Overview

Dataset statistics

Number of variables47
Number of observations2201
Missing cells1822
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory816.9 KiB
Average record size in memory380.1 B

Variable types

Numeric4
Text10
Categorical30
DateTime1
Boolean2

Alerts

opnsvcid has constant value ""Constant
last_load_dttm has constant value ""Constant
clgstdt is highly imbalanced (51.0%)Imbalance
clgenddt is highly imbalanced (51.0%)Imbalance
ropnymd is highly imbalanced (51.0%)Imbalance
maneipcnt is highly imbalanced (71.9%)Imbalance
multusnupsoyn is highly imbalanced (64.3%)Imbalance
wmeipcnt is highly imbalanced (70.3%)Imbalance
cndpermstymd is highly imbalanced (75.0%)Imbalance
cndpermntwhy is highly imbalanced (68.7%)Imbalance
cndpermendymd is highly imbalanced (75.0%)Imbalance
rdnwhladdr has 623 (28.3%) missing valuesMissing
dcbymd has 1002 (45.5%) missing valuesMissing
x has 81 (3.7%) missing valuesMissing
y has 81 (3.7%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 08:11:37.886956
Analysis finished2024-04-16 08:11:38.990531
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct2201
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1103.0009
Minimum3
Maximum2204
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.5 KiB
2024-04-16T17:11:39.046623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile113
Q1553
median1103
Q31653
95-th percentile2093
Maximum2204
Range2201
Interquartile range (IQR)1100

Descriptive statistics

Standard deviation635.51987
Coefficient of variation (CV)0.57617347
Kurtosis-1.1999881
Mean1103.0009
Median Absolute Deviation (MAD)550
Skewness8.5749531 × 10-6
Sum2427705
Variance403885.5
MonotonicityNot monotonic
2024-04-16T17:11:39.145334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 1
 
< 0.1%
1474 1
 
< 0.1%
1468 1
 
< 0.1%
1469 1
 
< 0.1%
1470 1
 
< 0.1%
1471 1
 
< 0.1%
1472 1
 
< 0.1%
1473 1
 
< 0.1%
1475 1
 
< 0.1%
1449 1
 
< 0.1%
Other values (2191) 2191
99.5%
ValueCountFrequency (%)
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
ValueCountFrequency (%)
2204 1
< 0.1%
2203 1
< 0.1%
2201 1
< 0.1%
2200 1
< 0.1%
2199 1
< 0.1%
2198 1
< 0.1%
2197 1
< 0.1%
2196 1
< 0.1%
2195 1
< 0.1%
2194 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct151
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3518614.9
Minimum3010000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.5 KiB
2024-04-16T17:11:39.253790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3010000
5-th percentile3250000
Q13290000
median3330000
Q33380000
95-th percentile4970000
Maximum6520000
Range3510000
Interquartile range (IQR)90000

Descriptive statistics

Standard deviation571064.34
Coefficient of variation (CV)0.16229805
Kurtosis8.7398987
Mean3518614.9
Median Absolute Deviation (MAD)40000
Skewness3.0093007
Sum7.7444715 × 109
Variance3.2611448 × 1011
MonotonicityNot monotonic
2024-04-16T17:11:39.367372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3290000 221
 
10.0%
3340000 171
 
7.8%
3300000 164
 
7.5%
3330000 159
 
7.2%
3310000 148
 
6.7%
3370000 131
 
6.0%
3320000 123
 
5.6%
3350000 116
 
5.3%
3380000 112
 
5.1%
3390000 93
 
4.2%
Other values (141) 763
34.7%
ValueCountFrequency (%)
3010000 8
0.4%
3020000 1
 
< 0.1%
3030000 1
 
< 0.1%
3040000 4
0.2%
3050000 1
 
< 0.1%
3070000 1
 
< 0.1%
3100000 5
0.2%
3110000 1
 
< 0.1%
3120000 1
 
< 0.1%
3150000 6
0.3%
ValueCountFrequency (%)
6520000 9
0.4%
6510000 7
 
0.3%
5710000 1
 
< 0.1%
5690000 1
 
< 0.1%
5680000 1
 
< 0.1%
5670000 6
 
0.3%
5600000 1
 
< 0.1%
5540000 1
 
< 0.1%
5530000 19
0.9%
5480000 8
0.4%

mgtno
Text

Distinct2085
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
2024-04-16T17:11:39.549688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters48422
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

Unique2020 ?
Unique (%)91.8%

Sample

1st row3250000-202-2002-00001
2nd row3250000-202-1985-00156
3rd row3250000-202-2001-00013
4th row3250000-202-2007-00001
5th row3250000-202-1988-00159
ValueCountFrequency (%)
5530000-202-2020-00001 4
 
0.2%
5530000-202-2020-00004 4
 
0.2%
3280000-202-2020-00001 3
 
0.1%
4970000-202-2019-00001 3
 
0.1%
3410000-202-2019-00001 3
 
0.1%
4060000-202-2018-00002 3
 
0.1%
4810000-202-2019-00003 3
 
0.1%
5440000-202-2020-00001 3
 
0.1%
3600000-202-2019-00001 3
 
0.1%
4010000-202-2018-00001 3
 
0.1%
Other values (2075) 2169
98.5%
2024-04-16T17:11:39.818666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19456
40.2%
2 7132
 
14.7%
- 6603
 
13.6%
3 4179
 
8.6%
1 3353
 
6.9%
9 2773
 
5.7%
8 1273
 
2.6%
4 1159
 
2.4%
5 920
 
1.9%
7 889
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41819
86.4%
Dash Punctuation 6603
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19456
46.5%
2 7132
 
17.1%
3 4179
 
10.0%
1 3353
 
8.0%
9 2773
 
6.6%
8 1273
 
3.0%
4 1159
 
2.8%
5 920
 
2.2%
7 889
 
2.1%
6 685
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 6603
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48422
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19456
40.2%
2 7132
 
14.7%
- 6603
 
13.6%
3 4179
 
8.6%
1 3353
 
6.9%
9 2773
 
5.7%
8 1273
 
2.6%
4 1159
 
2.4%
5 920
 
1.9%
7 889
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19456
40.2%
2 7132
 
14.7%
- 6603
 
13.6%
3 4179
 
8.6%
1 3353
 
6.9%
9 2773
 
5.7%
8 1273
 
2.6%
4 1159
 
2.4%
5 920
 
1.9%
7 889
 
1.8%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
11_44_01_P
2201 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11_44_01_P
2nd row11_44_01_P
3rd row11_44_01_P
4th row11_44_01_P
5th row11_44_01_P

Common Values

ValueCountFrequency (%)
11_44_01_P 2201
100.0%

Length

2024-04-16T17:11:39.924896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:40.012644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 2201
100.0%

updategbn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
I
1728 
U
473 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1728
78.5%
U 473
 
21.5%

Length

2024-04-16T17:11:40.084064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:40.160851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1728
78.5%
u 473
 
21.5%

updatedt
Date

Distinct362
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-31 02:40:00
2024-04-16T17:11:40.244850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T17:11:40.348983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1537 
목욕장업
664 

Length

Max length4
Median length4
Mean length4
Min length4

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> 1537
69.8%
목욕장업 664
30.2%

Length

2024-04-16T17:11:40.446031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:40.734448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1537
69.8%
목욕장업 664
30.2%

bplcnm
Text

Distinct1406
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
2024-04-16T17:11:40.953441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length3
Mean length4.7701045
Min length2

Characters and Unicode

Total characters10499
Distinct characters466
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1097 ?
Unique (%)49.8%

Sample

1st row옥샘탕
2nd row금수탕
3rd row백록담
4th row유나목욕탕
5th row녹수탕
ValueCountFrequency (%)
사우나 41
 
1.6%
목욕탕 22
 
0.9%
현대탕 21
 
0.8%
청수탕 21
 
0.8%
찜질방 20
 
0.8%
옥천탕 19
 
0.8%
산수탕 15
 
0.6%
천수탕 15
 
0.6%
장수탕 14
 
0.6%
평화탕 13
 
0.5%
Other values (1508) 2312
92.0%
2024-04-16T17:11:41.297931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 1414
 
13.5%
수 339
 
3.2%
313
 
3.0%
우 310
 
3.0%
사 298
 
2.8%
나 294
 
2.8%
천 262
 
2.5%
스 217
 
2.1%
대 195
 
1.9%
목 162
 
1.5%
Other values (456) 6695
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9908
94.4%
Space Separator 313
 
3.0%
Close Punctuation 75
 
0.7%
Uppercase Letter 75
 
0.7%
Open Punctuation 72
 
0.7%
Decimal Number 38
 
0.4%
Lowercase Letter 11
 
0.1%
Other Punctuation 5
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 1414
 
14.3%
수 339
 
3.4%
우 310
 
3.1%
사 298
 
3.0%
나 294
 
3.0%
천 262
 
2.6%
스 217
 
2.2%
대 195
 
2.0%
목 162
 
1.6%
성 144
 
1.5%
Other values (414) 6273
63.3%
Uppercase Letter
ValueCountFrequency (%)
G 10
13.3%
S 7
 
9.3%
A 7
 
9.3%
T 5
 
6.7%
L 5
 
6.7%
E 5
 
6.7%
M 4
 
5.3%
U 4
 
5.3%
H 3
 
4.0%
O 3
 
4.0%
Other values (12) 22
29.3%
Lowercase Letter
ValueCountFrequency (%)
o 4
36.4%
n 2
18.2%
p 1
 
9.1%
a 1
 
9.1%
d 1
 
9.1%
u 1
 
9.1%
r 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
2 18
47.4%
4 16
42.1%
5 2
 
5.3%
6 1
 
2.6%
3 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 2
40.0%
· 1
20.0%
& 1
20.0%
, 1
20.0%
Space Separator
ValueCountFrequency (%)
313
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Open Punctuation
ValueCountFrequency (%)
( 72
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9905
94.3%
Common 505
 
4.8%
Latin 86
 
0.8%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 1414
 
14.3%
수 339
 
3.4%
우 310
 
3.1%
사 298
 
3.0%
나 294
 
3.0%
천 262
 
2.6%
스 217
 
2.2%
대 195
 
2.0%
목 162
 
1.6%
성 144
 
1.5%
Other values (412) 6270
63.3%
Latin
ValueCountFrequency (%)
G 10
 
11.6%
S 7
 
8.1%
A 7
 
8.1%
T 5
 
5.8%
L 5
 
5.8%
E 5
 
5.8%
M 4
 
4.7%
U 4
 
4.7%
o 4
 
4.7%
H 3
 
3.5%
Other values (19) 32
37.2%
Common
ValueCountFrequency (%)
313
62.0%
) 75
 
14.9%
( 72
 
14.3%
2 18
 
3.6%
4 16
 
3.2%
5 2
 
0.4%
- 2
 
0.4%
. 2
 
0.4%
· 1
 
0.2%
& 1
 
0.2%
Other values (3) 3
 
0.6%
Han
ValueCountFrequency (%)
溫 2
66.7%
愛 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9905
94.3%
ASCII 590
 
5.6%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 1414
 
14.3%
수 339
 
3.4%
우 310
 
3.1%
사 298
 
3.0%
나 294
 
3.0%
천 262
 
2.6%
스 217
 
2.2%
대 195
 
2.0%
목 162
 
1.6%
성 144
 
1.5%
Other values (412) 6270
63.3%
ASCII
ValueCountFrequency (%)
313
53.1%
) 75
 
12.7%
( 72
 
12.2%
2 18
 
3.1%
4 16
 
2.7%
G 10
 
1.7%
S 7
 
1.2%
A 7
 
1.2%
T 5
 
0.8%
L 5
 
0.8%
Other values (31) 62
 
10.5%
CJK
ValueCountFrequency (%)
溫 2
66.7%
愛 1
33.3%
None
ValueCountFrequency (%)
· 1
100.0%

sitepostno
Text

Distinct887
Distinct (%)40.4%
Missing7
Missing (%)0.3%
Memory size17.3 KiB
2024-04-16T17:11:41.588562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters13164
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique386 ?
Unique (%)17.6%

Sample

1st row600051
2nd row600816
3rd row600091
4th row600061
5th row600062
ValueCountFrequency (%)
604851 15
 
0.7%
612846 12
 
0.5%
612847 12
 
0.5%
614822 10
 
0.5%
608828 10
 
0.5%
607833 10
 
0.5%
608808 10
 
0.5%
607832 9
 
0.4%
607831 9
 
0.4%
613805 9
 
0.4%
Other values (877) 2088
95.2%
2024-04-16T17:11:41.957300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 2397
18.2%
8 2258
17.2%
0 2079
15.8%
1 1974
15.0%
2 1047
8.0%
4 948
 
7.2%
3 801
 
6.1%
7 618
 
4.7%
5 523
 
4.0%
9 477
 
3.6%
Other values (5) 42
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13122
99.7%
Other Letter 42
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 2397
18.3%
8 2258
17.2%
0 2079
15.8%
1 1974
15.0%
2 1047
8.0%
4 948
 
7.2%
3 801
 
6.1%
7 618
 
4.7%
5 523
 
4.0%
9 477
 
3.6%
Other Letter
ValueCountFrequency (%)
번 14
33.3%
지 7
16.7%
우 7
16.7%
편 7
16.7%
호 7
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 13122
99.7%
Hangul 42
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
6 2397
18.3%
8 2258
17.2%
0 2079
15.8%
1 1974
15.0%
2 1047
8.0%
4 948
 
7.2%
3 801
 
6.1%
7 618
 
4.7%
5 523
 
4.0%
9 477
 
3.6%
Hangul
ValueCountFrequency (%)
번 14
33.3%
지 7
16.7%
우 7
16.7%
편 7
16.7%
호 7
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13122
99.7%
Hangul 42
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 2397
18.3%
8 2258
17.2%
0 2079
15.8%
1 1974
15.0%
2 1047
8.0%
4 948
 
7.2%
3 801
 
6.1%
7 618
 
4.7%
5 523
 
4.0%
9 477
 
3.6%
Hangul
ValueCountFrequency (%)
번 14
33.3%
지 7
16.7%
우 7
16.7%
편 7
16.7%
호 7
16.7%

sitewhladdr
Text

Distinct2003
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
2024-04-16T17:11:42.246220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length50
Mean length25.054521
Min length16

Characters and Unicode

Total characters55145
Distinct characters412
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1870 ?
Unique (%)85.0%

Sample

1st row부산광역시 중구 창선동1가 9-9번지
2nd row부산광역시 중구 중앙동4가 78-2번지
3rd row부산광역시 중구 대청동1가 34-1번지
4th row부산광역시 중구 신창동1가 5-1번지 (5~8층)
5th row부산광역시 중구 신창동2가 21-2번지
ValueCountFrequency (%)
부산광역시 1815
 
17.9%
t통b반 335
 
3.3%
부산진구 221
 
2.2%
사하구 171
 
1.7%
동래구 164
 
1.6%
해운대구 159
 
1.6%
남구 154
 
1.5%
연제구 131
 
1.3%
북구 130
 
1.3%
금정구 116
 
1.1%
Other values (3094) 6766
66.6%
2024-04-16T17:11:42.636682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10118
 
18.3%
동 2396
 
4.3%
1 2334
 
4.2%
산 2233
 
4.0%
부 2187
 
4.0%
시 2133
 
3.9%
지 2043
 
3.7%
구 1996
 
3.6%
광 1977
 
3.6%
- 1972
 
3.6%
Other values (402) 25756
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31336
56.8%
Decimal Number 10692
 
19.4%
Space Separator 10118
 
18.3%
Dash Punctuation 1972
 
3.6%
Uppercase Letter 714
 
1.3%
Other Punctuation 159
 
0.3%
Open Punctuation 66
 
0.1%
Close Punctuation 66
 
0.1%
Math Symbol 11
 
< 0.1%
Lowercase Letter 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2396
 
7.6%
산 2233
 
7.1%
부 2187
 
7.0%
시 2133
 
6.8%
지 2043
 
6.5%
구 1996
 
6.4%
광 1977
 
6.3%
번 1903
 
6.1%
역 1875
 
6.0%
남 403
 
1.3%
Other values (364) 12190
38.9%
Uppercase Letter
ValueCountFrequency (%)
B 349
48.9%
T 336
47.1%
I 7
 
1.0%
S 4
 
0.6%
A 3
 
0.4%
Y 3
 
0.4%
V 3
 
0.4%
G 2
 
0.3%
L 2
 
0.3%
C 2
 
0.3%
Other values (3) 3
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 2334
21.8%
2 1412
13.2%
3 1174
11.0%
4 1070
10.0%
5 995
9.3%
6 819
 
7.7%
0 780
 
7.3%
7 758
 
7.1%
8 710
 
6.6%
9 640
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
a 3
30.0%
p 3
30.0%
e 1
 
10.0%
w 1
 
10.0%
o 1
 
10.0%
r 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 155
97.5%
. 3
 
1.9%
@ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
10118
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1972
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31336
56.8%
Common 23084
41.9%
Latin 725
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2396
 
7.6%
산 2233
 
7.1%
부 2187
 
7.0%
시 2133
 
6.8%
지 2043
 
6.5%
구 1996
 
6.4%
광 1977
 
6.3%
번 1903
 
6.1%
역 1875
 
6.0%
남 403
 
1.3%
Other values (364) 12190
38.9%
Latin
ValueCountFrequency (%)
B 349
48.1%
T 336
46.3%
I 7
 
1.0%
S 4
 
0.6%
A 3
 
0.4%
a 3
 
0.4%
p 3
 
0.4%
Y 3
 
0.4%
V 3
 
0.4%
G 2
 
0.3%
Other values (10) 12
 
1.7%
Common
ValueCountFrequency (%)
10118
43.8%
1 2334
 
10.1%
- 1972
 
8.5%
2 1412
 
6.1%
3 1174
 
5.1%
4 1070
 
4.6%
5 995
 
4.3%
6 819
 
3.5%
0 780
 
3.4%
7 758
 
3.3%
Other values (8) 1652
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31336
56.8%
ASCII 23808
43.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10118
42.5%
1 2334
 
9.8%
- 1972
 
8.3%
2 1412
 
5.9%
3 1174
 
4.9%
4 1070
 
4.5%
5 995
 
4.2%
6 819
 
3.4%
0 780
 
3.3%
7 758
 
3.2%
Other values (27) 2376
 
10.0%
Hangul
ValueCountFrequency (%)
동 2396
 
7.6%
산 2233
 
7.1%
부 2187
 
7.0%
시 2133
 
6.8%
지 2043
 
6.5%
구 1996
 
6.4%
광 1977
 
6.3%
번 1903
 
6.1%
역 1875
 
6.0%
남 403
 
1.3%
Other values (364) 12190
38.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

rdnpostno
Text

Distinct1136
Distinct (%)51.7%
Missing4
Missing (%)0.2%
Memory size17.3 KiB
2024-04-16T17:11:42.889889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0018207
Min length5

Characters and Unicode

Total characters10989
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique875 ?
Unique (%)39.8%

Sample

1st row48947
2nd row48947
3rd row48947
4th row48948
5th row48947
ValueCountFrequency (%)
48947 679
30.9%
47709 8
 
0.4%
18606 8
 
0.4%
48099 8
 
0.4%
47248 5
 
0.2%
46327 5
 
0.2%
49014 4
 
0.2%
47142 4
 
0.2%
48531 4
 
0.2%
48053 4
 
0.2%
Other values (1126) 1468
66.8%
2024-04-16T17:11:43.236665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2994
27.2%
7 1460
13.3%
8 1451
13.2%
9 1253
11.4%
6 675
 
6.1%
0 667
 
6.1%
5 659
 
6.0%
2 636
 
5.8%
1 614
 
5.6%
3 566
 
5.2%
Other values (7) 14
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10975
99.9%
Other Letter 14
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 2994
27.3%
7 1460
13.3%
8 1451
13.2%
9 1253
11.4%
6 675
 
6.2%
0 667
 
6.1%
5 659
 
6.0%
2 636
 
5.8%
1 614
 
5.6%
3 566
 
5.2%
Other Letter
ValueCountFrequency (%)
도 2
14.3%
로 2
14.3%
명 2
14.3%
우 2
14.3%
편 2
14.3%
번 2
14.3%
호 2
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 10975
99.9%
Hangul 14
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 2994
27.3%
7 1460
13.3%
8 1451
13.2%
9 1253
11.4%
6 675
 
6.2%
0 667
 
6.1%
5 659
 
6.0%
2 636
 
5.8%
1 614
 
5.6%
3 566
 
5.2%
Hangul
ValueCountFrequency (%)
도 2
14.3%
로 2
14.3%
명 2
14.3%
우 2
14.3%
편 2
14.3%
번 2
14.3%
호 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10975
99.9%
Hangul 14
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2994
27.3%
7 1460
13.3%
8 1451
13.2%
9 1253
11.4%
6 675
 
6.2%
0 667
 
6.1%
5 659
 
6.0%
2 636
 
5.8%
1 614
 
5.6%
3 566
 
5.2%
Hangul
ValueCountFrequency (%)
도 2
14.3%
로 2
14.3%
명 2
14.3%
우 2
14.3%
편 2
14.3%
번 2
14.3%
호 2
14.3%

rdnwhladdr
Text

MISSING 

Distinct1447
Distinct (%)91.7%
Missing623
Missing (%)28.3%
Memory size17.3 KiB
2024-04-16T17:11:43.529207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length54
Mean length28.606464
Min length5

Characters and Unicode

Total characters45141
Distinct characters462
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

Unique1369 ?
Unique (%)86.8%

Sample

1st row부산광역시 중구 광복로55번길 14-2 (창선동1가)
2nd row부산광역시 중구 광복중앙로 25 (신창동1가)
3rd row부산광역시 중구 광복로43번길 12 (신창동2가)
4th row부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)
5th row부산광역시 중구 비프광장로 20, 10층 (남포동6가)
ValueCountFrequency (%)
부산광역시 1197
 
13.7%
부산진구 153
 
1.7%
남구 110
 
1.3%
해운대구 103
 
1.2%
사하구 100
 
1.1%
동래구 99
 
1.1%
연제구 85
 
1.0%
북구 82
 
0.9%
금정구 77
 
0.9%
경기도 77
 
0.9%
Other values (2692) 6676
76.2%
2024-04-16T17:11:43.942785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7186
 
15.9%
동 1848
 
4.1%
1 1651
 
3.7%
시 1558
 
3.5%
산 1528
 
3.4%
부 1492
 
3.3%
로 1471
 
3.3%
( 1411
 
3.1%
) 1411
 
3.1%
구 1401
 
3.1%
Other values (452) 24184
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26965
59.7%
Space Separator 7186
 
15.9%
Decimal Number 7050
 
15.6%
Open Punctuation 1414
 
3.1%
Close Punctuation 1414
 
3.1%
Other Punctuation 732
 
1.6%
Dash Punctuation 298
 
0.7%
Uppercase Letter 45
 
0.1%
Math Symbol 32
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1848
 
6.9%
시 1558
 
5.8%
산 1528
 
5.7%
부 1492
 
5.5%
로 1471
 
5.5%
구 1401
 
5.2%
광 1365
 
5.1%
역 1261
 
4.7%
길 885
 
3.3%
번 734
 
2.7%
Other values (413) 13422
49.8%
Uppercase Letter
ValueCountFrequency (%)
B 26
57.8%
A 5
 
11.1%
I 4
 
8.9%
G 2
 
4.4%
C 2
 
4.4%
T 1
 
2.2%
L 1
 
2.2%
M 1
 
2.2%
W 1
 
2.2%
K 1
 
2.2%
Decimal Number
ValueCountFrequency (%)
1 1651
23.4%
2 1068
15.1%
3 864
12.3%
0 590
 
8.4%
5 585
 
8.3%
4 540
 
7.7%
6 514
 
7.3%
7 467
 
6.6%
9 396
 
5.6%
8 375
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 721
98.5%
. 6
 
0.8%
* 3
 
0.4%
@ 1
 
0.1%
& 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
r 1
25.0%
e 1
25.0%
w 1
25.0%
o 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 1411
99.8%
[ 3
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 1411
99.8%
] 3
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 31
96.9%
～ 1
 
3.1%
Space Separator
ValueCountFrequency (%)
7186
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 298
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26965
59.7%
Common 18126
40.2%
Latin 50
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1848
 
6.9%
시 1558
 
5.8%
산 1528
 
5.7%
부 1492
 
5.5%
로 1471
 
5.5%
구 1401
 
5.2%
광 1365
 
5.1%
역 1261
 
4.7%
길 885
 
3.3%
번 734
 
2.7%
Other values (413) 13422
49.8%
Common
ValueCountFrequency (%)
7186
39.6%
1 1651
 
9.1%
( 1411
 
7.8%
) 1411
 
7.8%
2 1068
 
5.9%
3 864
 
4.8%
, 721
 
4.0%
0 590
 
3.3%
5 585
 
3.2%
4 540
 
3.0%
Other values (13) 2099
 
11.6%
Latin
ValueCountFrequency (%)
B 26
52.0%
A 5
 
10.0%
I 4
 
8.0%
G 2
 
4.0%
C 2
 
4.0%
r 1
 
2.0%
e 1
 
2.0%
w 1
 
2.0%
o 1
 
2.0%
T 1
 
2.0%
Other values (6) 6
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26965
59.7%
ASCII 18174
40.3%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7186
39.5%
1 1651
 
9.1%
( 1411
 
7.8%
) 1411
 
7.8%
2 1068
 
5.9%
3 864
 
4.8%
, 721
 
4.0%
0 590
 
3.2%
5 585
 
3.2%
4 540
 
3.0%
Other values (27) 2147
 
11.8%
Hangul
ValueCountFrequency (%)
동 1848
 
6.9%
시 1558
 
5.8%
산 1528
 
5.7%
부 1492
 
5.5%
로 1471
 
5.5%
구 1401
 
5.2%
광 1365
 
5.1%
역 1261
 
4.7%
길 885
 
3.3%
번 734
 
2.7%
Other values (413) 13422
49.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
None
ValueCountFrequency (%)
～ 1
100.0%

apvpermymd
Real number (ℝ)

Distinct1717
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19959797
Minimum19540131
Maximum20210129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.5 KiB
2024-04-16T17:11:44.057336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19540131
5-th percentile19701026
Q119840925
median19950204
Q320061128
95-th percentile20200514
Maximum20210129
Range669998
Interquartile range (IQR)220203

Descriptive statistics

Standard deviation155496.95
Coefficient of variation (CV)0.0077905077
Kurtosis-0.87817002
Mean19959797
Median Absolute Deviation (MAD)109603
Skewness0.054010815
Sum4.3931513 × 1010
Variance2.4179303 × 1010
MonotonicityNot monotonic
2024-04-16T17:11:44.164531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190201 15
 
0.7%
19630110 15
 
0.7%
20201231 10
 
0.5%
20191101 9
 
0.4%
20001130 9
 
0.4%
19921202 8
 
0.4%
20200207 7
 
0.3%
20200619 6
 
0.3%
20190308 6
 
0.3%
19960710 6
 
0.3%
Other values (1707) 2110
95.9%
ValueCountFrequency (%)
19540131 1
 
< 0.1%
19601210 3
 
0.1%
19630108 1
 
< 0.1%
19630109 3
 
0.1%
19630110 15
0.7%
19630610 4
 
0.2%
19631001 1
 
< 0.1%
19640211 1
 
< 0.1%
19640915 1
 
< 0.1%
19641015 1
 
< 0.1%
ValueCountFrequency (%)
20210129 2
0.1%
20210125 1
< 0.1%
20210119 2
0.1%
20210118 1
< 0.1%
20210115 2
0.1%
20210112 1
< 0.1%
20210107 2
0.1%
20210106 1
< 0.1%
20210105 1
< 0.1%
20210104 1
< 0.1%

dcbymd
Text

MISSING 

Distinct819
Distinct (%)68.3%
Missing1002
Missing (%)45.5%
Memory size17.3 KiB
2024-04-16T17:11:44.392963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.2627189
Min length4

Characters and Unicode

Total characters8708
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique704 ?
Unique (%)58.7%

Sample

1st row20070612
2nd row20120221
3rd row20140401
4th row20131227
5th row20030703
ValueCountFrequency (%)
폐업일자 221
 
18.4%
20050121 12
 
1.0%
20051017 7
 
0.6%
20001130 7
 
0.6%
20030401 5
 
0.4%
20170310 5
 
0.4%
20030122 4
 
0.3%
20141030 4
 
0.3%
20120621 4
 
0.3%
20090731 3
 
0.3%
Other values (809) 927
77.3%
2024-04-16T17:11:44.739240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2646
30.4%
2 1618
18.6%
1 1420
16.3%
9 363
 
4.2%
3 349
 
4.0%
7 306
 
3.5%
5 294
 
3.4%
6 283
 
3.2%
8 277
 
3.2%
4 268
 
3.1%
Other values (4) 884
 
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7824
89.8%
Other Letter 884
 
10.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2646
33.8%
2 1618
20.7%
1 1420
18.1%
9 363
 
4.6%
3 349
 
4.5%
7 306
 
3.9%
5 294
 
3.8%
6 283
 
3.6%
8 277
 
3.5%
4 268
 
3.4%
Other Letter
ValueCountFrequency (%)
폐 221
25.0%
업 221
25.0%
일 221
25.0%
자 221
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7824
89.8%
Hangul 884
 
10.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2646
33.8%
2 1618
20.7%
1 1420
18.1%
9 363
 
4.6%
3 349
 
4.5%
7 306
 
3.9%
5 294
 
3.8%
6 283
 
3.6%
8 277
 
3.5%
4 268
 
3.4%
Hangul
ValueCountFrequency (%)
폐 221
25.0%
업 221
25.0%
일 221
25.0%
자 221
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7824
89.8%
Hangul 884
 
10.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2646
33.8%
2 1618
20.7%
1 1420
18.1%
9 363
 
4.6%
3 349
 
4.5%
7 306
 
3.9%
5 294
 
3.8%
6 283
 
3.6%
8 277
 
3.5%
4 268
 
3.4%
Hangul
ValueCountFrequency (%)
폐 221
25.0%
업 221
25.0%
일 221
25.0%
자 221
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1966 
휴업시작일자
235 

Length

Max length6
Median length4
Mean length4.2135393
Min length4

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> 1966
89.3%
휴업시작일자 235
 
10.7%

Length

2024-04-16T17:11:44.858148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:44.949808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1966
89.3%
휴업시작일자 235
 
10.7%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1966 
휴업종료일자
235 

Length

Max length6
Median length4
Mean length4.2135393
Min length4

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> 1966
89.3%
휴업종료일자 235
 
10.7%

Length

2024-04-16T17:11:45.059632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:45.150867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1966
89.3%
휴업종료일자 235
 
10.7%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1966 
재개업일자
235 

Length

Max length5
Median length4
Mean length4.1067697
Min length4

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> 1966
89.3%
재개업일자 235
 
10.7%

Length

2024-04-16T17:11:45.256097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:45.356488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1966
89.3%
재개업일자 235
 
10.7%

trdstatenm
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
02
925 
01
612 
영업/정상
605 
폐업
 
53
영업상태
 
4

Length

Max length5
Median length2
Mean length2.8300772
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01
2nd row02
3rd row02
4th row02
5th row01

Common Values

ValueCountFrequency (%)
02 925
42.0%
01 612
27.8%
영업/정상 605
27.5%
폐업 53
 
2.4%
영업상태 4
 
0.2%
<NA> 2
 
0.1%

Length

2024-04-16T17:11:45.468009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:45.571492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 925
42.0%
01 612
27.8%
영업/정상 605
27.5%
폐업 53
 
2.4%
영업상태 4
 
0.2%
na 2
 
0.1%

dtlstatenm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
영업
1223 
폐업
978 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 1223
55.6%
폐업 978
44.4%

Length

2024-04-16T17:11:45.666669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:45.740407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 1223
55.6%
폐업 978
44.4%

x
Text

MISSING 

Distinct1931
Distinct (%)91.1%
Missing81
Missing (%)3.7%
Memory size17.3 KiB
2024-04-16T17:11:45.916014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.932547
Min length7

Characters and Unicode

Total characters42257
Distinct characters19
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

Unique1815 ?
Unique (%)85.6%

Sample

1st row385089.38491100000
2nd row385793.29931
3rd row385208.257554
4th row385157.86566400000
5th row385086.62014400000
ValueCountFrequency (%)
좌표정보(x 11
 
0.5%
192190.585454696 8
 
0.4%
144766.399755 4
 
0.2%
390974.056399381 4
 
0.2%
175185.261058397 4
 
0.2%
210858.16481015 4
 
0.2%
389394.976154 4
 
0.2%
389727.58350700000 4
 
0.2%
387810.283167969 4
 
0.2%
175563.262537041 3
 
0.1%
Other values (1921) 2070
97.6%
2024-04-16T17:11:46.218098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8715
20.6%
0 6835
16.2%
3 3993
9.4%
8 3352
 
7.9%
9 2973
 
7.0%
1 2461
 
5.8%
7 2425
 
5.7%
2 2419
 
5.7%
4 2332
 
5.5%
6 2287
 
5.4%
Other values (9) 4465
10.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31361
74.2%
Space Separator 8715
 
20.6%
Other Punctuation 2104
 
5.0%
Other Letter 44
 
0.1%
Close Punctuation 11
 
< 0.1%
Uppercase Letter 11
 
< 0.1%
Open Punctuation 11
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6835
21.8%
3 3993
12.7%
8 3352
10.7%
9 2973
9.5%
1 2461
 
7.8%
7 2425
 
7.7%
2 2419
 
7.7%
4 2332
 
7.4%
6 2287
 
7.3%
5 2284
 
7.3%
Other Letter
ValueCountFrequency (%)
표 11
25.0%
보 11
25.0%
정 11
25.0%
좌 11
25.0%
Space Separator
ValueCountFrequency (%)
8715
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2104
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42202
99.9%
Hangul 44
 
0.1%
Latin 11
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
8715
20.7%
0 6835
16.2%
3 3993
9.5%
8 3352
 
7.9%
9 2973
 
7.0%
1 2461
 
5.8%
7 2425
 
5.7%
2 2419
 
5.7%
4 2332
 
5.5%
6 2287
 
5.4%
Other values (4) 4410
10.4%
Hangul
ValueCountFrequency (%)
표 11
25.0%
보 11
25.0%
정 11
25.0%
좌 11
25.0%
Latin
ValueCountFrequency (%)
X 11
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42213
99.9%
Hangul 44
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8715
20.6%
0 6835
16.2%
3 3993
9.5%
8 3352
 
7.9%
9 2973
 
7.0%
1 2461
 
5.8%
7 2425
 
5.7%
2 2419
 
5.7%
4 2332
 
5.5%
6 2287
 
5.4%
Other values (5) 4421
10.5%
Hangul
ValueCountFrequency (%)
표 11
25.0%
보 11
25.0%
정 11
25.0%
좌 11
25.0%

y
Text

MISSING 

Distinct1931
Distinct (%)91.1%
Missing81
Missing (%)3.7%
Memory size17.3 KiB
2024-04-16T17:11:46.412328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.932547
Min length7

Characters and Unicode

Total characters42257
Distinct characters21
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1815 ?
Unique (%)85.6%

Sample

1st row180062.56761800000
2nd row180910.386636
3rd row180108.034984
4th row180248.21457300000
5th row180119.33406400000
ValueCountFrequency (%)
좌표정보(y 11
 
0.5%
401648.714565483 8
 
0.4%
144689.635335 4
 
0.2%
182797.894969615 4
 
0.2%
427812.896240081 4
 
0.2%
411413.605240051 4
 
0.2%
193519.152183 4
 
0.2%
191654.34294400000 4
 
0.2%
179178.742589729 4
 
0.2%
429343.513466697 3
 
0.1%
Other values (1921) 2070
97.6%
2024-04-16T17:11:46.707320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8682
20.5%
0 6787
16.1%
1 4088
9.7%
8 3286
 
7.8%
9 2882
 
6.8%
7 2709
 
6.4%
4 2494
 
5.9%
6 2315
 
5.5%
3 2298
 
5.4%
2 2290
 
5.4%
Other values (11) 4426
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31377
74.3%
Space Separator 8682
 
20.5%
Other Punctuation 2104
 
5.0%
Other Letter 44
 
0.1%
Dash Punctuation 15
 
< 0.1%
Close Punctuation 13
 
< 0.1%
Uppercase Letter 11
 
< 0.1%
Open Punctuation 11
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6787
21.6%
1 4088
13.0%
8 3286
10.5%
9 2882
9.2%
7 2709
 
8.6%
4 2494
 
7.9%
6 2315
 
7.4%
3 2298
 
7.3%
2 2290
 
7.3%
5 2228
 
7.1%
Other Letter
ValueCountFrequency (%)
좌 11
25.0%
표 11
25.0%
보 11
25.0%
정 11
25.0%
Close Punctuation
ValueCountFrequency (%)
) 11
84.6%
] 2
 
15.4%
Space Separator
ValueCountFrequency (%)
8682
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42202
99.9%
Hangul 44
 
0.1%
Latin 11
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
8682
20.6%
0 6787
16.1%
1 4088
9.7%
8 3286
 
7.8%
9 2882
 
6.8%
7 2709
 
6.4%
4 2494
 
5.9%
6 2315
 
5.5%
3 2298
 
5.4%
2 2290
 
5.4%
Other values (6) 4371
10.4%
Hangul
ValueCountFrequency (%)
좌 11
25.0%
표 11
25.0%
보 11
25.0%
정 11
25.0%
Latin
ValueCountFrequency (%)
Y 11
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42213
99.9%
Hangul 44
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8682
20.6%
0 6787
16.1%
1 4088
9.7%
8 3286
 
7.8%
9 2882
 
6.8%
7 2709
 
6.4%
4 2494
 
5.9%
6 2315
 
5.5%
3 2298
 
5.4%
2 2290
 
5.4%
Other values (7) 4382
10.4%
Hangul
ValueCountFrequency (%)
좌 11
25.0%
표 11
25.0%
보 11
25.0%
정 11
25.0%

lastmodts
Real number (ℝ)

Distinct1761
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0127397 × 1013
Minimum1.999021 × 1013
Maximum2.0210129 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.5 KiB
2024-04-16T17:11:46.823616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.999021 × 1013
5-th percentile2.0020829 × 1013
Q12.0060228 × 1013
median2.014061 × 1013
Q32.0190607 × 1013
95-th percentile2.020113 × 1013
Maximum2.0210129 × 1013
Range2.1991918 × 1011
Interquartile range (IQR)1.3037913 × 1011

Descriptive statistics

Standard deviation6.6083027 × 1010
Coefficient of variation (CV)0.0032832376
Kurtosis-1.2191358
Mean2.0127397 × 1013
Median Absolute Deviation (MAD)5.0608011 × 1010
Skewness-0.45647235
Sum4.43004 × 1016
Variance4.3669664 × 1021
MonotonicityNot monotonic
2024-04-16T17:11:46.940448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030409000000 29
 
1.3%
20020418000000 27
 
1.2%
20040318000000 16
 
0.7%
20050415000000 14
 
0.6%
20031217000000 12
 
0.5%
20030303000000 12
 
0.5%
20040324000000 11
 
0.5%
20020422000000 10
 
0.5%
20041208000000 9
 
0.4%
20030722000000 8
 
0.4%
Other values (1751) 2053
93.3%
ValueCountFrequency (%)
19990210000000 2
 
0.1%
19990212000000 1
 
< 0.1%
19990302000000 7
0.3%
19990310000000 6
0.3%
19990315000000 1
 
< 0.1%
19990325000000 2
 
0.1%
19990420000000 2
 
0.1%
19990421000000 7
0.3%
19990422000000 1
 
< 0.1%
19990427000000 1
 
< 0.1%
ValueCountFrequency (%)
20210129175409 2
0.1%
20210129150616 1
< 0.1%
20210128145512 1
< 0.1%
20210128104829 1
< 0.1%
20210127141705 1
< 0.1%
20210127100711 1
< 0.1%
20210126165157 1
< 0.1%
20210126164904 1
< 0.1%
20210126163636 1
< 0.1%
20210125160850 1
< 0.1%

uptaenm
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
공동탕업
1700 
목욕장업 기타
221 
공동탕업+찜질시설서비스영업
 
158
찜질시설서비스영업
 
77
한증막업
 
45

Length

Max length14
Median length4
Mean length5.1940027
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공동탕업+찜질시설서비스영업
2nd row한증막업
3rd row공동탕업+찜질시설서비스영업
4th row공동탕업+찜질시설서비스영업
5th row공동탕업

Common Values

ValueCountFrequency (%)
공동탕업 1700
77.2%
목욕장업 기타 221
 
10.0%
공동탕업+찜질시설서비스영업 158
 
7.2%
찜질시설서비스영업 77
 
3.5%
한증막업 45
 
2.0%

Length

2024-04-16T17:11:47.040463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:47.122847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1700
70.2%
목욕장업 221
 
9.1%
기타 221
 
9.1%
공동탕업+찜질시설서비스영업 158
 
6.5%
찜질시설서비스영업 77
 
3.2%
한증막업 45
 
1.9%

sitetel
Text

Distinct127
Distinct (%)5.8%
Missing22
Missing (%)1.0%
Memory size17.3 KiB
2024-04-16T17:11:47.248893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.879761
Min length4

Characters and Unicode

Total characters25886
Distinct characters16
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

Unique117 ?
Unique (%)5.4%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234
ValueCountFrequency (%)
051-123-1234 2017
84.4%
051 61
 
2.6%
전화번호 25
 
1.0%
061 16
 
0.7%
055 11
 
0.5%
031 10
 
0.4%
339 10
 
0.4%
02 5
 
0.2%
052 4
 
0.2%
064 4
 
0.2%
Other values (189) 226
 
9.5%
2024-04-16T17:11:47.486427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6240
24.1%
3 4182
16.2%
2 4135
16.0%
- 4034
15.6%
0 2283
 
8.8%
5 2202
 
8.5%
4 2089
 
8.1%
219
 
0.8%
6 126
 
0.5%
7 107
 
0.4%
Other values (6) 269
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21533
83.2%
Dash Punctuation 4034
 
15.6%
Space Separator 219
 
0.8%
Other Letter 100
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6240
29.0%
3 4182
19.4%
2 4135
19.2%
0 2283
 
10.6%
5 2202
 
10.2%
4 2089
 
9.7%
6 126
 
0.6%
7 107
 
0.5%
9 85
 
0.4%
8 84
 
0.4%
Other Letter
ValueCountFrequency (%)
전 25
25.0%
화 25
25.0%
번 25
25.0%
호 25
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 4034
100.0%
Space Separator
ValueCountFrequency (%)
219
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25786
99.6%
Hangul 100
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6240
24.2%
3 4182
16.2%
2 4135
16.0%
- 4034
15.6%
0 2283
 
8.9%
5 2202
 
8.5%
4 2089
 
8.1%
219
 
0.8%
6 126
 
0.5%
7 107
 
0.4%
Other values (2) 169
 
0.7%
Hangul
ValueCountFrequency (%)
전 25
25.0%
화 25
25.0%
번 25
25.0%
호 25
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25786
99.6%
Hangul 100
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6240
24.2%
3 4182
16.2%
2 4135
16.0%
- 4034
15.6%
0 2283
 
8.9%
5 2202
 
8.5%
4 2089
 
8.1%
219
 
0.8%
6 126
 
0.5%
7 107
 
0.4%
Other values (2) 169
 
0.7%
Hangul
ValueCountFrequency (%)
전 25
25.0%
화 25
25.0%
번 25
25.0%
호 25
25.0%

bdngownsenm
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1519 
자가
345 
임대
178 
건물소유구분명
159 

Length

Max length7
Median length4
Mean length3.7414811
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1519
69.0%
자가 345
 
15.7%
임대 178
 
8.1%
건물소유구분명 159
 
7.2%

Length

2024-04-16T17:11:47.584631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:47.673493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1519
69.0%
자가 345
 
15.7%
임대 178
 
8.1%
건물소유구분명 159
 
7.2%

bdngjisgflrcnt
Categorical

Distinct37
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
0
531 
<NA>
466 
3
331 
4
223 
2
180 
Other values (32)
470 

Length

Max length6
Median length1
Mean length1.6919582
Min length1

Unique

Unique10 ?
Unique (%)0.5%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row9
5th row4

Common Values

ValueCountFrequency (%)
0 531
24.1%
<NA> 466
21.2%
3 331
15.0%
4 223
10.1%
2 180
 
8.2%
5 146
 
6.6%
6 58
 
2.6%
1 55
 
2.5%
7 51
 
2.3%
8 35
 
1.6%
Other values (27) 125
 
5.7%

Length

2024-04-16T17:11:47.768591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 531
24.1%
na 466
21.2%
3 331
15.0%
4 223
10.1%
2 180
 
8.2%
5 146
 
6.6%
6 58
 
2.6%
1 55
 
2.5%
7 51
 
2.3%
8 35
 
1.6%
Other values (27) 125
 
5.7%

bdngunderflrcnt
Categorical

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
0
812 
<NA>
707 
1
508 
2
94 
3
 
32
Other values (5)
 
48

Length

Max length6
Median length1
Mean length1.9795547
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row3
5th row1

Common Values

ValueCountFrequency (%)
0 812
36.9%
<NA> 707
32.1%
1 508
23.1%
2 94
 
4.3%
3 32
 
1.5%
4 21
 
1.0%
5 10
 
0.5%
6 9
 
0.4%
건물지하층수 7
 
0.3%
7 1
 
< 0.1%

Length

2024-04-16T17:11:47.861529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:47.959973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 812
36.9%
na 707
32.1%
1 508
23.1%
2 94
 
4.3%
3 32
 
1.5%
4 21
 
1.0%
5 10
 
0.5%
6 9
 
0.4%
건물지하층수 7
 
0.3%
7 1
 
< 0.1%

maneipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1774 
0
360 
1
 
33
남성종사자수
 
19
2
 
6
Other values (4)
 
9

Length

Max length6
Median length4
Mean length3.461154
Min length1

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> 1774
80.6%
0 360
 
16.4%
1 33
 
1.5%
남성종사자수 19
 
0.9%
2 6
 
0.3%
5 4
 
0.2%
4 2
 
0.1%
3 2
 
0.1%
7 1
 
< 0.1%

Length

2024-04-16T17:11:48.063597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:48.156418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1774
80.6%
0 360
 
16.4%
1 33
 
1.5%
남성종사자수 19
 
0.9%
2 6
 
0.3%
5 4
 
0.2%
4 2
 
0.1%
3 2
 
0.1%
7 1
 
< 0.1%

multusnupsoyn
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
False
2052 
True
 
149
ValueCountFrequency (%)
False 2052
93.2%
True 149
 
6.8%
2024-04-16T17:11:48.254512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

balhansilyn
Boolean

Distinct2
Distinct (%)0.1%
Missing2
Missing (%)0.1%
Memory size4.4 KiB
False
1583 
True
616 
(Missing)
 
2
ValueCountFrequency (%)
False 1583
71.9%
True 616
 
28.0%
(Missing) 2
 
0.1%
2024-04-16T17:11:48.322388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

usejisgendflr
Categorical

Distinct15
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
840 
2
437 
3
235 
0
228 
1
145 
Other values (10)
316 

Length

Max length6
Median length1
Mean length2.3575647
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row8
5th row4

Common Values

ValueCountFrequency (%)
<NA> 840
38.2%
2 437
19.9%
3 235
 
10.7%
0 228
 
10.4%
1 145
 
6.6%
4 93
 
4.2%
사용끝지상층 91
 
4.1%
5 61
 
2.8%
6 26
 
1.2%
7 14
 
0.6%
Other values (5) 31
 
1.4%

Length

2024-04-16T17:11:48.409377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 840
38.2%
2 437
19.9%
3 235
 
10.7%
0 228
 
10.4%
1 145
 
6.6%
4 93
 
4.2%
사용끝지상층 91
 
4.1%
5 61
 
2.8%
6 26
 
1.2%
7 14
 
0.6%
Other values (5) 31
 
1.4%

useunderendflr
Categorical

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1314 
0
595 
사용끝지하층
149 
1
 
104
2
 
34
Other values (2)
 
5

Length

Max length6
Median length4
Mean length3.1294866
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1314
59.7%
0 595
27.0%
사용끝지하층 149
 
6.8%
1 104
 
4.7%
2 34
 
1.5%
3 4
 
0.2%
4 1
 
< 0.1%

Length

2024-04-16T17:11:48.499404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:48.586310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1314
59.7%
0 595
27.0%
사용끝지하층 149
 
6.8%
1 104
 
4.7%
2 34
 
1.5%
3 4
 
0.2%
4 1
 
< 0.1%

usejisgstflr
Categorical

Distinct14
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
689 
1
477 
0
388 
2
359 
3
92 
Other values (9)
196 

Length

Max length7
Median length1
Mean length2.1399364
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row5
5th row2

Common Values

ValueCountFrequency (%)
<NA> 689
31.3%
1 477
21.7%
0 388
17.6%
2 359
16.3%
3 92
 
4.2%
사용시작지상층 72
 
3.3%
4 53
 
2.4%
5 24
 
1.1%
6 17
 
0.8%
10 8
 
0.4%
Other values (4) 22
 
1.0%

Length

2024-04-16T17:11:48.702650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 689
31.3%
1 477
21.7%
0 388
17.6%
2 359
16.3%
3 92
 
4.2%
사용시작지상층 72
 
3.3%
4 53
 
2.4%
5 24
 
1.1%
6 17
 
0.8%
10 8
 
0.4%
Other values (4) 22
 
1.0%

useunderstflr
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1049 
0
855 
사용시작지하층
142 
1
134 
2
 
17

Length

Max length7
Median length4
Mean length2.8169014
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1049
47.7%
0 855
38.8%
사용시작지하층 142
 
6.5%
1 134
 
6.1%
2 17
 
0.8%
3 4
 
0.2%

Length

2024-04-16T17:11:48.796794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:48.893336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1049
47.7%
0 855
38.8%
사용시작지하층 142
 
6.5%
1 134
 
6.1%
2 17
 
0.8%
3 4
 
0.2%

washmccnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1247 
0
948 
세탁기수
 
6

Length

Max length4
Median length4
Mean length2.7078601
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1247
56.7%
0 948
43.1%
세탁기수 6
 
0.3%

Length

2024-04-16T17:11:49.237593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:49.323175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1247
56.7%
0 948
43.1%
세탁기수 6
 
0.3%

yangsilcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
0
1216 
<NA>
979 
양실수
 
6

Length

Max length4
Median length1
Mean length2.3398455
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1216
55.2%
<NA> 979
44.5%
양실수 6
 
0.3%

Length

2024-04-16T17:11:49.412936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:49.495553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1216
55.2%
na 979
44.5%
양실수 6
 
0.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1774 
0
362 
1
 
25
여성종사자수
 
19
2
 
11
Other values (3)
 
10

Length

Max length6
Median length4
Mean length3.461154
Min length1

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> 1774
80.6%
0 362
 
16.4%
1 25
 
1.1%
여성종사자수 19
 
0.9%
2 11
 
0.5%
5 6
 
0.3%
3 3
 
0.1%
4 1
 
< 0.1%

Length

2024-04-16T17:11:49.593409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:49.713933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1774
80.6%
0 362
 
16.4%
1 25
 
1.1%
여성종사자수 19
 
0.9%
2 11
 
0.5%
5 6
 
0.3%
3 3
 
0.1%
4 1
 
< 0.1%

yoksilcnt
Categorical

Distinct21
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
0
688 
<NA>
642 
2
613 
1
72 
4
 
52
Other values (16)
134 

Length

Max length4
Median length1
Mean length1.8891413
Min length1

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row2
5th row0

Common Values

ValueCountFrequency (%)
0 688
31.3%
<NA> 642
29.2%
2 613
27.9%
1 72
 
3.3%
4 52
 
2.4%
6 46
 
2.1%
8 31
 
1.4%
3 9
 
0.4%
7 9
 
0.4%
10 7
 
0.3%
Other values (11) 32
 
1.5%

Length

2024-04-16T17:11:49.847043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 688
31.3%
na 642
29.2%
2 613
27.9%
1 72
 
3.3%
4 52
 
2.4%
6 46
 
2.1%
8 31
 
1.4%
3 9
 
0.4%
7 9
 
0.4%
9 7
 
0.3%
Other values (11) 32
 
1.5%

sntuptaenm
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
공동탕업
1700 
목욕장업 기타
221 
공동탕업+찜질시설서비스영업
 
158
찜질시설서비스영업
 
77
한증막업
 
45

Length

Max length14
Median length4
Mean length5.1940027
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공동탕업+찜질시설서비스영업
2nd row한증막업
3rd row공동탕업+찜질시설서비스영업
4th row공동탕업+찜질시설서비스영업
5th row공동탕업

Common Values

ValueCountFrequency (%)
공동탕업 1700
77.2%
목욕장업 기타 221
 
10.0%
공동탕업+찜질시설서비스영업 158
 
7.2%
찜질시설서비스영업 77
 
3.5%
한증막업 45
 
2.0%

Length

2024-04-16T17:11:49.961865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:50.049651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1700
70.2%
목욕장업 221
 
9.1%
기타 221
 
9.1%
공동탕업+찜질시설서비스영업 158
 
6.5%
찜질시설서비스영업 77
 
3.2%
한증막업 45
 
1.9%

chaircnt
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
0
1215 
<NA>
979 
의자수
 
6
2
 
1

Length

Max length4
Median length1
Mean length2.3398455
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1215
55.2%
<NA> 979
44.5%
의자수 6
 
0.3%
2 1
 
< 0.1%

Length

2024-04-16T17:11:50.144631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:50.230043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1215
55.2%
na 979
44.5%
의자수 6
 
0.3%
2 1
 
< 0.1%

cndpermstymd
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1965 
조건부허가시작일자
234 
20190501
 
1
20190228
 
1

Length

Max length9
Median length4
Mean length4.5352113
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1965
89.3%
조건부허가시작일자 234
 
10.6%
20190501 1
 
< 0.1%
20190228 1
 
< 0.1%

Length

2024-04-16T17:11:50.315784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:50.398422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1965
89.3%
조건부허가시작일자 234
 
10.6%
20190501 1
 
< 0.1%
20190228 1
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1965 
조건부허가신고사유
235 
건축과-16824(2019.4.15),가설건축물 존치기간연장 신고
 
1

Length

Max length36
Median length4
Mean length4.5483871
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> 1965
89.3%
조건부허가신고사유 235
 
10.7%
건축과-16824(2019.4.15),가설건축물 존치기간연장 신고 1
 
< 0.1%

Length

2024-04-16T17:11:50.489968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:50.586811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1965
89.2%
조건부허가신고사유 235
 
10.7%
건축과-16824(2019.4.15),가설건축물 1
 
< 0.1%
존치기간연장 1
 
< 0.1%
신고 1
 
< 0.1%

cndpermendymd
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1965 
조건부허가종료일자
234 
20210421
 
1
20220831
 
1

Length

Max length9
Median length4
Mean length4.5352113
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1965
89.3%
조건부허가종료일자 234
 
10.6%
20210421 1
 
< 0.1%
20220831 1
 
< 0.1%

Length

2024-04-16T17:11:50.677177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:50.754259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1965
89.3%
조건부허가종료일자 234
 
10.6%
20210421 1
 
< 0.1%
20220831 1
 
< 0.1%

abedcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1274 
0
920 
침대수
 
7

Length

Max length4
Median length4
Mean length2.7428442
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1274
57.9%
0 920
41.8%
침대수 7
 
0.3%

Length

2024-04-16T17:11:50.844490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:50.924601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1274
57.9%
0 920
41.8%
침대수 7
 
0.3%

hanshilcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
0
1216 
<NA>
979 
한실수
 
6

Length

Max length4
Median length1
Mean length2.3398455
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1216
55.2%
<NA> 979
44.5%
한실수 6
 
0.3%

Length

2024-04-16T17:11:51.011659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:51.091465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1216
55.2%
na 979
44.5%
한실수 6
 
0.3%

rcvdryncnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
<NA>
1273 
0
921 
회수건조수
 
7

Length

Max length5
Median length4
Mean length2.7478419
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1273
57.8%
0 921
41.8%
회수건조수 7
 
0.3%

Length

2024-04-16T17:11:51.184801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:51.272722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1273
57.8%
0 921
41.8%
회수건조수 7
 
0.3%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 KiB
2021-02-01 05:11:03
2201 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-02-01 05:11:03
2nd row2021-02-01 05:11:03
3rd row2021-02-01 05:11:03
4th row2021-02-01 05:11:03
5th row2021-02-01 05:11:03

Common Values

ValueCountFrequency (%)
2021-02-01 05:11:03 2201
100.0%

Length

2024-04-16T17:11:51.349995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:11:51.422218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-02-01 2201
50.0%
05:11:03 2201
50.0%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
0332500003250000-202-2002-0000111_44_01_PI2018-08-31 23:59:59.0<NA>옥샘탕600051부산광역시 중구 창선동1가 9-9번지48947부산광역시 중구 광복로55번길 14-2 (창선동1가)20020513<NA><NA><NA><NA>01영업385089.38491100000180062.5676180000020180724131551공동탕업+찜질시설서비스영업051-123-1234<NA>00<NA>NN000000<NA>0공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-02-01 05:11:03
1432500003250000-202-1985-0015611_44_01_PI2018-08-31 23:59:59.0<NA>금수탕600816부산광역시 중구 중앙동4가 78-2번지48947<NA>1985040920070612<NA><NA><NA>02폐업385793.29931180910.38663620041116000000한증막업051-123-1234<NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA>한증막업<NA><NA><NA><NA><NA><NA><NA>2021-02-01 05:11:03
2532500003250000-202-2001-0001311_44_01_PI2018-08-31 23:59:59.0<NA>백록담600091부산광역시 중구 대청동1가 34-1번지48947<NA>2001111620120221<NA><NA><NA>02폐업385208.257554180108.03498420120227093749공동탕업+찜질시설서비스영업051-123-1234<NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA>공동탕업+찜질시설서비스영업<NA><NA><NA><NA><NA><NA><NA>2021-02-01 05:11:03
3632500003250000-202-2007-0000111_44_01_PI2018-08-31 23:59:59.0<NA>유나목욕탕600061부산광역시 중구 신창동1가 5-1번지 (5~8층)48948부산광역시 중구 광복중앙로 25 (신창동1가)2007040620140401<NA><NA><NA>02폐업385157.86566400000180248.2145730000020130208113918공동탕업+찜질시설서비스영업051-123-1234자가93<NA>NY805000<NA>2공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-02-01 05:11:03
4732500003250000-202-1988-0015911_44_01_PI2018-08-31 23:59:59.0<NA>녹수탕600062부산광역시 중구 신창동2가 21-2번지48947부산광역시 중구 광복로43번길 12 (신창동2가)19880913<NA><NA><NA><NA>01영업385086.62014400000180119.3340640000020130208111503공동탕업051-123-1234임대41<NA>NN402000<NA>0공동탕업0<NA><NA><NA>0002021-02-01 05:11:03
5832500003250000-202-1960-0014411_44_01_PU2018-11-30 02:40:00.0목욕장업금강스파600808부산광역시 중구 부평동3가 22-1번지 외 2필지48976부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)19601210<NA><NA><NA><NA>영업/정상영업384542.121201746179994.20210389820181128093116공동탕업+찜질시설서비스영업051-123-1234<NA>51<NA>NN515100<NA>0공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-02-01 05:11:03
6932500003250000-202-2009-0000111_44_01_PI2018-08-31 23:59:59.0<NA>오투(O2)600046부산광역시 중구 남포동6가 85번지 (10층)48981부산광역시 중구 비프광장로 20, 10층 (남포동6가)2009022320131227<NA><NA><NA>02폐업384892.63184400000179895.5128170000020130208114221공동탕업+찜질시설서비스영업051-123-1234임대104<NA>NY10010000<NA>0공동탕업+찜질시설서비스영업0<NA><NA><NA>0002021-02-01 05:11:03
71032500003250000-202-1984-0015411_44_01_PI2018-08-31 23:59:59.0<NA>영진사우나600045부산광역시 중구 남포동5가 88번지48947<NA>1984020120030703<NA><NA><NA>02폐업384910.466574179447.22650620030703000000한증막업051-123-1234<NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA>한증막업<NA><NA><NA><NA><NA><NA><NA>2021-02-01 05:11:03
81132500003250000-202-1984-0015211_44_01_PI2018-08-31 23:59:59.0<NA>거북목욕탕600110부산광역시 중구 영주동 292-10번지48916부산광역시 중구 영주로 20 (영주동)19840217<NA><NA><NA><NA>01영업385241.59002600000181147.1401790000020130208111357공동탕업051-123-1234<NA>00<NA>NN000000<NA>0공동탕업0<NA><NA><NA>0002021-02-01 05:11:03
91232500003250000-202-1973-0015011_44_01_PI2018-08-31 23:59:59.0<NA>부원탕600101부산광역시 중구 대창동1가 54-2번지48947<NA>1973011220051013<NA><NA><NA>02폐업<NA><NA>20040531000000공동탕업051-123-1234<NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA>2021-02-01 05:11:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
2191219453500005350000-202-2021-0000111_44_01_PU2021-01-15 02:40:00.0목욕장업인제 암반수 사우나621917경상남도 김해시 어방동 521-450819경상남도 김해시 활천로255번길 39, 2,3층 (어방동)20210107폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업373381.790161055195718.44168522820210113153039공동탕업전화번호건물소유구분명000YN00000006공동탕업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-02-01 05:11:03
2192219532100003210000-202-2021-0000211_44_01_PI2021-01-14 00:23:05.0목욕장업서초구립느티나무쉼터 내곡느티사우나137170서울특별시 서초구 염곡동 180-2 내곡동종합시설06793서울특별시 서초구 염곡말길 9, 1층 (염곡동)20210112폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업204418.836684211439958.44357870120210112134950공동탕업02 69537134임대000NN1사용끝지하층1사용시작지하층0004공동탕업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-02-01 05:11:03
2193219644800004480000-202-2021-0000111_44_01_PI2021-01-17 00:23:04.0목욕장업매포 복지목욕탕395904충청북도 단양군 매포읍 평동리 122727005충청북도 단양군 매포읍 평동로 12220210115폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업315613.611425393144.05982920210115115029목욕장업 기타전화번호자가300NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층0004목욕장업 기타0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-02-01 05:11:03
2194219744800004480000-202-2021-0000111_44_01_PI2021-01-17 00:23:04.0목욕장업매포 복지목욕탕395904충청북도 단양군 매포읍 평동리 122727005충청북도 단양군 매포읍 평동로 12220210115폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업315613.611425393144.05982920210115115029목욕장업 기타전화번호자가300NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층0004목욕장업 기타0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-02-01 05:11:03
2195219831700003170000-202-2021-0000111_44_01_PI2021-01-20 00:23:04.0목욕장업주식회사 인스타짐 독산역점153803서울특별시 금천구 가산동 685 디지털엠파이어빌딩 15층 1501,1502,1503,1504,1513호08595서울특별시 금천구 범안로 1130, 디지털엠파이어빌딩 15층 1501,1502,1503,1504,1513호 (가산동)20210118폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업189978.050925581440363.95445365920210118161728찜질시설서비스영업0216001614임대002YY15사용끝지하층15사용시작지하층0022찜질시설서비스영업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-02-01 05:11:03
2196219931000003100000-202-2021-0000111_44_01_PI2021-01-21 00:23:03.0목욕장업현정누리139841서울특별시 노원구 월계동 50-29 우현빌딩01904서울특별시 노원구 화랑로 325, 우현빌딩 5층 (월계동)20210119폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업205585.595612675456954.14737061120210119155557목욕장업 기타전화번호임대500YN사용끝지상층사용끝지하층사용시작지상층사용시작지하층0002목욕장업 기타0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-02-01 05:11:03
2197220034200003420000-202-2021-0000111_44_01_PI2021-01-21 00:23:03.0목욕장업웰니스클럽사우나701827대구광역시 동구 신천동 326-1 대구 메리어트 호텔 및 서비스드 레지던스41243대구광역시 동구 동부로26길 6, 대구 메리어트 호텔 및 서비스드 레지던스 5층 (신천동)20210119<NA><NA><NA><NA>영업/정상영업346922.110876265123.31582420210119145343목욕장업 기타053 327 7780<NA>000NN5<NA>5<NA>0002목욕장업 기타0<NA><NA><NA>0002021-02-01 05:11:03
2198220148800004880000-202-2021-0000111_44_01_PI2021-01-27 00:23:03.0목욕장업썬밸리해수사우나548924전라남도 고흥군 도덕면 용동리 산 4 고흥썬밸리콘도59545전라남도 고흥군 도덕면 고흥만로 1134, 고흥썬밸리콘도 2층20210125폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업218116.680341127449.78610220210125160850공동탕업061 830 2900자가1000NN사용끝지상층사용끝지하층2사용시작지하층0004공동탕업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-02-01 05:11:03
2199220332200003220000-202-2021-0000211_44_01_PI2021-01-31 00:23:03.0목욕장업마루135892서울특별시 강남구 신사동 585-1 네오스06032서울특별시 강남구 논현로 831, 네오스 지하1층, 지하2층 (신사동)20210129폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업202378.390574465446705.19714887120210129175409목욕장업 기타02 511 1570건물소유구분명000YN02010001목욕장업 기타0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-02-01 05:11:03
2200220432200003220000-202-2021-0000211_44_01_PI2021-01-31 00:23:03.0목욕장업마루135892서울특별시 강남구 신사동 585-1 네오스06032서울특별시 강남구 논현로 831, 네오스 지하1층, 지하2층 (신사동)20210129폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업202378.390574465446705.19714887120210129175409목욕장업 기타02 511 1570건물소유구분명000YN02010001목욕장업 기타0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-02-01 05:11:03