Overview

Dataset statistics

Number of variables7
Number of observations3000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory170.1 KiB
Average record size in memory58.0 B

Variable types

DateTime1
Categorical2
Text2
Numeric2

Dataset

Description기업별 채용정보 및 인재정보, 채용 관련 박람회 정보 등을 제공하는 중소기업 전문 일자리플랫폼((舊)잡월드-> i-ONE JOB)에 공고되는 산업별 채용 통계현황
URLhttps://www.data.go.kr/data/15083026/fileData.do

Alerts

업종코드 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 업종코드High correlation

Reproduction

Analysis started2023-12-12 08:20:31.673360
Analysis finished2023-12-12 08:20:32.769251
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준연월
Date

Distinct52
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
Minimum2018-09-01 00:00:00
Maximum2022-12-01 00:00:00
2023-12-12T17:20:32.857457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:33.007392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업종
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
생산·제조
508 
IT·인터넷
454 
경영·사무
372 
영업·고객상담
339 
유통·무역
319 
Other values (8)
1008 

Length

Max length7
Median length6
Mean length4.5613333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경영·사무
2nd row경영·사무
3rd row경영·사무
4th row경영·사무
5th row영업·고객상담

Common Values

ValueCountFrequency (%)
생산·제조 508
16.9%
IT·인터넷 454
15.1%
경영·사무 372
12.4%
영업·고객상담 339
11.3%
유통·무역 319
10.6%
의료 286
9.5%
서비스 188
 
6.3%
건설 184
 
6.1%
디자인 144
 
4.8%
전문직 100
 
3.3%
Other values (3) 106
 
3.5%

Length

2023-12-12T17:20:33.187198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
생산·제조 508
16.9%
it·인터넷 454
15.1%
경영·사무 372
12.4%
영업·고객상담 339
11.3%
유통·무역 319
10.6%
의료 286
9.5%
서비스 188
 
6.3%
건설 184
 
6.1%
디자인 144
 
4.8%
전문직 100
 
3.3%
Other values (3) 106
 
3.5%

업종코드
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
J3
508 
J4
454 
J1
372 
J2
339 
J10
319 
Other values (8)
1008 

Length

Max length3
Median length2
Mean length2.3123333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJ1
2nd rowJ1
3rd rowJ1
4th rowJ1
5th rowJ2

Common Values

ValueCountFrequency (%)
J3 508
16.9%
J4 454
15.1%
J1 372
12.4%
J2 339
11.3%
J10 319
10.6%
J13 286
9.5%
J11 188
 
6.3%
J9 184
 
6.1%
J12 144
 
4.8%
J5 100
 
3.3%
Other values (3) 106
 
3.5%

Length

2023-12-12T17:20:33.343199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
j3 508
16.9%
j4 454
15.1%
j1 372
12.4%
j2 339
11.3%
j10 319
10.6%
j13 286
9.5%
j11 188
 
6.3%
j9 184
 
6.1%
j12 144
 
4.8%
j5 100
 
3.3%
Other values (3) 106
 
3.5%

세부산업
Text

Distinct127
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2023-12-12T17:20:33.606121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.889
Min length2

Characters and Unicode

Total characters23667
Distinct characters268
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.4%

Sample

1st row기획·전략·경영
2nd row총무·법무·사무
3rd row경리·출납·결산
4th row사무보조·문서작성
5th row일반영업
ValueCountFrequency (%)
기획·전략·경영 51
 
1.7%
물류·유통·운송 51
 
1.7%
경리·출납·결산 51
 
1.7%
총무·법무·사무 51
 
1.7%
일반영업 51
 
1.7%
금속·금형 51
 
1.7%
연구소·r&d 50
 
1.7%
생산·제조·포장·조립 50
 
1.7%
생산관리·품질관리 50
 
1.7%
영업기획·관리·지원 50
 
1.7%
Other values (117) 2494
83.1%
2023-12-12T17:20:34.061324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
· 4134
 
17.5%
사 692
 
2.9%
무 629
 
2.7%
기 543
 
2.3%
리 478
 
2.0%
영 456
 
1.9%
업 372
 
1.6%
인 348
 
1.5%
자 304
 
1.3%
디 276
 
1.2%
Other values (258) 15435
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17932
75.8%
Other Punctuation 4184
 
17.7%
Uppercase Letter 1467
 
6.2%
Close Punctuation 30
 
0.1%
Open Punctuation 30
 
0.1%
Lowercase Letter 24
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 692
 
3.9%
무 629
 
3.5%
기 543
 
3.0%
리 478
 
2.7%
영 456
 
2.5%
업 372
 
2.1%
인 348
 
1.9%
자 304
 
1.7%
디 276
 
1.5%
관 265
 
1.5%
Other values (235) 13569
75.7%
Uppercase Letter
ValueCountFrequency (%)
C 230
15.7%
A 204
13.9%
D 196
13.4%
M 159
10.8%
R 138
9.4%
I 136
9.3%
P 85
 
5.8%
S 81
 
5.5%
T 78
 
5.3%
G 46
 
3.1%
Other values (6) 114
7.8%
Lowercase Letter
ValueCountFrequency (%)
a 8
33.3%
m 8
33.3%
e 8
33.3%
Other Punctuation
ValueCountFrequency (%)
· 4134
98.8%
& 50
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17932
75.8%
Common 4244
 
17.9%
Latin 1491
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 692
 
3.9%
무 629
 
3.5%
기 543
 
3.0%
리 478
 
2.7%
영 456
 
2.5%
업 372
 
2.1%
인 348
 
1.9%
자 304
 
1.7%
디 276
 
1.5%
관 265
 
1.5%
Other values (235) 13569
75.7%
Latin
ValueCountFrequency (%)
C 230
15.4%
A 204
13.7%
D 196
13.1%
M 159
10.7%
R 138
9.3%
I 136
9.1%
P 85
 
5.7%
S 81
 
5.4%
T 78
 
5.2%
G 46
 
3.1%
Other values (9) 138
9.3%
Common
ValueCountFrequency (%)
· 4134
97.4%
& 50
 
1.2%
) 30
 
0.7%
( 30
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17932
75.8%
None 4134
 
17.5%
ASCII 1601
 
6.8%

Most frequent character per block

None
ValueCountFrequency (%)
· 4134
100.0%
Hangul
ValueCountFrequency (%)
사 692
 
3.9%
무 629
 
3.5%
기 543
 
3.0%
리 478
 
2.7%
영 456
 
2.5%
업 372
 
2.1%
인 348
 
1.9%
자 304
 
1.7%
디 276
 
1.5%
관 265
 
1.5%
Other values (235) 13569
75.7%
ASCII
ValueCountFrequency (%)
C 230
14.4%
A 204
12.7%
D 196
12.2%
M 159
9.9%
R 138
8.6%
I 136
8.5%
P 85
 
5.3%
S 81
 
5.1%
T 78
 
4.9%
& 50
 
3.1%
Other values (12) 244
15.2%

세부산업코드
Text

Distinct127
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size23.6 KiB
2023-12-12T17:20:34.414065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.3123333
Min length4

Characters and Unicode

Total characters12937
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.4%

Sample

1st rowJ101
2nd rowJ102
3rd rowJ103
4th rowJ108
5th rowJ202
ValueCountFrequency (%)
j101 51
 
1.7%
j1001 51
 
1.7%
j103 51
 
1.7%
j102 51
 
1.7%
j202 51
 
1.7%
j301 51
 
1.7%
j518 50
 
1.7%
j315 50
 
1.7%
j309 50
 
1.7%
j209 50
 
1.7%
Other values (117) 2494
83.1%
2023-12-12T17:20:34.927233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
J 3000
23.2%
1 2699
20.9%
0 2535
19.6%
3 1208
9.3%
2 928
 
7.2%
4 805
 
6.2%
9 482
 
3.7%
5 383
 
3.0%
8 361
 
2.8%
7 306
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9937
76.8%
Uppercase Letter 3000
 
23.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2699
27.2%
0 2535
25.5%
3 1208
12.2%
2 928
 
9.3%
4 805
 
8.1%
9 482
 
4.9%
5 383
 
3.9%
8 361
 
3.6%
7 306
 
3.1%
6 230
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
J 3000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9937
76.8%
Latin 3000
 
23.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2699
27.2%
0 2535
25.5%
3 1208
12.2%
2 928
 
9.3%
4 805
 
8.1%
9 482
 
4.9%
5 383
 
3.9%
8 361
 
3.6%
7 306
 
3.1%
6 230
 
2.3%
Latin
ValueCountFrequency (%)
J 3000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12937
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
J 3000
23.2%
1 2699
20.9%
0 2535
19.6%
3 1208
9.3%
2 928
 
7.2%
4 805
 
6.2%
9 482
 
3.7%
5 383
 
3.0%
8 361
 
2.8%
7 306
 
2.4%

공고수
Real number (ℝ)

Distinct49
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.575
Minimum1
Maximum225
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2023-12-12T17:20:35.113737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile14
Maximum225
Range224
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.5645096
Coefficient of variation (CV)1.872024
Kurtosis245.02398
Mean4.575
Median Absolute Deviation (MAD)1
Skewness12.684935
Sum13725
Variance73.350825
MonotonicityNot monotonic
2023-12-12T17:20:35.275336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1 1028
34.3%
2 498
16.6%
3 327
 
10.9%
4 248
 
8.3%
5 192
 
6.4%
6 147
 
4.9%
7 96
 
3.2%
8 85
 
2.8%
9 68
 
2.3%
10 48
 
1.6%
Other values (39) 263
 
8.8%
ValueCountFrequency (%)
1 1028
34.3%
2 498
16.6%
3 327
 
10.9%
4 248
 
8.3%
5 192
 
6.4%
6 147
 
4.9%
7 96
 
3.2%
8 85
 
2.8%
9 68
 
2.3%
10 48
 
1.6%
ValueCountFrequency (%)
225 1
< 0.1%
160 1
< 0.1%
159 1
< 0.1%
119 1
< 0.1%
110 1
< 0.1%
96 1
< 0.1%
83 1
< 0.1%
69 1
< 0.1%
68 1
< 0.1%
61 1
< 0.1%

업종내비중(퍼센트)
Real number (ℝ)

Distinct573
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.599897
Minimum0.36
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.5 KiB
2023-12-12T17:20:35.774138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.36
5-th percentile2
Q16.25
median13.33
Q325
95-th percentile65.9955
Maximum100
Range99.64
Interquartile range (IQR)18.75

Descriptive statistics

Standard deviation20.700587
Coefficient of variation (CV)1.056158
Kurtosis5.4309281
Mean19.599897
Median Absolute Deviation (MAD)8.27
Skewness2.2482364
Sum58799.69
Variance428.51431
MonotonicityNot monotonic
2023-12-12T17:20:35.924152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.0 113
 
3.8%
20.0 94
 
3.1%
50.0 88
 
2.9%
100.0 87
 
2.9%
12.5 86
 
2.9%
33.33 85
 
2.8%
16.67 80
 
2.7%
14.29 56
 
1.9%
9.09 47
 
1.6%
10.0 42
 
1.4%
Other values (563) 2222
74.1%
ValueCountFrequency (%)
0.36 1
 
< 0.1%
0.5 1
 
< 0.1%
0.63 2
0.1%
0.67 4
0.1%
0.76 1
 
< 0.1%
0.83 1
 
< 0.1%
0.87 1
 
< 0.1%
0.88 2
0.1%
0.93 1
 
< 0.1%
0.94 2
0.1%
ValueCountFrequency (%)
100.0 87
2.9%
94.12 1
 
< 0.1%
92.86 1
 
< 0.1%
92.31 2
 
0.1%
91.67 1
 
< 0.1%
90.0 2
 
0.1%
87.5 1
 
< 0.1%
85.71 4
 
0.1%
83.33 4
 
0.1%
80.36 1
 
< 0.1%

Interactions

2023-12-12T17:20:32.293962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:32.111619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:32.396169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:32.201934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:20:36.025306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준연월업종업종코드공고수업종내비중(퍼센트)
기준연월1.0000.0000.0000.0000.279
업종0.0001.0001.0000.1600.582
업종코드0.0001.0001.0000.1600.582
공고수0.0000.1600.1601.0000.402
업종내비중(퍼센트)0.2790.5820.5820.4021.000
2023-12-12T17:20:36.136149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종코드업종
업종코드1.0001.000
업종1.0001.000
2023-12-12T17:20:36.233399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공고수업종내비중(퍼센트)업종업종코드
공고수1.0000.3900.0730.073
업종내비중(퍼센트)0.3901.0000.2860.286
업종0.0730.2861.0001.000
업종코드0.0730.2861.0001.000

Missing values

2023-12-12T17:20:32.568997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:20:32.708160image/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

기준연월업종업종코드세부산업세부산업코드공고수업종내비중(퍼센트)
02018-09경영·사무J1기획·전략·경영J1013272.73
12018-09경영·사무J1총무·법무·사무J10236.82
22018-09경영·사무J1경리·출납·결산J10312.27
32018-09경영·사무J1사무보조·문서작성J108818.18
42018-09영업·고객상담J2일반영업J2023100.0
52018-09생산·제조J3금속·금형J3012100.0
62018-09IT·인터넷J4서버·네트워크·보안J402112.5
72018-09IT·인터넷J4웹기획·PMJ403112.5
82018-09IT·인터넷J4웹개발J404112.5
92018-09IT·인터넷J4웹디자인J412562.5
기준연월업종업종코드세부산업세부산업코드공고수업종내비중(퍼센트)
29902022-12서비스J11외식·식음료J1107125.0
29912022-12서비스J11요리·제빵사·영양사J1112125.0
29922022-12서비스J11가사·청소·육아J1113125.0
29932022-12디자인J12그래픽디자인·CGJ1201150.0
29942022-12디자인J12제품·산업디자인J1203150.0
29952022-12의료J13간호사J1304444.44
29962022-12의료J13간호조무사J1305111.11
29972022-12의료J13의료기사J1306111.11
29982022-12의료J13사무·원무·코디J1307222.22
29992022-12의료J13의료기타직J1309111.11