Overview

Dataset statistics

Number of variables5
Number of observations183
Missing cells25
Missing cells (%)2.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory40.7 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description인천광역시 서구에 등록된 세탁업 현황(업종명, 업소명, 업소소재지, 소재지전화번호, 데이터기준일 등)입니다.
URLhttps://www.data.go.kr/data/15039941/fileData.do

Alerts

업종명 has constant value ""Constant
데이터기준일 has constant value ""Constant
소재지전화 has 25 (13.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:54:29.546174
Analysis finished2023-12-12 18:54:30.130173
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
세탁업
183 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세탁업 183
100.0%

Length

2023-12-13T03:54:30.281673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:54:30.457884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세탁업 183
100.0%

업소명
Text

Distinct171
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T03:54:30.834292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length5.4918033
Min length2

Characters and Unicode

Total characters1005
Distinct characters218
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique161 ?
Unique (%)88.0%

Sample

1st row어울림세탁
2nd row대명사
3rd row극동드라이크리닝
4th row태영세탁소
5th row대동세탁
ValueCountFrequency (%)
현대세탁 3
 
1.5%
풍림세탁소 3
 
1.5%
대주세탁 2
 
1.0%
장미세탁소 2
 
1.0%
대림세탁 2
 
1.0%
하얀세탁소 2
 
1.0%
광명세탁소 2
 
1.0%
백광세탁소 2
 
1.0%
한신세탁 2
 
1.0%
삼보세탁소 2
 
1.0%
Other values (172) 174
88.8%
2023-12-13T03:54:31.540509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 136
 
13.5%
탁 135
 
13.4%
소 74
 
7.4%
이 23
 
2.3%
크 21
 
2.1%
사 20
 
2.0%
린 20
 
2.0%
대 15
 
1.5%
동 14
 
1.4%
13
 
1.3%
Other values (208) 534
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 951
94.6%
Uppercase Letter 14
 
1.4%
Space Separator 13
 
1.3%
Decimal Number 8
 
0.8%
Open Punctuation 6
 
0.6%
Close Punctuation 6
 
0.6%
Lowercase Letter 6
 
0.6%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 136
 
14.3%
탁 135
 
14.2%
소 74
 
7.8%
이 23
 
2.4%
크 21
 
2.2%
사 20
 
2.1%
린 20
 
2.1%
대 15
 
1.6%
동 14
 
1.5%
라 12
 
1.3%
Other values (186) 481
50.6%
Uppercase Letter
ValueCountFrequency (%)
H 2
14.3%
C 2
14.3%
P 2
14.3%
L 2
14.3%
E 1
7.1%
T 1
7.1%
I 1
7.1%
V 1
7.1%
G 1
7.1%
K 1
7.1%
Decimal Number
ValueCountFrequency (%)
1 5
62.5%
4 1
 
12.5%
2 1
 
12.5%
9 1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
e 3
50.0%
m 1
 
16.7%
i 1
 
16.7%
r 1
 
16.7%
Space Separator
ValueCountFrequency (%)
13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 951
94.6%
Common 34
 
3.4%
Latin 20
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 136
 
14.3%
탁 135
 
14.2%
소 74
 
7.8%
이 23
 
2.4%
크 21
 
2.2%
사 20
 
2.1%
린 20
 
2.1%
대 15
 
1.6%
동 14
 
1.5%
라 12
 
1.3%
Other values (186) 481
50.6%
Latin
ValueCountFrequency (%)
e 3
15.0%
H 2
10.0%
C 2
10.0%
P 2
10.0%
L 2
10.0%
E 1
 
5.0%
T 1
 
5.0%
I 1
 
5.0%
V 1
 
5.0%
G 1
 
5.0%
Other values (4) 4
20.0%
Common
ValueCountFrequency (%)
13
38.2%
( 6
17.6%
) 6
17.6%
1 5
 
14.7%
- 1
 
2.9%
4 1
 
2.9%
2 1
 
2.9%
9 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 951
94.6%
ASCII 54
 
5.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 136
 
14.3%
탁 135
 
14.2%
소 74
 
7.8%
이 23
 
2.4%
크 21
 
2.2%
사 20
 
2.1%
린 20
 
2.1%
대 15
 
1.6%
동 14
 
1.5%
라 12
 
1.3%
Other values (186) 481
50.6%
ASCII
ValueCountFrequency (%)
13
24.1%
( 6
11.1%
) 6
11.1%
1 5
 
9.3%
e 3
 
5.6%
H 2
 
3.7%
C 2
 
3.7%
P 2
 
3.7%
L 2
 
3.7%
- 1
 
1.9%
Other values (12) 12
22.2%

업소 소재지
Text

Distinct182
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T03:54:32.015022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length46
Mean length32.770492
Min length9

Characters and Unicode

Total characters5997
Distinct characters232
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

Unique181 ?
Unique (%)98.9%

Sample

1st row인천광역시 서구 가정로223번길 28 (석남동, 금호어울림상가 2동 103호)
2nd row인천광역시 서구 심곡로8번길 3-9, 1층 (심곡동)
3rd row인천광역시 서구 승학로 198 (심곡동,극동늘푸른아파트상가202호)
4th row인천광역시 서구 대평로 10 (연희동,태영아파트상가104호)
5th row인천광역시 서구 탁옥로85번길 6 (심곡동,대동상가 203호)
ValueCountFrequency (%)
인천광역시 182
 
16.1%
서구 182
 
16.1%
가좌동 25
 
2.2%
1층 24
 
2.1%
석남동 22
 
1.9%
청라동 21
 
1.9%
상가동 19
 
1.7%
마전동 15
 
1.3%
가정동 13
 
1.2%
신현동 12
 
1.1%
Other values (402) 614
54.4%
2023-12-13T03:54:32.799339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
947
 
15.8%
1 276
 
4.6%
동 228
 
3.8%
서 202
 
3.4%
( 186
 
3.1%
) 186
 
3.1%
로 186
 
3.1%
인 185
 
3.1%
천 184
 
3.1%
시 183
 
3.1%
Other values (222) 3234
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3445
57.4%
Decimal Number 1026
 
17.1%
Space Separator 947
 
15.8%
Open Punctuation 186
 
3.1%
Close Punctuation 186
 
3.1%
Other Punctuation 141
 
2.4%
Dash Punctuation 37
 
0.6%
Uppercase Letter 25
 
0.4%
Lowercase Letter 2
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 228
 
6.6%
서 202
 
5.9%
로 186
 
5.4%
인 185
 
5.4%
천 184
 
5.3%
시 183
 
5.3%
광 183
 
5.3%
구 182
 
5.3%
역 182
 
5.3%
길 132
 
3.8%
Other values (189) 1598
46.4%
Uppercase Letter
ValueCountFrequency (%)
A 6
24.0%
C 3
12.0%
E 3
12.0%
K 2
 
8.0%
B 2
 
8.0%
L 2
 
8.0%
G 1
 
4.0%
W 1
 
4.0%
I 1
 
4.0%
V 1
 
4.0%
Other values (3) 3
12.0%
Decimal Number
ValueCountFrequency (%)
1 276
26.9%
2 146
14.2%
0 120
11.7%
3 108
 
10.5%
4 79
 
7.7%
7 65
 
6.3%
6 63
 
6.1%
8 60
 
5.8%
9 56
 
5.5%
5 53
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 139
98.6%
@ 1
 
0.7%
. 1
 
0.7%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
947
100.0%
Open Punctuation
ValueCountFrequency (%)
( 186
100.0%
Close Punctuation
ValueCountFrequency (%)
) 186
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3445
57.4%
Common 2525
42.1%
Latin 27
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 228
 
6.6%
서 202
 
5.9%
로 186
 
5.4%
인 185
 
5.4%
천 184
 
5.3%
시 183
 
5.3%
광 183
 
5.3%
구 182
 
5.3%
역 182
 
5.3%
길 132
 
3.8%
Other values (189) 1598
46.4%
Common
ValueCountFrequency (%)
947
37.5%
1 276
 
10.9%
( 186
 
7.4%
) 186
 
7.4%
2 146
 
5.8%
, 139
 
5.5%
0 120
 
4.8%
3 108
 
4.3%
4 79
 
3.1%
7 65
 
2.6%
Other values (9) 273
 
10.8%
Latin
ValueCountFrequency (%)
A 6
22.2%
C 3
11.1%
E 3
11.1%
K 2
 
7.4%
e 2
 
7.4%
B 2
 
7.4%
L 2
 
7.4%
G 1
 
3.7%
W 1
 
3.7%
I 1
 
3.7%
Other values (4) 4
14.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3445
57.4%
ASCII 2552
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
947
37.1%
1 276
 
10.8%
( 186
 
7.3%
) 186
 
7.3%
2 146
 
5.7%
, 139
 
5.4%
0 120
 
4.7%
3 108
 
4.2%
4 79
 
3.1%
7 65
 
2.5%
Other values (23) 300
 
11.8%
Hangul
ValueCountFrequency (%)
동 228
 
6.6%
서 202
 
5.9%
로 186
 
5.4%
인 185
 
5.4%
천 184
 
5.3%
시 183
 
5.3%
광 183
 
5.3%
구 182
 
5.3%
역 182
 
5.3%
길 132
 
3.8%
Other values (189) 1598
46.4%

소재지전화
Text

MISSING 

Distinct157
Distinct (%)99.4%
Missing25
Missing (%)13.7%
Memory size1.6 KiB
2023-12-13T03:54:33.222316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.006329
Min length12

Characters and Unicode

Total characters1897
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique156 ?
Unique (%)98.7%

Sample

1st row032-577-7061
2nd row032-887-0320
3rd row032-561-3281
4th row032-565-1429
5th row032-561-3434
ValueCountFrequency (%)
032-582-3351 2
 
1.3%
032-564-0321 1
 
0.6%
032-577-7061 1
 
0.6%
032-569-0999 1
 
0.6%
032-567-9382 1
 
0.6%
032-578-3355 1
 
0.6%
032-566-1159 1
 
0.6%
032-566-1744 1
 
0.6%
032-561-8423 1
 
0.6%
032-563-5523 1
 
0.6%
Other values (147) 147
93.0%
2023-12-13T03:54:34.004814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 316
16.7%
2 264
13.9%
3 258
13.6%
5 233
12.3%
0 222
11.7%
6 140
7.4%
7 123
 
6.5%
1 109
 
5.7%
8 86
 
4.5%
9 75
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1581
83.3%
Dash Punctuation 316
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 264
16.7%
3 258
16.3%
5 233
14.7%
0 222
14.0%
6 140
8.9%
7 123
7.8%
1 109
6.9%
8 86
 
5.4%
9 75
 
4.7%
4 71
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 316
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1897
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 316
16.7%
2 264
13.9%
3 258
13.6%
5 233
12.3%
0 222
11.7%
6 140
7.4%
7 123
 
6.5%
1 109
 
5.7%
8 86
 
4.5%
9 75
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1897
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 316
16.7%
2 264
13.9%
3 258
13.6%
5 233
12.3%
0 222
11.7%
6 140
7.4%
7 123
 
6.5%
1 109
 
5.7%
8 86
 
4.5%
9 75
 
4.0%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2023-03-30 00:00:00
Maximum2023-03-30 00:00:00
2023-12-13T03:54:34.228989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:34.420885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2023-12-13T03:54:29.920949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:54:30.069842image/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

업종명업소명업소 소재지소재지전화데이터기준일
0세탁업어울림세탁인천광역시 서구 가정로223번길 28 (석남동, 금호어울림상가 2동 103호)032-577-70612023-03-30
1세탁업대명사인천광역시 서구 심곡로8번길 3-9, 1층 (심곡동)032-887-03202023-03-30
2세탁업극동드라이크리닝인천광역시 서구 승학로 198 (심곡동,극동늘푸른아파트상가202호)032-561-32812023-03-30
3세탁업태영세탁소인천광역시 서구 대평로 10 (연희동,태영아파트상가104호)032-565-14292023-03-30
4세탁업대동세탁인천광역시 서구 탁옥로85번길 6 (심곡동,대동상가 203호)032-561-34342023-03-30
5세탁업광명세탁소인천광역시 서구 경명대로694번길 10, 제상가동 제1층 제102호 (공촌동, 경남아파트)032-565-39352023-03-30
6세탁업우성세탁소인천광역시 서구 대평로56번길 32 (연희동,우성(아)상가203호)032-564-86632023-03-30
7세탁업부성그린세탁소인천광역시 서구 도요지로227번길 20 (검암동)032-562-27612023-03-30
8세탁업현대세탁인천광역시 서구 건지로284번길 62-1 (가좌동)032-572-77252023-03-30
9세탁업뉴서울세탁소인천광역시 서구 봉오대로283번길 6 (가정동,뉴서울아파트상가101호)032-567-37872023-03-30
업종명업소명업소 소재지소재지전화데이터기준일
173세탁업운동화 손세탁 전문점인천광역시 서구 율도로83번길 1, 1층일부 (신현동)032-584-57002023-03-30
174세탁업광명사인천광역시 서구 새오개로77번길 1, 1층 일부호 (신현동)032-572-49872023-03-30
175세탁업서해세탁소인천광역시 서구 검단로487번길 43, 1동 102호 (마전동)032-563-35882023-03-30
176세탁업루원세탁마트인천광역시 서구 새오개로111번안길 26, 1층 102호 (신현동)032-572-90902023-03-30
177세탁업디엔세탁인천광역시 서구 봉오재3로 75, 115동 102호 (가정동, 루원 호반베르디움 더센트럴)032-563-27202023-03-30
178세탁업꼼꼼이크리닝인천광역시 서구 백범로604번길 35 (가좌동)<NA>2023-03-30
179세탁업코오롱세탁옷수선인천광역시 서구 청라커낼로 252, A139호 (청라동, 청라 롯데캐슬)<NA>2023-03-30
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