Overview

Dataset statistics

Number of variables81
Number of observations8536
Missing cells33899
Missing cells (%)4.9%
Duplicate rows448
Duplicate rows (%)5.2%
Total size in memory5.3 MiB
Average record size in memory650.0 B

Variable types

Unsupported5
Numeric2
Text11
Categorical62
DateTime1

Alerts

Dataset has 448 (5.2%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (89.4%)Imbalance
updategbn is highly imbalanced (64.3%)Imbalance
opnsvcnm is highly imbalanced (75.7%)Imbalance
clgstdt is highly imbalanced (95.8%)Imbalance
clgenddt is highly imbalanced (95.8%)Imbalance
ropnymd is highly imbalanced (88.0%)Imbalance
dtlstatenm is highly imbalanced (53.6%)Imbalance
stroomcnt is highly imbalanced (94.1%)Imbalance
bdngsrvnm is highly imbalanced (91.2%)Imbalance
bdngunderflrcnt is highly imbalanced (55.0%)Imbalance
cnstyarea is highly imbalanced (95.9%)Imbalance
svnsr is highly imbalanced (88.0%)Imbalance
plninsurstdt is highly imbalanced (88.0%)Imbalance
plninsurenddt is highly imbalanced (88.0%)Imbalance
maneipcnt is highly imbalanced (85.4%)Imbalance
playutscntdtl is highly imbalanced (88.0%)Imbalance
playfacilcnt is highly imbalanced (72.6%)Imbalance
multusnupsoyn is highly imbalanced (92.9%)Imbalance
stagear is highly imbalanced (90.5%)Imbalance
culwrkrsenm is highly imbalanced (88.0%)Imbalance
culphyedcobnm is highly imbalanced (86.9%)Imbalance
geicpfacilen is highly imbalanced (88.0%)Imbalance
balhansilyn is highly imbalanced (92.2%)Imbalance
bcfacilen is highly imbalanced (88.0%)Imbalance
insurorgnm is highly imbalanced (96.5%)Imbalance
insurstdt is highly imbalanced (88.0%)Imbalance
insurenddt is highly imbalanced (88.0%)Imbalance
afc is highly imbalanced (88.0%)Imbalance
useunderendflr is highly imbalanced (63.7%)Imbalance
useunderstflr is highly imbalanced (62.7%)Imbalance
shpinfo is highly imbalanced (88.0%)Imbalance
shpcnt is highly imbalanced (90.5%)Imbalance
shptottons is highly imbalanced (90.5%)Imbalance
infoben is highly imbalanced (88.0%)Imbalance
wmeipcnt is highly imbalanced (84.3%)Imbalance
engstntrnmaddr is highly imbalanced (95.4%)Imbalance
yoksilcnt is highly imbalanced (77.0%)Imbalance
dispenen is highly imbalanced (88.0%)Imbalance
capt is highly imbalanced (94.8%)Imbalance
mnfactreartclcn is highly imbalanced (88.0%)Imbalance
cndpermstymd is highly imbalanced (88.0%)Imbalance
cndpermntwhy is highly imbalanced (88.0%)Imbalance
cndpermendymd is highly imbalanced (88.0%)Imbalance
chaircnt is highly imbalanced (65.8%)Imbalance
nearenvnm is highly imbalanced (92.2%)Imbalance
jisgnumlay is highly imbalanced (93.5%)Imbalance
regnsenm is highly imbalanced (89.8%)Imbalance
undernumlay is highly imbalanced (93.5%)Imbalance
totnumlay is highly imbalanced (93.2%)Imbalance
meetsamtimesygstf is highly imbalanced (90.5%)Imbalance
sitepostno has 309 (3.6%) missing valuesMissing
rdnwhladdr has 2551 (29.9%) missing valuesMissing
dcbymd has 4518 (52.9%) missing valuesMissing
x has 384 (4.5%) missing valuesMissing
y has 387 (4.5%) missing valuesMissing
sitetel has 157 (1.8%) missing valuesMissing
facilscp has 8141 (95.4%) missing valuesMissing
facilar has 8141 (95.4%) missing valuesMissing
yangsilcnt has 919 (10.8%) missing valuesMissing
engstntrnmnm has 8342 (97.7%) 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 16:33:47.738410
Analysis finished2024-04-16 16:33:50.325578
Duration2.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.8 KiB

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3318912.5
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.2 KiB
2024-04-17T01:33:50.381022image/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 deviation42867.38
Coefficient of variation (CV)0.012916092
Kurtosis-0.97469731
Mean3318912.5
Median Absolute Deviation (MAD)30000
Skewness0.26480693
Sum2.832028 × 1010
Variance1.8376122 × 109
MonotonicityNot monotonic
2024-04-17T01:33:50.521121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1165
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) 1719
20.1%
ValueCountFrequency (%)
3250000 484
5.7%
3260000 406
 
4.8%
3270000 655
7.7%
3280000 374
 
4.4%
3290000 1060
12.4%
3300000 893
10.5%
3310000 285
 
3.3%
3320000 578
6.8%
3330000 1165
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 1165
13.6%
3320000 578
6.8%
3310000 285
 
3.3%

mgtno
Text

Distinct4239
Distinct (%)49.7%
Missing3
Missing (%)< 0.1%
Memory size66.8 KiB
2024-04-17T01:33:50.715385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.909528
Min length20

Characters and Unicode

Total characters186954
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

Unique155 ?
Unique (%)1.8%

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%
cdfi2262212014000001 9
 
0.1%
cdfi2262212017000002 9
 
0.1%
Other values (4229) 8423
98.7%
2024-04-17T01:33:51.052527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71972
38.5%
- 24441
 
13.1%
1 20178
 
10.8%
2 20125
 
10.8%
3 18264
 
9.8%
9 10162
 
5.4%
8 4976
 
2.7%
7 4872
 
2.6%
6 3741
 
2.0%
4 3621
 
1.9%
Other values (5) 4602
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160969
86.1%
Dash Punctuation 24441
 
13.1%
Uppercase Letter 1544
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71972
44.7%
1 20178
 
12.5%
2 20125
 
12.5%
3 18264
 
11.3%
9 10162
 
6.3%
8 4976
 
3.1%
7 4872
 
3.0%
6 3741
 
2.3%
4 3621
 
2.2%
5 3058
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 386
25.0%
D 386
25.0%
F 386
25.0%
I 386
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24441
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 185410
99.2%
Latin 1544
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 71972
38.8%
- 24441
 
13.2%
1 20178
 
10.9%
2 20125
 
10.9%
3 18264
 
9.9%
9 10162
 
5.5%
8 4976
 
2.7%
7 4872
 
2.6%
6 3741
 
2.0%
4 3621
 
2.0%
Latin
ValueCountFrequency (%)
C 386
25.0%
D 386
25.0%
F 386
25.0%
I 386
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 186954
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 71972
38.5%
- 24441
 
13.1%
1 20178
 
10.8%
2 20125
 
10.8%
3 18264
 
9.8%
9 10162
 
5.4%
8 4976
 
2.7%
7 4872
 
2.6%
6 3741
 
2.0%
4 3621
 
1.9%
Other values (5) 4602
 
2.5%

opnsvcid
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
03_11_03_P
8147 
03_11_04_P
 
286
03_11_01_P
 
85
03_11_05_P
 
9
03_11_02_P
 
3
Other values (3)
 
6

Length

Max length10
Median length10
Mean length9.9978913
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 8147
95.4%
03_11_04_P 286
 
3.4%
03_11_01_P 85
 
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

2024-04-17T01:33:51.182426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:51.283655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8147
95.4%
03_11_04_p 286
 
3.4%
03_11_01_p 85
 
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 size66.8 KiB
I
7410 
U
1123 
180000000
 
3

Length

Max length9
Median length1
Mean length1.0028116
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7410
86.8%
U 1123
 
13.2%
180000000 3
 
< 0.1%

Length

2024-04-17T01:33:51.393963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:51.485137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7410
86.8%
u 1123
 
13.2%
180000000 3
 
< 0.1%
Distinct294
Distinct (%)3.4%
Missing3
Missing (%)< 0.1%
Memory size66.8 KiB
Minimum2018-08-31 23:59:59
Maximum2021-10-01 02:40:00
2024-04-17T01:33:51.576356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:33:51.756341image/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 size66.8 KiB
<NA>
7281 
숙박업
1043 
외국인관광도시민박업
 
121
관광숙박업
 
85
자동차야영장업
 
2
Other values (3)
 
4

Length

Max length10
Median length4
Mean length3.9741097
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> 7281
85.3%
숙박업 1043
 
12.2%
외국인관광도시민박업 121
 
1.4%
관광숙박업 85
 
1.0%
자동차야영장업 2
 
< 0.1%
한옥체험업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

Length

2024-04-17T01:33:51.882865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:51.984979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7281
85.3%
숙박업 1043
 
12.2%
외국인관광도시민박업 121
 
1.4%
관광숙박업 85
 
1.0%
자동차야영장업 2
 
< 0.1%
한옥체험업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

bplcnm
Text

Distinct3426
Distinct (%)40.2%
Missing3
Missing (%)< 0.1%
Memory size66.8 KiB
2024-04-17T01:33:52.243673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length5.1981718
Min length1

Characters and Unicode

Total characters44356
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

Unique328 ?
Unique (%)3.8%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 칠구(K79)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 244
 
2.4%
모텔 184
 
1.8%
게스트하우스 121
 
1.2%
여관 82
 
0.8%
hotel 67
 
0.7%
부산 51
 
0.5%
house 48
 
0.5%
해운대 41
 
0.4%
37
 
0.4%
여인숙 36
 
0.4%
Other values (3528) 9295
91.1%
2024-04-17T01:33:52.609215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2940
 
6.6%
2013
 
4.5%
1789
 
4.0%
1741
 
3.9%
1690
 
3.8%
1519
 
3.4%
1396
 
3.1%
1273
 
2.9%
771
 
1.7%
755
 
1.7%
Other values (641) 28469
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37177
83.8%
Uppercase Letter 2494
 
5.6%
Space Separator 1690
 
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 (%)
2940
 
7.9%
2013
 
5.4%
1789
 
4.8%
1741
 
4.7%
1519
 
4.1%
1396
 
3.8%
1273
 
3.4%
771
 
2.1%
755
 
2.0%
622
 
1.7%
Other values (561) 22358
60.1%
Uppercase Letter
ValueCountFrequency (%)
E 262
 
10.5%
O 243
 
9.7%
H 226
 
9.1%
T 200
 
8.0%
S 171
 
6.9%
A 149
 
6.0%
L 146
 
5.9%
N 122
 
4.9%
U 103
 
4.1%
B 100
 
4.0%
Other values (16) 772
31.0%
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 (%)
1690
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 37175
83.8%
Latin 3756
 
8.5%
Common 3417
 
7.7%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2940
 
7.9%
2013
 
5.4%
1789
 
4.8%
1741
 
4.7%
1519
 
4.1%
1396
 
3.8%
1273
 
3.4%
771
 
2.1%
755
 
2.0%
622
 
1.7%
Other values (557) 22356
60.1%
Latin
ValueCountFrequency (%)
E 262
 
7.0%
O 243
 
6.5%
H 226
 
6.0%
e 202
 
5.4%
T 200
 
5.3%
S 171
 
4.6%
A 149
 
4.0%
o 148
 
3.9%
L 146
 
3.9%
N 122
 
3.2%
Other values (44) 1887
50.2%
Common
ValueCountFrequency (%)
1690
49.5%
) 532
 
15.6%
( 532
 
15.6%
2 130
 
3.8%
1 73
 
2.1%
5 66
 
1.9%
7 60
 
1.8%
. 57
 
1.7%
9 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 37169
83.8%
ASCII 7158
 
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 (%)
2940
 
7.9%
2013
 
5.4%
1789
 
4.8%
1741
 
4.7%
1519
 
4.1%
1396
 
3.8%
1273
 
3.4%
771
 
2.1%
755
 
2.0%
622
 
1.7%
Other values (556) 22350
60.1%
ASCII
ValueCountFrequency (%)
1690
23.6%
) 532
 
7.4%
( 532
 
7.4%
E 262
 
3.7%
O 243
 
3.4%
H 226
 
3.2%
e 202
 
2.8%
T 200
 
2.8%
S 171
 
2.4%
A 149
 
2.1%
Other values (64) 2951
41.2%
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%
Missing309
Missing (%)3.6%
Memory size66.8 KiB
2024-04-17T01:33:52.907262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters49362
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 215
 
2.6%
612847 184
 
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) 6433
78.2%
2024-04-17T01:33:53.300139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9857
20.0%
1 8061
16.3%
0 8010
16.2%
8 7939
16.1%
2 4308
8.7%
4 3453
 
7.0%
7 2602
 
5.3%
3 2458
 
5.0%
9 1407
 
2.9%
5 955
 
1.9%
Other values (5) 312
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49050
99.4%
Other Letter 312
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9857
20.1%
1 8061
16.4%
0 8010
16.3%
8 7939
16.2%
2 4308
8.8%
4 3453
 
7.0%
7 2602
 
5.3%
3 2458
 
5.0%
9 1407
 
2.9%
5 955
 
1.9%
Other Letter
ValueCountFrequency (%)
104
33.3%
52
16.7%
52
16.7%
52
16.7%
52
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 49050
99.4%
Hangul 312
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9857
20.1%
1 8061
16.4%
0 8010
16.3%
8 7939
16.2%
2 4308
8.8%
4 3453
 
7.0%
7 2602
 
5.3%
3 2458
 
5.0%
9 1407
 
2.9%
5 955
 
1.9%
Hangul
ValueCountFrequency (%)
104
33.3%
52
16.7%
52
16.7%
52
16.7%
52
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49050
99.4%
Hangul 312
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9857
20.1%
1 8061
16.4%
0 8010
16.3%
8 7939
16.2%
2 4308
8.8%
4 3453
 
7.0%
7 2602
 
5.3%
3 2458
 
5.0%
9 1407
 
2.9%
5 955
 
1.9%
Hangul
ValueCountFrequency (%)
104
33.3%
52
16.7%
52
16.7%
52
16.7%
52
16.7%
Distinct4109
Distinct (%)48.2%
Missing5
Missing (%)0.1%
Memory size66.8 KiB
2024-04-17T01:33:53.576748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length44
Mean length23.429727
Min length13

Characters and Unicode

Total characters199879
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

Unique271 ?
Unique (%)3.2%

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 8531
23.5%
해운대구 1165
 
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 (4328) 20728
57.1%
2024-04-17T01:33:54.002585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36224
18.1%
10355
 
5.2%
10102
 
5.1%
10008
 
5.0%
8905
 
4.5%
8776
 
4.4%
1 8614
 
4.3%
8558
 
4.3%
8537
 
4.3%
- 7914
 
4.0%
Other values (299) 81886
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113523
56.8%
Decimal Number 39882
 
20.0%
Space Separator 36224
 
18.1%
Dash Punctuation 7914
 
4.0%
Uppercase Letter 1783
 
0.9%
Other Punctuation 190
 
0.1%
Open Punctuation 124
 
0.1%
Close Punctuation 124
 
0.1%
Math Symbol 111
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10355
 
9.1%
10102
 
8.9%
10008
 
8.8%
8905
 
7.8%
8776
 
7.7%
8558
 
7.5%
8537
 
7.5%
7660
 
6.7%
7443
 
6.6%
1612
 
1.4%
Other values (263) 31567
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%
M 2
 
0.1%
G 2
 
0.1%
Other values (4) 4
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 8614
21.6%
2 5244
13.1%
3 4200
10.5%
4 4056
10.2%
5 3928
9.8%
0 3071
 
7.7%
6 3035
 
7.6%
7 2847
 
7.1%
8 2578
 
6.5%
9 2309
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 187
98.4%
. 2
 
1.1%
& 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
i 1
33.3%
e 1
33.3%
w 1
33.3%
Space Separator
ValueCountFrequency (%)
36224
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7914
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 124
100.0%
Math Symbol
ValueCountFrequency (%)
~ 111
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113523
56.8%
Common 84569
42.3%
Latin 1787
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10355
 
9.1%
10102
 
8.9%
10008
 
8.8%
8905
 
7.8%
8776
 
7.7%
8558
 
7.5%
8537
 
7.5%
7660
 
6.7%
7443
 
6.6%
1612
 
1.4%
Other values (263) 31567
27.8%
Common
ValueCountFrequency (%)
36224
42.8%
1 8614
 
10.2%
- 7914
 
9.4%
2 5244
 
6.2%
3 4200
 
5.0%
4 4056
 
4.8%
5 3928
 
4.6%
0 3071
 
3.6%
6 3035
 
3.6%
7 2847
 
3.4%
Other values (8) 5436
 
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%
M 2
 
0.1%
G 2
 
0.1%
Other values (8) 8
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113523
56.8%
ASCII 86355
43.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36224
41.9%
1 8614
 
10.0%
- 7914
 
9.2%
2 5244
 
6.1%
3 4200
 
4.9%
4 4056
 
4.7%
5 3928
 
4.5%
0 3071
 
3.6%
6 3035
 
3.5%
7 2847
 
3.3%
Other values (25) 7222
 
8.4%
Hangul
ValueCountFrequency (%)
10355
 
9.1%
10102
 
8.9%
10008
 
8.8%
8905
 
7.8%
8776
 
7.7%
8558
 
7.5%
8537
 
7.5%
7660
 
6.7%
7443
 
6.6%
1612
 
1.4%
Other values (263) 31567
27.8%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Unsupported

REJECTED  UNSUPPORTED 

Missing30
Missing (%)0.4%
Memory size66.8 KiB

rdnwhladdr
Text

MISSING 

Distinct3045
Distinct (%)50.9%
Missing2551
Missing (%)29.9%
Memory size66.8 KiB
2024-04-17T01:33:54.262393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length65
Mean length27.895906
Min length18

Characters and Unicode

Total characters166957
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

Unique320 ?
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 5985
 
19.1%
해운대구 947
 
3.0%
부산진구 726
 
2.3%
동래구 607
 
1.9%
사상구 516
 
1.6%
동구 489
 
1.6%
온천동 422
 
1.3%
수영구 399
 
1.3%
중구 394
 
1.3%
부전동 385
 
1.2%
Other values (2605) 20449
65.3%
2024-04-17T01:33:54.716321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25334
 
15.2%
7788
 
4.7%
7392
 
4.4%
7054
 
4.2%
6706
 
4.0%
1 6365
 
3.8%
6360
 
3.8%
6121
 
3.7%
5991
 
3.6%
) 5871
 
3.5%
Other values (359) 81975
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99330
59.5%
Decimal Number 27072
 
16.2%
Space Separator 25334
 
15.2%
Close Punctuation 5871
 
3.5%
Open Punctuation 5871
 
3.5%
Dash Punctuation 1807
 
1.1%
Other Punctuation 1313
 
0.8%
Math Symbol 259
 
0.2%
Uppercase Letter 93
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7788
 
7.8%
7392
 
7.4%
7054
 
7.1%
6706
 
6.8%
6360
 
6.4%
6121
 
6.2%
5991
 
6.0%
5703
 
5.7%
3993
 
4.0%
3750
 
3.8%
Other values (317) 38472
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%
G 2
 
2.2%
F 2
 
2.2%
U 2
 
2.2%
Other values (9) 10
 
10.8%
Decimal Number
ValueCountFrequency (%)
1 6365
23.5%
2 4128
15.2%
3 3036
11.2%
4 2303
 
8.5%
5 2178
 
8.0%
0 1953
 
7.2%
6 1924
 
7.1%
7 1866
 
6.9%
9 1708
 
6.3%
8 1611
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
i 1
25.0%
w 1
25.0%
b 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 1303
99.2%
. 9
 
0.7%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
25334
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5871
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5871
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1807
100.0%
Math Symbol
ValueCountFrequency (%)
~ 259
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99330
59.5%
Common 67527
40.4%
Latin 100
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7788
 
7.8%
7392
 
7.4%
7054
 
7.1%
6706
 
6.8%
6360
 
6.4%
6121
 
6.2%
5991
 
6.0%
5703
 
5.7%
3993
 
4.0%
3750
 
3.8%
Other values (317) 38472
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%
G 2
 
2.0%
F 2
 
2.0%
Other values (14) 16
16.0%
Common
ValueCountFrequency (%)
25334
37.5%
1 6365
 
9.4%
) 5871
 
8.7%
( 5871
 
8.7%
2 4128
 
6.1%
3 3036
 
4.5%
4 2303
 
3.4%
5 2178
 
3.2%
0 1953
 
2.9%
6 1924
 
2.8%
Other values (8) 8564
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99330
59.5%
ASCII 67624
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25334
37.5%
1 6365
 
9.4%
) 5871
 
8.7%
( 5871
 
8.7%
2 4128
 
6.1%
3 3036
 
4.5%
4 2303
 
3.4%
5 2178
 
3.2%
0 1953
 
2.9%
6 1924
 
2.8%
Other values (31) 8661
 
12.8%
Hangul
ValueCountFrequency (%)
7788
 
7.8%
7392
 
7.4%
7054
 
7.1%
6706
 
6.8%
6360
 
6.4%
6121
 
6.2%
5991
 
6.0%
5703
 
5.7%
3993
 
4.0%
3750
 
3.8%
Other values (317) 38472
38.7%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.8 KiB

dcbymd
Text

MISSING 

Distinct1377
Distinct (%)34.3%
Missing4518
Missing (%)52.9%
Memory size66.8 KiB
2024-04-17T01:33:54.966935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8705824
Min length4

Characters and Unicode

Total characters31624
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

Unique39 ?
Unique (%)1.0%

Sample

1st row20140310
2nd row20121231
3rd row20171120
4th row20210823
5th row20171107
ValueCountFrequency (%)
20041022 180
 
4.5%
폐업일자 130
 
3.2%
20030122 64
 
1.6%
20120711 52
 
1.3%
20021024 38
 
0.9%
20030305 26
 
0.6%
20030101 24
 
0.6%
20030227 22
 
0.5%
20051117 20
 
0.5%
20030123 18
 
0.4%
Other values (1367) 3444
85.7%
2024-04-17T01:33:55.326941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10464
33.1%
2 6623
20.9%
1 5645
17.9%
3 1445
 
4.6%
9 1425
 
4.5%
7 1219
 
3.9%
4 1140
 
3.6%
6 1097
 
3.5%
5 1070
 
3.4%
8 976
 
3.1%
Other values (4) 520
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31104
98.4%
Other Letter 520
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10464
33.6%
2 6623
21.3%
1 5645
18.1%
3 1445
 
4.6%
9 1425
 
4.6%
7 1219
 
3.9%
4 1140
 
3.7%
6 1097
 
3.5%
5 1070
 
3.4%
8 976
 
3.1%
Other Letter
ValueCountFrequency (%)
130
25.0%
130
25.0%
130
25.0%
130
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31104
98.4%
Hangul 520
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10464
33.6%
2 6623
21.3%
1 5645
18.1%
3 1445
 
4.6%
9 1425
 
4.6%
7 1219
 
3.9%
4 1140
 
3.7%
6 1097
 
3.5%
5 1070
 
3.4%
8 976
 
3.1%
Hangul
ValueCountFrequency (%)
130
25.0%
130
25.0%
130
25.0%
130
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31104
98.4%
Hangul 520
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10464
33.6%
2 6623
21.3%
1 5645
18.1%
3 1445
 
4.6%
9 1425
 
4.6%
7 1219
 
3.9%
4 1140
 
3.7%
6 1097
 
3.5%
5 1070
 
3.4%
8 976
 
3.1%
Hangul
ValueCountFrequency (%)
130
25.0%
130
25.0%
130
25.0%
130
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8389 
휴업시작일자
 
139
20210528
 
2
20160608
 
1
20160425
 
1
Other values (4)
 
4

Length

Max length8
Median length4
Mean length4.0363168
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
98.3%
휴업시작일자 139
 
1.6%
20210528 2
 
< 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

2024-04-17T01:33:55.447585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:55.548049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.3%
휴업시작일자 139
 
1.6%
20210528 2
 
< 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 size66.8 KiB
<NA>
8389 
휴업종료일자
 
139
20230131
 
2
20170607
 
1
20180424
 
1
Other values (4)
 
4

Length

Max length8
Median length4
Mean length4.0363168
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
98.3%
휴업종료일자 139
 
1.6%
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

2024-04-17T01:33:55.685235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:55.791864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.3%
휴업종료일자 139
 
1.6%
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 size66.8 KiB
<NA>
8397 
재개업일자
 
139

Length

Max length5
Median length4
Mean length4.016284
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
98.4%
재개업일자 139
 
1.6%

Length

2024-04-17T01:33:55.909153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:55.988204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
재개업일자 139
 
1.6%

trdstatenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
02
3708 
01
3400 
영업/정상
1119 
폐업
 
131
13
 
116
Other values (4)
 
62

Length

Max length5
Median length2
Mean length2.3942127
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
02 3708
43.4%
01 3400
39.8%
영업/정상 1119
 
13.1%
폐업 131
 
1.5%
13 116
 
1.4%
03 53
 
0.6%
휴업 4
 
< 0.1%
<NA> 4
 
< 0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:33:56.084422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:56.191887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3708
43.4%
01 3400
39.8%
영업/정상 1119
 
13.1%
폐업 131
 
1.5%
13 116
 
1.4%
03 53
 
0.6%
휴업 4
 
< 0.1%
na 4
 
< 0.1%
31 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
영업
4334 
폐업
3888 
영업중
 
302
휴업
 
8
<NA>
 
3

Length

Max length4
Median length2
Mean length2.0363168
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4334
50.8%
폐업 3888
45.5%
영업중 302
 
3.5%
휴업 8
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:33:56.332303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:56.451881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4334
50.8%
폐업 3888
45.5%
영업중 302
 
3.5%
휴업 8
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing384
Missing (%)4.5%
Memory size66.8 KiB

y
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing387
Missing (%)4.5%
Memory size66.8 KiB

lastmodts
Real number (ℝ)

Distinct3722
Distinct (%)43.6%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0134379 × 1013
Minimum1.9990211 × 1013
Maximum2.0210929 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.2 KiB
2024-04-17T01:33:56.560766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0020116 × 1013
Q12.0060629 × 1013
median2.0171127 × 1013
Q32.0180703 × 1013
95-th percentile2.0210629 × 1013
Maximum2.0210929 × 1013
Range2.2071817 × 1011
Interquartile range (IQR)1.2007417 × 1011

Descriptive statistics

Standard deviation6.9114874 × 1010
Coefficient of variation (CV)0.0034326797
Kurtosis-0.95916821
Mean2.0134379 × 1013
Median Absolute Deviation (MAD)2.9684997 × 1010
Skewness-0.77159275
Sum1.7180665 × 1017
Variance4.7768657 × 1021
MonotonicityNot monotonic
2024-04-17T01:33:56.671349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19990428000000 62
 
0.7%
20040902000000 60
 
0.7%
19990920000000 60
 
0.7%
20030122000000 58
 
0.7%
20040203000000 50
 
0.6%
20030414000000 36
 
0.4%
20070531000000 36
 
0.4%
20040427000000 32
 
0.4%
19990308000000 32
 
0.4%
20020515000000 32
 
0.4%
Other values (3712) 8075
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 (%)
20210929174334 1
< 0.1%
20210929151533 2
< 0.1%
20210929150937 2
< 0.1%
20210929131027 2
< 0.1%
20210928171955 2
< 0.1%
20210928144412 2
< 0.1%
20210928102756 2
< 0.1%
20210927151339 2
< 0.1%
20210927132440 2
< 0.1%
20210927131905 2
< 0.1%

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
여관업
5235 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
492
일반호텔
 
468
Other values (4)
676 

Length

Max length8
Median length3
Mean length3.7077085
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5235
61.3%
여인숙업 1076
 
12.6%
숙박업 기타 589
 
6.9%
숙박업(생활) 492
 
5.8%
일반호텔 468
 
5.5%
<NA> 341
 
4.0%
관광호텔 276
 
3.2%
업태구분명 50
 
0.6%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:33:56.784467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:56.881814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5235
57.4%
여인숙업 1076
 
11.8%
숙박업 589
 
6.5%
기타 589
 
6.5%
숙박업(생활 492
 
5.4%
일반호텔 468
 
5.1%
na 341
 
3.7%
관광호텔 276
 
3.0%
업태구분명 50
 
0.5%
휴양콘도미니엄업 9
 
0.1%

sitetel
Text

MISSING 

Distinct450
Distinct (%)5.4%
Missing157
Missing (%)1.8%
Memory size66.8 KiB
2024-04-17T01:33:57.060693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.88686
Min length4

Characters and Unicode

Total characters99600
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

Unique38 ?
Unique (%)0.5%

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 7459
78.0%
051 809
 
8.5%
전화번호 55
 
0.6%
070 14
 
0.1%
747 14
 
0.1%
806 13
 
0.1%
746 8
 
0.1%
805 8
 
0.1%
741 8
 
0.1%
803 7
 
0.1%
Other values (550) 1162
 
12.2%
2024-04-17T01:33:57.343467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23827
23.9%
2 15634
15.7%
3 15548
15.6%
- 14952
15.0%
0 9013
 
9.0%
5 8961
 
9.0%
4 8106
 
8.1%
1184
 
1.2%
7 713
 
0.7%
8 573
 
0.6%
Other values (6) 1089
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83244
83.6%
Dash Punctuation 14952
 
15.0%
Space Separator 1184
 
1.2%
Other Letter 220
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23827
28.6%
2 15634
18.8%
3 15548
18.7%
0 9013
 
10.8%
5 8961
 
10.8%
4 8106
 
9.7%
7 713
 
0.9%
8 573
 
0.7%
6 527
 
0.6%
9 342
 
0.4%
Other Letter
ValueCountFrequency (%)
55
25.0%
55
25.0%
55
25.0%
55
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 14952
100.0%
Space Separator
ValueCountFrequency (%)
1184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99380
99.8%
Hangul 220
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23827
24.0%
2 15634
15.7%
3 15548
15.6%
- 14952
15.0%
0 9013
 
9.1%
5 8961
 
9.0%
4 8106
 
8.2%
1184
 
1.2%
7 713
 
0.7%
8 573
 
0.6%
Other values (2) 869
 
0.9%
Hangul
ValueCountFrequency (%)
55
25.0%
55
25.0%
55
25.0%
55
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99380
99.8%
Hangul 220
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23827
24.0%
2 15634
15.7%
3 15548
15.6%
- 14952
15.0%
0 9013
 
9.1%
5 8961
 
9.0%
4 8106
 
8.2%
1184
 
1.2%
7 713
 
0.7%
8 573
 
0.6%
Other values (2) 869
 
0.9%
Hangul
ValueCountFrequency (%)
55
25.0%
55
25.0%
55
25.0%
55
25.0%

stroomcnt
Categorical

IMBALANCE 

Distinct30
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8275 
객실수
 
105
1
 
46
2
 
30
3
 
22
Other values (25)
 
58

Length

Max length4
Median length4
Mean length3.9366214
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> 8275
96.9%
객실수 105
 
1.2%
1 46
 
0.5%
2 30
 
0.4%
3 22
 
0.3%
7 8
 
0.1%
6 6
 
0.1%
0 5
 
0.1%
9 3
 
< 0.1%
11 3
 
< 0.1%
Other values (20) 33
 
0.4%

Length

2024-04-17T01:33:57.457876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8275
96.9%
객실수 105
 
1.2%
1 46
 
0.5%
2 30
 
0.4%
3 22
 
0.3%
7 8
 
0.1%
6 6
 
0.1%
0 5
 
0.1%
33 3
 
< 0.1%
8 3
 
< 0.1%
Other values (20) 33
 
0.4%

bdngownsenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
6468 
자가
1177 
임대
773 
건물소유구분명
 
118

Length

Max length7
Median length4
Mean length3.5845829
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6468
75.8%
자가 1177
 
13.8%
임대 773
 
9.1%
건물소유구분명 118
 
1.4%

Length

2024-04-17T01:33:57.551706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:57.639691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6468
75.8%
자가 1177
 
13.8%
임대 773
 
9.1%
건물소유구분명 118
 
1.4%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8235 
건물용도명
 
110
단독주택
 
74
아파트
 
60
숙박시설
 
24
Other values (6)
 
33

Length

Max length15
Median length4
Mean length4.0125351
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> 8235
96.5%
건물용도명 110
 
1.3%
단독주택 74
 
0.9%
아파트 60
 
0.7%
숙박시설 24
 
0.3%
다세대주택 15
 
0.2%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 주택(공동주택적용) 4
 
< 0.1%
호텔 4
 
< 0.1%

Length

2024-04-17T01:33:57.735936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8235
96.4%
건물용도명 110
 
1.3%
단독주택 74
 
0.9%
아파트 60
 
0.7%
숙박시설 24
 
0.3%
다세대주택 15
 
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 size66.8 KiB
0
2557 
<NA>
1675 
4
867 
3
749 
5
594 
Other values (30)
2094 

Length

Max length6
Median length1
Mean length1.6613168
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2557
30.0%
<NA> 1675
19.6%
4 867
 
10.2%
3 749
 
8.8%
5 594
 
7.0%
2 424
 
5.0%
8 322
 
3.8%
7 303
 
3.5%
6 303
 
3.5%
9 197
 
2.3%
Other values (25) 545
 
6.4%

Length

2024-04-17T01:33:57.835751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2557
30.0%
na 1675
19.6%
4 867
 
10.2%
3 749
 
8.8%
5 594
 
7.0%
2 424
 
5.0%
8 322
 
3.8%
6 303
 
3.5%
7 303
 
3.5%
9 197
 
2.3%
Other values (25) 545
 
6.4%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
0
4451 
<NA>
2241 
1
1494 
2
 
196
건물지하층수
 
50
Other values (9)
 
104

Length

Max length6
Median length1
Mean length1.8175961
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4451
52.1%
<NA> 2241
26.3%
1 1494
 
17.5%
2 196
 
2.3%
건물지하층수 50
 
0.6%
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

2024-04-17T01:33:57.950095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4451
52.1%
na 2241
26.3%
1 1496
 
17.5%
2 196
 
2.3%
건물지하층수 50
 
0.6%
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 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8359 
건축연면적
 
126
0
 
30
2282
 
3
20571
 
3
Other values (15)
 
15

Length

Max length5
Median length4
Mean length4.0031631
Min length1

Unique

Unique15 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8359
97.9%
건축연면적 126
 
1.5%
0 30
 
0.4%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
2875 1
 
< 0.1%
72 1
 
< 0.1%
39 1
 
< 0.1%
85 1
 
< 0.1%
437 1
 
< 0.1%
Other values (10) 10
 
0.1%

Length

2024-04-17T01:33:58.330813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8359
97.9%
건축연면적 126
 
1.5%
0 30
 
0.4%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
530 1
 
< 0.1%
155 1
 
< 0.1%
151 1
 
< 0.1%
13440 1
 
< 0.1%
2971 1
 
< 0.1%
Other values (10) 10
 
0.1%

svnsr
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
기념품종류
 
139

Length

Max length5
Median length4
Mean length4.016284
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
98.4%
기념품종류 139
 
1.6%

Length

2024-04-17T01:33:58.423095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:58.524291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
기념품종류 139
 
1.6%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
기획여행보험시작일자
 
139

Length

Max length10
Median length4
Mean length4.0977038
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
98.4%
기획여행보험시작일자 139
 
1.6%

Length

2024-04-17T01:33:58.622297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:58.703544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
기획여행보험시작일자 139
 
1.6%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
기획여행보험종료일자
 
139

Length

Max length10
Median length4
Mean length4.0977038
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
98.4%
기획여행보험종료일자 139
 
1.6%

Length

2024-04-17T01:33:58.789763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:58.871418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
기획여행보험종료일자 139
 
1.6%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
7779 
0
 
645
남성종사자수
 
82
1
 
12
3
 
5
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.7820993
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> 7779
91.1%
0 645
 
7.6%
남성종사자수 82
 
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

2024-04-17T01:33:58.957835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7779
91.1%
0 645
 
7.6%
남성종사자수 82
 
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 size66.8 KiB
<NA>
8397 
놀이기구수내역
 
139

Length

Max length7
Median length4
Mean length4.0488519
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
98.4%
놀이기구수내역 139
 
1.6%

Length

2024-04-17T01:33:59.083327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:59.203029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
놀이기구수내역 139
 
1.6%

playfacilcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
N
7456 
<NA>
933 
놀이시설수
 
111
0
 
33
Y
 
3

Length

Max length5
Median length1
Mean length1.3799203
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 7456
87.3%
<NA> 933
 
10.9%
놀이시설수 111
 
1.3%
0 33
 
0.4%
Y 3
 
< 0.1%

Length

2024-04-17T01:33:59.298386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:59.420915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 7456
87.3%
na 933
 
10.9%
놀이시설수 111
 
1.3%
0 33
 
0.4%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
N
8392 
<NA>
 
100
 
33
Y
 
11

Length

Max length4
Median length1
Mean length1.0351453
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8392
98.3%
<NA> 100
 
1.2%
33
 
0.4%
Y 11
 
0.1%

Length

2024-04-17T01:33:59.527738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:59.619858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8392
98.3%
na 100
 
1.2%
33
 
0.4%
y 11
 
0.1%

stagear
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8373 
무대면적
 
130
0
 
33

Length

Max length4
Median length4
Mean length3.9884021
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> 8373
98.1%
무대면적 130
 
1.5%
0 33
 
0.4%

Length

2024-04-17T01:33:59.713391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:59.798368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8373
98.1%
무대면적 130
 
1.5%
0 33
 
0.4%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
문화사업자구분명
 
139

Length

Max length8
Median length4
Mean length4.0651359
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
98.4%
문화사업자구분명 139
 
1.6%

Length

2024-04-17T01:33:59.893536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:59.987904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
문화사업자구분명 139
 
1.6%

culphyedcobnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8064 
외국인관광 도시민박업
 
283
문화체육업종명
 
89
관광숙박업
 
85
자동차야영장업
 
9
Other values (3)
 
6

Length

Max length11
Median length4
Mean length4.2772962
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> 8064
94.5%
외국인관광 도시민박업 283
 
3.3%
문화체육업종명 89
 
1.0%
관광숙박업 85
 
1.0%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%

Length

2024-04-17T01:34:00.094889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:00.222262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8064
91.4%
외국인관광 283
 
3.2%
도시민박업 283
 
3.2%
문화체육업종명 89
 
1.0%
관광숙박업 85
 
1.0%
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 size66.8 KiB
<NA>
8397 
 
139

Length

Max length4
Median length4
Mean length3.9511481
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
98.4%
139
 
1.6%

Length

2024-04-17T01:34:00.347329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:00.434936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
139
 
1.6%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
N
8379 
<NA>
 
100
 
33
Y
 
24

Length

Max length4
Median length1
Mean length1.0351453
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8379
98.2%
<NA> 100
 
1.2%
33
 
0.4%
Y 24
 
0.3%

Length

2024-04-17T01:34:00.532274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:00.650672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8379
98.2%
na 100
 
1.2%
33
 
0.4%
y 24
 
0.3%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
 
139

Length

Max length4
Median length4
Mean length3.9511481
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
98.4%
139
 
1.6%

Length

2024-04-17T01:34:00.769531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:00.877635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
139
 
1.6%

insurorgnm
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8374 
보험기관명
 
136
야영장사고배상책임보험
 
2
DB 손해보험
 
2
객실수/수용인원 : 2개/ 6명
 
2
Other values (20)
 
20

Length

Max length22
Median length4
Mean length4.0366682
Min length2

Unique

Unique20 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8374
98.1%
보험기관명 136
 
1.6%
야영장사고배상책임보험 2
 
< 0.1%
DB 손해보험 2
 
< 0.1%
객실수/수용인원 : 2개/ 6명 2
 
< 0.1%
객실수/수용인원:1/2 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

2024-04-17T01:34:01.003966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8374
97.9%
보험기관명 136
 
1.6%
객실수/수용인원 6
 
0.1%
5
 
0.1%
6명 2
 
< 0.1%
2개 2
 
< 0.1%
3/8 2
 
< 0.1%
손해보험 2
 
< 0.1%
db 2
 
< 0.1%
야영장사고배상책임보험 2
 
< 0.1%
Other values (21) 21
 
0.2%

insurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
보험시작일자
 
139

Length

Max length6
Median length4
Mean length4.0325679
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
98.4%
보험시작일자 139
 
1.6%

Length

2024-04-17T01:34:01.145104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:01.254532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
보험시작일자 139
 
1.6%

insurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
보험종료일자
 
139

Length

Max length6
Median length4
Mean length4.0325679
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
98.4%
보험종료일자 139
 
1.6%

Length

2024-04-17T01:34:01.353441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:01.462673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
보험종료일자 139
 
1.6%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
부대시설내역
 
139

Length

Max length6
Median length4
Mean length4.0325679
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
98.4%
부대시설내역 139
 
1.6%

Length

2024-04-17T01:34:01.570354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:01.687040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
부대시설내역 139
 
1.6%

usejisgendflr
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
2701 
0
1970 
4
762 
3
646 
5
472 
Other values (30)
1985 

Length

Max length6
Median length1
Mean length2.0180412
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2701
31.6%
0 1970
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) 464
 
5.4%

Length

2024-04-17T01:34:01.784574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2701
31.6%
0 1970
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) 464
 
5.4%

useunderendflr
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
0
4655 
<NA>
3612 
1
 
182
사용끝지하층
 
55
2
 
16
Other values (5)
 
16

Length

Max length6
Median length1
Mean length2.302015
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4655
54.5%
<NA> 3612
42.3%
1 182
 
2.1%
사용끝지하층 55
 
0.6%
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

2024-04-17T01:34:01.889783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:01.989748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4655
54.5%
na 3612
42.3%
1 182
 
2.1%
사용끝지하층 55
 
0.6%
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 size66.8 KiB
0
2462 
1
1907 
<NA>
1873 
2
989 
3
513 
Other values (15)
792 

Length

Max length7
Median length1
Mean length1.7017338
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2462
28.8%
1 1907
22.3%
<NA> 1873
21.9%
2 989
11.6%
3 513
 
6.0%
4 307
 
3.6%
5 194
 
2.3%
6 72
 
0.8%
7 59
 
0.7%
사용시작지상층 52
 
0.6%
Other values (10) 108
 
1.3%

Length

2024-04-17T01:34:02.111319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2462
28.8%
1 1907
22.3%
na 1873
21.9%
2 989
11.6%
3 513
 
6.0%
4 307
 
3.6%
5 194
 
2.3%
6 72
 
0.8%
7 59
 
0.7%
사용시작지상층 52
 
0.6%
Other values (10) 108
 
1.3%

useunderstflr
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
0
5594 
<NA>
2661 
1
 
215
사용시작지하층
 
53
4
 
8
Other values (3)
 
5

Length

Max length7
Median length1
Mean length1.9724695
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5594
65.5%
<NA> 2661
31.2%
1 215
 
2.5%
사용시작지하층 53
 
0.6%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:34:02.216487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:02.317932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5594
65.5%
na 2661
31.2%
1 215
 
2.5%
사용시작지하층 53
 
0.6%
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 size66.8 KiB
<NA>
8397 
선박제원
 
139

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
98.4%
선박제원 139
 
1.6%

Length

2024-04-17T01:34:02.416759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:02.499709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
선박제원 139
 
1.6%

shpcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8373 
선박척수
 
130
0
 
33

Length

Max length4
Median length4
Mean length3.9884021
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> 8373
98.1%
선박척수 130
 
1.5%
0 33
 
0.4%

Length

2024-04-17T01:34:02.597806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:02.710453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8373
98.1%
선박척수 130
 
1.5%
0 33
 
0.4%

shptottons
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8373 
선박총톤수
 
130
0
 
33

Length

Max length5
Median length4
Mean length4.0036317
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> 8373
98.1%
선박총톤수 130
 
1.5%
0 33
 
0.4%

Length

2024-04-17T01:34:02.813263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:02.906593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8373
98.1%
선박총톤수 130
 
1.5%
0 33
 
0.4%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
0
4998 
<NA>
3488 
세탁기수
 
50

Length

Max length4
Median length1
Mean length2.2434396
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4998
58.6%
<NA> 3488
40.9%
세탁기수 50
 
0.6%

Length

2024-04-17T01:34:02.999506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:03.086841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4998
58.6%
na 3488
40.9%
세탁기수 50
 
0.6%

facilscp
Text

MISSING 

Distinct151
Distinct (%)38.2%
Missing8141
Missing (%)95.4%
Memory size66.8 KiB
2024-04-17T01:34:03.331099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.9721519
Min length1

Characters and Unicode

Total characters1174
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 (%)20.8%

Sample

1st row시설규모
2nd row시설규모
3rd row시설규모
4th row시설규모
5th row시설규모
ValueCountFrequency (%)
시설규모 96
24.3%
85 16
 
4.1%
46 7
 
1.8%
67 6
 
1.5%
60 6
 
1.5%
599 6
 
1.5%
83 6
 
1.5%
63 5
 
1.3%
62 5
 
1.3%
84 4
 
1.0%
Other values (141) 238
60.3%
2024-04-17T01:34:03.731078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 120
10.2%
5 99
 
8.4%
96
 
8.2%
96
 
8.2%
96
 
8.2%
96
 
8.2%
8 82
 
7.0%
4 73
 
6.2%
6 73
 
6.2%
2 72
 
6.1%
Other values (4) 271
23.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 790
67.3%
Other Letter 384
32.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 120
15.2%
5 99
12.5%
8 82
10.4%
4 73
9.2%
6 73
9.2%
2 72
9.1%
9 69
8.7%
7 68
8.6%
3 68
8.6%
0 66
8.4%
Other Letter
ValueCountFrequency (%)
96
25.0%
96
25.0%
96
25.0%
96
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 790
67.3%
Hangul 384
32.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 120
15.2%
5 99
12.5%
8 82
10.4%
4 73
9.2%
6 73
9.2%
2 72
9.1%
9 69
8.7%
7 68
8.6%
3 68
8.6%
0 66
8.4%
Hangul
ValueCountFrequency (%)
96
25.0%
96
25.0%
96
25.0%
96
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 790
67.3%
Hangul 384
32.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 120
15.2%
5 99
12.5%
8 82
10.4%
4 73
9.2%
6 73
9.2%
2 72
9.1%
9 69
8.7%
7 68
8.6%
3 68
8.6%
0 66
8.4%
Hangul
ValueCountFrequency (%)
96
25.0%
96
25.0%
96
25.0%
96
25.0%

facilar
Text

MISSING 

Distinct222
Distinct (%)56.2%
Missing8141
Missing (%)95.4%
Memory size66.8 KiB
2024-04-17T01:34:04.057365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.9037975
Min length1

Characters and Unicode

Total characters1937
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 (%)44.6%

Sample

1st row시설면적
2nd row시설면적
3rd row시설면적
4th row시설면적
5th row시설면적
ValueCountFrequency (%)
시설면적 96
 
24.3%
45.5 6
 
1.5%
598.73 6
 
1.5%
0 4
 
1.0%
62.58 4
 
1.0%
218.85 4
 
1.0%
66.84 3
 
0.8%
8546.81 3
 
0.8%
59.4 3
 
0.8%
38.18 3
 
0.8%
Other values (212) 263
66.6%
2024-04-17T01:34:04.497182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 268
13.8%
1 167
 
8.6%
4 161
 
8.3%
8 154
 
8.0%
5 134
 
6.9%
2 124
 
6.4%
3 122
 
6.3%
6 121
 
6.2%
9 114
 
5.9%
7 107
 
5.5%
Other values (5) 465
24.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1285
66.3%
Other Letter 384
 
19.8%
Other Punctuation 268
 
13.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 167
13.0%
4 161
12.5%
8 154
12.0%
5 134
10.4%
2 124
9.6%
3 122
9.5%
6 121
9.4%
9 114
8.9%
7 107
8.3%
0 81
6.3%
Other Letter
ValueCountFrequency (%)
96
25.0%
96
25.0%
96
25.0%
96
25.0%
Other Punctuation
ValueCountFrequency (%)
. 268
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1553
80.2%
Hangul 384
 
19.8%

Most frequent character per script

Common
ValueCountFrequency (%)
. 268
17.3%
1 167
10.8%
4 161
10.4%
8 154
9.9%
5 134
8.6%
2 124
8.0%
3 122
7.9%
6 121
7.8%
9 114
7.3%
7 107
 
6.9%
Hangul
ValueCountFrequency (%)
96
25.0%
96
25.0%
96
25.0%
96
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1553
80.2%
Hangul 384
 
19.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 268
17.3%
1 167
10.8%
4 161
10.4%
8 154
9.9%
5 134
8.6%
2 124
8.0%
3 122
7.9%
6 121
7.8%
9 114
7.3%
7 107
 
6.9%
Hangul
ValueCountFrequency (%)
96
25.0%
96
25.0%
96
25.0%
96
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
 
139

Length

Max length4
Median length4
Mean length3.9511481
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
98.4%
139
 
1.6%

Length

2024-04-17T01:34:04.622146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:04.710873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
139
 
1.6%

yangsilcnt
Text

MISSING 

Distinct147
Distinct (%)1.9%
Missing919
Missing (%)10.8%
Memory size66.8 KiB
2024-04-17T01:34:04.874398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.741368
Min length1

Characters and Unicode

Total characters13264
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

Unique13 ?
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 (137) 3906
51.3%
2024-04-17T01:34:05.162654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3427
25.8%
0 1929
14.5%
2 1870
14.1%
3 1351
 
10.2%
4 1046
 
7.9%
5 822
 
6.2%
8 814
 
6.1%
6 638
 
4.8%
9 618
 
4.7%
7 599
 
4.5%
Other values (3) 150
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13114
98.9%
Other Letter 150
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3427
26.1%
0 1929
14.7%
2 1870
14.3%
3 1351
 
10.3%
4 1046
 
8.0%
5 822
 
6.3%
8 814
 
6.2%
6 638
 
4.9%
9 618
 
4.7%
7 599
 
4.6%
Other Letter
ValueCountFrequency (%)
50
33.3%
50
33.3%
50
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13114
98.9%
Hangul 150
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3427
26.1%
0 1929
14.7%
2 1870
14.3%
3 1351
 
10.3%
4 1046
 
8.0%
5 822
 
6.3%
8 814
 
6.2%
6 638
 
4.9%
9 618
 
4.7%
7 599
 
4.6%
Hangul
ValueCountFrequency (%)
50
33.3%
50
33.3%
50
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13114
98.9%
Hangul 150
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3427
26.1%
0 1929
14.7%
2 1870
14.3%
3 1351
 
10.3%
4 1046
 
8.0%
5 822
 
6.3%
8 814
 
6.2%
6 638
 
4.9%
9 618
 
4.7%
7 599
 
4.6%
Hangul
ValueCountFrequency (%)
50
33.3%
50
33.3%
50
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
7781 
0
 
651
여성종사자수
 
82
2
 
6
1
 
6
Other values (4)
 
10

Length

Max length6
Median length4
Mean length3.7830366
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> 7781
91.2%
0 651
 
7.6%
여성종사자수 82
 
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

2024-04-17T01:34:05.304599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:05.436134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7781
91.2%
0 651
 
7.6%
여성종사자수 82
 
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
Text

MISSING 

Distinct51
Distinct (%)26.3%
Missing8342
Missing (%)97.7%
Memory size66.8 KiB
2024-04-17T01:34:05.630944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length5
Mean length8.5515464
Min length4

Characters and Unicode

Total characters1659
Distinct characters59
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)20.6%

Sample

1st row영문상호명
2nd row영문상호명
3rd row영문상호명
4th row영문상호명
5th row영문상호명
ValueCountFrequency (%)
영문상호명 127
45.0%
house 31
 
11.0%
busan 9
 
3.2%
ocean 6
 
2.1%
hotel 6
 
2.1%
guest 5
 
1.8%
kim's 4
 
1.4%
suyeong 3
 
1.1%
cheonghaksodam 3
 
1.1%
in 3
 
1.1%
Other values (60) 85
30.1%
2024-04-17T01:34:05.930450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
 
7.7%
127
 
7.7%
127
 
7.7%
127
 
7.7%
127
 
7.7%
e 90
 
5.4%
88
 
5.3%
o 77
 
4.6%
a 58
 
3.5%
n 54
 
3.3%
Other values (49) 657
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 635
38.3%
Lowercase Letter 599
36.1%
Uppercase Letter 311
18.7%
Space Separator 88
 
5.3%
Decimal Number 12
 
0.7%
Dash Punctuation 7
 
0.4%
Other Punctuation 7
 
0.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 39
12.5%
S 36
11.6%
E 31
 
10.0%
O 24
 
7.7%
U 21
 
6.8%
B 19
 
6.1%
Y 16
 
5.1%
A 14
 
4.5%
P 13
 
4.2%
G 12
 
3.9%
Other values (14) 86
27.7%
Lowercase Letter
ValueCountFrequency (%)
e 90
15.0%
o 77
12.9%
a 58
9.7%
n 54
9.0%
u 49
 
8.2%
s 40
 
6.7%
h 28
 
4.7%
t 27
 
4.5%
i 24
 
4.0%
m 23
 
3.8%
Other values (12) 129
21.5%
Other Letter
ValueCountFrequency (%)
127
20.0%
127
20.0%
127
20.0%
127
20.0%
127
20.0%
Decimal Number
ValueCountFrequency (%)
0 7
58.3%
2 3
25.0%
1 2
 
16.7%
Other Punctuation
ValueCountFrequency (%)
' 5
71.4%
& 1
 
14.3%
. 1
 
14.3%
Space Separator
ValueCountFrequency (%)
88
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 910
54.9%
Hangul 635
38.3%
Common 114
 
6.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 90
 
9.9%
o 77
 
8.5%
a 58
 
6.4%
n 54
 
5.9%
u 49
 
5.4%
s 40
 
4.4%
H 39
 
4.3%
S 36
 
4.0%
E 31
 
3.4%
h 28
 
3.1%
Other values (36) 408
44.8%
Common
ValueCountFrequency (%)
88
77.2%
0 7
 
6.1%
- 7
 
6.1%
' 5
 
4.4%
2 3
 
2.6%
1 2
 
1.8%
& 1
 
0.9%
. 1
 
0.9%
Hangul
ValueCountFrequency (%)
127
20.0%
127
20.0%
127
20.0%
127
20.0%
127
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1024
61.7%
Hangul 635
38.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
127
20.0%
127
20.0%
127
20.0%
127
20.0%
127
20.0%
ASCII
ValueCountFrequency (%)
e 90
 
8.8%
88
 
8.6%
o 77
 
7.5%
a 58
 
5.7%
n 54
 
5.3%
u 49
 
4.8%
s 40
 
3.9%
H 39
 
3.8%
S 36
 
3.5%
E 31
 
3.0%
Other values (44) 462
45.1%

engstntrnmaddr
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8345 
영문상호주소
 
127
Guesthouse for Foreign Tourists
 
21
Foreigner Tourism City home-stay Business
 
14
Guest House
 
4
Other values (15)
 
25

Length

Max length41
Median length4
Mean length4.2299672
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> 8345
97.8%
영문상호주소 127
 
1.5%
Guesthouse for Foreign Tourists 21
 
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

2024-04-17T01:34:06.057496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8345
95.7%
영문상호주소 127
 
1.5%
for 28
 
0.3%
foreign 27
 
0.3%
guesthouse 24
 
0.3%
tourists 24
 
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 size66.8 KiB
0
5842 
<NA>
2456 
욕실수
 
50
15
 
16
12
 
14
Other values (28)
 
158

Length

Max length4
Median length1
Mean length1.8943299
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5842
68.4%
<NA> 2456
28.8%
욕실수 50
 
0.6%
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

2024-04-17T01:34:06.175758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 5842
68.4%
na 2456
28.8%
욕실수 50
 
0.6%
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 size66.8 KiB
여관업
5235 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
492
일반호텔
 
468
Other values (4)
676 

Length

Max length8
Median length3
Mean length3.7077085
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5235
61.3%
여인숙업 1076
 
12.6%
숙박업 기타 589
 
6.9%
숙박업(생활) 492
 
5.8%
일반호텔 468
 
5.5%
<NA> 341
 
4.0%
관광호텔 276
 
3.2%
위생업태명 50
 
0.6%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:34:06.283617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:06.384539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5235
57.4%
여인숙업 1076
 
11.8%
숙박업 589
 
6.5%
기타 589
 
6.5%
숙박업(생활 492
 
5.4%
일반호텔 468
 
5.1%
na 341
 
3.7%
관광호텔 276
 
3.0%
위생업태명 50
 
0.5%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
 
139

Length

Max length4
Median length4
Mean length3.9511481
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
98.4%
139
 
1.6%

Length

2024-04-17T01:34:06.738593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:06.840585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
139
 
1.6%

capt
Categorical

IMBALANCE 

Distinct43
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8295 
자본금
 
111
0
 
26
10000000
 
19
100000000
 
12
Other values (38)
 
73

Length

Max length10
Median length4
Mean length4.0315136
Min length1

Unique

Unique23 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8295
97.2%
자본금 111
 
1.3%
0 26
 
0.3%
10000000 19
 
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 (33) 47
 
0.6%

Length

2024-04-17T01:34:06.932742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8295
97.2%
자본금 111
 
1.3%
0 26
 
0.3%
10000000 19
 
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 (33) 47
 
0.6%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
제작취급품목내용
 
139

Length

Max length8
Median length4
Mean length4.0651359
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
98.4%
제작취급품목내용 139
 
1.6%

Length

2024-04-17T01:34:07.036330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:07.136323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
제작취급품목내용 139
 
1.6%

cndpermstymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
조건부허가시작일자
 
139

Length

Max length9
Median length4
Mean length4.0814199
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
98.4%
조건부허가시작일자 139
 
1.6%

Length

2024-04-17T01:34:07.235182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:07.321700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
조건부허가시작일자 139
 
1.6%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
조건부허가신고사유
 
139

Length

Max length9
Median length4
Mean length4.0814199
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
98.4%
조건부허가신고사유 139
 
1.6%

Length

2024-04-17T01:34:07.412539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:07.528259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
조건부허가신고사유 139
 
1.6%

cndpermendymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8397 
조건부허가종료일자
 
139

Length

Max length9
Median length4
Mean length4.0814199
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
98.4%
조건부허가종료일자 139
 
1.6%

Length

2024-04-17T01:34:07.615786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:07.714803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8397
98.4%
조건부허가종료일자 139
 
1.6%

chaircnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
4966 
0
3524 
좌석수
 
41
6
 
1
12
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length2.7550375
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4966
58.2%
0 3524
41.3%
좌석수 41
 
0.5%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-17T01:34:07.827584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:07.936277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4966
58.2%
0 3524
41.3%
좌석수 41
 
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 size66.8 KiB
<NA>
8303 
주변환경명
 
121
주택가주변
 
38
아파트지역
 
32
기타
 
25
Other values (3)
 
17

Length

Max length8
Median length4
Mean length4.0244845
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> 8303
97.3%
주변환경명 121
 
1.4%
주택가주변 38
 
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

2024-04-17T01:34:08.048754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:08.162173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8303
97.3%
주변환경명 121
 
1.4%
주택가주변 38
 
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 size66.8 KiB
<NA>
8265 
지상층수
 
109
2
 
33
4
 
19
1
 
15
Other values (22)
 
95

Length

Max length4
Median length4
Mean length3.9476336
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> 8265
96.8%
지상층수 109
 
1.3%
2 33
 
0.4%
4 19
 
0.2%
1 15
 
0.2%
0 13
 
0.2%
3 13
 
0.2%
5 11
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
Other values (17) 44
 
0.5%

Length

2024-04-17T01:34:08.285084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8265
96.8%
지상층수 109
 
1.3%
2 33
 
0.4%
4 19
 
0.2%
1 15
 
0.2%
0 13
 
0.2%
3 13
 
0.2%
5 11
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
Other values (17) 44
 
0.5%

regnsenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8192 
일반주거지역
 
119
지역구분명
 
105
일반상업지역
 
42
주거지역
 
31
Other values (5)
 
47

Length

Max length6
Median length4
Mean length4.0552952
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> 8192
96.0%
일반주거지역 119
 
1.4%
지역구분명 105
 
1.2%
일반상업지역 42
 
0.5%
주거지역 31
 
0.4%
준주거지역 31
 
0.4%
자연녹지지역 6
 
0.1%
상업지역 6
 
0.1%
녹지지역 3
 
< 0.1%
전용주거지역 1
 
< 0.1%

Length

2024-04-17T01:34:08.405327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:08.520458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8192
96.0%
일반주거지역 119
 
1.4%
지역구분명 105
 
1.2%
일반상업지역 42
 
0.5%
주거지역 31
 
0.4%
준주거지역 31
 
0.4%
자연녹지지역 6
 
0.1%
상업지역 6
 
0.1%
녹지지역 3
 
< 0.1%
전용주거지역 1
 
< 0.1%

undernumlay
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8334 
지하층수
 
114
0
 
32
1
 
29
2
 
21
Other values (4)
 
6

Length

Max length4
Median length4
Mean length3.9690722
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> 8334
97.6%
지하층수 114
 
1.3%
0 32
 
0.4%
1 29
 
0.3%
2 21
 
0.2%
3 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:34:08.648963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:08.771071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8334
97.6%
지하층수 114
 
1.3%
0 32
 
0.4%
1 29
 
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 size66.8 KiB
<NA>
8253 
총층수
 
105
2
 
40
4
 
21
1
 
20
Other values (21)
 
97

Length

Max length4
Median length4
Mean length3.9297095
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> 8253
96.7%
총층수 105
 
1.2%
2 40
 
0.5%
4 21
 
0.2%
1 20
 
0.2%
3 17
 
0.2%
5 14
 
0.2%
0 10
 
0.1%
6 8
 
0.1%
20 7
 
0.1%
Other values (16) 41
 
0.5%

Length

2024-04-17T01:34:08.895347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8253
96.7%
총층수 105
 
1.2%
2 40
 
0.5%
4 21
 
0.2%
1 20
 
0.2%
3 17
 
0.2%
5 14
 
0.2%
0 10
 
0.1%
6 8
 
0.1%
20 7
 
0.1%
Other values (16) 41
 
0.5%

abedcnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
0
4952 
<NA>
3532 
침대수
 
50
41
 
2

Length

Max length4
Median length1
Mean length2.2532802
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4952
58.0%
<NA> 3532
41.4%
침대수 50
 
0.6%
41 2
 
< 0.1%

Length

2024-04-17T01:34:08.997130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:09.086285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4952
58.0%
na 3532
41.4%
침대수 50
 
0.6%
41 2
 
< 0.1%

hanshilcnt
Categorical

Distinct49
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
0
3731 
<NA>
1480 
2
 
328
10
 
310
3
 
266
Other values (44)
2421 

Length

Max length4
Median length1
Mean length1.6811153
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3731
43.7%
<NA> 1480
 
17.3%
2 328
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 262
 
3.1%
8 226
 
2.6%
4 203
 
2.4%
6 200
 
2.3%
9 197
 
2.3%
Other values (39) 1333
 
15.6%

Length

2024-04-17T01:34:09.184941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3731
43.7%
na 1480
 
17.3%
2 328
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 262
 
3.1%
8 226
 
2.6%
4 203
 
2.4%
6 200
 
2.3%
9 197
 
2.3%
Other values (39) 1333
 
15.6%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
0
4960 
<NA>
3526 
회수건조수
 
50

Length

Max length5
Median length1
Mean length2.2626523
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4960
58.1%
<NA> 3526
41.3%
회수건조수 50
 
0.6%

Length

2024-04-17T01:34:09.298470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:09.392566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4960
58.1%
na 3526
41.3%
회수건조수 50
 
0.6%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
<NA>
8373 
회의실별동시수용인원
 
130
0
 
33

Length

Max length10
Median length4
Mean length4.0797798
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> 8373
98.1%
회의실별동시수용인원 130
 
1.5%
0 33
 
0.4%

Length

2024-04-17T01:34:09.487672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:09.581393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8373
98.1%
회의실별동시수용인원 130
 
1.5%
0 33
 
0.4%

last_load_dttm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.8 KiB
2021-10-01 05:09:04
5397 
2021-10-01 05:09:03
3017 
2021-10-01 05:09:05
 
116
<NA>
 
6

Length

Max length19
Median length19
Mean length18.989456
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-10-01 05:09:03
2nd row2021-10-01 05:09:03
3rd row2021-10-01 05:09:03
4th row2021-10-01 05:09:03
5th row2021-10-01 05:09:03

Common Values

ValueCountFrequency (%)
2021-10-01 05:09:04 5397
63.2%
2021-10-01 05:09:03 3017
35.3%
2021-10-01 05:09:05 116
 
1.4%
<NA> 6
 
0.1%

Length

2024-04-17T01:34:09.675946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:09.764116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-10-01 8530
50.0%
05:09:04 5397
31.6%
05:09:03 3017
 
17.7%
05:09:05 116
 
0.7%
na 6
 
< 0.1%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
0232500003250000-201-2017-0000203_11_03_PI2018-08-31 23:59:59.0<NA>(주)아이에이치엠 호텔포레 프리미어 남포지점600045부산광역시 중구 남포동5가 8-1번지48953.0부산광역시 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>2021-10-01 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>2021-10-01 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>2021-10-01 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>2021-10-01 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>2021-10-01 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>2021-10-01 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>2021-10-01 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>2021-10-01 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>2021-10-01 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>2021-10-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
85261302733600003360000-201-2021-0000103_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>2021-10-01 05:09:05
85271302833300003330000-214-2021-0000203_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>2021-10-01 05:09:05
85281302933800003380000-214-2021-0000403_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>2021-10-01 05:09:05
85291303033300003330000-214-2021-0000303_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>2021-10-01 05:09:05
8530130313280000CDFI226221202100000103_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>2021-10-01 05:09:05
85311303233300003330000-214-2021-0000303_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>2021-10-01 05:09:05
8532130333280000CDFI226221202100000103_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>2021-10-01 05:09:05
8533130413330000CDFI226221201500002603_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>2021-10-01 05:09:05
85341304233800003380000-214-2021-0000603_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>2021-10-01 05:09:05
8535130433380000CDFI226003202100000303_11_01_PU2021-06-24 02:40:00.0관광숙박업제이스테이 펜트하우스지번우편번호부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210525폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392732.161638137185542.45270223420210622151628업태구분명전화번호4건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명관광숙박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수219218.85양실수여성종사자수영문상호명영문상호주소욕실수위생업태명125000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수지역구분명지하층수총층수침대수한실수회수건조수회의실별동시수용인원2021-10-01 05:09:05

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnwhladdrdcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmlastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
313330000CDFI226003201800000503_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>2021-10-01 05:09:046
53250000CDFI226221201900000103_11_04_PU2021-05-05 02:40:00.0외국인관광도시민박업보수동방공호지번우편번호부산광역시 중구 보수동1가 116-156부산광역시 중구 책방골목길 13-11 (보수동1가)20210427휴업시작일자휴업종료일자재개업일자폐업폐업20210503101511업태구분명전화번호6건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수168167.82양실수여성종사자수영문상호명영문상호주소욕실수위생업태명자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수일반상업지역지하층수3침대수한실수회수건조수회의실별동시수용인원2021-10-01 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>2021-10-01 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>2021-10-01 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>2021-10-01 05:09:043
123280000CDFI226221202000000103_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 Tourists욕실수위생업태명10000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수아파트지역20일반주거지역220침대수한실수회수건조수회의실별동시수용인원2021-10-01 05:09:043
133280000CDFI226221202000000203_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 Tourists욕실수위생업태명0제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0아파트지역20주거지역220침대수한실수회수건조수02021-10-01 05:09:043
143280000CDFI226221202000000303_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>2021-10-01 05:09:043
1832900003290000-201-2019-0000203_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>2021-10-01 05:09:043
1932900003290000-201-2020-0000103_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>2021-10-01 05:09:043