Overview

Dataset statistics

Number of variables10
Number of observations136
Missing cells233
Missing cells (%)17.1%
Duplicate rows1
Duplicate rows (%)0.7%
Total size in memory10.9 KiB
Average record size in memory82.0 B

Variable types

Text3
Categorical6
Unsupported1

Alerts

Dataset has 1 (0.7%) 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 (59.6%)Imbalance
Unnamed: 0 has 35 (25.7%) missing valuesMissing
■C C T V 설치 현황■ has 27 (19.9%) missing valuesMissing
Unnamed: 4 has 35 (25.7%) missing valuesMissing
Unnamed: 9 has 136 (100.0%) missing valuesMissing
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:26:24.324205
Analysis finished2024-03-14 02:26:25.309565
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Text

MISSING 

Distinct101
Distinct (%)100.0%
Missing35
Missing (%)25.7%
Memory size1.2 KiB
2024-03-14T11:26:25.506768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.9207921
Min length1

Characters and Unicode

Total characters194
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)100.0%

Sample

1st row순번
2nd row1
3rd row2
4th row3
5th row4
ValueCountFrequency (%)
11 1
 
1.0%
78 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
66 1
 
1.0%
Other values (91) 91
90.1%
2024-03-14T11:26:25.859762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
10.8%
2 20
10.3%
3 20
10.3%
4 20
10.3%
5 20
10.3%
6 20
10.3%
7 20
10.3%
8 20
10.3%
9 20
10.3%
0 11
5.7%
Other values (2) 2
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 192
99.0%
Other Letter 2
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
10.9%
2 20
10.4%
3 20
10.4%
4 20
10.4%
5 20
10.4%
6 20
10.4%
7 20
10.4%
8 20
10.4%
9 20
10.4%
0 11
5.7%
Other Letter
ValueCountFrequency (%)
순 1
50.0%
번 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 192
99.0%
Hangul 2
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 21
10.9%
2 20
10.4%
3 20
10.4%
4 20
10.4%
5 20
10.4%
6 20
10.4%
7 20
10.4%
8 20
10.4%
9 20
10.4%
0 11
5.7%
Hangul
ValueCountFrequency (%)
순 1
50.0%
번 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 192
99.0%
Hangul 2
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21
10.9%
2 20
10.4%
3 20
10.4%
4 20
10.4%
5 20
10.4%
6 20
10.4%
7 20
10.4%
8 20
10.4%
9 20
10.4%
0 11
5.7%
Hangul
ValueCountFrequency (%)
순 1
50.0%
번 1
50.0%

■C C T V 설치 현황■
Text

MISSING 

Distinct109
Distinct (%)100.0%
Missing27
Missing (%)19.9%
Memory size1.2 KiB
2024-03-14T11:26:26.020774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length112
Median length2
Mean length6.8073394
Min length1

Characters and Unicode

Total characters742
Distinct characters105
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st rowNO
2nd row1
3rd row3
4th row4
5th row5
ValueCountFrequency (%)
11
 
6.3%
type 4
 
2.3%
pelco 2
 
1.1%
pan 2
 
1.1%
총 2
 
1.1%
총무담당관실로 1
 
0.6%
의회동 1
 
0.6%
카메라 1
 
0.6%
14대 1
 
0.6%
의회 1
 
0.6%
Other values (148) 148
85.1%
2024-03-14T11:26:26.269668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
124
 
16.7%
2 44
 
5.9%
1 42
 
5.7%
3 35
 
4.7%
0 32
 
4.3%
7 26
 
3.5%
4 25
 
3.4%
5 25
 
3.4%
9 24
 
3.2%
대 23
 
3.1%
Other values (95) 342
46.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 299
40.3%
Space Separator 124
16.7%
Other Letter 109
 
14.7%
Uppercase Letter 93
 
12.5%
Other Punctuation 35
 
4.7%
Lowercase Letter 32
 
4.3%
Dash Punctuation 16
 
2.2%
Open Punctuation 12
 
1.6%
Close Punctuation 12
 
1.6%
Other Number 6
 
0.8%
Other values (2) 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 23
21.1%
형 8
 
7.3%
삼 6
 
5.5%
성 6
 
5.5%
회 5
 
4.6%
전 3
 
2.8%
관 3
 
2.8%
외 3
 
2.8%
총 3
 
2.8%
의 2
 
1.8%
Other values (37) 47
43.1%
Uppercase Letter
ValueCountFrequency (%)
S 15
16.1%
P 15
16.1%
C 14
15.1%
D 10
10.8%
T 7
7.5%
N 7
7.5%
O 5
 
5.4%
E 5
 
5.4%
Y 4
 
4.3%
I 2
 
2.2%
Other values (8) 9
9.7%
Lowercase Letter
ValueCountFrequency (%)
o 6
18.8%
e 5
15.6%
l 5
15.6%
m 3
9.4%
c 2
 
6.2%
a 2
 
6.2%
n 1
 
3.1%
s 1
 
3.1%
i 1
 
3.1%
r 1
 
3.1%
Other values (5) 5
15.6%
Decimal Number
ValueCountFrequency (%)
2 44
14.7%
1 42
14.0%
3 35
11.7%
0 32
10.7%
7 26
8.7%
4 25
8.4%
5 25
8.4%
9 24
8.0%
6 23
7.7%
8 23
7.7%
Other Number
ValueCountFrequency (%)
② 2
33.3%
① 2
33.3%
③ 1
16.7%
④ 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 19
54.3%
* 9
25.7%
: 7
 
20.0%
Open Punctuation
ValueCountFrequency (%)
[ 9
75.0%
( 3
 
25.0%
Close Punctuation
ValueCountFrequency (%)
] 9
75.0%
) 3
 
25.0%
Space Separator
ValueCountFrequency (%)
124
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
˚ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 508
68.5%
Latin 125
 
16.8%
Hangul 109
 
14.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 23
21.1%
형 8
 
7.3%
삼 6
 
5.5%
성 6
 
5.5%
회 5
 
4.6%
전 3
 
2.8%
관 3
 
2.8%
외 3
 
2.8%
총 3
 
2.8%
의 2
 
1.8%
Other values (37) 47
43.1%
Latin
ValueCountFrequency (%)
S 15
12.0%
P 15
12.0%
C 14
 
11.2%
D 10
 
8.0%
T 7
 
5.6%
N 7
 
5.6%
o 6
 
4.8%
O 5
 
4.0%
E 5
 
4.0%
e 5
 
4.0%
Other values (23) 36
28.8%
Common
ValueCountFrequency (%)
124
24.4%
2 44
 
8.7%
1 42
 
8.3%
3 35
 
6.9%
0 32
 
6.3%
7 26
 
5.1%
4 25
 
4.9%
5 25
 
4.9%
9 24
 
4.7%
6 23
 
4.5%
Other values (15) 108
21.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 625
84.2%
Hangul 109
 
14.7%
Enclosed Alphanum 6
 
0.8%
Modifier Letters 2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
124
19.8%
2 44
 
7.0%
1 42
 
6.7%
3 35
 
5.6%
0 32
 
5.1%
7 26
 
4.2%
4 25
 
4.0%
5 25
 
4.0%
9 24
 
3.8%
6 23
 
3.7%
Other values (43) 225
36.0%
Hangul
ValueCountFrequency (%)
대 23
21.1%
형 8
 
7.3%
삼 6
 
5.5%
성 6
 
5.5%
회 5
 
4.6%
전 3
 
2.8%
관 3
 
2.8%
외 3
 
2.8%
총 3
 
2.8%
의 2
 
1.8%
Other values (37) 47
43.1%
Enclosed Alphanum
ValueCountFrequency (%)
② 2
33.3%
① 2
33.3%
③ 1
16.7%
④ 1
16.7%
Modifier Letters
ValueCountFrequency (%)
˚ 2
100.0%

Unnamed: 2
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct11
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
〃
91 
<NA>
35 
승강기
 
2
동
 
1
청사동
 
1
Other values (6)
 
6

Length

Max length4
Median length1
Mean length1.875
Min length1

Unique

Unique8 ?
Unique (%)5.9%

Sample

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

Common Values

ValueCountFrequency (%)
〃 91
66.9%
<NA> 35
 
25.7%
승강기 2
 
1.5%
동 1
 
0.7%
청사동 1
 
0.7%
" 1
 
0.7%
공연장 1
 
0.7%
주차장 1
 
0.7%
외곽 1
 
0.7%
별관 1
 
0.7%

Length

2024-03-14T11:26:26.375515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
〃 91
66.9%
na 35
 
25.7%
승강기 2
 
1.5%
동 1
 
0.7%
청사동 1
 
0.7%
1
 
0.7%
공연장 1
 
0.7%
주차장 1
 
0.7%
외곽 1
 
0.7%
별관 1
 
0.7%

Unnamed: 3
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)19.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
〃
53 
<NA>
35 
1F
8 
B1F
6 
2F
 
5
Other values (22)
29 

Length

Max length4
Median length3
Mean length2.2205882
Min length1

Unique

Unique17 ?
Unique (%)12.5%

Sample

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

Common Values

ValueCountFrequency (%)
〃 53
39.0%
<NA> 35
25.7%
1F 8
 
5.9%
B1F 6
 
4.4%
2F 5
 
3.7%
4F 3
 
2.2%
3F 3
 
2.2%
內 2
 
1.5%
옥상 2
 
1.5%
B2F 2
 
1.5%
Other values (17) 17
 
12.5%

Length

2024-03-14T11:26:26.483366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
〃 53
39.0%
na 35
25.7%
1f 8
 
5.9%
b1f 6
 
4.4%
2f 5
 
3.7%
4f 3
 
2.2%
3f 3
 
2.2%
옥상 2
 
1.5%
b2f 2
 
1.5%
內 2
 
1.5%
Other values (17) 17
 
12.5%

Unnamed: 4
Text

MISSING 

Distinct98
Distinct (%)97.0%
Missing35
Missing (%)25.7%
Memory size1.2 KiB
2024-03-14T11:26:26.724969image/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%
2024-03-14T11:26:27.104119image/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 (%)15.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
〃
46 
<NA>
35 
삼성 SCP-2273N
10 
Pelco DD53TC16
9 
삼성 SCC-331
9 
Other values (16)
27 

Length

Max length14
Median length13
Mean length5.9338235
Min length1

Unique

Unique8 ?
Unique (%)5.9%

Sample

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

Common Values

ValueCountFrequency (%)
〃 46
33.8%
<NA> 35
25.7%
삼성 SCP-2273N 10
 
7.4%
Pelco DD53TC16 9
 
6.6%
삼성 SCC-331 9
 
6.6%
삼성 SCP-2270 5
 
3.7%
삼성 SCU-2370 2
 
1.5%
삼성 SCD-2010N 2
 
1.5%
SCC-B5301 2
 
1.5%
한국씨텍 XV100 2
 
1.5%
Other values (11) 14
 
10.3%

Length

2024-03-14T11:26:27.294382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
〃 46
25.1%
na 35
19.1%
삼성 34
18.6%
pelco 11
 
6.0%
scp-2273n 10
 
5.5%
dd53tc16 9
 
4.9%
scc-331 9
 
4.9%
scp-2270 5
 
2.7%
es30pc 2
 
1.1%
scp-2250 2
 
1.1%
Other values (14) 20
10.9%

Unnamed: 6
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
〃
50 
<NA>
35 
3.5-94.5mm(27)
10 
6-12mm
9 
4-64mm(16)
9 
Other values (10)
23 

Length

Max length14
Median length10
Mean length4.3455882
Min length1

Unique

Unique4 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
〃 50
36.8%
<NA> 35
25.7%
3.5-94.5mm(27) 10
 
7.4%
6-12mm 9
 
6.6%
4-64mm(16) 9
 
6.6%
27배줌 9
 
6.6%
3.8-91.2mm(24) 2
 
1.5%
25배줌 2
 
1.5%
12배줌 2
 
1.5%
37배줌 2
 
1.5%
Other values (5) 6
 
4.4%

Length

2024-03-14T11:26:27.418157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
〃 50
36.8%
na 35
25.7%
3.5-94.5mm(27 10
 
7.4%
6-12mm 9
 
6.6%
4-64mm(16 9
 
6.6%
27배줌 9
 
6.6%
3.8-91.2mm(24 2
 
1.5%
25배줌 2
 
1.5%
12배줌 2
 
1.5%
37배줌 2
 
1.5%
Other values (5) 6
 
4.4%

Unnamed: 7
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
〃
68 
<NA>
35 
52만
13 
41만
11 
45만
 
5
Other values (3)
 
4

Length

Max length4
Median length1
Mean length2.2205882
Min length1

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
〃 68
50.0%
<NA> 35
25.7%
52만 13
 
9.6%
41만 11
 
8.1%
45만 5
 
3.7%
" 2
 
1.5%
화소 1
 
0.7%
적외선 1
 
0.7%

Length

2024-03-14T11:26:27.519132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:26:27.621202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
〃 68
50.0%
na 35
25.7%
52만 13
 
9.6%
41만 11
 
8.1%
45만 5
 
3.7%
2
 
1.5%
화소 1
 
0.7%
적외선 1
 
0.7%

Unnamed: 8
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
〃
74 
<NA>
35 
360˚ 회전형
13 
고정형
10 
180˚ 회전형
 
2
Other values (2)
 
2

Length

Max length8
Median length1
Mean length2.7058824
Min length1

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
〃 74
54.4%
<NA> 35
25.7%
360˚ 회전형 13
 
9.6%
고정형 10
 
7.4%
180˚ 회전형 2
 
1.5%
비 고 1
 
0.7%
" 1
 
0.7%

Length

2024-03-14T11:26:27.730834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:26:27.841612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
〃 74
48.7%
na 35
23.0%
회전형 15
 
9.9%
360˚ 13
 
8.6%
고정형 10
 
6.6%
180˚ 2
 
1.3%
비 1
 
0.7%
고 1
 
0.7%
1
 
0.7%

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing136
Missing (%)100.0%
Memory size1.3 KiB

Correlations

2024-03-14T11:26:27.914240image/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
2024-03-14T11:26:28.005805image/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
2024-03-14T11:26:28.104856image/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

2024-03-14T11:26:24.849486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:26:25.072912image/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.
2024-03-14T11:26:25.220113image/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: 8Unnamed: 9
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1순번NO동층위치모델/규격줌(배속)화소비 고<NA>
211청사동옥상옥상 헬기 착륙장Pelco ES30PC3.8-91.2mm(24)45만360˚ 회전형<NA>
323〃18F승강장 홀 입구(18층)삼성 SCC-3316-12mm〃고정형<NA>
434〃17F〃 (17층)〃〃〃〃<NA>
545〃16F〃 (16층)〃〃〃〃<NA>
656〃15F〃 (15층)〃〃〃〃<NA>
767〃14F〃 (14층)〃〃〃〃<NA>
878〃13F〃 (13층)〃〃〃〃<NA>
989〃12F〃 (12층)〃〃〃〃<NA>
Unnamed: 0■C C T V 설치 현황■Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9
126<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
127<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
128<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
129<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
130<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
132<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
133<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
134<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
135<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

Unnamed: 0■C C T V 설치 현황■Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA>27