Overview

Dataset statistics

Number of variables51
Number of observations6257
Missing cells5613
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 MiB
Average record size in memory413.0 B

Variable types

Numeric5
Text9
Categorical35
DateTime2

Alerts

opnsvcid is highly imbalanced (93.8%)Imbalance
clgstdt is highly imbalanced (65.5%)Imbalance
clgenddt is highly imbalanced (65.5%)Imbalance
ropnymd is highly imbalanced (65.5%)Imbalance
dtlstatenm is highly imbalanced (59.0%)Imbalance
uptaenm is highly imbalanced (76.8%)Imbalance
bdngjisgflrcnt is highly imbalanced (52.9%)Imbalance
bdngunderflrcnt is highly imbalanced (56.0%)Imbalance
maneipcnt is highly imbalanced (72.3%)Imbalance
sjyn is highly imbalanced (65.5%)Imbalance
multusnupsoyn is highly imbalanced (99.2%)Imbalance
balhansilyn is highly imbalanced (99.1%)Imbalance
useunderendflr is highly imbalanced (54.7%)Imbalance
useunderstflr is highly imbalanced (50.2%)Imbalance
medkind is highly imbalanced (65.5%)Imbalance
wmeipcnt is highly imbalanced (70.7%)Imbalance
trdscp is highly imbalanced (65.5%)Imbalance
sntuptaenm is highly imbalanced (76.8%)Imbalance
chaircnt is highly imbalanced (68.7%)Imbalance
cndpermstymd is highly imbalanced (78.1%)Imbalance
cndpermntwhy is highly imbalanced (78.1%)Imbalance
cndpermendymd is highly imbalanced (78.1%)Imbalance
totscp is highly imbalanced (91.3%)Imbalance
sitepostno has 106 (1.7%) missing valuesMissing
rdnwhladdr has 2051 (32.8%) missing valuesMissing
dcbymd has 2767 (44.2%) missing valuesMissing
x has 276 (4.4%) missing valuesMissing
y has 276 (4.4%) missing valuesMissing
sitetel has 119 (1.9%) missing valuesMissing
apvpermymd is highly skewed (γ1 = -29.93471274)Skewed
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 04:00:00.484581
Analysis finished2024-04-16 04:00:02.381686
Duration1.9 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct6257
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3129.3144
Minimum1
Maximum6259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.1 KiB
2024-04-16T13:00:02.432775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile313.8
Q11565
median3129
Q34693
95-th percentile5946.2
Maximum6259
Range6258
Interquartile range (IQR)3128

Descriptive statistics

Standard deviation1806.8284
Coefficient of variation (CV)0.57738794
Kurtosis-1.1996709
Mean3129.3144
Median Absolute Deviation (MAD)1564
Skewness0.00054332973
Sum19580120
Variance3264628.8
MonotonicityNot monotonic
2024-04-16T13:00:02.539743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 1
 
< 0.1%
4154 1
 
< 0.1%
4176 1
 
< 0.1%
4175 1
 
< 0.1%
4174 1
 
< 0.1%
4173 1
 
< 0.1%
4172 1
 
< 0.1%
4171 1
 
< 0.1%
4170 1
 
< 0.1%
4169 1
 
< 0.1%
Other values (6247) 6247
99.8%
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 (%)
6259 1
< 0.1%
6258 1
< 0.1%
6257 1
< 0.1%
6256 1
< 0.1%
6255 1
< 0.1%
6254 1
< 0.1%
6253 1
< 0.1%
6252 1
< 0.1%
6251 1
< 0.1%
6250 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct176
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3521108.2
Minimum3000000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.1 KiB
2024-04-16T13:00:02.673296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3250000
Q13300000
median3330000
Q33390000
95-th percentile4882000
Maximum6520000
Range3520000
Interquartile range (IQR)90000

Descriptive statistics

Standard deviation536011.83
Coefficient of variation (CV)0.15222816
Kurtosis8.6289506
Mean3521108.2
Median Absolute Deviation (MAD)40000
Skewness2.9411983
Sum2.2031574 × 1010
Variance2.8730869 × 1011
MonotonicityNot monotonic
2024-04-16T13:00:02.816326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3300000 540
 
8.6%
3290000 489
 
7.8%
3340000 434
 
6.9%
3330000 432
 
6.9%
3320000 420
 
6.7%
3350000 376
 
6.0%
3310000 347
 
5.5%
3370000 340
 
5.4%
3390000 325
 
5.2%
3380000 257
 
4.1%
Other values (166) 2297
36.7%
ValueCountFrequency (%)
3000000 3
 
< 0.1%
3010000 6
0.1%
3020000 14
0.2%
3030000 13
0.2%
3040000 12
0.2%
3050000 9
0.1%
3060000 10
0.2%
3070000 10
0.2%
3080000 8
0.1%
3090000 6
0.1%
ValueCountFrequency (%)
6520000 2
 
< 0.1%
6510000 21
0.3%
5710000 33
0.5%
5700000 1
 
< 0.1%
5690000 9
 
0.1%
5680000 5
 
0.1%
5670000 18
0.3%
5600000 3
 
< 0.1%
5590000 13
 
0.2%
5580000 4
 
0.1%

mgtno
Text

Distinct5857
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
2024-04-16T13:00:03.026464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length22.021576
Min length22

Characters and Unicode

Total characters137789
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5635 ?
Unique (%)90.1%

Sample

1st row3250000-205-2000-00006
2nd row3250000-205-1987-00594
3rd row3250000-205-1987-00590
4th row3250000-205-1993-00618
5th row3250000-205-1994-00626
ValueCountFrequency (%)
3770000-205-2020-00001 4
 
0.1%
5530000-205-2020-00006 4
 
0.1%
3990000-205-2020-00004 3
 
< 0.1%
5560000-205-2019-00003 3
 
< 0.1%
5660000-205-2019-00007 3
 
< 0.1%
3190000-205-2019-00005 3
 
< 0.1%
3900000-205-2019-00002 3
 
< 0.1%
3020000-205-2019-00001 3
 
< 0.1%
3660000-205-2020-00004 3
 
< 0.1%
4800000-205-2019-00004 3
 
< 0.1%
Other values (5847) 6225
99.5%
2024-04-16T13:00:03.324574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 55699
40.4%
- 18636
 
13.5%
2 14371
 
10.4%
3 11655
 
8.5%
5 9092
 
6.6%
1 8327
 
6.0%
9 7999
 
5.8%
8 3679
 
2.7%
4 3047
 
2.2%
7 3010
 
2.2%
Other values (5) 2274
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 118973
86.3%
Dash Punctuation 18636
 
13.5%
Uppercase Letter 180
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 55699
46.8%
2 14371
 
12.1%
3 11655
 
9.8%
5 9092
 
7.6%
1 8327
 
7.0%
9 7999
 
6.7%
8 3679
 
3.1%
4 3047
 
2.6%
7 3010
 
2.5%
6 2094
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
P 45
25.0%
H 45
25.0%
M 45
25.0%
C 45
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 18636
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 137609
99.9%
Latin 180
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 55699
40.5%
- 18636
 
13.5%
2 14371
 
10.4%
3 11655
 
8.5%
5 9092
 
6.6%
1 8327
 
6.1%
9 7999
 
5.8%
8 3679
 
2.7%
4 3047
 
2.2%
7 3010
 
2.2%
Latin
ValueCountFrequency (%)
P 45
25.0%
H 45
25.0%
M 45
25.0%
C 45
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 137789
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 55699
40.4%
- 18636
 
13.5%
2 14371
 
10.4%
3 11655
 
8.5%
5 9092
 
6.6%
1 8327
 
6.0%
9 7999
 
5.8%
8 3679
 
2.7%
4 3047
 
2.2%
7 3010
 
2.2%
Other values (5) 2274
 
1.7%

opnsvcid
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
06_20_01_P
6212 
06_20_02_P
 
45

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row06_20_01_P
2nd row06_20_01_P
3rd row06_20_01_P
4th row06_20_01_P
5th row06_20_01_P

Common Values

ValueCountFrequency (%)
06_20_01_P 6212
99.3%
06_20_02_P 45
 
0.7%

Length

2024-04-16T13:00:03.437238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:03.509891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
06_20_01_p 6212
99.3%
06_20_02_p 45
 
0.7%

updategbn
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
I
5436 
U
821 

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 5436
86.9%
U 821
 
13.1%

Length

2024-04-16T13:00:03.587304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:03.663443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5436
86.9%
u 821
 
13.1%
Distinct731
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-02 02:40:00
2024-04-16T13:00:03.765794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T13:00:03.926656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
4484 
세탁업
1728 
의료기관세탁물처리업
 
45

Length

Max length10
Median length4
Mean length3.766981
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> 4484
71.7%
세탁업 1728
 
27.6%
의료기관세탁물처리업 45
 
0.7%

Length

2024-04-16T13:00:04.136356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:04.224799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4484
71.7%
세탁업 1728
 
27.6%
의료기관세탁물처리업 45
 
0.7%

bplcnm
Text

Distinct3672
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
2024-04-16T13:00:04.426996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length4.879495
Min length1

Characters and Unicode

Total characters30531
Distinct characters632
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2762 ?
Unique (%)44.1%

Sample

1st row국일세탁소
2nd row백설세탁소
3rd row평화세탁소
4th row월풀빨래방대청점
5th row대신세탁소
ValueCountFrequency (%)
세탁소 282
 
4.0%
세탁 68
 
1.0%
크리닝 56
 
0.8%
현대 56
 
0.8%
빨래방 50
 
0.7%
백성사 47
 
0.7%
백조 40
 
0.6%
백양 39
 
0.5%
월풀빨래방 36
 
0.5%
현대세탁소 36
 
0.5%
Other values (3570) 6386
90.0%
2024-04-16T13:00:04.765190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3012
 
9.9%
2946
 
9.6%
1652
 
5.4%
998
 
3.3%
848
 
2.8%
661
 
2.2%
618
 
2.0%
575
 
1.9%
561
 
1.8%
515
 
1.7%
Other values (622) 18145
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28897
94.6%
Space Separator 848
 
2.8%
Uppercase Letter 219
 
0.7%
Decimal Number 151
 
0.5%
Close Punctuation 135
 
0.4%
Open Punctuation 131
 
0.4%
Lowercase Letter 97
 
0.3%
Other Punctuation 44
 
0.1%
Dash Punctuation 4
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3012
 
10.4%
2946
 
10.2%
1652
 
5.7%
998
 
3.5%
661
 
2.3%
618
 
2.1%
575
 
2.0%
561
 
1.9%
515
 
1.8%
457
 
1.6%
Other values (554) 16902
58.5%
Uppercase Letter
ValueCountFrequency (%)
K 37
16.9%
S 27
12.3%
C 20
 
9.1%
L 14
 
6.4%
M 13
 
5.9%
A 13
 
5.9%
H 12
 
5.5%
O 12
 
5.5%
P 10
 
4.6%
G 10
 
4.6%
Other values (12) 51
23.3%
Lowercase Letter
ValueCountFrequency (%)
e 23
23.7%
a 14
14.4%
n 9
 
9.3%
h 9
 
9.3%
o 5
 
5.2%
l 5
 
5.2%
w 5
 
5.2%
s 5
 
5.2%
r 4
 
4.1%
i 3
 
3.1%
Other values (9) 15
15.5%
Decimal Number
ValueCountFrequency (%)
1 47
31.1%
2 45
29.8%
4 18
 
11.9%
3 12
 
7.9%
9 8
 
5.3%
5 7
 
4.6%
7 5
 
3.3%
8 4
 
2.6%
6 3
 
2.0%
0 2
 
1.3%
Other Punctuation
ValueCountFrequency (%)
& 15
34.1%
. 14
31.8%
, 6
 
13.6%
! 3
 
6.8%
· 1
 
2.3%
/ 1
 
2.3%
: 1
 
2.3%
' 1
 
2.3%
# 1
 
2.3%
1
 
2.3%
Math Symbol
ValueCountFrequency (%)
+ 3
75.0%
~ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
848
100.0%
Close Punctuation
ValueCountFrequency (%)
) 135
100.0%
Open Punctuation
ValueCountFrequency (%)
( 131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28897
94.6%
Common 1317
 
4.3%
Latin 317
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3012
 
10.4%
2946
 
10.2%
1652
 
5.7%
998
 
3.5%
661
 
2.3%
618
 
2.1%
575
 
2.0%
561
 
1.9%
515
 
1.8%
457
 
1.6%
Other values (554) 16902
58.5%
Latin
ValueCountFrequency (%)
K 37
 
11.7%
S 27
 
8.5%
e 23
 
7.3%
C 20
 
6.3%
a 14
 
4.4%
L 14
 
4.4%
M 13
 
4.1%
A 13
 
4.1%
H 12
 
3.8%
O 12
 
3.8%
Other values (32) 132
41.6%
Common
ValueCountFrequency (%)
848
64.4%
) 135
 
10.3%
( 131
 
9.9%
1 47
 
3.6%
2 45
 
3.4%
4 18
 
1.4%
& 15
 
1.1%
. 14
 
1.1%
3 12
 
0.9%
9 8
 
0.6%
Other values (16) 44
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28897
94.6%
ASCII 1631
 
5.3%
None 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3012
 
10.4%
2946
 
10.2%
1652
 
5.7%
998
 
3.5%
661
 
2.3%
618
 
2.1%
575
 
2.0%
561
 
1.9%
515
 
1.8%
457
 
1.6%
Other values (554) 16902
58.5%
ASCII
ValueCountFrequency (%)
848
52.0%
) 135
 
8.3%
( 131
 
8.0%
1 47
 
2.9%
2 45
 
2.8%
K 37
 
2.3%
S 27
 
1.7%
e 23
 
1.4%
C 20
 
1.2%
4 18
 
1.1%
Other values (55) 300
 
18.4%
None
ValueCountFrequency (%)
· 1
50.0%
1
50.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

sitepostno
Text

MISSING 

Distinct1684
Distinct (%)27.4%
Missing106
Missing (%)1.7%
Memory size49.0 KiB
2024-04-16T13:00:05.034615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters36906
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique801 ?
Unique (%)13.0%

Sample

1st row600814
2nd row600091
3rd row600074
4th row600803
5th row600803
ValueCountFrequency (%)
619903 36
 
0.6%
604851 33
 
0.5%
616800 28
 
0.5%
607837 28
 
0.5%
지번우편번호 27
 
0.4%
604813 27
 
0.4%
612824 27
 
0.4%
617818 25
 
0.4%
614822 25
 
0.4%
616829 24
 
0.4%
Other values (1674) 5871
95.4%
2024-04-16T13:00:05.405627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 6432
17.4%
8 6108
16.6%
0 5789
15.7%
1 5580
15.1%
2 2847
7.7%
4 2672
7.2%
3 2522
 
6.8%
7 1973
 
5.3%
9 1431
 
3.9%
5 1387
 
3.8%
Other values (6) 165
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36741
99.6%
Other Letter 162
 
0.4%
Space Separator 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 6432
17.5%
8 6108
16.6%
0 5789
15.8%
1 5580
15.2%
2 2847
7.7%
4 2672
7.3%
3 2522
 
6.9%
7 1973
 
5.4%
9 1431
 
3.9%
5 1387
 
3.8%
Other Letter
ValueCountFrequency (%)
54
33.3%
27
16.7%
27
16.7%
27
16.7%
27
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36744
99.6%
Hangul 162
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
6 6432
17.5%
8 6108
16.6%
0 5789
15.8%
1 5580
15.2%
2 2847
7.7%
4 2672
7.3%
3 2522
 
6.9%
7 1973
 
5.4%
9 1431
 
3.9%
5 1387
 
3.8%
Hangul
ValueCountFrequency (%)
54
33.3%
27
16.7%
27
16.7%
27
16.7%
27
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36744
99.6%
Hangul 162
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 6432
17.5%
8 6108
16.6%
0 5789
15.8%
1 5580
15.2%
2 2847
7.7%
4 2672
7.3%
3 2522
 
6.9%
7 1973
 
5.4%
9 1431
 
3.9%
5 1387
 
3.8%
Hangul
ValueCountFrequency (%)
54
33.3%
27
16.7%
27
16.7%
27
16.7%
27
16.7%
Distinct5647
Distinct (%)90.5%
Missing16
Missing (%)0.3%
Memory size49.0 KiB
2024-04-16T13:00:05.683918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length55
Mean length26.436949
Min length4

Characters and Unicode

Total characters164993
Distinct characters554
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5251 ?
Unique (%)84.1%

Sample

1st row부산광역시 중구 중앙동4가 86-3번지
2nd row부산광역시 중구 대청동1가 33-8번지
3rd row부산광역시 중구 부평동4가 28-2번지
4th row부산광역시 중구 보수동1가 119-1번지
5th row부산광역시 중구 보수동1가 41-8번지 7통2반
ValueCountFrequency (%)
부산광역시 4741
 
15.6%
t통b반 668
 
2.2%
동래구 540
 
1.8%
부산진구 489
 
1.6%
북구 460
 
1.5%
경기도 453
 
1.5%
사하구 435
 
1.4%
해운대구 432
 
1.4%
남구 377
 
1.2%
금정구 376
 
1.2%
Other values (7976) 21445
70.5%
2024-04-16T13:00:06.087384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29751
 
18.0%
1 7575
 
4.6%
7558
 
4.6%
6309
 
3.8%
6080
 
3.7%
6045
 
3.7%
5799
 
3.5%
5722
 
3.5%
5644
 
3.4%
5225
 
3.2%
Other values (544) 79285
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 95657
58.0%
Decimal Number 32293
 
19.6%
Space Separator 29751
 
18.0%
Dash Punctuation 5120
 
3.1%
Uppercase Letter 1655
 
1.0%
Other Punctuation 189
 
0.1%
Open Punctuation 134
 
0.1%
Close Punctuation 134
 
0.1%
Lowercase Letter 55
 
< 0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7558
 
7.9%
6309
 
6.6%
6080
 
6.4%
6045
 
6.3%
5799
 
6.1%
5722
 
6.0%
5644
 
5.9%
5225
 
5.5%
5021
 
5.2%
1383
 
1.4%
Other values (482) 40871
42.7%
Uppercase Letter
ValueCountFrequency (%)
B 732
44.2%
T 693
41.9%
A 82
 
5.0%
S 23
 
1.4%
P 22
 
1.3%
K 21
 
1.3%
I 15
 
0.9%
G 10
 
0.6%
C 10
 
0.6%
L 9
 
0.5%
Other values (13) 38
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
e 14
25.5%
s 9
16.4%
c 6
10.9%
i 4
 
7.3%
a 4
 
7.3%
l 3
 
5.5%
r 3
 
5.5%
t 2
 
3.6%
k 2
 
3.6%
p 2
 
3.6%
Other values (6) 6
10.9%
Decimal Number
ValueCountFrequency (%)
1 7575
23.5%
2 4247
13.2%
3 3554
11.0%
0 3016
 
9.3%
4 2933
 
9.1%
5 2675
 
8.3%
6 2353
 
7.3%
7 2127
 
6.6%
8 1985
 
6.1%
9 1828
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 118
62.4%
@ 26
 
13.8%
. 22
 
11.6%
/ 20
 
10.6%
& 1
 
0.5%
· 1
 
0.5%
' 1
 
0.5%
Space Separator
ValueCountFrequency (%)
29751
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 134
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 95657
58.0%
Common 67623
41.0%
Latin 1713
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7558
 
7.9%
6309
 
6.6%
6080
 
6.4%
6045
 
6.3%
5799
 
6.1%
5722
 
6.0%
5644
 
5.9%
5225
 
5.5%
5021
 
5.2%
1383
 
1.4%
Other values (482) 40871
42.7%
Latin
ValueCountFrequency (%)
B 732
42.7%
T 693
40.5%
A 82
 
4.8%
S 23
 
1.3%
P 22
 
1.3%
K 21
 
1.2%
I 15
 
0.9%
e 14
 
0.8%
G 10
 
0.6%
C 10
 
0.6%
Other values (30) 91
 
5.3%
Common
ValueCountFrequency (%)
29751
44.0%
1 7575
 
11.2%
- 5120
 
7.6%
2 4247
 
6.3%
3 3554
 
5.3%
0 3016
 
4.5%
4 2933
 
4.3%
5 2675
 
4.0%
6 2353
 
3.5%
7 2127
 
3.1%
Other values (12) 4272
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 95656
58.0%
ASCII 69332
42.0%
Number Forms 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29751
42.9%
1 7575
 
10.9%
- 5120
 
7.4%
2 4247
 
6.1%
3 3554
 
5.1%
0 3016
 
4.4%
4 2933
 
4.2%
5 2675
 
3.9%
6 2353
 
3.4%
7 2127
 
3.1%
Other values (50) 5981
 
8.6%
Hangul
ValueCountFrequency (%)
7558
 
7.9%
6309
 
6.6%
6080
 
6.4%
6045
 
6.3%
5799
 
6.1%
5722
 
6.0%
5644
 
5.9%
5225
 
5.5%
5021
 
5.2%
1383
 
1.4%
Other values (481) 40870
42.7%
Number Forms
ValueCountFrequency (%)
3
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

rdnpostno
Real number (ℝ)

Distinct2390
Distinct (%)38.2%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean42907.305
Minimum1045
Maximum63630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.1 KiB
2024-04-16T13:00:06.386284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1045
5-th percentile10030.4
Q146531.5
median48423
Q348947
95-th percentile49481.3
Maximum63630
Range62585
Interquartile range (IQR)2415.5

Descriptive statistics

Standard deviation13187.46
Coefficient of variation (CV)0.30734766
Kurtosis2.2562343
Mean42907.305
Median Absolute Deviation (MAD)648
Skewness-1.8836363
Sum2.6838519 × 108
Variance1.7390909 × 108
MonotonicityNot monotonic
2024-04-16T13:00:06.490499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48947 2124
33.9%
48052 12
 
0.2%
48055 10
 
0.2%
49316 9
 
0.1%
48093 9
 
0.1%
49441 9
 
0.1%
48057 9
 
0.1%
48051 8
 
0.1%
48231 8
 
0.1%
48113 8
 
0.1%
Other values (2380) 4049
64.7%
ValueCountFrequency (%)
1045 1
 
< 0.1%
1053 1
 
< 0.1%
1055 1
 
< 0.1%
1134 1
 
< 0.1%
1178 3
< 0.1%
1204 1
 
< 0.1%
1379 1
 
< 0.1%
1421 1
 
< 0.1%
1448 1
 
< 0.1%
1452 3
< 0.1%
ValueCountFrequency (%)
63630 1
 
< 0.1%
63559 1
 
< 0.1%
63349 2
< 0.1%
63274 1
 
< 0.1%
63265 1
 
< 0.1%
63248 1
 
< 0.1%
63238 4
0.1%
63172 1
 
< 0.1%
63112 2
< 0.1%
63102 1
 
< 0.1%

rdnwhladdr
Text

MISSING 

Distinct3748
Distinct (%)89.1%
Missing2051
Missing (%)32.8%
Memory size49.0 KiB
2024-04-16T13:00:06.771752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length59
Mean length32.234189
Min length5

Characters and Unicode

Total characters135577
Distinct characters588
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3472 ?
Unique (%)82.5%

Sample

1st row부산광역시 중구 충장대로13번길 14 (중앙동4가)
2nd row부산광역시 중구 복병산길6번길 2-1 (대청동1가)
3rd row부산광역시 중구 흑교로21번길 19-1 (부평동4가)
4th row부산광역시 중구 보동길 96 (보수동1가)
5th row부산광역시 중구 고가길 78-19 (보수동1가)
ValueCountFrequency (%)
부산광역시 2702
 
10.3%
1층 1160
 
4.4%
경기도 458
 
1.7%
해운대구 324
 
1.2%
서울특별시 305
 
1.2%
부산진구 301
 
1.1%
상가동 285
 
1.1%
남구 258
 
1.0%
북구 240
 
0.9%
동래구 237
 
0.9%
Other values (6153) 19928
76.1%
2024-04-16T13:00:07.193464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21993
 
16.2%
1 6354
 
4.7%
5642
 
4.2%
4430
 
3.3%
3947
 
2.9%
( 3937
 
2.9%
) 3937
 
2.9%
3733
 
2.8%
3721
 
2.7%
3413
 
2.5%
Other values (578) 74470
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79081
58.3%
Decimal Number 22244
 
16.4%
Space Separator 21993
 
16.2%
Open Punctuation 3937
 
2.9%
Close Punctuation 3937
 
2.9%
Other Punctuation 3227
 
2.4%
Dash Punctuation 791
 
0.6%
Uppercase Letter 302
 
0.2%
Lowercase Letter 51
 
< 0.1%
Math Symbol 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5642
 
7.1%
4430
 
5.6%
3947
 
5.0%
3733
 
4.7%
3721
 
4.7%
3413
 
4.3%
3245
 
4.1%
2995
 
3.8%
2444
 
3.1%
1868
 
2.4%
Other values (517) 43643
55.2%
Uppercase Letter
ValueCountFrequency (%)
B 75
24.8%
A 74
24.5%
S 23
 
7.6%
C 21
 
7.0%
K 19
 
6.3%
T 14
 
4.6%
I 14
 
4.6%
P 13
 
4.3%
R 7
 
2.3%
E 5
 
1.7%
Other values (13) 37
12.3%
Lowercase Letter
ValueCountFrequency (%)
e 16
31.4%
s 9
17.6%
c 4
 
7.8%
l 3
 
5.9%
i 3
 
5.9%
a 3
 
5.9%
r 3
 
5.9%
k 2
 
3.9%
t 2
 
3.9%
y 1
 
2.0%
Other values (5) 5
 
9.8%
Decimal Number
ValueCountFrequency (%)
1 6354
28.6%
2 3295
14.8%
0 2320
 
10.4%
3 2219
 
10.0%
4 1748
 
7.9%
5 1547
 
7.0%
6 1394
 
6.3%
7 1232
 
5.5%
8 1097
 
4.9%
9 1038
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 3177
98.5%
. 19
 
0.6%
@ 18
 
0.6%
/ 7
 
0.2%
· 4
 
0.1%
& 1
 
< 0.1%
' 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
21993
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3937
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3937
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 791
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79081
58.3%
Common 56140
41.4%
Latin 356
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5642
 
7.1%
4430
 
5.6%
3947
 
5.0%
3733
 
4.7%
3721
 
4.7%
3413
 
4.3%
3245
 
4.1%
2995
 
3.8%
2444
 
3.1%
1868
 
2.4%
Other values (517) 43643
55.2%
Latin
ValueCountFrequency (%)
B 75
21.1%
A 74
20.8%
S 23
 
6.5%
C 21
 
5.9%
K 19
 
5.3%
e 16
 
4.5%
T 14
 
3.9%
I 14
 
3.9%
P 13
 
3.7%
s 9
 
2.5%
Other values (29) 78
21.9%
Common
ValueCountFrequency (%)
21993
39.2%
1 6354
 
11.3%
( 3937
 
7.0%
) 3937
 
7.0%
2 3295
 
5.9%
, 3177
 
5.7%
0 2320
 
4.1%
3 2219
 
4.0%
4 1748
 
3.1%
5 1547
 
2.8%
Other values (12) 5613
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79081
58.3%
ASCII 56489
41.7%
None 4
 
< 0.1%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21993
38.9%
1 6354
 
11.2%
( 3937
 
7.0%
) 3937
 
7.0%
2 3295
 
5.8%
, 3177
 
5.6%
0 2320
 
4.1%
3 2219
 
3.9%
4 1748
 
3.1%
5 1547
 
2.7%
Other values (49) 5962
 
10.6%
Hangul
ValueCountFrequency (%)
5642
 
7.1%
4430
 
5.6%
3947
 
5.0%
3733
 
4.7%
3721
 
4.7%
3413
 
4.3%
3245
 
4.1%
2995
 
3.8%
2444
 
3.1%
1868
 
2.4%
Other values (517) 43643
55.2%
None
ValueCountFrequency (%)
· 4
100.0%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Real number (ℝ)

SKEWED 

Distinct3100
Distinct (%)49.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20020066
Minimum9870512
Maximum20201231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.1 KiB
2024-04-16T13:00:07.323464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9870512
5-th percentile19870513
Q119911201
median20000707
Q320171025
95-th percentile20200624
Maximum20201231
Range10330719
Interquartile range (IQR)259824

Descriptive statistics

Standard deviation247931.07
Coefficient of variation (CV)0.012384129
Kurtosis1192.5449
Mean20020066
Median Absolute Deviation (MAD)110181
Skewness-29.934713
Sum1.2526555 × 1011
Variance6.1469817 × 1010
MonotonicityNot monotonic
2024-04-16T13:00:07.437936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19870513 255
 
4.1%
19870515 75
 
1.2%
19870509 57
 
0.9%
19870512 47
 
0.8%
19870518 41
 
0.7%
19870521 40
 
0.6%
19870523 39
 
0.6%
19870519 34
 
0.5%
19870529 33
 
0.5%
19870707 29
 
0.5%
Other values (3090) 5607
89.6%
ValueCountFrequency (%)
9870512 1
< 0.1%
9870518 1
< 0.1%
10870513 1
< 0.1%
19670519 1
< 0.1%
19671110 1
< 0.1%
19700217 1
< 0.1%
19791123 1
< 0.1%
19800103 1
< 0.1%
19850519 1
< 0.1%
19870201 1
< 0.1%
ValueCountFrequency (%)
20201231 1
 
< 0.1%
20201229 4
0.1%
20201224 4
0.1%
20201223 2
 
< 0.1%
20201221 1
 
< 0.1%
20201218 8
0.1%
20201214 4
0.1%
20201211 4
0.1%
20201210 2
 
< 0.1%
20201209 4
0.1%

dcbymd
Text

MISSING 

Distinct1970
Distinct (%)56.4%
Missing2767
Missing (%)44.2%
Memory size49.0 KiB
2024-04-16T13:00:07.666594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.5461318
Min length4

Characters and Unicode

Total characters26336
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1478 ?
Unique (%)42.3%

Sample

1st row20170511
2nd row20040220
3rd row20040920
4th row20080814
5th row20041208
ValueCountFrequency (%)
폐업일자 396
 
11.3%
20030227 81
 
2.3%
20050121 73
 
2.1%
20030704 41
 
1.2%
20031114 31
 
0.9%
20031028 25
 
0.7%
20051117 24
 
0.7%
20030805 20
 
0.6%
20051130 14
 
0.4%
20030930 14
 
0.4%
Other values (1960) 2771
79.4%
2024-04-16T13:00:08.016629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8217
31.2%
2 5125
19.5%
1 4488
17.0%
9 1321
 
5.0%
3 1284
 
4.9%
7 1069
 
4.1%
6 857
 
3.3%
5 827
 
3.1%
4 810
 
3.1%
8 753
 
2.9%
Other values (5) 1585
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24751
94.0%
Other Letter 1584
 
6.0%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8217
33.2%
2 5125
20.7%
1 4488
18.1%
9 1321
 
5.3%
3 1284
 
5.2%
7 1069
 
4.3%
6 857
 
3.5%
5 827
 
3.3%
4 810
 
3.3%
8 753
 
3.0%
Other Letter
ValueCountFrequency (%)
396
25.0%
396
25.0%
396
25.0%
396
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24752
94.0%
Hangul 1584
 
6.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8217
33.2%
2 5125
20.7%
1 4488
18.1%
9 1321
 
5.3%
3 1284
 
5.2%
7 1069
 
4.3%
6 857
 
3.5%
5 827
 
3.3%
4 810
 
3.3%
8 753
 
3.0%
Hangul
ValueCountFrequency (%)
396
25.0%
396
25.0%
396
25.0%
396
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24752
94.0%
Hangul 1584
 
6.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8217
33.2%
2 5125
20.7%
1 4488
18.1%
9 1321
 
5.3%
3 1284
 
5.2%
7 1069
 
4.3%
6 857
 
3.5%
5 827
 
3.3%
4 810
 
3.3%
8 753
 
3.0%
Hangul
ValueCountFrequency (%)
396
25.0%
396
25.0%
396
25.0%
396
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
5854 
휴업시작일자
 
403

Length

Max length6
Median length4
Mean length4.1288157
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> 5854
93.6%
휴업시작일자 403
 
6.4%

Length

2024-04-16T13:00:08.138301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:08.225070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5854
93.6%
휴업시작일자 403
 
6.4%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
5854 
휴업종료일자
 
403

Length

Max length6
Median length4
Mean length4.1288157
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> 5854
93.6%
휴업종료일자 403
 
6.4%

Length

2024-04-16T13:00:08.313239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:08.399467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5854
93.6%
휴업종료일자 403
 
6.4%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
5854 
재개업일자
 
403

Length

Max length5
Median length4
Mean length4.0644079
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> 5854
93.6%
재개업일자 403
 
6.4%

Length

2024-04-16T13:00:08.480322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:08.556055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5854
93.6%
재개업일자 403
 
6.4%

trdstatenm
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
02
2886 
01
1598 
영업/정상
1548 
폐업
 
207
<NA>
 
11
Other values (3)
 
7

Length

Max length14
Median length2
Mean length2.7508391
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
02 2886
46.1%
01 1598
25.5%
영업/정상 1548
24.7%
폐업 207
 
3.3%
<NA> 11
 
0.2%
영업상태 4
 
0.1%
제외/삭제/전출 2
 
< 0.1%
취소/말소/만료/정지/중지 1
 
< 0.1%

Length

2024-04-16T13:00:08.637502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:08.727989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 2886
46.1%
01 1598
25.5%
영업/정상 1548
24.7%
폐업 207
 
3.3%
na 11
 
0.2%
영업상태 4
 
0.1%
제외/삭제/전출 2
 
< 0.1%
취소/말소/만료/정지/중지 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
영업
3119 
폐업
3094 
영업중
 
34
변경
 
7
삭제
 
2

Length

Max length4
Median length2
Mean length2.0057536
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 3119
49.8%
폐업 3094
49.4%
영업중 34
 
0.5%
변경 7
 
0.1%
삭제 2
 
< 0.1%
직권폐업 1
 
< 0.1%

Length

2024-04-16T13:00:08.838413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:08.931900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 3119
49.8%
폐업 3094
49.4%
영업중 34
 
0.5%
변경 7
 
0.1%
삭제 2
 
< 0.1%
직권폐업 1
 
< 0.1%

x
Text

MISSING 

Distinct5257
Distinct (%)87.9%
Missing276
Missing (%)4.4%
Memory size49.0 KiB
2024-04-16T13:00:09.115277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.952182
Min length7

Characters and Unicode

Total characters119334
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

Unique4774 ?
Unique (%)79.8%

Sample

1st row385844.46764500000
2nd row385286.93835400000
3rd row384464.22393800000
4th row384660.977766
5th row384581.409949
ValueCountFrequency (%)
좌표정보(x 22
 
0.4%
209394.231297346 7
 
0.1%
186802.970551385 5
 
0.1%
378474.793935 5
 
0.1%
191055.247973785 5
 
0.1%
395388.715069604 5
 
0.1%
393449.69378400000 4
 
0.1%
187713.396145 4
 
0.1%
381579.27262100000 4
 
0.1%
382137.104187552 4
 
0.1%
Other values (5247) 5916
98.9%
2024-04-16T13:00:09.431680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25997
21.8%
0 18884
15.8%
3 10988
9.2%
8 9233
 
7.7%
9 8052
 
6.7%
2 7359
 
6.2%
1 7197
 
6.0%
7 6585
 
5.5%
4 6516
 
5.5%
5 6299
 
5.3%
Other values (9) 12224
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 87254
73.1%
Space Separator 25997
 
21.8%
Other Punctuation 5929
 
5.0%
Other Letter 88
 
0.1%
Close Punctuation 22
 
< 0.1%
Uppercase Letter 22
 
< 0.1%
Open Punctuation 22
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18884
21.6%
3 10988
12.6%
8 9233
10.6%
9 8052
9.2%
2 7359
 
8.4%
1 7197
 
8.2%
7 6585
 
7.5%
4 6516
 
7.5%
5 6299
 
7.2%
6 6141
 
7.0%
Other Letter
ValueCountFrequency (%)
22
25.0%
22
25.0%
22
25.0%
22
25.0%
Space Separator
ValueCountFrequency (%)
25997
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5929
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 119224
99.9%
Hangul 88
 
0.1%
Latin 22
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
25997
21.8%
0 18884
15.8%
3 10988
9.2%
8 9233
 
7.7%
9 8052
 
6.8%
2 7359
 
6.2%
1 7197
 
6.0%
7 6585
 
5.5%
4 6516
 
5.5%
5 6299
 
5.3%
Other values (4) 12114
10.2%
Hangul
ValueCountFrequency (%)
22
25.0%
22
25.0%
22
25.0%
22
25.0%
Latin
ValueCountFrequency (%)
X 22
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119246
99.9%
Hangul 88
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25997
21.8%
0 18884
15.8%
3 10988
9.2%
8 9233
 
7.7%
9 8052
 
6.8%
2 7359
 
6.2%
1 7197
 
6.0%
7 6585
 
5.5%
4 6516
 
5.5%
5 6299
 
5.3%
Other values (5) 12136
10.2%
Hangul
ValueCountFrequency (%)
22
25.0%
22
25.0%
22
25.0%
22
25.0%

y
Text

MISSING 

Distinct5257
Distinct (%)87.9%
Missing276
Missing (%)4.4%
Memory size49.0 KiB
2024-04-16T13:00:09.620814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.952182
Min length7

Characters and Unicode

Total characters119334
Distinct characters21
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4774 ?
Unique (%)79.8%

Sample

1st row180840.18410800000
2nd row180439.91103500000
3rd row180221.47261700000
4th row180177.894242
5th row180434.791445
ValueCountFrequency (%)
좌표정보(y 22
 
0.4%
443951.236927017 7
 
0.1%
450005.881977638 5
 
0.1%
180075.396084 5
 
0.1%
466454.4498163 5
 
0.1%
186268.853282623 5
 
0.1%
180727.61997800000 4
 
0.1%
229036.029237 4
 
0.1%
190921.66421500000 4
 
0.1%
191686.955693638 4
 
0.1%
Other values (5247) 5916
98.9%
2024-04-16T13:00:09.911200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25991
21.8%
0 18210
15.3%
1 11138
9.3%
8 8802
 
7.4%
9 8123
 
6.8%
4 7319
 
6.1%
7 7084
 
5.9%
2 6792
 
5.7%
5 6657
 
5.6%
6 6566
 
5.5%
Other values (11) 12652
10.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 87244
73.1%
Space Separator 25991
 
21.8%
Other Punctuation 5928
 
5.0%
Other Letter 88
 
0.1%
Close Punctuation 23
 
< 0.1%
Uppercase Letter 22
 
< 0.1%
Open Punctuation 22
 
< 0.1%
Dash Punctuation 16
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18210
20.9%
1 11138
12.8%
8 8802
10.1%
9 8123
9.3%
4 7319
8.4%
7 7084
 
8.1%
2 6792
 
7.8%
5 6657
 
7.6%
6 6566
 
7.5%
3 6553
 
7.5%
Other Letter
ValueCountFrequency (%)
22
25.0%
22
25.0%
22
25.0%
22
25.0%
Close Punctuation
ValueCountFrequency (%)
) 22
95.7%
] 1
 
4.3%
Space Separator
ValueCountFrequency (%)
25991
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5928
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 119224
99.9%
Hangul 88
 
0.1%
Latin 22
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
25991
21.8%
0 18210
15.3%
1 11138
9.3%
8 8802
 
7.4%
9 8123
 
6.8%
4 7319
 
6.1%
7 7084
 
5.9%
2 6792
 
5.7%
5 6657
 
5.6%
6 6566
 
5.5%
Other values (6) 12542
10.5%
Hangul
ValueCountFrequency (%)
22
25.0%
22
25.0%
22
25.0%
22
25.0%
Latin
ValueCountFrequency (%)
Y 22
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119246
99.9%
Hangul 88
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25991
21.8%
0 18210
15.3%
1 11138
9.3%
8 8802
 
7.4%
9 8123
 
6.8%
4 7319
 
6.1%
7 7084
 
5.9%
2 6792
 
5.7%
5 6657
 
5.6%
6 6566
 
5.5%
Other values (7) 12564
10.5%
Hangul
ValueCountFrequency (%)
22
25.0%
22
25.0%
22
25.0%
22
25.0%

lastmodts
Real number (ℝ)

Distinct4410
Distinct (%)70.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.011723 × 1013
Minimum1.9990128 × 1013
Maximum2.0201231 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.1 KiB
2024-04-16T13:00:10.034307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990128 × 1013
5-th percentile1.9990528 × 1013
Q12.0050215 × 1013
median2.0130123 × 1013
Q32.0190221 × 1013
95-th percentile2.0200911 × 1013
Maximum2.0201231 × 1013
Range2.1110316 × 1011
Interquartile range (IQR)1.4000614 × 1011

Descriptive statistics

Standard deviation6.8900579 × 1010
Coefficient of variation (CV)0.0034249536
Kurtosis-1.2552171
Mean2.011723 × 1013
Median Absolute Deviation (MAD)6.0484046 × 1010
Skewness-0.33826135
Sum1.2587351 × 1017
Variance4.7472898 × 1021
MonotonicityNot monotonic
2024-04-16T13:00:10.140179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070320000000 86
 
1.4%
19990318000000 83
 
1.3%
20020509000000 68
 
1.1%
20030415000000 60
 
1.0%
20020415000000 53
 
0.8%
20020510000000 48
 
0.8%
20020412000000 47
 
0.8%
19990429000000 37
 
0.6%
20030805000000 33
 
0.5%
20031118000000 31
 
0.5%
Other values (4400) 5711
91.3%
ValueCountFrequency (%)
19990128000000 1
 
< 0.1%
19990209000000 3
 
< 0.1%
19990210000000 3
 
< 0.1%
19990218000000 7
0.1%
19990219000000 13
0.2%
19990222000000 1
 
< 0.1%
19990223000000 14
0.2%
19990224000000 2
 
< 0.1%
19990225000000 6
0.1%
19990309000000 6
0.1%
ValueCountFrequency (%)
20201231160923 1
 
< 0.1%
20201231160617 1
 
< 0.1%
20201231112753 2
< 0.1%
20201230150502 1
 
< 0.1%
20201230123145 1
 
< 0.1%
20201229155205 1
 
< 0.1%
20201229145030 1
 
< 0.1%
20201229140444 1
 
< 0.1%
20201229114752 3
< 0.1%
20201229110959 1
 
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
일반세탁업
5702 
빨래방업
 
228
운동화전문세탁업
 
156
세탁업 기타
 
125
<NA>
 
35

Length

Max length8
Median length5
Mean length5.0527409
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 5702
91.1%
빨래방업 228
 
3.6%
운동화전문세탁업 156
 
2.5%
세탁업 기타 125
 
2.0%
<NA> 35
 
0.6%
업태구분명 11
 
0.2%

Length

2024-04-16T13:00:10.249209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:10.350198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 5702
89.3%
빨래방업 228
 
3.6%
운동화전문세탁업 156
 
2.4%
세탁업 125
 
2.0%
기타 125
 
2.0%
na 35
 
0.5%
업태구분명 11
 
0.2%

sitetel
Text

MISSING 

Distinct96
Distinct (%)1.6%
Missing119
Missing (%)1.9%
Memory size49.0 KiB
2024-04-16T13:00:10.485402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.932388
Min length4

Characters and Unicode

Total characters73241
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

Unique81 ?
Unique (%)1.3%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234
ValueCountFrequency (%)
051-123-1234 5983
95.1%
전화번호 44
 
0.7%
051 19
 
0.3%
02 19
 
0.3%
031 13
 
0.2%
053 6
 
0.1%
042 6
 
0.1%
043 6
 
0.1%
063 5
 
0.1%
062 5
 
0.1%
Other values (151) 188
 
3.0%
2024-04-16T13:00:10.744894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18051
24.6%
2 12108
16.5%
3 12071
16.5%
- 11974
16.3%
0 6169
 
8.4%
5 6099
 
8.3%
4 6060
 
8.3%
169
 
0.2%
8 118
 
0.2%
6 100
 
0.1%
Other values (6) 322
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60922
83.2%
Dash Punctuation 11974
 
16.3%
Other Letter 176
 
0.2%
Space Separator 169
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18051
29.6%
2 12108
19.9%
3 12071
19.8%
0 6169
 
10.1%
5 6099
 
10.0%
4 6060
 
9.9%
8 118
 
0.2%
6 100
 
0.2%
9 74
 
0.1%
7 72
 
0.1%
Other Letter
ValueCountFrequency (%)
44
25.0%
44
25.0%
44
25.0%
44
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 11974
100.0%
Space Separator
ValueCountFrequency (%)
169
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 73065
99.8%
Hangul 176
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18051
24.7%
2 12108
16.6%
3 12071
16.5%
- 11974
16.4%
0 6169
 
8.4%
5 6099
 
8.3%
4 6060
 
8.3%
169
 
0.2%
8 118
 
0.2%
6 100
 
0.1%
Other values (2) 146
 
0.2%
Hangul
ValueCountFrequency (%)
44
25.0%
44
25.0%
44
25.0%
44
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73065
99.8%
Hangul 176
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18051
24.7%
2 12108
16.6%
3 12071
16.5%
- 11974
16.4%
0 6169
 
8.4%
5 6099
 
8.3%
4 6060
 
8.3%
169
 
0.2%
8 118
 
0.2%
6 100
 
0.1%
Other values (2) 146
 
0.2%
Hangul
ValueCountFrequency (%)
44
25.0%
44
25.0%
44
25.0%
44
25.0%

bdngownsenm
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
4578 
임대
1147 
건물소유구분명
 
312
자가
 
220

Length

Max length7
Median length4
Mean length3.7126418
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4578
73.2%
임대 1147
 
18.3%
건물소유구분명 312
 
5.0%
자가 220
 
3.5%

Length

2024-04-16T13:00:10.846192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:10.926150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4578
73.2%
임대 1147
 
18.3%
건물소유구분명 312
 
5.0%
자가 220
 
3.5%

bdngjisgflrcnt
Categorical

IMBALANCE 

Distinct41
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
0
2593 
<NA>
1258 
2
868 
3
483 
1
445 
Other values (36)
610 

Length

Max length6
Median length1
Mean length1.6370465
Min length1

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row2
2nd row5
3rd row2
4th row4
5th row4

Common Values

ValueCountFrequency (%)
0 2593
41.4%
<NA> 1258
20.1%
2 868
 
13.9%
3 483
 
7.7%
1 445
 
7.1%
4 333
 
5.3%
5 117
 
1.9%
건물지상층수 25
 
0.4%
6 23
 
0.4%
7 11
 
0.2%
Other values (31) 101
 
1.6%

Length

2024-04-16T13:00:11.015004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2593
41.4%
na 1258
20.1%
2 868
 
13.9%
3 483
 
7.7%
1 445
 
7.1%
4 333
 
5.3%
5 117
 
1.9%
건물지상층수 25
 
0.4%
6 23
 
0.4%
7 11
 
0.2%
Other values (31) 101
 
1.6%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
0
3628 
<NA>
1929 
1
570 
2
 
41
3
 
27
Other values (5)
 
62

Length

Max length6
Median length1
Mean length1.9450216
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3628
58.0%
<NA> 1929
30.8%
1 570
 
9.1%
2 41
 
0.7%
3 27
 
0.4%
건물지하층수 25
 
0.4%
4 16
 
0.3%
5 13
 
0.2%
6 7
 
0.1%
10 1
 
< 0.1%

Length

2024-04-16T13:00:11.105417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:11.197108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3628
58.0%
na 1929
30.8%
1 570
 
9.1%
2 41
 
0.7%
3 27
 
0.4%
건물지하층수 25
 
0.4%
4 16
 
0.3%
5 13
 
0.2%
6 7
 
0.1%
10 1
 
< 0.1%

maneipcnt
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
4650 
0
1388 
1
 
149
남성종사자수
 
35
2
 
20
Other values (8)
 
15

Length

Max length6
Median length4
Mean length3.2579511
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4650
74.3%
0 1388
 
22.2%
1 149
 
2.4%
남성종사자수 35
 
0.6%
2 20
 
0.3%
7 5
 
0.1%
4 3
 
< 0.1%
5 2
 
< 0.1%
20 1
 
< 0.1%
9 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

Length

2024-04-16T13:00:11.299434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4650
74.3%
0 1388
 
22.2%
1 149
 
2.4%
남성종사자수 35
 
0.6%
2 20
 
0.3%
7 5
 
0.1%
4 3
 
< 0.1%
5 2
 
< 0.1%
20 1
 
< 0.1%
9 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

sjyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
5854 
 
403

Length

Max length4
Median length4
Mean length3.8067764
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> 5854
93.6%
403
 
6.4%

Length

2024-04-16T13:00:11.404770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:11.486359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5854
93.6%
403
 
6.4%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
N
6249 
<NA>
 
4
 
3
Y
 
1

Length

Max length4
Median length1
Mean length1.0019179
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
N 6249
99.9%
<NA> 4
 
0.1%
3
 
< 0.1%
Y 1
 
< 0.1%

Length

2024-04-16T13:00:11.569954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:11.655208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 6249
99.9%
na 4
 
0.1%
3
 
< 0.1%
y 1
 
< 0.1%

balhansilyn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
N
6250 
<NA>
 
4
 
3

Length

Max length4
Median length1
Mean length1.0019179
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 6250
99.9%
<NA> 4
 
0.1%
3
 
< 0.1%

Length

2024-04-16T13:00:11.742815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:11.821065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 6250
99.9%
na 4
 
0.1%
3
 
< 0.1%

usejisgendflr
Categorical

Distinct13
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
2914 
1
1967 
0
803 
2
296 
사용끝지상층
 
216
Other values (8)
 
61

Length

Max length6
Median length4
Mean length2.5702413
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2914
46.6%
1 1967
31.4%
0 803
 
12.8%
2 296
 
4.7%
사용끝지상층 216
 
3.5%
3 44
 
0.7%
4 8
 
0.1%
5 2
 
< 0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
Other values (3) 3
 
< 0.1%

Length

2024-04-16T13:00:11.903955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2914
46.6%
1 1967
31.4%
0 803
 
12.8%
2 296
 
4.7%
사용끝지상층 216
 
3.5%
3 44
 
0.7%
4 8
 
0.1%
5 2
 
< 0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
Other values (3) 3
 
< 0.1%

useunderendflr
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
4164 
0
1601 
사용끝지하층
 
329
1
 
144
2
 
15
Other values (2)
 
4

Length

Max length6
Median length4
Mean length3.2593895
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> 4164
66.5%
0 1601
 
25.6%
사용끝지하층 329
 
5.3%
1 144
 
2.3%
2 15
 
0.2%
3 3
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-16T13:00:11.992213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:12.079189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4164
66.5%
0 1601
 
25.6%
사용끝지하층 329
 
5.3%
1 144
 
2.3%
2 15
 
0.2%
3 3
 
< 0.1%
5 1
 
< 0.1%

usejisgstflr
Categorical

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
2187 
1
2036 
0
1467 
2
294 
사용시작지상층
 
193
Other values (9)
 
80

Length

Max length7
Median length1
Mean length2.2341378
Min length1

Unique

Unique4 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2187
35.0%
1 2036
32.5%
0 1467
23.4%
2 294
 
4.7%
사용시작지상층 193
 
3.1%
3 52
 
0.8%
4 13
 
0.2%
5 7
 
0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
Other values (4) 4
 
0.1%

Length

2024-04-16T13:00:12.179384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2187
35.0%
1 2036
32.5%
0 1467
23.4%
2 294
 
4.7%
사용시작지상층 193
 
3.1%
3 52
 
0.8%
4 13
 
0.2%
5 7
 
0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
Other values (4) 4
 
0.1%

useunderstflr
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
3222 
0
2540 
사용시작지하층
329 
1
 
149
2
 
12
Other values (2)
 
5

Length

Max length7
Median length4
Mean length2.8603164
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> 3222
51.5%
0 2540
40.6%
사용시작지하층 329
 
5.3%
1 149
 
2.4%
2 12
 
0.2%
3 4
 
0.1%
5 1
 
< 0.1%

Length

2024-04-16T13:00:12.277666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:12.364966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3222
51.5%
0 2540
40.6%
사용시작지하층 329
 
5.3%
1 149
 
2.4%
2 12
 
0.2%
3 4
 
0.1%
5 1
 
< 0.1%

washmccnt
Categorical

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
3055 
1
1043 
2
774 
0
739 
3
378 
Other values (11)
 
268

Length

Max length4
Median length1
Mean length2.4780246
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3055
48.8%
1 1043
 
16.7%
2 774
 
12.4%
0 739
 
11.8%
3 378
 
6.0%
4 166
 
2.7%
5 39
 
0.6%
세탁기수 25
 
0.4%
6 17
 
0.3%
7 6
 
0.1%
Other values (6) 15
 
0.2%

Length

2024-04-16T13:00:12.462661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3055
48.8%
1 1043
 
16.7%
2 774
 
12.4%
0 739
 
11.8%
3 378
 
6.0%
4 166
 
2.7%
5 39
 
0.6%
세탁기수 25
 
0.4%
6 17
 
0.3%
7 6
 
0.1%
Other values (6) 15
 
0.2%

medkind
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
5854 
수리대상 의료기기의 유형
 
403

Length

Max length13
Median length4
Mean length4.5796708
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> 5854
93.6%
수리대상 의료기기의 유형 403
 
6.4%

Length

2024-04-16T13:00:12.557013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:12.630707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5854
82.9%
수리대상 403
 
5.7%
의료기기의 403
 
5.7%
유형 403
 
5.7%

yangsilcnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
0
4039 
<NA>
2193 
양실수
 
25

Length

Max length4
Median length1
Mean length2.0594534
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 (%)
0 4039
64.6%
<NA> 2193
35.0%
양실수 25
 
0.4%

Length

2024-04-16T13:00:12.713904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:12.794102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4039
64.6%
na 2193
35.0%
양실수 25
 
0.4%

wmeipcnt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
4658 
0
1453 
1
 
86
여성종사자수
 
37
2
 
10
Other values (5)
 
13

Length

Max length6
Median length4
Mean length3.2630654
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4658
74.4%
0 1453
 
23.2%
1 86
 
1.4%
여성종사자수 37
 
0.6%
2 10
 
0.2%
4 7
 
0.1%
8 2
 
< 0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
32 1
 
< 0.1%

Length

2024-04-16T13:00:13.097819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:13.182656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4658
74.4%
0 1453
 
23.2%
1 86
 
1.4%
여성종사자수 37
 
0.6%
2 10
 
0.2%
4 7
 
0.1%
8 2
 
< 0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
32 1
 
< 0.1%

trdscp
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
5854 
영업규모
 
403

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5854
93.6%
영업규모 403
 
6.4%

Length

2024-04-16T13:00:13.282385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:13.355589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5854
93.6%
영업규모 403
 
6.4%

yoksilcnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
0
4039 
<NA>
2193 
욕실수
 
25

Length

Max length4
Median length1
Mean length2.0594534
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 (%)
0 4039
64.6%
<NA> 2193
35.0%
욕실수 25
 
0.4%

Length

2024-04-16T13:00:13.449090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:13.528483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4039
64.6%
na 2193
35.0%
욕실수 25
 
0.4%

sntuptaenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
일반세탁업
5702 
빨래방업
 
228
운동화전문세탁업
 
156
세탁업 기타
 
125
<NA>
 
35

Length

Max length8
Median length5
Mean length5.0527409
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 5702
91.1%
빨래방업 228
 
3.6%
운동화전문세탁업 156
 
2.5%
세탁업 기타 125
 
2.0%
<NA> 35
 
0.6%
위생업태명 11
 
0.2%

Length

2024-04-16T13:00:13.617704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:13.713707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 5702
89.3%
빨래방업 228
 
3.6%
운동화전문세탁업 156
 
2.4%
세탁업 125
 
2.0%
기타 125
 
2.0%
na 35
 
0.5%
위생업태명 11
 
0.2%

chaircnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
0
4035 
<NA>
2185 
의자수
 
25
3
 
4
2
 
2
Other values (4)
 
6

Length

Max length4
Median length1
Mean length2.0556177
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4035
64.5%
<NA> 2185
34.9%
의자수 25
 
0.4%
3 4
 
0.1%
2 2
 
< 0.1%
4 2
 
< 0.1%
6 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-16T13:00:13.832814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:13.948176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4035
64.5%
na 2185
34.9%
의자수 25
 
0.4%
3 4
 
0.1%
2 2
 
< 0.1%
4 2
 
< 0.1%
6 2
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

cndpermstymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
5853 
조건부허가시작일자
 
403
20201224
 
1

Length

Max length9
Median length4
Mean length4.3226786
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5853
93.5%
조건부허가시작일자 403
 
6.4%
20201224 1
 
< 0.1%

Length

2024-04-16T13:00:14.069536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:14.147817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5853
93.5%
조건부허가시작일자 403
 
6.4%
20201224 1
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
5853 
조건부허가신고사유
 
403
국유재산 유상 사용허가에 따른 조건부 영업
 
1

Length

Max length23
Median length4
Mean length4.3250759
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5853
93.5%
조건부허가신고사유 403
 
6.4%
국유재산 유상 사용허가에 따른 조건부 영업 1
 
< 0.1%

Length

2024-04-16T13:00:14.232784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:14.317455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5853
93.5%
조건부허가신고사유 403
 
6.4%
국유재산 1
 
< 0.1%
유상 1
 
< 0.1%
사용허가에 1
 
< 0.1%
따른 1
 
< 0.1%
조건부 1
 
< 0.1%
영업 1
 
< 0.1%

cndpermendymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
5853 
조건부허가종료일자
 
403
20220430
 
1

Length

Max length9
Median length4
Mean length4.3226786
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5853
93.5%
조건부허가종료일자 403
 
6.4%
20220430 1
 
< 0.1%

Length

2024-04-16T13:00:14.401002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:14.479603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5853
93.5%
조건부허가종료일자 403
 
6.4%
20220430 1
 
< 0.1%

totscp
Categorical

IMBALANCE 

Distinct32
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
5820 
총규모
 
392
1233
 
3
2831
 
3
10560
 
3
Other values (27)
 
36

Length

Max length7
Median length4
Mean length3.9456609
Min length3

Unique

Unique21 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5820
93.0%
총규모 392
 
6.3%
1233 3
 
< 0.1%
2831 3
 
< 0.1%
10560 3
 
< 0.1%
417.92 3
 
< 0.1%
541.8 3
 
< 0.1%
4925.07 3
 
< 0.1%
2123 2
 
< 0.1%
988 2
 
< 0.1%
Other values (22) 23
 
0.4%

Length

2024-04-16T13:00:14.573755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5820
93.0%
총규모 392
 
6.3%
1233 3
 
< 0.1%
2831 3
 
< 0.1%
10560 3
 
< 0.1%
417.92 3
 
< 0.1%
541.8 3
 
< 0.1%
4925.07 3
 
< 0.1%
988 2
 
< 0.1%
1024075 2
 
< 0.1%
Other values (22) 23
 
0.4%

abedcnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
3349 
0
2883 
침대수
 
25

Length

Max length4
Median length4
Mean length2.6137126
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> 3349
53.5%
0 2883
46.1%
침대수 25
 
0.4%

Length

2024-04-16T13:00:14.679859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:14.764503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3349
53.5%
0 2883
46.1%
침대수 25
 
0.4%

hanshilcnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
0
4039 
<NA>
2193 
한실수
 
25

Length

Max length4
Median length1
Mean length2.0594534
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 (%)
0 4039
64.6%
<NA> 2193
35.0%
한실수 25
 
0.4%

Length

2024-04-16T13:00:14.855973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T13:00:14.960293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4039
64.6%
na 2193
35.0%
한실수 25
 
0.4%

rcvdryncnt
Categorical

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
<NA>
3023 
1
1520 
0
1222 
2
 
249
3
 
108
Other values (9)
 
135

Length

Max length5
Median length1
Mean length2.466038
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3023
48.3%
1 1520
24.3%
0 1222
19.5%
2 249
 
4.0%
3 108
 
1.7%
4 54
 
0.9%
5 38
 
0.6%
회수건조수 25
 
0.4%
7 6
 
0.1%
8 5
 
0.1%
Other values (4) 7
 
0.1%

Length

2024-04-16T13:00:15.074822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3023
48.3%
1 1520
24.3%
0 1222
19.5%
2 249
 
4.0%
3 108
 
1.7%
4 54
 
0.9%
5 38
 
0.6%
회수건조수 25
 
0.4%
7 6
 
0.1%
8 5
 
0.1%
Other values (4) 7
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.0 KiB
Minimum2021-01-04 20:51:43
Maximum2021-01-04 20:51:44
2024-04-16T13:00:15.162779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T13:00:15.236760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntsjynmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntmedkindyangsilcntwmeipcnttrdscpyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdtotscpabedcnthanshilcntrcvdryncntlast_load_dttm
0332500003250000-205-2000-0000606_20_01_PI2018-08-31 23:59:59.0<NA>국일세탁소600814부산광역시 중구 중앙동4가 86-3번지48935부산광역시 중구 충장대로13번길 14 (중앙동4가)20000822<NA><NA><NA><NA>01영업385844.46764500000180840.1841080000020051205000000일반세탁업051-123-1234임대2<NA><NA><NA>NN1<NA>1<NA><NA><NA><NA><NA><NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 20:51:43
1432500003250000-205-1987-0059406_20_01_PI2018-08-31 23:59:59.0<NA>백설세탁소600091부산광역시 중구 대청동1가 33-8번지48932부산광역시 중구 복병산길6번길 2-1 (대청동1가)19870513<NA><NA><NA><NA>01영업385286.93835400000180439.9110350000020051115000000일반세탁업051-123-1234임대5<NA><NA><NA>NN2<NA>1<NA><NA><NA><NA><NA><NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 20:51:43
2532500003250000-205-1987-0059006_20_01_PI2018-08-31 23:59:59.0<NA>평화세탁소600074부산광역시 중구 부평동4가 28-2번지48974부산광역시 중구 흑교로21번길 19-1 (부평동4가)1987061220170511<NA><NA><NA>02폐업384464.22393800000180221.4726170000020170511094257일반세탁업051-123-1234임대2<NA><NA><NA>NN1<NA>1<NA><NA><NA><NA><NA><NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 20:51:43
3632500003250000-205-1993-0061806_20_01_PI2018-08-31 23:59:59.0<NA>월풀빨래방대청점600803부산광역시 중구 보수동1가 119-1번지48947<NA>1993080720040220<NA><NA><NA>02폐업384660.977766180177.89424220030826000000일반세탁업051-123-1234임대41<NA><NA>NN2<NA>2<NA><NA><NA><NA><NA><NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 20:51:43
4732500003250000-205-1994-0062606_20_01_PI2018-08-31 23:59:59.0<NA>대신세탁소600803부산광역시 중구 보수동1가 41-8번지 7통2반48947<NA>1994053120040920<NA><NA><NA>02폐업384581.409949180434.79144520030503000000일반세탁업051-123-1234임대4<NA><NA><NA>NN1<NA>1<NA><NA><NA><NA><NA><NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 20:51:43
5832500003250000-205-1996-0063906_20_01_PI2018-08-31 23:59:59.0<NA>아리랑 세탁소600811부산광역시 중구 영주동 695-3번지48947<NA>1996041520080814<NA><NA><NA>02폐업<NA><NA>20060427000000일반세탁업051-123-1234<NA><NA><NA><NA><NA>NN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 20:51:43
6932500003250000-205-1998-0000106_20_01_PI2018-08-31 23:59:59.0<NA>유성세탁소600802부산광역시 중구 보수동1가 33-278번지48959부산광역시 중구 보동길 96 (보수동1가)19980917<NA><NA><NA><NA>01영업384654.01100600000180952.7944690000020051205000000일반세탁업051-123-1234임대41<NA><NA>NN2<NA>2<NA><NA><NA><NA><NA><NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 20:51:43
71032500003250000-205-1988-0059806_20_01_PI2018-08-31 23:59:59.0<NA>청미사600803부산광역시 중구 보수동1가 59-384번지48960부산광역시 중구 고가길 78-19 (보수동1가)19881119<NA><NA><NA><NA>01영업384856.78227100000180697.6119430000020140120170208일반세탁업051-123-1234임대2<NA><NA><NA>NN1<NA>1<NA><NA><NA><NA><NA><NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 20:51:43
81132500003250000-205-1999-0000106_20_01_PI2018-08-31 23:59:59.0<NA>정일세탁 할인점600110부산광역시 중구 영주동 466-5번지48947<NA>1999020120041208<NA><NA><NA>02폐업385230.605157181026.92149820030503000000일반세탁업051-123-1234임대2<NA><NA><NA>NN1<NA>1<NA><NA><NA><NA><NA><NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 20:51:43
91232500003250000-205-1987-0058106_20_01_PI2018-08-31 23:59:59.0<NA>미성사600803부산광역시 중구 보수동1가 146-70번지48960부산광역시 중구 고가길 59 (보수동1가)1987051220150312<NA><NA><NA>02폐업384833.26910000000180583.7401600000020131227145304일반세탁업051-123-1234임대2<NA><NA><NA>NN2<NA>1<NA><NA><NA><NA><NA><NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 20:51:43
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntsjynmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntmedkindyangsilcntwmeipcnttrdscpyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdtotscpabedcnthanshilcntrcvdryncntlast_load_dttm
6247625046800004680000-205-2020-0000406_20_01_PI2020-12-25 00:23:06.0세탁업미스터리 명품세탁570962전라북도 익산시 마동 153-34 Mr.Lee명품세탁 201호54626전라북도 익산시 선화로 326-1, Mr.Lee명품세탁 2층 201호 (마동)20201223<NA><NA><NA><NA>영업/정상영업196852.258899271702.20482720201223094707일반세탁업063 857 0058임대400<NA>NN<NA><NA>2<NA>2<NA>00<NA>0일반세탁업0<NA><NA><NA><NA>0022021-01-04 20:51:44
6248625139400003960100-205-2020-0000606_20_01_PI2020-12-26 00:23:21.0세탁업원시티명품세탁410835경기도 고양시 일산동구 장항동 1762 킨텍스원시티 3블럭10394경기도 고양시 일산동구 월드고양로 21, 상가동-3, 1층 333호 (장항동, 킨텍스원시티 3블럭)20201224폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업177834.03921466462149.23475909820201224161640일반세탁업전화번호건물소유구분명000NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층2수리대상 의료기기의 유형00영업규모0일반세탁업0조건부허가시작일자조건부허가신고사유조건부허가종료일자총규모0022021-01-04 20:51:44
6249625236700003670000-205-2020-0000606_20_01_PI2020-12-26 00:23:21.0세탁업삼군대학군장수선305153대전광역시 유성구 추목동 268 간부회관 지상1층34059대전광역시 유성구 자운로 222, 간부회관 지상1층 (추목동)20201224<NA><NA><NA><NA>영업/정상영업231418.187176323934.74250620201224165641일반세탁업042 878 5580<NA>000<NA>NN<NA><NA><NA><NA>2<NA>00<NA>0일반세탁업020201224국유재산 유상 사용허가에 따른 조건부 영업20220430<NA>0012021-01-04 20:51:44
6250625365100006510000-205-2020-0001106_20_01_PI2020-12-26 00:23:21.0세탁업마마운동화이불빨래방일도점690834제주특별자치도 제주시 일도이동 994-963265제주특별자치도 제주시 신산로 3, 1층 (일도이동)20201224<NA><NA><NA><NA>영업/정상영업156450.6538391916.4632750520201224170809운동화전문세탁업<NA><NA>000<NA>NN<NA><NA><NA><NA>3<NA>00<NA>0운동화전문세탁업0<NA><NA><NA><NA>0022021-01-04 20:51:44
6251625432300003230000-205-2020-0001106_20_01_PI2020-12-26 00:23:21.0세탁업거여 파워 명품세탁138110서울특별시 송파구 거여동 295 거여6단지아파트5789서울특별시 송파구 양산로2길 38, 상가 101-2호 (거여동, 거여6단지아파트)20201224<NA><NA><NA><NA>영업/정상영업212899.338951049442943.33850695520201224135236일반세탁업<NA>임대000<NA>NN1<NA>1<NA>1<NA>00<NA>0일반세탁업0<NA><NA><NA><NA>0012021-01-04 20:51:44
6252625535300003530000-205-2020-0000406_20_01_PI2020-12-31 00:23:05.0세탁업신파세탁소405844인천광역시 남동구 남촌동 391-321624인천광역시 남동구 남촌동로 10, 상가동 201호 (남촌동)20201229폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업174959.512399082436700.48768963820201229155205일반세탁업전화번호임대000NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층1수리대상 의료기기의 유형00영업규모0일반세탁업0조건부허가시작일자조건부허가신고사유조건부허가종료일자총규모0012021-01-04 20:51:44
6253625641700004170000-205-2020-0000106_20_01_PI2020-12-31 00:23:05.0세탁업진성세탁소476841경기도 양평군 용문면 다문리 732-112523경기도 양평군 용문면 용문시장1길 6-1, 6호20201229<NA><NA><NA><NA>영업/정상영업252453.903116241442611.32825116120201229145030일반세탁업<NA><NA>000<NA>NN<NA><NA><NA><NA>0<NA>00<NA>0일반세탁업0<NA><NA><NA><NA>0002021-01-04 20:51:44
6254625736400003640000-205-2020-0000206_20_01_PI2020-12-31 00:23:05.0세탁업신동아 세탁소300835대전광역시 동구 홍도동 47-234556대전광역시 동구 동산초교로 41, 106호 (홍도동)20201229<NA><NA><NA><NA>영업/정상영업238092.285625316364.89431220201229093423일반세탁업042 633 2122<NA>000<NA>NN<NA><NA><NA><NA>3<NA>00<NA>0일반세탁업0<NA><NA><NA><NA>0002021-01-04 20:51:44
6255625844900005660000-205-2020-0000406_20_01_PI2020-12-31 00:23:05.0세탁업성성탑크린331300충청남도 천안시 서북구 성성동 84131078충청남도 천안시 서북구 성성6로 7-2, 1층 (성성동)20201229<NA><NA><NA><NA>영업/정상영업<NA><NA>20201229140444일반세탁업041 554 8100<NA>400<NA>NN1<NA>1<NA>1<NA>00<NA>0일반세탁업0<NA><NA><NA><NA>0022021-01-04 20:51:44
6256625955300005530000-205-2020-0000906_20_01_PI2021-01-02 00:23:15.0세탁업보은크리닝445160경기도 화성시 반송동 122-11 1층 전부호18459경기도 화성시 노작로2길 36, 1층 전부호 (반송동)20201231폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업206844.085320643410563.56916146320201231160923일반세탁업031 80587336건물소유구분명000NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층4수리대상 의료기기의 유형00영업규모0일반세탁업0조건부허가시작일자조건부허가신고사유조건부허가종료일자총규모0042021-01-04 20:51:44