Overview

Dataset statistics

Number of variables11
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory95.1 B

Variable types

Numeric1
Text2
DateTime3
Categorical5

Dataset

Description대구광역시 버스전용차선 무인단속카메라 설치현황입니다. (설치장소, 가로명, 설치일, 단속시행일, 촬영시간, 구간단속시행일)
Author대구광역시
URLhttps://www.data.go.kr/data/3078840/fileData.do

Alerts

시작1 has constant value ""Constant
끝1 has constant value ""Constant
기준일 has constant value ""Constant
끝2 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
시작2 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 시작2 and 1 other fieldsHigh correlation
시작2 is highly imbalanced (72.4%)Imbalance
끝2 is highly imbalanced (72.4%)Imbalance
연번 has unique valuesUnique
설치장소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 14:33:39.045494
Analysis finished2024-03-14 14:33:40.482331
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-03-14T23:33:40.672977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2024-03-14T23:33:41.111384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

설치장소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-14T23:33:42.011696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length24
Min length18

Characters and Unicode

Total characters504
Distinct characters110
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

Unique21 ?
Unique (%)100.0%

Sample

1st row팔달고가교 앞 (북구 태전동 872-1)
2nd row청구고등학교 앞 (동구 신천동 850-45)
3rd row지하철아양교역 앞 (동구 신암5동 1475)
4th row동구보건소 앞 (동구 검사동 990-172)
5th row과학고등학교 앞 (수성구 황금동 613)
ValueCountFrequency (%)
앞 13
 
12.1%
달구벌대로 4
 
3.7%
동구 4
 
3.7%
수성구 4
 
3.7%
건너 3
 
2.8%
남구 3
 
2.8%
달서구 3
 
2.8%
중구 2
 
1.9%
서구 2
 
1.9%
대구은행 2
 
1.9%
Other values (66) 67
62.6%
2024-03-14T23:33:43.327073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
86
 
17.1%
구 38
 
7.5%
( 22
 
4.4%
) 22
 
4.4%
앞 17
 
3.4%
동 16
 
3.2%
1 16
 
3.2%
대 14
 
2.8%
2 13
 
2.6%
로 12
 
2.4%
Other values (100) 248
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 275
54.6%
Space Separator 86
 
17.1%
Decimal Number 84
 
16.7%
Open Punctuation 22
 
4.4%
Close Punctuation 22
 
4.4%
Dash Punctuation 8
 
1.6%
Uppercase Letter 7
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 38
 
13.8%
앞 17
 
6.2%
동 16
 
5.8%
대 14
 
5.1%
로 12
 
4.4%
달 8
 
2.9%
성 7
 
2.5%
수 7
 
2.5%
역 7
 
2.5%
서 7
 
2.5%
Other values (82) 142
51.6%
Decimal Number
ValueCountFrequency (%)
1 16
19.0%
2 13
15.5%
3 11
13.1%
0 8
9.5%
5 8
9.5%
4 7
8.3%
7 7
8.3%
9 6
 
7.1%
6 6
 
7.1%
8 2
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
P 2
28.6%
A 2
28.6%
T 2
28.6%
W 1
14.3%
Space Separator
ValueCountFrequency (%)
86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 275
54.6%
Common 222
44.0%
Latin 7
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 38
 
13.8%
앞 17
 
6.2%
동 16
 
5.8%
대 14
 
5.1%
로 12
 
4.4%
달 8
 
2.9%
성 7
 
2.5%
수 7
 
2.5%
역 7
 
2.5%
서 7
 
2.5%
Other values (82) 142
51.6%
Common
ValueCountFrequency (%)
86
38.7%
( 22
 
9.9%
) 22
 
9.9%
1 16
 
7.2%
2 13
 
5.9%
3 11
 
5.0%
0 8
 
3.6%
- 8
 
3.6%
5 8
 
3.6%
4 7
 
3.2%
Other values (4) 21
 
9.5%
Latin
ValueCountFrequency (%)
P 2
28.6%
A 2
28.6%
T 2
28.6%
W 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 275
54.6%
ASCII 229
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
37.6%
( 22
 
9.6%
) 22
 
9.6%
1 16
 
7.0%
2 13
 
5.7%
3 11
 
4.8%
0 8
 
3.5%
- 8
 
3.5%
5 8
 
3.5%
4 7
 
3.1%
Other values (8) 28
 
12.2%
Hangul
ValueCountFrequency (%)
구 38
 
13.8%
앞 17
 
6.2%
동 16
 
5.8%
대 14
 
5.1%
로 12
 
4.4%
달 8
 
2.9%
성 7
 
2.5%
수 7
 
2.5%
역 7
 
2.5%
서 7
 
2.5%
Other values (82) 142
51.6%

가로명
Text

Distinct13
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-14T23:33:43.915102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.1904762
Min length3

Characters and Unicode

Total characters88
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)47.6%

Sample

1st row칠곡중앙대로
2nd row국채보상로
3rd row아양로
4th row동촌로
5th row동대구로
ValueCountFrequency (%)
달구벌대로 6
28.6%
국채보상로 3
14.3%
서대구로 2
 
9.5%
칠곡중앙대로 1
 
4.8%
아양로 1
 
4.8%
동촌로 1
 
4.8%
동대구로 1
 
4.8%
태평로 1
 
4.8%
화랑로 1
 
4.8%
대명로 1
 
4.8%
Other values (3) 3
14.3%
2024-03-14T23:33:44.902691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 21
23.9%
대 12
13.6%
구 9
10.2%
달 6
 
6.8%
벌 6
 
6.8%
국 3
 
3.4%
채 3
 
3.4%
보 3
 
3.4%
상 3
 
3.4%
중 2
 
2.3%
Other values (16) 20
22.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 88
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 21
23.9%
대 12
13.6%
구 9
10.2%
달 6
 
6.8%
벌 6
 
6.8%
국 3
 
3.4%
채 3
 
3.4%
보 3
 
3.4%
상 3
 
3.4%
중 2
 
2.3%
Other values (16) 20
22.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 88
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 21
23.9%
대 12
13.6%
구 9
10.2%
달 6
 
6.8%
벌 6
 
6.8%
국 3
 
3.4%
채 3
 
3.4%
보 3
 
3.4%
상 3
 
3.4%
중 2
 
2.3%
Other values (16) 20
22.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 88
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 21
23.9%
대 12
13.6%
구 9
10.2%
달 6
 
6.8%
벌 6
 
6.8%
국 3
 
3.4%
채 3
 
3.4%
보 3
 
3.4%
상 3
 
3.4%
중 2
 
2.3%
Other values (16) 20
22.7%

설치일
Date

Distinct13
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Memory size296.0 B
Minimum1999-10-06 00:00:00
Maximum2023-12-01 00:00:00
2024-03-14T23:33:45.244950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:33:45.825136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

단속시행일
Date

Distinct13
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Memory size296.0 B
Minimum1999-10-06 00:00:00
Maximum2023-12-01 00:00:00
2024-03-14T23:33:46.171469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:33:46.538293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

시작1
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size296.0 B
07:00:00
21 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07:00:00
2nd row07:00:00
3rd row07:00:00
4th row07:00:00
5th row07:00:00

Common Values

ValueCountFrequency (%)
07:00:00 21
100.0%

Length

2024-03-14T23:33:46.938253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:33:47.246018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07:00:00 21
100.0%

끝1
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size296.0 B
09:00:00
21 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09:00:00
2nd row09:00:00
3rd row09:00:00
4th row09:00:00
5th row09:00:00

Common Values

ValueCountFrequency (%)
09:00:00 21
100.0%

Length

2024-03-14T23:33:47.570468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:33:47.878391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09:00:00 21
100.0%

시작2
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size296.0 B
17:30:00
20 
<NA>
 
1

Length

Max length8
Median length8
Mean length7.8095238
Min length4

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row17:30:00
2nd row17:30:00
3rd row17:30:00
4th row17:30:00
5th row<NA>

Common Values

ValueCountFrequency (%)
17:30:00 20
95.2%
<NA> 1
 
4.8%

Length

2024-03-14T23:33:48.069749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:33:48.265992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
17:30:00 20
95.2%
na 1
 
4.8%

끝2
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size296.0 B
19:30:00
20 
<NA>
 
1

Length

Max length8
Median length8
Mean length7.8095238
Min length4

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row19:30:00
2nd row19:30:00
3rd row19:30:00
4th row19:30:00
5th row<NA>

Common Values

ValueCountFrequency (%)
19:30:00 20
95.2%
<NA> 1
 
4.8%

Length

2024-03-14T23:33:48.465377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:33:48.659726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
19:30:00 20
95.2%
na 1
 
4.8%

구간단속 시행일
Date

Distinct11
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Memory size296.0 B
Minimum2006-04-20 00:00:00
Maximum2023-12-01 00:00:00
2024-03-14T23:33:48.807823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:33:49.072405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-02-21
21 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-21
2nd row2024-02-21
3rd row2024-02-21
4th row2024-02-21
5th row2024-02-21

Common Values

ValueCountFrequency (%)
2024-02-21 21
100.0%

Length

2024-03-14T23:33:49.270986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:33:49.440011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-21 21
100.0%

Interactions

2024-03-14T23:33:39.484186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:33:49.550636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치장소가로명설치일단속시행일구간단속 시행일
연번1.0001.0000.3310.7410.7410.645
설치장소1.0001.0001.0001.0001.0001.000
가로명0.3311.0001.0000.8170.8170.000
설치일0.7411.0000.8171.0001.0001.000
단속시행일0.7411.0000.8171.0001.0001.000
구간단속 시행일0.6451.0000.0001.0001.0001.000
2024-03-14T23:33:49.723628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
끝2시작2
끝21.0001.000
시작21.0001.000
2024-03-14T23:33:49.861900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시작2끝2
연번1.0001.0001.000
시작21.0001.0001.000
끝21.0001.0001.000

Missing values

2024-03-14T23:33:39.929132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:33:40.360996image/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

연번설치장소가로명설치일단속시행일시작1끝1시작2끝2구간단속 시행일기준일
01팔달고가교 앞 (북구 태전동 872-1)칠곡중앙대로2000-04-012000-04-0107:00:0009:00:0017:30:0019:30:002007-02-012024-02-21
12청구고등학교 앞 (동구 신천동 850-45)국채보상로1999-10-061999-10-0607:00:0009:00:0017:30:0019:30:002006-04-282024-02-21
23지하철아양교역 앞 (동구 신암5동 1475)아양로2003-02-192003-04-0107:00:0009:00:0017:30:0019:30:002006-04-202024-02-21
34동구보건소 앞 (동구 검사동 990-172)동촌로2004-01-072004-03-0107:00:0009:00:0017:30:0019:30:002007-02-012024-02-21
45과학고등학교 앞 (수성구 황금동 613)동대구로2006-02-082006-04-2007:00:0009:00:00<NA><NA>2006-04-202024-02-21
56W병원 앞 (달서구 감삼동 102)달구벌대로2007-11-272008-02-0107:00:0009:00:0017:30:0019:30:002008-02-012024-02-21
67대구역센트럴자이 앞 (중구 태평로3가 230-1)태평로2007-11-272008-02-0107:00:0009:00:0017:30:0019:30:002008-02-012024-02-21
78중구청 건너 (중구 동인동4가 314-2)국채보상로2012-12-162013-02-0107:00:0009:00:0017:30:0019:30:002013-02-012024-02-21
89수성구청역 앞 (수성구 범어동 223-17)달구벌대로2012-12-162013-02-0107:00:0009:00:0017:30:0019:30:002013-02-012024-02-21
910평리광명네거리 (서구 평리동 1032-7)서대구로2013-11-132014-01-0207:00:0009:00:0017:30:0019:30:002014-01-022024-02-21
연번설치장소가로명설치일단속시행일시작1끝1시작2끝2구간단속 시행일기준일
1112동구시장 앞 (동구 화랑로 145)화랑로2017-06-232017-09-0507:00:0009:00:0017:30:0019:30:002017-09-052024-02-21
1213안지랑역 앞 (남구 대명로 136)대명로2017-06-232017-09-0507:00:0009:00:0017:30:0019:30:002017-09-052024-02-21
1314대구은행 만촌역지점 앞 (수성구 달구벌대로 2604)달구벌대로2017-06-232017-09-0507:00:0009:00:0017:30:0019:30:002017-09-052024-02-21
1415삼정브리티시 용산APT앞 (달서구 달구벌대로 1512)달구벌대로2017-06-232017-09-0507:00:0009:00:0017:30:0019:30:002017-09-052024-02-21
1516경상여자중학교 건너 (서구 국채보상로 405)국채보상로2017-12-152018-03-0507:00:0009:00:0017:30:0019:30:002018-03-052024-02-21
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1718대명시장 앞 (남구 명덕로 66)명덕로2018-12-132019-03-0407:00:0009:00:0017:30:0019:30:002019-03-042024-02-21
1819교대역 앞 (남구 중앙대로 199-3)중앙대로2018-12-132019-03-0407:00:0009:00:0017:30:0019:30:002019-03-042024-02-21
1920폴리텍대학 대구캠퍼스 앞(서구 서대구로 217)서대구로2023-12-012023-12-0107:00:0009:00:0017:30:0019:30:002023-12-012024-02-21
2021대구은행 본점 월편(수성구 달구벌대로 2319)달구벌대로2023-12-012023-12-0107:00:0009:00:0017:30:0019:30:002023-12-012024-02-21