Overview

Dataset statistics

Number of variables4
Number of observations60
Missing cells22
Missing cells (%)9.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory35.2 B

Variable types

Numeric1
Text3

Dataset

Description광주광역시 서구의 관내에 위치한 직업소개소의 사업소명, 사업소주소, 사업소전화번호 에대한 정보를 제공합니다.
Author광주광역시 서구
URLhttps://www.data.go.kr/data/15011799/fileData.do

Alerts

사업소전화번호 has 22 (36.7%) missing valuesMissing
순번 has unique valuesUnique
사업소명 has unique valuesUnique
사업소주소 has unique valuesUnique

Reproduction

Analysis started2023-12-23 07:31:04.606052
Analysis finished2023-12-23 07:31:06.881954
Duration2.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.5
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-23T07:31:07.246312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.95
Q115.75
median30.5
Q345.25
95-th percentile57.05
Maximum60
Range59
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation17.464249
Coefficient of variation (CV)0.57259833
Kurtosis-1.2
Mean30.5
Median Absolute Deviation (MAD)15
Skewness0
Sum1830
Variance305
MonotonicityStrictly increasing
2023-12-23T07:31:08.069463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.7%
32 1
 
1.7%
34 1
 
1.7%
35 1
 
1.7%
36 1
 
1.7%
37 1
 
1.7%
38 1
 
1.7%
39 1
 
1.7%
40 1
 
1.7%
41 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
1 1
1.7%
2 1
1.7%
3 1
1.7%
4 1
1.7%
5 1
1.7%
6 1
1.7%
7 1
1.7%
8 1
1.7%
9 1
1.7%
10 1
1.7%
ValueCountFrequency (%)
60 1
1.7%
59 1
1.7%
58 1
1.7%
57 1
1.7%
56 1
1.7%
55 1
1.7%
54 1
1.7%
53 1
1.7%
52 1
1.7%
51 1
1.7%

사업소명
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-23T07:31:09.039990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length14
Mean length8.5
Min length4

Characters and Unicode

Total characters510
Distinct characters150
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

Unique60 ?
Unique (%)100.0%

Sample

1st row최삼두직업소개소
2nd row가나인력
3rd row신용유료직업소개소
4th row가고파유료직업소개소
5th row잡 플러스
ValueCountFrequency (%)
주식회사 3
 
4.3%
미소피아 1
 
1.4%
호남간병인력 1
 
1.4%
호남인력대기소 1
 
1.4%
광주시외식업직업소개소 1
 
1.4%
신상무유료직업소개소 1
 
1.4%
한결직업소개소 1
 
1.4%
재)광주창조경제혁신센터 1
 
1.4%
월드인력 1
 
1.4%
가나인력 1
 
1.4%
Other values (58) 58
82.9%
2023-12-23T07:31:10.961754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 55
 
10.8%
인 24
 
4.7%
개 21
 
4.1%
력 20
 
3.9%
대 20
 
3.9%
업 19
 
3.7%
직 17
 
3.3%
기 17
 
3.3%
주 13
 
2.5%
자 13
 
2.5%
Other values (140) 291
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 459
90.0%
Lowercase Letter 16
 
3.1%
Space Separator 10
 
2.0%
Open Punctuation 6
 
1.2%
Close Punctuation 6
 
1.2%
Uppercase Letter 6
 
1.2%
Decimal Number 4
 
0.8%
Other Punctuation 2
 
0.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 55
 
12.0%
인 24
 
5.2%
개 21
 
4.6%
력 20
 
4.4%
대 20
 
4.4%
업 19
 
4.1%
직 17
 
3.7%
기 17
 
3.7%
주 13
 
2.8%
자 13
 
2.8%
Other values (115) 240
52.3%
Lowercase Letter
ValueCountFrequency (%)
o 5
31.2%
t 2
 
12.5%
a 1
 
6.2%
d 1
 
6.2%
c 1
 
6.2%
m 1
 
6.2%
n 1
 
6.2%
i 1
 
6.2%
u 1
 
6.2%
l 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
N 1
16.7%
L 1
16.7%
C 1
16.7%
S 1
16.7%
J 1
16.7%
K 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 1
25.0%
4 1
25.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 459
90.0%
Common 29
 
5.7%
Latin 22
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 55
 
12.0%
인 24
 
5.2%
개 21
 
4.6%
력 20
 
4.4%
대 20
 
4.4%
업 19
 
4.1%
직 17
 
3.7%
기 17
 
3.7%
주 13
 
2.8%
자 13
 
2.8%
Other values (115) 240
52.3%
Latin
ValueCountFrequency (%)
o 5
22.7%
t 2
 
9.1%
N 1
 
4.5%
a 1
 
4.5%
d 1
 
4.5%
c 1
 
4.5%
m 1
 
4.5%
L 1
 
4.5%
C 1
 
4.5%
n 1
 
4.5%
Other values (7) 7
31.8%
Common
ValueCountFrequency (%)
10
34.5%
( 6
20.7%
) 6
20.7%
. 2
 
6.9%
2 2
 
6.9%
1 1
 
3.4%
- 1
 
3.4%
4 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 459
90.0%
ASCII 51
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 55
 
12.0%
인 24
 
5.2%
개 21
 
4.6%
력 20
 
4.4%
대 20
 
4.4%
업 19
 
4.1%
직 17
 
3.7%
기 17
 
3.7%
주 13
 
2.8%
자 13
 
2.8%
Other values (115) 240
52.3%
ASCII
ValueCountFrequency (%)
10
19.6%
( 6
 
11.8%
) 6
 
11.8%
o 5
 
9.8%
. 2
 
3.9%
2 2
 
3.9%
t 2
 
3.9%
N 1
 
2.0%
a 1
 
2.0%
d 1
 
2.0%
Other values (15) 15
29.4%

사업소주소
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-23T07:31:12.492325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length24.466667
Min length15

Characters and Unicode

Total characters1468
Distinct characters87
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row광주광역시 서구 상무대로 973 (쌍촌동)
2nd row광주광역시 서구 화운로 304 (광천동)
3rd row광주광역시 서구 상무대로 794-1(마륵동)
4th row광주광역시 서구 천변좌로 100 (농성동)
5th row광주광역시 서구 군분로212번길 7-2 (농성동)
ValueCountFrequency (%)
광주광역시 60
20.4%
서구 60
20.4%
상무대로 14
 
4.8%
농성동 5
 
1.7%
쌍촌동 5
 
1.7%
화정동 5
 
1.7%
1층 4
 
1.4%
화운로 4
 
1.4%
3층 4
 
1.4%
경열로 3
 
1.0%
Other values (113) 130
44.2%
2023-12-23T07:31:15.259418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
234
 
15.9%
광 126
 
8.6%
구 61
 
4.2%
1 61
 
4.2%
시 61
 
4.2%
서 60
 
4.1%
역 60
 
4.1%
주 60
 
4.1%
로 60
 
4.1%
동 47
 
3.2%
Other values (77) 638
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 850
57.9%
Decimal Number 256
 
17.4%
Space Separator 234
 
15.9%
Close Punctuation 45
 
3.1%
Open Punctuation 45
 
3.1%
Other Punctuation 28
 
1.9%
Dash Punctuation 10
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 126
14.8%
구 61
 
7.2%
시 61
 
7.2%
서 60
 
7.1%
역 60
 
7.1%
주 60
 
7.1%
로 60
 
7.1%
동 47
 
5.5%
대 24
 
2.8%
화 21
 
2.5%
Other values (61) 270
31.8%
Decimal Number
ValueCountFrequency (%)
1 61
23.8%
2 38
14.8%
0 33
12.9%
3 26
10.2%
5 21
 
8.2%
4 19
 
7.4%
9 17
 
6.6%
7 16
 
6.2%
6 13
 
5.1%
8 12
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 24
85.7%
. 4
 
14.3%
Space Separator
ValueCountFrequency (%)
234
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 850
57.9%
Common 618
42.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 126
14.8%
구 61
 
7.2%
시 61
 
7.2%
서 60
 
7.1%
역 60
 
7.1%
주 60
 
7.1%
로 60
 
7.1%
동 47
 
5.5%
대 24
 
2.8%
화 21
 
2.5%
Other values (61) 270
31.8%
Common
ValueCountFrequency (%)
234
37.9%
1 61
 
9.9%
) 45
 
7.3%
( 45
 
7.3%
2 38
 
6.1%
0 33
 
5.3%
3 26
 
4.2%
, 24
 
3.9%
5 21
 
3.4%
4 19
 
3.1%
Other values (6) 72
 
11.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 850
57.9%
ASCII 618
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
234
37.9%
1 61
 
9.9%
) 45
 
7.3%
( 45
 
7.3%
2 38
 
6.1%
0 33
 
5.3%
3 26
 
4.2%
, 24
 
3.9%
5 21
 
3.4%
4 19
 
3.1%
Other values (6) 72
 
11.7%
Hangul
ValueCountFrequency (%)
광 126
14.8%
구 61
 
7.2%
시 61
 
7.2%
서 60
 
7.1%
역 60
 
7.1%
주 60
 
7.1%
로 60
 
7.1%
동 47
 
5.5%
대 24
 
2.8%
화 21
 
2.5%
Other values (61) 270
31.8%

사업소전화번호
Text

MISSING 

Distinct38
Distinct (%)100.0%
Missing22
Missing (%)36.7%
Memory size612.0 B
2023-12-23T07:31:16.271984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters456
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

Unique38 ?
Unique (%)100.0%

Sample

1st row062-373-9422
2nd row062-352-2323
3rd row062-352-1204
4th row062-366-8782
5th row062-371-0980
ValueCountFrequency (%)
062-372-6302 1
 
2.6%
062-523-9782 1
 
2.6%
062-372-7600 1
 
2.6%
062-350-8546 1
 
2.6%
062-369-0424 1
 
2.6%
062-362-3006 1
 
2.6%
062-350-6677 1
 
2.6%
062-363-2200 1
 
2.6%
062-384-8277 1
 
2.6%
062-433-8960 1
 
2.6%
Other values (28) 28
73.7%
2023-12-23T07:31:17.692709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 76
16.7%
2 71
15.6%
6 67
14.7%
0 65
14.3%
3 50
11.0%
5 26
 
5.7%
4 25
 
5.5%
7 22
 
4.8%
9 21
 
4.6%
1 17
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 380
83.3%
Dash Punctuation 76
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 71
18.7%
6 67
17.6%
0 65
17.1%
3 50
13.2%
5 26
 
6.8%
4 25
 
6.6%
7 22
 
5.8%
9 21
 
5.5%
1 17
 
4.5%
8 16
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 456
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 76
16.7%
2 71
15.6%
6 67
14.7%
0 65
14.3%
3 50
11.0%
5 26
 
5.7%
4 25
 
5.5%
7 22
 
4.8%
9 21
 
4.6%
1 17
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 76
16.7%
2 71
15.6%
6 67
14.7%
0 65
14.3%
3 50
11.0%
5 26
 
5.7%
4 25
 
5.5%
7 22
 
4.8%
9 21
 
4.6%
1 17
 
3.7%

Interactions

2023-12-23T07:31:05.604429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-23T07:31:18.217894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번사업소명사업소주소사업소전화번호
순번1.0001.0001.0001.000
사업소명1.0001.0001.0001.000
사업소주소1.0001.0001.0001.000
사업소전화번호1.0001.0001.0001.000

Missing values

2023-12-23T07:31:06.044826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T07:31:06.624499image/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

순번사업소명사업소주소사업소전화번호
01최삼두직업소개소광주광역시 서구 상무대로 973 (쌍촌동)062-373-9422
12가나인력광주광역시 서구 화운로 304 (광천동)062-352-2323
23신용유료직업소개소광주광역시 서구 상무대로 794-1(마륵동)<NA>
34가고파유료직업소개소광주광역시 서구 천변좌로 100 (농성동)062-352-1204
45잡 플러스광주광역시 서구 군분로212번길 7-2 (농성동)062-366-8782
56가야근로자대기소광주광역시 서구 상무대로 951-1 (쌍촌동)062-371-0980
67건강인력근로자대기소광주광역시 서구 상무대로 929, 1층 (쌍촌동)062-364-1000
7821세기근로자직업안내소광주광역시 서구 죽봉대로 129 (광천동)062-365-6001
89서강직업소개소광주광역시 서구 상무대로 987, 1층4호 (내방동)062-383-5210
910광주서구시니어클럽광주광역시 서구 쌍촌로36번길 13, 5층062-372-6302
순번사업소명사업소주소사업소전화번호
5051빛고을인력개발광주광역시 서구 월드컵4강로181번길 46, 2층<NA>
5152해피인력직업소개소광주광역시 서구 상무대로 916, 1층<NA>
5253(사)광주경영자총협회광주광역시 서구 상무대로 943, 4층062-654-3425
5354대한인력대기소광주광역시 서구 구성로 99<NA>
5455유덕재가노인복지센터광주광역시 서구 천변우하로 303<NA>
5556주식회사 엔에이(Na)광주광역시 서구 하남대로680번길 1, 6층 601호<NA>
5657비앤알상역광주광역시 서구 염화로 151, 3층<NA>
5758우리직업소개소광주광역시 서구 유덕로 25062-433-8960
5859드림월드인력광주광역시 서구 화정로150번길 12<NA>
596024시근로자대기소광주광역시 서구 군분로 230(농성동)062-368-9909