Overview

Dataset statistics

Number of variables7
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory63.3 B

Variable types

Text3
Categorical1
Numeric2
DateTime1

Dataset

Description충청북도 충주시 교차로내 교통정보 수집 목적으로 설치한 교통관제 웹카메라 정보(관리번호, 소재지 지번주소, 설치위치명, 관리기관, 위도, 경도, 데이터 기준일자)
Author충청북도 충주시
URLhttps://www.data.go.kr/data/15041999/fileData.do

Alerts

관리기관 has constant value ""Constant
데이터기준일자 has constant value ""Constant
관리번호 has unique valuesUnique
소재지지번주소 has unique valuesUnique
설치위치명 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-03-14 13:25:10.019500
Analysis finished2024-03-14 13:25:11.898552
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size320.0 B
2024-03-14T22:25:12.569392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters240
Distinct characters15
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st rowCCTV-웹-001
2nd rowCCTV-웹-002
3rd rowCCTV-웹-003
4th rowCCTV-웹-004
5th rowCCTV-웹-005
ValueCountFrequency (%)
cctv-웹-001 1
 
4.2%
cctv-웹-002 1
 
4.2%
cctv-웹-023 1
 
4.2%
cctv-웹-022 1
 
4.2%
cctv-웹-021 1
 
4.2%
cctv-웹-020 1
 
4.2%
cctv-웹-019 1
 
4.2%
cctv-웹-018 1
 
4.2%
cctv-웹-017 1
 
4.2%
cctv-웹-016 1
 
4.2%
Other values (14) 14
58.3%
2024-03-14T22:25:13.805144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 48
20.0%
- 48
20.0%
0 35
14.6%
T 24
10.0%
V 24
10.0%
웹 24
10.0%
1 13
 
5.4%
2 8
 
3.3%
3 3
 
1.2%
4 3
 
1.2%
Other values (5) 10
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 96
40.0%
Decimal Number 72
30.0%
Dash Punctuation 48
20.0%
Other Letter 24
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35
48.6%
1 13
 
18.1%
2 8
 
11.1%
3 3
 
4.2%
4 3
 
4.2%
5 2
 
2.8%
6 2
 
2.8%
7 2
 
2.8%
8 2
 
2.8%
9 2
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
C 48
50.0%
T 24
25.0%
V 24
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Other Letter
ValueCountFrequency (%)
웹 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120
50.0%
Latin 96
40.0%
Hangul 24
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 48
40.0%
0 35
29.2%
1 13
 
10.8%
2 8
 
6.7%
3 3
 
2.5%
4 3
 
2.5%
5 2
 
1.7%
6 2
 
1.7%
7 2
 
1.7%
8 2
 
1.7%
Latin
ValueCountFrequency (%)
C 48
50.0%
T 24
25.0%
V 24
25.0%
Hangul
ValueCountFrequency (%)
웹 24
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216
90.0%
Hangul 24
 
10.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 48
22.2%
- 48
22.2%
0 35
16.2%
T 24
11.1%
V 24
11.1%
1 13
 
6.0%
2 8
 
3.7%
3 3
 
1.4%
4 3
 
1.4%
5 2
 
0.9%
Other values (4) 8
 
3.7%
Hangul
ValueCountFrequency (%)
웹 24
100.0%

소재지지번주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size320.0 B
2024-03-14T22:25:14.482857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15.5
Mean length13.333333
Min length10

Characters and Unicode

Total characters320
Distinct characters53
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

Unique24 ?
Unique (%)100.0%

Sample

1st row충주시 칠금동 388-8
2nd row충주시 칠금동 103-2
3rd row충주시 금릉동 26
4th row충주시 연수동 1722
5th row충주시 연수동 438-5
ValueCountFrequency (%)
충주시 23
31.9%
칠금동 4
 
5.6%
교현동 3
 
4.2%
연수동 3
 
4.2%
대소원면 2
 
2.8%
문화동 2
 
2.8%
달천동 2
 
2.8%
호암동 2
 
2.8%
봉방동 2
 
2.8%
본리 1
 
1.4%
Other values (28) 28
38.9%
2024-03-14T22:25:15.457418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
15.0%
충 23
 
7.2%
시 23
 
7.2%
주 23
 
7.2%
1 23
 
7.2%
동 21
 
6.6%
5 14
 
4.4%
- 13
 
4.1%
2 13
 
4.1%
8 10
 
3.1%
Other values (43) 109
34.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 173
54.1%
Decimal Number 86
26.9%
Space Separator 48
 
15.0%
Dash Punctuation 13
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 23
13.3%
시 23
13.3%
주 23
13.3%
동 21
12.1%
번 9
 
5.2%
지 9
 
5.2%
금 5
 
2.9%
칠 4
 
2.3%
연 3
 
1.7%
수 3
 
1.7%
Other values (31) 50
28.9%
Decimal Number
ValueCountFrequency (%)
1 23
26.7%
5 14
16.3%
2 13
15.1%
8 10
11.6%
3 6
 
7.0%
7 5
 
5.8%
6 5
 
5.8%
0 5
 
5.8%
9 3
 
3.5%
4 2
 
2.3%
Space Separator
ValueCountFrequency (%)
48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 173
54.1%
Common 147
45.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 23
13.3%
시 23
13.3%
주 23
13.3%
동 21
12.1%
번 9
 
5.2%
지 9
 
5.2%
금 5
 
2.9%
칠 4
 
2.3%
연 3
 
1.7%
수 3
 
1.7%
Other values (31) 50
28.9%
Common
ValueCountFrequency (%)
48
32.7%
1 23
15.6%
5 14
 
9.5%
- 13
 
8.8%
2 13
 
8.8%
8 10
 
6.8%
3 6
 
4.1%
7 5
 
3.4%
6 5
 
3.4%
0 5
 
3.4%
Other values (2) 5
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 173
54.1%
ASCII 147
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48
32.7%
1 23
15.6%
5 14
 
9.5%
- 13
 
8.8%
2 13
 
8.8%
8 10
 
6.8%
3 6
 
4.1%
7 5
 
3.4%
6 5
 
3.4%
0 5
 
3.4%
Other values (2) 5
 
3.4%
Hangul
ValueCountFrequency (%)
충 23
13.3%
시 23
13.3%
주 23
13.3%
동 21
12.1%
번 9
 
5.2%
지 9
 
5.2%
금 5
 
2.9%
칠 4
 
2.3%
연 3
 
1.7%
수 3
 
1.7%
Other values (31) 50
28.9%

설치위치명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size320.0 B
2024-03-14T22:25:16.218361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.3333333
Min length5

Characters and Unicode

Total characters152
Distinct characters59
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row무술공원앞삼거리
2nd row금릉사거리
3rd row금릉초교사거리
4th row연수초교사거리
5th row체육관사거리
ValueCountFrequency (%)
무술공원앞삼거리 1
 
4.0%
제1로터리 1
 
4.0%
연수힐스테이트사거리 1
 
4.0%
안림사거리 1
 
4.0%
건대사거리 1
 
4.0%
문화사거리 1
 
4.0%
apt사거리 1
 
4.0%
유원 1
 
4.0%
법원사거리 1
 
4.0%
칠금사거리 1
 
4.0%
Other values (15) 15
60.0%
2024-03-14T22:25:17.201309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 26
17.1%
거 23
 
15.1%
사 22
 
14.5%
원 4
 
2.6%
금 3
 
2.0%
수 3
 
2.0%
삼 3
 
2.0%
로 2
 
1.3%
P 2
 
1.3%
T 2
 
1.3%
Other values (49) 62
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 144
94.7%
Uppercase Letter 6
 
3.9%
Space Separator 1
 
0.7%
Decimal Number 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 26
18.1%
거 23
16.0%
사 22
15.3%
원 4
 
2.8%
금 3
 
2.1%
수 3
 
2.1%
삼 3
 
2.1%
로 2
 
1.4%
대 2
 
1.4%
무 2
 
1.4%
Other values (44) 54
37.5%
Uppercase Letter
ValueCountFrequency (%)
P 2
33.3%
T 2
33.3%
A 2
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 144
94.7%
Latin 6
 
3.9%
Common 2
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 26
18.1%
거 23
16.0%
사 22
15.3%
원 4
 
2.8%
금 3
 
2.1%
수 3
 
2.1%
삼 3
 
2.1%
로 2
 
1.4%
대 2
 
1.4%
무 2
 
1.4%
Other values (44) 54
37.5%
Latin
ValueCountFrequency (%)
P 2
33.3%
T 2
33.3%
A 2
33.3%
Common
ValueCountFrequency (%)
1
50.0%
1 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 144
94.7%
ASCII 8
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 26
18.1%
거 23
16.0%
사 22
15.3%
원 4
 
2.8%
금 3
 
2.1%
수 3
 
2.1%
삼 3
 
2.1%
로 2
 
1.4%
대 2
 
1.4%
무 2
 
1.4%
Other values (44) 54
37.5%
ASCII
ValueCountFrequency (%)
P 2
25.0%
T 2
25.0%
A 2
25.0%
1
12.5%
1 1
12.5%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
충청북도 충주시청 교통정책과
24 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청북도 충주시청 교통정책과
2nd row충청북도 충주시청 교통정책과
3rd row충청북도 충주시청 교통정책과
4th row충청북도 충주시청 교통정책과
5th row충청북도 충주시청 교통정책과

Common Values

ValueCountFrequency (%)
충청북도 충주시청 교통정책과 24
100.0%

Length

2024-03-14T22:25:17.417320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:25:17.574033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청북도 24
33.3%
충주시청 24
33.3%
교통정책과 24
33.3%

위도
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.978042
Minimum36.957603
Maximum36.99915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-14T22:25:17.748450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.957603
5-th percentile36.961211
Q136.969363
median36.979805
Q336.985497
95-th percentile36.992652
Maximum36.99915
Range0.0415475
Interquartile range (IQR)0.016134175

Descriptive statistics

Standard deviation0.010292348
Coefficient of variation (CV)0.00027833676
Kurtosis-0.34992056
Mean36.978042
Median Absolute Deviation (MAD)0.0074067
Skewness-0.11116052
Sum887.473
Variance0.00010593243
MonotonicityNot monotonic
2024-03-14T22:25:17.960709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
36.9861322 1
 
4.2%
36.9723188 1
 
4.2%
36.9576028 1
 
4.2%
36.9871454 1
 
4.2%
36.9694146 1
 
4.2%
36.9663539 1
 
4.2%
36.9728644 1
 
4.2%
36.9822457 1
 
4.2%
36.9821659 1
 
4.2%
36.9810932 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
36.9576028 1
4.2%
36.960304 1
4.2%
36.9663539 1
4.2%
36.9671831 1
4.2%
36.9691806 1
4.2%
36.9692064 1
4.2%
36.9694146 1
4.2%
36.9723188 1
4.2%
36.9728644 1
4.2%
36.9749681 1
4.2%
ValueCountFrequency (%)
36.9991503 1
4.2%
36.9935387 1
4.2%
36.9876259 1
4.2%
36.9872777 1
4.2%
36.9871454 1
4.2%
36.9861322 1
4.2%
36.9852849 1
4.2%
36.9826647 1
4.2%
36.98254 1
4.2%
36.9822457 1
4.2%

경도
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.91927
Minimum127.83117
Maximum127.94684
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-14T22:25:18.168313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.83117
5-th percentile127.85118
Q1127.91547
median127.92551
Q3127.9355
95-th percentile127.94497
Maximum127.94684
Range0.1156737
Interquartile range (IQR)0.020029975

Descriptive statistics

Standard deviation0.028052047
Coefficient of variation (CV)0.00021929492
Kurtosis5.5101968
Mean127.91927
Median Absolute Deviation (MAD)0.0106946
Skewness-2.3036285
Sum3070.0625
Variance0.00078691734
MonotonicityNot monotonic
2024-03-14T22:25:18.465131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
127.9039782 1
 
4.2%
127.9330595 1
 
4.2%
127.940401 1
 
4.2%
127.9457739 1
 
4.2%
127.9468389 1
 
4.2%
127.9068169 1
 
4.2%
127.9229793 1
 
4.2%
127.9398351 1
 
4.2%
127.9284017 1
 
4.2%
127.9131371 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
127.8311652 1
4.2%
127.8418628 1
4.2%
127.9039782 1
4.2%
127.9068169 1
4.2%
127.9131371 1
4.2%
127.9134941 1
4.2%
127.9161344 1
4.2%
127.917774 1
4.2%
127.9178759 1
4.2%
127.9229793 1
4.2%
ValueCountFrequency (%)
127.9468389 1
4.2%
127.9457739 1
4.2%
127.940401 1
4.2%
127.9398351 1
4.2%
127.9393191 1
4.2%
127.9382826 1
4.2%
127.9345782 1
4.2%
127.9330595 1
4.2%
127.9284017 1
4.2%
127.9280931 1
4.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
Minimum2024-01-01 00:00:00
Maximum2024-01-01 00:00:00
2024-03-14T22:25:18.647607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:25:18.806940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-14T22:25:10.779107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:25:10.298735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:25:11.022500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:25:10.533614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T22:25:18.929107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호소재지지번주소설치위치명위도경도
관리번호1.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.000
설치위치명1.0001.0001.0001.0001.000
위도1.0001.0001.0001.0000.238
경도1.0001.0001.0000.2381.000
2024-03-14T22:25:19.092695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.188
경도-0.1881.000

Missing values

2024-03-14T22:25:11.369562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:25:11.749194image/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

관리번호소재지지번주소설치위치명관리기관위도경도데이터기준일자
0CCTV-웹-001충주시 칠금동 388-8무술공원앞삼거리충청북도 충주시청 교통정책과36.986132127.9039782024-01-01
1CCTV-웹-002충주시 칠금동 103-2금릉사거리충청북도 충주시청 교통정책과36.987626127.9177742024-01-01
2CCTV-웹-003충주시 금릉동 26금릉초교사거리충청북도 충주시청 교통정책과36.993539127.9280782024-01-01
3CCTV-웹-004충주시 연수동 1722연수초교사거리충청북도 충주시청 교통정책과36.987278127.9393192024-01-01
4CCTV-웹-005충주시 연수동 438-5체육관사거리충청북도 충주시청 교통정책과36.98254127.9345782024-01-01
5CCTV-웹-006충주시 칠금동 1135동신APT삼거리충청북도 충주시청 교통정책과36.982665127.9161342024-01-01
6CCTV-웹-007충주시 봉방동 86-1봉계사거리충청북도 충주시청 교통정책과36.978516127.9178762024-01-01
7CCTV-웹-008충주시 교현동 665대가미사거리충청북도 충주시청 교통정책과36.978219127.9280932024-01-01
8CCTV-웹-009충주시 봉방동 13-2삼원로터리사거리충청북도 충주시청 교통정책과36.974968127.9245812024-01-01
9CCTV-웹-010충주시 달천동 51-2사과나무사거리충청북도 충주시청 교통정책과36.969206127.9134942024-01-01
관리번호소재지지번주소설치위치명관리기관위도경도데이터기준일자
14CCTV-웹-015충주시 대소원면 본리 1102코이즈앞사거리충청북도 충주시청 교통정책과36.985285127.8311652024-01-01
15CCTV-웹-016충주시 호암동 558-18번지호암사거리충청북도 충주시청 교통정책과36.960304127.9264372024-01-01
16CCTV-웹-017충주시 칠금동 551-1번지칠금사거리충청북도 충주시청 교통정책과36.981093127.9131372024-01-01
17CCTV-웹-018충주시 교현동 1114번지법원사거리충청북도 충주시청 교통정책과36.982166127.9284022024-01-01
18CCTV-웹-019한림디자인고앞사거리유원 APT사거리충청북도 충주시청 교통정책과36.982246127.9398352024-01-01
19CCTV-웹-020충주시 문화동 572번지문화사거리충청북도 충주시청 교통정책과36.972864127.9229792024-01-01
20CCTV-웹-021충주시 달천동 880번지건대사거리충청북도 충주시청 교통정책과36.966354127.9068172024-01-01
21CCTV-웹-022충주시 안림동 1097-5번지안림사거리충청북도 충주시청 교통정책과36.969415127.9468392024-01-01
22CCTV-웹-023충주시 연수동 79-2번지연수힐스테이트사거리충청북도 충주시청 교통정책과36.987145127.9457742024-01-01
23CCTV-웹-024충주시 호암동 185-12번지더조은사거리충청북도 충주시청 교통정책과36.957603127.9404012024-01-01