구 7330
 
6.3%
로 6023
 
5.1%
동 5429
 
4.6%
길 4164
 
3.6%
산 3316
 
2.8%
서 2965
 
2.5%
남 2766
 
2.4%
경 2599
 
2.2%
중 2381
 
2.0%
Other values (443) 71811
61.3%
Common
ValueCountFrequency (%)
37153
42.3%
1 9925
 
11.3%
2 6482
 
7.4%
3 4591
 
5.2%
- 3855
 
4.4%
4 3766
 
4.3%
5 3384
 
3.9%
6 3238
 
3.7%
0 3061
 
3.5%
7 2923
 
3.3%
Other values (14) 9440
 
10.7%
Latin
ValueCountFrequency (%)
A 139
25.2%
B 130
23.6%
C 103
18.7%
D 73
13.2%
E 20
 
3.6%
F 17
 
3.1%
G 15
 
2.7%
I 9
 
1.6%
H 7
 
1.3%
L 6
 
1.1%
Other values (10) 33
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117058
57.0%
ASCII 88346
43.0%
None 24
 
< 0.1%
Compat Jamo 6
 
< 0.1%
Box Drawing 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37153
42.1%
1 9925
 
11.2%
2 6482
 
7.3%
3 4591
 
5.2%
- 3855
 
4.4%
4 3766
 
4.3%
5 3384
 
3.8%
6 3238
 
3.7%
0 3061
 
3.5%
7 2923
 
3.3%
Other values (31) 9968
 
11.3%
Hangul
ValueCountFrequency (%)
시 8281
 
7.1%
구 7330
 
6.3%
로 6023
 
5.1%
동 5429
 
4.6%
길 4164
 
3.6%
산 3316
 
2.8%
서 2965
 
2.5%
남 2766
 
2.4%
경 2599
 
2.2%
중 2381
 
2.0%
Other values (437) 71804
61.3%
None
ValueCountFrequency (%)
· 20
83.3%
？ 3
 
12.5%
㈜ 1
 
4.2%
Compat Jamo
ValueCountFrequency (%)
ㅜ 2
33.3%
ㅡ 1
16.7%
ㄱ 1
16.7%
ㅂ 1
16.7%
ㅇ 1
16.7%
Box Drawing
ValueCountFrequency (%)
┗ 1
100.0%

Missing values

2024-04-21T12:26:55.178276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T12:26:55.328139image/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.
2024-04-21T12:26:55.486020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시장명점포명취급품목주소
39488민속오일시장노점농산물제주시 오일장서길 26
70164제천중앙시장I&U(아이앤유)아동복충북 제천시 풍양로 108 나동 99호
78665평택통복시장동우평택대리점도매업(식육판매)경기 평택시 중앙1로 27
84760순천원도심상점가위드유의류전라남도 순천시 시민로 58-3
46011경산시중앙상점가배가네찹쌀도너츠도너츠경북 경산시 중앙로16길 16
51087삼익패션타운새롬도소매(액세서리,잡화)서울특별시 중구 남대문시장8길7 삼익패션타운70,71호
28782익산매일시장보람옷전북 익산시 중앙로3길 17-1, 1층 103호
32904부전상가시장부영수산수산물부산광역시 부산진구 부전로174번길 38
40863동산상가달라의류대구 중구 큰장로26길 65
56123한양대앞상점가서울 왕족발,보삼음식점(족발)서울특별시 성동구 마조로3가길 27(행당동)
시장명점포명취급품목주소
20613평촌1번가콘서트음식점업(일반음식점)경기도 안양시 동안구 호계동 1046-1
11717신중앙시장경진한복한복대전 동구 원동 40-1, 신중앙A 2층
69711충주관아골상가민들레공방소품충북 충주시 관아4길 15 205호
15036원마루시장㈜소반에식품잡화충북 청주시 서원구 원마루로8번길 8-3
89536부산자유시장유창상회<NA>부산시 동구 범일동 830-24 자유시장 2079
77595화서시장악세서리소매(액세서리)경기도 수원시 팔달구 화서동 97-1
11759인동시장바른농산농산물대전광역시 동구 대전천동로 450(인동)
47924영주문화시장블루의류경북 영주시 중앙로 81
27763전주남부시장우정집한식전북 전주시 완산구 풍남문2길 55
11847전통중앙도매시장영아네잡화대전광역시 동구 중앙로 204번길 28-1

Duplicate rows

Most frequently occurring

시장명점포명취급품목주소# duplicates
6민속오일시장노점농산물제주시 오일장서길 2623
20운수대통! 생거진천전통시장노점야채충북 진천군 진천읍 원덕로 3905
17완도전통시장(완도5일시장)노점기타전라남도 완도군 완도읍 개포로 59번길 16-44
0구룡포시장직거래장터농수산경북 포항시 남구 구룡포읍 호미로221번길 123
9민속오일시장할머니장터야채제주시 오일장서길 263
14양동경열로시장노점잡화광주광역시 서구 경열로 1443
15영암읍5일시장노점농산물전남 영암군 영암읍 오일시장길 283
25진주자유시장노점채소경상남도 진주시 도동천로 953
27함평5일시장노점건어물전남 함평군 함평읍 시장길 1053
28함평5일시장노점청과전남 함평군 함평읍 시장길 1053