Overview

Dataset statistics

Number of variables6
Number of observations51
Missing cells24
Missing cells (%)7.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory51.6 B

Variable types

Numeric1
Text4
DateTime1

Dataset

Description인천광역시 중구 현재 영업중인 직업소개소 사업장의 업소명, 소재지의 도로명주소, 전화번호 등에 대한 정보를 제공합니다.
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15074878&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
사업소전화번호 has 24 (47.1%) missing valuesMissing
순번 has unique valuesUnique
사업소명 has unique valuesUnique
대표자명 has unique valuesUnique
사업소도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-01-28 15:55:16.597222
Analysis finished2024-01-28 15:55:17.081942
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2024-01-29T00:55:17.139056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q113.5
median26
Q338.5
95-th percentile48.5
Maximum51
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.57177187
Kurtosis-1.2
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum1326
Variance221
MonotonicityStrictly increasing
2024-01-29T00:55:17.252415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
2 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
51 1
2.0%
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%

사업소명
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-01-29T00:55:17.461295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length6.627451
Min length4

Characters and Unicode

Total characters338
Distinct characters122
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row21세기인력사무소
2nd row피플러스
3rd row광진선박선원컨설팅
4th row라인인력
5th row스마트트레이드에듀
ValueCountFrequency (%)
21세기인력사무소 1
 
1.9%
주)진성토탈서비스 1
 
1.9%
인천인력 1
 
1.9%
다온인력지원센터 1
 
1.9%
희망인력 1
 
1.9%
참좋은직업소개소 1
 
1.9%
현주개발 1
 
1.9%
신공항인력 1
 
1.9%
운서인력 1
 
1.9%
ok인력 1
 
1.9%
Other values (44) 44
81.5%
2024-01-29T00:55:17.805752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 33
 
9.8%
력 27
 
8.0%
소 24
 
7.1%
개 22
 
6.5%
업 12
 
3.6%
직 11
 
3.3%
발 9
 
2.7%
스 6
 
1.8%
사 5
 
1.5%
이 5
 
1.5%
Other values (112) 184
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 318
94.1%
Decimal Number 7
 
2.1%
Close Punctuation 4
 
1.2%
Open Punctuation 4
 
1.2%
Space Separator 3
 
0.9%
Uppercase Letter 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 33
 
10.4%
력 27
 
8.5%
소 24
 
7.5%
개 22
 
6.9%
업 12
 
3.8%
직 11
 
3.5%
발 9
 
2.8%
스 6
 
1.9%
사 5
 
1.6%
이 5
 
1.6%
Other values (102) 164
51.6%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
2 1
 
14.3%
0 1
 
14.3%
8 1
 
14.3%
5 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
O 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 318
94.1%
Common 18
 
5.3%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 33
 
10.4%
력 27
 
8.5%
소 24
 
7.5%
개 22
 
6.9%
업 12
 
3.8%
직 11
 
3.5%
발 9
 
2.8%
스 6
 
1.9%
사 5
 
1.6%
이 5
 
1.6%
Other values (102) 164
51.6%
Common
ValueCountFrequency (%)
) 4
22.2%
( 4
22.2%
3
16.7%
1 3
16.7%
2 1
 
5.6%
0 1
 
5.6%
8 1
 
5.6%
5 1
 
5.6%
Latin
ValueCountFrequency (%)
K 1
50.0%
O 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 318
94.1%
ASCII 20
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 33
 
10.4%
력 27
 
8.5%
소 24
 
7.5%
개 22
 
6.9%
업 12
 
3.8%
직 11
 
3.5%
발 9
 
2.8%
스 6
 
1.9%
사 5
 
1.6%
이 5
 
1.6%
Other values (102) 164
51.6%
ASCII
ValueCountFrequency (%)
) 4
20.0%
( 4
20.0%
3
15.0%
1 3
15.0%
2 1
 
5.0%
K 1
 
5.0%
O 1
 
5.0%
0 1
 
5.0%
8 1
 
5.0%
5 1
 
5.0%

대표자명
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-01-29T00:55:17.997749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9803922
Min length2

Characters and Unicode

Total characters152
Distinct characters74
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row변각현
2nd row김달식
3rd row오보라
4th row양정아
5th row유재명
ValueCountFrequency (%)
변각현 1
 
2.0%
김영식 1
 
2.0%
전윤선 1
 
2.0%
김용식 1
 
2.0%
강성 1
 
2.0%
조고호 1
 
2.0%
윤석종 1
 
2.0%
이태연 1
 
2.0%
최효석 1
 
2.0%
박재영 1
 
2.0%
Other values (41) 41
80.4%
2024-01-29T00:55:18.277108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
영 8
 
5.3%
이 7
 
4.6%
김 7
 
4.6%
정 6
 
3.9%
최 6
 
3.9%
연 5
 
3.3%
성 4
 
2.6%
강 4
 
2.6%
박 4
 
2.6%
식 4
 
2.6%
Other values (64) 97
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 152
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 8
 
5.3%
이 7
 
4.6%
김 7
 
4.6%
정 6
 
3.9%
최 6
 
3.9%
연 5
 
3.3%
성 4
 
2.6%
강 4
 
2.6%
박 4
 
2.6%
식 4
 
2.6%
Other values (64) 97
63.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 152
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 8
 
5.3%
이 7
 
4.6%
김 7
 
4.6%
정 6
 
3.9%
최 6
 
3.9%
연 5
 
3.3%
성 4
 
2.6%
강 4
 
2.6%
박 4
 
2.6%
식 4
 
2.6%
Other values (64) 97
63.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 152
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
영 8
 
5.3%
이 7
 
4.6%
김 7
 
4.6%
정 6
 
3.9%
최 6
 
3.9%
연 5
 
3.3%
성 4
 
2.6%
강 4
 
2.6%
박 4
 
2.6%
식 4
 
2.6%
Other values (64) 97
63.8%

사업소전화번호
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing24
Missing (%)47.1%
Memory size540.0 B
2024-01-29T00:55:18.439563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.037037
Min length12

Characters and Unicode

Total characters325
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row032-751-1306
2nd row032-224-2564
3rd row032-765-9461
4th row032-777-1982
5th row032-752-0815
ValueCountFrequency (%)
032-751-1306 1
 
3.6%
032-224-2564 1
 
3.6%
032-763-8090 1
 
3.6%
032-881-4374 1
 
3.6%
1531 1
 
3.6%
032-885 1
 
3.6%
032-764-0033 1
 
3.6%
032-751-6964 1
 
3.6%
032-888-8689 1
 
3.6%
032-762-8787 1
 
3.6%
Other values (18) 18
64.3%
2024-01-29T00:55:18.706901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 53
16.3%
0 44
13.5%
3 41
12.6%
2 38
11.7%
7 35
10.8%
8 29
8.9%
5 21
 
6.5%
6 19
 
5.8%
1 18
 
5.5%
4 18
 
5.5%
Other values (2) 9
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 271
83.4%
Dash Punctuation 53
 
16.3%
Space Separator 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44
16.2%
3 41
15.1%
2 38
14.0%
7 35
12.9%
8 29
10.7%
5 21
7.7%
6 19
7.0%
1 18
6.6%
4 18
6.6%
9 8
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 325
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 53
16.3%
0 44
13.5%
3 41
12.6%
2 38
11.7%
7 35
10.8%
8 29
8.9%
5 21
 
6.5%
6 19
 
5.8%
1 18
 
5.5%
4 18
 
5.5%
Other values (2) 9
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 325
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 53
16.3%
0 44
13.5%
3 41
12.6%
2 38
11.7%
7 35
10.8%
8 29
8.9%
5 21
 
6.5%
6 19
 
5.8%
1 18
 
5.5%
4 18
 
5.5%
Other values (2) 9
 
2.8%

사업소도로명주소
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2024-01-29T00:55:18.969462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length36
Mean length31.588235
Min length21

Characters and Unicode

Total characters1611
Distinct characters137
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

Unique51 ?
Unique (%)100.0%

Sample

1st row인천광역시 중구 인중로 50. 2층 (신흥동3가)
2nd row인천광역시 중구 햇내로13번길 8. 프라임시티3 205호 (운서동)
3rd row인천광역시 중구 연안부두로 7. 1층 (항동7가)
4th row인천광역시 중구 하늘달빛로64번길 6-3. 스카이 메디컬 프라자 502호 (중산동)
5th row인천광역시 중구 영종대로 84. 신공항파크빌 710호 (운서동)
ValueCountFrequency (%)
인천광역시 51
 
16.1%
중구 51
 
16.1%
운서동 16
 
5.1%
2층 7
 
2.2%
신도시남로141번길 6
 
1.9%
1층 5
 
1.6%
영종대로 5
 
1.6%
참외전로 5
 
1.6%
신흥동3가 4
 
1.3%
인현동 4
 
1.3%
Other values (125) 162
51.3%
2024-01-29T00:55:19.338585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
265
 
16.4%
1 62
 
3.8%
인 61
 
3.8%
시 61
 
3.8%
중 61
 
3.8%
동 54
 
3.4%
광 52
 
3.2%
로 52
 
3.2%
역 51
 
3.2%
구 51
 
3.2%
Other values (127) 841
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 936
58.1%
Space Separator 265
 
16.4%
Decimal Number 255
 
15.8%
Close Punctuation 50
 
3.1%
Open Punctuation 50
 
3.1%
Other Punctuation 44
 
2.7%
Dash Punctuation 11
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 61
 
6.5%
시 61
 
6.5%
중 61
 
6.5%
동 54
 
5.8%
광 52
 
5.6%
로 52
 
5.6%
역 51
 
5.4%
구 51
 
5.4%
천 51
 
5.4%
운 26
 
2.8%
Other values (111) 416
44.4%
Decimal Number
ValueCountFrequency (%)
1 62
24.3%
2 41
16.1%
4 31
12.2%
3 29
11.4%
0 21
 
8.2%
7 19
 
7.5%
5 15
 
5.9%
6 14
 
5.5%
8 13
 
5.1%
9 10
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 41
93.2%
, 3
 
6.8%
Space Separator
ValueCountFrequency (%)
265
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 936
58.1%
Common 675
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 61
 
6.5%
시 61
 
6.5%
중 61
 
6.5%
동 54
 
5.8%
광 52
 
5.6%
로 52
 
5.6%
역 51
 
5.4%
구 51
 
5.4%
천 51
 
5.4%
운 26
 
2.8%
Other values (111) 416
44.4%
Common
ValueCountFrequency (%)
265
39.3%
1 62
 
9.2%
) 50
 
7.4%
( 50
 
7.4%
. 41
 
6.1%
2 41
 
6.1%
4 31
 
4.6%
3 29
 
4.3%
0 21
 
3.1%
7 19
 
2.8%
Other values (6) 66
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 936
58.1%
ASCII 675
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
265
39.3%
1 62
 
9.2%
) 50
 
7.4%
( 50
 
7.4%
. 41
 
6.1%
2 41
 
6.1%
4 31
 
4.6%
3 29
 
4.3%
0 21
 
3.1%
7 19
 
2.8%
Other values (6) 66
 
9.8%
Hangul
ValueCountFrequency (%)
인 61
 
6.5%
시 61
 
6.5%
중 61
 
6.5%
동 54
 
5.8%
광 52
 
5.6%
로 52
 
5.6%
역 51
 
5.4%
구 51
 
5.4%
천 51
 
5.4%
운 26
 
2.8%
Other values (111) 416
44.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
Minimum2023-01-13 00:00:00
Maximum2023-01-13 00:00:00
2024-01-29T00:55:19.427126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:55:19.491661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-29T00:55:16.880751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T00:55:19.542728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번사업소명대표자명사업소전화번호사업소도로명주소
순번1.0001.0001.0001.0001.000
사업소명1.0001.0001.0001.0001.000
대표자명1.0001.0001.0001.0001.000
사업소전화번호1.0001.0001.0001.0001.000
사업소도로명주소1.0001.0001.0001.0001.000

Missing values

2024-01-29T00:55:16.963133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:55:17.048062image/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

순번사업소명대표자명사업소전화번호사업소도로명주소데이터기준일자
0121세기인력사무소변각현<NA>인천광역시 중구 인중로 50. 2층 (신흥동3가)2023-01-13
12피플러스김달식032-751-1306인천광역시 중구 햇내로13번길 8. 프라임시티3 205호 (운서동)2023-01-13
23광진선박선원컨설팅오보라<NA>인천광역시 중구 연안부두로 7. 1층 (항동7가)2023-01-13
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