Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells27411
Missing cells (%)18.3%
Duplicate rows793
Duplicate rows (%)7.9%
Total size in memory1.3 MiB
Average record size in memory134.0 B

Variable types

Categorical4
Text3
DateTime2
Unsupported1
Numeric5

Dataset

Description숙박업체 현황(일반-여관업)
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=16497M8L2PU129446X15724732&infSeq=1

Alerts

Dataset has 793 (7.9%) duplicate rowsDuplicates
영업상태명 is highly overall correlated with 위생업종명High correlation
위생업태명 is highly overall correlated with 위생업종명High correlation
위생업종명 is highly overall correlated with 양실수(개) and 7 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
양실수(개) is highly overall correlated with 위생업종명High correlation
한실수(개) is highly overall correlated with 위생업종명High correlation
소재지우편번호 is highly overall correlated with WGS84위도 and 2 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
폐업일자 has 8019 (80.2%) missing valuesMissing
다중이용업소여부 has 10000 (100.0%) missing valuesMissing
양실수(개) has 4294 (42.9%) missing valuesMissing
한실수(개) has 4437 (44.4%) missing valuesMissing
소재지도로명주소 has 317 (3.2%) missing valuesMissing
소재지우편번호 has 102 (1.0%) missing valuesMissing
WGS84위도 has 120 (1.2%) missing valuesMissing
WGS84경도 has 120 (1.2%) missing valuesMissing
다중이용업소여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
양실수(개) has 612 (6.1%) zerosZeros
한실수(개) has 3563 (35.6%) zerosZeros

Reproduction

Analysis started2023-12-10 22:52:11.355283
Analysis finished2023-12-10 22:52:16.839517
Duration5.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가평군
1574 
수원시
1162 
안산시
903 
양평군
740 
부천시
580 
Other values (26)
5041 

Length

Max length4
Median length3
Mean length3.0489
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row포천시
2nd row수원시
3rd row화성시
4th row수원시
5th row가평군

Common Values

ValueCountFrequency (%)
가평군 1574
15.7%
수원시 1162
 
11.6%
안산시 903
 
9.0%
양평군 740
 
7.4%
부천시 580
 
5.8%
파주시 492
 
4.9%
포천시 414
 
4.1%
성남시 375
 
3.8%
화성시 367
 
3.7%
용인시 345
 
3.5%
Other values (21) 3048
30.5%

Length

2023-12-11T07:52:16.913059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가평군 1574
15.7%
수원시 1162
 
11.6%
안산시 903
 
9.0%
양평군 740
 
7.4%
부천시 580
 
5.8%
파주시 492
 
4.9%
포천시 414
 
4.1%
성남시 375
 
3.8%
화성시 367
 
3.7%
용인시 345
 
3.5%
Other values (21) 3048
30.5%

사업장명
Text

Distinct6652
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T07:52:17.256922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length35
Mean length5.7257
Min length1

Characters and Unicode

Total characters57257
Distinct characters878
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4939 ?
Unique (%)49.4%

Sample

1st row(주)이랜드파크 베어스타운
2nd row삼보모텔
3rd row휴콘도
4th row녹산장여관
5th row스위스산장
ValueCountFrequency (%)
캠핑장 153
 
1.2%
펜션 145
 
1.2%
호텔 142
 
1.2%
모텔 79
 
0.6%
hotel 64
 
0.5%
민박 40
 
0.3%
글램핑 37
 
0.3%
주식회사 31
 
0.3%
하우스 31
 
0.3%
더 30
 
0.2%
Other values (6945) 11494
93.9%
2023-12-11T07:52:17.855198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 2570
 
4.5%
2281
 
4.0%
스 1576
 
2.8%
여 1525
 
2.7%
모 1494
 
2.6%
장 1391
 
2.4%
관 1311
 
2.3%
호 1235
 
2.2%
이 1178
 
2.1%
리 1014
 
1.8%
Other values (868) 41682
72.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49355
86.2%
Space Separator 2281
 
4.0%
Uppercase Letter 2033
 
3.6%
Lowercase Letter 1313
 
2.3%
Decimal Number 954
 
1.7%
Close Punctuation 513
 
0.9%
Open Punctuation 513
 
0.9%
Other Punctuation 168
 
0.3%
Dash Punctuation 104
 
0.2%
Letter Number 12
 
< 0.1%
Other values (3) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 2570
 
5.2%
스 1576
 
3.2%
여 1525
 
3.1%
모 1494
 
3.0%
장 1391
 
2.8%
관 1311
 
2.7%
호 1235
 
2.5%
이 1178
 
2.4%
리 1014
 
2.1%
션 966
 
2.0%
Other values (787) 35095
71.1%
Uppercase Letter
ValueCountFrequency (%)
O 178
 
8.8%
T 173
 
8.5%
E 161
 
7.9%
H 156
 
7.7%
A 148
 
7.3%
L 147
 
7.2%
M 126
 
6.2%
S 111
 
5.5%
N 95
 
4.7%
I 77
 
3.8%
Other values (16) 661
32.5%
Lowercase Letter
ValueCountFrequency (%)
e 204
15.5%
o 164
12.5%
t 121
9.2%
l 104
7.9%
a 103
7.8%
n 84
 
6.4%
s 78
 
5.9%
r 75
 
5.7%
i 71
 
5.4%
u 54
 
4.1%
Other values (15) 255
19.4%
Decimal Number
ValueCountFrequency (%)
2 278
29.1%
1 191
20.0%
5 93
 
9.7%
7 78
 
8.2%
3 71
 
7.4%
6 58
 
6.1%
0 54
 
5.7%
4 54
 
5.7%
9 39
 
4.1%
8 38
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 81
48.2%
& 40
23.8%
, 31
 
18.5%
' 5
 
3.0%
· 4
 
2.4%
/ 3
 
1.8%
@ 1
 
0.6%
? 1
 
0.6%
# 1
 
0.6%
; 1
 
0.6%
Letter Number
ValueCountFrequency (%)
Ⅱ 10
83.3%
Ⅰ 2
 
16.7%
Math Symbol
ValueCountFrequency (%)
+ 7
87.5%
→ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
2281
100.0%
Close Punctuation
ValueCountFrequency (%)
) 513
100.0%
Open Punctuation
ValueCountFrequency (%)
( 513
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49344
86.2%
Common 4544
 
7.9%
Latin 3358
 
5.9%
Han 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 2570
 
5.2%
스 1576
 
3.2%
여 1525
 
3.1%
모 1494
 
3.0%
장 1391
 
2.8%
관 1311
 
2.7%
호 1235
 
2.5%
이 1178
 
2.4%
리 1014
 
2.1%
션 966
 
2.0%
Other values (782) 35084
71.1%
Latin
ValueCountFrequency (%)
e 204
 
6.1%
O 178
 
5.3%
T 173
 
5.2%
o 164
 
4.9%
E 161
 
4.8%
H 156
 
4.6%
A 148
 
4.4%
L 147
 
4.4%
M 126
 
3.8%
t 121
 
3.6%
Other values (43) 1780
53.0%
Common
ValueCountFrequency (%)
2281
50.2%
) 513
 
11.3%
( 513
 
11.3%
2 278
 
6.1%
1 191
 
4.2%
- 104
 
2.3%
5 93
 
2.0%
. 81
 
1.8%
7 78
 
1.7%
3 71
 
1.6%
Other values (18) 341
 
7.5%
Han
ValueCountFrequency (%)
夢 6
54.5%
美 2
 
18.2%
元 1
 
9.1%
休 1
 
9.1%
月 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49343
86.2%
ASCII 7884
 
13.8%
Number Forms 12
 
< 0.1%
CJK 11
 
< 0.1%
None 4
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 2570
 
5.2%
스 1576
 
3.2%
여 1525
 
3.1%
모 1494
 
3.0%
장 1391
 
2.8%
관 1311
 
2.7%
호 1235
 
2.5%
이 1178
 
2.4%
리 1014
 
2.1%
션 966
 
2.0%
Other values (781) 35083
71.1%
ASCII
ValueCountFrequency (%)
2281
28.9%
) 513
 
6.5%
( 513
 
6.5%
2 278
 
3.5%
e 204
 
2.6%
1 191
 
2.4%
O 178
 
2.3%
T 173
 
2.2%
o 164
 
2.1%
E 161
 
2.0%
Other values (66) 3228
40.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 10
83.3%
Ⅰ 2
 
16.7%
CJK
ValueCountFrequency (%)
夢 6
54.5%
美 2
 
18.2%
元 1
 
9.1%
休 1
 
9.1%
月 1
 
9.1%
None
ValueCountFrequency (%)
· 4
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

인허가일자
Date

Distinct4290
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1946-11-23 00:00:00
Maximum2023-12-05 00:00:00
2023-12-11T07:52:18.024082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.172672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업
3522 
정상
2132 
운영중
1232 
폐업
1187 
영업중
1038 
Other values (4)
889 

Length

Max length4
Median length2
Mean length2.386
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row휴업
2nd row영업
3rd row영업중
4th row운영중
5th row영업

Common Values

ValueCountFrequency (%)
영업 3522
35.2%
정상 2132
21.3%
운영중 1232
 
12.3%
폐업 1187
 
11.9%
영업중 1038
 
10.4%
폐업 등 792
 
7.9%
휴업 94
 
0.9%
직권말소 2
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2023-12-11T07:52:18.344228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:52:18.506144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 3522
32.6%
정상 2132
19.8%
폐업 1979
18.3%
운영중 1232
 
11.4%
영업중 1038
 
9.6%
등 792
 
7.3%
휴업 94
 
0.9%
직권말소 2
 
< 0.1%
등록취소 1
 
< 0.1%

폐업일자
Date

MISSING 

Distinct1224
Distinct (%)61.8%
Missing8019
Missing (%)80.2%
Memory size156.2 KiB
Minimum1987-04-30 00:00:00
Maximum2023-12-01 00:00:00
2023-12-11T07:52:18.679174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:18.844867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

다중이용업소여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

양실수(개)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct130
Distinct (%)2.3%
Missing4294
Missing (%)42.9%
Infinite0
Infinite (%)0.0%
Mean23.784087
Minimum0
Maximum826
Zeros612
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:52:19.019759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median19
Q329
95-th percentile48
Maximum826
Range826
Interquartile range (IQR)20

Descriptive statistics

Standard deviation41.478296
Coefficient of variation (CV)1.7439516
Kurtosis174.40655
Mean23.784087
Median Absolute Deviation (MAD)10
Skewness11.190211
Sum135712
Variance1720.4491
MonotonicityNot monotonic
2023-12-11T07:52:19.196887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 612
 
6.1%
10 222
 
2.2%
19 206
 
2.1%
18 203
 
2.0%
15 194
 
1.9%
12 184
 
1.8%
28 175
 
1.8%
20 175
 
1.8%
30 152
 
1.5%
24 146
 
1.5%
Other values (120) 3437
34.4%
(Missing) 4294
42.9%
ValueCountFrequency (%)
0 612
6.1%
1 103
 
1.0%
2 57
 
0.6%
3 48
 
0.5%
4 97
 
1.0%
5 106
 
1.1%
6 131
 
1.3%
7 88
 
0.9%
8 106
 
1.1%
9 93
 
0.9%
ValueCountFrequency (%)
826 5
0.1%
825 1
 
< 0.1%
510 1
 
< 0.1%
476 2
 
< 0.1%
440 2
 
< 0.1%
432 2
 
< 0.1%
416 4
< 0.1%
343 2
 
< 0.1%
333 1
 
< 0.1%
321 1
 
< 0.1%

위생업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8103 
숙박업(일반)
1897 

Length

Max length7
Median length4
Mean length4.5691
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row숙박업(일반)
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 8103
81.0%
숙박업(일반) 1897
 
19.0%

Length

2023-12-11T07:52:19.353708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:52:19.455937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8103
81.0%
숙박업(일반 1897
 
19.0%

위생업태명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4232 
여관업
4009 
숙박업(생활)
747 
일반호텔
 
398
여인숙업
 
357
Other values (3)
 
257

Length

Max length8
Median length4
Mean length3.8496
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row여관업
3rd row<NA>
4th row여관업
5th row숙박업(생활)

Common Values

ValueCountFrequency (%)
<NA> 4232
42.3%
여관업 4009
40.1%
숙박업(생활) 747
 
7.5%
일반호텔 398
 
4.0%
여인숙업 357
 
3.6%
관광호텔 129
 
1.3%
숙박업 기타 124
 
1.2%
휴양콘도미니엄업 4
 
< 0.1%

Length

2023-12-11T07:52:19.600631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:52:19.760444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4232
41.8%
여관업 4009
39.6%
숙박업(생활 747
 
7.4%
일반호텔 398
 
3.9%
여인숙업 357
 
3.5%
관광호텔 129
 
1.3%
숙박업 124
 
1.2%
기타 124
 
1.2%
휴양콘도미니엄업 4
 
< 0.1%

한실수(개)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct57
Distinct (%)1.0%
Missing4437
Missing (%)44.4%
Infinite0
Infinite (%)0.0%
Mean2.9532626
Minimum0
Maximum281
Zeros3563
Zeros (%)35.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:52:19.917822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile12
Maximum281
Range281
Interquartile range (IQR)3

Descriptive statistics

Standard deviation9.5407475
Coefficient of variation (CV)3.2305788
Kurtosis330.98125
Mean2.9532626
Median Absolute Deviation (MAD)0
Skewness14.793564
Sum16429
Variance91.025863
MonotonicityNot monotonic
2023-12-11T07:52:20.076407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3563
35.6%
2 245
 
2.5%
4 206
 
2.1%
1 196
 
2.0%
3 192
 
1.9%
5 184
 
1.8%
6 145
 
1.5%
10 131
 
1.3%
8 120
 
1.2%
7 112
 
1.1%
Other values (47) 469
 
4.7%
(Missing) 4437
44.4%
ValueCountFrequency (%)
0 3563
35.6%
1 196
 
2.0%
2 245
 
2.5%
3 192
 
1.9%
4 206
 
2.1%
5 184
 
1.8%
6 145
 
1.5%
7 112
 
1.1%
8 120
 
1.2%
9 98
 
1.0%
ValueCountFrequency (%)
281 1
 
< 0.1%
273 1
 
< 0.1%
185 1
 
< 0.1%
151 1
 
< 0.1%
150 4
< 0.1%
125 1
 
< 0.1%
107 1
 
< 0.1%
91 1
 
< 0.1%
85 2
< 0.1%
83 1
 
< 0.1%

소재지도로명주소
Text

MISSING 

Distinct6805
Distinct (%)70.3%
Missing317
Missing (%)3.2%
Memory size156.2 KiB
2023-12-11T07:52:20.424094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length107
Median length77
Mean length26.274295
Min length13

Characters and Unicode

Total characters254414
Distinct characters603
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5161 ?
Unique (%)53.3%

Sample

1st row경기도 포천시 내촌면 금강로2536번길 27
2nd row경기도 수원시 팔달구 매산로 17-8 (매산로1가)
3rd row경기도 화성시 서신면 해안길 272
4th row경기도 수원시 팔달구 정조로795번길 16-11, 1~3층 (남창동)
5th row경기도 가평군 청평면 북한강로1636번길 41, 1~2층
ValueCountFrequency (%)
경기도 9683
 
17.9%
가평군 1556
 
2.9%
수원시 1136
 
2.1%
안산시 887
 
1.6%
팔달구 759
 
1.4%
단원구 756
 
1.4%
양평군 731
 
1.3%
부천시 546
 
1.0%
파주시 449
 
0.8%
포천시 401
 
0.7%
Other values (7140) 37280
68.8%
2023-12-11T07:52:21.125851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44518
 
17.5%
경 9953
 
3.9%
기 9920
 
3.9%
도 9882
 
3.9%
1 9833
 
3.9%
로 7910
 
3.1%
시 7497
 
2.9%
2 7195
 
2.8%
동 6217
 
2.4%
길 5915
 
2.3%
Other values (593) 135574
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 145363
57.1%
Decimal Number 45877
 
18.0%
Space Separator 44518
 
17.5%
Close Punctuation 5036
 
2.0%
Open Punctuation 5035
 
2.0%
Dash Punctuation 4566
 
1.8%
Other Punctuation 3040
 
1.2%
Math Symbol 621
 
0.2%
Uppercase Letter 310
 
0.1%
Lowercase Letter 47
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 9953
 
6.8%
기 9920
 
6.8%
도 9882
 
6.8%
로 7910
 
5.4%
시 7497
 
5.2%
동 6217
 
4.3%
길 5915
 
4.1%
번 3767
 
2.6%
면 3642
 
2.5%
평 3630
 
2.5%
Other values (533) 77030
53.0%
Uppercase Letter
ValueCountFrequency (%)
A 86
27.7%
B 71
22.9%
C 35
11.3%
D 18
 
5.8%
E 15
 
4.8%
T 14
 
4.5%
H 11
 
3.5%
O 9
 
2.9%
M 7
 
2.3%
I 7
 
2.3%
Other values (10) 37
11.9%
Lowercase Letter
ValueCountFrequency (%)
t 7
14.9%
n 6
12.8%
e 6
12.8%
m 4
8.5%
o 4
8.5%
u 3
6.4%
h 3
6.4%
r 3
6.4%
i 3
6.4%
v 3
6.4%
Other values (3) 5
10.6%
Decimal Number
ValueCountFrequency (%)
1 9833
21.4%
2 7195
15.7%
3 4826
10.5%
4 3984
8.7%
5 3855
 
8.4%
6 3659
 
8.0%
7 3498
 
7.6%
8 3041
 
6.6%
0 2994
 
6.5%
9 2992
 
6.5%
Other Punctuation
ValueCountFrequency (%)
, 2970
97.7%
. 44
 
1.4%
: 12
 
0.4%
/ 7
 
0.2%
* 4
 
0.1%
· 2
 
0.1%
& 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 619
99.7%
> 1
 
0.2%
< 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 5032
99.9%
] 4
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 5031
99.9%
[ 4
 
0.1%
Space Separator
ValueCountFrequency (%)
44518
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4566
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145363
57.1%
Common 108693
42.7%
Latin 358
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 9953
 
6.8%
기 9920
 
6.8%
도 9882
 
6.8%
로 7910
 
5.4%
시 7497
 
5.2%
동 6217
 
4.3%
길 5915
 
4.1%
번 3767
 
2.6%
면 3642
 
2.5%
평 3630
 
2.5%
Other values (533) 77030
53.0%
Latin
ValueCountFrequency (%)
A 86
24.0%
B 71
19.8%
C 35
9.8%
D 18
 
5.0%
E 15
 
4.2%
T 14
 
3.9%
H 11
 
3.1%
O 9
 
2.5%
M 7
 
2.0%
I 7
 
2.0%
Other values (24) 85
23.7%
Common
ValueCountFrequency (%)
44518
41.0%
1 9833
 
9.0%
2 7195
 
6.6%
) 5032
 
4.6%
( 5031
 
4.6%
3 4826
 
4.4%
- 4566
 
4.2%
4 3984
 
3.7%
5 3855
 
3.5%
6 3659
 
3.4%
Other values (16) 16194
 
14.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 145363
57.1%
ASCII 109048
42.9%
None 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44518
40.8%
1 9833
 
9.0%
2 7195
 
6.6%
) 5032
 
4.6%
( 5031
 
4.6%
3 4826
 
4.4%
- 4566
 
4.2%
4 3984
 
3.7%
5 3855
 
3.5%
6 3659
 
3.4%
Other values (48) 16549
 
15.2%
Hangul
ValueCountFrequency (%)
경 9953
 
6.8%
기 9920
 
6.8%
도 9882
 
6.8%
로 7910
 
5.4%
시 7497
 
5.2%
동 6217
 
4.3%
길 5915
 
4.1%
번 3767
 
2.6%
면 3642
 
2.5%
평 3630
 
2.5%
Other values (533) 77030
53.0%
None
ValueCountFrequency (%)
· 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

소재지지번주소
Text

Distinct7536
Distinct (%)75.4%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-11T07:52:21.485442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length89
Median length78
Mean length23.025705
Min length14

Characters and Unicode

Total characters230211
Distinct characters510
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6128 ?
Unique (%)61.3%

Sample

1st row경기도 포천시 내촌면 소학리 295
2nd row경기도 수원시 팔달구 매산로1가 43-3
3rd row경기도 화성시 서신면 제부리 190-191
4th row경기도 수원시 팔달구 남창동 81번지 1~3층
5th row경기도 가평군 청평면 삼회리 463-6 외1필지
ValueCountFrequency (%)
경기도 9998
 
19.5%
가평군 1574
 
3.1%
수원시 1162
 
2.3%
안산시 903
 
1.8%
팔달구 772
 
1.5%
단원구 770
 
1.5%
양평군 740
 
1.4%
부천시 580
 
1.1%
파주시 492
 
1.0%
포천시 414
 
0.8%
Other values (8514) 33763
66.0%
2023-12-11T07:52:22.070533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46139
20.0%
도 10304
 
4.5%
기 10192
 
4.4%
경 10047
 
4.4%
1 9373
 
4.1%
- 8586
 
3.7%
시 7696
 
3.3%
동 6472
 
2.8%
2 6453
 
2.8%
3 5278
 
2.3%
Other values (500) 109671
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 126618
55.0%
Decimal Number 46237
 
20.1%
Space Separator 46139
 
20.0%
Dash Punctuation 8586
 
3.7%
Other Punctuation 1232
 
0.5%
Math Symbol 486
 
0.2%
Open Punctuation 311
 
0.1%
Close Punctuation 311
 
0.1%
Uppercase Letter 241
 
0.1%
Lowercase Letter 50
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 10304
 
8.1%
기 10192
 
8.0%
경 10047
 
7.9%
시 7696
 
6.1%
동 6472
 
5.1%
리 4952
 
3.9%
면 3711
 
2.9%
평 3535
 
2.8%
구 3478
 
2.7%
지 3192
 
2.5%
Other values (443) 63039
49.8%
Uppercase Letter
ValueCountFrequency (%)
A 65
27.0%
B 53
22.0%
C 28
11.6%
E 13
 
5.4%
T 13
 
5.4%
H 11
 
4.6%
O 9
 
3.7%
D 9
 
3.7%
F 6
 
2.5%
M 6
 
2.5%
Other values (9) 28
11.6%
Lowercase Letter
ValueCountFrequency (%)
t 7
14.0%
n 6
12.0%
e 6
12.0%
m 5
10.0%
a 4
8.0%
o 4
8.0%
h 3
6.0%
u 3
6.0%
i 3
6.0%
r 3
6.0%
Other values (4) 6
12.0%
Decimal Number
ValueCountFrequency (%)
1 9373
20.3%
2 6453
14.0%
3 5278
11.4%
4 4420
9.6%
5 4080
8.8%
6 3940
8.5%
7 3787
8.2%
0 3130
 
6.8%
8 3047
 
6.6%
9 2729
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 1151
93.4%
. 62
 
5.0%
: 12
 
1.0%
/ 3
 
0.2%
· 2
 
0.2%
; 1
 
0.1%
& 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 484
99.6%
> 1
 
0.2%
< 1
 
0.2%
Space Separator
ValueCountFrequency (%)
46139
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8586
100.0%
Open Punctuation
ValueCountFrequency (%)
( 311
100.0%
Close Punctuation
ValueCountFrequency (%)
) 311
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 126618
55.0%
Common 103302
44.9%
Latin 291
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 10304
 
8.1%
기 10192
 
8.0%
경 10047
 
7.9%
시 7696
 
6.1%
동 6472
 
5.1%
리 4952
 
3.9%
면 3711
 
2.9%
평 3535
 
2.8%
구 3478
 
2.7%
지 3192
 
2.5%
Other values (443) 63039
49.8%
Latin
ValueCountFrequency (%)
A 65
22.3%
B 53
18.2%
C 28
 
9.6%
E 13
 
4.5%
T 13
 
4.5%
H 11
 
3.8%
O 9
 
3.1%
D 9
 
3.1%
t 7
 
2.4%
F 6
 
2.1%
Other values (23) 77
26.5%
Common
ValueCountFrequency (%)
46139
44.7%
1 9373
 
9.1%
- 8586
 
8.3%
2 6453
 
6.2%
3 5278
 
5.1%
4 4420
 
4.3%
5 4080
 
3.9%
6 3940
 
3.8%
7 3787
 
3.7%
0 3130
 
3.0%
Other values (14) 8116
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 126618
55.0%
ASCII 103591
45.0%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46139
44.5%
1 9373
 
9.0%
- 8586
 
8.3%
2 6453
 
6.2%
3 5278
 
5.1%
4 4420
 
4.3%
5 4080
 
3.9%
6 3940
 
3.8%
7 3787
 
3.7%
0 3130
 
3.0%
Other values (46) 8405
 
8.1%
Hangul
ValueCountFrequency (%)
도 10304
 
8.1%
기 10192
 
8.0%
경 10047
 
7.9%
시 7696
 
6.1%
동 6472
 
5.1%
리 4952
 
3.9%
면 3711
 
2.9%
평 3535
 
2.8%
구 3478
 
2.7%
지 3192
 
2.5%
Other values (443) 63039
49.8%
None
ValueCountFrequency (%)
· 2
100.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1248
Distinct (%)12.6%
Missing102
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean13983.894
Minimum10000
Maximum18635
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:52:22.226829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile10835.7
Q112405
median13246
Q316261
95-th percentile18136
Maximum18635
Range8635
Interquartile range (IQR)3856

Descriptive statistics

Standard deviation2374.1932
Coefficient of variation (CV)0.16978055
Kurtosis-1.1744238
Mean13983.894
Median Absolute Deviation (MAD)2055
Skewness0.32254465
Sum1.3841258 × 108
Variance5636793.4
MonotonicityNot monotonic
2023-12-11T07:52:22.383271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16455 157
 
1.6%
15650 155
 
1.6%
18553 125
 
1.2%
16269 119
 
1.2%
12448 105
 
1.1%
15651 101
 
1.0%
14643 90
 
0.9%
12405 83
 
0.8%
15653 82
 
0.8%
12406 73
 
0.7%
Other values (1238) 8808
88.1%
(Missing) 102
 
1.0%
ValueCountFrequency (%)
10000 1
 
< 0.1%
10004 1
 
< 0.1%
10005 1
 
< 0.1%
10006 1
 
< 0.1%
10012 3
< 0.1%
10013 7
0.1%
10018 6
0.1%
10020 2
 
< 0.1%
10021 1
 
< 0.1%
10029 7
0.1%
ValueCountFrequency (%)
18635 6
0.1%
18626 1
 
< 0.1%
18624 3
 
< 0.1%
18623 13
0.1%
18608 1
 
< 0.1%
18606 1
 
< 0.1%
18595 4
 
< 0.1%
18593 8
0.1%
18584 1
 
< 0.1%
18577 14
0.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6535
Distinct (%)66.1%
Missing120
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean37.507958
Minimum36.912093
Maximum38.230563
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:52:22.516089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.912093
5-th percentile37.103657
Q137.272074
median37.484013
Q337.746289
95-th percentile37.958224
Maximum38.230563
Range1.3184707
Interquartile range (IQR)0.4742155

Descriptive statistics

Standard deviation0.27533981
Coefficient of variation (CV)0.0073408371
Kurtosis-0.95126062
Mean37.507958
Median Absolute Deviation (MAD)0.21920983
Skewness0.20382039
Sum370578.62
Variance0.07581201
MonotonicityNot monotonic
2023-12-11T07:52:22.672227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7941598866 28
 
0.3%
37.59769209 27
 
0.3%
37.7774433558 14
 
0.1%
37.302152807 13
 
0.1%
37.7794799902 10
 
0.1%
37.8213608047 10
 
0.1%
37.3637498416 9
 
0.1%
37.2040859565 9
 
0.1%
37.269406099 9
 
0.1%
37.2520973152 9
 
0.1%
Other values (6525) 9742
97.4%
(Missing) 120
 
1.2%
ValueCountFrequency (%)
36.9120927477 1
< 0.1%
36.915604861 1
< 0.1%
36.9162708577 2
< 0.1%
36.9201803045 2
< 0.1%
36.9202835686 1
< 0.1%
36.9205898266 1
< 0.1%
36.9210283233 1
< 0.1%
36.9402626726 1
< 0.1%
36.9408465325 1
< 0.1%
36.9433336192 1
< 0.1%
ValueCountFrequency (%)
38.2305634409 1
< 0.1%
38.2152513068 2
< 0.1%
38.2145976156 1
< 0.1%
38.2144854264 1
< 0.1%
38.2124865269 2
< 0.1%
38.2106053092 2
< 0.1%
38.1862048375 2
< 0.1%
38.1855182519 1
< 0.1%
38.184973564 1
< 0.1%
38.1848295956 1
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6535
Distinct (%)66.1%
Missing120
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean127.10105
Minimum126.39169
Maximum127.79744
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:52:22.844852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.39169
5-th percentile126.61456
Q1126.86477
median127.06035
Q3127.36023
95-th percentile127.56264
Maximum127.79744
Range1.4057535
Interquartile range (IQR)0.49546019

Descriptive statistics

Standard deviation0.29529763
Coefficient of variation (CV)0.0023233295
Kurtosis-0.91495449
Mean127.10105
Median Absolute Deviation (MAD)0.25282845
Skewness0.08730624
Sum1255758.4
Variance0.087200688
MonotonicityNot monotonic
2023-12-11T07:52:23.022429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.3872699728 28
 
0.3%
127.1386630585 27
 
0.3%
126.6876928223 14
 
0.1%
126.8500465633 13
 
0.1%
127.0586862959 10
 
0.1%
127.0928193138 10
 
0.1%
126.9430880619 9
 
0.1%
127.0706007625 9
 
0.1%
127.0048582037 9
 
0.1%
127.0763612225 9
 
0.1%
Other values (6525) 9742
97.4%
(Missing) 120
 
1.2%
ValueCountFrequency (%)
126.391690975 1
< 0.1%
126.3924075156 1
< 0.1%
126.4494001465 1
< 0.1%
126.4506324893 1
< 0.1%
126.5277844892 1
< 0.1%
126.5334603781 1
< 0.1%
126.5380751612 1
< 0.1%
126.5412815902 1
< 0.1%
126.5413025752 1
< 0.1%
126.541349858 2
< 0.1%
ValueCountFrequency (%)
127.797444475 2
< 0.1%
127.7947934275 1
< 0.1%
127.7941692302 2
< 0.1%
127.7914677089 1
< 0.1%
127.7913215403 1
< 0.1%
127.7912363328 1
< 0.1%
127.7903016955 1
< 0.1%
127.7896839147 1
< 0.1%
127.7880417331 1
< 0.1%
127.7774093593 1
< 0.1%

Interactions

2023-12-11T07:52:15.701397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:13.762814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:14.198821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:14.626478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:15.251112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:15.782941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:13.840575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:14.286647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:14.702890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:15.343507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:15.873626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:13.927979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:14.369931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:14.984210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:15.437753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:15.959594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:14.013126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:14.454067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:15.056110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:15.527458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:16.094537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:14.110521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:14.544611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:15.144622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:15.608769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:52:23.158792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명양실수(개)위생업태명한실수(개)소재지우편번호WGS84위도WGS84경도
시군명1.0000.5790.3420.6510.1740.9950.9410.924
영업상태명0.5791.0000.1030.4460.0000.4090.2710.446
양실수(개)0.3420.1031.0000.3530.1180.1470.1060.092
위생업태명0.6510.4460.3531.0000.3250.4800.3270.428
한실수(개)0.1740.0000.1180.3251.0000.1000.1570.016
소재지우편번호0.9950.4090.1470.4800.1001.0000.9170.907
WGS84위도0.9410.2710.1060.3270.1570.9171.0000.725
WGS84경도0.9240.4460.0920.4280.0160.9070.7251.000
2023-12-11T07:52:23.262351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명위생업태명위생업종명시군명
영업상태명1.0000.3221.0000.257
위생업태명0.3221.0001.0000.339
위생업종명1.0001.0001.0001.000
시군명0.2570.3391.0001.000
2023-12-11T07:52:23.365553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
양실수(개)한실수(개)소재지우편번호WGS84위도WGS84경도시군명영업상태명위생업종명위생업태명
양실수(개)1.000-0.3710.076-0.108-0.2900.1410.0461.0000.197
한실수(개)-0.3711.0000.164-0.2130.0710.0690.0001.0000.181
소재지우편번호0.0760.1641.000-0.925-0.2190.9540.2001.0000.267
WGS84위도-0.108-0.213-0.9251.0000.3430.7040.1271.0000.172
WGS84경도-0.2900.071-0.2190.3431.0000.6540.2211.0000.242
시군명0.1410.0690.9540.7040.6541.0000.2571.0000.339
영업상태명0.0460.0000.2000.1270.2210.2571.0001.0000.322
위생업종명1.0001.0001.0001.0001.0001.0001.0001.0001.000
위생업태명0.1970.1810.2670.1720.2420.3390.3221.0001.000

Missing values

2023-12-11T07:52:16.279812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:52:16.503510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T07:52:16.699225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부양실수(개)위생업종명위생업태명한실수(개)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
16931포천시(주)이랜드파크 베어스타운1991-01-07휴업<NA><NA><NA><NA><NA><NA>경기도 포천시 내촌면 금강로2536번길 27경기도 포천시 내촌면 소학리 2951118837.799914127.245205
7248수원시삼보모텔19931113영업<NA><NA>11<NA>여관업3경기도 수원시 팔달구 매산로 17-8 (매산로1가)경기도 수원시 팔달구 매산로1가 43-31645537.267931127.00339
17221화성시휴콘도20180614영업중<NA><NA><NA><NA><NA><NA>경기도 화성시 서신면 해안길 272경기도 화성시 서신면 제부리 190-1911855337.165465126.618342
8038수원시녹산장여관20150227운영중<NA><NA>24숙박업(일반)여관업0경기도 수원시 팔달구 정조로795번길 16-11, 1~3층 (남창동)경기도 수원시 팔달구 남창동 81번지 1~3층1626137.279644127.01535
747가평군스위스산장20210512영업<NA><NA>1<NA>숙박업(생활)0경기도 가평군 청평면 북한강로1636번길 41, 1~2층경기도 가평군 청평면 삼회리 463-6 외1필지1245837.666926127.385683
4268남양주시윤아2017-12-13정상<NA><NA><NA><NA><NA><NA>경기도 남양주시 수동면 모꼬지로311번길 5, m&l카페경기도 남양주시 수동면 송천리 11-13 m&amp;l카페1203437.69324127.355879
4875부천시레드모텔(RED)2001-12-18영업<NA><NA>32<NA>여관업0경기도 부천시 부일로432번길 20 (심곡동)경기도 부천시 심곡동 464-171463637.485711126.77781
17279화성시백미응서재20171201영업중<NA><NA><NA><NA><NA><NA>경기도 화성시 서신면 밸미길 84경기도 화성시 서신면 백미리 5641855637.141671126.690815
14428의정부시길손파크20050711폐업 등20160428<NA>9숙박업(일반)여관업1경기도 의정부시 태평로63번길 16 (의정부동)경기도 의정부시 의정부동 171-11번지1169537.73835127.050861
17309화성시미고펜션20170810영업중<NA><NA><NA><NA><NA><NA>경기도 화성시 서신면 해안길178번길 48-7경기도 화성시 서신면 제부리 1031855337.166008126.619822
시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부양실수(개)위생업종명위생업태명한실수(개)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
15765평택시궁전파크 여인숙20021127영업<NA><NA>9<NA>여관업0경기도 평택시 평택1로20번길 19 (평택동)경기도 평택시 평택동 35-111791036.993757127.088407
1761가평군시크릿 하우스2023-07-17정상<NA><NA><NA><NA><NA><NA>경기도 가평군 설악면 가마소길 17-107경기도 가평군 설악면 천안리 583-91246937.639903127.47537
4741부천시동성여인숙19800605영업<NA><NA>6<NA>여인숙업0경기도 부천시 경인옛로22번길 4 (소사본동)경기도 부천시 소사본동 761470437.481241126.79422
1944가평군올인2006-05-12정상<NA><NA><NA><NA><NA><NA>경기도 가평군 가평읍 북한강변로 1037, 올인펜션경기도 가평군 가평읍 달전리 110-1 올인펜션1242237.805126127.524946
729가평군리오모텔1999-04-06영업<NA><NA>12<NA>여관업0경기도 가평군 청평면 북한강로 1851, 1층~5층경기도 가평군 청평면 삼회리 305-4 1층~5층1245837.683187127.38559
3858군포시타워모텔19980312운영중<NA><NA>12숙박업(일반)여관업0경기도 군포시 산본로323번길 4-17, 9층 901호 (산본동, 군포프라자)경기도 군포시 산본동 1130번지 군포프라자 901호1586537.360013126.93258
3623구리시이레피엠씨20220707영업<NA><NA>69<NA>숙박업(생활)0경기도 구리시 안골로 65, 우남퍼스트빌스위트 74호(별첨)호 (수택동)경기도 구리시 수택동 379-12 우남퍼스트빌스위트1192737.597692127.138663
16198평택시그랜드장여관19960123폐업 등20030122<NA>0숙박업(일반)여관업0<NA>경기도 평택시 용이동 82-5번지17868<NA><NA>
2261가평군다온펜션2022-04-14정상<NA><NA><NA><NA><NA><NA>경기도 가평군 가평읍 경반안로 357-177경기도 가평군 가평읍 경반리 583-351241537.83147127.468556
3030고양시현대여관19770921운영중<NA><NA>0숙박업(일반)여관업11경기도 고양시 일산서구 일청로8번길 18-1 (일산동)경기도 고양시 일산서구 일산동 635-8번지1034237.684811126.771019

Duplicate rows

Most frequently occurring

시군명사업장명인허가일자영업상태명폐업일자양실수(개)위생업종명위생업태명한실수(개)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도# duplicates
543양주시양주 두리캠핑장20200914영업중<NA><NA><NA><NA><NA>경기도 양주시 마전로212번길 79-72 (마전동)경기도 양주시 마전동 1831149637.77948127.05868610
41가평군아이캐슬220210513영업<NA>5<NA>숙박업(생활)0경기도 가평군 북면 백둔로 510-20, 가동(2층~3층)나동(1층~2층)다동(1~2층)경기도 가평군 북면 백둔리 456-5 가동(2층~3층)나동(1층~2층)다동(1~2층)1240637.904661127.4541357
396수원시진풍모텔19880107영업<NA>6<NA>여관업10경기도 수원시 팔달구 정조로791번길 14 (팔달로2가)경기도 수원시 팔달구 팔달로2가 109-71626137.278655127.0158527
550양주시해피니스 캠핑장20210506영업중<NA><NA><NA><NA><NA>경기도 양주시 장흥면 권율로309번길 317-196경기도 양주시 장흥면 석현리 303-21151937.749416126.9370327
694파주시파주칼튼20060711영업<NA>42<NA>일반호텔0경기도 파주시 탄현면 성동로 34, 2동경기도 파주시 탄현면 성동리 679-1 2동1086237.777443126.6876937
707파주시호텔자자19881103영업<NA>25<NA>여관업1경기도 파주시 금정22길 26 (금촌동)경기도 파주시 금촌동 65-51092937.762309126.7744827
711평택시레몬라이프20011211영업<NA>19<NA>여관업4경기도 평택시 안중읍 안현로서4길 28경기도 평택시 안중읍 안중리 265-2 ,4 262-591793636.987216126.9280347
39가평군스위스산장20210512영업<NA>1<NA>숙박업(생활)0경기도 가평군 청평면 북한강로1636번길 41, 1~2층경기도 가평군 청평면 삼회리 463-6 외1필지1245837.666926127.3856836
82가평군황토집20210514영업<NA>1<NA>숙박업(생활)0경기도 가평군 청평면 북한강로1636번길 68-10, 1층경기도 가평군 청평면 삼회리 492-11 ,1층1245837.666929127.388126
114구리시담스모텔20041015영업<NA>25<NA>여관업0경기도 구리시 안골로97번길 17-14 (수택동)경기도 구리시 수택동 419-291192837.598448127.141146