Overview

Dataset statistics

Number of variables8
Number of observations122
Missing cells0
Missing cells (%)0.0%
Duplicate rows13
Duplicate rows (%)10.7%
Total size in memory7.8 KiB
Average record size in memory65.1 B

Variable types

Text2
Categorical5
DateTime1

Dataset

Description도봉구에 설치되어 있는 가로휴지통 현황 데이터(시설명, 설치위치, 설치지점 등)
Author서울특별시 도봉구
URLhttps://www.data.go.kr/data/15028106/fileData.do

Alerts

규격 has constant value ""Constant
데이터기준일 has constant value ""Constant
Dataset has 13 (10.7%) duplicate rowsDuplicates
주소1 is highly overall correlated with 동구분High correlation
동구분 is highly overall correlated with 주소1High correlation
설치지점 is highly overall correlated with 종류High correlation
종류 is highly overall correlated with 설치지점High correlation

Reproduction

Analysis started2023-12-12 10:26:41.022538
Analysis finished2023-12-12 10:26:41.671757
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct102
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T19:26:41.891593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length8.8360656
Min length4

Characters and Unicode

Total characters1078
Distinct characters170
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)67.2%

Sample

1st row금용 APT
2nd row창4동 주민센터 앞
3rd row방학3동 주민센터
4th row방학3동 주민센터 건너편
5th row시티부동산
ValueCountFrequency (%)
앞 45
 
18.6%
건너편 14
 
5.8%
주민센터 7
 
2.9%
버스정류장 5
 
2.1%
apt 5
 
2.1%
방학사거리 4
 
1.7%
창동역 3
 
1.2%
창4동 3
 
1.2%
1번출구 3
 
1.2%
맞은편 3
 
1.2%
Other values (112) 150
62.0%
2023-12-12T19:26:42.338646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
 
11.7%
앞 46
 
4.3%
학 41
 
3.8%
교 32
 
3.0%
동 30
 
2.8%
초 27
 
2.5%
등 27
 
2.5%
서 25
 
2.3%
울 24
 
2.2%
창 19
 
1.8%
Other values (160) 681
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 874
81.1%
Space Separator 126
 
11.7%
Decimal Number 36
 
3.3%
Uppercase Letter 28
 
2.6%
Close Punctuation 7
 
0.6%
Open Punctuation 7
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 46
 
5.3%
학 41
 
4.7%
교 32
 
3.7%
동 30
 
3.4%
초 27
 
3.1%
등 27
 
3.1%
서 25
 
2.9%
울 24
 
2.7%
창 19
 
2.2%
편 18
 
2.1%
Other values (143) 585
66.9%
Decimal Number
ValueCountFrequency (%)
1 15
41.7%
3 5
 
13.9%
2 5
 
13.9%
4 5
 
13.9%
0 2
 
5.6%
5 2
 
5.6%
9 1
 
2.8%
7 1
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
P 9
32.1%
T 8
28.6%
A 8
28.6%
I 1
 
3.6%
V 1
 
3.6%
S 1
 
3.6%
Space Separator
ValueCountFrequency (%)
126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 874
81.1%
Common 176
 
16.3%
Latin 28
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 46
 
5.3%
학 41
 
4.7%
교 32
 
3.7%
동 30
 
3.4%
초 27
 
3.1%
등 27
 
3.1%
서 25
 
2.9%
울 24
 
2.7%
창 19
 
2.2%
편 18
 
2.1%
Other values (143) 585
66.9%
Common
ValueCountFrequency (%)
126
71.6%
1 15
 
8.5%
) 7
 
4.0%
( 7
 
4.0%
3 5
 
2.8%
2 5
 
2.8%
4 5
 
2.8%
0 2
 
1.1%
5 2
 
1.1%
9 1
 
0.6%
Latin
ValueCountFrequency (%)
P 9
32.1%
T 8
28.6%
A 8
28.6%
I 1
 
3.6%
V 1
 
3.6%
S 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 874
81.1%
ASCII 204
 
18.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
61.8%
1 15
 
7.4%
P 9
 
4.4%
T 8
 
3.9%
A 8
 
3.9%
) 7
 
3.4%
( 7
 
3.4%
3 5
 
2.5%
2 5
 
2.5%
4 5
 
2.5%
Other values (7) 9
 
4.4%
Hangul
ValueCountFrequency (%)
앞 46
 
5.3%
학 41
 
4.7%
교 32
 
3.7%
동 30
 
3.4%
초 27
 
3.1%
등 27
 
3.1%
서 25
 
2.9%
울 24
 
2.7%
창 19
 
2.2%
편 18
 
2.1%
Other values (143) 585
66.9%

동구분
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
도봉로
37 
마들로
19 
노해로
16 
방학로
13 
해등로
12 
Other values (5)
25 

Length

Max length4
Median length3
Mean length3.0983607
Min length3

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row노해로
2nd row노해로
3rd row시루봉로
4th row시루봉로
5th row방학로

Common Values

ValueCountFrequency (%)
도봉로 37
30.3%
마들로 19
15.6%
노해로 16
13.1%
방학로 13
 
10.7%
해등로 12
 
9.8%
덕릉로 10
 
8.2%
우이천로 7
 
5.7%
시루봉로 5
 
4.1%
삼양로 2
 
1.6%
노헤로 1
 
0.8%

Length

2023-12-12T19:26:42.486634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:26:42.615489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도봉로 37
30.3%
마들로 19
15.6%
노해로 16
13.1%
방학로 13
 
10.7%
해등로 12
 
9.8%
덕릉로 10
 
8.2%
우이천로 7
 
5.7%
시루봉로 5
 
4.1%
삼양로 2
 
1.6%
노헤로 1
 
0.8%

주소1
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
도봉로
37 
마들로
19 
노해로
16 
방학로
13 
해등로
12 
Other values (5)
25 

Length

Max length4
Median length3
Mean length3.0983607
Min length3

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row노해로
2nd row노해로
3rd row시루봉로
4th row시루봉로
5th row방학로

Common Values

ValueCountFrequency (%)
도봉로 37
30.3%
마들로 19
15.6%
노해로 16
13.1%
방학로 13
 
10.7%
해등로 12
 
9.8%
덕릉로 10
 
8.2%
우이천로 7
 
5.7%
시루봉로 5
 
4.1%
삼양로 2
 
1.6%
노헤로 1
 
0.8%

Length

2023-12-12T19:26:42.756727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:26:42.881108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도봉로 37
30.3%
마들로 19
15.6%
노해로 16
13.1%
방학로 13
 
10.7%
해등로 12
 
9.8%
덕릉로 10
 
8.2%
우이천로 7
 
5.7%
시루봉로 5
 
4.1%
삼양로 2
 
1.6%
노헤로 1
 
0.8%

설치위치
Text

Distinct102
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T19:26:43.153329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length8.8360656
Min length4

Characters and Unicode

Total characters1078
Distinct characters170
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)67.2%

Sample

1st row금용 APT
2nd row창4동 주민센터 앞
3rd row방학3동 주민센터
4th row방학3동 주민센터 건너편
5th row시티부동산
ValueCountFrequency (%)
앞 45
 
18.6%
건너편 14
 
5.8%
주민센터 7
 
2.9%
버스정류장 5
 
2.1%
apt 5
 
2.1%
방학사거리 4
 
1.7%
창동역 3
 
1.2%
창4동 3
 
1.2%
1번출구 3
 
1.2%
맞은편 3
 
1.2%
Other values (112) 150
62.0%
2023-12-12T19:26:43.562975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
 
11.7%
앞 46
 
4.3%
학 41
 
3.8%
교 32
 
3.0%
동 30
 
2.8%
초 27
 
2.5%
등 27
 
2.5%
서 25
 
2.3%
울 24
 
2.2%
창 19
 
1.8%
Other values (160) 681
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 874
81.1%
Space Separator 126
 
11.7%
Decimal Number 36
 
3.3%
Uppercase Letter 28
 
2.6%
Close Punctuation 7
 
0.6%
Open Punctuation 7
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 46
 
5.3%
학 41
 
4.7%
교 32
 
3.7%
동 30
 
3.4%
초 27
 
3.1%
등 27
 
3.1%
서 25
 
2.9%
울 24
 
2.7%
창 19
 
2.2%
편 18
 
2.1%
Other values (143) 585
66.9%
Decimal Number
ValueCountFrequency (%)
1 15
41.7%
3 5
 
13.9%
2 5
 
13.9%
4 5
 
13.9%
0 2
 
5.6%
5 2
 
5.6%
9 1
 
2.8%
7 1
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
P 9
32.1%
T 8
28.6%
A 8
28.6%
I 1
 
3.6%
V 1
 
3.6%
S 1
 
3.6%
Space Separator
ValueCountFrequency (%)
126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 874
81.1%
Common 176
 
16.3%
Latin 28
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 46
 
5.3%
학 41
 
4.7%
교 32
 
3.7%
동 30
 
3.4%
초 27
 
3.1%
등 27
 
3.1%
서 25
 
2.9%
울 24
 
2.7%
창 19
 
2.2%
편 18
 
2.1%
Other values (143) 585
66.9%
Common
ValueCountFrequency (%)
126
71.6%
1 15
 
8.5%
) 7
 
4.0%
( 7
 
4.0%
3 5
 
2.8%
2 5
 
2.8%
4 5
 
2.8%
0 2
 
1.1%
5 2
 
1.1%
9 1
 
0.6%
Latin
ValueCountFrequency (%)
P 9
32.1%
T 8
28.6%
A 8
28.6%
I 1
 
3.6%
V 1
 
3.6%
S 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 874
81.1%
ASCII 204
 
18.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
61.8%
1 15
 
7.4%
P 9
 
4.4%
T 8
 
3.9%
A 8
 
3.9%
) 7
 
3.4%
( 7
 
3.4%
3 5
 
2.5%
2 5
 
2.5%
4 5
 
2.5%
Other values (7) 9
 
4.4%
Hangul
ValueCountFrequency (%)
앞 46
 
5.3%
학 41
 
4.7%
교 32
 
3.7%
동 30
 
3.4%
초 27
 
3.1%
등 27
 
3.1%
서 25
 
2.9%
울 24
 
2.7%
창 19
 
2.2%
편 18
 
2.1%
Other values (143) 585
66.9%

설치지점
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
정류장(버스,택시 등)
76 
기타(학교앞)
26 
기타(횡단보도)
14 
도로(가로)변
 
6

Length

Max length12
Median length12
Mean length10.229508
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정류장(버스,택시 등)
2nd row정류장(버스,택시 등)
3rd row정류장(버스,택시 등)
4th row정류장(버스,택시 등)
5th row정류장(버스,택시 등)

Common Values

ValueCountFrequency (%)
정류장(버스,택시 등) 76
62.3%
기타(학교앞) 26
 
21.3%
기타(횡단보도) 14
 
11.5%
도로(가로)변 6
 
4.9%

Length

2023-12-12T19:26:43.699867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:26:43.797457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정류장(버스,택시 76
38.4%
등 76
38.4%
기타(학교앞 26
 
13.1%
기타(횡단보도 14
 
7.1%
도로(가로)변 6
 
3.0%

종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
일반쓰레기수거용
90 
일반,재활용쓰레기수거용
26 
재활용 수거용
 
6

Length

Max length12
Median length8
Mean length8.8032787
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반쓰레기수거용 90
73.8%
일반,재활용쓰레기수거용 26
 
21.3%
재활용 수거용 6
 
4.9%

Length

2023-12-12T19:26:43.898994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:26:44.274384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반쓰레기수거용 90
70.3%
일반,재활용쓰레기수거용 26
 
20.3%
재활용 6
 
4.7%
수거용 6
 
4.7%

규격
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
서울시 표준
122 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울시 표준
2nd row서울시 표준
3rd row서울시 표준
4th row서울시 표준
5th row서울시 표준

Common Values

ValueCountFrequency (%)
서울시 표준 122
100.0%

Length

2023-12-12T19:26:44.359855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:26:44.452648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울시 122
50.0%
표준 122
50.0%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2018-01-01 00:00:00
Maximum2018-01-01 00:00:00
2023-12-12T19:26:44.529866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:26:44.616640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T19:26:44.684018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동구분주소1설치지점종류
동구분1.0001.0000.3000.113
주소11.0001.0000.3000.113
설치지점0.3000.3001.0000.670
종류0.1130.1130.6701.000
2023-12-12T19:26:44.810053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주소1동구분설치지점종류
주소11.0001.0000.1770.060
동구분1.0001.0000.1770.060
설치지점0.1770.1771.0000.697
종류0.0600.0600.6971.000
2023-12-12T19:26:44.901484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동구분주소1설치지점종류
동구분1.0001.0000.1770.060
주소11.0001.0000.1770.060
설치지점0.1770.1771.0000.697
종류0.0600.0600.6971.000

Missing values

2023-12-12T19:26:41.489634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:26:41.623438image/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

시설명동구분주소1설치위치설치지점종류규격데이터기준일
0금용 APT노해로노해로금용 APT정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
1창4동 주민센터 앞노해로노해로창4동 주민센터 앞정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
2방학3동 주민센터시루봉로시루봉로방학3동 주민센터정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
3방학3동 주민센터 건너편시루봉로시루봉로방학3동 주민센터 건너편정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
4시티부동산방학로방학로시티부동산정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
5성당 건너편시루봉로시루봉로성당 건너편정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
6방학2동 주민센터 앞시루봉로시루봉로방학2동 주민센터 앞정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
7방학2동 주민센터 건너편시루봉로시루봉로방학2동 주민센터 건너편정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
8신한은행 건너편방학로방학로신한은행 건너편정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
9연세치과 앞방학로방학로연세치과 앞정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
시설명동구분주소1설치위치설치지점종류규격데이터기준일
112우성1차 APT해등로해등로우성1차 APT정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
113우성2차 APT해등로해등로우성2차 APT정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
114삼익 103동 APT 앞해등로해등로삼익 103동 APT 앞정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
115삼익 109동 APT 앞해등로해등로삼익 109동 APT 앞정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
116숭미파출소 맞은편노해로노해로숭미파출소 맞은편정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
117선덕고등학교 앞해등로해등로선덕고등학교 앞정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
118주공1단지해등로해등로주공1단지정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
119염광APT노해로노해로염광APT정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
120쌍문3동 어린이집노해로노해로쌍문3동 어린이집정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01
121숭미초교 앞노해로노해로숭미초교 앞정류장(버스,택시 등)일반쓰레기수거용서울시 표준2018-01-01

Duplicate rows

Most frequently occurring

시설명동구분주소1설치위치설치지점종류규격데이터기준일# duplicates
0북서울중학교도봉로도봉로북서울중학교기타(학교앞)일반,재활용쓰레기수거용서울시 표준2018-01-012
1서울가인초등학교도봉로도봉로서울가인초등학교기타(학교앞)일반,재활용쓰레기수거용서울시 표준2018-01-012
2서울누원초등학교마들로마들로서울누원초등학교기타(학교앞)일반,재활용쓰레기수거용서울시 표준2018-01-012
3서울방학초등학교방학로방학로서울방학초등학교기타(학교앞)일반,재활용쓰레기수거용서울시 표준2018-01-012
4서울신화초등학교우이천로우이천로서울신화초등학교기타(학교앞)일반,재활용쓰레기수거용서울시 표준2018-01-012
5서울쌍문초등학교우이천로우이천로서울쌍문초등학교기타(학교앞)일반,재활용쓰레기수거용서울시 표준2018-01-012
6서울자운초등학교마들로마들로서울자운초등학교기타(학교앞)일반,재활용쓰레기수거용서울시 표준2018-01-012
7서울창경초등학교도봉로도봉로서울창경초등학교기타(학교앞)일반,재활용쓰레기수거용서울시 표준2018-01-012
8서울창도초등학교마들로마들로서울창도초등학교기타(학교앞)일반,재활용쓰레기수거용서울시 표준2018-01-012
9서울창림초등학교덕릉로덕릉로서울창림초등학교기타(학교앞)일반,재활용쓰레기수거용서울시 표준2018-01-012