Overview

Dataset statistics

Number of variables4
Number of observations284
Missing cells0
Missing cells (%)0.0%
Duplicate rows53
Duplicate rows (%)18.7%
Total size in memory9.6 KiB
Average record size in memory34.5 B

Variable types

Text1
Numeric2
Boolean1

Dataset

Description충청북도 단양군의 내부행정 업무를 위해 운영되고 있는 소통앱 데이터로 부서정보 데이터 입니다. 부서명, 조직순서, 정렬순서, 삭제 여부의 항목으로 구성되어있습니다.
Author충청북도 단양군
URLhttps://www.data.go.kr/data/15123654/fileData.do

Alerts

삭제여부 has constant value ""Constant
Dataset has 53 (18.7%) duplicate rowsDuplicates
조직순서 is highly overall correlated with 정렬순서High correlation
정렬순서 is highly overall correlated with 조직순서High correlation

Reproduction

Analysis started2023-12-12 21:46:40.527898
Analysis finished2023-12-12 21:46:41.144708
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

부서명
Text

Distinct193
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-13T06:46:41.377866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.6725352
Min length2

Characters and Unicode

Total characters1327
Distinct characters175
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)45.4%

Sample

1st row단양군
2nd row의회사무과
3rd row보건소
4th row농업기술센터
5th row단양읍
ValueCountFrequency (%)
총무팀 8
 
2.8%
민원재무팀 8
 
2.8%
산업개발팀 6
 
2.1%
복지팀 6
 
2.1%
가축방역팀 3
 
1.1%
농업축산과 3
 
1.1%
농업기반팀 3
 
1.1%
친환경농업팀 3
 
1.1%
원예특작팀 3
 
1.1%
축수산팀 3
 
1.1%
Other values (183) 238
83.8%
2023-12-13T06:46:41.919616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
팀 215
 
16.2%
지 43
 
3.2%
산 38
 
2.9%
과 34
 
2.6%
농 34
 
2.6%
업 33
 
2.5%
관 25
 
1.9%
정 24
 
1.8%
경 24
 
1.8%
건 22
 
1.7%
Other values (165) 835
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1325
99.8%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
팀 215
 
16.2%
지 43
 
3.2%
산 38
 
2.9%
과 34
 
2.6%
농 34
 
2.6%
업 33
 
2.5%
관 25
 
1.9%
정 24
 
1.8%
경 24
 
1.8%
건 22
 
1.7%
Other values (163) 833
62.9%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1325
99.8%
Common 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
팀 215
 
16.2%
지 43
 
3.2%
산 38
 
2.9%
과 34
 
2.6%
농 34
 
2.6%
업 33
 
2.5%
관 25
 
1.9%
정 24
 
1.8%
경 24
 
1.8%
건 22
 
1.7%
Other values (163) 833
62.9%
Common
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1325
99.8%
ASCII 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
팀 215
 
16.2%
지 43
 
3.2%
산 38
 
2.9%
과 34
 
2.6%
농 34
 
2.6%
업 33
 
2.5%
관 25
 
1.9%
정 24
 
1.8%
경 24
 
1.8%
건 22
 
1.7%
Other values (163) 833
62.9%
ASCII
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%

조직순서
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4401408
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T06:46:42.079809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile7
Maximum14
Range13
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.9999844
Coefficient of variation (CV)0.58136702
Kurtosis5.5651991
Mean3.4401408
Median Absolute Deviation (MAD)1
Skewness1.7206774
Sum977
Variance3.9999378
MonotonicityNot monotonic
2023-12-13T06:46:42.238082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
4 71
25.0%
3 68
23.9%
2 45
15.8%
1 45
15.8%
5 25
 
8.8%
6 13
 
4.6%
7 7
 
2.5%
8 3
 
1.1%
9 2
 
0.7%
10 1
 
0.4%
Other values (4) 4
 
1.4%
ValueCountFrequency (%)
1 45
15.8%
2 45
15.8%
3 68
23.9%
4 71
25.0%
5 25
 
8.8%
6 13
 
4.6%
7 7
 
2.5%
8 3
 
1.1%
9 2
 
0.7%
10 1
 
0.4%
ValueCountFrequency (%)
14 1
 
0.4%
13 1
 
0.4%
12 1
 
0.4%
11 1
 
0.4%
10 1
 
0.4%
9 2
 
0.7%
8 3
 
1.1%
7 7
 
2.5%
6 13
4.6%
5 25
8.8%

정렬순서
Real number (ℝ)

HIGH CORRELATION 

Distinct54
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1373239
Minimum1
Maximum55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T06:46:42.440448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile40.85
Maximum55
Range54
Interquartile range (IQR)4

Descriptive statistics

Standard deviation12.085041
Coefficient of variation (CV)1.485137
Kurtosis5.0314786
Mean8.1373239
Median Absolute Deviation (MAD)2
Skewness2.4421428
Sum2311
Variance146.04821
MonotonicityNot monotonic
2023-12-13T06:46:42.609731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 46
16.2%
1 45
15.8%
2 45
15.8%
4 42
14.8%
5 26
9.2%
6 14
 
4.9%
7 8
 
2.8%
8 4
 
1.4%
9 3
 
1.1%
16 2
 
0.7%
Other values (44) 49
17.3%
ValueCountFrequency (%)
1 45
15.8%
2 45
15.8%
3 46
16.2%
4 42
14.8%
5 26
9.2%
6 14
 
4.9%
7 8
 
2.8%
8 4
 
1.4%
9 3
 
1.1%
10 2
 
0.7%
ValueCountFrequency (%)
55 1
0.4%
54 1
0.4%
53 1
0.4%
52 1
0.4%
51 1
0.4%
50 1
0.4%
49 1
0.4%
48 1
0.4%
47 1
0.4%
46 1
0.4%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size416.0 B
False
284 
ValueCountFrequency (%)
False 284
100.0%
2023-12-13T06:46:42.733536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-13T06:46:40.842905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:46:40.658703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:46:40.931700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:46:40.753344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:46:42.797784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조직순서정렬순서
조직순서1.0000.782
정렬순서0.7821.000
2023-12-13T06:46:42.899714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조직순서정렬순서
조직순서1.0000.802
정렬순서0.8021.000

Missing values

2023-12-13T06:46:41.040198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:46:41.113884image/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

부서명조직순서정렬순서삭제여부
0단양군216N
1의회사무과334N
2보건소331N
3농업기술센터326N
4단양읍335N
5매포읍336N
6단성면337N
7대강면338N
8가곡면339N
9영춘면340N
부서명조직순서정렬순서삭제여부
274상수도팀22N
275하수도팀33N
276농업진흥팀11N
277인력육성팀22N
278농기계팀33N
279식량작물팀44N
280소득작목팀55N
281과학영농팀66N
282농산물가공팀77N
283정책지원팀33N

Duplicate rows

Most frequently occurring

부서명조직순서정렬순서삭제여부# duplicates
42총무팀11N8
19민원재무팀33N6
21복지팀22N6
27산업개발팀44N6
0가축방역팀55N3
36원예특작팀33N3
43축수산팀44N3
44친환경농업팀22N3
1감사팀33N2
2건설팀66N2