Overview

Dataset statistics

Number of variables5
Number of observations9235
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory369.9 KiB
Average record size in memory41.0 B

Variable types

Numeric1
Text2
Categorical2

Dataset

Description국민들의 폐전자제품 배출 편의성을 제고하기 위한 폐전자제품 수거함 위치정보 데이터로 수거함의 주소정보를 제공합니다.
Author한국환경공단
URLhttps://www.data.go.kr/data/15106385/fileData.do

Alerts

수거종류 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
장소구분 is highly overall correlated with 수거종류High correlation
순번 is highly overall correlated with 수거종류High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:54:26.246412
Analysis finished2023-12-12 20:54:27.610347
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct9235
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4618
Minimum1
Maximum9235
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.3 KiB
2023-12-13T05:54:27.719963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile462.7
Q12309.5
median4618
Q36926.5
95-th percentile8773.3
Maximum9235
Range9234
Interquartile range (IQR)4617

Descriptive statistics

Standard deviation2666.0592
Coefficient of variation (CV)0.57731901
Kurtosis-1.2
Mean4618
Median Absolute Deviation (MAD)2309
Skewness0
Sum42647230
Variance7107871.7
MonotonicityStrictly increasing
2023-12-13T05:54:27.884301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
6063 1
 
< 0.1%
6155 1
 
< 0.1%
6156 1
 
< 0.1%
6157 1
 
< 0.1%
6158 1
 
< 0.1%
6159 1
 
< 0.1%
6160 1
 
< 0.1%
6161 1
 
< 0.1%
6162 1
 
< 0.1%
Other values (9225) 9225
99.9%
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 (%)
9235 1
< 0.1%
9234 1
< 0.1%
9233 1
< 0.1%
9232 1
< 0.1%
9231 1
< 0.1%
9230 1
< 0.1%
9229 1
< 0.1%
9228 1
< 0.1%
9227 1
< 0.1%
9226 1
< 0.1%

상호명
Text

Distinct8809
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size72.3 KiB
2023-12-13T05:54:28.224442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length10.695073
Min length2

Characters and Unicode

Total characters98769
Distinct characters679
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8413 ?
Unique (%)91.1%

Sample

1st row도화1동 주민센터
2nd row도화2,3동 주민센터
3rd row용현2동 주민센터
4th row용현5동 주민센터
5th row용현3동 주민센터
ValueCountFrequency (%)
롯데하이마트 702
 
4.2%
본점 321
 
1.9%
kt플라자 261
 
1.6%
삼성디지털프라자 207
 
1.2%
이마트 135
 
0.8%
홈플러스 133
 
0.8%
ps&m 119
 
0.7%
롯데마트 107
 
0.6%
act대리점 61
 
0.4%
전자랜드 53
 
0.3%
Other values (8571) 14646
87.5%
2023-12-13T05:54:28.745780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 8327
 
8.4%
7544
 
7.6%
동 2807
 
2.8%
대 2699
 
2.7%
리 2662
 
2.7%
( 2403
 
2.4%
) 2403
 
2.4%
트 2127
 
2.2%
L 1880
 
1.9%
G 1862
 
1.9%
Other values (669) 64055
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73786
74.7%
Uppercase Letter 8734
 
8.8%
Space Separator 7553
 
7.6%
Open Punctuation 2403
 
2.4%
Close Punctuation 2403
 
2.4%
Math Symbol 1820
 
1.8%
Decimal Number 1673
 
1.7%
Lowercase Letter 181
 
0.2%
Other Punctuation 161
 
0.2%
Dash Punctuation 19
 
< 0.1%
Other values (4) 36
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 8327
 
11.3%
동 2807
 
3.8%
대 2699
 
3.7%
리 2662
 
3.6%
트 2127
 
2.9%
마 1501
 
2.0%
이 1411
 
1.9%
아 1254
 
1.7%
데 1053
 
1.4%
하 1041
 
1.4%
Other values (597) 48904
66.3%
Uppercase Letter
ValueCountFrequency (%)
L 1880
21.5%
G 1862
21.3%
U 1823
20.9%
T 1013
11.6%
K 722
 
8.3%
P 406
 
4.6%
S 269
 
3.1%
M 159
 
1.8%
C 141
 
1.6%
A 107
 
1.2%
Other values (14) 352
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
e 68
37.6%
t 26
 
14.4%
n 23
 
12.7%
h 9
 
5.0%
r 8
 
4.4%
a 7
 
3.9%
s 4
 
2.2%
v 4
 
2.2%
c 4
 
2.2%
l 3
 
1.7%
Other values (11) 25
 
13.8%
Decimal Number
ValueCountFrequency (%)
2 589
35.2%
1 559
33.4%
3 225
 
13.4%
5 92
 
5.5%
4 91
 
5.4%
6 39
 
2.3%
7 29
 
1.7%
8 21
 
1.3%
9 17
 
1.0%
0 10
 
0.6%
Other Punctuation
ValueCountFrequency (%)
& 137
85.1%
, 15
 
9.3%
* 4
 
2.5%
. 3
 
1.9%
@ 1
 
0.6%
: 1
 
0.6%
Space Separator
ValueCountFrequency (%)
7544
99.9%
  9
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 2403
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2403
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1820
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Control
ValueCountFrequency (%)
17
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73789
74.7%
Common 16062
 
16.3%
Latin 8917
 
9.0%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 8327
 
11.3%
동 2807
 
3.8%
대 2699
 
3.7%
리 2662
 
3.6%
트 2127
 
2.9%
마 1501
 
2.0%
이 1411
 
1.9%
아 1254
 
1.7%
데 1053
 
1.4%
하 1041
 
1.4%
Other values (597) 48907
66.3%
Latin
ValueCountFrequency (%)
L 1880
21.1%
G 1862
20.9%
U 1823
20.4%
T 1013
11.4%
K 722
 
8.1%
P 406
 
4.6%
S 269
 
3.0%
M 159
 
1.8%
C 141
 
1.6%
A 107
 
1.2%
Other values (36) 535
 
6.0%
Common
ValueCountFrequency (%)
7544
47.0%
( 2403
 
15.0%
) 2403
 
15.0%
+ 1820
 
11.3%
2 589
 
3.7%
1 559
 
3.5%
3 225
 
1.4%
& 137
 
0.9%
5 92
 
0.6%
4 91
 
0.6%
Other values (15) 199
 
1.2%
Han
ValueCountFrequency (%)
新 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73785
74.7%
ASCII 24967
 
25.3%
None 14
 
< 0.1%
Number Forms 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 8327
 
11.3%
동 2807
 
3.8%
대 2699
 
3.7%
리 2662
 
3.6%
트 2127
 
2.9%
마 1501
 
2.0%
이 1411
 
1.9%
아 1254
 
1.7%
데 1053
 
1.4%
하 1041
 
1.4%
Other values (596) 48903
66.3%
ASCII
ValueCountFrequency (%)
7544
30.2%
( 2403
 
9.6%
) 2403
 
9.6%
L 1880
 
7.5%
G 1862
 
7.5%
U 1823
 
7.3%
+ 1820
 
7.3%
T 1013
 
4.1%
K 722
 
2.9%
2 589
 
2.4%
Other values (58) 2908
 
11.6%
None
ValueCountFrequency (%)
  9
64.3%
㈜ 4
28.6%
２ 1
 
7.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
CJK
ValueCountFrequency (%)
新 1
100.0%

수거종류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.3 KiB
폐휴대폰
5861 
중소형폐가전
3374 

Length

Max length6
Median length4
Mean length4.7306984
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐휴대폰 5861
63.5%
중소형폐가전 3374
36.5%

Length

2023-12-13T05:54:28.930123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:54:29.063592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐휴대폰 5861
63.5%
중소형폐가전 3374
36.5%

수거장소(주소)
Text

Distinct8942
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size72.3 KiB
2023-12-13T05:54:29.626671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length39
Mean length16.917704
Min length9

Characters and Unicode

Total characters156235
Distinct characters529
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

Unique8676 ?
Unique (%)93.9%

Sample

1st row인천 미추홀구 경인로 295
2nd row인천 미추홀구 숙골로43번길 14-21
3rd row인천 미추홀구 낙섬중로 101
4th row인천 미추홀구 토금북로 60
5th row인천 미추홀구 인주대로 133
ValueCountFrequency (%)
경기 1381
 
3.5%
서울 1127
 
2.8%
경북 917
 
2.3%
대구 811
 
2.0%
경남 611
 
1.5%
인천 582
 
1.5%
광주 544
 
1.4%
부산 488
 
1.2%
충북 464
 
1.2%
청주시 393
 
1.0%
Other values (7211) 32564
81.7%
2023-12-13T05:54:30.186368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31156
 
19.9%
로 8464
 
5.4%
구 7322
 
4.7%
1 5925
 
3.8%
시 5006
 
3.2%
2 4162
 
2.7%
경 3631
 
2.3%
3 3193
 
2.0%
대 3193
 
2.0%
서 2775
 
1.8%
Other values (519) 81408
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93867
60.1%
Space Separator 31161
 
19.9%
Decimal Number 28587
 
18.3%
Dash Punctuation 952
 
0.6%
Close Punctuation 696
 
0.4%
Open Punctuation 696
 
0.4%
Other Punctuation 250
 
0.2%
Uppercase Letter 25
 
< 0.1%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 8464
 
9.0%
구 7322
 
7.8%
시 5006
 
5.3%
경 3631
 
3.9%
대 3193
 
3.4%
서 2775
 
3.0%
북 2412
 
2.6%
동 2394
 
2.6%
남 2390
 
2.5%
주 2315
 
2.5%
Other values (486) 53965
57.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
12.0%
K 3
12.0%
L 3
12.0%
C 3
12.0%
A 3
12.0%
H 2
8.0%
B 1
 
4.0%
D 1
 
4.0%
F 1
 
4.0%
N 1
 
4.0%
Other values (4) 4
16.0%
Decimal Number
ValueCountFrequency (%)
1 5925
20.7%
2 4162
14.6%
3 3193
11.2%
4 2509
8.8%
5 2492
8.7%
6 2256
 
7.9%
7 2180
 
7.6%
0 2134
 
7.5%
8 1929
 
6.7%
9 1807
 
6.3%
Other Punctuation
ValueCountFrequency (%)
, 230
92.0%
. 15
 
6.0%
· 5
 
2.0%
Space Separator
ValueCountFrequency (%)
31156
> 99.9%
  5
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 952
100.0%
Close Punctuation
ValueCountFrequency (%)
) 696
100.0%
Open Punctuation
ValueCountFrequency (%)
( 696
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93867
60.1%
Common 62343
39.9%
Latin 25
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 8464
 
9.0%
구 7322
 
7.8%
시 5006
 
5.3%
경 3631
 
3.9%
대 3193
 
3.4%
서 2775
 
3.0%
북 2412
 
2.6%
동 2394
 
2.6%
남 2390
 
2.5%
주 2315
 
2.5%
Other values (486) 53965
57.5%
Common
ValueCountFrequency (%)
31156
50.0%
1 5925
 
9.5%
2 4162
 
6.7%
3 3193
 
5.1%
4 2509
 
4.0%
5 2492
 
4.0%
6 2256
 
3.6%
7 2180
 
3.5%
0 2134
 
3.4%
8 1929
 
3.1%
Other values (9) 4407
 
7.1%
Latin
ValueCountFrequency (%)
S 3
12.0%
K 3
12.0%
L 3
12.0%
C 3
12.0%
A 3
12.0%
H 2
8.0%
B 1
 
4.0%
D 1
 
4.0%
F 1
 
4.0%
N 1
 
4.0%
Other values (4) 4
16.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93867
60.1%
ASCII 62358
39.9%
None 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31156
50.0%
1 5925
 
9.5%
2 4162
 
6.7%
3 3193
 
5.1%
4 2509
 
4.0%
5 2492
 
4.0%
6 2256
 
3.6%
7 2180
 
3.5%
0 2134
 
3.4%
8 1929
 
3.1%
Other values (21) 4422
 
7.1%
Hangul
ValueCountFrequency (%)
로 8464
 
9.0%
구 7322
 
7.8%
시 5006
 
5.3%
경 3631
 
3.9%
대 3193
 
3.4%
서 2775
 
3.0%
북 2412
 
2.6%
동 2394
 
2.6%
남 2390
 
2.5%
주 2315
 
2.5%
Other values (486) 53965
57.5%
None
ValueCountFrequency (%)
  5
50.0%
· 5
50.0%

장소구분
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.3 KiB
민팃ATM
5599 
공공주택(아파트 등)
2204 
롯데하이마트
 
420
KT대리점
 
262
LG베스트샵
 
255
Other values (4)
 
495

Length

Max length17
Median length5
Mean length6.9197618
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지자체(구청, 행정복지센터 등)
2nd row지자체(구청, 행정복지센터 등)
3rd row지자체(구청, 행정복지센터 등)
4th row지자체(구청, 행정복지센터 등)
5th row지자체(구청, 행정복지센터 등)

Common Values

ValueCountFrequency (%)
민팃ATM 5599
60.6%
공공주택(아파트 등) 2204
 
23.9%
롯데하이마트 420
 
4.5%
KT대리점 262
 
2.8%
LG베스트샵 255
 
2.8%
지자체(구청, 행정복지센터 등) 209
 
2.3%
삼성디지털프라자 170
 
1.8%
재활용도움센터(제주도) 108
 
1.2%
공공주택(아파트 등) 8
 
0.1%

Length

2023-12-13T05:54:30.344207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:54:30.473484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민팃atm 5599
47.2%
등 2421
20.4%
공공주택(아파트 2212
 
18.6%
롯데하이마트 420
 
3.5%
kt대리점 262
 
2.2%
lg베스트샵 255
 
2.1%
지자체(구청 209
 
1.8%
행정복지센터 209
 
1.8%
삼성디지털프라자 170
 
1.4%
재활용도움센터(제주도 108
 
0.9%

Interactions

2023-12-13T05:54:27.286614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:54:30.587037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번수거종류장소구분
순번1.0000.9890.772
수거종류0.9891.0001.000
장소구분0.7721.0001.000
2023-12-13T05:54:30.671646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수거종류장소구분
수거종류1.0001.000
장소구분1.0001.000
2023-12-13T05:54:30.746003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번수거종류장소구분
순번1.0000.9080.492
수거종류0.9081.0001.000
장소구분0.4921.0001.000

Missing values

2023-12-13T05:54:27.442779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:54:27.554363image/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

순번상호명수거종류수거장소(주소)장소구분
01도화1동 주민센터중소형폐가전인천 미추홀구 경인로 295지자체(구청, 행정복지센터 등)
12도화2,3동 주민센터중소형폐가전인천 미추홀구 숙골로43번길 14-21지자체(구청, 행정복지센터 등)
23용현2동 주민센터중소형폐가전인천 미추홀구 낙섬중로 101지자체(구청, 행정복지센터 등)
34용현5동 주민센터중소형폐가전인천 미추홀구 토금북로 60지자체(구청, 행정복지센터 등)
45용현3동 주민센터중소형폐가전인천 미추홀구 인주대로 133지자체(구청, 행정복지센터 등)
56주안1동 주민센터중소형폐가전인천 미추홀구 주안서로53번길 22지자체(구청, 행정복지센터 등)
67청학동 주민센터중소형폐가전인천 연수구 비류대로294번길 26지자체(구청, 행정복지센터 등)
78동춘1동 주민센터중소형폐가전인천 연수구 먼우금로 117지자체(구청, 행정복지센터 등)
89연수구청중소형폐가전인천 연수구 원인재로 115지자체(구청, 행정복지센터 등)
910남동구청중소형폐가전인천 남동구 소래로 633지자체(구청, 행정복지센터 등)
순번상호명수거종류수거장소(주소)장소구분
92259226진주성점중소형폐가전경상남도 진주시 진양호로 484LG베스트샵
92269227진주시청점중소형폐가전경상남도 진주시 동진로 230LG베스트샵
92279228창원역점중소형폐가전경상남도 창원시 의창구 창원대로 1LG베스트샵
92289229충렬사점중소형폐가전부산광역시 동래구 충렬대로350번길 2LG베스트샵
92299230칠암점중소형폐가전경상남도 진주시 진주대로816번길 2LG베스트샵
92309231통영점중소형폐가전경상남도 통영시 중앙로 328LG베스트샵
92319232하단점중소형폐가전부산광역시 사하구 낙동대로 427LG베스트샵
92329233마산본점중소형폐가전경상남도 창원시 마산회원구 3·15대로 625LG베스트샵
92339234합포점중소형폐가전경상남도 창원시 마산합포구 해안대로 234LG베스트샵
92349235화명점중소형폐가전부산광역시 북구 금곡대로 260LG베스트샵