Overview

Dataset statistics

Number of variables7
Number of observations709
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.0 KiB
Average record size in memory59.2 B

Variable types

Numeric3
Categorical2
Text2

Dataset

Description서울특별시 양천구에서 관리하는 의류수거함에 관한 데이터로 의류수거함의 위치정보(행정동, 주소 등 상세위치)와 기준일자를 포함합니다.
Author서울특별시 양천구
URLhttps://www.data.go.kr/data/15105196/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-29 23:01:27.835290
Analysis finished2024-04-29 23:01:31.339830
Duration3.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct709
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean355
Minimum1
Maximum709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-04-30T08:01:31.418278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile36.4
Q1178
median355
Q3532
95-th percentile673.6
Maximum709
Range708
Interquartile range (IQR)354

Descriptive statistics

Standard deviation204.81496
Coefficient of variation (CV)0.57694354
Kurtosis-1.2
Mean355
Median Absolute Deviation (MAD)177
Skewness0
Sum251695
Variance41949.167
MonotonicityStrictly increasing
2024-04-30T08:01:31.616923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
445 1
 
0.1%
469 1
 
0.1%
470 1
 
0.1%
471 1
 
0.1%
472 1
 
0.1%
473 1
 
0.1%
474 1
 
0.1%
475 1
 
0.1%
476 1
 
0.1%
Other values (699) 699
98.6%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
709 1
0.1%
708 1
0.1%
707 1
0.1%
706 1
0.1%
705 1
0.1%
704 1
0.1%
703 1
0.1%
702 1
0.1%
701 1
0.1%
700 1
0.1%

행정동
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
신정4동
131 
목2동
103 
신월7동
74 
신월4동
64 
목4동
52 
Other values (11)
285 

Length

Max length4
Median length4
Mean length3.7235543
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row목1동
2nd row목1동
3rd row목1동
4th row목2동
5th row목2동

Common Values

ValueCountFrequency (%)
신정4동 131
18.5%
목2동 103
14.5%
신월7동 74
10.4%
신월4동 64
9.0%
목4동 52
 
7.3%
신월5동 45
 
6.3%
신월2동 43
 
6.1%
목3동 38
 
5.4%
신월1동 37
 
5.2%
신월3동 31
 
4.4%
Other values (6) 91
12.8%

Length

2024-04-30T08:01:31.800940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신정4동 131
18.5%
목2동 103
14.5%
신월7동 74
10.4%
신월4동 64
9.0%
목4동 52
 
7.3%
신월5동 45
 
6.3%
신월2동 43
 
6.1%
목3동 38
 
5.4%
신월1동 37
 
5.2%
신월3동 31
 
4.4%
Other values (6) 91
12.8%

도로명주소
Text

Distinct707
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-04-30T08:01:32.115103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length20.503526
Min length13

Characters and Unicode

Total characters14537
Distinct characters83
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

Unique705 ?
Unique (%)99.4%

Sample

1st row서울특별시 양천구 오목로 56길 10
2nd row서울특별시 양천구 목동동로 206-1
3rd row서울특별시 양천구 오목로56길 14
4th row서울특별시 양천구 목동중앙본로2길 5
5th row서울특별시 양천구 목동중앙로7길 74
ValueCountFrequency (%)
서울특별시 709
25.8%
양천구 708
25.7%
목동중앙본로 44
 
1.6%
오목로 26
 
0.9%
곰달래로 24
 
0.9%
중앙로 21
 
0.8%
목동중앙북로 18
 
0.7%
월정로 16
 
0.6%
지양로7길 14
 
0.5%
12 14
 
0.5%
Other values (634) 1159
42.1%
2024-04-30T08:01:32.526383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2328
16.0%
양 762
 
5.2%
서 730
 
5.0%
로 713
 
4.9%
천 710
 
4.9%
시 709
 
4.9%
특 709
 
4.9%
구 709
 
4.9%
울 709
 
4.9%
별 709
 
4.9%
Other values (73) 5749
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9348
64.3%
Decimal Number 2653
 
18.2%
Space Separator 2328
 
16.0%
Dash Punctuation 208
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 762
 
8.2%
서 730
 
7.8%
로 713
 
7.6%
천 710
 
7.6%
시 709
 
7.6%
특 709
 
7.6%
구 709
 
7.6%
울 709
 
7.6%
별 709
 
7.6%
길 620
 
6.6%
Other values (61) 2268
24.3%
Decimal Number
ValueCountFrequency (%)
1 632
23.8%
2 447
16.8%
3 282
10.6%
5 249
 
9.4%
6 229
 
8.6%
4 203
 
7.7%
7 189
 
7.1%
8 153
 
5.8%
0 147
 
5.5%
9 122
 
4.6%
Space Separator
ValueCountFrequency (%)
2328
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 208
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9348
64.3%
Common 5189
35.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 762
 
8.2%
서 730
 
7.8%
로 713
 
7.6%
천 710
 
7.6%
시 709
 
7.6%
특 709
 
7.6%
구 709
 
7.6%
울 709
 
7.6%
별 709
 
7.6%
길 620
 
6.6%
Other values (61) 2268
24.3%
Common
ValueCountFrequency (%)
2328
44.9%
1 632
 
12.2%
2 447
 
8.6%
3 282
 
5.4%
5 249
 
4.8%
6 229
 
4.4%
- 208
 
4.0%
4 203
 
3.9%
7 189
 
3.6%
8 153
 
2.9%
Other values (2) 269
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9348
64.3%
ASCII 5189
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2328
44.9%
1 632
 
12.2%
2 447
 
8.6%
3 282
 
5.4%
5 249
 
4.8%
6 229
 
4.4%
- 208
 
4.0%
4 203
 
3.9%
7 189
 
3.6%
8 153
 
2.9%
Other values (2) 269
 
5.2%
Hangul
ValueCountFrequency (%)
양 762
 
8.2%
서 730
 
7.8%
로 713
 
7.6%
천 710
 
7.6%
시 709
 
7.6%
특 709
 
7.6%
구 709
 
7.6%
울 709
 
7.6%
별 709
 
7.6%
길 620
 
6.6%
Other values (61) 2268
24.3%

지번주소
Text

Distinct704
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-04-30T08:01:32.888318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length20.284908
Min length15

Characters and Unicode

Total characters14382
Distinct characters41
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

Unique700 ?
Unique (%)98.7%

Sample

1st row서울특별시 양천구 목1동 405-472
2nd row서울특별시 양천구 목1동 405-207
3rd row서울특별시 양천구 목1동 405-393
4th row서울특별시 양천구 목2동 750-6
5th row서울특별시 양천구 목2동 229-11
ValueCountFrequency (%)
서울특별시 709
25.0%
양천구 709
25.0%
신정4동 132
 
4.7%
목2동 103
 
3.6%
신월7동 74
 
2.6%
신월4동 64
 
2.3%
목4동 52
 
1.8%
신월5동 45
 
1.6%
신월2동 43
 
1.5%
목3동 38
 
1.3%
Other values (706) 865
30.5%
2024-04-30T08:01:33.385192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2159
 
15.0%
서 710
 
4.9%
양 709
 
4.9%
동 709
 
4.9%
구 709
 
4.9%
천 709
 
4.9%
울 709
 
4.9%
시 709
 
4.9%
별 709
 
4.9%
특 709
 
4.9%
Other values (31) 5841
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7621
53.0%
Decimal Number 3913
27.2%
Space Separator 2159
 
15.0%
Dash Punctuation 689
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 710
9.3%
양 709
9.3%
동 709
9.3%
구 709
9.3%
천 709
9.3%
울 709
9.3%
시 709
9.3%
별 709
9.3%
특 709
9.3%
신 513
6.7%
Other values (19) 726
9.5%
Decimal Number
ValueCountFrequency (%)
1 678
17.3%
4 568
14.5%
2 554
14.2%
3 396
10.1%
7 359
9.2%
5 353
9.0%
9 331
8.5%
8 249
 
6.4%
0 229
 
5.9%
6 196
 
5.0%
Space Separator
ValueCountFrequency (%)
2159
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 689
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7621
53.0%
Common 6761
47.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 710
9.3%
양 709
9.3%
동 709
9.3%
구 709
9.3%
천 709
9.3%
울 709
9.3%
시 709
9.3%
별 709
9.3%
특 709
9.3%
신 513
6.7%
Other values (19) 726
9.5%
Common
ValueCountFrequency (%)
2159
31.9%
- 689
 
10.2%
1 678
 
10.0%
4 568
 
8.4%
2 554
 
8.2%
3 396
 
5.9%
7 359
 
5.3%
5 353
 
5.2%
9 331
 
4.9%
8 249
 
3.7%
Other values (2) 425
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7621
53.0%
ASCII 6761
47.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2159
31.9%
- 689
 
10.2%
1 678
 
10.0%
4 568
 
8.4%
2 554
 
8.2%
3 396
 
5.9%
7 359
 
5.3%
5 353
 
5.2%
9 331
 
4.9%
8 249
 
3.7%
Other values (2) 425
 
6.3%
Hangul
ValueCountFrequency (%)
서 710
9.3%
양 709
9.3%
동 709
9.3%
구 709
9.3%
천 709
9.3%
울 709
9.3%
시 709
9.3%
별 709
9.3%
특 709
9.3%
신 513
6.7%
Other values (19) 726
9.5%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct702
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.529348
Minimum37.505653
Maximum37.549504
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-04-30T08:01:33.535599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.505653
5-th percentile37.516881
Q137.522196
median37.52652
Q337.538372
95-th percentile37.544869
Maximum37.549504
Range0.043850882
Interquartile range (IQR)0.016175967

Descriptive statistics

Standard deviation0.0093618478
Coefficient of variation (CV)0.00024945405
Kurtosis-0.9716587
Mean37.529348
Median Absolute Deviation (MAD)0.0060909137
Skewness0.30794186
Sum26608.308
Variance8.7644195 × 10-5
MonotonicityNot monotonic
2024-04-30T08:01:33.674070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5206094487 3
 
0.4%
37.5229343184 2
 
0.3%
37.5233574481 2
 
0.3%
37.5192865938 2
 
0.3%
37.5315260834 2
 
0.3%
37.5454834954 2
 
0.3%
37.5210261196 1
 
0.1%
37.5193211217 1
 
0.1%
37.5189501882 1
 
0.1%
37.5195852883 1
 
0.1%
Other values (692) 692
97.6%
ValueCountFrequency (%)
37.5056530706 1
0.1%
37.5061511774 1
0.1%
37.5062164133 1
0.1%
37.5063558885 1
0.1%
37.5066123798 1
0.1%
37.5077767267 1
0.1%
37.5079561488 1
0.1%
37.5096801347 1
0.1%
37.5139644266 1
0.1%
37.5140297082 1
0.1%
ValueCountFrequency (%)
37.5495039525 1
0.1%
37.5489204356 1
0.1%
37.5469882382 1
0.1%
37.5466711037 1
0.1%
37.5466215523 1
0.1%
37.5465703716 1
0.1%
37.5462828123 1
0.1%
37.5461898765 1
0.1%
37.5461542688 1
0.1%
37.5461309318 1
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct702
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.85211
Minimum126.82321
Maximum126.88137
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-04-30T08:01:33.806107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.82321
5-th percentile126.82963
Q1126.83705
median126.8538
Q3126.86642
95-th percentile126.87439
Maximum126.88137
Range0.058157569
Interquartile range (IQR)0.029369097

Descriptive statistics

Standard deviation0.015752237
Coefficient of variation (CV)0.00012417797
Kurtosis-1.3778605
Mean126.85211
Median Absolute Deviation (MAD)0.014697957
Skewness-0.023887722
Sum89938.144
Variance0.00024813297
MonotonicityNot monotonic
2024-04-30T08:01:33.942801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8323296666 3
 
0.4%
126.8591162831 2
 
0.3%
126.8628204938 2
 
0.3%
126.8762081423 2
 
0.3%
126.8346714306 2
 
0.3%
126.8718660723 2
 
0.3%
126.830728109 1
 
0.1%
126.8314334236 1
 
0.1%
126.8312808303 1
 
0.1%
126.8317234295 1
 
0.1%
Other values (692) 692
97.6%
ValueCountFrequency (%)
126.8232128329 1
0.1%
126.8245395754 1
0.1%
126.8246928599 1
0.1%
126.8247940652 1
0.1%
126.8249524948 1
0.1%
126.8251489293 1
0.1%
126.8253023681 1
0.1%
126.8258484567 1
0.1%
126.8259646168 1
0.1%
126.8265427156 1
0.1%
ValueCountFrequency (%)
126.8813704022 1
0.1%
126.8811657797 1
0.1%
126.8810064351 1
0.1%
126.8808861607 1
0.1%
126.88057367 1
0.1%
126.8805103457 1
0.1%
126.8803823975 1
0.1%
126.8802662811 1
0.1%
126.8800767744 1
0.1%
126.8799803146 1
0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-04-20
709 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-04-20
2nd row2024-04-20
3rd row2024-04-20
4th row2024-04-20
5th row2024-04-20

Common Values

ValueCountFrequency (%)
2024-04-20 709
100.0%

Length

2024-04-30T08:01:34.107823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T08:01:34.230027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-04-20 709
100.0%

Interactions

2024-04-30T08:01:30.729191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:01:29.959815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:01:30.408584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:01:30.854452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:01:30.153692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:01:30.514969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:01:30.963875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:01:30.295095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:01:30.610408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T08:01:34.292961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동위도경도
연번1.0000.9610.8800.911
행정동0.9611.0000.8610.904
위도0.8800.8611.0000.777
경도0.9110.9040.7771.000
2024-04-30T08:01:34.393158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도행정동
연번1.000-0.689-0.2790.824
위도-0.6891.0000.3230.564
경도-0.2790.3231.0000.653
행정동0.8240.5640.6531.000

Missing values

2024-04-30T08:01:31.136464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T08:01:31.284880image/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

연번행정동도로명주소지번주소위도경도데이터기준일자
01목1동서울특별시 양천구 오목로 56길 10서울특별시 양천구 목1동 405-47237.523696126.8736982024-04-20
12목1동서울특별시 양천구 목동동로 206-1서울특별시 양천구 목1동 405-20737.523923126.8720092024-04-20
23목1동서울특별시 양천구 오목로56길 14서울특별시 양천구 목1동 405-39337.523307126.8735572024-04-20
34목2동서울특별시 양천구 목동중앙본로2길 5서울특별시 양천구 목2동 750-637.539197126.8702292024-04-20
45목2동서울특별시 양천구 목동중앙로7길 74서울특별시 양천구 목2동 229-1137.539834126.8699482024-04-20
56목2동서울특별시 양천구 목동중앙본로 50-7서울특별시 양천구 목2동 229-137.54044126.869262024-04-20
67목2동서울특별시 양천구 목동중앙본로 56서울특별시 양천구 목2동 234-137.540835126.8691522024-04-20
78목2동서울특별시 양천구 목동중앙본로13길 12서울특별시 양천구 목2동 315-3737.541215126.8683662024-04-20
89목2동서울특별시 양천구 목동중앙본로 15길9서울특별시 양천구 목2동 315-3837.541351126.868422024-04-20
910목2동서울특별시 양천구 목동중앙본로 9길7서울특별시 양천구 목2동 315-6537.540125126.8684052024-04-20
연번행정동도로명주소지번주소위도경도데이터기준일자
699700신정7동서울특별시 양천구 신목로2길17서울특별시 양천구 신정7동 127-7137.519287126.8762082024-04-20
700701신정7동서울특별시 양천구 신목로2길21서울특별시 양천구 신정7동 127-6037.519612126.8763392024-04-20
701702신정7동서울특별시 양천구 목동남로68서울특별시 양천구 신정7동 210-437.50968126.8666252024-04-20
702703신정7동서울특별시 양천구 목동남로2길15서울특별시 양천구 신정7동 202-737.507956126.8644342024-04-20
703704신정7동서울특별시 양천구 목동남로2길21서울특별시 양천구 신정7동 202-1337.507777126.8645162024-04-20
704705신정7동서울특별시 양천구 목동남로2길47서울특별시 양천구 신정7동 192-237.506612126.8643072024-04-20
705706신정7동서울특별시 양천구 목동남로2길50-3서울특별시 양천구 신정7동 190-1837.506356126.863872024-04-20
706707신정7동서울특별시 양천구 목동남로2길58서울특별시 양천구 신정7동 191-337.506151126.8641332024-04-20
707708신정7동서울특별시 양천구 중앙로14나길29서울특별시 양천구 신정7동 177-437.505653126.8657472024-04-20
708709신정7동서울특별시 양천구 목동남로2길 57서울특별시 양천구 신정7동 181-137.506216126.8643582024-04-20