Overview

Dataset statistics

Number of variables47
Number of observations7014
Missing cells9142
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 (68.4%)Imbalance
clgenddt is highly imbalanced (68.4%)Imbalance
ropnymd is highly imbalanced (68.4%)Imbalance
uptaenm is highly imbalanced (92.7%)Imbalance
bdngunderflrcnt is highly imbalanced (54.3%)Imbalance
maneipcnt is highly imbalanced (56.4%)Imbalance
multusnupsoyn is highly imbalanced (99.0%)Imbalance
useunderendflr is highly imbalanced (53.9%)Imbalance
wmeipcnt is highly imbalanced (56.0%)Imbalance
sntuptaenm is highly imbalanced (92.6%)Imbalance
cndpermstymd is highly imbalanced (88.4%)Imbalance
cndpermntwhy is highly imbalanced (87.5%)Imbalance
cndpermendymd is highly imbalanced (88.4%)Imbalance
abedcnt is highly imbalanced (64.0%)Imbalance
sitepostno has 72 (1.0%) missing valuesMissing
rdnpostno has 2665 (38.0%) missing valuesMissing
rdnwhladdr has 2607 (37.2%) missing valuesMissing
dcbymd has 2766 (39.4%) missing valuesMissing
x has 328 (4.7%) missing valuesMissing
y has 328 (4.7%) missing valuesMissing
sitetel has 372 (5.3%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-17 01:46:27.190476
Analysis finished2024-04-17 01:46:29.263712
Duration2.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct7014
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3507.6802
Minimum1
Maximum7015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.8 KiB
2024-04-17T10:46:29.318533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile351.65
Q11754.25
median3507.5
Q35260.75
95-th percentile6664.35
Maximum7015
Range7014
Interquartile range (IQR)3506.5

Descriptive statistics

Standard deviation2025.1676
Coefficient of variation (CV)0.57735242
Kurtosis-1.1998413
Mean3507.6802
Median Absolute Deviation (MAD)1753.5
Skewness0.00028007026
Sum24602869
Variance4101304
MonotonicityNot monotonic
2024-04-17T10:46:29.435234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 1
 
< 0.1%
4674 1
 
< 0.1%
4685 1
 
< 0.1%
4684 1
 
< 0.1%
4683 1
 
< 0.1%
4682 1
 
< 0.1%
4681 1
 
< 0.1%
4680 1
 
< 0.1%
4679 1
 
< 0.1%
4678 1
 
< 0.1%
Other values (7004) 7004
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 (%)
7015 1
< 0.1%
7014 1
< 0.1%
7013 1
< 0.1%
7012 1
< 0.1%
7011 1
< 0.1%
7010 1
< 0.1%
7009 1
< 0.1%
7008 1
< 0.1%
7007 1
< 0.1%
7006 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct204
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3539328
Minimum3000000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.8 KiB
2024-04-17T10:46:29.572650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3190000
Q13290000
median3340000
Q33390000
95-th percentile5110000
Maximum6520000
Range3520000
Interquartile range (IQR)100000

Descriptive statistics

Standard deviation574624.47
Coefficient of variation (CV)0.16235412
Kurtosis6.8746975
Mean3539328
Median Absolute Deviation (MAD)50000
Skewness2.708092
Sum2.4824846 × 1010
Variance3.3019328 × 1011
MonotonicityNot monotonic
2024-04-17T10:46:29.692697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3290000 509
 
7.3%
3340000 503
 
7.2%
3300000 417
 
5.9%
3320000 410
 
5.8%
3330000 392
 
5.6%
3350000 377
 
5.4%
3390000 335
 
4.8%
3370000 327
 
4.7%
3310000 322
 
4.6%
3380000 282
 
4.0%
Other values (194) 3140
44.8%
ValueCountFrequency (%)
3000000 20
0.3%
3010000 20
0.3%
3020000 24
0.3%
3030000 10
0.1%
3040000 19
0.3%
3050000 24
0.3%
3060000 17
0.2%
3070000 13
0.2%
3080000 19
0.3%
3090000 8
 
0.1%
ValueCountFrequency (%)
6520000 8
 
0.1%
6510000 16
 
0.2%
5710000 24
0.3%
5700000 4
 
0.1%
5690000 14
 
0.2%
5680000 7
 
0.1%
5670000 56
0.8%
5600000 2
 
< 0.1%
5590000 7
 
0.1%
5580000 1
 
< 0.1%

mgtno
Text

Distinct6503
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
2024-04-17T10:46:29.907284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters154308
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

Unique6213 ?
Unique (%)88.6%

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%
3540000-203-2020-00002 3
 
< 0.1%
3540000-203-2019-00004 3
 
< 0.1%
3960100-203-2020-00002 3
 
< 0.1%
3730000-203-2019-00005 3
 
< 0.1%
4090000-203-2019-00006 3
 
< 0.1%
5310000-203-2019-00012 3
 
< 0.1%
3440000-203-2019-00004 3
 
< 0.1%
3820000-203-2019-00009 3
 
< 0.1%
3440000-203-2019-00005 3
 
< 0.1%
Other values (6493) 6983
99.6%
2024-04-17T10:46:30.195121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 65201
42.3%
- 21042
 
13.6%
3 19464
 
12.6%
2 16843
 
10.9%
1 8692
 
5.6%
9 7394
 
4.8%
5 3325
 
2.2%
4 3288
 
2.1%
8 3230
 
2.1%
6 2916
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 133266
86.4%
Dash Punctuation 21042
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 65201
48.9%
3 19464
 
14.6%
2 16843
 
12.6%
1 8692
 
6.5%
9 7394
 
5.5%
5 3325
 
2.5%
4 3288
 
2.5%
8 3230
 
2.4%
6 2916
 
2.2%
7 2913
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 21042
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 154308
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 65201
42.3%
- 21042
 
13.6%
3 19464
 
12.6%
2 16843
 
10.9%
1 8692
 
5.6%
9 7394
 
4.8%
5 3325
 
2.2%
4 3288
 
2.1%
8 3230
 
2.1%
6 2916
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 154308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 65201
42.3%
- 21042
 
13.6%
3 19464
 
12.6%
2 16843
 
10.9%
1 8692
 
5.6%
9 7394
 
4.8%
5 3325
 
2.2%
4 3288
 
2.1%
8 3230
 
2.1%
6 2916
 
1.9%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
05_19_01_P
7014 

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 7014
100.0%

Length

2024-04-17T10:46:30.309050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:30.586748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 7014
100.0%

updategbn
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
I
5805 
U
1209 

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 5805
82.8%
U 1209
 
17.2%

Length

2024-04-17T10:46:30.664975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:30.746547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5805
82.8%
u 1209
 
17.2%
Distinct873
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-31 02:40:00
2024-04-17T10:46:30.833817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T10:46:30.946278image/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 size54.9 KiB
<NA>
4571 
이용업
2443 

Length

Max length4
Median length4
Mean length3.6516966
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> 4571
65.2%
이용업 2443
34.8%

Length

2024-04-17T10:46:31.085965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:31.172675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4571
65.2%
이용업 2443
34.8%

bplcnm
Text

Distinct4637
Distinct (%)66.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
2024-04-17T10:46:31.399749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length5.3887938
Min length1

Characters and Unicode

Total characters37797
Distinct characters694
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

Unique3628 ?
Unique (%)51.7%

Sample

1st row태양탕구내
2nd row국사 이용원
3rd row녹수탕구내이용원
4th row부산호텔이용원
5th row터프가위 이용원
ValueCountFrequency (%)
이용원 430
 
5.1%
바버샵 110
 
1.3%
구내 57
 
0.7%
태후사랑 53
 
0.6%
퀸즈헤나 53
 
0.6%
컷트실 51
 
0.6%
구내이용원 41
 
0.5%
현대 36
 
0.4%
블루클럽 30
 
0.4%
우리 30
 
0.4%
Other values (4534) 7537
89.4%
2024-04-17T10:46:31.787147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3149
 
8.3%
2593
 
6.9%
2431
 
6.4%
1427
 
3.8%
1040
 
2.8%
901
 
2.4%
640
 
1.7%
602
 
1.6%
548
 
1.4%
456
 
1.2%
Other values (684) 24010
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34236
90.6%
Space Separator 1427
 
3.8%
Lowercase Letter 781
 
2.1%
Uppercase Letter 754
 
2.0%
Open Punctuation 206
 
0.5%
Close Punctuation 206
 
0.5%
Decimal Number 119
 
0.3%
Other Punctuation 59
 
0.2%
Dash Punctuation 8
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3149
 
9.2%
2593
 
7.6%
2431
 
7.1%
1040
 
3.0%
901
 
2.6%
640
 
1.9%
602
 
1.8%
548
 
1.6%
456
 
1.3%
453
 
1.3%
Other values (611) 21423
62.6%
Uppercase Letter
ValueCountFrequency (%)
B 104
13.8%
O 68
 
9.0%
R 68
 
9.0%
S 66
 
8.8%
E 62
 
8.2%
A 45
 
6.0%
H 45
 
6.0%
T 41
 
5.4%
P 31
 
4.1%
C 29
 
3.8%
Other values (16) 195
25.9%
Lowercase Letter
ValueCountFrequency (%)
r 108
13.8%
e 86
11.0%
a 79
10.1%
o 68
8.7%
b 60
 
7.7%
h 60
 
7.7%
s 53
 
6.8%
p 41
 
5.2%
n 37
 
4.7%
l 32
 
4.1%
Other values (15) 157
20.1%
Decimal Number
ValueCountFrequency (%)
2 24
20.2%
1 22
18.5%
8 20
16.8%
3 14
11.8%
9 12
10.1%
4 8
 
6.7%
5 7
 
5.9%
7 6
 
5.0%
0 5
 
4.2%
6 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 29
49.2%
& 11
 
18.6%
' 6
 
10.2%
, 5
 
8.5%
· 5
 
8.5%
# 2
 
3.4%
: 1
 
1.7%
Space Separator
ValueCountFrequency (%)
1427
100.0%
Open Punctuation
ValueCountFrequency (%)
( 206
100.0%
Close Punctuation
ValueCountFrequency (%)
) 206
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34231
90.6%
Common 2026
 
5.4%
Latin 1535
 
4.1%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3149
 
9.2%
2593
 
7.6%
2431
 
7.1%
1040
 
3.0%
901
 
2.6%
640
 
1.9%
602
 
1.8%
548
 
1.6%
456
 
1.3%
453
 
1.3%
Other values (606) 21418
62.6%
Latin
ValueCountFrequency (%)
r 108
 
7.0%
B 104
 
6.8%
e 86
 
5.6%
a 79
 
5.1%
O 68
 
4.4%
R 68
 
4.4%
o 68
 
4.4%
S 66
 
4.3%
E 62
 
4.0%
b 60
 
3.9%
Other values (41) 766
49.9%
Common
ValueCountFrequency (%)
1427
70.4%
( 206
 
10.2%
) 206
 
10.2%
. 29
 
1.4%
2 24
 
1.2%
1 22
 
1.1%
8 20
 
1.0%
3 14
 
0.7%
9 12
 
0.6%
& 11
 
0.5%
Other values (12) 55
 
2.7%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34231
90.6%
ASCII 3556
 
9.4%
None 5
 
< 0.1%
CJK 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3149
 
9.2%
2593
 
7.6%
2431
 
7.1%
1040
 
3.0%
901
 
2.6%
640
 
1.9%
602
 
1.8%
548
 
1.6%
456
 
1.3%
453
 
1.3%
Other values (606) 21418
62.6%
ASCII
ValueCountFrequency (%)
1427
40.1%
( 206
 
5.8%
) 206
 
5.8%
r 108
 
3.0%
B 104
 
2.9%
e 86
 
2.4%
a 79
 
2.2%
O 68
 
1.9%
R 68
 
1.9%
o 68
 
1.9%
Other values (62) 1136
31.9%
None
ValueCountFrequency (%)
· 5
100.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

sitepostno
Text

MISSING 

Distinct2073
Distinct (%)29.9%
Missing72
Missing (%)1.0%
Memory size54.9 KiB
2024-04-17T10:46:32.084623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters41652
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

Unique1018 ?
Unique (%)14.7%

Sample

1st row600046
2nd row600061
3rd row600062
4th row600022
5th row600816
ValueCountFrequency (%)
607833 33
 
0.5%
601829 28
 
0.4%
616801 28
 
0.4%
604851 27
 
0.4%
612847 27
 
0.4%
607826 24
 
0.3%
617818 24
 
0.3%
616807 23
 
0.3%
611803 22
 
0.3%
619903 21
 
0.3%
Other values (2063) 6685
96.3%
2024-04-17T10:46:32.482052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 7008
16.8%
6 6948
16.7%
0 6816
16.4%
1 6223
14.9%
2 3215
7.7%
4 3140
7.5%
3 2953
7.1%
7 2080
 
5.0%
5 1626
 
3.9%
9 1559
 
3.7%
Other values (5) 84
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41568
99.8%
Other Letter 84
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 7008
16.9%
6 6948
16.7%
0 6816
16.4%
1 6223
15.0%
2 3215
7.7%
4 3140
7.6%
3 2953
7.1%
7 2080
 
5.0%
5 1626
 
3.9%
9 1559
 
3.8%
Other Letter
ValueCountFrequency (%)
28
33.3%
14
16.7%
14
16.7%
14
16.7%
14
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 41568
99.8%
Hangul 84
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
8 7008
16.9%
6 6948
16.7%
0 6816
16.4%
1 6223
15.0%
2 3215
7.7%
4 3140
7.6%
3 2953
7.1%
7 2080
 
5.0%
5 1626
 
3.9%
9 1559
 
3.8%
Hangul
ValueCountFrequency (%)
28
33.3%
14
16.7%
14
16.7%
14
16.7%
14
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41568
99.8%
Hangul 84
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 7008
16.9%
6 6948
16.7%
0 6816
16.4%
1 6223
15.0%
2 3215
7.7%
4 3140
7.6%
3 2953
7.1%
7 2080
 
5.0%
5 1626
 
3.9%
9 1559
 
3.8%
Hangul
ValueCountFrequency (%)
28
33.3%
14
16.7%
14
16.7%
14
16.7%
14
16.7%
Distinct5881
Distinct (%)83.9%
Missing3
Missing (%)< 0.1%
Memory size54.9 KiB
2024-04-17T10:46:32.749263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length55
Mean length25.283554
Min length7

Characters and Unicode

Total characters177263
Distinct characters548
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

Unique5117 ?
Unique (%)73.0%

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 4911
 
14.8%
t통b반 768
 
2.3%
서울특별시 510
 
1.5%
부산진구 509
 
1.5%
사하구 505
 
1.5%
북구 482
 
1.5%
경기도 455
 
1.4%
동래구 417
 
1.3%
해운대구 392
 
1.2%
남구 392
 
1.2%
Other values (8027) 23788
71.8%
2024-04-17T10:46:33.151058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32784
 
18.5%
7970
 
4.5%
1 7477
 
4.2%
6979
 
3.9%
6607
 
3.7%
6602
 
3.7%
6324
 
3.6%
- 6169
 
3.5%
6163
 
3.5%
6094
 
3.4%
Other values (538) 84094
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102223
57.7%
Decimal Number 33701
 
19.0%
Space Separator 32784
 
18.5%
Dash Punctuation 6169
 
3.5%
Uppercase Letter 1662
 
0.9%
Open Punctuation 280
 
0.2%
Close Punctuation 279
 
0.2%
Other Punctuation 145
 
0.1%
Lowercase Letter 14
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7970
 
7.8%
6979
 
6.8%
6607
 
6.5%
6602
 
6.5%
6324
 
6.2%
6163
 
6.0%
6094
 
6.0%
5708
 
5.6%
5424
 
5.3%
1415
 
1.4%
Other values (490) 42937
42.0%
Uppercase Letter
ValueCountFrequency (%)
B 803
48.3%
T 771
46.4%
A 30
 
1.8%
S 9
 
0.5%
C 7
 
0.4%
I 6
 
0.4%
M 5
 
0.3%
L 5
 
0.3%
F 5
 
0.3%
K 4
 
0.2%
Other values (11) 17
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 7477
22.2%
2 4488
13.3%
3 3768
11.2%
4 3150
9.3%
5 2978
 
8.8%
0 2640
 
7.8%
6 2468
 
7.3%
7 2363
 
7.0%
8 2358
 
7.0%
9 2011
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
21.4%
s 3
21.4%
a 3
21.4%
p 3
21.4%
c 2
14.3%
Other Punctuation
ValueCountFrequency (%)
, 126
86.9%
. 10
 
6.9%
@ 6
 
4.1%
/ 3
 
2.1%
Math Symbol
ValueCountFrequency (%)
~ 3
75.0%
+ 1
 
25.0%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
32784
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6169
100.0%
Open Punctuation
ValueCountFrequency (%)
( 280
100.0%
Close Punctuation
ValueCountFrequency (%)
) 279
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102221
57.7%
Common 73362
41.4%
Latin 1678
 
0.9%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7970
 
7.8%
6979
 
6.8%
6607
 
6.5%
6602
 
6.5%
6324
 
6.2%
6163
 
6.0%
6094
 
6.0%
5708
 
5.6%
5424
 
5.3%
1415
 
1.4%
Other values (489) 42935
42.0%
Latin
ValueCountFrequency (%)
B 803
47.9%
T 771
45.9%
A 30
 
1.8%
S 9
 
0.5%
C 7
 
0.4%
I 6
 
0.4%
M 5
 
0.3%
L 5
 
0.3%
F 5
 
0.3%
K 4
 
0.2%
Other values (18) 33
 
2.0%
Common
ValueCountFrequency (%)
32784
44.7%
1 7477
 
10.2%
- 6169
 
8.4%
2 4488
 
6.1%
3 3768
 
5.1%
4 3150
 
4.3%
5 2978
 
4.1%
0 2640
 
3.6%
6 2468
 
3.4%
7 2363
 
3.2%
Other values (10) 5077
 
6.9%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102221
57.7%
ASCII 75038
42.3%
CJK 2
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32784
43.7%
1 7477
 
10.0%
- 6169
 
8.2%
2 4488
 
6.0%
3 3768
 
5.0%
4 3150
 
4.2%
5 2978
 
4.0%
0 2640
 
3.5%
6 2468
 
3.3%
7 2363
 
3.1%
Other values (36) 6753
 
9.0%
Hangul
ValueCountFrequency (%)
7970
 
7.8%
6979
 
6.8%
6607
 
6.5%
6602
 
6.5%
6324
 
6.2%
6163
 
6.0%
6094
 
6.0%
5708
 
5.6%
5424
 
5.3%
1415
 
1.4%
Other values (489) 42935
42.0%
CJK
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%

rdnpostno
Real number (ℝ)

MISSING 

Distinct2582
Distinct (%)59.4%
Missing2665
Missing (%)38.0%
Infinite0
Infinite (%)0.0%
Mean37669.668
Minimum1046
Maximum63629
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.8 KiB
2024-04-17T10:46:33.279382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1046
5-th percentile4412.8
Q124832
median46927
Q348437
95-th percentile52813
Maximum63629
Range62583
Interquartile range (IQR)23605

Descriptive statistics

Standard deviation16685.897
Coefficient of variation (CV)0.44295311
Kurtosis-0.53027017
Mean37669.668
Median Absolute Deviation (MAD)2450
Skewness-0.9664947
Sum1.6382539 × 108
Variance2.7841915 × 108
MonotonicityNot monotonic
2024-04-17T10:46:33.385791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47709 13
 
0.2%
49256 12
 
0.2%
49476 9
 
0.1%
46219 9
 
0.1%
49228 8
 
0.1%
49217 7
 
0.1%
48099 7
 
0.1%
11813 7
 
0.1%
48501 7
 
0.1%
47603 7
 
0.1%
Other values (2572) 4263
60.8%
(Missing) 2665
38.0%
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%
63595 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%

rdnwhladdr
Text

MISSING 

Distinct3779
Distinct (%)85.7%
Missing2607
Missing (%)37.2%
Memory size54.9 KiB
2024-04-17T10:46:33.656186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length55
Mean length30.881779
Min length16

Characters and Unicode

Total characters136096
Distinct characters590
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

Unique3385 ?
Unique (%)76.8%

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 2311
 
8.4%
1층 1155
 
4.2%
서울특별시 510
 
1.9%
경기도 455
 
1.7%
2층 347
 
1.3%
부산진구 272
 
1.0%
남구 232
 
0.8%
북구 224
 
0.8%
동래구 223
 
0.8%
사하구 220
 
0.8%
Other values (6279) 21450
78.3%
2024-04-17T10:46:34.062610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22998
 
16.9%
1 5877
 
4.3%
5450
 
4.0%
4480
 
3.3%
4137
 
3.0%
) 4132
 
3.0%
( 4131
 
3.0%
3997
 
2.9%
3378
 
2.5%
3266
 
2.4%
Other values (580) 74250
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79646
58.5%
Space Separator 22998
 
16.9%
Decimal Number 20955
 
15.4%
Close Punctuation 4132
 
3.0%
Open Punctuation 4131
 
3.0%
Other Punctuation 3183
 
2.3%
Dash Punctuation 859
 
0.6%
Uppercase Letter 173
 
0.1%
Lowercase Letter 11
 
< 0.1%
Math Symbol 4
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5450
 
6.8%
4480
 
5.6%
4137
 
5.2%
3997
 
5.0%
3378
 
4.2%
3266
 
4.1%
3082
 
3.9%
2827
 
3.5%
2318
 
2.9%
2282
 
2.9%
Other values (530) 44429
55.8%
Uppercase Letter
ValueCountFrequency (%)
B 61
35.3%
A 34
19.7%
C 11
 
6.4%
S 10
 
5.8%
T 9
 
5.2%
M 7
 
4.0%
F 5
 
2.9%
P 5
 
2.9%
I 5
 
2.9%
L 4
 
2.3%
Other values (10) 22
 
12.7%
Decimal Number
ValueCountFrequency (%)
1 5877
28.0%
2 3208
15.3%
3 2246
 
10.7%
0 1717
 
8.2%
4 1689
 
8.1%
5 1488
 
7.1%
6 1361
 
6.5%
7 1204
 
5.7%
9 1095
 
5.2%
8 1070
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 3159
99.2%
. 12
 
0.4%
@ 5
 
0.2%
/ 5
 
0.2%
& 1
 
< 0.1%
· 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 3
27.3%
c 2
18.2%
a 2
18.2%
p 2
18.2%
s 2
18.2%
Math Symbol
ValueCountFrequency (%)
~ 3
75.0%
+ 1
 
25.0%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
22998
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4132
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 859
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79646
58.5%
Common 56263
41.3%
Latin 187
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5450
 
6.8%
4480
 
5.6%
4137
 
5.2%
3997
 
5.0%
3378
 
4.2%
3266
 
4.1%
3082
 
3.9%
2827
 
3.5%
2318
 
2.9%
2282
 
2.9%
Other values (530) 44429
55.8%
Latin
ValueCountFrequency (%)
B 61
32.6%
A 34
18.2%
C 11
 
5.9%
S 10
 
5.3%
T 9
 
4.8%
M 7
 
3.7%
F 5
 
2.7%
P 5
 
2.7%
I 5
 
2.7%
L 4
 
2.1%
Other values (17) 36
19.3%
Common
ValueCountFrequency (%)
22998
40.9%
1 5877
 
10.4%
) 4132
 
7.3%
( 4131
 
7.3%
2 3208
 
5.7%
, 3159
 
5.6%
3 2246
 
4.0%
0 1717
 
3.1%
4 1689
 
3.0%
5 1488
 
2.6%
Other values (13) 5618
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79646
58.5%
ASCII 56446
41.5%
Number Forms 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22998
40.7%
1 5877
 
10.4%
) 4132
 
7.3%
( 4131
 
7.3%
2 3208
 
5.7%
, 3159
 
5.6%
3 2246
 
4.0%
0 1717
 
3.0%
4 1689
 
3.0%
5 1488
 
2.6%
Other values (37) 5801
 
10.3%
Hangul
ValueCountFrequency (%)
5450
 
6.8%
4480
 
5.6%
4137
 
5.2%
3997
 
5.0%
3378
 
4.2%
3266
 
4.1%
3082
 
3.9%
2827
 
3.5%
2318
 
2.9%
2282
 
2.9%
Other values (530) 44429
55.8%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%
None
ValueCountFrequency (%)
· 1
100.0%

apvpermymd
Real number (ℝ)

Distinct4028
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20028518
Minimum9710223
Maximum20210129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.8 KiB
2024-04-17T10:46:34.188371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9710223
5-th percentile19716996
Q119920744
median20041224
Q320190312
95-th percentile20200908
Maximum20210129
Range10499906
Interquartile range (IQR)269567.75

Descriptive statistics

Standard deviation199742.83
Coefficient of variation (CV)0.0099729211
Kurtosis1014.2203
Mean20028518
Median Absolute Deviation (MAD)148882.5
Skewness-19.963227
Sum1.4048003 × 1011
Variance3.98972 × 1010
MonotonicityNot monotonic
2024-04-17T10:46:34.332660image/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 (4018) 6785
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 (%)
20210129 6
0.1%
20210128 6
0.1%
20210127 5
0.1%
20210125 4
0.1%
20210122 4
0.1%
20210121 2
 
< 0.1%
20210120 1
 
< 0.1%
20210119 4
0.1%
20210118 2
 
< 0.1%
20210115 6
0.1%

dcbymd
Text

MISSING 

Distinct2326
Distinct (%)54.8%
Missing2766
Missing (%)39.4%
Memory size54.9 KiB
2024-04-17T10:46:34.561814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.6318267
Min length4

Characters and Unicode

Total characters32420
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

Unique1580 ?
Unique (%)37.2%

Sample

1st row20180501
2nd row20121212
3rd row20151228
4th row20121212
5th row20080710
ValueCountFrequency (%)
폐업일자 391
 
9.2%
20030715 58
 
1.4%
20050214 41
 
1.0%
20031213 36
 
0.8%
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 (2316) 3578
84.2%
2024-04-17T10:46:34.911707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10926
33.7%
2 6673
20.6%
1 5118
15.8%
3 1507
 
4.6%
9 1349
 
4.2%
5 1308
 
4.0%
4 1069
 
3.3%
7 1022
 
3.2%
6 957
 
3.0%
8 927
 
2.9%
Other values (4) 1564
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30856
95.2%
Other Letter 1564
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10926
35.4%
2 6673
21.6%
1 5118
16.6%
3 1507
 
4.9%
9 1349
 
4.4%
5 1308
 
4.2%
4 1069
 
3.5%
7 1022
 
3.3%
6 957
 
3.1%
8 927
 
3.0%
Other Letter
ValueCountFrequency (%)
391
25.0%
391
25.0%
391
25.0%
391
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30856
95.2%
Hangul 1564
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10926
35.4%
2 6673
21.6%
1 5118
16.6%
3 1507
 
4.9%
9 1349
 
4.4%
5 1308
 
4.2%
4 1069
 
3.5%
7 1022
 
3.3%
6 957
 
3.1%
8 927
 
3.0%
Hangul
ValueCountFrequency (%)
391
25.0%
391
25.0%
391
25.0%
391
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30856
95.2%
Hangul 1564
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10926
35.4%
2 6673
21.6%
1 5118
16.6%
3 1507
 
4.9%
9 1349
 
4.4%
5 1308
 
4.2%
4 1069
 
3.5%
7 1022
 
3.3%
6 957
 
3.1%
8 927
 
3.0%
Hangul
ValueCountFrequency (%)
391
25.0%
391
25.0%
391
25.0%
391
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
6613 
휴업시작일자
 
401

Length

Max length6
Median length4
Mean length4.1143427
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> 6613
94.3%
휴업시작일자 401
 
5.7%

Length

2024-04-17T10:46:35.037424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:35.124090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6613
94.3%
휴업시작일자 401
 
5.7%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
6613 
휴업종료일자
 
401

Length

Max length6
Median length4
Mean length4.1143427
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> 6613
94.3%
휴업종료일자 401
 
5.7%

Length

2024-04-17T10:46:35.230308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:35.317276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6613
94.3%
휴업종료일자 401
 
5.7%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
6613 
재개업일자
 
401

Length

Max length5
Median length4
Mean length4.0571714
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> 6613
94.3%
재개업일자 401
 
5.7%

Length

2024-04-17T10:46:35.403367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:35.501559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6613
94.3%
재개업일자 401
 
5.7%

trdstatenm
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
02
3330 
영업/정상
1896 
01
1241 
폐업
526 
<NA>
 
15

Length

Max length5
Median length2
Mean length2.8169376
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
02 3330
47.5%
영업/정상 1896
27.0%
01 1241
 
17.7%
폐업 526
 
7.5%
<NA> 15
 
0.2%
영업상태 6
 
0.1%

Length

2024-04-17T10:46:35.608121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:35.718832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3330
47.5%
영업/정상 1896
27.0%
01 1241
 
17.7%
폐업 526
 
7.5%
na 15
 
0.2%
영업상태 6
 
0.1%

dtlstatenm
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
폐업
3857 
영업
3157 

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 3857
55.0%
영업 3157
45.0%

Length

2024-04-17T10:46:35.836760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:35.921419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3857
55.0%
영업 3157
45.0%

x
Text

MISSING 

Distinct5519
Distinct (%)82.5%
Missing328
Missing (%)4.7%
Memory size54.9 KiB
2024-04-17T10:46:36.103570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.986389
Min length7

Characters and Unicode

Total characters133629
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

Unique4697 ?
Unique (%)70.3%

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%
389415.20340442 5
 
0.1%
382169.305404 5
 
0.1%
348500.487903 4
 
0.1%
211039.290221397 4
 
0.1%
385851.312113 4
 
0.1%
227418.333007098 4
 
0.1%
163370.80816500000 4
 
0.1%
Other values (5509) 6637
99.3%
2024-04-17T10:46:36.439266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31237
23.4%
0 17592
13.2%
3 12601
9.4%
8 10151
 
7.6%
9 9024
 
6.8%
1 8277
 
6.2%
2 8187
 
6.1%
7 7605
 
5.7%
4 7569
 
5.7%
5 7377
 
5.5%
Other values (9) 14009
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 95680
71.6%
Space Separator 31237
 
23.4%
Other Punctuation 6663
 
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 17592
18.4%
3 12601
13.2%
8 10151
10.6%
9 9024
9.4%
1 8277
8.7%
2 8187
8.6%
7 7605
7.9%
4 7569
7.9%
5 7377
7.7%
6 7297
7.6%
Other Letter
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%
Space Separator
ValueCountFrequency (%)
31237
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6663
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 133594
> 99.9%
Hangul 28
 
< 0.1%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
31237
23.4%
0 17592
13.2%
3 12601
9.4%
8 10151
 
7.6%
9 9024
 
6.8%
1 8277
 
6.2%
2 8187
 
6.1%
7 7605
 
5.7%
4 7569
 
5.7%
5 7377
 
5.5%
Other values (4) 13974
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 133601
> 99.9%
Hangul 28
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31237
23.4%
0 17592
13.2%
3 12601
9.4%
8 10151
 
7.6%
9 9024
 
6.8%
1 8277
 
6.2%
2 8187
 
6.1%
7 7605
 
5.7%
4 7569
 
5.7%
5 7377
 
5.5%
Other values (5) 13981
10.5%
Hangul
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%

y
Text

MISSING 

Distinct5519
Distinct (%)82.5%
Missing328
Missing (%)4.7%
Memory size54.9 KiB
2024-04-17T10:46:36.630182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.986389
Min length7

Characters and Unicode

Total characters133629
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

Unique4697 ?
Unique (%)70.3%

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%
193131.590860807 5
 
0.1%
191928.498233 5
 
0.1%
263629.524735 4
 
0.1%
447345.67067272 4
 
0.1%
181799.414753 4
 
0.1%
461105.136615343 4
 
0.1%
317277.39950900000 4
 
0.1%
Other values (5509) 6637
99.3%
2024-04-17T10:46:36.929048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31165
23.3%
0 16991
12.7%
1 12338
 
9.2%
8 9802
 
7.3%
9 8979
 
6.7%
4 8675
 
6.5%
7 8190
 
6.1%
2 8133
 
6.1%
3 7800
 
5.8%
5 7440
 
5.6%
Other values (10) 14116
10.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 95736
71.6%
Space Separator 31165
 
23.3%
Other Punctuation 6663
 
5.0%
Other Letter 28
 
< 0.1%
Dash Punctuation 16
 
< 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 16991
17.7%
1 12338
12.9%
8 9802
10.2%
9 8979
9.4%
4 8675
9.1%
7 8190
8.6%
2 8133
8.5%
3 7800
8.1%
5 7440
7.8%
6 7388
7.7%
Other Letter
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%
Space Separator
ValueCountFrequency (%)
31165
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6663
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
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 133594
> 99.9%
Hangul 28
 
< 0.1%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
31165
23.3%
0 16991
12.7%
1 12338
 
9.2%
8 9802
 
7.3%
9 8979
 
6.7%
4 8675
 
6.5%
7 8190
 
6.1%
2 8133
 
6.1%
3 7800
 
5.8%
5 7440
 
5.6%
Other values (5) 14081
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 133601
> 99.9%
Hangul 28
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31165
23.3%
0 16991
12.7%
1 12338
 
9.2%
8 9802
 
7.3%
9 8979
 
6.7%
4 8675
 
6.5%
7 8190
 
6.1%
2 8133
 
6.1%
3 7800
 
5.8%
5 7440
 
5.6%
Other values (6) 14088
10.5%
Hangul
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%

lastmodts
Real number (ℝ)

Distinct4816
Distinct (%)68.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0119978 × 1013
Minimum1.9990218 × 1013
Maximum2.0210129 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.8 KiB
2024-04-17T10:46:37.048694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile2.0020422 × 1013
Q12.0041103 × 1013
median2.0130362 × 1013
Q32.0190731 × 1013
95-th percentile2.0201111 × 1013
Maximum2.0210129 × 1013
Range2.1991117 × 1011
Interquartile range (IQR)1.4962812 × 1011

Descriptive statistics

Standard deviation7.1544541 × 1010
Coefficient of variation (CV)0.0035558956
Kurtosis-1.481698
Mean2.0119978 × 1013
Median Absolute Deviation (MAD)6.9759011 × 1010
Skewness-0.26159605
Sum1.4112153 × 1017
Variance5.1186213 × 1021
MonotonicityNot monotonic
2024-04-17T10:46:37.161688image/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%
20020423000000 34
 
0.5%
20060707000000 34
 
0.5%
20030318000000 33
 
0.5%
Other values (4806) 6610
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 (%)
20210129165532 2
< 0.1%
20210129153618 1
< 0.1%
20210129135310 2
< 0.1%
20210129120253 2
< 0.1%
20210129093016 1
< 0.1%
20210128142043 1
< 0.1%
20210128141634 1
< 0.1%
20210128132919 1
< 0.1%
20210128112653 1
< 0.1%
20210128103451 1
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
일반이용업
6884 
이용업 기타
 
106
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0149701
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 6884
98.1%
이용업 기타 106
 
1.5%
일반미용업 23
 
0.3%
<NA> 1
 
< 0.1%

Length

2024-04-17T10:46:37.281381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:37.372699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 6884
96.7%
이용업 106
 
1.5%
기타 106
 
1.5%
일반미용업 23
 
0.3%
na 1
 
< 0.1%

sitetel
Text

MISSING 

Distinct78
Distinct (%)1.2%
Missing372
Missing (%)5.3%
Memory size54.9 KiB
2024-04-17T10:46:37.495823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.90274
Min length4

Characters and Unicode

Total characters79058
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

Unique62 ?
Unique (%)0.9%

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 6469
95.3%
전화번호 76
 
1.1%
051 17
 
0.3%
031 13
 
0.2%
053 9
 
0.1%
052 8
 
0.1%
054 7
 
0.1%
02 6
 
0.1%
062 6
 
0.1%
041 5
 
0.1%
Other values (128) 173
 
2.5%
2024-04-17T10:46:37.988568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19522
24.7%
3 13053
16.5%
2 13042
16.5%
- 12938
16.4%
0 6618
 
8.4%
5 6596
 
8.3%
4 6540
 
8.3%
157
 
0.2%
7 81
 
0.1%
6 80
 
0.1%
Other values (6) 431
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65659
83.1%
Dash Punctuation 12938
 
16.4%
Other Letter 304
 
0.4%
Space Separator 157
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19522
29.7%
3 13053
19.9%
2 13042
19.9%
0 6618
 
10.1%
5 6596
 
10.0%
4 6540
 
10.0%
7 81
 
0.1%
6 80
 
0.1%
8 74
 
0.1%
9 53
 
0.1%
Other Letter
ValueCountFrequency (%)
76
25.0%
76
25.0%
76
25.0%
76
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 12938
100.0%
Space Separator
ValueCountFrequency (%)
157
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78754
99.6%
Hangul 304
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19522
24.8%
3 13053
16.6%
2 13042
16.6%
- 12938
16.4%
0 6618
 
8.4%
5 6596
 
8.4%
4 6540
 
8.3%
157
 
0.2%
7 81
 
0.1%
6 80
 
0.1%
Other values (2) 127
 
0.2%
Hangul
ValueCountFrequency (%)
76
25.0%
76
25.0%
76
25.0%
76
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78754
99.6%
Hangul 304
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19522
24.8%
3 13053
16.6%
2 13042
16.6%
- 12938
16.4%
0 6618
 
8.4%
5 6596
 
8.4%
4 6540
 
8.3%
157
 
0.2%
7 81
 
0.1%
6 80
 
0.1%
Other values (2) 127
 
0.2%
Hangul
ValueCountFrequency (%)
76
25.0%
76
25.0%
76
25.0%
76
25.0%

bdngownsenm
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
5321 
임대
1330 
건물소유구분명
 
322
자가
 
41

Length

Max length7
Median length4
Mean length3.7467921
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> 5321
75.9%
임대 1330
 
19.0%
건물소유구분명 322
 
4.6%
자가 41
 
0.6%

Length

2024-04-17T10:46:38.098443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:38.185130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5321
75.9%
임대 1330
 
19.0%
건물소유구분명 322
 
4.6%
자가 41
 
0.6%

bdngjisgflrcnt
Categorical

Distinct34
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
0
2692 
<NA>
1844 
3
579 
2
520 
4
486 
Other values (29)
893 

Length

Max length6
Median length1
Mean length1.8200741
Min length1

Unique

Unique9 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2692
38.4%
<NA> 1844
26.3%
3 579
 
8.3%
2 520
 
7.4%
4 486
 
6.9%
1 276
 
3.9%
5 276
 
3.9%
6 93
 
1.3%
7 67
 
1.0%
9 33
 
0.5%
Other values (24) 148
 
2.1%

Length

2024-04-17T10:46:38.276268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2692
38.4%
na 1844
26.3%
3 579
 
8.3%
2 520
 
7.4%
4 486
 
6.9%
1 276
 
3.9%
5 276
 
3.9%
6 93
 
1.3%
7 67
 
1.0%
9 33
 
0.5%
Other values (24) 148
 
2.1%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
0
3458 
<NA>
2360 
1
992 
2
 
114
건물지하층수
 
29
Other values (7)
 
61

Length

Max length6
Median length1
Mean length2.0305104
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3458
49.3%
<NA> 2360
33.6%
1 992
 
14.1%
2 114
 
1.6%
건물지하층수 29
 
0.4%
3 27
 
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

2024-04-17T10:46:38.390080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3458
49.3%
na 2360
33.6%
1 992
 
14.1%
2 114
 
1.6%
건물지하층수 29
 
0.4%
3 27
 
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 size54.9 KiB
<NA>
4766 
0
1927 
1
 
277
남성종사자수
 
35
2
 
8

Length

Max length6
Median length4
Mean length3.0635871
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> 4766
67.9%
0 1927
27.5%
1 277
 
3.9%
남성종사자수 35
 
0.5%
2 8
 
0.1%
11 1
 
< 0.1%

Length

2024-04-17T10:46:38.487278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:38.576281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4766
67.9%
0 1927
27.5%
1 277
 
3.9%
남성종사자수 35
 
0.5%
2 8
 
0.1%
11 1
 
< 0.1%

multusnupsoyn
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size13.8 KiB
False
7007 
True
 
6
(Missing)
 
1
ValueCountFrequency (%)
False 7007
99.9%
True 6
 
0.1%
(Missing) 1
 
< 0.1%
2024-04-17T10:46:38.656973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

balhansilyn
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
False
7014 
ValueCountFrequency (%)
False 7014
100.0%
2024-04-17T10:46:38.722488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

usejisgendflr
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
3603 
1
1342 
0
749 
2
587 
3
 
271
Other values (12)
462 

Length

Max length6
Median length4
Mean length2.7081551
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3603
51.4%
1 1342
 
19.1%
0 749
 
10.7%
2 587
 
8.4%
3 271
 
3.9%
사용끝지상층 231
 
3.3%
4 110
 
1.6%
5 61
 
0.9%
6 20
 
0.3%
7 12
 
0.2%
Other values (7) 28
 
0.4%

Length

2024-04-17T10:46:38.808674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3603
51.4%
1 1342
 
19.1%
0 749
 
10.7%
2 587
 
8.4%
3 271
 
3.9%
사용끝지상층 231
 
3.3%
4 110
 
1.6%
5 61
 
0.9%
6 20
 
0.3%
7 12
 
0.2%
Other values (7) 28
 
0.4%

useunderendflr
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
4922 
0
1328 
사용끝지하층
 
371
1
 
367
2
 
22
Other values (2)
 
4

Length

Max length6
Median length4
Mean length3.3696892
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> 4922
70.2%
0 1328
 
18.9%
사용끝지하층 371
 
5.3%
1 367
 
5.2%
2 22
 
0.3%
3 3
 
< 0.1%
4 1
 
< 0.1%

Length

2024-04-17T10:46:38.910494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:38.998788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4922
70.2%
0 1328
 
18.9%
사용끝지하층 371
 
5.3%
1 367
 
5.2%
2 22
 
0.3%
3 3
 
< 0.1%
4 1
 
< 0.1%

usejisgstflr
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
2888 
1
1561 
0
1133 
2
645 
3
321 
Other values (11)
466 

Length

Max length7
Median length1
Mean length2.4026233
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2888
41.2%
1 1561
22.3%
0 1133
 
16.2%
2 645
 
9.2%
3 321
 
4.6%
사용시작지상층 194
 
2.8%
4 126
 
1.8%
5 79
 
1.1%
6 26
 
0.4%
9 13
 
0.2%
Other values (6) 28
 
0.4%

Length

2024-04-17T10:46:39.100174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2888
41.2%
1 1561
22.3%
0 1133
 
16.2%
2 645
 
9.2%
3 321
 
4.6%
사용시작지상층 194
 
2.8%
4 126
 
1.8%
5 79
 
1.1%
6 26
 
0.4%
9 13
 
0.2%
Other values (6) 28
 
0.4%

useunderstflr
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
4258 
0
1931 
1
 
424
사용시작지하층
 
364
2
 
33
Other values (2)
 
4

Length

Max length7
Median length4
Mean length3.1327345
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> 4258
60.7%
0 1931
27.5%
1 424
 
6.0%
사용시작지하층 364
 
5.2%
2 33
 
0.5%
3 3
 
< 0.1%
22 1
 
< 0.1%

Length

2024-04-17T10:46:39.222771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:39.330983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4258
60.7%
0 1931
27.5%
1 424
 
6.0%
사용시작지하층 364
 
5.2%
2 33
 
0.5%
3 3
 
< 0.1%
22 1
 
< 0.1%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
3512 
0
3472 
세탁기수
 
30

Length

Max length4
Median length4
Mean length2.5149701
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> 3512
50.1%
0 3472
49.5%
세탁기수 30
 
0.4%

Length

2024-04-17T10:46:39.441173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:39.528466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3512
50.1%
0 3472
49.5%
세탁기수 30
 
0.4%

yangsilcnt
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
0
4141 
<NA>
2843 
양실수
 
29
38
 
1

Length

Max length4
Median length1
Mean length2.2244083
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 4141
59.0%
<NA> 2843
40.5%
양실수 29
 
0.4%
38 1
 
< 0.1%

Length

2024-04-17T10:46:39.616544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:39.702796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4141
59.0%
na 2843
40.5%
양실수 29
 
0.4%
38 1
 
< 0.1%

wmeipcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
4778 
0
2107 
1
 
92
여성종사자수
 
35
2
 
2

Length

Max length6
Median length4
Mean length3.0685771
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> 4778
68.1%
0 2107
30.0%
1 92
 
1.3%
여성종사자수 35
 
0.5%
2 2
 
< 0.1%

Length

2024-04-17T10:46:39.797462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:39.884520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4778
68.1%
0 2107
30.0%
1 92
 
1.3%
여성종사자수 35
 
0.5%
2 2
 
< 0.1%

yoksilcnt
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
0
4141 
<NA>
2843 
욕실수
 
29
2
 
1

Length

Max length4
Median length1
Mean length2.2242658
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 4141
59.0%
<NA> 2843
40.5%
욕실수 29
 
0.4%
2 1
 
< 0.1%

Length

2024-04-17T10:46:40.004172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:40.098467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4141
59.0%
na 2843
40.5%
욕실수 29
 
0.4%
2 1
 
< 0.1%

sntuptaenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
일반이용업
6883 
이용업 기타
 
106
일반미용업
 
23
<NA>
 
2

Length

Max length6
Median length5
Mean length5.0148275
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 6883
98.1%
이용업 기타 106
 
1.5%
일반미용업 23
 
0.3%
<NA> 2
 
< 0.1%

Length

2024-04-17T10:46:40.202212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:40.296314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 6883
96.7%
이용업 106
 
1.5%
기타 106
 
1.5%
일반미용업 23
 
0.3%
na 2
 
< 0.1%

chaircnt
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
2
2248 
3
1385 
4
738 
<NA>
678 
1
619 
Other values (12)
1346 

Length

Max length4
Median length1
Mean length1.3035358
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
2 2248
32.1%
3 1385
19.7%
4 738
 
10.5%
<NA> 678
 
9.7%
1 619
 
8.8%
0 423
 
6.0%
5 294
 
4.2%
6 196
 
2.8%
7 173
 
2.5%
8 122
 
1.7%
Other values (7) 138
 
2.0%

Length

2024-04-17T10:46:40.389655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 2248
32.1%
3 1385
19.7%
4 738
 
10.5%
na 678
 
9.7%
1 619
 
8.8%
0 423
 
6.0%
5 294
 
4.2%
6 196
 
2.8%
7 173
 
2.5%
8 122
 
1.7%
Other values (7) 138
 
2.0%

cndpermstymd
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
6608 
조건부허가시작일자
 
401
20050520
 
1
20050414
 
1
20210106
 
1
Other values (2)
 
2

Length

Max length9
Median length4
Mean length4.2887083
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> 6608
94.2%
조건부허가시작일자 401
 
5.7%
20050520 1
 
< 0.1%
20050414 1
 
< 0.1%
20210106 1
 
< 0.1%
20190201 1
 
< 0.1%
20190812 1
 
< 0.1%

Length

2024-04-17T10:46:40.491952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:40.585775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6608
94.2%
조건부허가시작일자 401
 
5.7%
20050520 1
 
< 0.1%
20050414 1
 
< 0.1%
20210106 1
 
< 0.1%
20190201 1
 
< 0.1%
20190812 1
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
6609 
조건부허가신고사유
 
401
가설건축물
 
1
외국국적동포 국내거소신고증 체류기간
 
1
전통시장 사용기간제한 허가승인(2018.01.01.~2020.12.31.)
 
1

Length

Max length41
Median length4
Mean length4.2939835
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> 6609
94.2%
조건부허가신고사유 401
 
5.7%
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

2024-04-17T10:46:40.698044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:40.807645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6609
94.2%
조건부허가신고사유 401
 
5.7%
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 size54.9 KiB
<NA>
6608 
조건부허가종료일자
 
401
20060425
 
1
20050414
 
1
20240422
 
1
Other values (2)
 
2

Length

Max length9
Median length4
Mean length4.2887083
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> 6608
94.2%
조건부허가종료일자 401
 
5.7%
20060425 1
 
< 0.1%
20050414 1
 
< 0.1%
20240422 1
 
< 0.1%
20201231 1
 
< 0.1%
20281022 1
 
< 0.1%

Length

2024-04-17T10:46:40.910355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:41.013047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6608
94.2%
조건부허가종료일자 401
 
5.7%
20060425 1
 
< 0.1%
20050414 1
 
< 0.1%
20240422 1
 
< 0.1%
20201231 1
 
< 0.1%
20281022 1
 
< 0.1%

abedcnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
3713 
0
3236 
침대수
 
30
1
 
20
2
 
7
Other values (3)
 
8

Length

Max length4
Median length4
Mean length2.5966638
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> 3713
52.9%
0 3236
46.1%
침대수 30
 
0.4%
1 20
 
0.3%
2 7
 
0.1%
3 4
 
0.1%
6 3
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-17T10:46:41.138676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:41.236164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3713
52.9%
0 3236
46.1%
침대수 30
 
0.4%
1 20
 
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 size54.9 KiB
0
4141 
<NA>
2844 
한실수
 
29

Length

Max length4
Median length1
Mean length2.2246935
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 4141
59.0%
<NA> 2844
40.5%
한실수 29
 
0.4%

Length

2024-04-17T10:46:41.340853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:41.429300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4141
59.0%
na 2844
40.5%
한실수 29
 
0.4%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
<NA>
3695 
0
3289 
회수건조수
 
30

Length

Max length5
Median length4
Mean length2.5975192
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> 3695
52.7%
0 3289
46.9%
회수건조수 30
 
0.4%

Length

2024-04-17T10:46:41.528366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:41.618291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3695
52.7%
0 3289
46.9%
회수건조수 30
 
0.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.9 KiB
Minimum2021-02-01 05:25:03
Maximum2021-02-01 05:25:04
2024-04-17T10:46:41.687654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T10:46:41.769556image/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>0002021-02-01 05:25:03
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>2021-02-01 05:25:03
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>0002021-02-01 05:25:03
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>2021-02-01 05:25:03
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>2021-02-01 05:25:03
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>2021-02-01 05:25:03
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>0002021-02-01 05:25:03
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>2021-02-01 05:25:03
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>0002021-02-01 05:25:03
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>0002021-02-01 05:25:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
7004700638600003860000-203-2021-0000205_19_01_PI2021-01-30 00:23:03.0이용업오땡큐 역곡점<NA>경기도 부천시 역곡동 85-9 1층 일부14670경기도 부천시 지봉로 108, 1층 일부 (역곡동)20210128<NA><NA><NA><NA>영업/정상영업183233.535127843442889.3877344220210128132919일반이용업<NA><NA>000NN<NA><NA><NA><NA>0000일반이용업2<NA><NA><NA>0002021-02-01 05:25:04
7005700740900004090000-203-2021-0000105_19_01_PI2021-01-30 00:23:03.0이용업착한머리415080경기도 김포시 구래동 6880-7 월드에비뉴주차빌딩10071경기도 김포시 김포한강7로 93, 월드에비뉴주차빌딩 148호 (구래동)20210128<NA><NA><NA><NA>영업/정상영업167087.307183519460438.37872208520210128112653일반이용업<NA><NA>000NN<NA><NA><NA><NA>0000일반이용업3<NA><NA><NA>0002021-02-01 05:25:04
7006700854500005450000-203-2021-0000105_19_01_PI2021-01-30 00:23:03.0이용업가위손666913경상남도 산청군 생초면 어서리 319-452203경상남도 산청군 생초면 생초로 26-220210128<NA><NA><NA><NA>영업/정상영업275833.334904175221822.38233597620210128141634일반이용업<NA>임대201NN1<NA>1<NA>0000일반이용업3<NA><NA><NA>0002021-02-01 05:25:04
7007700953100005310000-203-2021-0000105_19_01_PI2021-01-30 00:23:03.0이용업퀸즈헤나660923경상남도 진주시 금산면 중천리 247 2층일부52633경상남도 진주시 금산면 금산로 70, 2층일부20210128<NA><NA><NA><NA>영업/정상영업304116.67930452191157.78071063920210128094114일반이용업<NA><NA>000NN<NA><NA><NA><NA>0000일반이용업2<NA><NA><NA>0002021-02-01 05:25:04
7008701032800003280000-203-2021-0000105_19_01_PI2021-01-31 00:23:03.0이용업긱스(geeks)606042부산광역시 영도구 영선동2가 44-249056부산광역시 영도구 영선대로 67 (영선동2가)20210129폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업386100.884001403178372.43703474920210129120253일반이용업전화번호건물소유구분명000NN1사용끝지하층1사용시작지하층0000일반이용업4조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-02-01 05:25:04
7009701130400003040000-203-2021-0000105_19_01_PI2021-01-31 00:23:03.0이용업휴브리스 바버샵 자양점143190서울특별시 광진구 자양동 806-9 space 665064서울특별시 광진구 자양번영로 66, space 66 1층 (자양동)20210129<NA><NA><NA><NA>영업/정상영업206697.92786592448131.61815822520210129135310일반이용업<NA><NA>001NN1<NA>1<NA>0000일반이용업1<NA><NA><NA>0002021-02-01 05:25:04
7010701239100003910000-203-2021-0000105_19_01_PI2021-01-31 00:23:03.0이용업198바버샵450090경기도 평택시 지제동 447-717823경기도 평택시 지제로 78-36, 1층 (지제동)20210129<NA><NA><NA><NA>영업/정상영업205762.763593135391153.79567452920210129165532일반이용업<NA>임대001NN<NA><NA>1<NA>0000일반이용업2<NA><NA><NA>0002021-02-01 05:25:04
7011701332800003280000-203-2021-0000105_19_01_PI2021-01-31 00:23:03.0이용업긱스(geeks)606042부산광역시 영도구 영선동2가 44-249056부산광역시 영도구 영선대로 67 (영선동2가)20210129폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업386100.884001403178372.43703474920210129120253일반이용업전화번호건물소유구분명000NN1사용끝지하층1사용시작지하층0000일반이용업4조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-02-01 05:25:04
7012701430400003040000-203-2021-0000105_19_01_PI2021-01-31 00:23:03.0이용업휴브리스 바버샵 자양점143190서울특별시 광진구 자양동 806-9 space 665064서울특별시 광진구 자양번영로 66, space 66 1층 (자양동)20210129<NA><NA><NA><NA>영업/정상영업206697.92786592448131.61815822520210129135310일반이용업<NA><NA>001NN1<NA>1<NA>0000일반이용업1<NA><NA><NA>0002021-02-01 05:25:04
7013701539100003910000-203-2021-0000105_19_01_PI2021-01-31 00:23:03.0이용업198바버샵450090경기도 평택시 지제동 447-717823경기도 평택시 지제로 78-36, 1층 (지제동)20210129<NA><NA><NA><NA>영업/정상영업205762.763593135391153.79567452920210129165532일반이용업<NA>임대001NN<NA><NA>1<NA>0000일반이용업2<NA><NA><NA>0002021-02-01 05:25:04