Overview

Dataset statistics

Number of variables16
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory136.4 B

Variable types

Categorical12
Text2
Numeric2

Dataset

Description샘플 데이터
Author한국평가데이터㈜
URLhttps://bigdata-region.kr/#/dataset/fe14a358-cc16-41f0-af21-9eb2f509a230

Alerts

기준년월 has constant value ""Constant
등록일 has constant value ""Constant
작업자명 has constant value ""Constant
업종대분류코드 is highly overall correlated with 업종대분류명High correlation
기업규모명 is highly overall correlated with 기업규모High correlation
업종대분류명 is highly overall correlated with 업종대분류코드High correlation
기업규모 is highly overall correlated with 기업규모명High correlation
업력구간코드 is highly overall correlated with 업력구간명High correlation
여신금액합 is highly overall correlated with 시도명 and 2 other fieldsHigh correlation
시도명 is highly overall correlated with 여신금액합 and 1 other fieldsHigh correlation
시군구명 is highly overall correlated with 여신금액합 and 1 other fieldsHigh correlation
행정동명 is highly overall correlated with 여신금액합 and 2 other fieldsHigh correlation
업력구간명 is highly overall correlated with 업력구간코드High correlation
시도명 is highly imbalanced (78.9%)Imbalance
시군구명 is highly imbalanced (78.9%)Imbalance
업력구간코드 has 2 (6.7%) zerosZeros
여신금액합 has 9 (30.0%) zerosZeros

Reproduction

Analysis started2023-12-10 14:17:40.203141
Analysis finished2023-12-10 14:17:42.581500
Duration2.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2020-09
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-09
2nd row2020-09
3rd row2020-09
4th row2020-09
5th row2020-09

Common Values

ValueCountFrequency (%)
2020-09 30
100.0%

Length

2023-12-10T23:17:42.701849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:42.877896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-09 30
100.0%

시도명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
충북
29 
강원
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
충북 29
96.7%
강원 1
 
3.3%

Length

2023-12-10T23:17:43.055912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:43.219013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충북 29
96.7%
강원 1
 
3.3%

시군구명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
충주시
29 
강릉시
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
충주시 29
96.7%
강릉시 1
 
3.3%

Length

2023-12-10T23:17:43.399316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:43.557767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충주시 29
96.7%
강릉시 1
 
3.3%

행정동명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
대소원면
15 
달천동
7 
노은면
2 
목행.용탄동
2 
강남동
 
1
Other values (3)
3 

Length

Max length6
Median length5
Mean length3.7
Min length3

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row강남동
2nd row엄정면
3rd row금가면
4th row노은면
5th row노은면

Common Values

ValueCountFrequency (%)
대소원면 15
50.0%
달천동 7
23.3%
노은면 2
 
6.7%
목행.용탄동 2
 
6.7%
강남동 1
 
3.3%
엄정면 1
 
3.3%
금가면 1
 
3.3%
연수동 1
 
3.3%

Length

2023-12-10T23:17:43.949228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:44.460389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대소원면 15
50.0%
달천동 7
23.3%
노은면 2
 
6.7%
목행.용탄동 2
 
6.7%
강남동 1
 
3.3%
엄정면 1
 
3.3%
금가면 1
 
3.3%
연수동 1
 
3.3%

업종대분류코드
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
C
10 
N
4 
D
3 
G
3 
A
2 
Other values (7)
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique6 ?
Unique (%)20.0%

Sample

1st rowD
2nd rowC
3rd rowR
4th rowA
5th rowC

Common Values

ValueCountFrequency (%)
C 10
33.3%
N 4
 
13.3%
D 3
 
10.0%
G 3
 
10.0%
A 2
 
6.7%
B 2
 
6.7%
R 1
 
3.3%
H 1
 
3.3%
J 1
 
3.3%
K 1
 
3.3%
Other values (2) 2
 
6.7%

Length

2023-12-10T23:17:45.027930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
c 10
33.3%
n 4
 
13.3%
d 3
 
10.0%
g 3
 
10.0%
a 2
 
6.7%
b 2
 
6.7%
r 1
 
3.3%
h 1
 
3.3%
j 1
 
3.3%
k 1
 
3.3%
Other values (2) 2
 
6.7%

업종대분류명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
제조업
10 
사업시설 관리; 사업 지원 및 임대 서비스업
4 
전기; 가스; 증기 및 공기조절 공급업
3 
도매 및 소매업
3 
농업; 임업 및 어업
2 
Other values (7)
8 

Length

Max length24
Median length20
Mean length10.633333
Min length2

Unique

Unique6 ?
Unique (%)20.0%

Sample

1st row전기; 가스; 증기 및 공기조절 공급업
2nd row제조업
3rd row예술; 스포츠 및 여가관련 서비스업
4th row농업; 임업 및 어업
5th row제조업

Common Values

ValueCountFrequency (%)
제조업 10
33.3%
사업시설 관리; 사업 지원 및 임대 서비스업 4
 
13.3%
전기; 가스; 증기 및 공기조절 공급업 3
 
10.0%
도매 및 소매업 3
 
10.0%
농업; 임업 및 어업 2
 
6.7%
광업 2
 
6.7%
예술; 스포츠 및 여가관련 서비스업 1
 
3.3%
운수 및 창고업 1
 
3.3%
정보통신업 1
 
3.3%
금융 및 보험업 1
 
3.3%
Other values (2) 2
 
6.7%

Length

2023-12-10T23:17:45.442255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
및 18
18.0%
제조업 10
 
10.0%
서비스업 7
 
7.0%
사업시설 4
 
4.0%
관리 4
 
4.0%
사업 4
 
4.0%
지원 4
 
4.0%
임대 4
 
4.0%
전기 3
 
3.0%
가스 3
 
3.0%
Other values (25) 39
39.0%

업종중분류코드
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:17:45.758984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters90
Distinct characters21
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

Unique18 ?
Unique (%)60.0%

Sample

1st rowD35
2nd rowC17
3rd rowR91
4th rowA01
5th rowC33
ValueCountFrequency (%)
d35 3
 
10.0%
g46 3
 
10.0%
n76 2
 
6.7%
b07 2
 
6.7%
a01 2
 
6.7%
c30 1
 
3.3%
c33 1
 
3.3%
c29 1
 
3.3%
c11 1
 
3.3%
s94 1
 
3.3%
Other values (13) 13
43.3%
2023-12-10T23:17:46.237529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 10
11.1%
7 9
10.0%
0 8
 
8.9%
1 8
 
8.9%
6 7
 
7.8%
3 7
 
7.8%
5 6
 
6.7%
4 6
 
6.7%
9 5
 
5.6%
2 4
 
4.4%
Other values (11) 20
22.2%

Most occurring categories

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

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 10
33.3%
N 4
 
13.3%
D 3
 
10.0%
G 3
 
10.0%
A 2
 
6.7%
B 2
 
6.7%
H 1
 
3.3%
R 1
 
3.3%
K 1
 
3.3%
J 1
 
3.3%
Other values (2) 2
 
6.7%
Decimal Number
ValueCountFrequency (%)
7 9
15.0%
0 8
13.3%
1 8
13.3%
6 7
11.7%
3 7
11.7%
5 6
10.0%
4 6
10.0%
9 5
8.3%
2 4
6.7%

Most occurring scripts

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

Most frequent character per script

Latin
ValueCountFrequency (%)
C 10
33.3%
N 4
 
13.3%
D 3
 
10.0%
G 3
 
10.0%
A 2
 
6.7%
B 2
 
6.7%
H 1
 
3.3%
R 1
 
3.3%
K 1
 
3.3%
J 1
 
3.3%
Other values (2) 2
 
6.7%
Common
ValueCountFrequency (%)
7 9
15.0%
0 8
13.3%
1 8
13.3%
6 7
11.7%
3 7
11.7%
5 6
10.0%
4 6
10.0%
9 5
8.3%
2 4
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 10
11.1%
7 9
10.0%
0 8
 
8.9%
1 8
 
8.9%
6 7
 
7.8%
3 7
 
7.8%
5 6
 
6.7%
4 6
 
6.7%
9 5
 
5.6%
2 4
 
4.4%
Other values (11) 20
22.2%

업종중분류명
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:17:46.553442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length13.466667
Min length2

Characters and Unicode

Total characters404
Distinct characters95
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)60.0%

Sample

1st row전기; 가스; 증기 및 공기조절 공급업
2nd row펄프; 종이 및 종이제품 제조업
3rd row스포츠 및 오락관련 서비스업
4th row농업
5th row기타 제품 제조업
ValueCountFrequency (%)
및 18
 
15.4%
제조업 10
 
8.5%
제외 6
 
5.1%
서비스업 4
 
3.4%
전기 3
 
2.6%
증기 3
 
2.6%
공기조절 3
 
2.6%
공급업 3
 
2.6%
도매 3
 
2.6%
상품 3
 
2.6%
Other values (49) 61
52.1%
2023-12-10T23:17:47.414154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
21.5%
업 31
 
7.7%
제 23
 
5.7%
및 18
 
4.5%
기 16
 
4.0%
; 16
 
4.0%
조 14
 
3.5%
품 10
 
2.5%
스 8
 
2.0%
비 7
 
1.7%
Other values (85) 174
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 301
74.5%
Space Separator 87
 
21.5%
Other Punctuation 16
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 31
 
10.3%
제 23
 
7.6%
및 18
 
6.0%
기 16
 
5.3%
조 14
 
4.7%
품 10
 
3.3%
스 8
 
2.7%
비 7
 
2.3%
외 7
 
2.3%
공 7
 
2.3%
Other values (83) 160
53.2%
Space Separator
ValueCountFrequency (%)
87
100.0%
Other Punctuation
ValueCountFrequency (%)
; 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 301
74.5%
Common 103
 
25.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 31
 
10.3%
제 23
 
7.6%
및 18
 
6.0%
기 16
 
5.3%
조 14
 
4.7%
품 10
 
3.3%
스 8
 
2.7%
비 7
 
2.3%
외 7
 
2.3%
공 7
 
2.3%
Other values (83) 160
53.2%
Common
ValueCountFrequency (%)
87
84.5%
; 16
 
15.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 300
74.3%
ASCII 103
 
25.5%
Compat Jamo 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
84.5%
; 16
 
15.5%
Hangul
ValueCountFrequency (%)
업 31
 
10.3%
제 23
 
7.7%
및 18
 
6.0%
기 16
 
5.3%
조 14
 
4.7%
품 10
 
3.3%
스 8
 
2.7%
비 7
 
2.3%
외 7
 
2.3%
공 7
 
2.3%
Other values (82) 159
53.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

기업규모
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
4
20 
99
8 
3
 
1
2
 
1

Length

Max length2
Median length1
Mean length1.2666667
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row4
2nd row99
3rd row4
4th row99
5th row4

Common Values

ValueCountFrequency (%)
4 20
66.7%
99 8
 
26.7%
3 1
 
3.3%
2 1
 
3.3%

Length

2023-12-10T23:17:47.640520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:47.798041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 20
66.7%
99 8
 
26.7%
3 1
 
3.3%
2 1
 
3.3%

기업규모명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
소기업
20 
미분류
8 
중기업
 
1
중견기업
 
1

Length

Max length4
Median length3
Mean length3.0333333
Min length3

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
소기업 20
66.7%
미분류 8
 
26.7%
중기업 1
 
3.3%
중견기업 1
 
3.3%

Length

2023-12-10T23:17:48.027919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:48.271678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소기업 20
66.7%
미분류 8
 
26.7%
중기업 1
 
3.3%
중견기업 1
 
3.3%

업력구간코드
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1666667
Minimum0
Maximum60
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:48.425455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.45
Q12
median5
Q310
95-th percentile20
Maximum60
Range60
Interquartile range (IQR)8

Descriptive statistics

Standard deviation11.262031
Coefficient of variation (CV)1.3790242
Kurtosis15.911873
Mean8.1666667
Median Absolute Deviation (MAD)3
Skewness3.6431533
Sum245
Variance126.83333
MonotonicityNot monotonic
2023-12-10T23:17:48.599588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
5 10
33.3%
2 7
23.3%
10 6
20.0%
20 3
 
10.0%
0 2
 
6.7%
1 1
 
3.3%
60 1
 
3.3%
ValueCountFrequency (%)
0 2
 
6.7%
1 1
 
3.3%
2 7
23.3%
5 10
33.3%
10 6
20.0%
20 3
 
10.0%
60 1
 
3.3%
ValueCountFrequency (%)
60 1
 
3.3%
20 3
 
10.0%
10 6
20.0%
5 10
33.3%
2 7
23.3%
1 1
 
3.3%
0 2
 
6.7%

업력구간명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
5년이상 10년미만
10 
2년이상 5년미만
7 
10년이상 20년미만
6 
20년이상 30년미만
3 
1년미만
2 
Other values (2)
2 

Length

Max length11
Median length10
Mean length9.6666667
Min length4

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
5년이상 10년미만 10
33.3%
2년이상 5년미만 7
23.3%
10년이상 20년미만 6
20.0%
20년이상 30년미만 3
 
10.0%
1년미만 2
 
6.7%
1년이상 2년미만 1
 
3.3%
60년이상 70년미만 1
 
3.3%

Length

2023-12-10T23:17:48.818561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:48.988307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5년이상 10
17.2%
10년미만 10
17.2%
2년이상 7
12.1%
5년미만 7
12.1%
10년이상 6
10.3%
20년미만 6
10.3%
20년이상 3
 
5.2%
30년미만 3
 
5.2%
1년미만 2
 
3.4%
1년이상 1
 
1.7%
Other values (3) 3
 
5.2%

총기업수
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
22 
2
5 
6
 
1
7
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)10.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 22
73.3%
2 5
 
16.7%
6 1
 
3.3%
7 1
 
3.3%
3 1
 
3.3%

Length

2023-12-10T23:17:49.186960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:49.340791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 22
73.3%
2 5
 
16.7%
6 1
 
3.3%
7 1
 
3.3%
3 1
 
3.3%

여신금액합
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61015.3
Minimum0
Maximum1201876
Zeros9
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:49.528867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2925
Q326140
95-th percentile153683.4
Maximum1201876
Range1201876
Interquartile range (IQR)26140

Descriptive statistics

Standard deviation219216.68
Coefficient of variation (CV)3.5928148
Kurtosis27.787655
Mean61015.3
Median Absolute Deviation (MAD)2925
Skewness5.1985506
Sum1830459
Variance4.8055951 × 1010
MonotonicityNot monotonic
2023-12-10T23:17:49.779559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 9
30.0%
171786 1
 
3.3%
24928 1
 
3.3%
4872 1
 
3.3%
240 1
 
3.3%
5284 1
 
3.3%
80 1
 
3.3%
2800 1
 
3.3%
61639 1
 
3.3%
131558 1
 
3.3%
Other values (12) 12
40.0%
ValueCountFrequency (%)
0 9
30.0%
80 1
 
3.3%
240 1
 
3.3%
1416 1
 
3.3%
2112 1
 
3.3%
2800 1
 
3.3%
2810 1
 
3.3%
3040 1
 
3.3%
4872 1
 
3.3%
5284 1
 
3.3%
ValueCountFrequency (%)
1201876 1
3.3%
171786 1
3.3%
131558 1
3.3%
69372 1
3.3%
61639 1
3.3%
45676 1
3.3%
35758 1
3.3%
26544 1
3.3%
24928 1
3.3%
19760 1
3.3%

등록일
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2021-11-23
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-11-23
2nd row2021-11-23
3rd row2021-11-23
4th row2021-11-23
5th row2021-11-23

Common Values

ValueCountFrequency (%)
2021-11-23 30
100.0%

Length

2023-12-10T23:17:50.004043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:50.163831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-11-23 30
100.0%

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

2023-12-10T23:17:50.352069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:50.548823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kedsystem 30
100.0%

Interactions

2023-12-10T23:17:41.715790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:41.411907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:41.914418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:41.549015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:17:50.673884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명시군구명행정동명업종대분류코드업종대분류명업종중분류코드업종중분류명기업규모기업규모명업력구간코드업력구간명총기업수여신금액합
시도명1.0000.6551.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.427
시군구명0.6551.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.427
행정동명1.0001.0001.0000.0000.0000.0000.0000.0000.0000.6440.0000.0000.862
업종대분류코드0.0000.0000.0001.0001.0001.0001.0000.0000.0000.0000.0000.5950.847
업종대분류명0.0000.0000.0001.0001.0001.0001.0000.0000.0000.0000.0000.5950.847
업종중분류코드0.0000.0000.0001.0001.0001.0001.0000.9590.9590.8280.0000.0000.773
업종중분류명0.0000.0000.0001.0001.0001.0001.0000.9590.9590.8280.0000.0000.773
기업규모0.0000.0000.0000.0000.0000.9590.9591.0001.0000.0000.5420.0000.422
기업규모명0.0000.0000.0000.0000.0000.9590.9591.0001.0000.0000.5420.0000.422
업력구간코드0.0000.0000.6440.0000.0000.8280.8280.0000.0001.0001.0000.0000.000
업력구간명0.0000.0000.0000.0000.0000.0000.0000.5420.5421.0001.0000.0000.000
총기업수0.0000.0000.0000.5950.5950.0000.0000.0000.0000.0000.0001.0000.000
여신금액합0.4270.4270.8620.8470.8470.7730.7730.4220.4220.0000.0000.0001.000
2023-12-10T23:17:50.922022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종대분류코드기업규모명업종대분류명시도명시군구명기업규모총기업수업력구간명행정동명
업종대분류코드1.0000.0001.0000.0000.0000.0000.3030.0000.000
기업규모명0.0001.0000.0000.0000.0001.0000.0000.3720.000
업종대분류명1.0000.0001.0000.0000.0000.0000.3030.0000.000
시도명0.0000.0000.0001.0000.4540.0000.0000.0000.886
시군구명0.0000.0000.0000.4541.0000.0000.0000.0000.886
기업규모0.0001.0000.0000.0000.0001.0000.0000.3720.000
총기업수0.3030.0000.3030.0000.0000.0001.0000.0000.000
업력구간명0.0000.3720.0000.0000.0000.3720.0001.0000.000
행정동명0.0000.0000.0000.8860.8860.0000.0000.0001.000
2023-12-10T23:17:51.128548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업력구간코드여신금액합시도명시군구명행정동명업종대분류코드업종대분류명기업규모기업규모명업력구간명총기업수
업력구간코드1.000-0.0470.0000.0000.2930.0000.0000.0000.0000.9410.000
여신금액합-0.0471.0000.6550.6550.7390.4630.4630.4020.4020.0000.000
시도명0.0000.6551.0000.4540.8860.0000.0000.0000.0000.0000.000
시군구명0.0000.6550.4541.0000.8860.0000.0000.0000.0000.0000.000
행정동명0.2930.7390.8860.8861.0000.0000.0000.0000.0000.0000.000
업종대분류코드0.0000.4630.0000.0000.0001.0001.0000.0000.0000.0000.303
업종대분류명0.0000.4630.0000.0000.0001.0001.0000.0000.0000.0000.303
기업규모0.0000.4020.0000.0000.0000.0000.0001.0001.0000.3720.000
기업규모명0.0000.4020.0000.0000.0000.0000.0001.0001.0000.3720.000
업력구간명0.9410.0000.0000.0000.0000.0000.0000.3720.3721.0000.000
총기업수0.0000.0000.0000.0000.0000.3030.3030.0000.0000.0001.000

Missing values

2023-12-10T23:17:42.092108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:17:42.435913image/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

기준년월시도명시군구명행정동명업종대분류코드업종대분류명업종중분류코드업종중분류명기업규모기업규모명업력구간코드업력구간명총기업수여신금액합등록일작업자명
02020-09강원강릉시강남동D전기; 가스; 증기 및 공기조절 공급업D35전기; 가스; 증기 및 공기조절 공급업4소기업55년이상 10년미만11717862021-11-23KEDSYSTEM
12020-09충북충주시엄정면C제조업C17펄프; 종이 및 종이제품 제조업99미분류1010년이상 20년미만102021-11-23KEDSYSTEM
22020-09충북충주시금가면R예술; 스포츠 및 여가관련 서비스업R91스포츠 및 오락관련 서비스업4소기업1010년이상 20년미만112018762021-11-23KEDSYSTEM
32020-09충북충주시노은면A농업; 임업 및 어업A01농업99미분류1010년이상 20년미만102021-11-23KEDSYSTEM
42020-09충북충주시노은면C제조업C33기타 제품 제조업4소기업55년이상 10년미만114162021-11-23KEDSYSTEM
52020-09충북충주시달천동C제조업C10식료품 제조업4소기업22년이상 5년미만2197602021-11-23KEDSYSTEM
62020-09충북충주시달천동C제조업C20화학물질 및 화학제품 제조업; 의약품 제외4소기업55년이상 10년미만230402021-11-23KEDSYSTEM
72020-09충북충주시연수동D전기; 가스; 증기 및 공기조절 공급업D35전기; 가스; 증기 및 공기조절 공급업99미분류22년이상 5년미만202021-11-23KEDSYSTEM
82020-09충북충주시달천동G도매 및 소매업G46도매 및 상품 중개업4소기업1010년이상 20년미만1265442021-11-23KEDSYSTEM
92020-09충북충주시달천동G도매 및 소매업G46도매 및 상품 중개업4소기업55년이상 10년미만6456762021-11-23KEDSYSTEM
기준년월시도명시군구명행정동명업종대분류코드업종대분류명업종중분류코드업종중분류명기업규모기업규모명업력구간코드업력구간명총기업수여신금액합등록일작업자명
202020-09충북충주시대소원면D전기; 가스; 증기 및 공기조절 공급업D35전기; 가스; 증기 및 공기조절 공급업99미분류11년이상 2년미만102021-11-23KEDSYSTEM
212020-09충북충주시대소원면G도매 및 소매업G46도매 및 상품 중개업4소기업22년이상 5년미만7616392021-11-23KEDSYSTEM
222020-09충북충주시대소원면J정보통신업J59영상ㆍ오디오 기록물 제작 및 배급업4소기업22년이상 5년미만128002021-11-23KEDSYSTEM
232020-09충북충주시대소원면K금융 및 보험업K66금융 및 보험 관련 서비스업4소기업22년이상 5년미만1802021-11-23KEDSYSTEM
242020-09충북충주시대소원면M전문; 과학 및 기술 서비스업M70연구개발업4소기업55년이상 10년미만352842021-11-23KEDSYSTEM
252020-09충북충주시대소원면N사업시설 관리; 사업 지원 및 임대 서비스업N75사업지원 서비스업4소기업22년이상 5년미만12402021-11-23KEDSYSTEM
262020-09충북충주시대소원면N사업시설 관리; 사업 지원 및 임대 서비스업N76임대업; 부동산 제외99미분류01년미만102021-11-23KEDSYSTEM
272020-09충북충주시대소원면S협회 및 단체; 수리 및 기타 개인 서비스업S94협회 및 단체99미분류2020년이상 30년미만102021-11-23KEDSYSTEM
282020-09충북충주시목행.용탄동C제조업C11음료 제조업99미분류6060년이상 70년미만102021-11-23KEDSYSTEM
292020-09충북충주시목행.용탄동C제조업C13섬유제품 제조업; 의복제외4소기업55년이상 10년미만148722021-11-23KEDSYSTEM