Overview

Dataset statistics

Number of variables5
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory43.7 B

Variable types

Text3
Categorical2

Dataset

Description충청남도 논산시 직업소개소 현황 데이터로 요금, 소개소명, 구분, 행정구역, 사업소주소 정보를 제공하고 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=387&beforeMenuCd=DOM_000000201001001000&publicdatapk=15028911

Alerts

요금 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 요금High correlation
요금 is highly imbalanced (69.0%)Imbalance
업소명 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:40:57.142591
Analysis finished2024-01-09 20:40:57.486523
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-01-10T05:40:57.621616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.0833333
Min length4

Characters and Unicode

Total characters219
Distinct characters79
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st rowOK인력공사
2nd row가가인력공사
3rd row가나인력
4th row강경인력장묘사
5th row거성인력공사
ValueCountFrequency (%)
ok인력공사 1
 
2.8%
가가인력공사 1
 
2.8%
우리인력개발 1
 
2.8%
미래직업소개소 1
 
2.8%
성원인력 1
 
2.8%
성일인력용역 1
 
2.8%
성지드림빌보람의집 1
 
2.8%
영진인력 1
 
2.8%
예스민종합인력공사 1
 
2.8%
일진인력 1
 
2.8%
Other values (26) 26
72.2%
2024-01-10T05:40:57.972358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 30
 
13.7%
력 30
 
13.7%
사 14
 
6.4%
공 13
 
5.9%
소 9
 
4.1%
성 9
 
4.1%
업 7
 
3.2%
개 5
 
2.3%
산 4
 
1.8%
직 4
 
1.8%
Other values (69) 94
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 217
99.1%
Uppercase Letter 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 30
 
13.8%
력 30
 
13.8%
사 14
 
6.5%
공 13
 
6.0%
소 9
 
4.1%
성 9
 
4.1%
업 7
 
3.2%
개 5
 
2.3%
산 4
 
1.8%
직 4
 
1.8%
Other values (67) 92
42.4%
Uppercase Letter
ValueCountFrequency (%)
O 1
50.0%
K 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 217
99.1%
Latin 2
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 30
 
13.8%
력 30
 
13.8%
사 14
 
6.5%
공 13
 
6.0%
소 9
 
4.1%
성 9
 
4.1%
업 7
 
3.2%
개 5
 
2.3%
산 4
 
1.8%
직 4
 
1.8%
Other values (67) 92
42.4%
Latin
ValueCountFrequency (%)
O 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 217
99.1%
ASCII 2
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 30
 
13.8%
력 30
 
13.8%
사 14
 
6.5%
공 13
 
6.0%
소 9
 
4.1%
성 9
 
4.1%
업 7
 
3.2%
개 5
 
2.3%
산 4
 
1.8%
직 4
 
1.8%
Other values (67) 92
42.4%
ASCII
ValueCountFrequency (%)
O 1
50.0%
K 1
50.0%

요금
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
유료
34 
무료
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유료 34
94.4%
무료 2
 
5.6%

Length

2024-01-10T05:40:58.102880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:40:58.208102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 34
94.4%
무료 2
 
5.6%

행정동
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size420.0 B
취암동
20 
연무읍
7 
부창동
5 
강경읍
3 
연산면
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row부창동
2nd row부창동
3rd row강경읍
4th row강경읍
5th row취암동

Common Values

ValueCountFrequency (%)
취암동 20
55.6%
연무읍 7
 
19.4%
부창동 5
 
13.9%
강경읍 3
 
8.3%
연산면 1
 
2.8%

Length

2024-01-10T05:40:58.306299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:40:58.412491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취암동 20
55.6%
연무읍 7
 
19.4%
부창동 5
 
13.9%
강경읍 3
 
8.3%
연산면 1
 
2.8%

소재지도로명주소
Text

Distinct34
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-01-10T05:40:58.585612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length18.222222
Min length16

Characters and Unicode

Total characters656
Distinct characters46
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)88.9%

Sample

1st row충청남도 논산시 계백로 959-1
2nd row충청남도 논산시 계백로 960
3rd row충청남도 논산시 강경읍 옥녀봉로 12
4th row충청남도 논산시 강경읍 계백로72번길 1
5th row충청남도 논산시 논산대로 539
ValueCountFrequency (%)
충청남도 36
23.2%
논산시 36
23.2%
계백로 9
 
5.8%
연무읍 7
 
4.5%
안심로 6
 
3.9%
해월로 5
 
3.2%
관촉로 4
 
2.6%
강경읍 3
 
1.9%
219 2
 
1.3%
관촉로277번길 2
 
1.3%
Other values (44) 45
29.0%
2024-01-10T05:40:58.907509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
18.1%
산 38
 
5.8%
논 37
 
5.6%
시 37
 
5.6%
충 36
 
5.5%
남 36
 
5.5%
도 36
 
5.5%
청 36
 
5.5%
로 35
 
5.3%
1 24
 
3.7%
Other values (36) 222
33.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 405
61.7%
Decimal Number 124
 
18.9%
Space Separator 119
 
18.1%
Dash Punctuation 8
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 38
9.4%
논 37
 
9.1%
시 37
 
9.1%
충 36
 
8.9%
남 36
 
8.9%
도 36
 
8.9%
청 36
 
8.9%
로 35
 
8.6%
계 10
 
2.5%
백 10
 
2.5%
Other values (24) 94
23.2%
Decimal Number
ValueCountFrequency (%)
1 24
19.4%
2 20
16.1%
9 15
12.1%
0 13
10.5%
7 11
8.9%
4 11
8.9%
3 9
 
7.3%
5 9
 
7.3%
6 7
 
5.6%
8 5
 
4.0%
Space Separator
ValueCountFrequency (%)
119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 405
61.7%
Common 251
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 38
9.4%
논 37
 
9.1%
시 37
 
9.1%
충 36
 
8.9%
남 36
 
8.9%
도 36
 
8.9%
청 36
 
8.9%
로 35
 
8.6%
계 10
 
2.5%
백 10
 
2.5%
Other values (24) 94
23.2%
Common
ValueCountFrequency (%)
119
47.4%
1 24
 
9.6%
2 20
 
8.0%
9 15
 
6.0%
0 13
 
5.2%
7 11
 
4.4%
4 11
 
4.4%
3 9
 
3.6%
5 9
 
3.6%
- 8
 
3.2%
Other values (2) 12
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 405
61.7%
ASCII 251
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
119
47.4%
1 24
 
9.6%
2 20
 
8.0%
9 15
 
6.0%
0 13
 
5.2%
7 11
 
4.4%
4 11
 
4.4%
3 9
 
3.6%
5 9
 
3.6%
- 8
 
3.2%
Other values (2) 12
 
4.8%
Hangul
ValueCountFrequency (%)
산 38
9.4%
논 37
 
9.1%
시 37
 
9.1%
충 36
 
8.9%
남 36
 
8.9%
도 36
 
8.9%
청 36
 
8.9%
로 35
 
8.6%
계 10
 
2.5%
백 10
 
2.5%
Other values (24) 94
23.2%

소재지지번주소
Text

Distinct34
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-01-10T05:40:59.098415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length19.583333
Min length16

Characters and Unicode

Total characters705
Distinct characters46
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)88.9%

Sample

1st row충청남도 논산시 부창동 22-1
2nd row충청남도 논산시 부창동 24-5
3rd row충청남도 논산시 강경읍 중앙리 164-1
4th row충청남도 논산시 강경읍 채산리 552-19
5th row충청남도 논산시 지산동 274-1
ValueCountFrequency (%)
충청남도 36
23.2%
논산시 36
23.2%
취암동 11
 
7.1%
연무읍 7
 
4.5%
화지동 5
 
3.2%
안심리 4
 
2.6%
부창동 3
 
1.9%
강경읍 3
 
1.9%
반월동 3
 
1.9%
대교동 2
 
1.3%
Other values (42) 45
29.0%
2024-01-10T05:40:59.424820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
16.9%
산 42
 
6.0%
1 38
 
5.4%
충 36
 
5.1%
시 36
 
5.1%
청 36
 
5.1%
논 36
 
5.1%
남 36
 
5.1%
도 36
 
5.1%
- 35
 
5.0%
Other values (36) 255
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 393
55.7%
Decimal Number 158
22.4%
Space Separator 119
 
16.9%
Dash Punctuation 35
 
5.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 42
10.7%
충 36
9.2%
시 36
9.2%
청 36
9.2%
논 36
9.2%
남 36
9.2%
도 36
9.2%
동 27
 
6.9%
취 11
 
2.8%
리 11
 
2.8%
Other values (24) 86
21.9%
Decimal Number
ValueCountFrequency (%)
1 38
24.1%
2 26
16.5%
3 23
14.6%
9 16
10.1%
4 12
 
7.6%
5 11
 
7.0%
6 10
 
6.3%
0 10
 
6.3%
8 8
 
5.1%
7 4
 
2.5%
Space Separator
ValueCountFrequency (%)
119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 393
55.7%
Common 312
44.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 42
10.7%
충 36
9.2%
시 36
9.2%
청 36
9.2%
논 36
9.2%
남 36
9.2%
도 36
9.2%
동 27
 
6.9%
취 11
 
2.8%
리 11
 
2.8%
Other values (24) 86
21.9%
Common
ValueCountFrequency (%)
119
38.1%
1 38
 
12.2%
- 35
 
11.2%
2 26
 
8.3%
3 23
 
7.4%
9 16
 
5.1%
4 12
 
3.8%
5 11
 
3.5%
6 10
 
3.2%
0 10
 
3.2%
Other values (2) 12
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 393
55.7%
ASCII 312
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
119
38.1%
1 38
 
12.2%
- 35
 
11.2%
2 26
 
8.3%
3 23
 
7.4%
9 16
 
5.1%
4 12
 
3.8%
5 11
 
3.5%
6 10
 
3.2%
0 10
 
3.2%
Other values (2) 12
 
3.8%
Hangul
ValueCountFrequency (%)
산 42
10.7%
충 36
9.2%
시 36
9.2%
청 36
9.2%
논 36
9.2%
남 36
9.2%
도 36
9.2%
동 27
 
6.9%
취 11
 
2.8%
리 11
 
2.8%
Other values (24) 86
21.9%

Correlations

2024-01-10T05:40:59.527820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명요금행정동소재지도로명주소소재지지번주소
업소명1.0001.0001.0001.0001.000
요금1.0001.0000.5441.0001.000
행정동1.0000.5441.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.000
2024-01-10T05:40:59.637278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동요금
행정동1.0000.628
요금0.6281.000
2024-01-10T05:40:59.730880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
요금행정동
요금1.0000.628
행정동0.6281.000

Missing values

2024-01-10T05:40:57.377545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:40:57.455718image/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

업소명요금행정동소재지도로명주소소재지지번주소
0OK인력공사유료부창동충청남도 논산시 계백로 959-1충청남도 논산시 부창동 22-1
1가가인력공사유료부창동충청남도 논산시 계백로 960충청남도 논산시 부창동 24-5
2가나인력유료강경읍충청남도 논산시 강경읍 옥녀봉로 12충청남도 논산시 강경읍 중앙리 164-1
3강경인력장묘사유료강경읍충청남도 논산시 강경읍 계백로72번길 1충청남도 논산시 강경읍 채산리 552-19
4거성인력공사유료취암동충청남도 논산시 논산대로 539충청남도 논산시 지산동 274-1
5경진기업인력공사유료취암동충청남도 논산시 계백로 1044충청남도 논산시 취암동 1036-8
6구룡인력유료연무읍충청남도 논산시 연무읍 안심로 95충청남도 논산시 연무읍 안심리 9-56
7금성기업유료취암동충청남도 논산시 관촉로 273충청남도 논산시 취암동 1042-9
8논산시시니어클럽무료취암동충청남도 논산시 관촉로235번길 15-10충청남도 논산시 취암동 1082-3
9논산인력직업소개소유료취암동충청남도 논산시 중앙로480번길 41-1충청남도 논산시 화지동 59-1
업소명요금행정동소재지도로명주소소재지지번주소
26우리인력개발유료연무읍충청남도 논산시 연무읍 안심로 124-1충청남도 논산시 연무읍 동산리 894-20
27일진인력유료취암동충청남도 논산시 해월로 210충청남도 논산시 반월동 33-129
28제일인력공사유료취암동충청남도 논산시 해월로 213충청남도 논산시 화지동 32-22
29중부기업유료취암동충청남도 논산시 관촉로 290충청남도 논산시 취암동 1039-12
30천일인력유료부창동충청남도 논산시 계백로 945충청남도 논산시 부창동 218-1
31태성인력공사유료취암동충청남도 논산시 관촉로 268충청남도 논산시 취암동 296-28
32해피인력직업소개소유료취암동충청남도 논산시 관촉로277번길 13충청남도 논산시 취암동 1043-1
33현대인력유료취암동충청남도 논산시 해월로 219충청남도 논산시 화지동 32-23
34황산인력유료강경읍충청남도 논산시 강경읍 계백로 96충청남도 논산시 강경읍 대흥리 46-11
35효성인력공사유료연무읍충청남도 논산시 연무읍 안심로 161충청남도 논산시 연무읍 안심리 1126-34