Overview

Dataset statistics

Number of variables37
Number of observations100
Missing cells99
Missing cells (%)2.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.4 KiB
Average record size in memory301.3 B

Variable types

Text7
Categorical12
Numeric3
Boolean15

Alerts

li_nm has constant value ""Constant
intnt_hold_at has constant value ""Constant
wifi_hold_at has constant value ""Constant
last_updt_de has constant value ""Constant
ctprvn_nm is highly imbalanced (64.7%)Imbalance
adit_chair_hold_at is highly imbalanced (71.4%)Imbalance
tv_hold_at is highly imbalanced (59.8%)Imbalance
doorlock_at is highly imbalanced (75.8%)Imbalance
kitchen_hold_at is highly imbalanced (59.8%)Imbalance
desk_hold_at is highly imbalanced (71.4%)Imbalance
prjt_hold_at is highly imbalanced (59.8%)Imbalance
li_nm has 99 (99.0%) missing valuesMissing

Reproduction

Analysis started2023-12-10 09:50:12.170905
Analysis finished2023-12-10 09:50:13.219078
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

fclty_nm
Text

Distinct62
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:50:13.509166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length15.82
Min length3

Characters and Unicode

Total characters1582
Distinct characters268
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)32.0%

Sample

1st row(두드림 마곡점) 회의실 대여
2nd rowW 아트홀(세미나 대관)
3rd row(성북구) 마이원_커뮤니케이션룸
4th row(성북구) 마이원_커뮤니케이션룸
5th row(성북구) 마이원_커뮤니케이션룸
ValueCountFrequency (%)
회의실 10
 
3.8%
강의실 7
 
2.6%
세미나 6
 
2.3%
강남 5
 
1.9%
단독 4
 
1.5%
가산 4
 
1.5%
회의 4
 
1.5%
독산 4
 
1.5%
강의장 4
 
1.5%
주)와우디랩 3
 
1.1%
Other values (132) 215
80.8%
2023-12-10T18:50:14.237288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
166
 
10.5%
] 85
 
5.4%
[ 85
 
5.4%
, 37
 
2.3%
의 36
 
2.3%
강 33
 
2.1%
대 29
 
1.8%
스 27
 
1.7%
공 27
 
1.7%
구 24
 
1.5%
Other values (258) 1033
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1085
68.6%
Space Separator 166
 
10.5%
Close Punctuation 104
 
6.6%
Open Punctuation 104
 
6.6%
Decimal Number 41
 
2.6%
Other Punctuation 37
 
2.3%
Uppercase Letter 22
 
1.4%
Lowercase Letter 17
 
1.1%
Connector Punctuation 5
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 36
 
3.3%
강 33
 
3.0%
대 29
 
2.7%
스 27
 
2.5%
공 27
 
2.5%
구 24
 
2.2%
역 23
 
2.1%
회 22
 
2.0%
실 22
 
2.0%
이 21
 
1.9%
Other values (217) 821
75.7%
Uppercase Letter
ValueCountFrequency (%)
C 4
18.2%
L 3
13.6%
P 3
13.6%
B 2
9.1%
W 2
9.1%
F 2
9.1%
M 1
 
4.5%
D 1
 
4.5%
R 1
 
4.5%
K 1
 
4.5%
Other values (2) 2
9.1%
Lowercase Letter
ValueCountFrequency (%)
t 3
17.6%
i 2
11.8%
g 2
11.8%
o 2
11.8%
h 1
 
5.9%
l 1
 
5.9%
m 1
 
5.9%
n 1
 
5.9%
z 1
 
5.9%
s 1
 
5.9%
Other values (2) 2
11.8%
Decimal Number
ValueCountFrequency (%)
3 11
26.8%
2 11
26.8%
1 7
17.1%
5 3
 
7.3%
0 3
 
7.3%
4 2
 
4.9%
8 2
 
4.9%
7 1
 
2.4%
9 1
 
2.4%
Close Punctuation
ValueCountFrequency (%)
] 85
81.7%
) 19
 
18.3%
Open Punctuation
ValueCountFrequency (%)
[ 85
81.7%
( 19
 
18.3%
Space Separator
ValueCountFrequency (%)
166
100.0%
Other Punctuation
ValueCountFrequency (%)
, 37
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1081
68.3%
Common 458
29.0%
Latin 39
 
2.5%
Han 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 36
 
3.3%
강 33
 
3.1%
대 29
 
2.7%
스 27
 
2.5%
공 27
 
2.5%
구 24
 
2.2%
역 23
 
2.1%
회 22
 
2.0%
실 22
 
2.0%
이 21
 
1.9%
Other values (213) 817
75.6%
Latin
ValueCountFrequency (%)
C 4
 
10.3%
L 3
 
7.7%
t 3
 
7.7%
P 3
 
7.7%
B 2
 
5.1%
W 2
 
5.1%
i 2
 
5.1%
g 2
 
5.1%
o 2
 
5.1%
F 2
 
5.1%
Other values (14) 14
35.9%
Common
ValueCountFrequency (%)
166
36.2%
] 85
18.6%
[ 85
18.6%
, 37
 
8.1%
( 19
 
4.1%
) 19
 
4.1%
3 11
 
2.4%
2 11
 
2.4%
1 7
 
1.5%
_ 5
 
1.1%
Other values (7) 13
 
2.8%
Han
ValueCountFrequency (%)
望 1
25.0%
屋 1
25.0%
遠 1
25.0%
塔 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1081
68.3%
ASCII 497
31.4%
CJK 4
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
166
33.4%
] 85
17.1%
[ 85
17.1%
, 37
 
7.4%
( 19
 
3.8%
) 19
 
3.8%
3 11
 
2.2%
2 11
 
2.2%
1 7
 
1.4%
_ 5
 
1.0%
Other values (31) 52
 
10.5%
Hangul
ValueCountFrequency (%)
의 36
 
3.3%
강 33
 
3.1%
대 29
 
2.7%
스 27
 
2.5%
공 27
 
2.5%
구 24
 
2.2%
역 23
 
2.1%
회 22
 
2.0%
실 22
 
2.0%
이 21
 
1.9%
Other values (213) 817
75.6%
CJK
ValueCountFrequency (%)
望 1
25.0%
屋 1
25.0%
遠 1
25.0%
塔 1
25.0%

ctprvn_nm
Categorical

IMBALANCE 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
82 
경기도
10 
대구광역시
 
2
인천광역시
 
2
제주특별자치도
 
1
Other values (3)
 
3

Length

Max length7
Median length5
Mean length4.79
Min length3

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row서울특별시
2nd row경기도
3rd row서울특별시
4th row서울특별시
5th row서울특별시

Common Values

ValueCountFrequency (%)
서울특별시 82
82.0%
경기도 10
 
10.0%
대구광역시 2
 
2.0%
인천광역시 2
 
2.0%
제주특별자치도 1
 
1.0%
강원도 1
 
1.0%
대전광역시 1
 
1.0%
전라북도 1
 
1.0%

Length

2023-12-10T18:50:14.619046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:14.879698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 82
82.0%
경기도 10
 
10.0%
대구광역시 2
 
2.0%
인천광역시 2
 
2.0%
제주특별자치도 1
 
1.0%
강원도 1
 
1.0%
대전광역시 1
 
1.0%
전라북도 1
 
1.0%

signgu_nm
Categorical

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강남구
10 
종로구
10 
강서구
8 
금천구
7 
서초구
7 
Other values (25)
58 

Length

Max length7
Median length3
Mean length3.31
Min length2

Unique

Unique8 ?
Unique (%)8.0%

Sample

1st row강서구
2nd row성남시 수정구
3rd row성북구
4th row성북구
5th row성북구

Common Values

ValueCountFrequency (%)
강남구 10
 
10.0%
종로구 10
 
10.0%
강서구 8
 
8.0%
금천구 7
 
7.0%
서초구 7
 
7.0%
구로구 5
 
5.0%
송파구 5
 
5.0%
성동구 5
 
5.0%
성북구 4
 
4.0%
양천구 3
 
3.0%
Other values (20) 36
36.0%

Length

2023-12-10T18:50:15.129083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강남구 10
 
9.3%
종로구 10
 
9.3%
강서구 8
 
7.5%
금천구 7
 
6.5%
서초구 7
 
6.5%
구로구 5
 
4.7%
송파구 5
 
4.7%
성동구 5
 
4.7%
성북구 4
 
3.7%
관악구 3
 
2.8%
Other values (24) 43
40.2%

emd_nm
Categorical

Distinct47
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
마곡동
8 
서초동
 
6
구로동
 
5
가산동
 
5
역삼동
 
4
Other values (42)
72 

Length

Max length6
Median length3
Mean length3.16
Min length2

Unique

Unique21 ?
Unique (%)21.0%

Sample

1st row마곡동
2nd row창곡동
3rd row성북동
4th row성북동
5th row성북동

Common Values

ValueCountFrequency (%)
마곡동 8
 
8.0%
서초동 6
 
6.0%
구로동 5
 
5.0%
가산동 5
 
5.0%
역삼동 4
 
4.0%
성수2가3동 4
 
4.0%
잠실동 3
 
3.0%
성북동 3
 
3.0%
논현동 3
 
3.0%
신사동 3
 
3.0%
Other values (37) 56
56.0%

Length

2023-12-10T18:50:15.407593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
마곡동 8
 
8.0%
서초동 6
 
6.0%
구로동 5
 
5.0%
가산동 5
 
5.0%
역삼동 4
 
4.0%
성수2가3동 4
 
4.0%
자양동 3
 
3.0%
봉천동 3
 
3.0%
신월동 3
 
3.0%
신사동 3
 
3.0%
Other values (37) 56
56.0%

li_nm
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing99
Missing (%)99.0%
Memory size932.0 B
2023-12-10T18:50:15.617102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row관음리
ValueCountFrequency (%)
관음리 1
100.0%
2023-12-10T18:50:16.158985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 1
33.3%
음 1
33.3%
리 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 1
33.3%
음 1
33.3%
리 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 1
33.3%
음 1
33.3%
리 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 1
33.3%
음 1
33.3%
리 1
33.3%

lnbr_no
Text

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:50:16.564526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.92
Min length5

Characters and Unicode

Total characters792
Distinct characters14
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

Unique30 ?
Unique (%)30.0%

Sample

1st row794-1 번지
2nd row547-4 번지
3rd row35-2 번지
4th row35-2 번지
5th row35-2 번지
ValueCountFrequency (%)
번지 100
50.0%
779 3
 
1.5%
1128-4 3
 
1.5%
227-2 3
 
1.5%
183-4 3
 
1.5%
798-10 3
 
1.5%
799-9 3
 
1.5%
35-2 3
 
1.5%
300-1 3
 
1.5%
1319-5 2
 
1.0%
Other values (52) 74
37.0%
2023-12-10T18:50:17.363094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
100
12.6%
번 100
12.6%
지 100
12.6%
1 86
10.9%
- 84
10.6%
2 48
6.1%
4 42
 
5.3%
3 41
 
5.2%
7 40
 
5.1%
6 34
 
4.3%
Other values (4) 117
14.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 408
51.5%
Other Letter 200
25.3%
Space Separator 100
 
12.6%
Dash Punctuation 84
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 86
21.1%
2 48
11.8%
4 42
10.3%
3 41
10.0%
7 40
9.8%
6 34
 
8.3%
5 32
 
7.8%
9 29
 
7.1%
8 29
 
7.1%
0 27
 
6.6%
Other Letter
ValueCountFrequency (%)
번 100
50.0%
지 100
50.0%
Space Separator
ValueCountFrequency (%)
100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 592
74.7%
Hangul 200
 
25.3%

Most frequent character per script

Common
ValueCountFrequency (%)
100
16.9%
1 86
14.5%
- 84
14.2%
2 48
8.1%
4 42
7.1%
3 41
6.9%
7 40
 
6.8%
6 34
 
5.7%
5 32
 
5.4%
9 29
 
4.9%
Other values (2) 56
9.5%
Hangul
ValueCountFrequency (%)
번 100
50.0%
지 100
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 592
74.7%
Hangul 200
 
25.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
100
16.9%
1 86
14.5%
- 84
14.2%
2 48
8.1%
4 42
7.1%
3 41
6.9%
7 40
 
6.8%
6 34
 
5.7%
5 32
 
5.4%
9 29
 
4.9%
Other values (2) 56
9.5%
Hangul
ValueCountFrequency (%)
번 100
50.0%
지 100
50.0%

road_nm
Text

Distinct58
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:50:17.823850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.4
Min length2

Characters and Unicode

Total characters540
Distinct characters107
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

Unique29 ?
Unique (%)29.0%

Sample

1st row강서로
2nd row위례광장로
3rd row성북로
4th row성북로
5th row성북로
ValueCountFrequency (%)
아차산로 6
 
6.0%
범안로 4
 
4.0%
마곡중앙4로 3
 
3.0%
강남대로118길 3
 
3.0%
성북로 3
 
3.0%
디지털로32가길 3
 
3.0%
곰달래로 3
 
3.0%
가산디지털1로 3
 
3.0%
마곡중앙로 3
 
3.0%
달서대로85길 2
 
2.0%
Other values (48) 67
67.0%
2023-12-10T18:50:18.664282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 92
 
17.0%
길 51
 
9.4%
1 29
 
5.4%
대 24
 
4.4%
2 15
 
2.8%
3 12
 
2.2%
산 12
 
2.2%
8 11
 
2.0%
서 11
 
2.0%
7 11
 
2.0%
Other values (97) 272
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 438
81.1%
Decimal Number 102
 
18.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 92
21.0%
길 51
 
11.6%
대 24
 
5.5%
산 12
 
2.7%
서 11
 
2.5%
강 10
 
2.3%
남 10
 
2.3%
마 9
 
2.1%
동 8
 
1.8%
곡 7
 
1.6%
Other values (87) 204
46.6%
Decimal Number
ValueCountFrequency (%)
1 29
28.4%
2 15
14.7%
3 12
11.8%
8 11
 
10.8%
7 11
 
10.8%
5 8
 
7.8%
4 7
 
6.9%
9 4
 
3.9%
6 3
 
2.9%
0 2
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 438
81.1%
Common 102
 
18.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 92
21.0%
길 51
 
11.6%
대 24
 
5.5%
산 12
 
2.7%
서 11
 
2.5%
강 10
 
2.3%
남 10
 
2.3%
마 9
 
2.1%
동 8
 
1.8%
곡 7
 
1.6%
Other values (87) 204
46.6%
Common
ValueCountFrequency (%)
1 29
28.4%
2 15
14.7%
3 12
11.8%
8 11
 
10.8%
7 11
 
10.8%
5 8
 
7.8%
4 7
 
6.9%
9 4
 
3.9%
6 3
 
2.9%
0 2
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 438
81.1%
ASCII 102
 
18.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 92
21.0%
길 51
 
11.6%
대 24
 
5.5%
산 12
 
2.7%
서 11
 
2.5%
강 10
 
2.3%
남 10
 
2.3%
마 9
 
2.1%
동 8
 
1.8%
곡 7
 
1.6%
Other values (87) 204
46.6%
ASCII
ValueCountFrequency (%)
1 29
28.4%
2 15
14.7%
3 12
11.8%
8 11
 
10.8%
7 11
 
10.8%
5 8
 
7.8%
4 7
 
6.9%
9 4
 
3.9%
6 3
 
2.9%
0 2
 
2.0%

buld_no
Text

Distinct51
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:50:19.230978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.5
Min length1

Characters and Unicode

Total characters250
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)23.0%

Sample

1st row385
2nd row25
3rd row5-9
4th row5-9
5th row5-9
ValueCountFrequency (%)
18 6
 
6.0%
5 6
 
6.0%
20 6
 
6.0%
36 4
 
4.0%
25 3
 
3.0%
59-5 3
 
3.0%
5-9 3
 
3.0%
26 3
 
3.0%
113 3
 
3.0%
10 3
 
3.0%
Other values (41) 60
60.0%
2023-12-10T18:50:19.992683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 43
17.2%
5 41
16.4%
2 37
14.8%
3 31
12.4%
8 22
8.8%
6 16
 
6.4%
- 15
 
6.0%
0 14
 
5.6%
4 12
 
4.8%
9 10
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 235
94.0%
Dash Punctuation 15
 
6.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 43
18.3%
5 41
17.4%
2 37
15.7%
3 31
13.2%
8 22
9.4%
6 16
 
6.8%
0 14
 
6.0%
4 12
 
5.1%
9 10
 
4.3%
7 9
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 250
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 43
17.2%
5 41
16.4%
2 37
14.8%
3 31
12.4%
8 22
8.8%
6 16
 
6.4%
- 15
 
6.0%
0 14
 
5.6%
4 12
 
4.8%
9 10
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 43
17.2%
5 41
16.4%
2 37
14.8%
3 31
12.4%
8 22
8.8%
6 16
 
6.4%
- 15
 
6.0%
0 14
 
5.6%
4 12
 
4.8%
9 10
 
4.0%

lc_la
Real number (ℝ)

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.411182
Minimum33.472199
Maximum37.629839
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:50:20.310386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.472199
5-th percentile37.184009
Q137.476357
median37.511804
Q337.558817
95-th percentile37.588596
Maximum37.629839
Range4.15764
Interquartile range (IQR)0.0824605

Descriptive statistics

Standard deviation0.50661021
Coefficient of variation (CV)0.013541679
Kurtosis39.274764
Mean37.411182
Median Absolute Deviation (MAD)0.0440565
Skewness-5.8329639
Sum3741.1182
Variance0.2566539
MonotonicityNot monotonic
2023-12-10T18:50:20.610014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.537368 3
 
3.0%
37.482691 3
 
3.0%
37.506586 3
 
3.0%
37.558817 3
 
3.0%
37.52978 3
 
3.0%
37.544693 3
 
3.0%
37.558526 3
 
3.0%
37.588596 3
 
3.0%
37.450358 2
 
2.0%
37.507522 2
 
2.0%
Other values (51) 72
72.0%
ValueCountFrequency (%)
33.472199 1
1.0%
35.83704 2
2.0%
35.849948 1
1.0%
36.397944 1
1.0%
37.225381 2
2.0%
37.28667 2
2.0%
37.323255 1
1.0%
37.443643 1
1.0%
37.450358 2
2.0%
37.465522 2
2.0%
ValueCountFrequency (%)
37.629839 2
2.0%
37.601316 1
 
1.0%
37.593887 1
 
1.0%
37.588596 3
3.0%
37.579545 1
 
1.0%
37.57928 1
 
1.0%
37.578837 2
2.0%
37.576396 2
2.0%
37.574875 1
 
1.0%
37.57295 2
2.0%

lc_lo
Real number (ℝ)

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.01393
Minimum126.55041
Maximum128.49123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:50:20.885795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55041
5-th percentile126.82594
Q1126.89003
median126.99061
Q3127.05545
95-th percentile127.16938
Maximum128.49123
Range1.940823
Interquartile range (IQR)0.165418

Descriptive statistics

Standard deviation0.26162576
Coefficient of variation (CV)0.0020598195
Kurtosis20.730409
Mean127.01393
Median Absolute Deviation (MAD)0.0823905
Skewness4.0837234
Sum12701.393
Variance0.068448039
MonotonicityNot monotonic
2023-12-10T18:50:21.299470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.082565 3
 
3.0%
126.898448 3
 
3.0%
127.025064 3
 
3.0%
126.825939 3
 
3.0%
126.83676 3
 
3.0%
127.056934 3
 
3.0%
126.82862 3
 
3.0%
127.00528 3
 
3.0%
126.70607 2
 
2.0%
127.083923 2
 
2.0%
Other values (51) 72
72.0%
ValueCountFrequency (%)
126.550411 1
 
1.0%
126.70607 2
2.0%
126.790114 1
 
1.0%
126.825939 3
3.0%
126.825979 1
 
1.0%
126.82862 3
3.0%
126.83676 3
3.0%
126.838304 1
 
1.0%
126.883388 2
2.0%
126.884332 2
2.0%
ValueCountFrequency (%)
128.491234 2
2.0%
127.945518 1
 
1.0%
127.404123 1
 
1.0%
127.350279 1
 
1.0%
127.159861 1
 
1.0%
127.140076 2
2.0%
127.123456 1
 
1.0%
127.11876 2
2.0%
127.083923 2
2.0%
127.082565 3
3.0%

zip_no
Real number (ℝ)

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9435.59
Minimum2830
Maximum63248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:50:21.662068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2830
5-th percentile3042.55
Q14794
median6617
Q38590
95-th percentile26861.45
Maximum63248
Range60418
Interquartile range (IQR)3796

Descriptive statistics

Standard deviation10044.921
Coefficient of variation (CV)1.064578
Kurtosis13.420595
Mean9435.59
Median Absolute Deviation (MAD)1902
Skewness3.4865103
Sum943559
Variance1.0090045 × 108
MonotonicityNot monotonic
2023-12-10T18:50:21.955252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5026 3
 
3.0%
8393 3
 
3.0%
6120 3
 
3.0%
7807 3
 
3.0%
7925 3
 
3.0%
4794 3
 
3.0%
7631 3
 
3.0%
2880 3
 
3.0%
21556 2
 
2.0%
5565 2
 
2.0%
Other values (51) 72
72.0%
ValueCountFrequency (%)
2830 1
 
1.0%
2880 3
3.0%
3015 1
 
1.0%
3044 1
 
1.0%
3061 2
2.0%
3088 1
 
1.0%
3121 1
 
1.0%
3134 2
2.0%
3149 2
2.0%
3703 2
2.0%
ValueCountFrequency (%)
63248 1
1.0%
54908 1
1.0%
42714 2
2.0%
34052 1
1.0%
26483 1
1.0%
21556 2
2.0%
18449 2
2.0%
16508 2
2.0%
14558 1
1.0%
13647 2
2.0%

rdnmadr_nm
Text

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:50:22.586354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length19.04
Min length16

Characters and Unicode

Total characters1904
Distinct characters131
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

Unique30 ?
Unique (%)30.0%

Sample

1st row서울특별시 강서구 강서로 385
2nd row경기도 성남시 수정구 위례광장로 25
3rd row서울특별시 성북구 성북로 5-9
4th row서울특별시 성북구 성북로 5-9
5th row서울특별시 성북구 성북로 5-9
ValueCountFrequency (%)
서울특별시 82
 
20.1%
강남구 10
 
2.5%
경기도 10
 
2.5%
종로구 10
 
2.5%
강서구 8
 
2.0%
금천구 7
 
1.7%
서초구 7
 
1.7%
18 6
 
1.5%
20 6
 
1.5%
아차산로 6
 
1.5%
Other values (142) 256
62.7%
2023-12-10T18:50:23.791185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
308
 
16.2%
서 113
 
5.9%
로 107
 
5.6%
구 103
 
5.4%
시 101
 
5.3%
특 83
 
4.4%
별 83
 
4.4%
울 82
 
4.3%
1 72
 
3.8%
2 52
 
2.7%
Other values (121) 800
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1244
65.3%
Decimal Number 337
 
17.7%
Space Separator 308
 
16.2%
Dash Punctuation 15
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 113
 
9.1%
로 107
 
8.6%
구 103
 
8.3%
시 101
 
8.1%
특 83
 
6.7%
별 83
 
6.7%
울 82
 
6.6%
길 51
 
4.1%
대 30
 
2.4%
강 30
 
2.4%
Other values (109) 461
37.1%
Decimal Number
ValueCountFrequency (%)
1 72
21.4%
2 52
15.4%
5 49
14.5%
3 43
12.8%
8 33
9.8%
7 20
 
5.9%
4 19
 
5.6%
6 19
 
5.6%
0 16
 
4.7%
9 14
 
4.2%
Space Separator
ValueCountFrequency (%)
308
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1244
65.3%
Common 660
34.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 113
 
9.1%
로 107
 
8.6%
구 103
 
8.3%
시 101
 
8.1%
특 83
 
6.7%
별 83
 
6.7%
울 82
 
6.6%
길 51
 
4.1%
대 30
 
2.4%
강 30
 
2.4%
Other values (109) 461
37.1%
Common
ValueCountFrequency (%)
308
46.7%
1 72
 
10.9%
2 52
 
7.9%
5 49
 
7.4%
3 43
 
6.5%
8 33
 
5.0%
7 20
 
3.0%
4 19
 
2.9%
6 19
 
2.9%
0 16
 
2.4%
Other values (2) 29
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1244
65.3%
ASCII 660
34.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
308
46.7%
1 72
 
10.9%
2 52
 
7.9%
5 49
 
7.4%
3 43
 
6.5%
8 33
 
5.0%
7 20
 
3.0%
4 19
 
2.9%
6 19
 
2.9%
0 16
 
2.4%
Other values (2) 29
 
4.4%
Hangul
ValueCountFrequency (%)
서 113
 
9.1%
로 107
 
8.6%
구 103
 
8.3%
시 101
 
8.1%
특 83
 
6.7%
별 83
 
6.7%
울 82
 
6.6%
길 51
 
4.1%
대 30
 
2.4%
강 30
 
2.4%
Other values (109) 461
37.1%

lnm_addr
Text

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:50:24.508520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length19.37
Min length15

Characters and Unicode

Total characters1937
Distinct characters116
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

Unique30 ?
Unique (%)30.0%

Sample

1st row서울특별시 강서구 마곡동 794-1
2nd row경기도 성남시 수정구 창곡동 547-4
3rd row서울특별시 성북구 성북동1가 35-2
4th row서울특별시 성북구 성북동1가 35-2
5th row서울특별시 성북구 성북동1가 35-2
ValueCountFrequency (%)
서울특별시 82
 
20.1%
강남구 10
 
2.5%
종로구 10
 
2.5%
경기도 10
 
2.5%
마곡동 8
 
2.0%
강서구 8
 
2.0%
서초구 7
 
1.7%
금천구 7
 
1.7%
서초동 6
 
1.5%
송파구 5
 
1.2%
Other values (141) 255
62.5%
2023-12-10T18:50:25.338729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
308
 
15.9%
구 109
 
5.6%
서 108
 
5.6%
동 108
 
5.6%
시 100
 
5.2%
1 92
 
4.7%
- 84
 
4.3%
별 83
 
4.3%
특 83
 
4.3%
울 82
 
4.2%
Other values (106) 780
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1124
58.0%
Decimal Number 421
 
21.7%
Space Separator 308
 
15.9%
Dash Punctuation 84
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 109
 
9.7%
서 108
 
9.6%
동 108
 
9.6%
시 100
 
8.9%
별 83
 
7.4%
특 83
 
7.4%
울 82
 
7.3%
성 22
 
2.0%
로 22
 
2.0%
강 20
 
1.8%
Other values (94) 387
34.4%
Decimal Number
ValueCountFrequency (%)
1 92
21.9%
2 52
12.4%
3 42
10.0%
4 42
10.0%
7 41
9.7%
6 35
 
8.3%
5 32
 
7.6%
9 29
 
6.9%
8 29
 
6.9%
0 27
 
6.4%
Space Separator
ValueCountFrequency (%)
308
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1124
58.0%
Common 813
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 109
 
9.7%
서 108
 
9.6%
동 108
 
9.6%
시 100
 
8.9%
별 83
 
7.4%
특 83
 
7.4%
울 82
 
7.3%
성 22
 
2.0%
로 22
 
2.0%
강 20
 
1.8%
Other values (94) 387
34.4%
Common
ValueCountFrequency (%)
308
37.9%
1 92
 
11.3%
- 84
 
10.3%
2 52
 
6.4%
3 42
 
5.2%
4 42
 
5.2%
7 41
 
5.0%
6 35
 
4.3%
5 32
 
3.9%
9 29
 
3.6%
Other values (2) 56
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1124
58.0%
ASCII 813
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
308
37.9%
1 92
 
11.3%
- 84
 
10.3%
2 52
 
6.4%
3 42
 
5.2%
4 42
 
5.2%
7 41
 
5.0%
6 35
 
4.3%
5 32
 
3.9%
9 29
 
3.6%
Other values (2) 56
 
6.9%
Hangul
ValueCountFrequency (%)
구 109
 
9.7%
서 108
 
9.6%
동 108
 
9.6%
시 100
 
8.9%
별 83
 
7.4%
특 83
 
7.4%
울 82
 
7.3%
성 22
 
2.0%
로 22
 
2.0%
강 20
 
1.8%
Other values (94) 387
34.4%

fclty_ty_nm
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
세미나실
40 
회의실
37 
강의실
22 
컨퍼런스
 
1

Length

Max length4
Median length3
Mean length3.41
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row회의실
2nd row강의실
3rd row강의실
4th row회의실
5th row세미나실

Common Values

ValueCountFrequency (%)
세미나실 40
40.0%
회의실 37
37.0%
강의실 22
22.0%
컨퍼런스 1
 
1.0%

Length

2023-12-10T18:50:25.576965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:25.715332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세미나실 40
40.0%
회의실 37
37.0%
강의실 22
22.0%
컨퍼런스 1
 
1.0%

mon_oper_time
Categorical

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0~24시
24 
9~22시
10 
9~18시
9 
9~21시
6 
10~20시
5 
Other values (21)
46 

Length

Max length6
Median length5
Mean length5.24
Min length5

Unique

Unique6 ?
Unique (%)6.0%

Sample

1st row9~18시
2nd row9~22시
3rd row8~21시
4th row8~21시
5th row8~21시

Common Values

ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

Length

2023-12-10T18:50:25.889455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

tues_oper_time
Categorical

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0~24시
24 
9~22시
10 
9~18시
9 
9~21시
6 
10~20시
5 
Other values (21)
46 

Length

Max length6
Median length5
Mean length5.24
Min length5

Unique

Unique6 ?
Unique (%)6.0%

Sample

1st row9~18시
2nd row9~22시
3rd row8~21시
4th row8~21시
5th row8~21시

Common Values

ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

Length

2023-12-10T18:50:26.106682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

wed_oper_time
Categorical

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0~24시
24 
9~22시
10 
9~18시
9 
9~21시
6 
10~20시
5 
Other values (21)
46 

Length

Max length6
Median length5
Mean length5.24
Min length5

Unique

Unique6 ?
Unique (%)6.0%

Sample

1st row9~18시
2nd row9~22시
3rd row8~21시
4th row8~21시
5th row8~21시

Common Values

ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

Length

2023-12-10T18:50:26.295438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

thur_oper_time
Categorical

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0~24시
24 
9~22시
10 
9~18시
9 
9~21시
6 
10~20시
5 
Other values (21)
46 

Length

Max length6
Median length5
Mean length5.24
Min length5

Unique

Unique6 ?
Unique (%)6.0%

Sample

1st row9~18시
2nd row9~22시
3rd row8~21시
4th row8~21시
5th row8~21시

Common Values

ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

Length

2023-12-10T18:50:26.518788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

fri_oper_time
Categorical

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0~24시
24 
9~22시
10 
9~18시
9 
9~21시
6 
10~20시
5 
Other values (21)
46 

Length

Max length6
Median length5
Mean length5.24
Min length5

Unique

Unique6 ?
Unique (%)6.0%

Sample

1st row9~18시
2nd row9~22시
3rd row8~21시
4th row8~21시
5th row8~21시

Common Values

ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

Length

2023-12-10T18:50:26.841850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

sat_oper_time
Categorical

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0~24시
24 
9~22시
10 
9~18시
9 
9~21시
6 
10~20시
5 
Other values (21)
46 

Length

Max length6
Median length5
Mean length5.24
Min length5

Unique

Unique6 ?
Unique (%)6.0%

Sample

1st row9~18시
2nd row9~22시
3rd row8~21시
4th row8~21시
5th row8~21시

Common Values

ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

Length

2023-12-10T18:50:27.079739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

sun_oper_time
Categorical

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0~24시
24 
9~22시
10 
9~18시
9 
9~21시
6 
10~20시
5 
Other values (21)
46 

Length

Max length6
Median length5
Mean length5.24
Min length5

Unique

Unique6 ?
Unique (%)6.0%

Sample

1st row9~18시
2nd row9~22시
3rd row8~21시
4th row8~21시
5th row8~21시

Common Values

ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

Length

2023-12-10T18:50:27.796127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0~24시 24
24.0%
9~22시 10
 
10.0%
9~18시 9
 
9.0%
9~21시 6
 
6.0%
10~20시 5
 
5.0%
9~20시 5
 
5.0%
9~23시 5
 
5.0%
10~22시 3
 
3.0%
10~17시 3
 
3.0%
8~22시 3
 
3.0%
Other values (16) 27
27.0%

ado_fclty_hold_at
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
55 
True
45 
ValueCountFrequency (%)
False 55
55.0%
True 45
45.0%
2023-12-10T18:50:27.984976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

adit_chair_hold_at
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
95 
False
 
5
ValueCountFrequency (%)
True 95
95.0%
False 5
 
5.0%
2023-12-10T18:50:28.207332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

printer_hold_at
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
68 
True
32 
ValueCountFrequency (%)
False 68
68.0%
True 32
32.0%
2023-12-10T18:50:28.409368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

tv_hold_at
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
92 
False
 
8
ValueCountFrequency (%)
True 92
92.0%
False 8
 
8.0%
2023-12-10T18:50:28.607379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

doorlock_at
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
96 
True
 
4
ValueCountFrequency (%)
False 96
96.0%
True 4
 
4.0%
2023-12-10T18:50:28.816204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

parkng_posbl_at
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
62 
False
38 
ValueCountFrequency (%)
True 62
62.0%
False 38
38.0%
2023-12-10T18:50:28.969469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

intnt_hold_at
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
100 
ValueCountFrequency (%)
True 100
100.0%
2023-12-10T18:50:29.141484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

kitchen_hold_at
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
92 
True
 
8
ValueCountFrequency (%)
False 92
92.0%
True 8
 
8.0%
2023-12-10T18:50:29.352813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

mic_hold_at
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
55 
True
45 
ValueCountFrequency (%)
False 55
55.0%
True 45
45.0%
2023-12-10T18:50:29.541080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

desk_hold_at
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
95 
False
 
5
ValueCountFrequency (%)
True 95
95.0%
False 5
 
5.0%
2023-12-10T18:50:29.703966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

prjt_hold_at
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
92 
False
 
8
ValueCountFrequency (%)
True 92
92.0%
False 8
 
8.0%
2023-12-10T18:50:29.852103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

wifi_hold_at
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
100 
ValueCountFrequency (%)
True 100
100.0%
2023-12-10T18:50:29.997168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

wboard_hold_at
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
59 
False
41 
ValueCountFrequency (%)
True 59
59.0%
False 41
41.0%
2023-12-10T18:50:30.143094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

pc_hold_at
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
66 
True
34 
ValueCountFrequency (%)
False 66
66.0%
True 34
34.0%
2023-12-10T18:50:30.308094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

laptop_hold_at
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
66 
True
34 
ValueCountFrequency (%)
False 66
66.0%
True 34
34.0%
2023-12-10T18:50:30.471609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

last_updt_de
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20221115
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20221115
2nd row20221115
3rd row20221115
4th row20221115
5th row20221115

Common Values

ValueCountFrequency (%)
20221115 100
100.0%

Length

2023-12-10T18:50:30.650173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:30.811916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20221115 100
100.0%

Sample

fclty_nmctprvn_nmsigngu_nmemd_nmli_nmlnbr_noroad_nmbuld_nolc_lalc_lozip_nordnmadr_nmlnm_addrfclty_ty_nmmon_oper_timetues_oper_timewed_oper_timethur_oper_timefri_oper_timesat_oper_timesun_oper_timeado_fclty_hold_atadit_chair_hold_atprinter_hold_attv_hold_atdoorlock_atparkng_posbl_atintnt_hold_atkitchen_hold_atmic_hold_atdesk_hold_atprjt_hold_atwifi_hold_atwboard_hold_atpc_hold_atlaptop_hold_atlast_updt_de
0(두드림 마곡점) 회의실 대여서울특별시강서구마곡동<NA>794-1 번지강서로38537.560093126.8383047803서울특별시 강서구 강서로 385서울특별시 강서구 마곡동 794-1회의실9~18시9~18시9~18시9~18시9~18시9~18시9~18시NYNYNYYNNYYYYNN20221115
1W 아트홀(세미나 대관)경기도성남시 수정구창곡동<NA>547-4 번지위례광장로2537.466574127.14007613647경기도 성남시 수정구 위례광장로 25경기도 성남시 수정구 창곡동 547-4강의실9~22시9~22시9~22시9~22시9~22시9~22시9~22시YYNYNYYNYYYYNNN20221115
2(성북구) 마이원_커뮤니케이션룸서울특별시성북구성북동<NA>35-2 번지성북로5-937.588596127.005282880서울특별시 성북구 성북로 5-9서울특별시 성북구 성북동1가 35-2강의실8~21시8~21시8~21시8~21시8~21시8~21시8~21시NNNYNYYNNNYYNNN20221115
3(성북구) 마이원_커뮤니케이션룸서울특별시성북구성북동<NA>35-2 번지성북로5-937.588596127.005282880서울특별시 성북구 성북로 5-9서울특별시 성북구 성북동1가 35-2회의실8~21시8~21시8~21시8~21시8~21시8~21시8~21시NNNYNYYNNNYYNNN20221115
4(성북구) 마이원_커뮤니케이션룸서울특별시성북구성북동<NA>35-2 번지성북로5-937.588596127.005282880서울특별시 성북구 성북로 5-9서울특별시 성북구 성북동1가 35-2세미나실8~21시8~21시8~21시8~21시8~21시8~21시8~21시NNNYNYYNNNYYNNN20221115
5(세미나, 웨비나) 다목적홀서울특별시종로구와룡동<NA>109-1 번지돈화문로88-137.576396126.9906053134서울특별시 종로구 돈화문로 88-1서울특별시 종로구 와룡동 109-1강의실9~20시9~20시9~20시9~20시9~20시9~20시9~20시YYNYNNYNYYYYNNN20221115
6(세미나, 웨비나) 다목적홀서울특별시종로구와룡동<NA>109-1 번지돈화문로88-137.576396126.9906053134서울특별시 종로구 돈화문로 88-1서울특별시 종로구 와룡동 109-1회의실9~20시9~20시9~20시9~20시9~20시9~20시9~20시YYNYNNYNYYYYNNN20221115
7W 아트홀(세미나 대관)경기도성남시 수정구창곡동<NA>547-4 번지위례광장로2537.466574127.14007613647경기도 성남시 수정구 위례광장로 25경기도 성남시 수정구 창곡동 547-4세미나실9~22시9~22시9~22시9~22시9~22시9~22시9~22시YYNYNYYNYYYYNNN20221115
8(세미나,웨비나)종각역 인사라운지서울특별시종로구견지동<NA>92-1 번지인사동9길3137.57295126.9836183149서울특별시 종로구 인사동9길 31서울특별시 종로구 견지동 92-1회의실9~23시9~23시9~23시9~23시9~23시9~23시9~23시YYNYNNYNYYYYNNN20221115
9(세미나,웨비나)종각역 인사라운지서울특별시종로구견지동<NA>92-1 번지인사동9길3137.57295126.9836183149서울특별시 종로구 인사동9길 31서울특별시 종로구 견지동 92-1세미나실9~23시9~23시9~23시9~23시9~23시9~23시9~23시YYNYNNYNYYYYNNN20221115
fclty_nmctprvn_nmsigngu_nmemd_nmli_nmlnbr_noroad_nmbuld_nolc_lalc_lozip_nordnmadr_nmlnm_addrfclty_ty_nmmon_oper_timetues_oper_timewed_oper_timethur_oper_timefri_oper_timesat_oper_timesun_oper_timeado_fclty_hold_atadit_chair_hold_atprinter_hold_attv_hold_atdoorlock_atparkng_posbl_atintnt_hold_atkitchen_hold_atmic_hold_atdesk_hold_atprjt_hold_atwifi_hold_atwboard_hold_atpc_hold_atlaptop_hold_atlast_updt_de
90[리랩] 전주역 세미나 회의실전라북도전주시 덕진구우아1동<NA>746-43 번지동부대로68735.849948127.15986154908전라북도 전주시 덕진구 동부대로 687전라북도 전주시 덕진구 우아동3가 746-43세미나실9~23시9~23시9~23시9~23시9~23시9~23시9~23시YYNYNYYNYYYYNYY20221115
91[마곡, 발산] 세미나, 회의실서울특별시강서구마곡동<NA>798-10 번지마곡중앙로59-537.558817126.8259397807서울특별시 강서구 마곡중앙로 59-5서울특별시 강서구 마곡동 798-10강의실10~17시10~17시10~17시10~17시10~17시10~17시10~17시NYNYNYYNNYYYNNN20221115
92[마곡, 발산] 세미나, 회의실서울특별시강서구마곡동<NA>798-10 번지마곡중앙로59-537.558817126.8259397807서울특별시 강서구 마곡중앙로 59-5서울특별시 강서구 마곡동 798-10회의실10~17시10~17시10~17시10~17시10~17시10~17시10~17시NYNYNYYNNYYYNNN20221115
93[마곡, 발산] 세미나, 회의실서울특별시강서구마곡동<NA>798-10 번지마곡중앙로59-537.558817126.8259397807서울특별시 강서구 마곡중앙로 59-5서울특별시 강서구 마곡동 798-10세미나실10~17시10~17시10~17시10~17시10~17시10~17시10~17시NYNYNYYNNYYYNNN20221115
94[마곡][강서] 회의실,비대면교육서울특별시강서구마곡동<NA>799-9 번지마곡중앙4로1837.558526126.828627631서울특별시 강서구 마곡중앙4로 18서울특별시 강서구 마곡동 799-9강의실9~21시9~21시9~21시9~21시9~21시9~21시9~21시NYYYNYYNNYYYYYY20221115
95[마곡][강서] 회의실,비대면교육서울특별시강서구마곡동<NA>799-9 번지마곡중앙4로1837.558526126.828627631서울특별시 강서구 마곡중앙4로 18서울특별시 강서구 마곡동 799-9회의실9~21시9~21시9~21시9~21시9~21시9~21시9~21시NYYYNYYNNYYYYYY20221115
96[마곡][강서] 회의실,비대면교육서울특별시강서구마곡동<NA>799-9 번지마곡중앙4로1837.558526126.828627631서울특별시 강서구 마곡중앙4로 18서울특별시 강서구 마곡동 799-9세미나실9~21시9~21시9~21시9~21시9~21시9~21시9~21시NYYYNYYNNYYYYYY20221115
97[마곡]다이브스페이스 모임공간파티서울특별시강서구마곡동<NA>759-1 번지마곡서로15237.567686126.8259797788서울특별시 강서구 마곡서로 152서울특별시 강서구 마곡동 759-1세미나실0~24시0~24시0~24시0~24시0~24시0~24시0~24시NYNYNYYNNYYYYNN20221115
98[마포공덕애오개]마당이야기스터디룸서울특별시마포구공덕동<NA>463 번지마포대로17337.549902126.9544564130서울특별시 마포구 마포대로 173서울특별시 마포구 공덕동 463강의실10~21시10~21시10~21시10~21시10~21시10~21시10~21시NYYYNYYNNYYYNNN20221115
99[망원 옥탑] [望遠屋塔]서울특별시마포구망원동<NA>57-135 번지월드컵로17길3837.555723126.9079184012서울특별시 마포구 월드컵로17길 38서울특별시 마포구 망원동 57-135회의실0~24시0~24시0~24시0~24시0~24시0~24시0~24시NYNNYNYNNYNYNNN20221115