Overview

Dataset statistics

Number of variables16
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory139.3 B

Variable types

Text2
Numeric3
Categorical9
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

최대페이즈수 has constant value ""Constant
웹카메라부착여부 has constant value ""Constant
모니터링모니터번호 has constant value ""Constant
VMS종류 is highly overall correlated with 브이엠에스통신번호 and 5 other fieldsHigh correlation
설치회사 is highly overall correlated with 설치일자 and 4 other fieldsHigh correlation
시선유도등부착여부 is highly overall correlated with 브이엠에스통신번호 and 3 other fieldsHigh correlation
통신포트 is highly overall correlated with VMS종류 and 3 other fieldsHigh correlation
유지보수회사 is highly overall correlated with 브이엠에스통신번호 and 8 other fieldsHigh correlation
상태수집주기 is highly overall correlated with VMS종류 and 3 other fieldsHigh correlation
브이엠에스통신번호 is highly overall correlated with VMS종류 and 4 other fieldsHigh correlation
엑스좌표 is highly overall correlated with 설치일자High correlation
와이좌표 is highly overall correlated with 유지보수회사High correlation
설치일자 is highly overall correlated with 브이엠에스통신번호 and 8 other fieldsHigh correlation
모니터링피씨번호 is highly overall correlated with 브이엠에스통신번호 and 3 other fieldsHigh correlation
VMS종류 is highly imbalanced (51.3%)Imbalance
상태수집주기 is highly imbalanced (83.1%)Imbalance
통신포트 is highly imbalanced (83.1%)Imbalance
브이엠에스아이디 has unique valuesUnique
브이엠에스통신번호 has unique valuesUnique
설치위치 has unique valuesUnique
엑스좌표 has unique valuesUnique
와이좌표 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:55:39.239506
Analysis finished2023-12-12 10:55:42.698219
Duration3.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

브이엠에스아이디
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T19:55:42.957865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters400
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

Unique40 ?
Unique (%)100.0%

Sample

1st rowVM00000010
2nd rowVM00000020
3rd rowVM00000040
4th rowVM00000050
5th rowVM00000060
ValueCountFrequency (%)
vm00000010 1
 
2.5%
vm00000020 1
 
2.5%
vm00000340 1
 
2.5%
vm00000270 1
 
2.5%
vm00000280 1
 
2.5%
vm00000290 1
 
2.5%
vm00000300 1
 
2.5%
vm00000310 1
 
2.5%
vm00000320 1
 
2.5%
vm00000330 1
 
2.5%
Other values (30) 30
75.0%
2023-12-12T19:55:43.560686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 251
62.7%
V 40
 
10.0%
M 40
 
10.0%
3 14
 
3.5%
1 13
 
3.2%
2 13
 
3.2%
4 10
 
2.5%
5 4
 
1.0%
6 4
 
1.0%
7 4
 
1.0%
Other values (2) 7
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 320
80.0%
Uppercase Letter 80
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 251
78.4%
3 14
 
4.4%
1 13
 
4.1%
2 13
 
4.1%
4 10
 
3.1%
5 4
 
1.2%
6 4
 
1.2%
7 4
 
1.2%
8 4
 
1.2%
9 3
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
V 40
50.0%
M 40
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 320
80.0%
Latin 80
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 251
78.4%
3 14
 
4.4%
1 13
 
4.1%
2 13
 
4.1%
4 10
 
3.1%
5 4
 
1.2%
6 4
 
1.2%
7 4
 
1.2%
8 4
 
1.2%
9 3
 
0.9%
Latin
ValueCountFrequency (%)
V 40
50.0%
M 40
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 251
62.7%
V 40
 
10.0%
M 40
 
10.0%
3 14
 
3.5%
1 13
 
3.2%
2 13
 
3.2%
4 10
 
2.5%
5 4
 
1.0%
6 4
 
1.0%
7 4
 
1.0%
Other values (2) 7
 
1.8%

브이엠에스통신번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1023.175
Minimum1001
Maximum1044
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T19:55:43.864224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1001
5-th percentile1003.9
Q11011.75
median1024.5
Q31034.25
95-th percentile1042.05
Maximum1044
Range43
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation13.083337
Coefficient of variation (CV)0.012786999
Kurtosis-1.2945097
Mean1023.175
Median Absolute Deviation (MAD)11.5
Skewness-0.072962265
Sum40927
Variance171.17372
MonotonicityStrictly increasing
2023-12-12T19:55:44.124270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1001 1
 
2.5%
1026 1
 
2.5%
1028 1
 
2.5%
1029 1
 
2.5%
1030 1
 
2.5%
1031 1
 
2.5%
1032 1
 
2.5%
1033 1
 
2.5%
1034 1
 
2.5%
1035 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1001 1
2.5%
1002 1
2.5%
1004 1
2.5%
1005 1
2.5%
1006 1
2.5%
1007 1
2.5%
1008 1
2.5%
1009 1
2.5%
1010 1
2.5%
1011 1
2.5%
ValueCountFrequency (%)
1044 1
2.5%
1043 1
2.5%
1042 1
2.5%
1041 1
2.5%
1040 1
2.5%
1039 1
2.5%
1038 1
2.5%
1037 1
2.5%
1036 1
2.5%
1035 1
2.5%

설치위치
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T19:55:44.502368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.35
Min length3

Characters and Unicode

Total characters214
Distinct characters103
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

Unique40 ?
Unique (%)100.0%

Sample

1st row남동공단입구사거리
2nd row벽돌막사거리
3rd row문학사거리
4th row신복사거리
5th row부평IC
ValueCountFrequency (%)
남동공단입구사거리 1
 
2.3%
벽돌막사거리 1
 
2.3%
삼거리 1
 
2.3%
서운사거리 1
 
2.3%
작전역 1
 
2.3%
임학역 1
 
2.3%
삼산사거리 1
 
2.3%
갈산역 1
 
2.3%
청라보금자리 1
 
2.3%
가정치안센터 1
 
2.3%
Other values (34) 34
77.3%
2023-12-12T19:55:45.124450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 19
 
8.9%
거 18
 
8.4%
사 17
 
7.9%
서 5
 
2.3%
교 5
 
2.3%
구 5
 
2.3%
학 4
 
1.9%
4
 
1.9%
역 4
 
1.9%
부 3
 
1.4%
Other values (93) 130
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 194
90.7%
Uppercase Letter 15
 
7.0%
Space Separator 4
 
1.9%
Decimal Number 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 19
 
9.8%
거 18
 
9.3%
사 17
 
8.8%
서 5
 
2.6%
교 5
 
2.6%
구 5
 
2.6%
학 4
 
2.1%
역 4
 
2.1%
부 3
 
1.5%
수 3
 
1.5%
Other values (86) 111
57.2%
Uppercase Letter
ValueCountFrequency (%)
T 3
20.0%
C 3
20.0%
P 3
20.0%
I 3
20.0%
A 3
20.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 194
90.7%
Latin 15
 
7.0%
Common 5
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 19
 
9.8%
거 18
 
9.3%
사 17
 
8.8%
서 5
 
2.6%
교 5
 
2.6%
구 5
 
2.6%
학 4
 
2.1%
역 4
 
2.1%
부 3
 
1.5%
수 3
 
1.5%
Other values (86) 111
57.2%
Latin
ValueCountFrequency (%)
T 3
20.0%
C 3
20.0%
P 3
20.0%
I 3
20.0%
A 3
20.0%
Common
ValueCountFrequency (%)
4
80.0%
2 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 194
90.7%
ASCII 20
 
9.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 19
 
9.8%
거 18
 
9.3%
사 17
 
8.8%
서 5
 
2.6%
교 5
 
2.6%
구 5
 
2.6%
학 4
 
2.1%
역 4
 
2.1%
부 3
 
1.5%
수 3
 
1.5%
Other values (86) 111
57.2%
ASCII
ValueCountFrequency (%)
4
20.0%
T 3
15.0%
C 3
15.0%
P 3
15.0%
I 3
15.0%
A 3
15.0%
2 1
 
5.0%

VMS종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
VMP0
33 
VMP1
6 
VMP2
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)2.5%

Sample

1st rowVMP0
2nd rowVMP0
3rd rowVMP0
4th rowVMP0
5th rowVMP0

Common Values

ValueCountFrequency (%)
VMP0 33
82.5%
VMP1 6
 
15.0%
VMP2 1
 
2.5%

Length

2023-12-12T19:55:45.336359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:45.512631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
vmp0 33
82.5%
vmp1 6
 
15.0%
vmp2 1
 
2.5%

설치일자
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2008-06-09
11 
2010-07-01
6 
2012-06-19
5 
2014-08-30
4 
2011-11-01
3 
Other values (8)
11 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique6 ?
Unique (%)15.0%

Sample

1st row2008-06-09
2nd row2008-06-09
3rd row2008-06-09
4th row2008-06-09
5th row2008-06-09

Common Values

ValueCountFrequency (%)
2008-06-09 11
27.5%
2010-07-01 6
15.0%
2012-06-19 5
12.5%
2014-08-30 4
 
10.0%
2011-11-01 3
 
7.5%
2011-11-25 3
 
7.5%
2022-05-31 2
 
5.0%
2012-12-20 1
 
2.5%
2012-12-19 1
 
2.5%
2014-11-14 1
 
2.5%
Other values (3) 3
 
7.5%

Length

2023-12-12T19:55:45.670718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2008-06-09 11
27.5%
2010-07-01 6
15.0%
2012-06-19 5
12.5%
2014-08-30 4
 
10.0%
2011-11-01 3
 
7.5%
2011-11-25 3
 
7.5%
2022-05-31 2
 
5.0%
2012-12-20 1
 
2.5%
2012-12-19 1
 
2.5%
2014-11-14 1
 
2.5%
Other values (3) 3
 
7.5%

설치회사
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
래도
25 
싸인텔레콤
5 
현대ITS
4 
<NA>
 
2
케이ENG(주)
 
2
Other values (2)
 
2

Length

Max length8
Median length2
Mean length3.2
Min length2

Unique

Unique2 ?
Unique (%)5.0%

Sample

1st row<NA>
2nd row래도
3rd row래도
4th row래도
5th row래도

Common Values

ValueCountFrequency (%)
래도 25
62.5%
싸인텔레콤 5
 
12.5%
현대ITS 4
 
10.0%
<NA> 2
 
5.0%
케이ENG(주) 2
 
5.0%
상이군경 1
 
2.5%
장애인재단 1
 
2.5%

Length

2023-12-12T19:55:45.887264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:46.119043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
래도 25
62.5%
싸인텔레콤 5
 
12.5%
현대its 4
 
10.0%
na 2
 
5.0%
케이eng(주 2
 
5.0%
상이군경 1
 
2.5%
장애인재단 1
 
2.5%

유지보수회사
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
<NA>
30 
래도
6 
케이ENG(주)
 
2
현대ITS
 
1
상이군경
 
1

Length

Max length8
Median length4
Mean length3.925
Min length2

Unique

Unique2 ?
Unique (%)5.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 30
75.0%
래도 6
 
15.0%
케이ENG(주) 2
 
5.0%
현대ITS 1
 
2.5%
상이군경 1
 
2.5%

Length

2023-12-12T19:55:46.954715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:47.154076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
75.0%
래도 6
 
15.0%
케이eng(주 2
 
5.0%
현대its 1
 
2.5%
상이군경 1
 
2.5%

상태수집주기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
30
39 
300
 
1

Length

Max length3
Median length2
Mean length2.025
Min length2

Unique

Unique1 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
30 39
97.5%
300 1
 
2.5%

Length

2023-12-12T19:55:47.364412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:47.540034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 39
97.5%
300 1
 
2.5%

최대페이즈수
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
10
40 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10 40
100.0%

Length

2023-12-12T19:55:47.707510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:47.864227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 40
100.0%

엑스좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.68579
Minimum126.42491
Maximum126.74508
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T19:55:48.041448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.42491
5-th percentile126.6309
Q1126.66276
median126.69104
Q3126.72166
95-th percentile126.74348
Maximum126.74508
Range0.3201771
Interquartile range (IQR)0.058899575

Descriptive statistics

Standard deviation0.05434592
Coefficient of variation (CV)0.00042898197
Kurtosis13.025346
Mean126.68579
Median Absolute Deviation (MAD)0.0295595
Skewness-2.8782261
Sum5067.4317
Variance0.0029534791
MonotonicityNot monotonic
2023-12-12T19:55:48.293639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
126.7074108 1
 
2.5%
126.6745182 1
 
2.5%
126.7443085 1
 
2.5%
126.7184052 1
 
2.5%
126.7376385 1
 
2.5%
126.7323917 1
 
2.5%
126.721831 1
 
2.5%
126.6624866 1
 
2.5%
126.659711 1
 
2.5%
126.6553392 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
126.4249058 1
2.5%
126.6171233 1
2.5%
126.6316211 1
2.5%
126.6414904 1
2.5%
126.644876 1
2.5%
126.649798 1
2.5%
126.6553392 1
2.5%
126.6582075 1
2.5%
126.659711 1
2.5%
126.6624866 1
2.5%
ValueCountFrequency (%)
126.7450829 1
2.5%
126.7443085 1
2.5%
126.7434415 1
2.5%
126.7376385 1
2.5%
126.7340414 1
2.5%
126.7337747 1
2.5%
126.7323917 1
2.5%
126.7317265 1
2.5%
126.7269376 1
2.5%
126.721831 1
2.5%

와이좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.500716
Minimum37.395624
Maximum37.610715
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T19:55:48.556934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.395624
5-th percentile37.404993
Q137.448493
median37.517198
Q337.540788
95-th percentile37.594133
Maximum37.610715
Range0.2150913
Interquartile range (IQR)0.09229485

Descriptive statistics

Standard deviation0.062421596
Coefficient of variation (CV)0.0016645441
Kurtosis-1.0715606
Mean37.500716
Median Absolute Deviation (MAD)0.0579559
Skewness-0.017179143
Sum1500.0286
Variance0.0038964557
MonotonicityNot monotonic
2023-12-12T19:55:48.825330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
37.4173564 1
 
2.5%
37.6107155 1
 
2.5%
37.5307757 1
 
2.5%
37.5300697 1
 
2.5%
37.5440086 1
 
2.5%
37.5162681 1
 
2.5%
37.5181273 1
 
2.5%
37.5321909 1
 
2.5%
37.4833401 1
 
2.5%
37.5256369 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
37.3956242 1
2.5%
37.3957281 1
2.5%
37.405481 1
2.5%
37.4153642 1
2.5%
37.4173564 1
2.5%
37.4239019 1
2.5%
37.4301527 1
2.5%
37.4407821 1
2.5%
37.4423473 1
2.5%
37.4478919 1
2.5%
ValueCountFrequency (%)
37.6107155 1
2.5%
37.6085425 1
2.5%
37.5933745 1
2.5%
37.5914307 1
2.5%
37.5805716 1
2.5%
37.5759486 1
2.5%
37.5743586 1
2.5%
37.5665418 1
2.5%
37.5446028 1
2.5%
37.5440086 1
2.5%

시선유도등부착여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size172.0 B
False
31 
True
9 
ValueCountFrequency (%)
False 31
77.5%
True 9
 
22.5%
2023-12-12T19:55:49.050526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

웹카메라부착여부
Boolean

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size172.0 B
True
40 
ValueCountFrequency (%)
True 40
100.0%
2023-12-12T19:55:49.220711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

통신포트
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
3500
39 
30102
 
1

Length

Max length5
Median length4
Mean length4.025
Min length4

Unique

Unique1 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
3500 39
97.5%
30102 1
 
2.5%

Length

2023-12-12T19:55:49.407264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:49.586655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3500 39
97.5%
30102 1
 
2.5%

모니터링피씨번호
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
1
23 
2
15 
3
 
2

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 23
57.5%
2 15
37.5%
3 2
 
5.0%

Length

2023-12-12T19:55:49.770875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:49.956296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 23
57.5%
2 15
37.5%
3 2
 
5.0%

모니터링모니터번호
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
1
40 

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 40
100.0%

Length

2023-12-12T19:55:50.179284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:55:50.385768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 40
100.0%

Interactions

2023-12-12T19:55:41.518789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:40.579257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:41.014321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:41.681368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:40.730404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:41.164837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:41.871196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:40.869514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:55:41.345713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:55:50.531928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
브이엠에스아이디브이엠에스통신번호설치위치VMS종류설치일자설치회사유지보수회사상태수집주기엑스좌표와이좌표시선유도등부착여부통신포트모니터링피씨번호
브이엠에스아이디1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
브이엠에스통신번호1.0001.0001.0000.7390.8600.7280.5980.0000.0000.7490.9010.0000.743
설치위치1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
VMS종류1.0000.7391.0001.0001.0000.000NaN1.0000.3210.4250.5051.0000.449
설치일자1.0000.8601.0001.0001.0000.9901.0001.0000.7900.7340.7591.0000.841
설치회사1.0000.7281.0000.0000.9901.0001.000NaN0.5470.5900.000NaN0.858
유지보수회사1.0000.5981.000NaN1.0001.0001.000NaN0.3571.000NaNNaN1.000
상태수집주기1.0000.0001.0001.0001.000NaNNaN1.0000.3120.0000.0000.6690.000
엑스좌표1.0000.0001.0000.3210.7900.5470.3570.3121.0000.6560.0770.3120.310
와이좌표1.0000.7491.0000.4250.7340.5901.0000.0000.6561.0000.5590.0000.216
시선유도등부착여부1.0000.9011.0000.5050.7590.000NaN0.0000.0770.5591.0000.0000.163
통신포트1.0000.0001.0001.0001.000NaNNaN0.6690.3120.0000.0001.0000.000
모니터링피씨번호1.0000.7431.0000.4490.8410.8581.0000.0000.3100.2160.1630.0001.000
2023-12-12T19:55:50.831476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
VMS종류설치회사시선유도등부착여부모니터링피씨번호통신포트유지보수회사설치일자상태수집주기
VMS종류1.0000.0000.7570.1690.9871.0000.8540.987
설치회사0.0001.0000.0000.5291.0001.0000.7621.000
시선유도등부착여부0.7570.0001.0000.2620.0001.0000.6100.000
모니터링피씨번호0.1690.5290.2621.0000.0000.8660.6090.000
통신포트0.9871.0000.0000.0001.0001.0000.8430.466
유지보수회사1.0001.0001.0000.8661.0001.0000.7071.000
설치일자0.8540.7620.6100.6090.8430.7071.0000.843
상태수집주기0.9871.0000.0000.0000.4661.0000.8431.000
2023-12-12T19:55:51.074627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
브이엠에스통신번호엑스좌표와이좌표VMS종류설치일자설치회사유지보수회사상태수집주기시선유도등부착여부통신포트모니터링피씨번호
브이엠에스통신번호1.000-0.2690.2910.5460.5600.4570.5430.0000.6490.0000.554
엑스좌표-0.2691.0000.1300.2440.5080.3990.0000.3630.0740.3630.234
와이좌표0.2910.1301.0000.2430.3840.3280.7070.0000.3770.0000.090
VMS종류0.5460.2440.2431.0000.8540.0001.0000.9870.7570.9870.169
설치일자0.5600.5080.3840.8541.0000.7620.7070.8430.6100.8430.609
설치회사0.4570.3990.3280.0000.7621.0001.0001.0000.0001.0000.529
유지보수회사0.5430.0000.7071.0000.7071.0001.0001.0001.0001.0000.866
상태수집주기0.0000.3630.0000.9870.8431.0001.0001.0000.0000.4660.000
시선유도등부착여부0.6490.0740.3770.7570.6100.0001.0000.0001.0000.0000.262
통신포트0.0000.3630.0000.9870.8431.0001.0000.4660.0001.0000.000
모니터링피씨번호0.5540.2340.0900.1690.6090.5290.8660.0000.2620.0001.000

Missing values

2023-12-12T19:55:42.147802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:55:42.539754image/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

브이엠에스아이디브이엠에스통신번호설치위치VMS종류설치일자설치회사유지보수회사상태수집주기최대페이즈수엑스좌표와이좌표시선유도등부착여부웹카메라부착여부통신포트모니터링피씨번호모니터링모니터번호
0VM000000101001남동공단입구사거리VMP02008-06-09<NA><NA>3010126.70741137.417356NY350011
1VM000000201002벽돌막사거리VMP02008-06-09래도<NA>3010126.70202637.4678YY350011
2VM000000401004문학사거리VMP02008-06-09래도<NA>3010126.67843437.440782NY350011
3VM000000501005신복사거리VMP02008-06-09래도<NA>3010126.73377537.50692NY350011
4VM000000601006부평ICVMP02008-06-09래도<NA>3010126.72160637.520778NY350011
5VM000000701007능해ICVMP02008-06-09래도<NA>3010126.63162137.448694NY350011
6VM000000801008선학사거리VMP02008-06-09래도<NA>3010126.69924337.430153NY350011
7VM000000901009장승백이사거리VMP02008-06-09래도<NA>3010126.74344237.447892NY350011
8VM000001001010부개사거리VMP02008-06-09래도<NA>3010126.73404137.487122NY350011
9VM000001101011서구청VMP02008-06-09래도<NA>3010126.67641937.539715NY350011
브이엠에스아이디브이엠에스통신번호설치위치VMS종류설치일자설치회사유지보수회사상태수집주기최대페이즈수엑스좌표와이좌표시선유도등부착여부웹카메라부착여부통신포트모니터링피씨번호모니터링모니터번호
30VM000003501035가정치안센터 앞VMP02014-08-30래도래도3010126.65533937.525637NY350021
31VM000003601036뉴서울APT앞VMP02014-08-30래도래도3010126.6830837.524744NY350021
32VM000003701037뉴서울APT건너편VMP02014-08-30래도래도3010126.67917837.524244NY350021
33VM000003801038수협화전지점VMP02014-08-30래도래도3010126.73172637.530713NY350021
34VM000003901039송도2교VMP02014-11-14현대ITS현대ITS3010126.64979837.405481NY350021
35VM000004001040학익동풍림APT앞VMP02015-05-04케이ENG(주)케이ENG(주)3010126.65820837.442347NY350021
36VM000004101041영종 잠진도 입구VMP02015-05-05케이ENG(주)케이ENG(주)3010126.42490637.423902NY350021
37VM000004201042경인시점부VMP22018-01-01<NA><NA>30010126.6414937.454331NY3010211
38VM000004301043서구영어마을VMP02022-05-31상이군경상이군경3010126.70598637.591431NY350011
39VM000004401044이음대로VMP02022-05-31장애인재단<NA>3010126.70963437.580572NY350011