Overview

Dataset statistics

Number of variables81
Number of observations8556
Missing cells68054
Missing cells (%)9.8%
Duplicate rows711
Duplicate rows (%)8.3%
Total size in memory5.3 MiB
Average record size in memory651.0 B

Variable types

Unsupported17
Numeric3
Text10
Categorical49
DateTime2

Alerts

Dataset has 711 (8.3%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (89.3%)Imbalance
updategbn is highly imbalanced (60.2%)Imbalance
opnsvcnm is highly imbalanced (73.4%)Imbalance
clgstdt is highly imbalanced (95.4%)Imbalance
clgenddt is highly imbalanced (95.4%)Imbalance
ropnymd is highly imbalanced (87.3%)Imbalance
dtlstatenm is highly imbalanced (53.7%)Imbalance
stroomcnt is highly imbalanced (93.9%)Imbalance
bdngsrvnm is highly imbalanced (90.9%)Imbalance
cnstyarea is highly imbalanced (95.6%)Imbalance
svnsr is highly imbalanced (87.3%)Imbalance
plninsurstdt is highly imbalanced (87.3%)Imbalance
plninsurenddt is highly imbalanced (87.3%)Imbalance
maneipcnt is highly imbalanced (83.6%)Imbalance
playutscntdtl is highly imbalanced (87.3%)Imbalance
playfacilcnt is highly imbalanced (68.9%)Imbalance
multusnupsoyn is highly imbalanced (92.3%)Imbalance
stagear is highly imbalanced (89.5%)Imbalance
culwrkrsenm is highly imbalanced (87.3%)Imbalance
culphyedcobnm is highly imbalanced (86.5%)Imbalance
geicpfacilen is highly imbalanced (87.3%)Imbalance
balhansilyn is highly imbalanced (91.6%)Imbalance
bcfacilen is highly imbalanced (87.3%)Imbalance
insurorgnm is highly imbalanced (96.3%)Imbalance
insurstdt is highly imbalanced (87.3%)Imbalance
insurenddt is highly imbalanced (87.3%)Imbalance
afc is highly imbalanced (87.3%)Imbalance
shpinfo is highly imbalanced (87.3%)Imbalance
shpcnt is highly imbalanced (89.5%)Imbalance
shptottons is highly imbalanced (89.5%)Imbalance
infoben is highly imbalanced (87.3%)Imbalance
wmeipcnt is highly imbalanced (82.4%)Imbalance
engstntrnmaddr is highly imbalanced (95.2%)Imbalance
dispenen is highly imbalanced (87.3%)Imbalance
capt is highly imbalanced (94.6%)Imbalance
mnfactreartclcn is highly imbalanced (87.3%)Imbalance
cndpermstymd is highly imbalanced (87.3%)Imbalance
cndpermntwhy is highly imbalanced (87.3%)Imbalance
cndpermendymd is highly imbalanced (87.3%)Imbalance
nearenvnm is highly imbalanced (91.9%)Imbalance
jisgnumlay is highly imbalanced (93.2%)Imbalance
regnsenm is highly imbalanced (89.6%)Imbalance
undernumlay is highly imbalanced (93.3%)Imbalance
totnumlay is highly imbalanced (92.9%)Imbalance
meetsamtimesygstf is highly imbalanced (89.5%)Imbalance
sitepostno has 315 (3.7%) missing valuesMissing
rdnwhladdr has 2550 (29.8%) missing valuesMissing
dcbymd has 4481 (52.4%) missing valuesMissing
x has 385 (4.5%) missing valuesMissing
y has 388 (4.5%) missing valuesMissing
sitetel has 180 (2.1%) missing valuesMissing
bdngjisgflrcnt has 1678 (19.6%) missing valuesMissing
bdngunderflrcnt has 2244 (26.2%) missing valuesMissing
usejisgendflr has 2704 (31.6%) missing valuesMissing
useunderendflr has 3609 (42.2%) missing valuesMissing
usejisgstflr has 1876 (21.9%) missing valuesMissing
useunderstflr has 2658 (31.1%) missing valuesMissing
washmccnt has 3491 (40.8%) missing valuesMissing
facilscp has 8145 (95.2%) missing valuesMissing
facilar has 8145 (95.2%) missing valuesMissing
yangsilcnt has 924 (10.8%) missing valuesMissing
engstntrnmnm has 8350 (97.6%) missing valuesMissing
yoksilcnt has 2459 (28.7%) missing valuesMissing
chaircnt has 4865 (56.9%) missing valuesMissing
abedcnt has 3535 (41.3%) missing valuesMissing
hanshilcnt has 1483 (17.3%) missing valuesMissing
rcvdryncnt has 3529 (41.2%) 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
bdngjisgflrcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
bdngunderflrcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
usejisgendflr is an unsupported type, check if it needs cleaning or further analysisUnsupported
useunderendflr is an unsupported type, check if it needs cleaning or further analysisUnsupported
usejisgstflr is an unsupported type, check if it needs cleaning or further analysisUnsupported
useunderstflr is an unsupported type, check if it needs cleaning or further analysisUnsupported
washmccnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
yangsilcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
yoksilcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
chaircnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
abedcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
hanshilcnt is an unsupported type, check if it needs cleaning or further analysisUnsupported
rcvdryncnt is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 16:32:58.045770
Analysis finished2024-04-16 16:33:00.857764
Duration2.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size67.0 KiB

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3318932.5
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.3 KiB
2024-04-17T01:33:00.906509image/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 deviation42858.778
Coefficient of variation (CV)0.012913423
Kurtosis-0.9736969
Mean3318932.5
Median Absolute Deviation (MAD)30000
Skewness0.26409911
Sum2.838683 × 1010
Variance1.8368749 × 109
MonotonicityNot monotonic
2024-04-17T01:33:01.048077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1173
13.7%
3290000 1060
12.4%
3300000 893
10.4%
3390000 689
 
8.1%
3270000 655
 
7.7%
3320000 578
 
6.8%
3380000 502
 
5.9%
3250000 485
 
5.7%
3260000 406
 
4.7%
3370000 383
 
4.5%
Other values (6) 1729
20.2%
ValueCountFrequency (%)
3250000 485
5.7%
3260000 406
 
4.7%
3270000 655
7.7%
3280000 378
 
4.4%
3290000 1060
12.4%
3300000 893
10.4%
3310000 285
 
3.3%
3320000 578
6.8%
3330000 1173
13.7%
3340000 363
 
4.2%
ValueCountFrequency (%)
3400000 212
 
2.5%
3390000 689
8.1%
3380000 502
5.9%
3370000 383
 
4.5%
3360000 138
 
1.6%
3350000 353
 
4.1%
3340000 363
 
4.2%
3330000 1173
13.7%
3320000 578
6.8%
3310000 285
 
3.3%

mgtno
Text

Distinct4253
Distinct (%)49.7%
Missing3
Missing (%)< 0.1%
Memory size67.0 KiB
2024-04-17T01:33:01.256445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.908336
Min length20

Characters and Unicode

Total characters187382
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

Unique164 ?
Unique (%)1.9%

Sample

1st row3250000-201-2017-00002
2nd row3250000-201-2014-00001
3rd row3250000-214-2017-00003
4th row3250000-201-1971-00116
5th row3250000-201-2012-00005
ValueCountFrequency (%)
cdfi2262212019000001 15
 
0.2%
cdfi2262212015000001 12
 
0.1%
cdfi2262212018000001 12
 
0.1%
cdfi2262212016000001 11
 
0.1%
cdfi2262212017000001 11
 
0.1%
cdfi2262212015000002 11
 
0.1%
cdfi2262212016000002 10
 
0.1%
cdfi2262212020000001 10
 
0.1%
cdfi2262212014000001 9
 
0.1%
cdfi2260032021000001 9
 
0.1%
Other values (4243) 8443
98.7%
2024-04-17T01:33:01.572498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72145
38.5%
- 24483
 
13.1%
1 20224
 
10.8%
2 20202
 
10.8%
3 18296
 
9.8%
9 10163
 
5.4%
8 4982
 
2.7%
7 4876
 
2.6%
6 3747
 
2.0%
4 3637
 
1.9%
Other values (5) 4627
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 161331
86.1%
Dash Punctuation 24483
 
13.1%
Uppercase Letter 1568
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72145
44.7%
1 20224
 
12.5%
2 20202
 
12.5%
3 18296
 
11.3%
9 10163
 
6.3%
8 4982
 
3.1%
7 4876
 
3.0%
6 3747
 
2.3%
4 3637
 
2.3%
5 3059
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 392
25.0%
D 392
25.0%
F 392
25.0%
I 392
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24483
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 185814
99.2%
Latin 1568
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72145
38.8%
- 24483
 
13.2%
1 20224
 
10.9%
2 20202
 
10.9%
3 18296
 
9.8%
9 10163
 
5.5%
8 4982
 
2.7%
7 4876
 
2.6%
6 3747
 
2.0%
4 3637
 
2.0%
Latin
ValueCountFrequency (%)
C 392
25.0%
D 392
25.0%
F 392
25.0%
I 392
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 187382
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72145
38.5%
- 24483
 
13.1%
1 20224
 
10.8%
2 20202
 
10.8%
3 18296
 
9.8%
9 10163
 
5.4%
8 4982
 
2.7%
7 4876
 
2.6%
6 3747
 
2.0%
4 3637
 
1.9%
Other values (5) 4627
 
2.5%

opnsvcid
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
03_11_03_P
8161 
03_11_04_P
 
289
03_11_01_P
 
88
03_11_05_P
 
9
03_11_02_P
 
3
Other values (3)
 
6

Length

Max length10
Median length10
Mean length9.9978962
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 8161
95.4%
03_11_04_P 289
 
3.4%
03_11_01_P 88
 
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

2024-04-17T01:33:01.694530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:01.807470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8161
95.4%
03_11_04_p 289
 
3.4%
03_11_01_p 88
 
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 size67.0 KiB
I
7213 
U
1340 
180000000
 
3

Length

Max length9
Median length1
Mean length1.002805
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7213
84.3%
U 1340
 
15.7%
180000000 3
 
< 0.1%

Length

2024-04-17T01:33:01.928761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:02.035116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7213
84.3%
u 1340
 
15.7%
180000000 3
 
< 0.1%
Distinct327
Distinct (%)3.8%
Missing3
Missing (%)< 0.1%
Memory size67.0 KiB
Minimum2018-08-31 23:59:59
Maximum2021-12-01 02:40:00
2024-04-17T01:33:02.155122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:33:02.302441image/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 size67.0 KiB
<NA>
7086 
숙박업
1249 
외국인관광도시민박업
 
127
관광숙박업
 
88
자동차야영장업
 
2
Other values (3)
 
4

Length

Max length10
Median length4
Mean length3.9546517
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> 7086
82.8%
숙박업 1249
 
14.6%
외국인관광도시민박업 127
 
1.5%
관광숙박업 88
 
1.0%
자동차야영장업 2
 
< 0.1%
한옥체험업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

Length

2024-04-17T01:33:02.410522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:02.517170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7086
82.8%
숙박업 1249
 
14.6%
외국인관광도시민박업 127
 
1.5%
관광숙박업 88
 
1.0%
자동차야영장업 2
 
< 0.1%
한옥체험업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

bplcnm
Text

Distinct3444
Distinct (%)40.3%
Missing3
Missing (%)< 0.1%
Memory size67.0 KiB
2024-04-17T01:33:02.781735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length5.2020344
Min length1

Characters and Unicode

Total characters44493
Distinct characters653
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

Unique338 ?
Unique (%)4.0%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 칠구(K79)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 256
 
2.5%
모텔 182
 
1.8%
게스트하우스 121
 
1.2%
여관 82
 
0.8%
hotel 65
 
0.6%
부산 51
 
0.5%
house 48
 
0.5%
해운대 41
 
0.4%
여인숙 36
 
0.4%
35
 
0.3%
Other values (3551) 9330
91.1%
2024-04-17T01:33:03.186197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2950
 
6.6%
2015
 
4.5%
1789
 
4.0%
1724
 
3.9%
1711
 
3.8%
1514
 
3.4%
1421
 
3.2%
1271
 
2.9%
772
 
1.7%
757
 
1.7%
Other values (643) 28569
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37318
83.9%
Uppercase Letter 2484
 
5.6%
Space Separator 1711
 
3.8%
Lowercase Letter 1244
 
2.8%
Open Punctuation 534
 
1.2%
Close Punctuation 534
 
1.2%
Decimal Number 512
 
1.2%
Other Punctuation 102
 
0.2%
Dash Punctuation 31
 
0.1%
Letter Number 11
 
< 0.1%
Other values (4) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2950
 
7.9%
2015
 
5.4%
1789
 
4.8%
1724
 
4.6%
1514
 
4.1%
1421
 
3.8%
1271
 
3.4%
772
 
2.1%
757
 
2.0%
622
 
1.7%
Other values (563) 22483
60.2%
Uppercase Letter
ValueCountFrequency (%)
E 254
 
10.2%
O 243
 
9.8%
H 228
 
9.2%
T 200
 
8.1%
S 169
 
6.8%
A 149
 
6.0%
L 144
 
5.8%
N 124
 
5.0%
B 102
 
4.1%
U 101
 
4.1%
Other values (16) 770
31.0%
Lowercase Letter
ValueCountFrequency (%)
e 202
16.2%
o 140
11.3%
a 106
8.5%
s 105
8.4%
n 93
 
7.5%
u 91
 
7.3%
t 87
 
7.0%
h 59
 
4.7%
l 56
 
4.5%
i 54
 
4.3%
Other values (16) 251
20.2%
Decimal Number
ValueCountFrequency (%)
2 126
24.6%
1 71
13.9%
5 62
12.1%
7 60
11.7%
9 57
11.1%
0 40
 
7.8%
6 33
 
6.4%
3 28
 
5.5%
4 25
 
4.9%
8 10
 
2.0%
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 (%)
7
63.6%
4
36.4%
Math Symbol
ValueCountFrequency (%)
2
50.0%
+ 2
50.0%
Space Separator
ValueCountFrequency (%)
1711
100.0%
Open Punctuation
ValueCountFrequency (%)
( 534
100.0%
Close Punctuation
ValueCountFrequency (%)
) 534
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Symbol
ValueCountFrequency (%)
6
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37316
83.9%
Latin 3739
 
8.4%
Common 3430
 
7.7%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2950
 
7.9%
2015
 
5.4%
1789
 
4.8%
1724
 
4.6%
1514
 
4.1%
1421
 
3.8%
1271
 
3.4%
772
 
2.1%
757
 
2.0%
622
 
1.7%
Other values (559) 22481
60.2%
Latin
ValueCountFrequency (%)
E 254
 
6.8%
O 243
 
6.5%
H 228
 
6.1%
e 202
 
5.4%
T 200
 
5.3%
S 169
 
4.5%
A 149
 
4.0%
L 144
 
3.9%
o 140
 
3.7%
N 124
 
3.3%
Other values (44) 1886
50.4%
Common
ValueCountFrequency (%)
1711
49.9%
( 534
 
15.6%
) 534
 
15.6%
2 126
 
3.7%
1 71
 
2.1%
5 62
 
1.8%
7 60
 
1.7%
. 57
 
1.7%
9 57
 
1.7%
0 40
 
1.2%
Other values (15) 178
 
5.2%
Han
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37310
83.9%
ASCII 7153
 
16.1%
Number Forms 11
 
< 0.1%
None 10
 
< 0.1%
CJK 8
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2950
 
7.9%
2015
 
5.4%
1789
 
4.8%
1724
 
4.6%
1514
 
4.1%
1421
 
3.8%
1271
 
3.4%
772
 
2.1%
757
 
2.0%
622
 
1.7%
Other values (558) 22475
60.2%
ASCII
ValueCountFrequency (%)
1711
23.9%
( 534
 
7.5%
) 534
 
7.5%
E 254
 
3.6%
O 243
 
3.4%
H 228
 
3.2%
e 202
 
2.8%
T 200
 
2.8%
S 169
 
2.4%
A 149
 
2.1%
Other values (64) 2929
40.9%
Number Forms
ValueCountFrequency (%)
7
63.6%
4
36.4%
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%
Missing315
Missing (%)3.7%
Memory size67.0 KiB
2024-04-17T01:33:03.510270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters49446
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
 
3.8%
616801 254
 
3.1%
612040 219
 
2.7%
612847 185
 
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) 6442
78.2%
2024-04-17T01:33:03.918001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9872
20.0%
1 8072
16.3%
0 8030
16.2%
8 7943
16.1%
2 4317
8.7%
4 3463
 
7.0%
7 2602
 
5.3%
3 2460
 
5.0%
9 1410
 
2.9%
5 959
 
1.9%
Other values (5) 318
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49128
99.4%
Other Letter 318
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9872
20.1%
1 8072
16.4%
0 8030
16.3%
8 7943
16.2%
2 4317
8.8%
4 3463
 
7.0%
7 2602
 
5.3%
3 2460
 
5.0%
9 1410
 
2.9%
5 959
 
2.0%
Other Letter
ValueCountFrequency (%)
106
33.3%
53
16.7%
53
16.7%
53
16.7%
53
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 49128
99.4%
Hangul 318
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9872
20.1%
1 8072
16.4%
0 8030
16.3%
8 7943
16.2%
2 4317
8.8%
4 3463
 
7.0%
7 2602
 
5.3%
3 2460
 
5.0%
9 1410
 
2.9%
5 959
 
2.0%
Hangul
ValueCountFrequency (%)
106
33.3%
53
16.7%
53
16.7%
53
16.7%
53
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49128
99.4%
Hangul 318
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9872
20.1%
1 8072
16.4%
0 8030
16.3%
8 7943
16.2%
2 4317
8.8%
4 3463
 
7.0%
7 2602
 
5.3%
3 2460
 
5.0%
9 1410
 
2.9%
5 959
 
2.0%
Hangul
ValueCountFrequency (%)
106
33.3%
53
16.7%
53
16.7%
53
16.7%
53
16.7%
Distinct4129
Distinct (%)48.3%
Missing5
Missing (%)0.1%
Memory size67.0 KiB
2024-04-17T01:33:04.209990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length43
Mean length23.376213
Min length13

Characters and Unicode

Total characters199890
Distinct characters308
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique278 ?
Unique (%)3.3%

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 8551
23.5%
해운대구 1173
 
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 (4365) 20785
57.1%
2024-04-17T01:33:04.664167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36309
18.2%
10375
 
5.2%
10120
 
5.1%
10028
 
5.0%
8925
 
4.5%
8794
 
4.4%
1 8630
 
4.3%
8578
 
4.3%
8557
 
4.3%
- 7924
 
4.0%
Other values (298) 81650
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113366
56.7%
Decimal Number 39961
 
20.0%
Space Separator 36309
 
18.2%
Dash Punctuation 7924
 
4.0%
Uppercase Letter 1780
 
0.9%
Other Punctuation 190
 
0.1%
Open Punctuation 124
 
0.1%
Close Punctuation 124
 
0.1%
Math Symbol 111
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10375
 
9.2%
10120
 
8.9%
10028
 
8.8%
8925
 
7.9%
8794
 
7.8%
8578
 
7.6%
8557
 
7.5%
7454
 
6.6%
7236
 
6.4%
1625
 
1.4%
Other values (266) 31674
27.9%
Uppercase Letter
ValueCountFrequency (%)
B 876
49.2%
T 869
48.8%
A 11
 
0.6%
C 5
 
0.3%
K 5
 
0.3%
O 3
 
0.2%
E 2
 
0.1%
S 2
 
0.1%
G 2
 
0.1%
M 2
 
0.1%
Other values (3) 3
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 8630
21.6%
2 5249
13.1%
3 4208
10.5%
4 4073
10.2%
5 3937
9.9%
0 3077
 
7.7%
6 3039
 
7.6%
7 2852
 
7.1%
8 2584
 
6.5%
9 2312
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 187
98.4%
. 2
 
1.1%
& 1
 
0.5%
Space Separator
ValueCountFrequency (%)
36309
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7924
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 113366
56.7%
Common 84743
42.4%
Latin 1781
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10375
 
9.2%
10120
 
8.9%
10028
 
8.8%
8925
 
7.9%
8794
 
7.8%
8578
 
7.6%
8557
 
7.5%
7454
 
6.6%
7236
 
6.4%
1625
 
1.4%
Other values (266) 31674
27.9%
Common
ValueCountFrequency (%)
36309
42.8%
1 8630
 
10.2%
- 7924
 
9.4%
2 5249
 
6.2%
3 4208
 
5.0%
4 4073
 
4.8%
5 3937
 
4.6%
0 3077
 
3.6%
6 3039
 
3.6%
7 2852
 
3.4%
Other values (8) 5445
 
6.4%
Latin
ValueCountFrequency (%)
B 876
49.2%
T 869
48.8%
A 11
 
0.6%
C 5
 
0.3%
K 5
 
0.3%
O 3
 
0.2%
E 2
 
0.1%
S 2
 
0.1%
G 2
 
0.1%
M 2
 
0.1%
Other values (4) 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113366
56.7%
ASCII 86523
43.3%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36309
42.0%
1 8630
 
10.0%
- 7924
 
9.2%
2 5249
 
6.1%
3 4208
 
4.9%
4 4073
 
4.7%
5 3937
 
4.6%
0 3077
 
3.6%
6 3039
 
3.5%
7 2852
 
3.3%
Other values (21) 7225
 
8.4%
Hangul
ValueCountFrequency (%)
10375
 
9.2%
10120
 
8.9%
10028
 
8.8%
8925
 
7.9%
8794
 
7.8%
8578
 
7.6%
8557
 
7.5%
7454
 
6.6%
7236
 
6.4%
1625
 
1.4%
Other values (266) 31674
27.9%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Unsupported

REJECTED  UNSUPPORTED 

Missing34
Missing (%)0.4%
Memory size67.0 KiB

rdnwhladdr
Text

MISSING 

Distinct3060
Distinct (%)50.9%
Missing2550
Missing (%)29.8%
Memory size67.0 KiB
2024-04-17T01:33:04.935472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length62
Mean length27.896936
Min length5

Characters and Unicode

Total characters167549
Distinct characters367
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

Unique330 ?
Unique (%)5.5%

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 6005
 
19.1%
해운대구 955
 
3.0%
부산진구 726
 
2.3%
동래구 607
 
1.9%
사상구 516
 
1.6%
동구 489
 
1.6%
온천동 422
 
1.3%
수영구 400
 
1.3%
중구 395
 
1.3%
부전동 385
 
1.2%
Other values (2618) 20531
65.3%
2024-04-17T01:33:05.343832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25425
 
15.2%
7807
 
4.7%
7411
 
4.4%
7074
 
4.2%
6730
 
4.0%
1 6388
 
3.8%
6383
 
3.8%
6141
 
3.7%
6011
 
3.6%
( 5888
 
3.5%
Other values (357) 82291
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99700
59.5%
Decimal Number 27161
 
16.2%
Space Separator 25425
 
15.2%
Open Punctuation 5888
 
3.5%
Close Punctuation 5888
 
3.5%
Dash Punctuation 1810
 
1.1%
Other Punctuation 1323
 
0.8%
Math Symbol 260
 
0.2%
Uppercase Letter 90
 
0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7807
 
7.8%
7411
 
7.4%
7074
 
7.1%
6730
 
6.8%
6383
 
6.4%
6141
 
6.2%
6011
 
6.0%
5720
 
5.7%
4006
 
4.0%
3762
 
3.8%
Other values (319) 38655
38.8%
Uppercase Letter
ValueCountFrequency (%)
A 30
33.3%
B 21
23.3%
K 8
 
8.9%
O 5
 
5.6%
C 5
 
5.6%
E 3
 
3.3%
S 3
 
3.3%
U 2
 
2.2%
G 2
 
2.2%
F 2
 
2.2%
Other values (8) 9
 
10.0%
Decimal Number
ValueCountFrequency (%)
1 6388
23.5%
2 4136
15.2%
3 3041
11.2%
4 2311
 
8.5%
5 2194
 
8.1%
0 1967
 
7.2%
6 1933
 
7.1%
7 1872
 
6.9%
9 1707
 
6.3%
8 1612
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 1313
99.2%
. 9
 
0.7%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
25425
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5888
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5888
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1810
100.0%
Math Symbol
ValueCountFrequency (%)
~ 260
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99700
59.5%
Common 67755
40.4%
Latin 94
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7807
 
7.8%
7411
 
7.4%
7074
 
7.1%
6730
 
6.8%
6383
 
6.4%
6141
 
6.2%
6011
 
6.0%
5720
 
5.7%
4006
 
4.0%
3762
 
3.8%
Other values (319) 38655
38.8%
Latin
ValueCountFrequency (%)
A 30
31.9%
B 21
22.3%
K 8
 
8.5%
O 5
 
5.3%
C 5
 
5.3%
3
 
3.2%
E 3
 
3.2%
S 3
 
3.2%
U 2
 
2.1%
G 2
 
2.1%
Other values (10) 12
 
12.8%
Common
ValueCountFrequency (%)
25425
37.5%
1 6388
 
9.4%
( 5888
 
8.7%
) 5888
 
8.7%
2 4136
 
6.1%
3 3041
 
4.5%
4 2311
 
3.4%
5 2194
 
3.2%
0 1967
 
2.9%
6 1933
 
2.9%
Other values (8) 8584
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99700
59.5%
ASCII 67846
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25425
37.5%
1 6388
 
9.4%
( 5888
 
8.7%
) 5888
 
8.7%
2 4136
 
6.1%
3 3041
 
4.5%
4 2311
 
3.4%
5 2194
 
3.2%
0 1967
 
2.9%
6 1933
 
2.8%
Other values (27) 8675
 
12.8%
Hangul
ValueCountFrequency (%)
7807
 
7.8%
7411
 
7.4%
7074
 
7.1%
6730
 
6.8%
6383
 
6.4%
6141
 
6.2%
6011
 
6.0%
5720
 
5.7%
4006
 
4.0%
3762
 
3.8%
Other values (319) 38655
38.8%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size67.0 KiB

dcbymd
Text

MISSING 

Distinct1398
Distinct (%)34.3%
Missing4481
Missing (%)52.4%
Memory size67.0 KiB
2024-04-17T01:33:05.571726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8615951
Min length4

Characters and Unicode

Total characters32036
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

Unique45 ?
Unique (%)1.1%

Sample

1st row20140310
2nd row20121231
3rd row20171120
4th row20210823
5th row20171107
ValueCountFrequency (%)
20041022 180
 
4.4%
폐업일자 141
 
3.5%
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 (1388) 3490
85.6%
2024-04-17T01:33:05.912749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10548
32.9%
2 6730
21.0%
1 5786
18.1%
3 1446
 
4.5%
9 1430
 
4.5%
7 1221
 
3.8%
4 1146
 
3.6%
6 1106
 
3.5%
5 1079
 
3.4%
8 980
 
3.1%
Other values (4) 564
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31472
98.2%
Other Letter 564
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10548
33.5%
2 6730
21.4%
1 5786
18.4%
3 1446
 
4.6%
9 1430
 
4.5%
7 1221
 
3.9%
4 1146
 
3.6%
6 1106
 
3.5%
5 1079
 
3.4%
8 980
 
3.1%
Other Letter
ValueCountFrequency (%)
141
25.0%
141
25.0%
141
25.0%
141
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31472
98.2%
Hangul 564
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10548
33.5%
2 6730
21.4%
1 5786
18.4%
3 1446
 
4.6%
9 1430
 
4.5%
7 1221
 
3.9%
4 1146
 
3.6%
6 1106
 
3.5%
5 1079
 
3.4%
8 980
 
3.1%
Hangul
ValueCountFrequency (%)
141
25.0%
141
25.0%
141
25.0%
141
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31472
98.2%
Hangul 564
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10548
33.5%
2 6730
21.4%
1 5786
18.4%
3 1446
 
4.6%
9 1430
 
4.5%
7 1221
 
3.9%
4 1146
 
3.6%
6 1106
 
3.5%
5 1079
 
3.4%
8 980
 
3.1%
Hangul
ValueCountFrequency (%)
141
25.0%
141
25.0%
141
25.0%
141
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8400 
휴업시작일자
 
149
20210528
 
2
20160425
 
1
20170413
 
1
Other values (3)
 
3

Length

Max length8
Median length4
Mean length4.0381019
Min length4

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8400
98.2%
휴업시작일자 149
 
1.7%
20210528 2
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20210701 1
 
< 0.1%
20211031 1
 
< 0.1%

Length

2024-04-17T01:33:06.030167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:06.128713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8400
98.2%
휴업시작일자 149
 
1.7%
20210528 2
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20210701 1
 
< 0.1%
20211031 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8400 
휴업종료일자
 
149
20230131
 
2
20180424
 
1
20190501
 
1
Other values (3)
 
3

Length

Max length8
Median length4
Mean length4.0381019
Min length4

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8400
98.2%
휴업종료일자 149
 
1.7%
20230131 2
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20211231 1
 
< 0.1%
20220131 1
 
< 0.1%

Length

2024-04-17T01:33:06.249637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:06.364178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8400
98.2%
휴업종료일자 149
 
1.7%
20230131 2
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20211231 1
 
< 0.1%
20220131 1
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
재개업일자
 
150

Length

Max length5
Median length4
Mean length4.0175316
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> 8406
98.2%
재개업일자 150
 
1.8%

Length

2024-04-17T01:33:06.461478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:06.543958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
재개업일자 150
 
1.8%

trdstatenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
02
3707 
01
3208 
영업/정상
1288 
폐업
 
177
13
 
114
Other values (4)
 
62

Length

Max length5
Median length2
Mean length2.4525479
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
02 3707
43.3%
01 3208
37.5%
영업/정상 1288
 
15.1%
폐업 177
 
2.1%
13 114
 
1.3%
03 53
 
0.6%
휴업 4
 
< 0.1%
<NA> 4
 
< 0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:33:06.635131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:06.746146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3707
43.3%
01 3208
37.5%
영업/정상 1288
 
15.1%
폐업 177
 
2.1%
13 114
 
1.3%
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 size67.0 KiB
영업
4311 
폐업
3934 
영업중
 
300
휴업
 
7
<NA>
 
3

Length

Max length4
Median length2
Mean length2.0359981
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4311
50.4%
폐업 3934
46.0%
영업중 300
 
3.5%
휴업 7
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:33:06.868675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:06.983183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4311
50.4%
폐업 3934
46.0%
영업중 300
 
3.5%
휴업 7
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing385
Missing (%)4.5%
Memory size67.0 KiB

y
Real number (ℝ)

MISSING 

Distinct3995
Distinct (%)48.9%
Missing388
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean186694.84
Minimum169998.58
Maximum210387.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.3 KiB
2024-04-17T01:33:07.087363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169998.58
5-th percentile178695.65
Q1182878.03
median186875.02
Q3189941.84
95-th percentile193838.24
Maximum210387.32
Range40388.745
Interquartile range (IQR)7063.8097

Descriptive statistics

Standard deviation5120.7438
Coefficient of variation (CV)0.027428416
Kurtosis0.11189567
Mean186694.84
Median Absolute Deviation (MAD)3529.4934
Skewness0.11777307
Sum1.5249235 × 109
Variance26222017
MonotonicityNot monotonic
2024-04-17T01:33:07.209207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185933.100965604 21
 
0.2%
176595.034934652 11
 
0.1%
187092.852201 10
 
0.1%
186655.373923053 8
 
0.1%
179091.821335278 8
 
0.1%
192327.468209 8
 
0.1%
185542.452702234 8
 
0.1%
186807.811298995 7
 
0.1%
187863.015365939 7
 
0.1%
189143.147865081 7
 
0.1%
Other values (3985) 8073
94.4%
(Missing) 388
 
4.5%
ValueCountFrequency (%)
169998.576608 2
< 0.1%
171461.496152 2
< 0.1%
173969.719902491 1
< 0.1%
174251.232048 2
< 0.1%
174413.752458 1
< 0.1%
174599.932466 2
< 0.1%
174812.942743594 2
< 0.1%
174999.02898 2
< 0.1%
175045.348943 2
< 0.1%
175046.263792 2
< 0.1%
ValueCountFrequency (%)
210387.321730703 1
< 0.1%
209754.153703 1
< 0.1%
207378.835702 1
< 0.1%
207205.169925653 2
< 0.1%
206172.903942 2
< 0.1%
206065.80538 2
< 0.1%
205949.336131 2
< 0.1%
205793.809975 2
< 0.1%
205774.280535 2
< 0.1%
205756.904836 2
< 0.1%

lastmodts
Real number (ℝ)

Distinct3737
Distinct (%)43.7%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0135385 × 1013
Minimum1.9990211 × 1013
Maximum2.0211129 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.3 KiB
2024-04-17T01:33:07.348947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0020169 × 1013
Q12.0060707 × 1013
median2.0171127 × 1013
Q32.018071 × 1013
95-th percentile2.0210859 × 1013
Maximum2.0211129 × 1013
Range2.2091816 × 1011
Interquartile range (IQR)1.2000311 × 1011

Descriptive statistics

Standard deviation6.9831618 × 1010
Coefficient of variation (CV)0.0034681044
Kurtosis-0.96837153
Mean2.0135385 × 1013
Median Absolute Deviation (MAD)3.9177999 × 1010
Skewness-0.75997232
Sum1.7221795 × 1017
Variance4.8764548 × 1021
MonotonicityNot monotonic
2024-04-17T01:33:07.460186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19990428000000 62
 
0.7%
19990920000000 60
 
0.7%
20040902000000 60
 
0.7%
20030122000000 58
 
0.7%
20040203000000 50
 
0.6%
20030414000000 36
 
0.4%
20070531000000 36
 
0.4%
19990308000000 32
 
0.4%
20020515000000 32
 
0.4%
20030329000000 32
 
0.4%
Other values (3727) 8095
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 (%)
20211129160959 1
< 0.1%
20211129155731 2
< 0.1%
20211129144243 2
< 0.1%
20211129141448 2
< 0.1%
20211129120642 2
< 0.1%
20211129094121 2
< 0.1%
20211126163959 1
< 0.1%
20211126162753 2
< 0.1%
20211126144300 1
< 0.1%
20211126115916 2
< 0.1%

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
여관업
5229 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
502
일반호텔
 
481
Other values (4)
679 

Length

Max length8
Median length3
Mean length3.7127162
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5229
61.1%
여인숙업 1076
 
12.6%
숙박업 기타 589
 
6.9%
숙박업(생활) 502
 
5.9%
일반호텔 481
 
5.6%
<NA> 346
 
4.0%
관광호텔 273
 
3.2%
업태구분명 51
 
0.6%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:33:07.568599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:07.680484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5229
57.2%
여인숙업 1076
 
11.8%
숙박업 589
 
6.4%
기타 589
 
6.4%
숙박업(생활 502
 
5.5%
일반호텔 481
 
5.3%
na 346
 
3.8%
관광호텔 273
 
3.0%
업태구분명 51
 
0.6%
휴양콘도미니엄업 9
 
0.1%

sitetel
Text

MISSING 

Distinct552
Distinct (%)6.6%
Missing180
Missing (%)2.1%
Memory size67.0 KiB
2024-04-17T01:33:07.874635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.862106
Min length4

Characters and Unicode

Total characters99357
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

Unique50 ?
Unique (%)0.6%

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 7251
74.0%
051 985
 
10.1%
전화번호 65
 
0.7%
070 18
 
0.2%
747 14
 
0.1%
806 13
 
0.1%
746 10
 
0.1%
805 8
 
0.1%
731 8
 
0.1%
741 8
 
0.1%
Other values (664) 1419
 
14.5%
2024-04-17T01:33:08.403310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23542
23.7%
2 15372
15.5%
3 15294
15.4%
- 14548
14.6%
0 9168
 
9.2%
5 9067
 
9.1%
4 8009
 
8.1%
1431
 
1.4%
7 891
 
0.9%
8 695
 
0.7%
Other values (6) 1340
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83118
83.7%
Dash Punctuation 14548
 
14.6%
Space Separator 1431
 
1.4%
Other Letter 260
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23542
28.3%
2 15372
18.5%
3 15294
18.4%
0 9168
 
11.0%
5 9067
 
10.9%
4 8009
 
9.6%
7 891
 
1.1%
8 695
 
0.8%
6 658
 
0.8%
9 422
 
0.5%
Other Letter
ValueCountFrequency (%)
65
25.0%
65
25.0%
65
25.0%
65
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 14548
100.0%
Space Separator
ValueCountFrequency (%)
1431
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99097
99.7%
Hangul 260
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23542
23.8%
2 15372
15.5%
3 15294
15.4%
- 14548
14.7%
0 9168
 
9.3%
5 9067
 
9.1%
4 8009
 
8.1%
1431
 
1.4%
7 891
 
0.9%
8 695
 
0.7%
Other values (2) 1080
 
1.1%
Hangul
ValueCountFrequency (%)
65
25.0%
65
25.0%
65
25.0%
65
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99097
99.7%
Hangul 260
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23542
23.8%
2 15372
15.5%
3 15294
15.4%
- 14548
14.7%
0 9168
 
9.3%
5 9067
 
9.1%
4 8009
 
8.1%
1431
 
1.4%
7 891
 
0.9%
8 695
 
0.7%
Other values (2) 1080
 
1.1%
Hangul
ValueCountFrequency (%)
65
25.0%
65
25.0%
65
25.0%
65
25.0%

stroomcnt
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8277 
객실수
 
112
1
 
47
2
 
33
3
 
23
Other values (28)
 
64

Length

Max length4
Median length4
Mean length3.9330295
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> 8277
96.7%
객실수 112
 
1.3%
1 47
 
0.5%
2 33
 
0.4%
3 23
 
0.3%
7 8
 
0.1%
6 6
 
0.1%
0 6
 
0.1%
30 3
 
< 0.1%
9 3
 
< 0.1%
Other values (23) 38
 
0.4%

Length

2024-04-17T01:33:08.511463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8277
96.7%
객실수 112
 
1.3%
1 47
 
0.5%
2 33
 
0.4%
3 23
 
0.3%
7 8
 
0.1%
6 6
 
0.1%
0 6
 
0.1%
5 3
 
< 0.1%
225 3
 
< 0.1%
Other values (23) 38
 
0.4%

bdngownsenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
6479 
자가
1177 
임대
773 
건물소유구분명
 
127

Length

Max length7
Median length4
Mean length3.5887097
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6479
75.7%
자가 1177
 
13.8%
임대 773
 
9.0%
건물소유구분명 127
 
1.5%

Length

2024-04-17T01:33:08.609747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:08.697949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6479
75.7%
자가 1177
 
13.8%
임대 773
 
9.0%
건물소유구분명 127
 
1.5%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8241 
건물용도명
 
121
단독주택
 
77
아파트
 
60
숙박시설
 
24
Other values (6)
 
33

Length

Max length15
Median length4
Mean length4.0137915
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> 8241
96.3%
건물용도명 121
 
1.4%
단독주택 77
 
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

2024-04-17T01:33:08.818958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8241
96.3%
건물용도명 121
 
1.4%
단독주택 77
 
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
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1678
Missing (%)19.6%
Memory size67.0 KiB

bdngunderflrcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2244
Missing (%)26.2%
Memory size67.0 KiB

cnstyarea
Categorical

IMBALANCE 

Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8360 
건축연면적
 
130
0
 
39
2282
 
3
20571
 
3
Other values (19)
 
21

Length

Max length5
Median length4
Mean length3.9998831
Min length1

Unique

Unique17 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8360
97.7%
건축연면적 130
 
1.5%
0 39
 
0.5%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
761 2
 
< 0.1%
451 2
 
< 0.1%
437 1
 
< 0.1%
132 1
 
< 0.1%
352 1
 
< 0.1%
Other values (14) 14
 
0.2%

Length

2024-04-17T01:33:08.925918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8360
97.7%
건축연면적 130
 
1.5%
0 39
 
0.5%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
761 2
 
< 0.1%
451 2
 
< 0.1%
151 1
 
< 0.1%
85 1
 
< 0.1%
2971 1
 
< 0.1%
Other values (14) 14
 
0.2%

svnsr
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
기념품종류
 
150

Length

Max length5
Median length4
Mean length4.0175316
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> 8406
98.2%
기념품종류 150
 
1.8%

Length

2024-04-17T01:33:09.025009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:09.110177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
기념품종류 150
 
1.8%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
기획여행보험시작일자
 
150

Length

Max length10
Median length4
Mean length4.1051893
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> 8406
98.2%
기획여행보험시작일자 150
 
1.8%

Length

2024-04-17T01:33:09.208336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:09.295660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
기획여행보험시작일자 150
 
1.8%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
기획여행보험종료일자
 
150

Length

Max length10
Median length4
Mean length4.1051893
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> 8406
98.2%
기획여행보험종료일자 150
 
1.8%

Length

2024-04-17T01:33:09.394303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:09.481759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
기획여행보험종료일자 150
 
1.8%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
7647 
0
794 
남성종사자수
 
85
1
 
12
3
 
5
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.7310659
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> 7647
89.4%
0 794
 
9.3%
남성종사자수 85
 
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

2024-04-17T01:33:09.591505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7647
89.4%
0 794
 
9.3%
남성종사자수 85
 
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 size67.0 KiB
<NA>
8406 
놀이기구수내역
 
150

Length

Max length7
Median length4
Mean length4.0525947
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> 8406
98.2%
놀이기구수내역 150
 
1.8%

Length

2024-04-17T01:33:09.707186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:09.793080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
놀이기구수내역 150
 
1.8%

playfacilcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
N
7248 
<NA>
1137 
놀이시설수
 
119
0
 
49
Y
 
3

Length

Max length5
Median length1
Mean length1.4543011
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 7248
84.7%
<NA> 1137
 
13.3%
놀이시설수 119
 
1.4%
0 49
 
0.6%
Y 3
 
< 0.1%

Length

2024-04-17T01:33:09.887492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:09.991424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 7248
84.7%
na 1137
 
13.3%
놀이시설수 119
 
1.4%
0 49
 
0.6%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
N
8397 
<NA>
 
110
 
38
Y
 
11

Length

Max length4
Median length1
Mean length1.0385694
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8397
98.1%
<NA> 110
 
1.3%
38
 
0.4%
Y 11
 
0.1%

Length

2024-04-17T01:33:10.086402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:10.175235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8397
98.1%
na 110
 
1.3%
38
 
0.4%
y 11
 
0.1%

stagear
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8373 
무대면적
 
134
0
 
49

Length

Max length4
Median length4
Mean length3.9828191
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
97.9%
무대면적 134
 
1.6%
0 49
 
0.6%

Length

2024-04-17T01:33:10.280178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:10.388369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8373
97.9%
무대면적 134
 
1.6%
0 49
 
0.6%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
문화사업자구분명
 
150

Length

Max length8
Median length4
Mean length4.0701262
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> 8406
98.2%
문화사업자구분명 150
 
1.8%

Length

2024-04-17T01:33:10.500875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:10.590341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
문화사업자구분명 150
 
1.8%

culphyedcobnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8068 
외국인관광 도시민박업
 
286
문화체육업종명
 
99
관광숙박업
 
88
자동차야영장업
 
9
Other values (3)
 
6

Length

Max length11
Median length4
Mean length4.2829593
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> 8068
94.3%
외국인관광 도시민박업 286
 
3.3%
문화체육업종명 99
 
1.2%
관광숙박업 88
 
1.0%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%

Length

2024-04-17T01:33:10.681391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:10.777567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8068
91.2%
외국인관광 286
 
3.2%
도시민박업 286
 
3.2%
문화체육업종명 99
 
1.1%
관광숙박업 88
 
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 size67.0 KiB
<NA>
8406 
 
150

Length

Max length4
Median length4
Mean length3.9474053
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> 8406
98.2%
150
 
1.8%

Length

2024-04-17T01:33:10.893778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:10.977166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
150
 
1.8%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
N
8384 
<NA>
 
110
 
38
Y
 
24

Length

Max length4
Median length1
Mean length1.0385694
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8384
98.0%
<NA> 110
 
1.3%
38
 
0.4%
Y 24
 
0.3%

Length

2024-04-17T01:33:11.063657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:11.150280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8384
98.0%
na 110
 
1.3%
38
 
0.4%
y 24
 
0.3%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
 
150

Length

Max length4
Median length4
Mean length3.9474053
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> 8406
98.2%
150
 
1.8%

Length

2024-04-17T01:33:11.239136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:11.327255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
150
 
1.8%

insurorgnm
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8382 
보험기관명
 
146
현대해상
 
3
야영장사고배상책임보험
 
2
DB 손해보험
 
2
Other values (20)
 
21

Length

Max length22
Median length4
Mean length4.0377513
Min length2

Unique

Unique19 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8382
98.0%
보험기관명 146
 
1.7%
현대해상 3
 
< 0.1%
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%
Other values (15) 15
 
0.2%

Length

2024-04-17T01:33:11.438780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8382
97.8%
보험기관명 146
 
1.7%
객실수/수용인원 6
 
0.1%
5
 
0.1%
현대해상 3
 
< 0.1%
야영장사고배상책임보험 2
 
< 0.1%
db 2
 
< 0.1%
손해보험 2
 
< 0.1%
2개 2
 
< 0.1%
6명 2
 
< 0.1%
Other values (21) 22
 
0.3%

insurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
보험시작일자
 
150

Length

Max length6
Median length4
Mean length4.0350631
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> 8406
98.2%
보험시작일자 150
 
1.8%

Length

2024-04-17T01:33:11.575105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:11.661606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
보험시작일자 150
 
1.8%

insurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
보험종료일자
 
150

Length

Max length6
Median length4
Mean length4.0350631
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> 8406
98.2%
보험종료일자 150
 
1.8%

Length

2024-04-17T01:33:11.759593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:11.872294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
보험종료일자 150
 
1.8%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
부대시설내역
 
150

Length

Max length6
Median length4
Mean length4.0350631
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> 8406
98.2%
부대시설내역 150
 
1.8%

Length

2024-04-17T01:33:11.967077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:12.058168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
부대시설내역 150
 
1.8%

usejisgendflr
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2704
Missing (%)31.6%
Memory size67.0 KiB

useunderendflr
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3609
Missing (%)42.2%
Memory size67.0 KiB

usejisgstflr
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1876
Missing (%)21.9%
Memory size67.0 KiB

useunderstflr
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2658
Missing (%)31.1%
Memory size67.0 KiB

shpinfo
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
선박제원
 
150

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> 8406
98.2%
선박제원 150
 
1.8%

Length

2024-04-17T01:33:12.140927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:12.220157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
선박제원 150
 
1.8%

shpcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8373 
선박척수
 
134
0
 
49

Length

Max length4
Median length4
Mean length3.9828191
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
97.9%
선박척수 134
 
1.6%
0 49
 
0.6%

Length

2024-04-17T01:33:12.305599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:12.391909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8373
97.9%
선박척수 134
 
1.6%
0 49
 
0.6%

shptottons
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8373 
선박총톤수
 
134
0
 
49

Length

Max length5
Median length4
Mean length3.9984806
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
97.9%
선박총톤수 134
 
1.6%
0 49
 
0.6%

Length

2024-04-17T01:33:12.495318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:12.590742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8373
97.9%
선박총톤수 134
 
1.6%
0 49
 
0.6%

washmccnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3491
Missing (%)40.8%
Memory size67.0 KiB

facilscp
Text

MISSING 

Distinct155
Distinct (%)37.7%
Missing8145
Missing (%)95.2%
Memory size67.0 KiB
2024-04-17T01:33:12.838176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.0048662
Min length1

Characters and Unicode

Total characters1235
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

Unique84 ?
Unique (%)20.4%

Sample

1st row시설규모
2nd row시설규모
3rd row시설규모
4th row시설규모
5th row시설규모
ValueCountFrequency (%)
시설규모 106
25.8%
85 16
 
3.9%
46 7
 
1.7%
599 6
 
1.5%
67 6
 
1.5%
60 6
 
1.5%
83 6
 
1.5%
63 5
 
1.2%
62 5
 
1.2%
84 4
 
1.0%
Other values (145) 244
59.4%
2024-04-17T01:33:13.242740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 126
10.2%
106
 
8.6%
106
 
8.6%
106
 
8.6%
106
 
8.6%
5 102
 
8.3%
8 84
 
6.8%
4 75
 
6.1%
6 75
 
6.1%
2 73
 
5.9%
Other values (4) 276
22.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 811
65.7%
Other Letter 424
34.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 126
15.5%
5 102
12.6%
8 84
10.4%
4 75
9.2%
6 75
9.2%
2 73
9.0%
7 71
8.8%
9 69
8.5%
3 69
8.5%
0 67
8.3%
Other Letter
ValueCountFrequency (%)
106
25.0%
106
25.0%
106
25.0%
106
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 811
65.7%
Hangul 424
34.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 126
15.5%
5 102
12.6%
8 84
10.4%
4 75
9.2%
6 75
9.2%
2 73
9.0%
7 71
8.8%
9 69
8.5%
3 69
8.5%
0 67
8.3%
Hangul
ValueCountFrequency (%)
106
25.0%
106
25.0%
106
25.0%
106
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 811
65.7%
Hangul 424
34.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 126
15.5%
5 102
12.6%
8 84
10.4%
4 75
9.2%
6 75
9.2%
2 73
9.0%
7 71
8.8%
9 69
8.5%
3 69
8.5%
0 67
8.3%
Hangul
ValueCountFrequency (%)
106
25.0%
106
25.0%
106
25.0%
106
25.0%

facilar
Text

MISSING 

Distinct228
Distinct (%)55.5%
Missing8145
Missing (%)95.2%
Memory size67.0 KiB
2024-04-17T01:33:13.572829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.9148418
Min length1

Characters and Unicode

Total characters2020
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

Unique180 ?
Unique (%)43.8%

Sample

1st row시설면적
2nd row시설면적
3rd row시설면적
4th row시설면적
5th row시설면적
ValueCountFrequency (%)
시설면적 106
 
25.8%
45.5 6
 
1.5%
598.73 6
 
1.5%
62.58 4
 
1.0%
218.85 4
 
1.0%
337.46 3
 
0.7%
2281.67 3
 
0.7%
1497.35 3
 
0.7%
38.18 3
 
0.7%
326.98 3
 
0.7%
Other values (218) 270
65.7%
2024-04-17T01:33:14.019419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 276
13.7%
1 171
 
8.5%
4 167
 
8.3%
8 159
 
7.9%
5 139
 
6.9%
2 126
 
6.2%
3 124
 
6.1%
6 123
 
6.1%
9 118
 
5.8%
7 111
 
5.5%
Other values (5) 506
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1320
65.3%
Other Letter 424
 
21.0%
Other Punctuation 276
 
13.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 171
13.0%
4 167
12.7%
8 159
12.0%
5 139
10.5%
2 126
9.5%
3 124
9.4%
6 123
9.3%
9 118
8.9%
7 111
8.4%
0 82
6.2%
Other Letter
ValueCountFrequency (%)
106
25.0%
106
25.0%
106
25.0%
106
25.0%
Other Punctuation
ValueCountFrequency (%)
. 276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1596
79.0%
Hangul 424
 
21.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 276
17.3%
1 171
10.7%
4 167
10.5%
8 159
10.0%
5 139
8.7%
2 126
7.9%
3 124
7.8%
6 123
7.7%
9 118
7.4%
7 111
7.0%
Hangul
ValueCountFrequency (%)
106
25.0%
106
25.0%
106
25.0%
106
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1596
79.0%
Hangul 424
 
21.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 276
17.3%
1 171
10.7%
4 167
10.5%
8 159
10.0%
5 139
8.7%
2 126
7.9%
3 124
7.8%
6 123
7.7%
9 118
7.4%
7 111
7.0%
Hangul
ValueCountFrequency (%)
106
25.0%
106
25.0%
106
25.0%
106
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
 
150

Length

Max length4
Median length4
Mean length3.9474053
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> 8406
98.2%
150
 
1.8%

Length

2024-04-17T01:33:14.133774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:14.218560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
150
 
1.8%

yangsilcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing924
Missing (%)10.8%
Memory size67.0 KiB

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
7649 
0
800 
여성종사자수
 
85
2
 
6
1
 
6
Other values (4)
 
10

Length

Max length6
Median length4
Mean length3.7320009
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> 7649
89.4%
0 800
 
9.4%
여성종사자수 85
 
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

2024-04-17T01:33:14.302735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:14.408926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7649
89.4%
0 800
 
9.4%
여성종사자수 85
 
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 

Distinct53
Distinct (%)25.7%
Missing8350
Missing (%)97.6%
Memory size67.0 KiB
2024-04-17T01:33:14.606114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length5
Mean length8.4223301
Min length4

Characters and Unicode

Total characters1735
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

Unique42 ?
Unique (%)20.4%

Sample

1st row영문상호명
2nd row영문상호명
3rd row영문상호명
4th row영문상호명
5th row영문상호명
ValueCountFrequency (%)
영문상호명 137
46.6%
house 31
 
10.5%
busan 9
 
3.1%
ocean 6
 
2.0%
hotel 6
 
2.0%
guest 5
 
1.7%
kim's 4
 
1.4%
dyd 3
 
1.0%
cozy 3
 
1.0%
h-avenue 3
 
1.0%
Other values (62) 87
29.6%
2024-04-17T01:33:14.904671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
137
 
7.9%
137
 
7.9%
137
 
7.9%
137
 
7.9%
137
 
7.9%
e 95
 
5.5%
88
 
5.1%
o 80
 
4.6%
a 61
 
3.5%
n 56
 
3.2%
Other values (49) 670
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 685
39.5%
Lowercase Letter 623
35.9%
Uppercase Letter 313
18.0%
Space Separator 88
 
5.1%
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
11.5%
E 31
 
9.9%
O 24
 
7.7%
U 21
 
6.7%
B 19
 
6.1%
Y 16
 
5.1%
A 14
 
4.5%
P 13
 
4.2%
G 12
 
3.8%
Other values (14) 88
28.1%
Lowercase Letter
ValueCountFrequency (%)
e 95
15.2%
o 80
12.8%
a 61
9.8%
n 56
9.0%
u 49
 
7.9%
s 41
 
6.6%
h 30
 
4.8%
t 28
 
4.5%
i 24
 
3.9%
l 23
 
3.7%
Other values (12) 136
21.8%
Other Letter
ValueCountFrequency (%)
137
20.0%
137
20.0%
137
20.0%
137
20.0%
137
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 936
53.9%
Hangul 685
39.5%
Common 114
 
6.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 95
 
10.1%
o 80
 
8.5%
a 61
 
6.5%
n 56
 
6.0%
u 49
 
5.2%
s 41
 
4.4%
H 39
 
4.2%
S 36
 
3.8%
E 31
 
3.3%
h 30
 
3.2%
Other values (36) 418
44.7%
Common
ValueCountFrequency (%)
88
77.2%
- 7
 
6.1%
0 7
 
6.1%
' 5
 
4.4%
2 3
 
2.6%
1 2
 
1.8%
. 1
 
0.9%
& 1
 
0.9%
Hangul
ValueCountFrequency (%)
137
20.0%
137
20.0%
137
20.0%
137
20.0%
137
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1050
60.5%
Hangul 685
39.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
137
20.0%
137
20.0%
137
20.0%
137
20.0%
137
20.0%
ASCII
ValueCountFrequency (%)
e 95
 
9.0%
88
 
8.4%
o 80
 
7.6%
a 61
 
5.8%
n 56
 
5.3%
u 49
 
4.7%
s 41
 
3.9%
H 39
 
3.7%
S 36
 
3.4%
E 31
 
3.0%
Other values (44) 474
45.1%

engstntrnmaddr
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8353 
영문상호주소
 
137
Guesthouse for Foreign Tourists
 
23
Foreigner Tourism City home-stay Business
 
14
Guest House
 
4
Other values (15)
 
25

Length

Max length41
Median length4
Mean length4.2380785
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> 8353
97.6%
영문상호주소 137
 
1.6%
Guesthouse for Foreign Tourists 23
 
0.3%
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

2024-04-17T01:33:15.033422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8353
95.6%
영문상호주소 137
 
1.6%
for 30
 
0.3%
foreign 29
 
0.3%
guesthouse 26
 
0.3%
tourists 26
 
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
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2459
Missing (%)28.7%
Memory size67.0 KiB

sntuptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
여관업
5229 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
502
일반호텔
 
481
Other values (4)
679 

Length

Max length8
Median length3
Mean length3.7127162
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5229
61.1%
여인숙업 1076
 
12.6%
숙박업 기타 589
 
6.9%
숙박업(생활) 502
 
5.9%
일반호텔 481
 
5.6%
<NA> 346
 
4.0%
관광호텔 273
 
3.2%
위생업태명 51
 
0.6%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:33:15.136264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:15.232542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5229
57.2%
여인숙업 1076
 
11.8%
숙박업 589
 
6.4%
기타 589
 
6.4%
숙박업(생활 502
 
5.5%
일반호텔 481
 
5.3%
na 346
 
3.8%
관광호텔 273
 
3.0%
위생업태명 51
 
0.6%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
 
150

Length

Max length4
Median length4
Mean length3.9474053
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> 8406
98.2%
150
 
1.8%

Length

2024-04-17T01:33:15.343001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:15.427136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
150
 
1.8%

capt
Categorical

IMBALANCE 

Distinct44
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8301 
자본금
 
119
0
 
30
10000000
 
20
100000000
 
12
Other values (39)
 
74

Length

Max length10
Median length4
Mean length4.0302712
Min length1

Unique

Unique24 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8301
97.0%
자본금 119
 
1.4%
0 30
 
0.4%
10000000 20
 
0.2%
100000000 12
 
0.1%
200000000 7
 
0.1%
50000000 7
 
0.1%
20000000 5
 
0.1%
300000000 4
 
< 0.1%
150000000 3
 
< 0.1%
Other values (34) 48
 
0.6%

Length

2024-04-17T01:33:15.522736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8301
97.0%
자본금 119
 
1.4%
0 30
 
0.4%
10000000 20
 
0.2%
100000000 12
 
0.1%
200000000 7
 
0.1%
50000000 7
 
0.1%
20000000 5
 
0.1%
300000000 4
 
< 0.1%
150000000 3
 
< 0.1%
Other values (34) 48
 
0.6%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
제작취급품목내용
 
150

Length

Max length8
Median length4
Mean length4.0701262
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> 8406
98.2%
제작취급품목내용 150
 
1.8%

Length

2024-04-17T01:33:15.654024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:15.762481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
제작취급품목내용 150
 
1.8%

cndpermstymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
조건부허가시작일자
 
150

Length

Max length9
Median length4
Mean length4.0876578
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> 8406
98.2%
조건부허가시작일자 150
 
1.8%

Length

2024-04-17T01:33:15.860361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:15.955021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
조건부허가시작일자 150
 
1.8%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
조건부허가신고사유
 
150

Length

Max length9
Median length4
Mean length4.0876578
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> 8406
98.2%
조건부허가신고사유 150
 
1.8%

Length

2024-04-17T01:33:16.042585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:16.378694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
조건부허가신고사유 150
 
1.8%

cndpermendymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8406 
조건부허가종료일자
 
150

Length

Max length9
Median length4
Mean length4.0876578
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> 8406
98.2%
조건부허가종료일자 150
 
1.8%

Length

2024-04-17T01:33:16.458843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:16.545609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8406
98.2%
조건부허가종료일자 150
 
1.8%

chaircnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4865
Missing (%)56.9%
Memory size67.0 KiB

nearenvnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8311 
주변환경명
 
131
주택가주변
 
40
아파트지역
 
32
기타
 
25
Other values (3)
 
17

Length

Max length8
Median length4
Mean length4.0258298
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> 8311
97.1%
주변환경명 131
 
1.5%
주택가주변 40
 
0.5%
아파트지역 32
 
0.4%
기타 25
 
0.3%
학교정화(상대) 14
 
0.2%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-17T01:33:16.639964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:16.760170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8311
97.1%
주변환경명 131
 
1.5%
주택가주변 40
 
0.5%
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 size67.0 KiB
<NA>
8265 
지상층수
 
120
2
 
35
4
 
19
0
 
18
Other values (22)
 
99

Length

Max length4
Median length4
Mean length3.9446003
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
96.6%
지상층수 120
 
1.4%
2 35
 
0.4%
4 19
 
0.2%
0 18
 
0.2%
1 15
 
0.2%
3 15
 
0.2%
5 11
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
Other values (17) 44
 
0.5%

Length

2024-04-17T01:33:16.887922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8265
96.6%
지상층수 120
 
1.4%
2 35
 
0.4%
4 19
 
0.2%
0 18
 
0.2%
1 15
 
0.2%
3 15
 
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 size67.0 KiB
<NA>
8199 
일반주거지역
 
122
지역구분명
 
114
일반상업지역
 
42
준주거지역
 
32
Other values (5)
 
47

Length

Max length6
Median length4
Mean length4.057036
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> 8199
95.8%
일반주거지역 122
 
1.4%
지역구분명 114
 
1.3%
일반상업지역 42
 
0.5%
준주거지역 32
 
0.4%
주거지역 31
 
0.4%
자연녹지지역 6
 
0.1%
상업지역 6
 
0.1%
녹지지역 3
 
< 0.1%
전용주거지역 1
 
< 0.1%

Length

2024-04-17T01:33:17.008154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:17.147690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8199
95.8%
일반주거지역 122
 
1.4%
지역구분명 114
 
1.3%
일반상업지역 42
 
0.5%
준주거지역 32
 
0.4%
주거지역 31
 
0.4%
자연녹지지역 6
 
0.1%
상업지역 6
 
0.1%
녹지지역 3
 
< 0.1%
전용주거지역 1
 
< 0.1%

undernumlay
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8331 
지하층수
 
125
0
 
43
1
 
29
2
 
21
Other values (5)
 
7

Length

Max length4
Median length4
Mean length3.9649369
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8331
97.4%
지하층수 125
 
1.5%
0 43
 
0.5%
1 29
 
0.3%
2 21
 
0.2%
3 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:33:17.269270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:17.374493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8331
97.4%
지하층수 125
 
1.5%
0 43
 
0.5%
1 29
 
0.3%
2 21
 
0.2%
3 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%

totnumlay
Categorical

IMBALANCE 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8256 
총층수
 
116
2
 
41
4
 
21
1
 
20
Other values (21)
 
102

Length

Max length4
Median length4
Mean length3.9264843
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> 8256
96.5%
총층수 116
 
1.4%
2 41
 
0.5%
4 21
 
0.2%
1 20
 
0.2%
3 19
 
0.2%
5 14
 
0.2%
0 12
 
0.1%
6 8
 
0.1%
20 7
 
0.1%
Other values (16) 42
 
0.5%

Length

2024-04-17T01:33:17.485208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8256
96.5%
총층수 116
 
1.4%
2 41
 
0.5%
4 21
 
0.2%
1 20
 
0.2%
3 19
 
0.2%
5 14
 
0.2%
0 12
 
0.1%
6 8
 
0.1%
20 7
 
0.1%
Other values (16) 42
 
0.5%

abedcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3535
Missing (%)41.3%
Memory size67.0 KiB

hanshilcnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1483
Missing (%)17.3%
Memory size67.0 KiB

rcvdryncnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3529
Missing (%)41.2%
Memory size67.0 KiB

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8373 
회의실별동시수용인원
 
134
0
 
49

Length

Max length10
Median length4
Mean length4.0767882
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
97.9%
회의실별동시수용인원 134
 
1.6%
0 49
 
0.6%

Length

2024-04-17T01:33:17.582230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:33:17.676754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8373
97.9%
회의실별동시수용인원 134
 
1.6%
0 49
 
0.6%
Distinct3
Distinct (%)< 0.1%
Missing6
Missing (%)0.1%
Memory size67.0 KiB
Minimum2021-12-01 05:09:03
Maximum2021-12-01 05:09:05
2024-04-17T01:33:17.750616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:33:17.838657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
0232500003250000-201-2017-0000203_11_03_PI2018-08-31 23:59:59.0<NA>(주)아이에이치엠 호텔포레 프리미어 남포지점600045부산광역시 중구 남포동5가 8-1번지48953.0부산광역시 중구 구덕로 54-1 (남포동5가)20170213<NA><NA><NA><NA>01영업385079.145433179894.98255720171123163559일반호텔051-123-1234<NA>임대<NA>16.02.0<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>14.00.04.00.0<NA><NA><NA>0.0<NA><NA><NA>107.00<NA><NA>0.0일반호텔<NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA>0.00.00.0<NA>2021-12-01 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>8.04.0<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>8.00.06.00.0<NA><NA><NA>0.0<NA><NA><NA>81.0<NA><NA><NA>0.0일반호텔<NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA>0.00.00.0<NA>2021-12-01 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>5.01.0<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>3.00.01.00.0<NA><NA><NA>0.0<NA><NA><NA>16.00<NA><NA>0.0숙박업(생활)<NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA>0.00.00.0<NA>2021-12-01 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>NaNNaN<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA><NA><NA>NaN<NA><NA><NA>7.0<NA><NA><NA>NaN여관업<NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA>NaN3.0NaN<NA>2021-12-01 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>5.00.0<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>2.0NaN2.0NaN<NA><NA><NA>0.0<NA><NA><NA>5.0<NA><NA><NA>0.0숙박업 기타<NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA>0.00.00.0<NA>2021-12-01 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>0.00.0<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0.00.00.00.0<NA><NA><NA>0.0<NA><NA><NA>10.0<NA><NA><NA>0.0여관업<NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA>0.02.00.0<NA>2021-12-01 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>0.00.0<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0.00.00.00.0<NA><NA><NA>0.0<NA><NA><NA>16.0<NA><NA><NA>0.0여관업<NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA>0.02.00.0<NA>2021-12-01 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>10.01.0<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>11.00.08.00.0<NA><NA><NA>0.0<NA><NA><NA>25.0<NA><NA><NA>0.0여관업<NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA>0.00.00.0<NA>2021-12-01 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>3.00.0<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0.00.00.00.0<NA><NA><NA>0.0<NA><NA><NA>4.0<NA><NA><NA>0.0여관업<NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA>0.08.00.0<NA>2021-12-01 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>9.01.0<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9.00.01.00.0<NA><NA><NA>0.0<NA><NA><NA>51.0<NA><NA><NA>0.0관광호텔<NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA>0.0NaN0.0<NA>2021-12-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
85461302733600003360000-201-2021-0000103_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/정상영업373665.73430842179173.52698920210419165344관광호텔051 661 9000<NA><NA><NA>233<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>2910<NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>040<NA>2021-12-01 05:09:05
85471302833300003330000-214-2021-0000203_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/정상영업397359.716406649186807.81129920210331103454숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>3<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>22737<NA><NA><NA>0<NA><NA><NA>300<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-12-01 05:09:05
85481302933800003380000-214-2021-0000403_11_03_PU2021-11-26 02:40:00.0숙박업위더스오션613805부산광역시 수영구 광안동 201-1 광안 지웰에스테이트 더 테라스48303부산광역시 수영구 광남로94번길 16, 광안 지웰에스테이트 더 테라스 3~19층 305호 등 58개호 (광안동)20210406폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업392691.625721388185474.22691320211124134232숙박업(생활)전화번호객실수건물소유구분명건물용도명00건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자0놀이기구수내역놀이시설수N무대면적문화사업자구분명문화체육업종명N보험기관명보험시작일자보험종료일자부대시설내역19030선박제원선박척수선박총톤수0시설규모시설면적340영문상호명영문상호주소0숙박업(생활)자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주변환경명지상층수지역구분명지하층수총층수000회의실별동시수용인원2021-12-01 05:09:05
85491303033300003330000-214-2021-0000303_11_03_PU2021-04-21 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504720210419133601숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5NaN1NaN<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>2021-12-01 05:09:05
8550130313280000CDFI226221202100000103_11_04_PU2021-10-02 02:40:00.0외국인관광도시민박업윤슬가지번우편번호부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.397605613179078.07581920210930170851업태구분명전화번호1건물소유구분명단독주택건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4545.45양실수여성종사자수YoonSeulgaGuesthouse for Foreign Tourists욕실수위생업태명200000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주택가주변1일반주거지역01침대수한실수회수건조수02021-12-01 05:09:05
85511303233300003330000-214-2021-0000303_11_03_PU2021-04-21 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504720210419133601숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5NaN1NaN<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>2021-12-01 05:09:05
8552130333280000CDFI226221202100000103_11_04_PU2021-10-02 02:40:00.0외국인관광도시민박업윤슬가지번우편번호부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.397605613179078.07581920210930170851업태구분명전화번호1건물소유구분명단독주택건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4545.45양실수여성종사자수YoonSeulgaGuesthouse for Foreign Tourists욕실수위생업태명200000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주택가주변1일반주거지역01침대수한실수회수건조수02021-12-01 05:09:05
8553130413330000CDFI226221201500002603_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/정상영업중397758.722800944186726.0599220210524093757<NA><NA><NA><NA><NA>NaNNaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaNNaNNaNNaN<NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA>NaNNaNNaN<NA>2021-12-01 05:09:05
85541304233800003380000-214-2021-0000603_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/정상영업392732.161638137185542.45270220210625155820숙박업(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>2021-12-01 05:09:05
8555130433380000CDFI226003202100000303_11_01_PU2021-06-24 02:40:00.0관광숙박업제이스테이 펜트하우스지번우편번호부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210525폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392732.161638137185542.45270220210622151628업태구분명전화번호4건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명관광숙박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수219218.85양실수여성종사자수영문상호명영문상호주소욕실수위생업태명125000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수지역구분명지하층수총층수침대수한실수회수건조수회의실별동시수용인원2021-12-01 05:09:05

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnwhladdrdcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcshpinfoshpcntshptottonsfacilscpfacilarinfobenwmeipcntengstntrnmnmengstntrnmaddrsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdnearenvnmjisgnumlayregnsenmundernumlaytotnumlaymeetsamtimesygstflast_load_dttm# duplicates
413330000CDFI226003201800000503_11_01_PU2019-04-14 02:40:00.0관광숙박업일로이리조트<NA>부산광역시 해운대구 송정동 809번지부산광역시 해운대구 송정구덕포길 130 (송정동)<NA><NA><NA><NA>영업/정상영업중187863.01536620190412092534<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>관광숙박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA>599598.73<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4주거지역<NA>4<NA>2021-12-01 05:09:046
53250000CDFI226221201900000103_11_04_PU2021-05-05 02:40:00.0외국인관광도시민박업보수동방공호지번우편번호부산광역시 중구 보수동1가 116-156부산광역시 중구 책방골목길 13-11 (보수동1가)20210427휴업시작일자휴업종료일자재개업일자폐업폐업180168.55870820210503101511업태구분명전화번호6건물소유구분명건물용도명건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역선박제원선박척수선박총톤수168167.82여성종사자수영문상호명영문상호주소위생업태명자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자주변환경명지상층수일반상업지역지하층수3회의실별동시수용인원2021-12-01 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/정상영업중179818.66105720201031173301<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<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>2021-12-01 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/정상영업181704.05848320210618100954여관업051 467 5401<NA>자가<NA><NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA>여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-12-01 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/정상영업181627.55533520201027175551여관업<NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA>여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-12-01 05:09:053
143280000CDFI226221202000000103_11_04_PU2021-10-21 02:40:00.0외국인관광도시민박업오션하우스<NA>부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1904호 (동삼동, 함지그린아파트)<NA><NA><NA><NA>영업/정상영업중176595.03493520211019153414<NA><NA>2<NA>아파트0<NA><NA><NA><NA><NA>0<NA>0<NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA>004645.5<NA><NA>ocean houseGuesthouse for Foreign Tourists<NA><NA>10000000<NA><NA><NA><NA>아파트지역20일반주거지역22002021-12-01 05:09:053
153280000CDFI226221202000000203_11_04_PU2021-10-21 02:40:00.0외국인관광도시민박업에메랄드 오션뷰지번우편번호부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1902호 (동삼동, 함지그린아파트)폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중176595.03493520211019153331업태구분명전화번호1건물소유구분명아파트0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역선박제원004645.5여성종사자수Emerald ocean viewGuesthouse for Foreign Tourists위생업태명0제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자아파트지역20주거지역22002021-12-01 05:09:053
163280000CDFI226221202000000303_11_04_PU2021-11-26 02:40:00.0외국인관광도시민박업청학소담<NA>부산광역시 영도구 청학동 398-20부산광역시 영도구 청학서로16번길 43-14 (청학동)<NA><NA><NA><NA>영업/정상영업중179086.90220320211124114259<NA><NA>1<NA>단독주택0<NA><NA><NA><NA><NA>0<NA>0<NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA>008080.1<NA><NA>CheonghakSodamGuesthouse for Foreign Tourists<NA><NA>200000000<NA><NA><NA><NA>주택가주변0일반주거지역0102021-12-01 05:09:053
2132900003290000-201-2019-0000203_11_03_PU2020-12-15 02:40:00.0숙박업엑스모텔614846부산광역시 부산진구 부전동 226-5부산광역시 부산진구 신천대로50번길 34, 6층~9층 (부전동)<NA><NA><NA><NA>영업/정상영업185627.12814620201212162712일반호텔051 803 6996<NA><NA><NA><NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA>일반호텔<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-12-01 05:09:043
2232900003290000-201-2020-0000103_11_03_PU2020-12-15 02:40:00.0숙박업지지배614849부산광역시 부산진구 부전동 417-25부산광역시 부산진구 부전로 99-1, 3층 (부전동)<NA><NA><NA><NA>영업/정상영업186361.92755720201212135845여관업051 806 7779<NA>자가<NA><NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA>여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-12-01 05:09:053