Overview

Dataset statistics

Number of variables81
Number of observations8527
Missing cells25567
Missing cells (%)3.7%
Duplicate rows258
Duplicate rows (%)3.0%
Total size in memory5.3 MiB
Average record size in memory650.0 B

Variable types

Unsupported5
Numeric2
Text10
Categorical62
DateTime2

Alerts

Dataset has 258 (3.0%) duplicate rowsDuplicates
engstntrnmnm has a high cardinality: 51 distinct valuesHigh cardinality
opnsvcid is highly imbalanced (89.5%)Imbalance
updategbn is highly imbalanced (65.8%)Imbalance
opnsvcnm is highly imbalanced (76.6%)Imbalance
clgstdt is highly imbalanced (96.1%)Imbalance
clgenddt is highly imbalanced (96.0%)Imbalance
ropnymd is highly imbalanced (88.6%)Imbalance
dtlstatenm is highly imbalanced (53.6%)Imbalance
stroomcnt is highly imbalanced (94.4%)Imbalance
bdngsrvnm is highly imbalanced (91.6%)Imbalance
bdngunderflrcnt is highly imbalanced (54.9%)Imbalance
cnstyarea is highly imbalanced (96.2%)Imbalance
svnsr is highly imbalanced (88.6%)Imbalance
plninsurstdt is highly imbalanced (88.6%)Imbalance
plninsurenddt is highly imbalanced (88.6%)Imbalance
maneipcnt is highly imbalanced (85.9%)Imbalance
playutscntdtl is highly imbalanced (88.6%)Imbalance
playfacilcnt is highly imbalanced (74.2%)Imbalance
multusnupsoyn is highly imbalanced (93.1%)Imbalance
stagear is highly imbalanced (91.6%)Imbalance
culwrkrsenm is highly imbalanced (88.6%)Imbalance
culphyedcobnm is highly imbalanced (87.3%)Imbalance
geicpfacilen is highly imbalanced (88.6%)Imbalance
balhansilyn is highly imbalanced (92.4%)Imbalance
bcfacilen is highly imbalanced (88.6%)Imbalance
insurorgnm is highly imbalanced (96.7%)Imbalance
insurstdt is highly imbalanced (88.6%)Imbalance
insurenddt is highly imbalanced (88.6%)Imbalance
afc is highly imbalanced (88.6%)Imbalance
useunderendflr is highly imbalanced (63.5%)Imbalance
useunderstflr is highly imbalanced (62.5%)Imbalance
shpinfo is highly imbalanced (88.6%)Imbalance
shpcnt is highly imbalanced (91.6%)Imbalance
shptottons is highly imbalanced (91.6%)Imbalance
infoben is highly imbalanced (88.6%)Imbalance
wmeipcnt is highly imbalanced (84.9%)Imbalance
engstntrnmnm is highly imbalanced (96.3%)Imbalance
engstntrnmaddr is highly imbalanced (95.6%)Imbalance
yoksilcnt is highly imbalanced (76.9%)Imbalance
dispenen is highly imbalanced (88.6%)Imbalance
capt is highly imbalanced (95.1%)Imbalance
mnfactreartclcn is highly imbalanced (88.6%)Imbalance
cndpermstymd is highly imbalanced (88.6%)Imbalance
cndpermntwhy is highly imbalanced (88.6%)Imbalance
cndpermendymd is highly imbalanced (88.6%)Imbalance
chaircnt is highly imbalanced (65.7%)Imbalance
nearenvnm is highly imbalanced (92.5%)Imbalance
jisgnumlay is highly imbalanced (93.9%)Imbalance
regnsenm is highly imbalanced (90.3%)Imbalance
undernumlay is highly imbalanced (94.1%)Imbalance
totnumlay is highly imbalanced (93.5%)Imbalance
meetsamtimesygstf is highly imbalanced (91.6%)Imbalance
sitepostno has 299 (3.5%) missing valuesMissing
rdnwhladdr has 2550 (29.9%) missing valuesMissing
dcbymd has 4539 (53.2%) missing valuesMissing
x has 384 (4.5%) missing valuesMissing
y has 387 (4.5%) missing valuesMissing
sitetel has 142 (1.7%) missing valuesMissing
facilscp has 8151 (95.6%) missing valuesMissing
facilar has 8151 (95.6%) missing valuesMissing
yangsilcnt has 909 (10.7%) 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
y is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 16:34:13.617859
Analysis finished2024-04-16 16:34:16.095134
Duration2.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.7 KiB

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3318930.1
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.1 KiB
2024-04-17T01:34:16.137179image/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 deviation42878.974
Coefficient of variation (CV)0.012919517
Kurtosis-0.97558582
Mean3318930.1
Median Absolute Deviation (MAD)30000
Skewness0.26406885
Sum2.829056 × 1010
Variance1.8386064 × 109
MonotonicityNot monotonic
2024-04-17T01:34:16.232731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1161
13.6%
3290000 1060
12.4%
3300000 893
10.5%
3390000 689
8.1%
3270000 655
 
7.7%
3320000 578
 
6.8%
3380000 501
 
5.9%
3250000 484
 
5.7%
3260000 406
 
4.8%
3370000 383
 
4.5%
Other values (6) 1714
20.1%
ValueCountFrequency (%)
3250000 484
5.7%
3260000 406
 
4.8%
3270000 655
7.7%
3280000 369
 
4.3%
3290000 1060
12.4%
3300000 893
10.5%
3310000 285
 
3.3%
3320000 578
6.8%
3330000 1161
13.6%
3340000 359
 
4.2%
ValueCountFrequency (%)
3400000 210
 
2.5%
3390000 689
8.1%
3380000 501
5.9%
3370000 383
 
4.5%
3360000 138
 
1.6%
3350000 353
 
4.1%
3340000 359
 
4.2%
3330000 1161
13.6%
3320000 578
6.8%
3310000 285
 
3.3%

mgtno
Text

Distinct4231
Distinct (%)49.6%
Missing3
Missing (%)< 0.1%
Memory size66.7 KiB
2024-04-17T01:34:16.433719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.910371
Min length20

Characters and Unicode

Total characters186764
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

Unique147 ?
Unique (%)1.7%

Sample

1st row3250000-201-2017-00002
2nd row3250000-201-2014-00001
3rd row3250000-214-2017-00003
4th row3250000-201-1971-00116
5th row3250000-201-2012-00005
ValueCountFrequency (%)
cdfi2262212019000001 15
 
0.2%
cdfi2262212018000001 12
 
0.1%
cdfi2262212015000001 12
 
0.1%
cdfi2262212015000002 11
 
0.1%
cdfi2262212016000001 11
 
0.1%
cdfi2262212017000001 11
 
0.1%
cdfi2262212020000001 10
 
0.1%
cdfi2262212016000002 10
 
0.1%
cdfi2262212017000002 9
 
0.1%
cdfi2262212014000001 9
 
0.1%
Other values (4221) 8414
98.7%
2024-04-17T01:34:16.751415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71893
38.5%
- 24426
 
13.1%
1 20162
 
10.8%
2 20088
 
10.8%
3 18251
 
9.8%
9 10162
 
5.4%
8 4973
 
2.7%
7 4872
 
2.6%
6 3733
 
2.0%
4 3619
 
1.9%
Other values (5) 4585
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160810
86.1%
Dash Punctuation 24426
 
13.1%
Uppercase Letter 1528
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71893
44.7%
1 20162
 
12.5%
2 20088
 
12.5%
3 18251
 
11.3%
9 10162
 
6.3%
8 4973
 
3.1%
7 4872
 
3.0%
6 3733
 
2.3%
4 3619
 
2.3%
5 3057
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 382
25.0%
D 382
25.0%
F 382
25.0%
I 382
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24426
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 185236
99.2%
Latin 1528
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 71893
38.8%
- 24426
 
13.2%
1 20162
 
10.9%
2 20088
 
10.8%
3 18251
 
9.9%
9 10162
 
5.5%
8 4973
 
2.7%
7 4872
 
2.6%
6 3733
 
2.0%
4 3619
 
2.0%
Latin
ValueCountFrequency (%)
C 382
25.0%
D 382
25.0%
F 382
25.0%
I 382
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 186764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 71893
38.5%
- 24426
 
13.1%
1 20162
 
10.8%
2 20088
 
10.8%
3 18251
 
9.8%
9 10162
 
5.4%
8 4973
 
2.7%
7 4872
 
2.6%
6 3733
 
2.0%
4 3619
 
1.9%
Other values (5) 4585
 
2.5%

opnsvcid
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
03_11_03_P
8142 
03_11_04_P
 
285
03_11_01_P
 
82
03_11_05_P
 
9
03_11_02_P
 
3
Other values (3)
 
6

Length

Max length10
Median length10
Mean length9.9978891
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 8142
95.5%
03_11_04_P 285
 
3.3%
03_11_01_P 82
 
1.0%
03_11_05_P 9
 
0.1%
03_11_02_P 3
 
< 0.1%
<NA> 3
 
< 0.1%
03_11_06_P 2
 
< 0.1%
03_11_07_P 1
 
< 0.1%

Length

2024-04-17T01:34:16.872873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:16.975767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8142
95.5%
03_11_04_p 285
 
3.3%
03_11_01_p 82
 
1.0%
03_11_05_p 9
 
0.1%
03_11_02_p 3
 
< 0.1%
na 3
 
< 0.1%
03_11_06_p 2
 
< 0.1%
03_11_07_p 1
 
< 0.1%

updategbn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
I
7477 
U
1047 
180000000
 
3

Length

Max length9
Median length1
Mean length1.0028146
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7477
87.7%
U 1047
 
12.3%
180000000 3
 
< 0.1%

Length

2024-04-17T01:34:17.085233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:17.183010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7477
87.7%
u 1047
 
12.3%
180000000 3
 
< 0.1%
Distinct283
Distinct (%)3.3%
Missing3
Missing (%)< 0.1%
Memory size66.7 KiB
Minimum2018-08-31 23:59:59
Maximum2021-09-01 02:40:00
2024-04-17T01:34:17.281205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:34:17.402391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
7346 
숙박업
974 
외국인관광도시민박업
 
119
관광숙박업
 
82
자동차야영장업
 
2
Other values (3)
 
4

Length

Max length10
Median length4
Mean length3.9804152
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7346
86.1%
숙박업 974
 
11.4%
외국인관광도시민박업 119
 
1.4%
관광숙박업 82
 
1.0%
자동차야영장업 2
 
< 0.1%
한옥체험업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

Length

2024-04-17T01:34:17.520752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:17.628813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7346
86.1%
숙박업 974
 
11.4%
외국인관광도시민박업 119
 
1.4%
관광숙박업 82
 
1.0%
자동차야영장업 2
 
< 0.1%
한옥체험업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

bplcnm
Text

Distinct3416
Distinct (%)40.1%
Missing3
Missing (%)< 0.1%
Memory size66.7 KiB
2024-04-17T01:34:17.873280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length5.1941577
Min length1

Characters and Unicode

Total characters44275
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

Unique323 ?
Unique (%)3.8%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 칠구(K79)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 242
 
2.4%
모텔 186
 
1.8%
게스트하우스 121
 
1.2%
여관 82
 
0.8%
hotel 67
 
0.7%
부산 51
 
0.5%
house 48
 
0.5%
해운대 39
 
0.4%
37
 
0.4%
여인숙 36
 
0.4%
Other values (3517) 9281
91.1%
2024-04-17T01:34:18.230492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2934
 
6.6%
2013
 
4.5%
1789
 
4.0%
1749
 
4.0%
1683
 
3.8%
1522
 
3.4%
1384
 
3.1%
1273
 
2.9%
766
 
1.7%
754
 
1.7%
Other values (641) 28408
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37111
83.8%
Uppercase Letter 2486
 
5.6%
Space Separator 1683
 
3.8%
Lowercase Letter 1252
 
2.8%
Close Punctuation 532
 
1.2%
Open Punctuation 532
 
1.2%
Decimal Number 522
 
1.2%
Other Punctuation 102
 
0.2%
Dash Punctuation 31
 
0.1%
Letter Number 10
 
< 0.1%
Other values (4) 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2934
 
7.9%
2013
 
5.4%
1789
 
4.8%
1749
 
4.7%
1522
 
4.1%
1384
 
3.7%
1273
 
3.4%
766
 
2.1%
754
 
2.0%
622
 
1.7%
Other values (561) 22305
60.1%
Uppercase Letter
ValueCountFrequency (%)
E 262
 
10.5%
O 241
 
9.7%
H 226
 
9.1%
T 196
 
7.9%
S 171
 
6.9%
A 149
 
6.0%
L 146
 
5.9%
N 120
 
4.8%
U 103
 
4.1%
B 98
 
3.9%
Other values (16) 774
31.1%
Lowercase Letter
ValueCountFrequency (%)
e 202
16.1%
o 148
11.8%
a 104
8.3%
s 103
8.2%
n 95
 
7.6%
u 91
 
7.3%
t 87
 
6.9%
h 59
 
4.7%
l 58
 
4.6%
i 54
 
4.3%
Other values (16) 251
20.0%
Decimal Number
ValueCountFrequency (%)
2 130
24.9%
1 73
14.0%
5 66
12.6%
7 60
11.5%
9 57
10.9%
0 40
 
7.7%
6 33
 
6.3%
3 28
 
5.4%
4 25
 
4.8%
8 10
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 57
55.9%
& 25
24.5%
' 9
 
8.8%
, 6
 
5.9%
; 2
 
2.0%
2
 
2.0%
: 1
 
1.0%
Letter Number
ValueCountFrequency (%)
6
60.0%
4
40.0%
Math Symbol
ValueCountFrequency (%)
+ 4
66.7%
2
33.3%
Space Separator
ValueCountFrequency (%)
1683
100.0%
Close Punctuation
ValueCountFrequency (%)
) 532
100.0%
Open Punctuation
ValueCountFrequency (%)
( 532
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Symbol
ValueCountFrequency (%)
6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37109
83.8%
Latin 3748
 
8.5%
Common 3410
 
7.7%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2934
 
7.9%
2013
 
5.4%
1789
 
4.8%
1749
 
4.7%
1522
 
4.1%
1384
 
3.7%
1273
 
3.4%
766
 
2.1%
754
 
2.0%
622
 
1.7%
Other values (557) 22303
60.1%
Latin
ValueCountFrequency (%)
E 262
 
7.0%
O 241
 
6.4%
H 226
 
6.0%
e 202
 
5.4%
T 196
 
5.2%
S 171
 
4.6%
A 149
 
4.0%
o 148
 
3.9%
L 146
 
3.9%
N 120
 
3.2%
Other values (44) 1887
50.3%
Common
ValueCountFrequency (%)
1683
49.4%
) 532
 
15.6%
( 532
 
15.6%
2 130
 
3.8%
1 73
 
2.1%
5 66
 
1.9%
7 60
 
1.8%
9 57
 
1.7%
. 57
 
1.7%
0 40
 
1.2%
Other values (15) 180
 
5.3%
Han
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37103
83.8%
ASCII 7143
 
16.1%
Number Forms 10
 
< 0.1%
None 10
 
< 0.1%
CJK 8
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2934
 
7.9%
2013
 
5.4%
1789
 
4.8%
1749
 
4.7%
1522
 
4.1%
1384
 
3.7%
1273
 
3.4%
766
 
2.1%
754
 
2.0%
622
 
1.7%
Other values (556) 22297
60.1%
ASCII
ValueCountFrequency (%)
1683
23.6%
) 532
 
7.4%
( 532
 
7.4%
E 262
 
3.7%
O 241
 
3.4%
H 226
 
3.2%
e 202
 
2.8%
T 196
 
2.7%
S 171
 
2.4%
A 149
 
2.1%
Other values (64) 2949
41.3%
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 

Distinct494
Distinct (%)6.0%
Missing299
Missing (%)3.5%
Memory size66.7 KiB
2024-04-17T01:34:18.504252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters49368
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

Unique21 ?
Unique (%)0.3%

Sample

1st row600045
2nd row600051
3rd row600092
4th row600806
5th row600012
ValueCountFrequency (%)
612821 317
 
3.9%
616801 254
 
3.1%
612040 214
 
2.6%
612847 183
 
2.2%
607833 175
 
2.1%
601829 145
 
1.8%
617807 136
 
1.7%
613828 128
 
1.6%
607831 126
 
1.5%
607842 114
 
1.4%
Other values (484) 6436
78.2%
2024-04-17T01:34:18.891572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9849
20.0%
1 8055
16.3%
0 8003
16.2%
8 7937
16.1%
2 4304
8.7%
4 3451
 
7.0%
7 2601
 
5.3%
3 2458
 
5.0%
9 1407
 
2.9%
5 955
 
1.9%
Other values (5) 348
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49020
99.3%
Other Letter 348
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9849
20.1%
1 8055
16.4%
0 8003
16.3%
8 7937
16.2%
2 4304
8.8%
4 3451
 
7.0%
7 2601
 
5.3%
3 2458
 
5.0%
9 1407
 
2.9%
5 955
 
1.9%
Other Letter
ValueCountFrequency (%)
116
33.3%
58
16.7%
58
16.7%
58
16.7%
58
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 49020
99.3%
Hangul 348
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9849
20.1%
1 8055
16.4%
0 8003
16.3%
8 7937
16.2%
2 4304
8.8%
4 3451
 
7.0%
7 2601
 
5.3%
3 2458
 
5.0%
9 1407
 
2.9%
5 955
 
1.9%
Hangul
ValueCountFrequency (%)
116
33.3%
58
16.7%
58
16.7%
58
16.7%
58
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49020
99.3%
Hangul 348
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9849
20.1%
1 8055
16.4%
0 8003
16.3%
8 7937
16.2%
2 4304
8.8%
4 3451
 
7.0%
7 2601
 
5.3%
3 2458
 
5.0%
9 1407
 
2.9%
5 955
 
1.9%
Hangul
ValueCountFrequency (%)
116
33.3%
58
16.7%
58
16.7%
58
16.7%
58
16.7%
Distinct4100
Distinct (%)48.1%
Missing5
Missing (%)0.1%
Memory size66.7 KiB
2024-04-17T01:34:19.170001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length45
Mean length23.450481
Min length13

Characters and Unicode

Total characters199845
Distinct characters309
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

Unique266 ?
Unique (%)3.1%

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 8522
23.5%
해운대구 1161
 
3.2%
부산진구 1060
 
2.9%
동래구 893
 
2.5%
t통b반 868
 
2.4%
사상구 689
 
1.9%
동구 655
 
1.8%
온천동 644
 
1.8%
북구 582
 
1.6%
부전동 503
 
1.4%
Other values (4320) 20703
57.1%
2024-04-17T01:34:19.584498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36186
18.1%
10345
 
5.2%
10093
 
5.1%
9998
 
5.0%
8896
 
4.5%
8767
 
4.4%
1 8608
 
4.3%
8548
 
4.3%
8528
 
4.3%
- 7907
 
4.0%
Other values (299) 81969
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113551
56.8%
Decimal Number 39857
 
19.9%
Space Separator 36186
 
18.1%
Dash Punctuation 7907
 
4.0%
Uppercase Letter 1783
 
0.9%
Other Punctuation 194
 
0.1%
Open Punctuation 124
 
0.1%
Close Punctuation 124
 
0.1%
Math Symbol 115
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10345
 
9.1%
10093
 
8.9%
9998
 
8.8%
8896
 
7.8%
8767
 
7.7%
8548
 
7.5%
8528
 
7.5%
7728
 
6.8%
7513
 
6.6%
1606
 
1.4%
Other values (263) 31529
27.8%
Uppercase Letter
ValueCountFrequency (%)
B 876
49.1%
T 869
48.7%
A 11
 
0.6%
K 6
 
0.3%
C 5
 
0.3%
S 3
 
0.2%
O 3
 
0.2%
E 2
 
0.1%
G 2
 
0.1%
M 2
 
0.1%
Other values (4) 4
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 8608
21.6%
2 5239
13.1%
3 4195
10.5%
4 4053
10.2%
5 3930
9.9%
0 3068
 
7.7%
6 3032
 
7.6%
7 2849
 
7.1%
8 2576
 
6.5%
9 2307
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 191
98.5%
. 2
 
1.0%
& 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
i 1
33.3%
w 1
33.3%
e 1
33.3%
Space Separator
ValueCountFrequency (%)
36186
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7907
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 124
100.0%
Math Symbol
ValueCountFrequency (%)
~ 115
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113551
56.8%
Common 84507
42.3%
Latin 1787
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10345
 
9.1%
10093
 
8.9%
9998
 
8.8%
8896
 
7.8%
8767
 
7.7%
8548
 
7.5%
8528
 
7.5%
7728
 
6.8%
7513
 
6.6%
1606
 
1.4%
Other values (263) 31529
27.8%
Common
ValueCountFrequency (%)
36186
42.8%
1 8608
 
10.2%
- 7907
 
9.4%
2 5239
 
6.2%
3 4195
 
5.0%
4 4053
 
4.8%
5 3930
 
4.7%
0 3068
 
3.6%
6 3032
 
3.6%
7 2849
 
3.4%
Other values (8) 5440
 
6.4%
Latin
ValueCountFrequency (%)
B 876
49.0%
T 869
48.6%
A 11
 
0.6%
K 6
 
0.3%
C 5
 
0.3%
S 3
 
0.2%
O 3
 
0.2%
E 2
 
0.1%
G 2
 
0.1%
M 2
 
0.1%
Other values (8) 8
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113551
56.8%
ASCII 86293
43.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36186
41.9%
1 8608
 
10.0%
- 7907
 
9.2%
2 5239
 
6.1%
3 4195
 
4.9%
4 4053
 
4.7%
5 3930
 
4.6%
0 3068
 
3.6%
6 3032
 
3.5%
7 2849
 
3.3%
Other values (25) 7226
 
8.4%
Hangul
ValueCountFrequency (%)
10345
 
9.1%
10093
 
8.9%
9998
 
8.8%
8896
 
7.8%
8767
 
7.7%
8548
 
7.5%
8528
 
7.5%
7728
 
6.8%
7513
 
6.6%
1606
 
1.4%
Other values (263) 31529
27.8%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Unsupported

REJECTED  UNSUPPORTED 

Missing29
Missing (%)0.3%
Memory size66.7 KiB

rdnwhladdr
Text

MISSING 

Distinct3042
Distinct (%)50.9%
Missing2550
Missing (%)29.9%
Memory size66.7 KiB
2024-04-17T01:34:19.849234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length62
Mean length27.890246
Min length5

Characters and Unicode

Total characters166700
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

Unique319 ?
Unique (%)5.3%

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 5976
 
19.1%
해운대구 943
 
3.0%
부산진구 726
 
2.3%
동래구 607
 
1.9%
사상구 516
 
1.7%
동구 489
 
1.6%
온천동 422
 
1.3%
수영구 399
 
1.3%
중구 394
 
1.3%
부전동 385
 
1.2%
Other values (2605) 20410
65.3%
2024-04-17T01:34:20.263409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25290
 
15.2%
7779
 
4.7%
7383
 
4.4%
7045
 
4.2%
6696
 
4.0%
1 6360
 
3.8%
6350
 
3.8%
6111
 
3.7%
5982
 
3.6%
( 5862
 
3.5%
Other values (359) 81842
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99181
59.5%
Decimal Number 27036
 
16.2%
Space Separator 25290
 
15.2%
Open Punctuation 5862
 
3.5%
Close Punctuation 5862
 
3.5%
Dash Punctuation 1806
 
1.1%
Other Punctuation 1306
 
0.8%
Math Symbol 257
 
0.2%
Uppercase Letter 93
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7779
 
7.8%
7383
 
7.4%
7045
 
7.1%
6696
 
6.8%
6350
 
6.4%
6111
 
6.2%
5982
 
6.0%
5695
 
5.7%
3990
 
4.0%
3747
 
3.8%
Other values (317) 38403
38.7%
Uppercase Letter
ValueCountFrequency (%)
A 30
32.3%
B 21
22.6%
K 9
 
9.7%
C 5
 
5.4%
O 5
 
5.4%
S 4
 
4.3%
E 3
 
3.2%
F 2
 
2.2%
G 2
 
2.2%
U 2
 
2.2%
Other values (9) 10
 
10.8%
Decimal Number
ValueCountFrequency (%)
1 6360
23.5%
2 4124
15.3%
3 3032
11.2%
4 2300
 
8.5%
5 2172
 
8.0%
0 1950
 
7.2%
6 1921
 
7.1%
7 1865
 
6.9%
9 1705
 
6.3%
8 1607
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
i 1
25.0%
w 1
25.0%
e 1
25.0%
b 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 1296
99.2%
. 9
 
0.7%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
25290
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5862
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5862
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1806
100.0%
Math Symbol
ValueCountFrequency (%)
~ 257
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99181
59.5%
Common 67419
40.4%
Latin 100
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7779
 
7.8%
7383
 
7.4%
7045
 
7.1%
6696
 
6.8%
6350
 
6.4%
6111
 
6.2%
5982
 
6.0%
5695
 
5.7%
3990
 
4.0%
3747
 
3.8%
Other values (317) 38403
38.7%
Latin
ValueCountFrequency (%)
A 30
30.0%
B 21
21.0%
K 9
 
9.0%
C 5
 
5.0%
O 5
 
5.0%
S 4
 
4.0%
E 3
 
3.0%
3
 
3.0%
F 2
 
2.0%
G 2
 
2.0%
Other values (14) 16
16.0%
Common
ValueCountFrequency (%)
25290
37.5%
1 6360
 
9.4%
( 5862
 
8.7%
) 5862
 
8.7%
2 4124
 
6.1%
3 3032
 
4.5%
4 2300
 
3.4%
5 2172
 
3.2%
0 1950
 
2.9%
6 1921
 
2.8%
Other values (8) 8546
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99181
59.5%
ASCII 67516
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25290
37.5%
1 6360
 
9.4%
( 5862
 
8.7%
) 5862
 
8.7%
2 4124
 
6.1%
3 3032
 
4.5%
4 2300
 
3.4%
5 2172
 
3.2%
0 1950
 
2.9%
6 1921
 
2.8%
Other values (31) 8643
 
12.8%
Hangul
ValueCountFrequency (%)
7779
 
7.8%
7383
 
7.4%
7045
 
7.1%
6696
 
6.8%
6350
 
6.4%
6111
 
6.2%
5982
 
6.0%
5695
 
5.7%
3990
 
4.0%
3747
 
3.8%
Other values (317) 38403
38.7%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.7 KiB

dcbymd
Text

MISSING 

Distinct1364
Distinct (%)34.2%
Missing4539
Missing (%)53.2%
Memory size66.7 KiB
2024-04-17T01:34:20.503990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8776329
Min length4

Characters and Unicode

Total characters31416
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

Unique35 ?
Unique (%)0.9%

Sample

1st row20140310
2nd row20121231
3rd row20171120
4th row20171107
5th row20120514
ValueCountFrequency (%)
20041022 180
 
4.5%
폐업일자 122
 
3.1%
20030122 64
 
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 (1354) 3422
85.8%
2024-04-17T01:34:20.860415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10406
33.1%
2 6573
20.9%
1 5613
17.9%
3 1438
 
4.6%
9 1407
 
4.5%
7 1215
 
3.9%
4 1138
 
3.6%
6 1097
 
3.5%
5 1070
 
3.4%
8 971
 
3.1%
Other values (4) 488
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30928
98.4%
Other Letter 488
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10406
33.6%
2 6573
21.3%
1 5613
18.1%
3 1438
 
4.6%
9 1407
 
4.5%
7 1215
 
3.9%
4 1138
 
3.7%
6 1097
 
3.5%
5 1070
 
3.5%
8 971
 
3.1%
Other Letter
ValueCountFrequency (%)
122
25.0%
122
25.0%
122
25.0%
122
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30928
98.4%
Hangul 488
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10406
33.6%
2 6573
21.3%
1 5613
18.1%
3 1438
 
4.6%
9 1407
 
4.5%
7 1215
 
3.9%
4 1138
 
3.7%
6 1097
 
3.5%
5 1070
 
3.5%
8 971
 
3.1%
Hangul
ValueCountFrequency (%)
122
25.0%
122
25.0%
122
25.0%
122
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30928
98.4%
Hangul 488
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10406
33.6%
2 6573
21.3%
1 5613
18.1%
3 1438
 
4.6%
9 1407
 
4.5%
7 1215
 
3.9%
4 1138
 
3.7%
6 1097
 
3.5%
5 1070
 
3.5%
8 971
 
3.1%
Hangul
ValueCountFrequency (%)
122
25.0%
122
25.0%
122
25.0%
122
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8388 
휴업시작일자
 
130
20210528
 
2
20201012
 
1
20160608
 
1
Other values (5)
 
5

Length

Max length8
Median length4
Mean length4.0347133
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> 8388
98.4%
휴업시작일자 130
 
1.5%
20210528 2
 
< 0.1%
20201012 1
 
< 0.1%
20160608 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20210701 1
 
< 0.1%
20201001 1
 
< 0.1%

Length

2024-04-17T01:34:20.992078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:21.095372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8388
98.4%
휴업시작일자 130
 
1.5%
20210528 2
 
< 0.1%
20201012 1
 
< 0.1%
20160608 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20210701 1
 
< 0.1%
20201001 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8389 
휴업종료일자
 
130
20230131
 
2
20170607
 
1
20180424
 
1
Other values (4)
 
4

Length

Max length8
Median length4
Mean length4.0342442
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> 8389
98.4%
휴업종료일자 130
 
1.5%
20230131 2
 
< 0.1%
20170607 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20211231 1
 
< 0.1%
20211001 1
 
< 0.1%

Length

2024-04-17T01:34:21.208299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:21.317988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.4%
휴업종료일자 130
 
1.5%
20230131 2
 
< 0.1%
20170607 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20211231 1
 
< 0.1%
20211001 1
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
재개업일자
 
130

Length

Max length5
Median length4
Mean length4.0152457
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> 8397
98.5%
재개업일자 130
 
1.5%

Length

2024-04-17T01:34:21.444542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:21.538781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
재개업일자 130
 
1.5%

trdstatenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
02
3708 
01
3464 
영업/정상
1064 
13
 
117
폐업
 
109
Other values (4)
 
65

Length

Max length5
Median length2
Mean length2.3757476
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
02 3708
43.5%
01 3464
40.6%
영업/정상 1064
 
12.5%
13 117
 
1.4%
폐업 109
 
1.3%
03 53
 
0.6%
<NA> 6
 
0.1%
휴업 5
 
0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:34:21.632362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:21.732749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3708
43.5%
01 3464
40.6%
영업/정상 1064
 
12.5%
13 117
 
1.4%
폐업 109
 
1.3%
03 53
 
0.6%
na 6
 
0.1%
휴업 5
 
0.1%
31 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
영업
4348 
폐업
3866 
영업중
 
300
휴업
 
9
<NA>
 
3

Length

Max length4
Median length2
Mean length2.0361206
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4348
51.0%
폐업 3866
45.3%
영업중 300
 
3.5%
휴업 9
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:34:21.844778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:21.940883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4348
51.0%
폐업 3866
45.3%
영업중 300
 
3.5%
휴업 9
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing384
Missing (%)4.5%
Memory size66.7 KiB

y
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing387
Missing (%)4.5%
Memory size66.7 KiB

lastmodts
Real number (ℝ)

Distinct3713
Distinct (%)43.6%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0134033 × 1013
Minimum1.9990211 × 1013
Maximum2.021083 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.1 KiB
2024-04-17T01:34:22.079750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0020116 × 1013
Q12.0060619 × 1013
median2.0171127 × 1013
Q32.0180628 × 1013
95-th percentile2.0210611 × 1013
Maximum2.021083 × 1013
Range2.2061917 × 1011
Interquartile range (IQR)1.2000914 × 1011

Descriptive statistics

Standard deviation6.887489 × 1010
Coefficient of variation (CV)0.0034208193
Kurtosis-0.95680508
Mean2.0134033 × 1013
Median Absolute Deviation (MAD)2.0805994 × 1010
Skewness-0.77595586
Sum1.716225 × 1017
Variance4.7437504 × 1021
MonotonicityNot monotonic
2024-04-17T01:34:22.199978image/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%
19990308000000 32
 
0.4%
20020515000000 32
 
0.4%
20030329000000 32
 
0.4%
Other values (3703) 8066
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 (%)
20210830165719 2
< 0.1%
20210830160810 2
< 0.1%
20210830155331 2
< 0.1%
20210830154734 1
< 0.1%
20210830132935 2
< 0.1%
20210827165307 2
< 0.1%
20210827155342 2
< 0.1%
20210827110410 2
< 0.1%
20210827100620 2
< 0.1%
20210827095459 1
< 0.1%

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
여관업
5239 
여인숙업
1076 
숙박업 기타
591 
숙박업(생활)
 
491
일반호텔
 
459
Other values (4)
671 

Length

Max length8
Median length3
Mean length3.7077518
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5239
61.4%
여인숙업 1076
 
12.6%
숙박업 기타 591
 
6.9%
숙박업(생활) 491
 
5.8%
일반호텔 459
 
5.4%
<NA> 331
 
3.9%
관광호텔 275
 
3.2%
업태구분명 56
 
0.7%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:34:22.306147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:22.406800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5239
57.5%
여인숙업 1076
 
11.8%
숙박업 591
 
6.5%
기타 591
 
6.5%
숙박업(생활 491
 
5.4%
일반호텔 459
 
5.0%
na 331
 
3.6%
관광호텔 275
 
3.0%
업태구분명 56
 
0.6%
휴양콘도미니엄업 9
 
0.1%

sitetel
Text

MISSING 

Distinct414
Distinct (%)4.9%
Missing142
Missing (%)1.7%
Memory size66.7 KiB
2024-04-17T01:34:22.577247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.886822
Min length4

Characters and Unicode

Total characters99671
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

Unique34 ?
Unique (%)0.4%

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 7529
79.6%
051 746
 
7.9%
전화번호 59
 
0.6%
070 14
 
0.1%
806 13
 
0.1%
747 10
 
0.1%
741 8
 
0.1%
746 8
 
0.1%
803 7
 
0.1%
728 6
 
0.1%
Other values (508) 1064
 
11.2%
2024-04-17T01:34:22.847575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23916
24.0%
2 15723
15.8%
3 15644
15.7%
- 15086
15.1%
0 8968
 
9.0%
5 8900
 
8.9%
4 8120
 
8.1%
1085
 
1.1%
7 654
 
0.7%
8 532
 
0.5%
Other values (6) 1043
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83264
83.5%
Dash Punctuation 15086
 
15.1%
Space Separator 1085
 
1.1%
Other Letter 236
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23916
28.7%
2 15723
18.9%
3 15644
18.8%
0 8968
 
10.8%
5 8900
 
10.7%
4 8120
 
9.8%
7 654
 
0.8%
8 532
 
0.6%
6 480
 
0.6%
9 327
 
0.4%
Other Letter
ValueCountFrequency (%)
59
25.0%
59
25.0%
59
25.0%
59
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 15086
100.0%
Space Separator
ValueCountFrequency (%)
1085
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99435
99.8%
Hangul 236
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23916
24.1%
2 15723
15.8%
3 15644
15.7%
- 15086
15.2%
0 8968
 
9.0%
5 8900
 
9.0%
4 8120
 
8.2%
1085
 
1.1%
7 654
 
0.7%
8 532
 
0.5%
Other values (2) 807
 
0.8%
Hangul
ValueCountFrequency (%)
59
25.0%
59
25.0%
59
25.0%
59
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99435
99.8%
Hangul 236
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23916
24.1%
2 15723
15.8%
3 15644
15.7%
- 15086
15.2%
0 8968
 
9.0%
5 8900
 
9.0%
4 8120
 
8.2%
1085
 
1.1%
7 654
 
0.7%
8 532
 
0.5%
Other values (2) 807
 
0.8%
Hangul
ValueCountFrequency (%)
59
25.0%
59
25.0%
59
25.0%
59
25.0%

stroomcnt
Categorical

IMBALANCE 

Distinct30
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8287 
객실수
 
93
1
 
40
2
 
30
3
 
20
Other values (25)
 
57

Length

Max length4
Median length4
Mean length3.9411282
Min length1

Unique

Unique14 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8287
97.2%
객실수 93
 
1.1%
1 40
 
0.5%
2 30
 
0.4%
3 20
 
0.2%
7 8
 
0.1%
0 6
 
0.1%
6 6
 
0.1%
8 3
 
< 0.1%
30 3
 
< 0.1%
Other values (20) 31
 
0.4%

Length

2024-04-17T01:34:22.954080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8287
97.2%
객실수 93
 
1.1%
1 40
 
0.5%
2 30
 
0.4%
3 20
 
0.2%
7 8
 
0.1%
0 6
 
0.1%
6 6
 
0.1%
8 3
 
< 0.1%
30 3
 
< 0.1%
Other values (20) 31
 
0.4%

bdngownsenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
6466 
자가
1177 
임대
773 
건물소유구분명
 
111

Length

Max length7
Median length4
Mean length3.5816817
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6466
75.8%
자가 1177
 
13.8%
임대 773
 
9.1%
건물소유구분명 111
 
1.3%

Length

2024-04-17T01:34:23.050301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:23.137156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6466
75.8%
자가 1177
 
13.8%
임대 773
 
9.1%
건물소유구분명 111
 
1.3%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8244 
건물용도명
 
96
단독주택
 
74
아파트
 
60
숙박시설
 
21
Other values (6)
 
32

Length

Max length15
Median length4
Mean length4.0107893
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> 8244
96.7%
건물용도명 96
 
1.1%
단독주택 74
 
0.9%
아파트 60
 
0.7%
숙박시설 21
 
0.2%
다세대주택 14
 
0.2%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 주택(공동주택적용) 4
 
< 0.1%
호텔 4
 
< 0.1%

Length

2024-04-17T01:34:23.235246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8244
96.6%
건물용도명 96
 
1.1%
단독주택 74
 
0.9%
아파트 60
 
0.7%
숙박시설 21
 
0.2%
다세대주택 14
 
0.2%
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 size66.7 KiB
0
2554 
<NA>
1665 
4
867 
3
749 
5
594 
Other values (30)
2098 

Length

Max length6
Median length1
Mean length1.6618975
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2554
30.0%
<NA> 1665
19.5%
4 867
 
10.2%
3 749
 
8.8%
5 594
 
7.0%
2 423
 
5.0%
8 322
 
3.8%
7 303
 
3.6%
6 303
 
3.6%
9 197
 
2.3%
Other values (25) 550
 
6.5%

Length

2024-04-17T01:34:23.617064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2554
30.0%
na 1665
19.5%
4 867
 
10.2%
3 749
 
8.8%
5 594
 
7.0%
2 423
 
5.0%
8 322
 
3.8%
6 303
 
3.6%
7 303
 
3.6%
9 197
 
2.3%
Other values (25) 550
 
6.5%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
0
4445 
<NA>
2231 
1
1493 
2
 
196
건물지하층수
 
58
Other values (9)
 
104

Length

Max length6
Median length1
Mean length1.8196318
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4445
52.1%
<NA> 2231
26.2%
1 1493
 
17.5%
2 196
 
2.3%
건물지하층수 58
 
0.7%
4 36
 
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

2024-04-17T01:34:23.714950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4445
52.1%
na 2231
26.2%
1 1495
 
17.5%
2 196
 
2.3%
건물지하층수 58
 
0.7%
4 36
 
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 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8371 
건축연면적
 
114
0
 
23
20571
 
3
2282
 
3
Other values (13)
 
13

Length

Max length5
Median length4
Mean length4.0044564
Min length1

Unique

Unique13 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8371
98.2%
건축연면적 114
 
1.3%
0 23
 
0.3%
20571 3
 
< 0.1%
2282 3
 
< 0.1%
352 1
 
< 0.1%
72 1
 
< 0.1%
39 1
 
< 0.1%
85 1
 
< 0.1%
437 1
 
< 0.1%
Other values (8) 8
 
0.1%

Length

2024-04-17T01:34:23.824515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8371
98.2%
건축연면적 114
 
1.3%
0 23
 
0.3%
20571 3
 
< 0.1%
2282 3
 
< 0.1%
530 1
 
< 0.1%
2038 1
 
< 0.1%
13440 1
 
< 0.1%
2971 1
 
< 0.1%
984 1
 
< 0.1%
Other values (8) 8
 
0.1%

svnsr
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
기념품종류
 
130

Length

Max length5
Median length4
Mean length4.0152457
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> 8397
98.5%
기념품종류 130
 
1.5%

Length

2024-04-17T01:34:23.924298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:24.006296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
기념품종류 130
 
1.5%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
기획여행보험시작일자
 
130

Length

Max length10
Median length4
Mean length4.0914741
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> 8397
98.5%
기획여행보험시작일자 130
 
1.5%

Length

2024-04-17T01:34:24.107569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:24.191821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
기획여행보험시작일자 130
 
1.5%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
기획여행보험종료일자
 
130

Length

Max length10
Median length4
Mean length4.0914741
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> 8397
98.5%
기획여행보험종료일자 130
 
1.5%

Length

2024-04-17T01:34:24.281483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:24.378880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
기획여행보험종료일자 130
 
1.5%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
7817 
0
 
592
남성종사자수
 
88
1
 
12
3
 
5
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.8019233
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> 7817
91.7%
0 592
 
6.9%
남성종사자수 88
 
1.0%
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

2024-04-17T01:34:24.484138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7817
91.7%
0 592
 
6.9%
남성종사자수 88
 
1.0%
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 size66.7 KiB
<NA>
8397 
놀이기구수내역
 
130

Length

Max length7
Median length4
Mean length4.0457371
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> 8397
98.5%
놀이기구수내역 130
 
1.5%

Length

2024-04-17T01:34:24.592265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:24.681664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
놀이기구수내역 130
 
1.5%

playfacilcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
N
7526 
<NA>
875 
놀이시설수
 
99
0
 
24
Y
 
3

Length

Max length5
Median length1
Mean length1.3542864
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 7526
88.3%
<NA> 875
 
10.3%
놀이시설수 99
 
1.2%
0 24
 
0.3%
Y 3
 
< 0.1%

Length

2024-04-17T01:34:24.782021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:24.882418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 7526
88.3%
na 875
 
10.3%
놀이시설수 99
 
1.2%
0 24
 
0.3%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
N
8390 
<NA>
 
87
 
39
Y
 
11

Length

Max length4
Median length1
Mean length1.0306087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8390
98.4%
<NA> 87
 
1.0%
39
 
0.5%
Y 11
 
0.1%

Length

2024-04-17T01:34:24.979053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:25.075844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8390
98.4%
na 87
 
1.0%
39
 
0.5%
y 11
 
0.1%

stagear
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8385 
무대면적
 
118
0
 
24

Length

Max length4
Median length4
Mean length3.9915562
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> 8385
98.3%
무대면적 118
 
1.4%
0 24
 
0.3%

Length

2024-04-17T01:34:25.170182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:25.254289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8385
98.3%
무대면적 118
 
1.4%
0 24
 
0.3%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
문화사업자구분명
 
130

Length

Max length8
Median length4
Mean length4.0609828
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> 8397
98.5%
문화사업자구분명 130
 
1.5%

Length

2024-04-17T01:34:25.380919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:25.532238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
문화사업자구분명 130
 
1.5%

culphyedcobnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8074 
외국인관광 도시민박업
 
282
관광숙박업
 
82
문화체육업종명
 
74
자동차야영장업
 
9
Other values (3)
 
6

Length

Max length11
Median length4
Mean length4.2711387
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> 8074
94.7%
외국인관광 도시민박업 282
 
3.3%
관광숙박업 82
 
1.0%
문화체육업종명 74
 
0.9%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%

Length

2024-04-17T01:34:25.647073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:25.756435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8074
91.7%
외국인관광 282
 
3.2%
도시민박업 282
 
3.2%
관광숙박업 82
 
0.9%
문화체육업종명 74
 
0.8%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%

geicpfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
 
130

Length

Max length4
Median length4
Mean length3.9542629
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> 8397
98.5%
130
 
1.5%

Length

2024-04-17T01:34:25.869509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:25.953717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
130
 
1.5%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
N
8377 
<NA>
 
87
 
39
Y
 
24

Length

Max length4
Median length1
Mean length1.0306087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8377
98.2%
<NA> 87
 
1.0%
39
 
0.5%
Y 24
 
0.3%

Length

2024-04-17T01:34:26.041634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:26.135916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8377
98.2%
na 87
 
1.0%
39
 
0.5%
y 24
 
0.3%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
 
130

Length

Max length4
Median length4
Mean length3.9542629
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> 8397
98.5%
130
 
1.5%

Length

2024-04-17T01:34:26.241467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:26.338145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
130
 
1.5%

insurorgnm
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8375 
보험기관명
 
127
DB 손해보험
 
2
객실수/수용인원 : 2개/ 6명
 
2
객실수/수용인원:1/2
 
1
Other values (20)
 
20

Length

Max length22
Median length4
Mean length4.0348305
Min length2

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> 8375
98.2%
보험기관명 127
 
1.5%
DB 손해보험 2
 
< 0.1%
객실수/수용인원 : 2개/ 6명 2
 
< 0.1%
객실수/수용인원:1/2 1
 
< 0.1%
영업배상책임보험 증권 1
 
< 0.1%
객실수/수용인원 : 3/8 1
 
< 0.1%
객실수/수용인원:2/6 1
 
< 0.1%
객실수/수용인원: 3/8 1
 
< 0.1%
객실수/수용인원:2/3 1
 
< 0.1%
Other values (15) 15
 
0.2%

Length

2024-04-17T01:34:26.434412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8375
98.0%
보험기관명 127
 
1.5%
객실수/수용인원 6
 
0.1%
5
 
0.1%
db 2
 
< 0.1%
손해보험 2
 
< 0.1%
2개 2
 
< 0.1%
6명 2
 
< 0.1%
3/8 2
 
< 0.1%
농협손해보험주식회사 1
 
< 0.1%
Other values (22) 22
 
0.3%

insurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
보험시작일자
 
130

Length

Max length6
Median length4
Mean length4.0304914
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> 8397
98.5%
보험시작일자 130
 
1.5%

Length

2024-04-17T01:34:26.548278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:26.642239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
보험시작일자 130
 
1.5%

insurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
보험종료일자
 
130

Length

Max length6
Median length4
Mean length4.0304914
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> 8397
98.5%
보험종료일자 130
 
1.5%

Length

2024-04-17T01:34:26.767515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:26.869811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
보험종료일자 130
 
1.5%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
부대시설내역
 
130

Length

Max length6
Median length4
Mean length4.0304914
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> 8397
98.5%
부대시설내역 130
 
1.5%

Length

2024-04-17T01:34:26.967923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:27.062327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
부대시설내역 130
 
1.5%

usejisgendflr
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
2691 
0
1967 
4
762 
3
646 
5
472 
Other values (30)
1989 

Length

Max length6
Median length1
Mean length2.0188812
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2691
31.6%
0 1967
23.1%
4 762
 
8.9%
3 646
 
7.6%
5 472
 
5.5%
6 417
 
4.9%
2 389
 
4.6%
7 266
 
3.1%
8 260
 
3.0%
9 189
 
2.2%
Other values (25) 468
 
5.5%

Length

2024-04-17T01:34:27.161771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2691
31.6%
0 1967
23.1%
4 762
 
8.9%
3 646
 
7.6%
5 472
 
5.5%
6 417
 
4.9%
2 389
 
4.6%
7 266
 
3.1%
8 260
 
3.0%
9 189
 
2.2%
Other values (25) 468
 
5.5%

useunderendflr
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
0
4648 
<NA>
3602 
1
 
182
사용끝지하층
 
63
2
 
16
Other values (5)
 
16

Length

Max length6
Median length1
Mean length2.304562
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4648
54.5%
<NA> 3602
42.2%
1 182
 
2.1%
사용끝지하층 63
 
0.7%
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

2024-04-17T01:34:27.261071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:27.365238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4648
54.5%
na 3602
42.2%
1 182
 
2.1%
사용끝지하층 63
 
0.7%
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 size66.7 KiB
0
2460 
1
1907 
<NA>
1863 
2
988 
3
512 
Other values (15)
797 

Length

Max length7
Median length1
Mean length1.7031781
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2460
28.8%
1 1907
22.4%
<NA> 1863
21.8%
2 988
11.6%
3 512
 
6.0%
4 307
 
3.6%
5 195
 
2.3%
6 70
 
0.8%
7 59
 
0.7%
사용시작지상층 58
 
0.7%
Other values (10) 108
 
1.3%

Length

2024-04-17T01:34:27.494501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2460
28.8%
1 1907
22.4%
na 1863
21.8%
2 988
11.6%
3 512
 
6.0%
4 307
 
3.6%
5 195
 
2.3%
6 70
 
0.8%
7 59
 
0.7%
사용시작지상층 58
 
0.7%
Other values (10) 108
 
1.3%

useunderstflr
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
0
5587 
<NA>
2651 
1
 
215
사용시작지하층
 
61
4
 
8
Other values (3)
 
5

Length

Max length7
Median length1
Mean length1.9756069
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5587
65.5%
<NA> 2651
31.1%
1 215
 
2.5%
사용시작지하층 61
 
0.7%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:34:27.616131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:27.729608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5587
65.5%
na 2651
31.1%
1 215
 
2.5%
사용시작지하층 61
 
0.7%
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 size66.7 KiB
<NA>
8397 
선박제원
 
130

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> 8397
98.5%
선박제원 130
 
1.5%

Length

2024-04-17T01:34:27.860666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:27.968154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
선박제원 130
 
1.5%

shpcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8385 
선박척수
 
118
0
 
24

Length

Max length4
Median length4
Mean length3.9915562
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> 8385
98.3%
선박척수 118
 
1.4%
0 24
 
0.3%

Length

2024-04-17T01:34:28.067535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:28.155876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8385
98.3%
선박척수 118
 
1.4%
0 24
 
0.3%

shptottons
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8385 
선박총톤수
 
118
0
 
24

Length

Max length5
Median length4
Mean length4.0053946
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> 8385
98.3%
선박총톤수 118
 
1.4%
0 24
 
0.3%

Length

2024-04-17T01:34:28.274837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:28.381423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8385
98.3%
선박총톤수 118
 
1.4%
0 24
 
0.3%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
0
4991 
<NA>
3478 
세탁기수
 
58

Length

Max length4
Median length1
Mean length2.2440483
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4991
58.5%
<NA> 3478
40.8%
세탁기수 58
 
0.7%

Length

2024-04-17T01:34:28.472675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:28.559480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4991
58.5%
na 3478
40.8%
세탁기수 58
 
0.7%

facilscp
Text

MISSING 

Distinct150
Distinct (%)39.9%
Missing8151
Missing (%)95.6%
Memory size66.7 KiB
2024-04-17T01:34:28.808729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.9361702
Min length1

Characters and Unicode

Total characters1104
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

Unique82 ?
Unique (%)21.8%

Sample

1st row시설규모
2nd row시설규모
3rd row시설규모
4th row시설규모
5th row시설규모
ValueCountFrequency (%)
시설규모 82
 
21.8%
85 16
 
4.3%
46 7
 
1.9%
599 6
 
1.6%
67 6
 
1.6%
60 6
 
1.6%
83 6
 
1.6%
63 5
 
1.3%
62 5
 
1.3%
59 4
 
1.1%
Other values (140) 233
62.0%
2024-04-17T01:34:29.245574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 119
10.8%
5 96
 
8.7%
82
 
7.4%
82
 
7.4%
82
 
7.4%
82
 
7.4%
8 81
 
7.3%
6 73
 
6.6%
2 72
 
6.5%
4 71
 
6.4%
Other values (4) 264
23.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 776
70.3%
Other Letter 328
29.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 119
15.3%
5 96
12.4%
8 81
10.4%
6 73
9.4%
2 72
9.3%
4 71
9.1%
9 70
9.0%
7 68
8.8%
3 68
8.8%
0 58
7.5%
Other Letter
ValueCountFrequency (%)
82
25.0%
82
25.0%
82
25.0%
82
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 776
70.3%
Hangul 328
29.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 119
15.3%
5 96
12.4%
8 81
10.4%
6 73
9.4%
2 72
9.3%
4 71
9.1%
9 70
9.0%
7 68
8.8%
3 68
8.8%
0 58
7.5%
Hangul
ValueCountFrequency (%)
82
25.0%
82
25.0%
82
25.0%
82
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 776
70.3%
Hangul 328
29.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 119
15.3%
5 96
12.4%
8 81
10.4%
6 73
9.4%
2 72
9.3%
4 71
9.1%
9 70
9.0%
7 68
8.8%
3 68
8.8%
0 58
7.5%
Hangul
ValueCountFrequency (%)
82
25.0%
82
25.0%
82
25.0%
82
25.0%

facilar
Text

MISSING 

Distinct220
Distinct (%)58.5%
Missing8151
Missing (%)95.6%
Memory size66.7 KiB
2024-04-17T01:34:29.568865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.9414894
Min length1

Characters and Unicode

Total characters1858
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

Unique176 ?
Unique (%)46.8%

Sample

1st row시설면적
2nd row시설면적
3rd row시설면적
4th row시설면적
5th row시설면적
ValueCountFrequency (%)
시설면적 82
 
21.8%
45.5 6
 
1.6%
598.73 6
 
1.6%
62.58 4
 
1.1%
218.85 4
 
1.1%
84.59 3
 
0.8%
8546.81 3
 
0.8%
59.4 3
 
0.8%
2281.67 3
 
0.8%
66.84 3
 
0.8%
Other values (210) 259
68.9%
2024-04-17T01:34:30.036530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 265
14.3%
1 166
8.9%
4 157
 
8.4%
8 153
 
8.2%
5 131
 
7.1%
2 124
 
6.7%
3 121
 
6.5%
6 120
 
6.5%
9 113
 
6.1%
7 106
 
5.7%
Other values (5) 402
21.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1265
68.1%
Other Letter 328
 
17.7%
Other Punctuation 265
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 166
13.1%
4 157
12.4%
8 153
12.1%
5 131
10.4%
2 124
9.8%
3 121
9.6%
6 120
9.5%
9 113
8.9%
7 106
8.4%
0 74
5.8%
Other Letter
ValueCountFrequency (%)
82
25.0%
82
25.0%
82
25.0%
82
25.0%
Other Punctuation
ValueCountFrequency (%)
. 265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1530
82.3%
Hangul 328
 
17.7%

Most frequent character per script

Common
ValueCountFrequency (%)
. 265
17.3%
1 166
10.8%
4 157
10.3%
8 153
10.0%
5 131
8.6%
2 124
8.1%
3 121
7.9%
6 120
7.8%
9 113
7.4%
7 106
 
6.9%
Hangul
ValueCountFrequency (%)
82
25.0%
82
25.0%
82
25.0%
82
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1530
82.3%
Hangul 328
 
17.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 265
17.3%
1 166
10.8%
4 157
10.3%
8 153
10.0%
5 131
8.6%
2 124
8.1%
3 121
7.9%
6 120
7.8%
9 113
7.4%
7 106
 
6.9%
Hangul
ValueCountFrequency (%)
82
25.0%
82
25.0%
82
25.0%
82
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
 
130

Length

Max length4
Median length4
Mean length3.9542629
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> 8397
98.5%
130
 
1.5%

Length

2024-04-17T01:34:30.168593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:30.272806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
130
 
1.5%

yangsilcnt
Text

MISSING 

Distinct148
Distinct (%)1.9%
Missing909
Missing (%)10.7%
Memory size66.7 KiB
2024-04-17T01:34:30.479796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7423208
Min length1

Characters and Unicode

Total characters13273
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
 
4.8%
12 318
 
4.2%
14 314
 
4.1%
15 300
 
3.9%
13 248
 
3.3%
19 242
 
3.2%
16 221
 
2.9%
17 220
 
2.9%
Other values (138) 3907
51.3%
2024-04-17T01:34:30.806484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3427
25.8%
0 1922
14.5%
2 1870
14.1%
3 1346
 
10.1%
4 1043
 
7.9%
5 821
 
6.2%
8 816
 
6.1%
6 641
 
4.8%
9 620
 
4.7%
7 599
 
4.5%
Other values (3) 168
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13105
98.7%
Other Letter 168
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3427
26.2%
0 1922
14.7%
2 1870
14.3%
3 1346
 
10.3%
4 1043
 
8.0%
5 821
 
6.3%
8 816
 
6.2%
6 641
 
4.9%
9 620
 
4.7%
7 599
 
4.6%
Other Letter
ValueCountFrequency (%)
56
33.3%
56
33.3%
56
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13105
98.7%
Hangul 168
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3427
26.2%
0 1922
14.7%
2 1870
14.3%
3 1346
 
10.3%
4 1043
 
8.0%
5 821
 
6.3%
8 816
 
6.2%
6 641
 
4.9%
9 620
 
4.7%
7 599
 
4.6%
Hangul
ValueCountFrequency (%)
56
33.3%
56
33.3%
56
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13105
98.7%
Hangul 168
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3427
26.2%
0 1922
14.7%
2 1870
14.3%
3 1346
 
10.3%
4 1043
 
8.0%
5 821
 
6.3%
8 816
 
6.2%
6 641
 
4.9%
9 620
 
4.7%
7 599
 
4.6%
Hangul
ValueCountFrequency (%)
56
33.3%
56
33.3%
56
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
7819 
0
 
598
여성종사자수
 
88
2
 
6
1
 
6
Other values (4)
 
10

Length

Max length6
Median length4
Mean length3.8028615
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> 7819
91.7%
0 598
 
7.0%
여성종사자수 88
 
1.0%
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

2024-04-17T01:34:30.934690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:31.043676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7819
91.7%
0 598
 
7.0%
여성종사자수 88
 
1.0%
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

HIGH CARDINALITY  IMBALANCE 

Distinct51
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8346 
영문상호명
 
115
CheonghakSodam
 
3
Emerald ocean view
 
3
ocean house
 
3
Other values (46)
 
57

Length

Max length45
Median length4
Mean length4.1007388
Min length4

Unique

Unique39 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8346
97.9%
영문상호명 115
 
1.3%
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 (41) 43
 
0.5%

Length

2024-04-17T01:34:31.176293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8346
96.9%
영문상호명 115
 
1.3%
house 30
 
0.3%
busan 9
 
0.1%
ocean 6
 
0.1%
hotel 6
 
0.1%
guest 5
 
0.1%
kim's 4
 
< 0.1%
dyd 3
 
< 0.1%
cozy 3
 
< 0.1%
Other values (60) 86
 
1.0%

engstntrnmaddr
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8349 
영문상호주소
 
115
Guesthouse for Foreign Tourists
 
20
Foreigner Tourism City home-stay Business
 
14
Guest House
 
4
Other values (15)
 
25

Length

Max length41
Median length4
Mean length4.2242289
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> 8349
97.9%
영문상호주소 115
 
1.3%
Guesthouse for Foreign Tourists 20
 
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%
Entertainment Business for Foreigner only 2
 
< 0.1%
Other values (10) 11
 
0.1%

Length

2024-04-17T01:34:31.287530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8349
95.9%
영문상호주소 115
 
1.3%
for 27
 
0.3%
foreign 26
 
0.3%
guesthouse 23
 
0.3%
tourists 23
 
0.3%
business 22
 
0.3%
foreigner 19
 
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 size66.7 KiB
0
5835 
<NA>
2446 
욕실수
 
58
15
 
16
12
 
14
Other values (28)
 
158

Length

Max length4
Median length1
Mean length1.893632
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5835
68.4%
<NA> 2446
28.7%
욕실수 58
 
0.7%
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

2024-04-17T01:34:31.407242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 5835
68.4%
na 2446
28.7%
욕실수 58
 
0.7%
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 size66.7 KiB
여관업
5239 
여인숙업
1076 
숙박업 기타
591 
숙박업(생활)
 
491
일반호텔
 
459
Other values (4)
671 

Length

Max length8
Median length3
Mean length3.7077518
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5239
61.4%
여인숙업 1076
 
12.6%
숙박업 기타 591
 
6.9%
숙박업(생활) 491
 
5.8%
일반호텔 459
 
5.4%
<NA> 331
 
3.9%
관광호텔 275
 
3.2%
위생업태명 56
 
0.7%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:34:31.526441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:31.895096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5239
57.5%
여인숙업 1076
 
11.8%
숙박업 591
 
6.5%
기타 591
 
6.5%
숙박업(생활 491
 
5.4%
일반호텔 459
 
5.0%
na 331
 
3.6%
관광호텔 275
 
3.0%
위생업태명 56
 
0.6%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
 
130

Length

Max length4
Median length4
Mean length3.9542629
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> 8397
98.5%
130
 
1.5%

Length

2024-04-17T01:34:32.003564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:32.087839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
130
 
1.5%

capt
Categorical

IMBALANCE 

Distinct42
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8307 
자본금
 
99
0
 
19
10000000
 
18
100000000
 
12
Other values (37)
 
72

Length

Max length10
Median length4
Mean length4.0344787
Min length1

Unique

Unique22 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8307
97.4%
자본금 99
 
1.2%
0 19
 
0.2%
10000000 18
 
0.2%
100000000 12
 
0.1%
200000000 7
 
0.1%
50000000 7
 
0.1%
20000000 5
 
0.1%
300000000 4
 
< 0.1%
2000000000 3
 
< 0.1%
Other values (32) 46
 
0.5%

Length

2024-04-17T01:34:32.170794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8307
97.4%
자본금 99
 
1.2%
0 19
 
0.2%
10000000 18
 
0.2%
100000000 12
 
0.1%
200000000 7
 
0.1%
50000000 7
 
0.1%
20000000 5
 
0.1%
300000000 4
 
< 0.1%
2000000000 3
 
< 0.1%
Other values (32) 46
 
0.5%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
제작취급품목내용
 
130

Length

Max length8
Median length4
Mean length4.0609828
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> 8397
98.5%
제작취급품목내용 130
 
1.5%

Length

2024-04-17T01:34:32.279799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:32.384408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
제작취급품목내용 130
 
1.5%

cndpermstymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
조건부허가시작일자
 
130

Length

Max length9
Median length4
Mean length4.0762285
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> 8397
98.5%
조건부허가시작일자 130
 
1.5%

Length

2024-04-17T01:34:32.486748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:32.572357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
조건부허가시작일자 130
 
1.5%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
조건부허가신고사유
 
130

Length

Max length9
Median length4
Mean length4.0762285
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> 8397
98.5%
조건부허가신고사유 130
 
1.5%

Length

2024-04-17T01:34:32.670390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:32.757930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
조건부허가신고사유 130
 
1.5%

cndpermendymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8397 
조건부허가종료일자
 
130

Length

Max length9
Median length4
Mean length4.0762285
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> 8397
98.5%
조건부허가종료일자 130
 
1.5%

Length

2024-04-17T01:34:32.843271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:32.942992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.5%
조건부허가종료일자 130
 
1.5%

chaircnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
5000 
0
3476 
좌석수
 
46
6
 
1
12
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length2.7700246
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5000
58.6%
0 3476
40.8%
좌석수 46
 
0.5%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-17T01:34:33.039704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:33.138879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5000
58.6%
0 3476
40.8%
좌석수 46
 
0.5%
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 size66.7 KiB
<NA>
8307 
주변환경명
 
109
주택가주변
 
37
아파트지역
 
32
기타
 
25
Other values (3)
 
17

Length

Max length8
Median length4
Mean length4.0229858
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> 8307
97.4%
주변환경명 109
 
1.3%
주택가주변 37
 
0.4%
아파트지역 32
 
0.4%
기타 25
 
0.3%
학교정화(상대) 14
 
0.2%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-17T01:34:33.243000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:33.355433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8307
97.4%
주변환경명 109
 
1.3%
주택가주변 37
 
0.4%
아파트지역 32
 
0.4%
기타 25
 
0.3%
학교정화(상대 14
 
0.2%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대 1
 
< 0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8276 
지상층수
 
96
2
 
31
4
 
19
1
 
15
Other values (22)
 
90

Length

Max length4
Median length4
Mean length3.9499238
Min length1

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> 8276
97.1%
지상층수 96
 
1.1%
2 31
 
0.4%
4 19
 
0.2%
1 15
 
0.2%
3 13
 
0.2%
5 11
 
0.1%
0 9
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
Other values (17) 43
 
0.5%

Length

2024-04-17T01:34:33.472911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8276
97.1%
지상층수 96
 
1.1%
2 31
 
0.4%
4 19
 
0.2%
1 15
 
0.2%
3 13
 
0.2%
5 11
 
0.1%
0 9
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
Other values (17) 43
 
0.5%

regnsenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8202 
일반주거지역
 
119
지역구분명
 
91
일반상업지역
 
40
주거지역
 
31
Other values (5)
 
44

Length

Max length6
Median length4
Mean length4.0527735
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> 8202
96.2%
일반주거지역 119
 
1.4%
지역구분명 91
 
1.1%
일반상업지역 40
 
0.5%
주거지역 31
 
0.4%
준주거지역 29
 
0.3%
상업지역 6
 
0.1%
자연녹지지역 5
 
0.1%
녹지지역 3
 
< 0.1%
전용주거지역 1
 
< 0.1%

Length

2024-04-17T01:34:33.582054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:33.692811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8202
96.2%
일반주거지역 119
 
1.4%
지역구분명 91
 
1.1%
일반상업지역 40
 
0.5%
주거지역 31
 
0.4%
준주거지역 29
 
0.3%
상업지역 6
 
0.1%
자연녹지지역 5
 
0.1%
녹지지역 3
 
< 0.1%
전용주거지역 1
 
< 0.1%

undernumlay
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8345 
지하층수
 
102
1
 
28
0
 
25
2
 
21
Other values (4)
 
6

Length

Max length4
Median length4
Mean length3.9718541
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> 8345
97.9%
지하층수 102
 
1.2%
1 28
 
0.3%
0 25
 
0.3%
2 21
 
0.2%
3 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:34:33.820816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:33.922393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8345
97.9%
지하층수 102
 
1.2%
1 28
 
0.3%
0 25
 
0.3%
2 21
 
0.2%
3 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

totnumlay
Categorical

IMBALANCE 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8263 
총층수
 
92
2
 
37
4
 
21
1
 
20
Other values (21)
 
94

Length

Max length4
Median length4
Mean length3.9331535
Min length1

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> 8263
96.9%
총층수 92
 
1.1%
2 37
 
0.4%
4 21
 
0.2%
1 20
 
0.2%
3 17
 
0.2%
5 14
 
0.2%
6 8
 
0.1%
0 8
 
0.1%
20 7
 
0.1%
Other values (16) 40
 
0.5%

Length

2024-04-17T01:34:34.037907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8263
96.9%
총층수 92
 
1.1%
2 37
 
0.4%
4 21
 
0.2%
1 20
 
0.2%
3 17
 
0.2%
5 14
 
0.2%
6 8
 
0.1%
0 8
 
0.1%
20 7
 
0.1%
Other values (16) 40
 
0.5%

abedcnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
0
4945 
<NA>
3522 
침대수
 
58
41
 
2

Length

Max length4
Median length1
Mean length2.2529612
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4945
58.0%
<NA> 3522
41.3%
침대수 58
 
0.7%
41 2
 
< 0.1%

Length

2024-04-17T01:34:34.142509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:34.232339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4945
58.0%
na 3522
41.3%
침대수 58
 
0.7%
41 2
 
< 0.1%

hanshilcnt
Categorical

Distinct48
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
0
3725 
<NA>
1470 
2
 
328
10
 
310
3
 
266
Other values (43)
2428 

Length

Max length4
Median length1
Mean length1.6800751
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3725
43.7%
<NA> 1470
 
17.2%
2 328
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 262
 
3.1%
8 226
 
2.7%
4 203
 
2.4%
6 200
 
2.3%
9 197
 
2.3%
Other values (38) 1340
 
15.7%

Length

2024-04-17T01:34:34.368694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3725
43.7%
na 1470
 
17.2%
2 328
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 262
 
3.1%
8 226
 
2.7%
4 203
 
2.4%
6 200
 
2.3%
9 197
 
2.3%
Other values (38) 1340
 
15.7%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
0
4953 
<NA>
3516 
회수건조수
 
58

Length

Max length5
Median length1
Mean length2.2642195
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4953
58.1%
<NA> 3516
41.2%
회수건조수 58
 
0.7%

Length

2024-04-17T01:34:34.512046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:34.621352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4953
58.1%
na 3516
41.2%
회수건조수 58
 
0.7%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.7 KiB
<NA>
8385 
회의실별동시수용인원
 
118
0
 
24

Length

Max length10
Median length4
Mean length4.0745866
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> 8385
98.3%
회의실별동시수용인원 118
 
1.4%
0 24
 
0.3%

Length

2024-04-17T01:34:34.733003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:34.822448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8385
98.3%
회의실별동시수용인원 118
 
1.4%
0 24
 
0.3%
Distinct3
Distinct (%)< 0.1%
Missing6
Missing (%)0.1%
Memory size66.7 KiB
Minimum2021-09-01 05:09:03
Maximum2021-09-01 05:09:05
2024-04-17T01:34:34.895974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:34:34.984561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

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 8-1번지48953.0부산광역시 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>2021-09-01 05:09:03
1332500003250000-201-2014-0000103_11_03_PI2018-08-31 23:59:59.0<NA>호텔아벤트리부산600051부산광역시 중구 창선동1가 12-1번지48947.0부산광역시 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>2021-09-01 05:09:03
2432500003250000-214-2017-0000303_11_03_PI2018-08-31 23:59:59.0<NA>케이 칠구(K79)600092부산광역시 중구 대청동2가 23-3번지48948.0부산광역시 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>2021-09-01 05:09:03
3532500003250000-201-1971-0011603_11_03_PI2018-08-31 23:59:59.0<NA>영하장600806부산광역시 중구 부평동2가 24-3번지48977.0부산광역시 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>2021-09-01 05:09:03
4632500003250000-201-2012-0000503_11_03_PI2018-08-31 23:59:59.0<NA>누리게스트하우스 더셀프600012부산광역시 중구 중앙동2가 52-2번지48956.0부산광역시 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>2021-09-01 05:09:03
5732500003250000-201-1988-0006903_11_03_PI2018-08-31 23:59:59.0<NA>야(Ya)600083부산광역시 중구 보수동3가 5-21번지48947.0부산광역시 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>2021-09-01 05:09:03
6832500003250000-201-1970-0011603_11_03_PI2018-08-31 23:59:59.0<NA>세피아600071부산광역시 중구 부평동1가 41-7번지 ,848980.0부산광역시 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>2021-09-01 05:09:03
7932500003250000-201-2007-0000203_11_03_PI2018-08-31 23:59:59.0<NA>식스나인모텔600046부산광역시 중구 남포동6가 29번지 (8~11층)48982.0부산광역시 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>2021-09-01 05:09:03
81032500003250000-201-1971-0011703_11_03_PI2018-08-31 23:59:59.0<NA>동산장모텔600033부산광역시 중구 광복동3가 5-20번지48949.0부산광역시 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>2021-09-01 05:09:03
91132500003250000-201-1972-0000303_11_03_PI2018-08-31 23:59:59.0<NA>주식회사 경원건설 호텔노아600045부산광역시 중구 남포동5가 81-1번지48983.0부산광역시 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>2021-09-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
85171302733600003360000-201-2021-0000103_11_03_PU2021-04-21 02:40:00.0숙박업신라스테이 서부산618200부산광역시 강서구 명지동 3595-1 신라스테이 서부산점46726부산광역시 강서구 명지국제7로 38, 신라스테이 서부산점 (명지동)20210331<NA><NA><NA><NA>영업/정상영업373665.73430842179173.52698928820210419165344관광호텔051 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>2021-09-01 05:09:04
85181302833300003330000-214-2021-0000203_11_03_PI2021-04-02 00:22:59.0숙박업벨리아(BELLIA)612847부산광역시 해운대구 중동 1123 해운대푸르지오시티48099부산광역시 해운대구 해운대해변로298번길 29, 해운대푸르지오시티 (중동)20210331<NA><NA><NA><NA>영업/정상영업397359.716406649186807.81129899520210331103454숙박업(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>2021-09-01 05:09:04
85191302933800003380000-214-2021-0000403_11_03_PU2021-05-01 02:40:00.0숙박업위더스오션613805부산광역시 수영구 광안동 201-1 광안 지웰에스테이트 더 테라스48303부산광역시 수영구 광남로94번길 16, 광안 지웰에스테이트 더 테라스 3~19층 305호 외 33개호 (광안동)20210406<NA><NA><NA><NA>영업/정상영업392691.625721388185474.22691274120210429170842숙박업(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>2021-09-01 05:09:04
85201303033300003330000-214-2021-0000303_11_03_PU2021-04-21 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504686720210419133601숙박업(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>2021-09-01 05:09:05
8521130313280000CDFI226221202100000103_11_04_PU2021-06-23 02:40:00.0외국인관광도시민박업윤슬가<NA>부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415<NA><NA><NA><NA>영업/정상영업중387608.397605613179078.07581929720210621140737<NA><NA>1<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>2021-09-01 05:09:05
85221303233300003330000-214-2021-0000303_11_03_PU2021-04-21 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504686720210419133601숙박업(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>2021-09-01 05:09:05
8523130333280000CDFI226221202100000103_11_04_PU2021-06-23 02:40:00.0외국인관광도시민박업윤슬가<NA>부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415<NA><NA><NA><NA>영업/정상영업중387608.397605613179078.07581929720210621140737<NA><NA>1<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>2021-09-01 05:09:05
8524130413330000CDFI226221201500002603_11_04_PI2021-05-26 00:22:56.0외국인관광도시민박업미포유<NA>부산광역시 해운대구 중동 946-1NaN부산광역시 해운대구 달맞이길62번길 9-1 (중동)20150813<NA><NA><NA><NA>영업/정상영업중397758.722800944186726.05991974820210524093757<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-09-01 05:09:05
85251304233800003380000-214-2021-0000603_11_03_PU2021-06-27 02:40:00.0숙박업제이스테이 펜트하우스613805부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210526<NA><NA><NA><NA>영업/정상영업392732.161638137185542.45270223420210625155820숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5050<NA><NA><NA>0<NA><NA><NA>40<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-09-01 05:09:05
8526130433380000CDFI226003202100000303_11_01_PU2021-06-24 02:40:00.0관광숙박업제이스테이 펜트하우스지번우편번호부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210525폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392732.161638137185542.45270223420210622151628업태구분명전화번호4건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명관광숙박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수219218.85양실수여성종사자수영문상호명영문상호주소욕실수위생업태명125000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수지역구분명지하층수총층수침대수한실수회수건조수회의실별동시수용인원2021-09-01 05:09:05

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnwhladdrdcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmlastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
343330000CDFI226003201800000503_11_01_PU2019-04-14 02:40:00.0관광숙박업일로이리조트<NA>부산광역시 해운대구 송정동 809번지부산광역시 해운대구 송정구덕포길 130 (송정동)<NA><NA><NA><NA>영업/정상영업중20190412092534<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>2021-09-01 05:09:046
53250000CDFI226221201900000103_11_04_PU2021-05-05 02:40:00.0외국인관광도시민박업보수동방공호지번우편번호부산광역시 중구 보수동1가 116-156부산광역시 중구 책방골목길 13-11 (보수동1가)20210427휴업시작일자휴업종료일자재개업일자폐업폐업20210503101511업태구분명전화번호6건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수168167.82양실수여성종사자수영문상호명영문상호주소욕실수위생업태명자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수일반상업지역지하층수3침대수한실수회수건조수회의실별동시수용인원2021-09-01 05:09:043
63250000CDFI226221201900000203_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/정상영업중20201031173301<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>2021-09-01 05:09:043
1032700003270000-201-2019-0000303_11_03_PU2021-06-20 02:40:00.0숙박업대구여관601829부산광역시 동구 초량동 388-2 지하1층, 지상1~3층, 4층 일부부산광역시 동구 중앙대로221번길 14-5 (초량동)<NA><NA><NA><NA>영업/정상영업20210618100954여관업051 467 5401<NA>자가<NA>41<NA><NA><NA><NA>0<NA><NA>N<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>2021-09-01 05:09:043
1132700003270000-201-2019-0000503_11_03_PU2020-10-29 02:40:00.0숙박업단테하우스B601829부산광역시 동구 초량동 399부산광역시 동구 초량로13번길 58 (초량동)<NA><NA><NA><NA>영업/정상영업20201027175551여관업<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>2021-09-01 05:09:043
143280000CDFI226221202000000103_11_04_PU2021-05-23 02:40:00.0외국인관광도시민박업오션하우스지번우편번호부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1904호 (동삼동, 함지그린아파트)폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중20210521172412업태구분명전화번호2건물소유구분명아파트건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수4645.5양실수여성종사자수ocean houseGuesthouse for Foreign Tourists욕실수위생업태명10000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수아파트지역20일반주거지역220침대수한실수회수건조수회의실별동시수용인원2021-09-01 05:09:043
153280000CDFI226221202000000203_11_04_PU2021-07-19 02:40:00.0외국인관광도시민박업에메랄드 오션뷰지번우편번호부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1902호 (동삼동, 함지그린아파트)폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중20210717123956업태구분명전화번호1건물소유구분명아파트건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4645.5양실수여성종사자수Emerald ocean viewGuesthouse for Foreign Tourists욕실수위생업태명0제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0아파트지역20주거지역220침대수한실수회수건조수02021-09-01 05:09:043
163280000CDFI226221202000000303_11_04_PU2021-05-29 02:40:00.0외국인관광도시민박업청학소담<NA>부산광역시 영도구 청학동 398-20부산광역시 영도구 청학서로16번길 43-14 (청학동)<NA><NA><NA><NA>영업/정상영업중20210527105330<NA><NA>1<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>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>2021-09-01 05:09:043
2132900003290000-201-2019-0000203_11_03_PU2020-12-15 02:40:00.0숙박업엑스모텔614846부산광역시 부산진구 부전동 226-5부산광역시 부산진구 신천대로50번길 34, 6층~9층 (부전동)<NA><NA><NA><NA>영업/정상영업20201212162712일반호텔051 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>2021-09-01 05:09:043
2232900003290000-201-2020-0000103_11_03_PU2020-12-15 02:40:00.0숙박업지지배614849부산광역시 부산진구 부전동 417-25부산광역시 부산진구 부전로 99-1, 3층 (부전동)<NA><NA><NA><NA>영업/정상영업20201212135845여관업051 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>2021-09-01 05:09:043