Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory488.3 KiB
Average record size in memory50.0 B

Variable types

Text2
Categorical3

Dataset

Description경기도 광주시 흡연단속시스템 내 단속사진 현황에 관한 데이터로 단속키, 법정동코드, 사진구분, 사진명 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15122162/fileData.do

Alerts

법정동코드 has constant value ""Constant
사진순번 is highly imbalanced (90.6%)Imbalance
사진구분 is highly imbalanced (90.3%)Imbalance
사진명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:40:39.827223
Analysis finished2023-12-12 17:40:40.462626
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단속키
Text

Distinct9961
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T02:40:40.649601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters240000
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9922 ?
Unique (%)99.2%

Sample

1st rowS00599999920220120133312
2nd rowS00599999920220701112119
3rd rowS00599999920230515113831
4th rowS00599999920210827110247
5th rowS00599999920211213105604
ValueCountFrequency (%)
s00399999920210615095410 2
 
< 0.1%
s00399999920210422105423 2
 
< 0.1%
s00399999920210511112854 2
 
< 0.1%
s00299999920210525130423 2
 
< 0.1%
s00299999920210628103331 2
 
< 0.1%
s00399999920210527124751 2
 
< 0.1%
s00299999920210628095838 2
 
< 0.1%
s00399999920210527114336 2
 
< 0.1%
s00399999920210510143045 2
 
< 0.1%
s00299999920210526145238 2
 
< 0.1%
Other values (9951) 9980
99.8%
2023-12-13T02:40:41.046072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 64058
26.7%
0 51335
21.4%
2 36570
15.2%
1 28793
12.0%
5 16399
 
6.8%
3 12105
 
5.0%
S 10000
 
4.2%
4 9183
 
3.8%
6 3944
 
1.6%
8 3860
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230000
95.8%
Uppercase Letter 10000
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 64058
27.9%
0 51335
22.3%
2 36570
15.9%
1 28793
12.5%
5 16399
 
7.1%
3 12105
 
5.3%
4 9183
 
4.0%
6 3944
 
1.7%
8 3860
 
1.7%
7 3753
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
S 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 230000
95.8%
Latin 10000
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
9 64058
27.9%
0 51335
22.3%
2 36570
15.9%
1 28793
12.5%
5 16399
 
7.1%
3 12105
 
5.3%
4 9183
 
4.0%
6 3944
 
1.7%
8 3860
 
1.7%
7 3753
 
1.6%
Latin
ValueCountFrequency (%)
S 10000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 240000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 64058
26.7%
0 51335
21.4%
2 36570
15.2%
1 28793
12.0%
5 16399
 
6.8%
3 12105
 
5.0%
S 10000
 
4.2%
4 9183
 
3.8%
6 3944
 
1.6%
8 3860
 
1.6%

법정동코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4161000000
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4161000000
2nd row4161000000
3rd row4161000000
4th row4161000000
5th row4161000000

Common Values

ValueCountFrequency (%)
4161000000 10000
100.0%

Length

2023-12-13T02:40:41.207596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:40:41.306562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4161000000 10000
100.0%

사진순번
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9879 
1
 
121

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 9879
98.8%
1 121
 
1.2%

Length

2023-12-13T02:40:41.408413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:40:41.527599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9879
98.8%
1 121
 
1.2%

사진구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
JP
9875 
JS
 
125

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
JP 9875
98.8%
JS 125
 
1.2%

Length

2023-12-13T02:40:41.632551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:40:41.741020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
jp 9875
98.8%
js 125
 
1.2%

사진명
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T02:40:41.978757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length32
Mean length32.0125
Min length32

Characters and Unicode

Total characters320125
Distinct characters19
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st rowS00599999920220120133312_1_1.jpg
2nd rowS00599999920220701112119_1_1.jpg
3rd rowS00599999920230515113831_1_1.jpg
4th rowS00599999920210827110247_1_1.jpg
5th rowS00599999920211213105604_1_1.jpg
ValueCountFrequency (%)
s00599999920220120133312_1_1.jpg 1
 
< 0.1%
s00599999920230310101832_1_1.jpg 1
 
< 0.1%
s00599999920211001113115_1_1.jpg 1
 
< 0.1%
s00499999920230322114434_1_1.jpg 1
 
< 0.1%
s00599999920210702111733_1_1.jpg 1
 
< 0.1%
s00599999920210820122752_1_1.jpg 1
 
< 0.1%
s00599999920220211110245_1_1.jpg 1
 
< 0.1%
s00599999920210309143838_1_1.jpg 1
 
< 0.1%
s00599999920220318105232_1_1.jpg 1
 
< 0.1%
s00599999920230406154740_1_1.jpg 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-13T02:40:42.355308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 64058
20.0%
0 51335
16.0%
1 48540
15.2%
2 36573
11.4%
_ 19875
 
6.2%
5 16399
 
5.1%
3 12105
 
3.8%
g 10125
 
3.2%
S 10000
 
3.1%
p 10000
 
3.1%
Other values (9) 41115
12.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 249750
78.0%
Lowercase Letter 30500
 
9.5%
Connector Punctuation 19875
 
6.2%
Uppercase Letter 10000
 
3.1%
Other Punctuation 10000
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 64058
25.6%
0 51335
20.6%
1 48540
19.4%
2 36573
14.6%
5 16399
 
6.6%
3 12105
 
4.8%
4 9183
 
3.7%
6 3944
 
1.6%
8 3860
 
1.5%
7 3753
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
g 10125
33.2%
p 10000
32.8%
j 10000
32.8%
s 125
 
0.4%
i 125
 
0.4%
n 125
 
0.4%
Connector Punctuation
ValueCountFrequency (%)
_ 19875
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 10000
100.0%
Other Punctuation
ValueCountFrequency (%)
. 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 279625
87.3%
Latin 40500
 
12.7%

Most frequent character per script

Common
ValueCountFrequency (%)
9 64058
22.9%
0 51335
18.4%
1 48540
17.4%
2 36573
13.1%
_ 19875
 
7.1%
5 16399
 
5.9%
3 12105
 
4.3%
. 10000
 
3.6%
4 9183
 
3.3%
6 3944
 
1.4%
Other values (2) 7613
 
2.7%
Latin
ValueCountFrequency (%)
g 10125
25.0%
S 10000
24.7%
p 10000
24.7%
j 10000
24.7%
s 125
 
0.3%
i 125
 
0.3%
n 125
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 320125
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 64058
20.0%
0 51335
16.0%
1 48540
15.2%
2 36573
11.4%
_ 19875
 
6.2%
5 16399
 
5.1%
3 12105
 
3.8%
g 10125
 
3.2%
S 10000
 
3.1%
p 10000
 
3.1%
Other values (9) 41115
12.8%

Correlations

2023-12-13T02:40:42.458383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사진순번사진구분
사진순번1.0000.000
사진구분0.0001.000
2023-12-13T02:40:42.537756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사진구분사진순번
사진구분1.0000.000
사진순번0.0001.000
2023-12-13T02:40:42.617767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사진순번사진구분
사진순번1.0000.000
사진구분0.0001.000

Missing values

2023-12-13T02:40:40.275713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:40:40.398985image/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

단속키법정동코드사진순번사진구분사진명
13951S0059999992022012013331241610000000JPS00599999920220120133312_1_1.jpg
20148S0059999992022070111211941610000000JPS00599999920220701112119_1_1.jpg
31297S0059999992023051511383141610000000JPS00599999920230515113831_1_1.jpg
9398S0059999992021082711024741610000000JPS00599999920210827110247_1_1.jpg
12501S0059999992021121310560441610000000JPS00599999920211213105604_1_1.jpg
9870S0059999992021091012061141610000000JPS00599999920210910120611_1_1.jpg
14679S0059999992022020910562541610000000JPS00599999920220209105625_1_1.jpg
2837S0039999992021042210542341610000000JSS00399999920210422105423_sign.jpg
20303S0059999992022070611440941610000000JPS00599999920220706114409_1_1.jpg
23644S0059999992022101809464241610000000JPS00599999920221018094642_1_1.jpg
단속키법정동코드사진순번사진구분사진명
19878S0059999992022062410484141610000000JPS00599999920220624104841_1_1.jpg
7776S0059999992021070212102141610000000JPS00599999920210702121021_1_1.jpg
1941S0029999992021040509083641610000000JPS00299999920210405090836_1_1.jpg
6881S0059999992021060412064341610000000JPS00599999920210604120643_1_1.jpg
9986S0059999992021091511244241610000000JPS00599999920210915112442_1_1.jpg
3963S0049999992023020709430141610000000JPS00499999920230207094301_1_1.jpg
9301S0059999992021082511082941610000000JPS00599999920210825110829_1_1.jpg
4254S0049999992023030210553041610000000JPS00499999920230302105530_1_1.jpg
28058S0059999992023030711005041610000000JPS00599999920230307110050_1_1.jpg
15664S0059999992022030210404341610000000JPS00599999920220302104043_1_1.jpg