Overview

Dataset statistics

Number of variables81
Number of observations8478
Missing cells25583
Missing cells (%)3.7%
Duplicate rows310
Duplicate rows (%)3.7%
Total size in memory5.3 MiB
Average record size in memory651.0 B

Variable types

Unsupported4
Numeric3
Text10
Categorical63
DateTime1

Alerts

Dataset has 310 (3.7%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (89.6%)Imbalance
updategbn is highly imbalanced (79.7%)Imbalance
opnsvcnm is highly imbalanced (83.8%)Imbalance
clgstdt is highly imbalanced (97.6%)Imbalance
clgenddt is highly imbalanced (97.5%)Imbalance
ropnymd is highly imbalanced (93.6%)Imbalance
trdstatenm is highly imbalanced (53.3%)Imbalance
dtlstatenm is highly imbalanced (54.1%)Imbalance
stroomcnt is highly imbalanced (95.7%)Imbalance
bdngsrvnm is highly imbalanced (93.1%)Imbalance
bdngunderflrcnt is highly imbalanced (55.4%)Imbalance
cnstyarea is highly imbalanced (97.7%)Imbalance
svnsr is highly imbalanced (93.6%)Imbalance
plninsurstdt is highly imbalanced (93.6%)Imbalance
plninsurenddt is highly imbalanced (93.6%)Imbalance
maneipcnt is highly imbalanced (88.0%)Imbalance
playutscntdtl is highly imbalanced (93.6%)Imbalance
playfacilcnt is highly imbalanced (84.9%)Imbalance
multusnupsoyn is highly imbalanced (95.5%)Imbalance
stagear is highly imbalanced (93.6%)Imbalance
culwrkrsenm is highly imbalanced (93.6%)Imbalance
culphyedcobnm is highly imbalanced (88.5%)Imbalance
geicpfacilen is highly imbalanced (93.6%)Imbalance
balhansilyn is highly imbalanced (94.7%)Imbalance
bcfacilen is highly imbalanced (93.6%)Imbalance
insurorgnm is highly imbalanced (97.8%)Imbalance
insurstdt is highly imbalanced (93.6%)Imbalance
insurenddt is highly imbalanced (93.6%)Imbalance
afc is highly imbalanced (93.6%)Imbalance
useunderendflr is highly imbalanced (64.2%)Imbalance
useunderstflr is highly imbalanced (63.2%)Imbalance
shpinfo is highly imbalanced (93.6%)Imbalance
shpcnt is highly imbalanced (93.6%)Imbalance
shptottons is highly imbalanced (93.6%)Imbalance
infoben is highly imbalanced (93.6%)Imbalance
wmeipcnt is highly imbalanced (87.1%)Imbalance
engstntrnmnm is highly imbalanced (97.1%)Imbalance
engstntrnmaddr is highly imbalanced (96.7%)Imbalance
yoksilcnt is highly imbalanced (77.3%)Imbalance
dispenen is highly imbalanced (93.6%)Imbalance
capt is highly imbalanced (96.4%)Imbalance
mnfactreartclcn is highly imbalanced (93.6%)Imbalance
cndpermstymd is highly imbalanced (95.8%)Imbalance
cndpermntwhy is highly imbalanced (93.6%)Imbalance
cndpermendymd is highly imbalanced (95.8%)Imbalance
chaircnt is highly imbalanced (66.8%)Imbalance
nearenvnm is highly imbalanced (94.2%)Imbalance
jisgnumlay is highly imbalanced (95.0%)Imbalance
regnsenm is highly imbalanced (91.5%)Imbalance
undernumlay is highly imbalanced (96.0%)Imbalance
totnumlay is highly imbalanced (94.7%)Imbalance
meetsamtimesygstf is highly imbalanced (93.6%)Imbalance
sitepostno has 295 (3.5%) missing valuesMissing
rdnwhladdr has 2549 (30.1%) missing valuesMissing
dcbymd has 4607 (54.3%) missing valuesMissing
x has 385 (4.5%) missing valuesMissing
y has 388 (4.6%) missing valuesMissing
sitetel has 95 (1.1%) missing valuesMissing
facilscp has 8167 (96.3%) missing valuesMissing
facilar has 8167 (96.3%) missing valuesMissing
yangsilcnt has 899 (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 16:35:55.257193
Analysis finished2024-04-16 16:35:57.773584
Duration2.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.4 KiB

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3318915.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-17T01:35:57.817327image/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 deviation42884.456
Coefficient of variation (CV)0.012921225
Kurtosis-0.97770964
Mean3318915.6
Median Absolute Deviation (MAD)30000
Skewness0.26604561
Sum2.812781 × 1010
Variance1.8390765 × 109
MonotonicityNot monotonic
2024-04-17T01:35:57.915796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1135
13.4%
3290000 1059
12.5%
3300000 893
10.5%
3390000 688
8.1%
3270000 654
 
7.7%
3320000 578
 
6.8%
3380000 497
 
5.9%
3250000 478
 
5.6%
3260000 405
 
4.8%
3370000 383
 
4.5%
Other values (6) 1705
20.1%
ValueCountFrequency (%)
3250000 478
5.6%
3260000 405
 
4.8%
3270000 654
7.7%
3280000 364
 
4.3%
3290000 1059
12.5%
3300000 893
10.5%
3310000 285
 
3.4%
3320000 578
6.8%
3330000 1135
13.4%
3340000 358
 
4.2%
ValueCountFrequency (%)
3400000 207
 
2.4%
3390000 688
8.1%
3380000 497
5.9%
3370000 383
 
4.5%
3360000 138
 
1.6%
3350000 353
 
4.2%
3340000 358
 
4.2%
3330000 1135
13.4%
3320000 578
6.8%
3310000 285
 
3.4%

mgtno
Text

Distinct4199
Distinct (%)49.5%
Missing3
Missing (%)< 0.1%
Memory size66.4 KiB
2024-04-17T01:35:58.089811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.918112
Min length20

Characters and Unicode

Total characters185756
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

Unique122 ?
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%
cdfi2262212015000001 12
 
0.1%
cdfi2262212018000001 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 (4189) 8365
98.7%
2024-04-17T01:35:58.386435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71536
38.5%
- 24384
 
13.1%
1 20052
 
10.8%
2 19850
 
10.7%
3 18209
 
9.8%
9 10161
 
5.5%
8 4971
 
2.7%
7 4871
 
2.6%
6 3689
 
2.0%
4 3605
 
1.9%
Other values (5) 4428
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 159984
86.1%
Dash Punctuation 24384
 
13.1%
Uppercase Letter 1388
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71536
44.7%
1 20052
 
12.5%
2 19850
 
12.4%
3 18209
 
11.4%
9 10161
 
6.4%
8 4971
 
3.1%
7 4871
 
3.0%
6 3689
 
2.3%
4 3605
 
2.3%
5 3040
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 347
25.0%
D 347
25.0%
F 347
25.0%
I 347
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24384
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 184368
99.3%
Latin 1388
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 71536
38.8%
- 24384
 
13.2%
1 20052
 
10.9%
2 19850
 
10.8%
3 18209
 
9.9%
9 10161
 
5.5%
8 4971
 
2.7%
7 4871
 
2.6%
6 3689
 
2.0%
4 3605
 
2.0%
Latin
ValueCountFrequency (%)
C 347
25.0%
D 347
25.0%
F 347
25.0%
I 347
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 185756
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 71536
38.5%
- 24384
 
13.1%
1 20052
 
10.8%
2 19850
 
10.7%
3 18209
 
9.8%
9 10161
 
5.5%
8 4971
 
2.7%
7 4871
 
2.6%
6 3689
 
2.0%
4 3605
 
1.9%
Other values (5) 4428
 
2.4%

opnsvcid
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
03_11_03_P
8128 
03_11_04_P
 
262
03_11_01_P
 
72
03_11_05_P
 
9
03_11_02_P
 
3
Other values (2)
 
4

Length

Max length10
Median length10
Mean length9.9978769
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 8128
95.9%
03_11_04_P 262
 
3.1%
03_11_01_P 72
 
0.8%
03_11_05_P 9
 
0.1%
03_11_02_P 3
 
< 0.1%
<NA> 3
 
< 0.1%
03_11_06_P 1
 
< 0.1%

Length

2024-04-17T01:35:58.500898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:58.597254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8128
95.9%
03_11_04_p 262
 
3.1%
03_11_01_p 72
 
0.8%
03_11_05_p 9
 
0.1%
03_11_02_p 3
 
< 0.1%
na 3
 
< 0.1%
03_11_06_p 1
 
< 0.1%

updategbn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
I
7988 
U
 
487
180000000
 
3

Length

Max length9
Median length1
Mean length1.0028309
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7988
94.2%
U 487
 
5.7%
180000000 3
 
< 0.1%

Length

2024-04-17T01:35:58.701707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:58.829624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7988
94.2%
u 487
 
5.7%
180000000 3
 
< 0.1%
Distinct207
Distinct (%)2.4%
Missing3
Missing (%)< 0.1%
Memory size66.4 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-01 02:40:00
2024-04-17T01:35:58.926365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:35:59.056569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
7869 
숙박업
 
442
외국인관광도시민박업
 
92
관광숙박업
 
72
자동차야영장업
 
1
Other values (2)
 
2

Length

Max length10
Median length4
Mean length4.0220571
Min length3

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7869
92.8%
숙박업 442
 
5.2%
외국인관광도시민박업 92
 
1.1%
관광숙박업 72
 
0.8%
자동차야영장업 1
 
< 0.1%
한옥체험업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

Length

2024-04-17T01:35:59.182253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:59.278428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7869
92.8%
숙박업 442
 
5.2%
외국인관광도시민박업 92
 
1.1%
관광숙박업 72
 
0.8%
자동차야영장업 1
 
< 0.1%
한옥체험업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

bplcnm
Text

Distinct3365
Distinct (%)39.7%
Missing3
Missing (%)< 0.1%
Memory size66.4 KiB
2024-04-17T01:35:59.525858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length36
Mean length5.1247198
Min length1

Characters and Unicode

Total characters43432
Distinct characters651
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

Unique293 ?
Unique (%)3.5%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 칠구(K79)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 237
 
2.4%
모텔 196
 
1.9%
게스트하우스 120
 
1.2%
여관 82
 
0.8%
hotel 61
 
0.6%
부산 51
 
0.5%
house 50
 
0.5%
해운대 39
 
0.4%
36
 
0.4%
여인숙 36
 
0.4%
Other values (3454) 9166
91.0%
2024-04-17T01:35:59.915563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2913
 
6.7%
2018
 
4.6%
1791
 
4.1%
1776
 
4.1%
1616
 
3.7%
1494
 
3.4%
1327
 
3.1%
1279
 
2.9%
768
 
1.8%
713
 
1.6%
Other values (641) 27737
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36588
84.2%
Uppercase Letter 2343
 
5.4%
Space Separator 1616
 
3.7%
Lowercase Letter 1202
 
2.8%
Decimal Number 527
 
1.2%
Close Punctuation 499
 
1.1%
Open Punctuation 499
 
1.1%
Other Punctuation 104
 
0.2%
Dash Punctuation 30
 
0.1%
Letter Number 10
 
< 0.1%
Other values (4) 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2913
 
8.0%
2018
 
5.5%
1791
 
4.9%
1776
 
4.9%
1494
 
4.1%
1327
 
3.6%
1279
 
3.5%
768
 
2.1%
713
 
1.9%
622
 
1.7%
Other values (561) 21887
59.8%
Uppercase Letter
ValueCountFrequency (%)
E 253
 
10.8%
O 218
 
9.3%
H 204
 
8.7%
T 173
 
7.4%
S 168
 
7.2%
A 131
 
5.6%
L 130
 
5.5%
N 112
 
4.8%
U 104
 
4.4%
M 92
 
3.9%
Other values (16) 758
32.4%
Lowercase Letter
ValueCountFrequency (%)
e 195
16.2%
o 144
12.0%
s 102
8.5%
a 95
7.9%
n 91
 
7.6%
u 91
 
7.6%
t 84
 
7.0%
h 59
 
4.9%
l 54
 
4.5%
i 50
 
4.2%
Other values (16) 237
19.7%
Decimal Number
ValueCountFrequency (%)
2 126
23.9%
1 72
13.7%
5 67
12.7%
7 58
11.0%
9 56
10.6%
6 41
 
7.8%
0 38
 
7.2%
3 36
 
6.8%
4 23
 
4.4%
8 10
 
1.9%
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 (%)
1616
100.0%
Close Punctuation
ValueCountFrequency (%)
) 499
100.0%
Open Punctuation
ValueCountFrequency (%)
( 499
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
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 36586
84.2%
Latin 3555
 
8.2%
Common 3283
 
7.6%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2913
 
8.0%
2018
 
5.5%
1791
 
4.9%
1776
 
4.9%
1494
 
4.1%
1327
 
3.6%
1279
 
3.5%
768
 
2.1%
713
 
1.9%
622
 
1.7%
Other values (557) 21885
59.8%
Latin
ValueCountFrequency (%)
E 253
 
7.1%
O 218
 
6.1%
H 204
 
5.7%
e 195
 
5.5%
T 173
 
4.9%
S 168
 
4.7%
o 144
 
4.1%
A 131
 
3.7%
L 130
 
3.7%
N 112
 
3.2%
Other values (44) 1827
51.4%
Common
ValueCountFrequency (%)
1616
49.2%
) 499
 
15.2%
( 499
 
15.2%
2 126
 
3.8%
1 72
 
2.2%
5 67
 
2.0%
. 59
 
1.8%
7 58
 
1.8%
9 56
 
1.7%
6 41
 
1.2%
Other values (15) 190
 
5.8%
Han
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36580
84.2%
ASCII 6823
 
15.7%
Number Forms 10
 
< 0.1%
None 10
 
< 0.1%
CJK 8
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2913
 
8.0%
2018
 
5.5%
1791
 
4.9%
1776
 
4.9%
1494
 
4.1%
1327
 
3.6%
1279
 
3.5%
768
 
2.1%
713
 
1.9%
622
 
1.7%
Other values (556) 21879
59.8%
ASCII
ValueCountFrequency (%)
1616
23.7%
) 499
 
7.3%
( 499
 
7.3%
E 253
 
3.7%
O 218
 
3.2%
H 204
 
3.0%
e 195
 
2.9%
T 173
 
2.5%
S 168
 
2.5%
o 144
 
2.1%
Other values (64) 2854
41.8%
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%
Missing295
Missing (%)3.5%
Memory size66.4 KiB
2024-04-17T01:36:00.224827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters49098
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 208
 
2.5%
612847 183
 
2.2%
607833 175
 
2.1%
601829 145
 
1.8%
617807 136
 
1.7%
613828 129
 
1.6%
607831 126
 
1.5%
607842 114
 
1.4%
Other values (482) 6396
78.2%
2024-04-17T01:36:00.607008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9830
20.0%
1 8028
16.4%
0 7979
16.3%
8 7926
16.1%
2 4290
8.7%
4 3439
 
7.0%
7 2596
 
5.3%
3 2457
 
5.0%
9 1403
 
2.9%
5 952
 
1.9%
Other values (5) 198
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48900
99.6%
Other Letter 198
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9830
20.1%
1 8028
16.4%
0 7979
16.3%
8 7926
16.2%
2 4290
8.8%
4 3439
 
7.0%
7 2596
 
5.3%
3 2457
 
5.0%
9 1403
 
2.9%
5 952
 
1.9%
Other Letter
ValueCountFrequency (%)
66
33.3%
33
16.7%
33
16.7%
33
16.7%
33
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 48900
99.6%
Hangul 198
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9830
20.1%
1 8028
16.4%
0 7979
16.3%
8 7926
16.2%
2 4290
8.8%
4 3439
 
7.0%
7 2596
 
5.3%
3 2457
 
5.0%
9 1403
 
2.9%
5 952
 
1.9%
Hangul
ValueCountFrequency (%)
66
33.3%
33
16.7%
33
16.7%
33
16.7%
33
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48900
99.6%
Hangul 198
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9830
20.1%
1 8028
16.4%
0 7979
16.3%
8 7926
16.2%
2 4290
8.8%
4 3439
 
7.0%
7 2596
 
5.3%
3 2457
 
5.0%
9 1403
 
2.9%
5 952
 
1.9%
Hangul
ValueCountFrequency (%)
66
33.3%
33
16.7%
33
16.7%
33
16.7%
33
16.7%
Distinct4048
Distinct (%)47.8%
Missing5
Missing (%)0.1%
Memory size66.4 KiB
2024-04-17T01:36:00.910186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length45
Mean length23.587277
Min length13

Characters and Unicode

Total characters199855
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

Unique245 ?
Unique (%)2.9%

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 8473
23.5%
해운대구 1135
 
3.1%
부산진구 1059
 
2.9%
동래구 893
 
2.5%
t통b반 868
 
2.4%
사상구 688
 
1.9%
동구 654
 
1.8%
온천동 644
 
1.8%
북구 582
 
1.6%
부전동 503
 
1.4%
Other values (4233) 20569
57.0%
2024-04-17T01:36:01.358081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35977
18.0%
10295
 
5.2%
10042
 
5.0%
9948
 
5.0%
8840
 
4.4%
8721
 
4.4%
1 8571
 
4.3%
8499
 
4.3%
8479
 
4.2%
8273
 
4.1%
Other values (298) 82210
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113980
57.0%
Decimal Number 39679
 
19.9%
Space Separator 35977
 
18.0%
Dash Punctuation 7873
 
3.9%
Uppercase Letter 1782
 
0.9%
Other Punctuation 195
 
0.1%
Open Punctuation 124
 
0.1%
Close Punctuation 124
 
0.1%
Math Symbol 117
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10295
 
9.0%
10042
 
8.8%
9948
 
8.7%
8840
 
7.8%
8721
 
7.7%
8499
 
7.5%
8479
 
7.4%
8273
 
7.3%
8059
 
7.1%
1573
 
1.4%
Other values (262) 31251
27.4%
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%
G 2
 
0.1%
M 2
 
0.1%
E 2
 
0.1%
Other values (4) 4
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 8571
21.6%
2 5208
13.1%
3 4176
10.5%
4 4034
10.2%
5 3912
9.9%
0 3051
 
7.7%
6 3027
 
7.6%
7 2838
 
7.2%
8 2567
 
6.5%
9 2295
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 192
98.5%
. 2
 
1.0%
& 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
i 1
33.3%
e 1
33.3%
w 1
33.3%
Space Separator
ValueCountFrequency (%)
35977
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7873
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 124
100.0%
Math Symbol
ValueCountFrequency (%)
~ 117
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113980
57.0%
Common 84089
42.1%
Latin 1786
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10295
 
9.0%
10042
 
8.8%
9948
 
8.7%
8840
 
7.8%
8721
 
7.7%
8499
 
7.5%
8479
 
7.4%
8273
 
7.3%
8059
 
7.1%
1573
 
1.4%
Other values (262) 31251
27.4%
Common
ValueCountFrequency (%)
35977
42.8%
1 8571
 
10.2%
- 7873
 
9.4%
2 5208
 
6.2%
3 4176
 
5.0%
4 4034
 
4.8%
5 3912
 
4.7%
0 3051
 
3.6%
6 3027
 
3.6%
7 2838
 
3.4%
Other values (8) 5422
 
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%
G 2
 
0.1%
M 2
 
0.1%
E 2
 
0.1%
Other values (8) 8
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113980
57.0%
ASCII 85874
43.0%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35977
41.9%
1 8571
 
10.0%
- 7873
 
9.2%
2 5208
 
6.1%
3 4176
 
4.9%
4 4034
 
4.7%
5 3912
 
4.6%
0 3051
 
3.6%
6 3027
 
3.5%
7 2838
 
3.3%
Other values (25) 7207
 
8.4%
Hangul
ValueCountFrequency (%)
10295
 
9.0%
10042
 
8.8%
9948
 
8.7%
8840
 
7.8%
8721
 
7.7%
8499
 
7.5%
8479
 
7.4%
8273
 
7.3%
8059
 
7.1%
1573
 
1.4%
Other values (262) 31251
27.4%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Unsupported

REJECTED  UNSUPPORTED 

Missing11
Missing (%)0.1%
Memory size66.4 KiB

rdnwhladdr
Text

MISSING 

Distinct3007
Distinct (%)50.7%
Missing2549
Missing (%)30.1%
Memory size66.4 KiB
2024-04-17T01:36:01.639936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length61
Mean length27.840277
Min length5

Characters and Unicode

Total characters165065
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

Unique294 ?
Unique (%)5.0%

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 5928
 
19.1%
해운대구 917
 
3.0%
부산진구 725
 
2.3%
동래구 607
 
2.0%
사상구 515
 
1.7%
동구 489
 
1.6%
온천동 422
 
1.4%
수영구 395
 
1.3%
중구 388
 
1.3%
부전동 385
 
1.2%
Other values (2574) 20196
65.2%
2024-04-17T01:36:02.069804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25038
 
15.2%
7719
 
4.7%
7332
 
4.4%
6996
 
4.2%
6635
 
4.0%
6304
 
3.8%
1 6290
 
3.8%
6059
 
3.7%
5934
 
3.6%
) 5818
 
3.5%
Other values (359) 80940
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 98217
59.5%
Decimal Number 26760
 
16.2%
Space Separator 25038
 
15.2%
Close Punctuation 5818
 
3.5%
Open Punctuation 5818
 
3.5%
Dash Punctuation 1799
 
1.1%
Other Punctuation 1263
 
0.8%
Math Symbol 252
 
0.2%
Uppercase Letter 93
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7719
 
7.9%
7332
 
7.5%
6996
 
7.1%
6635
 
6.8%
6304
 
6.4%
6059
 
6.2%
5934
 
6.0%
5655
 
5.8%
3953
 
4.0%
3718
 
3.8%
Other values (317) 37912
38.6%
Uppercase Letter
ValueCountFrequency (%)
A 30
32.3%
B 21
22.6%
K 9
 
9.7%
O 5
 
5.4%
C 5
 
5.4%
S 4
 
4.3%
E 3
 
3.2%
U 2
 
2.2%
F 2
 
2.2%
G 2
 
2.2%
Other values (9) 10
 
10.8%
Decimal Number
ValueCountFrequency (%)
1 6290
23.5%
2 4112
15.4%
3 3006
11.2%
4 2279
 
8.5%
5 2136
 
8.0%
0 1918
 
7.2%
6 1897
 
7.1%
7 1839
 
6.9%
9 1697
 
6.3%
8 1586
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
b 1
25.0%
w 1
25.0%
i 1
25.0%
e 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 1253
99.2%
. 9
 
0.7%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
25038
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5818
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5818
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1799
100.0%
Math Symbol
ValueCountFrequency (%)
~ 252
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 98217
59.5%
Common 66748
40.4%
Latin 100
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7719
 
7.9%
7332
 
7.5%
6996
 
7.1%
6635
 
6.8%
6304
 
6.4%
6059
 
6.2%
5934
 
6.0%
5655
 
5.8%
3953
 
4.0%
3718
 
3.8%
Other values (317) 37912
38.6%
Latin
ValueCountFrequency (%)
A 30
30.0%
B 21
21.0%
K 9
 
9.0%
O 5
 
5.0%
C 5
 
5.0%
S 4
 
4.0%
3
 
3.0%
E 3
 
3.0%
U 2
 
2.0%
F 2
 
2.0%
Other values (14) 16
16.0%
Common
ValueCountFrequency (%)
25038
37.5%
1 6290
 
9.4%
) 5818
 
8.7%
( 5818
 
8.7%
2 4112
 
6.2%
3 3006
 
4.5%
4 2279
 
3.4%
5 2136
 
3.2%
0 1918
 
2.9%
6 1897
 
2.8%
Other values (8) 8436
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 98217
59.5%
ASCII 66845
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25038
37.5%
1 6290
 
9.4%
) 5818
 
8.7%
( 5818
 
8.7%
2 4112
 
6.2%
3 3006
 
4.5%
4 2279
 
3.4%
5 2136
 
3.2%
0 1918
 
2.9%
6 1897
 
2.8%
Other values (31) 8533
 
12.8%
Hangul
ValueCountFrequency (%)
7719
 
7.9%
7332
 
7.5%
6996
 
7.1%
6635
 
6.8%
6304
 
6.4%
6059
 
6.2%
5934
 
6.0%
5655
 
5.8%
3953
 
4.0%
3718
 
3.8%
Other values (317) 37912
38.6%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.4 KiB

dcbymd
Text

MISSING 

Distinct1340
Distinct (%)34.6%
Missing4607
Missing (%)54.3%
Memory size66.4 KiB
2024-04-17T01:36:02.307765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9369672
Min length4

Characters and Unicode

Total characters30724
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

Unique32 ?
Unique (%)0.8%

Sample

1st row20140310
2nd row20121231
3rd row20171120
4th row20171107
5th row20120514
ValueCountFrequency (%)
20041022 180
 
4.6%
20030122 64
 
1.7%
폐업일자 61
 
1.6%
20120711 52
 
1.3%
20021024 38
 
1.0%
20030305 26
 
0.7%
20030101 24
 
0.6%
20030227 22
 
0.6%
20051117 20
 
0.5%
20030901 18
 
0.5%
Other values (1330) 3366
87.0%
2024-04-17T01:36:02.690128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10262
33.4%
2 6441
21.0%
1 5539
18.0%
3 1432
 
4.7%
9 1398
 
4.6%
7 1187
 
3.9%
4 1129
 
3.7%
6 1082
 
3.5%
5 1063
 
3.5%
8 947
 
3.1%
Other values (4) 244
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30480
99.2%
Other Letter 244
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10262
33.7%
2 6441
21.1%
1 5539
18.2%
3 1432
 
4.7%
9 1398
 
4.6%
7 1187
 
3.9%
4 1129
 
3.7%
6 1082
 
3.5%
5 1063
 
3.5%
8 947
 
3.1%
Other Letter
ValueCountFrequency (%)
61
25.0%
61
25.0%
61
25.0%
61
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30480
99.2%
Hangul 244
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10262
33.7%
2 6441
21.1%
1 5539
18.2%
3 1432
 
4.7%
9 1398
 
4.6%
7 1187
 
3.9%
4 1129
 
3.7%
6 1082
 
3.5%
5 1063
 
3.5%
8 947
 
3.1%
Hangul
ValueCountFrequency (%)
61
25.0%
61
25.0%
61
25.0%
61
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30480
99.2%
Hangul 244
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10262
33.7%
2 6441
21.1%
1 5539
18.2%
3 1432
 
4.7%
9 1398
 
4.6%
7 1187
 
3.9%
4 1129
 
3.7%
6 1082
 
3.5%
5 1063
 
3.5%
8 947
 
3.1%
Hangul
ValueCountFrequency (%)
61
25.0%
61
25.0%
61
25.0%
61
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8408 
휴업시작일자
 
63
20201012
 
1
20160608
 
1
20160425
 
1
Other values (4)
 
4

Length

Max length8
Median length4
Mean length4.0181647
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> 8408
99.2%
휴업시작일자 63
 
0.7%
20201012 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

2024-04-17T01:36:02.823031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:02.970969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8408
99.2%
휴업시작일자 63
 
0.7%
20201012 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 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8408 
휴업종료일자
 
64
20170607
 
1
20180424
 
1
20190501
 
1
Other values (3)
 
3

Length

Max length8
Median length4
Mean length4.0179288
Min length4

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8408
99.2%
휴업종료일자 64
 
0.8%
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

2024-04-17T01:36:03.090659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:03.194568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8408
99.2%
휴업종료일자 64
 
0.8%
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 size66.4 KiB
<NA>
8414 
재개업일자
 
64

Length

Max length5
Median length4
Mean length4.007549
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> 8414
99.2%
재개업일자 64
 
0.8%

Length

2024-04-17T01:36:03.294851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:03.381701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
재개업일자 64
 
0.8%

trdstatenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
01
3982 
02
3709 
영업/정상
551 
13
 
121
폐업
 
53
Other values (4)
 
62

Length

Max length5
Median length2
Mean length2.1963907
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
01 3982
47.0%
02 3709
43.7%
영업/정상 551
 
6.5%
13 121
 
1.4%
폐업 53
 
0.6%
03 53
 
0.6%
<NA> 6
 
0.1%
휴업 2
 
< 0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:36:03.469682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:03.568023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01 3982
47.0%
02 3709
43.7%
영업/정상 551
 
6.5%
13 121
 
1.4%
폐업 53
 
0.6%
03 53
 
0.6%
na 6
 
0.1%
휴업 2
 
< 0.1%
31 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
영업
4381 
폐업
3810 
영업중
 
276
휴업
 
7
<NA>
 
3

Length

Max length4
Median length2
Mean length2.0334985
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4381
51.7%
폐업 3810
44.9%
영업중 276
 
3.3%
휴업 7
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:36:03.681347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:03.784805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4381
51.7%
폐업 3810
44.9%
영업중 276
 
3.3%
휴업 7
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing385
Missing (%)4.5%
Memory size66.4 KiB

y
Real number (ℝ)

MISSING 

Distinct3931
Distinct (%)48.6%
Missing388
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean186738.22
Minimum169998.58
Maximum209754.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-17T01:36:03.888726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169998.58
5-th percentile178698.94
Q1182936.76
median186938.08
Q3189975.47
95-th percentile193849.15
Maximum209754.15
Range39755.577
Interquartile range (IQR)7038.7153

Descriptive statistics

Standard deviation5112.6503
Coefficient of variation (CV)0.027378704
Kurtosis0.081660141
Mean186738.22
Median Absolute Deviation (MAD)3594.721
Skewness0.10935169
Sum1.5107122 × 109
Variance26139193
MonotonicityNot monotonic
2024-04-17T01:36:04.042675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185933.100965604 19
 
0.2%
176595.034934652 11
 
0.1%
187092.852201 10
 
0.1%
186243.806655 8
 
0.1%
186655.373923053 8
 
0.1%
187269.854013 8
 
0.1%
192327.468209 8
 
0.1%
189143.147865081 7
 
0.1%
186807.811298995 7
 
0.1%
187863.015365939 7
 
0.1%
Other values (3921) 7997
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)

Distinct3670
Distinct (%)43.3%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0131579 × 1013
Minimum1.9990211 × 1013
Maximum2.0210429 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-17T01:36:04.179540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0011009 × 1013
Q12.0060515 × 1013
median2.0171124 × 1013
Q32.0180502 × 1013
95-th percentile2.0200508 × 1013
Maximum2.0210429 × 1013
Range2.2021818 × 1011
Interquartile range (IQR)1.1998712 × 1011

Descriptive statistics

Standard deviation6.6985219 × 1010
Coefficient of variation (CV)0.0033273703
Kurtosis-0.93748233
Mean2.0131579 × 1013
Median Absolute Deviation (MAD)9.6959974 × 109
Skewness-0.82281184
Sum1.7061513 × 1017
Variance4.4870196 × 1021
MonotonicityNot monotonic
2024-04-17T01:36:04.307029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19990428000000 62
 
0.7%
19990920000000 60
 
0.7%
20040902000000 60
 
0.7%
20030122000000 58
 
0.7%
20040203000000 50
 
0.6%
20070531000000 36
 
0.4%
20030414000000 36
 
0.4%
20020515000000 32
 
0.4%
20030329000000 32
 
0.4%
20040427000000 32
 
0.4%
Other values (3660) 8017
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 (%)
20210429183739 1
< 0.1%
20210429170842 1
< 0.1%
20210429140349 2
< 0.1%
20210429134159 2
< 0.1%
20210428171334 2
< 0.1%
20210428170149 2
< 0.1%
20210428132728 2
< 0.1%
20210428132304 2
< 0.1%
20210428094817 2
< 0.1%
20210427152156 2
< 0.1%

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
여관업
5271 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
486
일반호텔
 
425
Other values (4)
631 

Length

Max length8
Median length3
Mean length3.6970984
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5271
62.2%
여인숙업 1076
 
12.7%
숙박업 기타 589
 
6.9%
숙박업(생활) 486
 
5.7%
일반호텔 425
 
5.0%
<NA> 321
 
3.8%
관광호텔 270
 
3.2%
업태구분명 31
 
0.4%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:36:04.440015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:04.558681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5271
58.1%
여인숙업 1076
 
11.9%
숙박업 589
 
6.5%
기타 589
 
6.5%
숙박업(생활 486
 
5.4%
일반호텔 425
 
4.7%
na 321
 
3.5%
관광호텔 270
 
3.0%
업태구분명 31
 
0.3%
휴양콘도미니엄업 9
 
0.1%

sitetel
Text

MISSING 

Distinct155
Distinct (%)1.8%
Missing95
Missing (%)1.1%
Memory size66.4 KiB
2024-04-17T01:36:04.704831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.963259
Min length4

Characters and Unicode

Total characters100288
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

Unique23 ?
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 8077
92.1%
051 262
 
3.0%
전화번호 19
 
0.2%
731 6
 
0.1%
070 6
 
0.1%
806 5
 
0.1%
7779 5
 
0.1%
803 5
 
0.1%
802 4
 
< 0.1%
645 4
 
< 0.1%
Other values (196) 378
 
4.3%
2024-04-17T01:36:04.939802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24716
24.6%
2 16356
16.3%
3 16336
16.3%
- 16172
16.1%
0 8602
 
8.6%
5 8585
 
8.6%
4 8287
 
8.3%
392
 
0.4%
7 266
 
0.3%
8 201
 
0.2%
Other values (6) 375
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83648
83.4%
Dash Punctuation 16172
 
16.1%
Space Separator 392
 
0.4%
Other Letter 76
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24716
29.5%
2 16356
19.6%
3 16336
19.5%
0 8602
 
10.3%
5 8585
 
10.3%
4 8287
 
9.9%
7 266
 
0.3%
8 201
 
0.2%
6 171
 
0.2%
9 128
 
0.2%
Other Letter
ValueCountFrequency (%)
19
25.0%
19
25.0%
19
25.0%
19
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 16172
100.0%
Space Separator
ValueCountFrequency (%)
392
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 100212
99.9%
Hangul 76
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24716
24.7%
2 16356
16.3%
3 16336
16.3%
- 16172
16.1%
0 8602
 
8.6%
5 8585
 
8.6%
4 8287
 
8.3%
392
 
0.4%
7 266
 
0.3%
8 201
 
0.2%
Other values (2) 299
 
0.3%
Hangul
ValueCountFrequency (%)
19
25.0%
19
25.0%
19
25.0%
19
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100212
99.9%
Hangul 76
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24716
24.7%
2 16356
16.3%
3 16336
16.3%
- 16172
16.1%
0 8602
 
8.6%
5 8585
 
8.6%
4 8287
 
8.3%
392
 
0.4%
7 266
 
0.3%
8 201
 
0.2%
Other values (2) 299
 
0.3%
Hangul
ValueCountFrequency (%)
19
25.0%
19
25.0%
19
25.0%
19
25.0%

stroomcnt
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8311 
객실수
 
52
1
 
31
2
 
27
3
 
19
Other values (20)
 
38

Length

Max length4
Median length4
Mean length3.9563576
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> 8311
98.0%
객실수 52
 
0.6%
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

2024-04-17T01:36:05.306428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8311
98.0%
객실수 52
 
0.6%
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 size66.4 KiB
<NA>
6472 
자가
1175 
임대
773 
건물소유구분명
 
58

Length

Max length7
Median length4
Mean length3.5609814
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6472
76.3%
자가 1175
 
13.9%
임대 773
 
9.1%
건물소유구분명 58
 
0.7%

Length

2024-04-17T01:36:05.401878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:05.497901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6472
76.3%
자가 1175
 
13.9%
임대 773
 
9.1%
건물소유구분명 58
 
0.7%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8259 
단독주택
 
69
아파트
 
54
건물용도명
 
50
숙박시설
 
16
Other values (6)
 
30

Length

Max length15
Median length4
Mean length4.0058976
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> 8259
97.4%
단독주택 69
 
0.8%
아파트 54
 
0.6%
건물용도명 50
 
0.6%
숙박시설 16
 
0.2%
다세대주택 12
 
0.1%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 주택(공동주택적용) 4
 
< 0.1%
호텔 4
 
< 0.1%

Length

2024-04-17T01:36:05.592836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8259
97.4%
단독주택 69
 
0.8%
아파트 54
 
0.6%
건물용도명 50
 
0.6%
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) 5
 
0.1%

bdngjisgflrcnt
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
2554 
<NA>
1657 
4
861 
3
749 
5
591 
Other values (30)
2066 

Length

Max length6
Median length1
Mean length1.6480302
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2554
30.1%
<NA> 1657
19.5%
4 861
 
10.2%
3 749
 
8.8%
5 591
 
7.0%
2 423
 
5.0%
8 319
 
3.8%
6 303
 
3.6%
7 302
 
3.6%
9 195
 
2.3%
Other values (25) 524
 
6.2%

Length

2024-04-17T01:36:05.692546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2554
30.1%
na 1657
19.5%
4 861
 
10.2%
3 749
 
8.8%
5 591
 
7.0%
2 423
 
5.0%
8 319
 
3.8%
6 303
 
3.6%
7 302
 
3.6%
9 195
 
2.3%
Other values (25) 524
 
6.2%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
4443 
<NA>
2223 
1
1484 
2
 
193
4
 
36
Other values (9)
 
99

Length

Max length6
Median length1
Mean length1.8056145
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4443
52.4%
<NA> 2223
26.2%
1 1484
 
17.5%
2 193
 
2.3%
4 36
 
0.4%
건물지하층수 31
 
0.4%
3 27
 
0.3%
5 17
 
0.2%
8 6
 
0.1%
6 4
 
< 0.1%
Other values (4) 14
 
0.2%

Length

2024-04-17T01:36:05.786153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4443
52.4%
na 2223
26.2%
1 1486
 
17.5%
2 193
 
2.3%
4 36
 
0.4%
건물지하층수 31
 
0.4%
3 27
 
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 size66.4 KiB
<NA>
8400 
건축연면적
 
61
2282
 
3
20571
 
3
72
 
1
Other values (10)
 
10

Length

Max length5
Median length4
Mean length4.0063694
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> 8400
99.1%
건축연면적 61
 
0.7%
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

2024-04-17T01:36:05.884989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8400
99.1%
건축연면적 61
 
0.7%
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 size66.4 KiB
<NA>
8414 
기념품종류
 
64

Length

Max length5
Median length4
Mean length4.007549
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> 8414
99.2%
기념품종류 64
 
0.8%

Length

2024-04-17T01:36:05.983505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:06.096930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
기념품종류 64
 
0.8%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
기획여행보험시작일자
 
64

Length

Max length10
Median length4
Mean length4.0452937
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> 8414
99.2%
기획여행보험시작일자 64
 
0.8%

Length

2024-04-17T01:36:06.185013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:06.269390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
기획여행보험시작일자 64
 
0.8%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
기획여행보험종료일자
 
64

Length

Max length10
Median length4
Mean length4.0452937
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> 8414
99.2%
기획여행보험종료일자 64
 
0.8%

Length

2024-04-17T01:36:06.358818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:06.445990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
기획여행보험종료일자 64
 
0.8%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
7904 
0
 
492
남성종사자수
 
52
1
 
12
3
 
5
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.8276716
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> 7904
93.2%
0 492
 
5.8%
남성종사자수 52
 
0.6%
1 12
 
0.1%
3 5
 
0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
35 1
 
< 0.1%

Length

2024-04-17T01:36:06.536894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7904
93.2%
0 492
 
5.8%
남성종사자수 52
 
0.6%
1 12
 
0.1%
3 5
 
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 size66.4 KiB
<NA>
8414 
놀이기구수내역
 
64

Length

Max length7
Median length4
Mean length4.0226469
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> 8414
99.2%
놀이기구수내역 64
 
0.8%

Length

2024-04-17T01:36:06.654405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:06.740560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
놀이기구수내역 64
 
0.8%

playfacilcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
N
8074 
<NA>
 
357
놀이시설수
 
44
Y
 
3

Length

Max length5
Median length1
Mean length1.1470866
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8074
95.2%
<NA> 357
 
4.2%
놀이시설수 44
 
0.5%
Y 3
 
< 0.1%

Length

2024-04-17T01:36:06.830580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:06.926020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8074
95.2%
na 357
 
4.2%
놀이시설수 44
 
0.5%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
N
8395 
<NA>
 
61
 
13
Y
 
9

Length

Max length4
Median length1
Mean length1.0215853
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8395
99.0%
<NA> 61
 
0.7%
13
 
0.2%
Y 9
 
0.1%

Length

2024-04-17T01:36:07.022755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:07.136180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8395
99.0%
na 61
 
0.7%
13
 
0.2%
y 9
 
0.1%

stagear
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
무대면적
 
64

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> 8414
99.2%
무대면적 64
 
0.8%

Length

2024-04-17T01:36:07.226630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:07.310917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
무대면적 64
 
0.8%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
문화사업자구분명
 
64

Length

Max length8
Median length4
Mean length4.0301958
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> 8414
99.2%
문화사업자구분명 64
 
0.8%

Length

2024-04-17T01:36:07.429369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:07.528002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
문화사업자구분명 64
 
0.8%

culphyedcobnm
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8098 
외국인관광 도시민박업
 
262
관광숙박업
 
72
문화체육업종명
 
33
자동차야영장업
 
9
Other values (2)
 
4

Length

Max length11
Median length4
Mean length4.240151
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> 8098
95.5%
외국인관광 도시민박업 262
 
3.1%
관광숙박업 72
 
0.8%
문화체육업종명 33
 
0.4%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 1
 
< 0.1%

Length

2024-04-17T01:36:07.636318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:07.738123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8098
92.7%
외국인관광 262
 
3.0%
도시민박업 262
 
3.0%
관광숙박업 72
 
0.8%
문화체육업종명 33
 
0.4%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 1
 
< 0.1%

geicpfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
 
64

Length

Max length4
Median length4
Mean length3.9773531
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> 8414
99.2%
64
 
0.8%

Length

2024-04-17T01:36:07.857576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:07.946700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
64
 
0.8%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
N
8380 
<NA>
 
61
Y
 
24
 
13

Length

Max length4
Median length1
Mean length1.0215853
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8380
98.8%
<NA> 61
 
0.7%
Y 24
 
0.3%
13
 
0.2%

Length

2024-04-17T01:36:08.036026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:08.155635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8380
98.8%
na 61
 
0.7%
y 24
 
0.3%
13
 
0.2%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
 
64

Length

Max length4
Median length4
Mean length3.9773531
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> 8414
99.2%
64
 
0.8%

Length

2024-04-17T01:36:08.258532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:08.349780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
64
 
0.8%

insurorgnm
Categorical

IMBALANCE 

Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8393 
보험기관명
 
61
객실수/수용인원 : 2개/ 6명
 
2
DB 손해보험
 
2
객실수/수용인원:3/10
 
1
Other values (19)
 
19

Length

Max length22
Median length4
Mean length4.027247
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> 8393
99.0%
보험기관명 61
 
0.7%
객실수/수용인원 : 2개/ 6명 2
 
< 0.1%
DB 손해보험 2
 
< 0.1%
객실수/수용인원:3/10 1
 
< 0.1%
객실수/수용인원:2/3 1
 
< 0.1%
객실수/수용인원:2/5 1
 
< 0.1%
객실수2/수용인원12 1
 
< 0.1%
객실수/수용인원 : 2개/10명 1
 
< 0.1%
객실수/수용인원 : 3/8 1
 
< 0.1%
Other values (14) 14
 
0.2%

Length

2024-04-17T01:36:08.446275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8393
98.8%
보험기관명 61
 
0.7%
객실수/수용인원 6
 
0.1%
5
 
0.1%
3/8 2
 
< 0.1%
2개 2
 
< 0.1%
6명 2
 
< 0.1%
db 2
 
< 0.1%
손해보험 2
 
< 0.1%
민박)객실3(20명 1
 
< 0.1%
Other values (21) 21
 
0.2%

insurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
보험시작일자
 
64

Length

Max length6
Median length4
Mean length4.0150979
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> 8414
99.2%
보험시작일자 64
 
0.8%

Length

2024-04-17T01:36:08.557692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:08.654181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
보험시작일자 64
 
0.8%

insurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
보험종료일자
 
64

Length

Max length6
Median length4
Mean length4.0150979
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> 8414
99.2%
보험종료일자 64
 
0.8%

Length

2024-04-17T01:36:08.753344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:08.848377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
보험종료일자 64
 
0.8%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
부대시설내역
 
64

Length

Max length6
Median length4
Mean length4.0150979
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> 8414
99.2%
부대시설내역 64
 
0.8%

Length

2024-04-17T01:36:08.938787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:09.038463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
부대시설내역 64
 
0.8%

usejisgendflr
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
2684 
0
1974 
4
755 
3
646 
5
469 
Other values (30)
1950 

Length

Max length6
Median length1
Mean length2.007313
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2684
31.7%
0 1974
23.3%
4 755
 
8.9%
3 646
 
7.6%
5 469
 
5.5%
6 415
 
4.9%
2 387
 
4.6%
7 267
 
3.1%
8 253
 
3.0%
9 187
 
2.2%
Other values (25) 441
 
5.2%

Length

2024-04-17T01:36:09.141896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2684
31.7%
0 1974
23.3%
4 755
 
8.9%
3 646
 
7.6%
5 469
 
5.5%
6 415
 
4.9%
2 387
 
4.6%
7 267
 
3.1%
8 253
 
3.0%
9 187
 
2.2%
Other values (25) 441
 
5.2%

useunderendflr
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
4629 
<NA>
3601 
1
 
182
사용끝지하층
 
34
2
 
16
Other values (5)
 
16

Length

Max length6
Median length1
Mean length2.294645
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4629
54.6%
<NA> 3601
42.5%
1 182
 
2.1%
사용끝지하층 34
 
0.4%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
10 2
 
< 0.1%
19 1
 
< 0.1%

Length

2024-04-17T01:36:09.248877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:09.353613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4629
54.6%
na 3601
42.5%
1 182
 
2.1%
사용끝지하층 34
 
0.4%
2 16
 
0.2%
7 5
 
0.1%
4 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 size66.4 KiB
0
2469 
1
1900 
<NA>
1856 
2
979 
3
505 
Other values (15)
769 

Length

Max length7
Median length1
Mean length1.6857749
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2469
29.1%
1 1900
22.4%
<NA> 1856
21.9%
2 979
 
11.5%
3 505
 
6.0%
4 305
 
3.6%
5 196
 
2.3%
6 69
 
0.8%
7 59
 
0.7%
8 34
 
0.4%
Other values (10) 106
 
1.3%

Length

2024-04-17T01:36:09.494121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2469
29.1%
1 1900
22.4%
na 1856
21.9%
2 979
 
11.5%
3 505
 
6.0%
4 305
 
3.6%
5 196
 
2.3%
6 69
 
0.8%
7 59
 
0.7%
8 34
 
0.4%
Other values (10) 106
 
1.3%

useunderstflr
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
5568 
<NA>
2650 
1
 
213
사용시작지하층
 
34
4
 
8
Other values (3)
 
5

Length

Max length7
Median length1
Mean length1.9617834
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5568
65.7%
<NA> 2650
31.3%
1 213
 
2.5%
사용시작지하층 34
 
0.4%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:36:09.597615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:09.709199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5568
65.7%
na 2650
31.3%
1 213
 
2.5%
사용시작지하층 34
 
0.4%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

shpinfo
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
선박제원
 
64

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> 8414
99.2%
선박제원 64
 
0.8%

Length

2024-04-17T01:36:09.827128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:09.918945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
선박제원 64
 
0.8%

shpcnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
선박척수
 
64

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> 8414
99.2%
선박척수 64
 
0.8%

Length

2024-04-17T01:36:10.011374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:10.088960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
선박척수 64
 
0.8%

shptottons
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
선박총톤수
 
64

Length

Max length5
Median length4
Mean length4.007549
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> 8414
99.2%
선박총톤수 64
 
0.8%

Length

2024-04-17T01:36:10.179974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:10.279375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
선박총톤수 64
 
0.8%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
4975 
<NA>
3472 
세탁기수
 
31

Length

Max length4
Median length1
Mean length2.2395612
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4975
58.7%
<NA> 3472
41.0%
세탁기수 31
 
0.4%

Length

2024-04-17T01:36:10.371883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:10.459384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4975
58.7%
na 3472
41.0%
세탁기수 31
 
0.4%

facilscp
Text

MISSING 

Distinct142
Distinct (%)45.7%
Missing8167
Missing (%)96.3%
Memory size66.4 KiB
2024-04-17T01:36:10.707685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.8231511
Min length2

Characters and Unicode

Total characters878
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 (%)24.8%

Sample

1st row시설규모
2nd row시설규모
3rd row시설규모
4th row시설규모
5th row시설규모
ValueCountFrequency (%)
시설규모 39
 
12.5%
85 15
 
4.8%
46 7
 
2.3%
60 6
 
1.9%
83 6
 
1.9%
599 6
 
1.9%
63 5
 
1.6%
67 5
 
1.6%
80 4
 
1.3%
84 4
 
1.3%
Other values (132) 214
68.8%
2024-04-17T01:36:11.097375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 111
12.6%
5 86
9.8%
8 79
9.0%
2 69
7.9%
6 67
7.6%
9 66
7.5%
4 65
7.4%
7 65
7.4%
3 62
 
7.1%
0 52
 
5.9%
Other values (4) 156
17.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 722
82.2%
Other Letter 156
 
17.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 111
15.4%
5 86
11.9%
8 79
10.9%
2 69
9.6%
6 67
9.3%
9 66
9.1%
4 65
9.0%
7 65
9.0%
3 62
8.6%
0 52
7.2%
Other Letter
ValueCountFrequency (%)
39
25.0%
39
25.0%
39
25.0%
39
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 722
82.2%
Hangul 156
 
17.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 111
15.4%
5 86
11.9%
8 79
10.9%
2 69
9.6%
6 67
9.3%
9 66
9.1%
4 65
9.0%
7 65
9.0%
3 62
8.6%
0 52
7.2%
Hangul
ValueCountFrequency (%)
39
25.0%
39
25.0%
39
25.0%
39
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 722
82.2%
Hangul 156
 
17.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 111
15.4%
5 86
11.9%
8 79
10.9%
2 69
9.6%
6 67
9.3%
9 66
9.1%
4 65
9.0%
7 65
9.0%
3 62
8.6%
0 52
7.2%
Hangul
ValueCountFrequency (%)
39
25.0%
39
25.0%
39
25.0%
39
25.0%

facilar
Text

MISSING 

Distinct205
Distinct (%)65.9%
Missing8167
Missing (%)96.3%
Memory size66.4 KiB
2024-04-17T01:36:11.436029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.0868167
Min length2

Characters and Unicode

Total characters1582
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

Unique166 ?
Unique (%)53.4%

Sample

1st row시설면적
2nd row시설면적
3rd row시설면적
4th row시설면적
5th row시설면적
ValueCountFrequency (%)
시설면적 39
 
12.5%
45.5 6
 
1.9%
598.73 6
 
1.9%
62.58 4
 
1.3%
62.25 3
 
1.0%
218.85 3
 
1.0%
1497.35 3
 
1.0%
57.09 3
 
1.0%
167.82 3
 
1.0%
8546.81 3
 
1.0%
Other values (195) 238
76.5%
2024-04-17T01:36:11.886194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 248
15.7%
1 156
9.9%
4 145
9.2%
8 141
8.9%
5 122
7.7%
6 113
7.1%
2 113
7.1%
3 112
7.1%
9 106
6.7%
7 103
6.5%
Other values (5) 223
14.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1178
74.5%
Other Punctuation 248
 
15.7%
Other Letter 156
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 156
13.2%
4 145
12.3%
8 141
12.0%
5 122
10.4%
6 113
9.6%
2 113
9.6%
3 112
9.5%
9 106
9.0%
7 103
8.7%
0 67
5.7%
Other Letter
ValueCountFrequency (%)
39
25.0%
39
25.0%
39
25.0%
39
25.0%
Other Punctuation
ValueCountFrequency (%)
. 248
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1426
90.1%
Hangul 156
 
9.9%

Most frequent character per script

Common
ValueCountFrequency (%)
. 248
17.4%
1 156
10.9%
4 145
10.2%
8 141
9.9%
5 122
8.6%
6 113
7.9%
2 113
7.9%
3 112
7.9%
9 106
7.4%
7 103
7.2%
Hangul
ValueCountFrequency (%)
39
25.0%
39
25.0%
39
25.0%
39
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1426
90.1%
Hangul 156
 
9.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 248
17.4%
1 156
10.9%
4 145
10.2%
8 141
9.9%
5 122
8.6%
6 113
7.9%
2 113
7.9%
3 112
7.9%
9 106
7.4%
7 103
7.2%
Hangul
ValueCountFrequency (%)
39
25.0%
39
25.0%
39
25.0%
39
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
 
64

Length

Max length4
Median length4
Mean length3.9773531
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> 8414
99.2%
64
 
0.8%

Length

2024-04-17T01:36:12.013894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:12.093949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
64
 
0.8%

yangsilcnt
Text

MISSING 

Distinct148
Distinct (%)2.0%
Missing899
Missing (%)10.6%
Memory size66.4 KiB
2024-04-17T01:36:12.244925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7386199
Min length1

Characters and Unicode

Total characters13177
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
 
13.7%
10 439
 
5.8%
18 368
 
4.9%
12 318
 
4.2%
14 314
 
4.1%
15 302
 
4.0%
13 248
 
3.3%
19 242
 
3.2%
17 222
 
2.9%
16 219
 
2.9%
Other values (138) 3866
51.0%
2024-04-17T01:36:12.559208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3431
26.0%
0 1920
14.6%
2 1872
14.2%
3 1342
 
10.2%
4 1039
 
7.9%
5 822
 
6.2%
8 812
 
6.2%
6 631
 
4.8%
9 614
 
4.7%
7 601
 
4.6%
Other values (3) 93
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13084
99.3%
Other Letter 93
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3431
26.2%
0 1920
14.7%
2 1872
14.3%
3 1342
 
10.3%
4 1039
 
7.9%
5 822
 
6.3%
8 812
 
6.2%
6 631
 
4.8%
9 614
 
4.7%
7 601
 
4.6%
Other Letter
ValueCountFrequency (%)
31
33.3%
31
33.3%
31
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13084
99.3%
Hangul 93
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3431
26.2%
0 1920
14.7%
2 1872
14.3%
3 1342
 
10.3%
4 1039
 
7.9%
5 822
 
6.3%
8 812
 
6.2%
6 631
 
4.8%
9 614
 
4.7%
7 601
 
4.6%
Hangul
ValueCountFrequency (%)
31
33.3%
31
33.3%
31
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13084
99.3%
Hangul 93
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3431
26.2%
0 1920
14.7%
2 1872
14.3%
3 1342
 
10.3%
4 1039
 
7.9%
5 822
 
6.3%
8 812
 
6.2%
6 631
 
4.8%
9 614
 
4.7%
7 601
 
4.6%
Hangul
ValueCountFrequency (%)
31
33.3%
31
33.3%
31
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
7906 
0
 
498
여성종사자수
 
52
2
 
6
1
 
6
Other values (4)
 
10

Length

Max length6
Median length4
Mean length3.8286152
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> 7906
93.3%
0 498
 
5.9%
여성종사자수 52
 
0.6%
2 6
 
0.1%
1 6
 
0.1%
3 5
 
0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

Length

2024-04-17T01:36:12.676305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:13.077478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7906
93.3%
0 498
 
5.9%
여성종사자수 52
 
0.6%
2 6
 
0.1%
1 6
 
0.1%
3 5
 
0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

engstntrnmnm
Categorical

IMBALANCE 

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8356 
영문상호명
 
61
CheonghakSodam
 
3
Emerald ocean view
 
3
ocean house
 
3
Other values (41)
 
52

Length

Max length45
Median length4
Mean length4.0911772
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> 8356
98.6%
영문상호명 61
 
0.7%
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%
YoonSeulga 2
 
< 0.1%
Other values (36) 38
 
0.4%

Length

2024-04-17T01:36:13.188920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8356
97.6%
영문상호명 61
 
0.7%
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%
brown-dot 3
 
< 0.1%
in 3
 
< 0.1%
Other values (55) 81
 
0.9%

engstntrnmaddr
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8359 
영문상호주소
 
61
Guesthouse for Foreign Tourists
 
15
Foreigner Tourism City home-stay Business
 
14
Guest House
 
4
Other values (15)
 
25

Length

Max length41
Median length4
Mean length4.1968625
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> 8359
98.6%
영문상호주소 61
 
0.7%
Guesthouse for Foreign Tourists 15
 
0.2%
Foreigner Tourism City home-stay Business 14
 
0.2%
Guest House 4
 
< 0.1%
Entertainment Business for foreigner only 3
 
< 0.1%
Oversea Travel Business 3
 
< 0.1%
TOURIST ACCOMMODATION 3
 
< 0.1%
TOURIST ACCOMMODATION (hostel) 3
 
< 0.1%
Hostel(Guesthouse) 2
 
< 0.1%
Other values (10) 11
 
0.1%

Length

2024-04-17T01:36:13.309106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8359
96.7%
영문상호주소 61
 
0.7%
for 22
 
0.3%
business 22
 
0.3%
foreign 21
 
0.2%
foreigner 19
 
0.2%
guesthouse 18
 
0.2%
tourists 18
 
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 size66.4 KiB
0
5819 
<NA>
2440 
욕실수
 
31
15
 
16
12
 
14
Other values (28)
 
158

Length

Max length4
Median length1
Mean length1.8903043
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5819
68.6%
<NA> 2440
28.8%
욕실수 31
 
0.4%
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

2024-04-17T01:36:13.428370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 5819
68.6%
na 2440
28.8%
욕실수 31
 
0.4%
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 size66.4 KiB
여관업
5271 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
486
일반호텔
 
425
Other values (4)
631 

Length

Max length8
Median length3
Mean length3.6970984
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5271
62.2%
여인숙업 1076
 
12.7%
숙박업 기타 589
 
6.9%
숙박업(생활) 486
 
5.7%
일반호텔 425
 
5.0%
<NA> 321
 
3.8%
관광호텔 270
 
3.2%
위생업태명 31
 
0.4%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:36:13.532674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:13.633860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5271
58.1%
여인숙업 1076
 
11.9%
숙박업 589
 
6.5%
기타 589
 
6.5%
숙박업(생활 486
 
5.4%
일반호텔 425
 
4.7%
na 321
 
3.5%
관광호텔 270
 
3.0%
위생업태명 31
 
0.3%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
 
64

Length

Max length4
Median length4
Mean length3.9773531
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> 8414
99.2%
64
 
0.8%

Length

2024-04-17T01:36:13.747120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:13.833828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
64
 
0.8%

capt
Categorical

IMBALANCE 

Distinct39
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8334 
자본금
 
50
10000000
 
18
100000000
 
12
200000000
 
7
Other values (34)
 
57

Length

Max length10
Median length4
Mean length4.0424628
Min length3

Unique

Unique21 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8334
98.3%
자본금 50
 
0.6%
10000000 18
 
0.2%
100000000 12
 
0.1%
200000000 7
 
0.1%
20000000 5
 
0.1%
50000000 5
 
0.1%
300000000 4
 
< 0.1%
12000000 3
 
< 0.1%
12500000 3
 
< 0.1%
Other values (29) 37
 
0.4%

Length

2024-04-17T01:36:13.945427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8334
98.3%
자본금 50
 
0.6%
10000000 18
 
0.2%
100000000 12
 
0.1%
200000000 7
 
0.1%
20000000 5
 
0.1%
50000000 5
 
0.1%
300000000 4
 
< 0.1%
12000000 3
 
< 0.1%
12500000 3
 
< 0.1%
Other values (29) 37
 
0.4%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
제작취급품목내용
 
64

Length

Max length8
Median length4
Mean length4.0301958
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> 8414
99.2%
제작취급품목내용 64
 
0.8%

Length

2024-04-17T01:36:14.054726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:14.156219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
제작취급품목내용 64
 
0.8%

cndpermstymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8412 
조건부허가시작일자
 
64
20180202
 
2

Length

Max length9
Median length4
Mean length4.0386884
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> 8412
99.2%
조건부허가시작일자 64
 
0.8%
20180202 2
 
< 0.1%

Length

2024-04-17T01:36:14.243531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:14.331237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8412
99.2%
조건부허가시작일자 64
 
0.8%
20180202 2
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
조건부허가신고사유
 
64

Length

Max length9
Median length4
Mean length4.0377448
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> 8414
99.2%
조건부허가신고사유 64
 
0.8%

Length

2024-04-17T01:36:14.452576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:14.554093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
조건부허가신고사유 64
 
0.8%

cndpermendymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8412 
조건부허가종료일자
 
64
20190202
 
2

Length

Max length9
Median length4
Mean length4.0386884
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> 8412
99.2%
조건부허가종료일자 64
 
0.8%
20190202 2
 
< 0.1%

Length

2024-04-17T01:36:14.639460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:14.723867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8412
99.2%
조건부허가종료일자 64
 
0.8%
20190202 2
 
< 0.1%

chaircnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
5262 
0
3180 
좌석수
 
31
6
 
1
12
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length2.8694268
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5262
62.1%
0 3180
37.5%
좌석수 31
 
0.4%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-17T01:36:14.815131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:14.930585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5262
62.1%
0 3180
37.5%
좌석수 31
 
0.4%
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 size66.4 KiB
<NA>
8321 
주변환경명
 
59
주택가주변
 
32
아파트지역
 
29
기타
 
22
Other values (3)
 
15

Length

Max length8
Median length4
Mean length4.0160415
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> 8321
98.1%
주변환경명 59
 
0.7%
주택가주변 32
 
0.4%
아파트지역 29
 
0.3%
기타 22
 
0.3%
학교정화(상대) 12
 
0.1%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-17T01:36:15.035311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:15.132231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8321
98.1%
주변환경명 59
 
0.7%
주택가주변 32
 
0.4%
아파트지역 29
 
0.3%
기타 22
 
0.3%
학교정화(상대 12
 
0.1%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대 1
 
< 0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8295 
지상층수
 
47
2
 
31
4
 
18
1
 
13
Other values (19)
 
74

Length

Max length4
Median length4
Mean length3.9561217
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8295
97.8%
지상층수 47
 
0.6%
2 31
 
0.4%
4 18
 
0.2%
1 13
 
0.2%
3 13
 
0.2%
5 8
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
19 6
 
0.1%
Other values (14) 33
 
0.4%

Length

2024-04-17T01:36:15.238699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8295
97.8%
지상층수 47
 
0.6%
2 31
 
0.4%
4 18
 
0.2%
1 13
 
0.2%
3 13
 
0.2%
5 8
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
19 6
 
0.1%
Other values (14) 33
 
0.4%

regnsenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8217 
일반주거지역
 
109
지역구분명
 
46
일반상업지역
 
37
주거지역
 
30
Other values (4)
 
39

Length

Max length6
Median length4
Mean length4.0439962
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> 8217
96.9%
일반주거지역 109
 
1.3%
지역구분명 46
 
0.5%
일반상업지역 37
 
0.4%
주거지역 30
 
0.4%
준주거지역 25
 
0.3%
상업지역 6
 
0.1%
자연녹지지역 5
 
0.1%
녹지지역 3
 
< 0.1%

Length

2024-04-17T01:36:15.358926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:15.491255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8217
96.9%
일반주거지역 109
 
1.3%
지역구분명 46
 
0.5%
일반상업지역 37
 
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 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8367 
지하층수
 
51
1
 
26
2
 
20
0
 
9
Other values (4)
 
5

Length

Max length4
Median length4
Mean length3.9787686
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8367
98.7%
지하층수 51
 
0.6%
1 26
 
0.3%
2 20
 
0.2%
0 9
 
0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:36:15.598649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:15.710222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8367
98.7%
지하층수 51
 
0.6%
1 26
 
0.3%
2 20
 
0.2%
0 9
 
0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

totnumlay
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8279 
총층수
 
46
2
 
36
4
 
20
1
 
18
Other values (20)
 
79

Length

Max length4
Median length4
Mean length3.9446803
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> 8279
97.7%
총층수 46
 
0.5%
2 36
 
0.4%
4 20
 
0.2%
1 18
 
0.2%
3 17
 
0.2%
5 12
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
11 6
 
0.1%
Other values (15) 30
 
0.4%

Length

2024-04-17T01:36:15.822266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8279
97.7%
총층수 46
 
0.5%
2 36
 
0.4%
4 20
 
0.2%
1 18
 
0.2%
3 17
 
0.2%
5 12
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
11 6
 
0.1%
Other values (15) 30
 
0.4%

abedcnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
4929 
<NA>
3516 
침대수
 
31
41
 
2

Length

Max length4
Median length1
Mean length2.2517103
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4929
58.1%
<NA> 3516
41.5%
침대수 31
 
0.4%
41 2
 
< 0.1%

Length

2024-04-17T01:36:15.944599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:16.043991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4929
58.1%
na 3516
41.5%
침대수 31
 
0.4%
41 2
 
< 0.1%

hanshilcnt
Categorical

Distinct48
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
3711 
<NA>
1462 
2
 
326
10
 
310
3
 
268
Other values (43)
2401 

Length

Max length4
Median length1
Mean length1.6748054
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3711
43.8%
<NA> 1462
 
17.2%
2 326
 
3.8%
10 310
 
3.7%
3 268
 
3.2%
1 262
 
3.1%
8 226
 
2.7%
4 203
 
2.4%
6 200
 
2.4%
9 197
 
2.3%
Other values (38) 1313
 
15.5%

Length

2024-04-17T01:36:16.147271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3711
43.8%
na 1462
 
17.2%
2 326
 
3.8%
10 310
 
3.7%
3 268
 
3.2%
1 262
 
3.1%
8 226
 
2.7%
4 203
 
2.4%
6 200
 
2.4%
9 197
 
2.3%
Other values (38) 1313
 
15.5%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
4937 
<NA>
3510 
회수건조수
 
31

Length

Max length5
Median length1
Mean length2.2566643
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4937
58.2%
<NA> 3510
41.4%
회수건조수 31
 
0.4%

Length

2024-04-17T01:36:16.254750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:16.357054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4937
58.2%
na 3510
41.4%
회수건조수 31
 
0.4%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8414 
회의실별동시수용인원
 
64

Length

Max length10
Median length4
Mean length4.0452937
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> 8414
99.2%
회의실별동시수용인원 64
 
0.8%

Length

2024-04-17T01:36:16.464173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:16.570959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8414
99.2%
회의실별동시수용인원 64
 
0.8%

last_load_dttm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
2021-05-01 05:09:04
4743 
2021-05-01 05:09:03
2859 
2021-05-01 05:09:05
870 
<NA>
 
6

Length

Max length19
Median length19
Mean length18.989384
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021-05-01 05:09:04 4743
55.9%
2021-05-01 05:09:03 2859
33.7%
2021-05-01 05:09:05 870
 
10.3%
<NA> 6
 
0.1%

Length

2024-04-17T01:36:16.675989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:16.792133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-05-01 8472
50.0%
05:09:04 4743
28.0%
05:09:03 2859
 
16.9%
05:09:05 870
 
5.1%
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>2021-05-01 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>2021-05-01 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>2021-05-01 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>2021-05-01 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>2021-05-01 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>2021-05-01 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>2021-05-01 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>2021-05-01 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>2021-05-01 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>2021-05-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
8468130243330000CDFI226221201200000403_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>2021-05-01 05:09:05
84691302532700003270000-214-2021-0000103_11_03_PU2021-04-17 02:40:00.0숙박업마리나레지던스호텔601829부산광역시 동구 초량동 503-5 조이팰리스48816.0부산광역시 동구 대영로243번길 73-5, 조이팰리스 2~7층 (초량동)20210322폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업385803.690264516181505.3492220210415160915숙박업(생활)전화번호객실수건물소유구분명건물용도명131건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수N무대면적문화사업자구분명문화체육업종명N보험기관명보험시작일자보험종료일자부대시설내역7020선박제원선박척수선박총톤수0시설규모시설면적24여성종사자수영문상호명영문상호주소0숙박업(생활)자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주변환경명지상층수지역구분명지하층수총층수000회의실별동시수용인원2021-05-01 05:09:05
8470130263340000CDFI226221202100000103_11_04_PI2021-03-26 00:22:59.0외국인관광도시민박업감천하텔지번우편번호부산광역시 사하구 감천동 31-149375.0부산광역시 사하구 감천로139번길 39 (감천동)20210324폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중382892.97830771178418.25355420210324104432업태구분명전화번호객실수건물소유구분명단독주택건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수4040.46양실수여성종사자수영문상호명영문상호주소욕실수위생업태명2000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주택가주변4일반주거지역지하층수4침대수한실수회수건조수회의실별동시수용인원2021-05-01 05:09:05
84711302733600003360000-201-2021-0000103_11_03_PU2021-04-21 02:40:00.0숙박업신라스테이 서부산618200부산광역시 강서구 명지동 3595-1 신라스테이 서부산점46726.0부산광역시 강서구 명지국제7로 38, 신라스테이 서부산점 (명지동)20210331<NA><NA><NA><NA>영업/정상영업373665.73430842179173.52698920210419165344관광호텔051 661 9000<NA><NA><NA>233<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>2910<NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>040<NA>2021-05-01 05:09:05
84721302833300003330000-214-2021-0000203_11_03_PI2021-04-02 00:22:59.0숙박업벨리아(BELLIA)612847부산광역시 해운대구 중동 1123 해운대푸르지오시티48099.0부산광역시 해운대구 해운대해변로298번길 29, 해운대푸르지오시티 (중동)20210331<NA><NA><NA><NA>영업/정상영업397359.716406649186807.81129920210331103454숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>3<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>22737<NA><NA><NA>0<NA><NA><NA>300<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-05-01 05:09:05
84731302933800003380000-214-2021-0000403_11_03_PU2021-05-01 02:40:00.0숙박업위더스오션613805부산광역시 수영구 광안동 201-1 광안 지웰에스테이트 더 테라스48303.0부산광역시 수영구 광남로94번길 16, 광안 지웰에스테이트 더 테라스 3~19층 305호 외 33개호 (광안동)20210406<NA><NA><NA><NA>영업/정상영업392691.625721388185474.22691320210429170842숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>19030<NA><NA><NA>0<NA><NA><NA>340<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-05-01 05:09:05
84741303033300003330000-214-2021-0000303_11_03_PU2021-04-21 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073.0부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504720210419133601숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5<NA>1<NA><NA><NA><NA>0<NA><NA><NA>82<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-05-01 05:09:05
8475130313280000CDFI226221202100000103_11_04_PI2021-04-18 00:22:58.0외국인관광도시민박업윤슬가<NA>부산광역시 영도구 청학동 398-1549031.0부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415<NA><NA><NA><NA>영업/정상영업중387608.397605613179078.07581920210416160045<NA><NA><NA><NA>단독주택<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>4545.45<NA><NA><NA>YoonSeulgaGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA><NA>주택가주변1일반주거지역<NA>1<NA><NA><NA><NA>2021-05-01 05:09:05
84761303233300003330000-214-2021-0000303_11_03_PU2021-04-21 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073.0부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504720210419133601숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5<NA>1<NA><NA><NA><NA>0<NA><NA><NA>82<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-05-01 05:09:05
8477130333280000CDFI226221202100000103_11_04_PI2021-04-18 00:22:58.0외국인관광도시민박업윤슬가<NA>부산광역시 영도구 청학동 398-1549031.0부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415<NA><NA><NA><NA>영업/정상영업중387608.397605613179078.07581920210416160045<NA><NA><NA><NA>단독주택<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>4545.45<NA><NA><NA>YoonSeulgaGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA><NA>주택가주변1일반주거지역<NA>1<NA><NA><NA><NA>2021-05-01 05:09:05

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnwhladdrdcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
263330000CDFI226003201800000503_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>2021-05-01 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>2021-05-01 05:09:053
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>2021-05-01 05:09:053
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>2021-05-01 05:09:053
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>2021-05-01 05:09:053
93280000CDFI226221202000000103_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>2021-05-01 05:09:053
103280000CDFI226221202000000203_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>2021-05-01 05:09:053
113280000CDFI226221202000000303_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>2021-05-01 05:09:053
1532900003290000-201-2019-0000203_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>2021-05-01 05:09:053
1632900003290000-201-2020-0000103_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>2021-05-01 05:09:053