Overview

Dataset statistics

Number of variables19
Number of observations30
Missing cells17
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory161.4 B

Variable types

DateTime2
Categorical12
Text3
Numeric2

Dataset

Description샘플 데이터
Author한국평가데이터㈜
URLhttps://bigdata-region.kr/#/dataset/bdf91610-b1ba-4012-9c93-cd5adcba6f1d

Alerts

기준년월 has constant value ""Constant
시도명 has constant value ""Constant
등록일 has constant value ""Constant
작업자명 has constant value ""Constant
업종대분류명 is highly overall correlated with 업종대분류코드High correlation
기업규모 is highly overall correlated with 기업규모명High correlation
대표자성별 is highly overall correlated with 업력구간코드 and 3 other fieldsHigh correlation
기업규모명 is highly overall correlated with 기업규모High correlation
대표자성별명 is highly overall correlated with 업력구간코드 and 3 other fieldsHigh correlation
업종대분류코드 is highly overall correlated with 업종대분류명High correlation
업력구간코드 is highly overall correlated with 업력구간명 and 2 other fieldsHigh correlation
연구개발투자금액 is highly overall correlated with 총기업수High correlation
시군구명 is highly overall correlated with 대표자성별 and 1 other fieldsHigh correlation
업력구간명 is highly overall correlated with 업력구간코드 and 2 other fieldsHigh correlation
총기업수 is highly overall correlated with 연구개발투자금액High correlation
총기업수 is highly imbalanced (73.5%)Imbalance
연구개발투자금액 has 17 (56.7%) missing valuesMissing

Reproduction

Analysis started2023-12-10 13:54:30.883881
Analysis finished2023-12-10 13:54:33.956879
Duration3.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2021-12-01 00:00:00
Maximum2021-12-01 00:00:00
2023-12-10T22:54:34.043366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:54:34.225093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
강원
30 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원 30
100.0%

Length

2023-12-10T22:54:34.412030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:34.567290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원 30
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
강릉시
14 
원주시
6 
삼척시
4 
동해시
2 
속초시
2 
Other values (2)
2 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
강릉시 14
46.7%
원주시 6
20.0%
삼척시 4
 
13.3%
동해시 2
 
6.7%
속초시 2
 
6.7%
고성군 1
 
3.3%
영월군 1
 
3.3%

Length

2023-12-10T22:54:34.724466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:34.909372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강릉시 14
46.7%
원주시 6
20.0%
삼척시 4
 
13.3%
동해시 2
 
6.7%
속초시 2
 
6.7%
고성군 1
 
3.3%
영월군 1
 
3.3%

행정동명
Text

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:54:35.215905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.1333333
Min length2

Characters and Unicode

Total characters94
Distinct characters39
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)66.7%

Sample

1st row강남동
2nd row강동면
3rd row경포동
4th row구정면
5th row사천면
ValueCountFrequency (%)
문막읍 3
 
10.0%
근덕면 3
 
10.0%
사천면 2
 
6.7%
포남1동 2
 
6.7%
간성읍 1
 
3.3%
강남동 1
 
3.3%
북평동 1
 
3.3%
단계동 1
 
3.3%
귀래면 1
 
3.3%
중동면 1
 
3.3%
Other values (14) 14
46.7%
2023-12-10T22:54:35.845437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 18
19.1%
면 10
 
10.6%
포 5
 
5.3%
읍 4
 
4.3%
덕 4
 
4.3%
남 4
 
4.3%
문 3
 
3.2%
근 3
 
3.2%
천 3
 
3.2%
막 3
 
3.2%
Other values (29) 37
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91
96.8%
Decimal Number 3
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 18
19.8%
면 10
 
11.0%
포 5
 
5.5%
읍 4
 
4.4%
덕 4
 
4.4%
남 4
 
4.4%
문 3
 
3.3%
근 3
 
3.3%
천 3
 
3.3%
막 3
 
3.3%
Other values (27) 34
37.4%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91
96.8%
Common 3
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 18
19.8%
면 10
 
11.0%
포 5
 
5.5%
읍 4
 
4.4%
덕 4
 
4.4%
남 4
 
4.4%
문 3
 
3.3%
근 3
 
3.3%
천 3
 
3.3%
막 3
 
3.3%
Other values (27) 34
37.4%
Common
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91
96.8%
ASCII 3
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 18
19.8%
면 10
 
11.0%
포 5
 
5.5%
읍 4
 
4.4%
덕 4
 
4.4%
남 4
 
4.4%
문 3
 
3.3%
근 3
 
3.3%
천 3
 
3.3%
막 3
 
3.3%
Other values (27) 34
37.4%
ASCII
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%

업종대분류코드
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
C
17 
F
5 
G
2 
B
2 
J
 
1
Other values (3)
3 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st rowG
2nd rowC
3rd rowJ
4th rowC
5th rowC

Common Values

ValueCountFrequency (%)
C 17
56.7%
F 5
 
16.7%
G 2
 
6.7%
B 2
 
6.7%
J 1
 
3.3%
N 1
 
3.3%
E 1
 
3.3%
M 1
 
3.3%

Length

2023-12-10T22:54:36.250885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:36.510684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
c 17
56.7%
f 5
 
16.7%
g 2
 
6.7%
b 2
 
6.7%
j 1
 
3.3%
n 1
 
3.3%
e 1
 
3.3%
m 1
 
3.3%

업종중분류코드
Text

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:54:36.841227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters90
Distinct characters18
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 (%)36.7%

Sample

1st rowG46
2nd rowC23
3rd rowJ58
4th rowC10
5th rowC20
ValueCountFrequency (%)
c23 5
16.7%
f42 4
13.3%
c10 2
 
6.7%
c22 2
 
6.7%
c25 2
 
6.7%
b07 2
 
6.7%
c29 2
 
6.7%
c27 1
 
3.3%
g46 1
 
3.3%
f41 1
 
3.3%
Other values (8) 8
26.7%
2023-12-10T22:54:37.316448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 22
24.4%
C 17
18.9%
4 7
 
7.8%
7 6
 
6.7%
3 6
 
6.7%
F 5
 
5.6%
0 5
 
5.6%
5 4
 
4.4%
1 3
 
3.3%
8 3
 
3.3%
Other values (8) 12
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
66.7%
Uppercase Letter 30
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 22
36.7%
4 7
 
11.7%
7 6
 
10.0%
3 6
 
10.0%
0 5
 
8.3%
5 4
 
6.7%
1 3
 
5.0%
8 3
 
5.0%
9 2
 
3.3%
6 2
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
C 17
56.7%
F 5
 
16.7%
B 2
 
6.7%
G 2
 
6.7%
J 1
 
3.3%
N 1
 
3.3%
E 1
 
3.3%
M 1
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 60
66.7%
Latin 30
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 22
36.7%
4 7
 
11.7%
7 6
 
10.0%
3 6
 
10.0%
0 5
 
8.3%
5 4
 
6.7%
1 3
 
5.0%
8 3
 
5.0%
9 2
 
3.3%
6 2
 
3.3%
Latin
ValueCountFrequency (%)
C 17
56.7%
F 5
 
16.7%
B 2
 
6.7%
G 2
 
6.7%
J 1
 
3.3%
N 1
 
3.3%
E 1
 
3.3%
M 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 22
24.4%
C 17
18.9%
4 7
 
7.8%
7 6
 
6.7%
3 6
 
6.7%
F 5
 
5.6%
0 5
 
5.6%
5 4
 
4.4%
1 3
 
3.3%
8 3
 
3.3%
Other values (8) 12
13.3%

업종대분류명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
제조업
17 
건설업
5 
도매 및 소매업
2 
광업
2 
정보통신업
 
1
Other values (3)
3 

Length

Max length24
Median length3
Mean length5.1333333
Min length2

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row도매 및 소매업
2nd row제조업
3rd row정보통신업
4th row제조업
5th row제조업

Common Values

ValueCountFrequency (%)
제조업 17
56.7%
건설업 5
 
16.7%
도매 및 소매업 2
 
6.7%
광업 2
 
6.7%
정보통신업 1
 
3.3%
사업시설 관리; 사업 지원 및 임대 서비스업 1
 
3.3%
수도; 하수 및 폐기물 처리; 원료 재생업 1
 
3.3%
전문; 과학 및 기술 서비스업 1
 
3.3%

Length

2023-12-10T22:54:37.572611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:37.754102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제조업 17
34.0%
및 5
 
10.0%
건설업 5
 
10.0%
도매 2
 
4.0%
소매업 2
 
4.0%
광업 2
 
4.0%
서비스업 2
 
4.0%
하수 1
 
2.0%
과학 1
 
2.0%
전문 1
 
2.0%
Other values (12) 12
24.0%

업종중분류명
Text

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:54:38.060634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length13.633333
Min length3

Characters and Unicode

Total characters409
Distinct characters86
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)36.7%

Sample

1st row도매 및 상품 중개업
2nd row비금속 광물제품 제조업
3rd row출판업
4th row식료품 제조업
5th row화학물질 및 화학제품 제조업; 의약품 제외
ValueCountFrequency (%)
제조업 17
 
15.3%
및 12
 
10.8%
제외 6
 
5.4%
비금속 5
 
4.5%
광물제품 5
 
4.5%
전문직별 4
 
3.6%
공사업 4
 
3.6%
기계 4
 
3.6%
기타 3
 
2.7%
비금속광물 2
 
1.8%
Other values (40) 49
44.1%
2023-12-10T22:54:38.576071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
19.8%
제 33
 
8.1%
업 31
 
7.6%
조 17
 
4.2%
품 15
 
3.7%
; 14
 
3.4%
비 13
 
3.2%
기 13
 
3.2%
및 12
 
2.9%
광 10
 
2.4%
Other values (76) 170
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 314
76.8%
Space Separator 81
 
19.8%
Other Punctuation 14
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 33
 
10.5%
업 31
 
9.9%
조 17
 
5.4%
품 15
 
4.8%
비 13
 
4.1%
기 13
 
4.1%
및 12
 
3.8%
광 10
 
3.2%
금 9
 
2.9%
물 9
 
2.9%
Other values (74) 152
48.4%
Space Separator
ValueCountFrequency (%)
81
100.0%
Other Punctuation
ValueCountFrequency (%)
; 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 314
76.8%
Common 95
 
23.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 33
 
10.5%
업 31
 
9.9%
조 17
 
5.4%
품 15
 
4.8%
비 13
 
4.1%
기 13
 
4.1%
및 12
 
3.8%
광 10
 
3.2%
금 9
 
2.9%
물 9
 
2.9%
Other values (74) 152
48.4%
Common
ValueCountFrequency (%)
81
85.3%
; 14
 
14.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 314
76.8%
ASCII 95
 
23.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
85.3%
; 14
 
14.7%
Hangul
ValueCountFrequency (%)
제 33
 
10.5%
업 31
 
9.9%
조 17
 
5.4%
품 15
 
4.8%
비 13
 
4.1%
기 13
 
4.1%
및 12
 
3.8%
광 10
 
3.2%
금 9
 
2.9%
물 9
 
2.9%
Other values (74) 152
48.4%

기업규모
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
4
22 
3
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row4
3rd row4
4th row3
5th row4

Common Values

ValueCountFrequency (%)
4 22
73.3%
3 8
 
26.7%

Length

2023-12-10T22:54:38.803922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:39.002588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 22
73.3%
3 8
 
26.7%

기업규모명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
소기업
22 
중기업
8 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중기업
2nd row소기업
3rd row소기업
4th row중기업
5th row소기업

Common Values

ValueCountFrequency (%)
소기업 22
73.3%
중기업 8
 
26.7%

Length

2023-12-10T22:54:39.191301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:39.369336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소기업 22
73.3%
중기업 8
 
26.7%

업력구간코드
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.7
Minimum2
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:54:39.511727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q15
median10
Q320
95-th percentile40
Maximum50
Range48
Interquartile range (IQR)15

Descriptive statistics

Standard deviation12.32645
Coefficient of variation (CV)0.8997409
Kurtosis1.9590871
Mean13.7
Median Absolute Deviation (MAD)5
Skewness1.5566118
Sum411
Variance151.94138
MonotonicityNot monotonic
2023-12-10T22:54:39.785315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
5 9
30.0%
10 8
26.7%
20 6
20.0%
2 3
 
10.0%
40 2
 
6.7%
50 1
 
3.3%
30 1
 
3.3%
ValueCountFrequency (%)
2 3
 
10.0%
5 9
30.0%
10 8
26.7%
20 6
20.0%
30 1
 
3.3%
40 2
 
6.7%
50 1
 
3.3%
ValueCountFrequency (%)
50 1
 
3.3%
40 2
 
6.7%
30 1
 
3.3%
20 6
20.0%
10 8
26.7%
5 9
30.0%
2 3
 
10.0%

업력구간명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
5년이상 10년미만
9 
10년이상 20년미만
8 
20년이상 30년미만
6 
2년이상 5년미만
3 
40년이상 50년미만
2 
Other values (2)
2 

Length

Max length11
Median length11
Mean length10.5
Min length9

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row10년이상 20년미만
2nd row10년이상 20년미만
3rd row10년이상 20년미만
4th row10년이상 20년미만
5th row5년이상 10년미만

Common Values

ValueCountFrequency (%)
5년이상 10년미만 9
30.0%
10년이상 20년미만 8
26.7%
20년이상 30년미만 6
20.0%
2년이상 5년미만 3
 
10.0%
40년이상 50년미만 2
 
6.7%
50년이상 60년미만 1
 
3.3%
30년이상 40년미만 1
 
3.3%

Length

2023-12-10T22:54:40.068401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:40.271600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5년이상 9
15.0%
10년미만 9
15.0%
10년이상 8
13.3%
20년미만 8
13.3%
20년이상 6
10.0%
30년미만 6
10.0%
2년이상 3
 
5.0%
5년미만 3
 
5.0%
40년이상 2
 
3.3%
50년미만 2
 
3.3%
Other values (4) 4
6.7%

대표자성별
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
M
23 
F
7 

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 23
76.7%
F 7
 
23.3%

Length

2023-12-10T22:54:40.509187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:40.679182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 23
76.7%
f 7
 
23.3%

대표자성별명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
남
23 
녀
7 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남 23
76.7%
녀 7
 
23.3%

Length

2023-12-10T22:54:40.974260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:41.119548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 23
76.7%
녀 7
 
23.3%

총기업수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
28 
2
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 28
93.3%
2 1
 
3.3%
3 1
 
3.3%

Length

2023-12-10T22:54:41.404375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:41.958013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 28
93.3%
2 1
 
3.3%
3 1
 
3.3%

기술점수
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
7
15 
6
9 
8
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row8
3rd row8
4th row7
5th row7

Common Values

ValueCountFrequency (%)
7 15
50.0%
6 9
30.0%
8 6
 
20.0%

Length

2023-12-10T22:54:42.179583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:42.368139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7 15
50.0%
6 9
30.0%
8 6
 
20.0%

연구개발투자금액
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)100.0%
Missing17
Missing (%)56.7%
Infinite0
Infinite (%)0.0%
Mean414342.15
Minimum940
Maximum4702592
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:54:42.522110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum940
5-th percentile1036
Q14710
median36451
Q3103936
95-th percentile2017105.4
Maximum4702592
Range4701652
Interquartile range (IQR)99226

Descriptive statistics

Standard deviation1290351.9
Coefficient of variation (CV)3.1142182
Kurtosis12.902762
Mean414342.15
Median Absolute Deviation (MAD)33731
Skewness3.5870836
Sum5386448
Variance1.665008 × 1012
MonotonicityNot monotonic
2023-12-10T22:54:42.693844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
4710 1
 
3.3%
103936 1
 
3.3%
44234 1
 
3.3%
2720 1
 
3.3%
1100 1
 
3.3%
28720 1
 
3.3%
50502 1
 
3.3%
15239 1
 
3.3%
940 1
 
3.3%
226781 1
 
3.3%
Other values (3) 3
 
10.0%
(Missing) 17
56.7%
ValueCountFrequency (%)
940 1
3.3%
1100 1
3.3%
2720 1
3.3%
4710 1
3.3%
15239 1
3.3%
28720 1
3.3%
36451 1
3.3%
44234 1
3.3%
50502 1
3.3%
103936 1
3.3%
ValueCountFrequency (%)
4702592 1
3.3%
226781 1
3.3%
168523 1
3.3%
103936 1
3.3%
50502 1
3.3%
44234 1
3.3%
36451 1
3.3%
28720 1
3.3%
15239 1
3.3%
4710 1
3.3%

등록일
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2021-11-23 00:00:00
Maximum2021-11-23 00:00:00
2023-12-10T22:54:42.884649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:54:43.069945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

작업자명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
KEDSYSTEM
30 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KEDSYSTEM 30
100.0%

Length

2023-12-10T22:54:43.257851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:54:43.407071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kedsystem 30
100.0%

Interactions

2023-12-10T22:54:33.047182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:54:32.793582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:54:33.184120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:54:32.917888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:54:43.553547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명행정동명업종대분류코드업종중분류코드업종대분류명업종중분류명기업규모기업규모명업력구간코드업력구간명대표자성별대표자성별명총기업수기술점수연구개발투자금액
시군구명1.0001.0000.6710.7140.6710.7140.3940.3940.5780.7220.5640.5640.4820.2110.000
행정동명1.0001.0000.9990.8870.9990.8870.9230.9230.9680.9110.8250.8250.0000.8090.000
업종대분류코드0.6710.9991.0001.0001.0001.0000.0000.0000.1540.0000.0000.0000.0000.0000.000
업종중분류코드0.7140.8871.0001.0001.0001.0000.4290.4290.0000.0000.2290.2290.8750.3661.000
업종대분류명0.6710.9991.0001.0001.0001.0000.0000.0000.1540.0000.0000.0000.0000.0000.000
업종중분류명0.7140.8871.0001.0001.0001.0000.4290.4290.0000.0000.2290.2290.8750.3661.000
기업규모0.3940.9230.0000.4290.0000.4291.0000.9900.6250.3900.0000.0000.1230.2900.000
기업규모명0.3940.9230.0000.4290.0000.4290.9901.0000.6250.3900.0000.0000.1230.2900.000
업력구간코드0.5780.9680.1540.0000.1540.0000.6250.6251.0001.0000.7850.7850.0000.7090.081
업력구간명0.7220.9110.0000.0000.0000.0000.3900.3901.0001.0000.5330.5330.0000.5200.000
대표자성별0.5640.8250.0000.2290.0000.2290.0000.0000.7850.5331.0000.9890.0000.0740.000
대표자성별명0.5640.8250.0000.2290.0000.2290.0000.0000.7850.5330.9891.0000.0000.0740.000
총기업수0.4820.0000.0000.8750.0000.8750.1230.1230.0000.0000.0000.0001.0000.3881.000
기술점수0.2110.8090.0000.3660.0000.3660.2900.2900.7090.5200.0740.0740.3881.0000.081
연구개발투자금액0.0000.0000.0001.0000.0001.0000.0000.0000.0810.0000.0000.0001.0000.0811.000
2023-12-10T22:54:43.889250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종대분류명기업규모기술점수대표자성별기업규모명대표자성별명업종대분류코드시군구명업력구간명총기업수
업종대분류명1.0000.0000.0000.0000.0000.0001.0000.4220.0000.000
기업규모0.0001.0000.4590.0000.9120.0000.0000.3750.3710.193
기술점수0.0000.4591.0000.1100.4590.1100.0000.1020.3680.132
대표자성별0.0000.0000.1101.0000.0000.9030.0000.5460.5140.000
기업규모명0.0000.9120.4590.0001.0000.0000.0000.3750.3710.193
대표자성별명0.0000.0000.1100.9030.0001.0000.0000.5460.5140.000
업종대분류코드1.0000.0000.0000.0000.0000.0001.0000.4220.0000.000
시군구명0.4220.3750.1020.5460.3750.5460.4221.0000.3140.332
업력구간명0.0000.3710.3680.5140.3710.5140.0000.3141.0000.000
총기업수0.0000.1930.1320.0000.1930.0000.0000.3320.0001.000
2023-12-10T22:54:44.104082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업력구간코드연구개발투자금액시군구명업종대분류코드업종대분류명기업규모기업규모명업력구간명대표자성별대표자성별명총기업수기술점수
업력구간코드1.0000.1100.3750.0000.0000.4160.4160.9790.5420.5420.0000.361
연구개발투자금액0.1101.0000.0000.0000.0000.0000.0000.0000.0000.0000.9530.151
시군구명0.3750.0001.0000.4220.4220.3750.3750.3140.5460.5460.3320.102
업종대분류코드0.0000.0000.4221.0001.0000.0000.0000.0000.0000.0000.0000.000
업종대분류명0.0000.0000.4221.0001.0000.0000.0000.0000.0000.0000.0000.000
기업규모0.4160.0000.3750.0000.0001.0000.9120.3710.0000.0000.1930.459
기업규모명0.4160.0000.3750.0000.0000.9121.0000.3710.0000.0000.1930.459
업력구간명0.9790.0000.3140.0000.0000.3710.3711.0000.5140.5140.0000.368
대표자성별0.5420.0000.5460.0000.0000.0000.0000.5141.0000.9030.0000.110
대표자성별명0.5420.0000.5460.0000.0000.0000.0000.5140.9031.0000.0000.110
총기업수0.0000.9530.3320.0000.0000.1930.1930.0000.0000.0001.0000.132
기술점수0.3610.1510.1020.0000.0000.4590.4590.3680.1100.1100.1321.000

Missing values

2023-12-10T22:54:33.382131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:54:33.802622image/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

기준년월시도명시군구명행정동명업종대분류코드업종중분류코드업종대분류명업종중분류명기업규모기업규모명업력구간코드업력구간명대표자성별대표자성별명총기업수기술점수연구개발투자금액등록일작업자명
02021-12강원강릉시강남동GG46도매 및 소매업도매 및 상품 중개업3중기업1010년이상 20년미만M남1747102021-11-23KEDSYSTEM
12021-12강원강릉시강동면CC23제조업비금속 광물제품 제조업4소기업1010년이상 20년미만M남181039362021-11-23KEDSYSTEM
22021-12강원강릉시경포동JJ58정보통신업출판업4소기업1010년이상 20년미만M남18<NA>2021-11-23KEDSYSTEM
32021-12강원강릉시구정면CC10제조업식료품 제조업3중기업1010년이상 20년미만M남17<NA>2021-11-23KEDSYSTEM
42021-12강원강릉시사천면CC20제조업화학물질 및 화학제품 제조업; 의약품 제외4소기업55년이상 10년미만M남17442342021-11-23KEDSYSTEM
52021-12강원강릉시사천면CC22제조업고무 및 플라스틱제품 제조업4소기업22년이상 5년미만M남16<NA>2021-11-23KEDSYSTEM
62021-12강원강릉시성덕동CC23제조업비금속 광물제품 제조업4소기업4040년이상 50년미만M남17<NA>2021-11-23KEDSYSTEM
72021-12강원강릉시성산면FF42건설업전문직별 공사업4소기업5050년이상 60년미만F녀17<NA>2021-11-23KEDSYSTEM
82021-12강원강릉시송정동NN75사업시설 관리; 사업 지원 및 임대 서비스업사업지원 서비스업4소기업55년이상 10년미만M남16<NA>2021-11-23KEDSYSTEM
92021-12강원강릉시중앙동BB07광업비금속광물 광업; 연료용 제외4소기업2020년이상 30년미만M남1727202021-11-23KEDSYSTEM
기준년월시도명시군구명행정동명업종대분류코드업종중분류코드업종대분류명업종중분류명기업규모기업규모명업력구간코드업력구간명대표자성별대표자성별명총기업수기술점수연구개발투자금액등록일작업자명
202021-12강원삼척시근덕면FF42건설업전문직별 공사업4소기업2020년이상 30년미만M남17<NA>2021-11-23KEDSYSTEM
212021-12강원속초시노학동MM72전문; 과학 및 기술 서비스업건축기술; 엔지니어링 및 기타 과학기술 서비스업4소기업2020년이상 30년미만M남17<NA>2021-11-23KEDSYSTEM
222021-12강원속초시대포동CC10제조업식료품 제조업4소기업55년이상 10년미만M남272267812021-11-23KEDSYSTEM
232021-12강원영월군중동면BB07광업비금속광물 광업; 연료용 제외3중기업3030년이상 40년미만F녀17<NA>2021-11-23KEDSYSTEM
242021-12강원원주시귀래면CC23제조업비금속 광물제품 제조업4소기업1010년이상 20년미만M남16<NA>2021-11-23KEDSYSTEM
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