Overview

Dataset statistics

Number of variables5
Number of observations162
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.6 KiB
Average record size in memory41.8 B

Variable types

Categorical2
Numeric1
Text1
DateTime1

Dataset

Description제주특별자치도 제주시 관내 홍보 가능 현수막 게시대 관련 현황 데이터를 제공합니다. 항목 : 구분, 지역, 관리번호, 장소
URLhttps://www.data.go.kr/data/3082905/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
관리번호 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
지역 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:26:44.679114
Analysis finished2023-12-12 14:26:45.132252
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
구형
132 
신형
30 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구형 132
81.5%
신형 30
 
18.5%

Length

2023-12-12T23:26:45.209013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:26:45.324926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구형 132
81.5%
신형 30
 
18.5%

지역
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
노형동
28 
오라동
16 
구좌읍
12 
한림읍
12 
화북동
11 
Other values (19)
83 

Length

Max length3
Median length3
Mean length2.9382716
Min length2

Unique

Unique2 ?
Unique (%)1.2%

Sample

1st row외도동
2nd row외도동
3rd row외도동
4th row내도동
5th row이호동

Common Values

ValueCountFrequency (%)
노형동 28
17.3%
오라동 16
 
9.9%
구좌읍 12
 
7.4%
한림읍 12
 
7.4%
화북동 11
 
6.8%
연동 10
 
6.2%
애월읍 9
 
5.6%
조천읍 8
 
4.9%
일도동 7
 
4.3%
건입동 7
 
4.3%
Other values (14) 42
25.9%

Length

2023-12-12T23:26:45.445023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노형동 28
17.3%
오라동 16
 
9.9%
구좌읍 12
 
7.4%
한림읍 12
 
7.4%
화북동 11
 
6.8%
연동 10
 
6.2%
애월읍 9
 
5.6%
조천읍 8
 
4.9%
일도동 7
 
4.3%
건입동 7
 
4.3%
Other values (14) 42
25.9%

관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct162
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.388889
Minimum1
Maximum302
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T23:26:45.599662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.05
Q143.25
median83.5
Q3123.75
95-th percentile221.95
Maximum302
Range301
Interquartile range (IQR)80.5

Descriptive statistics

Standard deviation69.758434
Coefficient of variation (CV)0.72371862
Kurtosis-0.12782395
Mean96.388889
Median Absolute Deviation (MAD)40.5
Skewness0.8169205
Sum15615
Variance4866.2391
MonotonicityNot monotonic
2023-12-12T23:26:45.765711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
123 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
112 1
 
0.6%
Other values (152) 152
93.8%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
302 1
0.6%
301 1
0.6%
228 1
0.6%
227 1
0.6%
226 1
0.6%
225 1
0.6%
224 1
0.6%
223 1
0.6%
222 1
0.6%
221 1
0.6%

장소
Text

Distinct161
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-12T23:26:46.075408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.6419753
Min length4

Characters and Unicode

Total characters1238
Distinct characters176
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)98.8%

Sample

1st row외도부영2차Ⅰ
2nd row외도부영2차Ⅱ
3rd row외도동주민센터
4th row도평입구
5th row구.이호검문소
ValueCountFrequency (%)
사거리ⅱ 6
 
2.9%
사거리ⅰ 6
 
2.9%
사거리 4
 
1.9%
옆 3
 
1.4%
우성아파트 3
 
1.4%
연동지구 3
 
1.4%
해태동산 2
 
1.0%
발전연구원 2
 
1.0%
애조로 2
 
1.0%
앞 2
 
1.0%
Other values (168) 177
84.3%
2023-12-12T23:26:46.518032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
6.9%
리 78
 
6.3%
거 69
 
5.6%
사 64
 
5.2%
Ⅰ 39
 
3.2%
Ⅱ 39
 
3.2%
로 36
 
2.9%
동 31
 
2.5%
교 28
 
2.3%
차 28
 
2.3%
Other values (166) 740
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1003
81.0%
Letter Number 90
 
7.3%
Space Separator 86
 
6.9%
Decimal Number 27
 
2.2%
Uppercase Letter 12
 
1.0%
Open Punctuation 8
 
0.6%
Close Punctuation 8
 
0.6%
Other Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 78
 
7.8%
거 69
 
6.9%
사 64
 
6.4%
로 36
 
3.6%
동 31
 
3.1%
교 28
 
2.8%
차 28
 
2.8%
삼 26
 
2.6%
구 26
 
2.6%
소 20
 
2.0%
Other values (144) 597
59.5%
Decimal Number
ValueCountFrequency (%)
2 13
48.1%
1 8
29.6%
9 2
 
7.4%
4 1
 
3.7%
3 1
 
3.7%
6 1
 
3.7%
8 1
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
16.7%
S 2
16.7%
C 2
16.7%
G 2
16.7%
T 2
16.7%
K 2
16.7%
Letter Number
ValueCountFrequency (%)
Ⅰ 39
43.3%
Ⅱ 39
43.3%
Ⅲ 11
 
12.2%
Ⅳ 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
& 2
50.0%
. 2
50.0%
Space Separator
ValueCountFrequency (%)
86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1003
81.0%
Common 133
 
10.7%
Latin 102
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 78
 
7.8%
거 69
 
6.9%
사 64
 
6.4%
로 36
 
3.6%
동 31
 
3.1%
교 28
 
2.8%
차 28
 
2.8%
삼 26
 
2.6%
구 26
 
2.6%
소 20
 
2.0%
Other values (144) 597
59.5%
Common
ValueCountFrequency (%)
86
64.7%
2 13
 
9.8%
1 8
 
6.0%
( 8
 
6.0%
) 8
 
6.0%
9 2
 
1.5%
& 2
 
1.5%
. 2
 
1.5%
4 1
 
0.8%
3 1
 
0.8%
Other values (2) 2
 
1.5%
Latin
ValueCountFrequency (%)
Ⅰ 39
38.2%
Ⅱ 39
38.2%
Ⅲ 11
 
10.8%
B 2
 
2.0%
S 2
 
2.0%
C 2
 
2.0%
G 2
 
2.0%
T 2
 
2.0%
K 2
 
2.0%
Ⅳ 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1003
81.0%
ASCII 145
 
11.7%
Number Forms 90
 
7.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
59.3%
2 13
 
9.0%
1 8
 
5.5%
( 8
 
5.5%
) 8
 
5.5%
B 2
 
1.4%
S 2
 
1.4%
C 2
 
1.4%
9 2
 
1.4%
G 2
 
1.4%
Other values (8) 12
 
8.3%
Hangul
ValueCountFrequency (%)
리 78
 
7.8%
거 69
 
6.9%
사 64
 
6.4%
로 36
 
3.6%
동 31
 
3.1%
교 28
 
2.8%
차 28
 
2.8%
삼 26
 
2.6%
구 26
 
2.6%
소 20
 
2.0%
Other values (144) 597
59.5%
Number Forms
ValueCountFrequency (%)
Ⅰ 39
43.3%
Ⅱ 39
43.3%
Ⅲ 11
 
12.2%
Ⅳ 1
 
1.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2023-01-01 00:00:00
Maximum2023-01-01 00:00:00
2023-12-12T23:26:46.639371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:26:46.729179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T23:26:44.886784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:26:46.804002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분지역관리번호
구분1.0000.6771.000
지역0.6771.0000.957
관리번호1.0000.9571.000
2023-12-12T23:26:46.892430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분지역
구분1.0000.506
지역0.5061.000
2023-12-12T23:26:46.973990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호구분지역
관리번호1.0000.9810.673
구분0.9811.0000.506
지역0.6730.5061.000

Missing values

2023-12-12T23:26:44.996001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:26:45.097536image/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

구분지역관리번호장소데이터기준일자
0구형외도동1외도부영2차Ⅰ2023-01-01
1구형외도동2외도부영2차Ⅱ2023-01-01
2구형외도동3외도동주민센터2023-01-01
3구형내도동4도평입구2023-01-01
4구형이호동5구.이호검문소2023-01-01
5구형이호동6이호1동2023-01-01
6구형이호동7현사마을 정거장2023-01-01
7구형도두동8도두주유소Ⅰ2023-01-01
8구형도두동9도두주유소Ⅱ2023-01-01
9구형노형동10탐라도서관입구2023-01-01
구분지역관리번호장소데이터기준일자
152신형화북동221제주교대Ⅰ2023-01-01
153신형화북동222제주교대Ⅱ2023-01-01
154신형화북동223삼화주공삼거리Ⅰ2023-01-01
155신형화북동224삼화주공삼거리Ⅱ2023-01-01
156신형화북동225삼화부영2차삼거리Ⅰ2023-01-01
157신형화북동226삼화부영2차삼거리Ⅱ2023-01-01
158신형화북동227삼화부영2차삼거리Ⅲ2023-01-01
159신형화북동228삼화부영2차삼거리Ⅳ2023-01-01
160신형연동301해태동산2023-01-01
161신형연동302해태동산2023-01-01