Overview

Dataset statistics

Number of variables5
Number of observations256
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.6 KiB
Average record size in memory42.5 B

Variable types

Categorical1
Text2
Numeric2

Dataset

Description자치구,안심 명,안심 주소,WGS Y 좌표,WGS X 좌표
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-20922/S/1/datasetView.do

Alerts

WGS Y 좌표 is highly overall correlated with 자치구High correlation
WGS X 좌표 is highly overall correlated with 자치구High correlation
자치구 is highly overall correlated with WGS Y 좌표 and 1 other fieldsHigh correlation
안심 명 has unique valuesUnique
안심 주소 has unique valuesUnique
WGS Y 좌표 has unique valuesUnique
WGS X 좌표 has unique valuesUnique

Reproduction

Analysis started2024-03-13 07:18:01.303626
Analysis finished2024-03-13 07:18:02.028498
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
마포구
 
15
관악구
 
15
동작구
 
14
강서구
 
14
광진구
 
14
Other values (21)
184 

Length

Max length4
Median length3
Mean length3.1367188
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
마포구 15
 
5.9%
관악구 15
 
5.9%
동작구 14
 
5.5%
강서구 14
 
5.5%
광진구 14
 
5.5%
서대문구 13
 
5.1%
영등포구 12
 
4.7%
양천구 11
 
4.3%
송파구 11
 
4.3%
동대문구 11
 
4.3%
Other values (16) 126
49.2%

Length

2024-03-13T16:18:02.102070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
마포구 15
 
5.9%
관악구 15
 
5.9%
동작구 14
 
5.5%
강서구 14
 
5.5%
광진구 14
 
5.5%
서대문구 13
 
5.1%
영등포구 12
 
4.7%
양천구 11
 
4.3%
송파구 11
 
4.3%
동대문구 11
 
4.3%
Other values (16) 126
49.2%

안심 명
Text

UNIQUE 

Distinct256
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-03-13T16:18:02.341397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length8.6210938
Min length4

Characters and Unicode

Total characters2207
Distinct characters257
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique256 ?
Unique (%)100.0%

Sample

1st row충무창업큐브
2nd row강동구 평생학습관
3rd row미성체육관
4th row고대앞마을 주민사랑방
5th row천호청소년문화의집
ValueCountFrequency (%)
주민센터 35
 
9.5%
신한은행 10
 
2.7%
공영주차장 9
 
2.4%
지점 5
 
1.4%
현대오일뱅크 3
 
0.8%
화곡 3
 
0.8%
영등포 2
 
0.5%
평생학습관 2
 
0.5%
상암동 2
 
0.5%
치안센터 2
 
0.5%
Other values (295) 295
80.2%
2024-03-13T16:18:02.674206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 138
 
6.3%
센 122
 
5.5%
터 122
 
5.5%
주 120
 
5.4%
117
 
5.3%
민 98
 
4.4%
관 48
 
2.2%
1 43
 
1.9%
공 38
 
1.7%
장 36
 
1.6%
Other values (247) 1325
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1976
89.5%
Space Separator 117
 
5.3%
Decimal Number 98
 
4.4%
Open Punctuation 5
 
0.2%
Close Punctuation 5
 
0.2%
Dash Punctuation 3
 
0.1%
Uppercase Letter 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 138
 
7.0%
센 122
 
6.2%
터 122
 
6.2%
주 120
 
6.1%
민 98
 
5.0%
관 48
 
2.4%
공 38
 
1.9%
장 36
 
1.8%
구 35
 
1.8%
회 33
 
1.7%
Other values (230) 1186
60.0%
Decimal Number
ValueCountFrequency (%)
1 43
43.9%
2 28
28.6%
3 9
 
9.2%
4 9
 
9.2%
6 2
 
2.0%
5 2
 
2.0%
0 2
 
2.0%
8 1
 
1.0%
9 1
 
1.0%
7 1
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
117
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1976
89.5%
Common 229
 
10.4%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 138
 
7.0%
센 122
 
6.2%
터 122
 
6.2%
주 120
 
6.1%
민 98
 
5.0%
관 48
 
2.4%
공 38
 
1.9%
장 36
 
1.8%
구 35
 
1.8%
회 33
 
1.7%
Other values (230) 1186
60.0%
Common
ValueCountFrequency (%)
117
51.1%
1 43
 
18.8%
2 28
 
12.2%
3 9
 
3.9%
4 9
 
3.9%
( 5
 
2.2%
) 5
 
2.2%
- 3
 
1.3%
6 2
 
0.9%
5 2
 
0.9%
Other values (5) 6
 
2.6%
Latin
ValueCountFrequency (%)
N 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1976
89.5%
ASCII 231
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 138
 
7.0%
센 122
 
6.2%
터 122
 
6.2%
주 120
 
6.1%
민 98
 
5.0%
관 48
 
2.4%
공 38
 
1.9%
장 36
 
1.8%
구 35
 
1.8%
회 33
 
1.7%
Other values (230) 1186
60.0%
ASCII
ValueCountFrequency (%)
117
50.6%
1 43
 
18.6%
2 28
 
12.1%
3 9
 
3.9%
4 9
 
3.9%
( 5
 
2.2%
) 5
 
2.2%
- 3
 
1.3%
6 2
 
0.9%
5 2
 
0.9%
Other values (7) 8
 
3.5%

안심 주소
Text

UNIQUE 

Distinct256
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-03-13T16:18:02.913499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length8.9921875
Min length5

Characters and Unicode

Total characters2302
Distinct characters200
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique256 ?
Unique (%)100.0%

Sample

1st row광희동 퇴계로 265
2nd row구천면로 395
3rd row난우16길 37
4th row안암로20길 13
5th row천중로 61
ValueCountFrequency (%)
10 10
 
1.9%
5 7
 
1.3%
11 6
 
1.1%
13 6
 
1.1%
22 6
 
1.1%
36 5
 
0.9%
26 5
 
0.9%
동일로 5
 
0.9%
6 4
 
0.7%
48 4
 
0.7%
Other values (394) 476
89.1%
2024-03-13T16:18:03.288433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
280
 
12.2%
로 237
 
10.3%
1 167
 
7.3%
길 158
 
6.9%
2 131
 
5.7%
5 91
 
4.0%
3 90
 
3.9%
4 84
 
3.6%
6 72
 
3.1%
7 63
 
2.7%
Other values (190) 929
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1123
48.8%
Decimal Number 861
37.4%
Space Separator 280
 
12.2%
Dash Punctuation 22
 
1.0%
Close Punctuation 8
 
0.3%
Open Punctuation 8
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 237
21.1%
길 158
 
14.1%
동 38
 
3.4%
대 26
 
2.3%
도 18
 
1.6%
남 17
 
1.5%
산 17
 
1.5%
봉 17
 
1.5%
천 16
 
1.4%
가 15
 
1.3%
Other values (176) 564
50.2%
Decimal Number
ValueCountFrequency (%)
1 167
19.4%
2 131
15.2%
5 91
10.6%
3 90
10.5%
4 84
9.8%
6 72
8.4%
7 63
 
7.3%
8 58
 
6.7%
9 55
 
6.4%
0 50
 
5.8%
Space Separator
ValueCountFrequency (%)
280
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1179
51.2%
Hangul 1123
48.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 237
21.1%
길 158
 
14.1%
동 38
 
3.4%
대 26
 
2.3%
도 18
 
1.6%
남 17
 
1.5%
산 17
 
1.5%
봉 17
 
1.5%
천 16
 
1.4%
가 15
 
1.3%
Other values (176) 564
50.2%
Common
ValueCountFrequency (%)
280
23.7%
1 167
14.2%
2 131
11.1%
5 91
 
7.7%
3 90
 
7.6%
4 84
 
7.1%
6 72
 
6.1%
7 63
 
5.3%
8 58
 
4.9%
9 55
 
4.7%
Other values (4) 88
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1179
51.2%
Hangul 1123
48.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
280
23.7%
1 167
14.2%
2 131
11.1%
5 91
 
7.7%
3 90
 
7.6%
4 84
 
7.1%
6 72
 
6.1%
7 63
 
5.3%
8 58
 
4.9%
9 55
 
4.7%
Other values (4) 88
 
7.5%
Hangul
ValueCountFrequency (%)
로 237
21.1%
길 158
 
14.1%
동 38
 
3.4%
대 26
 
2.3%
도 18
 
1.6%
남 17
 
1.5%
산 17
 
1.5%
봉 17
 
1.5%
천 16
 
1.4%
가 15
 
1.3%
Other values (176) 564
50.2%

WGS Y 좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct256
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.546948
Minimum37.440259
Maximum37.678691
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-03-13T16:18:03.404116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.440259
5-th percentile37.471787
Q137.502652
median37.545808
Q337.578749
95-th percentile37.63935
Maximum37.678691
Range0.23843176
Interquartile range (IQR)0.076096845

Descriptive statistics

Standard deviation0.052027371
Coefficient of variation (CV)0.0013856618
Kurtosis-0.4287282
Mean37.546948
Median Absolute Deviation (MAD)0.039035655
Skewness0.36540324
Sum9612.0187
Variance0.0027068473
MonotonicityNot monotonic
2024-03-13T16:18:03.522523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.56297 1
 
0.4%
37.47701714 1
 
0.4%
37.67291122 1
 
0.4%
37.630164 1
 
0.4%
37.67842 1
 
0.4%
37.62477802 1
 
0.4%
37.65748324 1
 
0.4%
37.66136038 1
 
0.4%
37.62281514 1
 
0.4%
37.45023 1
 
0.4%
Other values (246) 246
96.1%
ValueCountFrequency (%)
37.44025906 1
0.4%
37.443195 1
0.4%
37.45023 1
0.4%
37.45706564 1
0.4%
37.45897882 1
0.4%
37.463147 1
0.4%
37.46792 1
0.4%
37.4685737 1
0.4%
37.46951288 1
0.4%
37.470189 1
0.4%
ValueCountFrequency (%)
37.67869082 1
0.4%
37.67842 1
0.4%
37.67291122 1
0.4%
37.66967564 1
0.4%
37.66931252 1
0.4%
37.66136038 1
0.4%
37.65748324 1
0.4%
37.65416726 1
0.4%
37.65321749 1
0.4%
37.65301303 1
0.4%

WGS X 좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct256
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98363
Minimum126.81007
Maximum127.14853
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-03-13T16:18:03.636852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.81007
5-th percentile126.84003
Q1126.91584
median126.98557
Q3127.05074
95-th percentile127.12599
Maximum127.14853
Range0.3384599
Interquartile range (IQR)0.13490677

Descriptive statistics

Standard deviation0.085498474
Coefficient of variation (CV)0.00067330311
Kurtosis-0.98886653
Mean126.98363
Median Absolute Deviation (MAD)0.0688096
Skewness-0.01360394
Sum32507.81
Variance0.0073099891
MonotonicityNot monotonic
2024-03-13T16:18:03.773488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0012 1
 
0.4%
126.9798517 1
 
0.4%
127.0832362 1
 
0.4%
127.069856 1
 
0.4%
127.05189 1
 
0.4%
127.0737505 1
 
0.4%
127.0678641 1
 
0.4%
127.0740077 1
 
0.4%
127.0614537 1
 
0.4%
126.91286 1
 
0.4%
Other values (246) 246
96.1%
ValueCountFrequency (%)
126.8100744 1
0.4%
126.813542 1
0.4%
126.8178402846528 1
0.4%
126.8190678 1
0.4%
126.8271743 1
0.4%
126.8290822 1
0.4%
126.832253 1
0.4%
126.8331774 1
0.4%
126.8345672 1
0.4%
126.8347274 1
0.4%
ValueCountFrequency (%)
127.1485343 1
0.4%
127.1468273 1
0.4%
127.1433044 1
0.4%
127.14269 1
0.4%
127.14268 1
0.4%
127.1412225 1
0.4%
127.133714 1
0.4%
127.1333655 1
0.4%
127.1324383 1
0.4%
127.132364 1
0.4%

Interactions

2024-03-13T16:18:01.721622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T16:18:01.563750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T16:18:01.801464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T16:18:01.638877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T16:18:03.878855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자치구WGS Y 좌표WGS X 좌표
자치구1.0000.9330.934
WGS Y 좌표0.9331.0000.621
WGS X 좌표0.9340.6211.000
2024-03-13T16:18:03.973734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WGS Y 좌표WGS X 좌표자치구
WGS Y 좌표1.0000.2440.657
WGS X 좌표0.2441.0000.659
자치구0.6570.6591.000

Missing values

2024-03-13T16:18:01.915718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T16:18:01.996740image/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

자치구안심 명안심 주소WGS Y 좌표WGS X 좌표
0<NA>충무창업큐브광희동 퇴계로 26537.56297127.0012
1<NA>강동구 평생학습관구천면로 39537.55099127.14269
2<NA>미성체육관난우16길 3737.47781126.91912
3<NA>고대앞마을 주민사랑방안암로20길 1337.58748127.03495
4<NA>천호청소년문화의집천중로 6137.54515127.12879
5<NA>구립안말경로당풍성로45길 1137.53122127.129853
6중랑구상봉2동 주민센터동일로 114길 1037.59311127.0809
7중랑구면목5동 주민센터동일로 61937.585753127.079474
8중랑구중화1치안센터동일로 79237.60117127.07981
9중랑구면목4동주민센터면목로 24637.574701127.085609
자치구안심 명안심 주소WGS Y 좌표WGS X 좌표
246강동구강동구립해공도서관올림픽로 70237.544033127.12556
247강남구도곡2동주민센터남부순환로378길 34-937.483723127.046407
248강남구역삼청소년수련관논현로64길 737.493975127.040911
249강남구도곡1동 주민센터도곡로18길 5737.48831127.03888
250강남구대치4동 주민센터도곡로77길 2337.49973127.05785
251강남구현대오일뱅크 신사현대점서울특별시 강남구 도산대로 16337.51934127.02633
252강남구일원1동주민센터양재대로55길 1437.491855127.088026
253강남구역삼1동 주민센터역삼로7길 1637.495356127.033375
254강남구대치2동 주민센터영동대로65길 2437.502304127.064188
255강남구논현1동주민센터학동로20길 2537.511504127.028535