Overview

Dataset statistics

Number of variables6
Number of observations549
Missing cells0
Missing cells (%)0.0%
Duplicate rows2
Duplicate rows (%)0.4%
Total size in memory26.9 KiB
Average record size in memory50.2 B

Variable types

Categorical1
Text2
Numeric2
DateTime1

Dataset

Description서울특별시 금천구의 의류수거함에 관한 정보로 행정동, 도로명주소, 지번주소, 위도, 경도, 데이터기준일자 등을 제공합니다.
Author서울특별시 금천구
URLhttps://www.data.go.kr/data/15106679/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 2 (0.4%) duplicate rowsDuplicates

Reproduction

Analysis started2024-03-15 01:17:18.090502
Analysis finished2024-03-15 01:17:19.975760
Duration1.89 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동
Categorical

Distinct10
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
독산3동
100 
시흥4동
73 
시흥3동
72 
시흥1동
67 
독산2동
55 
Other values (5)
182 

Length

Max length4
Median length4
Mean length3.9380692
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
독산3동 100
18.2%
시흥4동 73
13.3%
시흥3동 72
13.1%
시흥1동 67
12.2%
독산2동 55
10.0%
시흥5동 49
8.9%
독산4동 47
8.6%
독산1동 46
8.4%
가산동 34
 
6.2%
시흥2동 6
 
1.1%

Length

2024-03-15T10:17:20.192974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:17:20.575169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
독산3동 100
18.2%
시흥4동 73
13.3%
시흥3동 72
13.1%
시흥1동 67
12.2%
독산2동 55
10.0%
시흥5동 49
8.9%
독산4동 47
8.6%
독산1동 46
8.4%
가산동 34
 
6.2%
시흥2동 6
 
1.1%

도로명주소
Text

Distinct547
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-03-15T10:17:21.451677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length18.735883
Min length14

Characters and Unicode

Total characters10286
Distinct characters57
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique545 ?
Unique (%)99.3%

Sample

1st row서울특별시 금천구 벚꽃로56길8(1)
2nd row서울특별시 금천구 벚꽃로56길8(2)
3rd row서울특별시 금천구 벚꽃로340-3
4th row서울특별시 금천구 벚꽃로56길32
5th row서울특별시 금천구 벚꽃로328
ValueCountFrequency (%)
서울특별시 549
32.8%
금천구 549
32.8%
범안로 7
 
0.4%
벚꽃로길 6
 
0.4%
15길 3
 
0.2%
17길 2
 
0.1%
두산로 2
 
0.1%
벚꽃로 2
 
0.1%
가산로5 2
 
0.1%
18길 2
 
0.1%
Other values (549) 551
32.9%
2024-03-15T10:17:22.746285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1127
 
11.0%
시 732
 
7.1%
금 575
 
5.6%
천 550
 
5.3%
서 549
 
5.3%
특 549
 
5.3%
별 549
 
5.3%
구 549
 
5.3%
울 549
 
5.3%
로 548
 
5.3%
Other values (47) 4009
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6819
66.3%
Decimal Number 2200
 
21.4%
Space Separator 1127
 
11.0%
Dash Punctuation 89
 
0.9%
Close Punctuation 24
 
0.2%
Open Punctuation 24
 
0.2%
Connector Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 732
10.7%
금 575
8.4%
천 550
8.1%
서 549
8.1%
특 549
8.1%
별 549
8.1%
구 549
8.1%
울 549
8.1%
로 548
8.0%
길 461
 
6.8%
Other values (32) 1208
17.7%
Decimal Number
ValueCountFrequency (%)
1 433
19.7%
2 343
15.6%
3 231
10.5%
4 230
10.5%
5 220
10.0%
0 171
 
7.8%
6 155
 
7.0%
8 153
 
7.0%
7 145
 
6.6%
9 119
 
5.4%
Space Separator
ValueCountFrequency (%)
1127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6819
66.3%
Common 3467
33.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 732
10.7%
금 575
8.4%
천 550
8.1%
서 549
8.1%
특 549
8.1%
별 549
8.1%
구 549
8.1%
울 549
8.1%
로 548
8.0%
길 461
 
6.8%
Other values (32) 1208
17.7%
Common
ValueCountFrequency (%)
1127
32.5%
1 433
 
12.5%
2 343
 
9.9%
3 231
 
6.7%
4 230
 
6.6%
5 220
 
6.3%
0 171
 
4.9%
6 155
 
4.5%
8 153
 
4.4%
7 145
 
4.2%
Other values (5) 259
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6819
66.3%
ASCII 3467
33.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1127
32.5%
1 433
 
12.5%
2 343
 
9.9%
3 231
 
6.7%
4 230
 
6.6%
5 220
 
6.3%
0 171
 
4.9%
6 155
 
4.5%
8 153
 
4.4%
7 145
 
4.2%
Other values (5) 259
 
7.5%
Hangul
ValueCountFrequency (%)
시 732
10.7%
금 575
8.4%
천 550
8.1%
서 549
8.1%
특 549
8.1%
별 549
8.1%
구 549
8.1%
울 549
8.1%
로 548
8.0%
길 461
 
6.8%
Other values (32) 1208
17.7%

지번주소
Text

Distinct544
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-03-15T10:17:23.978381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length32
Mean length22.491803
Min length16

Characters and Unicode

Total characters12348
Distinct characters255
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique540 ?
Unique (%)98.4%

Sample

1st row서울특별시 금천구 가산동 4-22
2nd row서울특별시 금천구 가산동 4-22
3rd row서울특별시 금천구 가산동 5-35
4th row서울특별시 금천구 가산동 32-25
5th row서울특별시 금천구 가산동 32-60
ValueCountFrequency (%)
서울특별시 549
22.3%
금천구 549
22.3%
시흥동 266
 
10.8%
독산동 247
 
10.1%
가산동 33
 
1.3%
두산위브아파트 3
 
0.1%
공영주차장 3
 
0.1%
769 3
 
0.1%
우성아파트 2
 
0.1%
한솔그린빌 2
 
0.1%
Other values (781) 800
32.6%
2024-03-15T10:17:25.724679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1908
 
15.5%
시 832
 
6.7%
금 562
 
4.6%
동 561
 
4.5%
천 559
 
4.5%
서 554
 
4.5%
울 552
 
4.5%
구 551
 
4.5%
특 549
 
4.4%
별 549
 
4.4%
Other values (245) 5171
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7325
59.3%
Decimal Number 2541
 
20.6%
Space Separator 1908
 
15.5%
Dash Punctuation 494
 
4.0%
Open Punctuation 29
 
0.2%
Close Punctuation 29
 
0.2%
Uppercase Letter 18
 
0.1%
Letter Number 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 832
11.4%
금 562
 
7.7%
동 561
 
7.7%
천 559
 
7.6%
서 554
 
7.6%
울 552
 
7.5%
구 551
 
7.5%
특 549
 
7.5%
별 549
 
7.5%
산 302
 
4.1%
Other values (217) 1754
23.9%
Decimal Number
ValueCountFrequency (%)
1 430
16.9%
9 344
13.5%
2 279
11.0%
8 251
9.9%
3 245
9.6%
0 224
8.8%
7 223
8.8%
4 221
8.7%
5 165
 
6.5%
6 159
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
I 4
22.2%
C 3
16.7%
E 2
11.1%
A 2
11.1%
G 2
11.1%
D 1
 
5.6%
S 1
 
5.6%
V 1
 
5.6%
H 1
 
5.6%
L 1
 
5.6%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
33.3%
Ⅴ 1
33.3%
Ⅱ 1
33.3%
Space Separator
ValueCountFrequency (%)
1908
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 494
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7325
59.3%
Common 5002
40.5%
Latin 21
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 832
11.4%
금 562
 
7.7%
동 561
 
7.7%
천 559
 
7.6%
서 554
 
7.6%
울 552
 
7.5%
구 551
 
7.5%
특 549
 
7.5%
별 549
 
7.5%
산 302
 
4.1%
Other values (217) 1754
23.9%
Common
ValueCountFrequency (%)
1908
38.1%
- 494
 
9.9%
1 430
 
8.6%
9 344
 
6.9%
2 279
 
5.6%
8 251
 
5.0%
3 245
 
4.9%
0 224
 
4.5%
7 223
 
4.5%
4 221
 
4.4%
Other values (5) 383
 
7.7%
Latin
ValueCountFrequency (%)
I 4
19.0%
C 3
14.3%
E 2
9.5%
A 2
9.5%
G 2
9.5%
Ⅲ 1
 
4.8%
D 1
 
4.8%
S 1
 
4.8%
Ⅴ 1
 
4.8%
V 1
 
4.8%
Other values (3) 3
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7325
59.3%
ASCII 5020
40.7%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1908
38.0%
- 494
 
9.8%
1 430
 
8.6%
9 344
 
6.9%
2 279
 
5.6%
8 251
 
5.0%
3 245
 
4.9%
0 224
 
4.5%
7 223
 
4.4%
4 221
 
4.4%
Other values (15) 401
 
8.0%
Hangul
ValueCountFrequency (%)
시 832
11.4%
금 562
 
7.7%
동 561
 
7.7%
천 559
 
7.6%
서 554
 
7.6%
울 552
 
7.5%
구 551
 
7.5%
특 549
 
7.5%
별 549
 
7.5%
산 302
 
4.1%
Other values (217) 1754
23.9%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
33.3%
Ⅴ 1
33.3%
Ⅱ 1
33.3%

위도
Real number (ℝ)

Distinct527
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.407502
Minimum32.52202
Maximum37.485182
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-03-15T10:17:26.146851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.52202
5-th percentile37.439415
Q137.452401
median37.462058
Q337.471593
95-th percentile37.478258
Maximum37.485182
Range4.9631616
Interquartile range (IQR)0.0191918

Descriptive statistics

Standard deviation0.51416298
Coefficient of variation (CV)0.013744916
Kurtosis87.213887
Mean37.407502
Median Absolute Deviation (MAD)0.0096393
Skewness-9.4257181
Sum20536.718
Variance0.26436357
MonotonicityNot monotonic
2024-03-15T10:17:26.604777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32.5220203 6
 
1.1%
37.4744482 3
 
0.5%
37.459698 3
 
0.5%
37.4851819 2
 
0.4%
37.470788 2
 
0.4%
37.4347332 2
 
0.4%
37.4395025 2
 
0.4%
37.4400945 2
 
0.4%
37.4400743 2
 
0.4%
37.436579 2
 
0.4%
Other values (517) 523
95.3%
ValueCountFrequency (%)
32.5220203 6
1.1%
37.4340072 1
 
0.2%
37.4341457 1
 
0.2%
37.434221 1
 
0.2%
37.4342989 1
 
0.2%
37.4344145 1
 
0.2%
37.4344636 1
 
0.2%
37.4345653 1
 
0.2%
37.4346291 1
 
0.2%
37.4347332 2
 
0.4%
ValueCountFrequency (%)
37.4851819 2
0.4%
37.4846973 1
0.2%
37.4844526 1
0.2%
37.4837832 1
0.2%
37.482682 1
0.2%
37.4802225 1
0.2%
37.4801802 1
0.2%
37.4794953 2
0.4%
37.4794604 1
0.2%
37.4793032 1
0.2%

경도
Real number (ℝ)

Distinct527
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.86892
Minimum123.74177
Maximum126.91708
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-03-15T10:17:27.021922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum123.74177
5-th percentile126.89174
Q1126.90039
median126.9046
Q3126.90682
95-th percentile126.91116
Maximum126.91708
Range3.1753019
Interquartile range (IQR)0.0064252

Descriptive statistics

Standard deviation0.32906725
Coefficient of variation (CV)0.0025937578
Kurtosis87.261299
Mean126.86892
Median Absolute Deviation (MAD)0.0029586
Skewness-9.4295168
Sum69651.038
Variance0.10828525
MonotonicityNot monotonic
2024-03-15T10:17:27.476040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
123.7417741 6
 
1.1%
126.8926779 3
 
0.5%
126.9071828 3
 
0.5%
126.8814385 2
 
0.4%
126.902115 2
 
0.4%
126.9065629 2
 
0.4%
126.9039396 2
 
0.4%
126.9046203 2
 
0.4%
126.9053551 2
 
0.4%
126.9025246 2
 
0.4%
Other values (517) 523
95.3%
ValueCountFrequency (%)
123.7417741 6
1.1%
126.8814385 2
 
0.4%
126.8816492 1
 
0.2%
126.8821717 1
 
0.2%
126.8824444 1
 
0.2%
126.8848226 1
 
0.2%
126.8874019 1
 
0.2%
126.8876632 1
 
0.2%
126.8895078 1
 
0.2%
126.8902542 1
 
0.2%
ValueCountFrequency (%)
126.917076 1
0.2%
126.9164369 1
0.2%
126.9159946 1
0.2%
126.9153933 1
0.2%
126.9146543 1
0.2%
126.9145808 1
0.2%
126.9140777 1
0.2%
126.9131492 1
0.2%
126.9131175 1
0.2%
126.9127856 1
0.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
Minimum2024-01-04 00:00:00
Maximum2024-01-04 00:00:00
2024-03-15T10:17:27.795158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:17:27.961364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T10:17:19.077904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:17:18.575119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:17:19.336091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:17:18.815929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:17:28.092839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동위도경도
행정동1.0000.5090.509
위도0.5091.0000.991
경도0.5090.9911.000
2024-03-15T10:17:28.249249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도행정동
위도1.000-0.2970.389
경도-0.2971.0000.389
행정동0.3890.3891.000

Missing values

2024-03-15T10:17:19.595655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:17:19.810021image/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

행정동도로명주소지번주소위도경도데이터기준일자
0가산동서울특별시 금천구 벚꽃로56길8(1)서울특별시 금천구 가산동 4-2237.485182126.8814392024-01-04
1가산동서울특별시 금천구 벚꽃로56길8(2)서울특별시 금천구 가산동 4-2237.485182126.8814392024-01-04
2가산동서울특별시 금천구 벚꽃로340-3서울특별시 금천구 가산동 5-3537.484697126.8816492024-01-04
3가산동서울특별시 금천구 벚꽃로56길32서울특별시 금천구 가산동 32-2537.484453126.8824442024-01-04
4가산동서울특별시 금천구 벚꽃로328서울특별시 금천구 가산동 32-6037.483783126.8821722024-01-04
5가산동서울특별시 금천구 벚꽃로38길 39서울특별시 금천구 가산동 83-1137.482682126.8848232024-01-04
6가산동서울특별시 금천구 가산로9길9서울특별시 금천구 가산동 144-437.476816126.8914562024-01-04
7가산동서울특별시 금천구 가산로99(1)서울특별시 금천구 가산동 769 두산위브아파트37.474448126.8926782024-01-04
8가산동서울특별시 금천구 가산로99(2)서울특별시 금천구 가산동 769 두산위브아파트37.474448126.8926782024-01-04
9가산동서울특별시 금천구 가산로91서울특별시 금천구 가산동 153-637.474055126.893952024-01-04
행정동도로명주소지번주소위도경도데이터기준일자
539시흥5동서울특별시 금천구 독산로22길65서울특별시 금천구 시흥동 824-1637.453137126.9099232024-01-04
540시흥5동서울특별시 금천구 탑골로4길18-4서울특별시 금천구 시흥동 244-3137.451493126.9125012024-01-04
541시흥5동서울특별시 금천구 탑골로2길19서울특별시 금천구 시흥동 1012 백운한비치아파트37.451505126.9118342024-01-04
542시흥5동서울특별시 금천구 탑골로2길15-5서울특별시 금천구 시흥동 247-1237.451555126.9113482024-01-04
543시흥5동서울특별시 금천구 탑골로22서울특별시 금천구 시흥동 247-1937.45181126.911662024-01-04
544시흥5동서울특별시 금천구 금하로23가길21서울특별시 금천구 시흥동 827-3537.451767126.9098982024-01-04
545시흥5동서울특별시 금천구 탑골로7길3-3서울특별시 금천구 시흥동 220-3437.452204126.912312024-01-04
546시흥5동서울특별시 금천구 탑골로3길28서울특별시 금천구 시흥동 220-7 백운빌리지37.452423126.9126462024-01-04
547시흥5동서울특별시 금천구 탑골로3길37서울특별시 금천구 시흥동 220-5137.452929126.9127862024-01-04
548시흥5동서울특별시 금천구 탑골로3길50서울특별시 금천구 시흥동 220-2 현대아파트37.453454126.9140782024-01-04

Duplicate rows

Most frequently occurring

행정동도로명주소지번주소위도경도데이터기준일자# duplicates
0시흥3동서울특별시 금천구 시흥대로2길52-3서울특별시 금천구 시흥동 973-1 백운맨션37.434733126.9065632024-01-042
1시흥4동서울특별시 금천구 독산로36길62서울특별시 금천구 시흥동 1016 한빛무궁화아파트37.460136126.9077532024-01-042