Overview

Dataset statistics

Number of variables4
Number of observations1311
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.4 KiB
Average record size in memory33.1 B

Variable types

Numeric1
Categorical2
Text1

Dataset

Description기반시설관리법 제6조(기반시설의 관리체계)에 따른 관리주체 목록입니다. 해당 관리주체를 대상으로 매년 2월초 실행계획 수립·시행 예정이므로 지속적인 업데이트 예정입니다.
Author국토안전관리원
URLhttps://www.data.go.kr/data/15110674/fileData.do

Alerts

순번 is highly overall correlated with 시설종류이름 High correlation
시설종류이름 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-23 07:44:01.962066
Analysis finished2023-12-23 07:44:04.565577
Duration2.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1311
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean656
Minimum1
Maximum1311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.7 KiB
2023-12-23T07:44:05.427090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile66.5
Q1328.5
median656
Q3983.5
95-th percentile1245.5
Maximum1311
Range1310
Interquartile range (IQR)655

Descriptive statistics

Standard deviation378.59741
Coefficient of variation (CV)0.5771302
Kurtosis-1.2
Mean656
Median Absolute Deviation (MAD)328
Skewness0
Sum860016
Variance143336
MonotonicityStrictly increasing
2023-12-23T07:44:07.193423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
882 1
 
0.1%
880 1
 
0.1%
879 1
 
0.1%
878 1
 
0.1%
877 1
 
0.1%
876 1
 
0.1%
875 1
 
0.1%
874 1
 
0.1%
873 1
 
0.1%
Other values (1301) 1301
99.2%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1311 1
0.1%
1310 1
0.1%
1309 1
0.1%
1308 1
0.1%
1307 1
0.1%
1306 1
0.1%
1305 1
0.1%
1304 1
0.1%
1303 1
0.1%
1302 1
0.1%

시설종류이름
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size10.4 KiB
도로
311 
하천
235 
하수도
235 
저수지
173 
수도
161 
Other values (11)
196 

Length

Max length3
Median length2
Mean length2.3455378
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
도로 311
23.7%
하천 235
17.9%
하수도 235
17.9%
저수지 173
13.2%
수도 161
12.3%
어항 66
 
5.0%
열공급 33
 
2.5%
철도 26
 
2.0%
항만 23
 
1.8%
공동구 20
 
1.5%
Other values (6) 28
 
2.1%

Length

2023-12-23T07:44:08.272765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도로 311
23.7%
하천 235
17.9%
하수도 235
17.9%
저수지 173
13.2%
수도 161
12.3%
어항 66
 
5.0%
열공급 33
 
2.5%
철도 26
 
2.0%
항만 23
 
1.8%
공동구 20
 
1.5%
Other values (6) 28
 
2.1%

관리감독기관
Categorical

Distinct23
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size10.4 KiB
경기도
177 
전라남도
128 
경상북도
121 
경상남도
107 
강원특별자치도
94 
Other values (18)
684 

Length

Max length9
Median length7
Mean length4.5286041
Min length3

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row환경부
2nd row산업통상자원부
3rd row부산광역시
4th row광주광역시
5th row울산광역시

Common Values

ValueCountFrequency (%)
경기도 177
13.5%
전라남도 128
9.8%
경상북도 121
 
9.2%
경상남도 107
 
8.2%
강원특별자치도 94
 
7.2%
서울특별시 90
 
6.9%
충청남도 85
 
6.5%
전라북도 75
 
5.7%
부산광역시 70
 
5.3%
충청북도 58
 
4.4%
Other values (13) 306
23.3%

Length

2023-12-23T07:44:09.644194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 177
13.5%
전라남도 128
9.8%
경상북도 121
 
9.2%
경상남도 107
 
8.2%
강원특별자치도 94
 
7.2%
서울특별시 90
 
6.9%
충청남도 85
 
6.5%
전라북도 75
 
5.7%
부산광역시 70
 
5.3%
충청북도 58
 
4.4%
Other values (13) 306
23.3%

관리주체(관리기관2)
Text

Distinct437
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size10.4 KiB
2023-12-23T07:44:12.099432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.9252479
Min length2

Characters and Unicode

Total characters10390
Distinct characters241
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique161 ?
Unique (%)12.3%

Sample

1st row한국수자원공사
2nd row한국수력원자력(주)
3rd row부산광역시
4th row광주광역시
5th row울산광역시
ValueCountFrequency (%)
경기도 132
 
5.8%
전라남도 120
 
5.3%
경상북도 106
 
4.7%
경상남도 88
 
3.9%
강원특별자치도 78
 
3.4%
서울특별시 78
 
3.4%
충청남도 71
 
3.1%
전라북도 66
 
2.9%
부산광역시 61
 
2.7%
충청북도 50
 
2.2%
Other values (407) 1414
62.5%
2023-12-23T07:44:14.265318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
953
 
9.2%
도 894
 
8.6%
시 640
 
6.2%
군 405
 
3.9%
경 371
 
3.6%
남 335
 
3.2%
구 288
 
2.8%
상 276
 
2.7%
광 257
 
2.5%
북 247
 
2.4%
Other values (231) 5724
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9285
89.4%
Space Separator 953
 
9.2%
Open Punctuation 53
 
0.5%
Close Punctuation 53
 
0.5%
Uppercase Letter 22
 
0.2%
Other Symbol 16
 
0.2%
Decimal Number 7
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 894
 
9.6%
시 640
 
6.9%
군 405
 
4.4%
경 371
 
4.0%
남 335
 
3.6%
구 288
 
3.1%
상 276
 
3.0%
광 257
 
2.8%
북 247
 
2.7%
전 229
 
2.5%
Other values (212) 5343
57.5%
Uppercase Letter
ValueCountFrequency (%)
S 5
22.7%
G 4
18.2%
K 3
13.6%
B 2
 
9.1%
J 2
 
9.1%
R 1
 
4.5%
C 1
 
4.5%
E 1
 
4.5%
L 1
 
4.5%
N 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
2 5
71.4%
3 1
 
14.3%
9 1
 
14.3%
Space Separator
ValueCountFrequency (%)
953
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9301
89.5%
Common 1067
 
10.3%
Latin 22
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 894
 
9.6%
시 640
 
6.9%
군 405
 
4.4%
경 371
 
4.0%
남 335
 
3.6%
구 288
 
3.1%
상 276
 
3.0%
광 257
 
2.8%
북 247
 
2.7%
전 229
 
2.5%
Other values (213) 5359
57.6%
Latin
ValueCountFrequency (%)
S 5
22.7%
G 4
18.2%
K 3
13.6%
B 2
 
9.1%
J 2
 
9.1%
R 1
 
4.5%
C 1
 
4.5%
E 1
 
4.5%
L 1
 
4.5%
N 1
 
4.5%
Common
ValueCountFrequency (%)
953
89.3%
( 53
 
5.0%
) 53
 
5.0%
2 5
 
0.5%
3 1
 
0.1%
9 1
 
0.1%
, 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9285
89.4%
ASCII 1089
 
10.5%
None 16
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
953
87.5%
( 53
 
4.9%
) 53
 
4.9%
S 5
 
0.5%
2 5
 
0.5%
G 4
 
0.4%
K 3
 
0.3%
B 2
 
0.2%
J 2
 
0.2%
3 1
 
0.1%
Other values (8) 8
 
0.7%
Hangul
ValueCountFrequency (%)
도 894
 
9.6%
시 640
 
6.9%
군 405
 
4.4%
경 371
 
4.0%
남 335
 
3.6%
구 288
 
3.1%
상 276
 
3.0%
광 257
 
2.8%
북 247
 
2.7%
전 229
 
2.5%
Other values (212) 5343
57.5%
None
ValueCountFrequency (%)
㈜ 16
100.0%

Interactions

2023-12-23T07:44:03.230742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-23T07:44:14.564074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시설종류이름관리감독기관
순번1.0000.9180.746
시설종류이름0.9181.0000.826
관리감독기관0.7460.8261.000
2023-12-23T07:44:14.837724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류이름관리감독기관
시설종류이름1.0000.414
관리감독기관0.4141.000
2023-12-23T07:44:15.044769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시설종류이름관리감독기관
순번1.0000.6890.387
시설종류이름0.6891.0000.414
관리감독기관0.3870.4141.000

Missing values

2023-12-23T07:44:03.898587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T07:44:04.416137image/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

순번시설종류이름관리감독기관관리주체(관리기관2)
01댐환경부한국수자원공사
12댐산업통상자원부한국수력원자력(주)
23댐부산광역시부산광역시
34댐광주광역시광주광역시
45댐울산광역시울산광역시
56댐경기도경기도 수원시
67댐경기도경기도 의정부시
78댐전라남도전라남도 함평군
89하천환경부한강유역환경청
910하천환경부낙동강유역환경청
순번시설종류이름관리감독기관관리주체(관리기관2)
13011302도로강원특별자치도강원특별자치도 횡성군
13021303도로강원특별자치도강원특별자치도 영월군
13031304도로강원특별자치도강원특별자치도 평창군
13041305도로강원특별자치도강원특별자치도 정선군
13051306도로강원특별자치도강원특별자치도 철원군
13061307도로강원특별자치도강원특별자치도 화천군
13071308도로강원특별자치도강원특별자치도 양구군
13081309도로강원특별자치도강원특별자치도 인제군
13091310도로강원특별자치도강원특별자치도 고성군
13101311도로강원특별자치도강원특별자치도 양양군