Overview

Dataset statistics

Number of variables7
Number of observations1361
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory78.5 KiB
Average record size in memory59.1 B

Variable types

Categorical3
Text2
Numeric2

Dataset

Description기업인력애로센터 보조사업(대중소기업 상생 일자리 프로그램)을 통한 기업-구직자 취업매칭 목록- 대기업의 우수한 교육 인프라를 활용해 현장맞춤형 직무교육 후, 협력중소기업 취업연계
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15100250/fileData.do

Reproduction

Analysis started2024-03-23 05:34:14.445593
Analysis finished2024-03-23 05:34:16.673505
Duration2.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

참여년도
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size10.8 KiB
2021
428 
2020
362 
2023
309 
2022
262 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2021 428
31.4%
2020 362
26.6%
2023 309
22.7%
2022 262
19.3%

Length

2024-03-23T14:34:16.856554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T14:34:17.075299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 428
31.4%
2020 362
26.6%
2023 309
22.7%
2022 262
19.3%

기업명
Text

Distinct1247
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size10.8 KiB
2024-03-23T14:34:17.416413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length22
Mean length8.4900808
Min length2

Characters and Unicode

Total characters11555
Distinct characters559
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1151 ?
Unique (%)84.6%

Sample

1st row(주)삼성비지니스솔루션
2nd row한샘키친강서대리점
3rd row야심족발
4th row(주)빌리버스
5th row스타테크(주)
ValueCountFrequency (%)
한샘리하우스 79
 
5.0%
롯데리아 69
 
4.4%
주식회사 36
 
2.3%
대리점 5
 
0.3%
디자인 4
 
0.3%
탑키친앤디자인 3
 
0.2%
키친프라자 3
 
0.2%
한샘 3
 
0.2%
유한회사 3
 
0.2%
주)피티엠 3
 
0.2%
Other values (1255) 1374
86.9%
2024-03-23T14:34:18.288681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 702
 
6.1%
주 596
 
5.2%
( 543
 
4.7%
) 542
 
4.7%
스 449
 
3.9%
점 412
 
3.6%
인 306
 
2.6%
한 287
 
2.5%
대 275
 
2.4%
이 267
 
2.3%
Other values (549) 7176
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9778
84.6%
Open Punctuation 546
 
4.7%
Close Punctuation 546
 
4.7%
Space Separator 227
 
2.0%
Uppercase Letter 226
 
2.0%
Lowercase Letter 131
 
1.1%
Decimal Number 60
 
0.5%
Other Punctuation 38
 
0.3%
Dash Punctuation 2
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 702
 
7.2%
주 596
 
6.1%
스 449
 
4.6%
점 412
 
4.2%
인 306
 
3.1%
한 287
 
2.9%
대 275
 
2.8%
이 267
 
2.7%
디 261
 
2.7%
아 257
 
2.6%
Other values (482) 5966
61.0%
Uppercase Letter
ValueCountFrequency (%)
D 25
 
11.1%
S 19
 
8.4%
N 18
 
8.0%
C 18
 
8.0%
I 16
 
7.1%
A 15
 
6.6%
T 13
 
5.8%
E 12
 
5.3%
M 11
 
4.9%
O 10
 
4.4%
Other values (13) 69
30.5%
Lowercase Letter
ValueCountFrequency (%)
e 16
12.2%
n 13
9.9%
o 13
9.9%
i 13
9.9%
s 12
9.2%
g 10
7.6%
t 10
7.6%
d 8
 
6.1%
a 7
 
5.3%
r 6
 
4.6%
Other values (10) 23
17.6%
Decimal Number
ValueCountFrequency (%)
1 13
21.7%
2 11
18.3%
5 10
16.7%
0 8
13.3%
3 8
13.3%
7 5
 
8.3%
9 2
 
3.3%
8 1
 
1.7%
6 1
 
1.7%
4 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
/ 14
36.8%
. 11
28.9%
& 8
21.1%
, 2
 
5.3%
． 2
 
5.3%
， 1
 
2.6%
Open Punctuation
ValueCountFrequency (%)
( 543
99.5%
（ 3
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 542
99.3%
） 4
 
0.7%
Space Separator
ValueCountFrequency (%)
226
99.6%
　 1
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9778
84.6%
Common 1420
 
12.3%
Latin 357
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 702
 
7.2%
주 596
 
6.1%
스 449
 
4.6%
점 412
 
4.2%
인 306
 
3.1%
한 287
 
2.9%
대 275
 
2.8%
이 267
 
2.7%
디 261
 
2.7%
아 257
 
2.6%
Other values (482) 5966
61.0%
Latin
ValueCountFrequency (%)
D 25
 
7.0%
S 19
 
5.3%
N 18
 
5.0%
C 18
 
5.0%
I 16
 
4.5%
e 16
 
4.5%
A 15
 
4.2%
n 13
 
3.6%
o 13
 
3.6%
i 13
 
3.6%
Other values (33) 191
53.5%
Common
ValueCountFrequency (%)
( 543
38.2%
) 542
38.2%
226
15.9%
/ 14
 
1.0%
1 13
 
0.9%
2 11
 
0.8%
. 11
 
0.8%
5 10
 
0.7%
& 8
 
0.6%
0 8
 
0.6%
Other values (14) 34
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9778
84.6%
ASCII 1766
 
15.3%
None 11
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 702
 
7.2%
주 596
 
6.1%
스 449
 
4.6%
점 412
 
4.2%
인 306
 
3.1%
한 287
 
2.9%
대 275
 
2.8%
이 267
 
2.7%
디 261
 
2.7%
아 257
 
2.6%
Other values (482) 5966
61.0%
ASCII
ValueCountFrequency (%)
( 543
30.7%
) 542
30.7%
226
12.8%
D 25
 
1.4%
S 19
 
1.1%
N 18
 
1.0%
C 18
 
1.0%
I 16
 
0.9%
e 16
 
0.9%
A 15
 
0.8%
Other values (52) 328
18.6%
None
ValueCountFrequency (%)
） 4
36.4%
（ 3
27.3%
． 2
18.2%
　 1
 
9.1%
， 1
 
9.1%

사업자번호
Real number (ℝ)

Distinct1126
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8856585 × 109
Minimum1.018648 × 109
Maximum8.9688008 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.1 KiB
2024-03-23T14:34:18.611506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.018648 × 109
5-th percentile1.1319397 × 109
Q11.6512012 × 109
median3.4927012 × 109
Q35.4307016 × 109
95-th percentile8.1612016 × 109
Maximum8.9688008 × 109
Range7.9501528 × 109
Interquartile range (IQR)3.7795004 × 109

Descriptive statistics

Standard deviation2.2901874 × 109
Coefficient of variation (CV)0.58939492
Kurtosis-0.94773168
Mean3.8856585 × 109
Median Absolute Deviation (MAD)1.8960998 × 109
Skewness0.44485336
Sum5.2883812 × 1012
Variance5.2449582 × 1018
MonotonicityNot monotonic
2024-03-23T14:34:18.864933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1273817191 4
 
0.3%
3477200018 4
 
0.3%
5068136266 4
 
0.3%
5068156660 4
 
0.3%
5458100671 4
 
0.3%
3380900475 3
 
0.2%
3408100829 3
 
0.2%
1208627419 3
 
0.2%
7081501392 3
 
0.2%
5028613548 3
 
0.2%
Other values (1116) 1326
97.4%
ValueCountFrequency (%)
1018648034 1
0.1%
1018654725 1
0.1%
1018661319 1
0.1%
1018703072 1
0.1%
1050981335 1
0.1%
1050992389 1
0.1%
1051195453 1
0.1%
1051448761 1
0.1%
1051682875 1
0.1%
1052180677 1
0.1%
ValueCountFrequency (%)
8968800786 1
0.1%
8943500140 1
0.1%
8940600372 2
0.1%
8928701466 1
0.1%
8918101419 1
0.1%
8878102568 1
0.1%
8878100804 1
0.1%
8872001331 2
0.1%
8861100282 1
0.1%
8828601481 2
0.1%

취업인원
Real number (ℝ)

Distinct14
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5841293
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.1 KiB
2024-03-23T14:34:19.067778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum14
Range13
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4221507
Coefficient of variation (CV)0.89774913
Kurtosis18.970488
Mean1.5841293
Median Absolute Deviation (MAD)0
Skewness3.8877168
Sum2156
Variance2.0225126
MonotonicityNot monotonic
2024-03-23T14:34:19.266754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 1004
73.8%
2 192
 
14.1%
3 74
 
5.4%
4 30
 
2.2%
5 20
 
1.5%
6 11
 
0.8%
7 10
 
0.7%
9 8
 
0.6%
8 6
 
0.4%
10 2
 
0.1%
Other values (4) 4
 
0.3%
ValueCountFrequency (%)
1 1004
73.8%
2 192
 
14.1%
3 74
 
5.4%
4 30
 
2.2%
5 20
 
1.5%
6 11
 
0.8%
7 10
 
0.7%
8 6
 
0.4%
9 8
 
0.6%
10 2
 
0.1%
ValueCountFrequency (%)
14 1
 
0.1%
13 1
 
0.1%
12 1
 
0.1%
11 1
 
0.1%
10 2
 
0.1%
9 8
 
0.6%
8 6
 
0.4%
7 10
0.7%
6 11
0.8%
5 20
1.5%

지역구분
Categorical

Distinct17
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size10.8 KiB
경기
455 
서울
417 
경북
124 
인천
70 
부산
47 
Other values (12)
248 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기
2nd row인천
3rd row경북
4th row서울
5th row경기

Common Values

ValueCountFrequency (%)
경기 455
33.4%
서울 417
30.6%
경북 124
 
9.1%
인천 70
 
5.1%
부산 47
 
3.5%
대구 46
 
3.4%
전남 37
 
2.7%
경남 34
 
2.5%
충남 26
 
1.9%
충북 24
 
1.8%
Other values (7) 81
 
6.0%

Length

2024-03-23T14:34:19.518335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 455
33.4%
서울 417
30.6%
경북 124
 
9.1%
인천 70
 
5.1%
부산 47
 
3.5%
대구 46
 
3.4%
전남 37
 
2.7%
경남 34
 
2.5%
충남 26
 
1.9%
충북 24
 
1.8%
Other values (7) 81
 
6.0%

업종
Categorical

Distinct20
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size10.8 KiB
건설업
381 
도매 및 소매업
283 
제조업
226 
숙박 및 음식점업
195 
정보통신업
95 
Other values (15)
181 

Length

Max length24
Median length23
Mean length6.9588538
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row도매 및 소매업
2nd row도매 및 소매업
3rd row숙박 및 음식점업
4th row도매 및 소매업
5th row건설업

Common Values

ValueCountFrequency (%)
건설업 381
28.0%
도매 및 소매업 283
20.8%
제조업 226
16.6%
숙박 및 음식점업 195
14.3%
정보통신업 95
 
7.0%
전문, 과학 및 기술 서비스업 80
 
5.9%
사업시설 관리 사업 지원 및 임대 서비스업 34
 
2.5%
사업시설 관리, 사업 지원 및 임대 서비스업 24
 
1.8%
운수 및 창고업 11
 
0.8%
부동산업 5
 
0.4%
Other values (10) 27
 
2.0%

Length

2024-03-23T14:34:19.728533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
및 647
20.9%
건설업 381
12.3%
소매업 283
9.1%
도매 283
9.1%
제조업 226
 
7.3%
숙박 195
 
6.3%
음식점업 195
 
6.3%
서비스업 152
 
4.9%
정보통신업 95
 
3.1%
기술 80
 
2.6%
Other values (36) 562
18.1%

산업분류
Text

Distinct281
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size10.8 KiB
2024-03-23T14:34:20.331827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length15.501837
Min length3

Characters and Unicode

Total characters21098
Distinct characters280
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)11.0%

Sample

1st row컴퓨터 및 주변장치, 소프트웨어 도매업
2nd row주방용품 및 가정용 유리, 요업제품 소매업
3rd row한식 일반 음식점업
4th row남녀용 겉옷 및 셔츠 도매업
5th row도배, 실내 장식 및 내장 목공사업
ValueCountFrequency (%)
및 752
 
12.1%
내장 274
 
4.4%
도배 273
 
4.4%
목공사업 273
 
4.4%
장식 228
 
3.7%
실내 228
 
3.7%
제조업 193
 
3.1%
기타 190
 
3.1%
음식점업 178
 
2.9%
유사 175
 
2.8%
Other values (472) 3435
55.4%
2024-03-23T14:34:21.215411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4846
23.0%
업 1385
 
6.6%
및 752
 
3.6%
, 678
 
3.2%
장 657
 
3.1%
사 593
 
2.8%
내 556
 
2.6%
공 498
 
2.4%
식 489
 
2.3%
도 478
 
2.3%
Other values (270) 10166
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15527
73.6%
Space Separator 4846
 
23.0%
Other Punctuation 714
 
3.4%
Decimal Number 7
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1385
 
8.9%
및 752
 
4.8%
장 657
 
4.2%
사 593
 
3.8%
내 556
 
3.6%
공 498
 
3.2%
식 489
 
3.1%
도 478
 
3.1%
기 372
 
2.4%
목 316
 
2.0%
Other values (264) 9431
60.7%
Other Punctuation
ValueCountFrequency (%)
, 678
95.0%
· 36
 
5.0%
Space Separator
ValueCountFrequency (%)
4846
100.0%
Decimal Number
ValueCountFrequency (%)
1 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15527
73.6%
Common 5571
 
26.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1385
 
8.9%
및 752
 
4.8%
장 657
 
4.2%
사 593
 
3.8%
내 556
 
3.6%
공 498
 
3.2%
식 489
 
3.1%
도 478
 
3.1%
기 372
 
2.4%
목 316
 
2.0%
Other values (264) 9431
60.7%
Common
ValueCountFrequency (%)
4846
87.0%
, 678
 
12.2%
· 36
 
0.6%
1 7
 
0.1%
( 2
 
< 0.1%
) 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15514
73.5%
ASCII 5535
 
26.2%
None 36
 
0.2%
Compat Jamo 13
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4846
87.6%
, 678
 
12.2%
1 7
 
0.1%
( 2
 
< 0.1%
) 2
 
< 0.1%
Hangul
ValueCountFrequency (%)
업 1385
 
8.9%
및 752
 
4.8%
장 657
 
4.2%
사 593
 
3.8%
내 556
 
3.6%
공 498
 
3.2%
식 489
 
3.2%
도 478
 
3.1%
기 372
 
2.4%
목 316
 
2.0%
Other values (263) 9418
60.7%
None
ValueCountFrequency (%)
· 36
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 13
100.0%

Interactions

2024-03-23T14:34:15.914101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:34:15.549304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:34:16.132682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:34:15.728851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T14:34:21.418247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
참여년도사업자번호취업인원지역구분업종
참여년도1.0000.0760.0940.2310.486
사업자번호0.0761.0000.1630.5790.313
취업인원0.0940.1631.0000.0960.223
지역구분0.2310.5790.0961.0000.385
업종0.4860.3130.2230.3851.000
2024-03-23T14:34:21.614985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역구분업종참여년도
지역구분1.0000.1270.129
업종0.1271.0000.247
참여년도0.1290.2471.000
2024-03-23T14:34:21.787004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업자번호취업인원참여년도지역구분업종
사업자번호1.0000.0100.0450.2680.104
취업인원0.0101.0000.0560.0370.072
참여년도0.0450.0561.0000.1290.247
지역구분0.2680.0370.1291.0000.127
업종0.1040.0720.2470.1271.000

Missing values

2024-03-23T14:34:16.364258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T14:34:16.580017image/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

참여년도기업명사업자번호취업인원지역구분업종산업분류
02023(주)삼성비지니스솔루션10186480341경기도매 및 소매업컴퓨터 및 주변장치, 소프트웨어 도매업
12023한샘키친강서대리점10514487611인천도매 및 소매업주방용품 및 가정용 유리, 요업제품 소매업
22023야심족발10577004191경북숙박 및 음식점업한식 일반 음식점업
32023(주)빌리버스10587086471서울도매 및 소매업남녀용 겉옷 및 셔츠 도매업
42023스타테크(주)10588179161경기건설업도배, 실내 장식 및 내장 목공사업
52023(주)에이샵10681825371서울도매 및 소매업컴퓨터 및 주변장치, 소프트웨어 소매업
62023타래I&D10708566831경기도매 및 소매업생활용 가구 도매업
72023(주)인밸류비즈10786112151서울정보통신업시스템 소프트웨어 개발 및 공급업
82023(주)두잇시스템10786464995서울정보통신업컴퓨터시스템 통합 자문 및 구축 서비스업
92023(주)챔프정보10786732975서울정보통신업시스템 소프트웨어 개발 및 공급업
참여년도기업명사업자번호취업인원지역구분업종산업분류
13512020노을21165096721서울건설업도배, 실내장식 및 내장 목공사업
13522020(주)디자인누리(오너쉽변경)13586502651경기도매 및 소매업생활용 가구 도매업
13532020한샘리하우스이끔대리점33809004751인천전문, 과학 및 기술 서비스업인테리어 디자인업
13542020(주)리움디자인86688013531경기건설업도배, 실내장식 및 내장 목공사업
13552020(주)한샘리하우스지와이디자인대리점53881016001서울전문, 과학 및 기술 서비스업인테리어 디자인업
13562020한샘리하우스수원중앙대리점48626008781경기도매 및 소매업그 외 기타 건축자재 도매업
13572020빅플래쉬42086019781서울전문, 과학 및 기술 서비스업광고 대행업
13582020더블유쇼핑22087083111서울정보통신업위성 및 기타 방송업
13592020(주)굿닥43188018181서울정보통신업응용 소프트웨어 개발 및 공급업
13602020도쿄일렉트론코리아13581840382경기도매 및 소매업전기용 기계·장비 및 관련 기자재 도매업