Overview

Dataset statistics

Number of variables19
Number of observations42
Missing cells12
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory164.1 B

Variable types

Text5
Numeric3
Categorical8
DateTime1
Boolean2

Dataset

Description인천광역시 VMS 기초 정보(VMS아이디, 통신번호, 설치위치, 설치일자, 설치회사, 수집주기, X좌표, Y좌표 등) 데이터입니다.
Author인천광역시
URLhttps://www.data.go.kr/data/15089888/fileData.do

Alerts

VMS종류 is highly overall correlated with 브이엠에스통신번호 and 2 other fieldsHigh correlation
설치회사 is highly overall correlated with 브이엠에스통신번호 and 6 other fieldsHigh correlation
시선유도등부착여부 is highly overall correlated with 브이엠에스통신번호 and 2 other fieldsHigh correlation
모니터링피씨번호 is highly overall correlated with 브이엠에스통신번호 and 5 other fieldsHigh correlation
통신포트 is highly overall correlated with 설치회사 and 2 other fieldsHigh correlation
유지보수회사 is highly overall correlated with 와이좌표 and 9 other fieldsHigh correlation
모니터링모니터번호 is highly overall correlated with 설치회사 and 2 other fieldsHigh correlation
최대페이즈수 is highly overall correlated with 설치회사 and 2 other fieldsHigh correlation
웹카메라부착여부 is highly overall correlated with 브이엠에스통신번호 and 4 other fieldsHigh correlation
상태수집주기 is highly overall correlated with 설치회사 and 2 other fieldsHigh correlation
브이엠에스통신번호 is highly overall correlated with VMS종류 and 4 other fieldsHigh correlation
엑스좌표 is highly overall correlated with 웹카메라부착여부High correlation
와이좌표 is highly overall correlated with 유지보수회사 and 1 other fieldsHigh correlation
상태수집주기 is highly imbalanced (83.8%)Imbalance
최대페이즈수 is highly imbalanced (83.8%)Imbalance
웹카메라부착여부 is highly imbalanced (62.9%)Imbalance
통신포트 is highly imbalanced (83.8%)Imbalance
모니터링모니터번호 is highly imbalanced (83.8%)Imbalance
웹카메라주소 has 3 (7.1%) missing valuesMissing
엑스좌표 has 3 (7.1%) missing valuesMissing
와이좌표 has 3 (7.1%) missing valuesMissing
웹캠아이피 has 3 (7.1%) missing valuesMissing
브이엠에스아이디 has unique valuesUnique
브이엠에스통신번호 has unique valuesUnique
설치위치 has unique valuesUnique
유선IP주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:55:22.072295
Analysis finished2023-12-12 10:55:26.253224
Duration4.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

브이엠에스아이디
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T19:55:26.484143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters420
Distinct characters12
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

Unique42 ?
Unique (%)100.0%

Sample

1st rowVM00000330
2nd rowVM00000340
3rd rowVM00000420
4th rowVM00000390
5th rowVM00000400
ValueCountFrequency (%)
vm00000330 1
 
2.4%
vm00000240 1
 
2.4%
vm00000370 1
 
2.4%
vm00000090 1
 
2.4%
vm00000100 1
 
2.4%
vm00000110 1
 
2.4%
vm00000120 1
 
2.4%
vm00000270 1
 
2.4%
vm00000260 1
 
2.4%
vm00000250 1
 
2.4%
Other values (32) 32
76.2%
2023-12-12T19:55:26.989986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 265
63.1%
V 42
 
10.0%
M 42
 
10.0%
1 15
 
3.6%
2 15
 
3.6%
3 14
 
3.3%
4 7
 
1.7%
6 4
 
1.0%
5 4
 
1.0%
9 4
 
1.0%
Other values (2) 8
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 336
80.0%
Uppercase Letter 84
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 265
78.9%
1 15
 
4.5%
2 15
 
4.5%
3 14
 
4.2%
4 7
 
2.1%
6 4
 
1.2%
5 4
 
1.2%
9 4
 
1.2%
7 4
 
1.2%
8 4
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
V 42
50.0%
M 42
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 336
80.0%
Latin 84
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 265
78.9%
1 15
 
4.5%
2 15
 
4.5%
3 14
 
4.2%
4 7
 
2.1%
6 4
 
1.2%
5 4
 
1.2%
9 4
 
1.2%
7 4
 
1.2%
8 4
 
1.2%
Latin
ValueCountFrequency (%)
V 42
50.0%
M 42
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 265
63.1%
V 42
 
10.0%
M 42
 
10.0%
1 15
 
3.6%
2 15
 
3.6%
3 14
 
3.3%
4 7
 
1.7%
6 4
 
1.0%
5 4
 
1.0%
9 4
 
1.0%
Other values (2) 8
 
1.9%

브이엠에스통신번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1021.5
Minimum1001
Maximum1042
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T19:55:27.231042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1001
5-th percentile1003.05
Q11011.25
median1021.5
Q31031.75
95-th percentile1039.95
Maximum1042
Range41
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation12.267844
Coefficient of variation (CV)0.012009637
Kurtosis-1.2
Mean1021.5
Median Absolute Deviation (MAD)10.5
Skewness0
Sum42903
Variance150.5
MonotonicityNot monotonic
2023-12-12T19:55:27.447145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
1033 1
 
2.4%
1022 1
 
2.4%
1010 1
 
2.4%
1011 1
 
2.4%
1012 1
 
2.4%
1027 1
 
2.4%
1026 1
 
2.4%
1025 1
 
2.4%
1024 1
 
2.4%
1023 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
1001 1
2.4%
1002 1
2.4%
1003 1
2.4%
1004 1
2.4%
1005 1
2.4%
1006 1
2.4%
1007 1
2.4%
1008 1
2.4%
1009 1
2.4%
1010 1
2.4%
ValueCountFrequency (%)
1042 1
2.4%
1041 1
2.4%
1040 1
2.4%
1039 1
2.4%
1038 1
2.4%
1037 1
2.4%
1036 1
2.4%
1035 1
2.4%
1034 1
2.4%
1033 1
2.4%

설치위치
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T19:55:27.855170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.3095238
Min length3

Characters and Unicode

Total characters223
Distinct characters101
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row청라보금자리
2nd row봉수대길사거리
3rd row인하대병원사거리
4th row송도2교
5th row학익동풍림APT앞
ValueCountFrequency (%)
청라보금자리 1
 
2.4%
백석교 1
 
2.4%
뉴서울apt건너편 1
 
2.4%
장승백이사거리 1
 
2.4%
부개사거리 1
 
2.4%
서구청 1
 
2.4%
계양ic 1
 
2.4%
검문소삼거리 1
 
2.4%
여래교 1
 
2.4%
유현사거리 1
 
2.4%
Other values (32) 32
76.2%
2023-12-12T19:55:28.513542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 20
 
9.0%
거 19
 
8.5%
사 18
 
8.1%
구 8
 
3.6%
서 7
 
3.1%
동 6
 
2.7%
교 5
 
2.2%
역 4
 
1.8%
학 4
 
1.8%
입 3
 
1.3%
Other values (91) 129
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 207
92.8%
Uppercase Letter 15
 
6.7%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 20
 
9.7%
거 19
 
9.2%
사 18
 
8.7%
구 8
 
3.9%
서 7
 
3.4%
동 6
 
2.9%
교 5
 
2.4%
역 4
 
1.9%
학 4
 
1.9%
입 3
 
1.4%
Other values (85) 113
54.6%
Uppercase Letter
ValueCountFrequency (%)
T 3
20.0%
P 3
20.0%
A 3
20.0%
I 3
20.0%
C 3
20.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 207
92.8%
Latin 15
 
6.7%
Common 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 20
 
9.7%
거 19
 
9.2%
사 18
 
8.7%
구 8
 
3.9%
서 7
 
3.4%
동 6
 
2.9%
교 5
 
2.4%
역 4
 
1.9%
학 4
 
1.9%
입 3
 
1.4%
Other values (85) 113
54.6%
Latin
ValueCountFrequency (%)
T 3
20.0%
P 3
20.0%
A 3
20.0%
I 3
20.0%
C 3
20.0%
Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 207
92.8%
ASCII 16
 
7.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 20
 
9.7%
거 19
 
9.2%
사 18
 
8.7%
구 8
 
3.9%
서 7
 
3.4%
동 6
 
2.9%
교 5
 
2.4%
역 4
 
1.9%
학 4
 
1.9%
입 3
 
1.4%
Other values (85) 113
54.6%
ASCII
ValueCountFrequency (%)
T 3
18.8%
P 3
18.8%
A 3
18.8%
I 3
18.8%
C 3
18.8%
2 1
 
6.2%

VMS종류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
1
35 
2
7 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 35
83.3%
2 7
 
16.7%

Length

2023-12-12T19:55:28.736203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:28.913975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 35
83.3%
2 7
 
16.7%

설치일자
Date

Distinct12
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum2008-06-09 00:00:00
Maximum2018-01-01 00:00:00
2023-12-12T19:55:29.074371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:29.261698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

설치회사
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size468.0 B
래도
25 
현대ITS
7 
싸인텔레콤
5 
<NA>
3 
케이ENG(주)
 
2

Length

Max length8
Median length2
Mean length3.2857143
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row래도
2nd row래도
3rd row<NA>
4th row현대ITS
5th row케이ENG(주)

Common Values

ValueCountFrequency (%)
래도 25
59.5%
현대ITS 7
 
16.7%
싸인텔레콤 5
 
11.9%
<NA> 3
 
7.1%
케이ENG(주) 2
 
4.8%

Length

2023-12-12T19:55:29.489079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:29.684073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
래도 25
59.5%
현대its 7
 
16.7%
싸인텔레콤 5
 
11.9%
na 3
 
7.1%
케이eng(주 2
 
4.8%

유지보수회사
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
<NA>
33 
래도
6 
케이ENG(주)
 
2
현대ITS
 
1

Length

Max length8
Median length4
Mean length3.9285714
Min length2

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row래도
2nd row래도
3rd row<NA>
4th row현대ITS
5th row케이ENG(주)

Common Values

ValueCountFrequency (%)
<NA> 33
78.6%
래도 6
 
14.3%
케이ENG(주) 2
 
4.8%
현대ITS 1
 
2.4%

Length

2023-12-12T19:55:29.901834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:30.086192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 33
78.6%
래도 6
 
14.3%
케이eng(주 2
 
4.8%
현대its 1
 
2.4%

상태수집주기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
30
41 
300
 
1

Length

Max length3
Median length2
Mean length2.0238095
Min length2

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row30
2nd row30
3rd row300
4th row30
5th row30

Common Values

ValueCountFrequency (%)
30 41
97.6%
300 1
 
2.4%

Length

2023-12-12T19:55:30.265201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:30.402965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 41
97.6%
300 1
 
2.4%

최대페이즈수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
10
41 
0
 
1

Length

Max length2
Median length2
Mean length1.9761905
Min length1

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row10
2nd row10
3rd row0
4th row10
5th row10

Common Values

ValueCountFrequency (%)
10 41
97.6%
0 1
 
2.4%

Length

2023-12-12T19:55:30.549276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:30.721414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 41
97.6%
0 1
 
2.4%

유선IP주소
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T19:55:31.026955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length13.595238
Min length12

Characters and Unicode

Total characters571
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row192.168.62.11
2nd row192.168.64.11
3rd row192.168.105.200
4th row192.168.24.252
5th row192.168.105.58
ValueCountFrequency (%)
192.168.62.11 1
 
2.4%
192.168.24.175 1
 
2.4%
192.168.71.23 1
 
2.4%
192.168.24.154 1
 
2.4%
192.168.24.155 1
 
2.4%
192.168.24.159 1
 
2.4%
192.168.24.158 1
 
2.4%
192.168.54.11 1
 
2.4%
192.168.55.11 1
 
2.4%
192.168.57.11 1
 
2.4%
Other values (32) 32
76.2%
2023-12-12T19:55:31.536661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 131
22.9%
. 126
22.1%
2 85
14.9%
8 50
 
8.8%
6 49
 
8.6%
9 45
 
7.9%
4 31
 
5.4%
5 21
 
3.7%
0 14
 
2.5%
7 12
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 445
77.9%
Other Punctuation 126
 
22.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 131
29.4%
2 85
19.1%
8 50
 
11.2%
6 49
 
11.0%
9 45
 
10.1%
4 31
 
7.0%
5 21
 
4.7%
0 14
 
3.1%
7 12
 
2.7%
3 7
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 571
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 131
22.9%
. 126
22.1%
2 85
14.9%
8 50
 
8.8%
6 49
 
8.6%
9 45
 
7.9%
4 31
 
5.4%
5 21
 
3.7%
0 14
 
2.5%
7 12
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 571
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 131
22.9%
. 126
22.1%
2 85
14.9%
8 50
 
8.8%
6 49
 
8.6%
9 45
 
7.9%
4 31
 
5.4%
5 21
 
3.7%
0 14
 
2.5%
7 12
 
2.1%

웹카메라주소
Text

MISSING 

Distinct39
Distinct (%)100.0%
Missing3
Missing (%)7.1%
Memory size468.0 B
2023-12-12T19:55:31.883711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length53
Mean length53
Min length53

Characters and Unicode

Total characters2067
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st rowhttp://192.168.48.40/webcam_view.jsp?vmsid=VM00000330
2nd rowhttp://192.168.48.40/webcam_view.jsp?vmsid=VM00000340
3rd rowhttp://192.168.48.40/webcam_view.jsp?vmsid=VM00000420
4th rowhttp://192.168.48.40/webcam_view.jsp?vmsid=VM00000390
5th rowhttp://192.168.48.40/webcam_view.jsp?vmsid=VM00000400
ValueCountFrequency (%)
http://192.168.48.40/webcam_view.jsp?vmsid=vm00000330 1
 
2.6%
http://192.168.48.40/webcam_view.jsp?vmsid=vm00000220 1
 
2.6%
http://192.168.48.40/webcam_view.jsp?vmsid=vm00000090 1
 
2.6%
http://192.168.48.40/webcam_view.jsp?vmsid=vm00000110 1
 
2.6%
http://192.168.48.40/webcam_view.jsp?vmsid=vm00000120 1
 
2.6%
http://192.168.48.40/webcam_view.jsp?vmsid=vm00000270 1
 
2.6%
http://192.168.48.40/webcam_view.jsp?vmsid=vm00000260 1
 
2.6%
http://192.168.48.40/webcam_view.jsp?vmsid=vm00000250 1
 
2.6%
http://192.168.48.40/webcam_view.jsp?vmsid=vm00000240 1
 
2.6%
http://192.168.48.40/webcam_view.jsp?vmsid=vm00000370 1
 
2.6%
Other values (29) 29
74.4%
2023-12-12T19:55:32.502532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 285
 
13.8%
. 156
 
7.5%
/ 117
 
5.7%
1 91
 
4.4%
4 85
 
4.1%
8 82
 
4.0%
v 78
 
3.8%
p 78
 
3.8%
i 78
 
3.8%
t 78
 
3.8%
Other values (22) 939
45.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 858
41.5%
Decimal Number 702
34.0%
Other Punctuation 351
17.0%
Uppercase Letter 78
 
3.8%
Math Symbol 39
 
1.9%
Connector Punctuation 39
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
v 78
9.1%
p 78
9.1%
i 78
9.1%
t 78
9.1%
m 78
9.1%
s 78
9.1%
w 78
9.1%
e 78
9.1%
d 39
 
4.5%
h 39
 
4.5%
Other values (4) 156
18.2%
Decimal Number
ValueCountFrequency (%)
0 285
40.6%
1 91
 
13.0%
4 85
 
12.1%
8 82
 
11.7%
2 52
 
7.4%
6 43
 
6.1%
9 42
 
6.0%
3 14
 
2.0%
5 4
 
0.6%
7 4
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 156
44.4%
/ 117
33.3%
? 39
 
11.1%
: 39
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
V 39
50.0%
M 39
50.0%
Math Symbol
ValueCountFrequency (%)
= 39
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1131
54.7%
Latin 936
45.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 285
25.2%
. 156
13.8%
/ 117
10.3%
1 91
 
8.0%
4 85
 
7.5%
8 82
 
7.3%
2 52
 
4.6%
6 43
 
3.8%
9 42
 
3.7%
= 39
 
3.4%
Other values (6) 139
12.3%
Latin
ValueCountFrequency (%)
v 78
 
8.3%
p 78
 
8.3%
i 78
 
8.3%
t 78
 
8.3%
m 78
 
8.3%
s 78
 
8.3%
w 78
 
8.3%
e 78
 
8.3%
d 39
 
4.2%
h 39
 
4.2%
Other values (6) 234
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 285
 
13.8%
. 156
 
7.5%
/ 117
 
5.7%
1 91
 
4.4%
4 85
 
4.1%
8 82
 
4.0%
v 78
 
3.8%
p 78
 
3.8%
i 78
 
3.8%
t 78
 
3.8%
Other values (22) 939
45.4%

엑스좌표
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct39
Distinct (%)100.0%
Missing3
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean126.68302
Minimum126.42491
Maximum126.74583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T19:55:32.851534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.42491
5-th percentile126.62185
Q1126.66188
median126.68138
Q3126.72474
95-th percentile126.74335
Maximum126.74583
Range0.320928
Interquartile range (IQR)0.0628645

Descriptive statistics

Standard deviation0.056171028
Coefficient of variation (CV)0.00044339825
Kurtosis10.944218
Mean126.68302
Median Absolute Deviation (MAD)0.031585
Skewness-2.5720483
Sum4940.6376
Variance0.0031551844
MonotonicityNot monotonic
2023-12-12T19:55:33.594858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
126.660151 1
 
2.4%
126.676221 1
 
2.4%
126.74529 1
 
2.4%
126.6455 1
 
2.4%
126.6766 1
 
2.4%
126.7174 1
 
2.4%
126.6636 1
 
2.4%
126.623 1
 
2.4%
126.6755 1
 
2.4%
126.745834 1
 
2.4%
Other values (29) 29
69.0%
(Missing) 3
 
7.1%
ValueCountFrequency (%)
126.424906 1
2.4%
126.611549 1
2.4%
126.623 1
2.4%
126.631419 1
2.4%
126.637966 1
2.4%
126.6455 1
2.4%
126.649798 1
2.4%
126.653242 1
2.4%
126.658948 1
2.4%
126.660151 1
2.4%
ValueCountFrequency (%)
126.745834 1
2.4%
126.74529 1
2.4%
126.74313 1
2.4%
126.737595 1
2.4%
126.734299 1
2.4%
126.732829 1
2.4%
126.731702 1
2.4%
126.730966 1
2.4%
126.730042 1
2.4%
126.7277 1
2.4%

와이좌표
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct39
Distinct (%)100.0%
Missing3
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean37.496212
Minimum37.3938
Maximum37.6109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T19:55:33.890909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.3938
5-th percentile37.404423
Q137.44831
median37.50695
Q337.533255
95-th percentile37.59507
Maximum37.6109
Range0.2171
Interquartile range (IQR)0.0849455

Descriptive statistics

Standard deviation0.060011899
Coefficient of variation (CV)0.001600479
Kurtosis-0.92557687
Mean37.496212
Median Absolute Deviation (MAD)0.050941
Skewness0.060124691
Sum1462.3523
Variance0.003601428
MonotonicityNot monotonic
2023-12-12T19:55:34.219847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
37.484002 1
 
2.4%
37.534456 1
 
2.4%
37.544502 1
 
2.4%
37.6074 1
 
2.4%
37.6109 1
 
2.4%
37.5937 1
 
2.4%
37.5731 1
 
2.4%
37.5656 1
 
2.4%
37.5737 1
 
2.4%
37.532054 1
 
2.4%
Other values (29) 29
69.0%
(Missing) 3
 
7.1%
ValueCountFrequency (%)
37.3938 1
2.4%
37.3949 1
2.4%
37.405481 1
2.4%
37.4156 1
2.4%
37.423091 1
2.4%
37.423902 1
2.4%
37.43075 1
2.4%
37.440951 1
2.4%
37.442013 1
2.4%
37.447819 1
2.4%
ValueCountFrequency (%)
37.6109 1
2.4%
37.6074 1
2.4%
37.5937 1
2.4%
37.5737 1
2.4%
37.5731 1
2.4%
37.5656 1
2.4%
37.550396 1
2.4%
37.544502 1
2.4%
37.544033 1
2.4%
37.534456 1
2.4%

시선유도등부착여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size174.0 B
False
33 
True
9 
ValueCountFrequency (%)
False 33
78.6%
True 9
 
21.4%
2023-12-12T19:55:34.454875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

웹카메라부착여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size174.0 B
True
39 
False
 
3
ValueCountFrequency (%)
True 39
92.9%
False 3
 
7.1%
2023-12-12T19:55:34.684322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

통신포트
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
3500
41 
30102
 
1

Length

Max length5
Median length4
Mean length4.0238095
Min length4

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row3500
2nd row3500
3rd row30102
4th row3500
5th row3500

Common Values

ValueCountFrequency (%)
3500 41
97.6%
30102 1
 
2.4%

Length

2023-12-12T19:55:34.924223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:35.136935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3500 41
97.6%
30102 1
 
2.4%

웹캠아이피
Text

MISSING 

Distinct39
Distinct (%)100.0%
Missing3
Missing (%)7.1%
Memory size468.0 B
2023-12-12T19:55:35.491468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length13.564103
Min length12

Characters and Unicode

Total characters529
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st row192.168.62.12
2nd row192.168.64.12
3rd row192.168.105.201
4th row192.168.24.253
5th row192.168.105.59
ValueCountFrequency (%)
192.168.62.12 1
 
2.6%
192.168.24.172 1
 
2.6%
192.168.24.166 1
 
2.6%
192.168.24.162 1
 
2.6%
192.168.24.161 1
 
2.6%
192.168.54.12 1
 
2.6%
192.168.55.12 1
 
2.6%
192.168.57.12 1
 
2.6%
192.168.24.176 1
 
2.6%
192.168.71.24 1
 
2.6%
Other values (29) 29
74.4%
2023-12-12T19:55:36.146765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 119
22.5%
. 117
22.1%
2 79
14.9%
6 55
10.4%
8 45
 
8.5%
9 44
 
8.3%
4 26
 
4.9%
7 14
 
2.6%
5 12
 
2.3%
0 10
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 412
77.9%
Other Punctuation 117
 
22.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 119
28.9%
2 79
19.2%
6 55
13.3%
8 45
 
10.9%
9 44
 
10.7%
4 26
 
6.3%
7 14
 
3.4%
5 12
 
2.9%
0 10
 
2.4%
3 8
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 117
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 529
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 119
22.5%
. 117
22.1%
2 79
14.9%
6 55
10.4%
8 45
 
8.5%
9 44
 
8.3%
4 26
 
4.9%
7 14
 
2.6%
5 12
 
2.3%
0 10
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 529
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 119
22.5%
. 117
22.1%
2 79
14.9%
6 55
10.4%
8 45
 
8.5%
9 44
 
8.3%
4 26
 
4.9%
7 14
 
2.6%
5 12
 
2.3%
0 10
 
1.9%

모니터링피씨번호
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
1
24 
2
15 
3
 
2
0
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row2
2nd row2
3rd row0
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 24
57.1%
2 15
35.7%
3 2
 
4.8%
0 1
 
2.4%

Length

2023-12-12T19:55:36.412628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:36.616422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 24
57.1%
2 15
35.7%
3 2
 
4.8%
0 1
 
2.4%

모니터링모니터번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
1
41 
0
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row1
2nd row1
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 41
97.6%
0 1
 
2.4%

Length

2023-12-12T19:55:36.833712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:37.030683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 41
97.6%
0 1
 
2.4%

Interactions

2023-12-12T19:55:24.965358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:23.997070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:24.472698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:25.105037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:24.139072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:24.641869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:25.263071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:24.308753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:24.807506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:55:37.193407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
브이엠에스아이디브이엠에스통신번호설치위치VMS종류설치일자설치회사유지보수회사상태수집주기최대페이즈수유선IP주소웹카메라주소엑스좌표와이좌표시선유도등부착여부웹카메라부착여부통신포트웹캠아이피모니터링피씨번호모니터링모니터번호
브이엠에스아이디1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
브이엠에스통신번호1.0001.0001.0000.8750.8480.8190.6830.0000.0001.0001.0000.0000.7500.8040.9500.0001.0000.7870.000
설치위치1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
VMS종류1.0000.8751.0001.0000.7170.333NaN0.0000.0001.0001.0000.5750.5860.8190.0000.0001.0000.4320.000
설치일자1.0000.8481.0000.7171.0000.9551.0001.0001.0001.0001.0000.8050.8280.5280.2131.0001.0000.9841.000
설치회사1.0000.8191.0000.3330.9551.0001.000NaNNaN1.0001.0000.6200.6260.0000.782NaN1.0000.501NaN
유지보수회사1.0000.6831.000NaN1.0001.0001.000NaNNaN1.0001.0000.3921.000NaNNaNNaN1.000NaNNaN
상태수집주기1.0000.0001.0000.0001.000NaNNaN1.0000.6711.0001.0000.4740.0000.0000.0000.6711.0001.0000.671
최대페이즈수1.0000.0001.0000.0001.000NaNNaN0.6711.0001.0001.0000.4740.0000.0000.0000.6711.0001.0000.671
유선IP주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
웹카메라주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000NaN1.0001.0001.0001.000
엑스좌표1.0000.0001.0000.5750.8050.6200.3920.4740.4741.0001.0001.0000.6350.456NaN0.4741.0000.4260.474
와이좌표1.0000.7501.0000.5860.8280.6261.0000.0000.0001.0001.0000.6351.0000.368NaN0.0001.0000.0000.000
시선유도등부착여부1.0000.8041.0000.8190.5280.000NaN0.0000.0001.0001.0000.4560.3681.0000.0000.0001.0000.3200.000
웹카메라부착여부1.0000.9501.0000.0000.2130.782NaN0.0000.0001.000NaNNaNNaN0.0001.0000.000NaN0.0000.000
통신포트1.0000.0001.0000.0001.000NaNNaN0.6710.6711.0001.0000.4740.0000.0000.0001.0001.0001.0000.671
웹캠아이피1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000NaN1.0001.0001.0001.000
모니터링피씨번호1.0000.7871.0000.4320.9840.501NaN1.0001.0001.0001.0000.4260.0000.3200.0001.0001.0001.0001.000
모니터링모니터번호1.0000.0001.0000.0001.000NaNNaN0.6710.6711.0001.0000.4740.0000.0000.0000.6711.0001.0001.000
2023-12-12T19:55:37.517740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
VMS종류설치회사시선유도등부착여부모니터링피씨번호통신포트유지보수회사모니터링모니터번호최대페이즈수웹카메라부착여부상태수집주기
VMS종류1.0000.2110.6100.2810.0001.0000.0000.0000.0000.000
설치회사0.2111.0000.0000.4921.0001.0001.0001.0000.5571.000
시선유도등부착여부0.6100.0001.0000.2040.0001.0000.0000.0000.0000.000
모니터링피씨번호0.2810.4920.2041.0000.9751.0000.9750.9750.0000.975
통신포트0.0001.0000.0000.9751.0001.0000.4680.4680.0000.468
유지보수회사1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
모니터링모니터번호0.0001.0000.0000.9750.4681.0001.0000.4680.0000.468
최대페이즈수0.0001.0000.0000.9750.4681.0000.4681.0000.0000.468
웹카메라부착여부0.0000.5570.0000.0000.0001.0000.0000.0001.0000.000
상태수집주기0.0001.0000.0000.9750.4681.0000.4680.4680.0001.000
2023-12-12T19:55:37.733898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
브이엠에스통신번호엑스좌표와이좌표VMS종류설치회사유지보수회사상태수집주기최대페이즈수시선유도등부착여부웹카메라부착여부통신포트모니터링피씨번호모니터링모니터번호
브이엠에스통신번호1.000-0.2560.2140.6290.5890.2890.0000.0000.5670.7240.0000.5580.000
엑스좌표-0.2561.0000.1110.3900.4310.0000.3180.3180.3061.0000.3180.2730.318
와이좌표0.2140.1111.0000.3950.3770.7070.0000.0000.2381.0000.0000.0000.000
VMS종류0.6290.3900.3951.0000.2111.0000.0000.0000.6100.0000.0000.2810.000
설치회사0.5890.4310.3770.2111.0001.0001.0001.0000.0000.5571.0000.4921.000
유지보수회사0.2890.0000.7071.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상태수집주기0.0000.3180.0000.0001.0001.0001.0000.4680.0000.0000.4680.9750.468
최대페이즈수0.0000.3180.0000.0001.0001.0000.4681.0000.0000.0000.4680.9750.468
시선유도등부착여부0.5670.3060.2380.6100.0001.0000.0000.0001.0000.0000.0000.2040.000
웹카메라부착여부0.7241.0001.0000.0000.5571.0000.0000.0000.0001.0000.0000.0000.000
통신포트0.0000.3180.0000.0001.0001.0000.4680.4680.0000.0001.0000.9750.468
모니터링피씨번호0.5580.2730.0000.2810.4921.0000.9750.9750.2040.0000.9751.0000.975
모니터링모니터번호0.0000.3180.0000.0001.0001.0000.4680.4680.0000.0000.4680.9751.000

Missing values

2023-12-12T19:55:25.504946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:55:25.866217image/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.
2023-12-12T19:55:26.121898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

브이엠에스아이디브이엠에스통신번호설치위치VMS종류설치일자설치회사유지보수회사상태수집주기최대페이즈수유선IP주소웹카메라주소엑스좌표와이좌표시선유도등부착여부웹카메라부착여부통신포트웹캠아이피모니터링피씨번호모니터링모니터번호
0VM000003301033청라보금자리12012-12-20래도래도3010192.168.62.11http://192.168.48.40/webcam_view.jsp?vmsid=VM00000330126.66364837.550396NY3500192.168.62.1221
1VM000003401034봉수대길사거리12012-12-19래도래도3010192.168.64.11http://192.168.48.40/webcam_view.jsp?vmsid=VM00000340126.66015137.484002NY3500192.168.64.1221
2VM000004201042인하대병원사거리12018-01-01<NA><NA>3000192.168.105.200http://192.168.48.40/webcam_view.jsp?vmsid=VM00000420126.63796637.456009NY30102192.168.105.20100
3VM000003901039송도2교12014-11-14현대ITS현대ITS3010192.168.24.252http://192.168.48.40/webcam_view.jsp?vmsid=VM00000390126.64979837.405481NY3500192.168.24.25321
4VM000004001040학익동풍림APT앞12015-05-04케이ENG(주)케이ENG(주)3010192.168.105.58http://192.168.48.40/webcam_view.jsp?vmsid=VM00000400126.65894837.442013NY3500192.168.105.5921
5VM000004101041영종잠진도입구12015-05-05케이ENG(주)케이ENG(주)3010192.168.105.67http://192.168.48.40/webcam_view.jsp?vmsid=VM00000410126.42490637.423902NY3500192.168.105.6621
6VM000001301013신촌사거리22010-07-01래도<NA>3010192.168.30.19http://192.168.48.40/webcam_view.jsp?vmsid=VM00000130126.695737.4793YY3500192.168.3.16211
7VM000001401014신연수사거리22010-07-01래도<NA>3010192.168.32.12http://192.168.48.40/webcam_view.jsp?vmsid=VM00000140126.691137.4156YY3500192.168.32.1311
8VM000001501015동막역사거리22010-07-01래도<NA>3010192.168.32.20http://192.168.48.40/webcam_view.jsp?vmsid=VM00000150126.669337.3949YY3500192.168.32.2111
9VM000001601016고잔사거리22010-07-01래도<NA>3010192.168.34.18http://192.168.48.40/webcam_view.jsp?vmsid=VM00000160126.689837.3938YY3500192.168.34.1911
브이엠에스아이디브이엠에스통신번호설치위치VMS종류설치일자설치회사유지보수회사상태수집주기최대페이즈수유선IP주소웹카메라주소엑스좌표와이좌표시선유도등부착여부웹카메라부착여부통신포트웹캠아이피모니터링피씨번호모니터링모니터번호
32VM000002201022시천교12011-11-01현대ITS<NA>3010192.168.24.171http://192.168.48.40/webcam_view.jsp?vmsid=VM00000220126.675537.5737NY3500192.168.24.17221
33VM000002801028서운사거리12012-06-19싸인텔레콤<NA>3010192.168.24.180http://192.168.48.40/webcam_view.jsp?vmsid=VM00000280126.74583437.532054NY3500192.168.24.18131
34VM000002901029작전역12012-06-19싸인텔레콤<NA>3010192.168.24.182http://192.168.48.40/webcam_view.jsp?vmsid=VM00000290126.73096637.530527NY3500192.168.24.18331
35VM000003001030임학역12012-06-19싸인텔레콤<NA>3010192.168.24.184http://192.168.48.40/webcam_view.jsp?vmsid=VM00000300126.73759537.544033NY3500192.168.24.18521
36VM000003101031삼산사거리12012-06-19싸인텔레콤<NA>3010192.168.24.186http://192.168.48.40/webcam_view.jsp?vmsid=VM00000310126.73004237.516806NY3500192.168.24.18721
37VM000003201032갈산역12012-06-19싸인텔레콤<NA>3010192.168.24.188http://192.168.48.40/webcam_view.jsp?vmsid=VM00000320126.7217837.520327NY3500192.168.24.18921
38VM000003501035가정치안센터앞12014-08-30래도래도3010192.168.71.6http://192.168.48.40/webcam_view.jsp?vmsid=VM00000350126.65324237.525533NY3500192.168.71.721
39VM000003601036뉴서울APT앞12014-08-30래도래도3010192.168.71.27http://192.168.48.40/webcam_view.jsp?vmsid=VM00000360126.68138337.524654NY3500192.168.71.2821
40VM000003701037뉴서울APT건너편12014-08-30래도래도3010192.168.71.23http://192.168.48.40/webcam_view.jsp?vmsid=VM00000370126.68134937.524221NY3500192.168.71.2421
41VM000003801038수협화전지점12014-08-30래도래도3010192.168.72.6http://192.168.48.40/webcam_view.jsp?vmsid=VM00000380126.73170237.530655NY3500192.168.72.721