Overview

Dataset statistics

Number of variables5
Number of observations390
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.1 KiB
Average record size in memory42.3 B

Variable types

Text2
Categorical3

Dataset

Description울산광역시 울주군의 제설함 설치 현황에 대한 데이터로 노선명, 위치, 제설함수량, 염화칼슘량, 모래량 등의 정보를 제공합니다.
Author울산광역시 울주군
URLhttps://www.data.go.kr/data/15054876/fileData.do

Alerts

염화칼슘(포) has constant value ""Constant
모래주머니(포) has constant value ""Constant
데이터기준일자 has constant value ""Constant
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:13:22.436130
Analysis finished2023-12-11 23:13:22.837179
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct390
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T08:13:23.111823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2340
Distinct characters28
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

Unique390 ?
Unique (%)100.0%

Sample

1st row범서-001
2nd row범서-002
3rd row범서-003
4th row범서-004
5th row범서-005
ValueCountFrequency (%)
범서-001 1
 
0.3%
상북-020 1
 
0.3%
상북-042 1
 
0.3%
상북-041 1
 
0.3%
상북-040 1
 
0.3%
상북-039 1
 
0.3%
상북-038 1
 
0.3%
상북-037 1
 
0.3%
상북-036 1
 
0.3%
상북-035 1
 
0.3%
Other values (380) 380
97.4%
2023-12-12T08:13:23.567195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 524
22.4%
- 390
16.7%
1 130
 
5.6%
동 119
 
5.1%
2 100
 
4.3%
삼 100
 
4.3%
3 91
 
3.9%
북 83
 
3.5%
상 83
 
3.5%
4 75
 
3.2%
Other values (18) 645
27.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1170
50.0%
Other Letter 780
33.3%
Dash Punctuation 390
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 119
15.3%
삼 100
12.8%
북 83
10.6%
상 83
10.6%
서 70
9.0%
촌 47
 
6.0%
두 47
 
6.0%
웅 47
 
6.0%
범 46
 
5.9%
양 28
 
3.6%
Other values (7) 110
14.1%
Decimal Number
ValueCountFrequency (%)
0 524
44.8%
1 130
 
11.1%
2 100
 
8.5%
3 91
 
7.8%
4 75
 
6.4%
5 60
 
5.1%
6 58
 
5.0%
7 56
 
4.8%
8 42
 
3.6%
9 34
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 390
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1560
66.7%
Hangul 780
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 119
15.3%
삼 100
12.8%
북 83
10.6%
상 83
10.6%
서 70
9.0%
촌 47
 
6.0%
두 47
 
6.0%
웅 47
 
6.0%
범 46
 
5.9%
양 28
 
3.6%
Other values (7) 110
14.1%
Common
ValueCountFrequency (%)
0 524
33.6%
- 390
25.0%
1 130
 
8.3%
2 100
 
6.4%
3 91
 
5.8%
4 75
 
4.8%
5 60
 
3.8%
6 58
 
3.7%
7 56
 
3.6%
8 42
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1560
66.7%
Hangul 780
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 524
33.6%
- 390
25.0%
1 130
 
8.3%
2 100
 
6.4%
3 91
 
5.8%
4 75
 
4.8%
5 60
 
3.8%
6 58
 
3.7%
7 56
 
3.6%
8 42
 
2.7%
Hangul
ValueCountFrequency (%)
동 119
15.3%
삼 100
12.8%
북 83
10.6%
상 83
10.6%
서 70
9.0%
촌 47
 
6.0%
두 47
 
6.0%
웅 47
 
6.0%
범 46
 
5.9%
양 28
 
3.6%
Other values (7) 110
14.1%

위치
Text

Distinct353
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T08:13:23.974592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.2641026
Min length6

Characters and Unicode

Total characters3613
Distinct characters90
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

Unique321 ?
Unique (%)82.3%

Sample

1st row굴화리 165-10
2nd row굴화리 165-12
3rd row굴화리 741
4th row굴화리 734
5th row굴화리 734
ValueCountFrequency (%)
산 71
 
8.3%
덕현리 55
 
6.4%
조일리 35
 
4.1%
삼정리 19
 
2.2%
곡천리 16
 
1.9%
구영리 16
 
1.9%
출강리 15
 
1.8%
작동리 14
 
1.6%
하잠리 14
 
1.6%
이천리 13
 
1.5%
Other values (395) 585
68.6%
2023-12-12T08:13:24.488136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
470
 
13.0%
리 388
 
10.7%
1 315
 
8.7%
- 310
 
8.6%
산 201
 
5.6%
2 191
 
5.3%
3 154
 
4.3%
4 154
 
4.3%
5 125
 
3.5%
7 119
 
3.3%
Other values (80) 1186
32.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1454
40.2%
Other Letter 1379
38.2%
Space Separator 470
 
13.0%
Dash Punctuation 310
 
8.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 388
28.1%
산 201
14.6%
천 64
 
4.6%
덕 58
 
4.2%
현 56
 
4.1%
일 38
 
2.8%
조 36
 
2.6%
정 32
 
2.3%
화 28
 
2.0%
대 25
 
1.8%
Other values (68) 453
32.8%
Decimal Number
ValueCountFrequency (%)
1 315
21.7%
2 191
13.1%
3 154
10.6%
4 154
10.6%
5 125
 
8.6%
7 119
 
8.2%
8 116
 
8.0%
6 102
 
7.0%
9 89
 
6.1%
0 89
 
6.1%
Space Separator
ValueCountFrequency (%)
470
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 310
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2234
61.8%
Hangul 1379
38.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 388
28.1%
산 201
14.6%
천 64
 
4.6%
덕 58
 
4.2%
현 56
 
4.1%
일 38
 
2.8%
조 36
 
2.6%
정 32
 
2.3%
화 28
 
2.0%
대 25
 
1.8%
Other values (68) 453
32.8%
Common
ValueCountFrequency (%)
470
21.0%
1 315
14.1%
- 310
13.9%
2 191
8.5%
3 154
 
6.9%
4 154
 
6.9%
5 125
 
5.6%
7 119
 
5.3%
8 116
 
5.2%
6 102
 
4.6%
Other values (2) 178
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2234
61.8%
Hangul 1379
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
470
21.0%
1 315
14.1%
- 310
13.9%
2 191
8.5%
3 154
 
6.9%
4 154
 
6.9%
5 125
 
5.6%
7 119
 
5.3%
8 116
 
5.2%
6 102
 
4.6%
Other values (2) 178
 
8.0%
Hangul
ValueCountFrequency (%)
리 388
28.1%
산 201
14.6%
천 64
 
4.6%
덕 58
 
4.2%
현 56
 
4.1%
일 38
 
2.8%
조 36
 
2.6%
정 32
 
2.3%
화 28
 
2.0%
대 25
 
1.8%
Other values (68) 453
32.8%

염화칼슘(포)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
5
390 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 390
100.0%

Length

2023-12-12T08:13:24.604182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:13:24.683282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 390
100.0%

모래주머니(포)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
10
390 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10
2nd row10
3rd row10
4th row10
5th row10

Common Values

ValueCountFrequency (%)
10 390
100.0%

Length

2023-12-12T08:13:25.035670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:13:25.122308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 390
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-09-15
390 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-15
2nd row2023-09-15
3rd row2023-09-15
4th row2023-09-15
5th row2023-09-15

Common Values

ValueCountFrequency (%)
2023-09-15 390
100.0%

Length

2023-12-12T08:13:25.207551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:13:25.301756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-15 390
100.0%

Missing values

2023-12-12T08:13:22.650120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:13:22.787625image/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

관리번호위치염화칼슘(포)모래주머니(포)데이터기준일자
0범서-001굴화리 165-105102023-09-15
1범서-002굴화리 165-125102023-09-15
2범서-003굴화리 7415102023-09-15
3범서-004굴화리 7345102023-09-15
4범서-005굴화리 7345102023-09-15
5범서-006굴화리 7345102023-09-15
6범서-007굴화리 162-15102023-09-15
7범서-008굴화리 산75-155102023-09-15
8범서-009굴화리 5495102023-09-15
9범서-010굴화리 705-75102023-09-15
관리번호위치염화칼슘(포)모래주머니(포)데이터기준일자
380삼동-074조일리 3205102023-09-15
381삼동-075조일리 산 288-55102023-09-15
382삼동-076조일리 4555102023-09-15
383삼동-077조일리 4635102023-09-15
384삼동-078조일리 산 1145102023-09-15
385삼동-079조일리 1406-55102023-09-15
386삼동-080조일리 1406-155102023-09-15
387삼동-081둔기리 산 297-35102023-09-15
388삼동-082둔기리 산 279-25102023-09-15
389삼동-083둔기리 437-75102023-09-15