Overview

Dataset statistics

Number of variables5
Number of observations866
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.0 KiB
Average record size in memory40.2 B

Variable types

Text4
DateTime1

Dataset

Description경상북도 포항시에 등록된 전문건설업체 현황으로 건설업체 명칭과 영업소소재지(도로명주소), 연락처, 대표자이름 데이터 제공일자 등을 제공함.
Author경상북도 포항시
URLhttps://www.data.go.kr/data/15112957/fileData.do

Alerts

데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2024-04-21 02:16:18.359432
Analysis finished2024-04-21 02:16:19.276600
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건설업체명
Text

Distinct864
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2024-04-21T11:16:19.466154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length14
Mean length7.2448037
Min length4

Characters and Unicode

Total characters6274
Distinct characters319
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique862 ?
Unique (%)99.5%

Sample

1st row(유)신영산업
2nd row(유)재복건설
3rd row(유)포항수도공업사
4th row(자)문화수도공업사
5th row(주)MK기업
ValueCountFrequency (%)
현대가스설비 2
 
0.2%
태성설비 2
 
0.2%
상생건설(주 1
 
0.1%
성동설비공사 1
 
0.1%
서림로재 1
 
0.1%
삼안건설(주 1
 
0.1%
삼양기초건설(주 1
 
0.1%
삼양산업(주 1
 
0.1%
삼우도장산업(주 1
 
0.1%
삼윤건설(주 1
 
0.1%
Other values (854) 854
98.6%
2024-04-21T11:16:19.850045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 698
 
11.1%
( 616
 
9.8%
) 616
 
9.8%
설 285
 
4.5%
건 255
 
4.1%
이 142
 
2.3%
스 124
 
2.0%
사 97
 
1.5%
업 96
 
1.5%
경 89
 
1.4%
Other values (309) 3256
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4985
79.5%
Open Punctuation 616
 
9.8%
Close Punctuation 616
 
9.8%
Uppercase Letter 40
 
0.6%
Other Punctuation 6
 
0.1%
Lowercase Letter 6
 
0.1%
Decimal Number 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 698
 
14.0%
설 285
 
5.7%
건 255
 
5.1%
이 142
 
2.8%
스 124
 
2.5%
사 97
 
1.9%
업 96
 
1.9%
경 89
 
1.8%
에 83
 
1.7%
비 82
 
1.6%
Other values (283) 3034
60.9%
Uppercase Letter
ValueCountFrequency (%)
E 8
20.0%
N 8
20.0%
G 7
17.5%
S 6
15.0%
H 2
 
5.0%
K 2
 
5.0%
B 2
 
5.0%
C 2
 
5.0%
L 1
 
2.5%
T 1
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
c 1
16.7%
d 1
16.7%
t 1
16.7%
o 1
16.7%
h 1
16.7%
e 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3
50.0%
& 1
 
16.7%
， 1
 
16.7%
, 1
 
16.7%
Decimal Number
ValueCountFrequency (%)
1 3
60.0%
3 1
 
20.0%
9 1
 
20.0%
Open Punctuation
ValueCountFrequency (%)
( 616
100.0%
Close Punctuation
ValueCountFrequency (%)
) 616
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4985
79.5%
Common 1243
 
19.8%
Latin 46
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 698
 
14.0%
설 285
 
5.7%
건 255
 
5.1%
이 142
 
2.8%
스 124
 
2.5%
사 97
 
1.9%
업 96
 
1.9%
경 89
 
1.8%
에 83
 
1.7%
비 82
 
1.6%
Other values (283) 3034
60.9%
Latin
ValueCountFrequency (%)
E 8
17.4%
N 8
17.4%
G 7
15.2%
S 6
13.0%
H 2
 
4.3%
K 2
 
4.3%
B 2
 
4.3%
C 2
 
4.3%
c 1
 
2.2%
d 1
 
2.2%
Other values (7) 7
15.2%
Common
ValueCountFrequency (%)
( 616
49.6%
) 616
49.6%
1 3
 
0.2%
. 3
 
0.2%
3 1
 
0.1%
& 1
 
0.1%
， 1
 
0.1%
, 1
 
0.1%
9 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4985
79.5%
ASCII 1288
 
20.5%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 698
 
14.0%
설 285
 
5.7%
건 255
 
5.1%
이 142
 
2.8%
스 124
 
2.5%
사 97
 
1.9%
업 96
 
1.9%
경 89
 
1.8%
에 83
 
1.7%
비 82
 
1.6%
Other values (283) 3034
60.9%
ASCII
ValueCountFrequency (%)
( 616
47.8%
) 616
47.8%
E 8
 
0.6%
N 8
 
0.6%
G 7
 
0.5%
S 6
 
0.5%
1 3
 
0.2%
. 3
 
0.2%
H 2
 
0.2%
K 2
 
0.2%
Other values (15) 17
 
1.3%
None
ValueCountFrequency (%)
， 1
100.0%

소재시 도로명주소
Text

Distinct829
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2024-04-21T11:16:20.121454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length45
Mean length28.598152
Min length19

Characters and Unicode

Total characters24766
Distinct characters208
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique800 ?
Unique (%)92.4%

Sample

1st row경상북도 포항시 남구 중앙로 22 (해도동)
2nd row경상북도 포항시 북구 용당로 60 , 201호 (용흥동)
3rd row경상북도 포항시 북구 법원로63번길 19-7 (장성동)
4th row경상북도 포항시 남구 중흥로152번길 25-2 (상도동)
5th row경상북도 포항시 남구 대송면 제내길31번길 7-1
ValueCountFrequency (%)
포항시 866
 
15.6%
경상북도 852
 
15.3%
남구 491
 
8.8%
북구 375
 
6.7%
2층 84
 
1.5%
장성동 84
 
1.5%
연일읍 80
 
1.4%
흥해읍 73
 
1.3%
오천읍 62
 
1.1%
해도동 53
 
1.0%
Other values (1028) 2543
45.7%
2024-04-21T11:16:20.593289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4697
19.0%
북 1243
 
5.0%
도 1097
 
4.4%
상 958
 
3.9%
1 911
 
3.7%
포 891
 
3.6%
구 886
 
3.6%
항 879
 
3.5%
시 868
 
3.5%
경 866
 
3.5%
Other values (198) 11470
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14705
59.4%
Space Separator 4697
 
19.0%
Decimal Number 3786
 
15.3%
Open Punctuation 581
 
2.3%
Close Punctuation 581
 
2.3%
Dash Punctuation 274
 
1.1%
Other Punctuation 133
 
0.5%
Uppercase Letter 8
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 1243
 
8.5%
도 1097
 
7.5%
상 958
 
6.5%
포 891
 
6.1%
구 886
 
6.0%
항 879
 
6.0%
시 868
 
5.9%
경 866
 
5.9%
로 757
 
5.1%
동 679
 
4.6%
Other values (178) 5581
38.0%
Decimal Number
ValueCountFrequency (%)
1 911
24.1%
2 627
16.6%
3 367
9.7%
4 334
 
8.8%
0 304
 
8.0%
5 285
 
7.5%
7 260
 
6.9%
8 244
 
6.4%
6 240
 
6.3%
9 214
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 119
89.5%
， 13
 
9.8%
. 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
A 4
50.0%
B 4
50.0%
Space Separator
ValueCountFrequency (%)
4697
100.0%
Open Punctuation
ValueCountFrequency (%)
( 581
100.0%
Close Punctuation
ValueCountFrequency (%)
) 581
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 274
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14705
59.4%
Common 10052
40.6%
Latin 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 1243
 
8.5%
도 1097
 
7.5%
상 958
 
6.5%
포 891
 
6.1%
구 886
 
6.0%
항 879
 
6.0%
시 868
 
5.9%
경 866
 
5.9%
로 757
 
5.1%
동 679
 
4.6%
Other values (178) 5581
38.0%
Common
ValueCountFrequency (%)
4697
46.7%
1 911
 
9.1%
2 627
 
6.2%
( 581
 
5.8%
) 581
 
5.8%
3 367
 
3.7%
4 334
 
3.3%
0 304
 
3.0%
5 285
 
2.8%
- 274
 
2.7%
Other values (7) 1091
 
10.9%
Latin
ValueCountFrequency (%)
A 4
44.4%
B 4
44.4%
b 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14705
59.4%
ASCII 10048
40.6%
None 13
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4697
46.7%
1 911
 
9.1%
2 627
 
6.2%
( 581
 
5.8%
) 581
 
5.8%
3 367
 
3.7%
4 334
 
3.3%
0 304
 
3.0%
5 285
 
2.8%
- 274
 
2.7%
Other values (9) 1087
 
10.8%
Hangul
ValueCountFrequency (%)
북 1243
 
8.5%
도 1097
 
7.5%
상 958
 
6.5%
포 891
 
6.1%
구 886
 
6.0%
항 879
 
6.0%
시 868
 
5.9%
경 866
 
5.9%
로 757
 
5.1%
동 679
 
4.6%
Other values (178) 5581
38.0%
None
ValueCountFrequency (%)
， 13
100.0%

대표전화번호
Text

Distinct829
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2024-04-21T11:16:20.868445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.045035
Min length11

Characters and Unicode

Total characters10431
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

Unique810 ?
Unique (%)93.5%

Sample

1st row054-275-7707
2nd row054-283-6642
3rd row054-252-6221
4th row054-277-2459
5th row054-255-0038
ValueCountFrequency (%)
000-0000-0000 18
 
2.1%
054-249-6000 3
 
0.3%
054-000-0000 3
 
0.3%
054-255-3301 2
 
0.2%
054-614-6161 2
 
0.2%
054-242-0445 2
 
0.2%
054-272-0443 2
 
0.2%
054-284-4249 2
 
0.2%
054-255-6604 2
 
0.2%
054-252-6297 2
 
0.2%
Other values (819) 828
95.6%
2024-04-21T11:16:21.278050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1732
16.6%
0 1648
15.8%
4 1360
13.0%
5 1344
12.9%
2 1287
12.3%
7 686
 
6.6%
8 575
 
5.5%
1 542
 
5.2%
3 483
 
4.6%
6 435
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8699
83.4%
Dash Punctuation 1732
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1648
18.9%
4 1360
15.6%
5 1344
15.5%
2 1287
14.8%
7 686
7.9%
8 575
 
6.6%
1 542
 
6.2%
3 483
 
5.6%
6 435
 
5.0%
9 339
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 1732
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10431
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1732
16.6%
0 1648
15.8%
4 1360
13.0%
5 1344
12.9%
2 1287
12.3%
7 686
 
6.6%
8 575
 
5.5%
1 542
 
5.2%
3 483
 
4.6%
6 435
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10431
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1732
16.6%
0 1648
15.8%
4 1360
13.0%
5 1344
12.9%
2 1287
12.3%
7 686
 
6.6%
8 575
 
5.5%
1 542
 
5.2%
3 483
 
4.6%
6 435
 
4.2%

대표자
Text

Distinct831
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2024-04-21T11:16:21.563872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length3
Mean length3.1709007
Min length2

Characters and Unicode

Total characters2746
Distinct characters207
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique797 ?
Unique (%)92.0%

Sample

1st row김주연
2nd row박준정
3rd row신수원
4th row신종복
5th row이종민
ValueCountFrequency (%)
최윤정 3
 
0.3%
김정태 2
 
0.2%
신현철 2
 
0.2%
박동규 2
 
0.2%
김영기 2
 
0.2%
김수인 2
 
0.2%
김성원 2
 
0.2%
황가원 2
 
0.2%
이정훈 2
 
0.2%
권세진 2
 
0.2%
Other values (821) 845
97.6%
2024-04-21T11:16:22.005979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 205
 
7.5%
이 156
 
5.7%
정 101
 
3.7%
상 68
 
2.5%
영 66
 
2.4%
박 64
 
2.3%
진 58
 
2.1%
최 57
 
2.1%
호 55
 
2.0%
수 52
 
1.9%
Other values (197) 1864
67.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2706
98.5%
Other Punctuation 37
 
1.3%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 205
 
7.6%
이 156
 
5.8%
정 101
 
3.7%
상 68
 
2.5%
영 66
 
2.4%
박 64
 
2.4%
진 58
 
2.1%
최 57
 
2.1%
호 55
 
2.0%
수 52
 
1.9%
Other values (192) 1824
67.4%
Other Punctuation
ValueCountFrequency (%)
, 35
94.6%
， 2
 
5.4%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2706
98.5%
Common 40
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 205
 
7.6%
이 156
 
5.8%
정 101
 
3.7%
상 68
 
2.5%
영 66
 
2.4%
박 64
 
2.4%
진 58
 
2.1%
최 57
 
2.1%
호 55
 
2.0%
수 52
 
1.9%
Other values (192) 1824
67.4%
Common
ValueCountFrequency (%)
, 35
87.5%
， 2
 
5.0%
) 1
 
2.5%
( 1
 
2.5%
2 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2706
98.5%
ASCII 38
 
1.4%
None 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 205
 
7.6%
이 156
 
5.8%
정 101
 
3.7%
상 68
 
2.5%
영 66
 
2.4%
박 64
 
2.4%
진 58
 
2.1%
최 57
 
2.1%
호 55
 
2.0%
수 52
 
1.9%
Other values (192) 1824
67.4%
ASCII
ValueCountFrequency (%)
, 35
92.1%
) 1
 
2.6%
( 1
 
2.6%
2 1
 
2.6%
None
ValueCountFrequency (%)
， 2
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
Minimum2024-04-05 00:00:00
Maximum2024-04-05 00:00:00
2024-04-21T11:16:22.121550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:16:22.216608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-04-21T11:16:19.118981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:16:19.227394image/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

건설업체명소재시 도로명주소대표전화번호대표자데이터기준일자
0(유)신영산업경상북도 포항시 남구 중앙로 22 (해도동)054-275-7707김주연2024-04-05
1(유)재복건설경상북도 포항시 북구 용당로 60 , 201호 (용흥동)054-283-6642박준정2024-04-05
2(유)포항수도공업사경상북도 포항시 북구 법원로63번길 19-7 (장성동)054-252-6221신수원2024-04-05
3(자)문화수도공업사경상북도 포항시 남구 중흥로152번길 25-2 (상도동)054-277-2459신종복2024-04-05
4(주)MK기업경상북도 포항시 남구 대송면 제내길31번길 7-1054-255-0038이종민2024-04-05
5(주)SH건설경상북도 포항시 북구 삼호로 135 (항구동)054-254-0766황기조2024-04-05
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