Overview

Dataset statistics

Number of variables10
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory83.6 B

Variable types

Numeric1
Text2
Boolean5
Categorical1
DateTime1

Dataset

Description전라남도 광양시 공공시설 운영 현황 목록입니다. 공공시설명, 소재지, 교통약자 시설 설치 여부가 포함되어 있습니다.
URLhttps://www.data.go.kr/data/15101642/fileData.do

Alerts

데이터기준일 has constant value ""Constant
순번 is highly overall correlated with 엘레베이터여부High correlation
엘레베이터여부 is highly overall correlated with 순번High correlation
장애인화장실여부 is highly imbalanced (76.1%)Imbalance
주차장여부 is highly imbalanced (86.1%)Imbalance
장애인주차장여부 is highly imbalanced (76.1%)Imbalance
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:44:09.478384
Analysis finished2023-12-12 08:44:10.540675
Duration1.06 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
2023-12-12T17:44:10.627465image/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
2023-12-12T17:44:10.771787image/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%

공공시설명
Text

Distinct50
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-12T17:44:10.996012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length8.7647059
Min length4

Characters and Unicode

Total characters447
Distinct characters122
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)96.1%

Sample

1st row광양청년꿈터
2nd row광양시청
3rd row광양시청 별관(시의회)
4th row근로자종합복지관
5th row제2의광양시노인복지회관
ValueCountFrequency (%)
청소년문화센터 2
 
3.3%
광양시청 2
 
3.3%
성황스포츠센터 2
 
3.3%
금호동주민자치센터 1
 
1.7%
종합복지센터 1
 
1.7%
다목적체육관 1
 
1.7%
광양중마도서관 1
 
1.7%
광양희망도서관 1
 
1.7%
광양 1
 
1.7%
용강도서관 1
 
1.7%
Other values (47) 47
78.3%
2023-12-12T17:44:11.351314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 21
 
4.7%
양 21
 
4.7%
터 19
 
4.3%
센 18
 
4.0%
관 15
 
3.4%
사 12
 
2.7%
소 11
 
2.5%
10
 
2.2%
무 10
 
2.2%
시 10
 
2.2%
Other values (112) 300
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 420
94.0%
Space Separator 10
 
2.2%
Open Punctuation 7
 
1.6%
Close Punctuation 7
 
1.6%
Decimal Number 3
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 21
 
5.0%
양 21
 
5.0%
터 19
 
4.5%
센 18
 
4.3%
관 15
 
3.6%
사 12
 
2.9%
소 11
 
2.6%
무 10
 
2.4%
시 10
 
2.4%
지 9
 
2.1%
Other values (107) 274
65.2%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 420
94.0%
Common 27
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 21
 
5.0%
양 21
 
5.0%
터 19
 
4.5%
센 18
 
4.3%
관 15
 
3.6%
사 12
 
2.9%
소 11
 
2.6%
무 10
 
2.4%
시 10
 
2.4%
지 9
 
2.1%
Other values (107) 274
65.2%
Common
ValueCountFrequency (%)
10
37.0%
( 7
25.9%
) 7
25.9%
2 2
 
7.4%
1 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 420
94.0%
ASCII 27
 
6.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 21
 
5.0%
양 21
 
5.0%
터 19
 
4.5%
센 18
 
4.3%
관 15
 
3.6%
사 12
 
2.9%
소 11
 
2.6%
무 10
 
2.4%
시 10
 
2.4%
지 9
 
2.1%
Other values (107) 274
65.2%
ASCII
ValueCountFrequency (%)
10
37.0%
( 7
25.9%
) 7
25.9%
2 2
 
7.4%
1 1
 
3.7%

소재지
Text

Distinct48
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-12T17:44:11.605054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length20.568627
Min length15

Characters and Unicode

Total characters1049
Distinct characters77
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

Unique45 ?
Unique (%)88.2%

Sample

1st row전라남도 광양시 중동 1658
2nd row전라남도 광양시 중동 1313
3rd row전라남도 광양시 중동 1318-2
4th row전라남도 광양시 중동 1349
5th row전라남도 광양시 중동 1359-3
ValueCountFrequency (%)
전라남도 51
21.7%
광양시 51
21.7%
광양읍 17
 
7.2%
중동 9
 
3.8%
칠성리 6
 
2.6%
옥룡면 4
 
1.7%
마동 3
 
1.3%
추산리 3
 
1.3%
봉강면 3
 
1.3%
금호동 2
 
0.9%
Other values (76) 86
36.6%
2023-12-12T17:44:12.019191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
239
22.8%
광 71
 
6.8%
양 68
 
6.5%
도 53
 
5.1%
전 51
 
4.9%
남 51
 
4.9%
시 51
 
4.9%
라 51
 
4.9%
1 39
 
3.7%
리 27
 
2.6%
Other values (67) 348
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 595
56.7%
Space Separator 239
22.8%
Decimal Number 188
 
17.9%
Dash Punctuation 27
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 71
11.9%
양 68
11.4%
도 53
 
8.9%
전 51
 
8.6%
남 51
 
8.6%
시 51
 
8.6%
라 51
 
8.6%
리 27
 
4.5%
동 19
 
3.2%
읍 18
 
3.0%
Other values (55) 135
22.7%
Decimal Number
ValueCountFrequency (%)
1 39
20.7%
2 27
14.4%
6 22
11.7%
3 19
10.1%
4 17
9.0%
9 17
9.0%
7 14
 
7.4%
8 13
 
6.9%
0 11
 
5.9%
5 9
 
4.8%
Space Separator
ValueCountFrequency (%)
239
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 595
56.7%
Common 454
43.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 71
11.9%
양 68
11.4%
도 53
 
8.9%
전 51
 
8.6%
남 51
 
8.6%
시 51
 
8.6%
라 51
 
8.6%
리 27
 
4.5%
동 19
 
3.2%
읍 18
 
3.0%
Other values (55) 135
22.7%
Common
ValueCountFrequency (%)
239
52.6%
1 39
 
8.6%
2 27
 
5.9%
- 27
 
5.9%
6 22
 
4.8%
3 19
 
4.2%
4 17
 
3.7%
9 17
 
3.7%
7 14
 
3.1%
8 13
 
2.9%
Other values (2) 20
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 595
56.7%
ASCII 454
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
239
52.6%
1 39
 
8.6%
2 27
 
5.9%
- 27
 
5.9%
6 22
 
4.8%
3 19
 
4.2%
4 17
 
3.7%
9 17
 
3.7%
7 14
 
3.1%
8 13
 
2.9%
Other values (2) 20
 
4.4%
Hangul
ValueCountFrequency (%)
광 71
11.9%
양 68
11.4%
도 53
 
8.9%
전 51
 
8.6%
남 51
 
8.6%
시 51
 
8.6%
라 51
 
8.6%
리 27
 
4.5%
동 19
 
3.2%
읍 18
 
3.0%
Other values (55) 135
22.7%

장애인화장실여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size183.0 B
True
49 
False
 
2
ValueCountFrequency (%)
True 49
96.1%
False 2
 
3.9%
2023-12-12T17:44:12.145954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

엘레베이터여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size183.0 B
True
33 
False
18 
ValueCountFrequency (%)
True 33
64.7%
False 18
35.3%
2023-12-12T17:44:12.224150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

주차장여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size183.0 B
True
50 
False
 
1
ValueCountFrequency (%)
True 50
98.0%
False 1
 
2.0%
2023-12-12T17:44:12.301105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

장애인주차장여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size183.0 B
True
49 
False
 
2
ValueCountFrequency (%)
True 49
96.1%
False 2
 
3.9%
2023-12-12T17:44:12.384335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

유도블럭점자블럭여부
Boolean

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size183.0 B
True
42 
False
9 
ValueCountFrequency (%)
True 42
82.4%
False 9
 
17.6%
2023-12-12T17:44:12.470190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

출입구 경사로-계단
Categorical

Distinct4
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size540.0 B
경사로, 계단
27 
경사로
21 
계단
 
2
경사로
 
1

Length

Max length7
Median length7
Mean length5.0980392
Min length2

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row경사로, 계단
2nd row경사로, 계단
3rd row경사로, 계단
4th row경사로
5th row경사로

Common Values

ValueCountFrequency (%)
경사로, 계단 27
52.9%
경사로 21
41.2%
계단 2
 
3.9%
경사로 1
 
2.0%

Length

2023-12-12T17:44:12.583199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:44:12.687355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경사로 49
62.8%
계단 29
37.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
Minimum2023-06-29 00:00:00
Maximum2023-06-29 00:00:00
2023-12-12T17:44:12.766438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:44:12.851826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T17:44:10.148184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:44:12.923817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번공공시설명소재지장애인화장실여부엘레베이터여부주차장여부장애인주차장여부유도블럭점자블럭여부출입구 경사로-계단
순번1.0001.0000.9300.0000.7220.1250.0000.6190.257
공공시설명1.0001.0000.9941.0001.0001.0001.0001.0001.000
소재지0.9300.9941.0000.0000.8091.0001.0000.0000.993
장애인화장실여부0.0001.0000.0001.0000.0000.0000.0000.0000.000
엘레베이터여부0.7221.0000.8090.0001.0000.0000.0000.4990.416
주차장여부0.1251.0001.0000.0000.0001.0000.4650.0000.000
장애인주차장여부0.0001.0001.0000.0000.0000.4651.0000.0000.000
유도블럭점자블럭여부0.6191.0000.0000.0000.4990.0000.0001.0000.000
출입구 경사로-계단0.2571.0000.9930.0000.4160.0000.0000.0001.000
2023-12-12T17:44:13.050004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출입구 경사로-계단장애인화장실여부주차장여부엘레베이터여부장애인주차장여부유도블럭점자블럭여부
출입구 경사로-계단1.0000.0000.0000.2720.0000.000
장애인화장실여부0.0001.0000.0000.0000.0000.000
주차장여부0.0000.0001.0000.0000.3080.000
엘레베이터여부0.2720.0000.0001.0000.0000.332
장애인주차장여부0.0000.0000.3080.0001.0000.000
유도블럭점자블럭여부0.0000.0000.0000.3320.0001.000
2023-12-12T17:44:13.168921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번장애인화장실여부엘레베이터여부주차장여부장애인주차장여부유도블럭점자블럭여부출입구 경사로-계단
순번1.0000.0000.6430.0640.0000.4760.050
장애인화장실여부0.0001.0000.0000.0000.0000.0000.000
엘레베이터여부0.6430.0001.0000.0000.0000.3320.272
주차장여부0.0640.0000.0001.0000.3080.0000.000
장애인주차장여부0.0000.0000.0000.3081.0000.0000.000
유도블럭점자블럭여부0.4760.0000.3320.0000.0001.0000.000
출입구 경사로-계단0.0500.0000.2720.0000.0000.0001.000

Missing values

2023-12-12T17:44:10.281778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:44:10.474085image/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

순번공공시설명소재지장애인화장실여부엘레베이터여부주차장여부장애인주차장여부유도블럭점자블럭여부출입구 경사로-계단데이터기준일
01광양청년꿈터전라남도 광양시 중동 1658YYYYY경사로, 계단2023-06-29
12광양시청전라남도 광양시 중동 1313YYYYY경사로, 계단2023-06-29
23광양시청 별관(시의회)전라남도 광양시 중동 1318-2YYYYY경사로, 계단2023-06-29
34근로자종합복지관전라남도 광양시 중동 1349YNYYN경사로2023-06-29
45제2의광양시노인복지회관전라남도 광양시 중동 1359-3YYYYY경사로2023-06-29
56중마권역 장애인종합복지관 건립전라남도 광양시 마동 1212YYYYY경사로2023-06-29
67광양시노인복지회관전라남도 광양시 광양읍 목성리 690-8YYYYY경사로2023-06-29
78장애인복지회관전라남도 광양시 광양읍 덕례리 1724-3YYYYY경사로2023-06-29
89광양시립영세공원전라남도 광양시 광양읍 죽림리 산 2-1YYYYY경사로2023-06-29
910광양노인전문요양원전라남도 광양시 옥곡면 대죽리 664YYYYY경사로, 계단2023-06-29
순번공공시설명소재지장애인화장실여부엘레베이터여부주차장여부장애인주차장여부유도블럭점자블럭여부출입구 경사로-계단데이터기준일
4142옥룡면사무소(사무소)전라남도 광양시 옥룡면 운평리 262YNYYY경사로, 계단2023-06-29
4243옥곡면사무소(제1종근린시설)전라남도 광양시 옥곡면 신금리 1375-3YNYNY경사로, 계단2023-06-29
4344진상면사무소전라남도 광양시 진상면 섬거리 292YNYYY경사로, 계단2023-06-29
4445진월면사무소(사무실 교육실)전라남도 광양시 진월면 선소리 167YNYYY경사로2023-06-29
4546다압면사무소전라남도 광양시 다압면 고사리 1376YNYYY경사로, 계단2023-06-29
4647중마동 주민자치센터전라남도 광양시 중동 1314-6YYYYY경사로2023-06-29
4748태인동 종합복지센터전라남도 광양시 태인동 398-0YYYYY경사로, 계단2023-06-29
4849금호동주민자치센터전라남도 광양시 금호동 624-22YYYYY경사로, 계단2023-06-29
4950성황스포츠센터 다목적체육관전라남도 광양시 성황도이로 66-22YYYYY경사로, 계단2023-06-29
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