Overview

Dataset statistics

Number of variables47
Number of observations6923
Missing cells9006
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 MiB
Average record size in memory381.0 B

Variable types

Numeric5
Text9
Categorical29
DateTime2
Boolean2

Alerts

opnsvcid has constant value ""Constant
balhansilyn has constant value ""Constant
clgstdt is highly imbalanced (69.1%)Imbalance
clgenddt is highly imbalanced (69.1%)Imbalance
ropnymd is highly imbalanced (69.1%)Imbalance
uptaenm is highly imbalanced (92.7%)Imbalance
bdngownsenm is highly imbalanced (50.1%)Imbalance
bdngunderflrcnt is highly imbalanced (54.3%)Imbalance
maneipcnt is highly imbalanced (57.1%)Imbalance
multusnupsoyn is highly imbalanced (99.0%)Imbalance
useunderendflr is highly imbalanced (54.3%)Imbalance
wmeipcnt is highly imbalanced (56.6%)Imbalance
sntuptaenm is highly imbalanced (92.6%)Imbalance
cndpermstymd is highly imbalanced (88.6%)Imbalance
cndpermntwhy is highly imbalanced (87.7%)Imbalance
cndpermendymd is highly imbalanced (88.6%)Imbalance
abedcnt is highly imbalanced (64.2%)Imbalance
rdnpostno has 2664 (38.5%) missing valuesMissing
rdnwhladdr has 2607 (37.7%) missing valuesMissing
dcbymd has 2732 (39.5%) missing valuesMissing
x has 327 (4.7%) missing valuesMissing
y has 327 (4.7%) missing valuesMissing
sitetel has 276 (4.0%) missing valuesMissing
apvpermymd is highly skewed (γ1 = -20.1168622)Skewed
skey has unique valuesUnique

Reproduction

Analysis started2024-04-17 01:47:02.424405
Analysis finished2024-04-17 01:47:04.357215
Duration1.93 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct6923
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3462.1694
Minimum1
Maximum6924
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.0 KiB
2024-04-17T10:47:04.413366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile347.1
Q11731.5
median3462
Q35192.5
95-th percentile6577.9
Maximum6924
Range6923
Interquartile range (IQR)3461

Descriptive statistics

Standard deviation1998.8861
Coefficient of variation (CV)0.57735074
Kurtosis-1.1998263
Mean3462.1694
Median Absolute Deviation (MAD)1731
Skewness0.00027940534
Sum23968599
Variance3995545.5
MonotonicityNot monotonic
2024-04-17T10:47:04.535138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 1
 
< 0.1%
4614 1
 
< 0.1%
4648 1
 
< 0.1%
4623 1
 
< 0.1%
4622 1
 
< 0.1%
4621 1
 
< 0.1%
4620 1
 
< 0.1%
4619 1
 
< 0.1%
4618 1
 
< 0.1%
4591 1
 
< 0.1%
Other values (6913) 6913
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
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%
ValueCountFrequency (%)
6924 1
< 0.1%
6923 1
< 0.1%
6922 1
< 0.1%
6921 1
< 0.1%
6920 1
< 0.1%
6919 1
< 0.1%
6918 1
< 0.1%
6917 1
< 0.1%
6916 1
< 0.1%
6915 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct202
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3534250.5
Minimum3000000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.0 KiB
2024-04-17T10:47:04.654934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3200000
Q13290000
median3340000
Q33390000
95-th percentile5090000
Maximum6520000
Range3520000
Interquartile range (IQR)100000

Descriptive statistics

Standard deviation567783.07
Coefficient of variation (CV)0.16065162
Kurtosis7.1532268
Mean3534250.5
Median Absolute Deviation (MAD)50000
Skewness2.7525733
Sum2.4467616 × 1010
Variance3.2237762 × 1011
MonotonicityNot monotonic
2024-04-17T10:47:04.777365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3290000 506
 
7.3%
3340000 501
 
7.2%
3300000 415
 
6.0%
3320000 410
 
5.9%
3330000 392
 
5.7%
3350000 377
 
5.4%
3390000 335
 
4.8%
3370000 327
 
4.7%
3310000 322
 
4.7%
3380000 282
 
4.1%
Other values (192) 3056
44.1%
ValueCountFrequency (%)
3000000 20
0.3%
3010000 19
0.3%
3020000 23
0.3%
3030000 10
0.1%
3040000 17
0.2%
3050000 22
0.3%
3060000 16
0.2%
3070000 13
0.2%
3080000 19
0.3%
3090000 8
 
0.1%
ValueCountFrequency (%)
6520000 7
 
0.1%
6510000 16
 
0.2%
5710000 23
0.3%
5700000 4
 
0.1%
5690000 13
 
0.2%
5680000 6
 
0.1%
5670000 55
0.8%
5600000 2
 
< 0.1%
5590000 4
 
0.1%
5580000 1
 
< 0.1%

mgtno
Text

Distinct6422
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
2024-04-17T10:47:05.167864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters152306
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

Unique6142 ?
Unique (%)88.7%

Sample

1st row3250000-203-1980-00478
2nd row3250000-203-2005-00004
3rd row3250000-203-2005-00005
4th row3250000-203-1972-00443
5th row3250000-203-2005-00001
ValueCountFrequency (%)
5530000-203-2020-00005 4
 
0.1%
3300000-203-2019-00008 3
 
< 0.1%
3290000-203-2019-00008 3
 
< 0.1%
6510000-203-2019-00005 3
 
< 0.1%
3920000-203-2019-00002 3
 
< 0.1%
3810000-203-2019-00008 3
 
< 0.1%
3690000-203-2018-00007 3
 
< 0.1%
3820000-203-2013-00009 3
 
< 0.1%
3180000-203-2019-00006 3
 
< 0.1%
3150000-203-2019-00007 3
 
< 0.1%
Other values (6412) 6892
99.6%
2024-04-17T10:47:05.461675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 64262
42.2%
- 20769
 
13.6%
3 19289
 
12.7%
2 16535
 
10.9%
1 8544
 
5.6%
9 7367
 
4.8%
5 3281
 
2.2%
4 3252
 
2.1%
8 3212
 
2.1%
7 2903
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 131537
86.4%
Dash Punctuation 20769
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 64262
48.9%
3 19289
 
14.7%
2 16535
 
12.6%
1 8544
 
6.5%
9 7367
 
5.6%
5 3281
 
2.5%
4 3252
 
2.5%
8 3212
 
2.4%
7 2903
 
2.2%
6 2892
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 20769
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 152306
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 64262
42.2%
- 20769
 
13.6%
3 19289
 
12.7%
2 16535
 
10.9%
1 8544
 
5.6%
9 7367
 
4.8%
5 3281
 
2.2%
4 3252
 
2.1%
8 3212
 
2.1%
7 2903
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 152306
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 64262
42.2%
- 20769
 
13.6%
3 19289
 
12.7%
2 16535
 
10.9%
1 8544
 
5.6%
9 7367
 
4.8%
5 3281
 
2.2%
4 3252
 
2.1%
8 3212
 
2.1%
7 2903
 
1.9%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
05_19_01_P
6923 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05_19_01_P
2nd row05_19_01_P
3rd row05_19_01_P
4th row05_19_01_P
5th row05_19_01_P

Common Values

ValueCountFrequency (%)
05_19_01_P 6923
100.0%

Length

2024-04-17T10:47:05.583849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:05.663326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 6923
100.0%

updategbn
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
I
5786 
U
1137 

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 5786
83.6%
U 1137
 
16.4%

Length

2024-04-17T10:47:05.742350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:05.820022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5786
83.6%
u 1137
 
16.4%
Distinct827
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
Minimum2018-08-31 23:59:59
Maximum2020-12-20 02:40:00
2024-04-17T10:47:05.907552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T10:47:06.019840image/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 size54.2 KiB
<NA>
4573 
이용업
2350 

Length

Max length4
Median length4
Mean length3.6605518
Min length3

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> 4573
66.1%
이용업 2350
33.9%

Length

2024-04-17T10:47:06.131558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:06.230402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4573
66.1%
이용업 2350
33.9%

bplcnm
Text

Distinct4567
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
2024-04-17T10:47:06.453700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length5.3602484
Min length1

Characters and Unicode

Total characters37109
Distinct characters687
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3575 ?
Unique (%)51.6%

Sample

1st row태양탕구내
2nd row국사 이용원
3rd row녹수탕구내이용원
4th row부산호텔이용원
5th row터프가위 이용원
ValueCountFrequency (%)
이용원 422
 
5.1%
바버샵 101
 
1.2%
구내 56
 
0.7%
태후사랑 53
 
0.6%
퀸즈헤나 52
 
0.6%
컷트실 51
 
0.6%
구내이용원 40
 
0.5%
현대 36
 
0.4%
블루클럽 30
 
0.4%
이발관 30
 
0.4%
Other values (4461) 7430
89.5%
2024-04-17T10:47:06.854614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3101
 
8.4%
2558
 
6.9%
2401
 
6.5%
1391
 
3.7%
1032
 
2.8%
897
 
2.4%
638
 
1.7%
599
 
1.6%
540
 
1.5%
454
 
1.2%
Other values (677) 23498
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33721
90.9%
Space Separator 1391
 
3.7%
Lowercase Letter 717
 
1.9%
Uppercase Letter 709
 
1.9%
Close Punctuation 197
 
0.5%
Open Punctuation 197
 
0.5%
Decimal Number 111
 
0.3%
Other Punctuation 57
 
0.2%
Dash Punctuation 8
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3101
 
9.2%
2558
 
7.6%
2401
 
7.1%
1032
 
3.1%
897
 
2.7%
638
 
1.9%
599
 
1.8%
540
 
1.6%
454
 
1.3%
447
 
1.3%
Other values (605) 21054
62.4%
Uppercase Letter
ValueCountFrequency (%)
B 99
14.0%
R 66
 
9.3%
O 64
 
9.0%
S 62
 
8.7%
E 59
 
8.3%
H 44
 
6.2%
A 42
 
5.9%
T 36
 
5.1%
P 30
 
4.2%
C 27
 
3.8%
Other values (16) 180
25.4%
Lowercase Letter
ValueCountFrequency (%)
r 102
14.2%
e 77
10.7%
a 74
10.3%
o 65
9.1%
h 56
7.8%
b 55
7.7%
s 47
 
6.6%
p 39
 
5.4%
n 35
 
4.9%
i 30
 
4.2%
Other values (14) 137
19.1%
Decimal Number
ValueCountFrequency (%)
2 23
20.7%
1 19
17.1%
8 18
16.2%
3 14
12.6%
9 10
9.0%
4 8
 
7.2%
5 7
 
6.3%
7 6
 
5.4%
0 5
 
4.5%
6 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 28
49.1%
& 11
 
19.3%
' 6
 
10.5%
, 5
 
8.8%
· 4
 
7.0%
# 2
 
3.5%
: 1
 
1.8%
Space Separator
ValueCountFrequency (%)
1391
100.0%
Close Punctuation
ValueCountFrequency (%)
) 197
100.0%
Open Punctuation
ValueCountFrequency (%)
( 197
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33716
90.9%
Common 1962
 
5.3%
Latin 1426
 
3.8%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3101
 
9.2%
2558
 
7.6%
2401
 
7.1%
1032
 
3.1%
897
 
2.7%
638
 
1.9%
599
 
1.8%
540
 
1.6%
454
 
1.3%
447
 
1.3%
Other values (600) 21049
62.4%
Latin
ValueCountFrequency (%)
r 102
 
7.2%
B 99
 
6.9%
e 77
 
5.4%
a 74
 
5.2%
R 66
 
4.6%
o 65
 
4.6%
O 64
 
4.5%
S 62
 
4.3%
E 59
 
4.1%
h 56
 
3.9%
Other values (40) 702
49.2%
Common
ValueCountFrequency (%)
1391
70.9%
) 197
 
10.0%
( 197
 
10.0%
. 28
 
1.4%
2 23
 
1.2%
1 19
 
1.0%
8 18
 
0.9%
3 14
 
0.7%
& 11
 
0.6%
9 10
 
0.5%
Other values (12) 54
 
2.8%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33716
90.9%
ASCII 3384
 
9.1%
CJK 5
 
< 0.1%
None 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3101
 
9.2%
2558
 
7.6%
2401
 
7.1%
1032
 
3.1%
897
 
2.7%
638
 
1.9%
599
 
1.8%
540
 
1.6%
454
 
1.3%
447
 
1.3%
Other values (600) 21049
62.4%
ASCII
ValueCountFrequency (%)
1391
41.1%
) 197
 
5.8%
( 197
 
5.8%
r 102
 
3.0%
B 99
 
2.9%
e 77
 
2.3%
a 74
 
2.2%
R 66
 
2.0%
o 65
 
1.9%
O 64
 
1.9%
Other values (61) 1052
31.1%
None
ValueCountFrequency (%)
· 4
100.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Distinct2030
Distinct (%)29.6%
Missing69
Missing (%)1.0%
Memory size54.2 KiB
2024-04-17T10:47:07.143310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters41124
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

Unique999 ?
Unique (%)14.6%

Sample

1st row600046
2nd row600061
3rd row600062
4th row600022
5th row600816
ValueCountFrequency (%)
607833 33
 
0.5%
601829 28
 
0.4%
616801 28
 
0.4%
612847 27
 
0.4%
604851 27
 
0.4%
607826 24
 
0.4%
617818 24
 
0.4%
616807 23
 
0.3%
611803 22
 
0.3%
604813 21
 
0.3%
Other values (2020) 6597
96.3%
2024-04-17T10:47:07.524413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 6932
16.9%
6 6901
16.8%
0 6744
16.4%
1 6150
15.0%
2 3169
7.7%
4 3087
7.5%
3 2897
7.0%
7 2049
 
5.0%
5 1581
 
3.8%
9 1530
 
3.7%
Other values (5) 84
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41040
99.8%
Other Letter 84
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 6932
16.9%
6 6901
16.8%
0 6744
16.4%
1 6150
15.0%
2 3169
7.7%
4 3087
7.5%
3 2897
7.1%
7 2049
 
5.0%
5 1581
 
3.9%
9 1530
 
3.7%
Other Letter
ValueCountFrequency (%)
28
33.3%
14
16.7%
14
16.7%
14
16.7%
14
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 41040
99.8%
Hangul 84
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
8 6932
16.9%
6 6901
16.8%
0 6744
16.4%
1 6150
15.0%
2 3169
7.7%
4 3087
7.5%
3 2897
7.1%
7 2049
 
5.0%
5 1581
 
3.9%
9 1530
 
3.7%
Hangul
ValueCountFrequency (%)
28
33.3%
14
16.7%
14
16.7%
14
16.7%
14
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41040
99.8%
Hangul 84
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 6932
16.9%
6 6901
16.8%
0 6744
16.4%
1 6150
15.0%
2 3169
7.7%
4 3087
7.5%
3 2897
7.1%
7 2049
 
5.0%
5 1581
 
3.9%
9 1530
 
3.7%
Hangul
ValueCountFrequency (%)
28
33.3%
14
16.7%
14
16.7%
14
16.7%
14
16.7%
Distinct5807
Distinct (%)83.9%
Missing3
Missing (%)< 0.1%
Memory size54.2 KiB
2024-04-17T10:47:07.796454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length55
Mean length25.312861
Min length7

Characters and Unicode

Total characters175165
Distinct characters542
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5060 ?
Unique (%)73.1%

Sample

1st row부산광역시 중구 남포동6가 115-5번지 (지하1층)
2nd row부산광역시 중구 신창동1가 35-2번지 (2층)
3rd row부산광역시 중구 신창동2가 21-2번지 (2층)
4th row부산광역시 중구 동광동2가 12-1번지 외11필지
5th row부산광역시 중구 중앙동4가 78-20번지 (1층)
ValueCountFrequency (%)
부산광역시 4902
 
15.0%
t통b반 768
 
2.4%
부산진구 506
 
1.5%
사하구 503
 
1.5%
서울특별시 485
 
1.5%
북구 481
 
1.5%
경기도 436
 
1.3%
동래구 415
 
1.3%
해운대구 392
 
1.2%
남구 391
 
1.2%
Other values (7889) 23400
71.6%
2024-04-17T10:47:08.192464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32343
 
18.5%
7871
 
4.5%
1 7387
 
4.2%
6893
 
3.9%
6652
 
3.8%
6531
 
3.7%
6298
 
3.6%
6216
 
3.5%
- 6092
 
3.5%
6073
 
3.5%
Other values (532) 82809
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 101086
57.7%
Decimal Number 33277
 
19.0%
Space Separator 32343
 
18.5%
Dash Punctuation 6092
 
3.5%
Uppercase Letter 1659
 
0.9%
Open Punctuation 279
 
0.2%
Close Punctuation 278
 
0.2%
Other Punctuation 142
 
0.1%
Math Symbol 4
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7871
 
7.8%
6893
 
6.8%
6652
 
6.6%
6531
 
6.5%
6298
 
6.2%
6216
 
6.1%
6073
 
6.0%
5676
 
5.6%
5395
 
5.3%
1369
 
1.4%
Other values (486) 42112
41.7%
Uppercase Letter
ValueCountFrequency (%)
B 804
48.5%
T 771
46.5%
A 30
 
1.8%
S 9
 
0.5%
I 6
 
0.4%
L 5
 
0.3%
F 5
 
0.3%
C 5
 
0.3%
K 4
 
0.2%
M 3
 
0.2%
Other values (11) 17
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 7387
22.2%
2 4421
13.3%
3 3719
11.2%
4 3109
9.3%
5 2950
 
8.9%
0 2594
 
7.8%
6 2447
 
7.4%
8 2338
 
7.0%
7 2329
 
7.0%
9 1983
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 126
88.7%
. 7
 
4.9%
@ 6
 
4.2%
/ 3
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
s 1
25.0%
p 1
25.0%
a 1
25.0%
e 1
25.0%
Math Symbol
ValueCountFrequency (%)
~ 3
75.0%
+ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
32343
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6092
100.0%
Open Punctuation
ValueCountFrequency (%)
( 279
100.0%
Close Punctuation
ValueCountFrequency (%)
) 278
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 101084
57.7%
Common 72415
41.3%
Latin 1664
 
0.9%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7871
 
7.8%
6893
 
6.8%
6652
 
6.6%
6531
 
6.5%
6298
 
6.2%
6216
 
6.1%
6073
 
6.0%
5676
 
5.6%
5395
 
5.3%
1369
 
1.4%
Other values (485) 42110
41.7%
Latin
ValueCountFrequency (%)
B 804
48.3%
T 771
46.3%
A 30
 
1.8%
S 9
 
0.5%
I 6
 
0.4%
L 5
 
0.3%
F 5
 
0.3%
C 5
 
0.3%
K 4
 
0.2%
M 3
 
0.2%
Other values (16) 22
 
1.3%
Common
ValueCountFrequency (%)
32343
44.7%
1 7387
 
10.2%
- 6092
 
8.4%
2 4421
 
6.1%
3 3719
 
5.1%
4 3109
 
4.3%
5 2950
 
4.1%
0 2594
 
3.6%
6 2447
 
3.4%
8 2338
 
3.2%
Other values (10) 5015
 
6.9%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 101084
57.7%
ASCII 74078
42.3%
CJK 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32343
43.7%
1 7387
 
10.0%
- 6092
 
8.2%
2 4421
 
6.0%
3 3719
 
5.0%
4 3109
 
4.2%
5 2950
 
4.0%
0 2594
 
3.5%
6 2447
 
3.3%
8 2338
 
3.2%
Other values (35) 6678
 
9.0%
Hangul
ValueCountFrequency (%)
7871
 
7.8%
6893
 
6.8%
6652
 
6.6%
6531
 
6.5%
6298
 
6.2%
6216
 
6.1%
6073
 
6.0%
5676
 
5.6%
5395
 
5.3%
1369
 
1.4%
Other values (485) 42110
41.7%
CJK
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Real number (ℝ)

MISSING 

Distinct2526
Distinct (%)59.3%
Missing2664
Missing (%)38.5%
Infinite0
Infinite (%)0.0%
Mean37928.069
Minimum1046
Maximum63629
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.0 KiB
2024-04-17T10:47:08.309417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1046
5-th percentile4424
Q126232
median46949
Q348445
95-th percentile52813
Maximum63629
Range62583
Interquartile range (IQR)22213

Descriptive statistics

Standard deviation16536.327
Coefficient of variation (CV)0.4359918
Kurtosis-0.44762944
Mean37928.069
Median Absolute Deviation (MAD)2398
Skewness-1.0031549
Sum1.6153565 × 108
Variance2.7345011 × 108
MonotonicityNot monotonic
2024-04-17T10:47:08.416847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47709 13
 
0.2%
49256 12
 
0.2%
46219 9
 
0.1%
49476 9
 
0.1%
49228 8
 
0.1%
49217 7
 
0.1%
11813 7
 
0.1%
47603 7
 
0.1%
48099 7
 
0.1%
48501 7
 
0.1%
Other values (2516) 4173
60.3%
(Missing) 2664
38.5%
ValueCountFrequency (%)
1046 1
 
< 0.1%
1054 1
 
< 0.1%
1055 1
 
< 0.1%
1073 3
< 0.1%
1076 1
 
< 0.1%
1077 2
< 0.1%
1082 1
 
< 0.1%
1116 1
 
< 0.1%
1125 1
 
< 0.1%
1157 1
 
< 0.1%
ValueCountFrequency (%)
63629 1
< 0.1%
63593 2
< 0.1%
63584 2
< 0.1%
63566 1
< 0.1%
63546 1
< 0.1%
63357 1
< 0.1%
63300 1
< 0.1%
63290 1
< 0.1%
63221 1
< 0.1%
63192 1
< 0.1%

rdnwhladdr
Text

MISSING 

Distinct3705
Distinct (%)85.8%
Missing2607
Missing (%)37.7%
Memory size54.2 KiB
2024-04-17T10:47:08.700293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length55
Mean length30.845227
Min length16

Characters and Unicode

Total characters133128
Distinct characters583
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3325 ?
Unique (%)77.0%

Sample

1st row부산광역시 중구 자갈치로15번길 4, 지하1층 (남포동6가)
2nd row부산광역시 중구 광복로43번길 12, 2층 (신창동2가)
3rd row부산광역시 중구 중구로 90, 3층 (대청동4가)
4th row부산광역시 중구 동영로 18 (동광동5가)
5th row부산광역시 중구 동영로 11, 1층 (동광동5가)
ValueCountFrequency (%)
부산광역시 2302
 
8.6%
1층 1120
 
4.2%
서울특별시 485
 
1.8%
경기도 436
 
1.6%
2층 336
 
1.3%
부산진구 269
 
1.0%
남구 231
 
0.9%
북구 223
 
0.8%
동래구 221
 
0.8%
사하구 218
 
0.8%
Other values (6156) 20945
78.2%
2024-04-17T10:47:09.115573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22476
 
16.9%
1 5760
 
4.3%
5341
 
4.0%
4393
 
3.3%
) 4051
 
3.0%
4050
 
3.0%
( 4050
 
3.0%
3924
 
2.9%
3350
 
2.5%
3236
 
2.4%
Other values (573) 72497
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77933
58.5%
Space Separator 22476
 
16.9%
Decimal Number 20513
 
15.4%
Close Punctuation 4051
 
3.0%
Open Punctuation 4050
 
3.0%
Other Punctuation 3087
 
2.3%
Dash Punctuation 843
 
0.6%
Uppercase Letter 167
 
0.1%
Math Symbol 4
 
< 0.1%
Letter Number 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5341
 
6.9%
4393
 
5.6%
4050
 
5.2%
3924
 
5.0%
3350
 
4.3%
3236
 
4.2%
3048
 
3.9%
2798
 
3.6%
2274
 
2.9%
2204
 
2.8%
Other values (528) 43315
55.6%
Uppercase Letter
ValueCountFrequency (%)
B 61
36.5%
A 34
20.4%
S 10
 
6.0%
T 9
 
5.4%
C 7
 
4.2%
I 5
 
3.0%
M 5
 
3.0%
P 5
 
3.0%
F 5
 
3.0%
L 4
 
2.4%
Other values (10) 22
 
13.2%
Decimal Number
ValueCountFrequency (%)
1 5760
28.1%
2 3138
15.3%
3 2207
 
10.8%
0 1685
 
8.2%
4 1642
 
8.0%
5 1453
 
7.1%
6 1320
 
6.4%
7 1184
 
5.8%
9 1073
 
5.2%
8 1051
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 3066
99.3%
. 9
 
0.3%
@ 5
 
0.2%
/ 5
 
0.2%
· 1
 
< 0.1%
& 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 3
75.0%
+ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
22476
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4051
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4050
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 843
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77933
58.5%
Common 55025
41.3%
Latin 170
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5341
 
6.9%
4393
 
5.6%
4050
 
5.2%
3924
 
5.0%
3350
 
4.3%
3236
 
4.2%
3048
 
3.9%
2798
 
3.6%
2274
 
2.9%
2204
 
2.8%
Other values (528) 43315
55.6%
Common
ValueCountFrequency (%)
22476
40.8%
1 5760
 
10.5%
) 4051
 
7.4%
( 4050
 
7.4%
2 3138
 
5.7%
, 3066
 
5.6%
3 2207
 
4.0%
0 1685
 
3.1%
4 1642
 
3.0%
5 1453
 
2.6%
Other values (13) 5497
 
10.0%
Latin
ValueCountFrequency (%)
B 61
35.9%
A 34
20.0%
S 10
 
5.9%
T 9
 
5.3%
C 7
 
4.1%
I 5
 
2.9%
M 5
 
2.9%
P 5
 
2.9%
F 5
 
2.9%
L 4
 
2.4%
Other values (12) 25
14.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77933
58.5%
ASCII 55192
41.5%
Number Forms 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22476
40.7%
1 5760
 
10.4%
) 4051
 
7.3%
( 4050
 
7.3%
2 3138
 
5.7%
, 3066
 
5.6%
3 2207
 
4.0%
0 1685
 
3.1%
4 1642
 
3.0%
5 1453
 
2.6%
Other values (33) 5664
 
10.3%
Hangul
ValueCountFrequency (%)
5341
 
6.9%
4393
 
5.6%
4050
 
5.2%
3924
 
5.0%
3350
 
4.3%
3236
 
4.2%
3048
 
3.9%
2798
 
3.6%
2274
 
2.9%
2204
 
2.8%
Other values (528) 43315
55.6%
Number Forms
ValueCountFrequency (%)
2
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

apvpermymd
Real number (ℝ)

SKEWED 

Distinct3998
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20026285
Minimum9710223
Maximum20201218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.0 KiB
2024-04-17T10:47:09.239600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9710223
5-th percentile19711207
Q119920418
median20041005
Q320190215
95-th percentile20200731
Maximum20201218
Range10490995
Interquartile range (IQR)269796.5

Descriptive statistics

Standard deviation200021.09
Coefficient of variation (CV)0.0099879279
Kurtosis1020.974
Mean20026285
Median Absolute Deviation (MAD)140698
Skewness-20.116862
Sum1.3864197 × 1011
Variance4.0008436 × 1010
MonotonicityNot monotonic
2024-04-17T10:47:09.355913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19770830 35
 
0.5%
19660301 35
 
0.5%
20190118 30
 
0.4%
20191004 22
 
0.3%
20191011 21
 
0.3%
20000420 19
 
0.3%
20190531 18
 
0.3%
20020506 17
 
0.2%
20190628 16
 
0.2%
20190215 16
 
0.2%
Other values (3988) 6694
96.7%
ValueCountFrequency (%)
9710223 1
 
< 0.1%
19300722 1
 
< 0.1%
19610922 1
 
< 0.1%
19621202 1
 
< 0.1%
19630110 6
0.1%
19630522 1
 
< 0.1%
19630525 1
 
< 0.1%
19630529 4
0.1%
19630601 1
 
< 0.1%
19630622 1
 
< 0.1%
ValueCountFrequency (%)
20201218 6
0.1%
20201217 3
 
< 0.1%
20201216 5
0.1%
20201215 5
0.1%
20201214 2
 
< 0.1%
20201211 8
0.1%
20201210 4
0.1%
20201209 1
 
< 0.1%
20201208 5
0.1%
20201207 2
 
< 0.1%

dcbymd
Text

MISSING 

Distinct2308
Distinct (%)55.1%
Missing2732
Missing (%)39.5%
Memory size54.2 KiB
2024-04-17T10:47:09.570744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.643999
Min length4

Characters and Unicode

Total characters32036
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

Unique1573 ?
Unique (%)37.5%

Sample

1st row20180501
2nd row20121212
3rd row20151228
4th row20121212
5th row20080710
ValueCountFrequency (%)
폐업일자 373
 
8.9%
20030715 58
 
1.4%
20050214 41
 
1.0%
20031213 36
 
0.9%
20030305 33
 
0.8%
20020222 33
 
0.8%
20030221 32
 
0.8%
20030101 17
 
0.4%
20051011 16
 
0.4%
20061226 13
 
0.3%
Other values (2298) 3539
84.4%
2024-04-17T10:47:09.901041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10837
33.8%
2 6552
20.5%
1 5044
15.7%
3 1495
 
4.7%
9 1347
 
4.2%
5 1304
 
4.1%
4 1068
 
3.3%
7 1019
 
3.2%
6 955
 
3.0%
8 923
 
2.9%
Other values (4) 1492
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30544
95.3%
Other Letter 1492
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10837
35.5%
2 6552
21.5%
1 5044
16.5%
3 1495
 
4.9%
9 1347
 
4.4%
5 1304
 
4.3%
4 1068
 
3.5%
7 1019
 
3.3%
6 955
 
3.1%
8 923
 
3.0%
Other Letter
ValueCountFrequency (%)
373
25.0%
373
25.0%
373
25.0%
373
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30544
95.3%
Hangul 1492
 
4.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10837
35.5%
2 6552
21.5%
1 5044
16.5%
3 1495
 
4.9%
9 1347
 
4.4%
5 1304
 
4.3%
4 1068
 
3.5%
7 1019
 
3.3%
6 955
 
3.1%
8 923
 
3.0%
Hangul
ValueCountFrequency (%)
373
25.0%
373
25.0%
373
25.0%
373
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30544
95.3%
Hangul 1492
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10837
35.5%
2 6552
21.5%
1 5044
16.5%
3 1495
 
4.9%
9 1347
 
4.4%
5 1304
 
4.3%
4 1068
 
3.5%
7 1019
 
3.3%
6 955
 
3.1%
8 923
 
3.0%
Hangul
ValueCountFrequency (%)
373
25.0%
373
25.0%
373
25.0%
373
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
6540 
휴업시작일자
 
383

Length

Max length6
Median length4
Mean length4.1106457
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> 6540
94.5%
휴업시작일자 383
 
5.5%

Length

2024-04-17T10:47:10.023689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:10.110625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6540
94.5%
휴업시작일자 383
 
5.5%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
6540 
휴업종료일자
 
383

Length

Max length6
Median length4
Mean length4.1106457
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> 6540
94.5%
휴업종료일자 383
 
5.5%

Length

2024-04-17T10:47:10.203411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:10.292271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6540
94.5%
휴업종료일자 383
 
5.5%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
6540 
재개업일자
 
383

Length

Max length5
Median length4
Mean length4.0553228
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> 6540
94.5%
재개업일자 383
 
5.5%

Length

2024-04-17T10:47:10.391212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:10.481410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6540
94.5%
재개업일자 383
 
5.5%

trdstatenm
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
02
3330 
영업/정상
1839 
01
1243 
폐업
487 
<NA>
 
18

Length

Max length5
Median length2
Mean length2.8038423
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
02 3330
48.1%
영업/정상 1839
26.6%
01 1243
 
18.0%
폐업 487
 
7.0%
<NA> 18
 
0.3%
영업상태 6
 
0.1%

Length

2024-04-17T10:47:10.565303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:10.653896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3330
48.1%
영업/정상 1839
26.6%
01 1243
 
18.0%
폐업 487
 
7.0%
na 18
 
0.3%
영업상태 6
 
0.1%

dtlstatenm
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
폐업
3818 
영업
3105 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3818
55.1%
영업 3105
44.9%

Length

2024-04-17T10:47:10.750010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:10.826331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3818
55.1%
영업 3105
44.9%

x
Text

MISSING 

Distinct5448
Distinct (%)82.6%
Missing327
Missing (%)4.7%
Memory size54.2 KiB
2024-04-17T10:47:11.009655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.986204
Min length7

Characters and Unicode

Total characters131829
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

Unique4641 ?
Unique (%)70.4%

Sample

1st row384763.36249800000
2nd row385005.25775
3rd row385086.62014400000
4th row385447.404485
5th row385737.436336
ValueCountFrequency (%)
좌표정보(x 7
 
0.1%
200573.641273539 6
 
0.1%
179617.369579689 6
 
0.1%
382169.305404 5
 
0.1%
389415.20340442 5
 
0.1%
384080.85541900000 4
 
0.1%
379140.640735214 4
 
0.1%
383359.409731 4
 
0.1%
163370.80816500000 4
 
0.1%
301328.475622934 4
 
0.1%
Other values (5438) 6547
99.3%
2024-04-17T10:47:11.346585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30797
23.4%
0 17479
13.3%
3 12470
9.5%
8 10033
 
7.6%
9 8902
 
6.8%
1 8113
 
6.2%
2 8037
 
6.1%
7 7471
 
5.7%
4 7458
 
5.7%
5 7249
 
5.5%
Other values (9) 13820
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94410
71.6%
Space Separator 30797
 
23.4%
Other Punctuation 6573
 
5.0%
Other Letter 28
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Uppercase Letter 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17479
18.5%
3 12470
13.2%
8 10033
10.6%
9 8902
9.4%
1 8113
8.6%
2 8037
8.5%
7 7471
7.9%
4 7458
7.9%
5 7249
7.7%
6 7198
7.6%
Other Letter
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%
Space Separator
ValueCountFrequency (%)
30797
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6573
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 131794
> 99.9%
Hangul 28
 
< 0.1%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
30797
23.4%
0 17479
13.3%
3 12470
9.5%
8 10033
 
7.6%
9 8902
 
6.8%
1 8113
 
6.2%
2 8037
 
6.1%
7 7471
 
5.7%
4 7458
 
5.7%
5 7249
 
5.5%
Other values (4) 13785
10.5%
Hangul
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%
Latin
ValueCountFrequency (%)
X 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 131801
> 99.9%
Hangul 28
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30797
23.4%
0 17479
13.3%
3 12470
9.5%
8 10033
 
7.6%
9 8902
 
6.8%
1 8113
 
6.2%
2 8037
 
6.1%
7 7471
 
5.7%
4 7458
 
5.7%
5 7249
 
5.5%
Other values (5) 13792
10.5%
Hangul
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%

y
Text

MISSING 

Distinct5448
Distinct (%)82.6%
Missing327
Missing (%)4.7%
Memory size54.2 KiB
2024-04-17T10:47:11.547376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.986204
Min length7

Characters and Unicode

Total characters131829
Distinct characters20
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

Unique4641 ?
Unique (%)70.4%

Sample

1st row179706.64036800000
2nd row179998.796394
3rd row180119.33406400000
4th row179824.590338
5th row180816.22011
ValueCountFrequency (%)
좌표정보(y 7
 
0.1%
451621.036467544 6
 
0.1%
461673.375689469 6
 
0.1%
191928.498233 5
 
0.1%
193131.590860807 5
 
0.1%
179983.87155900000 4
 
0.1%
180128.072887035 4
 
0.1%
180510.501555 4
 
0.1%
317277.39950900000 4
 
0.1%
186233.933566947 4
 
0.1%
Other values (5438) 6547
99.3%
2024-04-17T10:47:11.856499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30722
23.3%
0 16897
12.8%
1 12220
 
9.3%
8 9697
 
7.4%
9 8870
 
6.7%
4 8488
 
6.4%
7 8065
 
6.1%
2 7996
 
6.1%
3 7666
 
5.8%
6 7290
 
5.5%
Other values (10) 13918
10.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94470
71.7%
Space Separator 30722
 
23.3%
Other Punctuation 6573
 
5.0%
Other Letter 28
 
< 0.1%
Dash Punctuation 15
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Uppercase Letter 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16897
17.9%
1 12220
12.9%
8 9697
10.3%
9 8870
9.4%
4 8488
9.0%
7 8065
8.5%
2 7996
8.5%
3 7666
8.1%
6 7290
7.7%
5 7281
7.7%
Other Letter
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%
Space Separator
ValueCountFrequency (%)
30722
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6573
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 131794
> 99.9%
Hangul 28
 
< 0.1%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
30722
23.3%
0 16897
12.8%
1 12220
 
9.3%
8 9697
 
7.4%
9 8870
 
6.7%
4 8488
 
6.4%
7 8065
 
6.1%
2 7996
 
6.1%
3 7666
 
5.8%
6 7290
 
5.5%
Other values (5) 13883
10.5%
Hangul
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%
Latin
ValueCountFrequency (%)
Y 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 131801
> 99.9%
Hangul 28
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30722
23.3%
0 16897
12.8%
1 12220
 
9.3%
8 9697
 
7.4%
9 8870
 
6.7%
4 8488
 
6.4%
7 8065
 
6.1%
2 7996
 
6.1%
3 7666
 
5.8%
6 7290
 
5.5%
Other values (6) 13890
10.5%
Hangul
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%

lastmodts
Real number (ℝ)

Distinct4735
Distinct (%)68.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0118666 × 1013
Minimum1.9990218 × 1013
Maximum2.0201218 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.0 KiB
2024-04-17T10:47:11.984216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile2.0020422 × 1013
Q12.0040918 × 1013
median2.0130222 × 1013
Q32.0190628 × 1013
95-th percentile2.0201012 × 1013
Maximum2.0201218 × 1013
Range2.1100017 × 1011
Interquartile range (IQR)1.4971066 × 1011

Descriptive statistics

Standard deviation7.1114608 × 1010
Coefficient of variation (CV)0.0035347576
Kurtosis-1.488524
Mean2.0118666 × 1013
Median Absolute Deviation (MAD)6.9608104 × 1010
Skewness-0.24795876
Sum1.3928153 × 1017
Variance5.0572875 × 1021
MonotonicityNot monotonic
2024-04-17T10:47:12.358636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030211000000 63
 
0.9%
20070501000000 54
 
0.8%
20031215000000 38
 
0.5%
20020424000000 38
 
0.5%
20030311000000 38
 
0.5%
20030502000000 37
 
0.5%
19990428000000 35
 
0.5%
20060707000000 34
 
0.5%
20020423000000 34
 
0.5%
20030221000000 33
 
0.5%
Other values (4725) 6519
94.2%
ValueCountFrequency (%)
19990218000000 1
 
< 0.1%
19990223000000 4
 
0.1%
19990224000000 1
 
< 0.1%
19990225000000 3
 
< 0.1%
19990302000000 11
0.2%
19990303000000 12
0.2%
19990304000000 20
0.3%
19990308000000 17
0.2%
19990309000000 5
 
0.1%
19990310000000 18
0.3%
ValueCountFrequency (%)
20201218171521 1
 
< 0.1%
20201218161238 2
< 0.1%
20201218143632 2
< 0.1%
20201218133750 2
< 0.1%
20201218131731 1
 
< 0.1%
20201218094140 1
 
< 0.1%
20201217151333 1
 
< 0.1%
20201217122133 1
 
< 0.1%
20201217120119 1
 
< 0.1%
20201217113628 3
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
일반이용업
6796 
이용업 기타
 
103
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0147335
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 6796
98.2%
이용업 기타 103
 
1.5%
일반미용업 23
 
0.3%
<NA> 1
 
< 0.1%

Length

2024-04-17T10:47:12.474025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:12.570939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 6796
96.7%
이용업 103
 
1.5%
기타 103
 
1.5%
일반미용업 23
 
0.3%
na 1
 
< 0.1%

sitetel
Text

MISSING 

Distinct57
Distinct (%)0.9%
Missing276
Missing (%)4.0%
Memory size54.2 KiB
2024-04-17T10:47:12.709646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.936513
Min length4

Characters and Unicode

Total characters79342
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

Unique46 ?
Unique (%)0.7%

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 6531
96.8%
전화번호 49
 
0.7%
051 13
 
0.2%
053 8
 
0.1%
052 8
 
0.1%
041 5
 
0.1%
031 5
 
0.1%
042 4
 
0.1%
5333 3
 
< 0.1%
02 3
 
< 0.1%
Other values (95) 120
 
1.8%
2024-04-17T10:47:12.946696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19674
24.8%
3 13140
16.6%
2 13129
16.5%
- 13062
16.5%
0 6640
 
8.4%
5 6615
 
8.3%
4 6581
 
8.3%
106
 
0.1%
8 65
 
0.1%
6 50
 
0.1%
Other values (6) 280
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65978
83.2%
Dash Punctuation 13062
 
16.5%
Other Letter 196
 
0.2%
Space Separator 106
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19674
29.8%
3 13140
19.9%
2 13129
19.9%
0 6640
 
10.1%
5 6615
 
10.0%
4 6581
 
10.0%
8 65
 
0.1%
6 50
 
0.1%
7 47
 
0.1%
9 37
 
0.1%
Other Letter
ValueCountFrequency (%)
49
25.0%
49
25.0%
49
25.0%
49
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 13062
100.0%
Space Separator
ValueCountFrequency (%)
106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79146
99.8%
Hangul 196
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19674
24.9%
3 13140
16.6%
2 13129
16.6%
- 13062
16.5%
0 6640
 
8.4%
5 6615
 
8.4%
4 6581
 
8.3%
106
 
0.1%
8 65
 
0.1%
6 50
 
0.1%
Other values (2) 84
 
0.1%
Hangul
ValueCountFrequency (%)
49
25.0%
49
25.0%
49
25.0%
49
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79146
99.8%
Hangul 196
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19674
24.9%
3 13140
16.6%
2 13129
16.6%
- 13062
16.5%
0 6640
 
8.4%
5 6615
 
8.4%
4 6581
 
8.3%
106
 
0.1%
8 65
 
0.1%
6 50
 
0.1%
Other values (2) 84
 
0.1%
Hangul
ValueCountFrequency (%)
49
25.0%
49
25.0%
49
25.0%
49
25.0%

bdngownsenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
5264 
임대
1310 
건물소유구분명
 
308
자가
 
41

Length

Max length7
Median length4
Mean length3.7431749
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5264
76.0%
임대 1310
 
18.9%
건물소유구분명 308
 
4.4%
자가 41
 
0.6%

Length

2024-04-17T10:47:13.063955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:13.148205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5264
76.0%
임대 1310
 
18.9%
건물소유구분명 308
 
4.4%
자가 41
 
0.6%

bdngjisgflrcnt
Categorical

Distinct34
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
0
2622 
<NA>
1846 
3
574 
2
513 
4
484 
Other values (29)
884 

Length

Max length6
Median length1
Mean length1.8291203
Min length1

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row1
2nd row3
3rd row4
4th row16
5th row6

Common Values

ValueCountFrequency (%)
0 2622
37.9%
<NA> 1846
26.7%
3 574
 
8.3%
2 513
 
7.4%
4 484
 
7.0%
1 275
 
4.0%
5 275
 
4.0%
6 93
 
1.3%
7 68
 
1.0%
9 32
 
0.5%
Other values (24) 141
 
2.0%

Length

2024-04-17T10:47:13.245682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2622
37.9%
na 1846
26.7%
3 574
 
8.3%
2 513
 
7.4%
4 484
 
7.0%
1 275
 
4.0%
5 275
 
4.0%
6 93
 
1.3%
7 68
 
1.0%
9 32
 
0.5%
Other values (24) 141
 
2.0%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
0
3380 
<NA>
2362 
1
982 
2
 
113
3
 
26
Other values (7)
 
60

Length

Max length6
Median length1
Mean length2.042756
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3380
48.8%
<NA> 2362
34.1%
1 982
 
14.2%
2 113
 
1.6%
3 26
 
0.4%
건물지하층수 26
 
0.4%
5 16
 
0.2%
4 9
 
0.1%
6 6
 
0.1%
7 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2024-04-17T10:47:13.347437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3380
48.8%
na 2362
34.1%
1 982
 
14.2%
2 113
 
1.6%
3 26
 
0.4%
건물지하층수 26
 
0.4%
5 16
 
0.2%
4 9
 
0.1%
6 6
 
0.1%
7 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

maneipcnt
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
4759 
0
1858 
1
 
265
남성종사자수
 
32
2
 
8

Length

Max length6
Median length4
Mean length3.0855121
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> 4759
68.7%
0 1858
 
26.8%
1 265
 
3.8%
남성종사자수 32
 
0.5%
2 8
 
0.1%
11 1
 
< 0.1%

Length

2024-04-17T10:47:13.444309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:13.529461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4759
68.7%
0 1858
 
26.8%
1 265
 
3.8%
남성종사자수 32
 
0.5%
2 8
 
0.1%
11 1
 
< 0.1%

multusnupsoyn
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size13.7 KiB
False
6916 
True
 
6
(Missing)
 
1
ValueCountFrequency (%)
False 6916
99.9%
True 6
 
0.1%
(Missing) 1
 
< 0.1%
2024-04-17T10:47:13.621400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

balhansilyn
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
False
6923 
ValueCountFrequency (%)
False 6923
100.0%
2024-04-17T10:47:13.696196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

usejisgendflr
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
3586 
1
1309 
0
734 
2
585 
3
 
270
Other values (12)
439 

Length

Max length6
Median length4
Mean length2.7116857
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row2
3rd row2
4th row3
5th row1

Common Values

ValueCountFrequency (%)
<NA> 3586
51.8%
1 1309
 
18.9%
0 734
 
10.6%
2 585
 
8.5%
3 270
 
3.9%
사용끝지상층 215
 
3.1%
4 109
 
1.6%
5 56
 
0.8%
6 20
 
0.3%
7 12
 
0.2%
Other values (7) 27
 
0.4%

Length

2024-04-17T10:47:13.803735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3586
51.8%
1 1309
 
18.9%
0 734
 
10.6%
2 585
 
8.5%
3 270
 
3.9%
사용끝지상층 215
 
3.1%
4 109
 
1.6%
5 56
 
0.8%
6 20
 
0.3%
7 12
 
0.2%
Other values (7) 27
 
0.4%

useunderendflr
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
4884 
0
1297 
1
 
365
사용끝지하층
 
353
2
 
20
Other values (2)
 
4

Length

Max length6
Median length4
Mean length3.3713708
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4884
70.5%
0 1297
 
18.7%
1 365
 
5.3%
사용끝지하층 353
 
5.1%
2 20
 
0.3%
3 3
 
< 0.1%
4 1
 
< 0.1%

Length

2024-04-17T10:47:13.901871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:13.989791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4884
70.5%
0 1297
 
18.7%
1 365
 
5.3%
사용끝지하층 353
 
5.1%
2 20
 
0.3%
3 3
 
< 0.1%
4 1
 
< 0.1%

usejisgstflr
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
2873 
1
1526 
0
1121 
2
641 
3
320 
Other values (11)
442 

Length

Max length7
Median length1
Mean length2.4006933
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row2
3rd row2
4th row3
5th row1

Common Values

ValueCountFrequency (%)
<NA> 2873
41.5%
1 1526
22.0%
0 1121
 
16.2%
2 641
 
9.3%
3 320
 
4.6%
사용시작지상층 178
 
2.6%
4 124
 
1.8%
5 74
 
1.1%
6 26
 
0.4%
9 13
 
0.2%
Other values (6) 27
 
0.4%

Length

2024-04-17T10:47:14.089383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2873
41.5%
1 1526
22.0%
0 1121
 
16.2%
2 641
 
9.3%
3 320
 
4.6%
사용시작지상층 178
 
2.6%
4 124
 
1.8%
5 74
 
1.1%
6 26
 
0.4%
9 13
 
0.2%
Other values (6) 27
 
0.4%

useunderstflr
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
4220 
0
1900 
1
 
421
사용시작지하층
 
347
2
 
31
Other values (2)
 
4

Length

Max length7
Median length4
Mean length3.1295681
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4220
61.0%
0 1900
27.4%
1 421
 
6.1%
사용시작지하층 347
 
5.0%
2 31
 
0.4%
3 3
 
< 0.1%
22 1
 
< 0.1%

Length

2024-04-17T10:47:14.186334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:14.305318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4220
61.0%
0 1900
27.4%
1 421
 
6.1%
사용시작지하층 347
 
5.0%
2 31
 
0.4%
3 3
 
< 0.1%
22 1
 
< 0.1%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
3513 
0
3383 
세탁기수
 
27

Length

Max length4
Median length4
Mean length2.534017
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3513
50.7%
0 3383
48.9%
세탁기수 27
 
0.4%

Length

2024-04-17T10:47:14.422838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:14.516444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3513
50.7%
0 3383
48.9%
세탁기수 27
 
0.4%

yangsilcnt
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
0
4052 
<NA>
2844 
양실수
 
26
38
 
1

Length

Max length4
Median length1
Mean length2.2400693
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4052
58.5%
<NA> 2844
41.1%
양실수 26
 
0.4%
38 1
 
< 0.1%

Length

2024-04-17T10:47:14.638380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:14.726248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4052
58.5%
na 2844
41.1%
양실수 26
 
0.4%
38 1
 
< 0.1%

wmeipcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
4769 
0
2032 
1
 
88
여성종사자수
 
32
2
 
2

Length

Max length6
Median length4
Mean length3.089701
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> 4769
68.9%
0 2032
29.4%
1 88
 
1.3%
여성종사자수 32
 
0.5%
2 2
 
< 0.1%

Length

2024-04-17T10:47:14.813820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:14.896414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4769
68.9%
0 2032
29.4%
1 88
 
1.3%
여성종사자수 32
 
0.5%
2 2
 
< 0.1%

yoksilcnt
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
0
4052 
<NA>
2844 
욕실수
 
26
2
 
1

Length

Max length4
Median length1
Mean length2.2399249
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4052
58.5%
<NA> 2844
41.1%
욕실수 26
 
0.4%
2 1
 
< 0.1%

Length

2024-04-17T10:47:14.998696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:15.084790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4052
58.5%
na 2844
41.1%
욕실수 26
 
0.4%
2 1
 
< 0.1%

sntuptaenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
일반이용업
6795 
이용업 기타
 
103
일반미용업
 
23
<NA>
 
2

Length

Max length6
Median length5
Mean length5.0145891
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 6795
98.2%
이용업 기타 103
 
1.5%
일반미용업 23
 
0.3%
<NA> 2
 
< 0.1%

Length

2024-04-17T10:47:15.185799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:15.276217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 6795
96.7%
이용업 103
 
1.5%
기타 103
 
1.5%
일반미용업 23
 
0.3%
na 2
 
< 0.1%

chaircnt
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
2
2203 
3
1370 
4
729 
<NA>
680 
1
604 
Other values (12)
1337 

Length

Max length4
Median length1
Mean length1.3075256
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row4
3rd row2
4th row7
5th row4

Common Values

ValueCountFrequency (%)
2 2203
31.8%
3 1370
19.8%
4 729
 
10.5%
<NA> 680
 
9.8%
1 604
 
8.7%
0 420
 
6.1%
5 291
 
4.2%
6 196
 
2.8%
7 173
 
2.5%
8 122
 
1.8%
Other values (7) 135
 
2.0%

Length

2024-04-17T10:47:15.376035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 2203
31.8%
3 1370
19.8%
4 729
 
10.5%
na 680
 
9.8%
1 604
 
8.7%
0 420
 
6.1%
5 291
 
4.2%
6 196
 
2.8%
7 173
 
2.5%
8 122
 
1.8%
Other values (7) 135
 
2.0%

cndpermstymd
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
6535 
조건부허가시작일자
 
383
20050520
 
1
20050414
 
1
20181212
 
1
Other values (2)
 
2

Length

Max length9
Median length4
Mean length4.2795031
Min length4

Unique

Unique5 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row20050520
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6535
94.4%
조건부허가시작일자 383
 
5.5%
20050520 1
 
< 0.1%
20050414 1
 
< 0.1%
20181212 1
 
< 0.1%
20190201 1
 
< 0.1%
20190812 1
 
< 0.1%

Length

2024-04-17T10:47:15.485198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:15.581183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6535
94.4%
조건부허가시작일자 383
 
5.5%
20050520 1
 
< 0.1%
20050414 1
 
< 0.1%
20181212 1
 
< 0.1%
20190201 1
 
< 0.1%
20190812 1
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
6536 
조건부허가신고사유
 
383
가설건축물
 
1
외국국적동포 국내거소신고증 체류기간
 
1
전통시장 사용기간제한 허가승인(2018.01.01.~2020.12.31.)
 
1

Length

Max length41
Median length4
Mean length4.2848476
Min length4

Unique

Unique4 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6536
94.4%
조건부허가신고사유 383
 
5.5%
가설건축물 1
 
< 0.1%
외국국적동포 국내거소신고증 체류기간 1
 
< 0.1%
전통시장 사용기간제한 허가승인(2018.01.01.~2020.12.31.) 1
 
< 0.1%
영주증 유효기간 1
 
< 0.1%

Length

2024-04-17T10:47:15.704616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:15.799892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6536
94.3%
조건부허가신고사유 383
 
5.5%
가설건축물 1
 
< 0.1%
외국국적동포 1
 
< 0.1%
국내거소신고증 1
 
< 0.1%
체류기간 1
 
< 0.1%
전통시장 1
 
< 0.1%
사용기간제한 1
 
< 0.1%
허가승인(2018.01.01.~2020.12.31 1
 
< 0.1%
영주증 1
 
< 0.1%

cndpermendymd
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
6535 
조건부허가종료일자
 
383
20060425
 
1
20050414
 
1
20210422
 
1
Other values (2)
 
2

Length

Max length9
Median length4
Mean length4.2795031
Min length4

Unique

Unique5 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row20060425
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6535
94.4%
조건부허가종료일자 383
 
5.5%
20060425 1
 
< 0.1%
20050414 1
 
< 0.1%
20210422 1
 
< 0.1%
20201231 1
 
< 0.1%
20281022 1
 
< 0.1%

Length

2024-04-17T10:47:15.900558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:15.992529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6535
94.4%
조건부허가종료일자 383
 
5.5%
20060425 1
 
< 0.1%
20050414 1
 
< 0.1%
20210422 1
 
< 0.1%
20201231 1
 
< 0.1%
20281022 1
 
< 0.1%

abedcnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
3714 
0
3149 
침대수
 
27
1
 
18
2
 
7
Other values (3)
 
8

Length

Max length4
Median length4
Mean length2.617218
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3714
53.6%
0 3149
45.5%
침대수 27
 
0.4%
1 18
 
0.3%
2 7
 
0.1%
3 4
 
0.1%
6 3
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-17T10:47:16.104214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:16.204198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3714
53.6%
0 3149
45.5%
침대수 27
 
0.4%
1 18
 
0.3%
2 7
 
0.1%
3 4
 
0.1%
6 3
 
< 0.1%
5 1
 
< 0.1%

hanshilcnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
0
4052 
<NA>
2845 
한실수
 
26

Length

Max length4
Median length1
Mean length2.2403582
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4052
58.5%
<NA> 2845
41.1%
한실수 26
 
0.4%

Length

2024-04-17T10:47:16.314834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:16.416949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4052
58.5%
na 2845
41.1%
한실수 26
 
0.4%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
<NA>
3696 
0
3200 
회수건조수
 
27

Length

Max length5
Median length4
Mean length2.617218
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3696
53.4%
0 3200
46.2%
회수건조수 27
 
0.4%

Length

2024-04-17T10:47:16.512098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:47:16.599044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3696
53.4%
0 3200
46.2%
회수건조수 27
 
0.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.2 KiB
Minimum2020-12-22 14:05:05
Maximum2020-12-22 14:05:06
2024-04-17T10:47:16.668449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T10:47:16.747229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
0532500003250000-203-1980-0047805_19_01_PI2018-08-31 23:59:59.0<NA>태양탕구내600046부산광역시 중구 남포동6가 115-5번지 (지하1층)48982부산광역시 중구 자갈치로15번길 4, 지하1층 (남포동6가)1980120220180501<NA><NA><NA>02폐업384763.36249800000179706.6403680000020180501090321일반이용업051-123-1234임대11<NA>NN010100<NA>0일반이용업2<NA><NA><NA>0002020-12-22 14:05:05
1632500003250000-203-2005-0000405_19_01_PI2018-08-31 23:59:59.0<NA>국사 이용원600061부산광역시 중구 신창동1가 35-2번지 (2층)<NA><NA>2005052020121212<NA><NA><NA>02폐업385005.25775179998.79639420050520000000일반이용업051-123-1234<NA>3<NA><NA>NN2<NA>2<NA><NA><NA><NA><NA>일반이용업420050520가설건축물20060425<NA><NA><NA>2020-12-22 14:05:05
2732500003250000-203-2005-0000505_19_01_PI2018-08-31 23:59:59.0<NA>녹수탕구내이용원600062부산광역시 중구 신창동2가 21-2번지 (2층)48947부산광역시 중구 광복로43번길 12, 2층 (신창동2가)2005053120151228<NA><NA><NA>02폐업385086.62014400000180119.3340640000020130208134228일반이용업051-123-1234<NA>41<NA>NN202000<NA>0일반이용업2<NA><NA><NA>0002020-12-22 14:05:05
3832500003250000-203-1972-0044305_19_01_PI2018-08-31 23:59:59.0<NA>부산호텔이용원600022부산광역시 중구 동광동2가 12-1번지 외11필지<NA><NA>1972103120121212<NA><NA><NA>02폐업385447.404485179824.59033820060306000000일반이용업051-123-1234임대161<NA>NN3<NA>3<NA><NA><NA><NA><NA>일반이용업7<NA><NA><NA><NA><NA><NA>2020-12-22 14:05:05
4932500003250000-203-2005-0000105_19_01_PI2018-08-31 23:59:59.0<NA>터프가위 이용원600816부산광역시 중구 중앙동4가 78-20번지 (1층)<NA><NA>2005011920080710<NA><NA><NA>02폐업385737.436336180816.2201120050119000000일반이용업051-123-1234<NA>61<NA>NN1<NA>1<NA><NA><NA><NA><NA>일반이용업4<NA><NA><NA><NA><NA><NA>2020-12-22 14:05:05
51032500003250000-203-2005-0000205_19_01_PI2018-08-31 23:59:59.0<NA>알지 이용원600816부산광역시 중구 중앙동4가 84-26번지 (지하1층)<NA><NA>2005031420060201<NA><NA><NA>02폐업385685.971895180523.35229820050314000000일반이용업051-123-1234<NA>51<NA>NN<NA>1<NA>1<NA><NA><NA><NA>일반이용업7<NA><NA><NA><NA><NA><NA>2020-12-22 14:05:05
61132500003250000-203-1989-0051705_19_01_PI2018-08-31 23:59:59.0<NA>남성H전문600800부산광역시 중구 대청동4가 85-1번지 (3층)48933부산광역시 중구 중구로 90, 3층 (대청동4가)19890928<NA><NA><NA><NA>01영업385152.87363900000180604.3028620000020171110105721일반이용업051-123-1234임대41<NA>NN303000<NA>0일반이용업2<NA><NA><NA>0002020-12-22 14:05:05
71232500003250000-203-2002-0001005_19_01_PI2018-08-31 23:59:59.0<NA>미도이용원600807부산광역시 중구 부평동2가 27-4번지<NA><NA>2002052320090805<NA><NA><NA>02폐업384647.050294179711.51617220070117000000일반이용업051-123-1234임대4<NA><NA>NN2<NA>2<NA><NA><NA><NA><NA>일반이용업6<NA><NA><NA><NA><NA><NA>2020-12-22 14:05:05
81332500003250000-203-1979-0046105_19_01_PI2018-08-31 23:59:59.0<NA>부남600025부산광역시 중구 동광동5가 12-165번지48921부산광역시 중구 동영로 18 (동광동5가)19790623<NA><NA><NA><NA>01영업385465.80651300000181014.9432670000020131230110555일반이용업051-123-1234임대31<NA>NN101000<NA>0일반이용업5<NA><NA><NA>0002020-12-22 14:05:05
91432500003250000-203-1979-0046205_19_01_PI2018-08-31 23:59:59.0<NA>부전600025부산광역시 중구 동광동5가 13-68번지 (1층)48918부산광역시 중구 동영로 11, 1층 (동광동5가)19791231<NA><NA><NA><NA>01영업385407.17813300000180988.5592120000020130208125257일반이용업051-123-1234임대10<NA>NN101000<NA>0일반이용업4<NA><NA><NA>0002020-12-22 14:05:05
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
6913691531400003140000-203-2020-0000905_19_01_PI2020-12-18 00:23:06.0이용업대근이용원158825서울특별시 양천구 신월동 84-11 1층7906서울특별시 양천구 가로공원로 147, 1층 (신월동)20201216<NA><NA><NA><NA>영업/정상영업185107.344341505448286.80849384920201216110534일반이용업<NA><NA>000NN1<NA>1<NA>0000일반이용업3<NA><NA><NA>0002020-12-22 14:05:06
6914691630500003050000-203-2020-0000405_19_01_PI2020-12-19 00:23:16.0이용업휴브리스 바버샵(답십리발소)130883서울특별시 동대문구 답십리동 62-92537서울특별시 동대문구 답십리로 179-1, 2층 (답십리동)20201217폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업205251.540584297452302.78347504320201217120119일반이용업전화번호건물소유구분명000NN2사용끝지하층2사용시작지하층0010일반이용업3조건부허가시작일자조건부허가신고사유조건부허가종료일자0002020-12-22 14:05:06
6915691733300003330000-203-2020-0000905_19_01_PI2020-12-19 00:23:16.0이용업부바스바버샵612842부산광역시 해운대구 좌동 1478-1 해운대좌동에스케이허브올리브48111부산광역시 해운대구 양운로 56, 해운대좌동에스케이허브올리브 상가동 1층 111호 (좌동)20201217<NA><NA><NA><NA>영업/정상영업398264.638827631187644.19325244120201217112351일반이용업<NA><NA>1801NN<NA><NA>1<NA>0000일반이용업4<NA><NA><NA>0002020-12-22 14:05:06
6916691833700003370000-203-2020-0000705_19_01_PI2020-12-19 00:23:16.0이용업퀸즈헤나 헤어아트611820부산광역시 연제구 연산동 587-347520부산광역시 연제구 중앙대로1124번길 21, 2층 (연산동)20201217<NA><NA><NA><NA>영업/정상영업389599.262628968189662.92058642520201217122133이용업 기타<NA>임대200NN2<NA>2<NA>0000이용업 기타2<NA><NA><NA>0002020-12-22 14:05:06
6917691930800003080000-203-2020-0000905_19_01_PI2020-12-20 00:23:06.0이용업레드폴 바버샵 수유점142872서울특별시 강북구 수유동 30-20 동아빌딩1077서울특별시 강북구 노해로 41, 동아빌딩 3층 302-1호 (수유동)20201218폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업201913.995856767459660.41621854420201218143632이용업 기타전화번호건물소유구분명000NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층0000이용업 기타3조건부허가시작일자조건부허가신고사유조건부허가종료일자0002020-12-22 14:05:06
6918692055900005590000-203-2020-0000305_19_01_PI2020-12-20 00:23:06.0이용업두리사우나(이용원)482060경기도 양주시 덕정동 208-6 두리테크 덕정타운11456경기도 양주시 회정로 134, 두리테크 덕정타운 701호 (덕정동)20201218<NA><NA><NA><NA>영업/정상영업205952.007935825481622.81710925820201218133750일반이용업<NA><NA>000NN7<NA>7<NA>0000일반이용업2<NA><NA><NA>0002020-12-22 14:05:06
6919692136100003610000-203-2020-0000205_19_01_PI2020-12-20 00:23:06.0이용업동아이용원503807광주광역시 남구 백운동 38-361646광주광역시 남구 백운로75번길 3, 1층 (백운동)20201218<NA><NA><NA><NA>영업/정상영업191327.450819182308.16321420201218161238일반이용업062 6711498<NA>000NN<NA><NA><NA><NA>0000일반이용업2<NA><NA><NA>0002020-12-22 14:05:06
6920692230800003080000-203-2020-0000905_19_01_PI2020-12-20 00:23:06.0이용업레드폴 바버샵 수유점142872서울특별시 강북구 수유동 30-20 동아빌딩1077서울특별시 강북구 노해로 41, 동아빌딩 3층 302-1호 (수유동)20201218폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업201913.995856767459660.41621854420201218143632이용업 기타전화번호건물소유구분명000NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층0000이용업 기타3조건부허가시작일자조건부허가신고사유조건부허가종료일자0002020-12-22 14:05:06
6921692355900005590000-203-2020-0000305_19_01_PI2020-12-20 00:23:06.0이용업두리사우나(이용원)482060경기도 양주시 덕정동 208-6 두리테크 덕정타운11456경기도 양주시 회정로 134, 두리테크 덕정타운 701호 (덕정동)20201218<NA><NA><NA><NA>영업/정상영업205952.007935825481622.81710925820201218133750일반이용업<NA><NA>000NN7<NA>7<NA>0000일반이용업2<NA><NA><NA>0002020-12-22 14:05:06
6922692436100003610000-203-2020-0000205_19_01_PI2020-12-20 00:23:06.0이용업동아이용원503807광주광역시 남구 백운동 38-361646광주광역시 남구 백운로75번길 3, 1층 (백운동)20201218<NA><NA><NA><NA>영업/정상영업191327.450819182308.16321420201218161238일반이용업062 6711498<NA>000NN<NA><NA><NA><NA>0000일반이용업2<NA><NA><NA>0002020-12-22 14:05:06