Overview

Dataset statistics

Number of variables47
Number of observations2172
Missing cells1792
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory806.1 KiB
Average record size in memory380.1 B

Variable types

Numeric4
Text10
Categorical30
DateTime1
Boolean2

Alerts

opnsvcid has constant value ""Constant
clgstdt is highly imbalanced (51.1%)Imbalance
clgenddt is highly imbalanced (51.1%)Imbalance
ropnymd is highly imbalanced (51.1%)Imbalance
maneipcnt is highly imbalanced (71.2%)Imbalance
multusnupsoyn is highly imbalanced (64.6%)Imbalance
wmeipcnt is highly imbalanced (71.1%)Imbalance
cndpermstymd is highly imbalanced (75.1%)Imbalance
cndpermntwhy is highly imbalanced (68.8%)Imbalance
cndpermendymd is highly imbalanced (75.1%)Imbalance
rdnwhladdr has 619 (28.5%) missing valuesMissing
dcbymd has 979 (45.1%) missing valuesMissing
x has 84 (3.9%) missing valuesMissing
y has 84 (3.9%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 08:12:08.996988
Analysis finished2024-04-16 08:12:10.196871
Duration1.2 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct2172
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1088.5
Minimum3
Maximum2174
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.2 KiB
2024-04-16T17:12:10.253059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile111.55
Q1545.75
median1088.5
Q31631.25
95-th percentile2065.45
Maximum2174
Range2171
Interquartile range (IQR)1085.5

Descriptive statistics

Standard deviation627.14671
Coefficient of variation (CV)0.57615683
Kurtosis-1.2
Mean1088.5
Median Absolute Deviation (MAD)543
Skewness0
Sum2364222
Variance393313
MonotonicityNot monotonic
2024-04-16T17:12:10.361666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 1
 
< 0.1%
1448 1
 
< 0.1%
1462 1
 
< 0.1%
1461 1
 
< 0.1%
1460 1
 
< 0.1%
1459 1
 
< 0.1%
1458 1
 
< 0.1%
1457 1
 
< 0.1%
1456 1
 
< 0.1%
1455 1
 
< 0.1%
Other values (2162) 2162
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 (%)
2174 1
< 0.1%
2173 1
< 0.1%
2172 1
< 0.1%
2171 1
< 0.1%
2170 1
< 0.1%
2169 1
< 0.1%
2168 1
< 0.1%
2167 1
< 0.1%
2166 1
< 0.1%
2165 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct147
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3509471.2
Minimum3010000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.2 KiB
2024-04-16T17:12:10.484056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3010000
5-th percentile3260000
Q13290000
median3330000
Q33380000
95-th percentile4970000
Maximum6520000
Range3510000
Interquartile range (IQR)90000

Descriptive statistics

Standard deviation561273.68
Coefficient of variation (CV)0.15993112
Kurtosis9.6468161
Mean3509471.2
Median Absolute Deviation (MAD)40000
Skewness3.1451628
Sum7.6225715 × 109
Variance3.1502814 × 1011
MonotonicityNot monotonic
2024-04-16T17:12:10.625632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3290000 221
 
10.2%
3340000 171
 
7.9%
3300000 164
 
7.6%
3330000 159
 
7.3%
3310000 148
 
6.8%
3370000 131
 
6.0%
3320000 123
 
5.7%
3350000 116
 
5.3%
3380000 112
 
5.2%
3270000 93
 
4.3%
Other values (137) 734
33.8%
ValueCountFrequency (%)
3010000 8
0.4%
3020000 1
 
< 0.1%
3030000 1
 
< 0.1%
3040000 2
 
0.1%
3050000 1
 
< 0.1%
3070000 1
 
< 0.1%
3100000 4
0.2%
3110000 1
 
< 0.1%
3150000 6
0.3%
3160000 1
 
< 0.1%
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

Distinct2058
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2024-04-16T17:12:10.796350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters47784
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

Unique1995 ?
Unique (%)91.9%

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 (%)
5530000-202-2020-00004 4
 
0.2%
5530000-202-2020-00001 4
 
0.2%
4040000-202-2019-00001 3
 
0.1%
4810000-202-2018-00006 3
 
0.1%
3280000-202-2020-00001 3
 
0.1%
4010000-202-2018-00001 3
 
0.1%
5480000-202-2020-00002 3
 
0.1%
3310000-202-2020-00001 3
 
0.1%
4060000-202-2018-00002 3
 
0.1%
4800000-202-2019-00002 3
 
0.1%
Other values (2048) 2140
98.5%
2024-04-16T17:12:11.054271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19148
40.1%
2 7000
 
14.6%
- 6516
 
13.6%
3 4156
 
8.7%
1 3315
 
6.9%
9 2772
 
5.8%
8 1258
 
2.6%
4 1137
 
2.4%
5 916
 
1.9%
7 885
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41268
86.4%
Dash Punctuation 6516
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19148
46.4%
2 7000
 
17.0%
3 4156
 
10.1%
1 3315
 
8.0%
9 2772
 
6.7%
8 1258
 
3.0%
4 1137
 
2.8%
5 916
 
2.2%
7 885
 
2.1%
6 681
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 6516
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47784
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19148
40.1%
2 7000
 
14.6%
- 6516
 
13.6%
3 4156
 
8.7%
1 3315
 
6.9%
9 2772
 
5.8%
8 1258
 
2.6%
4 1137
 
2.4%
5 916
 
1.9%
7 885
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47784
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19148
40.1%
2 7000
 
14.6%
- 6516
 
13.6%
3 4156
 
8.7%
1 3315
 
6.9%
9 2772
 
5.8%
8 1258
 
2.6%
4 1137
 
2.4%
5 916
 
1.9%
7 885
 
1.9%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
11_44_01_P
2172 

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 2172
100.0%

Length

2024-04-16T17:12:11.162453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:11.232362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 2172
100.0%

updategbn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
I
1732 
U
440 

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 1732
79.7%
U 440
 
20.3%

Length

2024-04-16T17:12:11.302108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:11.374864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1732
79.7%
u 440
 
20.3%
Distinct341
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
Minimum2018-08-31 23:59:59
Maximum2020-12-20 02:40:00
2024-04-16T17:12:11.472222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T17:12:11.781109image/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 size17.1 KiB
<NA>
1548 
목욕장업
624 

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> 1548
71.3%
목욕장업 624
28.7%

Length

2024-04-16T17:12:11.880673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:11.958103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1548
71.3%
목욕장업 624
28.7%

bplcnm
Text

Distinct1379
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2024-04-16T17:12:12.169466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length3
Mean length4.7145488
Min length2

Characters and Unicode

Total characters10240
Distinct characters458
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

Unique1072 ?
Unique (%)49.4%

Sample

1st row옥샘탕
2nd row금수탕
3rd row백록담
4th row유나목욕탕
5th row녹수탕
ValueCountFrequency (%)
사우나 38
 
1.5%
청수탕 21
 
0.9%
현대탕 21
 
0.9%
목욕탕 21
 
0.9%
찜질방 20
 
0.8%
옥천탕 19
 
0.8%
산수탕 15
 
0.6%
천수탕 15
 
0.6%
장수탕 14
 
0.6%
제일탕 13
 
0.5%
Other values (1475) 2264
92.0%
2024-04-16T17:12:12.505186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1408
 
13.8%
334
 
3.3%
305
 
3.0%
291
 
2.8%
290
 
2.8%
288
 
2.8%
261
 
2.5%
212
 
2.1%
193
 
1.9%
147
 
1.4%
Other values (448) 6511
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9681
94.5%
Space Separator 290
 
2.8%
Close Punctuation 73
 
0.7%
Uppercase Letter 72
 
0.7%
Open Punctuation 70
 
0.7%
Decimal Number 37
 
0.4%
Lowercase Letter 9
 
0.1%
Other Punctuation 6
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1408
 
14.5%
334
 
3.5%
305
 
3.2%
291
 
3.0%
288
 
3.0%
261
 
2.7%
212
 
2.2%
193
 
2.0%
147
 
1.5%
144
 
1.5%
Other values (407) 6098
63.0%
Uppercase Letter
ValueCountFrequency (%)
G 10
13.9%
A 7
 
9.7%
S 6
 
8.3%
E 5
 
6.9%
L 5
 
6.9%
T 5
 
6.9%
U 4
 
5.6%
M 4
 
5.6%
H 3
 
4.2%
O 3
 
4.2%
Other values (12) 20
27.8%
Lowercase Letter
ValueCountFrequency (%)
o 3
33.3%
n 2
22.2%
a 1
 
11.1%
r 1
 
11.1%
u 1
 
11.1%
d 1
 
11.1%
Decimal Number
ValueCountFrequency (%)
2 18
48.6%
4 16
43.2%
6 1
 
2.7%
5 1
 
2.7%
3 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 2
33.3%
& 2
33.3%
· 1
16.7%
, 1
16.7%
Space Separator
ValueCountFrequency (%)
290
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9678
94.5%
Common 478
 
4.7%
Latin 81
 
0.8%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1408
 
14.5%
334
 
3.5%
305
 
3.2%
291
 
3.0%
288
 
3.0%
261
 
2.7%
212
 
2.2%
193
 
2.0%
147
 
1.5%
144
 
1.5%
Other values (405) 6095
63.0%
Latin
ValueCountFrequency (%)
G 10
 
12.3%
A 7
 
8.6%
S 6
 
7.4%
E 5
 
6.2%
L 5
 
6.2%
T 5
 
6.2%
U 4
 
4.9%
M 4
 
4.9%
H 3
 
3.7%
O 3
 
3.7%
Other values (18) 29
35.8%
Common
ValueCountFrequency (%)
290
60.7%
) 73
 
15.3%
( 70
 
14.6%
2 18
 
3.8%
4 16
 
3.3%
. 2
 
0.4%
& 2
 
0.4%
- 2
 
0.4%
· 1
 
0.2%
, 1
 
0.2%
Other values (3) 3
 
0.6%
Han
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9678
94.5%
ASCII 558
 
5.4%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1408
 
14.5%
334
 
3.5%
305
 
3.2%
291
 
3.0%
288
 
3.0%
261
 
2.7%
212
 
2.2%
193
 
2.0%
147
 
1.5%
144
 
1.5%
Other values (405) 6095
63.0%
ASCII
ValueCountFrequency (%)
290
52.0%
) 73
 
13.1%
( 70
 
12.5%
2 18
 
3.2%
4 16
 
2.9%
G 10
 
1.8%
A 7
 
1.3%
S 6
 
1.1%
E 5
 
0.9%
L 5
 
0.9%
Other values (30) 58
 
10.4%
CJK
ValueCountFrequency (%)
2
66.7%
1
33.3%
None
ValueCountFrequency (%)
· 1
100.0%
Distinct861
Distinct (%)39.8%
Missing7
Missing (%)0.3%
Memory size17.1 KiB
2024-04-16T17:12:12.969458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters12990
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

Unique363 ?
Unique (%)16.8%

Sample

1st row600051
2nd row600816
3rd row600091
4th row600061
5th row600062
ValueCountFrequency (%)
604851 15
 
0.7%
612846 12
 
0.6%
612847 12
 
0.6%
608808 10
 
0.5%
614822 10
 
0.5%
608828 10
 
0.5%
607833 10
 
0.5%
613832 9
 
0.4%
613805 9
 
0.4%
607826 9
 
0.4%
Other values (851) 2059
95.1%
2024-04-16T17:12:13.512364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 2391
18.4%
8 2236
17.2%
0 2058
15.8%
1 1954
15.0%
2 1025
7.9%
4 936
 
7.2%
3 777
 
6.0%
7 609
 
4.7%
5 503
 
3.9%
9 459
 
3.5%
Other values (5) 42
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12948
99.7%
Other Letter 42
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 2391
18.5%
8 2236
17.3%
0 2058
15.9%
1 1954
15.1%
2 1025
7.9%
4 936
 
7.2%
3 777
 
6.0%
7 609
 
4.7%
5 503
 
3.9%
9 459
 
3.5%
Other Letter
ValueCountFrequency (%)
14
33.3%
7
16.7%
7
16.7%
7
16.7%
7
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 12948
99.7%
Hangul 42
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
6 2391
18.5%
8 2236
17.3%
0 2058
15.9%
1 1954
15.1%
2 1025
7.9%
4 936
 
7.2%
3 777
 
6.0%
7 609
 
4.7%
5 503
 
3.9%
9 459
 
3.5%
Hangul
ValueCountFrequency (%)
14
33.3%
7
16.7%
7
16.7%
7
16.7%
7
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12948
99.7%
Hangul 42
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 2391
18.5%
8 2236
17.3%
0 2058
15.9%
1 1954
15.1%
2 1025
7.9%
4 936
 
7.2%
3 777
 
6.0%
7 609
 
4.7%
5 503
 
3.9%
9 459
 
3.5%
Hangul
ValueCountFrequency (%)
14
33.3%
7
16.7%
7
16.7%
7
16.7%
7
16.7%
Distinct1973
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2024-04-16T17:12:13.826514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length49
Mean length25.066759
Min length16

Characters and Unicode

Total characters54445
Distinct characters408
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

Unique1839 ?
Unique (%)84.7%

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
 
18.1%
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
 
1.2%
Other values (3006) 6612
66.1%
2024-04-16T17:12:14.240650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9964
 
18.3%
2375
 
4.4%
1 2298
 
4.2%
2227
 
4.1%
2186
 
4.0%
2109
 
3.9%
2068
 
3.8%
1979
 
3.6%
1974
 
3.6%
- 1950
 
3.6%
Other values (398) 25315
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30962
56.9%
Decimal Number 10548
 
19.4%
Space Separator 9964
 
18.3%
Dash Punctuation 1950
 
3.6%
Uppercase Letter 714
 
1.3%
Other Punctuation 153
 
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 (%)
2375
 
7.7%
2227
 
7.2%
2186
 
7.1%
2109
 
6.8%
2068
 
6.7%
1979
 
6.4%
1974
 
6.4%
1934
 
6.2%
1874
 
6.1%
387
 
1.2%
Other values (360) 11849
38.3%
Uppercase Letter
ValueCountFrequency (%)
B 349
48.9%
T 336
47.1%
I 7
 
1.0%
S 4
 
0.6%
V 3
 
0.4%
Y 3
 
0.4%
A 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 2298
21.8%
2 1386
13.1%
3 1160
11.0%
4 1065
10.1%
5 972
9.2%
6 810
 
7.7%
0 768
 
7.3%
7 753
 
7.1%
8 703
 
6.7%
9 633
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
p 3
30.0%
a 3
30.0%
r 1
 
10.0%
o 1
 
10.0%
w 1
 
10.0%
e 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 149
97.4%
. 3
 
2.0%
@ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
9964
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1950
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30962
56.9%
Common 22758
41.8%
Latin 725
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2375
 
7.7%
2227
 
7.2%
2186
 
7.1%
2109
 
6.8%
2068
 
6.7%
1979
 
6.4%
1974
 
6.4%
1934
 
6.2%
1874
 
6.1%
387
 
1.2%
Other values (360) 11849
38.3%
Latin
ValueCountFrequency (%)
B 349
48.1%
T 336
46.3%
I 7
 
1.0%
S 4
 
0.6%
V 3
 
0.4%
Y 3
 
0.4%
A 3
 
0.4%
p 3
 
0.4%
a 3
 
0.4%
G 2
 
0.3%
Other values (10) 12
 
1.7%
Common
ValueCountFrequency (%)
9964
43.8%
1 2298
 
10.1%
- 1950
 
8.6%
2 1386
 
6.1%
3 1160
 
5.1%
4 1065
 
4.7%
5 972
 
4.3%
6 810
 
3.6%
0 768
 
3.4%
7 753
 
3.3%
Other values (8) 1632
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30962
56.9%
ASCII 23482
43.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9964
42.4%
1 2298
 
9.8%
- 1950
 
8.3%
2 1386
 
5.9%
3 1160
 
4.9%
4 1065
 
4.5%
5 972
 
4.1%
6 810
 
3.4%
0 768
 
3.3%
7 753
 
3.2%
Other values (27) 2356
 
10.0%
Hangul
ValueCountFrequency (%)
2375
 
7.7%
2227
 
7.2%
2186
 
7.1%
2109
 
6.8%
2068
 
6.7%
1979
 
6.4%
1974
 
6.4%
1934
 
6.2%
1874
 
6.1%
387
 
1.2%
Other values (360) 11849
38.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct1110
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2024-04-16T17:12:14.474748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0018416
Min length5

Characters and Unicode

Total characters10864
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

Unique851 ?
Unique (%)39.2%

Sample

1st row48947
2nd row48947
3rd row48947
4th row48948
5th row48947
ValueCountFrequency (%)
48947 682
31.4%
47709 8
 
0.4%
48099 8
 
0.4%
18606 8
 
0.4%
46327 5
 
0.2%
47248 5
 
0.2%
58709 4
 
0.2%
15040 4
 
0.2%
48053 4
 
0.2%
18474 4
 
0.2%
Other values (1100) 1440
66.3%
2024-04-16T17:12:14.807931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2994
27.6%
7 1456
13.4%
8 1437
13.2%
9 1247
11.5%
6 666
 
6.1%
0 640
 
5.9%
5 635
 
5.8%
2 621
 
5.7%
1 602
 
5.5%
3 552
 
5.1%
Other values (7) 14
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10850
99.9%
Other Letter 14
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 2994
27.6%
7 1456
13.4%
8 1437
13.2%
9 1247
11.5%
6 666
 
6.1%
0 640
 
5.9%
5 635
 
5.9%
2 621
 
5.7%
1 602
 
5.5%
3 552
 
5.1%
Other Letter
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 10850
99.9%
Hangul 14
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 2994
27.6%
7 1456
13.4%
8 1437
13.2%
9 1247
11.5%
6 666
 
6.1%
0 640
 
5.9%
5 635
 
5.9%
2 621
 
5.7%
1 602
 
5.5%
3 552
 
5.1%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10850
99.9%
Hangul 14
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2994
27.6%
7 1456
13.4%
8 1437
13.2%
9 1247
11.5%
6 666
 
6.1%
0 640
 
5.9%
5 635
 
5.9%
2 621
 
5.7%
1 602
 
5.5%
3 552
 
5.1%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

rdnwhladdr
Text

MISSING 

Distinct1421
Distinct (%)91.5%
Missing619
Missing (%)28.5%
Memory size17.1 KiB
2024-04-16T17:12:15.197734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length53
Mean length28.52801
Min length5

Characters and Unicode

Total characters44304
Distinct characters457
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

Unique1345 ?
Unique (%)86.6%

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
 
13.9%
부산진구 153
 
1.8%
남구 110
 
1.3%
해운대구 103
 
1.2%
사하구 100
 
1.2%
동래구 99
 
1.2%
연제구 85
 
1.0%
북구 82
 
1.0%
경기도 77
 
0.9%
금정구 77
 
0.9%
Other values (2613) 6504
75.7%
2024-04-16T17:12:15.644487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7039
 
15.9%
1830
 
4.1%
1 1611
 
3.6%
1535
 
3.5%
1522
 
3.4%
1490
 
3.4%
1449
 
3.3%
) 1399
 
3.2%
( 1399
 
3.2%
1383
 
3.1%
Other values (447) 23647
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26482
59.8%
Space Separator 7039
 
15.9%
Decimal Number 6902
 
15.6%
Close Punctuation 1402
 
3.2%
Open Punctuation 1402
 
3.2%
Other Punctuation 707
 
1.6%
Dash Punctuation 289
 
0.7%
Uppercase Letter 44
 
0.1%
Math Symbol 32
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1830
 
6.9%
1535
 
5.8%
1522
 
5.7%
1490
 
5.6%
1449
 
5.5%
1383
 
5.2%
1361
 
5.1%
1260
 
4.8%
876
 
3.3%
733
 
2.8%
Other values (408) 13043
49.3%
Uppercase Letter
ValueCountFrequency (%)
B 25
56.8%
A 5
 
11.4%
I 4
 
9.1%
G 2
 
4.5%
C 2
 
4.5%
M 1
 
2.3%
K 1
 
2.3%
S 1
 
2.3%
T 1
 
2.3%
L 1
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 1611
23.3%
2 1046
15.2%
3 845
12.2%
0 574
 
8.3%
5 568
 
8.2%
4 531
 
7.7%
6 506
 
7.3%
7 463
 
6.7%
9 388
 
5.6%
8 370
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 696
98.4%
. 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%
Close Punctuation
ValueCountFrequency (%)
) 1399
99.8%
] 3
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1399
99.8%
[ 3
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 31
96.9%
1
 
3.1%
Space Separator
ValueCountFrequency (%)
7039
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 289
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26482
59.8%
Common 17773
40.1%
Latin 49
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1830
 
6.9%
1535
 
5.8%
1522
 
5.7%
1490
 
5.6%
1449
 
5.5%
1383
 
5.2%
1361
 
5.1%
1260
 
4.8%
876
 
3.3%
733
 
2.8%
Other values (408) 13043
49.3%
Common
ValueCountFrequency (%)
7039
39.6%
1 1611
 
9.1%
) 1399
 
7.9%
( 1399
 
7.9%
2 1046
 
5.9%
3 845
 
4.8%
, 696
 
3.9%
0 574
 
3.2%
5 568
 
3.2%
4 531
 
3.0%
Other values (13) 2065
 
11.6%
Latin
ValueCountFrequency (%)
B 25
51.0%
A 5
 
10.2%
I 4
 
8.2%
G 2
 
4.1%
C 2
 
4.1%
M 1
 
2.0%
K 1
 
2.0%
S 1
 
2.0%
r 1
 
2.0%
e 1
 
2.0%
Other values (6) 6
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26482
59.8%
ASCII 17820
40.2%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7039
39.5%
1 1611
 
9.0%
) 1399
 
7.9%
( 1399
 
7.9%
2 1046
 
5.9%
3 845
 
4.7%
, 696
 
3.9%
0 574
 
3.2%
5 568
 
3.2%
4 531
 
3.0%
Other values (27) 2112
 
11.9%
Hangul
ValueCountFrequency (%)
1830
 
6.9%
1535
 
5.8%
1522
 
5.7%
1490
 
5.6%
1449
 
5.5%
1383
 
5.2%
1361
 
5.1%
1260
 
4.8%
876
 
3.3%
733
 
2.8%
Other values (408) 13043
49.3%
None
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

apvpermymd
Real number (ℝ)

Distinct1703
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19956516
Minimum19540131
Maximum20201217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.2 KiB
2024-04-16T17:12:15.756899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19540131
5-th percentile19700968
Q119840908
median19941109
Q320060106
95-th percentile20200221
Maximum20201217
Range661086
Interquartile range (IQR)219198.25

Descriptive statistics

Standard deviation153898.4
Coefficient of variation (CV)0.0077116865
Kurtosis-0.84315013
Mean19956516
Median Absolute Deviation (MAD)108998
Skewness0.066004759
Sum4.3345553 × 1010
Variance2.3684717 × 1010
MonotonicityNot monotonic
2024-04-16T17:12:15.879286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190201 15
 
0.7%
19630110 15
 
0.7%
20191101 9
 
0.4%
20001130 9
 
0.4%
19921202 8
 
0.4%
20200207 7
 
0.3%
20200221 6
 
0.3%
20191206 6
 
0.3%
19960710 6
 
0.3%
20181123 6
 
0.3%
Other values (1693) 2085
96.0%
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 (%)
20201217 2
0.1%
20201215 2
0.1%
20201211 2
0.1%
20201203 1
< 0.1%
20201202 1
< 0.1%
20201120 2
0.1%
20201117 1
< 0.1%
20201111 1
< 0.1%
20201110 2
0.1%
20201109 2
0.1%

dcbymd
Text

MISSING 

Distinct816
Distinct (%)68.4%
Missing979
Missing (%)45.1%
Memory size17.1 KiB
2024-04-16T17:12:16.119368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.2690696
Min length4

Characters and Unicode

Total characters8672
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

Unique701 ?
Unique (%)58.8%

Sample

1st row20070612
2nd row20120221
3rd row20140401
4th row20131227
5th row20030703
ValueCountFrequency (%)
폐업일자 218
 
18.3%
20050121 12
 
1.0%
20051017 7
 
0.6%
20001130 7
 
0.6%
20030401 5
 
0.4%
20170310 5
 
0.4%
20120621 4
 
0.3%
20141030 4
 
0.3%
20030122 4
 
0.3%
20131002 3
 
0.3%
Other values (806) 924
77.5%
2024-04-16T17:12:16.520372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2640
30.4%
2 1610
18.6%
1 1413
16.3%
9 362
 
4.2%
3 349
 
4.0%
7 305
 
3.5%
5 293
 
3.4%
6 283
 
3.3%
8 277
 
3.2%
4 268
 
3.1%
Other values (4) 872
 
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7800
89.9%
Other Letter 872
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2640
33.8%
2 1610
20.6%
1 1413
18.1%
9 362
 
4.6%
3 349
 
4.5%
7 305
 
3.9%
5 293
 
3.8%
6 283
 
3.6%
8 277
 
3.6%
4 268
 
3.4%
Other Letter
ValueCountFrequency (%)
218
25.0%
218
25.0%
218
25.0%
218
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7800
89.9%
Hangul 872
 
10.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2640
33.8%
2 1610
20.6%
1 1413
18.1%
9 362
 
4.6%
3 349
 
4.5%
7 305
 
3.9%
5 293
 
3.8%
6 283
 
3.6%
8 277
 
3.6%
4 268
 
3.4%
Hangul
ValueCountFrequency (%)
218
25.0%
218
25.0%
218
25.0%
218
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7800
89.9%
Hangul 872
 
10.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2640
33.8%
2 1610
20.6%
1 1413
18.1%
9 362
 
4.6%
3 349
 
4.5%
7 305
 
3.9%
5 293
 
3.8%
6 283
 
3.6%
8 277
 
3.6%
4 268
 
3.4%
Hangul
ValueCountFrequency (%)
218
25.0%
218
25.0%
218
25.0%
218
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1941 
휴업시작일자
231 

Length

Max length6
Median length4
Mean length4.2127072
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> 1941
89.4%
휴업시작일자 231
 
10.6%

Length

2024-04-16T17:12:16.644631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:16.729990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1941
89.4%
휴업시작일자 231
 
10.6%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1941 
휴업종료일자
231 

Length

Max length6
Median length4
Mean length4.2127072
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> 1941
89.4%
휴업종료일자 231
 
10.6%

Length

2024-04-16T17:12:16.818580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:16.906445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1941
89.4%
휴업종료일자 231
 
10.6%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1941 
재개업일자
231 

Length

Max length5
Median length4
Mean length4.1063536
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> 1941
89.4%
재개업일자 231
 
10.6%

Length

2024-04-16T17:12:17.019907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:17.099876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1941
89.4%
재개업일자 231
 
10.6%

trdstatenm
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
02
925 
01
623 
영업/정상
568 
폐업
 
50
영업상태
 
4

Length

Max length5
Median length2
Mean length2.7900552
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
02 925
42.6%
01 623
28.7%
영업/정상 568
26.2%
폐업 50
 
2.3%
영업상태 4
 
0.2%
<NA> 2
 
0.1%

Length

2024-04-16T17:12:17.185121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:17.280561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 925
42.6%
01 623
28.7%
영업/정상 568
26.2%
폐업 50
 
2.3%
영업상태 4
 
0.2%
na 2
 
0.1%

dtlstatenm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
영업
1197 
폐업
975 

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 1197
55.1%
폐업 975
44.9%

Length

2024-04-16T17:12:17.393607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:17.473618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 1197
55.1%
폐업 975
44.9%

x
Text

MISSING 

Distinct1904
Distinct (%)91.2%
Missing84
Missing (%)3.9%
Memory size17.1 KiB
2024-04-16T17:12:17.661523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.950192
Min length7

Characters and Unicode

Total characters41656
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

Unique1790 ?
Unique (%)85.7%

Sample

1st row385089.38491100000
2nd row385793.29931
3rd row385208.257554
4th row385157.86566400000
5th row385086.62014400000
ValueCountFrequency (%)
좌표정보(x 8
 
0.4%
192190.585454696 8
 
0.4%
175185.261058397 4
 
0.2%
389727.58350700000 4
 
0.2%
387810.283167969 4
 
0.2%
389394.976154 4
 
0.2%
390974.056399381 4
 
0.2%
210858.16481015 4
 
0.2%
144766.399755 4
 
0.2%
229301.674137 3
 
0.1%
Other values (1894) 2041
97.7%
2024-04-16T17:12:17.989902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8527
20.5%
0 6851
16.4%
3 3946
9.5%
8 3312
 
8.0%
9 2937
 
7.1%
1 2406
 
5.8%
7 2393
 
5.7%
2 2374
 
5.7%
4 2293
 
5.5%
6 2247
 
5.4%
Other values (9) 4370
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30998
74.4%
Space Separator 8527
 
20.5%
Other Punctuation 2075
 
5.0%
Other Letter 32
 
0.1%
Close Punctuation 8
 
< 0.1%
Uppercase Letter 8
 
< 0.1%
Open Punctuation 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6851
22.1%
3 3946
12.7%
8 3312
10.7%
9 2937
9.5%
1 2406
 
7.8%
7 2393
 
7.7%
2 2374
 
7.7%
4 2293
 
7.4%
6 2247
 
7.2%
5 2239
 
7.2%
Other Letter
ValueCountFrequency (%)
8
25.0%
8
25.0%
8
25.0%
8
25.0%
Space Separator
ValueCountFrequency (%)
8527
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2075
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41616
99.9%
Hangul 32
 
0.1%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
8527
20.5%
0 6851
16.5%
3 3946
9.5%
8 3312
 
8.0%
9 2937
 
7.1%
1 2406
 
5.8%
7 2393
 
5.8%
2 2374
 
5.7%
4 2293
 
5.5%
6 2247
 
5.4%
Other values (4) 4330
10.4%
Hangul
ValueCountFrequency (%)
8
25.0%
8
25.0%
8
25.0%
8
25.0%
Latin
ValueCountFrequency (%)
X 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41624
99.9%
Hangul 32
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8527
20.5%
0 6851
16.5%
3 3946
9.5%
8 3312
 
8.0%
9 2937
 
7.1%
1 2406
 
5.8%
7 2393
 
5.7%
2 2374
 
5.7%
4 2293
 
5.5%
6 2247
 
5.4%
Other values (5) 4338
10.4%
Hangul
ValueCountFrequency (%)
8
25.0%
8
25.0%
8
25.0%
8
25.0%

y
Text

MISSING 

Distinct1904
Distinct (%)91.2%
Missing84
Missing (%)3.9%
Memory size17.1 KiB
2024-04-16T17:12:18.209954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.950192
Min length7

Characters and Unicode

Total characters41656
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

Unique1790 ?
Unique (%)85.7%

Sample

1st row180062.56761800000
2nd row180910.386636
3rd row180108.034984
4th row180248.21457300000
5th row180119.33406400000
ValueCountFrequency (%)
좌표정보(y 8
 
0.4%
401648.714565483 8
 
0.4%
427812.896240081 4
 
0.2%
191654.34294400000 4
 
0.2%
179178.742589729 4
 
0.2%
193519.152183 4
 
0.2%
182797.894969615 4
 
0.2%
411413.605240051 4
 
0.2%
144689.635335 4
 
0.2%
245277.792251 3
 
0.1%
Other values (1894) 2041
97.7%
2024-04-16T17:12:18.511574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8491
20.4%
0 6806
16.3%
1 4038
9.7%
8 3265
 
7.8%
9 2842
 
6.8%
7 2666
 
6.4%
4 2434
 
5.8%
6 2275
 
5.5%
2 2255
 
5.4%
3 2255
 
5.4%
Other values (11) 4329
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31016
74.5%
Space Separator 8491
 
20.4%
Other Punctuation 2075
 
5.0%
Other Letter 32
 
0.1%
Dash Punctuation 15
 
< 0.1%
Close Punctuation 11
 
< 0.1%
Uppercase Letter 8
 
< 0.1%
Open Punctuation 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6806
21.9%
1 4038
13.0%
8 3265
10.5%
9 2842
9.2%
7 2666
 
8.6%
4 2434
 
7.8%
6 2275
 
7.3%
2 2255
 
7.3%
3 2255
 
7.3%
5 2180
 
7.0%
Other Letter
ValueCountFrequency (%)
8
25.0%
8
25.0%
8
25.0%
8
25.0%
Close Punctuation
ValueCountFrequency (%)
) 8
72.7%
] 3
 
27.3%
Space Separator
ValueCountFrequency (%)
8491
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2075
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41616
99.9%
Hangul 32
 
0.1%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
8491
20.4%
0 6806
16.4%
1 4038
9.7%
8 3265
 
7.8%
9 2842
 
6.8%
7 2666
 
6.4%
4 2434
 
5.8%
6 2275
 
5.5%
2 2255
 
5.4%
3 2255
 
5.4%
Other values (6) 4289
10.3%
Hangul
ValueCountFrequency (%)
8
25.0%
8
25.0%
8
25.0%
8
25.0%
Latin
ValueCountFrequency (%)
Y 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41624
99.9%
Hangul 32
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8491
20.4%
0 6806
16.4%
1 4038
9.7%
8 3265
 
7.8%
9 2842
 
6.8%
7 2666
 
6.4%
4 2434
 
5.8%
6 2275
 
5.5%
2 2255
 
5.4%
3 2255
 
5.4%
Other values (7) 4297
10.3%
Hangul
ValueCountFrequency (%)
8
25.0%
8
25.0%
8
25.0%
8
25.0%

lastmodts
Real number (ℝ)

Distinct1734
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0125817 × 1013
Minimum1.999021 × 1013
Maximum2.0201218 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.2 KiB
2024-04-16T17:12:18.652625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.999021 × 1013
5-th percentile2.0020735 × 1013
Q12.0057884 × 1013
median2.0140311 × 1013
Q32.0190226 × 1013
95-th percentile2.0200928 × 1013
Maximum2.0201218 × 1013
Range2.1100814 × 1011
Interquartile range (IQR)1.3234213 × 1011

Descriptive statistics

Standard deviation6.5394914 × 1010
Coefficient of variation (CV)0.0032493048
Kurtosis-1.2275205
Mean2.0125817 × 1013
Median Absolute Deviation (MAD)5.0791536 × 1010
Skewness-0.45149474
Sum4.3713275 × 1016
Variance4.2764948 × 1021
MonotonicityNot monotonic
2024-04-16T17:12:18.762546image/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
 
0.6%
20030303000000 12
 
0.6%
20040324000000 11
 
0.5%
20020422000000 10
 
0.5%
20041208000000 9
 
0.4%
20030722000000 8
 
0.4%
Other values (1724) 2024
93.2%
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 (%)
20201218142502 1
< 0.1%
20201218142114 1
< 0.1%
20201218130732 1
< 0.1%
20201217134720 1
< 0.1%
20201217110351 1
< 0.1%
20201217105929 1
< 0.1%
20201217105512 1
< 0.1%
20201216164650 1
< 0.1%
20201216134859 1
< 0.1%
20201216112931 2
0.1%

uptaenm
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
공동탕업
1680 
목욕장업 기타
213 
공동탕업+찜질시설서비스영업
 
159
찜질시설서비스영업
 
75
한증막업
 
45

Length

Max length14
Median length4
Mean length5.198895
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 1680
77.3%
목욕장업 기타 213
 
9.8%
공동탕업+찜질시설서비스영업 159
 
7.3%
찜질시설서비스영업 75
 
3.5%
한증막업 45
 
2.1%

Length

2024-04-16T17:12:18.863181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:18.957821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1680
70.4%
목욕장업 213
 
8.9%
기타 213
 
8.9%
공동탕업+찜질시설서비스영업 159
 
6.7%
찜질시설서비스영업 75
 
3.1%
한증막업 45
 
1.9%
Distinct78
Distinct (%)3.6%
Missing17
Missing (%)0.8%
Memory size17.1 KiB
2024-04-16T17:12:19.093902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.935499
Min length4

Characters and Unicode

Total characters25721
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

Unique72 ?
Unique (%)3.3%

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 2061
90.6%
051 40
 
1.8%
전화번호 12
 
0.5%
055 8
 
0.4%
031 7
 
0.3%
064 4
 
0.2%
052 4
 
0.2%
5757 3
 
0.1%
533 3
 
0.1%
739 3
 
0.1%
Other values (119) 131
 
5.8%
2024-04-16T17:12:19.323103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6282
24.4%
3 4203
16.3%
2 4187
16.3%
- 4122
16.0%
0 2226
 
8.7%
5 2181
 
8.5%
4 2102
 
8.2%
126
 
0.5%
6 75
 
0.3%
7 66
 
0.3%
Other values (6) 151
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21425
83.3%
Dash Punctuation 4122
 
16.0%
Space Separator 126
 
0.5%
Other Letter 48
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6282
29.3%
3 4203
19.6%
2 4187
19.5%
0 2226
 
10.4%
5 2181
 
10.2%
4 2102
 
9.8%
6 75
 
0.4%
7 66
 
0.3%
8 55
 
0.3%
9 48
 
0.2%
Other Letter
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 4122
100.0%
Space Separator
ValueCountFrequency (%)
126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25673
99.8%
Hangul 48
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6282
24.5%
3 4203
16.4%
2 4187
16.3%
- 4122
16.1%
0 2226
 
8.7%
5 2181
 
8.5%
4 2102
 
8.2%
126
 
0.5%
6 75
 
0.3%
7 66
 
0.3%
Other values (2) 103
 
0.4%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25673
99.8%
Hangul 48
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6282
24.5%
3 4203
16.4%
2 4187
16.3%
- 4122
16.1%
0 2226
 
8.7%
5 2181
 
8.5%
4 2102
 
8.2%
126
 
0.5%
6 75
 
0.3%
7 66
 
0.3%
Other values (2) 103
 
0.4%
Hangul
ValueCountFrequency (%)
12
25.0%
12
25.0%
12
25.0%
12
25.0%

bdngownsenm
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1505 
자가
330 
임대
174 
건물소유구분명
163 

Length

Max length7
Median length4
Mean length3.7610497
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> 1505
69.3%
자가 330
 
15.2%
임대 174
 
8.0%
건물소유구분명 163
 
7.5%

Length

2024-04-16T17:12:19.442247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:19.545152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1505
69.3%
자가 330
 
15.2%
임대 174
 
8.0%
건물소유구분명 163
 
7.5%

bdngjisgflrcnt
Categorical

Distinct37
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
0
517 
<NA>
466 
3
329 
4
223 
2
176 
Other values (32)
461 

Length

Max length6
Median length1
Mean length1.7007366
Min length1

Unique

Unique10 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 517
23.8%
<NA> 466
21.5%
3 329
15.1%
4 223
10.3%
2 176
 
8.1%
5 145
 
6.7%
6 57
 
2.6%
7 51
 
2.3%
1 49
 
2.3%
8 35
 
1.6%
Other values (27) 124
 
5.7%

Length

2024-04-16T17:12:19.655233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 517
23.8%
na 466
21.5%
3 329
15.1%
4 223
10.3%
2 176
 
8.1%
5 145
 
6.7%
6 57
 
2.6%
7 51
 
2.3%
1 49
 
2.3%
8 35
 
1.6%
Other values (27) 124
 
5.7%

bdngunderflrcnt
Categorical

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
0
784 
<NA>
707 
1
507 
2
94 
3
 
32
Other values (5)
 
48

Length

Max length6
Median length1
Mean length1.9926335
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 784
36.1%
<NA> 707
32.6%
1 507
23.3%
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

2024-04-16T17:12:19.748228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:19.844174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 784
36.1%
na 707
32.6%
1 507
23.3%
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 

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1771 
0
336 
1
 
32
남성종사자수
 
21
5
 
4
Other values (3)
 
8

Length

Max length6
Median length4
Mean length3.4944751
Min length1

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> 1771
81.5%
0 336
 
15.5%
1 32
 
1.5%
남성종사자수 21
 
1.0%
5 4
 
0.2%
2 4
 
0.2%
4 2
 
0.1%
3 2
 
0.1%

Length

2024-04-16T17:12:19.962492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:20.056803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1771
81.5%
0 336
 
15.5%
1 32
 
1.5%
남성종사자수 21
 
1.0%
5 4
 
0.2%
2 4
 
0.2%
4 2
 
0.1%
3 2
 
0.1%

multusnupsoyn
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
False
2027 
True
 
145
ValueCountFrequency (%)
False 2027
93.3%
True 145
 
6.7%
2024-04-16T17:12:20.148072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing2
Missing (%)0.1%
Memory size4.4 KiB
False
1562 
True
608 
(Missing)
 
2
ValueCountFrequency (%)
False 1562
71.9%
True 608
 
28.0%
(Missing) 2
 
0.1%
2024-04-16T17:12:20.223722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

usejisgendflr
Categorical

Distinct14
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
838 
2
437 
3
232 
0
219 
1
134 
Other values (9)
312 

Length

Max length6
Median length1
Mean length2.3678637
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 838
38.6%
2 437
20.1%
3 232
 
10.7%
0 219
 
10.1%
1 134
 
6.2%
4 93
 
4.3%
사용끝지상층 89
 
4.1%
5 60
 
2.8%
6 26
 
1.2%
7 14
 
0.6%
Other values (4) 30
 
1.4%

Length

2024-04-16T17:12:20.310233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 838
38.6%
2 437
20.1%
3 232
 
10.7%
0 219
 
10.1%
1 134
 
6.2%
4 93
 
4.3%
사용끝지상층 89
 
4.1%
5 60
 
2.8%
6 26
 
1.2%
7 14
 
0.6%
Other values (4) 30
 
1.4%

useunderendflr
Categorical

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1299 
0
588 
사용끝지하층
146 
1
 
103
2
 
31
Other values (2)
 
5

Length

Max length6
Median length4
Mean length3.1302947
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1299
59.8%
0 588
27.1%
사용끝지하층 146
 
6.7%
1 103
 
4.7%
2 31
 
1.4%
3 4
 
0.2%
4 1
 
< 0.1%

Length

2024-04-16T17:12:20.403277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:20.495006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1299
59.8%
0 588
27.1%
사용끝지하층 146
 
6.7%
1 103
 
4.7%
2 31
 
1.4%
3 4
 
0.2%
4 1
 
< 0.1%

usejisgstflr
Categorical

Distinct14
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
687 
1
464 
0
380 
2
357 
3
91 
Other values (9)
193 

Length

Max length7
Median length1
Mean length2.1491713
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 687
31.6%
1 464
21.4%
0 380
17.5%
2 357
16.4%
3 91
 
4.2%
사용시작지상층 71
 
3.3%
4 53
 
2.4%
5 23
 
1.1%
6 17
 
0.8%
10 8
 
0.4%
Other values (4) 21
 
1.0%

Length

2024-04-16T17:12:20.600843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 687
31.6%
1 464
21.4%
0 380
17.5%
2 357
16.4%
3 91
 
4.2%
사용시작지상층 71
 
3.3%
4 53
 
2.4%
5 23
 
1.1%
6 17
 
0.8%
10 8
 
0.4%
Other values (4) 21
 
1.0%

useunderstflr
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1034 
0
849 
사용시작지하층
140 
1
128 
2
 
17

Length

Max length7
Median length4
Mean length2.8149171
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1034
47.6%
0 849
39.1%
사용시작지하층 140
 
6.4%
1 128
 
5.9%
2 17
 
0.8%
3 4
 
0.2%

Length

2024-04-16T17:12:20.975631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:21.072788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1034
47.6%
0 849
39.1%
사용시작지하층 140
 
6.4%
1 128
 
5.9%
2 17
 
0.8%
3 4
 
0.2%

washmccnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1248 
0
918 
세탁기수
 
6

Length

Max length4
Median length4
Mean length2.7320442
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1248
57.5%
0 918
42.3%
세탁기수 6
 
0.3%

Length

2024-04-16T17:12:21.183063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:21.284247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1248
57.5%
0 918
42.3%
세탁기수 6
 
0.3%

yangsilcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
0
1187 
<NA>
979 
양실수
 
6

Length

Max length4
Median length1
Mean length2.3577348
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1187
54.7%
<NA> 979
45.1%
양실수 6
 
0.3%

Length

2024-04-16T17:12:21.390962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:21.487294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1187
54.7%
na 979
45.1%
양실수 6
 
0.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1771 
0
338 
1
 
23
여성종사자수
 
21
2
 
10
Other values (3)
 
9

Length

Max length6
Median length4
Mean length3.4944751
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> 1771
81.5%
0 338
 
15.6%
1 23
 
1.1%
여성종사자수 21
 
1.0%
2 10
 
0.5%
5 5
 
0.2%
3 3
 
0.1%
4 1
 
< 0.1%

Length

2024-04-16T17:12:21.598040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:21.709630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1771
81.5%
0 338
 
15.6%
1 23
 
1.1%
여성종사자수 21
 
1.0%
2 10
 
0.5%
5 5
 
0.2%
3 3
 
0.1%
4 1
 
< 0.1%

yoksilcnt
Categorical

Distinct21
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
0
687 
<NA>
643 
2
605 
1
 
63
4
 
47
Other values (16)
127 

Length

Max length4
Median length1
Mean length1.9014733
Min length1

Unique

Unique5 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 687
31.6%
<NA> 643
29.6%
2 605
27.9%
1 63
 
2.9%
4 47
 
2.2%
6 45
 
2.1%
8 29
 
1.3%
7 9
 
0.4%
3 7
 
0.3%
10 7
 
0.3%
Other values (11) 30
 
1.4%

Length

2024-04-16T17:12:21.846318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 687
31.6%
na 643
29.6%
2 605
27.9%
1 63
 
2.9%
4 47
 
2.2%
6 45
 
2.1%
8 29
 
1.3%
7 9
 
0.4%
10 7
 
0.3%
9 7
 
0.3%
Other values (11) 30
 
1.4%

sntuptaenm
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
공동탕업
1680 
목욕장업 기타
213 
공동탕업+찜질시설서비스영업
 
159
찜질시설서비스영업
 
75
한증막업
 
45

Length

Max length14
Median length4
Mean length5.198895
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 1680
77.3%
목욕장업 기타 213
 
9.8%
공동탕업+찜질시설서비스영업 159
 
7.3%
찜질시설서비스영업 75
 
3.5%
한증막업 45
 
2.1%

Length

2024-04-16T17:12:21.949694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:22.041262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1680
70.4%
목욕장업 213
 
8.9%
기타 213
 
8.9%
공동탕업+찜질시설서비스영업 159
 
6.7%
찜질시설서비스영업 75
 
3.1%
한증막업 45
 
1.9%

chaircnt
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
0
1186 
<NA>
979 
의자수
 
6
2
 
1

Length

Max length4
Median length1
Mean length2.3577348
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1186
54.6%
<NA> 979
45.1%
의자수 6
 
0.3%
2 1
 
< 0.1%

Length

2024-04-16T17:12:22.161597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:22.247957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1186
54.6%
na 979
45.1%
의자수 6
 
0.3%
2 1
 
< 0.1%

cndpermstymd
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1940 
조건부허가시작일자
230 
20190501
 
1
20190228
 
1

Length

Max length9
Median length4
Mean length4.5331492
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> 1940
89.3%
조건부허가시작일자 230
 
10.6%
20190501 1
 
< 0.1%
20190228 1
 
< 0.1%

Length

2024-04-16T17:12:22.330926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:22.420452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1940
89.3%
조건부허가시작일자 230
 
10.6%
20190501 1
 
< 0.1%
20190228 1
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1940 
조건부허가신고사유
231 
건축과-16824(2019.4.15),가설건축물 존치기간연장 신고
 
1

Length

Max length36
Median length4
Mean length4.5465009
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> 1940
89.3%
조건부허가신고사유 231
 
10.6%
건축과-16824(2019.4.15),가설건축물 존치기간연장 신고 1
 
< 0.1%

Length

2024-04-16T17:12:22.537041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:22.641921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1940
89.2%
조건부허가신고사유 231
 
10.6%
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 size17.1 KiB
<NA>
1940 
조건부허가종료일자
230 
20210421
 
1
20220831
 
1

Length

Max length9
Median length4
Mean length4.5331492
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> 1940
89.3%
조건부허가종료일자 230
 
10.6%
20210421 1
 
< 0.1%
20220831 1
 
< 0.1%

Length

2024-04-16T17:12:22.753517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:22.833001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1940
89.3%
조건부허가종료일자 230
 
10.6%
20210421 1
 
< 0.1%
20220831 1
 
< 0.1%

abedcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1275 
0
890 
침대수
 
7

Length

Max length4
Median length4
Mean length2.7674954
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1275
58.7%
0 890
41.0%
침대수 7
 
0.3%

Length

2024-04-16T17:12:22.925526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:23.008154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1275
58.7%
0 890
41.0%
침대수 7
 
0.3%

hanshilcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
0
1187 
<NA>
979 
한실수
 
6

Length

Max length4
Median length1
Mean length2.3577348
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1187
54.7%
<NA> 979
45.1%
한실수 6
 
0.3%

Length

2024-04-16T17:12:23.122584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:23.210031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1187
54.7%
na 979
45.1%
한실수 6
 
0.3%

rcvdryncnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
<NA>
1274 
0
891 
회수건조수
 
7

Length

Max length5
Median length4
Mean length2.7725599
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
58.7%
0 891
41.0%
회수건조수 7
 
0.3%

Length

2024-04-16T17:12:23.303616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:23.409034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1274
58.7%
0 891
41.0%
회수건조수 7
 
0.3%

last_load_dttm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.1 KiB
2020-12-22 13:48:41
1496 
2020-12-22 13:48:40
676 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-22 13:48:40
2nd row2020-12-22 13:48:40
3rd row2020-12-22 13:48:40
4th row2020-12-22 13:48:40
5th row2020-12-22 13:48:40

Common Values

ValueCountFrequency (%)
2020-12-22 13:48:41 1496
68.9%
2020-12-22 13:48:40 676
31.1%

Length

2024-04-16T17:12:23.507137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T17:12:23.587178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-22 2172
50.0%
13:48:41 1496
34.4%
13:48:40 676
 
15.6%

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>0002020-12-22 13:48:40
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>2020-12-22 13:48:40
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>2020-12-22 13:48:40
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>0002020-12-22 13:48:40
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>0002020-12-22 13:48:40
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>0002020-12-22 13:48:40
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>0002020-12-22 13:48:40
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>2020-12-22 13:48:40
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>0002020-12-22 13:48:40
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>2020-12-22 13:48:40
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
2162216548100004810000-202-2020-0000311_44_01_PI2020-11-22 00:23:08.0목욕장업수 사우나 찜질방550040전라남도 여수시 종화동 581-259746전라남도 여수시 이순신광장로 204 (종화동)20201120폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업268152.705214138119.44642820201120090406공동탕업+찜질시설서비스영업061 662 6200건물소유구분명520NN사용끝지상층사용끝지하층220002공동탕업+찜질시설서비스영업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002020-12-22 13:48:41
2163216648100004810000-202-2020-0000311_44_01_PI2020-11-22 00:23:08.0목욕장업수 사우나 찜질방550040전라남도 여수시 종화동 581-259746전라남도 여수시 이순신광장로 204 (종화동)20201120폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업268152.705214138119.44642820201120090406공동탕업+찜질시설서비스영업061 662 6200건물소유구분명520NN사용끝지상층사용끝지하층220002공동탕업+찜질시설서비스영업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002020-12-22 13:48:41
2164216742800004280000-202-2020-0000111_44_01_PI2020-12-04 00:23:19.0목욕장업힐스템건강찜질232806강원도 평창군 평창읍 중리 308-525375강원도 평창군 평창읍 천변길 5120201202폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업323799.724008626430324.51870678620201202110331찜질시설서비스영업전화번호건물소유구분명001NY사용끝지상층사용끝지하층사용시작지상층사용시작지하층0000찜질시설서비스영업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002020-12-22 13:48:41
2165216855400005540000-202-2020-0000111_44_01_PI2020-12-05 00:23:25.0목욕장업GG사우나464872경기도 광주시 곤지암읍 곤지암리 436-112804경기도 광주시 곤지암읍 곤지암로50번길 420201203폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업230148.466237277427604.91749303220201203135730공동탕업031 764 6158임대511NN사용끝지상층사용끝지하층사용시작지상층10012공동탕업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002020-12-22 13:48:41
2166216934600003460000-202-2020-0000111_44_01_PU2020-12-18 02:40:00.0목욕장업히트짐범어점706824대구광역시 수성구 범어동 559-3 대백상호신용금고 지하1층42117대구광역시 수성구 달구벌대로 2382-1, 대백상호신용금고 지하1층 (범어동)20201211폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업346559.922604263306.49908620201216112931공동탕업053 7512020임대520NY01010002공동탕업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002020-12-22 13:48:41
2167217034600003460000-202-2020-0000111_44_01_PU2020-12-18 02:40:00.0목욕장업히트짐범어점706824대구광역시 수성구 범어동 559-3 대백상호신용금고 지하1층42117대구광역시 수성구 달구벌대로 2382-1, 대백상호신용금고 지하1층 (범어동)20201211폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업346559.922604263306.49908620201216112931공동탕업053 7512020임대520NY01010002공동탕업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002020-12-22 13:48:41
2168217165200006520000-202-2020-0000511_44_01_PI2020-12-17 00:23:06.0목욕장업그랑조이697807제주특별자치도 서귀포시 색달동 210163535제주특별자치도 서귀포시 중문관광로72번길 60, 지하 2층(구관) (색달동)20201215폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업144475.137879-27188.466696820201215170116공동탕업전화번호건물소유구분명000NN사용끝지상층사용끝지하층2사용시작지하층0002공동탕업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002020-12-22 13:48:41
2169217265200006520000-202-2020-0000611_44_01_PI2020-12-17 00:23:06.0목욕장업그랑조이 힐스윗697807제주특별자치도 서귀포시 색달동 210163535제주특별자치도 서귀포시 중문관광로72번길 60, 3층(신관) (색달동)20201215<NA><NA><NA><NA>영업/정상영업144475.137879-27188.466696820201215165921공동탕업<NA><NA>000NN<NA><NA>3<NA>0000공동탕업0<NA><NA><NA>0002020-12-22 13:48:41
2170217365100006510000-202-2020-0000211_44_01_PI2020-12-19 00:23:16.0목욕장업그랜드하얏트제주690802제주특별자치도 제주시 노형동 925 제주 드림타워 복합리조트63082제주특별자치도 제주시 노연로 12, 제주 드림타워 복합리조트 6층 (노형동)20201217폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업151732.711618-1108.9748299520201217105929공동탕업064795 6336건물소유구분명000YN6사용끝지하층6사용시작지하층0002공동탕업0조건부허가시작일자조건부허가신고사유조건부허가종료일자0002020-12-22 13:48:41
2171217447900004790000-202-2020-0000111_44_01_PI2020-12-19 00:23:16.0목욕장업어울림 목욕탕579824전라북도 부안군 계화면 창북리 472 계화면복지회관56301전라북도 부안군 계화면 창북3길 11-3, 계화면복지회관20201217<NA><NA><NA><NA>영업/정상영업172596.707531251310.92887320201217105512목욕장업 기타<NA><NA>200NY<NA><NA>1<NA>0004목욕장업 기타0<NA><NA><NA>0002020-12-22 13:48:41