Overview

Dataset statistics

Number of variables5
Number of observations125
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory44.1 B

Variable types

Numeric3
Text1
Categorical1

Dataset

Description대전광역시 서구 관내 장애인 주차장의 위치정보 현황에 대한 데이터입니다.(장애인 주차장 위치, 행정동명, 위도, 경도)
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15075610/fileData.do

Alerts

위도 is highly overall correlated with 행정동명High correlation
경도 is highly overall correlated with 행정동명High correlation
행정동명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-23 07:43:53.165436
Analysis finished2023-12-23 07:43:59.499364
Duration6.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct125
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63
Minimum1
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-23T07:44:00.009469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.2
Q132
median63
Q394
95-th percentile118.8
Maximum125
Range124
Interquartile range (IQR)62

Descriptive statistics

Standard deviation36.228442
Coefficient of variation (CV)0.57505463
Kurtosis-1.2
Mean63
Median Absolute Deviation (MAD)31
Skewness0
Sum7875
Variance1312.5
MonotonicityStrictly increasing
2023-12-23T07:44:01.158120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
80 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
Other values (115) 115
92.0%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
125 1
0.8%
124 1
0.8%
123 1
0.8%
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%

장애인주차장위치
Text

Distinct124
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-23T07:44:02.265646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length14.048
Min length10

Characters and Unicode

Total characters1756
Distinct characters70
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

Unique123 ?
Unique (%)98.4%

Sample

1st row대전 서구 대덕대로 176번길
2nd row대전 서구 가장동 27-1
3rd row대전 서구 갈마1동 427-20
4th row대전 서구 갈마중로30번길 15-1
5th row대전 서구 계룡로326번길 50
ValueCountFrequency (%)
대전 122
25.9%
서구 122
25.9%
관저동 9
 
1.9%
도산로 8
 
1.7%
복수동 6
 
1.3%
변동 4
 
0.8%
대덕대로 4
 
0.8%
도마동 4
 
0.8%
대전서구 3
 
0.6%
탄방동 3
 
0.6%
Other values (165) 186
39.5%
2023-12-23T07:44:04.914810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
348
19.8%
대 147
 
8.4%
서 128
 
7.3%
구 125
 
7.1%
전 125
 
7.1%
1 92
 
5.2%
로 72
 
4.1%
동 60
 
3.4%
5 47
 
2.7%
2 42
 
2.4%
Other values (60) 570
32.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 972
55.4%
Decimal Number 410
23.3%
Space Separator 348
 
19.8%
Dash Punctuation 25
 
1.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 147
15.1%
서 128
13.2%
구 125
12.9%
전 125
12.9%
로 72
 
7.4%
동 60
 
6.2%
길 36
 
3.7%
번 33
 
3.4%
도 19
 
2.0%
관 16
 
1.6%
Other values (47) 211
21.7%
Decimal Number
ValueCountFrequency (%)
1 92
22.4%
5 47
11.5%
2 42
10.2%
0 38
9.3%
6 37
9.0%
3 34
 
8.3%
8 32
 
7.8%
9 31
 
7.6%
4 30
 
7.3%
7 27
 
6.6%
Space Separator
ValueCountFrequency (%)
348
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 972
55.4%
Common 784
44.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 147
15.1%
서 128
13.2%
구 125
12.9%
전 125
12.9%
로 72
 
7.4%
동 60
 
6.2%
길 36
 
3.7%
번 33
 
3.4%
도 19
 
2.0%
관 16
 
1.6%
Other values (47) 211
21.7%
Common
ValueCountFrequency (%)
348
44.4%
1 92
 
11.7%
5 47
 
6.0%
2 42
 
5.4%
0 38
 
4.8%
6 37
 
4.7%
3 34
 
4.3%
8 32
 
4.1%
9 31
 
4.0%
4 30
 
3.8%
Other values (3) 53
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 972
55.4%
ASCII 784
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
348
44.4%
1 92
 
11.7%
5 47
 
6.0%
2 42
 
5.4%
0 38
 
4.8%
6 37
 
4.7%
3 34
 
4.3%
8 32
 
4.1%
9 31
 
4.0%
4 30
 
3.8%
Other values (3) 53
 
6.8%
Hangul
ValueCountFrequency (%)
대 147
15.1%
서 128
13.2%
구 125
12.9%
전 125
12.9%
로 72
 
7.4%
동 60
 
6.2%
길 36
 
3.7%
번 33
 
3.4%
도 19
 
2.0%
관 16
 
1.6%
Other values (47) 211
21.7%

행정동명
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
관저2동
11 
변동
11 
탄방동
10 
월평1동
9 
둔산2동
8 
Other values (19)
76 

Length

Max length4
Median length4
Mean length3.456
Min length2

Unique

Unique2 ?
Unique (%)1.6%

Sample

1st row둔산2동
2nd row가장동
3rd row갈마1동
4th row갈마2동
5th row갈마1동

Common Values

ValueCountFrequency (%)
관저2동 11
 
8.8%
변동 11
 
8.8%
탄방동 10
 
8.0%
월평1동 9
 
7.2%
둔산2동 8
 
6.4%
도마2동 8
 
6.4%
갈마2동 7
 
5.6%
용문동 6
 
4.8%
괴정동 6
 
4.8%
도마1동 6
 
4.8%
Other values (14) 43
34.4%

Length

2023-12-23T07:44:06.360373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
관저2동 11
 
8.8%
변동 11
 
8.8%
탄방동 10
 
8.0%
월평1동 9
 
7.2%
둔산2동 8
 
6.4%
도마2동 8
 
6.4%
갈마2동 7
 
5.6%
용문동 6
 
4.8%
괴정동 6
 
4.8%
도마1동 6
 
4.8%
Other values (14) 43
34.4%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct124
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.329564
Minimum36.254192
Maximum36.36871
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-23T07:44:08.102738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.254192
5-th percentile36.297305
Q136.308296
median36.333289
Q336.347782
95-th percentile36.360982
Maximum36.36871
Range0.11451787
Interquartile range (IQR)0.03948656

Descriptive statistics

Standard deviation0.023140784
Coefficient of variation (CV)0.0006369684
Kurtosis-0.49523387
Mean36.329564
Median Absolute Deviation (MAD)0.01770175
Skewness-0.43499327
Sum4541.1955
Variance0.0005354959
MonotonicityNot monotonic
2023-12-23T07:44:09.983229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.28433818 2
 
1.6%
36.34746444 1
 
0.8%
36.30365591 1
 
0.8%
36.29916569 1
 
0.8%
36.30001975 1
 
0.8%
36.34236216 1
 
0.8%
36.32248607 1
 
0.8%
36.3282156 1
 
0.8%
36.32530253 1
 
0.8%
36.32937069 1
 
0.8%
Other values (114) 114
91.2%
ValueCountFrequency (%)
36.25419197 1
0.8%
36.28418072 1
0.8%
36.28433818 2
1.6%
36.29125671 1
0.8%
36.29638453 1
0.8%
36.2972263 1
0.8%
36.29762146 1
0.8%
36.29771076 1
0.8%
36.29786853 1
0.8%
36.29875806 1
0.8%
ValueCountFrequency (%)
36.36870984 1
0.8%
36.36661532 1
0.8%
36.36635803 1
0.8%
36.3658579 1
0.8%
36.36348732 1
0.8%
36.36278226 1
0.8%
36.3611387 1
0.8%
36.36035379 1
0.8%
36.35957625 1
0.8%
36.35947069 1
0.8%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct124
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.37072
Minimum127.32253
Maximum127.40034
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-23T07:44:11.262028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.32253
5-th percentile127.33739
Q1127.36345
median127.37597
Q3127.38097
95-th percentile127.39204
Maximum127.40034
Range0.0778044
Interquartile range (IQR)0.0175109

Descriptive statistics

Standard deviation0.016930432
Coefficient of variation (CV)0.00013292248
Kurtosis0.06305748
Mean127.37072
Median Absolute Deviation (MAD)0.0076198
Skewness-0.86160837
Sum15921.34
Variance0.00028663953
MonotonicityNot monotonic
2023-12-23T07:44:12.337347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.3509851 2
 
1.6%
127.3786491 1
 
0.8%
127.3483647 1
 
0.8%
127.3397731 1
 
0.8%
127.3410241 1
 
0.8%
127.3924699 1
 
0.8%
127.3777444 1
 
0.8%
127.3824995 1
 
0.8%
127.3803617 1
 
0.8%
127.3758297 1
 
0.8%
Other values (114) 114
91.2%
ValueCountFrequency (%)
127.3225335 1
0.8%
127.3323695 1
0.8%
127.334156 1
0.8%
127.3354162 1
0.8%
127.3358103 1
0.8%
127.3365673 1
0.8%
127.3373469 1
0.8%
127.3375854 1
0.8%
127.3378339 1
0.8%
127.3394666 1
0.8%
ValueCountFrequency (%)
127.4003379 1
0.8%
127.3998786 1
0.8%
127.3998091 1
0.8%
127.3982013 1
0.8%
127.3955421 1
0.8%
127.39469 1
0.8%
127.3924699 1
0.8%
127.3903052 1
0.8%
127.3893075 1
0.8%
127.3891979 1
0.8%

Interactions

2023-12-23T07:43:57.432998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:43:54.102398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:43:55.835804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:43:57.911948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:43:54.614373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:43:56.263479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:43:58.405234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:43:55.301666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:43:56.700974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-23T07:44:12.867789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동명위도경도
연번1.0000.6190.3190.411
행정동명0.6191.0000.9540.894
위도0.3190.9541.0000.652
경도0.4110.8940.6521.000
2023-12-23T07:44:13.338545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도행정동명
연번1.0000.086-0.0580.259
위도0.0861.0000.3610.723
경도-0.0580.3611.0000.564
행정동명0.2590.7230.5641.000

Missing values

2023-12-23T07:43:58.840312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T07:43:59.268709image/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

연번장애인주차장위치행정동명위도경도
01대전 서구 대덕대로 176번길둔산2동36.347464127.378649
12대전 서구 가장동 27-1가장동36.329844127.388958
23대전 서구 갈마1동 427-20갈마1동36.340856127.366236
34대전 서구 갈마중로30번길 15-1갈마2동36.346272127.372832
45대전 서구 계룡로326번길 50갈마1동36.350082127.36566
56대전 서구 관저동 1510관저2동36.299389127.337834
67대전 서구 관저동 981관저1동36.308296127.336567
78대전 서구 관저동로105번길 20관저2동36.30167127.339552
89대전 서구 괴곡동 782-1기성동36.284338127.350985
910대전 서구 괴정동 80-42괴정동36.337256127.384389
연번장애인주차장위치행정동명위도경도
115116대전 서구 변동로 37변동36.326117127.377504
116117대전 서구 관저중로64번길 84관저2동36.297226127.339467
117118대전 서구 도솔로 96도마2동36.319122127.373751
118119대전 서구 유등로669번길 17탄방동36.347782127.400338
119120대전 서구 대덕대로335번길월평2동36.362782127.377993
120121대전 서구 벌곡로1379번길가수원동36.303832127.352672
121122대전 서구 월평동 1508월평2동36.363487127.376661
122123대전 서구 만년남로3번길만년동36.365858127.373266
123124대전 서구 관저중로 98관저2동36.300908127.335416
124125대전 서구 관저동 1904관저1동36.307096127.341254