Overview

Dataset statistics

Number of variables7
Number of observations150
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.8 KiB
Average record size in memory59.9 B

Variable types

Numeric3
Categorical1
Text2
DateTime1

Dataset

Description광주광역시 광산구에 위치한 현수막지정게시대 현황(용도구분, 주소, 설치위치, 위도, 경도, 데이터기준일자 등) 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15055951/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 19:49:40.019972
Analysis finished2023-12-12 19:49:41.652087
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct150
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.5
Minimum1
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T04:49:41.771623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.45
Q138.25
median75.5
Q3112.75
95-th percentile142.55
Maximum150
Range149
Interquartile range (IQR)74.5

Descriptive statistics

Standard deviation43.445368
Coefficient of variation (CV)0.57543534
Kurtosis-1.2
Mean75.5
Median Absolute Deviation (MAD)37.5
Skewness0
Sum11325
Variance1887.5
MonotonicityStrictly increasing
2023-12-13T04:49:41.960744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
96 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
105 1
 
0.7%
Other values (140) 140
93.3%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%

용도구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
상업용
100 
행정용
18 
육교용(행정)
 
10
저단용(행정)
 
10
저단용(상업)
 
9

Length

Max length8
Median length3
Mean length3.8733333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row육교용(행정)
2nd row육교용(행정)
3rd row육교용(행정)
4th row육교용(행정)
5th row육교용(행정)

Common Values

ValueCountFrequency (%)
상업용 100
66.7%
행정용 18
 
12.0%
육교용(행정) 10
 
6.7%
저단용(행정) 10
 
6.7%
저단용(상업) 9
 
6.0%
행정용(정치용) 3
 
2.0%

Length

2023-12-13T04:49:42.126003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:49:42.246455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상업용 100
66.7%
행정용 18
 
12.0%
육교용(행정 10
 
6.7%
저단용(행정 10
 
6.7%
저단용(상업 9
 
6.0%
행정용(정치용 3
 
2.0%

주소
Text

Distinct108
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T04:49:42.560825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length18.526667
Min length17

Characters and Unicode

Total characters2779
Distinct characters55
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

Unique78 ?
Unique (%)52.0%

Sample

1st row광주광역시 광산구 우산동 1100-4
2nd row광주광역시 광산구 우산동 1572-4
3rd row광주광역시 광산구 월곡동 321-32
4th row광주광역시 광산구 흑석동 501
5th row광주광역시 광산구 운남동 456-39
ValueCountFrequency (%)
광주광역시 150
25.1%
광산구 150
25.1%
수완동 20
 
3.4%
장덕동 15
 
2.5%
신가동 15
 
2.5%
월계동 13
 
2.2%
우산동 12
 
2.0%
운남동 10
 
1.7%
하남동 6
 
1.0%
월곡동 6
 
1.0%
Other values (128) 200
33.5%
2023-12-13T04:49:43.105310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 450
16.2%
447
16.1%
산 173
 
6.2%
1 160
 
5.8%
역 150
 
5.4%
시 150
 
5.4%
구 150
 
5.4%
주 150
 
5.4%
동 150
 
5.4%
- 72
 
2.6%
Other values (45) 727
26.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1654
59.5%
Decimal Number 606
 
21.8%
Space Separator 447
 
16.1%
Dash Punctuation 72
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 450
27.2%
산 173
 
10.5%
역 150
 
9.1%
시 150
 
9.1%
구 150
 
9.1%
주 150
 
9.1%
동 150
 
9.1%
신 28
 
1.7%
월 23
 
1.4%
수 20
 
1.2%
Other values (33) 210
12.7%
Decimal Number
ValueCountFrequency (%)
1 160
26.4%
7 62
 
10.2%
6 61
 
10.1%
0 60
 
9.9%
5 53
 
8.7%
2 49
 
8.1%
3 48
 
7.9%
4 40
 
6.6%
8 37
 
6.1%
9 36
 
5.9%
Space Separator
ValueCountFrequency (%)
447
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1654
59.5%
Common 1125
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 450
27.2%
산 173
 
10.5%
역 150
 
9.1%
시 150
 
9.1%
구 150
 
9.1%
주 150
 
9.1%
동 150
 
9.1%
신 28
 
1.7%
월 23
 
1.4%
수 20
 
1.2%
Other values (33) 210
12.7%
Common
ValueCountFrequency (%)
447
39.7%
1 160
 
14.2%
- 72
 
6.4%
7 62
 
5.5%
6 61
 
5.4%
0 60
 
5.3%
5 53
 
4.7%
2 49
 
4.4%
3 48
 
4.3%
4 40
 
3.6%
Other values (2) 73
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1654
59.5%
ASCII 1125
40.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 450
27.2%
산 173
 
10.5%
역 150
 
9.1%
시 150
 
9.1%
구 150
 
9.1%
주 150
 
9.1%
동 150
 
9.1%
신 28
 
1.7%
월 23
 
1.4%
수 20
 
1.2%
Other values (33) 210
12.7%
ASCII
ValueCountFrequency (%)
447
39.7%
1 160
 
14.2%
- 72
 
6.4%
7 62
 
5.5%
6 61
 
5.4%
0 60
 
5.3%
5 53
 
4.7%
2 49
 
4.4%
3 48
 
4.3%
4 40
 
3.6%
Other values (2) 73
 
6.5%

설치위치
Text

UNIQUE 

Distinct150
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T04:49:43.423553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length10.046667
Min length4

Characters and Unicode

Total characters1507
Distinct characters193
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

Unique150 ?
Unique (%)100.0%

Sample

1st row우산육교
2nd row시영육교
3rd row대반육교
4th row장덕육교
5th row금구육교
ValueCountFrequency (%)
사거리 15
 
5.9%
앞 12
 
4.7%
수완현진에버빌 5
 
2.0%
입구 4
 
1.6%
101동 4
 
1.6%
출입구 4
 
1.6%
광주송정역 3
 
1.2%
선운 3
 
1.2%
농수산물유통센터 3
 
1.2%
삼거리 3
 
1.2%
Other values (177) 200
78.1%
2023-12-13T04:49:43.964844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
106
 
7.0%
리 55
 
3.6%
거 51
 
3.4%
1 49
 
3.3%
사 44
 
2.9%
2 33
 
2.2%
교 29
 
1.9%
주 28
 
1.9%
남 28
 
1.9%
수 27
 
1.8%
Other values (183) 1057
70.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1180
78.3%
Decimal Number 134
 
8.9%
Space Separator 106
 
7.0%
Uppercase Letter 24
 
1.6%
Open Punctuation 21
 
1.4%
Close Punctuation 21
 
1.4%
Dash Punctuation 21
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 55
 
4.7%
거 51
 
4.3%
사 44
 
3.7%
교 29
 
2.5%
주 28
 
2.4%
남 28
 
2.4%
수 27
 
2.3%
로 25
 
2.1%
단 25
 
2.1%
동 23
 
1.9%
Other values (160) 845
71.6%
Uppercase Letter
ValueCountFrequency (%)
C 5
20.8%
I 4
16.7%
L 3
12.5%
S 2
 
8.3%
B 2
 
8.3%
H 2
 
8.3%
K 2
 
8.3%
O 2
 
8.3%
A 1
 
4.2%
W 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 49
36.6%
2 33
24.6%
0 15
 
11.2%
3 12
 
9.0%
7 8
 
6.0%
4 7
 
5.2%
6 5
 
3.7%
5 4
 
3.0%
8 1
 
0.7%
Space Separator
ValueCountFrequency (%)
106
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1180
78.3%
Common 303
 
20.1%
Latin 24
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 55
 
4.7%
거 51
 
4.3%
사 44
 
3.7%
교 29
 
2.5%
주 28
 
2.4%
남 28
 
2.4%
수 27
 
2.3%
로 25
 
2.1%
단 25
 
2.1%
동 23
 
1.9%
Other values (160) 845
71.6%
Common
ValueCountFrequency (%)
106
35.0%
1 49
16.2%
2 33
 
10.9%
( 21
 
6.9%
) 21
 
6.9%
- 21
 
6.9%
0 15
 
5.0%
3 12
 
4.0%
7 8
 
2.6%
4 7
 
2.3%
Other values (3) 10
 
3.3%
Latin
ValueCountFrequency (%)
C 5
20.8%
I 4
16.7%
L 3
12.5%
S 2
 
8.3%
B 2
 
8.3%
H 2
 
8.3%
K 2
 
8.3%
O 2
 
8.3%
A 1
 
4.2%
W 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1180
78.3%
ASCII 327
 
21.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
106
32.4%
1 49
15.0%
2 33
 
10.1%
( 21
 
6.4%
) 21
 
6.4%
- 21
 
6.4%
0 15
 
4.6%
3 12
 
3.7%
7 8
 
2.4%
4 7
 
2.1%
Other values (13) 34
 
10.4%
Hangul
ValueCountFrequency (%)
리 55
 
4.7%
거 51
 
4.3%
사 44
 
3.7%
교 29
 
2.5%
주 28
 
2.4%
남 28
 
2.4%
수 27
 
2.3%
로 25
 
2.1%
단 25
 
2.1%
동 23
 
1.9%
Other values (160) 845
71.6%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct108
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.183145
Minimum35.121602
Maximum35.223776
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T04:49:44.184889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.121602
5-th percentile35.138584
Q135.171544
median35.185449
Q335.199414
95-th percentile35.219298
Maximum35.223776
Range0.10217319
Interquartile range (IQR)0.027870289

Descriptive statistics

Standard deviation0.023948323
Coefficient of variation (CV)0.00068067602
Kurtosis-0.35257241
Mean35.183145
Median Absolute Deviation (MAD)0.01396512
Skewness-0.41437102
Sum5277.4718
Variance0.00057352219
MonotonicityNot monotonic
2023-12-13T04:49:44.399788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.1937822912646 5
 
3.3%
35.190890804998 5
 
3.3%
35.1994138846228 4
 
2.7%
35.1750790623901 3
 
2.0%
35.2163649630738 3
 
2.0%
35.1647996018509 3
 
2.0%
35.1950709054229 3
 
2.0%
35.1957220387376 2
 
1.3%
35.1730849763999 2
 
1.3%
35.2002109537745 2
 
1.3%
Other values (98) 118
78.7%
ValueCountFrequency (%)
35.1216024758722 1
0.7%
35.1253581342106 1
0.7%
35.1307525666753 1
0.7%
35.1341977613052 1
0.7%
35.1371583720369 1
0.7%
35.1372516596463 1
0.7%
35.137730740457 1
0.7%
35.1378077684261 1
0.7%
35.1395334290538 2
1.3%
35.1424999991155 1
0.7%
ValueCountFrequency (%)
35.2237756658701 1
0.7%
35.2234459777486 2
1.3%
35.2219088770465 1
0.7%
35.220568431405 1
0.7%
35.2200457496215 1
0.7%
35.2193959657693 2
1.3%
35.2191792770696 1
0.7%
35.2181263821311 1
0.7%
35.218015057575 1
0.7%
35.2176974228069 1
0.7%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct108
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.81384
Minimum126.69876
Maximum126.84705
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T04:49:44.616994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.69876
5-th percentile126.77634
Q1126.80161
median126.81609
Q3126.82605
95-th percentile126.8424
Maximum126.84705
Range0.14828489
Interquartile range (IQR)0.024435632

Descriptive statistics

Standard deviation0.021936373
Coefficient of variation (CV)0.00017298091
Kurtosis5.5788611
Mean126.81384
Median Absolute Deviation (MAD)0.011881745
Skewness-1.6450457
Sum19022.076
Variance0.00048120447
MonotonicityNot monotonic
2023-12-13T04:49:44.858166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.823282292028 5
 
3.3%
126.813579608765 5
 
3.3%
126.820850099891 4
 
2.7%
126.811251436065 3
 
2.0%
126.833740860508 3
 
2.0%
126.80158647203 3
 
2.0%
126.823309587818 3
 
2.0%
126.813041287976 2
 
1.3%
126.797726537382 2
 
1.3%
126.842580426011 2
 
1.3%
Other values (98) 118
78.7%
ValueCountFrequency (%)
126.698760479436 1
0.7%
126.730652823806 1
0.7%
126.744667263244 1
0.7%
126.770276288372 1
0.7%
126.771129714513 1
0.7%
126.772238464655 1
0.7%
126.772580682271 1
0.7%
126.775761283645 1
0.7%
126.777038813649 1
0.7%
126.779398379652 2
1.3%
ValueCountFrequency (%)
126.847045367286 1
0.7%
126.844900771365 1
0.7%
126.843278214037 2
1.3%
126.843268763016 1
0.7%
126.843164242285 1
0.7%
126.842580426011 2
1.3%
126.842184224219 2
1.3%
126.841820914535 1
0.7%
126.841572334977 1
0.7%
126.840812197636 2
1.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-13T04:49:45.022266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:49:45.156362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T04:49:40.997954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:49:40.370465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:49:40.715377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:49:41.138466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:49:40.494827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:49:40.818268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:49:41.263973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:49:40.610079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:49:40.898741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:49:45.265279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번용도구분위도경도
연번1.0000.8720.6540.433
용도구분0.8721.0000.4040.400
위도0.6540.4041.0000.668
경도0.4330.4000.6681.000
2023-12-13T04:49:45.766083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도용도구분
연번1.0000.118-0.0260.692
위도0.1181.0000.7840.222
경도-0.0260.7841.0000.208
용도구분0.6920.2220.2081.000

Missing values

2023-12-13T04:49:41.438321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:49:41.587481image/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

연번용도구분주소설치위치위도경도데이터기준일자
01육교용(행정)광주광역시 광산구 우산동 1100-4우산육교35.158618126.807882022-12-31
12육교용(행정)광주광역시 광산구 우산동 1572-4시영육교35.164807126.8078352022-12-31
23육교용(행정)광주광역시 광산구 월곡동 321-32대반육교35.176083126.8084572022-12-31
34육교용(행정)광주광역시 광산구 흑석동 501장덕육교35.185397126.8122982022-12-31
45육교용(행정)광주광역시 광산구 운남동 456-39금구육교35.176762126.8179692022-12-31
56육교용(행정)광주광역시 광산구 운남동 455-24운남육교35.179336126.8207582022-12-31
67육교용(행정)광주광역시 광산구 운남동 222-5신가육교35.179056126.8265832022-12-31
78육교용(행정)광주광역시 광산구 신가동 1053아름2육교35.186584126.8211732022-12-31
89육교용(행정)광주광역시 광산구 수완동 1431솔빛육교35.190382126.8261112022-12-31
910육교용(행정)광주광역시 광산구 수완동 914수완육교35.197878126.8227072022-12-31
연번용도구분주소설치위치위도경도데이터기준일자
140141상업용광주광역시 광산구 수완동 11-9산월IC-335.20191126.8386252022-12-31
141142상업용광주광역시 광산구 신촌동 1090-27마이스터고등학교앞35.143509126.8001142022-12-31
142143상업용광주광역시 광산구 우산동 1611-16광주여대 공용주차장-135.1648126.8015862022-12-31
143144상업용광주광역시 광산구 우산동 1611-16광주여대 공용주차장-235.1648126.8015862022-12-31
144145상업용광주광역시 광산구 신창동 1114첨단 교차로35.199545126.8415722022-12-31
145146상업용광주광역시 광산구 우산동 1611-16광주여대 공영주차장(3)35.1648126.8015862022-12-31
146147상업용광주광역시 광산구 운남동 795운남주공6단지(2)35.179107126.8173292022-12-31
147148상업용광주광역시 광산구 수완동 930수완현진에버빌 승강장 (3)35.195071126.823312022-12-31
148149상업용광주광역시 광산구 수완동 1803수완현진에버빌103동앞 사거리(2)35.193782126.8232822022-12-31
149150상업용광주광역시 광산구 장덕동 1490장덕4번로 먹자골목 입구35.190708126.8106982022-12-31