Overview

Dataset statistics

Number of variables12
Number of observations1106
Missing cells697
Missing cells (%)5.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory110.3 KiB
Average record size in memory102.1 B

Variable types

Numeric5
Categorical3
Text4

Dataset

Description송신 서버 번호,데이터 번호,패킷 사이즈,데이터 사이즈,패킷 구분 명,패킷 명,패킷 길이,패킷 단위,패킷 범주,설명,정렬 순서,공개 구분 명
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15956/S/1/datasetView.do

Alerts

패킷 사이즈 is highly overall correlated with 데이터 사이즈 and 1 other fieldsHigh correlation
데이터 사이즈 is highly overall correlated with 패킷 사이즈 and 1 other fieldsHigh correlation
정렬 순서 is highly overall correlated with 패킷 사이즈 and 1 other fieldsHigh correlation
데이터 번호 is highly imbalanced (69.2%)Imbalance
공개 구분 명 is highly imbalanced (84.0%)Imbalance
패킷 단위 has 410 (37.1%) missing valuesMissing
패킷 범주 has 230 (20.8%) missing valuesMissing
설명 has 57 (5.2%) missing valuesMissing

Reproduction

Analysis started2024-05-18 00:50:34.830603
Analysis finished2024-05-18 00:50:45.739017
Duration10.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

송신 서버 번호
Real number (ℝ)

Distinct73
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.387884
Minimum1
Maximum126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2024-05-18T09:50:45.916262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15
Q130
median50
Q385
95-th percentile120
Maximum126
Range125
Interquartile range (IQR)55

Descriptive statistics

Standard deviation36.719859
Coefficient of variation (CV)0.59816134
Kurtosis-1.2332655
Mean61.387884
Median Absolute Deviation (MAD)29
Skewness0.29793098
Sum67895
Variance1348.3481
MonotonicityNot monotonic
2024-05-18T09:50:46.229015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
120 63
 
5.7%
114 60
 
5.4%
24 56
 
5.1%
15 42
 
3.8%
73 31
 
2.8%
30 31
 
2.8%
77 30
 
2.7%
48 30
 
2.7%
17 30
 
2.7%
49 30
 
2.7%
Other values (63) 703
63.6%
ValueCountFrequency (%)
1 6
 
0.5%
2 6
 
0.5%
3 5
 
0.5%
13 23
2.1%
14 4
 
0.4%
15 42
3.8%
16 16
 
1.4%
17 30
2.7%
18 16
 
1.4%
19 9
 
0.8%
ValueCountFrequency (%)
126 8
 
0.7%
125 8
 
0.7%
124 16
 
1.4%
123 8
 
0.7%
122 8
 
0.7%
121 7
 
0.6%
120 63
5.7%
117 7
 
0.6%
114 60
5.4%
113 8
 
0.7%

데이터 번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
1
1015 
2
 
57
3
 
34

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 1015
91.8%
2 57
 
5.2%
3 34
 
3.1%

Length

2024-05-18T09:50:46.639126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:50:46.907339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1015
91.8%
2 57
 
5.2%
3 34
 
3.1%

패킷 사이즈
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean141.58951
Minimum19
Maximum446
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2024-05-18T09:50:47.240225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile24.25
Q156
median87
Q3185
95-th percentile446
Maximum446
Range427
Interquartile range (IQR)129

Descriptive statistics

Standard deviation120.47304
Coefficient of variation (CV)0.85086133
Kurtosis1.1913719
Mean141.58951
Median Absolute Deviation (MAD)51
Skewness1.4283737
Sum156598
Variance14513.754
MonotonicityNot monotonic
2024-05-18T09:50:47.682506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
185 240
21.7%
87 90
 
8.1%
56 65
 
5.9%
69 63
 
5.7%
446 63
 
5.7%
202 62
 
5.6%
425 60
 
5.4%
44 32
 
2.9%
206 28
 
2.5%
19 28
 
2.5%
Other values (34) 375
33.9%
ValueCountFrequency (%)
19 28
2.5%
22 6
 
0.5%
23 15
1.4%
24 7
 
0.6%
25 5
 
0.5%
26 6
 
0.5%
27 5
 
0.5%
30 6
 
0.5%
31 8
 
0.7%
32 4
 
0.4%
ValueCountFrequency (%)
446 63
 
5.7%
425 60
 
5.4%
206 28
 
2.5%
202 62
 
5.6%
185 240
21.7%
125 16
 
1.4%
121 10
 
0.9%
106 20
 
1.8%
99 14
 
1.3%
90 22
 
2.0%

데이터 사이즈
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.98101
Minimum4
Maximum428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2024-05-18T09:50:48.029530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile8
Q136
median64
Q3167
95-th percentile428
Maximum428
Range424
Interquartile range (IQR)131

Descriptive statistics

Standard deviation120.89974
Coefficient of variation (CV)0.9830765
Kurtosis1.1620204
Mean122.98101
Median Absolute Deviation (MAD)49
Skewness1.4256066
Sum136017
Variance14616.748
MonotonicityNot monotonic
2024-05-18T09:50:48.422174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
167 240
21.7%
64 90
 
8.1%
38 65
 
5.9%
428 63
 
5.7%
184 62
 
5.6%
407 60
 
5.4%
48 42
 
3.8%
8 41
 
3.7%
36 32
 
2.9%
26 32
 
2.9%
Other values (29) 379
34.3%
ValueCountFrequency (%)
4 3
 
0.3%
5 8
 
0.7%
6 4
 
0.4%
7 11
 
1.0%
8 41
3.7%
11 7
 
0.6%
15 19
1.7%
16 5
 
0.5%
17 9
 
0.8%
20 6
 
0.5%
ValueCountFrequency (%)
428 63
 
5.7%
407 60
 
5.4%
192 28
 
2.5%
184 62
 
5.6%
167 240
21.7%
115 16
 
1.4%
99 10
 
0.9%
92 20
 
1.8%
81 14
 
1.3%
64 90
 
8.1%

패킷 구분 명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
테일
936 
헤더
170 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
테일 936
84.6%
헤더 170
 
15.4%

Length

2024-05-18T09:50:48.803005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:50:49.059509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
테일 936
84.6%
헤더 170
 
15.4%

패킷 명
Text

Distinct356
Distinct (%)32.2%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2024-05-18T09:50:49.555691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length5.7432188
Min length2

Characters and Unicode

Total characters6352
Distinct characters307
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

Unique176 ?
Unique (%)15.9%

Sample

1st row모델명
2nd row시리얼
3rd row온도
4th row습도
5th rowPM2.5
ValueCountFrequency (%)
모델명 74
 
5.1%
시리얼 68
 
4.7%
온도 39
 
2.7%
최대 36
 
2.5%
초미세먼지 28
 
1.9%
미세먼지 26
 
1.8%
풍향 24
 
1.7%
진동(y 24
 
1.7%
풍속 24
 
1.7%
진동(z 24
 
1.7%
Other values (412) 1079
74.6%
2024-05-18T09:50:50.603893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
375
 
5.9%
_ 185
 
2.9%
시 147
 
2.3%
i 135
 
2.1%
m 129
 
2.0%
도 119
 
1.9%
( 110
 
1.7%
) 109
 
1.7%
지 108
 
1.7%
a 101
 
1.6%
Other values (297) 4834
76.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3821
60.2%
Lowercase Letter 1196
 
18.8%
Space Separator 375
 
5.9%
Uppercase Letter 256
 
4.0%
Decimal Number 228
 
3.6%
Connector Punctuation 185
 
2.9%
Open Punctuation 110
 
1.7%
Close Punctuation 109
 
1.7%
Other Punctuation 53
 
0.8%
Dash Punctuation 18
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 147
 
3.8%
도 119
 
3.1%
지 108
 
2.8%
소 95
 
2.5%
동 93
 
2.4%
리 90
 
2.4%
모 88
 
2.3%
진 84
 
2.2%
먼 83
 
2.2%
세 83
 
2.2%
Other values (232) 2831
74.1%
Uppercase Letter
ValueCountFrequency (%)
I 30
11.7%
D 24
 
9.4%
T 22
 
8.6%
S 19
 
7.4%
O 19
 
7.4%
P 18
 
7.0%
F 15
 
5.9%
R 15
 
5.9%
N 13
 
5.1%
E 13
 
5.1%
Other values (14) 68
26.6%
Lowercase Letter
ValueCountFrequency (%)
i 135
 
11.3%
m 129
 
10.8%
a 101
 
8.4%
n 94
 
7.9%
e 72
 
6.0%
x 67
 
5.6%
v 64
 
5.4%
t 63
 
5.3%
s 56
 
4.7%
o 53
 
4.4%
Other values (13) 362
30.3%
Decimal Number
ValueCountFrequency (%)
2 62
27.2%
1 54
23.7%
0 44
19.3%
3 32
14.0%
5 26
11.4%
4 7
 
3.1%
6 2
 
0.9%
8 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
: 18
34.0%
, 14
26.4%
/ 13
24.5%
. 8
15.1%
Space Separator
ValueCountFrequency (%)
375
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 185
100.0%
Open Punctuation
ValueCountFrequency (%)
( 110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3821
60.2%
Latin 1452
 
22.9%
Common 1079
 
17.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 147
 
3.8%
도 119
 
3.1%
지 108
 
2.8%
소 95
 
2.5%
동 93
 
2.4%
리 90
 
2.4%
모 88
 
2.3%
진 84
 
2.2%
먼 83
 
2.2%
세 83
 
2.2%
Other values (232) 2831
74.1%
Latin
ValueCountFrequency (%)
i 135
 
9.3%
m 129
 
8.9%
a 101
 
7.0%
n 94
 
6.5%
e 72
 
5.0%
x 67
 
4.6%
v 64
 
4.4%
t 63
 
4.3%
s 56
 
3.9%
o 53
 
3.7%
Other values (37) 618
42.6%
Common
ValueCountFrequency (%)
375
34.8%
_ 185
17.1%
( 110
 
10.2%
) 109
 
10.1%
2 62
 
5.7%
1 54
 
5.0%
0 44
 
4.1%
3 32
 
3.0%
5 26
 
2.4%
: 18
 
1.7%
Other values (8) 64
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3821
60.2%
ASCII 2531
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
375
 
14.8%
_ 185
 
7.3%
i 135
 
5.3%
m 129
 
5.1%
( 110
 
4.3%
) 109
 
4.3%
a 101
 
4.0%
n 94
 
3.7%
e 72
 
2.8%
x 67
 
2.6%
Other values (55) 1154
45.6%
Hangul
ValueCountFrequency (%)
시 147
 
3.8%
도 119
 
3.1%
지 108
 
2.8%
소 95
 
2.5%
동 93
 
2.4%
리 90
 
2.4%
모 88
 
2.3%
진 84
 
2.2%
먼 83
 
2.2%
세 83
 
2.2%
Other values (232) 2831
74.1%

패킷 길이
Real number (ℝ)

Distinct26
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.9330922
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2024-05-18T09:50:51.003552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile15
Maximum50
Range49
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.5061094
Coefficient of variation (CV)0.7594875
Kurtosis10.847384
Mean5.9330922
Median Absolute Deviation (MAD)2
Skewness2.2080245
Sum6562
Variance20.305022
MonotonicityNot monotonic
2024-05-18T09:50:51.404400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
7 282
25.5%
1 152
13.7%
4 132
11.9%
2 101
 
9.1%
3 93
 
8.4%
5 84
 
7.6%
6 63
 
5.7%
12 31
 
2.8%
11 27
 
2.4%
8 26
 
2.4%
Other values (16) 115
10.4%
ValueCountFrequency (%)
1 152
13.7%
2 101
 
9.1%
3 93
 
8.4%
4 132
11.9%
5 84
 
7.6%
6 63
 
5.7%
7 282
25.5%
8 26
 
2.4%
9 13
 
1.2%
10 22
 
2.0%
ValueCountFrequency (%)
50 1
 
0.1%
32 1
 
0.1%
27 1
 
0.1%
25 1
 
0.1%
23 4
 
0.4%
21 1
 
0.1%
20 10
0.9%
19 13
1.2%
18 2
 
0.2%
17 1
 
0.1%

패킷 단위
Text

MISSING 

Distinct68
Distinct (%)9.8%
Missing410
Missing (%)37.1%
Memory size8.8 KiB
2024-05-18T09:50:51.831826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length2.2643678
Min length1

Characters and Unicode

Total characters1576
Distinct characters83
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)2.9%

Sample

1st row℃
2nd row%
3rd row㎍/m³
4th row㎍/m³
5th rowppb
ValueCountFrequency (%)
ppm 103
14.8%
㎍/㎥ 72
 
10.3%
64
 
9.2%
g 63
 
9.0%
℃ 51
 
7.3%
정수 44
 
6.3%
m/s 43
 
6.2%
시 23
 
3.3%
분 20
 
2.9%
mm/s 18
 
2.6%
Other values (55) 197
28.2%
2024-05-18T09:50:52.670167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
p 232
14.7%
m 212
13.5%
/ 159
 
10.1%
㎍ 81
 
5.1%
g 81
 
5.1%
㎥ 72
 
4.6%
% 68
 
4.3%
s 61
 
3.9%
℃ 51
 
3.2%
수 49
 
3.1%
Other values (73) 510
32.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 711
45.1%
Other Punctuation 242
 
15.4%
Other Symbol 220
 
14.0%
Other Letter 208
 
13.2%
Uppercase Letter 142
 
9.0%
Other Number 16
 
1.0%
Space Separator 14
 
0.9%
Decimal Number 13
 
0.8%
Open Punctuation 5
 
0.3%
Close Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 49
23.6%
정 44
21.2%
시 28
13.5%
분 23
11.1%
일 7
 
3.4%
월 7
 
3.4%
면 6
 
2.9%
초 5
 
2.4%
명 5
 
2.4%
회 4
 
1.9%
Other values (19) 30
14.4%
Uppercase Letter
ValueCountFrequency (%)
U 28
19.7%
P 24
16.9%
V 17
12.0%
B 15
10.6%
C 11
 
7.7%
W 10
 
7.0%
I 6
 
4.2%
E 5
 
3.5%
M 5
 
3.5%
R 4
 
2.8%
Other values (9) 17
12.0%
Lowercase Letter
ValueCountFrequency (%)
p 232
32.6%
m 212
29.8%
g 81
 
11.4%
s 61
 
8.6%
u 31
 
4.4%
d 17
 
2.4%
x 17
 
2.4%
l 17
 
2.4%
b 15
 
2.1%
h 11
 
1.5%
Other values (4) 17
 
2.4%
Other Symbol
ValueCountFrequency (%)
㎍ 81
36.8%
㎥ 72
32.7%
℃ 51
23.2%
° 7
 
3.2%
㏈ 7
 
3.2%
㎡ 2
 
0.9%
Decimal Number
ValueCountFrequency (%)
3 4
30.8%
5 2
15.4%
4 2
15.4%
2 2
15.4%
1 2
15.4%
0 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
/ 159
65.7%
% 68
28.1%
; 8
 
3.3%
& 4
 
1.7%
? 3
 
1.2%
Other Number
ValueCountFrequency (%)
³ 16
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 852
54.1%
Common 515
32.7%
Hangul 208
 
13.2%
Greek 1
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 232
27.2%
m 212
24.9%
g 81
 
9.5%
s 61
 
7.2%
u 31
 
3.6%
U 28
 
3.3%
P 24
 
2.8%
d 17
 
2.0%
V 17
 
2.0%
x 17
 
2.0%
Other values (22) 132
15.5%
Hangul
ValueCountFrequency (%)
수 49
23.6%
정 44
21.2%
시 28
13.5%
분 23
11.1%
일 7
 
3.4%
월 7
 
3.4%
면 6
 
2.9%
초 5
 
2.4%
명 5
 
2.4%
회 4
 
1.9%
Other values (19) 30
14.4%
Common
ValueCountFrequency (%)
/ 159
30.9%
㎍ 81
15.7%
㎥ 72
14.0%
% 68
13.2%
℃ 51
 
9.9%
³ 16
 
3.1%
14
 
2.7%
; 8
 
1.6%
° 7
 
1.4%
㏈ 7
 
1.4%
Other values (11) 32
 
6.2%
Greek
ValueCountFrequency (%)
μ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1131
71.8%
Hangul 208
 
13.2%
CJK Compat 162
 
10.3%
Letterlike Symbols 51
 
3.2%
None 24
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
p 232
20.5%
m 212
18.7%
/ 159
14.1%
g 81
 
7.2%
% 68
 
6.0%
s 61
 
5.4%
u 31
 
2.7%
U 28
 
2.5%
P 24
 
2.1%
d 17
 
1.5%
Other values (36) 218
19.3%
CJK Compat
ValueCountFrequency (%)
㎍ 81
50.0%
㎥ 72
44.4%
㏈ 7
 
4.3%
㎡ 2
 
1.2%
Letterlike Symbols
ValueCountFrequency (%)
℃ 51
100.0%
Hangul
ValueCountFrequency (%)
수 49
23.6%
정 44
21.2%
시 28
13.5%
분 23
11.1%
일 7
 
3.4%
월 7
 
3.4%
면 6
 
2.9%
초 5
 
2.4%
명 5
 
2.4%
회 4
 
1.9%
Other values (19) 30
14.4%
None
ValueCountFrequency (%)
³ 16
66.7%
° 7
29.2%
μ 1
 
4.2%

패킷 범주
Text

MISSING 

Distinct181
Distinct (%)20.7%
Missing230
Missing (%)20.8%
Memory size8.8 KiB
2024-05-18T09:50:53.167086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length99
Median length40
Mean length8.466895
Min length1

Characters and Unicode

Total characters7417
Distinct characters139
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

Unique82 ?
Unique (%)9.4%

Sample

1st row-30 ~ 50
2nd row-30 ~ 50
3rd row0~1000
4th row0~1000
5th row0 ~ 60,000
ValueCountFrequency (%)
261
 
16.9%
0 133
 
8.6%
1 62
 
4.0%
0~1 52
 
3.4%
0~1600 48
 
3.1%
0~100 44
 
2.9%
정상 38
 
2.5%
0~1500 36
 
2.3%
비정상(오류 33
 
2.1%
100.0 30
 
1.9%
Other values (211) 805
52.2%
2024-05-18T09:50:54.099782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2341
31.6%
~ 721
 
9.7%
676
 
9.1%
1 611
 
8.2%
9 546
 
7.4%
5 188
 
2.5%
, 165
 
2.2%
. 154
 
2.1%
2 135
 
1.8%
6 128
 
1.7%
Other values (129) 1752
23.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4170
56.2%
Math Symbol 740
 
10.0%
Space Separator 676
 
9.1%
Other Letter 576
 
7.8%
Other Punctuation 537
 
7.2%
Uppercase Letter 351
 
4.7%
Lowercase Letter 143
 
1.9%
Open Punctuation 80
 
1.1%
Close Punctuation 79
 
1.1%
Dash Punctuation 63
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 103
17.9%
상 89
15.5%
비 35
 
6.1%
류 33
 
5.7%
오 33
 
5.7%
자 31
 
5.4%
리 29
 
5.0%
수 28
 
4.9%
고 18
 
3.1%
장 17
 
3.0%
Other values (64) 160
27.8%
Uppercase Letter
ValueCountFrequency (%)
F 50
14.2%
X 50
14.2%
D 37
10.5%
S 31
8.8%
O 30
8.5%
M 26
7.4%
N 24
6.8%
H 22
6.3%
Y 19
 
5.4%
T 17
 
4.8%
Other values (12) 45
12.8%
Lowercase Letter
ValueCountFrequency (%)
l 27
18.9%
x 19
13.3%
m 18
12.6%
u 13
9.1%
d 12
8.4%
o 10
 
7.0%
y 8
 
5.6%
r 6
 
4.2%
s 5
 
3.5%
a 4
 
2.8%
Other values (7) 21
14.7%
Decimal Number
ValueCountFrequency (%)
0 2341
56.1%
1 611
 
14.7%
9 546
 
13.1%
5 188
 
4.5%
2 135
 
3.2%
6 128
 
3.1%
3 112
 
2.7%
8 51
 
1.2%
4 41
 
1.0%
7 17
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 165
30.7%
. 154
28.7%
: 99
18.4%
% 71
13.2%
/ 45
 
8.4%
# 1
 
0.2%
& 1
 
0.2%
; 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 721
97.4%
+ 10
 
1.4%
= 9
 
1.2%
Space Separator
ValueCountFrequency (%)
676
100.0%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6347
85.6%
Hangul 576
 
7.8%
Latin 494
 
6.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 103
17.9%
상 89
15.5%
비 35
 
6.1%
류 33
 
5.7%
오 33
 
5.7%
자 31
 
5.4%
리 29
 
5.0%
수 28
 
4.9%
고 18
 
3.1%
장 17
 
3.0%
Other values (64) 160
27.8%
Latin
ValueCountFrequency (%)
F 50
 
10.1%
X 50
 
10.1%
D 37
 
7.5%
S 31
 
6.3%
O 30
 
6.1%
l 27
 
5.5%
M 26
 
5.3%
N 24
 
4.9%
H 22
 
4.5%
Y 19
 
3.8%
Other values (29) 178
36.0%
Common
ValueCountFrequency (%)
0 2341
36.9%
~ 721
 
11.4%
676
 
10.7%
1 611
 
9.6%
9 546
 
8.6%
5 188
 
3.0%
, 165
 
2.6%
. 154
 
2.4%
2 135
 
2.1%
6 128
 
2.0%
Other values (16) 682
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6839
92.2%
Hangul 576
 
7.8%
Letterlike Symbols 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2341
34.2%
~ 721
 
10.5%
676
 
9.9%
1 611
 
8.9%
9 546
 
8.0%
5 188
 
2.7%
, 165
 
2.4%
. 154
 
2.3%
2 135
 
2.0%
6 128
 
1.9%
Other values (54) 1174
17.2%
Hangul
ValueCountFrequency (%)
정 103
17.9%
상 89
15.5%
비 35
 
6.1%
류 33
 
5.7%
오 33
 
5.7%
자 31
 
5.4%
리 29
 
5.0%
수 28
 
4.9%
고 18
 
3.1%
장 17
 
3.0%
Other values (64) 160
27.8%
Letterlike Symbols
ValueCountFrequency (%)
℃ 2
100.0%

설명
Text

MISSING 

Distinct625
Distinct (%)59.6%
Missing57
Missing (%)5.2%
Memory size8.8 KiB
2024-05-18T09:50:54.638640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length56
Mean length20.004766
Min length1

Characters and Unicode

Total characters20985
Distinct characters373
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique497 ?
Unique (%)47.4%

Sample

1st row모델명
2nd row시러얼
3rd row10분당 온도체크값(평균)
4th row10분당 습도체크값(평균)
5th row10분당 초미세먼지체크값(평균)
ValueCountFrequency (%)
294
 
6.3%
표현범위 254
 
5.4%
평균 231
 
4.9%
→ 200
 
4.3%
관측값 199
 
4.3%
2분 183
 
3.9%
0 168
 
3.6%
× 135
 
2.9%
100 80
 
1.7%
최대 67
 
1.4%
Other values (601) 2861
61.2%
2024-05-18T09:50:55.733146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5516
26.3%
0 1656
 
7.9%
1 737
 
3.5%
) 471
 
2.2%
( 458
 
2.2%
분 375
 
1.8%
2 340
 
1.6%
값 334
 
1.6%
측 293
 
1.4%
관 284
 
1.4%
Other values (363) 10521
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8551
40.7%
Space Separator 5516
26.3%
Decimal Number 3275
 
15.6%
Lowercase Letter 990
 
4.7%
Other Punctuation 822
 
3.9%
Uppercase Letter 499
 
2.4%
Close Punctuation 471
 
2.2%
Open Punctuation 458
 
2.2%
Math Symbol 366
 
1.7%
Dash Punctuation 33
 
0.2%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
분 375
 
4.4%
값 334
 
3.9%
측 293
 
3.4%
관 284
 
3.3%
현 283
 
3.3%
위 281
 
3.3%
표 277
 
3.2%
범 254
 
3.0%
평 254
 
3.0%
균 254
 
3.0%
Other values (284) 5662
66.2%
Lowercase Letter
ValueCountFrequency (%)
r 178
18.0%
a 160
16.2%
m 142
14.3%
p 90
9.1%
e 73
7.4%
x 69
 
7.0%
i 46
 
4.6%
t 46
 
4.6%
s 45
 
4.5%
y 30
 
3.0%
Other values (14) 111
11.2%
Uppercase Letter
ValueCountFrequency (%)
I 51
 
10.2%
O 45
 
9.0%
M 43
 
8.6%
Y 36
 
7.2%
D 33
 
6.6%
S 29
 
5.8%
F 28
 
5.6%
P 28
 
5.6%
T 27
 
5.4%
N 23
 
4.6%
Other values (14) 156
31.3%
Decimal Number
ValueCountFrequency (%)
0 1656
50.6%
1 737
22.5%
2 340
 
10.4%
3 138
 
4.2%
6 128
 
3.9%
5 128
 
3.9%
9 58
 
1.8%
8 49
 
1.5%
4 26
 
0.8%
7 15
 
0.5%
Other Punctuation
ValueCountFrequency (%)
? 252
30.7%
; 179
21.8%
: 130
15.8%
& 92
 
11.2%
. 76
 
9.2%
, 40
 
4.9%
/ 28
 
3.4%
% 15
 
1.8%
* 10
 
1.2%
Math Symbol
ValueCountFrequency (%)
→ 200
54.6%
× 135
36.9%
＋ 21
 
5.7%
~ 5
 
1.4%
+ 3
 
0.8%
= 2
 
0.5%
Space Separator
ValueCountFrequency (%)
5516
100.0%
Close Punctuation
ValueCountFrequency (%)
) 471
100.0%
Open Punctuation
ValueCountFrequency (%)
( 458
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10945
52.2%
Hangul 8551
40.7%
Latin 1489
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
분 375
 
4.4%
값 334
 
3.9%
측 293
 
3.4%
관 284
 
3.3%
현 283
 
3.3%
위 281
 
3.3%
표 277
 
3.2%
범 254
 
3.0%
평 254
 
3.0%
균 254
 
3.0%
Other values (284) 5662
66.2%
Latin
ValueCountFrequency (%)
r 178
 
12.0%
a 160
 
10.7%
m 142
 
9.5%
p 90
 
6.0%
e 73
 
4.9%
x 69
 
4.6%
I 51
 
3.4%
i 46
 
3.1%
t 46
 
3.1%
O 45
 
3.0%
Other values (38) 589
39.6%
Common
ValueCountFrequency (%)
5516
50.4%
0 1656
 
15.1%
1 737
 
6.7%
) 471
 
4.3%
( 458
 
4.2%
2 340
 
3.1%
? 252
 
2.3%
→ 200
 
1.8%
; 179
 
1.6%
3 138
 
1.3%
Other values (21) 998
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12075
57.5%
Hangul 8551
40.7%
Arrows 200
 
1.0%
None 156
 
0.7%
Letterlike Symbols 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5516
45.7%
0 1656
 
13.7%
1 737
 
6.1%
) 471
 
3.9%
( 458
 
3.8%
2 340
 
2.8%
? 252
 
2.1%
; 179
 
1.5%
r 178
 
1.5%
a 160
 
1.3%
Other values (65) 2128
 
17.6%
Hangul
ValueCountFrequency (%)
분 375
 
4.4%
값 334
 
3.9%
측 293
 
3.4%
관 284
 
3.3%
현 283
 
3.3%
위 281
 
3.3%
표 277
 
3.2%
범 254
 
3.0%
평 254
 
3.0%
균 254
 
3.0%
Other values (284) 5662
66.2%
Arrows
ValueCountFrequency (%)
→ 200
100.0%
None
ValueCountFrequency (%)
× 135
86.5%
＋ 21
 
13.5%
Letterlike Symbols
ValueCountFrequency (%)
℃ 3
100.0%

정렬 순서
Real number (ℝ)

HIGH CORRELATION 

Distinct84
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.63743
Minimum1
Maximum630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2024-05-18T09:50:56.010111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q140
median80
Q3190
95-th percentile340
Maximum630
Range629
Interquartile range (IQR)150

Descriptive statistics

Standard deviation119.81816
Coefficient of variation (CV)0.9613337
Kurtosis2.7647929
Mean124.63743
Median Absolute Deviation (MAD)60
Skewness1.5853196
Sum137849
Variance14356.392
MonotonicityNot monotonic
2024-05-18T09:50:56.488457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 78
 
7.1%
20 77
 
7.0%
10 77
 
7.0%
40 75
 
6.8%
50 71
 
6.4%
60 61
 
5.5%
70 51
 
4.6%
80 47
 
4.2%
90 30
 
2.7%
100 29
 
2.6%
Other values (74) 510
46.1%
ValueCountFrequency (%)
1 4
 
0.4%
2 4
 
0.4%
3 4
 
0.4%
4 4
 
0.4%
5 3
 
0.3%
6 2
 
0.2%
7 2
 
0.2%
8 2
 
0.2%
9 1
 
0.1%
10 77
7.0%
ValueCountFrequency (%)
630 1
0.1%
620 1
0.1%
610 1
0.1%
600 2
0.2%
590 2
0.2%
580 2
0.2%
570 2
0.2%
560 2
0.2%
550 2
0.2%
540 2
0.2%

공개 구분 명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
개방
1066 
내부
 
30
비공개
 
10

Length

Max length3
Median length2
Mean length2.0090416
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개방 1066
96.4%
내부 30
 
2.7%
비공개 10
 
0.9%

Length

2024-05-18T09:50:56.819421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:50:57.100320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개방 1066
96.4%
내부 30
 
2.7%
비공개 10
 
0.9%

Interactions

2024-05-18T09:50:43.091920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:37.376809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:39.171751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:40.660702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:41.894242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:43.368936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:37.767135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:39.519412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:40.913374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:42.190541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:43.627166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:38.067010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:39.792025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:41.167978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:42.404644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:43.886063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:38.417461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:40.263554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:41.415496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:42.567639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:44.167610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:38.807970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:40.448807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:41.672469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:50:42.823260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T09:50:57.234676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
송신 서버 번호데이터 번호패킷 사이즈데이터 사이즈패킷 구분 명패킷 길이패킷 단위정렬 순서공개 구분 명
송신 서버 번호1.0000.5150.7940.7910.2180.2540.8520.5560.544
데이터 번호0.5151.0000.7560.7540.0000.2940.8190.0900.000
패킷 사이즈0.7940.7561.0001.0000.3460.4120.8660.6050.362
데이터 사이즈0.7910.7541.0001.0000.3450.4150.8710.6080.332
패킷 구분 명0.2180.0000.3460.3451.0000.6320.7100.6210.038
패킷 길이0.2540.2940.4120.4150.6321.0000.8930.3430.000
패킷 단위0.8520.8190.8660.8710.7100.8931.0000.8170.754
정렬 순서0.5560.0900.6050.6080.6210.3430.8171.0000.121
공개 구분 명0.5440.0000.3620.3320.0380.0000.7540.1211.000
2024-05-18T09:50:57.637813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
패킷 구분 명데이터 번호공개 구분 명
패킷 구분 명1.0000.0000.062
데이터 번호0.0001.0000.000
공개 구분 명0.0620.0001.000
2024-05-18T09:50:57.928818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
송신 서버 번호패킷 사이즈데이터 사이즈패킷 길이정렬 순서데이터 번호패킷 구분 명공개 구분 명
송신 서버 번호1.0000.2410.2490.2410.1760.3590.1670.386
패킷 사이즈0.2411.0000.9910.2470.5880.4340.2480.161
데이터 사이즈0.2490.9911.0000.2230.6020.4320.2480.145
패킷 길이0.2410.2470.2231.000-0.0560.1950.4780.000
정렬 순서0.1760.5880.602-0.0561.0000.0530.4790.071
데이터 번호0.3590.4340.4320.1950.0531.0000.0000.000
패킷 구분 명0.1670.2480.2480.4780.4790.0001.0000.062
공개 구분 명0.3860.1610.1450.0000.0710.0000.0621.000

Missing values

2024-05-18T09:50:44.626940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T09:50:45.231005image/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.
2024-05-18T09:50:45.585624image/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
01615936헤더모델명11<NA><NA>모델명1개방
11615936헤더시리얼12<NA><NA>시러얼2개방
21615936테일온도6℃-30 ~ 5010분당 온도체크값(평균)3개방
31615936테일습도6%-30 ~ 5010분당 습도체크값(평균)4개방
41615936테일PM2.56㎍/m³0~100010분당 초미세먼지체크값(평균)5개방
51615936테일PM106㎍/m³0~100010분당 미세먼지체크값(평균)6개방
61615936테일TVOCS6ppb0 ~ 60,00010분당 TVOCs체크값(평균)7개방
71615936테일CO2EQ6ppm0 ~ 10,00010분당 CO2eq체크값(평균)8개방
81516948테일패드 이상1<NA>정상 : 0, 비정상(오류) : 1<NA>19개방
97415638헤더모델명7<NA>SDOT001모델명10개방
송신 서버 번호데이터 번호패킷 사이즈데이터 사이즈패킷 구분 명패킷 명패킷 길이패킷 단위패킷 범주설명정렬 순서공개 구분 명
109611227테일정보41PU5<NA>값460개방
109721368헤더모델명12<NA><NA>모델명10개방
109821368헤더시리얼16<NA><NA>DevEUI(로라장치 고유시리얼)20개방
109921368테일신호등이 초록불에 건너는 사람 감지회수 Counter2회0 ~ 99신호등이 초록불에 건너는 사람 감지회수(5분동안총합)30개방
110021368테일신호등이 빨간불에 건너는 사람 감지회수2회0 ~ 99신호등이 빨간불에 건너는 사람 감지회수(5분동안총합)40개방
110131237헤더모델명6<NA><NA>IoT기기 모델명(NTS100)10비공개
11021315234테일인터페이스코드3<NA>X03<NA>30개방
11031315234테일시퀀스번호3<NA>000 ~ 999<NA>40개방
11048813115테일서브시스템 ID2<NA><NA>Zone내 서브시스템 ID30개방
11058813115테일진입차량수_L3<NA><NA>왼쪽방향 진입차량수40개방