Overview

Dataset statistics

Number of variables5
Number of observations101
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory42.3 B

Variable types

Numeric1
Categorical2
Text2

Dataset

Description광주광역시 서구 관내의 현수막지정게시대에 대한 용도구분(상업용, 행정용), 주소, 설치위치 등에 관한 정보입니다.
URLhttps://www.data.go.kr/data/15035571/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 용도구분High correlation
용도구분 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
설치위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:43:12.650219
Analysis finished2023-12-12 08:43:13.605223
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct101
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51
Minimum1
Maximum101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-12T17:43:13.719126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q126
median51
Q376
95-th percentile96
Maximum101
Range100
Interquartile range (IQR)50

Descriptive statistics

Standard deviation29.300171
Coefficient of variation (CV)0.57451315
Kurtosis-1.2
Mean51
Median Absolute Deviation (MAD)25
Skewness0
Sum5151
Variance858.5
MonotonicityStrictly increasing
2023-12-12T17:43:13.939255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (91) 91
90.1%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
101 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%

용도구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
상업용
77 
행정용
24 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상업용 77
76.2%
행정용 24
 
23.8%

Length

2023-12-12T17:43:14.127005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:43:14.252629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상업용 77
76.2%
행정용 24
 
23.8%

주소
Text

Distinct86
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-12-12T17:43:14.553320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length17.356436
Min length16

Characters and Unicode

Total characters1753
Distinct characters43
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

Unique74 ?
Unique (%)73.3%

Sample

1st row광주광역시 서구 농성동 671-2
2nd row광주광역시 서구 농성동 165-1
3rd row광주광역시 서구 양동 407-12
4th row광주광역시 서구 농성동 21-9
5th row광주광역시 서구 농성동 453-5
ValueCountFrequency (%)
광주광역시 101
25.0%
서구 101
25.0%
풍암동 20
 
5.0%
금호동 14
 
3.5%
치평동 11
 
2.7%
쌍촌동 10
 
2.5%
화정동 10
 
2.5%
동천동 8
 
2.0%
유촌동 8
 
2.0%
농성동 8
 
2.0%
Other values (91) 113
28.0%
2023-12-12T17:43:15.115076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
307
17.5%
광 204
11.6%
동 109
 
6.2%
역 101
 
5.8%
시 101
 
5.8%
서 101
 
5.8%
구 101
 
5.8%
주 101
 
5.8%
1 85
 
4.8%
- 52
 
3.0%
Other values (33) 491
28.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1012
57.7%
Decimal Number 382
 
21.8%
Space Separator 307
 
17.5%
Dash Punctuation 52
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 204
20.2%
동 109
10.8%
역 101
10.0%
시 101
10.0%
서 101
10.0%
구 101
10.0%
주 101
10.0%
풍 20
 
2.0%
암 20
 
2.0%
촌 18
 
1.8%
Other values (21) 136
13.4%
Decimal Number
ValueCountFrequency (%)
1 85
22.3%
2 42
11.0%
7 42
11.0%
0 34
 
8.9%
3 33
 
8.6%
6 32
 
8.4%
4 30
 
7.9%
5 28
 
7.3%
8 28
 
7.3%
9 28
 
7.3%
Space Separator
ValueCountFrequency (%)
307
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1012
57.7%
Common 741
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 204
20.2%
동 109
10.8%
역 101
10.0%
시 101
10.0%
서 101
10.0%
구 101
10.0%
주 101
10.0%
풍 20
 
2.0%
암 20
 
2.0%
촌 18
 
1.8%
Other values (21) 136
13.4%
Common
ValueCountFrequency (%)
307
41.4%
1 85
 
11.5%
- 52
 
7.0%
2 42
 
5.7%
7 42
 
5.7%
0 34
 
4.6%
3 33
 
4.5%
6 32
 
4.3%
4 30
 
4.0%
5 28
 
3.8%
Other values (2) 56
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1012
57.7%
ASCII 741
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
307
41.4%
1 85
 
11.5%
- 52
 
7.0%
2 42
 
5.7%
7 42
 
5.7%
0 34
 
4.6%
3 33
 
4.5%
6 32
 
4.3%
4 30
 
4.0%
5 28
 
3.8%
Other values (2) 56
 
7.6%
Hangul
ValueCountFrequency (%)
광 204
20.2%
동 109
10.8%
역 101
10.0%
시 101
10.0%
서 101
10.0%
구 101
10.0%
주 101
10.0%
풍 20
 
2.0%
암 20
 
2.0%
촌 18
 
1.8%
Other values (21) 136
13.4%

설치위치
Text

UNIQUE 

Distinct101
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-12-12T17:43:15.546220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length15
Mean length9.5247525
Min length3

Characters and Unicode

Total characters962
Distinct characters187
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)100.0%

Sample

1st row농성공원(상공회의소 맞은편)
2nd row농성한전맞은편
3rd row양동그린파크
4th row농성중흥파크
5th row농성광천교A
ValueCountFrequency (%)
주민센터 6
 
4.3%
건너편 5
 
3.6%
입구 4
 
2.9%
옆 3
 
2.2%
삼거리 2
 
1.4%
유촌동 2
 
1.4%
육교 2
 
1.4%
앞 2
 
1.4%
치평동 1
 
0.7%
농성1동 1
 
0.7%
Other values (110) 110
79.7%
2023-12-12T17:43:16.110541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38
 
4.0%
리 30
 
3.1%
거 27
 
2.8%
( 26
 
2.7%
동 26
 
2.7%
) 24
 
2.5%
구 20
 
2.1%
주 18
 
1.9%
교 17
 
1.8%
암 15
 
1.6%
Other values (177) 721
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 840
87.3%
Space Separator 38
 
4.0%
Open Punctuation 26
 
2.7%
Close Punctuation 24
 
2.5%
Decimal Number 22
 
2.3%
Uppercase Letter 10
 
1.0%
Lowercase Letter 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 30
 
3.6%
거 27
 
3.2%
동 26
 
3.1%
구 20
 
2.4%
주 18
 
2.1%
교 17
 
2.0%
암 15
 
1.8%
트 15
 
1.8%
아 15
 
1.8%
터 14
 
1.7%
Other values (159) 643
76.5%
Decimal Number
ValueCountFrequency (%)
1 6
27.3%
2 6
27.3%
0 5
22.7%
3 2
 
9.1%
5 1
 
4.5%
6 1
 
4.5%
4 1
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 2
20.0%
A 2
20.0%
K 2
20.0%
L 2
20.0%
M 1
10.0%
C 1
10.0%
Space Separator
ValueCountFrequency (%)
38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 840
87.3%
Common 111
 
11.5%
Latin 11
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 30
 
3.6%
거 27
 
3.2%
동 26
 
3.1%
구 20
 
2.4%
주 18
 
2.1%
교 17
 
2.0%
암 15
 
1.8%
트 15
 
1.8%
아 15
 
1.8%
터 14
 
1.7%
Other values (159) 643
76.5%
Common
ValueCountFrequency (%)
38
34.2%
( 26
23.4%
) 24
21.6%
1 6
 
5.4%
2 6
 
5.4%
0 5
 
4.5%
3 2
 
1.8%
5 1
 
0.9%
6 1
 
0.9%
4 1
 
0.9%
Latin
ValueCountFrequency (%)
B 2
18.2%
A 2
18.2%
K 2
18.2%
L 2
18.2%
M 1
9.1%
C 1
9.1%
b 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 840
87.3%
ASCII 122
 
12.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38
31.1%
( 26
21.3%
) 24
19.7%
1 6
 
4.9%
2 6
 
4.9%
0 5
 
4.1%
B 2
 
1.6%
A 2
 
1.6%
3 2
 
1.6%
K 2
 
1.6%
Other values (8) 9
 
7.4%
Hangul
ValueCountFrequency (%)
리 30
 
3.6%
거 27
 
3.2%
동 26
 
3.1%
구 20
 
2.4%
주 18
 
2.1%
교 17
 
2.0%
암 15
 
1.8%
트 15
 
1.8%
아 15
 
1.8%
터 14
 
1.7%
Other values (159) 643
76.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-06-20
101 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-20
2nd row2023-06-20
3rd row2023-06-20
4th row2023-06-20
5th row2023-06-20

Common Values

ValueCountFrequency (%)
2023-06-20 101
100.0%

Length

2023-12-12T17:43:16.291786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:43:16.425167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-20 101
100.0%

Interactions

2023-12-12T17:43:12.898321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:43:16.520608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번용도구분주소
연번1.0000.9930.978
용도구분0.9931.0000.982
주소0.9780.9821.000
2023-12-12T17:43:16.649492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번용도구분
연번1.0000.887
용도구분0.8871.000

Missing values

2023-12-12T17:43:13.406090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:43:13.545289image/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

연번용도구분주소설치위치데이터기준일자
01상업용광주광역시 서구 농성동 671-2농성공원(상공회의소 맞은편)2023-06-20
12상업용광주광역시 서구 농성동 165-1농성한전맞은편2023-06-20
23상업용광주광역시 서구 양동 407-12양동그린파크2023-06-20
34상업용광주광역시 서구 농성동 21-9농성중흥파크2023-06-20
45상업용광주광역시 서구 농성동 453-5농성광천교A2023-06-20
56상업용광주광역시 서구 농성동 611-1농성광천교b2023-06-20
67상업용광주광역시 서구 농성동 671-2농성역2023-06-20
78상업용광주광역시 서구 내방동 291-5서부소방서2023-06-20
89상업용광주광역시 서구 동천동 356동천동우미린천변삼거리2023-06-20
910상업용광주광역시 서구 동천동 652동천휴먼시아304동앞2023-06-20
연번용도구분주소설치위치데이터기준일자
9192행정용광주광역시 서구 치평동 1165상무지구먹자골목입구2023-06-20
9293행정용광주광역시 서구 광천동 236-2터미널앞보행섬(목포방면)2023-06-20
9394행정용광주광역시 서구 광천동 236-2터미널앞보행섬(백화점방면)2023-06-20
9495행정용광주광역시 서구 화정동 406-7염주체육관육교2023-06-20
9596행정용광주광역시 서구 치평동 1326상무역사거리2023-06-20
9697행정용광주광역시 서구 금호동 244-5만호초 육교 밑2023-06-20
9798행정용광주광역시 서구 쌍촌동 1006쌍촌역사거리(상무역방면)2023-06-20
9899행정용광주광역시 서구 쌍촌동 1006쌍촌역사거리(화정역방면)2023-06-20
99100행정용광주광역시 서구 풍암동 858마재우체국 버스정류장 건너편2023-06-20
100101행정용광주광역시 서구 화정동 899(구)서광주세무서사거리2023-06-20