Overview

Dataset statistics

Number of variables5
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory48.0 B

Variable types

Numeric2
Categorical1
Text2

Dataset

Description경상북도 의성군에서 보유한 보조단체코드 등에 대한 데이터로 관리번호, 단체코드, 단체구분, 단체명, 단체설명 등을 제공합니다.
Author경상북도 의성군
URLhttps://www.data.go.kr/data/15123668/fileData.do

Alerts

관리번호 is highly overall correlated with 단체구분High correlation
단체구분 is highly overall correlated with 관리번호High correlation
관리번호 has unique valuesUnique
단체코드 has unique valuesUnique
단체명 has unique valuesUnique
단체설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:13:59.690833
Analysis finished2023-12-12 11:14:03.631363
Duration3.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T20:14:03.739506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.05
Q16.25
median11.5
Q316.75
95-th percentile20.95
Maximum22
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.5646597
Kurtosis-1.2
Mean11.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum253
Variance42.166667
MonotonicityStrictly increasing
2023-12-12T20:14:03.917014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 1
 
4.5%
13 1
 
4.5%
22 1
 
4.5%
21 1
 
4.5%
20 1
 
4.5%
19 1
 
4.5%
18 1
 
4.5%
17 1
 
4.5%
16 1
 
4.5%
15 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1 1
4.5%
2 1
4.5%
3 1
4.5%
4 1
4.5%
5 1
4.5%
6 1
4.5%
7 1
4.5%
8 1
4.5%
9 1
4.5%
10 1
4.5%
ValueCountFrequency (%)
22 1
4.5%
21 1
4.5%
20 1
4.5%
19 1
4.5%
18 1
4.5%
17 1
4.5%
16 1
4.5%
15 1
4.5%
14 1
4.5%
13 1
4.5%

단체코드
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-12T20:14:04.089690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.05
Q16.25
median11.5
Q316.75
95-th percentile20.95
Maximum22
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.5646597
Kurtosis-1.2
Mean11.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum253
Variance42.166667
MonotonicityNot monotonic
2023-12-12T20:14:04.268080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
18 1
 
4.5%
3 1
 
4.5%
2 1
 
4.5%
22 1
 
4.5%
21 1
 
4.5%
19 1
 
4.5%
1 1
 
4.5%
14 1
 
4.5%
13 1
 
4.5%
12 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1 1
4.5%
2 1
4.5%
3 1
4.5%
4 1
4.5%
5 1
4.5%
6 1
4.5%
7 1
4.5%
8 1
4.5%
9 1
4.5%
10 1
4.5%
ValueCountFrequency (%)
22 1
4.5%
21 1
4.5%
20 1
4.5%
19 1
4.5%
18 1
4.5%
17 1
4.5%
16 1
4.5%
15 1
4.5%
14 1
4.5%
13 1
4.5%

단체구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
A
17 
B
5 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
A 17
77.3%
B 5
 
22.7%

Length

2023-12-12T20:14:04.445599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:14:04.593245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 17
77.3%
b 5
 
22.7%

단체명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T20:14:04.855100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length4
Mean length4.1818182
Min length3

Characters and Unicode

Total characters92
Distinct characters47
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

Unique22 ?
Unique (%)100.0%

Sample

1st row개인사업자
2nd row공공법인
3rd row교육기관
4th row기타법인
5th row사단법인
ValueCountFrequency (%)
개인사업자 1
 
4.5%
공공법인 1
 
4.5%
연합회 1
 
4.5%
마을회 1
 
4.5%
기타단체 1
 
4.5%
경로당 1
 
4.5%
협동조합 1
 
4.5%
합자회사 1
 
4.5%
합명회사 1
 
4.5%
특수법인 1
 
4.5%
Other values (12) 12
54.5%
2023-12-12T20:14:05.379618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 8
 
8.7%
사 7
 
7.6%
법 7
 
7.6%
회 7
 
7.6%
합 6
 
6.5%
단 4
 
4.3%
조 3
 
3.3%
기 3
 
3.3%
개 2
 
2.2%
타 2
 
2.2%
Other values (37) 43
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 8
 
8.7%
사 7
 
7.6%
법 7
 
7.6%
회 7
 
7.6%
합 6
 
6.5%
단 4
 
4.3%
조 3
 
3.3%
기 3
 
3.3%
개 2
 
2.2%
타 2
 
2.2%
Other values (37) 43
46.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 8
 
8.7%
사 7
 
7.6%
법 7
 
7.6%
회 7
 
7.6%
합 6
 
6.5%
단 4
 
4.3%
조 3
 
3.3%
기 3
 
3.3%
개 2
 
2.2%
타 2
 
2.2%
Other values (37) 43
46.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 8
 
8.7%
사 7
 
7.6%
법 7
 
7.6%
회 7
 
7.6%
합 6
 
6.5%
단 4
 
4.3%
조 3
 
3.3%
기 3
 
3.3%
개 2
 
2.2%
타 2
 
2.2%
Other values (37) 43
46.7%

단체설명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T20:14:05.670868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length4
Mean length4.5454545
Min length3

Characters and Unicode

Total characters100
Distinct characters54
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

Unique22 ?
Unique (%)100.0%

Sample

1st row개인사업자
2nd row공공법인
3rd row교육기관
4th row기타법인
5th row사단법인
ValueCountFrequency (%)
개인사업자 1
 
4.5%
공공법인 1
 
4.5%
어린이집연합회 1
 
4.5%
마을회 1
 
4.5%
기타단체 1
 
4.5%
경로당 1
 
4.5%
협동조합 1
 
4.5%
합자회사 1
 
4.5%
합명회사 1
 
4.5%
특수법인 1
 
4.5%
Other values (12) 12
54.5%
2023-12-12T20:14:06.152350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 8
 
8.0%
사 7
 
7.0%
법 7
 
7.0%
회 7
 
7.0%
합 6
 
6.0%
단 4
 
4.0%
조 3
 
3.0%
기 3
 
3.0%
개 2
 
2.0%
수 2
 
2.0%
Other values (44) 51
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 100
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 8
 
8.0%
사 7
 
7.0%
법 7
 
7.0%
회 7
 
7.0%
합 6
 
6.0%
단 4
 
4.0%
조 3
 
3.0%
기 3
 
3.0%
개 2
 
2.0%
수 2
 
2.0%
Other values (44) 51
51.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 100
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 8
 
8.0%
사 7
 
7.0%
법 7
 
7.0%
회 7
 
7.0%
합 6
 
6.0%
단 4
 
4.0%
조 3
 
3.0%
기 3
 
3.0%
개 2
 
2.0%
수 2
 
2.0%
Other values (44) 51
51.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 100
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 8
 
8.0%
사 7
 
7.0%
법 7
 
7.0%
회 7
 
7.0%
합 6
 
6.0%
단 4
 
4.0%
조 3
 
3.0%
기 3
 
3.0%
개 2
 
2.0%
수 2
 
2.0%
Other values (44) 51
51.0%

Interactions

2023-12-12T20:14:03.104044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:14:02.718846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:14:03.231349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:14:02.961786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:14:06.286637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호단체코드단체구분단체명단체설명
관리번호1.0000.4511.0001.0001.000
단체코드0.4511.0000.5751.0001.000
단체구분1.0000.5751.0001.0001.000
단체명1.0001.0001.0001.0001.000
단체설명1.0001.0001.0001.0001.000
2023-12-12T20:14:06.446316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호단체코드단체구분
관리번호1.0000.1190.775
단체코드0.1191.0000.319
단체구분0.7750.3191.000

Missing values

2023-12-12T20:14:03.397521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:14:03.556598image/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

관리번호단체코드단체구분단체명단체설명
0118A개인사업자개인사업자
127A공공법인공공법인
238A교육기관교육기관
349A기타법인기타법인
4516A사단법인사단법인
5610A사회복지법인사회복지법인
674A영농조합영농조합
7820A온천관광지개발조합탑산약수온천관광지개발조합
896A유한회사유한회사
9105A의료법인의료법인
관리번호단체코드단체구분단체명단체설명
12133A주식회사주식회사
131411A특수법인특수법인
141512A합명회사합명회사
151613A합자회사합자회사
161714A협동조합협동조합
17181B경로당경로당
181919B기타단체기타단체
192021B마을회마을회
202122B연합회어린이집연합회
21222B작목반작목반