Overview

Dataset statistics

Number of variables37
Number of observations2321
Missing cells5851
Missing cells (%)6.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory677.8 KiB
Average record size in memory299.1 B

Variable types

Text13
Categorical8
Numeric2
Boolean14

Dataset

Description경기도 포천시에서 제공하는 민간/공공시설(음식점, 카페 등)의 사회적약자(장애인 등)를 위한 편의정보 데이터 입니다.
Author경기도 포천시
URLhttps://www.data.go.kr/data/15109536/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
데이터기준일 has constant value ""Constant
영업상태 has constant value ""Constant
장애인용욕실_샤워_탈의실 has constant value ""Constant
객실_침대 has constant value ""Constant
업종분류 is highly imbalanced (63.6%)Imbalance
휴무일 is highly imbalanced (53.7%)Imbalance
반려동물출입 is highly imbalanced (90.9%)Imbalance
장애인전용주차구역 is highly imbalanced (63.6%)Imbalance
주차구역위치 is highly imbalanced (73.0%)Imbalance
장애인용승강기_계단 is highly imbalanced (68.5%)Imbalance
장애인용화장실 is highly imbalanced (74.6%)Imbalance
화장실위치 is highly imbalanced (85.2%)Imbalance
점자블록 is highly imbalanced (59.3%)Imbalance
유도및안내설비 is highly imbalanced (92.3%)Imbalance
경보및피난설비 is highly imbalanced (59.7%)Imbalance
관람석_열람석 is highly imbalanced (99.0%)Imbalance
접수대_작업대 is highly imbalanced (99.5%)Imbalance
매표소_판매기_음료대 is highly imbalanced (98.6%)Imbalance
임산부등을위한휴게실 is highly imbalanced (99.0%)Imbalance
전화번호 has 253 (10.9%) missing valuesMissing
영업시간 has 643 (27.7%) missing valuesMissing
홈페이지 has 1855 (79.9%) missing valuesMissing
메뉴정보 has 518 (22.3%) missing valuesMissing
이용요금 has 2282 (98.3%) missing valuesMissing
한줄소개 has 123 (5.3%) missing valuesMissing
키워드 has 176 (7.6%) missing valuesMissing
관리번호 has unique valuesUnique
편의시설사진정보 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:49:04.285748
Analysis finished2023-12-12 11:49:07.157625
Duration2.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct2321
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
2023-12-12T20:49:07.460265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters18568
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

Unique2321 ?
Unique (%)100.0%

Sample

1st row01-00001
2nd row01-00002
3rd row01-00003
4th row01-00004
5th row01-00005
ValueCountFrequency (%)
01-00001 1
 
< 0.1%
01-01524 1
 
< 0.1%
01-01551 1
 
< 0.1%
01-01545 1
 
< 0.1%
01-01546 1
 
< 0.1%
01-01547 1
 
< 0.1%
01-01548 1
 
< 0.1%
01-01549 1
 
< 0.1%
01-01550 1
 
< 0.1%
01-01552 1
 
< 0.1%
Other values (2311) 2311
99.6%
2023-12-12T20:49:08.018472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6832
36.8%
1 3727
20.1%
- 2321
 
12.5%
2 1009
 
5.4%
4 748
 
4.0%
3 677
 
3.6%
5 673
 
3.6%
6 670
 
3.6%
7 654
 
3.5%
8 640
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16247
87.5%
Dash Punctuation 2321
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6832
42.1%
1 3727
22.9%
2 1009
 
6.2%
4 748
 
4.6%
3 677
 
4.2%
5 673
 
4.1%
6 670
 
4.1%
7 654
 
4.0%
8 640
 
3.9%
9 617
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 2321
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18568
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6832
36.8%
1 3727
20.1%
- 2321
 
12.5%
2 1009
 
5.4%
4 748
 
4.0%
3 677
 
3.6%
5 673
 
3.6%
6 670
 
3.6%
7 654
 
3.5%
8 640
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6832
36.8%
1 3727
20.1%
- 2321
 
12.5%
2 1009
 
5.4%
4 748
 
4.0%
3 677
 
3.6%
5 673
 
3.6%
6 670
 
3.6%
7 654
 
3.5%
8 640
 
3.4%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
경기도
2321 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 2321
100.0%

Length

2023-12-12T20:49:08.190555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:49:08.343848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 2321
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
포천시
2321 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
포천시 2321
100.0%

Length

2023-12-12T20:49:08.481906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:49:08.593959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
포천시 2321
100.0%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
2022-12-09
2321 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-09
2nd row2022-12-09
3rd row2022-12-09
4th row2022-12-09
5th row2022-12-09

Common Values

ValueCountFrequency (%)
2022-12-09 2321
100.0%

Length

2023-12-12T20:49:08.720440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:49:08.828902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-09 2321
100.0%

위도
Real number (ℝ)

Distinct2271
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.895476
Minimum37.756589
Maximum38.159061
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2023-12-12T20:49:09.016722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.756589
5-th percentile37.777611
Q137.828453
median37.885176
Q337.953085
95-th percentile38.090182
Maximum38.159061
Range0.40247242
Interquartile range (IQR)0.12463225

Descriptive statistics

Standard deviation0.092068714
Coefficient of variation (CV)0.0024295437
Kurtosis0.018069981
Mean37.895476
Median Absolute Deviation (MAD)0.05726482
Skewness0.89678334
Sum87955.4
Variance0.0084766481
MonotonicityNot monotonic
2023-12-12T20:49:09.224313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.88368634 3
 
0.1%
38.08029201 2
 
0.1%
37.82998276 2
 
0.1%
37.82995987 2
 
0.1%
37.95604215 2
 
0.1%
37.8288765 2
 
0.1%
37.77120973 2
 
0.1%
38.0753181 2
 
0.1%
37.82967117 2
 
0.1%
37.81447293 2
 
0.1%
Other values (2261) 2300
99.1%
ValueCountFrequency (%)
37.75658902 1
< 0.1%
37.75727763 1
< 0.1%
37.75861651 1
< 0.1%
37.75865387 1
< 0.1%
37.75876157 1
< 0.1%
37.75911838 1
< 0.1%
37.75979123 1
< 0.1%
37.75983915 1
< 0.1%
37.75995565 1
< 0.1%
37.76029414 1
< 0.1%
ValueCountFrequency (%)
38.15906144 1
< 0.1%
38.15884549 1
< 0.1%
38.15884399 1
< 0.1%
38.15876156 1
< 0.1%
38.15860175 1
< 0.1%
38.15844015 1
< 0.1%
38.1583805 1
< 0.1%
38.15831699 1
< 0.1%
38.15828876 1
< 0.1%
38.15824144 1
< 0.1%

경도
Real number (ℝ)

Distinct2262
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.20765
Minimum127.09924
Maximum127.42103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2023-12-12T20:49:09.396506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.09924
5-th percentile127.13666
Q1127.15077
median127.19823
Q3127.24259
95-th percentile127.32763
Maximum127.42103
Range0.3217854
Interquartile range (IQR)0.0918167

Descriptive statistics

Standard deviation0.065703091
Coefficient of variation (CV)0.00051650268
Kurtosis0.19684511
Mean127.20765
Median Absolute Deviation (MAD)0.0464487
Skewness0.96880948
Sum295248.95
Variance0.0043168962
MonotonicityNot monotonic
2023-12-12T20:49:09.616031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.2021728 3
 
0.1%
127.2007446 2
 
0.1%
127.2025909 2
 
0.1%
127.1633238 2
 
0.1%
127.1638887 2
 
0.1%
127.1436462 2
 
0.1%
127.1470498 2
 
0.1%
127.1660309 2
 
0.1%
127.2007828 2
 
0.1%
127.2025299 2
 
0.1%
Other values (2252) 2300
99.1%
ValueCountFrequency (%)
127.099245 1
< 0.1%
127.1013904 1
< 0.1%
127.1025396 1
< 0.1%
127.1042856 1
< 0.1%
127.1046157 1
< 0.1%
127.1071574 1
< 0.1%
127.113362 1
< 0.1%
127.1141412 1
< 0.1%
127.1152982 1
< 0.1%
127.1154098 1
< 0.1%
ValueCountFrequency (%)
127.4210304 1
< 0.1%
127.4206615 1
< 0.1%
127.4200568 1
< 0.1%
127.4199923 2
0.1%
127.4189711 1
< 0.1%
127.416518 2
0.1%
127.414001 1
< 0.1%
127.4136025 1
< 0.1%
127.4118967 1
< 0.1%
127.4088367 1
< 0.1%

업체명
Text

Distinct2266
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
2023-12-12T20:49:10.044252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length6.1684619
Min length1

Characters and Unicode

Total characters14317
Distinct characters752
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2219 ?
Unique (%)95.6%

Sample

1st row춘하추동
2nd row삼거리식당
3rd row풍미식당
4th row천호식당
5th row우리집한식뷔페
ValueCountFrequency (%)
송우점 36
 
1.3%
포천점 36
 
1.3%
포천송우점 29
 
1.0%
포천송우리점 21
 
0.7%
포천신읍점 20
 
0.7%
본점 14
 
0.5%
포천일동점 13
 
0.5%
송우리점 11
 
0.4%
포천시청점 10
 
0.4%
대진대점 8
 
0.3%
Other values (2403) 2644
93.0%
2023-12-12T20:49:10.666120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
552
 
3.9%
점 361
 
2.5%
천 291
 
2.0%
이 284
 
2.0%
리 265
 
1.9%
포 255
 
1.8%
식 216
 
1.5%
우 197
 
1.4%
국 197
 
1.4%
가 194
 
1.4%
Other values (742) 11505
80.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13118
91.6%
Space Separator 552
 
3.9%
Uppercase Letter 202
 
1.4%
Lowercase Letter 168
 
1.2%
Decimal Number 139
 
1.0%
Close Punctuation 48
 
0.3%
Open Punctuation 48
 
0.3%
Other Punctuation 40
 
0.3%
Dash Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 361
 
2.8%
천 291
 
2.2%
이 284
 
2.2%
리 265
 
2.0%
포 255
 
1.9%
식 216
 
1.6%
우 197
 
1.5%
국 197
 
1.5%
가 194
 
1.5%
당 177
 
1.3%
Other values (673) 10681
81.4%
Uppercase Letter
ValueCountFrequency (%)
A 25
12.4%
C 19
 
9.4%
E 16
 
7.9%
B 15
 
7.4%
T 13
 
6.4%
N 12
 
5.9%
O 12
 
5.9%
H 11
 
5.4%
F 10
 
5.0%
G 9
 
4.5%
Other values (14) 60
29.7%
Lowercase Letter
ValueCountFrequency (%)
e 31
18.5%
a 18
10.7%
o 17
10.1%
f 16
9.5%
c 14
 
8.3%
p 8
 
4.8%
m 8
 
4.8%
s 8
 
4.8%
i 6
 
3.6%
r 6
 
3.6%
Other values (13) 36
21.4%
Decimal Number
ValueCountFrequency (%)
1 24
17.3%
9 22
15.8%
3 15
10.8%
5 15
10.8%
0 15
10.8%
2 14
10.1%
8 12
8.6%
7 8
 
5.8%
4 7
 
5.0%
6 7
 
5.0%
Other Punctuation
ValueCountFrequency (%)
& 16
40.0%
! 7
17.5%
. 7
17.5%
, 5
 
12.5%
· 3
 
7.5%
/ 1
 
2.5%
# 1
 
2.5%
Space Separator
ValueCountFrequency (%)
552
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13109
91.6%
Common 829
 
5.8%
Latin 370
 
2.6%
Han 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 361
 
2.8%
천 291
 
2.2%
이 284
 
2.2%
리 265
 
2.0%
포 255
 
1.9%
식 216
 
1.6%
우 197
 
1.5%
국 197
 
1.5%
가 194
 
1.5%
당 177
 
1.4%
Other values (664) 10672
81.4%
Latin
ValueCountFrequency (%)
e 31
 
8.4%
A 25
 
6.8%
C 19
 
5.1%
a 18
 
4.9%
o 17
 
4.6%
E 16
 
4.3%
f 16
 
4.3%
B 15
 
4.1%
c 14
 
3.8%
T 13
 
3.5%
Other values (37) 186
50.3%
Common
ValueCountFrequency (%)
552
66.6%
) 48
 
5.8%
( 48
 
5.8%
1 24
 
2.9%
9 22
 
2.7%
& 16
 
1.9%
3 15
 
1.8%
5 15
 
1.8%
0 15
 
1.8%
2 14
 
1.7%
Other values (12) 60
 
7.2%
Han
ValueCountFrequency (%)
閣 1
11.1%
田 1
11.1%
秋 1
11.1%
家 1
11.1%
世 1
11.1%
牛 1
11.1%
魚 1
11.1%
靑 1
11.1%
和 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13108
91.6%
ASCII 1196
 
8.4%
CJK 9
 
0.1%
None 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
552
46.2%
) 48
 
4.0%
( 48
 
4.0%
e 31
 
2.6%
A 25
 
2.1%
1 24
 
2.0%
9 22
 
1.8%
C 19
 
1.6%
a 18
 
1.5%
o 17
 
1.4%
Other values (58) 392
32.8%
Hangul
ValueCountFrequency (%)
점 361
 
2.8%
천 291
 
2.2%
이 284
 
2.2%
리 265
 
2.0%
포 255
 
1.9%
식 216
 
1.6%
우 197
 
1.5%
국 197
 
1.5%
가 194
 
1.5%
당 177
 
1.4%
Other values (663) 10671
81.4%
None
ValueCountFrequency (%)
· 3
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%
CJK
ValueCountFrequency (%)
閣 1
11.1%
田 1
11.1%
秋 1
11.1%
家 1
11.1%
世 1
11.1%
牛 1
11.1%
魚 1
11.1%
靑 1
11.1%
和 1
11.1%

업종분류
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
1
1976 
2
267 
4
 
75
3
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 1976
85.1%
2 267
 
11.5%
4 75
 
3.2%
3 3
 
0.1%

Length

2023-12-12T20:49:10.828030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:49:10.948415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1976
85.1%
2 267
 
11.5%
4 75
 
3.2%
3 3
 
0.1%

소재지 지번주소
Text

Distinct1923
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
2023-12-12T20:49:11.347069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length19.967255
Min length13

Characters and Unicode

Total characters46344
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

Unique1670 ?
Unique (%)72.0%

Sample

1st row경기도 포천시 내촌면 내리 521-5
2nd row경기도 포천시 내촌면 내리 479-1
3rd row경기도 포천시 내촌면 내리 465-18
4th row경기도 포천시 신북면 가채리 185
5th row경기도 포천시 내촌면 신팔리 374-8
ValueCountFrequency (%)
경기도 2321
21.0%
포천시 2321
21.0%
소흘읍 700
 
6.3%
송우리 442
 
4.0%
신읍동 366
 
3.3%
영북면 177
 
1.6%
일동면 165
 
1.5%
신북면 132
 
1.2%
선단동 131
 
1.2%
가산면 116
 
1.0%
Other values (1896) 4182
37.8%
2023-12-12T20:49:12.047056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8732
18.8%
기 2467
 
5.3%
천 2427
 
5.2%
도 2359
 
5.1%
경 2321
 
5.0%
포 2321
 
5.0%
시 2321
 
5.0%
- 2051
 
4.4%
1 1779
 
3.8%
리 1764
 
3.8%
Other values (106) 17802
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26271
56.7%
Decimal Number 9290
 
20.0%
Space Separator 8732
 
18.8%
Dash Punctuation 2051
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 2467
 
9.4%
천 2427
 
9.2%
도 2359
 
9.0%
경 2321
 
8.8%
포 2321
 
8.8%
시 2321
 
8.8%
리 1764
 
6.7%
읍 1116
 
4.2%
면 1064
 
4.1%
동 1047
 
4.0%
Other values (94) 7064
26.9%
Decimal Number
ValueCountFrequency (%)
1 1779
19.1%
2 1208
13.0%
3 961
10.3%
4 959
10.3%
5 909
9.8%
7 836
9.0%
6 831
8.9%
9 630
 
6.8%
0 613
 
6.6%
8 564
 
6.1%
Space Separator
ValueCountFrequency (%)
8732
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2051
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26271
56.7%
Common 20073
43.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 2467
 
9.4%
천 2427
 
9.2%
도 2359
 
9.0%
경 2321
 
8.8%
포 2321
 
8.8%
시 2321
 
8.8%
리 1764
 
6.7%
읍 1116
 
4.2%
면 1064
 
4.1%
동 1047
 
4.0%
Other values (94) 7064
26.9%
Common
ValueCountFrequency (%)
8732
43.5%
- 2051
 
10.2%
1 1779
 
8.9%
2 1208
 
6.0%
3 961
 
4.8%
4 959
 
4.8%
5 909
 
4.5%
7 836
 
4.2%
6 831
 
4.1%
9 630
 
3.1%
Other values (2) 1177
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26271
56.7%
ASCII 20073
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8732
43.5%
- 2051
 
10.2%
1 1779
 
8.9%
2 1208
 
6.0%
3 961
 
4.8%
4 959
 
4.8%
5 909
 
4.5%
7 836
 
4.2%
6 831
 
4.1%
9 630
 
3.1%
Other values (2) 1177
 
5.9%
Hangul
ValueCountFrequency (%)
기 2467
 
9.4%
천 2427
 
9.2%
도 2359
 
9.0%
경 2321
 
8.8%
포 2321
 
8.8%
시 2321
 
8.8%
리 1764
 
6.7%
읍 1116
 
4.2%
면 1064
 
4.1%
동 1047
 
4.0%
Other values (94) 7064
26.9%

소재지 도로명주소
Text

Distinct1927
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
2023-12-12T20:49:12.453562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length30
Mean length19.605343
Min length13

Characters and Unicode

Total characters45504
Distinct characters172
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

Unique1675 ?
Unique (%)72.2%

Sample

1st row경기도 포천시 내촌면 내촌로 71
2nd row경기도 포천시 내촌면 내촌로 63
3rd row경기도 포천시 내촌면 포천로 8-1
4th row경기도 포천시 신북면 중앙로 336
5th row경기도 포천시 내촌면 금강로 2999
ValueCountFrequency (%)
포천시 2322
20.9%
경기도 2321
20.9%
소흘읍 700
 
6.3%
호국로 233
 
2.1%
영북면 177
 
1.6%
일동면 165
 
1.5%
신북면 132
 
1.2%
화동로 126
 
1.1%
가산면 116
 
1.0%
내촌면 113
 
1.0%
Other values (1443) 4705
42.3%
2023-12-12T20:49:12.913169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8789
19.3%
천 2516
 
5.5%
포 2470
 
5.4%
기 2338
 
5.1%
경 2329
 
5.1%
시 2326
 
5.1%
도 2321
 
5.1%
로 2143
 
4.7%
1 1908
 
4.2%
면 1064
 
2.3%
Other values (162) 17300
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28160
61.9%
Space Separator 8789
 
19.3%
Decimal Number 8088
 
17.8%
Dash Punctuation 467
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 2516
 
8.9%
포 2470
 
8.8%
기 2338
 
8.3%
경 2329
 
8.3%
시 2326
 
8.3%
도 2321
 
8.2%
로 2143
 
7.6%
면 1064
 
3.8%
읍 722
 
2.6%
소 712
 
2.5%
Other values (150) 9219
32.7%
Decimal Number
ValueCountFrequency (%)
1 1908
23.6%
2 1019
12.6%
3 822
10.2%
5 723
 
8.9%
4 634
 
7.8%
0 628
 
7.8%
6 625
 
7.7%
9 606
 
7.5%
7 573
 
7.1%
8 550
 
6.8%
Space Separator
ValueCountFrequency (%)
8789
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 467
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28160
61.9%
Common 17344
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 2516
 
8.9%
포 2470
 
8.8%
기 2338
 
8.3%
경 2329
 
8.3%
시 2326
 
8.3%
도 2321
 
8.2%
로 2143
 
7.6%
면 1064
 
3.8%
읍 722
 
2.6%
소 712
 
2.5%
Other values (150) 9219
32.7%
Common
ValueCountFrequency (%)
8789
50.7%
1 1908
 
11.0%
2 1019
 
5.9%
3 822
 
4.7%
5 723
 
4.2%
4 634
 
3.7%
0 628
 
3.6%
6 625
 
3.6%
9 606
 
3.5%
7 573
 
3.3%
Other values (2) 1017
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28160
61.9%
ASCII 17344
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8789
50.7%
1 1908
 
11.0%
2 1019
 
5.9%
3 822
 
4.7%
5 723
 
4.2%
4 634
 
3.7%
0 628
 
3.6%
6 625
 
3.6%
9 606
 
3.5%
7 573
 
3.3%
Other values (2) 1017
 
5.9%
Hangul
ValueCountFrequency (%)
천 2516
 
8.9%
포 2470
 
8.8%
기 2338
 
8.3%
경 2329
 
8.3%
시 2326
 
8.3%
도 2321
 
8.2%
로 2143
 
7.6%
면 1064
 
3.8%
읍 722
 
2.6%
소 712
 
2.5%
Other values (150) 9219
32.7%

전화번호
Text

MISSING 

Distinct2064
Distinct (%)99.8%
Missing253
Missing (%)10.9%
Memory size18.3 KiB
2023-12-12T20:49:13.211519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.079304
Min length9

Characters and Unicode

Total characters24980
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

Unique2060 ?
Unique (%)99.6%

Sample

1st row031-532-2610
2nd row031-532-2966
3rd row031-534-7668
4th row031-535-6908
5th row031-544-0663
ValueCountFrequency (%)
031-531-7970 2
 
0.1%
031-535-1220 2
 
0.1%
031-543-7191 2
 
0.1%
031-541-9903 2
 
0.1%
031-532-4114 1
 
< 0.1%
031-543-9292 1
 
< 0.1%
031-544-6766 1
 
< 0.1%
031-543-0804 1
 
< 0.1%
031-544-3579 1
 
< 0.1%
031-536-8597 1
 
< 0.1%
Other values (2054) 2054
99.3%
2023-12-12T20:49:13.717278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 4459
17.9%
- 4133
16.5%
1 3210
12.9%
0 3156
12.6%
5 3152
12.6%
4 1844
7.4%
2 1354
 
5.4%
7 961
 
3.8%
9 934
 
3.7%
8 919
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20847
83.5%
Dash Punctuation 4133
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 4459
21.4%
1 3210
15.4%
0 3156
15.1%
5 3152
15.1%
4 1844
8.8%
2 1354
 
6.5%
7 961
 
4.6%
9 934
 
4.5%
8 919
 
4.4%
6 858
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 4133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24980
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 4459
17.9%
- 4133
16.5%
1 3210
12.9%
0 3156
12.6%
5 3152
12.6%
4 1844
7.4%
2 1354
 
5.4%
7 961
 
3.8%
9 934
 
3.7%
8 919
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24980
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 4459
17.9%
- 4133
16.5%
1 3210
12.9%
0 3156
12.6%
5 3152
12.6%
4 1844
7.4%
2 1354
 
5.4%
7 961
 
3.8%
9 934
 
3.7%
8 919
 
3.7%

영업시간
Text

MISSING 

Distinct387
Distinct (%)23.1%
Missing643
Missing (%)27.7%
Memory size18.3 KiB
2023-12-12T20:49:14.099038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length11
Mean length12.52205
Min length11

Characters and Unicode

Total characters21012
Distinct characters25
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

Unique250 ?
Unique (%)14.9%

Sample

1st row10:30~19:30
2nd row10:30~20:00
3rd row07:00~22:00
4th row10:00~18:30
5th row08:00~20:00
ValueCountFrequency (%)
11:00~21:00 118
 
6.4%
10:00~22:00 112
 
6.1%
10:00~21:00 100
 
5.4%
11:00~22:00 96
 
5.2%
11:00~20:00 60
 
3.3%
10:00~20:00 57
 
3.1%
09:00~21:00 56
 
3.0%
09:00~18:00 43
 
2.3%
11:00~21:30 28
 
1.5%
09:00~20:00 28
 
1.5%
Other values (394) 1140
62.0%
2023-12-12T20:49:14.623099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8324
39.6%
: 3676
17.5%
1 2657
 
12.6%
2 1872
 
8.9%
~ 1837
 
8.7%
3 664
 
3.2%
9 396
 
1.9%
8 208
 
1.0%
4 170
 
0.8%
161
 
0.8%
Other values (15) 1047
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14703
70.0%
Other Punctuation 3689
 
17.6%
Math Symbol 1998
 
9.5%
Other Letter 461
 
2.2%
Space Separator 161
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8324
56.6%
1 2657
 
18.1%
2 1872
 
12.7%
3 664
 
4.5%
9 396
 
2.7%
8 208
 
1.4%
4 170
 
1.2%
6 147
 
1.0%
5 136
 
0.9%
7 129
 
0.9%
Other Letter
ValueCountFrequency (%)
일 148
32.1%
요 115
24.9%
주 58
 
12.6%
말 58
 
12.6%
토 51
 
11.1%
금 12
 
2.6%
화 7
 
1.5%
월 4
 
0.9%
수 4
 
0.9%
목 4
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 3676
99.6%
/ 13
 
0.4%
Math Symbol
ValueCountFrequency (%)
~ 1837
91.9%
+ 161
 
8.1%
Space Separator
ValueCountFrequency (%)
161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20551
97.8%
Hangul 461
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8324
40.5%
: 3676
17.9%
1 2657
 
12.9%
2 1872
 
9.1%
~ 1837
 
8.9%
3 664
 
3.2%
9 396
 
1.9%
8 208
 
1.0%
4 170
 
0.8%
161
 
0.8%
Other values (5) 586
 
2.9%
Hangul
ValueCountFrequency (%)
일 148
32.1%
요 115
24.9%
주 58
 
12.6%
말 58
 
12.6%
토 51
 
11.1%
금 12
 
2.6%
화 7
 
1.5%
월 4
 
0.9%
수 4
 
0.9%
목 4
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20551
97.8%
Hangul 461
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8324
40.5%
: 3676
17.9%
1 2657
 
12.9%
2 1872
 
9.1%
~ 1837
 
8.9%
3 664
 
3.2%
9 396
 
1.9%
8 208
 
1.0%
4 170
 
0.8%
161
 
0.8%
Other values (5) 586
 
2.9%
Hangul
ValueCountFrequency (%)
일 148
32.1%
요 115
24.9%
주 58
 
12.6%
말 58
 
12.6%
토 51
 
11.1%
금 12
 
2.6%
화 7
 
1.5%
월 4
 
0.9%
수 4
 
0.9%
목 4
 
0.9%

휴무일
Categorical

IMBALANCE 

Distinct48
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
<NA>
930 
연중무휴
610 
일요일
331 
월요일
152 
화요일
 
79
Other values (43)
219 

Length

Max length19
Median length4
Mean length4.0379147
Min length2

Unique

Unique20 ?
Unique (%)0.9%

Sample

1st row연중무휴
2nd row<NA>
3rd row두번째주/네번째주 일요일
4th row<NA>
5th row주말

Common Values

ValueCountFrequency (%)
<NA> 930
40.1%
연중무휴 610
26.3%
일요일 331
 
14.3%
월요일 152
 
6.5%
화요일 79
 
3.4%
수요일 46
 
2.0%
주말 27
 
1.2%
목요일 24
 
1.0%
토요일 13
 
0.6%
두번째주/네번째주 일요일 13
 
0.6%
Other values (38) 96
 
4.1%

Length

2023-12-12T20:49:14.839004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 930
38.6%
연중무휴 613
25.4%
일요일 367
 
15.2%
월요일 176
 
7.3%
화요일 93
 
3.9%
수요일 51
 
2.1%
두번째주/네번째주 44
 
1.8%
주말 28
 
1.2%
목요일 24
 
1.0%
토요일 21
 
0.9%
Other values (18) 63
 
2.6%

홈페이지
Text

MISSING 

Distinct420
Distinct (%)90.1%
Missing1855
Missing (%)79.9%
Memory size18.3 KiB
2023-12-12T20:49:15.186940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length123
Median length59
Mean length29.349785
Min length15

Characters and Unicode

Total characters13677
Distinct characters175
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique388 ?
Unique (%)83.3%

Sample

1st rowhttp://www.원조파주골순두부.com/
2nd rowhttp://www.tudari.co.kr/
3rd rowhttp://spgarden.modoo.at/
4th rowhttps://blog.naver.com/olimpo_food
5th rowhttp://ok114.co.kr/0315335081
ValueCountFrequency (%)
https://www.ediya.com 7
 
1.5%
http://www.kimbab1009.com 4
 
0.9%
https://www.mega-mgccoffee.com 4
 
0.9%
http://www.ediya.com 4
 
0.9%
http://www.lahongbang.com 3
 
0.6%
https://www.isaac-toast.co.kr/main/main.html 3
 
0.6%
https://myungranghotdog.com 3
 
0.6%
http://www.toreore.com 3
 
0.6%
http://오구쌀피자.kr 3
 
0.6%
https://www.lotteria.com 2
 
0.4%
Other values (408) 431
92.3%
2023-12-12T20:49:15.732641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 1425
 
10.4%
t 1225
 
9.0%
. 982
 
7.2%
o 928
 
6.8%
w 739
 
5.4%
a 647
 
4.7%
h 633
 
4.6%
p 579
 
4.2%
m 570
 
4.2%
c 567
 
4.1%
Other values (165) 5382
39.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9776
71.5%
Other Punctuation 2932
 
21.4%
Decimal Number 569
 
4.2%
Other Letter 163
 
1.2%
Uppercase Letter 99
 
0.7%
Connector Punctuation 85
 
0.6%
Dash Punctuation 50
 
0.4%
Math Symbol 2
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 6
 
3.7%
피 5
 
3.1%
장 4
 
2.5%
명 4
 
2.5%
대 4
 
2.5%
오 3
 
1.8%
순 3
 
1.8%
쌀 3
 
1.8%
구 3
 
1.8%
집 3
 
1.8%
Other values (97) 125
76.7%
Lowercase Letter
ValueCountFrequency (%)
t 1225
12.5%
o 928
 
9.5%
w 739
 
7.6%
a 647
 
6.6%
h 633
 
6.5%
p 579
 
5.9%
m 570
 
5.8%
c 567
 
5.8%
s 459
 
4.7%
n 446
 
4.6%
Other values (16) 2983
30.5%
Uppercase Letter
ValueCountFrequency (%)
E 16
16.2%
B 16
16.2%
C 14
14.1%
M 8
8.1%
A 7
 
7.1%
T 5
 
5.1%
Y 5
 
5.1%
W 4
 
4.0%
L 3
 
3.0%
S 3
 
3.0%
Other values (11) 18
18.2%
Decimal Number
ValueCountFrequency (%)
1 107
18.8%
0 83
14.6%
3 61
10.7%
4 54
9.5%
5 52
9.1%
2 52
9.1%
9 50
8.8%
8 43
7.6%
7 39
 
6.9%
6 28
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/ 1425
48.6%
. 982
33.5%
: 466
 
15.9%
% 36
 
1.2%
? 15
 
0.5%
& 7
 
0.2%
@ 1
 
< 0.1%
Connector Punctuation
ValueCountFrequency (%)
_ 85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%
Math Symbol
ValueCountFrequency (%)
= 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9875
72.2%
Common 3639
 
26.6%
Hangul 163
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 6
 
3.7%
피 5
 
3.1%
장 4
 
2.5%
명 4
 
2.5%
대 4
 
2.5%
오 3
 
1.8%
순 3
 
1.8%
쌀 3
 
1.8%
구 3
 
1.8%
집 3
 
1.8%
Other values (97) 125
76.7%
Latin
ValueCountFrequency (%)
t 1225
 
12.4%
o 928
 
9.4%
w 739
 
7.5%
a 647
 
6.6%
h 633
 
6.4%
p 579
 
5.9%
m 570
 
5.8%
c 567
 
5.7%
s 459
 
4.6%
n 446
 
4.5%
Other values (37) 3082
31.2%
Common
ValueCountFrequency (%)
/ 1425
39.2%
. 982
27.0%
: 466
 
12.8%
1 107
 
2.9%
_ 85
 
2.3%
0 83
 
2.3%
3 61
 
1.7%
4 54
 
1.5%
5 52
 
1.4%
2 52
 
1.4%
Other values (11) 272
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13514
98.8%
Hangul 163
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 1425
 
10.5%
t 1225
 
9.1%
. 982
 
7.3%
o 928
 
6.9%
w 739
 
5.5%
a 647
 
4.8%
h 633
 
4.7%
p 579
 
4.3%
m 570
 
4.2%
c 567
 
4.2%
Other values (58) 5219
38.6%
Hangul
ValueCountFrequency (%)
자 6
 
3.7%
피 5
 
3.1%
장 4
 
2.5%
명 4
 
2.5%
대 4
 
2.5%
오 3
 
1.8%
순 3
 
1.8%
쌀 3
 
1.8%
구 3
 
1.8%
집 3
 
1.8%
Other values (97) 125
76.7%

메뉴정보
Text

MISSING 

Distinct1774
Distinct (%)98.4%
Missing518
Missing (%)22.3%
Memory size18.3 KiB
2023-12-12T20:49:15.991787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length97
Median length57
Mean length32.51858
Min length2

Characters and Unicode

Total characters58631
Distinct characters627
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1752 ?
Unique (%)97.2%

Sample

1st row잔치국수:6000원+콩국수:8000원+비빔국수:7000원
2nd row비빔국수:8000원+칼국수:8000원+찐만두:12000원
3rd row제육정식+김치찌개+육개장+우렁된장
4th row두부김치:10000원+손만둣국:7000원
5th row옻닭:65000원+엄백숙:65000원+묵은지볶음탕:70000원+도리탕:65000원+능이백숙70000원
ValueCountFrequency (%)
백반:6000원 4
 
0.2%
한식뷔페:6000원 4
 
0.2%
가정식백반:6000원 3
 
0.2%
짜장면+짬뽕+탕수육 3
 
0.2%
백반 3
 
0.2%
삼겹살+닭도리탕+김치찌개 2
 
0.1%
물냉면:8000원+비빔냉면:8000원+회냉면:9000원 2
 
0.1%
파인트:8900원+쿼터:17000원+패밀리:24000원 2
 
0.1%
아메리카노:3000원+에스프레소:3000원+카페라떼:3500원 2
 
0.1%
짜장면:5000원+짬뽕:6000원+간짜장:6000원 2
 
0.1%
Other values (1764) 1776
98.5%
2023-12-12T20:49:16.472429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14457
24.7%
: 4816
 
8.2%
원 4751
 
8.1%
+ 3426
 
5.8%
1 1640
 
2.8%
5 1193
 
2.0%
3 870
 
1.5%
2 855
 
1.5%
8 778
 
1.3%
9 696
 
1.2%
Other values (617) 25149
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27695
47.2%
Decimal Number 22122
37.7%
Other Punctuation 4829
 
8.2%
Math Symbol 3429
 
5.8%
Open Punctuation 224
 
0.4%
Close Punctuation 224
 
0.4%
Lowercase Letter 54
 
0.1%
Uppercase Letter 48
 
0.1%
Dash Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 4751
 
17.2%
리 597
 
2.2%
이 575
 
2.1%
국 490
 
1.8%
카 490
 
1.8%
장 482
 
1.7%
치 473
 
1.7%
탕 438
 
1.6%
비 426
 
1.5%
라 402
 
1.5%
Other values (573) 18571
67.1%
Lowercase Letter
ValueCountFrequency (%)
g 24
44.4%
p 5
 
9.3%
l 4
 
7.4%
m 3
 
5.6%
k 3
 
5.6%
s 2
 
3.7%
t 2
 
3.7%
h 2
 
3.7%
o 2
 
3.7%
i 2
 
3.7%
Other values (5) 5
 
9.3%
Decimal Number
ValueCountFrequency (%)
0 14457
65.4%
1 1640
 
7.4%
5 1193
 
5.4%
3 870
 
3.9%
2 855
 
3.9%
8 778
 
3.5%
9 696
 
3.1%
4 617
 
2.8%
7 512
 
2.3%
6 504
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
L 15
31.2%
M 7
14.6%
A 6
 
12.5%
O 5
 
10.4%
T 4
 
8.3%
H 4
 
8.3%
B 3
 
6.2%
X 2
 
4.2%
S 1
 
2.1%
C 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
: 4816
99.7%
/ 7
 
0.1%
& 5
 
0.1%
. 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 3426
99.9%
~ 3
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 224
100.0%
Close Punctuation
ValueCountFrequency (%)
) 224
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30834
52.6%
Hangul 27695
47.2%
Latin 102
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 4751
 
17.2%
리 597
 
2.2%
이 575
 
2.1%
국 490
 
1.8%
카 490
 
1.8%
장 482
 
1.7%
치 473
 
1.7%
탕 438
 
1.6%
비 426
 
1.5%
라 402
 
1.5%
Other values (573) 18571
67.1%
Latin
ValueCountFrequency (%)
g 24
23.5%
L 15
14.7%
M 7
 
6.9%
A 6
 
5.9%
O 5
 
4.9%
p 5
 
4.9%
T 4
 
3.9%
l 4
 
3.9%
H 4
 
3.9%
m 3
 
2.9%
Other values (15) 25
24.5%
Common
ValueCountFrequency (%)
0 14457
46.9%
: 4816
 
15.6%
+ 3426
 
11.1%
1 1640
 
5.3%
5 1193
 
3.9%
3 870
 
2.8%
2 855
 
2.8%
8 778
 
2.5%
9 696
 
2.3%
4 617
 
2.0%
Other values (9) 1486
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30936
52.8%
Hangul 27695
47.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14457
46.7%
: 4816
 
15.6%
+ 3426
 
11.1%
1 1640
 
5.3%
5 1193
 
3.9%
3 870
 
2.8%
2 855
 
2.8%
8 778
 
2.5%
9 696
 
2.2%
4 617
 
2.0%
Other values (34) 1588
 
5.1%
Hangul
ValueCountFrequency (%)
원 4751
 
17.2%
리 597
 
2.2%
이 575
 
2.1%
국 490
 
1.8%
카 490
 
1.8%
장 482
 
1.7%
치 473
 
1.7%
탕 438
 
1.6%
비 426
 
1.5%
라 402
 
1.5%
Other values (573) 18571
67.1%

이용요금
Text

MISSING 

Distinct30
Distinct (%)76.9%
Missing2282
Missing (%)98.3%
Memory size18.3 KiB
2023-12-12T20:49:16.753964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length28
Mean length14.25641
Min length8

Characters and Unicode

Total characters556
Distinct characters87
Distinct categories7 ?
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 (%)66.7%

Sample

1st row한식뷔페:6000원
2nd row한식뷔페:6500원
3rd row1인:8000원
4th row한식뷔페:6000원
5th row뷔페:6000원
ValueCountFrequency (%)
한식뷔페:6000원 6
 
14.6%
한식뷔페:7000원 3
 
7.3%
한식부페:7000원 2
 
4.9%
한식뷔페:8000원 2
 
4.9%
성인:7000원 1
 
2.4%
한식뷔페:6600원 1
 
2.4%
성인:7000원+아동:5000원 1
 
2.4%
한식뷔페:9000원+소인:4000원 1
 
2.4%
1팩:3000원+김치류:7000원 1
 
2.4%
들밥뷔페:8000원 1
 
2.4%
Other values (22) 22
53.7%
2023-12-12T20:49:17.197620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 151
27.2%
: 52
 
9.4%
원 52
 
9.4%
한 24
 
4.3%
1 21
 
3.8%
페 20
 
3.6%
6 19
 
3.4%
식 18
 
3.2%
뷔 17
 
3.1%
+ 12
 
2.2%
Other values (77) 170
30.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 246
44.2%
Decimal Number 232
41.7%
Other Punctuation 58
 
10.4%
Math Symbol 12
 
2.2%
Open Punctuation 3
 
0.5%
Close Punctuation 3
 
0.5%
Space Separator 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 52
21.1%
한 24
 
9.8%
페 20
 
8.1%
식 18
 
7.3%
뷔 17
 
6.9%
인 11
 
4.5%
무 6
 
2.4%
리 6
 
2.4%
필 6
 
2.4%
장 4
 
1.6%
Other values (59) 82
33.3%
Decimal Number
ValueCountFrequency (%)
0 151
65.1%
1 21
 
9.1%
6 19
 
8.2%
7 9
 
3.9%
9 8
 
3.4%
5 8
 
3.4%
8 6
 
2.6%
3 4
 
1.7%
2 4
 
1.7%
4 2
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 52
89.7%
, 3
 
5.2%
/ 2
 
3.4%
& 1
 
1.7%
Math Symbol
ValueCountFrequency (%)
+ 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 310
55.8%
Hangul 246
44.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 52
21.1%
한 24
 
9.8%
페 20
 
8.1%
식 18
 
7.3%
뷔 17
 
6.9%
인 11
 
4.5%
무 6
 
2.4%
리 6
 
2.4%
필 6
 
2.4%
장 4
 
1.6%
Other values (59) 82
33.3%
Common
ValueCountFrequency (%)
0 151
48.7%
: 52
 
16.8%
1 21
 
6.8%
6 19
 
6.1%
+ 12
 
3.9%
7 9
 
2.9%
9 8
 
2.6%
5 8
 
2.6%
8 6
 
1.9%
3 4
 
1.3%
Other values (8) 20
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 310
55.8%
Hangul 246
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 151
48.7%
: 52
 
16.8%
1 21
 
6.8%
6 19
 
6.1%
+ 12
 
3.9%
7 9
 
2.9%
9 8
 
2.6%
5 8
 
2.6%
8 6
 
1.9%
3 4
 
1.3%
Other values (8) 20
 
6.5%
Hangul
ValueCountFrequency (%)
원 52
21.1%
한 24
 
9.8%
페 20
 
8.1%
식 18
 
7.3%
뷔 17
 
6.9%
인 11
 
4.5%
무 6
 
2.4%
리 6
 
2.4%
필 6
 
2.4%
장 4
 
1.6%
Other values (59) 82
33.3%

한줄소개
Text

MISSING 

Distinct2117
Distinct (%)96.3%
Missing123
Missing (%)5.3%
Memory size18.3 KiB
2023-12-12T20:49:17.569029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length50
Mean length16.187898
Min length2

Characters and Unicode

Total characters35581
Distinct characters843
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

Unique2075 ?
Unique (%)94.4%

Sample

1st row국물이 진한 포천 춘하추동입니다.
2nd row한식이 생각날때 가는집 삼거리 식당입니다
3rd row배고플때 생각나는 포천 풍미식당입니다.
4th row포천시 신북면 한식 맛집입니다.
5th row집밥이 생각나는 포천 우리집 한식뷔페 입니다.
ValueCountFrequency (%)
포천 376
 
5.4%
맛있는 256
 
3.7%
있는 183
 
2.6%
입니다 133
 
1.9%
음식점입니다 99
 
1.4%
수 68
 
1.0%
일품인 62
 
0.9%
좋은 62
 
0.9%
곳 48
 
0.7%
맛집 36
 
0.5%
Other values (3675) 5608
80.9%
2023-12-12T20:49:18.169060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4750
 
13.3%
다 2125
 
6.0%
니 2050
 
5.8%
입 1997
 
5.6%
. 670
 
1.9%
는 663
 
1.9%
이 598
 
1.7%
천 566
 
1.6%
포 548
 
1.5%
한 506
 
1.4%
Other values (833) 21108
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29788
83.7%
Space Separator 4750
 
13.3%
Other Punctuation 710
 
2.0%
Decimal Number 159
 
0.4%
Lowercase Letter 92
 
0.3%
Uppercase Letter 65
 
0.2%
Close Punctuation 6
 
< 0.1%
Open Punctuation 6
 
< 0.1%
Math Symbol 4
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 2125
 
7.1%
니 2050
 
6.9%
입 1997
 
6.7%
는 663
 
2.2%
이 598
 
2.0%
천 566
 
1.9%
포 548
 
1.8%
한 506
 
1.7%
있 488
 
1.6%
가 451
 
1.5%
Other values (770) 19796
66.5%
Uppercase Letter
ValueCountFrequency (%)
E 8
12.3%
A 7
10.8%
C 5
 
7.7%
P 5
 
7.7%
T 5
 
7.7%
F 4
 
6.2%
L 4
 
6.2%
B 4
 
6.2%
O 4
 
6.2%
D 3
 
4.6%
Other values (11) 16
24.6%
Lowercase Letter
ValueCountFrequency (%)
e 12
13.0%
c 10
 
10.9%
b 10
 
10.9%
s 6
 
6.5%
f 6
 
6.5%
a 6
 
6.5%
o 5
 
5.4%
q 4
 
4.3%
i 4
 
4.3%
m 4
 
4.3%
Other values (10) 25
27.2%
Decimal Number
ValueCountFrequency (%)
0 35
22.0%
1 29
18.2%
9 18
11.3%
5 16
10.1%
2 15
9.4%
4 12
 
7.5%
8 11
 
6.9%
6 8
 
5.0%
7 8
 
5.0%
3 7
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 670
94.4%
, 13
 
1.8%
! 11
 
1.5%
& 10
 
1.4%
: 3
 
0.4%
% 2
 
0.3%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
4750
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29787
83.7%
Common 5636
 
15.8%
Latin 157
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 2125
 
7.1%
니 2050
 
6.9%
입 1997
 
6.7%
는 663
 
2.2%
이 598
 
2.0%
천 566
 
1.9%
포 548
 
1.8%
한 506
 
1.7%
있 488
 
1.6%
가 451
 
1.5%
Other values (769) 19795
66.5%
Latin
ValueCountFrequency (%)
e 12
 
7.6%
c 10
 
6.4%
b 10
 
6.4%
E 8
 
5.1%
A 7
 
4.5%
s 6
 
3.8%
f 6
 
3.8%
a 6
 
3.8%
C 5
 
3.2%
P 5
 
3.2%
Other values (31) 82
52.2%
Common
ValueCountFrequency (%)
4750
84.3%
. 670
 
11.9%
0 35
 
0.6%
1 29
 
0.5%
9 18
 
0.3%
5 16
 
0.3%
2 15
 
0.3%
, 13
 
0.2%
4 12
 
0.2%
8 11
 
0.2%
Other values (12) 67
 
1.2%
Han
ValueCountFrequency (%)
世 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29787
83.7%
ASCII 5793
 
16.3%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4750
82.0%
. 670
 
11.6%
0 35
 
0.6%
1 29
 
0.5%
9 18
 
0.3%
5 16
 
0.3%
2 15
 
0.3%
, 13
 
0.2%
e 12
 
0.2%
4 12
 
0.2%
Other values (53) 223
 
3.8%
Hangul
ValueCountFrequency (%)
다 2125
 
7.1%
니 2050
 
6.9%
입 1997
 
6.7%
는 663
 
2.2%
이 598
 
2.0%
천 566
 
1.9%
포 548
 
1.8%
한 506
 
1.7%
있 488
 
1.6%
가 451
 
1.5%
Other values (769) 19795
66.5%
CJK
ValueCountFrequency (%)
世 1
100.0%

키워드
Text

MISSING 

Distinct1980
Distinct (%)92.3%
Missing176
Missing (%)7.6%
Memory size18.3 KiB
2023-12-12T20:49:18.480610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length15.38042
Min length7

Characters and Unicode

Total characters32991
Distinct characters670
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1882 ?
Unique (%)87.7%

Sample

1st row#잔치국수+#포천+#국수맛집
2nd row#한식+#집밥+#단체+#가성비
3rd row#국수+#포천+#내촌+#숨은맛집
4th row#포천시+#신북면+#한식맛집
5th row#포천+#뷔페+#한식+#집밥느낌
ValueCountFrequency (%)
카페+#아메리카노+#포천 8
 
0.4%
포천+#호국로+#카페 7
 
0.3%
포천+#중앙로+#치과 7
 
0.3%
포천+#호국로+#음식점 6
 
0.3%
포천+#카페+#아메리카노 6
 
0.3%
포천+#카페+#커피 6
 
0.3%
포천+#솔모루로+#치과 6
 
0.3%
포천+#솔모루로+#내과 5
 
0.2%
포천+#갈비+#맛집 5
 
0.2%
포천+#솔모루로+#한의원 5
 
0.2%
Other values (1972) 2086
97.2%
2023-12-12T20:49:18.929958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
# 7056
21.4%
+ 4913
 
14.9%
포 1512
 
4.6%
천 1500
 
4.5%
식 482
 
1.5%
국 438
 
1.3%
리 419
 
1.3%
로 379
 
1.1%
면 352
 
1.1%
집 331
 
1.0%
Other values (660) 15609
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20905
63.4%
Other Punctuation 7058
 
21.4%
Math Symbol 4913
 
14.9%
Decimal Number 60
 
0.2%
Lowercase Letter 31
 
0.1%
Uppercase Letter 22
 
0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 1512
 
7.2%
천 1500
 
7.2%
식 482
 
2.3%
국 438
 
2.1%
리 419
 
2.0%
로 379
 
1.8%
면 352
 
1.7%
집 331
 
1.6%
이 321
 
1.5%
카 303
 
1.4%
Other values (620) 14868
71.1%
Lowercase Letter
ValueCountFrequency (%)
c 7
22.6%
b 6
19.4%
e 3
9.7%
q 2
 
6.5%
v 2
 
6.5%
g 2
 
6.5%
p 2
 
6.5%
f 2
 
6.5%
n 1
 
3.2%
k 1
 
3.2%
Other values (3) 3
9.7%
Uppercase Letter
ValueCountFrequency (%)
B 5
22.7%
Q 2
 
9.1%
N 2
 
9.1%
E 2
 
9.1%
F 2
 
9.1%
O 2
 
9.1%
I 1
 
4.5%
C 1
 
4.5%
A 1
 
4.5%
J 1
 
4.5%
Other values (3) 3
13.6%
Decimal Number
ValueCountFrequency (%)
2 11
18.3%
0 10
16.7%
9 7
11.7%
1 6
10.0%
4 6
10.0%
5 6
10.0%
3 5
8.3%
6 4
 
6.7%
7 3
 
5.0%
8 2
 
3.3%
Other Punctuation
ValueCountFrequency (%)
# 7056
> 99.9%
& 2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 4913
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20905
63.4%
Common 12033
36.5%
Latin 53
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 1512
 
7.2%
천 1500
 
7.2%
식 482
 
2.3%
국 438
 
2.1%
리 419
 
2.0%
로 379
 
1.8%
면 352
 
1.7%
집 331
 
1.6%
이 321
 
1.5%
카 303
 
1.4%
Other values (620) 14868
71.1%
Latin
ValueCountFrequency (%)
c 7
 
13.2%
b 6
 
11.3%
B 5
 
9.4%
e 3
 
5.7%
Q 2
 
3.8%
q 2
 
3.8%
v 2
 
3.8%
g 2
 
3.8%
N 2
 
3.8%
E 2
 
3.8%
Other values (16) 20
37.7%
Common
ValueCountFrequency (%)
# 7056
58.6%
+ 4913
40.8%
2 11
 
0.1%
0 10
 
0.1%
9 7
 
0.1%
1 6
 
< 0.1%
4 6
 
< 0.1%
5 6
 
< 0.1%
3 5
 
< 0.1%
6 4
 
< 0.1%
Other values (4) 9
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20905
63.4%
ASCII 12086
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
# 7056
58.4%
+ 4913
40.7%
2 11
 
0.1%
0 10
 
0.1%
c 7
 
0.1%
9 7
 
0.1%
1 6
 
< 0.1%
4 6
 
< 0.1%
b 6
 
< 0.1%
5 6
 
< 0.1%
Other values (30) 58
 
0.5%
Hangul
ValueCountFrequency (%)
포 1512
 
7.2%
천 1500
 
7.2%
식 482
 
2.3%
국 438
 
2.1%
리 419
 
2.0%
로 379
 
1.8%
면 352
 
1.7%
집 331
 
1.6%
이 321
 
1.5%
카 303
 
1.4%
Other values (620) 14868
71.1%

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
영업
2321 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 2321
100.0%

Length

2023-12-12T20:49:19.391510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:49:19.475185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 2321
100.0%

반려동물출입
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2294 
True
 
27
ValueCountFrequency (%)
False 2294
98.8%
True 27
 
1.2%
2023-12-12T20:49:19.546989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

건물출입구접근로및높이차이제거
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
1614 
True
707 
ValueCountFrequency (%)
False 1614
69.5%
True 707
30.5%
2023-12-12T20:49:19.627534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

장애인전용주차구역
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2160 
True
 
161
ValueCountFrequency (%)
False 2160
93.1%
True 161
 
6.9%
2023-12-12T20:49:19.716461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

주차구역위치
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
<NA>
2160 
외부
 
106
내부
 
55

Length

Max length4
Median length4
Mean length3.8612667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2160
93.1%
외부 106
 
4.6%
내부 55
 
2.4%

Length

2023-12-12T20:49:19.857456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:49:19.961188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2160
93.1%
외부 106
 
4.6%
내부 55
 
2.4%

장애인용승강기_계단
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2189 
True
 
132
ValueCountFrequency (%)
False 2189
94.3%
True 132
 
5.7%
2023-12-12T20:49:20.034405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

장애인용화장실
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2222 
True
 
99
ValueCountFrequency (%)
False 2222
95.7%
True 99
 
4.3%
2023-12-12T20:49:20.109643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

화장실위치
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
<NA>
2222 
건물내부
 
67
상가내부
 
31
건물외부
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2222
95.7%
건물내부 67
 
2.9%
상가내부 31
 
1.3%
건물외부 1
 
< 0.1%

Length

2023-12-12T20:49:20.229532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:49:20.328156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2222
95.7%
건물내부 67
 
2.9%
상가내부 31
 
1.3%
건물외부 1
 
< 0.1%

장애인용욕실_샤워_탈의실
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2321 
ValueCountFrequency (%)
False 2321
100.0%
2023-12-12T20:49:20.415898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

점자블록
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2132 
True
 
189
ValueCountFrequency (%)
False 2132
91.9%
True 189
 
8.1%
2023-12-12T20:49:20.504510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

유도및안내설비
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2299 
True
 
22
ValueCountFrequency (%)
False 2299
99.1%
True 22
 
0.9%
2023-12-12T20:49:20.596250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

경보및피난설비
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2135 
True
 
186
ValueCountFrequency (%)
False 2135
92.0%
True 186
 
8.0%
2023-12-12T20:49:20.688217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

객실_침대
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2321 
ValueCountFrequency (%)
False 2321
100.0%
2023-12-12T20:49:20.797108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관람석_열람석
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2319 
True
 
2
ValueCountFrequency (%)
False 2319
99.9%
True 2
 
0.1%
2023-12-12T20:49:20.891556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

접수대_작업대
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2320 
True
 
1
ValueCountFrequency (%)
False 2320
> 99.9%
True 1
 
< 0.1%
2023-12-12T20:49:20.991377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

매표소_판매기_음료대
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2318 
True
 
3
ValueCountFrequency (%)
False 2318
99.9%
True 3
 
0.1%
2023-12-12T20:49:21.084914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

임산부등을위한휴게실
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
False
2319 
True
 
2
ValueCountFrequency (%)
False 2319
99.9%
True 2
 
0.1%
2023-12-12T20:49:21.186164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

편의시설사진정보
Text

UNIQUE 

Distinct2321
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.3 KiB
2023-12-12T20:49:21.424392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length170
Median length37
Mean length49.401982
Min length37

Characters and Unicode

Total characters114662
Distinct characters16
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

Unique2321 ?
Unique (%)100.0%

Sample

1st row01-01-00001-01.jpg|01-01-00001-02.jpg|01-01-00001-03.jpg
2nd row01-01-00002-01.jpg|01-01-00002-02.jpg
3rd row01-01-00003-01.jpg|01-01-00003-02.jpg|01-01-00003-03.jpg
4th row01-01-00004-01.jpg|01-01-00004-02.jpg
5th row01-01-00005-01.jpg|01-01-00005-02.jpg|01-01-00005-03.jpg
ValueCountFrequency (%)
01-01-00001-01.jpg|01-01-00001-02.jpg|01-01-00001-03.jpg 1
 
< 0.1%
01-01-01524-01.jpg|01-01-01524-02.jpg|01-01-01524-03.jpg 1
 
< 0.1%
01-01-01551-01.jpg|01-01-01551-02.jpg 1
 
< 0.1%
01-01-01545-01.jpg|01-01-01545-02.jpg 1
 
< 0.1%
01-01-01546-01.jpg|01-01-01546-02.jpg|01-01-01546-03.jpg 1
 
< 0.1%
01-01-01547-01.jpg|01-01-01547-02.jpg 1
 
< 0.1%
01-01-01548-01.jpg|01-01-01548-02.jpg|01-01-01548-03.jpg|01-01-01548-04.jpg|01-01-01548-05.jpg|01-01-01548-06.jpg 1
 
< 0.1%
01-01-01549-01.jpg|01-01-01549-02.jpg 1
 
< 0.1%
01-01-01550-01.jpg|01-01-01550-02.jpg 1
 
< 0.1%
01-01-01552-01.jpg|01-01-01552-02.jpg 1
 
< 0.1%
Other values (2311) 2311
99.6%
2023-12-12T20:49:21.935856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 30627
26.7%
- 18471
16.1%
1 18100
15.8%
. 6157
 
5.4%
j 6157
 
5.4%
p 6157
 
5.4%
g 6157
 
5.4%
2 5060
 
4.4%
| 3836
 
3.3%
3 2808
 
2.4%
Other values (6) 11132
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67727
59.1%
Dash Punctuation 18471
 
16.1%
Lowercase Letter 18471
 
16.1%
Other Punctuation 6157
 
5.4%
Math Symbol 3836
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30627
45.2%
1 18100
26.7%
2 5060
 
7.5%
3 2808
 
4.1%
4 2331
 
3.4%
5 1919
 
2.8%
6 1857
 
2.7%
7 1772
 
2.6%
8 1686
 
2.5%
9 1567
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
j 6157
33.3%
p 6157
33.3%
g 6157
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 18471
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6157
100.0%
Math Symbol
ValueCountFrequency (%)
| 3836
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96191
83.9%
Latin 18471
 
16.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 30627
31.8%
- 18471
19.2%
1 18100
18.8%
. 6157
 
6.4%
2 5060
 
5.3%
| 3836
 
4.0%
3 2808
 
2.9%
4 2331
 
2.4%
5 1919
 
2.0%
6 1857
 
1.9%
Other values (3) 5025
 
5.2%
Latin
ValueCountFrequency (%)
j 6157
33.3%
p 6157
33.3%
g 6157
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 114662
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 30627
26.7%
- 18471
16.1%
1 18100
15.8%
. 6157
 
5.4%
j 6157
 
5.4%
p 6157
 
5.4%
g 6157
 
5.4%
2 5060
 
4.4%
| 3836
 
3.3%
3 2808
 
2.4%
Other values (6) 11132
 
9.7%

시설(업소)사진정보
Text

Distinct2320
Distinct (%)100.0%
Missing1
Missing (%)< 0.1%
Memory size18.3 KiB
2023-12-12T20:49:22.219970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters41760
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2320 ?
Unique (%)100.0%

Sample

1st row01-01-00001-04.jpg
2nd row01-01-00002-03.jpg
3rd row01-01-00003-04.jpg
4th row01-01-00004-03.jpg
5th row01-01-00005-04.jpg
ValueCountFrequency (%)
01-01-00001-04.jpg 1
 
< 0.1%
01-01-01524-04.jpg 1
 
< 0.1%
01-01-01551-03.jpg 1
 
< 0.1%
01-01-01545-03.jpg 1
 
< 0.1%
01-01-01546-04.jpg 1
 
< 0.1%
01-01-01547-03.jpg 1
 
< 0.1%
01-01-01548-07.jpg 1
 
< 0.1%
01-01-01549-03.jpg 1
 
< 0.1%
01-01-01550-03.jpg 1
 
< 0.1%
01-01-01552-03.jpg 1
 
< 0.1%
Other values (2310) 2310
99.6%
2023-12-12T20:49:22.711337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11469
27.5%
- 6960
16.7%
1 6046
14.5%
. 2320
 
5.6%
j 2320
 
5.6%
p 2320
 
5.6%
g 2320
 
5.6%
3 1988
 
4.8%
4 1514
 
3.6%
2 1008
 
2.4%
Other values (5) 3495
 
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25520
61.1%
Dash Punctuation 6960
 
16.7%
Lowercase Letter 6960
 
16.7%
Other Punctuation 2320
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11469
44.9%
1 6046
23.7%
3 1988
 
7.8%
4 1514
 
5.9%
2 1008
 
3.9%
5 768
 
3.0%
7 738
 
2.9%
6 718
 
2.8%
8 652
 
2.6%
9 619
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
j 2320
33.3%
p 2320
33.3%
g 2320
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 6960
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2320
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34800
83.3%
Latin 6960
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11469
33.0%
- 6960
20.0%
1 6046
17.4%
. 2320
 
6.7%
3 1988
 
5.7%
4 1514
 
4.4%
2 1008
 
2.9%
5 768
 
2.2%
7 738
 
2.1%
6 718
 
2.1%
Other values (2) 1271
 
3.7%
Latin
ValueCountFrequency (%)
j 2320
33.3%
p 2320
33.3%
g 2320
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11469
27.5%
- 6960
16.7%
1 6046
14.5%
. 2320
 
5.6%
j 2320
 
5.6%
p 2320
 
5.6%
g 2320
 
5.6%
3 1988
 
4.8%
4 1514
 
3.6%
2 1008
 
2.4%
Other values (5) 3495
 
8.4%

Sample

관리번호시도명시군구명데이터기준일위도경도업체명업종분류소재지 지번주소소재지 도로명주소전화번호영업시간휴무일홈페이지메뉴정보이용요금한줄소개키워드영업상태반려동물출입건물출입구접근로및높이차이제거장애인전용주차구역주차구역위치장애인용승강기_계단장애인용화장실화장실위치장애인용욕실_샤워_탈의실점자블록유도및안내설비경보및피난설비객실_침대관람석_열람석접수대_작업대매표소_판매기_음료대임산부등을위한휴게실편의시설사진정보시설(업소)사진정보
001-00001경기도포천시2022-12-0937.786377127.2277춘하추동1경기도 포천시 내촌면 내리 521-5경기도 포천시 내촌면 내촌로 71031-532-261010:30~19:30연중무휴<NA>잔치국수:6000원+콩국수:8000원+비빔국수:7000원<NA>국물이 진한 포천 춘하추동입니다.#잔치국수+#포천+#국수맛집영업NNN<NA>NN<NA>NNNNNNNNN01-01-00001-01.jpg|01-01-00001-02.jpg|01-01-00001-03.jpg01-01-00001-04.jpg
101-00002경기도포천시2022-12-0937.785954127.227018삼거리식당1경기도 포천시 내촌면 내리 479-1경기도 포천시 내촌면 내촌로 63<NA><NA><NA><NA><NA><NA>한식이 생각날때 가는집 삼거리 식당입니다#한식+#집밥+#단체+#가성비영업NNN<NA>NN<NA>NNNNNNNNN01-01-00002-01.jpg|01-01-00002-02.jpg01-01-00002-03.jpg
201-00003경기도포천시2022-12-0937.786016127.226198풍미식당1경기도 포천시 내촌면 내리 465-18경기도 포천시 내촌면 포천로 8-1031-532-296610:30~20:00두번째주/네번째주 일요일<NA>비빔국수:8000원+칼국수:8000원+찐만두:12000원<NA>배고플때 생각나는 포천 풍미식당입니다.#국수+#포천+#내촌+#숨은맛집영업NNN<NA>NN<NA>NNNNNNNNN01-01-00003-01.jpg|01-01-00003-02.jpg|01-01-00003-03.jpg01-01-00003-04.jpg
301-00004경기도포천시2022-12-0937.914267127.21405천호식당1경기도 포천시 신북면 가채리 185경기도 포천시 신북면 중앙로 336031-534-7668<NA><NA><NA>제육정식+김치찌개+육개장+우렁된장<NA>포천시 신북면 한식 맛집입니다.#포천시+#신북면+#한식맛집영업NNN<NA>NN<NA>NNNNNNNNN01-01-00004-01.jpg|01-01-00004-02.jpg01-01-00004-03.jpg
401-00005경기도포천시2022-12-0937.830968127.265266우리집한식뷔페1경기도 포천시 내촌면 신팔리 374-8경기도 포천시 내촌면 금강로 2999031-535-6908<NA>주말<NA><NA><NA>집밥이 생각나는 포천 우리집 한식뷔페 입니다.#포천+#뷔페+#한식+#집밥느낌영업NNN<NA>NN<NA>NNNNNNNNN01-01-00005-01.jpg|01-01-00005-02.jpg|01-01-00005-03.jpg01-01-00005-04.jpg
501-00006경기도포천시2022-12-0937.85218127.203263돼지네식당1경기도 포천시 군내면 유교리 206-5경기도 포천시 군내면 마전길 25-20031-544-0663<NA><NA><NA><NA><NA>든든하게 배 채울수 있는 돼지네식당입니다#포천+#돼지네식당+#군내+#배달영업NNN<NA>NN<NA>NNNNNNNNN01-01-00006-01.jpg|01-01-00006-02.jpg|01-01-00006-03.jpg01-01-00006-04.jpg
601-00007경기도포천시2022-12-0937.787326127.222872내촌가든반점1경기도 포천시 내촌면 내리 521경기도 포천시 내촌면 내진로30번길 64031-532-2929<NA><NA><NA>두부김치:10000원+손만둣국:7000원<NA>고소한 두부집 내촌면 두부김치집입니다#내촌면+#두부요리+#두부본연의맛영업NYN<NA>NN<NA>NNNNNNNNN01-01-00007-01.jpg|01-01-00007-02.jpg01-01-00007-03.jpg
701-00008경기도포천시2022-12-0937.988573127.24369곰고개식당1경기도 포천시 영중면 양문리 686-5경기도 포천시 영중면 호국로 2756-22031-532-857107:00~22:00연중무휴<NA>옻닭:65000원+엄백숙:65000원+묵은지볶음탕:70000원+도리탕:65000원+능이백숙70000원<NA>닭요리의 고수 영중면 곰고개식당입니다#영중면+#금고개식당+#옻닭+#닭요리고수영업NNN<NA>NN<NA>NNNNNNNNN01-01-00008-01.jpg|01-01-00008-02.jpg|01-01-00008-03.jpg|01-01-00008-04.jpg01-01-00008-05.jpg
801-00009경기도포천시2022-12-0937.79418127.230047곰터먹촌1경기도 포천시 내촌면 내리 273-5경기도 포천시 내촌면 내촌로 169031-534-706710:00~18:30연중무휴<NA>김치말이국수:8000원+김치말이밥:8000원+곰탕:8000원<NA>계속 생각나는 포천 곰터먹촌입니다.#국수+#곰탕+#포천+#맛집+#입맛도는영업NNN<NA>NN<NA>NNNNNNNNN01-01-00009-01.jpg|01-01-00009-02.jpg|01-01-00009-03.jpg01-01-00009-04.jpg
901-00010경기도포천시2022-12-0938.02757127.278837원조파주골순두부집1경기도 포천시 영중면 성동리 135-8경기도 포천시 영중면 성장로 179031-532-659008:00~20:00연중무휴http://www.원조파주골순두부.com/순두부정식:8000원+두부전골:9000원+두부튀김:9000원<NA>원조의 원조 파주골순두부입니다#포천+#원졸파주골순두부+#순두부+#장인영업NNN<NA>NN<NA>NNNNNNNNN01-01-00010-01.jpg|01-01-00010-02.jpg01-01-00010-03.jpg
관리번호시도명시군구명데이터기준일위도경도업체명업종분류소재지 지번주소소재지 도로명주소전화번호영업시간휴무일홈페이지메뉴정보이용요금한줄소개키워드영업상태반려동물출입건물출입구접근로및높이차이제거장애인전용주차구역주차구역위치장애인용승강기_계단장애인용화장실화장실위치장애인용욕실_샤워_탈의실점자블록유도및안내설비경보및피난설비객실_침대관람석_열람석접수대_작업대매표소_판매기_음료대임산부등을위한휴게실편의시설사진정보시설(업소)사진정보
231104-00066경기도포천시2022-12-0937.895695127.202629참의원4경기도 포천시 신읍동 29-12경기도 포천시 구절초로 17031-535-531009:00~18:00<NA><NA><NA><NA>관절 치료 전문 참의원입니다#포천+#구절초로+#병원영업NYN<NA>NN<NA>NNNNNNNNN01-04-00066-01.jpg|01-04-00066-02.jpg|01-04-00066-03.jpg|01-04-00066-04.jpg01-04-00066-05.jpg
231204-00067경기도포천시2022-12-0937.896225127.20266금강한의원4경기도 포천시 신읍동 27-11경기도 포천시 중앙로 110031-533-753309:00~19:00일요일<NA><NA><NA>한방 치료와 한약 전문 금강한의원입니다#포천+#중앙로+#한의원영업NYN<NA>NN<NA>NNNNNNNNN01-04-00067-01.jpg|01-04-00067-02.jpg01-04-00067-03.jpg
231304-00068경기도포천시2022-12-0937.896446127.202942경희한의원4경기도 포천시 신읍동 25-2경기도 포천시 중앙로110번길 4031-535-470609:00~18:00일요일<NA><NA><NA>한약과 한방 치료 전문 경희한의원입니다#포천+#중앙로+#한의원영업NNN<NA>NN<NA>NNNNNNNNN01-04-00068-01.jpg|01-04-00068-02.jpg|01-04-00068-03.jpg|01-04-00068-04.jpg01-04-00068-05.jpg
231404-00069경기도포천시2022-12-0937.897289127.203339포천치과의원4경기도 포천시 신읍동 43-44경기도 포천시 중앙로 124-1031-535-428409:00~18:30일요일<NA><NA><NA>건강한 치아 건강 유지를 도와주는 포천치과의원입니다#포천+#중앙로+#치과영업NNN<NA>NN<NA>NNNNNNNNN01-04-00069-01.jpg|01-04-00069-02.jpg01-04-00069-03.jpg
231504-00070경기도포천시2022-12-0937.897667127.203796두리이비인후과4경기도 포천시 신읍동 42-9경기도 포천시 중앙로 130031-534-777209:00~18:00일요일<NA><NA><NA>친절한 이비인후과 두리이비인후과입니다#포천+#중앙로+#이비인후과영업NNN<NA>NN<NA>NNNNNNNNN01-04-00070-01.jpg|01-04-00070-02.jpg01-04-00070-03.jpg
231604-00071경기도포천시2022-12-0937.897984127.204132온담치과의원4경기도 포천시 신읍동 193-10경기도 포천시 중앙로 136031-533-208009:00~18:00일요일<NA><NA><NA>튼튼하고 건강한 치아 건강 유지를 도와주는 온담치과의원입니다#포천+#중앙로+#치과영업NNN<NA>NN<NA>NNNNNNNNN01-04-00071-01.jpg|01-04-00071-02.jpg01-04-00071-03.jpg
231704-00072경기도포천시2022-12-0937.89835127.204422서울의원4경기도 포천시 신읍동 193-1경기도 포천시 중앙로 138031-536-119709:00~18:00일요일<NA><NA><NA>의사 선생님과 간호사 선생님이 친절한 피부과 서울의원입니다#포천+#중앙로+#이비인후과영업NNN<NA>NN<NA>NNNYNNNNN01-04-00072-01.jpg|01-04-00072-02.jpg01-04-00072-03.jpg
231804-00073경기도포천시2022-12-0937.898159127.203751파우pc방4경기도 포천시 신읍동 191-3경기도 포천시 중앙로 133<NA><NA><NA><NA><NA><NA>파우pc방입니다<NA>영업NYN<NA>NN<NA>NNNYNNNNN01-04-00073-01.jpg|01-04-00073-02.jpg|01-04-00073-03.jpg|01-04-00073-04.jpg|01-04-00073-05.jpg01-04-00073-06.jpg
231904-00074경기도포천시2022-12-0937.854176127.166199서울 최 내과의원4경기도 포천시 선단동 55-1경기도 포천시 호국로 1001 4층 3호0507-1311-825210:00~17:30+주말 10:00~13:00<NA><NA><NA><NA>친절한 내과 서울최내과의원입니다#포천+#대진대+#내과영업NYN<NA>YY건물내부NNNNNNNNN01-04-00074-01.jpg|01-04-00074-02.jpg|01-04-00074-03.jpg|01-04-00074-04.jpg01-04-00074-05.jpg
232004-00075경기도포천시2022-12-0937.854259127.166306명인치과4경기도 포천시 선단동 55-1경기도 포천시 호국로 1001031-542-227509:30~18:30+목요일 09:30~20:30+토요일 09:30~12:30일요일<NA><NA><NA>건강한 치아 건강 유지를 도와주는 명인치과입니다#포천+#대진대+#치과영업NNN<NA>YY건물내부NNNNNNNNN01-04-00075-01.jpg|01-04-00075-02.jpg|01-04-00075-03.jpg|01-04-00075-04.jpg01-04-00075-05.jpg