Overview

Dataset statistics

Number of variables9
Number of observations111
Missing cells22
Missing cells (%)2.2%
Duplicate rows1
Duplicate rows (%)0.9%
Total size in memory7.9 KiB
Average record size in memory73.2 B

Variable types

Unsupported2
Categorical6
Text1

Alerts

Dataset has 1 (0.9%) duplicate rowsDuplicates
Unnamed: 5 is highly overall correlated with Unnamed: 2 and 3 other fieldsHigh correlation
Unnamed: 6 is highly overall correlated with Unnamed: 2 and 3 other fieldsHigh correlation
Unnamed: 2 is highly overall correlated with Unnamed: 3 and 3 other fieldsHigh correlation
Unnamed: 3 is highly overall correlated with Unnamed: 2 and 1 other fieldsHigh correlation
Unnamed: 7 is highly overall correlated with Unnamed: 5 and 1 other fieldsHigh correlation
Unnamed: 8 is highly overall correlated with Unnamed: 2 and 3 other fieldsHigh correlation
Unnamed: 2 is highly imbalanced (67.0%)Imbalance
Unnamed: 0 has 10 (9.0%) missing valuesMissing
■C C T V 설치 현황■ has 2 (1.8%) missing valuesMissing
Unnamed: 4 has 10 (9.0%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
■C C T V 설치 현황■ is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:26:29.465260
Analysis finished2024-03-14 02:26:30.258353
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10
Missing (%)9.0%
Memory size1020.0 B

■C C T V 설치 현황■
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)1.8%
Memory size1020.0 B

Unnamed: 2
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct11
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size1020.0 B
〃
91 
<NA>
10 
승강기
 
2
동
 
1
청사동
 
1
Other values (6)
 
6

Length

Max length4
Median length1
Mean length1.3963964
Min length1

Unique

Unique8 ?
Unique (%)7.2%

Sample

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

Common Values

ValueCountFrequency (%)
〃 91
82.0%
<NA> 10
 
9.0%
승강기 2
 
1.8%
동 1
 
0.9%
청사동 1
 
0.9%
" 1
 
0.9%
공연장 1
 
0.9%
주차장 1
 
0.9%
외곽 1
 
0.9%
별관 1
 
0.9%

Length

2024-03-14T11:26:30.316059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
〃 91
82.0%
na 10
 
9.0%
승강기 2
 
1.8%
동 1
 
0.9%
청사동 1
 
0.9%
1
 
0.9%
공연장 1
 
0.9%
주차장 1
 
0.9%
외곽 1
 
0.9%
별관 1
 
0.9%

Unnamed: 3
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Memory size1020.0 B
〃
53 
<NA>
10 
1F
8 
B1F
6 
2F
 
5
Other values (22)
29 

Length

Max length4
Median length1
Mean length1.8198198
Min length1

Unique

Unique17 ?
Unique (%)15.3%

Sample

1st row<NA>
2nd row층
3rd row옥상
4th row18F
5th row17F

Common Values

ValueCountFrequency (%)
〃 53
47.7%
<NA> 10
 
9.0%
1F 8
 
7.2%
B1F 6
 
5.4%
2F 5
 
4.5%
4F 3
 
2.7%
3F 3
 
2.7%
內 2
 
1.8%
옥상 2
 
1.8%
B2F 2
 
1.8%
Other values (17) 17
 
15.3%

Length

2024-03-14T11:26:30.424696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
〃 53
47.7%
na 10
 
9.0%
1f 8
 
7.2%
b1f 6
 
5.4%
2f 5
 
4.5%
4f 3
 
2.7%
3f 3
 
2.7%
옥상 2
 
1.8%
b2f 2
 
1.8%
內 2
 
1.8%
Other values (17) 17
 
15.3%

Unnamed: 4
Text

MISSING 

Distinct98
Distinct (%)97.0%
Missing10
Missing (%)9.0%
Memory size1020.0 B
2024-03-14T11:26:30.659200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length12
Mean length10.762376
Min length2

Characters and Unicode

Total characters1087
Distinct characters140
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)94.1%

Sample

1st row위치
2nd row옥상 헬기 착륙장
3rd row승강장 홀 입구(18층)
4th row 〃 (17층)
5th row 〃 (16층)
ValueCountFrequency (%)
앞 28
 
12.0%
〃 24
 
10.3%
홀 10
 
4.3%
승강장 10
 
4.3%
주차장 7
 
3.0%
복도 4
 
1.7%
공연장 3
 
1.3%
중앙 3
 
1.3%
內 3
 
1.3%
민원실 3
 
1.3%
Other values (113) 138
59.2%
2024-03-14T11:26:30.998461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
449
41.3%
장 34
 
3.1%
층 29
 
2.7%
) 28
 
2.6%
( 28
 
2.6%
앞 28
 
2.6%
〃 24
 
2.2%
1 23
 
2.1%
기 20
 
1.8%
실 19
 
1.7%
Other values (130) 405
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 491
45.2%
Space Separator 449
41.3%
Decimal Number 60
 
5.5%
Close Punctuation 28
 
2.6%
Open Punctuation 28
 
2.6%
Other Punctuation 24
 
2.2%
Uppercase Letter 4
 
0.4%
Lowercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 34
 
6.9%
층 29
 
5.9%
앞 28
 
5.7%
기 20
 
4.1%
실 19
 
3.9%
입 18
 
3.7%
문 14
 
2.9%
구 14
 
2.9%
강 14
 
2.9%
승 13
 
2.6%
Other values (110) 288
58.7%
Decimal Number
ValueCountFrequency (%)
1 23
38.3%
2 10
16.7%
3 5
 
8.3%
4 5
 
8.3%
7 4
 
6.7%
5 3
 
5.0%
6 3
 
5.0%
8 3
 
5.0%
9 2
 
3.3%
0 2
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
I 1
25.0%
O 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
t 1
33.3%
u 1
33.3%
n 1
33.3%
Space Separator
ValueCountFrequency (%)
449
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Other Punctuation
ValueCountFrequency (%)
〃 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 589
54.2%
Hangul 488
44.9%
Latin 7
 
0.6%
Han 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 34
 
7.0%
층 29
 
5.9%
앞 28
 
5.7%
기 20
 
4.1%
실 19
 
3.9%
입 18
 
3.7%
문 14
 
2.9%
구 14
 
2.9%
강 14
 
2.9%
승 13
 
2.7%
Other values (109) 285
58.4%
Common
ValueCountFrequency (%)
449
76.2%
) 28
 
4.8%
( 28
 
4.8%
〃 24
 
4.1%
1 23
 
3.9%
2 10
 
1.7%
3 5
 
0.8%
4 5
 
0.8%
7 4
 
0.7%
5 3
 
0.5%
Other values (4) 10
 
1.7%
Latin
ValueCountFrequency (%)
B 2
28.6%
t 1
14.3%
I 1
14.3%
u 1
14.3%
O 1
14.3%
n 1
14.3%
Han
ValueCountFrequency (%)
內 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 572
52.6%
Hangul 488
44.9%
None 24
 
2.2%
CJK 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
449
78.5%
) 28
 
4.9%
( 28
 
4.9%
1 23
 
4.0%
2 10
 
1.7%
3 5
 
0.9%
4 5
 
0.9%
7 4
 
0.7%
5 3
 
0.5%
6 3
 
0.5%
Other values (9) 14
 
2.4%
Hangul
ValueCountFrequency (%)
장 34
 
7.0%
층 29
 
5.9%
앞 28
 
5.7%
기 20
 
4.1%
실 19
 
3.9%
입 18
 
3.7%
문 14
 
2.9%
구 14
 
2.9%
강 14
 
2.9%
승 13
 
2.7%
Other values (109) 285
58.4%
None
ValueCountFrequency (%)
〃 24
100.0%
CJK
ValueCountFrequency (%)
內 3
100.0%

Unnamed: 5
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Memory size1020.0 B
〃
46 
삼성 SCP-2273N
10 
<NA>
10 
Pelco DD53TC16
9 
삼성 SCC-331
9 
Other values (16)
27 

Length

Max length14
Median length13
Mean length6.3693694
Min length1

Unique

Unique8 ?
Unique (%)7.2%

Sample

1st row<NA>
2nd row모델/규격
3rd rowPelco ES30PC
4th row삼성 SCC-331
5th row〃

Common Values

ValueCountFrequency (%)
〃 46
41.4%
삼성 SCP-2273N 10
 
9.0%
<NA> 10
 
9.0%
Pelco DD53TC16 9
 
8.1%
삼성 SCC-331 9
 
8.1%
삼성 SCP-2270 5
 
4.5%
삼성 SCU-2370 2
 
1.8%
삼성 SCD-2010N 2
 
1.8%
SCC-B5301 2
 
1.8%
한국씨텍 XV100 2
 
1.8%
Other values (11) 14
 
12.6%

Length

2024-03-14T11:26:31.115746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
〃 46
29.1%
삼성 34
21.5%
pelco 11
 
7.0%
scp-2273n 10
 
6.3%
na 10
 
6.3%
dd53tc16 9
 
5.7%
scc-331 9
 
5.7%
scp-2270 5
 
3.2%
es30pc 2
 
1.3%
scp-2250 2
 
1.3%
Other values (14) 20
12.7%

Unnamed: 6
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size1020.0 B
〃
50 
<NA>
10 
3.5-94.5mm(27)
10 
6-12mm
9 
4-64mm(16)
9 
Other values (10)
23 

Length

Max length14
Median length10
Mean length4.4234234
Min length1

Unique

Unique4 ?
Unique (%)3.6%

Sample

1st row<NA>
2nd row줌(배속)
3rd row3.8-91.2mm(24)
4th row6-12mm
5th row〃

Common Values

ValueCountFrequency (%)
〃 50
45.0%
<NA> 10
 
9.0%
3.5-94.5mm(27) 10
 
9.0%
6-12mm 9
 
8.1%
4-64mm(16) 9
 
8.1%
27배줌 9
 
8.1%
3.8-91.2mm(24) 2
 
1.8%
25배줌 2
 
1.8%
12배줌 2
 
1.8%
37배줌 2
 
1.8%
Other values (5) 6
 
5.4%

Length

2024-03-14T11:26:31.223520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
〃 50
45.0%
na 10
 
9.0%
3.5-94.5mm(27 10
 
9.0%
6-12mm 9
 
8.1%
4-64mm(16 9
 
8.1%
27배줌 9
 
8.1%
3.8-91.2mm(24 2
 
1.8%
25배줌 2
 
1.8%
12배줌 2
 
1.8%
37배줌 2
 
1.8%
Other values (5) 6
 
5.4%

Unnamed: 7
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size1020.0 B
〃
68 
52만
13 
41만
11 
<NA>
10 
45만
 
5
Other values (3)
 
4

Length

Max length4
Median length1
Mean length1.8198198
Min length1

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st row<NA>
2nd row화소
3rd row45만
4th row〃
5th row〃

Common Values

ValueCountFrequency (%)
〃 68
61.3%
52만 13
 
11.7%
41만 11
 
9.9%
<NA> 10
 
9.0%
45만 5
 
4.5%
" 2
 
1.8%
화소 1
 
0.9%
적외선 1
 
0.9%

Length

2024-03-14T11:26:31.592430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:26:31.825544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
〃 68
61.3%
52만 13
 
11.7%
41만 11
 
9.9%
na 10
 
9.0%
45만 5
 
4.5%
2
 
1.8%
화소 1
 
0.9%
적외선 1
 
0.9%

Unnamed: 8
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size1020.0 B
〃
74 
360˚ 회전형
13 
<NA>
10 
고정형
10 
180˚ 회전형
 
2
Other values (2)
 
2

Length

Max length8
Median length1
Mean length2.4144144
Min length1

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st row<NA>
2nd row비 고
3rd row360˚ 회전형
4th row고정형
5th row〃

Common Values

ValueCountFrequency (%)
〃 74
66.7%
360˚ 회전형 13
 
11.7%
<NA> 10
 
9.0%
고정형 10
 
9.0%
180˚ 회전형 2
 
1.8%
비 고 1
 
0.9%
" 1
 
0.9%

Length

2024-03-14T11:26:31.967600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:26:32.059891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
〃 74
58.3%
회전형 15
 
11.8%
360˚ 13
 
10.2%
na 10
 
7.9%
고정형 10
 
7.9%
180˚ 2
 
1.6%
비 1
 
0.8%
고 1
 
0.8%
1
 
0.8%

Correlations

2024-03-14T11:26:32.133180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
Unnamed: 21.0000.9301.0000.9650.8930.7120.893
Unnamed: 30.9301.0001.0000.7630.7920.7510.890
Unnamed: 41.0001.0001.0000.9760.9060.9640.977
Unnamed: 50.9650.7630.9761.0001.0000.9770.943
Unnamed: 60.8930.7920.9061.0001.0000.9850.869
Unnamed: 70.7120.7510.9640.9770.9851.0000.661
Unnamed: 80.8930.8900.9770.9430.8690.6611.000
2024-03-14T11:26:32.237890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 7Unnamed: 5Unnamed: 8Unnamed: 2Unnamed: 3Unnamed: 6
Unnamed: 71.0000.8300.4680.4560.3900.779
Unnamed: 50.8301.0000.7390.6610.2950.965
Unnamed: 80.4680.7391.0000.7260.5860.637
Unnamed: 20.4560.6610.7261.0000.6230.627
Unnamed: 30.3900.2950.5860.6231.0000.352
Unnamed: 60.7790.9650.6370.6270.3521.000
2024-03-14T11:26:32.334563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
Unnamed: 21.0000.6230.6610.6270.4560.726
Unnamed: 30.6231.0000.2950.3520.3900.586
Unnamed: 50.6610.2951.0000.9650.8300.739
Unnamed: 60.6270.3520.9651.0000.7790.637
Unnamed: 70.4560.3900.8300.7791.0000.468
Unnamed: 80.7260.5860.7390.6370.4681.000

Missing values

2024-03-14T11:26:29.957994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:26:30.066212image/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.
2024-03-14T11:26:30.175591image/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

Unnamed: 0■C C T V 설치 현황■Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
0NaNNaN<NA><NA><NA><NA><NA><NA><NA>
1순번NO동층위치모델/규격줌(배속)화소비 고
211청사동옥상옥상 헬기 착륙장Pelco ES30PC3.8-91.2mm(24)45만360˚ 회전형
323〃18F승강장 홀 입구(18층)삼성 SCC-3316-12mm〃고정형
434〃17F〃 (17층)〃〃〃〃
545〃16F〃 (16층)〃〃〃〃
656〃15F〃 (15층)〃〃〃〃
767〃14F〃 (14층)〃〃〃〃
878〃13F〃 (13층)〃〃〃〃
989〃12F〃 (12층)〃〃〃〃
Unnamed: 0■C C T V 설치 현황■Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
10110098〃〃〃 11호기삼성 SCD-2010N〃〃〃
102NaN* 의회동 카메라 총 14대 의회 총무담당관실로 이관 조치(2012년 9월 27일)<NA><NA><NA><NA><NA><NA><NA>
103NaNNaN<NA><NA><NA><NA><NA><NA><NA>
104NaN* 고정형 ①29대 : 렌즈일체형 TYPE, 삼성SCC-331, SCD-2022R<NA><NA><NA><NA><NA><NA><NA>
105NaN②13대 : 디지털 칼라 TYPE, 삼성SCC-B5301[9대], 삼성SCD-2010N[2대], SID-45S[2대]<NA><NA><NA><NA><NA><NA><NA>
106NaN* 회전형 ①33대 : Speed Dome TYPE, Pelco DD53TC16, 삼성 SCP-2120N<NA><NA><NA><NA><NA><NA><NA>
107NaN② 5대 : 옥외Poly형 OutDoor Pan, Pelco ES30PC<NA><NA><NA><NA><NA><NA><NA>
108NaN③ 7대 : Wall TYPE INDOOR PAN, 삼성SCC-331+SPT-2408+렌즈(6-12mm)조립형<NA><NA><NA><NA><NA><NA><NA>
109NaN④13대 : DOH-240si[1대], 삼성SPD-3700TN[2대], SCP-2270[5대], SCP-2120N[1대], SCU-2370[2대], 한국씨텍 XV-100[2대]<NA><NA><NA><NA><NA><NA><NA>
110NaN총 : 100대 - 고정형*29대(승강기제외), 승강기용*11대, 360˚회전형*43대, 180˚회전형*7대, 외곽*8대, 별관*2대<NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8# duplicates
0<NA><NA><NA><NA><NA><NA><NA>10