Overview

Dataset statistics

Number of variables3
Number of observations340
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.1 KiB
Average record size in memory24.4 B

Variable types

Text2
Categorical1

Dataset

Description인천광역시 연수구 폐기물 무단투기 고정형 CCTV 설치현황 데이터로서 관리번호, 행정동, 설치장소 등의 항목으로 이루어져 있습니다.
URLhttps://www.data.go.kr/data/15116352/fileData.do

Alerts

관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:08:44.772947
Analysis finished2023-12-12 12:08:45.262019
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct340
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-12T21:08:45.606250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.2323529
Min length5

Characters and Unicode

Total characters2459
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique340 ?
Unique (%)100.0%

Sample

1st row폐기물-1
2nd row폐기물-1-1
3rd row폐기물-2
4th row폐기물-2-1
5th row폐기물-3
ValueCountFrequency (%)
폐기물-1 1
 
0.3%
폐기물-136 1
 
0.3%
폐기물-142-1 1
 
0.3%
폐기물-142 1
 
0.3%
폐기물-141 1
 
0.3%
폐기물-140 1
 
0.3%
폐기물-139 1
 
0.3%
폐기물-138-1 1
 
0.3%
폐기물-138 1
 
0.3%
폐기물-137-1 1
 
0.3%
Other values (330) 330
97.1%
2023-12-12T21:08:46.258598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 474
19.3%
340
13.8%
340
13.8%
340
13.8%
1 338
13.7%
2 101
 
4.1%
6 73
 
3.0%
9 68
 
2.8%
0 68
 
2.8%
3 67
 
2.7%
Other values (4) 250
10.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1020
41.5%
Decimal Number 965
39.2%
Dash Punctuation 474
19.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 338
35.0%
2 101
 
10.5%
6 73
 
7.6%
9 68
 
7.0%
0 68
 
7.0%
3 67
 
6.9%
5 65
 
6.7%
4 63
 
6.5%
7 62
 
6.4%
8 60
 
6.2%
Other Letter
ValueCountFrequency (%)
340
33.3%
340
33.3%
340
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 474
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1439
58.5%
Hangul 1020
41.5%

Most frequent character per script

Common
ValueCountFrequency (%)
- 474
32.9%
1 338
23.5%
2 101
 
7.0%
6 73
 
5.1%
9 68
 
4.7%
0 68
 
4.7%
3 67
 
4.7%
5 65
 
4.5%
4 63
 
4.4%
7 62
 
4.3%
Hangul
ValueCountFrequency (%)
340
33.3%
340
33.3%
340
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1439
58.5%
Hangul 1020
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 474
32.9%
1 338
23.5%
2 101
 
7.0%
6 73
 
5.1%
9 68
 
4.7%
0 68
 
4.7%
3 67
 
4.7%
5 65
 
4.5%
4 63
 
4.4%
7 62
 
4.3%
Hangul
ValueCountFrequency (%)
340
33.3%
340
33.3%
340
33.3%

행정동
Categorical

Distinct10
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
청학동
91 
연수1동
64 
옥련1동
63 
선학동
52 
옥련2동
32 
Other values (5)
38 

Length

Max length4
Median length4
Mean length3.5735294
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row옥련1동
2nd row옥련1동
3rd row옥련1동
4th row옥련1동
5th row옥련1동

Common Values

ValueCountFrequency (%)
청학동 91
26.8%
연수1동 64
18.8%
옥련1동 63
18.5%
선학동 52
15.3%
옥련2동 32
 
9.4%
연수2동 17
 
5.0%
동춘1동 15
 
4.4%
동춘2동 2
 
0.6%
동춘동 2
 
0.6%
송도5동 2
 
0.6%

Length

2023-12-12T21:08:46.442652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:08:46.619961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청학동 91
26.8%
연수1동 64
18.8%
옥련1동 63
18.5%
선학동 52
15.3%
옥련2동 32
 
9.4%
연수2동 17
 
5.0%
동춘1동 15
 
4.4%
동춘2동 2
 
0.6%
동춘동 2
 
0.6%
송도5동 2
 
0.6%
Distinct204
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-12T21:08:46.974694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length41
Mean length28.626471
Min length17

Characters and Unicode

Total characters9733
Distinct characters299
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)25.9%

Sample

1st row인천광역시 연수구 옥련동 194-34 옥련백산2차아파트 입구
2nd row인천광역시 연수구 옥련동 194-34 옥련백산2차아파트 입구
3rd row인천광역시 연수구 옥련동 314-4 송도초등학교 후문 황제헤어 앞
4th row인천광역시 연수구 옥련동 314-4 송도초등학교 후문 황제헤어 앞
5th row인천광역시 연수구 옥련동 319-17 영남빌라 앞
ValueCountFrequency (%)
인천광역시 340
 
17.1%
연수구 340
 
17.1%
104
 
5.2%
청학동 83
 
4.2%
옥련동 76
 
3.8%
연수동 58
 
2.9%
선학동 39
 
2.0%
부근 32
 
1.6%
맞은편 28
 
1.4%
모퉁이 22
 
1.1%
Other values (442) 872
43.7%
2023-12-12T21:08:47.514462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1657
 
17.0%
435
 
4.5%
433
 
4.4%
397
 
4.1%
360
 
3.7%
356
 
3.7%
347
 
3.6%
345
 
3.5%
342
 
3.5%
340
 
3.5%
Other values (289) 4721
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6311
64.8%
Space Separator 1657
 
17.0%
Decimal Number 1426
 
14.7%
Dash Punctuation 284
 
2.9%
Uppercase Letter 29
 
0.3%
Open Punctuation 12
 
0.1%
Close Punctuation 12
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
435
 
6.9%
433
 
6.9%
397
 
6.3%
360
 
5.7%
356
 
5.6%
347
 
5.5%
345
 
5.5%
342
 
5.4%
340
 
5.4%
173
 
2.7%
Other values (264) 2783
44.1%
Decimal Number
ValueCountFrequency (%)
1 224
15.7%
5 206
14.4%
4 196
13.7%
3 159
11.2%
2 138
9.7%
6 106
7.4%
7 102
7.2%
9 101
7.1%
8 98
6.9%
0 96
6.7%
Uppercase Letter
ValueCountFrequency (%)
U 5
17.2%
G 5
17.2%
T 4
13.8%
C 3
10.3%
K 3
10.3%
S 3
10.3%
I 2
 
6.9%
N 2
 
6.9%
B 1
 
3.4%
D 1
 
3.4%
Space Separator
ValueCountFrequency (%)
1657
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 284
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6311
64.8%
Common 3393
34.9%
Latin 29
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
435
 
6.9%
433
 
6.9%
397
 
6.3%
360
 
5.7%
356
 
5.6%
347
 
5.5%
345
 
5.5%
342
 
5.4%
340
 
5.4%
173
 
2.7%
Other values (264) 2783
44.1%
Common
ValueCountFrequency (%)
1657
48.8%
- 284
 
8.4%
1 224
 
6.6%
5 206
 
6.1%
4 196
 
5.8%
3 159
 
4.7%
2 138
 
4.1%
6 106
 
3.1%
7 102
 
3.0%
9 101
 
3.0%
Other values (5) 220
 
6.5%
Latin
ValueCountFrequency (%)
U 5
17.2%
G 5
17.2%
T 4
13.8%
C 3
10.3%
K 3
10.3%
S 3
10.3%
I 2
 
6.9%
N 2
 
6.9%
B 1
 
3.4%
D 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6311
64.8%
ASCII 3422
35.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1657
48.4%
- 284
 
8.3%
1 224
 
6.5%
5 206
 
6.0%
4 196
 
5.7%
3 159
 
4.6%
2 138
 
4.0%
6 106
 
3.1%
7 102
 
3.0%
9 101
 
3.0%
Other values (15) 249
 
7.3%
Hangul
ValueCountFrequency (%)
435
 
6.9%
433
 
6.9%
397
 
6.3%
360
 
5.7%
356
 
5.6%
347
 
5.5%
345
 
5.5%
342
 
5.4%
340
 
5.4%
173
 
2.7%
Other values (264) 2783
44.1%

Missing values

2023-12-12T21:08:45.078329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:08:45.212610image/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

관리번호행정동설치장소
0폐기물-1옥련1동인천광역시 연수구 옥련동 194-34 옥련백산2차아파트 입구
1폐기물-1-1옥련1동인천광역시 연수구 옥련동 194-34 옥련백산2차아파트 입구
2폐기물-2옥련1동인천광역시 연수구 옥련동 314-4 송도초등학교 후문 황제헤어 앞
3폐기물-2-1옥련1동인천광역시 연수구 옥련동 314-4 송도초등학교 후문 황제헤어 앞
4폐기물-3옥련1동인천광역시 연수구 옥련동 319-17 영남빌라 앞
5폐기물-3-1옥련1동인천광역시 연수구 옥련동 319-17 영남빌라 앞
6폐기물-4옥련1동인천광역시 연수구 옥련동 327-21 송도초등학교 후문 주택가 사거리
7폐기물-4-1옥련1동인천광역시 연수구 옥련동 327-21 송도초등학교 후문 주택가 사거리
8폐기물-5옥련1동인천광역시 연수구 옥련동 643-1 옥련동주민센터 뒤편
9폐기물-5-1옥련1동인천광역시 연수구 옥련동 643-1 옥련동주민센터 뒤편
관리번호행정동설치장소
330폐기물-203청학동인천광역시 연수구 청학동 542-4 성산빌라 앞 중앙어린이공원 입구
331폐기물-204청학동인천광역시 연수구 청학동 540-10 주택 모퉁이
332폐기물-205청학동인천광역시 연수구 청학동 541-16 대야힐빌리지 6동 앞
333폐기물-206청학동인천광역시 연수구 청학동 90-11 청학동 공영주차장(2) 앞
334폐기물-207청학동인천광역시 연수구 청학동 562-9 행복주택 앞
335폐기물-208동춘1동인천광역시 연수구 동춘동 224-2 새명빌딩 주차장 앞
336폐기물-208-1동춘1동인천광역시 연수구 동춘동 224-2 새명빌딩 주차장 앞
337폐기물-209동춘1동인천광역시 연수구 동춘동 822 덕화요양원 앞
338폐기물-209-1동춘1동인천광역시 연수구 동춘동 822 덕화요양원 앞
339폐기물-210동춘1동인천광역시 연수구 동춘동 820-47 빌라 앞 삼거리