Overview

Dataset statistics

Number of variables51
Number of observations4754
Missing cells4250
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 MiB
Average record size in memory413.0 B

Variable types

Numeric5
Text9
Categorical33
DateTime2
Boolean2

Alerts

opnsvcid has constant value ""Constant
multusnupsoyn has constant value ""Constant
balhansilyn has constant value ""Constant
last_load_dttm has constant value ""Constant
updategbn is highly imbalanced (71.6%)Imbalance
opnsvcnm is highly imbalanced (66.0%)Imbalance
clgstdt is highly imbalanced (92.8%)Imbalance
clgenddt is highly imbalanced (92.8%)Imbalance
ropnymd is highly imbalanced (92.8%)Imbalance
uptaenm is highly imbalanced (83.7%)Imbalance
bdngownsenm is highly imbalanced (52.3%)Imbalance
bdngjisgflrcnt is highly imbalanced (50.8%)Imbalance
bdngunderflrcnt is highly imbalanced (53.8%)Imbalance
maneipcnt is highly imbalanced (86.3%)Imbalance
sjyn is highly imbalanced (92.8%)Imbalance
usejisgendflr is highly imbalanced (52.9%)Imbalance
useunderendflr is highly imbalanced (60.9%)Imbalance
useunderstflr is highly imbalanced (54.8%)Imbalance
washmccnt is highly imbalanced (53.9%)Imbalance
medkind is highly imbalanced (92.8%)Imbalance
wmeipcnt is highly imbalanced (87.0%)Imbalance
trdscp is highly imbalanced (92.8%)Imbalance
sntuptaenm is highly imbalanced (83.7%)Imbalance
chaircnt is highly imbalanced (67.4%)Imbalance
cndpermstymd is highly imbalanced (92.8%)Imbalance
cndpermntwhy is highly imbalanced (92.8%)Imbalance
cndpermendymd is highly imbalanced (92.8%)Imbalance
totscp is highly imbalanced (92.8%)Imbalance
rcvdryncnt is highly imbalanced (56.6%)Imbalance
rdnwhladdr has 2046 (43.0%) missing valuesMissing
dcbymd has 1743 (36.7%) missing valuesMissing
x has 203 (4.3%) missing valuesMissing
y has 203 (4.3%) missing valuesMissing
apvpermymd is highly skewed (γ1 = -32.74109831)Skewed
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 03:58:51.900032
Analysis finished2024-04-16 03:58:53.595581
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct4754
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2396.3702
Minimum1
Maximum6367
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.9 KiB
2024-04-16T12:58:53.647197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile238.65
Q11189.25
median2377.5
Q33565.75
95-th percentile4516.35
Maximum6367
Range6366
Interquartile range (IQR)2376.5

Descriptive statistics

Standard deviation1411.301
Coefficient of variation (CV)0.5889328
Kurtosis-0.92156495
Mean2396.3702
Median Absolute Deviation (MAD)1188.5
Skewness0.12900083
Sum11392344
Variance1991770.6
MonotonicityNot monotonic
2024-04-16T12:58:53.755885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 1
 
< 0.1%
3175 1
 
< 0.1%
3173 1
 
< 0.1%
3172 1
 
< 0.1%
3171 1
 
< 0.1%
3170 1
 
< 0.1%
3169 1
 
< 0.1%
3168 1
 
< 0.1%
3167 1
 
< 0.1%
3166 1
 
< 0.1%
Other values (4744) 4744
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 (%)
6367 1
< 0.1%
6366 1
< 0.1%
6365 1
< 0.1%
6363 1
< 0.1%
6327 1
< 0.1%
6306 1
< 0.1%
6220 1
< 0.1%
6216 1
< 0.1%
6213 1
< 0.1%
6160 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3326672.3
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.9 KiB
2024-04-16T12:58:53.853183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13300000
median3320000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation38601.568
Coefficient of variation (CV)0.011603658
Kurtosis-0.85025039
Mean3326672.3
Median Absolute Deviation (MAD)30000
Skewness0.13875238
Sum1.5815 × 1010
Variance1.4900811 × 109
MonotonicityNot monotonic
2024-04-16T12:58:53.950434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3300000 540
11.4%
3290000 490
10.3%
3340000 434
9.1%
3330000 434
9.1%
3320000 420
8.8%
3350000 376
7.9%
3310000 348
7.3%
3370000 340
7.2%
3390000 325
6.8%
3380000 257
 
5.4%
Other values (6) 790
16.6%
ValueCountFrequency (%)
3250000 92
 
1.9%
3260000 159
 
3.3%
3270000 151
 
3.2%
3280000 203
 
4.3%
3290000 490
10.3%
3300000 540
11.4%
3310000 348
7.3%
3320000 420
8.8%
3330000 434
9.1%
3340000 434
9.1%
ValueCountFrequency (%)
3400000 137
 
2.9%
3390000 325
6.8%
3380000 257
5.4%
3370000 340
7.2%
3360000 48
 
1.0%
3350000 376
7.9%
3340000 434
9.1%
3330000 434
9.1%
3320000 420
8.8%
3310000 348
7.3%

mgtno
Text

Distinct4731
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
2024-04-16T12:58:54.131925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters104588
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

Unique4718 ?
Unique (%)99.2%

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 (%)
3290000-205-2020-00002 3
 
0.1%
3370000-205-2020-00001 3
 
0.1%
3320000-205-2019-00002 3
 
0.1%
3330000-205-2019-00006 3
 
0.1%
3330000-205-2019-00004 3
 
0.1%
3290000-205-2019-00001 3
 
0.1%
3330000-205-2019-00005 3
 
0.1%
3310000-205-2019-00001 3
 
0.1%
3380000-205-2019-00005 3
 
0.1%
3400000-205-2019-00001 3
 
0.1%
Other values (4721) 4724
99.4%
2024-04-16T12:58:54.390863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 39957
38.2%
- 14262
 
13.6%
3 10387
 
9.9%
2 10052
 
9.6%
9 6968
 
6.7%
5 6714
 
6.4%
1 6526
 
6.2%
8 3248
 
3.1%
7 2716
 
2.6%
4 2241
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90326
86.4%
Dash Punctuation 14262
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 39957
44.2%
3 10387
 
11.5%
2 10052
 
11.1%
9 6968
 
7.7%
5 6714
 
7.4%
1 6526
 
7.2%
8 3248
 
3.6%
7 2716
 
3.0%
4 2241
 
2.5%
6 1517
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 14262
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 104588
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 39957
38.2%
- 14262
 
13.6%
3 10387
 
9.9%
2 10052
 
9.6%
9 6968
 
6.7%
5 6714
 
6.4%
1 6526
 
6.2%
8 3248
 
3.1%
7 2716
 
2.6%
4 2241
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 104588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 39957
38.2%
- 14262
 
13.6%
3 10387
 
9.9%
2 10052
 
9.6%
9 6968
 
6.7%
5 6714
 
6.4%
1 6526
 
6.2%
8 3248
 
3.1%
7 2716
 
2.6%
4 2241
 
2.1%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
06_20_01_P
4754 

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 4754
100.0%

Length

2024-04-16T12:58:54.509629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:58:54.591992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
06_20_01_p 4754
100.0%

updategbn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
I
4519 
U
 
235

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 4519
95.1%
U 235
 
4.9%

Length

2024-04-16T12:58:54.680865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:58:54.766294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4519
95.1%
u 235
 
4.9%

updatedt
Date

Distinct218
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-01 02:40:00
2024-04-16T12:58:54.869410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T12:58:54.999069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4453 
세탁업
 
301

Length

Max length4
Median length4
Mean length3.9366849
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> 4453
93.7%
세탁업 301
 
6.3%

Length

2024-04-16T12:58:55.097649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:58:55.168566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4453
93.7%
세탁업 301
 
6.3%

bplcnm
Text

Distinct2832
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
2024-04-16T12:58:55.358294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length4.4707615
Min length1

Characters and Unicode

Total characters21254
Distinct characters535
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

Unique2179 ?
Unique (%)45.8%

Sample

1st row국일세탁소
2nd row백설세탁소
3rd row평화세탁소
4th row월풀빨래방대청점
5th row대신세탁소
ValueCountFrequency (%)
세탁소 248
 
4.6%
현대 55
 
1.0%
백성사 47
 
0.9%
세탁 44
 
0.8%
백조 40
 
0.7%
백양 39
 
0.7%
크리닝 38
 
0.7%
월풀빨래방 36
 
0.7%
빨래방 36
 
0.7%
백성 33
 
0.6%
Other values (2716) 4726
88.5%
2024-04-16T12:58:55.707711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 2130
 
10.0%
탁 2074
 
9.8%
소 1228
 
5.8%
사 903
 
4.2%
597
 
2.8%
백 580
 
2.7%
성 484
 
2.3%
대 427
 
2.0%
크 384
 
1.8%
리 367
 
1.7%
Other values (525) 12080
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20254
95.3%
Space Separator 597
 
2.8%
Uppercase Letter 146
 
0.7%
Decimal Number 93
 
0.4%
Close Punctuation 47
 
0.2%
Open Punctuation 46
 
0.2%
Lowercase Letter 35
 
0.2%
Other Punctuation 29
 
0.1%
Dash Punctuation 3
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 2130
 
10.5%
탁 2074
 
10.2%
소 1228
 
6.1%
사 903
 
4.5%
백 580
 
2.9%
성 484
 
2.4%
대 427
 
2.1%
크 384
 
1.9%
리 367
 
1.8%
동 309
 
1.5%
Other values (465) 11368
56.1%
Uppercase Letter
ValueCountFrequency (%)
K 30
20.5%
S 17
11.6%
L 12
 
8.2%
C 11
 
7.5%
M 10
 
6.8%
O 9
 
6.2%
G 8
 
5.5%
H 7
 
4.8%
I 7
 
4.8%
T 5
 
3.4%
Other values (11) 30
20.5%
Lowercase Letter
ValueCountFrequency (%)
e 10
28.6%
h 4
 
11.4%
a 4
 
11.4%
o 2
 
5.7%
c 2
 
5.7%
n 2
 
5.7%
r 2
 
5.7%
k 1
 
2.9%
p 1
 
2.9%
y 1
 
2.9%
Other values (6) 6
17.1%
Decimal Number
ValueCountFrequency (%)
2 31
33.3%
1 27
29.0%
4 18
19.4%
9 5
 
5.4%
8 4
 
4.3%
3 4
 
4.3%
0 2
 
2.2%
7 1
 
1.1%
6 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 13
44.8%
& 9
31.0%
, 3
 
10.3%
＆ 1
 
3.4%
' 1
 
3.4%
: 1
 
3.4%
# 1
 
3.4%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
~ 1
33.3%
Space Separator
ValueCountFrequency (%)
597
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20254
95.3%
Common 818
 
3.8%
Latin 182
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 2130
 
10.5%
탁 2074
 
10.2%
소 1228
 
6.1%
사 903
 
4.5%
백 580
 
2.9%
성 484
 
2.4%
대 427
 
2.1%
크 384
 
1.9%
리 367
 
1.8%
동 309
 
1.5%
Other values (465) 11368
56.1%
Latin
ValueCountFrequency (%)
K 30
16.5%
S 17
 
9.3%
L 12
 
6.6%
C 11
 
6.0%
e 10
 
5.5%
M 10
 
5.5%
O 9
 
4.9%
G 8
 
4.4%
H 7
 
3.8%
I 7
 
3.8%
Other values (28) 61
33.5%
Common
ValueCountFrequency (%)
597
73.0%
) 47
 
5.7%
( 46
 
5.6%
2 31
 
3.8%
1 27
 
3.3%
4 18
 
2.2%
. 13
 
1.6%
& 9
 
1.1%
9 5
 
0.6%
8 4
 
0.5%
Other values (12) 21
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20254
95.3%
ASCII 998
 
4.7%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 2130
 
10.5%
탁 2074
 
10.2%
소 1228
 
6.1%
사 903
 
4.5%
백 580
 
2.9%
성 484
 
2.4%
대 427
 
2.1%
크 384
 
1.9%
리 367
 
1.8%
동 309
 
1.5%
Other values (465) 11368
56.1%
ASCII
ValueCountFrequency (%)
597
59.8%
) 47
 
4.7%
( 46
 
4.6%
2 31
 
3.1%
K 30
 
3.0%
1 27
 
2.7%
4 18
 
1.8%
S 17
 
1.7%
. 13
 
1.3%
L 12
 
1.2%
Other values (48) 160
 
16.0%
None
ValueCountFrequency (%)
＆ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

sitepostno
Text

Distinct787
Distinct (%)16.7%
Missing36
Missing (%)0.8%
Memory size37.3 KiB
2024-04-16T12:58:55.987208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters28308
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

Unique161 ?
Unique (%)3.4%

Sample

1st row600814
2nd row600091
3rd row600074
4th row600803
5th row600803
ValueCountFrequency (%)
619903 35
 
0.7%
604851 33
 
0.7%
607837 28
 
0.6%
616800 28
 
0.6%
604813 27
 
0.6%
612824 27
 
0.6%
617818 25
 
0.5%
614822 25
 
0.5%
616829 24
 
0.5%
607828 23
 
0.5%
Other values (777) 4443
94.2%
2024-04-16T12:58:56.354034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 5854
20.7%
8 5043
17.8%
1 4484
15.8%
0 4397
15.5%
2 2074
 
7.3%
4 1705
 
6.0%
3 1570
 
5.5%
7 1467
 
5.2%
9 1026
 
3.6%
5 682
 
2.4%
Other values (5) 6
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28302
> 99.9%
Other Letter 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 5854
20.7%
8 5043
17.8%
1 4484
15.8%
0 4397
15.5%
2 2074
 
7.3%
4 1705
 
6.0%
3 1570
 
5.5%
7 1467
 
5.2%
9 1026
 
3.6%
5 682
 
2.4%
Other Letter
ValueCountFrequency (%)
번 2
33.3%
지 1
16.7%
우 1
16.7%
편 1
16.7%
호 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 28302
> 99.9%
Hangul 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
6 5854
20.7%
8 5043
17.8%
1 4484
15.8%
0 4397
15.5%
2 2074
 
7.3%
4 1705
 
6.0%
3 1570
 
5.5%
7 1467
 
5.2%
9 1026
 
3.6%
5 682
 
2.4%
Hangul
ValueCountFrequency (%)
번 2
33.3%
지 1
16.7%
우 1
16.7%
편 1
16.7%
호 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28302
> 99.9%
Hangul 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 5854
20.7%
8 5043
17.8%
1 4484
15.8%
0 4397
15.5%
2 2074
 
7.3%
4 1705
 
6.0%
3 1570
 
5.5%
7 1467
 
5.2%
9 1026
 
3.6%
5 682
 
2.4%
Hangul
ValueCountFrequency (%)
번 2
33.3%
지 1
16.7%
우 1
16.7%
편 1
16.7%
호 1
16.7%

sitewhladdr
Text

Distinct4549
Distinct (%)95.8%
Missing7
Missing (%)0.1%
Memory size37.3 KiB
2024-04-16T12:58:56.794703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length53
Mean length25.921424
Min length18

Characters and Unicode

Total characters123049
Distinct characters400
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

Unique4375 ?
Unique (%)92.2%

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 4747
 
21.5%
t통b반 668
 
3.0%
동래구 540
 
2.4%
부산진구 490
 
2.2%
사하구 435
 
2.0%
해운대구 434
 
2.0%
북구 420
 
1.9%
금정구 376
 
1.7%
남구 346
 
1.6%
연제구 338
 
1.5%
Other values (5377) 13307
60.2%
2024-04-16T12:58:57.164676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21746
 
17.7%
동 5919
 
4.8%
산 5681
 
4.6%
1 5635
 
4.6%
부 5507
 
4.5%
광 4878
 
4.0%
구 4848
 
3.9%
지 4811
 
3.9%
시 4788
 
3.9%
역 4751
 
3.9%
Other values (390) 54485
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70682
57.4%
Decimal Number 24591
 
20.0%
Space Separator 21746
 
17.7%
Dash Punctuation 4134
 
3.4%
Uppercase Letter 1544
 
1.3%
Other Punctuation 128
 
0.1%
Close Punctuation 104
 
0.1%
Open Punctuation 104
 
0.1%
Lowercase Letter 14
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5919
 
8.4%
산 5681
 
8.0%
부 5507
 
7.8%
광 4878
 
6.9%
구 4848
 
6.9%
지 4811
 
6.8%
시 4788
 
6.8%
역 4751
 
6.7%
번 4644
 
6.6%
상 957
 
1.4%
Other values (341) 23898
33.8%
Uppercase Letter
ValueCountFrequency (%)
B 708
45.9%
T 688
44.6%
A 63
 
4.1%
P 17
 
1.1%
S 15
 
1.0%
K 14
 
0.9%
G 10
 
0.6%
L 8
 
0.5%
I 6
 
0.4%
C 3
 
0.2%
Other values (8) 12
 
0.8%
Decimal Number
ValueCountFrequency (%)
1 5635
22.9%
2 3330
13.5%
3 2806
11.4%
4 2263
9.2%
0 2217
 
9.0%
5 2081
 
8.5%
6 1753
 
7.1%
7 1640
 
6.7%
8 1511
 
6.1%
9 1355
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
a 2
14.3%
c 2
14.3%
l 2
14.3%
s 2
14.3%
k 2
14.3%
p 1
7.1%
i 1
7.1%
r 1
7.1%
e 1
7.1%
Other Punctuation
ValueCountFrequency (%)
, 72
56.2%
@ 26
 
20.3%
/ 20
 
15.6%
. 8
 
6.2%
' 1
 
0.8%
· 1
 
0.8%
Space Separator
ValueCountFrequency (%)
21746
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70682
57.4%
Common 50808
41.3%
Latin 1559
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5919
 
8.4%
산 5681
 
8.0%
부 5507
 
7.8%
광 4878
 
6.9%
구 4848
 
6.9%
지 4811
 
6.8%
시 4788
 
6.8%
역 4751
 
6.7%
번 4644
 
6.6%
상 957
 
1.4%
Other values (341) 23898
33.8%
Latin
ValueCountFrequency (%)
B 708
45.4%
T 688
44.1%
A 63
 
4.0%
P 17
 
1.1%
S 15
 
1.0%
K 14
 
0.9%
G 10
 
0.6%
L 8
 
0.5%
I 6
 
0.4%
C 3
 
0.2%
Other values (18) 27
 
1.7%
Common
ValueCountFrequency (%)
21746
42.8%
1 5635
 
11.1%
- 4134
 
8.1%
2 3330
 
6.6%
3 2806
 
5.5%
4 2263
 
4.5%
0 2217
 
4.4%
5 2081
 
4.1%
6 1753
 
3.5%
7 1640
 
3.2%
Other values (11) 3203
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70682
57.4%
ASCII 52365
42.6%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21746
41.5%
1 5635
 
10.8%
- 4134
 
7.9%
2 3330
 
6.4%
3 2806
 
5.4%
4 2263
 
4.3%
0 2217
 
4.2%
5 2081
 
4.0%
6 1753
 
3.3%
7 1640
 
3.1%
Other values (37) 4760
 
9.1%
Hangul
ValueCountFrequency (%)
동 5919
 
8.4%
산 5681
 
8.0%
부 5507
 
7.8%
광 4878
 
6.9%
구 4848
 
6.9%
지 4811
 
6.8%
시 4788
 
6.8%
역 4751
 
6.7%
번 4644
 
6.6%
상 957
 
1.4%
Other values (341) 23898
33.8%
None
ValueCountFrequency (%)
· 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

rdnpostno
Real number (ℝ)

Distinct1360
Distinct (%)28.6%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean48306.45
Minimum46002
Maximum49525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.9 KiB
2024-04-16T12:58:57.280216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46311.8
Q147719
median48947
Q348947
95-th percentile49268
Maximum49525
Range3523
Interquartile range (IQR)1228

Descriptive statistics

Standard deviation933.60737
Coefficient of variation (CV)0.019326764
Kurtosis-0.29609807
Mean48306.45
Median Absolute Deviation (MAD)286
Skewness-0.98585964
Sum2.2960056 × 108
Variance871622.72
MonotonicityNot monotonic
2024-04-16T12:58:57.396873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48947 2118
44.6%
48052 12
 
0.3%
48055 10
 
0.2%
49441 9
 
0.2%
48093 9
 
0.2%
49316 9
 
0.2%
48051 8
 
0.2%
46997 8
 
0.2%
48057 8
 
0.2%
48119 8
 
0.2%
Other values (1350) 2554
53.7%
ValueCountFrequency (%)
46002 1
 
< 0.1%
46007 4
0.1%
46008 2
< 0.1%
46009 2
< 0.1%
46010 2
< 0.1%
46011 1
 
< 0.1%
46013 1
 
< 0.1%
46015 1
 
< 0.1%
46016 1
 
< 0.1%
46017 3
0.1%
ValueCountFrequency (%)
49525 2
< 0.1%
49523 1
 
< 0.1%
49520 2
< 0.1%
49519 2
< 0.1%
49516 1
 
< 0.1%
49515 2
< 0.1%
49514 1
 
< 0.1%
49511 3
0.1%
49510 2
< 0.1%
49509 1
 
< 0.1%

rdnwhladdr
Text

MISSING 

Distinct2640
Distinct (%)97.5%
Missing2046
Missing (%)43.0%
Memory size37.3 KiB
2024-04-16T12:58:57.717588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length55
Mean length30.436854
Min length19

Characters and Unicode

Total characters82423
Distinct characters434
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

Unique2584 ?
Unique (%)95.4%

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 2708
 
17.6%
1층 378
 
2.5%
해운대구 326
 
2.1%
부산진구 302
 
2.0%
동래구 237
 
1.5%
사하구 233
 
1.5%
남구 227
 
1.5%
북구 200
 
1.3%
금정구 195
 
1.3%
사상구 176
 
1.1%
Other values (3291) 10384
67.6%
2024-04-16T12:58:58.156297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12659
 
15.4%
동 3685
 
4.5%
1 3404
 
4.1%
산 3311
 
4.0%
부 3208
 
3.9%
시 2875
 
3.5%
광 2865
 
3.5%
구 2764
 
3.4%
역 2709
 
3.3%
) 2665
 
3.2%
Other values (424) 42278
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48896
59.3%
Decimal Number 13415
 
16.3%
Space Separator 12659
 
15.4%
Close Punctuation 2665
 
3.2%
Open Punctuation 2665
 
3.2%
Other Punctuation 1527
 
1.9%
Dash Punctuation 433
 
0.5%
Uppercase Letter 141
 
0.2%
Lowercase Letter 16
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3685
 
7.5%
산 3311
 
6.8%
부 3208
 
6.6%
시 2875
 
5.9%
광 2865
 
5.9%
구 2764
 
5.7%
역 2709
 
5.5%
로 2642
 
5.4%
길 1594
 
3.3%
번 1531
 
3.1%
Other values (375) 21712
44.4%
Uppercase Letter
ValueCountFrequency (%)
A 41
29.1%
B 27
19.1%
S 13
 
9.2%
K 12
 
8.5%
T 9
 
6.4%
C 8
 
5.7%
P 8
 
5.7%
I 5
 
3.5%
H 4
 
2.8%
G 3
 
2.1%
Other values (8) 11
 
7.8%
Decimal Number
ValueCountFrequency (%)
1 3404
25.4%
2 2056
15.3%
3 1424
10.6%
0 1325
 
9.9%
4 1151
 
8.6%
5 995
 
7.4%
6 854
 
6.4%
7 791
 
5.9%
9 721
 
5.4%
8 694
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
e 3
18.8%
c 3
18.8%
s 2
12.5%
l 2
12.5%
k 2
12.5%
i 1
 
6.2%
r 1
 
6.2%
a 1
 
6.2%
p 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 1500
98.2%
@ 17
 
1.1%
/ 7
 
0.5%
· 1
 
0.1%
. 1
 
0.1%
' 1
 
0.1%
Space Separator
ValueCountFrequency (%)
12659
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2665
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2665
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 433
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48896
59.3%
Common 33369
40.5%
Latin 158
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3685
 
7.5%
산 3311
 
6.8%
부 3208
 
6.6%
시 2875
 
5.9%
광 2865
 
5.9%
구 2764
 
5.7%
역 2709
 
5.5%
로 2642
 
5.4%
길 1594
 
3.3%
번 1531
 
3.1%
Other values (375) 21712
44.4%
Latin
ValueCountFrequency (%)
A 41
25.9%
B 27
17.1%
S 13
 
8.2%
K 12
 
7.6%
T 9
 
5.7%
C 8
 
5.1%
P 8
 
5.1%
I 5
 
3.2%
H 4
 
2.5%
e 3
 
1.9%
Other values (18) 28
17.7%
Common
ValueCountFrequency (%)
12659
37.9%
1 3404
 
10.2%
) 2665
 
8.0%
( 2665
 
8.0%
2 2056
 
6.2%
, 1500
 
4.5%
3 1424
 
4.3%
0 1325
 
4.0%
4 1151
 
3.4%
5 995
 
3.0%
Other values (11) 3525
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48896
59.3%
ASCII 33525
40.7%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12659
37.8%
1 3404
 
10.2%
) 2665
 
7.9%
( 2665
 
7.9%
2 2056
 
6.1%
, 1500
 
4.5%
3 1424
 
4.2%
0 1325
 
4.0%
4 1151
 
3.4%
5 995
 
3.0%
Other values (37) 3681
 
11.0%
Hangul
ValueCountFrequency (%)
동 3685
 
7.5%
산 3311
 
6.8%
부 3208
 
6.6%
시 2875
 
5.9%
광 2865
 
5.9%
구 2764
 
5.7%
역 2709
 
5.5%
로 2642
 
5.4%
길 1594
 
3.3%
번 1531
 
3.1%
Other values (375) 21712
44.4%
None
ValueCountFrequency (%)
· 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

apvpermymd
Real number (ℝ)

SKEWED 

Distinct2691
Distinct (%)56.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19966406
Minimum9870512
Maximum20210318
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.9 KiB
2024-04-16T12:58:58.275574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9870512
5-th percentile19870513
Q119890622
median19951010
Q320040427
95-th percentile20160206
Maximum20210318
Range10339806
Interquartile range (IQR)149804.5

Descriptive statistics

Standard deviation262304.96
Coefficient of variation (CV)0.013137315
Kurtosis1226.2637
Mean19966406
Median Absolute Deviation (MAD)79414
Skewness-32.741098
Sum9.4920294 × 1010
Variance6.880389 × 1010
MonotonicityNot monotonic
2024-04-16T12:58:58.393104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19870513 255
 
5.4%
19870515 75
 
1.6%
19870509 57
 
1.2%
19870512 47
 
1.0%
19870518 41
 
0.9%
19870521 40
 
0.8%
19870523 39
 
0.8%
19870519 34
 
0.7%
19870529 33
 
0.7%
19870707 29
 
0.6%
Other values (2681) 4104
86.3%
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 (%)
20210318 1
< 0.1%
20210310 1
< 0.1%
20210309 1
< 0.1%
20210222 1
< 0.1%
20210201 1
< 0.1%
20210125 1
< 0.1%
20201207 1
< 0.1%
20201204 2
< 0.1%
20201106 2
< 0.1%
20201104 1
< 0.1%

dcbymd
Text

MISSING 

Distinct1901
Distinct (%)63.1%
Missing1743
Missing (%)36.7%
Memory size37.3 KiB
2024-04-16T12:58:58.653994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9574892
Min length4

Characters and Unicode

Total characters23960
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

Unique1434 ?
Unique (%)47.6%

Sample

1st row20170511
2nd row20040220
3rd row20040920
4th row20080814
5th row20041208
ValueCountFrequency (%)
20030227 81
 
2.7%
20050121 73
 
2.4%
20030704 41
 
1.4%
폐업일자 32
 
1.1%
20031114 31
 
1.0%
20031028 25
 
0.8%
20051117 24
 
0.8%
20030805 20
 
0.7%
20051130 14
 
0.5%
20030930 14
 
0.5%
Other values (1891) 2656
88.2%
2024-04-16T12:58:59.021323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7908
33.0%
2 4874
20.3%
1 4316
18.0%
9 1264
 
5.3%
3 1254
 
5.2%
7 1043
 
4.4%
6 834
 
3.5%
5 822
 
3.4%
4 795
 
3.3%
8 721
 
3.0%
Other values (5) 129
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23831
99.5%
Other Letter 128
 
0.5%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7908
33.2%
2 4874
20.5%
1 4316
18.1%
9 1264
 
5.3%
3 1254
 
5.3%
7 1043
 
4.4%
6 834
 
3.5%
5 822
 
3.4%
4 795
 
3.3%
8 721
 
3.0%
Other Letter
ValueCountFrequency (%)
폐 32
25.0%
업 32
25.0%
일 32
25.0%
자 32
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23832
99.5%
Hangul 128
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7908
33.2%
2 4874
20.5%
1 4316
18.1%
9 1264
 
5.3%
3 1254
 
5.3%
7 1043
 
4.4%
6 834
 
3.5%
5 822
 
3.4%
4 795
 
3.3%
8 721
 
3.0%
Hangul
ValueCountFrequency (%)
폐 32
25.0%
업 32
25.0%
일 32
25.0%
자 32
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23832
99.5%
Hangul 128
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7908
33.2%
2 4874
20.5%
1 4316
18.1%
9 1264
 
5.3%
3 1254
 
5.3%
7 1043
 
4.4%
6 834
 
3.5%
5 822
 
3.4%
4 795
 
3.3%
8 721
 
3.0%
Hangul
ValueCountFrequency (%)
폐 32
25.0%
업 32
25.0%
일 32
25.0%
자 32
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4713 
휴업시작일자
 
41

Length

Max length6
Median length4
Mean length4.0172486
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> 4713
99.1%
휴업시작일자 41
 
0.9%

Length

2024-04-16T12:58:59.142181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:58:59.223637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4713
99.1%
휴업시작일자 41
 
0.9%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4713 
휴업종료일자
 
41

Length

Max length6
Median length4
Mean length4.0172486
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> 4713
99.1%
휴업종료일자 41
 
0.9%

Length

2024-04-16T12:58:59.310551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:58:59.396090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4713
99.1%
휴업종료일자 41
 
0.9%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4713 
재개업일자
 
41

Length

Max length5
Median length4
Mean length4.0086243
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> 4713
99.1%
재개업일자 41
 
0.9%

Length

2024-04-16T12:58:59.478712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:58:59.555027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4713
99.1%
재개업일자 41
 
0.9%

trdstatenm
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
02
2886 
01
1567 
영업/정상
 
206
폐업
 
93
<NA>
 
2

Length

Max length5
Median length2
Mean length2.1308372
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
02 2886
60.7%
01 1567
33.0%
영업/정상 206
 
4.3%
폐업 93
 
2.0%
<NA> 2
 
< 0.1%

Length

2024-04-16T12:58:59.633987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:58:59.721012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 2886
60.7%
01 1567
33.0%
영업/정상 206
 
4.3%
폐업 93
 
2.0%
na 2
 
< 0.1%

dtlstatenm
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
폐업
2979 
영업
1775 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2979
62.7%
영업 1775
37.3%

Length

2024-04-16T12:58:59.807241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:58:59.881585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2979
62.7%
영업 1775
37.3%

x
Text

MISSING 

Distinct4239
Distinct (%)93.1%
Missing203
Missing (%)4.3%
Memory size37.3 KiB
2024-04-16T12:59:00.034923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.994287
Min length7

Characters and Unicode

Total characters90994
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

Unique3980 ?
Unique (%)87.5%

Sample

1st row385844.46764500000
2nd row385286.93835400000
3rd row384464.22393800000
4th row384660.977766
5th row384581.409949
ValueCountFrequency (%)
395388.715069604 5
 
0.1%
378474.793935 5
 
0.1%
386910.508505 4
 
0.1%
392810.80546300000 4
 
0.1%
382137.104187552 4
 
0.1%
381579.27262100000 4
 
0.1%
393449.69378400000 4
 
0.1%
383207.082975 4
 
0.1%
392456.73180800000 4
 
0.1%
384581.157472 4
 
0.1%
Other values (4229) 4509
99.1%
2024-04-16T12:59:00.319442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18860
20.7%
0 16857
18.5%
3 9074
10.0%
8 7365
 
8.1%
9 6197
 
6.8%
2 4922
 
5.4%
1 4827
 
5.3%
4 4755
 
5.2%
7 4732
 
5.2%
. 4541
 
5.0%
Other values (9) 8864
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67579
74.3%
Space Separator 18860
 
20.7%
Other Punctuation 4541
 
5.0%
Other Letter 8
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16857
24.9%
3 9074
13.4%
8 7365
10.9%
9 6197
 
9.2%
2 4922
 
7.3%
1 4827
 
7.1%
4 4755
 
7.0%
7 4732
 
7.0%
5 4512
 
6.7%
6 4338
 
6.4%
Other Letter
ValueCountFrequency (%)
좌 2
25.0%
표 2
25.0%
정 2
25.0%
보 2
25.0%
Space Separator
ValueCountFrequency (%)
18860
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4541
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 90984
> 99.9%
Hangul 8
 
< 0.1%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
18860
20.7%
0 16857
18.5%
3 9074
10.0%
8 7365
 
8.1%
9 6197
 
6.8%
2 4922
 
5.4%
1 4827
 
5.3%
4 4755
 
5.2%
7 4732
 
5.2%
. 4541
 
5.0%
Other values (4) 8854
9.7%
Hangul
ValueCountFrequency (%)
좌 2
25.0%
표 2
25.0%
정 2
25.0%
보 2
25.0%
Latin
ValueCountFrequency (%)
X 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90986
> 99.9%
Hangul 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18860
20.7%
0 16857
18.5%
3 9074
10.0%
8 7365
 
8.1%
9 6197
 
6.8%
2 4922
 
5.4%
1 4827
 
5.3%
4 4755
 
5.2%
7 4732
 
5.2%
. 4541
 
5.0%
Other values (5) 8856
9.7%
Hangul
ValueCountFrequency (%)
좌 2
25.0%
표 2
25.0%
정 2
25.0%
보 2
25.0%

y
Text

MISSING 

Distinct4239
Distinct (%)93.1%
Missing203
Missing (%)4.3%
Memory size37.3 KiB
2024-04-16T12:59:00.500326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.994287
Min length7

Characters and Unicode

Total characters90994
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

Unique3980 ?
Unique (%)87.5%

Sample

1st row180840.18410800000
2nd row180439.91103500000
3rd row180221.47261700000
4th row180177.894242
5th row180434.791445
ValueCountFrequency (%)
186268.853282623 5
 
0.1%
180075.396084 5
 
0.1%
190996.315979 4
 
0.1%
183841.99707300000 4
 
0.1%
191686.955693638 4
 
0.1%
190921.66421500000 4
 
0.1%
180727.61997800000 4
 
0.1%
193582.095669 4
 
0.1%
183776.52526400000 4
 
0.1%
192148.620318 4
 
0.1%
Other values (4229) 4509
99.1%
2024-04-16T12:59:00.777857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18837
20.7%
0 16438
18.1%
1 9246
10.2%
8 7053
 
7.8%
9 6357
 
7.0%
7 5292
 
5.8%
2 4740
 
5.2%
5 4713
 
5.2%
6 4595
 
5.0%
4 4587
 
5.0%
Other values (9) 9136
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67602
74.3%
Space Separator 18837
 
20.7%
Other Punctuation 4541
 
5.0%
Other Letter 8
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16438
24.3%
1 9246
13.7%
8 7053
10.4%
9 6357
 
9.4%
7 5292
 
7.8%
2 4740
 
7.0%
5 4713
 
7.0%
6 4595
 
6.8%
4 4587
 
6.8%
3 4581
 
6.8%
Other Letter
ValueCountFrequency (%)
좌 2
25.0%
표 2
25.0%
정 2
25.0%
보 2
25.0%
Space Separator
ValueCountFrequency (%)
18837
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4541
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 90984
> 99.9%
Hangul 8
 
< 0.1%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
18837
20.7%
0 16438
18.1%
1 9246
10.2%
8 7053
 
7.8%
9 6357
 
7.0%
7 5292
 
5.8%
2 4740
 
5.2%
5 4713
 
5.2%
6 4595
 
5.1%
4 4587
 
5.0%
Other values (4) 9126
10.0%
Hangul
ValueCountFrequency (%)
좌 2
25.0%
표 2
25.0%
정 2
25.0%
보 2
25.0%
Latin
ValueCountFrequency (%)
Y 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90986
> 99.9%
Hangul 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18837
20.7%
0 16438
18.1%
1 9246
10.2%
8 7053
 
7.8%
9 6357
 
7.0%
7 5292
 
5.8%
2 4740
 
5.2%
5 4713
 
5.2%
6 4595
 
5.1%
4 4587
 
5.0%
Other values (5) 9128
10.0%
Hangul
ValueCountFrequency (%)
좌 2
25.0%
표 2
25.0%
정 2
25.0%
보 2
25.0%

lastmodts
Real number (ℝ)

Distinct3286
Distinct (%)69.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0093066 × 1013
Minimum1.9990128 × 1013
Maximum2.0210429 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.9 KiB
2024-04-16T12:59:00.904706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990128 × 1013
5-th percentile1.9990426 × 1013
Q12.0031006 × 1013
median2.0100204 × 1013
Q32.0140508 × 1013
95-th percentile2.0190556 × 1013
Maximum2.0210429 × 1013
Range2.2030114 × 1011
Interquartile range (IQR)1.0950217 × 1011

Descriptive statistics

Standard deviation6.1426417 × 1010
Coefficient of variation (CV)0.0030570952
Kurtosis-1.1726353
Mean2.0093066 × 1013
Median Absolute Deviation (MAD)5.8986659 × 1010
Skewness-0.023020817
Sum9.5522437 × 1016
Variance3.7732047 × 1021
MonotonicityNot monotonic
2024-04-16T12:59:01.019014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070320000000 86
 
1.8%
19990318000000 83
 
1.7%
20020509000000 68
 
1.4%
20030415000000 60
 
1.3%
20020415000000 53
 
1.1%
20020510000000 48
 
1.0%
20020412000000 47
 
1.0%
19990429000000 37
 
0.8%
20030805000000 33
 
0.7%
20031118000000 31
 
0.7%
Other values (3276) 4208
88.5%
ValueCountFrequency (%)
19990128000000 1
 
< 0.1%
19990209000000 3
 
0.1%
19990210000000 3
 
0.1%
19990218000000 7
0.1%
19990219000000 13
0.3%
19990222000000 1
 
< 0.1%
19990223000000 14
0.3%
19990224000000 2
 
< 0.1%
19990225000000 6
0.1%
19990309000000 6
0.1%
ValueCountFrequency (%)
20210429144524 1
< 0.1%
20210429100353 1
< 0.1%
20210422100833 1
< 0.1%
20210419141357 1
< 0.1%
20210415155140 1
< 0.1%
20210414191530 1
< 0.1%
20210414182501 1
< 0.1%
20210413104305 1
< 0.1%
20210408105318 1
< 0.1%
20210406163026 1
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
일반세탁업
4493 
빨래방업
 
172
운동화전문세탁업
 
52
세탁업 기타
 
36
<NA>
 
1

Length

Max length8
Median length5
Mean length5.0039966
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 4493
94.5%
빨래방업 172
 
3.6%
운동화전문세탁업 52
 
1.1%
세탁업 기타 36
 
0.8%
<NA> 1
 
< 0.1%

Length

2024-04-16T12:59:01.130845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:01.216857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 4493
93.8%
빨래방업 172
 
3.6%
운동화전문세탁업 52
 
1.1%
세탁업 36
 
0.8%
기타 36
 
0.8%
na 1
 
< 0.1%

sitetel
Text

Distinct51
Distinct (%)1.1%
Missing11
Missing (%)0.2%
Memory size37.3 KiB
2024-04-16T12:59:01.382394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.977862
Min length4

Characters and Unicode

Total characters56811
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

Unique47 ?
Unique (%)1.0%

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 4682
97.1%
051 50
 
1.0%
전화번호 10
 
0.2%
6998 2
 
< 0.1%
205 2
 
< 0.1%
721 2
 
< 0.1%
724 2
 
< 0.1%
973 2
 
< 0.1%
8219 2
 
< 0.1%
852 2
 
< 0.1%
Other values (64) 64
 
1.3%
2024-04-16T12:59:01.681236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14127
24.9%
2 9404
16.6%
3 9404
16.6%
- 9364
16.5%
5 4785
 
8.4%
0 4759
 
8.4%
4 4711
 
8.3%
77
 
0.1%
7 39
 
0.1%
6 38
 
0.1%
Other values (6) 103
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47330
83.3%
Dash Punctuation 9364
 
16.5%
Space Separator 77
 
0.1%
Other Letter 40
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14127
29.8%
2 9404
19.9%
3 9404
19.9%
5 4785
 
10.1%
0 4759
 
10.1%
4 4711
 
10.0%
7 39
 
0.1%
6 38
 
0.1%
8 35
 
0.1%
9 28
 
0.1%
Other Letter
ValueCountFrequency (%)
전 10
25.0%
화 10
25.0%
번 10
25.0%
호 10
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 9364
100.0%
Space Separator
ValueCountFrequency (%)
77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56771
99.9%
Hangul 40
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14127
24.9%
2 9404
16.6%
3 9404
16.6%
- 9364
16.5%
5 4785
 
8.4%
0 4759
 
8.4%
4 4711
 
8.3%
77
 
0.1%
7 39
 
0.1%
6 38
 
0.1%
Other values (2) 63
 
0.1%
Hangul
ValueCountFrequency (%)
전 10
25.0%
화 10
25.0%
번 10
25.0%
호 10
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56771
99.9%
Hangul 40
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14127
24.9%
2 9404
16.6%
3 9404
16.6%
- 9364
16.5%
5 4785
 
8.4%
0 4759
 
8.4%
4 4711
 
8.3%
77
 
0.1%
7 39
 
0.1%
6 38
 
0.1%
Other values (2) 63
 
0.1%
Hangul
ValueCountFrequency (%)
전 10
25.0%
화 10
25.0%
번 10
25.0%
호 10
25.0%

bdngownsenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
3708 
임대
824 
자가
 
185
건물소유구분명
 
37

Length

Max length7
Median length4
Mean length3.5988641
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3708
78.0%
임대 824
 
17.3%
자가 185
 
3.9%
건물소유구분명 37
 
0.8%

Length

2024-04-16T12:59:01.787421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:01.870235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3708
78.0%
임대 824
 
17.3%
자가 185
 
3.9%
건물소유구분명 37
 
0.8%

bdngjisgflrcnt
Categorical

IMBALANCE 

Distinct41
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
0
1575 
<NA>
1188 
2
776 
3
397 
1
293 
Other values (36)
525 

Length

Max length6
Median length1
Mean length1.7715608
Min length1

Unique

Unique9 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 1575
33.1%
<NA> 1188
25.0%
2 776
16.3%
3 397
 
8.4%
1 293
 
6.2%
4 287
 
6.0%
5 111
 
2.3%
6 18
 
0.4%
7 11
 
0.2%
15 9
 
0.2%
Other values (31) 89
 
1.9%

Length

2024-04-16T12:59:01.958687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 1575
33.1%
na 1188
25.0%
2 776
16.3%
3 397
 
8.4%
1 293
 
6.2%
4 287
 
6.0%
5 111
 
2.3%
6 18
 
0.4%
7 11
 
0.2%
15 9
 
0.2%
Other values (31) 89
 
1.9%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
0
2330 
<NA>
1853 
1
467 
2
 
40
3
 
25
Other values (5)
 
39

Length

Max length6
Median length1
Mean length2.1758519
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 2330
49.0%
<NA> 1853
39.0%
1 467
 
9.8%
2 40
 
0.8%
3 25
 
0.5%
5 13
 
0.3%
4 13
 
0.3%
6 6
 
0.1%
건물지하층수 6
 
0.1%
10 1
 
< 0.1%

Length

2024-04-16T12:59:02.058267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:02.151211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2330
49.0%
na 1853
39.0%
1 467
 
9.8%
2 40
 
0.8%
3 25
 
0.5%
5 13
 
0.3%
4 13
 
0.3%
6 6
 
0.1%
건물지하층수 6
 
0.1%
10 1
 
< 0.1%

maneipcnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4456 
0
 
230
1
 
41
남성종사자수
 
17
2
 
5
Other values (3)
 
5

Length

Max length6
Median length4
Mean length3.8300379
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> 4456
93.7%
0 230
 
4.8%
1 41
 
0.9%
남성종사자수 17
 
0.4%
2 5
 
0.1%
5 2
 
< 0.1%
7 2
 
< 0.1%
20 1
 
< 0.1%

Length

2024-04-16T12:59:02.257027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:02.358319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4456
93.7%
0 230
 
4.8%
1 41
 
0.9%
남성종사자수 17
 
0.4%
2 5
 
0.1%
5 2
 
< 0.1%
7 2
 
< 0.1%
20 1
 
< 0.1%

sjyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4713 
다
 
41

Length

Max length4
Median length4
Mean length3.9741271
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> 4713
99.1%
다 41
 
0.9%

Length

2024-04-16T12:59:02.479386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:02.571830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4713
99.1%
다 41
 
0.9%

multusnupsoyn
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
False
4754 
ValueCountFrequency (%)
False 4754
100.0%
2024-04-16T12:59:02.641956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

balhansilyn
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
False
4754 
ValueCountFrequency (%)
False 4754
100.0%
2024-04-16T12:59:02.711255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

usejisgendflr
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
2419 
1
1372 
0
644 
2
252 
3
 
40
Other values (8)
 
27

Length

Max length6
Median length4
Mean length2.5376525
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2419
50.9%
1 1372
28.9%
0 644
 
13.5%
2 252
 
5.3%
3 40
 
0.8%
사용끝지상층 10
 
0.2%
4 8
 
0.2%
5 2
 
< 0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
Other values (3) 3
 
0.1%

Length

2024-04-16T12:59:02.808299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2419
50.9%
1 1372
28.9%
0 644
 
13.5%
2 252
 
5.3%
3 40
 
0.8%
사용끝지상층 10
 
0.2%
4 8
 
0.2%
5 2
 
< 0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
Other values (3) 3
 
0.1%

useunderendflr
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
3403 
0
1239 
1
 
68
사용끝지하층
 
28
2
 
14

Length

Max length6
Median length4
Mean length3.1769037
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> 3403
71.6%
0 1239
 
26.1%
1 68
 
1.4%
사용끝지하층 28
 
0.6%
2 14
 
0.3%
3 2
 
< 0.1%

Length

2024-04-16T12:59:02.932085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:03.041592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3403
71.6%
0 1239
 
26.1%
1 68
 
1.4%
사용끝지하층 28
 
0.6%
2 14
 
0.3%
3 2
 
< 0.1%

usejisgstflr
Categorical

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
1771 
0
1343 
1
1331 
2
235 
3
 
40
Other values (8)
 
34

Length

Max length7
Median length1
Mean length2.1268406
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1771
37.3%
0 1343
28.2%
1 1331
28.0%
2 235
 
4.9%
3 40
 
0.8%
4 13
 
0.3%
5 7
 
0.1%
사용시작지상층 7
 
0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
Other values (3) 3
 
0.1%

Length

2024-04-16T12:59:03.162115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1771
37.3%
0 1343
28.2%
1 1331
28.0%
2 235
 
4.9%
3 40
 
0.8%
4 13
 
0.3%
5 7
 
0.1%
사용시작지상층 7
 
0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
Other values (3) 3
 
0.1%

useunderstflr
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
2464 
0
2178 
1
 
70
사용시작지하층
 
28
2
 
11

Length

Max length7
Median length4
Mean length2.5902398
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> 2464
51.8%
0 2178
45.8%
1 70
 
1.5%
사용시작지하층 28
 
0.6%
2 11
 
0.2%
3 3
 
0.1%

Length

2024-04-16T12:59:03.288839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:03.396555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2464
51.8%
0 2178
45.8%
1 70
 
1.5%
사용시작지하층 28
 
0.6%
2 11
 
0.2%
3 3
 
0.1%

washmccnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
2976 
0
628 
1
571 
2
309 
3
 
177
Other values (9)
 
93

Length

Max length4
Median length4
Mean length2.8824148
Min length1

Unique

Unique4 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2976
62.6%
0 628
 
13.2%
1 571
 
12.0%
2 309
 
6.5%
3 177
 
3.7%
4 56
 
1.2%
5 17
 
0.4%
6 7
 
0.1%
세탁기수 6
 
0.1%
7 3
 
0.1%
Other values (4) 4
 
0.1%

Length

2024-04-16T12:59:03.501360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2976
62.6%
0 628
 
13.2%
1 571
 
12.0%
2 309
 
6.5%
3 177
 
3.7%
4 56
 
1.2%
5 17
 
0.4%
6 7
 
0.1%
세탁기수 6
 
0.1%
7 3
 
0.1%
Other values (4) 4
 
0.1%

medkind
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4713 
수리대상 의료기기의 유형
 
41

Length

Max length13
Median length4
Mean length4.0776188
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> 4713
99.1%
수리대상 의료기기의 유형 41
 
0.9%

Length

2024-04-16T12:59:03.602401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:03.673638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4713
97.5%
수리대상 41
 
0.8%
의료기기의 41
 
0.8%
유형 41
 
0.8%

yangsilcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
0
2635 
<NA>
2113 
양실수
 
6

Length

Max length4
Median length1
Mean length2.3359276
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 2635
55.4%
<NA> 2113
44.4%
양실수 6
 
0.1%

Length

2024-04-16T12:59:04.041544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:04.125258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2635
55.4%
na 2113
44.4%
양실수 6
 
0.1%

wmeipcnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4463 
0
 
243
1
 
22
여성종사자수
 
17
2
 
4
Other values (3)
 
5

Length

Max length6
Median length4
Mean length3.8342448
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> 4463
93.9%
0 243
 
5.1%
1 22
 
0.5%
여성종사자수 17
 
0.4%
2 4
 
0.1%
4 2
 
< 0.1%
8 2
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-16T12:59:04.214680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:04.306131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4463
93.9%
0 243
 
5.1%
1 22
 
0.5%
여성종사자수 17
 
0.4%
2 4
 
0.1%
4 2
 
< 0.1%
8 2
 
< 0.1%
3 1
 
< 0.1%

trdscp
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4713 
영업규모
 
41

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> 4713
99.1%
영업규모 41
 
0.9%

Length

2024-04-16T12:59:04.409456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:04.486519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4713
99.1%
영업규모 41
 
0.9%

yoksilcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
0
2635 
<NA>
2113 
욕실수
 
6

Length

Max length4
Median length1
Mean length2.3359276
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 2635
55.4%
<NA> 2113
44.4%
욕실수 6
 
0.1%

Length

2024-04-16T12:59:04.576610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:04.666790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2635
55.4%
na 2113
44.4%
욕실수 6
 
0.1%

sntuptaenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
일반세탁업
4493 
빨래방업
 
172
운동화전문세탁업
 
52
세탁업 기타
 
36
<NA>
 
1

Length

Max length8
Median length5
Mean length5.0039966
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 4493
94.5%
빨래방업 172
 
3.6%
운동화전문세탁업 52
 
1.1%
세탁업 기타 36
 
0.8%
<NA> 1
 
< 0.1%

Length

2024-04-16T12:59:04.766284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:04.862032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 4493
93.8%
빨래방업 172
 
3.6%
운동화전문세탁업 52
 
1.1%
세탁업 36
 
0.8%
기타 36
 
0.8%
na 1
 
< 0.1%

chaircnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
0
2631 
<NA>
2105 
의자수
 
6
3
 
4
2
 
2
Other values (4)
 
6

Length

Max length4
Median length1
Mean length2.3308793
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 2631
55.3%
<NA> 2105
44.3%
의자수 6
 
0.1%
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

2024-04-16T12:59:04.959814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:05.060702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2631
55.3%
na 2105
44.3%
의자수 6
 
0.1%
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 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4713 
조건부허가시작일자
 
41

Length

Max length9
Median length4
Mean length4.0431216
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> 4713
99.1%
조건부허가시작일자 41
 
0.9%

Length

2024-04-16T12:59:05.161952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:05.233992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4713
99.1%
조건부허가시작일자 41
 
0.9%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4713 
조건부허가신고사유
 
41

Length

Max length9
Median length4
Mean length4.0431216
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> 4713
99.1%
조건부허가신고사유 41
 
0.9%

Length

2024-04-16T12:59:05.311830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:05.381984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4713
99.1%
조건부허가신고사유 41
 
0.9%

cndpermendymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4713 
조건부허가종료일자
 
41

Length

Max length9
Median length4
Mean length4.0431216
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> 4713
99.1%
조건부허가종료일자 41
 
0.9%

Length

2024-04-16T12:59:05.459052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:05.534431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4713
99.1%
조건부허가종료일자 41
 
0.9%

totscp
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
4713 
총규모
 
41

Length

Max length4
Median length4
Mean length3.9913757
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> 4713
99.1%
총규모 41
 
0.9%

Length

2024-04-16T12:59:05.616018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:05.696292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4713
99.1%
총규모 41
 
0.9%

abedcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
3264 
0
1484 
침대수
 
6

Length

Max length4
Median length4
Mean length3.0622634
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> 3264
68.7%
0 1484
31.2%
침대수 6
 
0.1%

Length

2024-04-16T12:59:05.779630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:05.860825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3264
68.7%
0 1484
31.2%
침대수 6
 
0.1%

hanshilcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
0
2635 
<NA>
2113 
한실수
 
6

Length

Max length4
Median length1
Mean length2.3359276
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 2635
55.4%
<NA> 2113
44.4%
한실수 6
 
0.1%

Length

2024-04-16T12:59:05.948475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T12:59:06.026182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2635
55.4%
na 2113
44.4%
한실수 6
 
0.1%

rcvdryncnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
<NA>
2938 
1
1016 
0
676 
2
 
45
3
 
38
Other values (6)
 
41

Length

Max length5
Median length4
Mean length2.8592764
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> 2938
61.8%
1 1016
 
21.4%
0 676
 
14.2%
2 45
 
0.9%
3 38
 
0.8%
4 18
 
0.4%
5 12
 
0.3%
회수건조수 6
 
0.1%
7 3
 
0.1%
11 1
 
< 0.1%

Length

2024-04-16T12:59:06.117407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2938
61.8%
1 1016
 
21.4%
0 676
 
14.2%
2 45
 
0.9%
3 38
 
0.8%
4 18
 
0.4%
5 12
 
0.3%
회수건조수 6
 
0.1%
7 3
 
0.1%
11 1
 
< 0.1%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.3 KiB
Minimum2021-05-01 05:17:03
Maximum2021-05-01 05:17:03
2024-04-16T12:59:06.200204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T12:59:06.269895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

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>2021-05-01 05:17:03
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>2021-05-01 05:17:03
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>2021-05-01 05:17:03
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>2021-05-01 05:17:03
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>2021-05-01 05:17:03
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>2021-05-01 05:17:03
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>2021-05-01 05:17:03
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>2021-05-01 05:17:03
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>2021-05-01 05:17:03
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>2021-05-01 05:17:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntsjynmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntmedkindyangsilcntwmeipcnttrdscpyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdtotscpabedcnthanshilcntrcvdryncntlast_load_dttm
4744616033600003360000-205-2020-0000106_20_01_PI2020-11-08 00:23:09.0세탁업강서구지역자활센터(동백일터클리닝)618220부산광역시 강서구 미음동 1570-11 부산조선해양기자재제1공업협동조합 2동 1층일부호46744부산광역시 강서구 미음산단로295번길 6, 부산조선해양기자재제1공업협동조합 2동 1층 일부호 (미음동)20201106폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업369503.739457083185074.53273134420201106133258일반세탁업051 973 6998건물소유구분명건물지상층수건물지하층수남성종사자수다NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층세탁기수수리대상 의료기기의 유형양실수여성종사자수영업규모욕실수일반세탁업의자수조건부허가시작일자조건부허가신고사유조건부허가종료일자총규모침대수한실수회수건조수2021-05-01 05:17:03
4745621333700003370000-205-2020-0000406_20_01_PI2020-12-06 00:23:07.0세탁업연제지역자활센터 마마운동화이불빨래방 연제점611827부산광역시 연제구 연산동 806-1947600부산광역시 연제구 중앙천로25번길 48, 1층 (연산동)20201204폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업389465.446070878188458.54725942520201204111348운동화전문세탁업051 852 8219건물소유구분명400다NN1사용끝지하층1사용시작지하층2수리대상 의료기기의 유형00영업규모0운동화전문세탁업0조건부허가시작일자조건부허가신고사유조건부허가종료일자총규모0002021-05-01 05:17:03
4746621633700003370000-205-2020-0000406_20_01_PI2020-12-06 00:23:07.0세탁업연제지역자활센터 마마운동화이불빨래방 연제점611827부산광역시 연제구 연산동 806-1947600부산광역시 연제구 중앙천로25번길 48, 1층 (연산동)20201204폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업389465.446070878188458.54725942520201204111348운동화전문세탁업051 852 8219건물소유구분명400다NN1사용끝지하층1사용시작지하층2수리대상 의료기기의 유형00영업규모0운동화전문세탁업0조건부허가시작일자조건부허가신고사유조건부허가종료일자총규모0002021-05-01 05:17:03
4747622033300003330000-205-2020-0000706_20_01_PI2020-12-09 00:23:07.0세탁업신태양 크리닝612828부산광역시 해운대구 재송동 456-3 송원탕48056부산광역시 해운대구 재반로27번길 48-19, 송원탕 1층 일부호 (재송동)20201207<NA><NA><NA><NA>영업/정상영업393518.305559754189142.76753396320201207141952일반세탁업<NA><NA>001<NA>NN<NA><NA><NA><NA>2<NA>01<NA>0일반세탁업0<NA><NA><NA><NA>0012021-05-01 05:17:03
4748630632900003290000-205-2021-0000106_20_01_PI2021-01-27 00:23:03.0세탁업명품 세탁소614854부산광역시 부산진구 양정동 142-847217부산광역시 부산진구 중앙대로980번길 23, 1층 (양정동)20210125<NA><NA><NA><NA>영업/정상영업389000.026546689188309.63768621220210125160833일반세탁업051 853 6616<NA>200<NA>NN<NA><NA>1<NA>2<NA>00<NA>0일반세탁업0<NA><NA><NA><NA>0002021-05-01 05:17:03
4749632734000003400000-205-2021-0000106_20_01_PU2021-03-06 02:40:00.0세탁업주식회사 아이이불부산지번우편번호부산광역시 기장군 정관읍 달산리 1006-246024부산광역시 기장군 정관읍 달산4길 102, 1층20210201폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업398182.056479827204263.04180513420210304113252일반세탁업전화번호건물소유구분명000다NN10101수리대상 의료기기의 유형00영업규모0일반세탁업0조건부허가시작일자조건부허가신고사유조건부허가종료일자총규모0012021-05-01 05:17:03
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