Overview

Dataset statistics

Number of variables28
Number of observations100
Missing cells151
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.5 KiB
Average record size in memory230.3 B

Variable types

Text10
Categorical6
Numeric4
Boolean8

Alerts

ctgry_one_nm has constant value ""Constant
valet_parkng_posbl_at has constant value ""Constant
pet_posbl_at has constant value ""Constant
halal_food_hold_at has constant value ""Constant
gfre_food_hold_at has constant value ""Constant
infn_chair_lend_posbl_at is highly imbalanced (91.9%)Imbalance
wchair_hold_at is highly imbalanced (91.9%)Imbalance
vgtr_menu_hold_at is highly imbalanced (91.9%)Imbalance
last_updt_de is highly imbalanced (80.6%)Imbalance
li_nm has 96 (96.0%) missing valuesMissing
tel_no has 15 (15.0%) missing valuesMissing
workday_oper_time_dc has 20 (20.0%) missing valuesMissing
wkend_oper_time_dc has 20 (20.0%) missing valuesMissing
fclty_nm has unique valuesUnique
lc_la has unique valuesUnique
lc_lo has unique valuesUnique
lnm_addr has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:40:58.104073
Analysis finished2023-12-10 09:40:59.633683
Duration1.53 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

fclty_nm
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:40:59.972748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length7.01
Min length2

Characters and Unicode

Total characters701
Distinct characters189
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row0731양꼬치
2nd rowYUMMYTHAI
3rd row10.5INCH
4th row1000란무까타
5th row100하노이쌀국수
ValueCountFrequency (%)
72420 8
 
6.2%
감성타코 7
 
5.4%
1984나폴리 4
 
3.1%
0731양꼬치 1
 
0.8%
88버거 1
 
0.8%
가드너아드리아 1
 
0.8%
가데나 1
 
0.8%
가네샤 1
 
0.8%
가네끼스시 1
 
0.8%
가남지 1
 
0.8%
Other values (103) 103
79.8%
2023-12-10T18:41:00.791151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 37
 
5.3%
29
 
4.1%
1 28
 
4.0%
0 25
 
3.6%
8 22
 
3.1%
점 22
 
3.1%
4 21
 
3.0%
9 18
 
2.6%
가 18
 
2.6%
7 17
 
2.4%
Other values (179) 464
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 374
53.4%
Decimal Number 196
28.0%
Uppercase Letter 85
 
12.1%
Space Separator 29
 
4.1%
Lowercase Letter 13
 
1.9%
Other Punctuation 4
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 22
 
5.9%
가 18
 
4.8%
스 13
 
3.5%
이 11
 
2.9%
타 11
 
2.9%
리 10
 
2.7%
감 9
 
2.4%
레 8
 
2.1%
나 8
 
2.1%
성 8
 
2.1%
Other values (136) 256
68.4%
Uppercase Letter
ValueCountFrequency (%)
A 11
12.9%
E 9
 
10.6%
T 8
 
9.4%
M 6
 
7.1%
I 5
 
5.9%
O 5
 
5.9%
N 5
 
5.9%
B 4
 
4.7%
L 4
 
4.7%
U 3
 
3.5%
Other values (12) 25
29.4%
Decimal Number
ValueCountFrequency (%)
2 37
18.9%
1 28
14.3%
0 25
12.8%
8 22
11.2%
4 21
10.7%
9 18
9.2%
7 17
8.7%
5 14
 
7.1%
3 10
 
5.1%
6 4
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
23.1%
r 3
23.1%
a 2
15.4%
g 1
 
7.7%
o 1
 
7.7%
u 1
 
7.7%
n 1
 
7.7%
c 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
& 1
 
25.0%
Space Separator
ValueCountFrequency (%)
29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 374
53.4%
Common 229
32.7%
Latin 98
 
14.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 22
 
5.9%
가 18
 
4.8%
스 13
 
3.5%
이 11
 
2.9%
타 11
 
2.9%
리 10
 
2.7%
감 9
 
2.4%
레 8
 
2.1%
나 8
 
2.1%
성 8
 
2.1%
Other values (136) 256
68.4%
Latin
ValueCountFrequency (%)
A 11
 
11.2%
E 9
 
9.2%
T 8
 
8.2%
M 6
 
6.1%
I 5
 
5.1%
O 5
 
5.1%
N 5
 
5.1%
B 4
 
4.1%
L 4
 
4.1%
e 3
 
3.1%
Other values (20) 38
38.8%
Common
ValueCountFrequency (%)
2 37
16.2%
29
12.7%
1 28
12.2%
0 25
10.9%
8 22
9.6%
4 21
9.2%
9 18
7.9%
7 17
7.4%
5 14
 
6.1%
3 10
 
4.4%
Other values (3) 8
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 374
53.4%
ASCII 327
46.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 37
 
11.3%
29
 
8.9%
1 28
 
8.6%
0 25
 
7.6%
8 22
 
6.7%
4 21
 
6.4%
9 18
 
5.5%
7 17
 
5.2%
5 14
 
4.3%
A 11
 
3.4%
Other values (33) 105
32.1%
Hangul
ValueCountFrequency (%)
점 22
 
5.9%
가 18
 
4.8%
스 13
 
3.5%
이 11
 
2.9%
타 11
 
2.9%
리 10
 
2.7%
감 9
 
2.4%
레 8
 
2.1%
나 8
 
2.1%
성 8
 
2.1%
Other values (136) 256
68.4%

ctgry_one_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
음식점/유흥시설
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row음식점/유흥시설
2nd row음식점/유흥시설
3rd row음식점/유흥시설
4th row음식점/유흥시설
5th row음식점/유흥시설

Common Values

ValueCountFrequency (%)
음식점/유흥시설 100
100.0%

Length

2023-12-10T18:41:01.041646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:41:01.191471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식점/유흥시설 100
100.0%

ctgry_two_nm
Categorical

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
유럽음식
46 
동남아시아음식
23 
동아시아음식
17 
남미음식
9 
북미음식
 
2
Other values (3)
 
3

Length

Max length7
Median length4
Mean length5.09
Min length4

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row동아시아음식
2nd row동남아시아음식
3rd row유럽음식
4th row동남아시아음식
5th row동남아시아음식

Common Values

ValueCountFrequency (%)
유럽음식 46
46.0%
동남아시아음식 23
23.0%
동아시아음식 17
 
17.0%
남미음식 9
 
9.0%
북미음식 2
 
2.0%
아프리카음식 1
 
1.0%
지중해음식 1
 
1.0%
인도아시아음식 1
 
1.0%

Length

2023-12-10T18:41:01.391261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:41:01.593491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유럽음식 46
46.0%
동남아시아음식 23
23.0%
동아시아음식 17
 
17.0%
남미음식 9
 
9.0%
북미음식 2
 
2.0%
아프리카음식 1
 
1.0%
지중해음식 1
 
1.0%
인도아시아음식 1
 
1.0%

ctgry_three_nm
Categorical

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
이탈리아
43 
베트남
13 
일본
10 
기타
9 
멕시코
9 
Other values (11)
16 

Length

Max length13
Median length11
Mean length3.48
Min length2

Unique

Unique9 ?
Unique (%)9.0%

Sample

1st row인도
2nd row태국
3rd row이탈리아
4th row기타
5th row베트남

Common Values

ValueCountFrequency (%)
이탈리아 43
43.0%
베트남 13
 
13.0%
일본 10
 
10.0%
기타 9
 
9.0%
멕시코 9
 
9.0%
중국 5
 
5.0%
인도 2
 
2.0%
태국 1
 
1.0%
아프리카 1
 
1.0%
이탈리아 프랑스 1
 
1.0%
Other values (6) 6
 
6.0%

Length

2023-12-10T18:41:01.830433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이탈리아 46
42.6%
베트남 14
 
13.0%
일본 11
 
10.2%
기타 9
 
8.3%
멕시코 9
 
8.3%
중국 5
 
4.6%
프랑스 3
 
2.8%
인도 2
 
1.9%
태국 2
 
1.9%
미국 2
 
1.9%
Other values (5) 5
 
4.6%

ctprvn_nm
Categorical

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
44 
경기도
19 
부산광역시
11 
대전광역시
7 
대구광역시
 
4
Other values (9)
15 

Length

Max length7
Median length5
Mean length4.62
Min length3

Unique

Unique4 ?
Unique (%)4.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 44
44.0%
경기도 19
19.0%
부산광역시 11
 
11.0%
대전광역시 7
 
7.0%
대구광역시 4
 
4.0%
인천광역시 3
 
3.0%
광주광역시 2
 
2.0%
세종특별자치시 2
 
2.0%
충청남도 2
 
2.0%
울산광역시 2
 
2.0%
Other values (4) 4
 
4.0%

Length

2023-12-10T18:41:02.156002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 44
44.0%
경기도 19
19.0%
부산광역시 11
 
11.0%
대전광역시 7
 
7.0%
대구광역시 4
 
4.0%
인천광역시 3
 
3.0%
광주광역시 2
 
2.0%
세종특별자치시 2
 
2.0%
충청남도 2
 
2.0%
울산광역시 2
 
2.0%
Other values (4) 4
 
4.0%

signgu_nm
Categorical

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강남구
8 
중구
7 
유성구
 
6
마포구
 
6
종로구
 
5
Other values (43)
68 

Length

Max length8
Median length3
Mean length3.48
Min length2

Unique

Unique24 ?
Unique (%)24.0%

Sample

1st row안산시 단원구
2nd row강북구
3rd row수원시 팔달구
4th row평택시
5th row중구

Common Values

ValueCountFrequency (%)
강남구 8
 
8.0%
중구 7
 
7.0%
유성구 6
 
6.0%
마포구 6
 
6.0%
종로구 5
 
5.0%
서초구 4
 
4.0%
동작구 3
 
3.0%
남구 3
 
3.0%
광진구 3
 
3.0%
수성구 3
 
3.0%
Other values (38) 52
52.0%

Length

2023-12-10T18:41:02.419175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강남구 8
 
7.1%
중구 7
 
6.2%
유성구 6
 
5.3%
마포구 6
 
5.3%
종로구 5
 
4.4%
안산시 4
 
3.5%
서초구 4
 
3.5%
동작구 3
 
2.7%
광진구 3
 
2.7%
수성구 3
 
2.7%
Other values (45) 64
56.6%

legaldong_nm
Text

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:41:02.914242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.04
Min length2

Characters and Unicode

Total characters304
Distinct characters103
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

Unique84 ?
Unique (%)84.0%

Sample

1st row원곡동
2nd row미아동
3rd row남창동
4th row평택동
5th row순화동
ValueCountFrequency (%)
신사동 3
 
3.0%
서교동 3
 
3.0%
사당동 2
 
2.0%
역삼동 2
 
2.0%
온천동 2
 
2.0%
만촌동 2
 
2.0%
서초동 2
 
2.0%
서귀동 1
 
1.0%
우동 1
 
1.0%
신성동 1
 
1.0%
Other values (81) 81
81.0%
2023-12-10T18:41:03.853200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 98
32.2%
서 9
 
3.0%
신 8
 
2.6%
사 7
 
2.3%
남 5
 
1.6%
삼 5
 
1.6%
대 4
 
1.3%
읍 4
 
1.3%
가 4
 
1.3%
정 4
 
1.3%
Other values (93) 156
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 300
98.7%
Decimal Number 4
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 98
32.7%
서 9
 
3.0%
신 8
 
2.7%
사 7
 
2.3%
남 5
 
1.7%
삼 5
 
1.7%
대 4
 
1.3%
읍 4
 
1.3%
가 4
 
1.3%
정 4
 
1.3%
Other values (90) 152
50.7%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
3 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 300
98.7%
Common 4
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 98
32.7%
서 9
 
3.0%
신 8
 
2.7%
사 7
 
2.3%
남 5
 
1.7%
삼 5
 
1.7%
대 4
 
1.3%
읍 4
 
1.3%
가 4
 
1.3%
정 4
 
1.3%
Other values (90) 152
50.7%
Common
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
3 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 300
98.7%
ASCII 4
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 98
32.7%
서 9
 
3.0%
신 8
 
2.7%
사 7
 
2.3%
남 5
 
1.7%
삼 5
 
1.7%
대 4
 
1.3%
읍 4
 
1.3%
가 4
 
1.3%
정 4
 
1.3%
Other values (90) 152
50.7%
ASCII
ValueCountFrequency (%)
1 2
50.0%
5 1
25.0%
3 1
25.0%

li_nm
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing96
Missing (%)96.0%
Memory size932.0 B
2023-12-10T18:41:04.306058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.75
Min length2

Characters and Unicode

Total characters11
Distinct characters8
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

Unique4 ?
Unique (%)100.0%

Sample

1st row평리
2nd row침산리
3rd row고한리
4th row남문리
ValueCountFrequency (%)
평리 1
25.0%
침산리 1
25.0%
고한리 1
25.0%
남문리 1
25.0%
2023-12-10T18:41:04.924970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 4
36.4%
평 1
 
9.1%
침 1
 
9.1%
산 1
 
9.1%
고 1
 
9.1%
한 1
 
9.1%
남 1
 
9.1%
문 1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 4
36.4%
평 1
 
9.1%
침 1
 
9.1%
산 1
 
9.1%
고 1
 
9.1%
한 1
 
9.1%
남 1
 
9.1%
문 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 4
36.4%
평 1
 
9.1%
침 1
 
9.1%
산 1
 
9.1%
고 1
 
9.1%
한 1
 
9.1%
남 1
 
9.1%
문 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 4
36.4%
평 1
 
9.1%
침 1
 
9.1%
산 1
 
9.1%
고 1
 
9.1%
한 1
 
9.1%
남 1
 
9.1%
문 1
 
9.1%

lnbr_no
Text

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:41:05.450426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.97
Min length5

Characters and Unicode

Total characters797
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

Unique96 ?
Unique (%)96.0%

Sample

1st row764-9 번지
2nd row75-89 번지
3rd row113-5 번지
4th row291-9 번지
5th row217 번지
ValueCountFrequency (%)
번지 100
50.0%
948-3 2
 
1.0%
113-5 2
 
1.0%
121-4 1
 
0.5%
802 1
 
0.5%
1304-2 1
 
0.5%
648-20 1
 
0.5%
465 1
 
0.5%
1538-14 1
 
0.5%
395-69 1
 
0.5%
Other values (89) 89
44.5%
2023-12-10T18:41:06.308172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
100
12.5%
번 100
12.5%
지 100
12.5%
1 91
11.4%
- 82
10.3%
2 54
6.8%
3 45
 
5.6%
5 37
 
4.6%
4 37
 
4.6%
6 33
 
4.1%
Other values (4) 118
14.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 415
52.1%
Other Letter 200
25.1%
Space Separator 100
 
12.5%
Dash Punctuation 82
 
10.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 91
21.9%
2 54
13.0%
3 45
10.8%
5 37
8.9%
4 37
8.9%
6 33
 
8.0%
0 32
 
7.7%
8 31
 
7.5%
7 29
 
7.0%
9 26
 
6.3%
Other Letter
ValueCountFrequency (%)
번 100
50.0%
지 100
50.0%
Space Separator
ValueCountFrequency (%)
100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 597
74.9%
Hangul 200
 
25.1%

Most frequent character per script

Common
ValueCountFrequency (%)
100
16.8%
1 91
15.2%
- 82
13.7%
2 54
9.0%
3 45
7.5%
5 37
 
6.2%
4 37
 
6.2%
6 33
 
5.5%
0 32
 
5.4%
8 31
 
5.2%
Other values (2) 55
9.2%
Hangul
ValueCountFrequency (%)
번 100
50.0%
지 100
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 597
74.9%
Hangul 200
 
25.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
100
16.8%
1 91
15.2%
- 82
13.7%
2 54
9.0%
3 45
7.5%
5 37
 
6.2%
4 37
 
6.2%
6 33
 
5.5%
0 32
 
5.4%
8 31
 
5.2%
Other values (2) 55
9.2%
Hangul
ValueCountFrequency (%)
번 100
50.0%
지 100
50.0%

road_nm
Text

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:41:06.760514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length5.55
Min length3

Characters and Unicode

Total characters555
Distinct characters155
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)94.0%

Sample

1st row관산길
2nd row오패산로31길
3rd row행궁로
4th row중앙2로
5th row서소문로9길
ValueCountFrequency (%)
테헤란로 2
 
2.0%
중앙로 2
 
2.0%
국채보상로200길 2
 
2.0%
동작대로1길 1
 
1.0%
아차산로 1
 
1.0%
압구정로46길 1
 
1.0%
반석로 1
 
1.0%
대학길 1
 
1.0%
보라매로5가길 1
 
1.0%
대덕대로 1
 
1.0%
Other values (87) 87
87.0%
2023-12-10T18:41:07.422535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 92
 
16.6%
길 61
 
11.0%
1 29
 
5.2%
번 19
 
3.4%
대 18
 
3.2%
2 13
 
2.3%
0 13
 
2.3%
동 13
 
2.3%
3 12
 
2.2%
8 10
 
1.8%
Other values (145) 275
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 436
78.6%
Decimal Number 118
 
21.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 92
21.1%
길 61
 
14.0%
번 19
 
4.4%
대 18
 
4.1%
동 13
 
3.0%
문 7
 
1.6%
앙 7
 
1.6%
산 7
 
1.6%
중 7
 
1.6%
서 6
 
1.4%
Other values (134) 199
45.6%
Decimal Number
ValueCountFrequency (%)
1 29
24.6%
2 13
11.0%
0 13
11.0%
3 12
10.2%
8 10
 
8.5%
5 10
 
8.5%
6 9
 
7.6%
4 8
 
6.8%
7 7
 
5.9%
9 7
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 436
78.6%
Common 119
 
21.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 92
21.1%
길 61
 
14.0%
번 19
 
4.4%
대 18
 
4.1%
동 13
 
3.0%
문 7
 
1.6%
앙 7
 
1.6%
산 7
 
1.6%
중 7
 
1.6%
서 6
 
1.4%
Other values (134) 199
45.6%
Common
ValueCountFrequency (%)
1 29
24.4%
2 13
10.9%
0 13
10.9%
3 12
10.1%
8 10
 
8.4%
5 10
 
8.4%
6 9
 
7.6%
4 8
 
6.7%
7 7
 
5.9%
9 7
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 436
78.6%
ASCII 119
 
21.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 92
21.1%
길 61
 
14.0%
번 19
 
4.4%
대 18
 
4.1%
동 13
 
3.0%
문 7
 
1.6%
앙 7
 
1.6%
산 7
 
1.6%
중 7
 
1.6%
서 6
 
1.4%
Other values (134) 199
45.6%
ASCII
ValueCountFrequency (%)
1 29
24.4%
2 13
10.9%
0 13
10.9%
3 12
10.1%
8 10
 
8.4%
5 10
 
8.4%
6 9
 
7.6%
4 8
 
6.7%
7 7
 
5.9%
9 7
 
5.9%

buld_no
Text

Distinct84
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:41:07.856464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length2.71
Min length1

Characters and Unicode

Total characters271
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

Unique74 ?
Unique (%)74.0%

Sample

1st row3
2nd row43
3rd row43
4th row17
5th row28
ValueCountFrequency (%)
23 5
 
5.0%
13 3
 
3.0%
3 3
 
3.0%
14 3
 
3.0%
16 2
 
2.0%
43 2
 
2.0%
50 2
 
2.0%
11 2
 
2.0%
12 2
 
2.0%
95 2
 
2.0%
Other values (74) 74
74.0%
2023-12-10T18:41:08.707736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 61
22.5%
3 35
12.9%
4 30
11.1%
2 24
 
8.9%
- 23
 
8.5%
0 20
 
7.4%
5 19
 
7.0%
6 18
 
6.6%
9 17
 
6.3%
7 12
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 248
91.5%
Dash Punctuation 23
 
8.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 61
24.6%
3 35
14.1%
4 30
12.1%
2 24
 
9.7%
0 20
 
8.1%
5 19
 
7.7%
6 18
 
7.3%
9 17
 
6.9%
7 12
 
4.8%
8 12
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 271
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 61
22.5%
3 35
12.9%
4 30
11.1%
2 24
 
8.9%
- 23
 
8.5%
0 20
 
7.4%
5 19
 
7.0%
6 18
 
6.6%
9 17
 
6.3%
7 12
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 271
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 61
22.5%
3 35
12.9%
4 30
11.1%
2 24
 
8.9%
- 23
 
8.5%
0 20
 
7.4%
5 19
 
7.0%
6 18
 
6.6%
9 17
 
6.3%
7 12
 
4.4%

lc_la
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.892984
Minimum33.249248
Maximum37.891627
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:41:08.982625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.249248
5-th percentile35.154322
Q136.37528
median37.477401
Q337.546324
95-th percentile37.641711
Maximum37.891627
Range4.642379
Interquartile range (IQR)1.171044

Descriptive statistics

Standard deviation0.96236518
Coefficient of variation (CV)0.026085317
Kurtosis0.96349696
Mean36.892984
Median Absolute Deviation (MAD)0.143932
Skewness-1.3244962
Sum3689.2984
Variance0.92614675
MonotonicityNot monotonic
2023-12-10T18:41:09.210056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.331773 1
 
1.0%
37.324042 1
 
1.0%
37.502417 1
 
1.0%
37.523955 1
 
1.0%
36.389757 1
 
1.0%
37.468722 1
 
1.0%
37.491312 1
 
1.0%
36.385492 1
 
1.0%
36.389038 1
 
1.0%
37.488532 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
33.249248 1
1.0%
35.059837 1
1.0%
35.126903 1
1.0%
35.127536 1
1.0%
35.137671 1
1.0%
35.155198 1
1.0%
35.15694 1
1.0%
35.169633 1
1.0%
35.17447 1
1.0%
35.191148 1
1.0%
ValueCountFrequency (%)
37.891627 1
1.0%
37.71809 1
1.0%
37.714492 1
1.0%
37.689839 1
1.0%
37.655363 1
1.0%
37.640992 1
1.0%
37.619637 1
1.0%
37.618466 1
1.0%
37.613469 1
1.0%
37.612311 1
1.0%

lc_lo
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.35771
Minimum126.30048
Maximum129.31794
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:41:09.467100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.30048
5-th percentile126.69204
Q1126.92405
median127.02213
Q3127.30601
95-th percentile129.08809
Maximum129.31794
Range3.017463
Interquartile range (IQR)0.381954

Descriptive statistics

Standard deviation0.80196552
Coefficient of variation (CV)0.0062969529
Kurtosis0.71073783
Mean127.35771
Median Absolute Deviation (MAD)0.110844
Skewness1.5040081
Sum12735.771
Variance0.64314869
MonotonicityNot monotonic
2023-12-10T18:41:09.724422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.796648 1
 
1.0%
126.806189 1
 
1.0%
127.025074 1
 
1.0%
127.03665 1
 
1.0%
127.299722 1
 
1.0%
126.937587 1
 
1.0%
126.924119 1
 
1.0%
127.378888 1
 
1.0%
127.351283 1
 
1.0%
126.884361 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.300479 1
1.0%
126.499521 1
1.0%
126.567122 1
1.0%
126.646385 1
1.0%
126.682491 1
1.0%
126.692539 1
1.0%
126.695853 1
1.0%
126.704153 1
1.0%
126.76296 1
1.0%
126.796648 1
1.0%
ValueCountFrequency (%)
129.317942 1
1.0%
129.288294 1
1.0%
129.170166 1
1.0%
129.128803 1
1.0%
129.103616 1
1.0%
129.087277 1
1.0%
129.084834 1
1.0%
129.077441 1
1.0%
129.075076 1
1.0%
129.064135 1
1.0%

zip_no
Real number (ℝ)

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20281.82
Minimum1219
Maximum63590
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:41:09.983289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1219
5-th percentile3043.6
Q15477
median12226.5
Q334125.5
95-th percentile49680.1
Maximum63590
Range62371
Interquartile range (IQR)28648.5

Descriptive statistics

Standard deviation17988.679
Coefficient of variation (CV)0.88693614
Kurtosis-0.74046174
Mean20281.82
Median Absolute Deviation (MAD)8179
Skewness0.8104396
Sum2028182
Variance3.2359258 × 108
MonotonicityNot monotonic
2023-12-10T18:41:10.623442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42048 2
 
2.0%
15374 1
 
1.0%
5051 1
 
1.0%
6611 1
 
1.0%
6020 1
 
1.0%
34065 1
 
1.0%
8813 1
 
1.0%
7071 1
 
1.0%
34121 1
 
1.0%
34116 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
1219 1
1.0%
2727 1
1.0%
2845 1
1.0%
3011 1
1.0%
3036 1
1.0%
3044 1
1.0%
3085 1
1.0%
3174 1
1.0%
3308 1
1.0%
3330 1
1.0%
ValueCountFrequency (%)
63590 1
1.0%
62224 1
1.0%
61695 1
1.0%
54999 1
1.0%
52684 1
1.0%
49522 1
1.0%
48791 1
1.0%
48511 1
1.0%
48082 1
1.0%
48059 1
1.0%

rdnmadr_nm
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:41:11.226644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length19.42
Min length15

Characters and Unicode

Total characters1942
Distinct characters184
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

Unique98 ?
Unique (%)98.0%

Sample

1st row경기도 안산시 단원구 관산길 3
2nd row서울특별시 강북구 오패산로31길 43
3rd row경기도 수원시 팔달구 행궁로 43
4th row경기도 평택시 중앙2로 17
5th row서울특별시 중구 서소문로9길 28
ValueCountFrequency (%)
서울특별시 44
 
10.6%
경기도 19
 
4.6%
부산광역시 11
 
2.7%
강남구 8
 
1.9%
중구 7
 
1.7%
대전광역시 7
 
1.7%
마포구 6
 
1.4%
유성구 6
 
1.4%
종로구 5
 
1.2%
23 5
 
1.2%
Other values (243) 297
71.6%
2023-12-10T18:41:11.964432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
317
 
16.3%
시 99
 
5.1%
로 98
 
5.0%
구 94
 
4.8%
1 91
 
4.7%
길 61
 
3.1%
서 58
 
3.0%
특 47
 
2.4%
3 47
 
2.4%
별 47
 
2.4%
Other values (174) 983
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1233
63.5%
Decimal Number 368
 
18.9%
Space Separator 317
 
16.3%
Dash Punctuation 23
 
1.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 99
 
8.0%
로 98
 
7.9%
구 94
 
7.6%
길 61
 
4.9%
서 58
 
4.7%
특 47
 
3.8%
별 47
 
3.8%
울 46
 
3.7%
광 37
 
3.0%
대 31
 
2.5%
Other values (161) 615
49.9%
Decimal Number
ValueCountFrequency (%)
1 91
24.7%
3 47
12.8%
4 38
10.3%
2 37
10.1%
0 33
 
9.0%
5 30
 
8.2%
6 27
 
7.3%
9 24
 
6.5%
8 22
 
6.0%
7 19
 
5.2%
Space Separator
ValueCountFrequency (%)
317
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1233
63.5%
Common 709
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 99
 
8.0%
로 98
 
7.9%
구 94
 
7.6%
길 61
 
4.9%
서 58
 
4.7%
특 47
 
3.8%
별 47
 
3.8%
울 46
 
3.7%
광 37
 
3.0%
대 31
 
2.5%
Other values (161) 615
49.9%
Common
ValueCountFrequency (%)
317
44.7%
1 91
 
12.8%
3 47
 
6.6%
4 38
 
5.4%
2 37
 
5.2%
0 33
 
4.7%
5 30
 
4.2%
6 27
 
3.8%
9 24
 
3.4%
- 23
 
3.2%
Other values (3) 42
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1233
63.5%
ASCII 709
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
317
44.7%
1 91
 
12.8%
3 47
 
6.6%
4 38
 
5.4%
2 37
 
5.2%
0 33
 
4.7%
5 30
 
4.2%
6 27
 
3.8%
9 24
 
3.4%
- 23
 
3.2%
Other values (3) 42
 
5.9%
Hangul
ValueCountFrequency (%)
시 99
 
8.0%
로 98
 
7.9%
구 94
 
7.6%
길 61
 
4.9%
서 58
 
4.7%
특 47
 
3.8%
별 47
 
3.8%
울 46
 
3.7%
광 37
 
3.0%
대 31
 
2.5%
Other values (161) 615
49.9%

lnm_addr
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:41:12.533478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length20.28
Min length15

Characters and Unicode

Total characters2028
Distinct characters164
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

Unique100 ?
Unique (%)100.0%

Sample

1st row경기도 안산시 단원구 원곡동 764-9
2nd row서울특별시 강북구 미아동 75-89
3rd row경기도 수원시 팔달구 남창동 113-5
4th row경기도 평택시 평택동 291-9
5th row서울특별시 중구 순화동 217
ValueCountFrequency (%)
서울특별시 44
 
10.4%
경기도 19
 
4.5%
부산광역시 11
 
2.6%
강남구 8
 
1.9%
중구 7
 
1.7%
대전광역시 7
 
1.7%
마포구 6
 
1.4%
유성구 6
 
1.4%
종로구 5
 
1.2%
안산시 4
 
0.9%
Other values (259) 306
72.3%
2023-12-10T18:41:13.452308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
396
19.5%
동 109
 
5.4%
시 98
 
4.8%
구 94
 
4.6%
1 93
 
4.6%
- 82
 
4.0%
서 61
 
3.0%
2 54
 
2.7%
별 47
 
2.3%
특 47
 
2.3%
Other values (154) 947
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1131
55.8%
Decimal Number 419
 
20.7%
Space Separator 396
 
19.5%
Dash Punctuation 82
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 109
 
9.6%
시 98
 
8.7%
구 94
 
8.3%
서 61
 
5.4%
별 47
 
4.2%
특 47
 
4.2%
울 46
 
4.1%
광 35
 
3.1%
역 31
 
2.7%
산 26
 
2.3%
Other values (142) 537
47.5%
Decimal Number
ValueCountFrequency (%)
1 93
22.2%
2 54
12.9%
3 46
11.0%
5 38
9.1%
4 37
 
8.8%
6 33
 
7.9%
0 32
 
7.6%
8 31
 
7.4%
7 29
 
6.9%
9 26
 
6.2%
Space Separator
ValueCountFrequency (%)
396
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1131
55.8%
Common 897
44.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 109
 
9.6%
시 98
 
8.7%
구 94
 
8.3%
서 61
 
5.4%
별 47
 
4.2%
특 47
 
4.2%
울 46
 
4.1%
광 35
 
3.1%
역 31
 
2.7%
산 26
 
2.3%
Other values (142) 537
47.5%
Common
ValueCountFrequency (%)
396
44.1%
1 93
 
10.4%
- 82
 
9.1%
2 54
 
6.0%
3 46
 
5.1%
5 38
 
4.2%
4 37
 
4.1%
6 33
 
3.7%
0 32
 
3.6%
8 31
 
3.5%
Other values (2) 55
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1131
55.8%
ASCII 897
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
396
44.1%
1 93
 
10.4%
- 82
 
9.1%
2 54
 
6.0%
3 46
 
5.1%
5 38
 
4.2%
4 37
 
4.1%
6 33
 
3.7%
0 32
 
3.6%
8 31
 
3.5%
Other values (2) 55
 
6.1%
Hangul
ValueCountFrequency (%)
동 109
 
9.6%
시 98
 
8.7%
구 94
 
8.3%
서 61
 
5.4%
별 47
 
4.2%
특 47
 
4.2%
울 46
 
4.1%
광 35
 
3.1%
역 31
 
2.7%
산 26
 
2.3%
Other values (142) 537
47.5%

tel_no
Real number (ℝ)

MISSING 

Distinct84
Distinct (%)98.8%
Missing15
Missing (%)15.0%
Infinite0
Infinite (%)0.0%
Mean1.4990918 × 1010
Minimum23184246
Maximum5.0714902 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:41:13.918883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23184246
5-th percentile23648326
Q12.2272051 × 108
median5.1466198 × 108
Q35.0713132 × 1010
95-th percentile5.0714048 × 1010
Maximum5.0714902 × 1010
Range5.0691718 × 1010
Interquartile range (IQR)5.0490412 × 1010

Descriptive statistics

Standard deviation2.2606559 × 1010
Coefficient of variation (CV)1.508017
Kurtosis-1.0690595
Mean1.4990918 × 1010
Median Absolute Deviation (MAD)4.8916729 × 108
Skewness0.96593986
Sum1.2742281 × 1012
Variance5.1105652 × 1020
MonotonicityNot monotonic
2023-12-10T18:41:14.367810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25212420 2
 
2.0%
7042450064 1
 
1.0%
50713679698 1
 
1.0%
25494698 1
 
1.0%
50713846100 1
 
1.0%
261239799 1
 
1.0%
28313472 1
 
1.0%
428617557 1
 
1.0%
428629288 1
 
1.0%
7081512224 1
 
1.0%
Other values (74) 74
74.0%
(Missing) 15
 
15.0%
ValueCountFrequency (%)
23184246 1
1.0%
23223302 1
1.0%
23328836 1
1.0%
23378883 1
1.0%
23571111 1
1.0%
23957187 1
1.0%
24172420 1
1.0%
24628883 1
1.0%
25168884 1
1.0%
25212420 2
2.0%
ValueCountFrequency (%)
50714901985 1
1.0%
50714885995 1
1.0%
50714471294 1
1.0%
50714121518 1
1.0%
50714074450 1
1.0%
50713941718 1
1.0%
50713896282 1
1.0%
50713846100 1
1.0%
50713711077 1
1.0%
50713702088 1
1.0%

workday_oper_time_dc
Text

MISSING 

Distinct42
Distinct (%)52.5%
Missing20
Missing (%)20.0%
Memory size932.0 B
2023-12-10T18:41:14.900771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length12.8125
Min length7

Characters and Unicode

Total characters1025
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

Unique31 ?
Unique (%)38.8%

Sample

1st row월-금 10시-20시
2nd row월-금 0시-24시
3rd row월-금 12시-22시
4th row화-금 11시-22시
5th row월-금 12시-22시
ValueCountFrequency (%)
월-금 60
37.7%
11시30분-22시 17
 
10.7%
화-금 11
 
6.9%
11시-21시 10
 
6.3%
11시-22시 7
 
4.4%
12시-22시 7
 
4.4%
11시30분-21시 6
 
3.8%
11시30분-21시30분 3
 
1.9%
10시-22시 3
 
1.9%
월,수-금 3
 
1.9%
Other values (27) 32
20.1%
2023-12-10T18:41:15.502697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 162
15.8%
시 162
15.8%
- 158
15.4%
2 122
11.9%
79
7.7%
금 78
7.6%
월 67
6.5%
0 66
6.4%
3 47
 
4.6%
분 42
 
4.1%
Other values (7) 42
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 407
39.7%
Other Letter 370
36.1%
Dash Punctuation 158
 
15.4%
Space Separator 79
 
7.7%
Other Punctuation 11
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 162
39.8%
2 122
30.0%
0 66
16.2%
3 47
 
11.5%
4 5
 
1.2%
7 4
 
1.0%
8 1
 
0.2%
Other Letter
ValueCountFrequency (%)
시 162
43.8%
금 78
21.1%
월 67
18.1%
분 42
 
11.4%
화 13
 
3.5%
수 5
 
1.4%
목 3
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%
Space Separator
ValueCountFrequency (%)
79
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 655
63.9%
Hangul 370
36.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 162
24.7%
- 158
24.1%
2 122
18.6%
79
12.1%
0 66
10.1%
3 47
 
7.2%
, 11
 
1.7%
4 5
 
0.8%
7 4
 
0.6%
8 1
 
0.2%
Hangul
ValueCountFrequency (%)
시 162
43.8%
금 78
21.1%
월 67
18.1%
분 42
 
11.4%
화 13
 
3.5%
수 5
 
1.4%
목 3
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 655
63.9%
Hangul 370
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 162
24.7%
- 158
24.1%
2 122
18.6%
79
12.1%
0 66
10.1%
3 47
 
7.2%
, 11
 
1.7%
4 5
 
0.8%
7 4
 
0.6%
8 1
 
0.2%
Hangul
ValueCountFrequency (%)
시 162
43.8%
금 78
21.1%
월 67
18.1%
분 42
 
11.4%
화 13
 
3.5%
수 5
 
1.4%
목 3
 
0.8%

wkend_oper_time_dc
Text

MISSING 

Distinct47
Distinct (%)58.8%
Missing20
Missing (%)20.0%
Memory size932.0 B
2023-12-10T18:41:15.887238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length12.6625
Min length2

Characters and Unicode

Total characters1013
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

Unique35 ?
Unique (%)43.8%

Sample

1st row토-일 10시-20시
2nd row토-일 0시-24시
3rd row토 12시-14시30분
4th row토 11시-22시,일 11시-15시
5th row토-일 12시-22시
ValueCountFrequency (%)
토-일 58
35.6%
토 18
 
11.0%
12시-22시 11
 
6.7%
11시-21시 9
 
5.5%
11시30분-22시 8
 
4.9%
11시30분-21시 7
 
4.3%
11시30분-22시,일 4
 
2.5%
12시-21시 4
 
2.5%
11시-22시 4
 
2.5%
휴무 2
 
1.2%
Other values (35) 38
23.3%
2023-12-10T18:41:16.457016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 170
16.8%
1 168
16.6%
- 143
14.1%
2 128
12.6%
83
8.2%
토 76
7.5%
일 65
 
6.4%
0 64
 
6.3%
3 48
 
4.7%
분 42
 
4.1%
Other values (8) 26
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 423
41.8%
Other Letter 357
35.2%
Dash Punctuation 143
 
14.1%
Space Separator 83
 
8.2%
Other Punctuation 7
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 168
39.7%
2 128
30.3%
0 64
 
15.1%
3 48
 
11.3%
4 6
 
1.4%
7 5
 
1.2%
5 2
 
0.5%
8 1
 
0.2%
9 1
 
0.2%
Other Letter
ValueCountFrequency (%)
시 170
47.6%
토 76
21.3%
일 65
 
18.2%
분 42
 
11.8%
휴 2
 
0.6%
무 2
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 143
100.0%
Space Separator
ValueCountFrequency (%)
83
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 656
64.8%
Hangul 357
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 168
25.6%
- 143
21.8%
2 128
19.5%
83
12.7%
0 64
 
9.8%
3 48
 
7.3%
, 7
 
1.1%
4 6
 
0.9%
7 5
 
0.8%
5 2
 
0.3%
Other values (2) 2
 
0.3%
Hangul
ValueCountFrequency (%)
시 170
47.6%
토 76
21.3%
일 65
 
18.2%
분 42
 
11.8%
휴 2
 
0.6%
무 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 656
64.8%
Hangul 357
35.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 170
47.6%
토 76
21.3%
일 65
 
18.2%
분 42
 
11.8%
휴 2
 
0.6%
무 2
 
0.6%
ASCII
ValueCountFrequency (%)
1 168
25.6%
- 143
21.8%
2 128
19.5%
83
12.7%
0 64
 
9.8%
3 48
 
7.3%
, 7
 
1.1%
4 6
 
0.9%
7 5
 
0.8%
5 2
 
0.3%
Other values (2) 2
 
0.3%

fre_parkng_at
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
64 
True
36 
ValueCountFrequency (%)
False 64
64.0%
True 36
36.0%
2023-12-10T18:41:16.674422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

valet_parkng_posbl_at
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
100 
ValueCountFrequency (%)
False 100
100.0%
2023-12-10T18:41:16.809238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

infn_chair_lend_posbl_at
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
99 
True
 
1
ValueCountFrequency (%)
False 99
99.0%
True 1
 
1.0%
2023-12-10T18:41:16.940465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

wchair_hold_at
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
99 
True
 
1
ValueCountFrequency (%)
False 99
99.0%
True 1
 
1.0%
2023-12-10T18:41:17.073485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

pet_posbl_at
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
100 
ValueCountFrequency (%)
False 100
100.0%
2023-12-10T18:41:17.209869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

vgtr_menu_hold_at
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
99 
True
 
1
ValueCountFrequency (%)
False 99
99.0%
True 1
 
1.0%
2023-12-10T18:41:17.349476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

halal_food_hold_at
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
100 
ValueCountFrequency (%)
False 100
100.0%
2023-12-10T18:41:17.491780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

gfre_food_hold_at
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
100 
ValueCountFrequency (%)
False 100
100.0%
2023-12-10T18:41:17.662947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

last_updt_de
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20221130
97 
20221010
 
3

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20221130
2nd row20221010
3rd row20221130
4th row20221130
5th row20221130

Common Values

ValueCountFrequency (%)
20221130 97
97.0%
20221010 3
 
3.0%

Length

2023-12-10T18:41:17.878280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:41:18.045141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20221130 97
97.0%
20221010 3
 
3.0%

Sample

fclty_nmctgry_one_nmctgry_two_nmctgry_three_nmctprvn_nmsigngu_nmlegaldong_nmli_nmlnbr_noroad_nmbuld_nolc_lalc_lozip_nordnmadr_nmlnm_addrtel_noworkday_oper_time_dcwkend_oper_time_dcfre_parkng_atvalet_parkng_posbl_atinfn_chair_lend_posbl_atwchair_hold_atpet_posbl_atvgtr_menu_hold_athalal_food_hold_atgfre_food_hold_atlast_updt_de
00731양꼬치음식점/유흥시설동아시아음식인도경기도안산시 단원구원곡동<NA>764-9 번지관산길337.331773126.79664815374경기도 안산시 단원구 관산길 3경기도 안산시 단원구 원곡동 764-9<NA><NA><NA>YNNNNNNN20221130
1YUMMYTHAI음식점/유흥시설동남아시아음식태국서울특별시강북구미아동<NA>75-89 번지오패산로31길4337.613469127.0315691219서울특별시 강북구 오패산로31길 43서울특별시 강북구 미아동 75-89<NA><NA><NA>NNNNNNNN20221010
210.5INCH음식점/유흥시설유럽음식이탈리아경기도수원시 팔달구남창동<NA>113-5 번지행궁로4337.278747127.01535516261경기도 수원시 팔달구 행궁로 43경기도 수원시 팔달구 남창동 113-5<NA><NA><NA>NNNNNNNN20221130
31000란무까타음식점/유흥시설동남아시아음식기타경기도평택시평택동<NA>291-9 번지중앙2로1736.991785127.08896817909경기도 평택시 중앙2로 17경기도 평택시 평택동 291-9<NA><NA><NA>YNNNNNNN20221130
4100하노이쌀국수음식점/유흥시설동남아시아음식베트남서울특별시중구순화동<NA>217 번지서소문로9길2837.563415126.9705944516서울특별시 중구 서소문로9길 28서울특별시 중구 순화동 21723184246월-금 10시-20시토-일 10시-20시NNNNNNNN20221130
51010아프리카유나이티드레스토랑음식점/유흥시설아프리카음식아프리카서울특별시용산구이태원동<NA>118-34 번지이태원로16637.534206126.9924054391서울특별시 용산구 이태원로 166서울특별시 용산구 이태원동 118-347089554851월-금 0시-24시토-일 0시-24시NNNNNNNN20221130
61011다이닝키친음식점/유흥시설유럽음식이탈리아광주광역시남구봉선동<NA>1011-20 번지봉선1로36번길135.127536126.9093361695광주광역시 남구 봉선1로36번길 1광주광역시 남구 봉선동 1011-2050713271015월-금 12시-22시토 12시-14시30분NNNNNNNN20221130
7ZAMZAM음식점/유흥시설동남아시아음식기타경기도화성시향남읍평리30-23 번지3.1만세로113037.133881126.91037118593경기도 화성시 3.1만세로 1130경기도 화성시 향남읍 평리 30-23<NA><NA><NA>NNNNNNNN20221010
8123포음식점/유흥시설동남아시아음식베트남경기도파주시문발동<NA>644 번지문발로28437.71809126.69253910881경기도 파주시 문발로 284경기도 파주시 문발동 644<NA><NA><NA>YNNNNNNN20221130
9126음식점/유흥시설동남아시아음식기타서울특별시광진구구의동<NA>671 번지광나루로39길1137.545494127.0887784977서울특별시 광진구 광나루로39길 11서울특별시 광진구 구의동 67150713074825화-금 11시-22시토 11시-22시,일 11시-15시YNNNNNNN20221130
fclty_nmctgry_one_nmctgry_two_nmctgry_three_nmctprvn_nmsigngu_nmlegaldong_nmli_nmlnbr_noroad_nmbuld_nolc_lalc_lozip_nordnmadr_nmlnm_addrtel_noworkday_oper_time_dcwkend_oper_time_dcfre_parkng_atvalet_parkng_posbl_atinfn_chair_lend_posbl_atwchair_hold_atpet_posbl_atvgtr_menu_hold_athalal_food_hold_atgfre_food_hold_atlast_updt_de
90감바레우쿠짱음식점/유흥시설동아시아음식일본서울특별시서초구방배동<NA>925-22 번지효령로31길8637.484815126.994716682서울특별시 서초구 효령로31길 86서울특별시 서초구 방배동 925-2250714121518월-금 11시30분-20시30분토-일 11시30분-15시30분YNNNNNNN20221130
91감베로니음식점/유흥시설유럽음식이탈리아서울특별시용산구갈월동<NA>89-22 번지한강대로81길537.543012126.9719364321서울특별시 용산구 한강대로81길 5서울특별시 용산구 갈월동 89-22232731791월-금 11시-21시토 11시-19시NNNNNNNN20221130
92감성타코 가로수길점음식점/유흥시설남미음식멕시코서울특별시강남구신사동<NA>542-6 번지가로수길2637.519652127.0233046036서울특별시 강남구 가로수길 26서울특별시 강남구 신사동 542-625168884월-금 12시-22시토-일 12시-22시NNNNNNNN20221130
93감성타코 건대점음식점/유흥시설남미음식멕시코서울특별시광진구화양동<NA>10-1 번지능동로13길3937.543431127.070185016서울특별시 광진구 능동로13길 39서울특별시 광진구 화양동 10-124628883월-금 12시-22시토-일 12시-22시YNNNNNNN20221130
94감성타코 광화문점음식점/유흥시설남미음식멕시코서울특별시종로구내수동<NA>73 번지새문안로3길2337.572859126.9724593174서울특별시 종로구 새문안로3길 23서울특별시 종로구 내수동 7327388887월-금 11시30분-22시토-일 12시-22시YNNNNNNN20221130
95감성타코 신사점음식점/유흥시설남미음식멕시코서울특별시강남구신사동<NA>523-16 번지강남대로162길3137.520641127.0209556028서울특별시 강남구 강남대로162길 31서울특별시 강남구 신사동 523-1625473366월-금 11시30분-22시토-일 12시-22시YNNNNNNN20221130
96감성타코 판교점음식점/유흥시설남미음식멕시코경기도성남시 분당구삼평동<NA>740 번지동판교로177번길2537.397326127.11356813525경기도 성남시 분당구 동판교로177번길 25경기도 성남시 분당구 삼평동 740317818885월-금 11시30분-22시토-일 11시30분-22시YNNNNNNN20221130
97감성타코 합정점음식점/유흥시설남미음식멕시코서울특별시마포구합정동<NA>473 번지월드컵로3길1437.551119126.91224024서울특별시 마포구 월드컵로3길 14서울특별시 마포구 합정동 47323328836월-금 11시30분-22시토-일 12시-22시YNNNNNNN20221130
98감성타코 홍대점음식점/유흥시설남미음식멕시코서울특별시마포구서교동<NA>358-121 번지와우산로21길20-1137.552811126.9227244040서울특별시 마포구 와우산로21길 20-11서울특별시 마포구 서교동 358-12123378883월-금 11시30분-22시토-일 12시-22시NNNNNNNN20221130
99갓덴스시음식점/유흥시설동아시아음식일본 아시아서울특별시강남구역삼동<NA>822-4 번지테헤란로10937.498825127.0289926134서울특별시 강남구 테헤란로 109서울특별시 강남구 역삼동 822-4 강남제일빌딩220511477월-금 11시-21시30분토-일 11시-21시30분YNNNNNNN20221130