Overview

Dataset statistics

Number of variables5
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory44.2 B

Variable types

Text2
Categorical2
Numeric1

Dataset

Description인천광역시 계양구 관내 현수막 지정 게시대 현황에 대한 데이터로, 게시대 명칭, 게시대 위치, 행정동 구분, 게시대 수, 설치연도 등을 제공합니다.
Author인천광역시 계양구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15038061&srcSe=7661IVAWM27C61E190

Alerts

게시대수 has constant value ""Constant
게시대명칭 has unique valuesUnique

Reproduction

Analysis started2024-01-28 17:18:17.583657
Analysis finished2024-01-28 17:18:18.053992
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

게시대명칭
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-01-29T02:18:18.181166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length10.783333
Min length5

Characters and Unicode

Total characters647
Distinct characters145
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row효성사거리
2nd row새말사거리(풍산금속옆)
3rd row효성동유승A(옆)
4th row북인천여중(옆)
5th row새말사거리엠코코리아(옆)
ValueCountFrequency (%)
앞 3
 
3.9%
작전역 2
 
2.6%
공영주차장 2
 
2.6%
임학사거리롯데마트(옆 1
 
1.3%
교통연수원(옆 1
 
1.3%
옆 1
 
1.3%
버스정류장 1
 
1.3%
계산풀장입구 1
 
1.3%
장기동사거리 1
 
1.3%
박촌삼거리 1
 
1.3%
Other values (63) 63
81.8%
2024-01-29T02:18:18.454126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 52
 
8.0%
) 52
 
8.0%
옆 23
 
3.6%
18
 
2.8%
리 17
 
2.6%
동 16
 
2.5%
건 16
 
2.5%
너 16
 
2.5%
계 15
 
2.3%
거 14
 
2.2%
Other values (135) 408
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 491
75.9%
Open Punctuation 52
 
8.0%
Close Punctuation 52
 
8.0%
Uppercase Letter 24
 
3.7%
Space Separator 18
 
2.8%
Decimal Number 9
 
1.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
옆 23
 
4.7%
리 17
 
3.5%
동 16
 
3.3%
건 16
 
3.3%
너 16
 
3.3%
계 15
 
3.1%
거 14
 
2.9%
양 14
 
2.9%
앞 13
 
2.6%
공 12
 
2.4%
Other values (121) 335
68.2%
Uppercase Letter
ValueCountFrequency (%)
A 13
54.2%
C 5
 
20.8%
I 4
 
16.7%
G 1
 
4.2%
V 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 5
55.6%
3 1
 
11.1%
4 1
 
11.1%
5 1
 
11.1%
2 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 491
75.9%
Common 132
 
20.4%
Latin 24
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
옆 23
 
4.7%
리 17
 
3.5%
동 16
 
3.3%
건 16
 
3.3%
너 16
 
3.3%
계 15
 
3.1%
거 14
 
2.9%
양 14
 
2.9%
앞 13
 
2.6%
공 12
 
2.4%
Other values (121) 335
68.2%
Common
ValueCountFrequency (%)
( 52
39.4%
) 52
39.4%
18
 
13.6%
1 5
 
3.8%
3 1
 
0.8%
4 1
 
0.8%
5 1
 
0.8%
@ 1
 
0.8%
2 1
 
0.8%
Latin
ValueCountFrequency (%)
A 13
54.2%
C 5
 
20.8%
I 4
 
16.7%
G 1
 
4.2%
V 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 491
75.9%
ASCII 156
 
24.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 52
33.3%
) 52
33.3%
18
 
11.5%
A 13
 
8.3%
C 5
 
3.2%
1 5
 
3.2%
I 4
 
2.6%
3 1
 
0.6%
4 1
 
0.6%
5 1
 
0.6%
Other values (4) 4
 
2.6%
Hangul
ValueCountFrequency (%)
옆 23
 
4.7%
리 17
 
3.5%
동 16
 
3.3%
건 16
 
3.3%
너 16
 
3.3%
계 15
 
3.1%
거 14
 
2.9%
양 14
 
2.9%
앞 13
 
2.6%
공 12
 
2.4%
Other values (121) 335
68.2%

게시대위치
Text

Distinct54
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-01-29T02:18:18.651862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length19.566667
Min length17

Characters and Unicode

Total characters1174
Distinct characters42
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

Unique50 ?
Unique (%)83.3%

Sample

1st row인천광역시 계양구 효성동 324-4
2nd row인천광역시 계양구 효성동 327-15번지
3rd row인천광역시 계양구 효성동 556번지
4th row인천광역시 계양구 효성동 558번지
5th row인천광역시 계양구 효성동 537번지
ValueCountFrequency (%)
인천광역시 60
25.0%
계양구 60
25.0%
작전동 18
 
7.5%
계산동 12
 
5.0%
용종동 11
 
4.6%
효성동 6
 
2.5%
박촌동 3
 
1.2%
서운동 3
 
1.2%
병방동 3
 
1.2%
238번지 3
 
1.2%
Other values (57) 61
25.4%
2024-01-29T02:18:18.976373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
180
15.3%
계 72
 
6.1%
동 61
 
5.2%
양 61
 
5.2%
인 60
 
5.1%
광 60
 
5.1%
역 60
 
5.1%
시 60
 
5.1%
구 60
 
5.1%
천 60
 
5.1%
Other values (32) 440
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 760
64.7%
Decimal Number 214
 
18.2%
Space Separator 180
 
15.3%
Dash Punctuation 20
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 72
9.5%
동 61
 
8.0%
양 61
 
8.0%
인 60
 
7.9%
광 60
 
7.9%
역 60
 
7.9%
시 60
 
7.9%
구 60
 
7.9%
천 60
 
7.9%
번 50
 
6.6%
Other values (20) 156
20.5%
Decimal Number
ValueCountFrequency (%)
1 39
18.2%
2 33
15.4%
4 25
11.7%
5 23
10.7%
8 22
10.3%
3 20
9.3%
0 18
8.4%
7 16
7.5%
9 9
 
4.2%
6 9
 
4.2%
Space Separator
ValueCountFrequency (%)
180
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 760
64.7%
Common 414
35.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 72
9.5%
동 61
 
8.0%
양 61
 
8.0%
인 60
 
7.9%
광 60
 
7.9%
역 60
 
7.9%
시 60
 
7.9%
구 60
 
7.9%
천 60
 
7.9%
번 50
 
6.6%
Other values (20) 156
20.5%
Common
ValueCountFrequency (%)
180
43.5%
1 39
 
9.4%
2 33
 
8.0%
4 25
 
6.0%
5 23
 
5.6%
8 22
 
5.3%
- 20
 
4.8%
3 20
 
4.8%
0 18
 
4.3%
7 16
 
3.9%
Other values (2) 18
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 760
64.7%
ASCII 414
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180
43.5%
1 39
 
9.4%
2 33
 
8.0%
4 25
 
6.0%
5 23
 
5.6%
8 22
 
5.3%
- 20
 
4.8%
3 20
 
4.8%
0 18
 
4.3%
7 16
 
3.9%
Other values (2) 18
 
4.3%
Hangul
ValueCountFrequency (%)
계 72
9.5%
동 61
 
8.0%
양 61
 
8.0%
인 60
 
7.9%
광 60
 
7.9%
역 60
 
7.9%
시 60
 
7.9%
구 60
 
7.9%
천 60
 
7.9%
번 50
 
6.6%
Other values (20) 156
20.5%

행정동
Categorical

Distinct19
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
계산동
12 
작전1동
9 
효성2동
5 
계산3동
5 
동양동
4 
Other values (14)
25 

Length

Max length4
Median length3
Mean length3.4666667
Min length3

Unique

Unique7 ?
Unique (%)11.7%

Sample

1st row효성2동
2nd row효성2동
3rd row효성2동
4th row효성2동
5th row효성2동

Common Values

ValueCountFrequency (%)
계산동 12
20.0%
작전1동 9
15.0%
효성2동 5
8.3%
계산3동 5
8.3%
동양동 4
 
6.7%
용종동 4
 
6.7%
서운동 3
 
5.0%
작전3동 3
 
5.0%
작전2동 2
 
3.3%
작전동 2
 
3.3%
Other values (9) 11
18.3%

Length

2024-01-29T02:18:19.088267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계산동 12
20.0%
작전1동 9
15.0%
효성2동 5
8.3%
계산3동 5
8.3%
동양동 4
 
6.7%
용종동 4
 
6.7%
서운동 3
 
5.0%
작전3동 3
 
5.0%
병방동 2
 
3.3%
계산1동 2
 
3.3%
Other values (9) 11
18.3%

게시대수
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
6
60 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6
2nd row6
3rd row6
4th row6
5th row6

Common Values

ValueCountFrequency (%)
6 60
100.0%

Length

2024-01-29T02:18:19.186447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:18:19.267660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6 60
100.0%

설치연도
Real number (ℝ)

Distinct6
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.95
Minimum2015
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-01-29T02:18:19.331776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015.95
Q12016
median2017
Q32017
95-th percentile2020
Maximum2021
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2271643
Coefficient of variation (CV)0.00060842574
Kurtosis2.6969861
Mean2016.95
Median Absolute Deviation (MAD)0
Skewness1.521218
Sum121017
Variance1.5059322
MonotonicityNot monotonic
2024-01-29T02:18:19.414319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2017 33
55.0%
2016 17
28.3%
2020 4
 
6.7%
2015 3
 
5.0%
2019 2
 
3.3%
2021 1
 
1.7%
ValueCountFrequency (%)
2015 3
 
5.0%
2016 17
28.3%
2017 33
55.0%
2019 2
 
3.3%
2020 4
 
6.7%
2021 1
 
1.7%
ValueCountFrequency (%)
2021 1
 
1.7%
2020 4
 
6.7%
2019 2
 
3.3%
2017 33
55.0%
2016 17
28.3%
2015 3
 
5.0%

Interactions

2024-01-29T02:18:17.810542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T02:18:19.483786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
게시대명칭게시대위치행정동설치연도
게시대명칭1.0001.0001.0001.000
게시대위치1.0001.0000.9780.918
행정동1.0000.9781.0000.000
설치연도1.0000.9180.0001.000
2024-01-29T02:18:19.562978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치연도행정동
설치연도1.0000.000
행정동0.0001.000

Missing values

2024-01-29T02:18:17.930262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:18:18.025412image/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

게시대명칭게시대위치행정동게시대수설치연도
0효성사거리인천광역시 계양구 효성동 324-4효성2동62017
1새말사거리(풍산금속옆)인천광역시 계양구 효성동 327-15번지효성2동62017
2효성동유승A(옆)인천광역시 계양구 효성동 556번지효성2동62016
3북인천여중(옆)인천광역시 계양구 효성동 558번지효성2동62016
4새말사거리엠코코리아(옆)인천광역시 계양구 효성동 537번지효성2동62017
5구일빌딩(뒤)인천광역시 계양구 효성동 61번지효성1동62017
6부평IC계산중앙교회(옆)인천광역시 계양구 작전동 478-3번지작전1동62017
7부평IC하이마트(앞)인천광역시 계양구 작전동 471번지작전1동62017
8안남고교(앞)인천광역시 계양구 작전동 412번지작전1동62016
9서운중(옆)삼거리인천광역시 계양구 서운동 55-262번지서운동62016
게시대명칭게시대위치행정동게시대수설치연도
50동양동 주공1단지(옆)인천광역시 계양구 동양동 591-2번지동양동62017
51하야동(벌말)고속도로교각하부인천광역시 계양구 하야동 68-3번지하야동62017
52계양경기장 앞인천광역시 계양구 계산동 1107계산동62015
53임학사거리(서해아파트 건너)인천광역시 계양구 용종동 206용종동62015
54계양역 공영주차장앞인천광역시 계양구 귤현동 451-100귤현동62016
55작전역 4번출구 공영주차장 앞인천광역시 계양구 작전동 887작전동62017
56작전역 5번출구 공영주차장 앞인천광역시 계양구 작전동 878작전동62017
57계양포도원 방면 삼거리인천광역시 계양구 병방동 441병방동62020
58버스정류장 옆인천광역시 계양구 서운동 225서운동62020
59서운산업단지 남측입구인천광역시 계양구 서운동 218서운동62021