Overview

Dataset statistics

Number of variables4
Number of observations49
Missing cells33
Missing cells (%)16.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory34.6 B

Variable types

Text3
Categorical1

Dataset

Description전라북도 고창군 관내 직업소개소에 대한 데이터로 직업소개소 업체명,주소, 전화번호, 유료 및 무료 여부를 포함한 데이터
Author전라북도 고창군
URLhttps://www.data.go.kr/data/15081261/fileData.do

Alerts

유무료 is highly imbalanced (85.6%)Imbalance
전화번호 has 33 (67.3%) missing valuesMissing
업체명 has unique valuesUnique

Reproduction

Analysis started2024-04-21 03:11:40.708660
Analysis finished2024-04-21 03:11:42.593613
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size520.0 B
2024-04-21T12:11:43.249999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length5.755102
Min length4

Characters and Unicode

Total characters282
Distinct characters86
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st row고창인력관리공단
2nd row제일인력
3rd row석영인력사무소
4th row국제인력사무소
5th row일대신인력사무소
ValueCountFrequency (%)
직업소개소 2
 
3.8%
대풍인력 2
 
3.8%
고창인력관리공단 1
 
1.9%
성송인력 1
 
1.9%
심원인력 1
 
1.9%
신효림 1
 
1.9%
신세계인력 1
 
1.9%
공음인력 1
 
1.9%
우성인력 1
 
1.9%
유한회사 1
 
1.9%
Other values (41) 41
77.4%
2024-04-21T12:11:44.562429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 45
 
16.0%
력 44
 
15.6%
소 22
 
7.8%
개 9
 
3.2%
대 9
 
3.2%
고 7
 
2.5%
사 7
 
2.5%
업 6
 
2.1%
직 6
 
2.1%
무 6
 
2.1%
Other values (76) 121
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 275
97.5%
Space Separator 4
 
1.4%
Uppercase Letter 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 45
 
16.4%
력 44
 
16.0%
소 22
 
8.0%
개 9
 
3.3%
대 9
 
3.3%
고 7
 
2.5%
사 7
 
2.5%
업 6
 
2.2%
직 6
 
2.2%
무 6
 
2.2%
Other values (72) 114
41.5%
Uppercase Letter
ValueCountFrequency (%)
J 1
33.3%
O 1
33.3%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 275
97.5%
Common 4
 
1.4%
Latin 3
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 45
 
16.4%
력 44
 
16.0%
소 22
 
8.0%
개 9
 
3.3%
대 9
 
3.3%
고 7
 
2.5%
사 7
 
2.5%
업 6
 
2.2%
직 6
 
2.2%
무 6
 
2.2%
Other values (72) 114
41.5%
Latin
ValueCountFrequency (%)
J 1
33.3%
O 1
33.3%
B 1
33.3%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 275
97.5%
ASCII 7
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 45
 
16.4%
력 44
 
16.0%
소 22
 
8.0%
개 9
 
3.3%
대 9
 
3.3%
고 7
 
2.5%
사 7
 
2.5%
업 6
 
2.2%
직 6
 
2.2%
무 6
 
2.2%
Other values (72) 114
41.5%
ASCII
ValueCountFrequency (%)
4
57.1%
J 1
 
14.3%
O 1
 
14.3%
B 1
 
14.3%

주소
Text

Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size520.0 B
2024-04-21T12:11:45.480754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length18.265306
Min length14

Characters and Unicode

Total characters895
Distinct characters102
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)95.9%

Sample

1st row 고창군 고창읍 보릿골로 115， 1층 106호
2nd row 고창군 고창읍 성산6길 1
3rd row 고창군 고창읍 천변북로 115-4
4th row 고창군 고창읍 보릿골로 55， 대신종합철물건재
5th row 고창군 고창읍 보릿골로 139
ValueCountFrequency (%)
고창군 49
23.3%
고창읍 30
 
14.3%
보릿골로 12
 
5.7%
공음면 4
 
1.9%
아산면 4
 
1.9%
녹두로 4
 
1.9%
해리면 3
 
1.4%
천변북로 3
 
1.4%
동리로 3
 
1.4%
해리중앙로 2
 
1.0%
Other values (86) 96
45.7%
2024-04-21T12:11:46.828986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
210
23.5%
고 80
 
8.9%
창 79
 
8.8%
군 49
 
5.5%
1 36
 
4.0%
로 35
 
3.9%
읍 30
 
3.4%
2 20
 
2.2%
면 19
 
2.1%
길 14
 
1.6%
Other values (92) 323
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 526
58.8%
Space Separator 210
 
23.5%
Decimal Number 137
 
15.3%
Dash Punctuation 10
 
1.1%
Other Punctuation 6
 
0.7%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 80
15.2%
창 79
15.0%
군 49
 
9.3%
로 35
 
6.7%
읍 30
 
5.7%
면 19
 
3.6%
길 14
 
2.7%
산 14
 
2.7%
보 13
 
2.5%
골 12
 
2.3%
Other values (75) 181
34.4%
Decimal Number
ValueCountFrequency (%)
1 36
26.3%
2 20
14.6%
6 14
 
10.2%
7 13
 
9.5%
3 12
 
8.8%
4 11
 
8.0%
5 11
 
8.0%
0 9
 
6.6%
8 8
 
5.8%
9 3
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
210
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
， 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 526
58.8%
Common 367
41.0%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 80
15.2%
창 79
15.0%
군 49
 
9.3%
로 35
 
6.7%
읍 30
 
5.7%
면 19
 
3.6%
길 14
 
2.7%
산 14
 
2.7%
보 13
 
2.5%
골 12
 
2.3%
Other values (75) 181
34.4%
Common
ValueCountFrequency (%)
210
57.2%
1 36
 
9.8%
2 20
 
5.4%
6 14
 
3.8%
7 13
 
3.5%
3 12
 
3.3%
4 11
 
3.0%
5 11
 
3.0%
- 10
 
2.7%
0 9
 
2.5%
Other values (5) 21
 
5.7%
Latin
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 526
58.8%
ASCII 363
40.6%
None 6
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
210
57.9%
1 36
 
9.9%
2 20
 
5.5%
6 14
 
3.9%
7 13
 
3.6%
3 12
 
3.3%
4 11
 
3.0%
5 11
 
3.0%
- 10
 
2.8%
0 9
 
2.5%
Other values (6) 17
 
4.7%
Hangul
ValueCountFrequency (%)
고 80
15.2%
창 79
15.0%
군 49
 
9.3%
로 35
 
6.7%
읍 30
 
5.7%
면 19
 
3.6%
길 14
 
2.7%
산 14
 
2.7%
보 13
 
2.5%
골 12
 
2.3%
Other values (75) 181
34.4%
None
ValueCountFrequency (%)
， 6
100.0%

전화번호
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing33
Missing (%)67.3%
Memory size520.0 B
2024-04-21T12:11:47.523450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters192
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

Unique16 ?
Unique (%)100.0%

Sample

1st row063-561-5234
2nd row063-564-0600
3rd row063-564-0201
4th row063-561-3456
5th row063-562-2786
ValueCountFrequency (%)
063-561-5234 1
 
6.2%
063-564-0600 1
 
6.2%
063-564-0201 1
 
6.2%
063-561-3456 1
 
6.2%
063-562-2786 1
 
6.2%
063-561-1604 1
 
6.2%
063-562-9299 1
 
6.2%
063-561-1662 1
 
6.2%
063-564-9400 1
 
6.2%
063-564-0185 1
 
6.2%
Other values (6) 6
37.5%
2024-04-21T12:11:48.583553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 41
21.4%
- 32
16.7%
0 25
13.0%
5 21
10.9%
3 20
10.4%
2 16
 
8.3%
1 14
 
7.3%
4 11
 
5.7%
9 6
 
3.1%
7 4
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160
83.3%
Dash Punctuation 32
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 41
25.6%
0 25
15.6%
5 21
13.1%
3 20
12.5%
2 16
 
10.0%
1 14
 
8.8%
4 11
 
6.9%
9 6
 
3.8%
7 4
 
2.5%
8 2
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 192
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 41
21.4%
- 32
16.7%
0 25
13.0%
5 21
10.9%
3 20
10.4%
2 16
 
8.3%
1 14
 
7.3%
4 11
 
5.7%
9 6
 
3.1%
7 4
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 192
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 41
21.4%
- 32
16.7%
0 25
13.0%
5 21
10.9%
3 20
10.4%
2 16
 
8.3%
1 14
 
7.3%
4 11
 
5.7%
9 6
 
3.1%
7 4
 
2.1%

유무료
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size520.0 B
유료
48 
무료
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
유료 48
98.0%
무료 1
 
2.0%

Length

2024-04-21T12:11:48.979756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T12:11:49.272021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 48
98.0%
무료 1
 
2.0%

Correlations

2024-04-21T12:11:49.446999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명주소전화번호유무료
업체명1.0001.0001.0001.000
주소1.0001.0001.0001.000
전화번호1.0001.0001.0001.000
유무료1.0001.0001.0001.000

Missing values

2024-04-21T12:11:42.202235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T12:11:42.484727image/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

업체명주소전화번호유무료
0고창인력관리공단고창군 고창읍 보릿골로 115， 1층 106호<NA>유료
1제일인력고창군 고창읍 성산6길 1<NA>유료
2석영인력사무소고창군 고창읍 천변북로 115-4<NA>유료
3국제인력사무소고창군 고창읍 보릿골로 55， 대신종합철물건재<NA>유료
4일대신인력사무소고창군 고창읍 보릿골로 139<NA>유료
5믿음인력고창군 고창읍 천변남로 76-1<NA>유료
6새고창인력고창군 고창읍 중거리당산로 143<NA>유료
7황소인력고창군 고창읍 보릿골로 57-10<NA>유료
8대영인력고창군 대산면 대성로 214<NA>유료
9배풍인력고창군 흥덕면 선운대로 3766<NA>유료
업체명주소전화번호유무료
39대성인력고창군 고창읍 성산1길 32<NA>유료
40도원인력고창군 고창읍 성산8길 1063-561-1662유료
41태양직업소개소고창군 고창읍 동리로 22063-564-9400유료
42개미건설철거인력고창군 고창읍 천변북로 41-1063-564-0185유료
43우리인력고창군 고창읍 보릿골로 105063-561-2231유료
44고창인력소개소고창군 고창읍 보릿골로 84063-562-9229유료
45안전인력고창군 고창읍 천변남로 34063-564-6266유료
46팔도유료직업소개소고창군 고창읍 보릿골로 131063-562-1151유료
47대산인력직업소개소고창군 대산면 대성로 267063-563-5772유료
48고인돌인력고창군 고창읍 보릿골로 137063-564-1472유료