Overview

Dataset statistics

Number of variables4
Number of observations508
Missing cells50
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.0 KiB
Average record size in memory32.3 B

Variable types

Categorical1
Text3

Dataset

Description수성구 공중위생업 현황(2018.08.01. 기준)
Author대구광역시 수성구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15054678&dataSetDetailId=150546782e94f536ca8f3&provdMethod=FILE

Alerts

소재지전화 has 50 (9.8%) missing valuesMissing

Reproduction

Analysis started2024-04-17 11:54:16.010812
Analysis finished2024-04-17 11:54:16.407205
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
세탁업
270 
건물위생관리업
98 
숙박업(일반)
82 
목욕장업
57 
숙박업(생활)
 
1

Length

Max length7
Median length3
Mean length4.5374016
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
세탁업 270
53.1%
건물위생관리업 98
 
19.3%
숙박업(일반) 82
 
16.1%
목욕장업 57
 
11.2%
숙박업(생활) 1
 
0.2%

Length

2024-04-17T20:54:16.466767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:54:16.555180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세탁업 270
53.1%
건물위생관리업 98
 
19.3%
숙박업(일반 82
 
16.1%
목욕장업 57
 
11.2%
숙박업(생활 1
 
0.2%

업소명
Text

Distinct476
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-04-17T20:54:16.787049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length16
Mean length5.8661417
Min length1

Characters and Unicode

Total characters2980
Distinct characters355
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

Unique451 ?
Unique (%)88.8%

Sample

1st row호텔아리아나
2nd row오렌지모텔
3rd row(주)대구그랜드호텔
4th row송림장
5th row유림여관
ValueCountFrequency (%)
주 6
 
1.1%
주식회사 4
 
0.8%
경북세탁소 4
 
0.8%
한일세탁소 3
 
0.6%
보성크리닝 3
 
0.6%
월드명품세탁 3
 
0.6%
보성세탁소 3
 
0.6%
우방세탁소 3
 
0.6%
화성세탁소 2
 
0.4%
제일세탁소 2
 
0.4%
Other values (478) 495
93.8%
2024-04-17T20:54:17.120862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 218
 
7.3%
탁 209
 
7.0%
소 150
 
5.0%
( 80
 
2.7%
) 80
 
2.7%
주 79
 
2.7%
리 73
 
2.4%
크 65
 
2.2%
성 61
 
2.0%
스 57
 
1.9%
Other values (345) 1908
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2700
90.6%
Open Punctuation 80
 
2.7%
Close Punctuation 80
 
2.7%
Uppercase Letter 67
 
2.2%
Space Separator 22
 
0.7%
Decimal Number 14
 
0.5%
Lowercase Letter 8
 
0.3%
Other Punctuation 6
 
0.2%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 218
 
8.1%
탁 209
 
7.7%
소 150
 
5.6%
주 79
 
2.9%
리 73
 
2.7%
크 65
 
2.4%
성 61
 
2.3%
스 57
 
2.1%
텔 54
 
2.0%
닝 46
 
1.7%
Other values (307) 1688
62.5%
Uppercase Letter
ValueCountFrequency (%)
S 8
 
11.9%
M 6
 
9.0%
K 5
 
7.5%
O 5
 
7.5%
T 5
 
7.5%
E 4
 
6.0%
U 4
 
6.0%
I 3
 
4.5%
L 3
 
4.5%
J 3
 
4.5%
Other values (10) 21
31.3%
Decimal Number
ValueCountFrequency (%)
2 6
42.9%
3 3
21.4%
4 2
 
14.3%
1 1
 
7.1%
6 1
 
7.1%
5 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
o 2
25.0%
h 1
12.5%
s 1
12.5%
g 1
12.5%
u 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 5
83.3%
& 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2700
90.6%
Common 205
 
6.9%
Latin 75
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 218
 
8.1%
탁 209
 
7.7%
소 150
 
5.6%
주 79
 
2.9%
리 73
 
2.7%
크 65
 
2.4%
성 61
 
2.3%
스 57
 
2.1%
텔 54
 
2.0%
닝 46
 
1.7%
Other values (307) 1688
62.5%
Latin
ValueCountFrequency (%)
S 8
 
10.7%
M 6
 
8.0%
K 5
 
6.7%
O 5
 
6.7%
T 5
 
6.7%
E 4
 
5.3%
U 4
 
5.3%
I 3
 
4.0%
L 3
 
4.0%
J 3
 
4.0%
Other values (16) 29
38.7%
Common
ValueCountFrequency (%)
( 80
39.0%
) 80
39.0%
22
 
10.7%
2 6
 
2.9%
. 5
 
2.4%
- 3
 
1.5%
3 3
 
1.5%
4 2
 
1.0%
1 1
 
0.5%
& 1
 
0.5%
Other values (2) 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2700
90.6%
ASCII 280
 
9.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 218
 
8.1%
탁 209
 
7.7%
소 150
 
5.6%
주 79
 
2.9%
리 73
 
2.7%
크 65
 
2.4%
성 61
 
2.3%
스 57
 
2.1%
텔 54
 
2.0%
닝 46
 
1.7%
Other values (307) 1688
62.5%
ASCII
ValueCountFrequency (%)
( 80
28.6%
) 80
28.6%
22
 
7.9%
S 8
 
2.9%
M 6
 
2.1%
2 6
 
2.1%
K 5
 
1.8%
. 5
 
1.8%
O 5
 
1.8%
T 5
 
1.8%
Other values (28) 58
20.7%

업소소재지(도로명)
Text

Distinct499
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-04-17T20:54:17.391005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length49
Mean length29.385827
Min length20

Characters and Unicode

Total characters14928
Distinct characters195
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

Unique490 ?
Unique (%)96.5%

Sample

1st row대구광역시 수성구 동대구로 27 (두산동)
2nd row대구광역시 수성구 용학로25길 14 (두산동)
3rd row대구광역시 수성구 동대구로 305 (범어동)
4th row대구광역시 수성구 수성로 4 (상동)
5th row대구광역시 수성구 신천동로 268-1 (중동)
ValueCountFrequency (%)
대구광역시 508
 
17.1%
수성구 508
 
17.1%
만촌동 62
 
2.1%
범어동 61
 
2.1%
지산동 61
 
2.1%
황금동 54
 
1.8%
두산동 53
 
1.8%
상가동 34
 
1.1%
상동 27
 
0.9%
중동 26
 
0.9%
Other values (682) 1580
53.1%
2024-04-17T20:54:17.773938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2643
17.7%
구 1126
 
7.5%
동 711
 
4.8%
수 680
 
4.6%
성 636
 
4.3%
대 615
 
4.1%
시 550
 
3.7%
1 527
 
3.5%
( 523
 
3.5%
) 523
 
3.5%
Other values (185) 6394
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8707
58.3%
Space Separator 2643
 
17.7%
Decimal Number 2435
 
16.3%
Open Punctuation 523
 
3.5%
Close Punctuation 523
 
3.5%
Dash Punctuation 79
 
0.5%
Uppercase Letter 16
 
0.1%
Math Symbol 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1126
12.9%
동 711
 
8.2%
수 680
 
7.8%
성 636
 
7.3%
대 615
 
7.1%
시 550
 
6.3%
역 508
 
5.8%
광 508
 
5.8%
로 504
 
5.8%
길 271
 
3.1%
Other values (163) 2598
29.8%
Decimal Number
ValueCountFrequency (%)
1 527
21.6%
2 404
16.6%
3 268
11.0%
0 247
10.1%
4 224
9.2%
6 214
8.8%
5 198
 
8.1%
7 151
 
6.2%
8 103
 
4.2%
9 99
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 8
50.0%
D 2
 
12.5%
S 2
 
12.5%
K 2
 
12.5%
C 1
 
6.2%
E 1
 
6.2%
Space Separator
ValueCountFrequency (%)
2643
100.0%
Open Punctuation
ValueCountFrequency (%)
( 523
100.0%
Close Punctuation
ValueCountFrequency (%)
) 523
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8707
58.3%
Common 6204
41.6%
Latin 17
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1126
12.9%
동 711
 
8.2%
수 680
 
7.8%
성 636
 
7.3%
대 615
 
7.1%
시 550
 
6.3%
역 508
 
5.8%
광 508
 
5.8%
로 504
 
5.8%
길 271
 
3.1%
Other values (163) 2598
29.8%
Common
ValueCountFrequency (%)
2643
42.6%
1 527
 
8.5%
( 523
 
8.4%
) 523
 
8.4%
2 404
 
6.5%
3 268
 
4.3%
0 247
 
4.0%
4 224
 
3.6%
6 214
 
3.4%
5 198
 
3.2%
Other values (5) 433
 
7.0%
Latin
ValueCountFrequency (%)
B 8
47.1%
D 2
 
11.8%
S 2
 
11.8%
K 2
 
11.8%
C 1
 
5.9%
E 1
 
5.9%
e 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8707
58.3%
ASCII 6221
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2643
42.5%
1 527
 
8.5%
( 523
 
8.4%
) 523
 
8.4%
2 404
 
6.5%
3 268
 
4.3%
0 247
 
4.0%
4 224
 
3.6%
6 214
 
3.4%
5 198
 
3.2%
Other values (12) 450
 
7.2%
Hangul
ValueCountFrequency (%)
구 1126
12.9%
동 711
 
8.2%
수 680
 
7.8%
성 636
 
7.3%
대 615
 
7.1%
시 550
 
6.3%
역 508
 
5.8%
광 508
 
5.8%
로 504
 
5.8%
길 271
 
3.1%
Other values (163) 2598
29.8%

소재지전화
Text

MISSING 

Distinct453
Distinct (%)98.9%
Missing50
Missing (%)9.8%
Memory size4.1 KiB
2024-04-17T20:54:17.994249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.008734
Min length12

Characters and Unicode

Total characters5500
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

Unique448 ?
Unique (%)97.8%

Sample

1st row053-765-7776
2nd row053-765-3888
3rd row053-742-0001
4th row053-768-6662
5th row053-763-4657
ValueCountFrequency (%)
053-742-0001 2
 
0.4%
053-765-3888 2
 
0.4%
053-781-1000 2
 
0.4%
053-765-2003 2
 
0.4%
053-763-7311 2
 
0.4%
053-744-2898 1
 
0.2%
053-954-7707 1
 
0.2%
053-742-1530 1
 
0.2%
053-791-0943 1
 
0.2%
053-746-1777 1
 
0.2%
Other values (443) 443
96.7%
2024-04-17T20:54:18.318806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 916
16.7%
5 750
13.6%
0 739
13.4%
3 693
12.6%
7 649
11.8%
6 387
7.0%
8 303
 
5.5%
4 299
 
5.4%
2 278
 
5.1%
1 277
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4584
83.3%
Dash Punctuation 916
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 750
16.4%
0 739
16.1%
3 693
15.1%
7 649
14.2%
6 387
8.4%
8 303
6.6%
4 299
 
6.5%
2 278
 
6.1%
1 277
 
6.0%
9 209
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 916
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 916
16.7%
5 750
13.6%
0 739
13.4%
3 693
12.6%
7 649
11.8%
6 387
7.0%
8 303
 
5.5%
4 299
 
5.4%
2 278
 
5.1%
1 277
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 916
16.7%
5 750
13.6%
0 739
13.4%
3 693
12.6%
7 649
11.8%
6 387
7.0%
8 303
 
5.5%
4 299
 
5.4%
2 278
 
5.1%
1 277
 
5.0%

Missing values

2024-04-17T20:54:16.316869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T20:54:16.381245image/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

업종명업소명업소소재지(도로명)소재지전화
0숙박업(일반)호텔아리아나대구광역시 수성구 동대구로 27 (두산동)053-765-7776
1숙박업(일반)오렌지모텔대구광역시 수성구 용학로25길 14 (두산동)053-765-3888
2숙박업(일반)(주)대구그랜드호텔대구광역시 수성구 동대구로 305 (범어동)053-742-0001
3숙박업(일반)송림장대구광역시 수성구 수성로 4 (상동)053-768-6662
4숙박업(일반)유림여관대구광역시 수성구 신천동로 268-1 (중동)053-763-4657
5숙박업(일반)리버사이드모텔대구광역시 수성구 신천동로 34 (상동)053-764-0466
6숙박업(일반)더썸모텔대구광역시 수성구 용학로 141 (두산동)053-782-8500
7숙박업(일반)보잉호텔수성대구광역시 수성구 희망로 221 (황금동)053-764-1155
8숙박업(일반)원빈장대구광역시 수성구 화랑로 202 (만촌동)053-954-9945
9숙박업(일반)석경탕여관대구광역시 수성구 수성로 224 (중동)053-765-2003
업종명업소명업소소재지(도로명)소재지전화
498건물위생관리업고려종합개발(주)대구광역시 수성구 청수로 108 퍼플하임수성 501호 (두산동)<NA>
499건물위생관리업대성안전산업대구광역시 수성구 파동로 197 2층 (파동)053-766-9900
500건물위생관리업(주)스쿨에스지대구광역시 수성구 동대구로 167 3층 (황금동)053-765-0577
501건물위생관리업이브클린대구광역시 수성구 수성로64길 38 (수성동2가)<NA>
502건물위생관리업주식회사맑은공기대구광역시 수성구 용학로46길 40 상가1동 1층 3호 (지산동 지산호반맨션)053-783-5501
503건물위생관리업달구벌청소용역대구광역시 수성구 파동로 208 1층 (파동)<NA>
504건물위생관리업(주)두희이앤씨대구광역시 수성구 만촌로 157 2층 (만촌동)<NA>
505건물위생관리업주식회사 브라이트지엔에스대구광역시 수성구 청수로45길 41 상가동 201호 (황금동 황금3주공아파트)<NA>
506건물위생관리업나노바스대구광역시 수성구 달구벌대로627길 22-3 1층 (매호동)<NA>
507숙박업(생활)퀸즈텔대구광역시 수성구 청수로26길 56 (두산동)053-763-4266