Overview

Dataset statistics

Number of variables4
Number of observations2292
Missing cells1160
Missing cells (%)12.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory71.8 KiB
Average record size in memory32.1 B

Variable types

Categorical1
Text3

Dataset

Description경상북도 구미시 관애의 공중위생업소 현황 데이터로 업종명, 업소명, 소재지, 전화번호 정보를 제공하고 있습니다.
Author경상북도 구미시
URLhttps://www.data.go.kr/data/15006802/fileData.do

Alerts

소재지전화 has 1160 (50.6%) missing valuesMissing

Reproduction

Analysis started2023-12-11 23:43:11.006825
Analysis finished2023-12-11 23:43:11.993627
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.0 KiB
미용업
1779 
세탁업
183 
건물위생관리업
 
160
이용업
 
129
목욕장업
 
41

Length

Max length7
Median length3
Mean length3.2971204
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 1779
77.6%
세탁업 183
 
8.0%
건물위생관리업 160
 
7.0%
이용업 129
 
5.6%
목욕장업 41
 
1.8%

Length

2023-12-12T08:43:12.074527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:43:12.187472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미용업 1779
77.6%
세탁업 183
 
8.0%
건물위생관리업 160
 
7.0%
이용업 129
 
5.6%
목욕장업 41
 
1.8%

업소명
Text

Distinct2276
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size18.0 KiB
2023-12-12T08:43:12.428600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length5.5244328
Min length1

Characters and Unicode

Total characters12662
Distinct characters625
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

Unique2261 ?
Unique (%)98.6%

Sample

1st row제이원스파랜드
2nd row해평정다운목욕탕
3rd row파크비지니스관광호텔주식회사
4th row토미짐앤스파
5th row오션월드목욕탕사우나
ValueCountFrequency (%)
한불피부관리실 4
 
0.2%
합자회사 3
 
0.1%
헤어샵 3
 
0.1%
세탁소 3
 
0.1%
헤어아트 3
 
0.1%
현대이용소 3
 
0.1%
하나미용실 2
 
0.1%
순수헤어 2
 
0.1%
탑헤어 2
 
0.1%
라보떼 2
 
0.1%
Other values (2289) 2308
98.8%
2023-12-12T08:43:12.841260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 853
 
6.7%
헤 809
 
6.4%
이 403
 
3.2%
미 352
 
2.8%
리 287
 
2.3%
스 262
 
2.1%
용 255
 
2.0%
소 218
 
1.7%
일 196
 
1.5%
네 189
 
1.5%
Other values (615) 8838
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12418
98.1%
Decimal Number 74
 
0.6%
Close Punctuation 48
 
0.4%
Open Punctuation 48
 
0.4%
Space Separator 43
 
0.3%
Uppercase Letter 16
 
0.1%
Other Punctuation 9
 
0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 853
 
6.9%
헤 809
 
6.5%
이 403
 
3.2%
미 352
 
2.8%
리 287
 
2.3%
스 262
 
2.1%
용 255
 
2.1%
소 218
 
1.8%
일 196
 
1.6%
네 189
 
1.5%
Other values (587) 8594
69.2%
Decimal Number
ValueCountFrequency (%)
2 20
27.0%
0 14
18.9%
1 13
17.6%
9 8
 
10.8%
8 6
 
8.1%
5 5
 
6.8%
4 3
 
4.1%
7 2
 
2.7%
6 2
 
2.7%
3 1
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
C 3
18.8%
S 3
18.8%
T 2
12.5%
G 2
12.5%
L 2
12.5%
P 2
12.5%
W 1
 
6.2%
O 1
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
c 2
33.3%
u 1
16.7%
b 1
16.7%
l 1
16.7%
m 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 6
66.7%
, 3
33.3%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Space Separator
ValueCountFrequency (%)
43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12418
98.1%
Common 222
 
1.8%
Latin 22
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 853
 
6.9%
헤 809
 
6.5%
이 403
 
3.2%
미 352
 
2.8%
리 287
 
2.3%
스 262
 
2.1%
용 255
 
2.1%
소 218
 
1.8%
일 196
 
1.6%
네 189
 
1.5%
Other values (587) 8594
69.2%
Common
ValueCountFrequency (%)
) 48
21.6%
( 48
21.6%
43
19.4%
2 20
9.0%
0 14
 
6.3%
1 13
 
5.9%
9 8
 
3.6%
8 6
 
2.7%
. 6
 
2.7%
5 5
 
2.3%
Other values (5) 11
 
5.0%
Latin
ValueCountFrequency (%)
C 3
13.6%
S 3
13.6%
T 2
9.1%
c 2
9.1%
G 2
9.1%
L 2
9.1%
P 2
9.1%
u 1
 
4.5%
b 1
 
4.5%
l 1
 
4.5%
Other values (3) 3
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12418
98.1%
ASCII 244
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 853
 
6.9%
헤 809
 
6.5%
이 403
 
3.2%
미 352
 
2.8%
리 287
 
2.3%
스 262
 
2.1%
용 255
 
2.1%
소 218
 
1.8%
일 196
 
1.6%
네 189
 
1.5%
Other values (587) 8594
69.2%
ASCII
ValueCountFrequency (%)
) 48
19.7%
( 48
19.7%
43
17.6%
2 20
8.2%
0 14
 
5.7%
1 13
 
5.3%
9 8
 
3.3%
8 6
 
2.5%
. 6
 
2.5%
5 5
 
2.0%
Other values (18) 33
13.5%

영업소 주소
Text

Distinct2207
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size18.0 KiB
2023-12-12T08:43:13.154621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length49
Mean length30.771815
Min length18

Characters and Unicode

Total characters70529
Distinct characters313
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2126 ?
Unique (%)92.8%

Sample

1st row경상북도 구미시 산동읍 강동로 1159-57, 주1동 지하101호
2nd row경상북도 구미시 해평면 해평시장2길 20, 1,2,3층
3rd row경상북도 구미시 금오산로 217-16, 2,7층 (남통동, 파크비지니스관광호텔)
4th row경상북도 구미시 인동35길 32 (구평동, 2층 3층)
5th row경상북도 구미시 산호대로23길 13, D동 1,2,3층 (옥계동)
ValueCountFrequency (%)
경상북도 2292
 
15.5%
구미시 2292
 
15.5%
1층 1153
 
7.8%
2층 229
 
1.6%
형곡동 212
 
1.4%
봉곡동 176
 
1.2%
원평동 173
 
1.2%
옥계동 159
 
1.1%
고아읍 150
 
1.0%
인의동 148
 
1.0%
Other values (1941) 7773
52.7%
2023-12-12T08:43:13.678880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12468
 
17.7%
1 4220
 
6.0%
동 3066
 
4.3%
상 2911
 
4.1%
구 2553
 
3.6%
도 2486
 
3.5%
미 2473
 
3.5%
시 2466
 
3.5%
북 2372
 
3.4%
경 2306
 
3.3%
Other values (303) 33208
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38856
55.1%
Space Separator 12468
 
17.7%
Decimal Number 12212
 
17.3%
Other Punctuation 2179
 
3.1%
Close Punctuation 1975
 
2.8%
Open Punctuation 1975
 
2.8%
Dash Punctuation 767
 
1.1%
Uppercase Letter 89
 
0.1%
Lowercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3066
 
7.9%
상 2911
 
7.5%
구 2553
 
6.6%
도 2486
 
6.4%
미 2473
 
6.4%
시 2466
 
6.3%
북 2372
 
6.1%
경 2306
 
5.9%
로 1950
 
5.0%
층 1625
 
4.2%
Other values (268) 14648
37.7%
Uppercase Letter
ValueCountFrequency (%)
A 40
44.9%
B 19
21.3%
C 5
 
5.6%
D 5
 
5.6%
W 2
 
2.2%
T 2
 
2.2%
I 2
 
2.2%
S 2
 
2.2%
O 2
 
2.2%
P 2
 
2.2%
Other values (6) 8
 
9.0%
Decimal Number
ValueCountFrequency (%)
1 4220
34.6%
2 1892
15.5%
3 1343
 
11.0%
0 1103
 
9.0%
4 794
 
6.5%
5 724
 
5.9%
6 612
 
5.0%
7 542
 
4.4%
8 522
 
4.3%
9 460
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 2174
99.8%
/ 3
 
0.1%
. 1
 
< 0.1%
: 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
12468
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1975
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1975
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 767
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38856
55.1%
Common 31576
44.8%
Latin 97
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3066
 
7.9%
상 2911
 
7.5%
구 2553
 
6.6%
도 2486
 
6.4%
미 2473
 
6.4%
시 2466
 
6.3%
북 2372
 
6.1%
경 2306
 
5.9%
로 1950
 
5.0%
층 1625
 
4.2%
Other values (268) 14648
37.7%
Common
ValueCountFrequency (%)
12468
39.5%
1 4220
 
13.4%
, 2174
 
6.9%
) 1975
 
6.3%
( 1975
 
6.3%
2 1892
 
6.0%
3 1343
 
4.3%
0 1103
 
3.5%
4 794
 
2.5%
- 767
 
2.4%
Other values (8) 2865
 
9.1%
Latin
ValueCountFrequency (%)
A 40
41.2%
B 19
19.6%
e 8
 
8.2%
C 5
 
5.2%
D 5
 
5.2%
W 2
 
2.1%
T 2
 
2.1%
I 2
 
2.1%
S 2
 
2.1%
O 2
 
2.1%
Other values (7) 10
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38856
55.1%
ASCII 31673
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12468
39.4%
1 4220
 
13.3%
, 2174
 
6.9%
) 1975
 
6.2%
( 1975
 
6.2%
2 1892
 
6.0%
3 1343
 
4.2%
0 1103
 
3.5%
4 794
 
2.5%
- 767
 
2.4%
Other values (25) 2962
 
9.4%
Hangul
ValueCountFrequency (%)
동 3066
 
7.9%
상 2911
 
7.5%
구 2553
 
6.6%
도 2486
 
6.4%
미 2473
 
6.4%
시 2466
 
6.3%
북 2372
 
6.1%
경 2306
 
5.9%
로 1950
 
5.0%
층 1625
 
4.2%
Other values (268) 14648
37.7%

소재지전화
Text

MISSING 

Distinct1121
Distinct (%)99.0%
Missing1160
Missing (%)50.6%
Memory size18.0 KiB
2023-12-12T08:43:13.938580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.023852
Min length11

Characters and Unicode

Total characters13611
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

Unique1110 ?
Unique (%)98.1%

Sample

1st row054-471-4777
2nd row054-451-9000
3rd row054-471-8965
4th row054-473-8819
5th row054-472-3000
ValueCountFrequency (%)
054-444-3378 2
 
0.2%
054-452-5100 2
 
0.2%
054-457-0046 2
 
0.2%
070-7777-1005 2
 
0.2%
054-474-8989 2
 
0.2%
054-444-7389 2
 
0.2%
054-451-7445 2
 
0.2%
054-454-0037 2
 
0.2%
054-461-6556 2
 
0.2%
054-472-3132 2
 
0.2%
Other values (1111) 1112
98.2%
2023-12-12T08:43:14.301745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2818
20.7%
- 2264
16.6%
5 2138
15.7%
0 1725
12.7%
7 930
 
6.8%
6 730
 
5.4%
2 678
 
5.0%
1 675
 
5.0%
3 653
 
4.8%
8 594
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11347
83.4%
Dash Punctuation 2264
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 2818
24.8%
5 2138
18.8%
0 1725
15.2%
7 930
 
8.2%
6 730
 
6.4%
2 678
 
6.0%
1 675
 
5.9%
3 653
 
5.8%
8 594
 
5.2%
9 406
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 2264
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13611
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 2818
20.7%
- 2264
16.6%
5 2138
15.7%
0 1725
12.7%
7 930
 
6.8%
6 730
 
5.4%
2 678
 
5.0%
1 675
 
5.0%
3 653
 
4.8%
8 594
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13611
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2818
20.7%
- 2264
16.6%
5 2138
15.7%
0 1725
12.7%
7 930
 
6.8%
6 730
 
5.4%
2 678
 
5.0%
1 675
 
5.0%
3 653
 
4.8%
8 594
 
4.4%

Missing values

2023-12-12T08:43:11.844347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:43:11.958314image/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

업종명업소명영업소 주소소재지전화
0목욕장업제이원스파랜드경상북도 구미시 산동읍 강동로 1159-57, 주1동 지하101호<NA>
1목욕장업해평정다운목욕탕경상북도 구미시 해평면 해평시장2길 20, 1,2,3층054-471-4777
2목욕장업파크비지니스관광호텔주식회사경상북도 구미시 금오산로 217-16, 2,7층 (남통동, 파크비지니스관광호텔)054-451-9000
3목욕장업토미짐앤스파경상북도 구미시 인동35길 32 (구평동, 2층 3층)054-471-8965
4목욕장업오션월드목욕탕사우나경상북도 구미시 산호대로23길 13, D동 1,2,3층 (옥계동)054-473-8819
5목욕장업황금스파경상북도 구미시 여헌로 14 (인의동,외5필지)054-472-3000
6목욕장업엠투피휘트니스앤스파경상북도 구미시 구미대로 4 (임은동)054-462-1231
7목욕장업발리스파테라스5경상북도 구미시 구미중앙로11길 6 (원평동,외1필지 지하1층)054-456-8248
8목욕장업(주)호텔금오산사우나경상북도 구미시 금오산로 400, 2층 (남통동)054-450-4058
9목욕장업형곡온천휘트니스경상북도 구미시 신시로7길 12-12 (형곡동,외2필지 효성주상복합 나오스빌 201,301,501호)054-457-4545
업종명업소명영업소 주소소재지전화
2282건물위생관리업(주)구미방역종합관리경상북도 구미시 송정대로 119 (송정동, 한우2차상가동 201호)054-452-3790
2283건물위생관리업(주)영덕기업경상북도 구미시 신시로6길 4 (형곡동,진흥명문빌라지하)054-455-6628
2284건물위생관리업신그린환경경상북도 구미시 형곡로38길 9-5, 정우주택17차 1층 102호 (형곡동, 정우주택17차)054-482-3294
2285건물위생관리업시민청소용역경상북도 구미시 문장로17길 6-16, 1층 (도량동)054-455-6152
2286건물위생관리업지오서브랜드(주)경상북도 구미시 3공단1로 284, 3층 (임수동, 태영빌딩)054-457-0184
2287건물위생관리업남경기업경상북도 구미시 수출대로3길 107, A동 2층 209호 (공단동)054-469-3066
2288건물위생관리업(주)명성기업경상북도 구미시 여헌로 8, 2층 (인의동)054-473-8070
2289건물위생관리업화진산업(주)경상북도 구미시 송원동로 72 (원평동,터미널상가2층1,2호)054-456-1722
2290건물위생관리업보금산업합자회사경상북도 구미시 금오시장로 13, 3층 301호 (원평동)054-455-5652
2291건물위생관리업구미크리닝경상북도 구미시 옥계2공단로 280 (구포동,구포전원상가3층7호)054-455-1452