Overview

Dataset statistics

Number of variables11
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory96.6 B

Variable types

Categorical5
Numeric3
Text2
DateTime1

Dataset

Description샘플 데이터
Author한국평가데이터㈜
URLhttps://www.bigdata-region.kr/#/dataset/e71717b2-3313-4ce8-a70f-4136b386341f

Alerts

기준년월 has constant value ""Constant
산업재해보상보험1순번 has constant value ""Constant
업종명 has constant value ""Constant
등록일자 has constant value ""Constant
작업자명 has constant value ""Constant
산업재해보상보험2순번 has unique valuesUnique
전체주소 has unique valuesUnique
회사명 has unique valuesUnique
종업원수 has 3 (10.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:18:21.776508
Analysis finished2023-12-10 14:18:23.752447
Duration1.98 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
2018-11
29 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-11
2nd row2018-11
3rd row2018-11
4th row2018-11
5th row2018-11

Common Values

ValueCountFrequency (%)
2018-11 29
100.0%

Length

2023-12-10T23:18:23.837625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:18:23.954136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-11 29
100.0%

산업재해보상보험1순번
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
1
29 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 29
100.0%

Length

2023-12-10T23:18:24.068002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:18:24.178061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 29
100.0%

산업재해보상보험2순번
Real number (ℝ)

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12563.103
Minimum10406
Maximum15383
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-10T23:18:24.314073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10406
5-th percentile10668
Q111346
median12351
Q313557
95-th percentile15288.8
Maximum15383
Range4977
Interquartile range (IQR)2211

Descriptive statistics

Standard deviation1531.8686
Coefficient of variation (CV)0.12193393
Kurtosis-0.76078323
Mean12563.103
Median Absolute Deviation (MAD)1098
Skewness0.58013407
Sum364330
Variance2346621.3
MonotonicityStrictly increasing
2023-12-10T23:18:24.482320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
10406 1
 
3.4%
10598 1
 
3.4%
15383 1
 
3.4%
15322 1
 
3.4%
15239 1
 
3.4%
15122 1
 
3.4%
14547 1
 
3.4%
14469 1
 
3.4%
13586 1
 
3.4%
13557 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
10406 1
3.4%
10598 1
3.4%
10773 1
3.4%
10799 1
3.4%
10858 1
3.4%
11253 1
3.4%
11267 1
3.4%
11346 1
3.4%
11584 1
3.4%
11651 1
3.4%
ValueCountFrequency (%)
15383 1
3.4%
15322 1
3.4%
15239 1
3.4%
15122 1
3.4%
14547 1
3.4%
14469 1
3.4%
13586 1
3.4%
13557 1
3.4%
13533 1
3.4%
12764 1
3.4%

전체주소
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-10T23:18:24.951272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length27.310345
Min length17

Characters and Unicode

Total characters792
Distinct characters135
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row서울 마포구 성암로 229 1층 (상암동)
2nd row경기도 광주시 오포읍 봉골길171번길 12-10 (오포읍)
3rd row경상남도 창원시 마산합포구 진동면 요장해안길 205 (진동면)
4th row충남 금산군 복수면 적선길 79
5th row서울특별시 강북구 삼각산로30길 12 (수유동) 1층
ValueCountFrequency (%)
서울 12
 
6.7%
1층 6
 
3.4%
경기 4
 
2.2%
중구 4
 
2.2%
진동면 2
 
1.1%
7 2
 
1.1%
전북 2
 
1.1%
수유동 2
 
1.1%
12 2
 
1.1%
강북구 2
 
1.1%
Other values (135) 140
78.7%
2023-12-10T23:18:25.521188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
159
 
20.1%
1 37
 
4.7%
동 30
 
3.8%
로 24
 
3.0%
) 24
 
3.0%
( 24
 
3.0%
구 22
 
2.8%
2 19
 
2.4%
서 15
 
1.9%
울 14
 
1.8%
Other values (125) 424
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 448
56.6%
Space Separator 159
 
20.1%
Decimal Number 129
 
16.3%
Close Punctuation 24
 
3.0%
Open Punctuation 24
 
3.0%
Dash Punctuation 6
 
0.8%
Uppercase Letter 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 30
 
6.7%
로 24
 
5.4%
구 22
 
4.9%
서 15
 
3.3%
울 14
 
3.1%
길 13
 
2.9%
시 13
 
2.9%
층 9
 
2.0%
진 8
 
1.8%
산 8
 
1.8%
Other values (109) 292
65.2%
Decimal Number
ValueCountFrequency (%)
1 37
28.7%
2 19
14.7%
3 13
 
10.1%
6 13
 
10.1%
5 12
 
9.3%
0 11
 
8.5%
7 9
 
7.0%
9 6
 
4.7%
8 6
 
4.7%
4 3
 
2.3%
Space Separator
ValueCountFrequency (%)
159
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 448
56.6%
Common 342
43.2%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 30
 
6.7%
로 24
 
5.4%
구 22
 
4.9%
서 15
 
3.3%
울 14
 
3.1%
길 13
 
2.9%
시 13
 
2.9%
층 9
 
2.0%
진 8
 
1.8%
산 8
 
1.8%
Other values (109) 292
65.2%
Common
ValueCountFrequency (%)
159
46.5%
1 37
 
10.8%
) 24
 
7.0%
( 24
 
7.0%
2 19
 
5.6%
3 13
 
3.8%
6 13
 
3.8%
5 12
 
3.5%
0 11
 
3.2%
7 9
 
2.6%
Other values (4) 21
 
6.1%
Latin
ValueCountFrequency (%)
B 1
50.0%
c 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 448
56.6%
ASCII 344
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
159
46.2%
1 37
 
10.8%
) 24
 
7.0%
( 24
 
7.0%
2 19
 
5.5%
3 13
 
3.8%
6 13
 
3.8%
5 12
 
3.5%
0 11
 
3.2%
7 9
 
2.6%
Other values (6) 23
 
6.7%
Hangul
ValueCountFrequency (%)
동 30
 
6.7%
로 24
 
5.4%
구 22
 
4.9%
서 15
 
3.3%
울 14
 
3.1%
길 13
 
2.9%
시 13
 
2.9%
층 9
 
2.0%
진 8
 
1.8%
산 8
 
1.8%
Other values (109) 292
65.2%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
29 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
29
100.0%

Length

2023-12-10T23:18:25.757902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:18:25.900907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

우편번호
Real number (ℝ)

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16834.897
Minimum1021
Maximum56174
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-10T23:18:26.039386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1021
5-th percentile1227.6
Q14334
median10013
Q325019
95-th percentile53655.2
Maximum56174
Range55153
Interquartile range (IQR)20685

Descriptive statistics

Standard deviation17443.66
Coefficient of variation (CV)1.0361608
Kurtosis0.095780958
Mean16834.897
Median Absolute Deviation (MAD)7183
Skewness1.1455337
Sum488212
Variance3.0428127 × 108
MonotonicityNot monotonic
2023-12-10T23:18:26.261045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
4563 2
 
6.9%
3927 1
 
3.4%
6034 1
 
3.4%
1455 1
 
3.4%
12000 1
 
3.4%
16570 1
 
3.4%
39033 1
 
3.4%
1021 1
 
3.4%
56174 1
 
3.4%
25019 1
 
3.4%
Other values (18) 18
62.1%
ValueCountFrequency (%)
1021 1
3.4%
1076 1
3.4%
1455 1
3.4%
2457 1
3.4%
2830 1
3.4%
3368 1
3.4%
3927 1
3.4%
4334 1
3.4%
4502 1
3.4%
4563 2
6.9%
ValueCountFrequency (%)
56174 1
3.4%
54898 1
3.4%
51791 1
3.4%
41914 1
3.4%
39033 1
3.4%
32701 1
3.4%
31172 1
3.4%
25019 1
3.4%
21544 1
3.4%
21389 1
3.4%

회사명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-10T23:18:26.588536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters58
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row돈탄
2nd row동명
3rd row동영
4th row동우
5th row동인
ValueCountFrequency (%)
돈탄 1
 
3.4%
로엘 1
 
3.4%
미르 1
 
3.4%
미래 1
 
3.4%
미노 1
 
3.4%
모스 1
 
3.4%
모란 1
 
3.4%
만지 1
 
3.4%
만송 1
 
3.4%
만선 1
 
3.4%
Other values (19) 19
65.5%
2023-12-10T23:18:27.102561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
미 5
 
8.6%
동 4
 
6.9%
로 4
 
6.9%
만 3
 
5.2%
돈 2
 
3.4%
드 2
 
3.4%
라 2
 
3.4%
모 2
 
3.4%
두 2
 
3.4%
우 2
 
3.4%
Other values (30) 30
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
미 5
 
8.6%
동 4
 
6.9%
로 4
 
6.9%
만 3
 
5.2%
돈 2
 
3.4%
드 2
 
3.4%
라 2
 
3.4%
모 2
 
3.4%
두 2
 
3.4%
우 2
 
3.4%
Other values (30) 30
51.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
미 5
 
8.6%
동 4
 
6.9%
로 4
 
6.9%
만 3
 
5.2%
돈 2
 
3.4%
드 2
 
3.4%
라 2
 
3.4%
모 2
 
3.4%
두 2
 
3.4%
우 2
 
3.4%
Other values (30) 30
51.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
미 5
 
8.6%
동 4
 
6.9%
로 4
 
6.9%
만 3
 
5.2%
돈 2
 
3.4%
드 2
 
3.4%
라 2
 
3.4%
모 2
 
3.4%
두 2
 
3.4%
우 2
 
3.4%
Other values (30) 30
51.7%

종업원수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5862069
Minimum0
Maximum6
Zeros3
Zeros (%)10.3%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-10T23:18:27.282119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.323341
Coefficient of variation (CV)0.83428023
Kurtosis3.5257693
Mean1.5862069
Median Absolute Deviation (MAD)0
Skewness1.7367616
Sum46
Variance1.7512315
MonotonicityNot monotonic
2023-12-10T23:18:27.400566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 16
55.2%
2 5
 
17.2%
0 3
 
10.3%
4 2
 
6.9%
3 2
 
6.9%
6 1
 
3.4%
ValueCountFrequency (%)
0 3
 
10.3%
1 16
55.2%
2 5
 
17.2%
3 2
 
6.9%
4 2
 
6.9%
6 1
 
3.4%
ValueCountFrequency (%)
6 1
 
3.4%
4 2
 
6.9%
3 2
 
6.9%
2 5
 
17.2%
1 16
55.2%
0 3
 
10.3%

설립일자
Date

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2003-01-01 00:00:00
Maximum2018-11-01 00:00:00
2023-12-10T23:18:27.555399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:27.735237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
2018-12-11
29 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-12-11
2nd row2018-12-11
3rd row2018-12-11
4th row2018-12-11
5th row2018-12-11

Common Values

ValueCountFrequency (%)
2018-12-11 29
100.0%

Length

2023-12-10T23:18:27.903327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:18:28.044128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-12-11 29
100.0%

작업자명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
KED_SYSTEM
29 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KED_SYSTEM 29
100.0%

Length

2023-12-10T23:18:28.174775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:18:28.309339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ked_system 29
100.0%

Interactions

2023-12-10T23:18:23.015138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:22.072317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:22.654072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:23.157752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:22.432782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:22.778430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:23.291879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:22.527076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:18:22.895478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:18:28.409789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
산업재해보상보험2순번전체주소우편번호회사명종업원수설립일자
산업재해보상보험2순번1.0001.0000.0001.0000.2940.518
전체주소1.0001.0001.0001.0001.0001.000
우편번호0.0001.0001.0001.0000.0000.000
회사명1.0001.0001.0001.0001.0001.000
종업원수0.2941.0000.0001.0001.0000.752
설립일자0.5181.0000.0001.0000.7521.000
2023-12-10T23:18:28.560560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
산업재해보상보험2순번우편번호종업원수
산업재해보상보험2순번1.000-0.042-0.149
우편번호-0.0421.0000.108
종업원수-0.1490.1081.000

Missing values

2023-12-10T23:18:23.462459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:18:23.667691image/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

기준년월산업재해보상보험1순번산업재해보상보험2순번전체주소업종명우편번호회사명종업원수설립일자등록일자작업자명
02018-11110406서울 마포구 성암로 229 1층 (상암동)3927돈탄42012-12-012018-12-11KED_SYSTEM
12018-11110598경기도 광주시 오포읍 봉골길171번길 12-10 (오포읍)12774동명22017-08-012018-12-11KED_SYSTEM
22018-11110773경상남도 창원시 마산합포구 진동면 요장해안길 205 (진동면)51791동영12014-07-012018-12-11KED_SYSTEM
32018-11110799충남 금산군 복수면 적선길 7932701동우12017-09-012018-12-11KED_SYSTEM
42018-11110858서울특별시 강북구 삼각산로30길 12 (수유동) 1층1076동인02014-04-012018-12-11KED_SYSTEM
52018-11111253서울 중구 중림로 10 (중림동 삼성사이버빌리지) 3동5호4502두툼62015-09-032018-12-11KED_SYSTEM
62018-11111267경기 김포시 하성면 하사리 113-3번지10013두현12013-07-012018-12-11KED_SYSTEM
72018-11111346서울 중구 청계천로 246 1층가 263 (방산동 평화시장)4563드림12013-11-052018-12-11KED_SYSTEM
82018-11111584인천광역시 부평구 부평대로 지하 7 (부평동 부평역지하상가) c동42호21389디퓸12017-07-012018-12-11KED_SYSTEM
92018-11111651전북 전주시 덕진구 명륜5길 14 (덕진동1가)54898땡큐12015-01-012018-12-11KED_SYSTEM
기준년월산업재해보상보험1순번산업재해보상보험2순번전체주소업종명우편번호회사명종업원수설립일자등록일자작업자명
192018-11112764서울 광진구 능동로 332 706호 (중곡동 동아빌딩)4928리드12007-01-022018-12-11KED_SYSTEM
202018-11113533서울 은평구 진흥로 201 (불광동)3368만선32003-01-012018-12-11KED_SYSTEM
212018-11113557강원 양양군 양양읍 거마천로 59-1825019만송12017-06-012018-12-11KED_SYSTEM
222018-11113586서울 중구 장충단로 275 1층 23호 (을지로6가 두산타워빌딩)4563만지12016-08-062018-12-11KED_SYSTEM
232018-11114469전북 정읍시 샘골로 135 (수성동) 1층56174모란32018-05-032018-12-11KED_SYSTEM
242018-11114547서울 강북구 삼각산로 59 (수유동)1021모스12018-02-012018-12-11KED_SYSTEM
252018-11115122경상북도 군위군 효령면 장군로 768 (효령면)39033미노42013-07-012018-12-11KED_SYSTEM
262018-11115239경기 수원시 권선구 권선로 655 (권선동) 3층16570미래02017-11-012018-12-11KED_SYSTEM
272018-11115322경기 남양주시 진접읍 부마로106번길 8912000미르02016-07-012018-12-11KED_SYSTEM
282018-11115383서울 도봉구 도봉로112길 20 (창동)1455미미12018-06-052018-12-11KED_SYSTEM