Overview

Dataset statistics

Number of variables12
Number of observations303
Missing cells206
Missing cells (%)5.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.8 KiB
Average record size in memory97.4 B

Variable types

Categorical6
Text6

Dataset

Description파일 다운로드
Author서울교통공사
URLhttps://data.seoul.go.kr/dataList/OA-2732/F/1/datasetView.do

Alerts

측정 지점 is highly overall correlated with 권고기준.3High correlation
권고기준.3 is highly overall correlated with 측정 지점High correlation
시 설 명 (역사명) has 206 (68.0%) missing valuesMissing

Reproduction

Analysis started2024-04-29 22:00:07.992199
Analysis finished2024-04-29 22:00:09.066005
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

호선
Categorical

Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2
113 
3
90 
4
68 
1
30 
<NA>
 
2

Length

Max length4
Median length1
Mean length1.019802
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 113
37.3%
3 90
29.7%
4 68
22.4%
1 30
 
9.9%
<NA> 2
 
0.7%

Length

2024-04-30T07:00:09.124933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:00:09.220663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 113
37.3%
3 90
29.7%
4 68
22.4%
1 30
 
9.9%
na 2
 
0.7%

시 설 명 (역사명)
Text

MISSING 

Distinct88
Distinct (%)90.7%
Missing206
Missing (%)68.0%
Memory size2.5 KiB
2024-04-30T07:00:09.451720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.3608247
Min length3

Characters and Unicode

Total characters423
Distinct characters120
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)81.4%

Sample

1st row서울역
2nd row시 청
3rd row종 각
4th row종로3가
5th row종로5가
ValueCountFrequency (%)
신 5
 
3.4%
대 5
 
3.4%
동대문 4
 
2.7%
사 3
 
2.0%
당 3
 
2.0%
수 3
 
2.0%
청 3
 
2.0%
아 2
 
1.4%
삼 2
 
1.4%
시 2
 
1.4%
Other values (99) 115
78.2%
2024-04-30T07:00:09.850008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
135
31.9%
대 17
 
4.0%
신 13
 
3.1%
동 13
 
3.1%
구 11
 
2.6%
로 10
 
2.4%
입 7
 
1.7%
문 7
 
1.7%
가 6
 
1.4%
청 6
 
1.4%
Other values (110) 198
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 279
66.0%
Space Separator 135
31.9%
Decimal Number 6
 
1.4%
Control 3
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 17
 
6.1%
신 13
 
4.7%
동 13
 
4.7%
구 11
 
3.9%
로 10
 
3.6%
입 7
 
2.5%
문 7
 
2.5%
가 6
 
2.2%
청 6
 
2.2%
지 5
 
1.8%
Other values (105) 184
65.9%
Decimal Number
ValueCountFrequency (%)
3 4
66.7%
5 1
 
16.7%
4 1
 
16.7%
Space Separator
ValueCountFrequency (%)
135
100.0%
Control
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 279
66.0%
Common 144
34.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 17
 
6.1%
신 13
 
4.7%
동 13
 
4.7%
구 11
 
3.9%
로 10
 
3.6%
입 7
 
2.5%
문 7
 
2.5%
가 6
 
2.2%
청 6
 
2.2%
지 5
 
1.8%
Other values (105) 184
65.9%
Common
ValueCountFrequency (%)
135
93.8%
3 4
 
2.8%
3
 
2.1%
5 1
 
0.7%
4 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 279
66.0%
ASCII 144
34.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
135
93.8%
3 4
 
2.8%
3
 
2.1%
5 1
 
0.7%
4 1
 
0.7%
Hangul
ValueCountFrequency (%)
대 17
 
6.1%
신 13
 
4.7%
동 13
 
4.7%
구 11
 
3.9%
로 10
 
3.6%
입 7
 
2.5%
문 7
 
2.5%
가 6
 
2.2%
청 6
 
2.2%
지 5
 
1.8%
Other values (105) 184
65.9%

측정 지점
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
평 균
97 
승강장
97 
대합실
97 
환승통로
10 
<NA>
 
1

Length

Max length6
Median length3
Mean length3.3663366
Min length3

Unique

Unique2 ?
Unique (%)0.7%

Sample

1st row<NA>
2nd row공기질 기준
3rd row평 균
4th row승강장
5th row대합실

Common Values

ValueCountFrequency (%)
평 균 97
32.0%
승강장 97
32.0%
대합실 97
32.0%
환승통로 10
 
3.3%
<NA> 1
 
0.3%
공기질 기준 1
 
0.3%

Length

2024-04-30T07:00:09.973127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:00:10.080565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
평 97
24.2%
균 97
24.2%
승강장 97
24.2%
대합실 97
24.2%
환승통로 10
 
2.5%
na 1
 
0.2%
공기질 1
 
0.2%
기준 1
 
0.2%

유지기준
Text

Distinct231
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-04-30T07:00:10.414100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.1947195
Min length2

Characters and Unicode

Total characters1271
Distinct characters17
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique173 ?
Unique (%)57.1%

Sample

1st rowPM10
2nd row140 ㎍/㎥
3rd row101.6
4th row112.9
5th row90.3
ValueCountFrequency (%)
78.6 4
 
1.3%
93.8 4
 
1.3%
107 4
 
1.3%
96.2 3
 
1.0%
80.5 3
 
1.0%
98.3 3
 
1.0%
96 3
 
1.0%
101.6 3
 
1.0%
96.5 3
 
1.0%
85.4 3
 
1.0%
Other values (222) 271
89.1%
2024-04-30T07:00:10.868397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 268
21.1%
1 217
17.1%
8 139
10.9%
9 132
10.4%
0 103
 
8.1%
7 91
 
7.2%
2 74
 
5.8%
6 74
 
5.8%
5 64
 
5.0%
3 57
 
4.5%
Other values (7) 52
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 997
78.4%
Other Punctuation 269
 
21.2%
Other Symbol 2
 
0.2%
Uppercase Letter 2
 
0.2%
Control 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 217
21.8%
8 139
13.9%
9 132
13.2%
0 103
10.3%
7 91
9.1%
2 74
 
7.4%
6 74
 
7.4%
5 64
 
6.4%
3 57
 
5.7%
4 46
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 268
99.6%
/ 1
 
0.4%
Other Symbol
ValueCountFrequency (%)
㎍ 1
50.0%
㎥ 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
M 1
50.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1269
99.8%
Latin 2
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 268
21.1%
1 217
17.1%
8 139
11.0%
9 132
10.4%
0 103
 
8.1%
7 91
 
7.2%
2 74
 
5.8%
6 74
 
5.8%
5 64
 
5.0%
3 57
 
4.5%
Other values (5) 50
 
3.9%
Latin
ValueCountFrequency (%)
P 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1269
99.8%
CJK Compat 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 268
21.1%
1 217
17.1%
8 139
11.0%
9 132
10.4%
0 103
 
8.1%
7 91
 
7.2%
2 74
 
5.8%
6 74
 
5.8%
5 64
 
5.0%
3 57
 
4.5%
Other values (5) 50
 
3.9%
CJK Compat
ValueCountFrequency (%)
㎍ 1
50.0%
㎥ 1
50.0%

유지기준.1
Text

Distinct285
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-04-30T07:00:11.236217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.8151815
Min length3

Characters and Unicode

Total characters1459
Distinct characters17
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique269 ?
Unique (%)88.8%

Sample

1st rowCO2
2nd row1,000 ppm
3rd row552.9
4th row579
5th row526.8
ValueCountFrequency (%)
492.4 3
 
1.0%
517.4 3
 
1.0%
418.8 2
 
0.7%
457 2
 
0.7%
492.5 2
 
0.7%
481.4 2
 
0.7%
485.1 2
 
0.7%
484.4 2
 
0.7%
417 2
 
0.7%
466.6 2
 
0.7%
Other values (276) 282
92.8%
2024-04-30T07:00:11.724555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 272
18.6%
. 272
18.6%
5 184
12.6%
6 119
8.2%
1 113
7.7%
8 96
 
6.6%
9 92
 
6.3%
2 90
 
6.2%
7 88
 
6.0%
3 75
 
5.1%
Other values (7) 58
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1180
80.9%
Other Punctuation 273
 
18.7%
Lowercase Letter 3
 
0.2%
Uppercase Letter 2
 
0.1%
Control 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 272
23.1%
5 184
15.6%
6 119
10.1%
1 113
9.6%
8 96
 
8.1%
9 92
 
7.8%
2 90
 
7.6%
7 88
 
7.5%
3 75
 
6.4%
0 51
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 272
99.6%
, 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
p 2
66.7%
m 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
O 1
50.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1454
99.7%
Latin 5
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
4 272
18.7%
. 272
18.7%
5 184
12.7%
6 119
8.2%
1 113
7.8%
8 96
 
6.6%
9 92
 
6.3%
2 90
 
6.2%
7 88
 
6.1%
3 75
 
5.2%
Other values (3) 53
 
3.6%
Latin
ValueCountFrequency (%)
p 2
40.0%
m 1
20.0%
C 1
20.0%
O 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1459
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 272
18.6%
. 272
18.6%
5 184
12.6%
6 119
8.2%
1 113
7.7%
8 96
 
6.6%
9 92
 
6.3%
2 90
 
6.2%
7 88
 
6.0%
3 75
 
5.1%
Other values (7) 58
 
4.0%

유지기준.2
Text

Distinct86
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-04-30T07:00:11.968022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length3.7986799
Min length2

Characters and Unicode

Total characters1151
Distinct characters18
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)8.6%

Sample

1st rowHCHO
2nd row100 ㎍/㎥
3rd row14.1
4th row14.4
5th row13.8
ValueCountFrequency (%)
13.4 13
 
4.3%
13.5 13
 
4.3%
13.3 12
 
3.9%
13.9 11
 
3.6%
13.1 10
 
3.3%
14.4 8
 
2.6%
13.8 8
 
2.6%
13.6 8
 
2.6%
16.6 7
 
2.3%
16 7
 
2.3%
Other values (77) 207
68.1%
2024-04-30T07:00:12.302977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 325
28.2%
. 269
23.4%
3 121
 
10.5%
4 82
 
7.1%
6 71
 
6.2%
5 62
 
5.4%
8 58
 
5.0%
9 53
 
4.6%
2 50
 
4.3%
7 44
 
3.8%
Other values (8) 16
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 874
75.9%
Other Punctuation 270
 
23.5%
Uppercase Letter 4
 
0.3%
Other Symbol 2
 
0.2%
Control 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 325
37.2%
3 121
 
13.8%
4 82
 
9.4%
6 71
 
8.1%
5 62
 
7.1%
8 58
 
6.6%
9 53
 
6.1%
2 50
 
5.7%
7 44
 
5.0%
0 8
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
H 2
50.0%
C 1
25.0%
O 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 269
99.6%
/ 1
 
0.4%
Other Symbol
ValueCountFrequency (%)
㎍ 1
50.0%
㎥ 1
50.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1147
99.7%
Latin 4
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 325
28.3%
. 269
23.5%
3 121
 
10.5%
4 82
 
7.1%
6 71
 
6.2%
5 62
 
5.4%
8 58
 
5.1%
9 53
 
4.6%
2 50
 
4.4%
7 44
 
3.8%
Other values (5) 12
 
1.0%
Latin
ValueCountFrequency (%)
H 2
50.0%
C 1
25.0%
O 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1149
99.8%
CJK Compat 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 325
28.3%
. 269
23.4%
3 121
 
10.5%
4 82
 
7.1%
6 71
 
6.2%
5 62
 
5.4%
8 58
 
5.0%
9 53
 
4.6%
2 50
 
4.4%
7 44
 
3.8%
Other values (6) 14
 
1.2%
CJK Compat
ValueCountFrequency (%)
㎍ 1
50.0%
㎥ 1
50.0%

유지기준.3
Categorical

Distinct18
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0.8
54 
1
50 
0.7
43 
0.9
42 
1.1
27 
Other values (13)
87 

Length

Max length5
Median length3
Mean length2.6732673
Min length1

Unique

Unique4 ?
Unique (%)1.3%

Sample

1st rowCO
2nd row9 ppm
3rd row0.7
4th row0.7
5th row0.7

Common Values

ValueCountFrequency (%)
0.8 54
17.8%
1 50
16.5%
0.7 43
14.2%
0.9 42
13.9%
1.1 27
8.9%
0.6 24
7.9%
0.5 19
 
6.3%
0.4 18
 
5.9%
1.7 7
 
2.3%
1.2 5
 
1.7%
Other values (8) 14
 
4.6%

Length

2024-04-30T07:00:12.444715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.8 54
17.8%
1 50
16.4%
0.7 43
14.1%
0.9 42
13.8%
1.1 27
8.9%
0.6 24
7.9%
0.5 19
 
6.2%
0.4 18
 
5.9%
1.7 7
 
2.3%
1.2 5
 
1.6%
Other values (9) 15
 
4.9%

권고기준
Categorical

Distinct48
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0.032
 
17
0.033
 
16
0.019
 
15
0.035
 
13
0.021
 
12
Other values (43)
230 

Length

Max length8
Median length5
Mean length4.9471947
Min length3

Unique

Unique10 ?
Unique (%)3.3%

Sample

1st rowNO2
2nd row0.05 ppm
3rd row0.047
4th row0.052
5th row0.042

Common Values

ValueCountFrequency (%)
0.032 17
 
5.6%
0.033 16
 
5.3%
0.019 15
 
5.0%
0.035 13
 
4.3%
0.021 12
 
4.0%
0.029 12
 
4.0%
0.014 12
 
4.0%
0.024 12
 
4.0%
0.026 12
 
4.0%
0.015 12
 
4.0%
Other values (38) 170
56.1%

Length

2024-04-30T07:00:12.567325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.032 17
 
5.6%
0.033 16
 
5.3%
0.019 15
 
4.9%
0.035 13
 
4.3%
0.021 12
 
3.9%
0.029 12
 
3.9%
0.014 12
 
3.9%
0.024 12
 
3.9%
0.026 12
 
3.9%
0.015 12
 
3.9%
Other values (38) 171
56.2%

권고기준.1
Text

Distinct76
Distinct (%)25.1%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-04-30T07:00:12.752042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length3.6435644
Min length1

Characters and Unicode

Total characters1104
Distinct characters19
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)10.9%

Sample

1st rowRn
2nd row4 pCi/ℓ
3rd row0.37
4th row0.35
5th row0.38
ValueCountFrequency (%)
0.38 29
 
9.5%
0.3 28
 
9.2%
0.4 24
 
7.9%
0.5 16
 
5.3%
0.48 11
 
3.6%
0.33 11
 
3.6%
0.35 11
 
3.6%
0.53 9
 
3.0%
0.7 9
 
3.0%
0.2 8
 
2.6%
Other values (67) 148
48.7%
2024-04-30T07:00:13.079553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 299
27.1%
0 293
26.5%
3 133
12.0%
8 81
 
7.3%
5 73
 
6.6%
4 69
 
6.2%
2 43
 
3.9%
7 31
 
2.8%
1 26
 
2.4%
6 25
 
2.3%
Other values (9) 31
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 797
72.2%
Other Punctuation 300
 
27.2%
Lowercase Letter 4
 
0.4%
Uppercase Letter 2
 
0.2%
Control 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 293
36.8%
3 133
16.7%
8 81
 
10.2%
5 73
 
9.2%
4 69
 
8.7%
2 43
 
5.4%
7 31
 
3.9%
1 26
 
3.3%
6 25
 
3.1%
9 23
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
p 1
25.0%
i 1
25.0%
ℓ 1
25.0%
n 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 299
99.7%
/ 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
R 1
50.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1099
99.5%
Latin 5
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
. 299
27.2%
0 293
26.7%
3 133
12.1%
8 81
 
7.4%
5 73
 
6.6%
4 69
 
6.3%
2 43
 
3.9%
7 31
 
2.8%
1 26
 
2.4%
6 25
 
2.3%
Other values (4) 26
 
2.4%
Latin
ValueCountFrequency (%)
p 1
20.0%
C 1
20.0%
i 1
20.0%
R 1
20.0%
n 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1103
99.9%
Letterlike Symbols 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 299
27.1%
0 293
26.6%
3 133
12.1%
8 81
 
7.3%
5 73
 
6.6%
4 69
 
6.3%
2 43
 
3.9%
7 31
 
2.8%
1 26
 
2.4%
6 25
 
2.3%
Other values (8) 30
 
2.7%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 1
100.0%

권고기준.2
Text

Distinct282
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-04-30T07:00:13.416370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.4026403
Min length2

Characters and Unicode

Total characters1334
Distinct characters18
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique264 ?
Unique (%)87.1%

Sample

1st rowVOC
2nd row500 ㎍/㎥
3rd row101.3
4th row85.4
5th row117.1
ValueCountFrequency (%)
84.5 4
 
1.3%
28.7 3
 
1.0%
113.4 2
 
0.7%
177.9 2
 
0.7%
279.3 2
 
0.7%
67.7 2
 
0.7%
102.1 2
 
0.7%
108.8 2
 
0.7%
105.2 2
 
0.7%
84 2
 
0.7%
Other values (273) 281
92.4%
2024-04-30T07:00:13.930460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 285
21.4%
1 202
15.1%
2 117
8.8%
9 110
 
8.2%
3 103
 
7.7%
8 100
 
7.5%
5 93
 
7.0%
6 89
 
6.7%
7 86
 
6.4%
4 84
 
6.3%
Other values (8) 65
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1042
78.1%
Other Punctuation 286
 
21.4%
Uppercase Letter 3
 
0.2%
Other Symbol 2
 
0.1%
Control 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 202
19.4%
2 117
11.2%
9 110
10.6%
3 103
9.9%
8 100
9.6%
5 93
8.9%
6 89
8.5%
7 86
8.3%
4 84
8.1%
0 58
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
V 1
33.3%
O 1
33.3%
C 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 285
99.7%
/ 1
 
0.3%
Other Symbol
ValueCountFrequency (%)
㎍ 1
50.0%
㎥ 1
50.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1331
99.8%
Latin 3
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 285
21.4%
1 202
15.2%
2 117
8.8%
9 110
 
8.3%
3 103
 
7.7%
8 100
 
7.5%
5 93
 
7.0%
6 89
 
6.7%
7 86
 
6.5%
4 84
 
6.3%
Other values (5) 62
 
4.7%
Latin
ValueCountFrequency (%)
V 1
33.3%
O 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1332
99.9%
CJK Compat 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 285
21.4%
1 202
15.2%
2 117
8.8%
9 110
 
8.3%
3 103
 
7.7%
8 100
 
7.5%
5 93
 
7.0%
6 89
 
6.7%
7 86
 
6.5%
4 84
 
6.3%
Other values (6) 63
 
4.7%
CJK Compat
ValueCountFrequency (%)
㎍ 1
50.0%
㎥ 1
50.0%

권고기준.3
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0.0008
127 
0.0017
68 
0.0016
29 
0.0013
18 
0.0025
 
11
Other values (15)
50 

Length

Max length9
Median length6
Mean length5.8184818
Min length1

Unique

Unique5 ?
Unique (%)1.7%

Sample

1st row석면
2nd row0.01 개/cc
3rd row0.0013
4th row0.0017
5th row0.0008

Common Values

ValueCountFrequency (%)
0.0008 127
41.9%
0.0017 68
22.4%
0.0016 29
 
9.6%
0.0013 18
 
5.9%
0.0025 11
 
3.6%
0 10
 
3.3%
0.0012 7
 
2.3%
0.0015 5
 
1.7%
0.0024 5
 
1.7%
0.002 4
 
1.3%
Other values (10) 19
 
6.3%

Length

2024-04-30T07:00:14.076085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.0008 127
41.8%
0.0017 68
22.4%
0.0016 29
 
9.5%
0.0013 18
 
5.9%
0.0025 11
 
3.6%
0 10
 
3.3%
0.0012 7
 
2.3%
0.0015 5
 
1.6%
0.0024 5
 
1.6%
0.0021 4
 
1.3%
Other values (11) 20
 
6.6%

권고기준.4
Categorical

Distinct21
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0.003
74 
0.002
64 
0.004
40 
0.005
23 
0.007
15 
Other values (16)
87 

Length

Max length8
Median length5
Mean length4.9834983
Min length2

Unique

Unique4 ?
Unique (%)1.3%

Sample

1st rowO3
2nd row0.06 ppm
3rd row0.005
4th row0.006
5th row0.003

Common Values

ValueCountFrequency (%)
0.003 74
24.4%
0.002 64
21.1%
0.004 40
13.2%
0.005 23
 
7.6%
0.007 15
 
5.0%
0.006 15
 
5.0%
0.008 11
 
3.6%
0.001 9
 
3.0%
0.009 8
 
2.6%
0.016 7
 
2.3%
Other values (11) 37
12.2%

Length

2024-04-30T07:00:14.219188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.003 74
24.3%
0.002 64
21.1%
0.004 40
13.2%
0.005 23
 
7.6%
0.007 15
 
4.9%
0.006 15
 
4.9%
0.008 11
 
3.6%
0.001 9
 
3.0%
0.009 8
 
2.6%
0.016 7
 
2.3%
Other values (12) 38
12.5%

Correlations

2024-04-30T07:00:14.294964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선시 설 명 (역사명)측정 지점유지기준.2유지기준.3권고기준권고기준.1권고기준.3권고기준.4
호선1.0000.0000.0000.4140.4560.0000.4620.2500.459
시 설 명\n(역사명)0.0001.000NaN0.9740.8820.0000.9710.0000.000
측정\n지점0.000NaN1.0000.8500.7400.7730.8440.8200.813
유지기준.20.4140.9740.8501.0000.8020.6180.0000.8170.824
유지기준.30.4560.8820.7400.8021.0000.8660.8580.7670.758
권고기준0.0000.0000.7730.6180.8661.0000.0000.7920.808
권고기준.10.4620.9710.8440.0000.8580.0001.0000.8910.600
권고기준.30.2500.0000.8200.8170.7670.7920.8911.0000.732
권고기준.40.4590.0000.8130.8240.7580.8080.6000.7321.000
2024-04-30T07:00:14.409163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
권고기준.3측정 지점권고기준.4유지기준.3호선권고기준
권고기준.31.0000.5690.2960.3410.1350.295
측정\n지점0.5691.0000.4840.4870.0000.451
권고기준.40.2960.4841.0000.3270.2600.305
유지기준.30.3410.4870.3271.0000.2230.390
호선0.1350.0000.2600.2231.0000.000
권고기준0.2950.4510.3050.3900.0001.000
2024-04-30T07:00:14.500371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선측정 지점유지기준.3권고기준권고기준.3권고기준.4
호선1.0000.0000.2230.0000.1350.260
측정\n지점0.0001.0000.4870.4510.5690.484
유지기준.30.2230.4871.0000.3900.3410.327
권고기준0.0000.4510.3901.0000.2950.305
권고기준.30.1350.5690.3410.2951.0000.296
권고기준.40.2600.4840.3270.3050.2961.000

Missing values

2024-04-30T07:00:08.868865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:00:09.012869image/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

호선시 설 명 (역사명)측정 지점유지기준유지기준.1유지기준.2유지기준.3권고기준권고기준.1권고기준.2권고기준.3권고기준.4
0<NA><NA><NA>PM10CO2HCHOCONO2RnVOC석면O3
1<NA><NA>공기질 기준140 ㎍/㎥1,000 ppm100 ㎍/㎥9 ppm0.05 ppm4 pCi/ℓ500 ㎍/㎥0.01 개/cc0.06 ppm
21서울역평 균101.6552.914.10.70.0470.37101.30.00130.005
31<NA>승강장112.957914.40.70.0520.3585.40.00170.006
41<NA>대합실90.3526.813.80.70.0420.38117.10.00080.003
51시 청평 균106.7479.113.90.80.040.3895.30.00090.002
61<NA>승강장116.8481.214.40.70.0460.3861.700.002
71<NA>대합실96.547713.40.90.0340.38128.90.00170.001
81종 각평 균122.3522.918.910.0330.5341.80.00080.002
91<NA>승강장125.553119.610.0330.5341.10.00080.002
호선시 설 명 (역사명)측정 지점유지기준유지기준.1유지기준.2유지기준.3권고기준권고기준.1권고기준.2권고기준.3권고기준.4
2934총신대 입구평 균83.3468.5180.70.0330.3769.20.00080.003
2944<NA>승강장84.8481.617.90.70.0320.48220.00160.002
2954<NA>대합실81.8455.4180.60.0330.25116.300.003
2964사 당평 균96.2517.417.70.50.0280.3452.90.00080.003
2974<NA>승강장94.953917.60.70.0270.4824.90.00080.002
2984<NA>대합실103.1505.317.20.40.0280.2525.900.005
2994<NA>환승통로90.7507.818.40.50.0290.3107.80.00160.002
3004남태령평 균110.2481.414.30.60.0260.92257.10.00160.005
3014<NA>승강장116487.212.70.70.0320.95173.90.00160.005
3024<NA>대합실104.3475.615.90.40.0190.88340.30.00160.004