Overview

Dataset statistics

Number of variables11
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory94.4 B

Variable types

DateTime2
Categorical7
Text2

Dataset

Description샘플 데이터
Author한국평가데이터㈜
URLhttps://www.bigdata-region.kr/#/dataset/52792d6a-d843-4bef-a73d-8fd86494f6a7

Alerts

기준 년월 has constant value ""Constant
등록 일자 has constant value ""Constant
작업자명 has constant value ""Constant
시도명 is highly overall correlated with 시군구명High correlation
시군구명 is highly overall correlated with 시도명High correlation

Reproduction

Analysis started2023-12-10 14:15:50.339953
Analysis finished2023-12-10 14:15:52.107821
Duration1.77 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준 년월
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2000-01-01 00:00:00
Maximum2000-01-01 00:00:00
2023-12-10T23:15:52.591290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:52.760446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

시도명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
충북
21 
충남
9 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충북 21
70.0%
충남 9
30.0%

Length

2023-12-10T23:15:52.964163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:53.116690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충북 21
70.0%
충남 9
30.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
청주시 흥덕구
6 
음성군
4 
천안시 서북구
4 
청주시 상당구
3 
괴산군
3 
Other values (7)
10 

Length

Max length7
Median length7
Mean length5.4
Min length3

Unique

Unique5 ?
Unique (%)16.7%

Sample

1st row충주시
2nd row충주시
3rd row청주시 흥덕구
4th row청주시 흥덕구
5th row청주시 흥덕구

Common Values

ValueCountFrequency (%)
청주시 흥덕구 6
20.0%
음성군 4
13.3%
천안시 서북구 4
13.3%
청주시 상당구 3
10.0%
괴산군 3
10.0%
천안시 동남구 3
10.0%
충주시 2
 
6.7%
청주시 청원구 1
 
3.3%
청주시 서원구 1
 
3.3%
진천군 1
 
3.3%
Other values (2) 2
 
6.7%

Length

2023-12-10T23:15:53.355526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
청주시 11
22.9%
천안시 7
14.6%
흥덕구 6
12.5%
음성군 4
 
8.3%
서북구 4
 
8.3%
상당구 3
 
6.2%
괴산군 3
 
6.2%
동남구 3
 
6.2%
충주시 2
 
4.2%
청원구 1
 
2.1%
Other values (4) 4
 
8.3%

행정동명
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:15:53.723951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.8
Min length2

Characters and Unicode

Total characters114
Distinct characters46
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

Unique18 ?
Unique (%)60.0%

Sample

1st row중앙탑면
2nd row성내.충인동
3rd row봉명2.송정동
4th row봉명2.송정동
5th row봉명2.송정동
ValueCountFrequency (%)
봉명2.송정동 3
 
10.0%
강내면 3
 
10.0%
중앙동 2
 
6.7%
직산읍 2
 
6.7%
대소면 2
 
6.7%
금왕읍 1
 
3.3%
중앙탑면 1
 
3.3%
문광면 1
 
3.3%
수신면 1
 
3.3%
신안동 1
 
3.3%
Other values (13) 13
43.3%
2023-12-10T23:15:54.341245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 16
 
14.0%
동 11
 
9.6%
. 6
 
5.3%
내 5
 
4.4%
2 5
 
4.4%
성 4
 
3.5%
읍 4
 
3.5%
명 4
 
3.5%
정 4
 
3.5%
강 3
 
2.6%
Other values (36) 52
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 103
90.4%
Other Punctuation 6
 
5.3%
Decimal Number 5
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 16
 
15.5%
동 11
 
10.7%
내 5
 
4.9%
성 4
 
3.9%
읍 4
 
3.9%
명 4
 
3.9%
정 4
 
3.9%
강 3
 
2.9%
중 3
 
2.9%
앙 3
 
2.9%
Other values (34) 46
44.7%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%
Decimal Number
ValueCountFrequency (%)
2 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 103
90.4%
Common 11
 
9.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 16
 
15.5%
동 11
 
10.7%
내 5
 
4.9%
성 4
 
3.9%
읍 4
 
3.9%
명 4
 
3.9%
정 4
 
3.9%
강 3
 
2.9%
중 3
 
2.9%
앙 3
 
2.9%
Other values (34) 46
44.7%
Common
ValueCountFrequency (%)
. 6
54.5%
2 5
45.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 103
90.4%
ASCII 11
 
9.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 16
 
15.5%
동 11
 
10.7%
내 5
 
4.9%
성 4
 
3.9%
읍 4
 
3.9%
명 4
 
3.9%
정 4
 
3.9%
강 3
 
2.9%
중 3
 
2.9%
앙 3
 
2.9%
Other values (34) 46
44.7%
ASCII
ValueCountFrequency (%)
. 6
54.5%
2 5
45.5%

업종대분류코드
Categorical

Distinct10
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
C
15 
G
3 
A
3 
F
2 
S
2 
Other values (5)
5 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique5 ?
Unique (%)16.7%

Sample

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

Common Values

ValueCountFrequency (%)
C 15
50.0%
G 3
 
10.0%
A 3
 
10.0%
F 2
 
6.7%
S 2
 
6.7%
M 1
 
3.3%
J 1
 
3.3%
Z 1
 
3.3%
L 1
 
3.3%
Q 1
 
3.3%

Length

2023-12-10T23:15:54.555094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:54.781414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
c 15
50.0%
g 3
 
10.0%
a 3
 
10.0%
f 2
 
6.7%
s 2
 
6.7%
m 1
 
3.3%
j 1
 
3.3%
z 1
 
3.3%
l 1
 
3.3%
q 1
 
3.3%

업종중분류코드
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:15:55.021898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters90
Distinct characters20
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

Unique17 ?
Unique (%)56.7%

Sample

1st rowC27
2nd rowC14
3rd rowG46
4th rowC22
5th rowC20
ValueCountFrequency (%)
a01 3
 
10.0%
c33 2
 
6.7%
s94 2
 
6.7%
g47 2
 
6.7%
c25 2
 
6.7%
c20 2
 
6.7%
l68 1
 
3.3%
c27 1
 
3.3%
c17 1
 
3.3%
c29 1
 
3.3%
Other values (13) 13
43.3%
2023-12-10T23:15:55.381040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 15
16.7%
2 11
12.2%
1 10
11.1%
4 8
8.9%
7 6
 
6.7%
0 6
 
6.7%
3 6
 
6.7%
9 6
 
6.7%
5 3
 
3.3%
A 3
 
3.3%
Other values (10) 16
17.8%

Most occurring categories

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

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 15
50.0%
A 3
 
10.0%
G 3
 
10.0%
S 2
 
6.7%
F 2
 
6.7%
M 1
 
3.3%
J 1
 
3.3%
Z 1
 
3.3%
L 1
 
3.3%
Q 1
 
3.3%
Decimal Number
ValueCountFrequency (%)
2 11
18.3%
1 10
16.7%
4 8
13.3%
7 6
10.0%
0 6
10.0%
3 6
10.0%
9 6
10.0%
5 3
 
5.0%
6 2
 
3.3%
8 2
 
3.3%

Most occurring scripts

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

Most frequent character per script

Latin
ValueCountFrequency (%)
C 15
50.0%
A 3
 
10.0%
G 3
 
10.0%
S 2
 
6.7%
F 2
 
6.7%
M 1
 
3.3%
J 1
 
3.3%
Z 1
 
3.3%
L 1
 
3.3%
Q 1
 
3.3%
Common
ValueCountFrequency (%)
2 11
18.3%
1 10
16.7%
4 8
13.3%
7 6
10.0%
0 6
10.0%
3 6
10.0%
9 6
10.0%
5 3
 
5.0%
6 2
 
3.3%
8 2
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 15
16.7%
2 11
12.2%
1 10
11.1%
4 8
8.9%
7 6
 
6.7%
0 6
 
6.7%
3 6
 
6.7%
9 6
 
6.7%
5 3
 
3.3%
A 3
 
3.3%
Other values (10) 16
17.8%

가공기업구분코드
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
4
15 
3
8 
99
6 
2
 
1

Length

Max length2
Median length1
Mean length1.2
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row3
2nd row4
3rd row99
4th row3
5th row3

Common Values

ValueCountFrequency (%)
4 15
50.0%
3 8
26.7%
99 6
 
20.0%
2 1
 
3.3%

Length

2023-12-10T23:15:55.539474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:55.659072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 15
50.0%
3 8
26.7%
99 6
 
20.0%
2 1
 
3.3%

상표권구분명
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
도형복합
8 
한글상표
7 
[미분류]
5 
복합문자
4 
도형상표
3 

Length

Max length5
Median length4
Mean length4.1666667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row도형복합
2nd row도형상표
3rd row도형복합
4th row영문상표
5th row복합문자

Common Values

ValueCountFrequency (%)
도형복합 8
26.7%
한글상표 7
23.3%
[미분류] 5
16.7%
복합문자 4
13.3%
도형상표 3
 
10.0%
영문상표 3
 
10.0%

Length

2023-12-10T23:15:55.802956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:56.015568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도형복합 8
26.7%
한글상표 7
23.3%
미분류 5
16.7%
복합문자 4
13.3%
도형상표 3
 
10.0%
영문상표 3
 
10.0%

총기업수
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
19 
2
7 
3
2 
4
2 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 19
63.3%
2 7
 
23.3%
3 2
 
6.7%
4 2
 
6.7%

Length

2023-12-10T23:15:56.229918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:56.402790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 19
63.3%
2 7
 
23.3%
3 2
 
6.7%
4 2
 
6.7%

등록 일자
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2019-12-21 00:00:00
Maximum2019-12-21 00:00:00
2023-12-10T23:15:56.604757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:56.758903image/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
KED_SYSTEM
30 

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 30
100.0%

Length

2023-12-10T23:15:56.963993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:57.117069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ked_system 30
100.0%

Correlations

2023-12-10T23:15:57.228114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명시군구명행정동명업종대분류코드업종중분류코드가공기업구분코드상표권구분명총기업수
시도명1.0001.0001.0000.0000.1020.4530.0000.000
시군구명1.0001.0001.0000.7670.8330.0000.8050.513
행정동명1.0001.0001.0000.8800.7310.0000.0000.681
업종대분류코드0.0000.7670.8801.0001.0000.6700.0000.522
업종중분류코드0.1020.8330.7311.0001.0000.7660.7350.000
가공기업구분코드0.4530.0000.0000.6700.7661.0000.0000.000
상표권구분명0.0000.8050.0000.0000.7350.0001.0000.000
총기업수0.0000.5130.6810.5220.0000.0000.0001.000
2023-12-10T23:15:57.408412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가공기업구분코드시군구명시도명상표권구분명업종대분류코드총기업수
가공기업구분코드1.0000.0000.2890.0000.4020.000
시군구명0.0001.0000.8020.3740.4160.183
시도명0.2890.8021.0000.0000.0000.000
상표권구분명0.0000.3740.0001.0000.0000.000
업종대분류코드0.4020.4160.0000.0001.0000.280
총기업수0.0000.1830.0000.0000.2801.000
2023-12-10T23:15:57.598470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명시군구명업종대분류코드가공기업구분코드상표권구분명총기업수
시도명1.0000.8020.0000.2890.0000.000
시군구명0.8021.0000.4160.0000.3740.183
업종대분류코드0.0000.4161.0000.4020.0000.280
가공기업구분코드0.2890.0000.4021.0000.0000.000
상표권구분명0.0000.3740.0000.0001.0000.000
총기업수0.0000.1830.2800.0000.0001.000

Missing values

2023-12-10T23:15:51.709737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:15:52.002058image/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

기준 년월시도명시군구명행정동명업종대분류코드업종중분류코드가공기업구분코드상표권구분명총기업수등록 일자작업자명
02000-01충북충주시중앙탑면CC273도형복합32019-12-21KED_SYSTEM
12000-01충북충주시성내.충인동CC144도형상표12019-12-21KED_SYSTEM
22000-01충북청주시 흥덕구봉명2.송정동GG4699도형복합12019-12-21KED_SYSTEM
32000-01충북청주시 흥덕구봉명2.송정동CC223영문상표12019-12-21KED_SYSTEM
42000-01충북청주시 흥덕구봉명2.송정동CC203복합문자22019-12-21KED_SYSTEM
52000-01충북청주시 흥덕구강내면MM724영문상표12019-12-21KED_SYSTEM
62000-01충북청주시 흥덕구강내면CC134복합문자12019-12-21KED_SYSTEM
72000-01충북청주시 흥덕구강내면CC103한글상표12019-12-21KED_SYSTEM
82000-01충북청주시 청원구내덕2동JJ594복합문자12019-12-21KED_SYSTEM
92000-01충북청주시 서원구현도면ZZ994한글상표12019-12-21KED_SYSTEM
기준 년월시도명시군구명행정동명업종대분류코드업종중분류코드가공기업구분코드상표권구분명총기업수등록 일자작업자명
202000-01충북괴산군문광면CC114[미분류]12019-12-21KED_SYSTEM
212000-01충남홍성군은하면GG4799한글상표12019-12-21KED_SYSTEM
222000-01충남청양군목면AA0199도형복합42019-12-21KED_SYSTEM
232000-01충남천안시 서북구직산읍CC333영문상표12019-12-21KED_SYSTEM
242000-01충남천안시 서북구직산읍CC234[미분류]22019-12-21KED_SYSTEM
252000-01충남천안시 서북구성거읍CC294도형복합12019-12-21KED_SYSTEM
262000-01충남천안시 서북구부성2동CC334[미분류]12019-12-21KED_SYSTEM
272000-01충남천안시 동남구신안동SS9499도형복합12019-12-21KED_SYSTEM
282000-01충남천안시 동남구수신면CC174도형상표22019-12-21KED_SYSTEM
292000-01충남천안시 동남구병천면QQ8799도형상표22019-12-21KED_SYSTEM