Overview

Dataset statistics

Number of variables4
Number of observations449
Missing cells0
Missing cells (%)0.0%
Duplicate rows7
Duplicate rows (%)1.6%
Total size in memory14.2 KiB
Average record size in memory32.3 B

Variable types

Categorical1
Text2
DateTime1

Dataset

Description서울특별시 광진구의 의류수거함 위치를 제공합니다.(행정동, 지번주소, 도로명주소, 데이터기준일 등의 정보를 제공합니다.)
Author서울특별시 광진구
URLhttps://www.data.go.kr/data/15109594/fileData.do

Alerts

기준일 has constant value ""Constant
Dataset has 7 (1.6%) duplicate rowsDuplicates

Reproduction

Analysis started2024-05-04 07:55:13.066614
Analysis finished2024-05-04 07:55:13.671371
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동
Categorical

Distinct15
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
중곡4동
58 
구의2동
52 
중곡2동
51 
자양2동
50 
자양1동
33 
Other values (10)
205 

Length

Max length4
Median length4
Mean length3.7461024
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중곡1동
2nd row중곡1동
3rd row중곡1동
4th row중곡1동
5th row중곡1동

Common Values

ValueCountFrequency (%)
중곡4동 58
12.9%
구의2동 52
11.6%
중곡2동 51
11.4%
자양2동 50
11.1%
자양1동 33
7.3%
군자동 32
7.1%
능동 25
 
5.6%
구의3동 24
 
5.3%
자양4동 23
 
5.1%
중곡1동 22
 
4.9%
Other values (5) 79
17.6%

Length

2024-05-04T07:55:13.923643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
중곡4동 58
12.9%
구의2동 52
11.6%
중곡2동 51
11.4%
자양2동 50
11.1%
자양1동 33
7.3%
군자동 32
7.1%
능동 25
 
5.6%
구의3동 24
 
5.3%
자양4동 23
 
5.1%
중곡1동 22
 
4.9%
Other values (5) 79
17.6%

지번주소
Text

Distinct441
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-05-04T07:55:14.754524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length9.169265
Min length6

Characters and Unicode

Total characters4117
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique433 ?
Unique (%)96.4%

Sample

1st row중곡동 645-8
2nd row중곡동 259-12
3rd row중곡동 258-9
4th row중곡동 257-13
5th row중곡동 244-27
ValueCountFrequency (%)
중곡동 148
 
16.5%
자양동 118
 
13.1%
구의동 94
 
10.5%
군자동 32
 
3.6%
능동 25
 
2.8%
광장동 17
 
1.9%
화양동 15
 
1.7%
617-31 2
 
0.2%
107-94 2
 
0.2%
643-5 2
 
0.2%
Other values (438) 444
49.4%
2024-05-04T07:55:16.135142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
452
 
11.0%
동 449
 
10.9%
- 412
 
10.0%
1 365
 
8.9%
2 288
 
7.0%
3 212
 
5.1%
6 208
 
5.1%
4 178
 
4.3%
5 177
 
4.3%
자 150
 
3.6%
Other values (17) 1226
29.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1928
46.8%
Other Letter 1324
32.2%
Space Separator 452
 
11.0%
Dash Punctuation 412
 
10.0%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 449
33.9%
자 150
 
11.3%
중 148
 
11.2%
곡 148
 
11.2%
양 133
 
10.0%
의 94
 
7.1%
구 94
 
7.1%
군 32
 
2.4%
능 25
 
1.9%
광 17
 
1.3%
Other values (4) 34
 
2.6%
Decimal Number
ValueCountFrequency (%)
1 365
18.9%
2 288
14.9%
3 212
11.0%
6 208
10.8%
4 178
9.2%
5 177
9.2%
7 129
 
6.7%
8 127
 
6.6%
9 125
 
6.5%
0 119
 
6.2%
Space Separator
ValueCountFrequency (%)
452
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 412
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2793
67.8%
Hangul 1324
32.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 449
33.9%
자 150
 
11.3%
중 148
 
11.2%
곡 148
 
11.2%
양 133
 
10.0%
의 94
 
7.1%
구 94
 
7.1%
군 32
 
2.4%
능 25
 
1.9%
광 17
 
1.3%
Other values (4) 34
 
2.6%
Common
ValueCountFrequency (%)
452
16.2%
- 412
14.8%
1 365
13.1%
2 288
10.3%
3 212
7.6%
6 208
7.4%
4 178
 
6.4%
5 177
 
6.3%
7 129
 
4.6%
8 127
 
4.5%
Other values (3) 245
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2793
67.8%
Hangul 1324
32.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
452
16.2%
- 412
14.8%
1 365
13.1%
2 288
10.3%
3 212
7.6%
6 208
7.4%
4 178
 
6.4%
5 177
 
6.3%
7 129
 
4.6%
8 127
 
4.5%
Other values (3) 245
8.8%
Hangul
ValueCountFrequency (%)
동 449
33.9%
자 150
 
11.3%
중 148
 
11.2%
곡 148
 
11.2%
양 133
 
10.0%
의 94
 
7.1%
구 94
 
7.1%
군 32
 
2.4%
능 25
 
1.9%
광 17
 
1.3%
Other values (4) 34
 
2.6%

도로명주소
Text

Distinct442
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-05-04T07:55:17.329803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length9.5991091
Min length5

Characters and Unicode

Total characters4310
Distinct characters69
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

Unique435 ?
Unique (%)96.9%

Sample

1st row천호대로107길 52-6
2nd row긴고랑로12길 59
3rd row능동로41길 30
4th row능동로41길 42
5th row능동로43길 38
ValueCountFrequency (%)
36 11
 
1.2%
33 11
 
1.2%
10 10
 
1.1%
25 9
 
1.0%
30 9
 
1.0%
용마산로 9
 
1.0%
40 8
 
0.9%
7 8
 
0.9%
34 8
 
0.9%
20 7
 
0.8%
Other values (433) 813
90.0%
2024-05-04T07:55:19.188416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
456
 
10.6%
로 449
 
10.4%
길 388
 
9.0%
1 307
 
7.1%
2 261
 
6.1%
3 258
 
6.0%
4 186
 
4.3%
5 171
 
4.0%
6 127
 
2.9%
8 117
 
2.7%
Other values (59) 1590
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2062
47.8%
Decimal Number 1729
40.1%
Space Separator 456
 
10.6%
Dash Punctuation 63
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 449
21.8%
길 388
18.8%
동 87
 
4.2%
자 83
 
4.0%
양 83
 
4.0%
산 78
 
3.8%
능 64
 
3.1%
뚝 52
 
2.5%
섬 52
 
2.5%
마 50
 
2.4%
Other values (47) 676
32.8%
Decimal Number
ValueCountFrequency (%)
1 307
17.8%
2 261
15.1%
3 258
14.9%
4 186
10.8%
5 171
9.9%
6 127
7.3%
8 117
 
6.8%
7 114
 
6.6%
0 103
 
6.0%
9 85
 
4.9%
Space Separator
ValueCountFrequency (%)
456
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2248
52.2%
Hangul 2062
47.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 449
21.8%
길 388
18.8%
동 87
 
4.2%
자 83
 
4.0%
양 83
 
4.0%
산 78
 
3.8%
능 64
 
3.1%
뚝 52
 
2.5%
섬 52
 
2.5%
마 50
 
2.4%
Other values (47) 676
32.8%
Common
ValueCountFrequency (%)
456
20.3%
1 307
13.7%
2 261
11.6%
3 258
11.5%
4 186
8.3%
5 171
 
7.6%
6 127
 
5.6%
8 117
 
5.2%
7 114
 
5.1%
0 103
 
4.6%
Other values (2) 148
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2248
52.2%
Hangul 2062
47.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
456
20.3%
1 307
13.7%
2 261
11.6%
3 258
11.5%
4 186
8.3%
5 171
 
7.6%
6 127
 
5.6%
8 117
 
5.2%
7 114
 
5.1%
0 103
 
4.6%
Other values (2) 148
 
6.6%
Hangul
ValueCountFrequency (%)
로 449
21.8%
길 388
18.8%
동 87
 
4.2%
자 83
 
4.0%
양 83
 
4.0%
산 78
 
3.8%
능 64
 
3.1%
뚝 52
 
2.5%
섬 52
 
2.5%
마 50
 
2.4%
Other values (47) 676
32.8%

기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum2024-04-12 00:00:00
Maximum2024-04-12 00:00:00
2024-05-04T07:55:19.874477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:55:20.392123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-05-04T07:55:13.329301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T07:55:13.559700image/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

행정동지번주소도로명주소기준일
0중곡1동중곡동 645-8천호대로107길 52-62024-04-12
1중곡1동중곡동 259-12긴고랑로12길 592024-04-12
2중곡1동중곡동 258-9능동로41길 302024-04-12
3중곡1동중곡동 257-13능동로41길 422024-04-12
4중곡1동중곡동 244-27능동로43길 382024-04-12
5중곡1동중곡동 244-33능동로43길 38-132024-04-12
6중곡1동중곡동 162-22긴고랑로14길 332024-04-12
7중곡1동중곡동 163-5능동로 3632024-04-12
8중곡1동중곡동 163-7능동로 3552024-04-12
9중곡1동중곡동 646-6천호대로107길 362024-04-12
행정동지번주소도로명주소기준일
439군자동군자동 117-36동일로52길 3-42024-04-12
440군자동군자동 473-21천호대로 5382024-04-12
441군자동군자동 367-1광나루로19길 512024-04-12
442군자동군자동 300능동로23길 11-62024-04-12
443군자동군자동 90-20능동로21길 482024-04-12
444군자동군자동 290능동로21길 332024-04-12
445군자동군자동 149-12능동로21길 652024-04-12
446군자동군자동 300능동로23길 11-62024-04-12
447군자동군자동 229능동로23길 262024-04-12
448군자동군자동 361-23광나루로 3852024-04-12

Duplicate rows

Most frequently occurring

행정동지번주소도로명주소기준일# duplicates
0구의2동구의동 34-1자양로50길 662024-04-122
1구의2동구의동 617-31자양로33길 412024-04-122
2군자동군자동 300능동로23길 11-62024-04-122
3군자동군자동 361-23광나루로 3852024-04-122
4자양1동자양동 862자양로 552024-04-122
5중곡2동중곡동 150-138긴고랑로29길 242024-04-122
6중곡4동중곡동 107-94영화사로9길 452024-04-122