Overview

Dataset statistics

Number of variables81
Number of observations8464
Missing cells25598
Missing cells (%)3.7%
Duplicate rows94
Duplicate rows (%)1.1%
Total size in memory5.3 MiB
Average record size in memory651.0 B

Variable types

Unsupported4
Numeric3
Text10
Categorical63
DateTime1

Alerts

Dataset has 94 (1.1%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (89.8%)Imbalance
updategbn is highly imbalanced (83.7%)Imbalance
opnsvcnm is highly imbalanced (85.2%)Imbalance
clgstdt is highly imbalanced (98.2%)Imbalance
clgenddt is highly imbalanced (98.1%)Imbalance
ropnymd is highly imbalanced (95.2%)Imbalance
trdstatenm is highly imbalanced (54.9%)Imbalance
dtlstatenm is highly imbalanced (54.2%)Imbalance
stroomcnt is highly imbalanced (96.0%)Imbalance
bdngsrvnm is highly imbalanced (93.7%)Imbalance
bdngunderflrcnt is highly imbalanced (55.6%)Imbalance
cnstyarea is highly imbalanced (98.1%)Imbalance
svnsr is highly imbalanced (95.2%)Imbalance
plninsurstdt is highly imbalanced (95.2%)Imbalance
plninsurenddt is highly imbalanced (95.2%)Imbalance
maneipcnt is highly imbalanced (88.6%)Imbalance
playutscntdtl is highly imbalanced (95.2%)Imbalance
playfacilcnt is highly imbalanced (89.0%)Imbalance
multusnupsoyn is highly imbalanced (96.1%)Imbalance
stagear is highly imbalanced (95.2%)Imbalance
culwrkrsenm is highly imbalanced (95.2%)Imbalance
culphyedcobnm is highly imbalanced (89.0%)Imbalance
geicpfacilen is highly imbalanced (95.2%)Imbalance
balhansilyn is highly imbalanced (95.3%)Imbalance
bcfacilen is highly imbalanced (95.2%)Imbalance
insurorgnm is highly imbalanced (98.1%)Imbalance
insurstdt is highly imbalanced (95.2%)Imbalance
insurenddt is highly imbalanced (95.2%)Imbalance
afc is highly imbalanced (95.2%)Imbalance
useunderendflr is highly imbalanced (64.5%)Imbalance
useunderstflr is highly imbalanced (63.4%)Imbalance
shpinfo is highly imbalanced (95.2%)Imbalance
shpcnt is highly imbalanced (95.2%)Imbalance
shptottons is highly imbalanced (95.2%)Imbalance
infoben is highly imbalanced (95.2%)Imbalance
wmeipcnt is highly imbalanced (87.7%)Imbalance
engstntrnmnm is highly imbalanced (97.4%)Imbalance
engstntrnmaddr is highly imbalanced (97.1%)Imbalance
yoksilcnt is highly imbalanced (77.5%)Imbalance
dispenen is highly imbalanced (95.2%)Imbalance
capt is highly imbalanced (96.8%)Imbalance
mnfactreartclcn is highly imbalanced (95.2%)Imbalance
cndpermstymd is highly imbalanced (96.8%)Imbalance
cndpermntwhy is highly imbalanced (95.2%)Imbalance
cndpermendymd is highly imbalanced (96.8%)Imbalance
chaircnt is highly imbalanced (67.2%)Imbalance
nearenvnm is highly imbalanced (94.8%)Imbalance
jisgnumlay is highly imbalanced (95.4%)Imbalance
regnsenm is highly imbalanced (92.0%)Imbalance
undernumlay is highly imbalanced (96.4%)Imbalance
totnumlay is highly imbalanced (95.2%)Imbalance
meetsamtimesygstf is highly imbalanced (95.2%)Imbalance
sitepostno has 298 (3.5%) missing valuesMissing
rdnwhladdr has 2549 (30.1%) missing valuesMissing
dcbymd has 4623 (54.6%) missing valuesMissing
x has 385 (4.5%) missing valuesMissing
y has 388 (4.6%) missing valuesMissing
facilscp has 8173 (96.6%) missing valuesMissing
facilar has 8173 (96.6%) missing valuesMissing
yangsilcnt has 900 (10.6%) missing valuesMissing
skey is an unsupported type, check if it needs cleaning or further analysisUnsupported
rdnpostno is an unsupported type, check if it needs cleaning or further analysisUnsupported
apvpermymd is an unsupported type, check if it needs cleaning or further analysisUnsupported
x is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 16:36:20.683639
Analysis finished2024-04-16 16:36:23.205641
Duration2.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.3 KiB

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3318883.1
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.5 KiB
2024-04-17T01:36:23.247765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13290000
median3320000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation42879.712
Coefficient of variation (CV)0.012919922
Kurtosis-0.97658066
Mean3318883.1
Median Absolute Deviation (MAD)30000
Skewness0.26692497
Sum2.808107 × 1010
Variance1.8386697 × 109
MonotonicityNot monotonic
2024-04-17T01:36:23.339323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1131
13.4%
3290000 1059
12.5%
3300000 893
10.6%
3390000 688
8.1%
3270000 653
 
7.7%
3320000 578
 
6.8%
3380000 493
 
5.8%
3250000 478
 
5.6%
3260000 405
 
4.8%
3370000 383
 
4.5%
Other values (6) 1700
20.1%
ValueCountFrequency (%)
3250000 478
5.6%
3260000 405
 
4.8%
3270000 653
7.7%
3280000 362
 
4.3%
3290000 1059
12.5%
3300000 893
10.6%
3310000 284
 
3.4%
3320000 578
6.8%
3330000 1131
13.4%
3340000 358
 
4.2%
ValueCountFrequency (%)
3400000 206
 
2.4%
3390000 688
8.1%
3380000 493
5.8%
3370000 383
 
4.5%
3360000 137
 
1.6%
3350000 353
 
4.2%
3340000 358
 
4.2%
3330000 1131
13.4%
3320000 578
6.8%
3310000 284
 
3.4%

mgtno
Text

Distinct4192
Distinct (%)49.5%
Missing3
Missing (%)< 0.1%
Memory size66.3 KiB
2024-04-17T01:36:23.515167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.919868
Min length20

Characters and Unicode

Total characters185464
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

Unique118 ?
Unique (%)1.4%

Sample

1st row3250000-201-2017-00002
2nd row3250000-201-2014-00001
3rd row3250000-214-2017-00003
4th row3250000-201-1971-00116
5th row3250000-201-2012-00005
ValueCountFrequency (%)
cdfi2262212019000001 15
 
0.2%
cdfi2262212018000001 12
 
0.1%
cdfi2262212015000001 12
 
0.1%
cdfi2262212015000002 11
 
0.1%
cdfi2262212016000001 11
 
0.1%
cdfi2262212017000001 11
 
0.1%
cdfi2262212016000002 10
 
0.1%
cdfi2262212020000001 10
 
0.1%
cdfi2262212017000002 9
 
0.1%
cdfi2260032020000001 9
 
0.1%
Other values (4182) 8351
98.7%
2024-04-17T01:36:23.833192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71424
38.5%
- 24366
 
13.1%
1 20021
 
10.8%
2 19792
 
10.7%
3 18187
 
9.8%
9 10160
 
5.5%
8 4969
 
2.7%
7 4871
 
2.6%
6 3680
 
2.0%
4 3599
 
1.9%
Other values (5) 4395
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 159742
86.1%
Dash Punctuation 24366
 
13.1%
Uppercase Letter 1356
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71424
44.7%
1 20021
 
12.5%
2 19792
 
12.4%
3 18187
 
11.4%
9 10160
 
6.4%
8 4969
 
3.1%
7 4871
 
3.0%
6 3680
 
2.3%
4 3599
 
2.3%
5 3039
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 339
25.0%
D 339
25.0%
F 339
25.0%
I 339
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24366
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 184108
99.3%
Latin 1356
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 71424
38.8%
- 24366
 
13.2%
1 20021
 
10.9%
2 19792
 
10.8%
3 18187
 
9.9%
9 10160
 
5.5%
8 4969
 
2.7%
7 4871
 
2.6%
6 3680
 
2.0%
4 3599
 
2.0%
Latin
ValueCountFrequency (%)
C 339
25.0%
D 339
25.0%
F 339
25.0%
I 339
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 185464
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 71424
38.5%
- 24366
 
13.1%
1 20021
 
10.8%
2 19792
 
10.7%
3 18187
 
9.8%
9 10160
 
5.5%
8 4969
 
2.7%
7 4871
 
2.6%
6 3680
 
2.0%
4 3599
 
1.9%
Other values (5) 4395
 
2.4%

opnsvcid
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
03_11_03_P
8122 
03_11_04_P
 
259
03_11_01_P
 
68
03_11_05_P
 
9
<NA>
 
3
Other values (2)
 
3

Length

Max length10
Median length10
Mean length9.9978733
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row03_11_03_P
2nd row03_11_03_P
3rd row03_11_03_P
4th row03_11_03_P
5th row03_11_03_P

Common Values

ValueCountFrequency (%)
03_11_03_P 8122
96.0%
03_11_04_P 259
 
3.1%
03_11_01_P 68
 
0.8%
03_11_05_P 9
 
0.1%
<NA> 3
 
< 0.1%
03_11_02_P 2
 
< 0.1%
03_11_06_P 1
 
< 0.1%

Length

2024-04-17T01:36:23.946412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:24.044774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8122
96.0%
03_11_04_p 259
 
3.1%
03_11_01_p 68
 
0.8%
03_11_05_p 9
 
0.1%
na 3
 
< 0.1%
03_11_02_p 2
 
< 0.1%
03_11_06_p 1
 
< 0.1%

updategbn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
I
8101 
U
 
360
180000000
 
3

Length

Max length9
Median length1
Mean length1.0028355
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 8101
95.7%
U 360
 
4.3%
180000000 3
 
< 0.1%

Length

2024-04-17T01:36:24.150220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:24.240218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 8101
95.7%
u 360
 
4.3%
180000000 3
 
< 0.1%
Distinct186
Distinct (%)2.2%
Missing3
Missing (%)< 0.1%
Memory size66.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-04-01 02:40:00
2024-04-17T01:36:24.335730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:36:24.464746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
7988 
숙박업
 
320
외국인관광도시민박업
 
86
관광숙박업
 
68
자동차야영장업
 
1

Length

Max length10
Median length4
Mean length4.0316635
Min length3

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> 7988
94.4%
숙박업 320
 
3.8%
외국인관광도시민박업 86
 
1.0%
관광숙박업 68
 
0.8%
자동차야영장업 1
 
< 0.1%
한옥체험업 1
 
< 0.1%

Length

2024-04-17T01:36:24.589393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:24.682089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7988
94.4%
숙박업 320
 
3.8%
외국인관광도시민박업 86
 
1.0%
관광숙박업 68
 
0.8%
자동차야영장업 1
 
< 0.1%
한옥체험업 1
 
< 0.1%

bplcnm
Text

Distinct3352
Distinct (%)39.6%
Missing3
Missing (%)< 0.1%
Memory size66.3 KiB
2024-04-17T01:36:24.946021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length36
Mean length5.1170074
Min length1

Characters and Unicode

Total characters43295
Distinct characters646
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique285 ?
Unique (%)3.4%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 칠구(K79)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 235
 
2.3%
모텔 192
 
1.9%
게스트하우스 120
 
1.2%
여관 82
 
0.8%
hotel 61
 
0.6%
부산 50
 
0.5%
house 50
 
0.5%
해운대 39
 
0.4%
여인숙 36
 
0.4%
36
 
0.4%
Other values (3441) 9146
91.0%
2024-04-17T01:36:25.316556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2907
 
6.7%
2018
 
4.7%
1791
 
4.1%
1790
 
4.1%
1603
 
3.7%
1492
 
3.4%
1309
 
3.0%
1277
 
2.9%
768
 
1.8%
714
 
1.6%
Other values (636) 27626
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36506
84.3%
Uppercase Letter 2327
 
5.4%
Space Separator 1603
 
3.7%
Lowercase Letter 1198
 
2.8%
Decimal Number 509
 
1.2%
Open Punctuation 498
 
1.2%
Close Punctuation 498
 
1.2%
Other Punctuation 104
 
0.2%
Dash Punctuation 28
 
0.1%
Letter Number 10
 
< 0.1%
Other values (4) 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2907
 
8.0%
2018
 
5.5%
1791
 
4.9%
1790
 
4.9%
1492
 
4.1%
1309
 
3.6%
1277
 
3.5%
768
 
2.1%
714
 
2.0%
622
 
1.7%
Other values (556) 21818
59.8%
Uppercase Letter
ValueCountFrequency (%)
E 248
 
10.7%
O 218
 
9.4%
H 202
 
8.7%
T 173
 
7.4%
S 168
 
7.2%
L 128
 
5.5%
A 128
 
5.5%
N 110
 
4.7%
U 102
 
4.4%
M 92
 
4.0%
Other values (16) 758
32.6%
Lowercase Letter
ValueCountFrequency (%)
e 195
16.3%
o 144
12.0%
s 102
8.5%
a 95
7.9%
n 91
 
7.6%
u 91
 
7.6%
t 82
 
6.8%
h 57
 
4.8%
l 54
 
4.5%
i 50
 
4.2%
Other values (16) 237
19.8%
Decimal Number
ValueCountFrequency (%)
2 122
24.0%
1 68
13.4%
5 63
12.4%
7 60
11.8%
9 54
10.6%
6 41
 
8.1%
0 36
 
7.1%
3 36
 
7.1%
4 19
 
3.7%
8 10
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 59
56.7%
& 25
24.0%
' 9
 
8.7%
, 6
 
5.8%
; 2
 
1.9%
2
 
1.9%
: 1
 
1.0%
Letter Number
ValueCountFrequency (%)
6
60.0%
4
40.0%
Math Symbol
ValueCountFrequency (%)
+ 4
66.7%
2
33.3%
Space Separator
ValueCountFrequency (%)
1603
100.0%
Open Punctuation
ValueCountFrequency (%)
( 498
100.0%
Close Punctuation
ValueCountFrequency (%)
) 498
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Other Symbol
ValueCountFrequency (%)
6
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36504
84.3%
Latin 3535
 
8.2%
Common 3248
 
7.5%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2907
 
8.0%
2018
 
5.5%
1791
 
4.9%
1790
 
4.9%
1492
 
4.1%
1309
 
3.6%
1277
 
3.5%
768
 
2.1%
714
 
2.0%
622
 
1.7%
Other values (552) 21816
59.8%
Latin
ValueCountFrequency (%)
E 248
 
7.0%
O 218
 
6.2%
H 202
 
5.7%
e 195
 
5.5%
T 173
 
4.9%
S 168
 
4.8%
o 144
 
4.1%
L 128
 
3.6%
A 128
 
3.6%
N 110
 
3.1%
Other values (44) 1821
51.5%
Common
ValueCountFrequency (%)
1603
49.4%
( 498
 
15.3%
) 498
 
15.3%
2 122
 
3.8%
1 68
 
2.1%
5 63
 
1.9%
7 60
 
1.8%
. 59
 
1.8%
9 54
 
1.7%
6 41
 
1.3%
Other values (15) 182
 
5.6%
Han
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36498
84.3%
ASCII 6768
 
15.6%
Number Forms 10
 
< 0.1%
None 10
 
< 0.1%
CJK 8
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2907
 
8.0%
2018
 
5.5%
1791
 
4.9%
1790
 
4.9%
1492
 
4.1%
1309
 
3.6%
1277
 
3.5%
768
 
2.1%
714
 
2.0%
622
 
1.7%
Other values (551) 21810
59.8%
ASCII
ValueCountFrequency (%)
1603
23.7%
( 498
 
7.4%
) 498
 
7.4%
E 248
 
3.7%
O 218
 
3.2%
H 202
 
3.0%
e 195
 
2.9%
T 173
 
2.6%
S 168
 
2.5%
o 144
 
2.1%
Other values (64) 2821
41.7%
Number Forms
ValueCountFrequency (%)
6
60.0%
4
40.0%
None
ValueCountFrequency (%)
6
60.0%
2
 
20.0%
2
 
20.0%
CJK
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%
Punctuation
ValueCountFrequency (%)
1
100.0%

sitepostno
Text

MISSING 

Distinct492
Distinct (%)6.0%
Missing298
Missing (%)3.5%
Memory size66.3 KiB
2024-04-17T01:36:25.556691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters48996
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

Unique19 ?
Unique (%)0.2%

Sample

1st row600045
2nd row600051
3rd row600092
4th row600806
5th row600012
ValueCountFrequency (%)
612821 317
 
3.9%
616801 254
 
3.1%
612040 206
 
2.5%
612847 182
 
2.2%
607833 175
 
2.1%
601829 145
 
1.8%
617807 136
 
1.7%
613828 128
 
1.6%
607831 126
 
1.5%
607842 114
 
1.4%
Other values (482) 6383
78.2%
2024-04-17T01:36:25.901133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9824
20.1%
1 8022
16.4%
0 7972
16.3%
8 7921
16.2%
2 4285
8.7%
4 3436
 
7.0%
7 2595
 
5.3%
3 2455
 
5.0%
9 1403
 
2.9%
5 951
 
1.9%
Other values (5) 132
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48864
99.7%
Other Letter 132
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9824
20.1%
1 8022
16.4%
0 7972
16.3%
8 7921
16.2%
2 4285
8.8%
4 3436
 
7.0%
7 2595
 
5.3%
3 2455
 
5.0%
9 1403
 
2.9%
5 951
 
1.9%
Other Letter
ValueCountFrequency (%)
44
33.3%
22
16.7%
22
16.7%
22
16.7%
22
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 48864
99.7%
Hangul 132
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9824
20.1%
1 8022
16.4%
0 7972
16.3%
8 7921
16.2%
2 4285
8.8%
4 3436
 
7.0%
7 2595
 
5.3%
3 2455
 
5.0%
9 1403
 
2.9%
5 951
 
1.9%
Hangul
ValueCountFrequency (%)
44
33.3%
22
16.7%
22
16.7%
22
16.7%
22
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48864
99.7%
Hangul 132
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9824
20.1%
1 8022
16.4%
0 7972
16.3%
8 7921
16.2%
2 4285
8.8%
4 3436
 
7.0%
7 2595
 
5.3%
3 2455
 
5.0%
9 1403
 
2.9%
5 951
 
1.9%
Hangul
ValueCountFrequency (%)
44
33.3%
22
16.7%
22
16.7%
22
16.7%
22
16.7%
Distinct4038
Distinct (%)47.7%
Missing5
Missing (%)0.1%
Memory size66.3 KiB
2024-04-17T01:36:26.187258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length45
Mean length23.612838
Min length13

Characters and Unicode

Total characters199741
Distinct characters308
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique241 ?
Unique (%)2.8%

Sample

1st row부산광역시 중구 남포동5가 8-1번지
2nd row부산광역시 중구 창선동1가 12-1번지
3rd row부산광역시 중구 대청동2가 23-3번지
4th row부산광역시 중구 부평동2가 24-3번지
5th row부산광역시 중구 중앙동2가 52-2번지
ValueCountFrequency (%)
부산광역시 8459
23.5%
해운대구 1131
 
3.1%
부산진구 1059
 
2.9%
동래구 893
 
2.5%
t통b반 868
 
2.4%
사상구 688
 
1.9%
동구 653
 
1.8%
온천동 644
 
1.8%
북구 582
 
1.6%
부전동 503
 
1.4%
Other values (4214) 20521
57.0%
2024-04-17T01:36:26.590426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35910
18.0%
10280
 
5.1%
10028
 
5.0%
9933
 
5.0%
8824
 
4.4%
8708
 
4.4%
1 8547
 
4.3%
8483
 
4.2%
8465
 
4.2%
8387
 
4.2%
Other values (298) 82176
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 114016
57.1%
Decimal Number 39609
 
19.8%
Space Separator 35910
 
18.0%
Dash Punctuation 7860
 
3.9%
Uppercase Letter 1782
 
0.9%
Other Punctuation 195
 
0.1%
Close Punctuation 124
 
0.1%
Open Punctuation 124
 
0.1%
Math Symbol 117
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10280
 
9.0%
10028
 
8.8%
9933
 
8.7%
8824
 
7.7%
8708
 
7.6%
8483
 
7.4%
8465
 
7.4%
8387
 
7.4%
8179
 
7.2%
1568
 
1.4%
Other values (262) 31161
27.3%
Uppercase Letter
ValueCountFrequency (%)
B 875
49.1%
T 869
48.8%
A 11
 
0.6%
K 6
 
0.3%
C 5
 
0.3%
S 3
 
0.2%
O 3
 
0.2%
E 2
 
0.1%
G 2
 
0.1%
M 2
 
0.1%
Other values (4) 4
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 8547
21.6%
2 5199
13.1%
3 4172
10.5%
4 4030
10.2%
5 3901
9.8%
0 3049
 
7.7%
6 3025
 
7.6%
7 2836
 
7.2%
8 2562
 
6.5%
9 2288
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 192
98.5%
. 2
 
1.0%
& 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
w 1
33.3%
i 1
33.3%
e 1
33.3%
Space Separator
ValueCountFrequency (%)
35910
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7860
100.0%
Close Punctuation
ValueCountFrequency (%)
) 124
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Math Symbol
ValueCountFrequency (%)
~ 117
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 114016
57.1%
Common 83939
42.0%
Latin 1786
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10280
 
9.0%
10028
 
8.8%
9933
 
8.7%
8824
 
7.7%
8708
 
7.6%
8483
 
7.4%
8465
 
7.4%
8387
 
7.4%
8179
 
7.2%
1568
 
1.4%
Other values (262) 31161
27.3%
Common
ValueCountFrequency (%)
35910
42.8%
1 8547
 
10.2%
- 7860
 
9.4%
2 5199
 
6.2%
3 4172
 
5.0%
4 4030
 
4.8%
5 3901
 
4.6%
0 3049
 
3.6%
6 3025
 
3.6%
7 2836
 
3.4%
Other values (8) 5410
 
6.4%
Latin
ValueCountFrequency (%)
B 875
49.0%
T 869
48.7%
A 11
 
0.6%
K 6
 
0.3%
C 5
 
0.3%
S 3
 
0.2%
O 3
 
0.2%
E 2
 
0.1%
G 2
 
0.1%
M 2
 
0.1%
Other values (8) 8
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 114016
57.1%
ASCII 85724
42.9%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35910
41.9%
1 8547
 
10.0%
- 7860
 
9.2%
2 5199
 
6.1%
3 4172
 
4.9%
4 4030
 
4.7%
5 3901
 
4.6%
0 3049
 
3.6%
6 3025
 
3.5%
7 2836
 
3.3%
Other values (25) 7195
 
8.4%
Hangul
ValueCountFrequency (%)
10280
 
9.0%
10028
 
8.8%
9933
 
8.7%
8824
 
7.7%
8708
 
7.6%
8483
 
7.4%
8465
 
7.4%
8387
 
7.4%
8179
 
7.2%
1568
 
1.4%
Other values (262) 31161
27.3%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Unsupported

REJECTED  UNSUPPORTED 

Missing11
Missing (%)0.1%
Memory size66.3 KiB

rdnwhladdr
Text

MISSING 

Distinct2998
Distinct (%)50.7%
Missing2549
Missing (%)30.1%
Memory size66.3 KiB
2024-04-17T01:36:26.902689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length58
Mean length27.821809
Min length5

Characters and Unicode

Total characters164566
Distinct characters369
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique288 ?
Unique (%)4.9%

Sample

1st row부산광역시 중구 구덕로 54-1 (남포동5가)
2nd row부산광역시 중구 광복로39번길 6 (창선동1가)
3rd row부산광역시 중구 광복로49번길 38 (대청동2가)
4th row부산광역시 중구 중구로23번길 34 (부평동2가)
5th row부산광역시 중구 중앙대로49번길 13 (중앙동2가)
ValueCountFrequency (%)
부산광역시 5914
 
19.2%
해운대구 913
 
3.0%
부산진구 725
 
2.3%
동래구 607
 
2.0%
사상구 515
 
1.7%
동구 488
 
1.6%
온천동 422
 
1.4%
수영구 391
 
1.3%
중구 388
 
1.3%
부전동 385
 
1.2%
Other values (2561) 20126
65.2%
2024-04-17T01:36:27.395002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24959
 
15.2%
7704
 
4.7%
7317
 
4.4%
6981
 
4.2%
6615
 
4.0%
6291
 
3.8%
1 6278
 
3.8%
6044
 
3.7%
5920
 
3.6%
) 5805
 
3.5%
Other values (359) 80652
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 97919
59.5%
Decimal Number 26681
 
16.2%
Space Separator 24959
 
15.2%
Close Punctuation 5805
 
3.5%
Open Punctuation 5805
 
3.5%
Dash Punctuation 1797
 
1.1%
Other Punctuation 1255
 
0.8%
Math Symbol 249
 
0.2%
Uppercase Letter 89
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7704
 
7.9%
7317
 
7.5%
6981
 
7.1%
6615
 
6.8%
6291
 
6.4%
6044
 
6.2%
5920
 
6.0%
5641
 
5.8%
3941
 
4.0%
3707
 
3.8%
Other values (317) 37758
38.6%
Uppercase Letter
ValueCountFrequency (%)
A 28
31.5%
B 19
21.3%
K 9
 
10.1%
O 5
 
5.6%
C 5
 
5.6%
S 4
 
4.5%
E 3
 
3.4%
U 2
 
2.2%
G 2
 
2.2%
F 2
 
2.2%
Other values (9) 10
 
11.2%
Decimal Number
ValueCountFrequency (%)
1 6278
23.5%
2 4102
15.4%
3 2990
11.2%
4 2270
 
8.5%
5 2134
 
8.0%
0 1914
 
7.2%
6 1889
 
7.1%
7 1834
 
6.9%
9 1690
 
6.3%
8 1580
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
b 1
25.0%
w 1
25.0%
e 1
25.0%
i 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 1245
99.2%
. 9
 
0.7%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
24959
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5805
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5805
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1797
100.0%
Math Symbol
ValueCountFrequency (%)
~ 249
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 97919
59.5%
Common 66551
40.4%
Latin 96
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7704
 
7.9%
7317
 
7.5%
6981
 
7.1%
6615
 
6.8%
6291
 
6.4%
6044
 
6.2%
5920
 
6.0%
5641
 
5.8%
3941
 
4.0%
3707
 
3.8%
Other values (317) 37758
38.6%
Latin
ValueCountFrequency (%)
A 28
29.2%
B 19
19.8%
K 9
 
9.4%
O 5
 
5.2%
C 5
 
5.2%
S 4
 
4.2%
3
 
3.1%
E 3
 
3.1%
U 2
 
2.1%
G 2
 
2.1%
Other values (14) 16
16.7%
Common
ValueCountFrequency (%)
24959
37.5%
1 6278
 
9.4%
) 5805
 
8.7%
( 5805
 
8.7%
2 4102
 
6.2%
3 2990
 
4.5%
4 2270
 
3.4%
5 2134
 
3.2%
0 1914
 
2.9%
6 1889
 
2.8%
Other values (8) 8405
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 97919
59.5%
ASCII 66644
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24959
37.5%
1 6278
 
9.4%
) 5805
 
8.7%
( 5805
 
8.7%
2 4102
 
6.2%
3 2990
 
4.5%
4 2270
 
3.4%
5 2134
 
3.2%
0 1914
 
2.9%
6 1889
 
2.8%
Other values (31) 8498
 
12.8%
Hangul
ValueCountFrequency (%)
7704
 
7.9%
7317
 
7.5%
6981
 
7.1%
6615
 
6.8%
6291
 
6.4%
6044
 
6.2%
5920
 
6.0%
5641
 
5.8%
3941
 
4.0%
3707
 
3.8%
Other values (317) 37758
38.6%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.3 KiB

dcbymd
Text

MISSING 

Distinct1334
Distinct (%)34.7%
Missing4623
Missing (%)54.6%
Memory size66.3 KiB
2024-04-17T01:36:27.641573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.95522
Min length4

Characters and Unicode

Total characters30556
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)0.8%

Sample

1st row20140310
2nd row20121231
3rd row20171120
4th row20171107
5th row20120514
ValueCountFrequency (%)
20041022 180
 
4.7%
20030122 64
 
1.7%
20120711 52
 
1.4%
폐업일자 43
 
1.1%
20021024 38
 
1.0%
20030305 26
 
0.7%
20030101 24
 
0.6%
20030227 22
 
0.6%
20051117 20
 
0.5%
20030123 18
 
0.5%
Other values (1324) 3354
87.3%
2024-04-17T01:36:28.031030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10235
33.5%
2 6415
21.0%
1 5518
18.1%
3 1428
 
4.7%
9 1398
 
4.6%
7 1187
 
3.9%
4 1118
 
3.7%
6 1077
 
3.5%
5 1061
 
3.5%
8 947
 
3.1%
Other values (4) 172
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30384
99.4%
Other Letter 172
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10235
33.7%
2 6415
21.1%
1 5518
18.2%
3 1428
 
4.7%
9 1398
 
4.6%
7 1187
 
3.9%
4 1118
 
3.7%
6 1077
 
3.5%
5 1061
 
3.5%
8 947
 
3.1%
Other Letter
ValueCountFrequency (%)
43
25.0%
43
25.0%
43
25.0%
43
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30384
99.4%
Hangul 172
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10235
33.7%
2 6415
21.1%
1 5518
18.2%
3 1428
 
4.7%
9 1398
 
4.6%
7 1187
 
3.9%
4 1118
 
3.7%
6 1077
 
3.5%
5 1061
 
3.5%
8 947
 
3.1%
Hangul
ValueCountFrequency (%)
43
25.0%
43
25.0%
43
25.0%
43
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30384
99.4%
Hangul 172
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10235
33.7%
2 6415
21.1%
1 5518
18.2%
3 1428
 
4.7%
9 1398
 
4.6%
7 1187
 
3.9%
4 1118
 
3.7%
6 1077
 
3.5%
5 1061
 
3.5%
8 947
 
3.1%
Hangul
ValueCountFrequency (%)
43
25.0%
43
25.0%
43
25.0%
43
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8412 
휴업시작일자
 
44
20201012
 
1
20200120
 
1
20160608
 
1
Other values (5)
 
5

Length

Max length8
Median length4
Mean length4.0141777
Min length4

Unique

Unique8 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8412
99.4%
휴업시작일자 44
 
0.5%
20201012 1
 
< 0.1%
20200120 1
 
< 0.1%
20160608 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20180719 1
 
< 0.1%
20201001 1
 
< 0.1%

Length

2024-04-17T01:36:28.162056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:28.278760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8412
99.4%
휴업시작일자 44
 
0.5%
20201012 1
 
< 0.1%
20200120 1
 
< 0.1%
20160608 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20180719 1
 
< 0.1%
20201001 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8412 
휴업종료일자
 
45
20220119
 
1
20170607
 
1
20180424
 
1
Other values (4)
 
4

Length

Max length8
Median length4
Mean length4.0139414
Min length4

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8412
99.4%
휴업종료일자 45
 
0.5%
20220119 1
 
< 0.1%
20170607 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20181231 1
 
< 0.1%
20211001 1
 
< 0.1%

Length

2024-04-17T01:36:28.418167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:28.523071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8412
99.4%
휴업종료일자 45
 
0.5%
20220119 1
 
< 0.1%
20170607 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20181231 1
 
< 0.1%
20211001 1
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
재개업일자
 
45

Length

Max length5
Median length4
Mean length4.0053166
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> 8419
99.5%
재개업일자 45
 
0.5%

Length

2024-04-17T01:36:28.632329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:28.714447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
재개업일자 45
 
0.5%

trdstatenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
01
4096 
02
3711 
영업/정상
431 
13
 
124
03
 
53
Other values (4)
 
49

Length

Max length5
Median length2
Mean length2.1541824
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
01 4096
48.4%
02 3711
43.8%
영업/정상 431
 
5.1%
13 124
 
1.5%
03 53
 
0.6%
폐업 39
 
0.5%
<NA> 6
 
0.1%
휴업 3
 
< 0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:36:28.802955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:28.907941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01 4096
48.4%
02 3711
43.8%
영업/정상 431
 
5.1%
13 124
 
1.5%
03 53
 
0.6%
폐업 39
 
0.5%
na 6
 
0.1%
휴업 3
 
< 0.1%
31 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
영업
4384 
폐업
3798 
영업중
 
270
휴업
 
8
<NA>
 
3

Length

Max length4
Median length2
Mean length2.032845
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4384
51.8%
폐업 3798
44.9%
영업중 270
 
3.2%
휴업 8
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:36:29.045255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:29.143178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4384
51.8%
폐업 3798
44.9%
영업중 270
 
3.2%
휴업 8
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing385
Missing (%)4.5%
Memory size66.3 KiB

y
Real number (ℝ)

MISSING 

Distinct3922
Distinct (%)48.6%
Missing388
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean186745.46
Minimum169998.58
Maximum209754.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.5 KiB
2024-04-17T01:36:29.494724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169998.58
5-th percentile178698.11
Q1182934.97
median186953.02
Q3189982.56
95-th percentile193849.19
Maximum209754.15
Range39755.577
Interquartile range (IQR)7047.5906

Descriptive statistics

Standard deviation5115.0861
Coefficient of variation (CV)0.027390685
Kurtosis0.081967835
Mean186745.46
Median Absolute Deviation (MAD)3606.025
Skewness0.10898411
Sum1.5081563 × 109
Variance26164106
MonotonicityNot monotonic
2024-04-17T01:36:29.662560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185933.100965604 16
 
0.2%
187092.852201 14
 
0.2%
176595.034934652 11
 
0.1%
187269.854013 8
 
0.1%
192327.468209 8
 
0.1%
186655.373923053 8
 
0.1%
186243.806655 8
 
0.1%
187863.015365939 7
 
0.1%
189143.147865081 7
 
0.1%
186685.231621 6
 
0.1%
Other values (3912) 7983
94.3%
(Missing) 388
 
4.6%
ValueCountFrequency (%)
169998.576608 2
< 0.1%
171461.496152 2
< 0.1%
174251.232048 2
< 0.1%
174413.752458 1
< 0.1%
174599.932466 2
< 0.1%
174999.02898 2
< 0.1%
175045.348943 2
< 0.1%
175046.263792 2
< 0.1%
175057.331511 2
< 0.1%
175075.261586 2
< 0.1%
ValueCountFrequency (%)
209754.153703 1
< 0.1%
207516.984282 2
< 0.1%
207378.835702 1
< 0.1%
206172.903942 2
< 0.1%
206065.80538 2
< 0.1%
205949.336131 2
< 0.1%
205793.809975 2
< 0.1%
205774.280535 2
< 0.1%
205756.904836 2
< 0.1%
205755.902784 2
< 0.1%

lastmodts
Real number (ℝ)

Distinct3659
Distinct (%)43.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0130937 × 1013
Minimum1.9990211 × 1013
Maximum2.021033 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.5 KiB
2024-04-17T01:36:29.805573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0011004 × 1013
Q12.0060509 × 1013
median2.0171124 × 1013
Q32.0180501 × 1013
95-th percentile2.0190322 × 1013
Maximum2.021033 × 1013
Range2.2011917 × 1011
Interquartile range (IQR)1.1999217 × 1011

Descriptive statistics

Standard deviation6.6502595 × 1010
Coefficient of variation (CV)0.0033035022
Kurtosis-0.93484127
Mean2.0130937 × 1013
Median Absolute Deviation (MAD)9.6840033 × 109
Skewness-0.83556427
Sum1.7032786 × 1017
Variance4.4225951 × 1021
MonotonicityNot monotonic
2024-04-17T01:36:29.939013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19990428000000 62
 
0.7%
20040902000000 60
 
0.7%
19990920000000 60
 
0.7%
20030122000000 58
 
0.7%
20040203000000 50
 
0.6%
20070531000000 36
 
0.4%
20030414000000 36
 
0.4%
20030329000000 32
 
0.4%
20020515000000 32
 
0.4%
19990308000000 32
 
0.4%
Other values (3649) 8003
94.6%
ValueCountFrequency (%)
19990211000000 2
 
< 0.1%
19990218000000 20
0.2%
19990223000000 2
 
< 0.1%
19990225000000 6
 
0.1%
19990302000000 4
 
< 0.1%
19990303000000 18
0.2%
19990308000000 32
0.4%
19990309000000 6
 
0.1%
19990310000000 2
 
< 0.1%
19990315000000 2
 
< 0.1%
ValueCountFrequency (%)
20210330174734 2
< 0.1%
20210330150908 2
< 0.1%
20210330144645 2
< 0.1%
20210330110806 2
< 0.1%
20210330100929 2
< 0.1%
20210329164925 2
< 0.1%
20210329163453 2
< 0.1%
20210329160912 2
< 0.1%
20210329160901 2
< 0.1%
20210329160854 2
< 0.1%

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
여관업
5277 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
481
일반호텔
 
419
Other values (4)
622 

Length

Max length8
Median length3
Mean length3.6930529
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반호텔
2nd row일반호텔
3rd row숙박업(생활)
4th row여관업
5th row숙박업 기타

Common Values

ValueCountFrequency (%)
여관업 5277
62.3%
여인숙업 1076
 
12.7%
숙박업 기타 589
 
7.0%
숙박업(생활) 481
 
5.7%
일반호텔 419
 
5.0%
<NA> 322
 
3.8%
관광호텔 269
 
3.2%
업태구분명 22
 
0.3%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:36:30.052615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:30.151734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5277
58.3%
여인숙업 1076
 
11.9%
숙박업 589
 
6.5%
기타 589
 
6.5%
숙박업(생활 481
 
5.3%
일반호텔 419
 
4.6%
na 322
 
3.6%
관광호텔 269
 
3.0%
업태구분명 22
 
0.2%
휴양콘도미니엄업 9
 
0.1%
Distinct101
Distinct (%)1.2%
Missing78
Missing (%)0.9%
Memory size66.3 KiB
2024-04-17T01:36:30.389848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.980205
Min length4

Characters and Unicode

Total characters100466
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

Unique21 ?
Unique (%)0.3%

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 8198
95.1%
051 157
 
1.8%
전화번호 9
 
0.1%
070 6
 
0.1%
645 4
 
< 0.1%
741 4
 
< 0.1%
802 4
 
< 0.1%
7779 3
 
< 0.1%
806 3
 
< 0.1%
464 3
 
< 0.1%
Other values (129) 231
 
2.7%
2024-04-17T01:36:30.764409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24895
24.8%
2 16536
16.5%
3 16494
16.4%
- 16412
16.3%
0 8528
 
8.5%
5 8507
 
8.5%
4 8340
 
8.3%
240
 
0.2%
7 159
 
0.2%
8 126
 
0.1%
Other values (6) 229
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83778
83.4%
Dash Punctuation 16412
 
16.3%
Space Separator 240
 
0.2%
Other Letter 36
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24895
29.7%
2 16536
19.7%
3 16494
19.7%
0 8528
 
10.2%
5 8507
 
10.2%
4 8340
 
10.0%
7 159
 
0.2%
8 126
 
0.2%
6 115
 
0.1%
9 78
 
0.1%
Other Letter
ValueCountFrequency (%)
9
25.0%
9
25.0%
9
25.0%
9
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 16412
100.0%
Space Separator
ValueCountFrequency (%)
240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 100430
> 99.9%
Hangul 36
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24895
24.8%
2 16536
16.5%
3 16494
16.4%
- 16412
16.3%
0 8528
 
8.5%
5 8507
 
8.5%
4 8340
 
8.3%
240
 
0.2%
7 159
 
0.2%
8 126
 
0.1%
Other values (2) 193
 
0.2%
Hangul
ValueCountFrequency (%)
9
25.0%
9
25.0%
9
25.0%
9
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100430
> 99.9%
Hangul 36
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24895
24.8%
2 16536
16.5%
3 16494
16.4%
- 16412
16.3%
0 8528
 
8.5%
5 8507
 
8.5%
4 8340
 
8.3%
240
 
0.2%
7 159
 
0.2%
8 126
 
0.1%
Other values (2) 193
 
0.2%
Hangul
ValueCountFrequency (%)
9
25.0%
9
25.0%
9
25.0%
9
25.0%

stroomcnt
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8313 
객실수
 
36
1
 
31
2
 
27
3
 
19
Other values (20)
 
38

Length

Max length4
Median length4
Mean length3.9581758
Min length1

Unique

Unique12 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8313
98.2%
객실수 36
 
0.4%
1 31
 
0.4%
2 27
 
0.3%
3 19
 
0.2%
7 5
 
0.1%
6 5
 
0.1%
5 3
 
< 0.1%
11 3
 
< 0.1%
49 3
 
< 0.1%
Other values (15) 19
 
0.2%

Length

2024-04-17T01:36:30.898987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8313
98.2%
객실수 36
 
0.4%
1 31
 
0.4%
2 27
 
0.3%
3 19
 
0.2%
7 5
 
0.1%
6 5
 
0.1%
5 3
 
< 0.1%
11 3
 
< 0.1%
49 3
 
< 0.1%
Other values (15) 19
 
0.2%

bdngownsenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
6475 
자가
1175 
임대
773 
건물소유구분명
 
41

Length

Max length7
Median length4
Mean length3.5542297
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6475
76.5%
자가 1175
 
13.9%
임대 773
 
9.1%
건물소유구분명 41
 
0.5%

Length

2024-04-17T01:36:31.002393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:31.135740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6475
76.5%
자가 1175
 
13.9%
임대 773
 
9.1%
건물소유구분명 41
 
0.5%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8265 
단독주택
 
66
아파트
 
54
건물용도명
 
34
숙박시설
 
16
Other values (6)
 
29

Length

Max length15
Median length4
Mean length4.0042533
Min length2

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> 8265
97.6%
단독주택 66
 
0.8%
아파트 54
 
0.6%
건물용도명 34
 
0.4%
숙박시설 16
 
0.2%
다세대주택 12
 
0.1%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 주택(공동주택적용) 4
 
< 0.1%
호텔 3
 
< 0.1%

Length

2024-04-17T01:36:31.236056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8265
97.6%
단독주택 66
 
0.8%
아파트 54
 
0.6%
건물용도명 34
 
0.4%
숙박시설 16
 
0.2%
다세대주택 12
 
0.1%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 4
 
< 0.1%
주택(공동주택적용 4
 
< 0.1%
Other values (2) 4
 
< 0.1%

bdngjisgflrcnt
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
0
2555 
<NA>
1658 
4
859 
3
751 
5
587 
Other values (30)
2054 

Length

Max length6
Median length1
Mean length1.6444943
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row16
2nd row8
3rd row5
4th row<NA>
5th row5

Common Values

ValueCountFrequency (%)
0 2555
30.2%
<NA> 1658
19.6%
4 859
 
10.1%
3 751
 
8.9%
5 587
 
6.9%
2 423
 
5.0%
8 319
 
3.8%
6 303
 
3.6%
7 300
 
3.5%
9 195
 
2.3%
Other values (25) 514
 
6.1%

Length

2024-04-17T01:36:31.338147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2555
30.2%
na 1658
19.6%
4 859
 
10.1%
3 751
 
8.9%
5 587
 
6.9%
2 423
 
5.0%
8 319
 
3.8%
6 303
 
3.6%
7 300
 
3.5%
9 195
 
2.3%
Other values (25) 514
 
6.1%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
0
4442 
<NA>
2224 
1
1479 
2
 
193
4
 
36
Other values (9)
 
90

Length

Max length6
Median length1
Mean length1.8025756
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row4
3rd row1
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 4442
52.5%
<NA> 2224
26.3%
1 1479
 
17.5%
2 193
 
2.3%
4 36
 
0.4%
3 26
 
0.3%
건물지하층수 23
 
0.3%
5 17
 
0.2%
8 6
 
0.1%
6 4
 
< 0.1%
Other values (4) 14
 
0.2%

Length

2024-04-17T01:36:31.435447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4442
52.5%
na 2224
26.3%
1 1481
 
17.5%
2 193
 
2.3%
4 36
 
0.4%
3 26
 
0.3%
건물지하층수 23
 
0.3%
5 17
 
0.2%
8 6
 
0.1%
6 4
 
< 0.1%
Other values (3) 12
 
0.1%

cnstyarea
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8405 
건축연면적
 
42
2282
 
3
20571
 
3
72
 
1
Other values (10)
 
10

Length

Max length5
Median length4
Mean length4.0041352
Min length2

Unique

Unique11 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8405
99.3%
건축연면적 42
 
0.5%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
72 1
 
< 0.1%
39 1
 
< 0.1%
85 1
 
< 0.1%
437 1
 
< 0.1%
132 1
 
< 0.1%
352 1
 
< 0.1%
Other values (5) 5
 
0.1%

Length

2024-04-17T01:36:31.540239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8405
99.3%
건축연면적 42
 
0.5%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
72 1
 
< 0.1%
39 1
 
< 0.1%
85 1
 
< 0.1%
437 1
 
< 0.1%
132 1
 
< 0.1%
352 1
 
< 0.1%
Other values (5) 5
 
0.1%

svnsr
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
기념품종류
 
45

Length

Max length5
Median length4
Mean length4.0053166
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> 8419
99.5%
기념품종류 45
 
0.5%

Length

2024-04-17T01:36:31.637023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:31.718202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
기념품종류 45
 
0.5%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
기획여행보험시작일자
 
45

Length

Max length10
Median length4
Mean length4.0318998
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> 8419
99.5%
기획여행보험시작일자 45
 
0.5%

Length

2024-04-17T01:36:31.811564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:31.900742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
기획여행보험시작일자 45
 
0.5%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
기획여행보험종료일자
 
45

Length

Max length10
Median length4
Mean length4.0318998
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> 8419
99.5%
기획여행보험종료일자 45
 
0.5%

Length

2024-04-17T01:36:32.015041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:32.120646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
기획여행보험종료일자 45
 
0.5%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
7913 
0
 
489
남성종사자수
 
35
1
 
10
3
 
4
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.8254962
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7913
93.5%
0 489
 
5.8%
남성종사자수 35
 
0.4%
1 10
 
0.1%
3 4
 
< 0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
35 1
 
< 0.1%

Length

2024-04-17T01:36:32.234797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7913
93.5%
0 489
 
5.8%
남성종사자수 35
 
0.4%
1 10
 
0.1%
3 4
 
< 0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
35 1
 
< 0.1%

playutscntdtl
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
놀이기구수내역
 
45

Length

Max length7
Median length4
Mean length4.0159499
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> 8419
99.5%
놀이기구수내역 45
 
0.5%

Length

2024-04-17T01:36:32.361652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:32.466951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
놀이기구수내역 45
 
0.5%

playfacilcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
N
8195 
<NA>
 
241
놀이시설수
 
25
Y
 
3

Length

Max length5
Median length1
Mean length1.0972353
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8195
96.8%
<NA> 241
 
2.8%
놀이시설수 25
 
0.3%
Y 3
 
< 0.1%

Length

2024-04-17T01:36:32.587056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:32.705529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8195
96.8%
na 241
 
2.8%
놀이시설수 25
 
0.3%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
N
8393 
<NA>
 
58
Y
 
9
 
4

Length

Max length4
Median length1
Mean length1.0205577
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8393
99.2%
<NA> 58
 
0.7%
Y 9
 
0.1%
4
 
< 0.1%

Length

2024-04-17T01:36:32.827797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:32.958995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8393
99.2%
na 58
 
0.7%
y 9
 
0.1%
4
 
< 0.1%

stagear
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
무대면적
 
45

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> 8419
99.5%
무대면적 45
 
0.5%

Length

2024-04-17T01:36:33.085249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:33.223330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
무대면적 45
 
0.5%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
문화사업자구분명
 
45

Length

Max length8
Median length4
Mean length4.0212665
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> 8419
99.5%
문화사업자구분명 45
 
0.5%

Length

2024-04-17T01:36:33.339617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:33.460234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
문화사업자구분명 45
 
0.5%

culphyedcobnm
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8102 
외국인관광 도시민박업
 
259
관광숙박업
 
68
문화체육업종명
 
23
자동차야영장업
 
9
Other values (2)
 
3

Length

Max length11
Median length4
Mean length4.2339319
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> 8102
95.7%
외국인관광 도시민박업 259
 
3.1%
관광숙박업 68
 
0.8%
문화체육업종명 23
 
0.3%
자동차야영장업 9
 
0.1%
관광펜션업 2
 
< 0.1%
한옥체험업 1
 
< 0.1%

Length

2024-04-17T01:36:33.571239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:33.712962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8102
92.9%
외국인관광 259
 
3.0%
도시민박업 259
 
3.0%
관광숙박업 68
 
0.8%
문화체육업종명 23
 
0.3%
자동차야영장업 9
 
0.1%
관광펜션업 2
 
< 0.1%
한옥체험업 1
 
< 0.1%

geicpfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
 
45

Length

Max length4
Median length4
Mean length3.9840501
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> 8419
99.5%
45
 
0.5%

Length

2024-04-17T01:36:33.873655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:34.011235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
45
 
0.5%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
N
8378 
<NA>
 
58
Y
 
24
 
4

Length

Max length4
Median length1
Mean length1.0205577
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8378
99.0%
<NA> 58
 
0.7%
Y 24
 
0.3%
4
 
< 0.1%

Length

2024-04-17T01:36:34.193819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:34.301453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8378
99.0%
na 58
 
0.7%
y 24
 
0.3%
4
 
< 0.1%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
 
45

Length

Max length4
Median length4
Mean length3.9840501
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> 8419
99.5%
45
 
0.5%

Length

2024-04-17T01:36:34.398252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:34.480643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
45
 
0.5%

insurorgnm
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8398 
보험기관명
 
44
객실수/수용인원 : 2개/ 6명
 
2
객실 1개/4인
 
1
영업배상책임보험 증권
 
1
Other values (18)
 
18

Length

Max length22
Median length4
Mean length4.0245747
Min length2

Unique

Unique20 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8398
99.2%
보험기관명 44
 
0.5%
객실수/수용인원 : 2개/ 6명 2
 
< 0.1%
객실 1개/4인 1
 
< 0.1%
영업배상책임보험 증권 1
 
< 0.1%
객실수/수용인원 : 3/8 1
 
< 0.1%
객실수/수용인원:2/6 1
 
< 0.1%
객실수/수용인원: 3/8 1
 
< 0.1%
객실수/수용인원:2/3 1
 
< 0.1%
객실수/수용인원:2/5 1
 
< 0.1%
Other values (13) 13
 
0.2%

Length

2024-04-17T01:36:34.588083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8398
99.0%
보험기관명 44
 
0.5%
객실수/수용인원 6
 
0.1%
5
 
0.1%
2개 2
 
< 0.1%
6명 2
 
< 0.1%
3/8 2
 
< 0.1%
농협손해보험주식회사 1
 
< 0.1%
3실 1
 
< 0.1%
일반과세자(숙박업 1
 
< 0.1%
Other values (19) 19
 
0.2%

insurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
보험시작일자
 
45

Length

Max length6
Median length4
Mean length4.0106333
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> 8419
99.5%
보험시작일자 45
 
0.5%

Length

2024-04-17T01:36:34.701314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:34.791935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
보험시작일자 45
 
0.5%

insurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
보험종료일자
 
45

Length

Max length6
Median length4
Mean length4.0106333
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> 8419
99.5%
보험종료일자 45
 
0.5%

Length

2024-04-17T01:36:34.886149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:34.973103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
보험종료일자 45
 
0.5%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
부대시설내역
 
45

Length

Max length6
Median length4
Mean length4.0106333
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> 8419
99.5%
부대시설내역 45
 
0.5%

Length

2024-04-17T01:36:35.065988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:35.176159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
부대시설내역 45
 
0.5%

usejisgendflr
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
2685 
0
1979 
4
751 
3
648 
5
465 
Other values (30)
1936 

Length

Max length6
Median length1
Mean length2.0042533
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row14
2nd row8
3rd row3
4th row<NA>
5th row2

Common Values

ValueCountFrequency (%)
<NA> 2685
31.7%
0 1979
23.4%
4 751
 
8.9%
3 648
 
7.7%
5 465
 
5.5%
6 415
 
4.9%
2 387
 
4.6%
7 264
 
3.1%
8 253
 
3.0%
9 187
 
2.2%
Other values (25) 430
 
5.1%

Length

2024-04-17T01:36:35.290582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2685
31.7%
0 1979
23.4%
4 751
 
8.9%
3 648
 
7.7%
5 465
 
5.5%
6 415
 
4.9%
2 387
 
4.6%
7 264
 
3.1%
8 253
 
3.0%
9 187
 
2.2%
Other values (25) 430
 
5.1%

useunderendflr
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
0
4628 
<NA>
3600 
1
 
180
사용끝지하층
 
25
2
 
16
Other values (5)
 
15

Length

Max length6
Median length1
Mean length2.2911153
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4628
54.7%
<NA> 3600
42.5%
1 180
 
2.1%
사용끝지하층 25
 
0.3%
2 16
 
0.2%
4 4
 
< 0.1%
7 4
 
< 0.1%
3 4
 
< 0.1%
10 2
 
< 0.1%
19 1
 
< 0.1%

Length

2024-04-17T01:36:35.425566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:35.565377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4628
54.7%
na 3600
42.5%
1 180
 
2.1%
사용끝지하층 25
 
0.3%
2 16
 
0.2%
4 4
 
< 0.1%
7 4
 
< 0.1%
3 4
 
< 0.1%
10 2
 
< 0.1%
19 1
 
< 0.1%

usejisgstflr
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
0
2472 
1
1898 
<NA>
1857 
2
978 
3
498 
Other values (15)
761 

Length

Max length7
Median length1
Mean length1.6815926
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row4
2nd row6
3rd row1
4th row<NA>
5th row2

Common Values

ValueCountFrequency (%)
0 2472
29.2%
1 1898
22.4%
<NA> 1857
21.9%
2 978
 
11.6%
3 498
 
5.9%
4 305
 
3.6%
5 196
 
2.3%
6 69
 
0.8%
7 59
 
0.7%
8 34
 
0.4%
Other values (10) 98
 
1.2%

Length

2024-04-17T01:36:35.686702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2472
29.2%
1 1898
22.4%
na 1857
21.9%
2 978
 
11.6%
3 498
 
5.9%
4 305
 
3.6%
5 196
 
2.3%
6 69
 
0.8%
7 59
 
0.7%
8 34
 
0.4%
Other values (10) 98
 
1.2%

useunderstflr
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
0
5565 
<NA>
2649 
1
 
211
사용시작지하층
 
25
4
 
8
Other values (3)
 
6

Length

Max length7
Median length1
Mean length1.9566399
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5565
65.7%
<NA> 2649
31.3%
1 211
 
2.5%
사용시작지하층 25
 
0.3%
4 8
 
0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
2 2
 
< 0.1%

Length

2024-04-17T01:36:35.805204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:35.926328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5565
65.7%
na 2649
31.3%
1 211
 
2.5%
사용시작지하층 25
 
0.3%
4 8
 
0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
2 2
 
< 0.1%

shpinfo
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
선박제원
 
45

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> 8419
99.5%
선박제원 45
 
0.5%

Length

2024-04-17T01:36:36.043671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:36.153488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
선박제원 45
 
0.5%

shpcnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
선박척수
 
45

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> 8419
99.5%
선박척수 45
 
0.5%

Length

2024-04-17T01:36:36.271599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:36.353437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
선박척수 45
 
0.5%

shptottons
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
선박총톤수
 
45

Length

Max length5
Median length4
Mean length4.0053166
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> 8419
99.5%
선박총톤수 45
 
0.5%

Length

2024-04-17T01:36:36.446130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:36.539292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
선박총톤수 45
 
0.5%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
0
4968 
<NA>
3473 
세탁기수
 
23

Length

Max length4
Median length1
Mean length2.2391304
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4968
58.7%
<NA> 3473
41.0%
세탁기수 23
 
0.3%

Length

2024-04-17T01:36:36.961005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:37.048908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4968
58.7%
na 3473
41.0%
세탁기수 23
 
0.3%

facilscp
Text

MISSING 

Distinct139
Distinct (%)47.8%
Missing8173
Missing (%)96.6%
Memory size66.3 KiB
2024-04-17T01:36:37.300827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.766323
Min length2

Characters and Unicode

Total characters805
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)26.5%

Sample

1st row시설규모
2nd row시설규모
3rd row시설규모
4th row시설규모
5th row시설규모
ValueCountFrequency (%)
시설규모 25
 
8.6%
85 15
 
5.2%
46 7
 
2.4%
599 6
 
2.1%
60 6
 
2.1%
83 6
 
2.1%
63 5
 
1.7%
67 5
 
1.7%
84 4
 
1.4%
57 4
 
1.4%
Other values (129) 208
71.5%
2024-04-17T01:36:37.684762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 111
13.8%
5 81
10.1%
8 79
9.8%
2 69
8.6%
6 67
8.3%
4 63
7.8%
9 63
7.8%
7 62
7.7%
3 59
7.3%
0 51
6.3%
Other values (4) 100
12.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 705
87.6%
Other Letter 100
 
12.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 111
15.7%
5 81
11.5%
8 79
11.2%
2 69
9.8%
6 67
9.5%
4 63
8.9%
9 63
8.9%
7 62
8.8%
3 59
8.4%
0 51
7.2%
Other Letter
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 705
87.6%
Hangul 100
 
12.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 111
15.7%
5 81
11.5%
8 79
11.2%
2 69
9.8%
6 67
9.5%
4 63
8.9%
9 63
8.9%
7 62
8.8%
3 59
8.4%
0 51
7.2%
Hangul
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 705
87.6%
Hangul 100
 
12.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 111
15.7%
5 81
11.5%
8 79
11.2%
2 69
9.8%
6 67
9.5%
4 63
8.9%
9 63
8.9%
7 62
8.8%
3 59
8.4%
0 51
7.2%
Hangul
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%

facilar
Text

MISSING 

Distinct201
Distinct (%)69.1%
Missing8173
Missing (%)96.6%
Memory size66.3 KiB
2024-04-17T01:36:37.982444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.1237113
Min length2

Characters and Unicode

Total characters1491
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

Unique164 ?
Unique (%)56.4%

Sample

1st row시설면적
2nd row시설면적
3rd row시설면적
4th row시설면적
5th row시설면적
ValueCountFrequency (%)
시설면적 25
 
8.6%
45.5 6
 
2.1%
598.73 6
 
2.1%
62.58 4
 
1.4%
62.25 3
 
1.0%
337.46 3
 
1.0%
392.02 3
 
1.0%
210.42 3
 
1.0%
66.84 3
 
1.0%
545.44 3
 
1.0%
Other values (191) 232
79.7%
2024-04-17T01:36:38.406539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 242
16.2%
1 156
10.5%
8 139
9.3%
4 138
9.3%
5 116
7.8%
6 113
7.6%
2 111
7.4%
3 108
7.2%
9 103
6.9%
7 99
6.6%
Other values (5) 166
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1149
77.1%
Other Punctuation 242
 
16.2%
Other Letter 100
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 156
13.6%
8 139
12.1%
4 138
12.0%
5 116
10.1%
6 113
9.8%
2 111
9.7%
3 108
9.4%
9 103
9.0%
7 99
8.6%
0 66
5.7%
Other Letter
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%
Other Punctuation
ValueCountFrequency (%)
. 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1391
93.3%
Hangul 100
 
6.7%

Most frequent character per script

Common
ValueCountFrequency (%)
. 242
17.4%
1 156
11.2%
8 139
10.0%
4 138
9.9%
5 116
8.3%
6 113
8.1%
2 111
8.0%
3 108
7.8%
9 103
7.4%
7 99
7.1%
Hangul
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1391
93.3%
Hangul 100
 
6.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 242
17.4%
1 156
11.2%
8 139
10.0%
4 138
9.9%
5 116
8.3%
6 113
8.1%
2 111
8.0%
3 108
7.8%
9 103
7.4%
7 99
7.1%
Hangul
ValueCountFrequency (%)
25
25.0%
25
25.0%
25
25.0%
25
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
 
45

Length

Max length4
Median length4
Mean length3.9840501
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> 8419
99.5%
45
 
0.5%

Length

2024-04-17T01:36:38.526114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:38.612367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
45
 
0.5%

yangsilcnt
Text

MISSING 

Distinct148
Distinct (%)2.0%
Missing900
Missing (%)10.6%
Memory size66.3 KiB
2024-04-17T01:36:38.760381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7371761
Min length1

Characters and Unicode

Total characters13140
Distinct characters13
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

Unique14 ?
Unique (%)0.2%

Sample

1st row107
2nd row81
3rd row16
4th row7
5th row5
ValueCountFrequency (%)
0 1041
 
13.8%
10 437
 
5.8%
18 368
 
4.9%
12 318
 
4.2%
14 314
 
4.2%
15 302
 
4.0%
13 248
 
3.3%
19 244
 
3.2%
17 222
 
2.9%
16 219
 
2.9%
Other values (138) 3851
50.9%
2024-04-17T01:36:39.072872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3431
26.1%
0 1916
14.6%
2 1869
14.2%
3 1339
 
10.2%
4 1037
 
7.9%
5 821
 
6.2%
8 811
 
6.2%
6 631
 
4.8%
9 615
 
4.7%
7 601
 
4.6%
Other values (3) 69
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13071
99.5%
Other Letter 69
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3431
26.2%
0 1916
14.7%
2 1869
14.3%
3 1339
 
10.2%
4 1037
 
7.9%
5 821
 
6.3%
8 811
 
6.2%
6 631
 
4.8%
9 615
 
4.7%
7 601
 
4.6%
Other Letter
ValueCountFrequency (%)
23
33.3%
23
33.3%
23
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13071
99.5%
Hangul 69
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3431
26.2%
0 1916
14.7%
2 1869
14.3%
3 1339
 
10.2%
4 1037
 
7.9%
5 821
 
6.3%
8 811
 
6.2%
6 631
 
4.8%
9 615
 
4.7%
7 601
 
4.6%
Hangul
ValueCountFrequency (%)
23
33.3%
23
33.3%
23
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13071
99.5%
Hangul 69
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3431
26.2%
0 1916
14.7%
2 1869
14.3%
3 1339
 
10.2%
4 1037
 
7.9%
5 821
 
6.3%
8 811
 
6.2%
6 631
 
4.8%
9 615
 
4.7%
7 601
 
4.6%
Hangul
ValueCountFrequency (%)
23
33.3%
23
33.3%
23
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
7915 
0
 
494
여성종사자수
 
35
1
 
6
3
 
5
Other values (4)
 
9

Length

Max length6
Median length4
Mean length3.8264414
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7915
93.5%
0 494
 
5.8%
여성종사자수 35
 
0.4%
1 6
 
0.1%
3 5
 
0.1%
2 4
 
< 0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

Length

2024-04-17T01:36:39.181887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:39.281731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7915
93.5%
0 494
 
5.8%
여성종사자수 35
 
0.4%
1 6
 
0.1%
3 5
 
0.1%
2 4
 
< 0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

engstntrnmnm
Categorical

IMBALANCE 

Distinct45
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8363 
영문상호명
 
42
CheonghakSodam
 
3
Emerald ocean view
 
3
ocean house
 
3
Other values (40)
 
50

Length

Max length45
Median length4
Mean length4.0876654
Min length4

Unique

Unique34 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8363
98.8%
영문상호명 42
 
0.5%
CheonghakSodam 3
 
< 0.1%
Emerald ocean view 3
 
< 0.1%
ocean house 3
 
< 0.1%
DYD COZY HOUSE 3
 
< 0.1%
H-avenue Hotel Gwanganlihaebyeon 3
 
< 0.1%
Brown-dot Hotel Suyeong 3
 
< 0.1%
BUSAN HAPPY HOUSE 3
 
< 0.1%
PartyPartyRoomRoom 2
 
< 0.1%
Other values (35) 36
 
0.4%

Length

2024-04-17T01:36:39.399188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8363
97.8%
영문상호명 42
 
0.5%
house 29
 
0.3%
busan 9
 
0.1%
ocean 6
 
0.1%
hotel 6
 
0.1%
guest 5
 
0.1%
kim's 4
 
< 0.1%
happy 3
 
< 0.1%
suyeong 3
 
< 0.1%
Other values (54) 79
 
0.9%

engstntrnmaddr
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8366 
영문상호주소
 
42
Foreigner Tourism City home-stay Business
 
14
Guesthouse for Foreign Tourists
 
13
Guest House
 
4
Other values (15)
 
25

Length

Max length41
Median length4
Mean length4.1863185
Min length4

Unique

Unique9 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8366
98.8%
영문상호주소 42
 
0.5%
Foreigner Tourism City home-stay Business 14
 
0.2%
Guesthouse for Foreign Tourists 13
 
0.2%
Guest House 4
 
< 0.1%
Entertainment Business for foreigner only 3
 
< 0.1%
TOURIST ACCOMMODATION (hostel) 3
 
< 0.1%
TOURIST ACCOMMODATION 3
 
< 0.1%
Oversea Travel Business 3
 
< 0.1%
Entertainment Business for Foreigner only 2
 
< 0.1%
Other values (10) 11
 
0.1%

Length

2024-04-17T01:36:39.513546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8366
97.1%
영문상호주소 42
 
0.5%
business 22
 
0.3%
for 20
 
0.2%
foreigner 19
 
0.2%
foreign 19
 
0.2%
guesthouse 16
 
0.2%
tourists 16
 
0.2%
home-stay 15
 
0.2%
tourism 14
 
0.2%
Other values (18) 71
 
0.8%

yoksilcnt
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
0
5812 
<NA>
2441 
욕실수
 
23
15
 
16
12
 
14
Other values (28)
 
158

Length

Max length4
Median length1
Mean length1.890241
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5812
68.7%
<NA> 2441
28.8%
욕실수 23
 
0.3%
15 16
 
0.2%
12 14
 
0.2%
18 12
 
0.1%
10 12
 
0.1%
14 10
 
0.1%
22 10
 
0.1%
9 10
 
0.1%
Other values (23) 104
 
1.2%

Length

2024-04-17T01:36:39.620701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 5812
68.7%
na 2441
28.8%
욕실수 23
 
0.3%
15 16
 
0.2%
12 14
 
0.2%
18 12
 
0.1%
10 12
 
0.1%
14 10
 
0.1%
9 10
 
0.1%
8 10
 
0.1%
Other values (23) 104
 
1.2%

sntuptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
여관업
5277 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
481
일반호텔
 
419
Other values (4)
622 

Length

Max length8
Median length3
Mean length3.6930529
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반호텔
2nd row일반호텔
3rd row숙박업(생활)
4th row여관업
5th row숙박업 기타

Common Values

ValueCountFrequency (%)
여관업 5277
62.3%
여인숙업 1076
 
12.7%
숙박업 기타 589
 
7.0%
숙박업(생활) 481
 
5.7%
일반호텔 419
 
5.0%
<NA> 322
 
3.8%
관광호텔 269
 
3.2%
위생업태명 22
 
0.3%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:36:39.725607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:39.830876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5277
58.3%
여인숙업 1076
 
11.9%
숙박업 589
 
6.5%
기타 589
 
6.5%
숙박업(생활 481
 
5.3%
일반호텔 419
 
4.6%
na 322
 
3.6%
관광호텔 269
 
3.0%
위생업태명 22
 
0.2%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
 
45

Length

Max length4
Median length4
Mean length3.9840501
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> 8419
99.5%
45
 
0.5%

Length

2024-04-17T01:36:39.960984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:40.055567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
45
 
0.5%

capt
Categorical

IMBALANCE 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8341 
자본금
 
32
10000000
 
18
100000000
 
12
50000000
 
5
Other values (33)
 
56

Length

Max length10
Median length4
Mean length4.043242
Min length3

Unique

Unique20 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8341
98.5%
자본금 32
 
0.4%
10000000 18
 
0.2%
100000000 12
 
0.1%
50000000 5
 
0.1%
200000000 5
 
0.1%
20000000 5
 
0.1%
300000000 4
 
< 0.1%
12500000 3
 
< 0.1%
12000000 3
 
< 0.1%
Other values (28) 36
 
0.4%

Length

2024-04-17T01:36:40.170713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8341
98.5%
자본금 32
 
0.4%
10000000 18
 
0.2%
100000000 12
 
0.1%
50000000 5
 
0.1%
200000000 5
 
0.1%
20000000 5
 
0.1%
300000000 4
 
< 0.1%
12500000 3
 
< 0.1%
12000000 3
 
< 0.1%
Other values (28) 36
 
0.4%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
제작취급품목내용
 
45

Length

Max length8
Median length4
Mean length4.0212665
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> 8419
99.5%
제작취급품목내용 45
 
0.5%

Length

2024-04-17T01:36:40.308916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:40.419117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
제작취급품목내용 45
 
0.5%

cndpermstymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8417 
조건부허가시작일자
 
45
20180202
 
2

Length

Max length9
Median length4
Mean length4.0275284
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> 8417
99.4%
조건부허가시작일자 45
 
0.5%
20180202 2
 
< 0.1%

Length

2024-04-17T01:36:40.506182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:40.595138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8417
99.4%
조건부허가시작일자 45
 
0.5%
20180202 2
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
조건부허가신고사유
 
45

Length

Max length9
Median length4
Mean length4.0265832
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> 8419
99.5%
조건부허가신고사유 45
 
0.5%

Length

2024-04-17T01:36:40.696396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:40.784475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
조건부허가신고사유 45
 
0.5%

cndpermendymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8417 
조건부허가종료일자
 
45
20190202
 
2

Length

Max length9
Median length4
Mean length4.0275284
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> 8417
99.4%
조건부허가종료일자 45
 
0.5%
20190202 2
 
< 0.1%

Length

2024-04-17T01:36:40.875092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:40.964223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8417
99.4%
조건부허가종료일자 45
 
0.5%
20190202 2
 
< 0.1%

chaircnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
5321 
0
3115 
좌석수
 
23
6
 
1
12
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length2.8915406
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5321
62.9%
0 3115
36.8%
좌석수 23
 
0.3%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-17T01:36:41.073973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:41.192712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5321
62.9%
0 3115
36.8%
좌석수 23
 
0.3%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

nearenvnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8328 
주변환경명
 
41
주택가주변
 
30
아파트지역
 
29
기타
 
21
Other values (3)
 
15

Length

Max length8
Median length4
Mean length4.0139414
Min length2

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> 8328
98.4%
주변환경명 41
 
0.5%
주택가주변 30
 
0.4%
아파트지역 29
 
0.3%
기타 21
 
0.2%
학교정화(상대) 12
 
0.1%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-17T01:36:41.316570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:41.434811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8328
98.4%
주변환경명 41
 
0.5%
주택가주변 30
 
0.4%
아파트지역 29
 
0.3%
기타 21
 
0.2%
학교정화(상대 12
 
0.1%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대 1
 
< 0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8302 
2
 
31
지상층수
 
29
4
 
18
3
 
13
Other values (18)
 
71

Length

Max length4
Median length4
Mean length3.9569943
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> 8302
98.1%
2 31
 
0.4%
지상층수 29
 
0.3%
4 18
 
0.2%
3 13
 
0.2%
1 11
 
0.1%
5 8
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
19 6
 
0.1%
Other values (13) 32
 
0.4%

Length

2024-04-17T01:36:41.569589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8302
98.1%
2 31
 
0.4%
지상층수 29
 
0.3%
4 18
 
0.2%
3 13
 
0.2%
1 11
 
0.1%
5 8
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
19 6
 
0.1%
Other values (13) 32
 
0.4%

regnsenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8223 
일반주거지역
 
106
일반상업지역
 
35
지역구분명
 
31
주거지역
 
30
Other values (4)
 
39

Length

Max length6
Median length4
Mean length4.0411153
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> 8223
97.2%
일반주거지역 106
 
1.3%
일반상업지역 35
 
0.4%
지역구분명 31
 
0.4%
주거지역 30
 
0.4%
준주거지역 25
 
0.3%
상업지역 6
 
0.1%
자연녹지지역 5
 
0.1%
녹지지역 3
 
< 0.1%

Length

2024-04-17T01:36:41.686461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:41.804943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8223
97.2%
일반주거지역 106
 
1.3%
일반상업지역 35
 
0.4%
지역구분명 31
 
0.4%
주거지역 30
 
0.4%
준주거지역 25
 
0.3%
상업지역 6
 
0.1%
자연녹지지역 5
 
0.1%
녹지지역 3
 
< 0.1%

undernumlay
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8372 
지하층수
 
33
1
 
26
2
 
20
0
 
9
Other values (3)
 
4

Length

Max length4
Median length4
Mean length3.9790879
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> 8372
98.9%
지하층수 33
 
0.4%
1 26
 
0.3%
2 20
 
0.2%
0 9
 
0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-17T01:36:41.921785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:42.025540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8372
98.9%
지하층수 33
 
0.4%
1 26
 
0.3%
2 20
 
0.2%
0 9
 
0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%

totnumlay
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8286 
2
 
36
총층수
 
29
4
 
20
3
 
17
Other values (20)
 
76

Length

Max length4
Median length4
Mean length3.947897
Min length1

Unique

Unique8 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8286
97.9%
2 36
 
0.4%
총층수 29
 
0.3%
4 20
 
0.2%
3 17
 
0.2%
1 16
 
0.2%
5 11
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
11 6
 
0.1%
Other values (15) 29
 
0.3%

Length

2024-04-17T01:36:42.130801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8286
97.9%
2 36
 
0.4%
총층수 29
 
0.3%
4 20
 
0.2%
3 17
 
0.2%
1 16
 
0.2%
5 11
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
11 6
 
0.1%
Other values (15) 29
 
0.3%

abedcnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
0
4922 
<NA>
3517 
침대수
 
23
41
 
2

Length

Max length4
Median length1
Mean length2.2522448
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4922
58.2%
<NA> 3517
41.6%
침대수 23
 
0.3%
41 2
 
< 0.1%

Length

2024-04-17T01:36:42.228701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:42.321719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4922
58.2%
na 3517
41.6%
침대수 23
 
0.3%
41 2
 
< 0.1%

hanshilcnt
Categorical

Distinct48
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
0
3705 
<NA>
1463 
2
 
326
10
 
310
3
 
268
Other values (43)
2392 

Length

Max length4
Median length1
Mean length1.6743856
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3705
43.8%
<NA> 1463
 
17.3%
2 326
 
3.9%
10 310
 
3.7%
3 268
 
3.2%
1 262
 
3.1%
8 226
 
2.7%
4 202
 
2.4%
6 200
 
2.4%
9 197
 
2.3%
Other values (38) 1305
 
15.4%

Length

2024-04-17T01:36:42.426621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3705
43.8%
na 1463
 
17.3%
2 326
 
3.9%
10 310
 
3.7%
3 268
 
3.2%
1 262
 
3.1%
8 226
 
2.7%
4 202
 
2.4%
6 200
 
2.4%
9 197
 
2.3%
Other values (38) 1305
 
15.4%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
0
4930 
<NA>
3511 
회수건조수
 
23

Length

Max length5
Median length1
Mean length2.2553166
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4930
58.2%
<NA> 3511
41.5%
회수건조수 23
 
0.3%

Length

2024-04-17T01:36:42.550530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:42.642810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4930
58.2%
na 3511
41.5%
회수건조수 23
 
0.3%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
<NA>
8419 
회의실별동시수용인원
 
45

Length

Max length10
Median length4
Mean length4.0318998
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> 8419
99.5%
회의실별동시수용인원 45
 
0.5%

Length

2024-04-17T01:36:42.731755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:42.819547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8419
99.5%
회의실별동시수용인원 45
 
0.5%

last_load_dttm
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.3 KiB
2021-04-01 05:09:04
4668 
2021-04-01 05:09:03
3790 
<NA>
 
6

Length

Max length19
Median length19
Mean length18.989367
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-04-01 05:09:03
2nd row2021-04-01 05:09:03
3rd row2021-04-01 05:09:03
4th row2021-04-01 05:09:03
5th row2021-04-01 05:09:03

Common Values

ValueCountFrequency (%)
2021-04-01 05:09:04 4668
55.2%
2021-04-01 05:09:03 3790
44.8%
<NA> 6
 
0.1%

Length

2024-04-17T01:36:42.904722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:42.997702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-04-01 8458
50.0%
05:09:04 4668
27.6%
05:09:03 3790
22.4%
na 6
 
< 0.1%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
0232500003250000-201-2017-0000203_11_03_PI2018-08-31 23:59:59.0<NA>(주)아이에이치엠 호텔포레 프리미어 남포지점600045부산광역시 중구 남포동5가 8-1번지48953부산광역시 중구 구덕로 54-1 (남포동5가)20170213<NA><NA><NA><NA>01영업385079.145433179894.98255720171123163559일반호텔051-123-1234<NA>임대<NA>162<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>14040<NA><NA><NA>0<NA><NA><NA>1070<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-04-01 05:09:03
1332500003250000-201-2014-0000103_11_03_PI2018-08-31 23:59:59.0<NA>호텔아벤트리부산600051부산광역시 중구 창선동1가 12-1번지48947부산광역시 중구 광복로39번길 6 (창선동1가)20140318<NA><NA><NA><NA>01영업385065.851535180046.79139420180727133623일반호텔051-123-1234<NA>자가<NA>84<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>8060<NA><NA><NA>0<NA><NA><NA>81<NA><NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-04-01 05:09:03
2432500003250000-214-2017-0000303_11_03_PI2018-08-31 23:59:59.0<NA>케이 칠구(K79)600092부산광역시 중구 대청동2가 23-3번지48948부산광역시 중구 광복로49번길 38 (대청동2가)20170731<NA><NA><NA><NA>01영업385140.157403180362.44609920180814140805숙박업(생활)051-123-1234<NA><NA><NA>51<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>3010<NA><NA><NA>0<NA><NA><NA>160<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-04-01 05:09:03
3532500003250000-201-1971-0011603_11_03_PI2018-08-31 23:59:59.0<NA>영하장600806부산광역시 중구 부평동2가 24-3번지48977부산광역시 중구 중구로23번길 34 (부평동2가)1971080720140310<NA><NA><NA>02폐업384736.73365180083.04251420121015144713여관업051-123-1234<NA>임대<NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>7<NA><NA><NA><NA>여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3<NA><NA>2021-04-01 05:09:03
4632500003250000-201-2012-0000503_11_03_PI2018-08-31 23:59:59.0<NA>누리게스트하우스 더셀프600012부산광역시 중구 중앙동2가 52-2번지48956부산광역시 중구 중앙대로49번길 13 (중앙동2가)2012112720121231<NA><NA><NA>02폐업385546.889042180289.00649820121127133856숙박업 기타051-123-1234<NA>임대<NA>50<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>2<NA>2<NA><NA><NA><NA>0<NA><NA><NA>5<NA><NA><NA>0숙박업 기타<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-04-01 05:09:03
5732500003250000-201-1988-0006903_11_03_PI2018-08-31 23:59:59.0<NA>야(Ya)600083부산광역시 중구 보수동3가 5-21번지48947부산광역시 중구 보수대로106번길 5 (보수동3가)1988012620171120<NA><NA><NA>02폐업384329.080801180631.27368220171120143429여관업051-123-1234<NA>임대<NA>00<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>10<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>020<NA>2021-04-01 05:09:03
6832500003250000-201-1970-0011603_11_03_PI2018-08-31 23:59:59.0<NA>세피아600071부산광역시 중구 부평동1가 41-7번지 ,848980부산광역시 중구 광복로12번길 7-5 (부평동1가, 41-7,8)19700828<NA><NA><NA><NA>01영업384788.862125179954.32496120180727110634여관업051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>16<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>020<NA>2021-04-01 05:09:03
7932500003250000-201-2007-0000203_11_03_PI2018-08-31 23:59:59.0<NA>식스나인모텔600046부산광역시 중구 남포동6가 29번지 (8~11층)48982부산광역시 중구 자갈치로 21 (남포동6가)20070712<NA><NA><NA><NA>01영업384804.909084179701.53297720180502092950여관업051-123-1234<NA>자가<NA>101<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>11080<NA><NA><NA>0<NA><NA><NA>25<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-04-01 05:09:03
81032500003250000-201-1971-0011703_11_03_PI2018-08-31 23:59:59.0<NA>동산장모텔600033부산광역시 중구 광복동3가 5-20번지48949부산광역시 중구 광복로67번길 30-22 (광복동3가)19710315<NA><NA><NA><NA>01영업385245.417649180087.31460420180727170224여관업051-123-1234<NA><NA><NA>30<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>4<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>080<NA>2021-04-01 05:09:03
91132500003250000-201-1972-0000303_11_03_PI2018-08-31 23:59:59.0<NA>주식회사 경원건설 호텔노아600045부산광역시 중구 남포동5가 81-1번지48983부산광역시 중구 자갈치로47번길 3-1 (남포동5가)19721010<NA><NA><NA><NA>01영업385043.08817179794.6106720171220145009관광호텔051-123-1234<NA>자가<NA>91<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9010<NA><NA><NA>0<NA><NA><NA>51<NA><NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>2021-04-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
84541289433300003330000-214-2021-0000103_11_03_PI2021-01-24 00:23:04.0숙박업에이치 스테이 호텔612821부산광역시 해운대구 우동 539-10 해운대 라뮤에뜨48094.0부산광역시 해운대구 해운대로 620, 해운대 라뮤에뜨 (우동)20210122<NA><NA><NA><NA>영업/정상영업396596.443478014186999.88452720210122133657숙박업(생활)051 7602100<NA><NA><NA>420<NA><NA><NA><NA>2<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>39<NA>7<NA><NA><NA><NA>0<NA><NA><NA>301<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-04-01 05:09:04
84551290433300003330000-214-2021-0000103_11_03_PI2021-01-24 00:23:04.0숙박업에이치 스테이 호텔612821부산광역시 해운대구 우동 539-10 해운대 라뮤에뜨48094.0부산광역시 해운대구 해운대로 620, 해운대 라뮤에뜨 (우동)20210122<NA><NA><NA><NA>영업/정상영업396596.443478014186999.88452720210122133657숙박업(생활)051 7602100<NA><NA><NA>420<NA><NA><NA><NA>2<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>39<NA>7<NA><NA><NA><NA>0<NA><NA><NA>301<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-04-01 05:09:04
8456129553390000CDFI226003202100000103_11_01_PU2021-02-18 02:40:00.0관광숙박업ND1226 HOTEL<NA>부산광역시 사상구 괘법동 517-146960.0부산광역시 사상구 낙동대로 1226 (괘법동)20210205<NA><NA><NA><NA>영업/정상영업중380057.991425369187370.83623620210216161824<NA><NA>32<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>관광숙박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:09:04
8457129583390000CDFI226003202100000103_11_01_PU2021-02-18 02:40:00.0관광숙박업ND1226 HOTEL<NA>부산광역시 사상구 괘법동 517-146960.0부산광역시 사상구 낙동대로 1226 (괘법동)20210205<NA><NA><NA><NA>영업/정상영업중380057.991425369187370.83623620210216161824<NA><NA>32<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>관광숙박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:09:04
8458129623380000CDFI226003202100000103_11_01_PI2021-02-10 00:23:02.0관광숙박업광안273<NA>부산광역시 수영구 민락동 176-1448286.0부산광역시 수영구 광안해변로 273, 2~4층 (민락동)20210208<NA><NA><NA><NA>영업/정상영업중393429.955148773186148.12377420210208173959<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>관광숙박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>311310.57<NA><NA><NA><NA><NA><NA><NA><NA>10000000<NA><NA><NA><NA><NA><NA><NA><NA><NA>4<NA><NA><NA><NA>2021-04-01 05:09:04
84591299833800003380000-214-2021-0000303_11_03_PI2021-02-19 00:23:01.0숙박업주식회사이너플랜613805부산광역시 수영구 광안동 202-1848303.0부산광역시 수영구 남천바다로33번길 35, 401~405,501~505,601~605,701~705,801~805호 4~8층 (광안동)20210217폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업392654.443900347185470.14027720210217121659숙박업(생활)070 46552587객실수건물소유구분명건물용도명00건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자0놀이기구수내역놀이시설수N무대면적문화사업자구분명문화체육업종명N보험기관명보험시작일자보험종료일자부대시설내역8040선박제원선박척수선박총톤수0시설규모시설면적250영문상호명영문상호주소0숙박업(생활)자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주변환경명지상층수지역구분명지하층수총층수000회의실별동시수용인원2021-04-01 05:09:04
8460130233330000CDFI226221201500002403_11_04_PI2021-02-25 00:23:01.0외국인관광도시민박업마망하우스<NA>부산광역시 해운대구 우동NaN부산광역시 해운대구 해운대로 428, 119동 4층 403호 (우동, 동부올림픽타운)20151007<NA><NA><NA><NA>영업/정상영업중395088.21080900000187543.08045620210223162649<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>10000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:09:04
8461130243330000CDFI226221201200000403_11_04_PI2021-03-04 00:23:00.0외국인관광도시민박업아리랑스테이612759부산광역시 해운대구 좌동 1438 해운대대우2차아파트 202동 2601호NaN부산광역시 해운대구 좌동순환로 275, 202동 2601호 (좌동, 해운대대우2차아파트)2012050320210302<NA><NA><NA>폐업폐업398866.445014628188038.17640620210302160229<NA><NA><NA><NA>아파트<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>155155.31<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>아파트지역<NA>일반주거지역<NA><NA><NA><NA><NA><NA>2021-04-01 05:09:04
84621302532700003270000-214-2021-0000103_11_03_PI2021-03-24 00:23:10.0숙박업마리나레지던스호텔601829부산광역시 동구 초량동 503-5 조이팰리스48816.0부산광역시 동구 대영로243번길 73-5, 조이팰리스 2~7층 (초량동)20210322폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업385803.690264516181505.3492220210322141833숙박업(생활)전화번호객실수건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수N무대면적문화사업자구분명문화체육업종명N보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수시설규모시설면적양실수여성종사자수영문상호명영문상호주소욕실수숙박업(생활)자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수지역구분명지하층수총층수침대수한실수회수건조수회의실별동시수용인원2021-04-01 05:09:04
8463130263340000CDFI226221202100000103_11_04_PI2021-03-26 00:22:59.0외국인관광도시민박업감천하텔지번우편번호부산광역시 사하구 감천동 31-149375.0부산광역시 사하구 감천로139번길 39 (감천동)20210324폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중382892.97830771178418.25355420210324104432업태구분명전화번호객실수건물소유구분명단독주택건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수4040.46양실수여성종사자수영문상호명영문상호주소욕실수위생업태명2000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주택가주변4일반주거지역지하층수4침대수한실수회수건조수회의실별동시수용인원2021-04-01 05:09:04

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnwhladdrdcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
273330000CDFI226003201800000503_11_01_PU2019-04-14 02:40:00.0관광숙박업일로이리조트<NA>부산광역시 해운대구 송정동 809번지부산광역시 해운대구 송정구덕포길 130 (송정동)<NA><NA><NA><NA>영업/정상영업중187863.01536620190412092534<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>관광숙박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>599598.73<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4주거지역<NA>4<NA><NA><NA><NA>2021-04-01 05:09:046
23250000CDFI226221201900000103_11_04_PU2020-11-03 02:40:00.0외국인관광도시민박업보수동방공호<NA>부산광역시 중구 보수동1가 116-156부산광역시 중구 책방골목길 13-11 (보수동1가)<NA><NA><NA><NA>영업/정상영업중180168.55870820201031173213<NA><NA>6<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>168167.82<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>일반상업지역<NA>3<NA><NA><NA><NA>2021-04-01 05:09:043
33250000CDFI226221201900000203_11_04_PU2020-11-03 02:40:00.0외국인관광도시민박업제이온게스트하우스<NA>부산광역시 중구 부평동2가 21-8부산광역시 중구 중구로29번길 38, 4층 (부평동2가)<NA><NA><NA><NA>영업/정상영업중179818.66105720201031173301<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3838.18<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-04-01 05:09:043
732700003270000-201-2019-0000303_11_03_PI2019-06-23 02:21:37.0숙박업대구여관601829부산광역시 동구 초량동 388-2번지 지하1층, 지상1~3층, 4층 일부부산광역시 동구 중앙대로221번길 14-5 (초량동)<NA><NA><NA><NA>영업/정상영업181704.05848320190621114502여관업051-123-1234<NA>자가<NA>41<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4111<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>060<NA>2021-04-01 05:09:043
832700003270000-201-2019-0000503_11_03_PU2020-10-29 02:40:00.0숙박업단테하우스B601829부산광역시 동구 초량동 399부산광역시 동구 초량로13번길 58 (초량동)<NA><NA><NA><NA>영업/정상영업181627.55533520201027175551여관업<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4010<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-04-01 05:09:043
113280000CDFI226221202000000103_11_04_PU2021-03-28 02:40:00.0외국인관광도시민박업오션하우스<NA>부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1904호 (동삼동, 함지그린아파트)<NA><NA><NA><NA>영업/정상영업중176595.03493520210326171249<NA><NA>2<NA>아파트<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4645.5<NA><NA><NA>ocean houseGuesthouse for Foreign Tourists<NA><NA><NA>10000000<NA><NA><NA><NA><NA>아파트지역20일반주거지역220<NA><NA><NA><NA>2021-04-01 05:09:043
123280000CDFI226221202000000203_11_04_PU2021-03-28 02:40:00.0외국인관광도시민박업에메랄드 오션뷰<NA>부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1902호 (동삼동, 함지그린아파트)<NA><NA><NA><NA>영업/정상영업중176595.03493520210326105821<NA><NA>1<NA>아파트<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4645.5<NA><NA><NA>Emerald ocean viewGuesthouse for Foreign Tourists<NA><NA><NA><NA><NA><NA><NA><NA><NA>아파트지역20주거지역220<NA><NA><NA><NA>2021-04-01 05:09:043
133280000CDFI226221202000000303_11_04_PU2020-06-07 02:40:00.0외국인관광도시민박업청학소담<NA>부산광역시 영도구 청학동 398-20번지부산광역시 영도구 청학서로16번길 43-14 (청학동)<NA><NA><NA><NA>영업/정상영업중179086.90220320200605103404<NA>051-123-12341<NA>단독주택<NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>외국인관광 도시민박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>8080.1<NA><NA><NA>CheonghakSodamGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA><NA>주택가주변<NA>일반주거지역<NA>1<NA><NA><NA><NA>2021-04-01 05:09:043
1732900003290000-201-2019-0000203_11_03_PU2020-12-15 02:40:00.0숙박업엑스모텔614846부산광역시 부산진구 부전동 226-5부산광역시 부산진구 신천대로50번길 34, 6층~9층 (부전동)<NA><NA><NA><NA>영업/정상영업185627.12814620201212162712일반호텔051 803 6996<NA><NA><NA>102<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9060<NA><NA><NA>0<NA><NA><NA>290<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-04-01 05:09:043
1832900003290000-201-2020-0000103_11_03_PU2020-12-15 02:40:00.0숙박업지지배614849부산광역시 부산진구 부전동 417-25부산광역시 부산진구 부전로 99-1, 3층 (부전동)<NA><NA><NA><NA>영업/정상영업186361.92755720201212135845여관업051 806 7779<NA>자가<NA>41<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA>3<NA><NA><NA><NA>0<NA><NA><NA>60<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-04-01 05:09:043