Overview

Dataset statistics

Number of variables5
Number of observations458
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.5 KiB
Average record size in memory41.3 B

Variable types

Numeric1
Categorical3
Text1

Dataset

Description서울특별시 양천구 폐건건지폐형광등 분리수거함의 설치 위치(상세주소), 행정동, 수거함 종류 등의 정보를 제공합니다.
Author서울특별시 양천구
URLhttps://www.data.go.kr/data/15038109/fileData.do

Alerts

수거함종류 has constant value ""Constant
데이터기준일자 has constant value ""Constant
번호 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 번호High correlation
번호 has unique valuesUnique
수거함 설치위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:54:37.987866
Analysis finished2023-12-12 23:54:38.391754
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct458
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean229.5
Minimum1
Maximum458
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-13T08:54:38.466573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile23.85
Q1115.25
median229.5
Q3343.75
95-th percentile435.15
Maximum458
Range457
Interquartile range (IQR)228.5

Descriptive statistics

Standard deviation132.35747
Coefficient of variation (CV)0.576721
Kurtosis-1.2
Mean229.5
Median Absolute Deviation (MAD)114.5
Skewness0
Sum105111
Variance17518.5
MonotonicityStrictly increasing
2023-12-13T08:54:38.584685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
316 1
 
0.2%
314 1
 
0.2%
313 1
 
0.2%
312 1
 
0.2%
311 1
 
0.2%
310 1
 
0.2%
309 1
 
0.2%
308 1
 
0.2%
307 1
 
0.2%
Other values (448) 448
97.8%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
458 1
0.2%
457 1
0.2%
456 1
0.2%
455 1
0.2%
454 1
0.2%
453 1
0.2%
452 1
0.2%
451 1
0.2%
450 1
0.2%
449 1
0.2%

행정동
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
신정3동
91 
목1동
43 
목5동
43 
신정7동
35 
신월2동
34 
Other values (12)
212 

Length

Max length4
Median length4
Mean length3.6659389
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신정3동 91
19.9%
목1동 43
9.4%
목5동 43
9.4%
신정7동 35
 
7.6%
신월2동 34
 
7.4%
목4동 31
 
6.8%
신월4동 29
 
6.3%
목2동 25
 
5.5%
신정2동 22
 
4.8%
신정6동 19
 
4.1%
Other values (7) 86
18.8%

Length

2023-12-13T08:54:38.700081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신정3동 91
19.9%
목1동 43
9.4%
목5동 43
9.4%
신정7동 35
 
7.6%
신월2동 34
 
7.4%
목4동 31
 
6.8%
신월4동 29
 
6.3%
목2동 25
 
5.5%
신정2동 22
 
4.8%
신정6동 19
 
4.1%
Other values (7) 86
18.8%

수거함 설치위치
Text

UNIQUE 

Distinct458
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-13T08:54:38.924736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length38
Mean length31.713974
Min length22

Characters and Unicode

Total characters14525
Distinct characters284
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique458 ?
Unique (%)100.0%

Sample

1st row서울특별시 양천구 목1동 404 푸르지오아파트
2nd row서울특별시 양천구 목1동 404-3 힘찬병원
3rd row서울특별시 양천구 목1동 405-208 생명과학박물관 앞
4th row서울특별시 양천구 목1동 405 대림아파트 관리동
5th row서울특별시 양천구 목1동 405-472 삼거리(대림아파트 담장 옆)
ValueCountFrequency (%)
양천구 459
 
16.4%
서울특별시 458
 
16.3%
신정3동 92
 
3.3%
목1동 44
 
1.6%
목5동 43
 
1.5%
신정7동 35
 
1.2%
신월2동 34
 
1.2%
목4동 31
 
1.1%
101동 30
 
1.1%
신월4동 29
 
1.0%
Other values (770) 1549
55.2%
2023-12-13T08:54:39.292727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2367
 
16.3%
동 849
 
5.8%
1 770
 
5.3%
구 475
 
3.3%
양 473
 
3.3%
천 466
 
3.2%
울 466
 
3.2%
서 465
 
3.2%
별 462
 
3.2%
시 462
 
3.2%
Other values (274) 7270
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8811
60.7%
Decimal Number 3111
 
21.4%
Space Separator 2367
 
16.3%
Dash Punctuation 183
 
1.3%
Other Punctuation 16
 
0.1%
Lowercase Letter 10
 
0.1%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Letter Number 7
 
< 0.1%
Uppercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 849
 
9.6%
구 475
 
5.4%
양 473
 
5.4%
천 466
 
5.3%
울 466
 
5.3%
서 465
 
5.3%
별 462
 
5.2%
시 462
 
5.2%
특 458
 
5.2%
신 407
 
4.6%
Other values (251) 3828
43.4%
Decimal Number
ValueCountFrequency (%)
1 770
24.8%
2 445
14.3%
3 415
13.3%
0 362
11.6%
4 237
 
7.6%
5 227
 
7.3%
7 213
 
6.8%
9 204
 
6.6%
6 142
 
4.6%
8 96
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
T 1
 
16.7%
K 1
 
16.7%
A 1
 
16.7%
Lowercase Letter
ValueCountFrequency (%)
e 6
60.0%
s 2
 
20.0%
k 2
 
20.0%
Space Separator
ValueCountFrequency (%)
2367
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 183
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8811
60.7%
Common 5691
39.2%
Latin 23
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 849
 
9.6%
구 475
 
5.4%
양 473
 
5.4%
천 466
 
5.3%
울 466
 
5.3%
서 465
 
5.3%
별 462
 
5.2%
시 462
 
5.2%
특 458
 
5.2%
신 407
 
4.6%
Other values (251) 3828
43.4%
Common
ValueCountFrequency (%)
2367
41.6%
1 770
 
13.5%
2 445
 
7.8%
3 415
 
7.3%
0 362
 
6.4%
4 237
 
4.2%
5 227
 
4.0%
7 213
 
3.7%
9 204
 
3.6%
- 183
 
3.2%
Other values (5) 268
 
4.7%
Latin
ValueCountFrequency (%)
Ⅱ 7
30.4%
e 6
26.1%
B 3
13.0%
s 2
 
8.7%
k 2
 
8.7%
T 1
 
4.3%
K 1
 
4.3%
A 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8811
60.7%
ASCII 5707
39.3%
Number Forms 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2367
41.5%
1 770
 
13.5%
2 445
 
7.8%
3 415
 
7.3%
0 362
 
6.3%
4 237
 
4.2%
5 227
 
4.0%
7 213
 
3.7%
9 204
 
3.6%
- 183
 
3.2%
Other values (12) 284
 
5.0%
Hangul
ValueCountFrequency (%)
동 849
 
9.6%
구 475
 
5.4%
양 473
 
5.4%
천 466
 
5.3%
울 466
 
5.3%
서 465
 
5.3%
별 462
 
5.2%
시 462
 
5.2%
특 458
 
5.2%
신 407
 
4.6%
Other values (251) 3828
43.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 7
100.0%

수거함종류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
폐형광등폐건전지 통합수거함
458 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐형광등폐건전지 통합수거함
2nd row폐형광등폐건전지 통합수거함
3rd row폐형광등폐건전지 통합수거함
4th row폐형광등폐건전지 통합수거함
5th row폐형광등폐건전지 통합수거함

Common Values

ValueCountFrequency (%)
폐형광등폐건전지 통합수거함 458
100.0%

Length

2023-12-13T08:54:39.402710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:54:39.490981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐형광등폐건전지 458
50.0%
통합수거함 458
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-09-20
458 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-20
2nd row2023-09-20
3rd row2023-09-20
4th row2023-09-20
5th row2023-09-20

Common Values

ValueCountFrequency (%)
2023-09-20 458
100.0%

Length

2023-12-13T08:54:39.588901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:54:39.682005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-20 458
100.0%

Interactions

2023-12-13T08:54:38.188279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:54:39.730131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호행정동
번호1.0000.958
행정동0.9581.000
2023-12-13T08:54:39.808160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호행정동
번호1.0000.809
행정동0.8091.000

Missing values

2023-12-13T08:54:38.272833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:54:38.353051image/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

번호행정동수거함 설치위치수거함종류데이터기준일자
01목1동서울특별시 양천구 목1동 404 푸르지오아파트폐형광등폐건전지 통합수거함2023-09-20
12목1동서울특별시 양천구 목1동 404-3 힘찬병원폐형광등폐건전지 통합수거함2023-09-20
23목1동서울특별시 양천구 목1동 405-208 생명과학박물관 앞폐형광등폐건전지 통합수거함2023-09-20
34목1동서울특별시 양천구 목1동 405 대림아파트 관리동폐형광등폐건전지 통합수거함2023-09-20
45목1동서울특별시 양천구 목1동 405-472 삼거리(대림아파트 담장 옆)폐형광등폐건전지 통합수거함2023-09-20
56목1동서울특별시 양천구 목1동 927-4 횃불교회 앞폐형광등폐건전지 통합수거함2023-09-20
67목1동서울특별시 양천구 목1동 808-5 대원칸타빌(아) 관리동폐형광등폐건전지 통합수거함2023-09-20
78목1동서울특별시 양천구 목1동 808-9 우당아파트 관리동폐형광등폐건전지 통합수거함2023-09-20
89목1동서울특별시 양천구 목1동 914 목동운동장 1게이트 재활용선별장 앞폐형광등폐건전지 통합수거함2023-09-20
910목1동서울특별시 양천구 목1동 916 현대하이페리온 101동폐형광등폐건전지 통합수거함2023-09-20
번호행정동수거함 설치위치수거함종류데이터기준일자
448449신정7동서울특별시 양천구 신정7동 337-2 목동2차우성아파트 1단지 101동폐형광등폐건전지 통합수거함2023-09-20
449450신정7동서울특별시 양천구 신정7동 337-2 목동2차우성아파트 1단지 102동폐형광등폐건전지 통합수거함2023-09-20
450451신정7동서울특별시 양천구 신정7동 338 목동3차우성아파트 관리사무소,301동 옆쪽폐형광등폐건전지 통합수거함2023-09-20
451452신정7동서울특별시 양천구 신정7동 1314 중앙하이츠 아파트, 102동쪽 경비실폐형광등폐건전지 통합수거함2023-09-20
452453신정7동서울특별시 양천구 신정7동 323-9 이스타빌3차 주상복합, 지하추자장 1폐형광등폐건전지 통합수거함2023-09-20
453454신정7동서울특별시 양천구 신정7동 323-9 이스타빌3차 주상복합, 지하추자장 2폐형광등폐건전지 통합수거함2023-09-20
454455신정7동서울특별시 양천구 신정7동 201-1 세양청마루 2차 주상복합폐형광등폐건전지 통합수거함2023-09-20
455456신정7동서울특별시 양천구 신정7동 171-61 파크자이아파트 101동폐형광등폐건전지 통합수거함2023-09-20
456457신정7동서울특별시 양천구 신정7동 171-61 파크자이아파트 104동폐형광등폐건전지 통합수거함2023-09-20
457458신정7동서울특별시 양천구 신정7동 171-61 파크자이아파트 107동폐형광등폐건전지 통합수거함2023-09-20