Overview

Dataset statistics

Number of variables47
Number of observations6948
Missing cells9045
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 (69.0%)Imbalance
clgenddt is highly imbalanced (69.0%)Imbalance
ropnymd is highly imbalanced (69.0%)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 (56.9%)Imbalance
multusnupsoyn is highly imbalanced (99.0%)Imbalance
useunderendflr is highly imbalanced (54.3%)Imbalance
wmeipcnt is highly imbalanced (56.4%)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 (64.1%)Imbalance
sitepostno has 70 (1.0%) missing valuesMissing
rdnpostno has 2665 (38.4%) missing valuesMissing
rdnwhladdr has 2607 (37.5%) missing valuesMissing
dcbymd has 2737 (39.4%) missing valuesMissing
x has 327 (4.7%) missing valuesMissing
y has 327 (4.7%) missing valuesMissing
sitetel has 308 (4.4%) missing valuesMissing
apvpermymd is highly skewed (γ1 = -20.07943491)Skewed
skey has unique valuesUnique

Reproduction

Analysis started2024-04-17 01:46:44.794873
Analysis finished2024-04-17 01:46:47.028904
Duration2.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct6948
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3474.6724
Minimum1
Maximum6949
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2024-04-17T10:46:47.082886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile348.35
Q11737.75
median3474.5
Q35211.25
95-th percentile6601.65
Maximum6949
Range6948
Interquartile range (IQR)3473.5

Descriptive statistics

Standard deviation2006.1064
Coefficient of variation (CV)0.57735122
Kurtosis-1.1998303
Mean3474.6724
Median Absolute Deviation (MAD)1737
Skewness0.00027973724
Sum24142024
Variance4024462.7
MonotonicityNot monotonic
2024-04-17T10:46:47.193318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 1
 
< 0.1%
4629 1
 
< 0.1%
4665 1
 
< 0.1%
4639 1
 
< 0.1%
4638 1
 
< 0.1%
4637 1
 
< 0.1%
4636 1
 
< 0.1%
4635 1
 
< 0.1%
4634 1
 
< 0.1%
4633 1
 
< 0.1%
Other values (6938) 6938
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 (%)
6949 1
< 0.1%
6948 1
< 0.1%
6947 1
< 0.1%
6946 1
< 0.1%
6945 1
< 0.1%
6944 1
< 0.1%
6943 1
< 0.1%
6942 1
< 0.1%
6941 1
< 0.1%
6940 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct202
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3537093.6
Minimum3000000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2024-04-17T10:46:47.307232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3200000
Q13290000
median3340000
Q33390000
95-th percentile5100000
Maximum6520000
Range3520000
Interquartile range (IQR)100000

Descriptive statistics

Standard deviation571426.75
Coefficient of variation (CV)0.16155262
Kurtosis6.9630768
Mean3537093.6
Median Absolute Deviation (MAD)50000
Skewness2.7235361
Sum2.4575726 × 1010
Variance3.2652853 × 1011
MonotonicityNot monotonic
2024-04-17T10:46:47.429757image/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
 
5.6%
3350000 377
 
5.4%
3390000 335
 
4.8%
3370000 327
 
4.7%
3310000 322
 
4.6%
3380000 282
 
4.1%
Other values (192) 3081
44.3%
ValueCountFrequency (%)
3000000 20
0.3%
3010000 20
0.3%
3020000 24
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 24
0.3%
5700000 4
 
0.1%
5690000 13
 
0.2%
5680000 6
 
0.1%
5670000 56
0.8%
5600000 2
 
< 0.1%
5590000 5
 
0.1%
5580000 1
 
< 0.1%

mgtno
Text

Distinct6447
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
2024-04-17T10:46:47.626582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters152856
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

Unique6167 ?
Unique (%)88.8%

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%
5230000-203-2020-00001 3
 
< 0.1%
3430000-203-2019-00003 3
 
< 0.1%
3800000-203-2019-00002 3
 
< 0.1%
3570000-203-2020-00002 3
 
< 0.1%
3470000-203-2020-00005 3
 
< 0.1%
3420000-203-2020-00005 3
 
< 0.1%
5670206-203-2020-00001 3
 
< 0.1%
4060000-203-2020-00002 3
 
< 0.1%
5080000-203-2019-00005 3
 
< 0.1%
Other values (6437) 6917
99.6%
2024-04-17T10:46:47.908801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 64536
42.2%
- 20844
 
13.6%
3 19332
 
12.6%
2 16615
 
10.9%
1 8558
 
5.6%
9 7374
 
4.8%
5 3302
 
2.2%
4 3266
 
2.1%
8 3218
 
2.1%
7 2910
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 132012
86.4%
Dash Punctuation 20844
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 64536
48.9%
3 19332
 
14.6%
2 16615
 
12.6%
1 8558
 
6.5%
9 7374
 
5.6%
5 3302
 
2.5%
4 3266
 
2.5%
8 3218
 
2.4%
7 2910
 
2.2%
6 2901
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 20844
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 152856
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 64536
42.2%
- 20844
 
13.6%
3 19332
 
12.6%
2 16615
 
10.9%
1 8558
 
5.6%
9 7374
 
4.8%
5 3302
 
2.2%
4 3266
 
2.1%
8 3218
 
2.1%
7 2910
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 152856
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 64536
42.2%
- 20844
 
13.6%
3 19332
 
12.6%
2 16615
 
10.9%
1 8558
 
5.6%
9 7374
 
4.8%
5 3302
 
2.2%
4 3266
 
2.1%
8 3218
 
2.1%
7 2910
 
1.9%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
05_19_01_P
6948 

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 6948
100.0%

Length

2024-04-17T10:46:48.022651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:48.099277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 6948
100.0%

updategbn
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
I
5789 
U
1159 

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 5789
83.3%
U 1159
 
16.7%

Length

2024-04-17T10:46:48.194654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:48.273175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5789
83.3%
u 1159
 
16.7%
Distinct840
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-02 02:40:00
2024-04-17T10:46:48.366505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T10:46:48.478950image/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 size54.4 KiB
<NA>
4572 
이용업
2376 

Length

Max length4
Median length4
Mean length3.6580311
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> 4572
65.8%
이용업 2376
34.2%

Length

2024-04-17T10:46:48.583147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:48.663530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4572
65.8%
이용업 2376
34.2%

bplcnm
Text

Distinct4591
Distinct (%)66.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
2024-04-17T10:46:48.898393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length5.3700345
Min length1

Characters and Unicode

Total characters37311
Distinct characters690
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

Unique3599 ?
Unique (%)51.8%

Sample

1st row태양탕구내
2nd row국사 이용원
3rd row녹수탕구내이용원
4th row부산호텔이용원
5th row터프가위 이용원
ValueCountFrequency (%)
이용원 425
 
5.1%
바버샵 102
 
1.2%
구내 56
 
0.7%
태후사랑 53
 
0.6%
퀸즈헤나 52
 
0.6%
컷트실 51
 
0.6%
구내이용원 41
 
0.5%
현대 36
 
0.4%
이발관 31
 
0.4%
블루클럽 30
 
0.4%
Other values (4487) 7460
89.5%
2024-04-17T10:46:49.298088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3117
 
8.4%
2571
 
6.9%
2413
 
6.5%
1402
 
3.8%
1032
 
2.8%
898
 
2.4%
639
 
1.7%
600
 
1.6%
541
 
1.4%
454
 
1.2%
Other values (680) 23644
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33866
90.8%
Space Separator 1402
 
3.8%
Lowercase Letter 737
 
2.0%
Uppercase Letter 728
 
2.0%
Open Punctuation 200
 
0.5%
Close Punctuation 200
 
0.5%
Decimal Number 112
 
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 (%)
3117
 
9.2%
2571
 
7.6%
2413
 
7.1%
1032
 
3.0%
898
 
2.7%
639
 
1.9%
600
 
1.8%
541
 
1.6%
454
 
1.3%
448
 
1.3%
Other values (608) 21153
62.5%
Uppercase Letter
ValueCountFrequency (%)
B 103
14.1%
R 67
 
9.2%
O 65
 
8.9%
S 63
 
8.7%
E 61
 
8.4%
H 45
 
6.2%
A 43
 
5.9%
T 39
 
5.4%
P 31
 
4.3%
C 27
 
3.7%
Other values (16) 184
25.3%
Lowercase Letter
ValueCountFrequency (%)
r 104
14.1%
e 79
10.7%
a 76
10.3%
o 67
9.1%
h 59
8.0%
b 56
 
7.6%
s 50
 
6.8%
p 40
 
5.4%
n 35
 
4.7%
i 30
 
4.1%
Other values (14) 141
19.1%
Decimal Number
ValueCountFrequency (%)
2 23
20.5%
1 20
17.9%
8 18
16.1%
3 14
12.5%
9 10
8.9%
4 8
 
7.1%
5 7
 
6.2%
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 (%)
1402
100.0%
Open Punctuation
ValueCountFrequency (%)
( 200
100.0%
Close Punctuation
ValueCountFrequency (%)
) 200
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33861
90.8%
Common 1980
 
5.3%
Latin 1465
 
3.9%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3117
 
9.2%
2571
 
7.6%
2413
 
7.1%
1032
 
3.0%
898
 
2.7%
639
 
1.9%
600
 
1.8%
541
 
1.6%
454
 
1.3%
448
 
1.3%
Other values (603) 21148
62.5%
Latin
ValueCountFrequency (%)
r 104
 
7.1%
B 103
 
7.0%
e 79
 
5.4%
a 76
 
5.2%
o 67
 
4.6%
R 67
 
4.6%
O 65
 
4.4%
S 63
 
4.3%
E 61
 
4.2%
h 59
 
4.0%
Other values (40) 721
49.2%
Common
ValueCountFrequency (%)
1402
70.8%
( 200
 
10.1%
) 200
 
10.1%
. 28
 
1.4%
2 23
 
1.2%
1 20
 
1.0%
8 18
 
0.9%
3 14
 
0.7%
& 11
 
0.6%
9 10
 
0.5%
Other values (12) 54
 
2.7%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33861
90.8%
ASCII 3441
 
9.2%
CJK 5
 
< 0.1%
None 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3117
 
9.2%
2571
 
7.6%
2413
 
7.1%
1032
 
3.0%
898
 
2.7%
639
 
1.9%
600
 
1.8%
541
 
1.6%
454
 
1.3%
448
 
1.3%
Other values (603) 21148
62.5%
ASCII
ValueCountFrequency (%)
1402
40.7%
( 200
 
5.8%
) 200
 
5.8%
r 104
 
3.0%
B 103
 
3.0%
e 79
 
2.3%
a 76
 
2.2%
o 67
 
1.9%
R 67
 
1.9%
O 65
 
1.9%
Other values (61) 1078
31.3%
None
ValueCountFrequency (%)
· 4
100.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

sitepostno
Text

MISSING 

Distinct2045
Distinct (%)29.7%
Missing70
Missing (%)1.0%
Memory size54.4 KiB
2024-04-17T10:46:49.599117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters41268
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

Unique1006 ?
Unique (%)14.6%

Sample

1st row600046
2nd row600061
3rd row600062
4th row600022
5th row600816
ValueCountFrequency (%)
607833 33
 
0.5%
616801 28
 
0.4%
601829 28
 
0.4%
604851 27
 
0.4%
612847 27
 
0.4%
617818 24
 
0.3%
607826 24
 
0.3%
616807 23
 
0.3%
611803 22
 
0.3%
604813 21
 
0.3%
Other values (2035) 6621
96.3%
2024-04-17T10:46:49.984825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 6951
16.8%
6 6910
16.7%
0 6766
16.4%
1 6169
14.9%
2 3181
7.7%
4 3100
7.5%
3 2912
7.1%
7 2063
 
5.0%
5 1593
 
3.9%
9 1539
 
3.7%
Other values (5) 84
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41184
99.8%
Other Letter 84
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 6951
16.9%
6 6910
16.8%
0 6766
16.4%
1 6169
15.0%
2 3181
7.7%
4 3100
7.5%
3 2912
7.1%
7 2063
 
5.0%
5 1593
 
3.9%
9 1539
 
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 41184
99.8%
Hangul 84
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
8 6951
16.9%
6 6910
16.8%
0 6766
16.4%
1 6169
15.0%
2 3181
7.7%
4 3100
7.5%
3 2912
7.1%
7 2063
 
5.0%
5 1593
 
3.9%
9 1539
 
3.7%
Hangul
ValueCountFrequency (%)
28
33.3%
14
16.7%
14
16.7%
14
16.7%
14
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41184
99.8%
Hangul 84
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 6951
16.9%
6 6910
16.8%
0 6766
16.4%
1 6169
15.0%
2 3181
7.7%
4 3100
7.5%
3 2912
7.1%
7 2063
 
5.0%
5 1593
 
3.9%
9 1539
 
3.7%
Hangul
ValueCountFrequency (%)
28
33.3%
14
16.7%
14
16.7%
14
16.7%
14
16.7%
Distinct5828
Distinct (%)83.9%
Missing3
Missing (%)< 0.1%
Memory size54.4 KiB
2024-04-17T10:46:50.257781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length55
Mean length25.309719
Min length7

Characters and Unicode

Total characters175776
Distinct characters545
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

Unique5077 ?
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
 
14.9%
t통b반 768
 
2.3%
부산진구 506
 
1.5%
사하구 503
 
1.5%
서울특별시 492
 
1.5%
북구 482
 
1.5%
경기도 442
 
1.3%
동래구 415
 
1.3%
해운대구 392
 
1.2%
남구 391
 
1.2%
Other values (7931) 23517
71.7%
2024-04-17T10:46:50.685150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32470
 
18.5%
7897
 
4.5%
1 7418
 
4.2%
6915
 
3.9%
6636
 
3.8%
6543
 
3.7%
6302
 
3.6%
6198
 
3.5%
- 6111
 
3.5%
6076
 
3.5%
Other values (535) 83210
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 101419
57.7%
Decimal Number 33401
 
19.0%
Space Separator 32470
 
18.5%
Dash Punctuation 6111
 
3.5%
Uppercase Letter 1664
 
0.9%
Open Punctuation 279
 
0.2%
Close Punctuation 278
 
0.2%
Other Punctuation 145
 
0.1%
Math Symbol 4
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7897
 
7.8%
6915
 
6.8%
6636
 
6.5%
6543
 
6.5%
6302
 
6.2%
6198
 
6.1%
6076
 
6.0%
5678
 
5.6%
5396
 
5.3%
1390
 
1.4%
Other values (489) 42388
41.8%
Uppercase Letter
ValueCountFrequency (%)
B 805
48.4%
T 771
46.3%
A 30
 
1.8%
S 9
 
0.5%
C 7
 
0.4%
I 6
 
0.4%
L 5
 
0.3%
M 5
 
0.3%
F 5
 
0.3%
K 4
 
0.2%
Other values (11) 17
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 7418
22.2%
2 4440
13.3%
3 3734
11.2%
4 3118
9.3%
5 2958
 
8.9%
0 2609
 
7.8%
6 2453
 
7.3%
8 2344
 
7.0%
7 2338
 
7.0%
9 1989
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 126
86.9%
. 10
 
6.9%
@ 6
 
4.1%
/ 3
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
s 1
25.0%
e 1
25.0%
a 1
25.0%
p 1
25.0%
Math Symbol
ValueCountFrequency (%)
~ 3
75.0%
+ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
32470
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6111
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 101417
57.7%
Common 72688
41.4%
Latin 1669
 
0.9%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7897
 
7.8%
6915
 
6.8%
6636
 
6.5%
6543
 
6.5%
6302
 
6.2%
6198
 
6.1%
6076
 
6.0%
5678
 
5.6%
5396
 
5.3%
1390
 
1.4%
Other values (488) 42386
41.8%
Latin
ValueCountFrequency (%)
B 805
48.2%
T 771
46.2%
A 30
 
1.8%
S 9
 
0.5%
C 7
 
0.4%
I 6
 
0.4%
L 5
 
0.3%
M 5
 
0.3%
F 5
 
0.3%
K 4
 
0.2%
Other values (16) 22
 
1.3%
Common
ValueCountFrequency (%)
32470
44.7%
1 7418
 
10.2%
- 6111
 
8.4%
2 4440
 
6.1%
3 3734
 
5.1%
4 3118
 
4.3%
5 2958
 
4.1%
0 2609
 
3.6%
6 2453
 
3.4%
8 2344
 
3.2%
Other values (10) 5033
 
6.9%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 101417
57.7%
ASCII 74356
42.3%
CJK 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32470
43.7%
1 7418
 
10.0%
- 6111
 
8.2%
2 4440
 
6.0%
3 3734
 
5.0%
4 3118
 
4.2%
5 2958
 
4.0%
0 2609
 
3.5%
6 2453
 
3.3%
8 2344
 
3.2%
Other values (35) 6701
 
9.0%
Hangul
ValueCountFrequency (%)
7897
 
7.8%
6915
 
6.8%
6636
 
6.5%
6543
 
6.5%
6302
 
6.2%
6198
 
6.1%
6076
 
6.0%
5678
 
5.6%
5396
 
5.3%
1390
 
1.4%
Other values (488) 42386
41.8%
CJK
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Real number (ℝ)

MISSING 

Distinct2545
Distinct (%)59.4%
Missing2665
Missing (%)38.4%
Infinite0
Infinite (%)0.0%
Mean37845.636
Minimum1046
Maximum63629
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2024-04-17T10:46:50.812617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1046
5-th percentile4424
Q126027
median46941
Q348445
95-th percentile52813
Maximum63629
Range62583
Interquartile range (IQR)22418

Descriptive statistics

Standard deviation16577.162
Coefficient of variation (CV)0.43802043
Kurtosis-0.47396613
Mean37845.636
Median Absolute Deviation (MAD)2415
Skewness-0.99202548
Sum1.6209286 × 108
Variance2.7480229 × 108
MonotonicityNot monotonic
2024-04-17T10:46:51.155866image/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%
48099 7
 
0.1%
48501 7
 
0.1%
49217 7
 
0.1%
11813 7
 
0.1%
47603 7
 
0.1%
Other values (2535) 4197
60.4%
(Missing) 2665
38.4%
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 

Distinct3727
Distinct (%)85.9%
Missing2607
Missing (%)37.5%
Memory size54.4 KiB
2024-04-17T10:46:51.436779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length55
Mean length30.864317
Min length16

Characters and Unicode

Total characters133982
Distinct characters584
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

Unique3345 ?
Unique (%)77.1%

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
 
8.5%
1층 1127
 
4.2%
서울특별시 492
 
1.8%
경기도 442
 
1.6%
2층 338
 
1.3%
부산진구 269
 
1.0%
남구 231
 
0.9%
북구 224
 
0.8%
동래구 221
 
0.8%
사하구 218
 
0.8%
Other values (6199) 21092
78.2%
2024-04-17T10:46:51.864149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22621
 
16.9%
1 5799
 
4.3%
5368
 
4.0%
4414
 
3.3%
4073
 
3.0%
) 4071
 
3.0%
( 4070
 
3.0%
3936
 
2.9%
3355
 
2.5%
3240
 
2.4%
Other values (574) 73035
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78424
58.5%
Space Separator 22621
 
16.9%
Decimal Number 20651
 
15.4%
Close Punctuation 4071
 
3.0%
Open Punctuation 4070
 
3.0%
Other Punctuation 3117
 
2.3%
Dash Punctuation 848
 
0.6%
Uppercase Letter 172
 
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 (%)
5368
 
6.8%
4414
 
5.6%
4073
 
5.2%
3936
 
5.0%
3355
 
4.3%
3240
 
4.1%
3050
 
3.9%
2799
 
3.6%
2291
 
2.9%
2223
 
2.8%
Other values (529) 43675
55.7%
Uppercase Letter
ValueCountFrequency (%)
B 62
36.0%
A 34
19.8%
S 10
 
5.8%
C 9
 
5.2%
T 9
 
5.2%
M 7
 
4.1%
F 5
 
2.9%
I 5
 
2.9%
P 5
 
2.9%
L 4
 
2.3%
Other values (10) 22
 
12.8%
Decimal Number
ValueCountFrequency (%)
1 5799
28.1%
2 3159
15.3%
3 2218
 
10.7%
0 1702
 
8.2%
4 1653
 
8.0%
5 1462
 
7.1%
6 1327
 
6.4%
7 1190
 
5.8%
9 1086
 
5.3%
8 1055
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 3093
99.2%
. 12
 
0.4%
@ 5
 
0.2%
/ 5
 
0.2%
& 1
 
< 0.1%
· 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 3
75.0%
+ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
22621
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4071
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4070
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 848
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 78424
58.5%
Common 55383
41.3%
Latin 175
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5368
 
6.8%
4414
 
5.6%
4073
 
5.2%
3936
 
5.0%
3355
 
4.3%
3240
 
4.1%
3050
 
3.9%
2799
 
3.6%
2291
 
2.9%
2223
 
2.8%
Other values (529) 43675
55.7%
Common
ValueCountFrequency (%)
22621
40.8%
1 5799
 
10.5%
) 4071
 
7.4%
( 4070
 
7.3%
2 3159
 
5.7%
, 3093
 
5.6%
3 2218
 
4.0%
0 1702
 
3.1%
4 1653
 
3.0%
5 1462
 
2.6%
Other values (13) 5535
 
10.0%
Latin
ValueCountFrequency (%)
B 62
35.4%
A 34
19.4%
S 10
 
5.7%
C 9
 
5.1%
T 9
 
5.1%
M 7
 
4.0%
F 5
 
2.9%
I 5
 
2.9%
P 5
 
2.9%
L 4
 
2.3%
Other values (12) 25
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78424
58.5%
ASCII 55555
41.5%
Number Forms 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22621
40.7%
1 5799
 
10.4%
) 4071
 
7.3%
( 4070
 
7.3%
2 3159
 
5.7%
, 3093
 
5.6%
3 2218
 
4.0%
0 1702
 
3.1%
4 1653
 
3.0%
5 1462
 
2.6%
Other values (33) 5707
 
10.3%
Hangul
ValueCountFrequency (%)
5368
 
6.8%
4414
 
5.6%
4073
 
5.2%
3936
 
5.0%
3355
 
4.3%
3240
 
4.1%
3050
 
3.9%
2799
 
3.6%
2291
 
2.9%
2223
 
2.8%
Other values (529) 43675
55.7%
Number Forms
ValueCountFrequency (%)
2
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

apvpermymd
Real number (ℝ)

SKEWED 

Distinct4007
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20026904
Minimum9710223
Maximum20201231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2024-04-17T10:46:51.984995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9710223
5-th percentile19711212
Q119920517
median20041065
Q320190222
95-th percentile20200810
Maximum20201231
Range10491008
Interquartile range (IQR)269704.75

Descriptive statistics

Standard deviation199927.98
Coefficient of variation (CV)0.0099829698
Kurtosis1019.4387
Mean20026904
Median Absolute Deviation (MAD)140851.5
Skewness-20.079435
Sum1.3914693 × 1011
Variance3.9971196 × 1010
MonotonicityNot monotonic
2024-04-17T10:46:52.108572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19660301 35
 
0.5%
19770830 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 (3997) 6719
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 (%)
20201231 2
 
< 0.1%
20201230 1
 
< 0.1%
20201229 4
0.1%
20201228 6
0.1%
20201224 4
0.1%
20201223 2
 
< 0.1%
20201222 2
 
< 0.1%
20201221 2
 
< 0.1%
20201218 6
0.1%
20201217 3
< 0.1%

dcbymd
Text

MISSING 

Distinct2314
Distinct (%)55.0%
Missing2737
Missing (%)39.4%
Memory size54.4 KiB
2024-04-17T10:46:52.319156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.6428402
Min length4

Characters and Unicode

Total characters32184
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

Unique1575 ?
Unique (%)37.4%

Sample

1st row20180501
2nd row20121212
3rd row20151228
4th row20121212
5th row20080710
ValueCountFrequency (%)
폐업일자 376
 
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%
20030215 13
 
0.3%
Other values (2304) 3556
84.4%
2024-04-17T10:46:52.673385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10878
33.8%
2 6614
20.6%
1 5063
15.7%
3 1507
 
4.7%
9 1348
 
4.2%
5 1304
 
4.1%
4 1068
 
3.3%
7 1019
 
3.2%
6 955
 
3.0%
8 924
 
2.9%
Other values (4) 1504
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30680
95.3%
Other Letter 1504
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10878
35.5%
2 6614
21.6%
1 5063
16.5%
3 1507
 
4.9%
9 1348
 
4.4%
5 1304
 
4.3%
4 1068
 
3.5%
7 1019
 
3.3%
6 955
 
3.1%
8 924
 
3.0%
Other Letter
ValueCountFrequency (%)
376
25.0%
376
25.0%
376
25.0%
376
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30680
95.3%
Hangul 1504
 
4.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10878
35.5%
2 6614
21.6%
1 5063
16.5%
3 1507
 
4.9%
9 1348
 
4.4%
5 1304
 
4.3%
4 1068
 
3.5%
7 1019
 
3.3%
6 955
 
3.1%
8 924
 
3.0%
Hangul
ValueCountFrequency (%)
376
25.0%
376
25.0%
376
25.0%
376
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30680
95.3%
Hangul 1504
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10878
35.5%
2 6614
21.6%
1 5063
16.5%
3 1507
 
4.9%
9 1348
 
4.4%
5 1304
 
4.3%
4 1068
 
3.5%
7 1019
 
3.3%
6 955
 
3.1%
8 924
 
3.0%
Hangul
ValueCountFrequency (%)
376
25.0%
376
25.0%
376
25.0%
376
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
<NA>
6562 
휴업시작일자
 
386

Length

Max length6
Median length4
Mean length4.1111111
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> 6562
94.4%
휴업시작일자 386
 
5.6%

Length

2024-04-17T10:46:52.797298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:52.883193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6562
94.4%
휴업시작일자 386
 
5.6%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
<NA>
6562 
휴업종료일자
 
386

Length

Max length6
Median length4
Mean length4.1111111
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> 6562
94.4%
휴업종료일자 386
 
5.6%

Length

2024-04-17T10:46:52.977182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:53.061385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6562
94.4%
휴업종료일자 386
 
5.6%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
<NA>
6562 
재개업일자
 
386

Length

Max length5
Median length4
Mean length4.0555556
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> 6562
94.4%
재개업일자 386
 
5.6%

Length

2024-04-17T10:46:53.142741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:53.225112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6562
94.4%
재개업일자 386
 
5.6%

trdstatenm
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
02
3330 
영업/정상
1848 
01
1242 
폐업
504 
<NA>
 
18

Length

Max length5
Median length2
Mean length2.8048359
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
02 3330
47.9%
영업/정상 1848
26.6%
01 1242
 
17.9%
폐업 504
 
7.3%
<NA> 18
 
0.3%
영업상태 6
 
0.1%

Length

2024-04-17T10:46:53.307766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:53.407579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3330
47.9%
영업/정상 1848
26.6%
01 1242
 
17.9%
폐업 504
 
7.3%
na 18
 
0.3%
영업상태 6
 
0.1%

dtlstatenm
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
폐업
3835 
영업
3113 

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 3835
55.2%
영업 3113
44.8%

Length

2024-04-17T10:46:53.509948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:53.596995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3835
55.2%
영업 3113
44.8%

x
Text

MISSING 

Distinct5469
Distinct (%)82.6%
Missing327
Missing (%)4.7%
Memory size54.4 KiB
2024-04-17T10:46:53.771116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.986256
Min length7

Characters and Unicode

Total characters132329
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

Unique4659 ?
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%
389415.20340442 5
 
0.1%
382169.305404 5
 
0.1%
392357.064184 4
 
0.1%
208342.503089715 4
 
0.1%
400804.64364100000 4
 
0.1%
394263.364966 4
 
0.1%
301328.475622934 4
 
0.1%
Other values (5459) 6572
99.3%
2024-04-17T10:46:54.070479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30917
23.4%
0 17513
13.2%
3 12506
9.5%
8 10068
 
7.6%
9 8938
 
6.8%
1 8165
 
6.2%
2 8087
 
6.1%
7 7496
 
5.7%
4 7488
 
5.7%
5 7283
 
5.5%
Other values (9) 13868
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94765
71.6%
Space Separator 30917
 
23.4%
Other Punctuation 6598
 
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 17513
18.5%
3 12506
13.2%
8 10068
10.6%
9 8938
9.4%
1 8165
8.6%
2 8087
8.5%
7 7496
7.9%
4 7488
7.9%
5 7283
7.7%
6 7221
7.6%
Other Letter
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%
Space Separator
ValueCountFrequency (%)
30917
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6598
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 132294
> 99.9%
Hangul 28
 
< 0.1%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
30917
23.4%
0 17513
13.2%
3 12506
9.5%
8 10068
 
7.6%
9 8938
 
6.8%
1 8165
 
6.2%
2 8087
 
6.1%
7 7496
 
5.7%
4 7488
 
5.7%
5 7283
 
5.5%
Other values (4) 13833
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 132301
> 99.9%
Hangul 28
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30917
23.4%
0 17513
13.2%
3 12506
9.5%
8 10068
 
7.6%
9 8938
 
6.8%
1 8165
 
6.2%
2 8087
 
6.1%
7 7496
 
5.7%
4 7488
 
5.7%
5 7283
 
5.5%
Other values (5) 13840
10.5%
Hangul
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%

y
Text

MISSING 

Distinct5469
Distinct (%)82.6%
Missing327
Missing (%)4.7%
Memory size54.4 KiB
2024-04-17T10:46:54.274557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.986256
Min length7

Characters and Unicode

Total characters132329
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

Unique4659 ?
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%
193131.590860807 5
 
0.1%
191928.498233 5
 
0.1%
185295.821253 4
 
0.1%
471448.128699459 4
 
0.1%
189454.38252300000 4
 
0.1%
191382.712014 4
 
0.1%
186233.933566947 4
 
0.1%
Other values (5459) 6572
99.3%
2024-04-17T10:46:54.583263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30845
23.3%
0 16920
12.8%
1 12252
 
9.3%
8 9735
 
7.4%
9 8901
 
6.7%
4 8537
 
6.5%
7 8106
 
6.1%
2 8032
 
6.1%
3 7700
 
5.8%
5 7325
 
5.5%
Other values (10) 13976
10.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94822
71.7%
Space Separator 30845
 
23.3%
Other Punctuation 6598
 
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 16920
17.8%
1 12252
12.9%
8 9735
10.3%
9 8901
9.4%
4 8537
9.0%
7 8106
8.5%
2 8032
8.5%
3 7700
8.1%
5 7325
7.7%
6 7314
7.7%
Other Letter
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%
Space Separator
ValueCountFrequency (%)
30845
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6598
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 132294
> 99.9%
Hangul 28
 
< 0.1%
Latin 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
30845
23.3%
0 16920
12.8%
1 12252
 
9.3%
8 9735
 
7.4%
9 8901
 
6.7%
4 8537
 
6.5%
7 8106
 
6.1%
2 8032
 
6.1%
3 7700
 
5.8%
5 7325
 
5.5%
Other values (5) 13941
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 132301
> 99.9%
Hangul 28
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30845
23.3%
0 16920
12.8%
1 12252
 
9.3%
8 9735
 
7.4%
9 8901
 
6.7%
4 8537
 
6.5%
7 8106
 
6.1%
2 8032
 
6.1%
3 7700
 
5.8%
5 7325
 
5.5%
Other values (6) 13948
10.5%
Hangul
ValueCountFrequency (%)
7
25.0%
7
25.0%
7
25.0%
7
25.0%

lastmodts
Real number (ℝ)

Distinct4760
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0118985 × 1013
Minimum1.9990218 × 1013
Maximum2.0201231 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2024-04-17T10:46:54.706576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile2.0020422 × 1013
Q12.0040984 × 1013
median2.0130222 × 1013
Q32.019071 × 1013
95-th percentile2.020102 × 1013
Maximum2.0201231 × 1013
Range2.1101317 × 1011
Interquartile range (IQR)1.4972614 × 1011

Descriptive statistics

Standard deviation7.11824 × 1010
Coefficient of variation (CV)0.0035380711
Kurtosis-1.4871741
Mean2.0118985 × 1013
Median Absolute Deviation (MAD)6.9617165 × 1010
Skewness-0.25311028
Sum1.3978671 × 1017
Variance5.0669341 × 1021
MonotonicityNot monotonic
2024-04-17T10:46:54.823824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030211000000 63
 
0.9%
20070501000000 54
 
0.8%
20030311000000 38
 
0.5%
20020424000000 38
 
0.5%
20031215000000 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 (4750) 6544
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 (%)
20201231174955 1
 
< 0.1%
20201231151223 1
 
< 0.1%
20201231132019 1
 
< 0.1%
20201231122437 1
 
< 0.1%
20201231091804 1
 
< 0.1%
20201231090420 1
 
< 0.1%
20201230194012 1
 
< 0.1%
20201230151058 3
< 0.1%
20201230145005 1
 
< 0.1%
20201230143812 3
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
일반이용업
6820 
이용업 기타
 
104
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0148244
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 6820
98.2%
이용업 기타 104
 
1.5%
일반미용업 23
 
0.3%
<NA> 1
 
< 0.1%

Length

2024-04-17T10:46:54.939821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:55.034267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 6820
96.7%
이용업 104
 
1.5%
기타 104
 
1.5%
일반미용업 23
 
0.3%
na 1
 
< 0.1%

sitetel
Text

MISSING 

Distinct65
Distinct (%)1.0%
Missing308
Missing (%)4.4%
Memory size54.4 KiB
2024-04-17T10:46:55.163939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.931175
Min length4

Characters and Unicode

Total characters79223
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

Unique52 ?
Unique (%)0.8%

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 6508
96.3%
전화번호 53
 
0.8%
051 14
 
0.2%
031 10
 
0.1%
053 9
 
0.1%
052 8
 
0.1%
054 6
 
0.1%
041 5
 
0.1%
042 4
 
0.1%
4225 3
 
< 0.1%
Other values (108) 140
 
2.1%
2024-04-17T10:46:55.413184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19621
24.8%
3 13108
16.5%
2 13097
16.5%
- 13016
16.4%
0 6631
 
8.4%
5 6608
 
8.3%
4 6569
 
8.3%
127
 
0.2%
8 71
 
0.1%
7 63
 
0.1%
Other values (6) 312
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65868
83.1%
Dash Punctuation 13016
 
16.4%
Other Letter 212
 
0.3%
Space Separator 127
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19621
29.8%
3 13108
19.9%
2 13097
19.9%
0 6631
 
10.1%
5 6608
 
10.0%
4 6569
 
10.0%
8 71
 
0.1%
7 63
 
0.1%
6 61
 
0.1%
9 39
 
0.1%
Other Letter
ValueCountFrequency (%)
53
25.0%
53
25.0%
53
25.0%
53
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 13016
100.0%
Space Separator
ValueCountFrequency (%)
127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79011
99.7%
Hangul 212
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19621
24.8%
3 13108
16.6%
2 13097
16.6%
- 13016
16.5%
0 6631
 
8.4%
5 6608
 
8.4%
4 6569
 
8.3%
127
 
0.2%
8 71
 
0.1%
7 63
 
0.1%
Other values (2) 100
 
0.1%
Hangul
ValueCountFrequency (%)
53
25.0%
53
25.0%
53
25.0%
53
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79011
99.7%
Hangul 212
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19621
24.8%
3 13108
16.6%
2 13097
16.6%
- 13016
16.5%
0 6631
 
8.4%
5 6608
 
8.4%
4 6569
 
8.3%
127
 
0.2%
8 71
 
0.1%
7 63
 
0.1%
Other values (2) 100
 
0.1%
Hangul
ValueCountFrequency (%)
53
25.0%
53
25.0%
53
25.0%
53
25.0%

bdngownsenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
<NA>
5282 
임대
1317 
건물소유구분명
 
308
자가
 
41

Length

Max length7
Median length4
Mean length3.7420841
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> 5282
76.0%
임대 1317
 
19.0%
건물소유구분명 308
 
4.4%
자가 41
 
0.6%

Length

2024-04-17T10:46:55.514310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:55.596566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5282
76.0%
임대 1317
 
19.0%
건물소유구분명 308
 
4.4%
자가 41
 
0.6%

bdngjisgflrcnt
Categorical

Distinct34
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
0
2643 
<NA>
1844 
3
576 
2
516 
4
484 
Other values (29)
885 

Length

Max length6
Median length1
Mean length1.8254174
Min length1

Unique

Unique9 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2643
38.0%
<NA> 1844
26.5%
3 576
 
8.3%
2 516
 
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) 142
 
2.0%

Length

2024-04-17T10:46:55.685349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2643
38.0%
na 1844
26.5%
3 576
 
8.3%
2 516
 
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) 142
 
2.0%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
0
3403 
<NA>
2360 
1
985 
2
 
113
3
 
27
Other values (7)
 
60

Length

Max length6
Median length1
Mean length2.0381405
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3403
49.0%
<NA> 2360
34.0%
1 985
 
14.2%
2 113
 
1.6%
3 27
 
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

2024-04-17T10:46:55.784178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3403
49.0%
na 2360
34.0%
1 985
 
14.2%
2 113
 
1.6%
3 27
 
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 size54.4 KiB
<NA>
4760 
0
1877 
1
 
270
남성종사자수
 
32
2
 
8

Length

Max length6
Median length4
Mean length3.0784398
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> 4760
68.5%
0 1877
 
27.0%
1 270
 
3.9%
남성종사자수 32
 
0.5%
2 8
 
0.1%
11 1
 
< 0.1%

Length

2024-04-17T10:46:55.878902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:55.964538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4760
68.5%
0 1877
 
27.0%
1 270
 
3.9%
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
6941 
True
 
6
(Missing)
 
1
ValueCountFrequency (%)
False 6941
99.9%
True 6
 
0.1%
(Missing) 1
 
< 0.1%
2024-04-17T10:46:56.044770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

balhansilyn
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
False
6948 
ValueCountFrequency (%)
False 6948
100.0%
2024-04-17T10:46:56.105572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

usejisgendflr
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
<NA>
3592 
1
1318 
0
739 
2
585 
3
 
270
Other values (12)
444 

Length

Max length6
Median length4
Mean length2.7095567
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3592
51.7%
1 1318
 
19.0%
0 739
 
10.6%
2 585
 
8.4%
3 270
 
3.9%
사용끝지상층 217
 
3.1%
4 109
 
1.6%
5 59
 
0.8%
6 20
 
0.3%
7 12
 
0.2%
Other values (7) 27
 
0.4%

Length

2024-04-17T10:46:56.183810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3592
51.7%
1 1318
 
19.0%
0 739
 
10.6%
2 585
 
8.4%
3 270
 
3.9%
사용끝지상층 217
 
3.1%
4 109
 
1.6%
5 59
 
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 size54.4 KiB
<NA>
4896 
0
1306 
1
 
366
사용끝지하층
 
355
2
 
21
Other values (2)
 
4

Length

Max length6
Median length4
Mean length3.3694588
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> 4896
70.5%
0 1306
 
18.8%
1 366
 
5.3%
사용끝지하층 355
 
5.1%
2 21
 
0.3%
3 3
 
< 0.1%
4 1
 
< 0.1%

Length

2024-04-17T10:46:56.281192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:56.367559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4896
70.5%
0 1306
 
18.8%
1 366
 
5.3%
사용끝지하층 355
 
5.1%
2 21
 
0.3%
3 3
 
< 0.1%
4 1
 
< 0.1%

usejisgstflr
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
<NA>
2877 
1
1536 
0
1126 
2
641 
3
320 
Other values (11)
448 

Length

Max length7
Median length1
Mean length2.3991077
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2877
41.4%
1 1536
22.1%
0 1126
 
16.2%
2 641
 
9.2%
3 320
 
4.6%
사용시작지상층 180
 
2.6%
4 125
 
1.8%
5 77
 
1.1%
6 26
 
0.4%
9 13
 
0.2%
Other values (6) 27
 
0.4%

Length

2024-04-17T10:46:56.468718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2877
41.4%
1 1536
22.1%
0 1126
 
16.2%
2 641
 
9.2%
3 320
 
4.6%
사용시작지상층 180
 
2.6%
4 125
 
1.8%
5 77
 
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 size54.4 KiB
<NA>
4232 
0
1909 
1
 
423
사용시작지하층
 
348
2
 
32
Other values (2)
 
4

Length

Max length7
Median length4
Mean length3.1279505
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> 4232
60.9%
0 1909
27.5%
1 423
 
6.1%
사용시작지하층 348
 
5.0%
2 32
 
0.5%
3 3
 
< 0.1%
22 1
 
< 0.1%

Length

2024-04-17T10:46:56.571314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:56.661722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4232
60.9%
0 1909
27.5%
1 423
 
6.1%
사용시작지하층 348
 
5.0%
2 32
 
0.5%
3 3
 
< 0.1%
22 1
 
< 0.1%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
<NA>
3512 
0
3409 
세탁기수
 
27

Length

Max length4
Median length4
Mean length2.5280656
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
50.5%
0 3409
49.1%
세탁기수 27
 
0.4%

Length

2024-04-17T10:46:56.765226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:56.848039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3512
50.5%
0 3409
49.1%
세탁기수 27
 
0.4%

yangsilcnt
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
0
4078 
<NA>
2843 
양실수
 
26
38
 
1

Length

Max length4
Median length1
Mean length2.2351756
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 4078
58.7%
<NA> 2843
40.9%
양실수 26
 
0.4%
38 1
 
< 0.1%

Length

2024-04-17T10:46:56.943395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:57.046551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4078
58.7%
na 2843
40.9%
양실수 26
 
0.4%
38 1
 
< 0.1%

wmeipcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
<NA>
4771 
0
2054 
1
 
88
여성종사자수
 
33
2
 
2

Length

Max length6
Median length4
Mean length3.0837651
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> 4771
68.7%
0 2054
29.6%
1 88
 
1.3%
여성종사자수 33
 
0.5%
2 2
 
< 0.1%

Length

2024-04-17T10:46:57.142089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:57.225549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4771
68.7%
0 2054
29.6%
1 88
 
1.3%
여성종사자수 33
 
0.5%
2 2
 
< 0.1%

yoksilcnt
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
0
4078 
<NA>
2843 
욕실수
 
26
2
 
1

Length

Max length4
Median length1
Mean length2.2350317
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 4078
58.7%
<NA> 2843
40.9%
욕실수 26
 
0.4%
2 1
 
< 0.1%

Length

2024-04-17T10:46:57.318630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:57.420721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4078
58.7%
na 2843
40.9%
욕실수 26
 
0.4%
2 1
 
< 0.1%

sntuptaenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
일반이용업
6819 
이용업 기타
 
104
일반미용업
 
23
<NA>
 
2

Length

Max length6
Median length5
Mean length5.0146805
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 6819
98.1%
이용업 기타 104
 
1.5%
일반미용업 23
 
0.3%
<NA> 2
 
< 0.1%

Length

2024-04-17T10:46:57.523909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:57.893795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 6819
96.7%
이용업 104
 
1.5%
기타 104
 
1.5%
일반미용업 23
 
0.3%
na 2
 
< 0.1%

chaircnt
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
2
2218 
3
1376 
4
731 
<NA>
678 
1
608 
Other values (12)
1337 

Length

Max length4
Median length1
Mean length1.3055556
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
2 2218
31.9%
3 1376
19.8%
4 731
 
10.5%
<NA> 678
 
9.8%
1 608
 
8.8%
0 420
 
6.0%
5 291
 
4.2%
6 196
 
2.8%
7 173
 
2.5%
8 122
 
1.8%
Other values (7) 135
 
1.9%

Length

2024-04-17T10:46:57.981572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 2218
31.9%
3 1376
19.8%
4 731
 
10.5%
na 678
 
9.8%
1 608
 
8.8%
0 420
 
6.0%
5 291
 
4.2%
6 196
 
2.8%
7 173
 
2.5%
8 122
 
1.8%
Other values (7) 135
 
1.9%

cndpermstymd
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
<NA>
6557 
조건부허가시작일자
 
386
20050520
 
1
20050414
 
1
20181212
 
1
Other values (2)
 
2

Length

Max length9
Median length4
Mean length4.2806563
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> 6557
94.4%
조건부허가시작일자 386
 
5.6%
20050520 1
 
< 0.1%
20050414 1
 
< 0.1%
20181212 1
 
< 0.1%
20190201 1
 
< 0.1%
20190812 1
 
< 0.1%

Length

2024-04-17T10:46:58.104942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:58.212113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6557
94.4%
조건부허가시작일자 386
 
5.6%
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 size54.4 KiB
<NA>
6558 
조건부허가신고사유
 
386
가설건축물
 
1
외국국적동포 국내거소신고증 체류기간
 
1
전통시장 사용기간제한 허가승인(2018.01.01.~2020.12.31.)
 
1

Length

Max length41
Median length4
Mean length4.2859816
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> 6558
94.4%
조건부허가신고사유 386
 
5.6%
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

2024-04-17T10:46:58.318268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:58.413543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6558
94.3%
조건부허가신고사유 386
 
5.6%
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 size54.4 KiB
<NA>
6557 
조건부허가종료일자
 
386
20060425
 
1
20050414
 
1
20210422
 
1
Other values (2)
 
2

Length

Max length9
Median length4
Mean length4.2806563
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> 6557
94.4%
조건부허가종료일자 386
 
5.6%
20060425 1
 
< 0.1%
20050414 1
 
< 0.1%
20210422 1
 
< 0.1%
20201231 1
 
< 0.1%
20281022 1
 
< 0.1%

Length

2024-04-17T10:46:58.519917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:58.617493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6557
94.4%
조건부허가종료일자 386
 
5.6%
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 size54.4 KiB
<NA>
3713 
0
3175 
침대수
 
27
1
 
18
2
 
7
Other values (3)
 
8

Length

Max length4
Median length4
Mean length2.6109672
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
53.4%
0 3175
45.7%
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

2024-04-17T10:46:58.724904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:58.832249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3713
53.4%
0 3175
45.7%
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 size54.4 KiB
0
4078 
<NA>
2844 
한실수
 
26

Length

Max length4
Median length1
Mean length2.2354634
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 4078
58.7%
<NA> 2844
40.9%
한실수 26
 
0.4%

Length

2024-04-17T10:46:58.937893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:59.022817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4078
58.7%
na 2844
40.9%
한실수 26
 
0.4%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
<NA>
3695 
0
3226 
회수건조수
 
27

Length

Max length5
Median length4
Mean length2.6109672
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
53.2%
0 3226
46.4%
회수건조수 27
 
0.4%

Length

2024-04-17T10:46:59.120003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:59.210010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3695
53.2%
0 3226
46.4%
회수건조수 27
 
0.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
Minimum2021-01-05 10:24:02
Maximum2021-01-05 10:24:03
2024-04-17T10:46:59.285477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T10:46:59.368433image/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>0002021-01-05 10:24:02
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>2021-01-05 10:24:02
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>0002021-01-05 10:24:03
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>2021-01-05 10:24:03
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>2021-01-05 10:24:03
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>2021-01-05 10:24:03
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>0002021-01-05 10:24:03
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>2021-01-05 10:24:03
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>0002021-01-05 10:24:03
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>0002021-01-05 10:24:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
6938694040600004060000-203-2020-0000405_19_01_PI2020-12-30 00:23:06.0이용업탐라이발관413190경기도 파주시 와동동 1426-110896경기도 파주시 와석순환로 511, 5층 (와동동)20201228<NA><NA><NA><NA>영업/정상영업178973.380048169469145.09914058520201228141156일반이용업<NA><NA>1230NN5<NA>5<NA>0000일반이용업2<NA><NA><NA>0002021-01-05 10:24:03
6939694150200005040000-203-2020-0000505_19_01_PI2020-12-30 00:23:06.0이용업더컷(The cut)791270경상북도 포항시 북구 양덕동 1724-1 1층37593경상북도 포항시 북구 장량로190번길 29, 1층 (양덕동)20201228<NA><NA><NA><NA>영업/정상영업416258.300015947289177.57845518420201228161005일반이용업<NA><NA>000NN1<NA>1<NA>0000일반이용업2<NA><NA><NA>0002021-01-05 10:24:03
6940694236700003670000-203-2020-0000505_19_01_PI2020-12-30 00:23:06.0이용업불가마사우나305301대전광역시 유성구 봉명동 538-134186대전광역시 유성구 계룡로113번길 76, 8층 (봉명동)20201228<NA><NA><NA><NA>영업/정상영업230896.922887317369.75955720201228141733일반이용업<NA><NA>000NN<NA><NA><NA><NA>0000일반이용업2<NA><NA><NA>0002021-01-05 10:24:03
6941694352400005240000-203-2020-0000305_19_01_PI2020-12-31 00:23:05.0이용업세영이용원755805경상북도 봉화군 봉화읍 내성리 195-5 세현목욕탕36238경상북도 봉화군 봉화읍 내성로3길 7, 세현목욕탕20201229폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업355046.921713833377690.03535602520201229112115일반이용업전화번호임대000NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층0000일반이용업1조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-01-05 10:24:03
6942694451600005160000-203-2020-0000405_19_01_PI2020-12-31 00:23:05.0이용업도평이발관763853경상북도 청송군 현동면 도평리 709-437456경상북도 청송군 현동면 청송로 265620201229<NA><NA><NA><NA>영업/정상영업381175.490581008311806.27926529420201229100008일반이용업<NA>임대001NN<NA><NA><NA><NA>0000일반이용업2<NA><NA><NA>0002021-01-05 10:24:03
6943694532300003230000-203-2020-0000805_19_01_PI2020-12-31 00:23:05.0이용업문정 이발관138824서울특별시 송파구 문정동 13-1 신성빌딩5797서울특별시 송파구 송이로32길 19, 신성빌딩 1층 101호 (문정동)20201229<NA><NA><NA><NA>영업/정상영업211228.419979407442900.48868209620201229145904이용업 기타<NA><NA>100NN<NA><NA><NA><NA>0000이용업 기타3<NA><NA><NA>0002021-01-05 10:24:03
6944694655400005540000-203-2020-0000205_19_01_PI2020-12-31 00:23:05.0이용업스파렉스이용원464896경기도 광주시 오포읍 양벌리 350-312793경기도 광주시 오포읍 마루들길 259-6, 4층20201229<NA><NA><NA><NA>영업/정상영업223042.196990478430713.39079915120201229135847일반이용업<NA><NA>000NN<NA><NA>4<NA>0000일반이용업2<NA><NA><NA>0002021-01-05 10:24:03
6945694747100004710000-203-2020-0000205_19_01_PI2021-01-01 00:23:05.0이용업해성사우나 구내이용원576807전라북도 김제시 요촌동 57854383전라북도 김제시 중앙로 93, 해성사우나 지하1층 (요촌동)20201230폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업189672.903175256076.1520820201230145005일반이용업063 547 0178건물소유구분명000NN사용끝지상층사용끝지하층사용시작지상층10000일반이용업2조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-01-05 10:24:03
6946694846700004670000-203-2020-0000605_19_01_PI2021-01-02 00:23:15.0이용업장미이용원573420전라북도 군산시 경장동 466-154084전라북도 군산시 번영로 20, 1층 (경장동)20201231폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업175142.438988274897.57140320201231132019일반이용업전화번호건물소유구분명000NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층0000일반이용업2조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-01-05 10:24:03
6947694939900003990000-203-2020-0000605_19_01_PI2021-01-02 00:23:15.0이용업가꾸는동안 퇴계원1호점<NA>경기도 남양주시 퇴계원읍 퇴계원리 221 강남아파트 상가나동 109호일부12123경기도 남양주시 퇴계원읍 퇴계원로50번길 10, 강남아파트 상가나동 109호일부20201231<NA><NA><NA><NA>영업/정상영업212609.205711087460898.22035550220201231151223일반이용업<NA><NA>000NN1<NA>1<NA>0000일반이용업2<NA><NA><NA>0002021-01-05 10:24:03