Overview

Dataset statistics

Number of variables12
Number of observations341
Missing cells99
Missing cells (%)2.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.1 KiB
Average record size in memory96.4 B

Variable types

Categorical8
Text4

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15956/S/1/datasetView.do

Alerts

패킷 단위 is highly overall correlated with 송신 서버 번호 and 6 other fieldsHigh correlation
데이터 사이즈 is highly overall correlated with 송신 서버 번호 and 5 other fieldsHigh correlation
패킷 구분 명 is highly overall correlated with 송신 서버 번호 and 6 other fieldsHigh correlation
패킷 길이 is highly overall correlated with 데이터 번호 and 3 other fieldsHigh correlation
데이터 번호 is highly overall correlated with 송신 서버 번호 and 6 other fieldsHigh correlation
공개 구분 명 is highly overall correlated with 송신 서버 번호 and 6 other fieldsHigh correlation
패킷 사이즈 is highly overall correlated with 송신 서버 번호 and 5 other fieldsHigh correlation
송신 서버 번호 is highly overall correlated with 데이터 번호 and 5 other fieldsHigh correlation
데이터 번호 is highly imbalanced (50.9%)Imbalance
패킷 구분 명 is highly imbalanced (54.3%)Imbalance
공개 구분 명 is highly imbalanced (97.1%)Imbalance
패킷 범주 has 73 (21.4%) missing valuesMissing
설명 has 26 (7.6%) missing valuesMissing

Reproduction

Analysis started2024-05-18 00:50:12.417197
Analysis finished2024-05-18 00:50:17.476347
Duration5.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

송신 서버 번호
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
24
56 
17
30 
36
30 
34
30 
48
24 
Other values (18)
171 

Length

Max length17
Median length2
Mean length2.0117302
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowtrnsmit_server_no
2nd row14
3rd row14
4th row14
5th row14

Common Values

ValueCountFrequency (%)
24 56
16.4%
17 30
 
8.8%
36 30
 
8.8%
34 30
 
8.8%
48 24
 
7.0%
15 22
 
6.5%
22 21
 
6.2%
16 16
 
4.7%
18 16
 
4.7%
40 16
 
4.7%
Other values (13) 80
23.5%

Length

2024-05-18T09:50:17.767122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
24 56
16.4%
17 30
 
8.8%
36 30
 
8.8%
34 30
 
8.8%
48 24
 
7.0%
15 22
 
6.5%
22 21
 
6.2%
16 16
 
4.7%
18 16
 
4.7%
40 16
 
4.7%
Other values (13) 80
23.5%

데이터 번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
1
268 
2
38 
3
34 
data_no
 
1

Length

Max length7
Median length1
Mean length1.0175953
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
1 268
78.6%
2 38
 
11.1%
3 34
 
10.0%
data_no 1
 
0.3%

Length

2024-05-18T09:50:18.219541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:50:18.612085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 268
78.6%
2 38
 
11.1%
3 34
 
10.0%
data_no 1
 
0.3%

패킷 사이즈
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
87
90 
206
28 
143
24 
69
22 
106
20 
Other values (19)
157 

Length

Max length11
Median length2
Mean length2.2844575
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowpacket_size
2nd row37
3rd row37
4th row37
5th row37

Common Values

ValueCountFrequency (%)
87 90
26.4%
206 28
 
8.2%
143 24
 
7.0%
69 22
 
6.5%
106 20
 
5.9%
59 16
 
4.7%
62 16
 
4.7%
125 16
 
4.7%
19 13
 
3.8%
55 12
 
3.5%
Other values (14) 84
24.6%

Length

2024-05-18T09:50:18.932876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
87 90
26.4%
206 28
 
8.2%
143 24
 
7.0%
69 22
 
6.5%
106 20
 
5.9%
59 16
 
4.7%
62 16
 
4.7%
125 16
 
4.7%
19 13
 
3.8%
55 12
 
3.5%
Other values (14) 84
24.6%

데이터 사이즈
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
64
90 
48
38 
192
28 
125
24 
92
20 
Other values (17)
141 

Length

Max length9
Median length2
Mean length2.1290323
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowdata_size
2nd row29
3rd row29
4th row29
5th row29

Common Values

ValueCountFrequency (%)
64 90
26.4%
48 38
11.1%
192 28
 
8.2%
125 24
 
7.0%
92 20
 
5.9%
43 18
 
5.3%
36 16
 
4.7%
115 16
 
4.7%
23 12
 
3.5%
8 11
 
3.2%
Other values (12) 68
19.9%

Length

2024-05-18T09:50:19.326176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
64 90
26.4%
48 38
11.1%
192 28
 
8.2%
125 24
 
7.0%
92 20
 
5.9%
43 18
 
5.3%
36 16
 
4.7%
115 16
 
4.7%
23 12
 
3.5%
8 11
 
3.2%
Other values (12) 68
19.9%

패킷 구분 명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
테일
276 
헤더
64 
packet_se_nm
 
1

Length

Max length12
Median length2
Mean length2.0293255
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowpacket_se_nm
2nd row헤더
3rd row헤더
4th row테일
5th row테일

Common Values

ValueCountFrequency (%)
테일 276
80.9%
헤더 64
 
18.8%
packet_se_nm 1
 
0.3%

Length

2024-05-18T09:50:19.753402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:50:20.102709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
테일 276
80.9%
헤더 64
 
18.8%
packet_se_nm 1
 
0.3%

패킷 명
Text

Distinct188
Distinct (%)55.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-05-18T09:50:20.885681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length5.6158358
Min length2

Characters and Unicode

Total characters1915
Distinct characters264
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)39.9%

Sample

1st rowpacket_nm
2nd row모델명
3rd row시리얼
4th row센싱시간
5th row복합악취센싱값
ValueCountFrequency (%)
모델명 25
 
4.9%
시리얼 22
 
4.3%
1 11
 
2.1%
온도 10
 
1.9%
2 10
 
1.9%
디밍분 9
 
1.7%
상태 9
 
1.7%
디밍시 9
 
1.7%
3 9
 
1.7%
디밍값 9
 
1.7%
Other values (222) 392
76.1%
2024-05-18T09:50:22.349277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
194
 
10.1%
시 71
 
3.7%
지 34
 
1.8%
기 33
 
1.7%
리 33
 
1.7%
등 32
 
1.7%
디 31
 
1.6%
도 31
 
1.6%
밍 30
 
1.6%
소 30
 
1.6%
Other values (254) 1396
72.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1492
77.9%
Space Separator 194
 
10.1%
Uppercase Letter 97
 
5.1%
Decimal Number 55
 
2.9%
Lowercase Letter 43
 
2.2%
Close Punctuation 11
 
0.6%
Open Punctuation 11
 
0.6%
Other Punctuation 7
 
0.4%
Dash Punctuation 4
 
0.2%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 71
 
4.8%
지 34
 
2.3%
기 33
 
2.2%
리 33
 
2.2%
등 32
 
2.1%
디 31
 
2.1%
도 31
 
2.1%
밍 30
 
2.0%
소 30
 
2.0%
명 29
 
1.9%
Other values (204) 1138
76.3%
Uppercase Letter
ValueCountFrequency (%)
I 14
14.4%
F 11
11.3%
D 11
11.3%
O 10
10.3%
P 9
9.3%
S 8
8.2%
G 7
7.2%
T 5
 
5.2%
C 4
 
4.1%
A 4
 
4.1%
Other values (8) 14
14.4%
Lowercase Letter
ValueCountFrequency (%)
e 6
14.0%
t 4
 
9.3%
a 4
 
9.3%
o 3
 
7.0%
n 3
 
7.0%
y 3
 
7.0%
v 3
 
7.0%
l 3
 
7.0%
m 2
 
4.7%
p 2
 
4.7%
Other values (6) 10
23.3%
Decimal Number
ValueCountFrequency (%)
1 15
27.3%
2 15
27.3%
3 12
21.8%
4 4
 
7.3%
0 3
 
5.5%
5 3
 
5.5%
6 2
 
3.6%
8 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
/ 4
57.1%
, 2
28.6%
. 1
 
14.3%
Space Separator
ValueCountFrequency (%)
194
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1492
77.9%
Common 283
 
14.8%
Latin 140
 
7.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 71
 
4.8%
지 34
 
2.3%
기 33
 
2.2%
리 33
 
2.2%
등 32
 
2.1%
디 31
 
2.1%
도 31
 
2.1%
밍 30
 
2.0%
소 30
 
2.0%
명 29
 
1.9%
Other values (204) 1138
76.3%
Latin
ValueCountFrequency (%)
I 14
 
10.0%
F 11
 
7.9%
D 11
 
7.9%
O 10
 
7.1%
P 9
 
6.4%
S 8
 
5.7%
G 7
 
5.0%
e 6
 
4.3%
T 5
 
3.6%
C 4
 
2.9%
Other values (24) 55
39.3%
Common
ValueCountFrequency (%)
194
68.6%
1 15
 
5.3%
2 15
 
5.3%
3 12
 
4.2%
) 11
 
3.9%
( 11
 
3.9%
4 4
 
1.4%
- 4
 
1.4%
/ 4
 
1.4%
0 3
 
1.1%
Other values (6) 10
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1492
77.9%
ASCII 423
 
22.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
194
45.9%
1 15
 
3.5%
2 15
 
3.5%
I 14
 
3.3%
3 12
 
2.8%
F 11
 
2.6%
) 11
 
2.6%
D 11
 
2.6%
( 11
 
2.6%
O 10
 
2.4%
Other values (40) 119
28.1%
Hangul
ValueCountFrequency (%)
시 71
 
4.8%
지 34
 
2.3%
기 33
 
2.2%
리 33
 
2.2%
등 32
 
2.1%
디 31
 
2.1%
도 31
 
2.1%
밍 30
 
2.0%
소 30
 
2.0%
명 29
 
1.9%
Other values (204) 1138
76.3%

패킷 길이
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
1
63 
2
56 
5
38 
3
37 
6
32 
Other values (20)
115 

Length

Max length11
Median length1
Mean length1.1994135
Min length1

Unique

Unique8 ?
Unique (%)2.3%

Sample

1st rowpacket_byte
2nd row4
3rd row4
4th row25
5th row4

Common Values

ValueCountFrequency (%)
1 63
18.5%
2 56
16.4%
5 38
11.1%
3 37
10.9%
6 32
9.4%
4 22
 
6.5%
7 15
 
4.4%
8 14
 
4.1%
10 11
 
3.2%
15 9
 
2.6%
Other values (15) 44
12.9%

Length

2024-05-18T09:50:22.895145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 63
18.5%
2 56
16.4%
5 38
11.1%
3 37
10.9%
6 32
9.4%
4 22
 
6.5%
7 15
 
4.4%
8 14
 
4.1%
10 11
 
3.2%
15 9
 
2.6%
Other values (15) 44
12.9%

패킷 단위
Categorical

HIGH CORRELATION 

Distinct39
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
138 
정수
39 
%
27 
시
23 
분
20 
Other values (34)
94 

Length

Max length11
Median length9
Mean length2.9002933
Min length1

Unique

Unique16 ?
Unique (%)4.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 138
40.5%
정수 39
 
11.4%
% 27
 
7.9%
시 23
 
6.7%
분 20
 
5.9%
㎍/㎥ 14
 
4.1%
℃ 9
 
2.6%
ppm 7
 
2.1%
g 6
 
1.8%
0:정상 1:발생 5
 
1.5%
Other values (29) 53
 
15.5%

Length

2024-05-18T09:50:23.537912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 138
39.7%
정수 39
 
11.2%
27
 
7.8%
시 23
 
6.6%
분 20
 
5.7%
㎍/㎥ 14
 
4.0%
℃ 9
 
2.6%
ppm 7
 
2.0%
g 6
 
1.7%
ppb 5
 
1.4%
Other values (32) 60
17.2%

패킷 범주
Text

MISSING 

Distinct104
Distinct (%)38.8%
Missing73
Missing (%)21.4%
Memory size2.8 KiB
2024-05-18T09:50:24.444108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length99
Median length39
Mean length11.037313
Min length1

Characters and Unicode

Total characters2958
Distinct characters113
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)20.1%

Sample

1st rowpacket_ctgry
2nd row정상 : 0, 비정상(오류) : 1
3rd row정상 : 0, 비정상(오류) : 1
4th row정상 : 0, 비정상(오류) : 1
5th row정상 : 0, 비정상(오류) : 1
ValueCountFrequency (%)
120
 
19.2%
0 58
 
9.3%
1 35
 
5.6%
정상 20
 
3.2%
비정상(오류 17
 
2.7%
0(정상)/1(고장 15
 
2.4%
00~59 15
 
2.4%
99999 13
 
2.1%
0~100 12
 
1.9%
xx,00~23 12
 
1.9%
Other values (129) 307
49.2%
2024-05-18T09:50:26.125135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 641
21.7%
356
 
12.0%
9 337
 
11.4%
~ 189
 
6.4%
1 146
 
4.9%
, 79
 
2.7%
정 67
 
2.3%
5 65
 
2.2%
) 61
 
2.1%
( 61
 
2.1%
Other values (103) 956
32.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1369
46.3%
Other Letter 391
 
13.2%
Space Separator 356
 
12.0%
Other Punctuation 218
 
7.4%
Math Symbol 207
 
7.0%
Uppercase Letter 201
 
6.8%
Close Punctuation 61
 
2.1%
Open Punctuation 61
 
2.1%
Lowercase Letter 57
 
1.9%
Dash Punctuation 36
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 67
17.1%
상 54
13.8%
수 27
 
6.9%
자 27
 
6.9%
리 27
 
6.9%
비 19
 
4.9%
오 17
 
4.3%
류 17
 
4.3%
고 17
 
4.3%
소 15
 
3.8%
Other values (38) 104
26.6%
Uppercase Letter
ValueCountFrequency (%)
X 55
27.4%
F 50
24.9%
S 15
 
7.5%
O 15
 
7.5%
N 9
 
4.5%
D 9
 
4.5%
M 8
 
4.0%
U 6
 
3.0%
L 4
 
2.0%
E 4
 
2.0%
Other values (13) 26
12.9%
Lowercase Letter
ValueCountFrequency (%)
x 7
12.3%
c 6
10.5%
o 5
 
8.8%
y 5
 
8.8%
a 4
 
7.0%
t 4
 
7.0%
e 4
 
7.0%
s 3
 
5.3%
r 3
 
5.3%
g 2
 
3.5%
Other values (9) 14
24.6%
Decimal Number
ValueCountFrequency (%)
0 641
46.8%
9 337
24.6%
1 146
 
10.7%
5 65
 
4.7%
2 59
 
4.3%
3 54
 
3.9%
6 32
 
2.3%
7 15
 
1.1%
4 15
 
1.1%
8 5
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 79
36.2%
: 57
26.1%
. 46
21.1%
/ 25
 
11.5%
% 11
 
5.0%
Math Symbol
ValueCountFrequency (%)
~ 189
91.3%
+ 9
 
4.3%
= 9
 
4.3%
Space Separator
ValueCountFrequency (%)
356
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2309
78.1%
Hangul 391
 
13.2%
Latin 258
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 67
17.1%
상 54
13.8%
수 27
 
6.9%
자 27
 
6.9%
리 27
 
6.9%
비 19
 
4.9%
오 17
 
4.3%
류 17
 
4.3%
고 17
 
4.3%
소 15
 
3.8%
Other values (38) 104
26.6%
Latin
ValueCountFrequency (%)
X 55
21.3%
F 50
19.4%
S 15
 
5.8%
O 15
 
5.8%
N 9
 
3.5%
D 9
 
3.5%
M 8
 
3.1%
x 7
 
2.7%
c 6
 
2.3%
U 6
 
2.3%
Other values (32) 78
30.2%
Common
ValueCountFrequency (%)
0 641
27.8%
356
15.4%
9 337
14.6%
~ 189
 
8.2%
1 146
 
6.3%
, 79
 
3.4%
5 65
 
2.8%
) 61
 
2.6%
( 61
 
2.6%
2 59
 
2.6%
Other values (13) 315
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2567
86.8%
Hangul 391
 
13.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 641
25.0%
356
13.9%
9 337
13.1%
~ 189
 
7.4%
1 146
 
5.7%
, 79
 
3.1%
5 65
 
2.5%
) 61
 
2.4%
( 61
 
2.4%
2 59
 
2.3%
Other values (55) 573
22.3%
Hangul
ValueCountFrequency (%)
정 67
17.1%
상 54
13.8%
수 27
 
6.9%
자 27
 
6.9%
리 27
 
6.9%
비 19
 
4.9%
오 17
 
4.3%
류 17
 
4.3%
고 17
 
4.3%
소 15
 
3.8%
Other values (38) 104
26.6%

설명
Text

MISSING 

Distinct203
Distinct (%)64.4%
Missing26
Missing (%)7.6%
Memory size2.8 KiB
2024-05-18T09:50:26.996494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length50
Mean length11.4
Min length1

Characters and Unicode

Total characters3591
Distinct characters313
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)46.7%

Sample

1st rowdc
2nd row모델명
3rd row시리얼고유기기번호
4th row타임스탬프값
5th row10분간 측정한 복합악취10분간 측정한 복합악취센싱값(2초 센싱후 10분간 평균값 전송) / 절대값이 아닌 상대값으로 변동 추이를 확인하는 값
ValueCountFrequency (%)
모델명 19
 
2.3%
60분 18
 
2.2%
시리얼 15
 
1.8%
ex 13
 
1.6%
평균 13
 
1.6%
디밍 12
 
1.5%
10분당 12
 
1.5%
1 11
 
1.4%
여부 11
 
1.4%
10
 
1.2%
Other values (367) 678
83.5%
2024-05-18T09:50:27.966643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
498
 
13.9%
0 107
 
3.0%
시 87
 
2.4%
1 76
 
2.1%
) 69
 
1.9%
분 60
 
1.7%
( 56
 
1.6%
값 45
 
1.3%
기 42
 
1.2%
간 42
 
1.2%
Other values (303) 2509
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2132
59.4%
Space Separator 498
 
13.9%
Decimal Number 342
 
9.5%
Uppercase Letter 235
 
6.5%
Lowercase Letter 148
 
4.1%
Other Punctuation 85
 
2.4%
Close Punctuation 69
 
1.9%
Open Punctuation 56
 
1.6%
Dash Punctuation 20
 
0.6%
Math Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 87
 
4.1%
분 60
 
2.8%
값 45
 
2.1%
기 42
 
2.0%
간 42
 
2.0%
지 41
 
1.9%
디 38
 
1.8%
동 38
 
1.8%
등 36
 
1.7%
밍 35
 
1.6%
Other values (232) 1668
78.2%
Lowercase Letter
ValueCountFrequency (%)
e 29
19.6%
x 17
11.5%
a 14
9.5%
o 11
 
7.4%
t 10
 
6.8%
r 9
 
6.1%
g 7
 
4.7%
l 7
 
4.7%
u 6
 
4.1%
v 6
 
4.1%
Other values (13) 32
21.6%
Uppercase Letter
ValueCountFrequency (%)
F 25
 
10.6%
O 25
 
10.6%
I 23
 
9.8%
S 20
 
8.5%
D 16
 
6.8%
N 14
 
6.0%
Y 12
 
5.1%
M 12
 
5.1%
T 12
 
5.1%
X 10
 
4.3%
Other values (13) 66
28.1%
Decimal Number
ValueCountFrequency (%)
0 107
31.3%
1 76
22.2%
3 36
 
10.5%
2 36
 
10.5%
6 29
 
8.5%
5 18
 
5.3%
4 14
 
4.1%
9 10
 
2.9%
7 9
 
2.6%
8 7
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 25
29.4%
: 20
23.5%
/ 9
 
10.6%
. 9
 
10.6%
; 7
 
8.2%
& 7
 
8.2%
* 5
 
5.9%
% 3
 
3.5%
Math Symbol
ValueCountFrequency (%)
~ 3
75.0%
= 1
 
25.0%
Space Separator
ValueCountFrequency (%)
498
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2132
59.4%
Common 1076
30.0%
Latin 383
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 87
 
4.1%
분 60
 
2.8%
값 45
 
2.1%
기 42
 
2.0%
간 42
 
2.0%
지 41
 
1.9%
디 38
 
1.8%
동 38
 
1.8%
등 36
 
1.7%
밍 35
 
1.6%
Other values (232) 1668
78.2%
Latin
ValueCountFrequency (%)
e 29
 
7.6%
F 25
 
6.5%
O 25
 
6.5%
I 23
 
6.0%
S 20
 
5.2%
x 17
 
4.4%
D 16
 
4.2%
a 14
 
3.7%
N 14
 
3.7%
Y 12
 
3.1%
Other values (36) 188
49.1%
Common
ValueCountFrequency (%)
498
46.3%
0 107
 
9.9%
1 76
 
7.1%
) 69
 
6.4%
( 56
 
5.2%
3 36
 
3.3%
2 36
 
3.3%
6 29
 
2.7%
, 25
 
2.3%
- 20
 
1.9%
Other values (15) 124
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2132
59.4%
ASCII 1457
40.6%
Letterlike Symbols 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
498
34.2%
0 107
 
7.3%
1 76
 
5.2%
) 69
 
4.7%
( 56
 
3.8%
3 36
 
2.5%
2 36
 
2.5%
e 29
 
2.0%
6 29
 
2.0%
F 25
 
1.7%
Other values (60) 496
34.0%
Hangul
ValueCountFrequency (%)
시 87
 
4.1%
분 60
 
2.8%
값 45
 
2.1%
기 42
 
2.0%
간 42
 
2.0%
지 41
 
1.9%
디 38
 
1.8%
동 38
 
1.8%
등 36
 
1.7%
밍 35
 
1.6%
Other values (232) 1668
78.2%
Letterlike Symbols
ValueCountFrequency (%)
℃ 2
100.0%

정렬 순서
Text

Distinct52
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-05-18T09:50:28.386888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length2
Mean length2.3225806
Min length1

Characters and Unicode

Total characters792
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)3.8%

Sample

1st rowsort_ordr
2nd row1
3rd row2
4th row3
5th row4
ValueCountFrequency (%)
10 26
 
7.6%
20 26
 
7.6%
30 25
 
7.3%
40 24
 
7.0%
50 22
 
6.5%
60 20
 
5.9%
70 15
 
4.4%
80 14
 
4.1%
110 9
 
2.6%
100 9
 
2.6%
Other values (42) 151
44.3%
2024-05-18T09:50:29.247762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 323
40.8%
1 130
16.4%
2 94
 
11.9%
3 45
 
5.7%
4 41
 
5.2%
5 40
 
5.1%
6 35
 
4.4%
7 28
 
3.5%
8 27
 
3.4%
9 20
 
2.5%
Other values (6) 9
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 783
98.9%
Lowercase Letter 8
 
1.0%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 323
41.3%
1 130
16.6%
2 94
 
12.0%
3 45
 
5.7%
4 41
 
5.2%
5 40
 
5.1%
6 35
 
4.5%
7 28
 
3.6%
8 27
 
3.4%
9 20
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
r 3
37.5%
o 2
25.0%
s 1
 
12.5%
t 1
 
12.5%
d 1
 
12.5%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 784
99.0%
Latin 8
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 323
41.2%
1 130
16.6%
2 94
 
12.0%
3 45
 
5.7%
4 41
 
5.2%
5 40
 
5.1%
6 35
 
4.5%
7 28
 
3.6%
8 27
 
3.4%
9 20
 
2.6%
Latin
ValueCountFrequency (%)
r 3
37.5%
o 2
25.0%
s 1
 
12.5%
t 1
 
12.5%
d 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 792
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 323
40.8%
1 130
16.4%
2 94
 
11.9%
3 45
 
5.7%
4 41
 
5.2%
5 40
 
5.1%
6 35
 
4.4%
7 28
 
3.5%
8 27
 
3.4%
9 20
 
2.5%
Other values (6) 9
 
1.1%

공개 구분 명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
개방
340 
public_nm
 
1

Length

Max length9
Median length2
Mean length2.0205279
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowpublic_nm
2nd row개방
3rd row개방
4th row개방
5th row개방

Common Values

ValueCountFrequency (%)
개방 340
99.7%
public_nm 1
 
0.3%

Length

2024-05-18T09:50:29.686373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:50:29.974418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개방 340
99.7%
public_nm 1
 
0.3%

Correlations

2024-05-18T09:50:30.125478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
송신 서버 번호데이터 번호패킷 사이즈데이터 사이즈패킷 구분 명패킷 길이패킷 단위정렬 순서공개 구분 명
송신 서버 번호1.0000.9180.9940.9900.8730.8610.9570.0001.000
데이터 번호0.9181.0001.0001.0000.6740.8450.9340.7881.000
패킷 사이즈0.9941.0001.0000.9990.9250.8680.9550.0001.000
데이터 사이즈0.9901.0000.9991.0000.8760.8690.9670.0001.000
패킷 구분 명0.8730.6740.9250.8761.0000.9370.9180.9911.000
패킷 길이0.8610.8450.8680.8690.9371.0000.9530.7111.000
패킷 단위0.9570.9340.9550.9670.9180.9531.0000.8961.000
정렬 순서0.0000.7880.0000.0000.9910.7110.8961.0001.000
공개 구분 명1.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-05-18T09:50:30.373376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
패킷 단위데이터 사이즈패킷 구분 명패킷 길이데이터 번호공개 구분 명패킷 사이즈송신 서버 번호
패킷 단위1.0000.5820.6980.6030.7010.9060.5950.543
데이터 사이즈0.5821.0000.7030.4260.9730.9700.9800.868
패킷 구분 명0.6980.7031.0000.8030.7030.9990.7010.695
패킷 길이0.6030.4260.8031.0000.6090.9650.4140.410
데이터 번호0.7010.9730.7030.6091.0000.9970.9700.742
공개 구분 명0.9060.9700.9990.9650.9971.0000.9670.969
패킷 사이즈0.5950.9800.7010.4140.9700.9671.0000.905
송신 서버 번호0.5430.8680.6950.4100.7420.9690.9051.000
2024-05-18T09:50:30.643252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
송신 서버 번호데이터 번호패킷 사이즈데이터 사이즈패킷 구분 명패킷 길이패킷 단위공개 구분 명
송신 서버 번호1.0000.7420.9050.8680.6950.4100.5430.969
데이터 번호0.7421.0000.9700.9730.7030.6090.7010.997
패킷 사이즈0.9050.9701.0000.9800.7010.4140.5950.967
데이터 사이즈0.8680.9730.9801.0000.7030.4260.5820.970
패킷 구분 명0.6950.7030.7010.7031.0000.8030.6980.999
패킷 길이0.4100.6090.4140.4260.8031.0000.6030.965
패킷 단위0.5430.7010.5950.5820.6980.6031.0000.906
공개 구분 명0.9690.9970.9670.9700.9990.9650.9061.000

Missing values

2024-05-18T09:50:15.812071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T09:50:16.657027image/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.
2024-05-18T09:50:17.168183image/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

송신 서버 번호데이터 번호패킷 사이즈데이터 사이즈패킷 구분 명패킷 명패킷 길이패킷 단위패킷 범주설명정렬 순서공개 구분 명
0trnsmit_server_nodata_nopacket_sizedata_sizepacket_se_nmpacket_nmpacket_bytepacket_unitpacket_ctgrydcsort_ordrpublic_nm
11413729헤더모델명4<NA><NA>모델명1개방
21413729헤더시리얼4<NA><NA>시리얼고유기기번호2개방
31413729테일센싱시간25시<NA>타임스탬프값3개방
41413729테일복합악취센싱값4<NA><NA>10분간 측정한 복합악취10분간 측정한 복합악취센싱값(2초 센싱후 10분간 평균값 전송) / 절대값이 아닌 상대값으로 변동 추이를 확인하는 값4개방
51516948헤더모델명10문자열<NA>L.SEND 모델명(LS-OLOR153)1개방
61516948헤더설치기기별 시리얼(고유번호)11문자열<NA>L.SEND 일련번호(1804TBXXXXX, XXXXX는 가변숫자)2개방
71516948테일고전압 회로 오류1<NA>정상 : 0, 비정상(오류) : 1<NA>3개방
81516948테일배터리 부족1<NA>정상 : 0, 비정상(오류) : 1<NA>4개방
91516948테일임피던스 회로 오류1<NA>정상 : 0, 비정상(오류) : 1<NA>5개방
송신 서버 번호데이터 번호패킷 사이즈데이터 사이즈패킷 구분 명패킷 명패킷 길이패킷 단위패킷 범주설명정렬 순서공개 구분 명
331481143125테일진동(x)7g0.00~16.0060분 평균 진동(x)150개방
332481143125테일진동(y)7g0.00~16.0060분 평균 진동(y)160개방
333481143125테일진동(z)7g0.00~16.0060분 평균 진동(z)170개방
334481143125테일진동(x) 최대7g0.00~16.0060분 최대 진동(x)180개방
335481143125테일진동(y) 최대7g0.00~16.0060분 최대 진동(y)190개방
336481143125테일진동(z) 최대7g0.00~16.0060분 최대 진동(z)200개방
337481143125테일흑구 온도7℃-40.0~120.060분 평균 흑구온도210개방
338481143125테일초미세먼지 보정4㎍/㎥0~1500초미세먼지 국가 관측망 기준 보정 데이터(UI 표현 대상)220개방
339481143125테일미세먼지 보정4㎍/㎥0~1500미세먼지 국가 관측망 기준 보정 데이터(UI 표현 대상)230개방
340481143125테일전송시간12<NA>%Y%M%D%H%I201912130901240개방