Overview

Dataset statistics

Number of variables6
Number of observations108
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory52.2 B

Variable types

Categorical3
Text1
Numeric1
DateTime1

Dataset

Description전라북도 정읍시에 소재한 현수막 지정게시대 현황중(읍면동, 위치, 규격, 게시면수 상업용, 게시면수 행정용)등의 자료를 제공합니다.
Author전라북도 정읍시
URLhttps://www.data.go.kr/data/15025500/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
게시면수(상업용) is highly overall correlated with 게시면수(행정용)High correlation
읍면동 is highly overall correlated with 규격(m)High correlation
규격(m) is highly overall correlated with 읍면동High correlation
게시면수(행정용) is highly overall correlated with 게시면수(상업용)High correlation
게시면수(상업용) has 19 (17.6%) zerosZeros

Reproduction

Analysis started2023-12-16 15:53:24.385046
Analysis finished2023-12-16 15:53:27.628614
Duration3.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size996.0 B
수성동
22 
초산동
8 
농소동
8 
연지동
7 
신태인읍
6 
Other values (18)
57 

Length

Max length4
Median length3
Mean length3.0648148
Min length2

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
수성동 22
20.4%
초산동 8
 
7.4%
농소동 8
 
7.4%
연지동 7
 
6.5%
신태인읍 6
 
5.6%
내장상동 6
 
5.6%
상교동 6
 
5.6%
북면 5
 
4.6%
시기동 5
 
4.6%
태인면 4
 
3.7%
Other values (13) 31
28.7%

Length

2023-12-16T15:53:28.150052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수성동 22
20.4%
농소동 8
 
7.4%
초산동 8
 
7.4%
연지동 7
 
6.5%
신태인읍 6
 
5.6%
내장상동 6
 
5.6%
상교동 6
 
5.6%
북면 5
 
4.6%
시기동 5
 
4.6%
태인면 4
 
3.7%
Other values (13) 31
28.7%

위치
Text

Distinct92
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-16T15:53:29.831901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.6203704
Min length3

Characters and Unicode

Total characters607
Distinct characters119
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)82.4%

Sample

1st row한진A사거리
2nd row공단사거리
3rd row파출소
4th row실내(좌)체육관
5th row실내(우)체육관
ValueCountFrequency (%)
면사무소 9
 
8.3%
주민센터 8
 
7.4%
파출소 2
 
1.9%
한진a사거리 1
 
0.9%
정읍고 1
 
0.9%
삼화그린아파트 1
 
0.9%
성림(우)사거리 1
 
0.9%
성림(좌)사거리 1
 
0.9%
시기파출소 1
 
0.9%
내장터미널 1
 
0.9%
Other values (82) 82
75.9%
2023-12-16T15:53:32.555278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 48
 
7.9%
) 48
 
7.9%
우 21
 
3.5%
좌 21
 
3.5%
소 20
 
3.3%
사 20
 
3.3%
리 15
 
2.5%
주 15
 
2.5%
거 14
 
2.3%
무 12
 
2.0%
Other values (109) 373
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 495
81.5%
Open Punctuation 48
 
7.9%
Close Punctuation 48
 
7.9%
Uppercase Letter 11
 
1.8%
Decimal Number 5
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
우 21
 
4.2%
좌 21
 
4.2%
소 20
 
4.0%
사 20
 
4.0%
리 15
 
3.0%
주 15
 
3.0%
거 14
 
2.8%
무 12
 
2.4%
터 12
 
2.4%
교 11
 
2.2%
Other values (102) 334
67.5%
Uppercase Letter
ValueCountFrequency (%)
C 4
36.4%
I 4
36.4%
A 3
27.3%
Decimal Number
ValueCountFrequency (%)
2 4
80.0%
1 1
 
20.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 495
81.5%
Common 101
 
16.6%
Latin 11
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
우 21
 
4.2%
좌 21
 
4.2%
소 20
 
4.0%
사 20
 
4.0%
리 15
 
3.0%
주 15
 
3.0%
거 14
 
2.8%
무 12
 
2.4%
터 12
 
2.4%
교 11
 
2.2%
Other values (102) 334
67.5%
Common
ValueCountFrequency (%)
( 48
47.5%
) 48
47.5%
2 4
 
4.0%
1 1
 
1.0%
Latin
ValueCountFrequency (%)
C 4
36.4%
I 4
36.4%
A 3
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 495
81.5%
ASCII 112
 
18.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 48
42.9%
) 48
42.9%
C 4
 
3.6%
I 4
 
3.6%
2 4
 
3.6%
A 3
 
2.7%
1 1
 
0.9%
Hangul
ValueCountFrequency (%)
우 21
 
4.2%
좌 21
 
4.2%
소 20
 
4.0%
사 20
 
4.0%
리 15
 
3.0%
주 15
 
3.0%
거 14
 
2.8%
무 12
 
2.4%
터 12
 
2.4%
교 11
 
2.2%
Other values (102) 334
67.5%

규격(m)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size996.0 B
6.0
77 
5.5
31 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6.0
2nd row6.0
3rd row6.0
4th row6.0
5th row6.0

Common Values

ValueCountFrequency (%)
6.0 77
71.3%
5.5 31
28.7%

Length

2023-12-16T15:53:33.291713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:53:33.780521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6.0 77
71.3%
5.5 31
28.7%

게시면수(상업용)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8981481
Minimum0
Maximum6
Zeros19
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-16T15:53:34.311422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median5
Q35
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.0641117
Coefficient of variation (CV)0.52951085
Kurtosis-0.4026573
Mean3.8981481
Median Absolute Deviation (MAD)1
Skewness-0.99136875
Sum421
Variance4.2605573
MonotonicityNot monotonic
2023-12-16T15:53:35.214519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 41
38.0%
6 21
19.4%
0 19
17.6%
4 14
 
13.0%
3 8
 
7.4%
2 5
 
4.6%
ValueCountFrequency (%)
0 19
17.6%
2 5
 
4.6%
3 8
 
7.4%
4 14
 
13.0%
5 41
38.0%
6 21
19.4%
ValueCountFrequency (%)
6 21
19.4%
5 41
38.0%
4 14
 
13.0%
3 8
 
7.4%
2 5
 
4.6%
0 19
17.6%

게시면수(행정용)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size996.0 B
0
70 
2
18 
6
10 
5
9 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row0
2nd row0
3rd row2
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 70
64.8%
2 18
 
16.7%
6 10
 
9.3%
5 9
 
8.3%
3 1
 
0.9%

Length

2023-12-16T15:53:35.929543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:53:36.553303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 70
64.8%
2 18
 
16.7%
6 10
 
9.3%
5 9
 
8.3%
3 1
 
0.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size996.0 B
Minimum2022-12-15 00:00:00
Maximum2022-12-15 00:00:00
2023-12-16T15:53:37.141005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:53:37.777050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-16T15:53:25.724374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-16T15:53:38.196035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동위치규격(m)게시면수(상업용)게시면수(행정용)
읍면동1.0000.0000.7730.1490.200
위치0.0001.0000.0000.0000.000
규격(m)0.7730.0001.0000.3690.187
게시면수(상업용)0.1490.0000.3691.0000.777
게시면수(행정용)0.2000.0000.1870.7771.000
2023-12-16T15:53:38.603208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동게시면수(행정용)규격(m)
읍면동1.0000.0790.622
게시면수(행정용)0.0791.0000.224
규격(m)0.6220.2241.000
2023-12-16T15:53:38.968977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
게시면수(상업용)읍면동규격(m)게시면수(행정용)
게시면수(상업용)1.0000.0430.2600.655
읍면동0.0431.0000.6220.079
규격(m)0.2600.6221.0000.224
게시면수(행정용)0.6550.0790.2241.000

Missing values

2023-12-16T15:53:26.504411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:53:27.257969image/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

읍면동위치규격(m)게시면수(상업용)게시면수(행정용)데이터기준일자
0신태인읍한진A사거리6.0602022-12-15
1신태인읍공단사거리6.0602022-12-15
2신태인읍파출소6.0222022-12-15
3신태인읍실내(좌)체육관6.0502022-12-15
4신태인읍실내(우)체육관6.0502022-12-15
5신태인읍신태인시장6.0422022-12-15
6북면회전교차로(좌)6.0502022-12-15
7북면회전교차로(중)6.0502022-12-15
8북면회전교차로(우)6.0502022-12-15
9북면캐스코앞6.0502022-12-15
읍면동위치규격(m)게시면수(상업용)게시면수(행정용)데이터기준일자
98농소동농소주공옆6.0402022-12-15
99농소동도매시장6.0322022-12-15
100농소동덕천공단6.0502022-12-15
101농소동주천삼거리6.0602022-12-15
102상교동신정사거리6.0502022-12-15
103상교동주민센터6.0062022-12-15
104상교동정읍체육센터6.0602022-12-15
105상교동연지교(좌)6.0052022-12-15
106상교동연지교(중)6.0502022-12-15
107상교동연지교(우)6.0502022-12-15