Overview

Dataset statistics

Number of variables16
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.9 KiB
Average record size in memory132.3 B

Variable types

Categorical15
Numeric1

Dataset

Description샘플 데이터
Author한국기업데이터㈜
URLhttps://www.bigdata-region.kr/#/dataset/6f393bec-a1e1-4e09-8075-8c53e19d51f5

Alerts

STDR_YM has constant value ""Constant
CTPRVN_NM has constant value ""Constant
SIGNGU_NM has constant value ""Constant
ADSTRD_NM has constant value ""Constant
REGIST_DE has constant value ""Constant
OPERTOR_NM has constant value ""Constant
INDUTY_MLSFC_NM is highly overall correlated with INDUTY_LCLAS_CODE and 2 other fieldsHigh correlation
INDUTY_LCLAS_CODE is highly overall correlated with INDUTY_MLSFC_CODE and 2 other fieldsHigh correlation
PRCSS_ENTRPRS_SE_CODE is highly overall correlated with PRCSS_ENTRPRS_SE_NMHigh correlation
PRCSS_ENTRPRS_SE_NM is highly overall correlated with PRCSS_ENTRPRS_SE_CODEHigh correlation
INDUTY_LCLAS_NM is highly overall correlated with INDUTY_LCLAS_CODE and 2 other fieldsHigh correlation
INDUTY_MLSFC_CODE is highly overall correlated with INDUTY_LCLAS_CODE and 2 other fieldsHigh correlation
PDSMLPZ_SCTN_CODE is highly overall correlated with PDSMLPZ_SCTN_NMHigh correlation
PDSMLPZ_SCTN_NM is highly overall correlated with PDSMLPZ_SCTN_CODEHigh correlation
TOT_ENTRPRS_CO is highly imbalanced (63.1%)Imbalance
PDSMLPZ_SCTN_CODE has 5 (5.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:47:17.590051
Analysis finished2023-12-10 13:47:20.038468
Duration2.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

STDR_YM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2020-01
100 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-01
2nd row2020-01
3rd row2020-01
4th row2020-01
5th row2020-01

Common Values

ValueCountFrequency (%)
2020-01 100
100.0%

Length

2023-12-10T22:47:20.186675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:47:20.358526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-01 100
100.0%

CTPRVN_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기 100
100.0%

Length

2023-12-10T22:47:20.511845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:47:20.779984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기 100
100.0%

SIGNGU_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
가평군
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가평군 100
100.0%

Length

2023-12-10T22:47:20.974765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:47:21.119572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가평군 100
100.0%

ADSTRD_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
가평읍
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가평읍 100
100.0%

Length

2023-12-10T22:47:21.283136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:47:21.437809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가평읍 100
100.0%

INDUTY_LCLAS_CODE
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
F
36 
C
18 
G
16 
L
10 
H
7 
Other values (6)
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
F 36
36.0%
C 18
18.0%
G 16
16.0%
L 10
 
10.0%
H 7
 
7.0%
A 5
 
5.0%
J 3
 
3.0%
I 2
 
2.0%
D 1
 
1.0%
E 1
 
1.0%

Length

2023-12-10T22:47:21.602699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
f 36
36.0%
c 18
18.0%
g 16
16.0%
l 10
 
10.0%
h 7
 
7.0%
a 5
 
5.0%
j 3
 
3.0%
i 2
 
2.0%
d 1
 
1.0%
e 1
 
1.0%

INDUTY_MLSFC_CODE
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
F42
21 
F41
15 
G46
13 
L68
10 
H49
6 
Other values (21)
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique11 ?
Unique (%)11.0%

Sample

1st rowA01
2nd rowA01
3rd rowA01
4th rowA02
5th rowA02

Common Values

ValueCountFrequency (%)
F42 21
21.0%
F41 15
15.0%
G46 13
13.0%
L68 10
10.0%
H49 6
 
6.0%
C26 3
 
3.0%
G47 3
 
3.0%
A01 3
 
3.0%
C10 3
 
3.0%
A02 2
 
2.0%
Other values (16) 21
21.0%

Length

2023-12-10T22:47:21.771061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
f42 21
21.0%
f41 15
15.0%
g46 13
13.0%
l68 10
10.0%
h49 6
 
6.0%
c26 3
 
3.0%
g47 3
 
3.0%
a01 3
 
3.0%
c10 3
 
3.0%
c33 2
 
2.0%
Other values (16) 21
21.0%

INDUTY_LCLAS_NM
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
건설업
36 
제조업
18 
도매 및 소매업
16 
부동산업
10 
운수 및 창고업
7 
Other values (6)
13 

Length

Max length23
Median length3
Mean length5.26
Min length3

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row농업; 임업 및 어업
2nd row농업; 임업 및 어업
3rd row농업; 임업 및 어업
4th row농업; 임업 및 어업
5th row농업; 임업 및 어업

Common Values

ValueCountFrequency (%)
건설업 36
36.0%
제조업 18
18.0%
도매 및 소매업 16
16.0%
부동산업 10
 
10.0%
운수 및 창고업 7
 
7.0%
농업; 임업 및 어업 5
 
5.0%
정보통신업 3
 
3.0%
숙박 및 음식점업 2
 
2.0%
전기; 가스; 증기 및 공기조절 공급업 1
 
1.0%
수도; 하수 및 폐기물 처리; 원료 재생업 1
 
1.0%

Length

2023-12-10T22:47:21.996470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
건설업 36
20.2%
및 33
18.5%
제조업 18
10.1%
도매 16
9.0%
소매업 16
9.0%
부동산업 10
 
5.6%
운수 7
 
3.9%
창고업 7
 
3.9%
농업 5
 
2.8%
임업 5
 
2.8%
Other values (17) 25
14.0%

INDUTY_MLSFC_NM
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
전문직별 공사업
21 
종합 건설업
15 
도매 및 상품 중개업
13 
부동산업
10 
육상운송 및 파이프라인 운송업
6 
Other values (21)
35 

Length

Max length28
Median length22
Mean length9.59
Min length2

Unique

Unique11 ?
Unique (%)11.0%

Sample

1st row농업
2nd row농업
3rd row농업
4th row임업
5th row임업

Common Values

ValueCountFrequency (%)
전문직별 공사업 21
21.0%
종합 건설업 15
15.0%
도매 및 상품 중개업 13
13.0%
부동산업 10
10.0%
육상운송 및 파이프라인 운송업 6
 
6.0%
전자부품; 컴퓨터; 영상; 음향 및 통신장비 제조업 3
 
3.0%
소매업; 자동차 제외 3
 
3.0%
농업 3
 
3.0%
식료품 제조업 3
 
3.0%
임업 2
 
2.0%
Other values (16) 21
21.0%

Length

2023-12-10T22:47:22.192734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
및 32
 
11.6%
전문직별 21
 
7.6%
공사업 21
 
7.6%
제조업 18
 
6.5%
건설업 15
 
5.4%
종합 15
 
5.4%
상품 13
 
4.7%
중개업 13
 
4.7%
도매 13
 
4.7%
부동산업 10
 
3.6%
Other values (50) 106
38.3%

PRCSS_ENTRPRS_SE_CODE
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
4
67 
99
21 
3
8 
98
 
4

Length

Max length2
Median length1
Mean length1.25
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row99
3rd row99
4th row4
5th row98

Common Values

ValueCountFrequency (%)
4 67
67.0%
99 21
 
21.0%
3 8
 
8.0%
98 4
 
4.0%

Length

2023-12-10T22:47:22.538228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:47:22.711154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 67
67.0%
99 21
 
21.0%
3 8
 
8.0%
98 4
 
4.0%

PRCSS_ENTRPRS_SE_NM
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
소기업
67 
미분류
21 
중기업
8 
판단제외
 
4

Length

Max length4
Median length3
Mean length3.04
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소기업 67
67.0%
미분류 21
 
21.0%
중기업 8
 
8.0%
판단제외 4
 
4.0%

Length

2023-12-10T22:47:22.900991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:47:23.082281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소기업 67
67.0%
미분류 21
 
21.0%
중기업 8
 
8.0%
판단제외 4
 
4.0%

PDSMLPZ_SCTN_CODE
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.58
Minimum0
Maximum50
Zeros5
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:47:23.253602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.95
Q12
median5
Q310
95-th percentile20.5
Maximum50
Range50
Interquartile range (IQR)8

Descriptive statistics

Standard deviation9.6799073
Coefficient of variation (CV)1.2770326
Kurtosis8.1225124
Mean7.58
Median Absolute Deviation (MAD)4
Skewness2.6674754
Sum758
Variance93.700606
MonotonicityNot monotonic
2023-12-10T22:47:23.519340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2 27
27.0%
10 26
26.0%
5 16
16.0%
1 14
14.0%
20 7
 
7.0%
0 5
 
5.0%
50 2
 
2.0%
40 2
 
2.0%
30 1
 
1.0%
ValueCountFrequency (%)
0 5
 
5.0%
1 14
14.0%
2 27
27.0%
5 16
16.0%
10 26
26.0%
20 7
 
7.0%
30 1
 
1.0%
40 2
 
2.0%
50 2
 
2.0%
ValueCountFrequency (%)
50 2
 
2.0%
40 2
 
2.0%
30 1
 
1.0%
20 7
 
7.0%
10 26
26.0%
5 16
16.0%
2 27
27.0%
1 14
14.0%
0 5
 
5.0%

PDSMLPZ_SCTN_NM
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2년 이상 5년 미만
27 
10년 이상 20년 미만
26 
5년 이상 10년 미만
16 
1년 이상 2년 미만
14 
20년 이상 30년 미만
7 
Other values (4)
10 

Length

Max length13
Median length12
Mean length11.62
Min length5

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row5년 이상 10년 미만
2nd row2년 이상 5년 미만
3rd row5년 이상 10년 미만
4th row2년 이상 5년 미만
5th row50년 이상 60년 미만

Common Values

ValueCountFrequency (%)
2년 이상 5년 미만 27
27.0%
10년 이상 20년 미만 26
26.0%
5년 이상 10년 미만 16
16.0%
1년 이상 2년 미만 14
14.0%
20년 이상 30년 미만 7
 
7.0%
1년 미만 5
 
5.0%
50년 이상 60년 미만 2
 
2.0%
40년 이상 50년 미만 2
 
2.0%
30년 이상 40년 미만 1
 
1.0%

Length

2023-12-10T22:47:23.834963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:47:24.094484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미만 100
25.6%
이상 95
24.4%
5년 43
11.0%
10년 42
10.8%
2년 41
10.5%
20년 33
 
8.5%
1년 19
 
4.9%
30년 8
 
2.1%
50년 4
 
1.0%
40년 3
 
0.8%

CREDT_GRAD_NM
Categorical

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
B
16 
NR
16 
CCC+
9 
BB+
8 
D
7 
Other values (13)
44 

Length

Max length4
Median length3
Mean length2.27
Min length1

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st rowD
2nd rowNR
3rd rowNR
4th rowBB
5th rowA

Common Values

ValueCountFrequency (%)
B 16
16.0%
NR 16
16.0%
CCC+ 9
9.0%
BB+ 8
8.0%
D 7
7.0%
BB- 6
 
6.0%
B- 6
 
6.0%
BB 6
 
6.0%
BBB- 5
 
5.0%
BBB 5
 
5.0%
Other values (8) 16
16.0%

Length

2023-12-10T22:47:24.385500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
b 26
26.0%
bb 20
20.0%
nr 16
16.0%
bbb 12
12.0%
ccc 11
11.0%
d 7
 
7.0%
cc 3
 
3.0%
a 3
 
3.0%
c 2
 
2.0%

TOT_ENTRPRS_CO
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
86 
2
10 
4
 
3
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 86
86.0%
2 10
 
10.0%
4 3
 
3.0%
3 1
 
1.0%

Length

2023-12-10T22:47:24.668058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:47:24.873635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 86
86.0%
2 10
 
10.0%
4 3
 
3.0%
3 1
 
1.0%

REGIST_DE
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2020-10-24
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-10-24
2nd row2020-10-24
3rd row2020-10-24
4th row2020-10-24
5th row2020-10-24

Common Values

ValueCountFrequency (%)
2020-10-24 100
100.0%

Length

2023-12-10T22:47:25.077447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:47:25.208864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-10-24 100
100.0%

OPERTOR_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KEDSYS
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KEDSYS 100
100.0%

Length

2023-12-10T22:47:25.355857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:47:25.519351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kedsys 100
100.0%

Interactions

2023-12-10T22:47:18.941278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:47:25.635593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
INDUTY_LCLAS_CODEINDUTY_MLSFC_CODEINDUTY_LCLAS_NMINDUTY_MLSFC_NMPRCSS_ENTRPRS_SE_CODEPRCSS_ENTRPRS_SE_NMPDSMLPZ_SCTN_CODEPDSMLPZ_SCTN_NMCREDT_GRAD_NMTOT_ENTRPRS_CO
INDUTY_LCLAS_CODE1.0001.0001.0001.0000.3670.3670.2100.1280.0000.000
INDUTY_MLSFC_CODE1.0001.0001.0001.0000.6040.6040.2060.3310.0000.000
INDUTY_LCLAS_NM1.0001.0001.0001.0000.3670.3670.2100.1280.0000.000
INDUTY_MLSFC_NM1.0001.0001.0001.0000.6040.6040.2060.3310.0000.000
PRCSS_ENTRPRS_SE_CODE0.3670.6040.3670.6041.0001.0000.4000.3960.6910.000
PRCSS_ENTRPRS_SE_NM0.3670.6040.3670.6041.0001.0000.4000.3960.6910.000
PDSMLPZ_SCTN_CODE0.2100.2060.2100.2060.4000.4001.0001.0000.7280.000
PDSMLPZ_SCTN_NM0.1280.3310.1280.3310.3960.3961.0001.0000.7730.000
CREDT_GRAD_NM0.0000.0000.0000.0000.6910.6910.7280.7731.0000.000
TOT_ENTRPRS_CO0.0000.0000.0000.0000.0000.0000.0000.0000.0001.000
2023-12-10T22:47:25.927155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
INDUTY_MLSFC_NMTOT_ENTRPRS_COINDUTY_LCLAS_CODEPRCSS_ENTRPRS_SE_CODEPDSMLPZ_SCTN_NMCREDT_GRAD_NMPRCSS_ENTRPRS_SE_NMINDUTY_LCLAS_NMINDUTY_MLSFC_CODE
INDUTY_MLSFC_NM1.0000.0000.9120.3140.1050.0000.3140.9121.000
TOT_ENTRPRS_CO0.0001.0000.0000.0000.0000.0000.0000.0000.000
INDUTY_LCLAS_CODE0.9120.0001.0000.2190.0470.0000.2191.0000.912
PRCSS_ENTRPRS_SE_CODE0.3140.0000.2191.0000.2550.4201.0000.2190.314
PDSMLPZ_SCTN_NM0.1050.0000.0470.2551.0000.3520.2550.0470.105
CREDT_GRAD_NM0.0000.0000.0000.4200.3521.0000.4200.0000.000
PRCSS_ENTRPRS_SE_NM0.3140.0000.2191.0000.2550.4201.0000.2190.314
INDUTY_LCLAS_NM0.9120.0001.0000.2190.0470.0000.2191.0000.912
INDUTY_MLSFC_CODE1.0000.0000.9120.3140.1050.0000.3140.9121.000
2023-12-10T22:47:26.241758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
PDSMLPZ_SCTN_CODEINDUTY_LCLAS_CODEINDUTY_MLSFC_CODEINDUTY_LCLAS_NMINDUTY_MLSFC_NMPRCSS_ENTRPRS_SE_CODEPRCSS_ENTRPRS_SE_NMPDSMLPZ_SCTN_NMCREDT_GRAD_NMTOT_ENTRPRS_CO
PDSMLPZ_SCTN_CODE1.0000.1410.1020.1410.1020.2960.2960.9840.4330.000
INDUTY_LCLAS_CODE0.1411.0000.9121.0000.9120.2190.2190.0470.0000.000
INDUTY_MLSFC_CODE0.1020.9121.0000.9121.0000.3140.3140.1050.0000.000
INDUTY_LCLAS_NM0.1411.0000.9121.0000.9120.2190.2190.0470.0000.000
INDUTY_MLSFC_NM0.1020.9121.0000.9121.0000.3140.3140.1050.0000.000
PRCSS_ENTRPRS_SE_CODE0.2960.2190.3140.2190.3141.0001.0000.2550.4200.000
PRCSS_ENTRPRS_SE_NM0.2960.2190.3140.2190.3141.0001.0000.2550.4200.000
PDSMLPZ_SCTN_NM0.9840.0470.1050.0470.1050.2550.2551.0000.3520.000
CREDT_GRAD_NM0.4330.0000.0000.0000.0000.4200.4200.3521.0000.000
TOT_ENTRPRS_CO0.0000.0000.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-10T22:47:19.506507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:47:19.889740image/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

STDR_YMCTPRVN_NMSIGNGU_NMADSTRD_NMINDUTY_LCLAS_CODEINDUTY_MLSFC_CODEINDUTY_LCLAS_NMINDUTY_MLSFC_NMPRCSS_ENTRPRS_SE_CODEPRCSS_ENTRPRS_SE_NMPDSMLPZ_SCTN_CODEPDSMLPZ_SCTN_NMCREDT_GRAD_NMTOT_ENTRPRS_COREGIST_DEOPERTOR_NM
02020-01경기가평군가평읍AA01농업; 임업 및 어업농업4소기업55년 이상 10년 미만D12020-10-24KEDSYS
12020-01경기가평군가평읍AA01농업; 임업 및 어업농업99미분류22년 이상 5년 미만NR12020-10-24KEDSYS
22020-01경기가평군가평읍AA01농업; 임업 및 어업농업99미분류55년 이상 10년 미만NR12020-10-24KEDSYS
32020-01경기가평군가평읍AA02농업; 임업 및 어업임업4소기업22년 이상 5년 미만BB12020-10-24KEDSYS
42020-01경기가평군가평읍AA02농업; 임업 및 어업임업98판단제외5050년 이상 60년 미만A12020-10-24KEDSYS
52020-01경기가평군가평읍CC10제조업식료품 제조업4소기업11년 이상 2년 미만B-12020-10-24KEDSYS
62020-01경기가평군가평읍CC10제조업식료품 제조업4소기업11년 이상 2년 미만D12020-10-24KEDSYS
72020-01경기가평군가평읍CC10제조업식료품 제조업99미분류1010년 이상 20년 미만D12020-10-24KEDSYS
82020-01경기가평군가평읍CC11제조업음료 제조업4소기업1010년 이상 20년 미만BB12020-10-24KEDSYS
92020-01경기가평군가평읍CC16제조업목재 및 나무제품 제조업; 가구 제외4소기업22년 이상 5년 미만B12020-10-24KEDSYS
STDR_YMCTPRVN_NMSIGNGU_NMADSTRD_NMINDUTY_LCLAS_CODEINDUTY_MLSFC_CODEINDUTY_LCLAS_NMINDUTY_MLSFC_NMPRCSS_ENTRPRS_SE_CODEPRCSS_ENTRPRS_SE_NMPDSMLPZ_SCTN_CODEPDSMLPZ_SCTN_NMCREDT_GRAD_NMTOT_ENTRPRS_COREGIST_DEOPERTOR_NM
902020-01경기가평군가평읍LL68부동산업부동산업3중기업22년 이상 5년 미만CCC+12020-10-24KEDSYS
912020-01경기가평군가평읍LL68부동산업부동산업4소기업01년 미만C12020-10-24KEDSYS
922020-01경기가평군가평읍LL68부동산업부동산업4소기업11년 이상 2년 미만B12020-10-24KEDSYS
932020-01경기가평군가평읍LL68부동산업부동산업4소기업1010년 이상 20년 미만B+12020-10-24KEDSYS
942020-01경기가평군가평읍LL68부동산업부동산업4소기업22년 이상 5년 미만CCC+12020-10-24KEDSYS
952020-01경기가평군가평읍LL68부동산업부동산업4소기업55년 이상 10년 미만CCC+12020-10-24KEDSYS
962020-01경기가평군가평읍LL68부동산업부동산업98판단제외1010년 이상 20년 미만CCC12020-10-24KEDSYS
972020-01경기가평군가평읍LL68부동산업부동산업99미분류11년 이상 2년 미만CC12020-10-24KEDSYS
982020-01경기가평군가평읍LL68부동산업부동산업99미분류1010년 이상 20년 미만NR22020-10-24KEDSYS
992020-01경기가평군가평읍LL68부동산업부동산업99미분류22년 이상 5년 미만B32020-10-24KEDSYS