Overview

Dataset statistics

Number of variables9
Number of observations38
Missing cells30
Missing cells (%)8.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory79.5 B

Variable types

Numeric4
Categorical4
Text1

Dataset

Description진주시 무장애도시 홈페이지에서 사용하는 시설정보(BF인증시설, 힐링 산책로, 전동휠체어 충전소)에 대한 정보 총 91건을 제공합니다.
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15040736

Alerts

구분 has constant value ""Constant
일련번호 is highly overall correlated with 인증년도 and 2 other fieldsHigh correlation
인증년도 is highly overall correlated with 일련번호 and 3 other fieldsHigh correlation
좌표(위도) is highly overall correlated with 일련번호 and 2 other fieldsHigh correlation
좌표(경도) is highly overall correlated with 좌표(위도)High correlation
인증종류 is highly overall correlated with 인증년도High correlation
등급 is highly overall correlated with 일련번호 and 1 other fieldsHigh correlation
인증종류 is highly imbalanced (82.4%)Imbalance
등급 is highly imbalanced (60.2%)Imbalance
좌표(위도) has 15 (39.5%) missing valuesMissing
좌표(경도) has 15 (39.5%) missing valuesMissing
건축물 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:30:18.025971
Analysis finished2023-12-11 00:30:19.850954
Duration1.82 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.236842
Minimum1
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-11T09:30:19.901292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.85
Q110.25
median19.5
Q327.75
95-th percentile35.3
Maximum38
Range37
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation10.82648
Coefficient of variation (CV)0.56279921
Kurtosis-1.146597
Mean19.236842
Median Absolute Deviation (MAD)9
Skewness-0.017826704
Sum731
Variance117.21266
MonotonicityNot monotonic
2023-12-11T09:30:20.006261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
26 2
 
5.3%
1 1
 
2.6%
29 1
 
2.6%
22 1
 
2.6%
23 1
 
2.6%
24 1
 
2.6%
25 1
 
2.6%
27 1
 
2.6%
28 1
 
2.6%
30 1
 
2.6%
Other values (27) 27
71.1%
ValueCountFrequency (%)
1 1
2.6%
2 1
2.6%
3 1
2.6%
4 1
2.6%
5 1
2.6%
6 1
2.6%
7 1
2.6%
8 1
2.6%
9 1
2.6%
10 1
2.6%
ValueCountFrequency (%)
38 1
2.6%
37 1
2.6%
35 1
2.6%
34 1
2.6%
33 1
2.6%
32 1
2.6%
31 1
2.6%
30 1
2.6%
29 1
2.6%
28 1
2.6%

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
BF인증시설
38 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
BF인증시설 38
100.0%

Length

2023-12-11T09:30:20.113389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:30:20.188544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bf인증시설 38
100.0%

건축물
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-11T09:30:20.365707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length9.6578947
Min length3

Characters and Unicode

Total characters367
Distinct characters123
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

Unique38 ?
Unique (%)100.0%

Sample

1st row진주(부산방향)휴게소
2nd row진주역사
3rd row한국토지주택공사 본사사옥
4th row남가람 문화거리 공중화장실
5th row진양고등학교
ValueCountFrequency (%)
진주 3
 
4.3%
진주시 3
 
4.3%
경로당 3
 
4.3%
상봉동 2
 
2.9%
신진주역세권 2
 
2.9%
어린이도서관 2
 
2.9%
등산로변 2
 
2.9%
화장실 2
 
2.9%
진주(부산방향)휴게소 1
 
1.4%
월아산 1
 
1.4%
Other values (49) 49
70.0%
2023-12-11T09:30:20.677194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
 
8.7%
진 15
 
4.1%
주 15
 
4.1%
로 11
 
3.0%
경 11
 
3.0%
당 9
 
2.5%
센 8
 
2.2%
터 8
 
2.2%
교 8
 
2.2%
공 8
 
2.2%
Other values (113) 242
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 331
90.2%
Space Separator 32
 
8.7%
Close Punctuation 2
 
0.5%
Open Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 15
 
4.5%
주 15
 
4.5%
로 11
 
3.3%
경 11
 
3.3%
당 9
 
2.7%
센 8
 
2.4%
터 8
 
2.4%
교 8
 
2.4%
공 8
 
2.4%
산 8
 
2.4%
Other values (110) 230
69.5%
Space Separator
ValueCountFrequency (%)
32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 331
90.2%
Common 36
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 15
 
4.5%
주 15
 
4.5%
로 11
 
3.3%
경 11
 
3.3%
당 9
 
2.7%
센 8
 
2.4%
터 8
 
2.4%
교 8
 
2.4%
공 8
 
2.4%
산 8
 
2.4%
Other values (110) 230
69.5%
Common
ValueCountFrequency (%)
32
88.9%
) 2
 
5.6%
( 2
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 331
90.2%
ASCII 36
 
9.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
88.9%
) 2
 
5.6%
( 2
 
5.6%
Hangul
ValueCountFrequency (%)
진 15
 
4.5%
주 15
 
4.5%
로 11
 
3.3%
경 11
 
3.3%
당 9
 
2.7%
센 8
 
2.4%
터 8
 
2.4%
교 8
 
2.4%
공 8
 
2.4%
산 8
 
2.4%
Other values (110) 230
69.5%

인증종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
건축물
37 
여객시설
 
1

Length

Max length4
Median length3
Mean length3.0263158
Min length3

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row건축물
2nd row여객시설
3rd row건축물
4th row건축물
5th row건축물

Common Values

ValueCountFrequency (%)
건축물 37
97.4%
여객시설 1
 
2.6%

Length

2023-12-11T09:30:20.787240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:30:20.884834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건축물 37
97.4%
여객시설 1
 
2.6%

등급
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
우수
35 
최우수
 
3

Length

Max length3
Median length2
Mean length2.0789474
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row최우수
2nd row최우수
3rd row최우수
4th row우수
5th row우수

Common Values

ValueCountFrequency (%)
우수 35
92.1%
최우수 3
 
7.9%

Length

2023-12-11T09:30:20.968029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:30:21.055331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
우수 35
92.1%
최우수 3
 
7.9%

인증기관
Categorical

Distinct8
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size436.0 B
한국생산성본부인증원
9 
한국장애인개발원
8 
한국토지주택공사
8 
한국감정원
3 
한국환경건축연구원
3 
Other values (3)
7 

Length

Max length11
Median length10
Mean length8.5263158
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한국장애인개발원
2nd row한국토지주택공사
3rd row한국장애인개발원
4th row한국장애인개발원
5th row한국생산성본부인증원

Common Values

ValueCountFrequency (%)
한국생산성본부인증원 9
23.7%
한국장애인개발원 8
21.1%
한국토지주택공사 8
21.1%
한국감정원 3
 
7.9%
한국환경건축연구원 3
 
7.9%
한국건물에너지기술원 3
 
7.9%
한국교육녹색환경연구원 2
 
5.3%
한국부동산원 2
 
5.3%

Length

2023-12-11T09:30:21.138549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:30:21.233034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국생산성본부인증원 9
23.7%
한국장애인개발원 8
21.1%
한국토지주택공사 8
21.1%
한국감정원 3
 
7.9%
한국환경건축연구원 3
 
7.9%
한국건물에너지기술원 3
 
7.9%
한국교육녹색환경연구원 2
 
5.3%
한국부동산원 2
 
5.3%

인증년도
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.1053
Minimum2010
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-11T09:30:21.327939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2010
5-th percentile2014.7
Q12019
median2021
Q32022
95-th percentile2023
Maximum2023
Range13
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.7390023
Coefficient of variation (CV)0.0013558711
Kurtosis4.7634938
Mean2020.1053
Median Absolute Deviation (MAD)1
Skewness-1.9821631
Sum76764
Variance7.5021337
MonotonicityIncreasing
2023-12-11T09:30:21.420789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2021 11
28.9%
2022 8
21.1%
2019 4
 
10.5%
2020 4
 
10.5%
2023 4
 
10.5%
2018 3
 
7.9%
2010 1
 
2.6%
2013 1
 
2.6%
2015 1
 
2.6%
2017 1
 
2.6%
ValueCountFrequency (%)
2010 1
 
2.6%
2013 1
 
2.6%
2015 1
 
2.6%
2017 1
 
2.6%
2018 3
 
7.9%
2019 4
 
10.5%
2020 4
 
10.5%
2021 11
28.9%
2022 8
21.1%
2023 4
 
10.5%
ValueCountFrequency (%)
2023 4
 
10.5%
2022 8
21.1%
2021 11
28.9%
2020 4
 
10.5%
2019 4
 
10.5%
2018 3
 
7.9%
2017 1
 
2.6%
2015 1
 
2.6%
2013 1
 
2.6%
2010 1
 
2.6%

좌표(위도)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)95.7%
Missing15
Missing (%)39.5%
Infinite0
Infinite (%)0.0%
Mean35.186241
Minimum35.124876
Maximum35.330581
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-11T09:30:21.510282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.124876
5-th percentile35.151271
Q135.168706
median35.177541
Q335.196986
95-th percentile35.256479
Maximum35.330581
Range0.20570483
Interquartile range (IQR)0.028280092

Descriptive statistics

Standard deviation0.040874461
Coefficient of variation (CV)0.0011616604
Kurtosis6.9635525
Mean35.186241
Median Absolute Deviation (MAD)0.017908
Skewness2.2442991
Sum809.28354
Variance0.0016707216
MonotonicityNot monotonic
2023-12-11T09:30:21.594281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
35.153130700654685 2
 
5.3%
35.177541 1
 
2.6%
35.1924308851339 1
 
2.6%
35.201508608058454 1
 
2.6%
35.17048701929352 1
 
2.6%
35.19664285472158 1
 
2.6%
35.19856191633737 1
 
2.6%
35.20250744156044 1
 
2.6%
35.33058052336678 1
 
2.6%
35.18075719989984 1
 
2.6%
Other values (12) 12
31.6%
(Missing) 15
39.5%
ValueCountFrequency (%)
35.124875691248654 1
2.6%
35.151064 1
2.6%
35.153130700654685 2
5.3%
35.159633 1
2.6%
35.166924390870435 1
2.6%
35.17048701929352 1
2.6%
35.17347986146018 1
2.6%
35.175006 1
2.6%
35.17578831559866 1
2.6%
35.17614802357983 1
2.6%
ValueCountFrequency (%)
35.33058052336678 1
2.6%
35.262476 1
2.6%
35.20250744156044 1
2.6%
35.201508608058454 1
2.6%
35.19856191633737 1
2.6%
35.19732873942723 1
2.6%
35.19664285472158 1
2.6%
35.1924308851339 1
2.6%
35.184952 1
2.6%
35.18075719989984 1
2.6%

좌표(경도)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)95.7%
Missing15
Missing (%)39.5%
Infinite0
Infinite (%)0.0%
Mean128.10712
Minimum127.92774
Maximum128.16916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-11T09:30:21.678374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.92774
5-th percentile128.06318
Q1128.08325
median128.11831
Q3128.14784
95-th percentile128.16721
Maximum128.16916
Range0.24141825
Interquartile range (IQR)0.064588524

Descriptive statistics

Standard deviation0.051690842
Coefficient of variation (CV)0.00040349703
Kurtosis5.7389148
Mean128.10712
Median Absolute Deviation (MAD)0.031692938
Skewness-1.8176445
Sum2946.4638
Variance0.0026719432
MonotonicityNot monotonic
2023-12-11T09:30:21.772610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
128.11858523894452 2
 
5.3%
128.114515 1
 
2.6%
128.06258367723305 1
 
2.6%
127.92774494878908 1
 
2.6%
128.16916320322738 1
 
2.6%
128.09122227980365 1
 
2.6%
128.07512426670127 1
 
2.6%
128.08177511675618 1
 
2.6%
128.06856750154935 1
 
2.6%
128.08472883556863 1
 
2.6%
Other values (12) 12
31.6%
(Missing) 15
39.5%
ValueCountFrequency (%)
127.92774494878908 1
2.6%
128.06258367723305 1
2.6%
128.06856750154935 1
2.6%
128.07173503117758 1
2.6%
128.07512426670127 1
2.6%
128.08177511675618 1
2.6%
128.08472883556863 1
2.6%
128.08912590297618 1
2.6%
128.09122227980365 1
2.6%
128.09898314552265 1
2.6%
ValueCountFrequency (%)
128.16916320322738 1
2.6%
128.167224 1
2.6%
128.16709449640567 1
2.6%
128.15253822972787 1
2.6%
128.15000293839296 1
2.6%
128.149433 1
2.6%
128.146248 1
2.6%
128.12199 1
2.6%
128.11858523894452 2
5.3%
128.118496 1
2.6%

Interactions

2023-12-11T09:30:19.343426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:18.372347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:18.866640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:19.118359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:19.400710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:18.444887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:18.934900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:19.171847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:19.461212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:18.513475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:19.000923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:19.229271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:19.517025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:18.569449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:19.057537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:30:19.283863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:30:21.851558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호건축물인증종류등급인증기관인증년도좌표(위도)좌표(경도)
일련번호1.0001.0000.0000.9460.5890.8660.6480.394
건축물1.0001.0001.0001.0001.0001.0001.0001.000
인증종류0.0001.0001.0000.3110.0001.0000.0000.000
등급0.9461.0000.3111.0000.0001.0000.3660.572
인증기관0.5891.0000.0000.0001.0000.3910.0000.000
인증년도0.8661.0001.0001.0000.3911.0000.3130.212
좌표(위도)0.6481.0000.0000.3660.0000.3131.0000.759
좌표(경도)0.3941.0000.0000.5720.0000.2120.7591.000
2023-12-11T09:30:21.936419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인증기관등급인증종류
인증기관1.0000.0000.000
등급0.0001.0000.200
인증종류0.0000.2001.000
2023-12-11T09:30:22.002830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호인증년도좌표(위도)좌표(경도)인증종류등급인증기관
일련번호1.0000.9690.606-0.4280.0000.7060.308
인증년도0.9691.0000.660-0.4330.9130.9130.144
좌표(위도)0.6060.6601.000-0.5050.0000.2160.000
좌표(경도)-0.428-0.433-0.5051.0000.0000.3610.000
인증종류0.0000.9130.0000.0001.0000.2000.000
등급0.7060.9130.2160.3610.2001.0000.000
인증기관0.3080.1440.0000.0000.0000.0001.000

Missing values

2023-12-11T09:30:19.604796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:30:19.726871image/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.
2023-12-11T09:30:19.811311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

일련번호구분건축물인증종류등급인증기관인증년도좌표(위도)좌표(경도)
01BF인증시설진주(부산방향)휴게소건축물최우수한국장애인개발원201035.159633128.12199
12BF인증시설진주역사여객시설최우수한국토지주택공사201335.151064128.11831
23BF인증시설한국토지주택공사 본사사옥건축물최우수한국장애인개발원201535.178585128.146248
34BF인증시설남가람 문화거리 공중화장실건축물우수한국장애인개발원201735.176148128.089126
45BF인증시설진양고등학교건축물우수한국생산성본부인증원201835.175788128.152538
56BF인증시설신진주역세권 공원화장실건축물우수한국토지주택공사201835.153131128.118585
67BF인증시설신진주역세권 지하주차장건축물우수한국토지주택공사201835.153131128.118585
78BF인증시설진주충무공초등학교건축물우수한국감정원201935.17348128.150003
89BF인증시설진주 상봉어린이집건축물우수한국감정원201935.197329128.071735
910BF인증시설예하초등학교건축물우수한국감정원201935.124876128.098983
일련번호구분건축물인증종류등급인증기관인증년도좌표(위도)좌표(경도)
2829BF인증시설가호동행정복지센터건축물우수한국건물에너지기술원2022<NA><NA>
2930BF인증시설진양호 우드랜드 조성공사건축물우수한국건물에너지기술원2022<NA><NA>
3031BF인증시설상봉동 대봉경로당건축물우수한국생산성본부인증원2022<NA><NA>
3132BF인증시설평거동 숯골경로당건축물우수한국생산성본부인증원2022<NA><NA>
3233BF인증시설홍락원건축물우수한국부동산원2022<NA><NA>
3334BF인증시설진주 남부 어린이도서관건축물우수한국장애인개발원2022<NA><NA>
3435BF인증시설대곡면문화융합센터건축물우수한국생산성본부인증원2023<NA><NA>
3526BF인증시설금산경로당건축물우수한국장애인개발원2023<NA><NA>
3637BF인증시설진주시 장애인 문화체육센터건축물우수한국부동산원2023<NA><NA>
3738BF인증시설경남진주혁신도시 복합혁신센터건축물우수한국교육녹색환경연구원2023<NA><NA>