Overview

Dataset statistics

Number of variables18
Number of observations684
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory98.3 KiB
Average record size in memory147.2 B

Variable types

Categorical17
Text1

Dataset

Description창업기업수를 지역별, 업종별(농업, 임업, 어업, 광업, 제조업, 건설업, 서비스업 등)로 나타낸 데이터
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=3102

Alerts

통계표ID has constant value ""Constant
기관코드 has constant value ""Constant
항목영문명 has constant value ""Constant
수록주기 has constant value ""Constant
항목명 has constant value ""Constant
항목 ID has constant value ""Constant
단위명 has constant value ""Constant
단위영문명 has constant value ""Constant
분류명2 has constant value ""Constant
통계표명 has constant value ""Constant
분류명1 has constant value ""Constant
수록시점 is highly overall correlated with 수집날짜High correlation
수집날짜 is highly overall correlated with 수록시점High correlation
분류값 ID2 is highly overall correlated with 분류값 명2High correlation
분류값 명2 is highly overall correlated with 분류값 ID2High correlation
분류값 ID1 is highly overall correlated with 분류값 명1High correlation
분류값 명1 is highly overall correlated with 분류값 ID1High correlation

Reproduction

Analysis started2024-01-09 22:18:16.400170
Analysis finished2024-01-09 22:18:17.097098
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계표ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
DT_142N_F205
684 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDT_142N_F205
2nd rowDT_142N_F205
3rd rowDT_142N_F205
4th rowDT_142N_F205
5th rowDT_142N_F205

Common Values

ValueCountFrequency (%)
DT_142N_F205 684
100.0%

Length

2024-01-10T07:18:17.145766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:17.217959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
dt_142n_f205 684
100.0%

기관코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
142
684 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row142
2nd row142
3rd row142
4th row142
5th row142

Common Values

ValueCountFrequency (%)
142 684
100.0%

Length

2024-01-10T07:18:17.290956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:17.364047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
142 684
100.0%

분류값 명2
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
소계
 
38
경기
 
38
강원
 
38
충북
 
38
충남
 
38
Other values (13)
494 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소계
2nd row경기
3rd row강원
4th row충북
5th row충남

Common Values

ValueCountFrequency (%)
소계 38
 
5.6%
경기 38
 
5.6%
강원 38
 
5.6%
충북 38
 
5.6%
충남 38
 
5.6%
전북 38
 
5.6%
전남 38
 
5.6%
경북 38
 
5.6%
경남 38
 
5.6%
제주 38
 
5.6%
Other values (8) 304
44.4%

Length

2024-01-10T07:18:17.436520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소계 38
 
5.6%
경기 38
 
5.6%
울산 38
 
5.6%
대전 38
 
5.6%
광주 38
 
5.6%
인천 38
 
5.6%
대구 38
 
5.6%
부산 38
 
5.6%
서울 38
 
5.6%
제주 38
 
5.6%
Other values (8) 304
44.4%

항목영문명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
By industry(number of new enterprises)
684 

Length

Max length38
Median length38
Mean length38
Min length38

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBy industry(number of new enterprises)
2nd rowBy industry(number of new enterprises)
3rd rowBy industry(number of new enterprises)
4th rowBy industry(number of new enterprises)
5th rowBy industry(number of new enterprises)

Common Values

ValueCountFrequency (%)
By industry(number of new enterprises) 684
100.0%

Length

2024-01-10T07:18:17.526037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:17.599957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
by 684
20.0%
industry(number 684
20.0%
of 684
20.0%
new 684
20.0%
enterprises 684
20.0%

수록주기
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
M
684 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 684
100.0%

Length

2024-01-10T07:18:17.679332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:17.761744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 684
100.0%

항목명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
전체
684 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전체 684
100.0%

Length

2024-01-10T07:18:17.857741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:17.954498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 684
100.0%

항목 ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
16142T1
684 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row16142T1
2nd row16142T1
3rd row16142T1
4th row16142T1
5th row16142T1

Common Values

ValueCountFrequency (%)
16142T1 684
100.0%

Length

2024-01-10T07:18:18.030191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:18.105021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
16142t1 684
100.0%

단위명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
개
684 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개 684
100.0%

Length

2024-01-10T07:18:18.185964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:18.258975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개 684
100.0%

분류값 ID1
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
A1
 
36
A11
 
36
B1
 
36
C1
 
36
D1
 
36
Other values (14)
504 

Length

Max length3
Median length3
Mean length2.7368421
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA1
2nd rowA1
3rd rowA1
4th rowA1
5th rowA1

Common Values

ValueCountFrequency (%)
A1 36
 
5.3%
A11 36
 
5.3%
B1 36
 
5.3%
C1 36
 
5.3%
D1 36
 
5.3%
F1 36
 
5.3%
S11 36
 
5.3%
S12 36
 
5.3%
S13 36
 
5.3%
S14 36
 
5.3%
Other values (9) 324
47.4%

Length

2024-01-10T07:18:18.334519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
a1 36
 
5.3%
s15 36
 
5.3%
s22 36
 
5.3%
s21 36
 
5.3%
s20 36
 
5.3%
s19 36
 
5.3%
s18 36
 
5.3%
s17 36
 
5.3%
s16 36
 
5.3%
s14 36
 
5.3%
Other values (9) 324
47.4%

분류값 ID2
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
Z1
 
38
Z10
 
38
Z11
 
38
Z12
 
38
Z13
 
38
Other values (13)
494 

Length

Max length3
Median length2.5
Mean length2.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowZ1
2nd rowZ10
3rd rowZ11
4th rowZ12
5th rowZ13

Common Values

ValueCountFrequency (%)
Z1 38
 
5.6%
Z10 38
 
5.6%
Z11 38
 
5.6%
Z12 38
 
5.6%
Z13 38
 
5.6%
Z14 38
 
5.6%
Z15 38
 
5.6%
Z16 38
 
5.6%
Z17 38
 
5.6%
Z18 38
 
5.6%
Other values (8) 304
44.4%

Length

2024-01-10T07:18:18.424311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
z1 38
 
5.6%
z10 38
 
5.6%
z8 38
 
5.6%
z7 38
 
5.6%
z6 38
 
5.6%
z5 38
 
5.6%
z4 38
 
5.6%
z3 38
 
5.6%
z2 38
 
5.6%
z18 38
 
5.6%
Other values (8) 304
44.4%

단위영문명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
EA
684 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
EA 684
100.0%

Length

2024-01-10T07:18:18.516660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:18.586567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ea 684
100.0%

분류명2
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
지역별
684 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지역별 684
100.0%

Length

2024-01-10T07:18:18.659740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:18.732268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지역별 684
100.0%

수치값
Text

Distinct418
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
2024-01-10T07:18:18.993286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.6652047
Min length1

Characters and Unicode

Total characters1823
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique300 ?
Unique (%)43.9%

Sample

1st row104068
2nd row31662
3rd row2856
4th row3145
5th row4424
ValueCountFrequency (%)
x 25
 
3.7%
5 10
 
1.5%
9 9
 
1.3%
4 9
 
1.3%
8 8
 
1.2%
3 8
 
1.2%
85 7
 
1.0%
12 7
 
1.0%
17 6
 
0.9%
92 6
 
0.9%
Other values (408) 589
86.1%
2024-01-10T07:18:19.397936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 328
18.0%
2 198
10.9%
3 192
10.5%
5 191
10.5%
4 158
8.7%
6 154
8.4%
8 151
8.3%
7 148
8.1%
9 137
7.5%
0 137
7.5%
Other values (2) 29
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1794
98.4%
Uppercase Letter 25
 
1.4%
Dash Punctuation 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 328
18.3%
2 198
11.0%
3 192
10.7%
5 191
10.6%
4 158
8.8%
6 154
8.6%
8 151
8.4%
7 148
8.2%
9 137
7.6%
0 137
7.6%
Uppercase Letter
ValueCountFrequency (%)
X 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1798
98.6%
Latin 25
 
1.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 328
18.2%
2 198
11.0%
3 192
10.7%
5 191
10.6%
4 158
8.8%
6 154
8.6%
8 151
8.4%
7 148
8.2%
9 137
7.6%
0 137
7.6%
Latin
ValueCountFrequency (%)
X 25
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1823
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 328
18.0%
2 198
10.9%
3 192
10.5%
5 191
10.5%
4 158
8.7%
6 154
8.4%
8 151
8.3%
7 148
8.1%
9 137
7.5%
0 137
7.5%
Other values (2) 29
 
1.6%

분류값 명1
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
합계
 
36
기술기반업종
 
36
농업 임업 및 어업 및 광업
 
36
제조업
 
36
전기 가스 증기 및 공기 조절 공급업
 
36
Other values (14)
504 

Length

Max length23
Median length18
Mean length11.210526
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
합계 36
 
5.3%
기술기반업종 36
 
5.3%
농업 임업 및 어업 및 광업 36
 
5.3%
제조업 36
 
5.3%
전기 가스 증기 및 공기 조절 공급업 36
 
5.3%
건설업 36
 
5.3%
수도 하수 및 폐기물 처리 원료 재생업 36
 
5.3%
도매 및 소매업 36
 
5.3%
운수 및 창고업 36
 
5.3%
숙박 및 음식점업 36
 
5.3%
Other values (9) 324
47.4%

Length

2024-01-10T07:18:19.512532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
및 504
 
20.3%
서비스업 216
 
8.7%
합계 36
 
1.4%
지원 36
 
1.4%
금융 36
 
1.4%
보험업 36
 
1.4%
부동산업 36
 
1.4%
전문 36
 
1.4%
과학 36
 
1.4%
기술 36
 
1.4%
Other values (41) 1476
59.4%

수록시점
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
202308
342 
202309
342 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202308
2nd row202308
3rd row202308
4th row202308
5th row202308

Common Values

ValueCountFrequency (%)
202308 342
50.0%
202309 342
50.0%

Length

2024-01-10T07:18:19.601733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:19.679204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202308 342
50.0%
202309 342
50.0%

통계표명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
지역별 · 업종별 창업기업수
684 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지역별 · 업종별 창업기업수
2nd row지역별 · 업종별 창업기업수
3rd row지역별 · 업종별 창업기업수
4th row지역별 · 업종별 창업기업수
5th row지역별 · 업종별 창업기업수

Common Values

ValueCountFrequency (%)
지역별 · 업종별 창업기업수 684
100.0%

Length

2024-01-10T07:18:19.764732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:19.836121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지역별 684
25.0%
· 684
25.0%
업종별 684
25.0%
창업기업수 684
25.0%

분류명1
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
업종별
684 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
업종별 684
100.0%

Length

2024-01-10T07:18:19.909771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:19.983937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
업종별 684
100.0%

수집날짜
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
20231109
342 
20231209
342 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20231109
2nd row20231109
3rd row20231109
4th row20231109
5th row20231109

Common Values

ValueCountFrequency (%)
20231109 342
50.0%
20231209 342
50.0%

Length

2024-01-10T07:18:20.056758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:18:20.129750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20231109 342
50.0%
20231209 342
50.0%

Correlations

2024-01-10T07:18:20.181345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류값 명2분류값 ID1분류값 ID2분류값 명1수록시점수집날짜
분류값 명21.0000.0001.0000.0000.0000.000
분류값 ID10.0001.0000.0001.0000.0000.000
분류값 ID21.0000.0001.0000.0000.0000.000
분류값 명10.0001.0000.0001.0000.0000.000
수록시점0.0000.0000.0000.0001.0001.000
수집날짜0.0000.0000.0000.0001.0001.000
2024-01-10T07:18:20.263172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수록시점수집날짜분류값 ID2분류값 명2분류값 ID1분류값 명1
수록시점1.0000.9970.0000.0000.0000.000
수집날짜0.9971.0000.0000.0000.0000.000
분류값 ID20.0000.0001.0001.0000.0000.000
분류값 명20.0000.0001.0001.0000.0000.000
분류값 ID10.0000.0000.0000.0001.0001.000
분류값 명10.0000.0000.0000.0001.0001.000
2024-01-10T07:18:20.342696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류값 명2분류값 ID1분류값 ID2분류값 명1수록시점수집날짜
분류값 명21.0000.0001.0000.0000.0000.000
분류값 ID10.0001.0000.0001.0000.0000.000
분류값 ID21.0000.0001.0000.0000.0000.000
분류값 명10.0001.0000.0001.0000.0000.000
수록시점0.0000.0000.0000.0001.0000.997
수집날짜0.0000.0000.0000.0000.9971.000

Missing values

2024-01-10T07:18:16.850947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:18:17.032495image/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

통계표ID기관코드분류값 명2항목영문명수록주기항목명항목 ID단위명분류값 ID1분류값 ID2단위영문명분류명2수치값분류값 명1수록시점통계표명분류명1수집날짜
0DT_142N_F205142소계By industry(number of new enterprises)M전체16142T1개A1Z1EA지역별104068합계202308지역별 · 업종별 창업기업수업종별20231109
1DT_142N_F205142경기By industry(number of new enterprises)M전체16142T1개A1Z10EA지역별31662합계202308지역별 · 업종별 창업기업수업종별20231109
2DT_142N_F205142강원By industry(number of new enterprises)M전체16142T1개A1Z11EA지역별2856합계202308지역별 · 업종별 창업기업수업종별20231109
3DT_142N_F205142충북By industry(number of new enterprises)M전체16142T1개A1Z12EA지역별3145합계202308지역별 · 업종별 창업기업수업종별20231109
4DT_142N_F205142충남By industry(number of new enterprises)M전체16142T1개A1Z13EA지역별4424합계202308지역별 · 업종별 창업기업수업종별20231109
5DT_142N_F205142전북By industry(number of new enterprises)M전체16142T1개A1Z14EA지역별3444합계202308지역별 · 업종별 창업기업수업종별20231109
6DT_142N_F205142전남By industry(number of new enterprises)M전체16142T1개A1Z15EA지역별3417합계202308지역별 · 업종별 창업기업수업종별20231109
7DT_142N_F205142경북By industry(number of new enterprises)M전체16142T1개A1Z16EA지역별4670합계202308지역별 · 업종별 창업기업수업종별20231109
8DT_142N_F205142경남By industry(number of new enterprises)M전체16142T1개A1Z17EA지역별5452합계202308지역별 · 업종별 창업기업수업종별20231109
9DT_142N_F205142제주By industry(number of new enterprises)M전체16142T1개A1Z18EA지역별1447합계202308지역별 · 업종별 창업기업수업종별20231109
통계표ID기관코드분류값 명2항목영문명수록주기항목명항목 ID단위명분류값 ID1분류값 ID2단위영문명분류명2수치값분류값 명1수록시점통계표명분류명1수집날짜
674DT_142N_F205142경남By industry(number of new enterprises)M전체16142T1개S23Z17EA지역별214협회 및 단체 수리 및 기타 개인 서비스업202309지역별 · 업종별 창업기업수업종별20231209
675DT_142N_F205142제주By industry(number of new enterprises)M전체16142T1개S23Z18EA지역별64협회 및 단체 수리 및 기타 개인 서비스업202309지역별 · 업종별 창업기업수업종별20231209
676DT_142N_F205142서울By industry(number of new enterprises)M전체16142T1개S23Z2EA지역별778협회 및 단체 수리 및 기타 개인 서비스업202309지역별 · 업종별 창업기업수업종별20231209
677DT_142N_F205142부산By industry(number of new enterprises)M전체16142T1개S23Z3EA지역별255협회 및 단체 수리 및 기타 개인 서비스업202309지역별 · 업종별 창업기업수업종별20231209
678DT_142N_F205142대구By industry(number of new enterprises)M전체16142T1개S23Z4EA지역별180협회 및 단체 수리 및 기타 개인 서비스업202309지역별 · 업종별 창업기업수업종별20231209
679DT_142N_F205142인천By industry(number of new enterprises)M전체16142T1개S23Z5EA지역별259협회 및 단체 수리 및 기타 개인 서비스업202309지역별 · 업종별 창업기업수업종별20231209
680DT_142N_F205142광주By industry(number of new enterprises)M전체16142T1개S23Z6EA지역별197협회 및 단체 수리 및 기타 개인 서비스업202309지역별 · 업종별 창업기업수업종별20231209
681DT_142N_F205142대전By industry(number of new enterprises)M전체16142T1개S23Z7EA지역별148협회 및 단체 수리 및 기타 개인 서비스업202309지역별 · 업종별 창업기업수업종별20231209
682DT_142N_F205142울산By industry(number of new enterprises)M전체16142T1개S23Z8EA지역별62협회 및 단체 수리 및 기타 개인 서비스업202309지역별 · 업종별 창업기업수업종별20231209
683DT_142N_F205142세종By industry(number of new enterprises)M전체16142T1개S23Z9EA지역별31협회 및 단체 수리 및 기타 개인 서비스업202309지역별 · 업종별 창업기업수업종별20231209