Overview

Dataset statistics

Number of variables11
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory91.6 B

Variable types

Numeric1
Categorical9
Text1

Dataset

Description대전광역시 서구 급경사지 현황 데이터입니다.(순번, 시도명, 시군구명, 읍면동, 행정동, 행정동코드, 법정동, 법정동코드, 지번주소, 도로명주소, 지번, 용도, 구조, 유형, 지구명, 관리기관, 공공/민간, 등급)
URLhttps://www.data.go.kr/data/15104098/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
관리기관 is highly overall correlated with 순번 and 2 other fieldsHigh correlation
종류 is highly overall correlated with 순번 and 2 other fieldsHigh correlation
순번 is highly overall correlated with 읍면동 and 3 other fieldsHigh correlation
읍면동 is highly overall correlated with 순번High correlation
유형 is highly overall correlated with 등급High correlation
공공-민간 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
등급 is highly overall correlated with 유형 and 1 other fieldsHigh correlation
구조 is highly imbalanced (76.2%)Imbalance
유형 is highly imbalanced (86.1%)Imbalance
공공-민간 is highly imbalanced (53.7%)Imbalance
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:37:04.561059
Analysis finished2023-12-11 23:37:06.036711
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-12T08:37:06.189528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q113.5
median26
Q338.5
95-th percentile48.5
Maximum51
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.57177187
Kurtosis-1.2
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum1326
Variance221
MonotonicityStrictly increasing
2023-12-12T08:37:06.478678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
2 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
51 1
2.0%
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
대전
51 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전 51
100.0%

Length

2023-12-12T08:37:06.743349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:06.938420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전 51
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
서구
51 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서구 51
100.0%

Length

2023-12-12T08:37:07.147987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:07.261090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구 51
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size540.0 B
정림동
11 
흑석동
7 
원정동
5 
괴곡동
4 
복수동
3 
Other values (12)
21 

Length

Max length4
Median length3
Mean length2.9215686
Min length2

Unique

Unique6 ?
Unique (%)11.8%

Sample

1st row장안동
2nd row흑석동
3rd row도마동
4th row탄방동
5th row오동

Common Values

ValueCountFrequency (%)
정림동 11
21.6%
흑석동 7
13.7%
원정동 5
9.8%
괴곡동 4
 
7.8%
복수동 3
 
5.9%
변동 3
 
5.9%
장안동 3
 
5.9%
도마동 3
 
5.9%
용촌동 2
 
3.9%
월평동 2
 
3.9%
Other values (7) 8
15.7%

Length

2023-12-12T08:37:07.393441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
정림동 11
21.6%
흑석동 7
13.7%
원정동 5
9.8%
괴곡동 4
 
7.8%
복수동 3
 
5.9%
변동 3
 
5.9%
장안동 3
 
5.9%
도마동 3
 
5.9%
매노동 2
 
3.9%
용촌동 2
 
3.9%
Other values (7) 8
15.7%

지번
Text

Distinct43
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-12T08:37:07.610856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.7058824
Min length2

Characters and Unicode

Total characters240
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)72.5%

Sample

1st row산54
2nd row산12
3rd row413-3
4th row1084
5th row산29-1
ValueCountFrequency (%)
산 6
 
10.5%
1011 4
 
7.0%
산54-6 2
 
3.5%
841-2 2
 
3.5%
460-11 2
 
3.5%
38-2 2
 
3.5%
600-6 2
 
3.5%
19-2 1
 
1.8%
산54 1
 
1.8%
19-3 1
 
1.8%
Other values (34) 34
59.6%
2023-12-12T08:37:07.963948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 44
18.3%
- 36
15.0%
4 24
10.0%
산 20
8.3%
2 20
8.3%
8 17
 
7.1%
0 15
 
6.2%
3 15
 
6.2%
5 14
 
5.8%
6 10
 
4.2%
Other values (3) 25
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 178
74.2%
Dash Punctuation 36
 
15.0%
Other Letter 20
 
8.3%
Space Separator 6
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 44
24.7%
4 24
13.5%
2 20
11.2%
8 17
 
9.6%
0 15
 
8.4%
3 15
 
8.4%
5 14
 
7.9%
6 10
 
5.6%
9 10
 
5.6%
7 9
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Other Letter
ValueCountFrequency (%)
산 20
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220
91.7%
Hangul 20
 
8.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 44
20.0%
- 36
16.4%
4 24
10.9%
2 20
9.1%
8 17
 
7.7%
0 15
 
6.8%
3 15
 
6.8%
5 14
 
6.4%
6 10
 
4.5%
9 10
 
4.5%
Other values (2) 15
 
6.8%
Hangul
ValueCountFrequency (%)
산 20
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220
91.7%
Hangul 20
 
8.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 44
20.0%
- 36
16.4%
4 24
10.9%
2 20
9.1%
8 17
 
7.7%
0 15
 
6.8%
3 15
 
6.8%
5 14
 
6.4%
6 10
 
4.5%
9 10
 
4.5%
Other values (2) 15
 
6.8%
Hangul
ValueCountFrequency (%)
산 20
100.0%

종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size540.0 B
철도
23 
도로
12 
기타
12 
공원
4 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row도로
2nd row도로
3rd row공원
4th row공원
5th row도로

Common Values

ValueCountFrequency (%)
철도 23
45.1%
도로 12
23.5%
기타 12
23.5%
공원 4
 
7.8%

Length

2023-12-12T08:37:08.087033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:08.178993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철도 23
45.1%
도로 12
23.5%
기타 12
23.5%
공원 4
 
7.8%

구조
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
복합
48 
암반
 
2
토사
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
복합 48
94.1%
암반 2
 
3.9%
토사 1
 
2.0%

Length

2023-12-12T08:37:08.305286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:08.407055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
복합 48
94.1%
암반 2
 
3.9%
토사 1
 
2.0%

유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
인공
50 
자연 또는 산지
 
1

Length

Max length8
Median length2
Mean length2.1176471
Min length2

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
인공 50
98.0%
자연 또는 산지 1
 
2.0%

Length

2023-12-12T08:37:08.521949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:08.668927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인공 50
94.3%
자연 1
 
1.9%
또는 1
 
1.9%
산지 1
 
1.9%

관리기관
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
지자체
28 
국가철도공단
23 

Length

Max length6
Median length3
Mean length4.3529412
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지자체 28
54.9%
국가철도공단 23
45.1%

Length

2023-12-12T08:37:08.776453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:08.878562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지자체 28
54.9%
국가철도공단 23
45.1%

공공-민간
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
공공
46 
민간
5 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공 46
90.2%
민간 5
 
9.8%

Length

2023-12-12T08:37:09.293612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:09.406197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공 46
90.2%
민간 5
 
9.8%

등급
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size540.0 B
B
26 
C
20 
A
3 
D
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
B 26
51.0%
C 20
39.2%
A 3
 
5.9%
D 2
 
3.9%

Length

2023-12-12T08:37:09.501574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:09.607445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b 26
51.0%
c 20
39.2%
a 3
 
5.9%
d 2
 
3.9%

Interactions

2023-12-12T08:37:05.404531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:37:09.736660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번읍면동지번종류구조유형관리기관공공-민간등급
순번1.0000.8550.9940.8590.0000.1250.9960.7560.497
읍면동0.8551.0001.0000.6380.0000.5600.6300.2240.000
지번0.9941.0001.0001.0001.0001.0001.0001.0000.801
종류0.8590.6381.0001.0000.0000.1221.0000.7680.625
구조0.0000.0001.0000.0001.0000.0000.0000.0000.486
유형0.1250.5601.0000.1220.0001.0000.0000.0000.873
관리기관0.9960.6301.0001.0000.0000.0001.0000.2900.746
공공-민간0.7560.2241.0000.7680.0000.0000.2901.0000.503
등급0.4970.0000.8010.6250.4860.8730.7460.5031.000
2023-12-12T08:37:09.851045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관등급공공-민간종류읍면동구조유형
관리기관1.0000.5270.1860.9790.4730.0000.000
등급0.5271.0000.3330.2850.0000.4780.662
공공-민간0.1860.3331.0000.5470.1480.0000.000
종류0.9790.2850.5471.0000.3430.0000.071
읍면동0.4730.0000.1480.3431.0000.0000.416
구조0.0000.4780.0000.0000.0001.0000.000
유형0.0000.6620.0000.0710.4160.0001.000
2023-12-12T08:37:09.970143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번읍면동종류구조유형관리기관공공-민간등급
순번1.0000.5060.6810.0000.0640.8600.5420.256
읍면동0.5061.0000.3430.0000.4160.4730.1480.000
종류0.6810.3431.0000.0000.0710.9790.5470.285
구조0.0000.0000.0001.0000.0000.0000.0000.478
유형0.0640.4160.0710.0001.0000.0000.0000.662
관리기관0.8600.4730.9790.0000.0001.0000.1860.527
공공-민간0.5420.1480.5470.0000.0000.1861.0000.333
등급0.2560.0000.2850.4780.6620.5270.3331.000

Missing values

2023-12-12T08:37:05.622131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:37:05.926716image/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

순번시도명시군구명읍면동지번종류구조유형관리기관공공-민간등급
01대전서구장안동산54도로복합인공지자체공공C
12대전서구흑석동산12도로복합인공지자체공공C
23대전서구도마동413-3공원복합인공지자체공공C
34대전서구탄방동1084공원복합인공지자체공공B
45대전서구오동산29-1도로복합인공지자체공공B
56대전서구장안동287-4공원복합인공지자체공공C
67대전서구월평동산11-4공원복합인공지자체공공C
78대전서구월평동산15-1기타복합자연 또는 산지지자체공공D
89대전서구도마동317-128도로복합인공지자체공공C
910대전서구정림동산34-19도로복합인공지자체공공C
순번시도명시군구명읍면동지번종류구조유형관리기관공공-민간등급
4142대전서구흑석동754철도복합인공국가철도공단공공B
4243대전서구매노동600-6철도복합인공국가철도공단공공B
4344대전서구매노동600-6철도복합인공국가철도공단공공A
4445대전서구용촌동산 38-2철도복합인공국가철도공단공공B
4546대전서구용촌동산 38-2철도복합인공국가철도공단공공B
4647대전서구원정동969철도복합인공국가철도공단공공B
4748대전서구원정동1011철도복합인공국가철도공단공공B
4849대전서구원정동1011철도복합인공국가철도공단공공B
4950대전서구원정동1011철도복합인공국가철도공단공공B
5051대전서구원정동1011철도복합인공국가철도공단공공B