Overview

Dataset statistics

Number of variables81
Number of observations8560
Missing cells33856
Missing cells (%)4.9%
Duplicate rows359
Duplicate rows (%)4.2%
Total size in memory5.3 MiB
Average record size in memory650.0 B

Variable types

Unsupported5
Numeric2
Text11
Categorical61
DateTime2

Alerts

Dataset has 359 (4.2%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (89.2%)Imbalance
updategbn is highly imbalanced (56.2%)Imbalance
opnsvcnm is highly imbalanced (71.2%)Imbalance
clgstdt is highly imbalanced (95.4%)Imbalance
clgenddt is highly imbalanced (95.4%)Imbalance
ropnymd is highly imbalanced (86.2%)Imbalance
dtlstatenm is highly imbalanced (53.7%)Imbalance
stroomcnt is highly imbalanced (92.9%)Imbalance
bdngsrvnm is highly imbalanced (90.7%)Imbalance
bdngunderflrcnt is highly imbalanced (54.9%)Imbalance
cnstyarea is highly imbalanced (94.7%)Imbalance
svnsr is highly imbalanced (86.2%)Imbalance
plninsurstdt is highly imbalanced (86.2%)Imbalance
plninsurenddt is highly imbalanced (86.2%)Imbalance
maneipcnt is highly imbalanced (82.2%)Imbalance
playutscntdtl is highly imbalanced (86.2%)Imbalance
playfacilcnt is highly imbalanced (64.8%)Imbalance
multusnupsoyn is highly imbalanced (91.4%)Imbalance
stagear is highly imbalanced (86.7%)Imbalance
culwrkrsenm is highly imbalanced (86.2%)Imbalance
culphyedcobnm is highly imbalanced (86.1%)Imbalance
geicpfacilen is highly imbalanced (86.2%)Imbalance
balhansilyn is highly imbalanced (90.7%)Imbalance
bcfacilen is highly imbalanced (86.2%)Imbalance
insurorgnm is highly imbalanced (96.1%)Imbalance
insurstdt is highly imbalanced (86.2%)Imbalance
insurenddt is highly imbalanced (86.2%)Imbalance
afc is highly imbalanced (86.2%)Imbalance
useunderendflr is highly imbalanced (62.0%)Imbalance
useunderstflr is highly imbalanced (62.7%)Imbalance
shpinfo is highly imbalanced (86.2%)Imbalance
shpcnt is highly imbalanced (86.7%)Imbalance
shptottons is highly imbalanced (86.7%)Imbalance
infoben is highly imbalanced (86.2%)Imbalance
wmeipcnt is highly imbalanced (80.8%)Imbalance
engstntrnmaddr is highly imbalanced (95.0%)Imbalance
yoksilcnt is highly imbalanced (77.0%)Imbalance
dispenen is highly imbalanced (86.2%)Imbalance
capt is highly imbalanced (93.9%)Imbalance
mnfactreartclcn is highly imbalanced (86.2%)Imbalance
cndpermstymd is highly imbalanced (86.2%)Imbalance
cndpermntwhy is highly imbalanced (86.2%)Imbalance
cndpermendymd is highly imbalanced (86.2%)Imbalance
chaircnt is highly imbalanced (65.5%)Imbalance
nearenvnm is highly imbalanced (91.5%)Imbalance
jisgnumlay is highly imbalanced (92.3%)Imbalance
regnsenm is highly imbalanced (89.3%)Imbalance
undernumlay is highly imbalanced (91.9%)Imbalance
totnumlay is highly imbalanced (92.0%)Imbalance
meetsamtimesygstf is highly imbalanced (86.7%)Imbalance
sitepostno has 315 (3.7%) missing valuesMissing
rdnwhladdr has 2550 (29.8%) missing valuesMissing
dcbymd has 4444 (51.9%) missing valuesMissing
x has 385 (4.5%) missing valuesMissing
y has 388 (4.5%) missing valuesMissing
sitetel has 221 (2.6%) missing valuesMissing
facilscp has 8115 (94.8%) missing valuesMissing
facilar has 8115 (94.8%) missing valuesMissing
yangsilcnt has 923 (10.8%) missing valuesMissing
engstntrnmnm has 8337 (97.4%) missing valuesMissing
skey is an unsupported type, check if it needs cleaning or further analysisUnsupported
rdnpostno is an unsupported type, check if it needs cleaning or further analysisUnsupported
apvpermymd is an unsupported type, check if it needs cleaning or further analysisUnsupported
x is an unsupported type, check if it needs cleaning or further analysisUnsupported
y is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 16:32:31.193524
Analysis finished2024-04-16 16:32:34.380025
Duration3.19 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%
Mean3318959.9
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.4 KiB
2024-04-17T01:32:34.426388image/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 deviation42881.464
Coefficient of variation (CV)0.012920151
Kurtosis-0.97459682
Mean3318959.9
Median Absolute Deviation (MAD)30000
Skewness0.26421643
Sum2.840034 × 1010
Variance1.8388199 × 109
MonotonicityNot monotonic
2024-04-17T01:32:34.529317image/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
 
8.0%
3270000 655
 
7.7%
3320000 578
 
6.8%
3380000 503
 
5.9%
3250000 485
 
5.7%
3260000 406
 
4.7%
3370000 383
 
4.5%
Other values (6) 1732
20.2%
ValueCountFrequency (%)
3250000 485
5.7%
3260000 406
 
4.7%
3270000 655
7.7%
3280000 379
 
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 215
 
2.5%
3390000 689
8.0%
3380000 503
5.9%
3370000 383
 
4.5%
3360000 138
 
1.6%
3350000 352
 
4.1%
3340000 363
 
4.2%
3330000 1173
13.7%
3320000 578
6.8%
3310000 285
 
3.3%

mgtno
Text

Distinct4257
Distinct (%)49.7%
Missing3
Missing (%)< 0.1%
Memory size67.0 KiB
2024-04-17T01:32:34.713138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.907912
Min length20

Characters and Unicode

Total characters187466
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

Unique168 ?
Unique (%)2.0%

Sample

1st row3250000-201-2017-00002
2nd row3250000-201-2014-00001
3rd row3250000-214-2017-00003
4th row3250000-201-1971-00116
5th row3250000-201-2012-00005
ValueCountFrequency (%)
cdfi2262212019000001 15
 
0.2%
cdfi2262212018000001 12
 
0.1%
cdfi2262212015000001 12
 
0.1%
cdfi2262212015000002 11
 
0.1%
cdfi2262212017000001 11
 
0.1%
cdfi2262212016000001 11
 
0.1%
cdfi2262212020000001 10
 
0.1%
cdfi2262212016000002 10
 
0.1%
cdfi2260032021000001 9
 
0.1%
cdfi2262212014000001 9
 
0.1%
Other values (4247) 8447
98.7%
2024-04-17T01:32:35.228178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72174
38.5%
- 24489
 
13.1%
1 20233
 
10.8%
2 20224
 
10.8%
3 18296
 
9.8%
9 10164
 
5.4%
8 4984
 
2.7%
7 4876
 
2.6%
6 3749
 
2.0%
4 3643
 
1.9%
Other values (5) 4634
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 161401
86.1%
Dash Punctuation 24489
 
13.1%
Uppercase Letter 1576
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72174
44.7%
1 20233
 
12.5%
2 20224
 
12.5%
3 18296
 
11.3%
9 10164
 
6.3%
8 4984
 
3.1%
7 4876
 
3.0%
6 3749
 
2.3%
4 3643
 
2.3%
5 3058
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 394
25.0%
D 394
25.0%
F 394
25.0%
I 394
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24489
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 185890
99.2%
Latin 1576
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72174
38.8%
- 24489
 
13.2%
1 20233
 
10.9%
2 20224
 
10.9%
3 18296
 
9.8%
9 10164
 
5.5%
8 4984
 
2.7%
7 4876
 
2.6%
6 3749
 
2.0%
4 3643
 
2.0%
Latin
ValueCountFrequency (%)
C 394
25.0%
D 394
25.0%
F 394
25.0%
I 394
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 187466
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72174
38.5%
- 24489
 
13.1%
1 20233
 
10.8%
2 20224
 
10.8%
3 18296
 
9.8%
9 10164
 
5.4%
8 4984
 
2.7%
7 4876
 
2.6%
6 3749
 
2.0%
4 3643
 
1.9%
Other values (5) 4634
 
2.5%

opnsvcid
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
03_11_03_P
8163 
03_11_04_P
 
290
03_11_01_P
 
88
03_11_05_P
 
9
03_11_02_P
 
3
Other values (3)
 
7

Length

Max length10
Median length10
Mean length9.9978972
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 8163
95.4%
03_11_04_P 290
 
3.4%
03_11_01_P 88
 
1.0%
03_11_05_P 9
 
0.1%
03_11_02_P 3
 
< 0.1%
03_11_06_P 3
 
< 0.1%
<NA> 3
 
< 0.1%
03_11_07_P 1
 
< 0.1%

Length

2024-04-17T01:32:35.355974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:35.466367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8163
95.4%
03_11_04_p 290
 
3.4%
03_11_01_p 88
 
1.0%
03_11_05_p 9
 
0.1%
03_11_02_p 3
 
< 0.1%
03_11_06_p 3
 
< 0.1%
na 3
 
< 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
6979 
U
1578 
180000000
 
3

Length

Max length9
Median length1
Mean length1.0028037
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6979
81.5%
U 1578
 
18.4%
180000000 3
 
< 0.1%

Length

2024-04-17T01:32:35.610029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:35.719466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6979
81.5%
u 1578
 
18.4%
180000000 3
 
< 0.1%
Distinct341
Distinct (%)4.0%
Missing3
Missing (%)< 0.1%
Memory size67.0 KiB
Minimum2018-08-31 23:59:59
Maximum2022-01-01 02:40:00
2024-04-17T01:32:35.819533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:32:35.942671image/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>
6874 
숙박업
1447 
외국인관광도시민박업
 
144
관광숙박업
 
88
한옥체험업
 
3
Other values (3)
 
4

Length

Max length10
Median length4
Mean length3.9435748
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> 6874
80.3%
숙박업 1447
 
16.9%
외국인관광도시민박업 144
 
1.7%
관광숙박업 88
 
1.0%
한옥체험업 3
 
< 0.1%
자동차야영장업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

Length

2024-04-17T01:32:36.073768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:36.187775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6874
80.3%
숙박업 1447
 
16.9%
외국인관광도시민박업 144
 
1.7%
관광숙박업 88
 
1.0%
한옥체험업 3
 
< 0.1%
자동차야영장업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

bplcnm
Text

Distinct3452
Distinct (%)40.3%
Missing3
Missing (%)< 0.1%
Memory size67.0 KiB
2024-04-17T01:32:36.439423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length5.2128082
Min length1

Characters and Unicode

Total characters44606
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

Unique342 ?
Unique (%)4.0%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 칠구(K79)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 254
 
2.5%
모텔 182
 
1.8%
게스트하우스 120
 
1.2%
여관 82
 
0.8%
hotel 65
 
0.6%
부산 49
 
0.5%
house 48
 
0.5%
해운대 41
 
0.4%
여인숙 36
 
0.4%
35
 
0.3%
Other values (3563) 9342
91.1%
2024-04-17T01:32:36.824300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2946
 
6.6%
2017
 
4.5%
1789
 
4.0%
1726
 
3.9%
1714
 
3.8%
1518
 
3.4%
1419
 
3.2%
1273
 
2.9%
770
 
1.7%
762
 
1.7%
Other values (643) 28672
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37390
83.8%
Uppercase Letter 2486
 
5.6%
Space Separator 1714
 
3.8%
Lowercase Letter 1254
 
2.8%
Close Punctuation 542
 
1.2%
Open Punctuation 542
 
1.2%
Decimal Number 520
 
1.2%
Other Punctuation 104
 
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 (%)
2946
 
7.9%
2017
 
5.4%
1789
 
4.8%
1726
 
4.6%
1518
 
4.1%
1419
 
3.8%
1273
 
3.4%
770
 
2.1%
762
 
2.0%
622
 
1.7%
Other values (563) 22548
60.3%
Uppercase Letter
ValueCountFrequency (%)
E 254
 
10.2%
O 241
 
9.7%
H 226
 
9.1%
T 200
 
8.0%
S 167
 
6.7%
A 151
 
6.1%
L 144
 
5.8%
N 124
 
5.0%
B 104
 
4.2%
U 101
 
4.1%
Other values (16) 774
31.1%
Lowercase Letter
ValueCountFrequency (%)
e 204
16.3%
o 142
11.3%
a 108
8.6%
s 107
8.5%
n 93
 
7.4%
u 91
 
7.3%
t 87
 
6.9%
h 59
 
4.7%
l 56
 
4.5%
i 54
 
4.3%
Other values (16) 253
20.2%
Decimal Number
ValueCountFrequency (%)
2 134
25.8%
1 71
13.7%
7 60
11.5%
5 60
11.5%
9 55
10.6%
0 42
 
8.1%
6 33
 
6.3%
3 28
 
5.4%
4 27
 
5.2%
8 10
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 57
54.8%
& 27
26.0%
' 9
 
8.7%
, 6
 
5.8%
; 2
 
1.9%
2
 
1.9%
: 1
 
1.0%
Letter Number
ValueCountFrequency (%)
7
63.6%
4
36.4%
Math Symbol
ValueCountFrequency (%)
2
50.0%
+ 2
50.0%
Space Separator
ValueCountFrequency (%)
1714
100.0%
Close Punctuation
ValueCountFrequency (%)
) 542
100.0%
Open Punctuation
ValueCountFrequency (%)
( 542
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Symbol
ValueCountFrequency (%)
6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37388
83.8%
Latin 3751
 
8.4%
Common 3459
 
7.8%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2946
 
7.9%
2017
 
5.4%
1789
 
4.8%
1726
 
4.6%
1518
 
4.1%
1419
 
3.8%
1273
 
3.4%
770
 
2.1%
762
 
2.0%
622
 
1.7%
Other values (559) 22546
60.3%
Latin
ValueCountFrequency (%)
E 254
 
6.8%
O 241
 
6.4%
H 226
 
6.0%
e 204
 
5.4%
T 200
 
5.3%
S 167
 
4.5%
A 151
 
4.0%
L 144
 
3.8%
o 142
 
3.8%
N 124
 
3.3%
Other values (44) 1898
50.6%
Common
ValueCountFrequency (%)
1714
49.6%
) 542
 
15.7%
( 542
 
15.7%
2 134
 
3.9%
1 71
 
2.1%
7 60
 
1.7%
5 60
 
1.7%
. 57
 
1.6%
9 55
 
1.6%
0 42
 
1.2%
Other values (15) 182
 
5.3%
Han
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37382
83.8%
ASCII 7194
 
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 (%)
2946
 
7.9%
2017
 
5.4%
1789
 
4.8%
1726
 
4.6%
1518
 
4.1%
1419
 
3.8%
1273
 
3.4%
770
 
2.1%
762
 
2.0%
622
 
1.7%
Other values (558) 22540
60.3%
ASCII
ValueCountFrequency (%)
1714
23.8%
) 542
 
7.5%
( 542
 
7.5%
E 254
 
3.5%
O 241
 
3.4%
H 226
 
3.1%
e 204
 
2.8%
T 200
 
2.8%
S 167
 
2.3%
A 151
 
2.1%
Other values (64) 2953
41.0%
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
2024-04-17T01:32:37.105856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters49470
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
 
1.6%
613828 128
 
1.6%
607831 126
 
1.5%
607842 114
 
1.4%
Other values (484) 6446
78.2%
2024-04-17T01:32:37.486215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9873
20.0%
1 8080
16.3%
0 8032
16.2%
8 7938
16.0%
2 4319
8.7%
4 3462
 
7.0%
7 2602
 
5.3%
3 2456
 
5.0%
9 1413
 
2.9%
5 959
 
1.9%
Other values (5) 336
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49134
99.3%
Other Letter 336
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9873
20.1%
1 8080
16.4%
0 8032
16.3%
8 7938
16.2%
2 4319
8.8%
4 3462
 
7.0%
7 2602
 
5.3%
3 2456
 
5.0%
9 1413
 
2.9%
5 959
 
2.0%
Other Letter
ValueCountFrequency (%)
112
33.3%
56
16.7%
56
16.7%
56
16.7%
56
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 49134
99.3%
Hangul 336
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9873
20.1%
1 8080
16.4%
0 8032
16.3%
8 7938
16.2%
2 4319
8.8%
4 3462
 
7.0%
7 2602
 
5.3%
3 2456
 
5.0%
9 1413
 
2.9%
5 959
 
2.0%
Hangul
ValueCountFrequency (%)
112
33.3%
56
16.7%
56
16.7%
56
16.7%
56
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49134
99.3%
Hangul 336
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9873
20.1%
1 8080
16.4%
0 8032
16.3%
8 7938
16.2%
2 4319
8.8%
4 3462
 
7.0%
7 2602
 
5.3%
3 2456
 
5.0%
9 1413
 
2.9%
5 959
 
2.0%
Hangul
ValueCountFrequency (%)
112
33.3%
56
16.7%
56
16.7%
56
16.7%
56
16.7%
Distinct4143
Distinct (%)48.4%
Missing5
Missing (%)0.1%
Memory size67.0 KiB
2024-04-17T01:32:37.792371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length43
Mean length23.326125
Min length13

Characters and Unicode

Total characters199555
Distinct characters309
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

Unique281 ?
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 8555
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%
수영구 503
 
1.4%
Other values (4387) 20804
57.1%
2024-04-17T01:32:38.235632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36331
18.2%
10379
 
5.2%
10122
 
5.1%
10032
 
5.0%
8933
 
4.5%
8794
 
4.4%
1 8640
 
4.3%
8580
 
4.3%
8561
 
4.3%
- 7927
 
4.0%
Other values (299) 81256
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 112972
56.6%
Decimal Number 39989
 
20.0%
Space Separator 36331
 
18.2%
Dash Punctuation 7927
 
4.0%
Uppercase Letter 1780
 
0.9%
Other Punctuation 194
 
0.1%
Open Punctuation 124
 
0.1%
Close Punctuation 124
 
0.1%
Math Symbol 113
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10379
 
9.2%
10122
 
9.0%
10032
 
8.9%
8933
 
7.9%
8794
 
7.8%
8580
 
7.6%
8561
 
7.6%
7233
 
6.4%
7015
 
6.2%
1625
 
1.4%
Other values (267) 31698
28.1%
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%
S 2
 
0.1%
G 2
 
0.1%
E 2
 
0.1%
M 2
 
0.1%
Other values (3) 3
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 8640
21.6%
2 5253
13.1%
3 4210
10.5%
4 4075
10.2%
5 3937
9.8%
0 3081
 
7.7%
6 3040
 
7.6%
7 2853
 
7.1%
8 2583
 
6.5%
9 2317
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 191
98.5%
. 2
 
1.0%
& 1
 
0.5%
Space Separator
ValueCountFrequency (%)
36331
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7927
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 124
100.0%
Math Symbol
ValueCountFrequency (%)
~ 113
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 112972
56.6%
Common 84802
42.5%
Latin 1781
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10379
 
9.2%
10122
 
9.0%
10032
 
8.9%
8933
 
7.9%
8794
 
7.8%
8580
 
7.6%
8561
 
7.6%
7233
 
6.4%
7015
 
6.2%
1625
 
1.4%
Other values (267) 31698
28.1%
Common
ValueCountFrequency (%)
36331
42.8%
1 8640
 
10.2%
- 7927
 
9.3%
2 5253
 
6.2%
3 4210
 
5.0%
4 4075
 
4.8%
5 3937
 
4.6%
0 3081
 
3.6%
6 3040
 
3.6%
7 2853
 
3.4%
Other values (8) 5455
 
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%
S 2
 
0.1%
G 2
 
0.1%
E 2
 
0.1%
M 2
 
0.1%
Other values (4) 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 112972
56.6%
ASCII 86582
43.4%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36331
42.0%
1 8640
 
10.0%
- 7927
 
9.2%
2 5253
 
6.1%
3 4210
 
4.9%
4 4075
 
4.7%
5 3937
 
4.5%
0 3081
 
3.6%
6 3040
 
3.5%
7 2853
 
3.3%
Other values (21) 7235
 
8.4%
Hangul
ValueCountFrequency (%)
10379
 
9.2%
10122
 
9.0%
10032
 
8.9%
8933
 
7.9%
8794
 
7.8%
8580
 
7.6%
8561
 
7.6%
7233
 
6.4%
7015
 
6.2%
1625
 
1.4%
Other values (267) 31698
28.1%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Unsupported

REJECTED  UNSUPPORTED 

Missing37
Missing (%)0.4%
Memory size67.0 KiB

rdnwhladdr
Text

MISSING 

Distinct3063
Distinct (%)51.0%
Missing2550
Missing (%)29.8%
Memory size67.0 KiB
2024-04-17T01:32:38.519579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length62
Mean length27.887521
Min length5

Characters and Unicode

Total characters167604
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

Unique333 ?
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 6009
 
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 401
 
1.3%
중구 395
 
1.3%
부전동 385
 
1.2%
Other values (2618) 20549
65.3%
2024-04-17T01:32:38.940120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25444
 
15.2%
7807
 
4.7%
7415
 
4.4%
7078
 
4.2%
6739
 
4.0%
1 6387
 
3.8%
6383
 
3.8%
6145
 
3.7%
6015
 
3.6%
) 5889
 
3.5%
Other values (357) 82302
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99756
59.5%
Decimal Number 27146
 
16.2%
Space Separator 25444
 
15.2%
Close Punctuation 5889
 
3.5%
Open Punctuation 5889
 
3.5%
Dash Punctuation 1807
 
1.1%
Other Punctuation 1312
 
0.8%
Math Symbol 267
 
0.2%
Uppercase Letter 90
 
0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7807
 
7.8%
7415
 
7.4%
7078
 
7.1%
6739
 
6.8%
6383
 
6.4%
6145
 
6.2%
6015
 
6.0%
5722
 
5.7%
4007
 
4.0%
3761
 
3.8%
Other values (319) 38684
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%
F 2
 
2.2%
G 2
 
2.2%
Other values (8) 9
 
10.0%
Decimal Number
ValueCountFrequency (%)
1 6387
23.5%
2 4134
15.2%
3 3039
11.2%
4 2313
 
8.5%
5 2190
 
8.1%
0 1962
 
7.2%
6 1937
 
7.1%
7 1867
 
6.9%
9 1708
 
6.3%
8 1609
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 1302
99.2%
. 9
 
0.7%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
25444
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5889
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5889
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1807
100.0%
Math Symbol
ValueCountFrequency (%)
~ 267
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99756
59.5%
Common 67754
40.4%
Latin 94
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7807
 
7.8%
7415
 
7.4%
7078
 
7.1%
6739
 
6.8%
6383
 
6.4%
6145
 
6.2%
6015
 
6.0%
5722
 
5.7%
4007
 
4.0%
3761
 
3.8%
Other values (319) 38684
38.8%
Latin
ValueCountFrequency (%)
A 30
31.9%
B 21
22.3%
K 8
 
8.5%
O 5
 
5.3%
C 5
 
5.3%
E 3
 
3.2%
3
 
3.2%
S 3
 
3.2%
U 2
 
2.1%
F 2
 
2.1%
Other values (10) 12
 
12.8%
Common
ValueCountFrequency (%)
25444
37.6%
1 6387
 
9.4%
) 5889
 
8.7%
( 5889
 
8.7%
2 4134
 
6.1%
3 3039
 
4.5%
4 2313
 
3.4%
5 2190
 
3.2%
0 1962
 
2.9%
6 1937
 
2.9%
Other values (8) 8570
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99756
59.5%
ASCII 67845
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25444
37.5%
1 6387
 
9.4%
) 5889
 
8.7%
( 5889
 
8.7%
2 4134
 
6.1%
3 3039
 
4.5%
4 2313
 
3.4%
5 2190
 
3.2%
0 1962
 
2.9%
6 1937
 
2.9%
Other values (27) 8661
 
12.8%
Hangul
ValueCountFrequency (%)
7807
 
7.8%
7415
 
7.4%
7078
 
7.1%
6739
 
6.8%
6383
 
6.4%
6145
 
6.2%
6015
 
6.0%
5722
 
5.7%
4007
 
4.0%
3761
 
3.8%
Other values (319) 38684
38.8%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

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

dcbymd
Text

MISSING 

Distinct1409
Distinct (%)34.2%
Missing4444
Missing (%)51.9%
Memory size67.0 KiB
2024-04-17T01:32:39.211229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8474247
Min length4

Characters and Unicode

Total characters32300
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

Unique47 ?
Unique (%)1.1%

Sample

1st row20140310
2nd row20121231
3rd row20171120
4th row20210823
5th row20171107
ValueCountFrequency (%)
20041022 180
 
4.4%
폐업일자 157
 
3.8%
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%
20030901 18
 
0.4%
Other values (1399) 3515
85.4%
2024-04-17T01:32:39.582856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10589
32.8%
2 6812
21.1%
1 5841
18.1%
3 1453
 
4.5%
9 1434
 
4.4%
7 1223
 
3.8%
4 1148
 
3.6%
6 1107
 
3.4%
5 1080
 
3.3%
8 985
 
3.0%
Other values (4) 628
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31672
98.1%
Other Letter 628
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10589
33.4%
2 6812
21.5%
1 5841
18.4%
3 1453
 
4.6%
9 1434
 
4.5%
7 1223
 
3.9%
4 1148
 
3.6%
6 1107
 
3.5%
5 1080
 
3.4%
8 985
 
3.1%
Other Letter
ValueCountFrequency (%)
157
25.0%
157
25.0%
157
25.0%
157
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31672
98.1%
Hangul 628
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10589
33.4%
2 6812
21.5%
1 5841
18.4%
3 1453
 
4.6%
9 1434
 
4.5%
7 1223
 
3.9%
4 1148
 
3.6%
6 1107
 
3.5%
5 1080
 
3.4%
8 985
 
3.1%
Hangul
ValueCountFrequency (%)
157
25.0%
157
25.0%
157
25.0%
157
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31672
98.1%
Hangul 628
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10589
33.4%
2 6812
21.5%
1 5841
18.4%
3 1453
 
4.6%
9 1434
 
4.5%
7 1223
 
3.9%
4 1148
 
3.6%
6 1107
 
3.5%
5 1080
 
3.4%
8 985
 
3.1%
Hangul
ValueCountFrequency (%)
157
25.0%
157
25.0%
157
25.0%
157
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8387 
휴업시작일자
 
163
20210916
 
2
20210528
 
2
20211129
 
1
Other values (5)
 
5

Length

Max length8
Median length4
Mean length4.042757
Min length4

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8387
98.0%
휴업시작일자 163
 
1.9%
20210916 2
 
< 0.1%
20210528 2
 
< 0.1%
20211129 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20210701 1
 
< 0.1%
20211031 1
 
< 0.1%

Length

2024-04-17T01:32:39.738888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:39.855489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.0%
휴업시작일자 163
 
1.9%
20210916 2
 
< 0.1%
20210528 2
 
< 0.1%
20211129 1
 
< 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 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8387 
휴업종료일자
 
163
20221130
 
2
20230131
 
2
20221128
 
1
Other values (5)
 
5

Length

Max length8
Median length4
Mean length4.042757
Min length4

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8387
98.0%
휴업종료일자 163
 
1.9%
20221130 2
 
< 0.1%
20230131 2
 
< 0.1%
20221128 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20211231 1
 
< 0.1%
20220131 1
 
< 0.1%

Length

2024-04-17T01:32:39.979452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:40.162834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.0%
휴업종료일자 163
 
1.9%
20221130 2
 
< 0.1%
20230131 2
 
< 0.1%
20221128 1
 
< 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>
8394 
재개업일자
 
166

Length

Max length5
Median length4
Mean length4.0193925
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> 8394
98.1%
재개업일자 166
 
1.9%

Length

2024-04-17T01:32:40.330328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:40.426433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
재개업일자 166
 
1.9%

trdstatenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
02
3707 
01
3012 
영업/정상
1476 
폐업
 
202
13
 
98
Other values (4)
 
65

Length

Max length5
Median length2
Mean length2.5182243
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 3012
35.2%
영업/정상 1476
 
17.2%
폐업 202
 
2.4%
13 98
 
1.1%
03 53
 
0.6%
휴업 7
 
0.1%
<NA> 4
 
< 0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:32:40.528786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:40.639733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3707
43.3%
01 3012
35.2%
영업/정상 1476
 
17.2%
폐업 202
 
2.4%
13 98
 
1.1%
03 53
 
0.6%
휴업 7
 
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
4293 
폐업
3959 
영업중
 
294
휴업
 
10
<NA>
 
3

Length

Max length4
Median length2
Mean length2.0352804
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4293
50.2%
폐업 3959
46.2%
영업중 294
 
3.4%
휴업 10
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:32:40.767002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:40.911156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4293
50.2%
폐업 3959
46.2%
영업중 294
 
3.4%
휴업 10
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

y
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing388
Missing (%)4.5%
Memory size67.0 KiB

lastmodts
Real number (ℝ)

Distinct3741
Distinct (%)43.7%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0136431 × 1013
Minimum1.9990211 × 1013
Maximum2.021123 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.4 KiB
2024-04-17T01:32:41.047881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0020186 × 1013
Q12.0060707 × 1013
median2.0171127 × 1013
Q32.0180723 × 1013
95-th percentile2.0211111 × 1013
Maximum2.021123 × 1013
Range2.2101916 × 1011
Interquartile range (IQR)1.2001615 × 1011

Descriptive statistics

Standard deviation7.0645634 × 1010
Coefficient of variation (CV)0.0035083494
Kurtosis-0.98362231
Mean2.0136431 × 1013
Median Absolute Deviation (MAD)3.9390032 × 1010
Skewness-0.74826282
Sum1.7230744 × 1017
Variance4.9908056 × 1021
MonotonicityNot monotonic
2024-04-17T01:32:41.202618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19990428000000 62
 
0.7%
20040902000000 60
 
0.7%
19990920000000 60
 
0.7%
20030122000000 58
 
0.7%
20040203000000 50
 
0.6%
20030414000000 36
 
0.4%
20070531000000 36
 
0.4%
20040427000000 32
 
0.4%
20020515000000 32
 
0.4%
20030329000000 32
 
0.4%
Other values (3731) 8099
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 (%)
20211230161337 2
< 0.1%
20211230155824 2
< 0.1%
20211230144122 2
< 0.1%
20211230124410 2
< 0.1%
20211230114159 2
< 0.1%
20211230114026 2
< 0.1%
20211230094418 2
< 0.1%
20211229161740 2
< 0.1%
20211229160539 1
< 0.1%
20211229154951 1
< 0.1%

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
여관업
5227 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
506
일반호텔
 
481
Other values (4)
681 

Length

Max length8
Median length3
Mean length3.7148364
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5227
61.1%
여인숙업 1076
 
12.6%
숙박업 기타 589
 
6.9%
숙박업(생활) 506
 
5.9%
일반호텔 481
 
5.6%
<NA> 345
 
4.0%
관광호텔 273
 
3.2%
업태구분명 54
 
0.6%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:32:41.354462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:41.466996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5227
57.1%
여인숙업 1076
 
11.8%
숙박업 589
 
6.4%
기타 589
 
6.4%
숙박업(생활 506
 
5.5%
일반호텔 481
 
5.3%
na 345
 
3.8%
관광호텔 273
 
3.0%
업태구분명 54
 
0.6%
휴양콘도미니엄업 9
 
0.1%

sitetel
Text

MISSING 

Distinct645
Distinct (%)7.7%
Missing221
Missing (%)2.6%
Memory size67.0 KiB
2024-04-17T01:32:41.605015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.83883
Min length4

Characters and Unicode

Total characters98724
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

Unique53 ?
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 7020
70.3%
051 1149
 
11.5%
전화번호 70
 
0.7%
070 20
 
0.2%
747 18
 
0.2%
746 14
 
0.1%
806 11
 
0.1%
741 8
 
0.1%
728 8
 
0.1%
633 8
 
0.1%
Other values (764) 1653
 
16.6%
2024-04-17T01:32:41.850350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23167
23.5%
2 15071
15.3%
3 14995
15.2%
- 14086
14.3%
0 9288
9.4%
5 9113
 
9.2%
4 7944
 
8.0%
1654
 
1.7%
7 1015
 
1.0%
8 827
 
0.8%
Other values (6) 1564
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82704
83.8%
Dash Punctuation 14086
 
14.3%
Space Separator 1654
 
1.7%
Other Letter 280
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23167
28.0%
2 15071
18.2%
3 14995
18.1%
0 9288
11.2%
5 9113
 
11.0%
4 7944
 
9.6%
7 1015
 
1.2%
8 827
 
1.0%
6 777
 
0.9%
9 507
 
0.6%
Other Letter
ValueCountFrequency (%)
70
25.0%
70
25.0%
70
25.0%
70
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 14086
100.0%
Space Separator
ValueCountFrequency (%)
1654
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98444
99.7%
Hangul 280
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23167
23.5%
2 15071
15.3%
3 14995
15.2%
- 14086
14.3%
0 9288
9.4%
5 9113
 
9.3%
4 7944
 
8.1%
1654
 
1.7%
7 1015
 
1.0%
8 827
 
0.8%
Other values (2) 1284
 
1.3%
Hangul
ValueCountFrequency (%)
70
25.0%
70
25.0%
70
25.0%
70
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98444
99.7%
Hangul 280
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23167
23.5%
2 15071
15.3%
3 14995
15.2%
- 14086
14.3%
0 9288
9.4%
5 9113
 
9.3%
4 7944
 
8.1%
1654
 
1.7%
7 1015
 
1.0%
8 827
 
0.8%
Other values (2) 1284
 
1.3%
Hangul
ValueCountFrequency (%)
70
25.0%
70
25.0%
70
25.0%
70
25.0%

stroomcnt
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8225 
객실수
 
125
1
 
64
2
 
50
3
 
25
Other values (28)
 
71

Length

Max length4
Median length4
Mean length3.916472
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> 8225
96.1%
객실수 125
 
1.5%
1 64
 
0.7%
2 50
 
0.6%
3 25
 
0.3%
7 9
 
0.1%
0 8
 
0.1%
6 6
 
0.1%
5 6
 
0.1%
8 4
 
< 0.1%
Other values (23) 38
 
0.4%

Length

2024-04-17T01:32:41.963705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8225
96.1%
객실수 125
 
1.5%
1 64
 
0.7%
2 50
 
0.6%
3 25
 
0.3%
7 9
 
0.1%
0 8
 
0.1%
6 6
 
0.1%
5 6
 
0.1%
8 4
 
< 0.1%
Other values (23) 38
 
0.4%

bdngownsenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
6469 
자가
1177 
임대
773 
건물소유구분명
 
141

Length

Max length7
Median length4
Mean length3.5938084
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6469
75.6%
자가 1177
 
13.8%
임대 773
 
9.0%
건물소유구분명 141
 
1.6%

Length

2024-04-17T01:32:42.072753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:42.176749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6469
75.6%
자가 1177
 
13.8%
임대 773
 
9.0%
건물소유구분명 141
 
1.6%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8231 
건물용도명
 
135
단독주택
 
77
아파트
 
60
숙박시설
 
24
Other values (6)
 
33

Length

Max length15
Median length4
Mean length4.0154206
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> 8231
96.2%
건물용도명 135
 
1.6%
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

2024-04-17T01:32:42.293330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8231
96.1%
건물용도명 135
 
1.6%
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
Categorical

Distinct36
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
0
2547 
<NA>
1675 
4
874 
3
751 
5
598 
Other values (31)
2115 

Length

Max length6
Median length1
Mean length1.6627336
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2547
29.8%
<NA> 1675
19.6%
4 874
 
10.2%
3 751
 
8.8%
5 598
 
7.0%
2 424
 
5.0%
8 330
 
3.9%
6 304
 
3.6%
7 303
 
3.5%
9 199
 
2.3%
Other values (26) 555
 
6.5%

Length

2024-04-17T01:32:42.404625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2547
29.8%
na 1675
19.6%
4 874
 
10.2%
3 751
 
8.8%
5 598
 
7.0%
2 424
 
5.0%
8 330
 
3.9%
6 304
 
3.6%
7 303
 
3.5%
9 199
 
2.3%
Other values (26) 555
 
6.5%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
0
4450 
<NA>
2241 
1
1512 
2
 
199
건물지하층수
 
54
Other values (9)
 
104

Length

Max length6
Median length1
Mean length1.8176402
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4450
52.0%
<NA> 2241
26.2%
1 1512
 
17.7%
2 199
 
2.3%
건물지하층수 54
 
0.6%
4 36
 
0.4%
3 27
 
0.3%
5 17
 
0.2%
8 6
 
0.1%
6 5
 
0.1%
Other values (4) 13
 
0.2%

Length

2024-04-17T01:32:42.520479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4450
52.0%
na 2241
26.2%
1 1514
 
17.7%
2 199
 
2.3%
건물지하층수 54
 
0.6%
4 36
 
0.4%
3 27
 
0.3%
5 17
 
0.2%
8 6
 
0.1%
6 5
 
0.1%
Other values (3) 11
 
0.1%

cnstyarea
Categorical

IMBALANCE 

Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8308 
건축연면적
 
143
0
 
82
2282
 
3
20571
 
3
Other values (19)
 
21

Length

Max length5
Median length4
Mean length3.9863318
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> 8308
97.1%
건축연면적 143
 
1.7%
0 82
 
1.0%
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

2024-04-17T01:32:42.624529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8308
97.1%
건축연면적 143
 
1.7%
0 82
 
1.0%
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>
8394 
기념품종류
 
166

Length

Max length5
Median length4
Mean length4.0193925
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> 8394
98.1%
기념품종류 166
 
1.9%

Length

2024-04-17T01:32:42.723761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:42.805398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
기념품종류 166
 
1.9%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
기획여행보험시작일자
 
166

Length

Max length10
Median length4
Mean length4.1163551
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> 8394
98.1%
기획여행보험시작일자 166
 
1.9%

Length

2024-04-17T01:32:42.891546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:42.974504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
기획여행보험시작일자 166
 
1.9%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
기획여행보험종료일자
 
166

Length

Max length10
Median length4
Mean length4.1163551
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> 8394
98.1%
기획여행보험종료일자 166
 
1.9%

Length

2024-04-17T01:32:43.308882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:43.386383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
기획여행보험종료일자 166
 
1.9%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
7523 
0
917 
남성종사자수
 
90
1
 
12
3
 
5
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.6892523
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> 7523
87.9%
0 917
 
10.7%
남성종사자수 90
 
1.1%
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

2024-04-17T01:32:43.474367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7523
87.9%
0 917
 
10.7%
남성종사자수 90
 
1.1%
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>
8394 
놀이기구수내역
 
166

Length

Max length7
Median length4
Mean length4.0581776
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> 8394
98.1%
놀이기구수내역 166
 
1.9%

Length

2024-04-17T01:32:43.583605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:43.675175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
놀이기구수내역 166
 
1.9%

playfacilcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
N
7017 
<NA>
1316 
놀이시설수
 
132
0
 
92
Y
 
3

Length

Max length5
Median length1
Mean length1.5228972
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 7017
82.0%
<NA> 1316
 
15.4%
놀이시설수 132
 
1.5%
0 92
 
1.1%
Y 3
 
< 0.1%

Length

2024-04-17T01:32:43.770345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:43.881334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 7017
82.0%
na 1316
 
15.4%
놀이시설수 132
 
1.5%
0 92
 
1.1%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
N
8377 
<NA>
 
131
 
41
Y
 
11

Length

Max length4
Median length1
Mean length1.0459112
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8377
97.9%
<NA> 131
 
1.5%
41
 
0.5%
Y 11
 
0.1%

Length

2024-04-17T01:32:43.990272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:44.081148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8377
97.9%
na 131
 
1.5%
41
 
0.5%
y 11
 
0.1%

stagear
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8321 
무대면적
 
147
0
 
92

Length

Max length4
Median length4
Mean length3.967757
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> 8321
97.2%
무대면적 147
 
1.7%
0 92
 
1.1%

Length

2024-04-17T01:32:44.169790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:44.256464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8321
97.2%
무대면적 147
 
1.7%
0 92
 
1.1%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
문화사업자구분명
 
166

Length

Max length8
Median length4
Mean length4.0775701
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> 8394
98.1%
문화사업자구분명 166
 
1.9%

Length

2024-04-17T01:32:44.349036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:44.449690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
문화사업자구분명 166
 
1.9%

culphyedcobnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8057 
외국인관광 도시민박업
 
287
문화체육업종명
 
112
관광숙박업
 
88
자동차야영장업
 
9
Other values (3)
 
7

Length

Max length11
Median length4
Mean length4.2883178
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> 8057
94.1%
외국인관광 도시민박업 287
 
3.4%
문화체육업종명 112
 
1.3%
관광숙박업 88
 
1.0%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%

Length

2024-04-17T01:32:44.550029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:44.651442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8057
91.1%
외국인관광 287
 
3.2%
도시민박업 287
 
3.2%
문화체육업종명 112
 
1.3%
관광숙박업 88
 
1.0%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%

geicpfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
 
166

Length

Max length4
Median length4
Mean length3.9418224
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> 8394
98.1%
166
 
1.9%

Length

2024-04-17T01:32:44.778331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:44.873076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
166
 
1.9%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
N
8364 
<NA>
 
131
 
41
Y
 
24

Length

Max length4
Median length1
Mean length1.0459112
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8364
97.7%
<NA> 131
 
1.5%
41
 
0.5%
Y 24
 
0.3%

Length

2024-04-17T01:32:44.962673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:45.048888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8364
97.7%
na 131
 
1.5%
41
 
0.5%
y 24
 
0.3%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
 
166

Length

Max length4
Median length4
Mean length3.9418224
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> 8394
98.1%
166
 
1.9%

Length

2024-04-17T01:32:45.141685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:45.230572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
166
 
1.9%

insurorgnm
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8370 
보험기관명
 
162
현대해상
 
3
야영장사고배상책임보험
 
2
DB 손해보험
 
2
Other values (20)
 
21

Length

Max length22
Median length4
Mean length4.0396028
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> 8370
97.8%
보험기관명 162
 
1.9%
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

2024-04-17T01:32:45.341989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8370
97.6%
보험기관명 162
 
1.9%
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>
8394 
보험시작일자
 
166

Length

Max length6
Median length4
Mean length4.038785
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> 8394
98.1%
보험시작일자 166
 
1.9%

Length

2024-04-17T01:32:45.466044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:45.560326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
보험시작일자 166
 
1.9%

insurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
보험종료일자
 
166

Length

Max length6
Median length4
Mean length4.038785
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> 8394
98.1%
보험종료일자 166
 
1.9%

Length

2024-04-17T01:32:45.660228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:45.751179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
보험종료일자 166
 
1.9%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
부대시설내역
 
166

Length

Max length6
Median length4
Mean length4.038785
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> 8394
98.1%
부대시설내역 166
 
1.9%

Length

2024-04-17T01:32:45.850319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:45.957630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
부대시설내역 166
 
1.9%

usejisgendflr
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
2698 
0
1964 
4
768 
3
650 
5
474 
Other values (30)
2006 

Length

Max length6
Median length1
Mean length2.0181075
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2698
31.5%
0 1964
22.9%
4 768
 
9.0%
3 650
 
7.6%
5 474
 
5.5%
6 417
 
4.9%
2 391
 
4.6%
7 270
 
3.2%
8 261
 
3.0%
9 185
 
2.2%
Other values (25) 482
 
5.6%

Length

2024-04-17T01:32:46.056666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2698
31.5%
0 1964
22.9%
4 768
 
9.0%
3 650
 
7.6%
5 474
 
5.5%
6 417
 
4.9%
2 391
 
4.6%
7 270
 
3.2%
8 261
 
3.0%
9 185
 
2.2%
Other values (25) 482
 
5.6%

useunderendflr
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
0
4691 
<NA>
3596 
1
 
184
사용끝지하층
 
59
2
 
16
Other values (4)
 
14

Length

Max length6
Median length1
Mean length2.2948598
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4691
54.8%
<NA> 3596
42.0%
1 184
 
2.1%
사용끝지하층 59
 
0.7%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
19 1
 
< 0.1%

Length

2024-04-17T01:32:46.156805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:46.260173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4691
54.8%
na 3596
42.0%
1 184
 
2.1%
사용끝지하층 59
 
0.7%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
19 1
 
< 0.1%

usejisgstflr
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
0
2455 
1
1919 
<NA>
1871 
2
1001 
3
515 
Other values (15)
799 

Length

Max length7
Median length1
Mean length1.7015187
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2455
28.7%
1 1919
22.4%
<NA> 1871
21.9%
2 1001
11.7%
3 515
 
6.0%
4 312
 
3.6%
5 191
 
2.2%
6 76
 
0.9%
7 59
 
0.7%
사용시작지상층 56
 
0.7%
Other values (10) 105
 
1.2%

Length

2024-04-17T01:32:46.371694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2455
28.7%
1 1919
22.4%
na 1871
21.9%
2 1001
11.7%
3 515
 
6.0%
4 312
 
3.6%
5 191
 
2.2%
6 76
 
0.9%
7 59
 
0.7%
사용시작지상층 56
 
0.7%
Other values (10) 105
 
1.2%

useunderstflr
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
0
5628 
<NA>
2645 
1
 
217
사용시작지하층
 
57
4
 
8
Other values (3)
 
5

Length

Max length7
Median length1
Mean length1.9669393
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5628
65.7%
<NA> 2645
30.9%
1 217
 
2.5%
사용시작지하층 57
 
0.7%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:32:46.481913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:46.602851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5628
65.7%
na 2645
30.9%
1 217
 
2.5%
사용시작지하층 57
 
0.7%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

shpinfo
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
선박제원
 
166

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> 8394
98.1%
선박제원 166
 
1.9%

Length

2024-04-17T01:32:46.716556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:46.805789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
선박제원 166
 
1.9%

shpcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8321 
선박척수
 
147
0
 
92

Length

Max length4
Median length4
Mean length3.967757
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> 8321
97.2%
선박척수 147
 
1.7%
0 92
 
1.1%

Length

2024-04-17T01:32:46.902868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:47.009647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8321
97.2%
선박척수 147
 
1.7%
0 92
 
1.1%

shptottons
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8321 
선박총톤수
 
147
0
 
92

Length

Max length5
Median length4
Mean length3.9849299
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> 8321
97.2%
선박총톤수 147
 
1.7%
0 92
 
1.1%

Length

2024-04-17T01:32:47.120875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:47.224478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8321
97.2%
선박총톤수 147
 
1.7%
0 92
 
1.1%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
0
5018 
<NA>
3488 
세탁기수
 
54

Length

Max length4
Median length1
Mean length2.2413551
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5018
58.6%
<NA> 3488
40.7%
세탁기수 54
 
0.6%

Length

2024-04-17T01:32:47.332691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:47.418404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5018
58.6%
na 3488
40.7%
세탁기수 54
 
0.6%

facilscp
Text

MISSING 

Distinct155
Distinct (%)34.8%
Missing8115
Missing (%)94.8%
Memory size67.0 KiB
2024-04-17T01:32:47.669147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.9280899
Min length1

Characters and Unicode

Total characters1303
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 (%)18.9%

Sample

1st row시설규모
2nd row시설규모
3rd row시설규모
4th row시설규모
5th row시설규모
ValueCountFrequency (%)
시설규모 117
26.3%
0 24
 
5.4%
85 16
 
3.6%
46 7
 
1.6%
599 6
 
1.3%
60 6
 
1.3%
83 6
 
1.3%
67 6
 
1.3%
62 5
 
1.1%
63 5
 
1.1%
Other values (145) 247
55.5%
2024-04-17T01:32:48.060380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 126
9.7%
117
9.0%
117
9.0%
117
9.0%
117
9.0%
5 102
 
7.8%
0 89
 
6.8%
8 84
 
6.4%
6 76
 
5.8%
4 75
 
5.8%
Other values (4) 283
21.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 835
64.1%
Other Letter 468
35.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 126
15.1%
5 102
12.2%
0 89
10.7%
8 84
10.1%
6 76
9.1%
4 75
9.0%
2 73
8.7%
7 71
8.5%
9 70
8.4%
3 69
8.3%
Other Letter
ValueCountFrequency (%)
117
25.0%
117
25.0%
117
25.0%
117
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 835
64.1%
Hangul 468
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 126
15.1%
5 102
12.2%
0 89
10.7%
8 84
10.1%
6 76
9.1%
4 75
9.0%
2 73
8.7%
7 71
8.5%
9 70
8.4%
3 69
8.3%
Hangul
ValueCountFrequency (%)
117
25.0%
117
25.0%
117
25.0%
117
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 835
64.1%
Hangul 468
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 126
15.1%
5 102
12.2%
0 89
10.7%
8 84
10.1%
6 76
9.1%
4 75
9.0%
2 73
8.7%
7 71
8.5%
9 70
8.4%
3 69
8.3%
Hangul
ValueCountFrequency (%)
117
25.0%
117
25.0%
117
25.0%
117
25.0%

facilar
Text

MISSING 

Distinct229
Distinct (%)51.5%
Missing8115
Missing (%)94.8%
Memory size67.0 KiB
2024-04-17T01:32:48.379149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.6988764
Min length1

Characters and Unicode

Total characters2091
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

Unique181 ?
Unique (%)40.7%

Sample

1st row시설면적
2nd row시설면적
3rd row시설면적
4th row시설면적
5th row시설면적
ValueCountFrequency (%)
시설면적 117
26.3%
0 24
 
5.4%
598.73 6
 
1.3%
45.5 6
 
1.3%
62.58 4
 
0.9%
218.85 4
 
0.9%
337.46 3
 
0.7%
1497.35 3
 
0.7%
326.98 3
 
0.7%
62.25 3
 
0.7%
Other values (219) 272
61.1%
2024-04-17T01:32:48.826785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 277
13.2%
1 171
 
8.2%
4 167
 
8.0%
8 161
 
7.7%
5 139
 
6.6%
2 126
 
6.0%
3 124
 
5.9%
6 124
 
5.9%
9 119
 
5.7%
117
 
5.6%
Other values (5) 566
27.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1346
64.4%
Other Letter 468
 
22.4%
Other Punctuation 277
 
13.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 171
12.7%
4 167
12.4%
8 161
12.0%
5 139
10.3%
2 126
9.4%
3 124
9.2%
6 124
9.2%
9 119
8.8%
7 111
8.2%
0 104
7.7%
Other Letter
ValueCountFrequency (%)
117
25.0%
117
25.0%
117
25.0%
117
25.0%
Other Punctuation
ValueCountFrequency (%)
. 277
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1623
77.6%
Hangul 468
 
22.4%

Most frequent character per script

Common
ValueCountFrequency (%)
. 277
17.1%
1 171
10.5%
4 167
10.3%
8 161
9.9%
5 139
8.6%
2 126
7.8%
3 124
7.6%
6 124
7.6%
9 119
7.3%
7 111
6.8%
Hangul
ValueCountFrequency (%)
117
25.0%
117
25.0%
117
25.0%
117
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1623
77.6%
Hangul 468
 
22.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 277
17.1%
1 171
10.5%
4 167
10.3%
8 161
9.9%
5 139
8.6%
2 126
7.8%
3 124
7.6%
6 124
7.6%
9 119
7.3%
7 111
6.8%
Hangul
ValueCountFrequency (%)
117
25.0%
117
25.0%
117
25.0%
117
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
 
166

Length

Max length4
Median length4
Mean length3.9418224
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> 8394
98.1%
166
 
1.9%

Length

2024-04-17T01:32:48.945467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:49.043282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
166
 
1.9%

yangsilcnt
Text

MISSING 

Distinct151
Distinct (%)2.0%
Missing923
Missing (%)10.8%
Memory size67.0 KiB
2024-04-17T01:32:49.195055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7421762
Min length1

Characters and Unicode

Total characters13305
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)0.2%

Sample

1st row107
2nd row81
3rd row16
4th row7
5th row5
ValueCountFrequency (%)
0 1040
 
13.6%
10 440
 
5.8%
18 370
 
4.8%
12 318
 
4.2%
14 314
 
4.1%
15 300
 
3.9%
13 248
 
3.2%
19 242
 
3.2%
16 221
 
2.9%
17 217
 
2.8%
Other values (141) 3927
51.4%
2024-04-17T01:32:49.553588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3432
25.8%
0 1929
14.5%
2 1880
14.1%
3 1353
 
10.2%
4 1051
 
7.9%
5 822
 
6.2%
8 815
 
6.1%
6 639
 
4.8%
9 622
 
4.7%
7 600
 
4.5%
Other values (3) 162
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13143
98.8%
Other Letter 162
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3432
26.1%
0 1929
14.7%
2 1880
14.3%
3 1353
 
10.3%
4 1051
 
8.0%
5 822
 
6.3%
8 815
 
6.2%
6 639
 
4.9%
9 622
 
4.7%
7 600
 
4.6%
Other Letter
ValueCountFrequency (%)
54
33.3%
54
33.3%
54
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13143
98.8%
Hangul 162
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3432
26.1%
0 1929
14.7%
2 1880
14.3%
3 1353
 
10.3%
4 1051
 
8.0%
5 822
 
6.3%
8 815
 
6.2%
6 639
 
4.9%
9 622
 
4.7%
7 600
 
4.6%
Hangul
ValueCountFrequency (%)
54
33.3%
54
33.3%
54
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13143
98.8%
Hangul 162
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3432
26.1%
0 1929
14.7%
2 1880
14.3%
3 1353
 
10.3%
4 1051
 
8.0%
5 822
 
6.3%
8 815
 
6.2%
6 639
 
4.9%
9 622
 
4.7%
7 600
 
4.6%
Hangul
ValueCountFrequency (%)
54
33.3%
54
33.3%
54
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
7525 
0
923 
여성종사자수
 
90
2
 
6
1
 
6
Other values (4)
 
10

Length

Max length6
Median length4
Mean length3.6901869
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> 7525
87.9%
0 923
 
10.8%
여성종사자수 90
 
1.1%
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

2024-04-17T01:32:49.680294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:49.796171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7525
87.9%
0 923
 
10.8%
여성종사자수 90
 
1.1%
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 

Distinct54
Distinct (%)24.2%
Missing8337
Missing (%)97.4%
Memory size67.0 KiB
2024-04-17T01:32:50.000099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length5
Mean length8.2107623
Min length4

Characters and Unicode

Total characters1831
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

Unique43 ?
Unique (%)19.3%

Sample

1st row영문상호명
2nd row영문상호명
3rd row영문상호명
4th row영문상호명
5th row영문상호명
ValueCountFrequency (%)
영문상호명 153
48.9%
house 31
 
9.9%
busan 9
 
2.9%
ocean 6
 
1.9%
hotel 6
 
1.9%
guest 5
 
1.6%
kim's 4
 
1.3%
suyeong 3
 
1.0%
the 3
 
1.0%
in 3
 
1.0%
Other values (65) 90
28.8%
2024-04-17T01:32:50.300122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
153
 
8.4%
153
 
8.4%
153
 
8.4%
153
 
8.4%
153
 
8.4%
e 97
 
5.3%
90
 
4.9%
o 82
 
4.5%
a 61
 
3.3%
n 58
 
3.2%
Other values (49) 678
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 765
41.8%
Lowercase Letter 637
34.8%
Uppercase Letter 313
17.1%
Space Separator 90
 
4.9%
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 97
15.2%
o 82
12.9%
a 61
9.6%
n 58
9.1%
u 50
 
7.8%
s 42
 
6.6%
h 30
 
4.7%
t 28
 
4.4%
i 24
 
3.8%
g 24
 
3.8%
Other values (12) 141
22.1%
Other Letter
ValueCountFrequency (%)
153
20.0%
153
20.0%
153
20.0%
153
20.0%
153
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 (%)
90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 950
51.9%
Hangul 765
41.8%
Common 116
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 97
 
10.2%
o 82
 
8.6%
a 61
 
6.4%
n 58
 
6.1%
u 50
 
5.3%
s 42
 
4.4%
H 39
 
4.1%
S 36
 
3.8%
E 31
 
3.3%
h 30
 
3.2%
Other values (36) 424
44.6%
Common
ValueCountFrequency (%)
90
77.6%
- 7
 
6.0%
0 7
 
6.0%
' 5
 
4.3%
2 3
 
2.6%
1 2
 
1.7%
. 1
 
0.9%
& 1
 
0.9%
Hangul
ValueCountFrequency (%)
153
20.0%
153
20.0%
153
20.0%
153
20.0%
153
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1066
58.2%
Hangul 765
41.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
153
20.0%
153
20.0%
153
20.0%
153
20.0%
153
20.0%
ASCII
ValueCountFrequency (%)
e 97
 
9.1%
90
 
8.4%
o 82
 
7.7%
a 61
 
5.7%
n 58
 
5.4%
u 50
 
4.7%
s 42
 
3.9%
H 39
 
3.7%
S 36
 
3.4%
E 31
 
2.9%
Other values (44) 480
45.0%

engstntrnmaddr
Categorical

IMBALANCE 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8340 
영문상호주소
 
153
Guesthouse for Foreign Tourists
 
23
Foreigner Tourism City home-stay Business
 
14
Guest House
 
4
Other values (16)
 
26

Length

Max length41
Median length4
Mean length4.2448598
Min length4

Unique

Unique10 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8340
97.4%
영문상호주소 153
 
1.8%
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 (11) 12
 
0.1%

Length

2024-04-17T01:32:50.420818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8340
95.3%
영문상호주소 153
 
1.7%
for 31
 
0.4%
foreign 29
 
0.3%
guesthouse 27
 
0.3%
tourists 27
 
0.3%
business 22
 
0.3%
foreigner 19
 
0.2%
home-stay 15
 
0.2%
tourism 14
 
0.2%
Other values (19) 72
 
0.8%

yoksilcnt
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
0
5862 
<NA>
2456 
욕실수
 
54
15
 
16
12
 
14
Other values (28)
 
158

Length

Max length4
Median length1
Mean length1.892757
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5862
68.5%
<NA> 2456
28.7%
욕실수 54
 
0.6%
15 16
 
0.2%
12 14
 
0.2%
18 12
 
0.1%
10 12
 
0.1%
14 10
 
0.1%
22 10
 
0.1%
9 10
 
0.1%
Other values (23) 104
 
1.2%

Length

2024-04-17T01:32:50.538302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 5862
68.5%
na 2456
28.7%
욕실수 54
 
0.6%
15 16
 
0.2%
12 14
 
0.2%
18 12
 
0.1%
10 12
 
0.1%
14 10
 
0.1%
9 10
 
0.1%
8 10
 
0.1%
Other values (23) 104
 
1.2%

sntuptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
여관업
5227 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
506
일반호텔
 
481
Other values (4)
681 

Length

Max length8
Median length3
Mean length3.7148364
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5227
61.1%
여인숙업 1076
 
12.6%
숙박업 기타 589
 
6.9%
숙박업(생활) 506
 
5.9%
일반호텔 481
 
5.6%
<NA> 345
 
4.0%
관광호텔 273
 
3.2%
위생업태명 54
 
0.6%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:32:50.655050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:50.768815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5227
57.1%
여인숙업 1076
 
11.8%
숙박업 589
 
6.4%
기타 589
 
6.4%
숙박업(생활 506
 
5.5%
일반호텔 481
 
5.3%
na 345
 
3.8%
관광호텔 273
 
3.0%
위생업태명 54
 
0.6%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
 
166

Length

Max length4
Median length4
Mean length3.9418224
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> 8394
98.1%
166
 
1.9%

Length

2024-04-17T01:32:50.877855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:51.230266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
166
 
1.9%

capt
Categorical

IMBALANCE 

Distinct44
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8254 
자본금
 
132
0
 
68
10000000
 
20
100000000
 
12
Other values (39)
 
74

Length

Max length10
Median length4
Mean length4.0154206
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> 8254
96.4%
자본금 132
 
1.5%
0 68
 
0.8%
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

2024-04-17T01:32:51.317035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8254
96.4%
자본금 132
 
1.5%
0 68
 
0.8%
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>
8394 
제작취급품목내용
 
166

Length

Max length8
Median length4
Mean length4.0775701
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> 8394
98.1%
제작취급품목내용 166
 
1.9%

Length

2024-04-17T01:32:51.415478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:51.511058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
제작취급품목내용 166
 
1.9%

cndpermstymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
조건부허가시작일자
 
166

Length

Max length9
Median length4
Mean length4.0969626
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> 8394
98.1%
조건부허가시작일자 166
 
1.9%

Length

2024-04-17T01:32:51.604408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:51.685814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
조건부허가시작일자 166
 
1.9%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
조건부허가신고사유
 
166

Length

Max length9
Median length4
Mean length4.0969626
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> 8394
98.1%
조건부허가신고사유 166
 
1.9%

Length

2024-04-17T01:32:51.785001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:51.897321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
조건부허가신고사유 166
 
1.9%

cndpermendymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8394 
조건부허가종료일자
 
166

Length

Max length9
Median length4
Mean length4.0969626
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> 8394
98.1%
조건부허가종료일자 166
 
1.9%

Length

2024-04-17T01:32:51.981712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:52.064232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8394
98.1%
조건부허가종료일자 166
 
1.9%

chaircnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
4725 
0
3795 
좌석수
 
35
6
 
1
12
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length2.6642523
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4725
55.2%
0 3795
44.3%
좌석수 35
 
0.4%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-17T01:32:52.165002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:52.280197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4725
55.2%
0 3795
44.3%
좌석수 35
 
0.4%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

nearenvnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8298 
주변환경명
 
148
주택가주변
 
40
아파트지역
 
32
기타
 
25
Other values (3)
 
17

Length

Max length8
Median length4
Mean length4.0278037
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> 8298
96.9%
주변환경명 148
 
1.7%
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

2024-04-17T01:32:52.387265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:52.491699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8298
96.9%
주변환경명 148
 
1.7%
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>
8219 
지상층수
 
133
0
 
55
2
 
35
4
 
19
Other values (22)
 
99

Length

Max length4
Median length4
Mean length3.9316589
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> 8219
96.0%
지상층수 133
 
1.6%
0 55
 
0.6%
2 35
 
0.4%
4 19
 
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

2024-04-17T01:32:52.624404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8219
96.0%
지상층수 133
 
1.6%
0 55
 
0.6%
2 35
 
0.4%
4 19
 
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>
8189 
지역구분명
 
128
일반주거지역
 
122
일반상업지역
 
42
준주거지역
 
32
Other values (5)
 
47

Length

Max length6
Median length4
Mean length4.0586449
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> 8189
95.7%
지역구분명 128
 
1.5%
일반주거지역 122
 
1.4%
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

2024-04-17T01:32:52.740673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:52.856089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8189
95.7%
지역구분명 128
 
1.5%
일반주거지역 122
 
1.4%
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>
8280 
지하층수
 
138
0
 
85
1
 
29
2
 
21
Other values (5)
 
7

Length

Max length4
Median length4
Mean length3.9502336
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> 8280
96.7%
지하층수 138
 
1.6%
0 85
 
1.0%
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

2024-04-17T01:32:52.993806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:53.110261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8280
96.7%
지하층수 138
 
1.6%
0 85
 
1.0%
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>
8212 
총층수
 
129
0
 
47
2
 
41
4
 
21
Other values (21)
 
110

Length

Max length4
Median length4
Mean length3.9127336
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> 8212
95.9%
총층수 129
 
1.5%
0 47
 
0.5%
2 41
 
0.5%
4 21
 
0.2%
1 20
 
0.2%
3 19
 
0.2%
5 14
 
0.2%
6 8
 
0.1%
20 7
 
0.1%
Other values (16) 42
 
0.5%

Length

2024-04-17T01:32:53.223886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8212
95.9%
총층수 129
 
1.5%
0 47
 
0.5%
2 41
 
0.5%
4 21
 
0.2%
1 20
 
0.2%
3 19
 
0.2%
5 14
 
0.2%
6 8
 
0.1%
20 7
 
0.1%
Other values (16) 42
 
0.5%

abedcnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
0
4974 
<NA>
3530 
침대수
 
54
41
 
2

Length

Max length4
Median length1
Mean length2.25
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4974
58.1%
<NA> 3530
41.2%
침대수 54
 
0.6%
41 2
 
< 0.1%

Length

2024-04-17T01:32:53.344191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:53.438918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4974
58.1%
na 3530
41.2%
침대수 54
 
0.6%
41 2
 
< 0.1%

hanshilcnt
Categorical

Distinct48
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
0
3753 
<NA>
1480 
2
 
328
10
 
310
3
 
266
Other values (43)
2423 

Length

Max length4
Median length1
Mean length1.6800234
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3753
43.8%
<NA> 1480
 
17.3%
2 328
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 262
 
3.1%
8 227
 
2.7%
4 201
 
2.3%
6 200
 
2.3%
9 197
 
2.3%
Other values (38) 1336
 
15.6%

Length

2024-04-17T01:32:53.537172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3753
43.8%
na 1480
 
17.3%
2 328
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 262
 
3.1%
8 227
 
2.7%
4 201
 
2.3%
6 200
 
2.3%
9 197
 
2.3%
Other values (38) 1336
 
15.6%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
0
4982 
<NA>
3524 
회수건조수
 
54

Length

Max length5
Median length1
Mean length2.2602804
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4982
58.2%
<NA> 3524
41.2%
회수건조수 54
 
0.6%

Length

2024-04-17T01:32:53.644865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:53.737998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4982
58.2%
na 3524
41.2%
회수건조수 54
 
0.6%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
<NA>
8321 
회의실별동시수용인원
 
147
0
 
92

Length

Max length10
Median length4
Mean length4.0707944
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> 8321
97.2%
회의실별동시수용인원 147
 
1.7%
0 92
 
1.1%

Length

2024-04-17T01:32:53.825602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:32:53.918514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8321
97.2%
회의실별동시수용인원 147
 
1.7%
0 92
 
1.1%
Distinct3
Distinct (%)< 0.1%
Missing6
Missing (%)0.1%
Memory size67.0 KiB
Minimum2022-01-01 05:09:03
Maximum2022-01-01 05:09:05
2024-04-17T01:32:53.995753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:32:54.092129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
0232500003250000-201-2017-0000203_11_03_PI2018-08-31 23:59:59.0<NA>(주)아이에이치엠 호텔포레 프리미어 남포지점600045부산광역시 중구 남포동5가 8-1번지48953.0부산광역시 중구 구덕로 54-1 (남포동5가)20170213<NA><NA><NA><NA>01영업385079.145433179894.98255720171123163559일반호텔051-123-1234<NA>임대<NA>162<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>14040<NA><NA><NA>0<NA><NA><NA>1070<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:03
1332500003250000-201-2014-0000103_11_03_PI2018-08-31 23:59:59.0<NA>호텔아벤트리부산600051부산광역시 중구 창선동1가 12-1번지48947.0부산광역시 중구 광복로39번길 6 (창선동1가)20140318<NA><NA><NA><NA>01영업385065.851535180046.79139420180727133623일반호텔051-123-1234<NA>자가<NA>84<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>8060<NA><NA><NA>0<NA><NA><NA>81<NA><NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:03
2432500003250000-214-2017-0000303_11_03_PI2018-08-31 23:59:59.0<NA>케이 칠구(K79)600092부산광역시 중구 대청동2가 23-3번지48948.0부산광역시 중구 광복로49번길 38 (대청동2가)20170731<NA><NA><NA><NA>01영업385140.157403180362.44609920180814140805숙박업(생활)051-123-1234<NA><NA><NA>51<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>3010<NA><NA><NA>0<NA><NA><NA>160<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:03
3532500003250000-201-1971-0011603_11_03_PI2018-08-31 23:59:59.0<NA>영하장600806부산광역시 중구 부평동2가 24-3번지48977.0부산광역시 중구 중구로23번길 34 (부평동2가)1971080720140310<NA><NA><NA>02폐업384736.73365180083.04251420121015144713여관업051-123-1234<NA>임대<NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>7<NA><NA><NA><NA>여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3<NA><NA>2022-01-01 05:09:03
4632500003250000-201-2012-0000503_11_03_PI2018-08-31 23:59:59.0<NA>누리게스트하우스 더셀프600012부산광역시 중구 중앙동2가 52-2번지48956.0부산광역시 중구 중앙대로49번길 13 (중앙동2가)2012112720121231<NA><NA><NA>02폐업385546.889042180289.00649820121127133856숙박업 기타051-123-1234<NA>임대<NA>50<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>2<NA>2<NA><NA><NA><NA>0<NA><NA><NA>5<NA><NA><NA>0숙박업 기타<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:03
5732500003250000-201-1988-0006903_11_03_PI2018-08-31 23:59:59.0<NA>야(Ya)600083부산광역시 중구 보수동3가 5-21번지48947.0부산광역시 중구 보수대로106번길 5 (보수동3가)1988012620171120<NA><NA><NA>02폐업384329.080801180631.27368220171120143429여관업051-123-1234<NA>임대<NA>00<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>10<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>020<NA>2022-01-01 05:09:03
6832500003250000-201-1970-0011603_11_03_PI2018-08-31 23:59:59.0<NA>세피아600071부산광역시 중구 부평동1가 41-7번지 ,848980.0부산광역시 중구 광복로12번길 7-5 (부평동1가, 41-7,8)19700828<NA><NA><NA><NA>01영업384788.862125179954.32496120180727110634여관업051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>16<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>020<NA>2022-01-01 05:09:03
7932500003250000-201-2007-0000203_11_03_PI2018-08-31 23:59:59.0<NA>식스나인모텔600046부산광역시 중구 남포동6가 29번지 (8~11층)48982.0부산광역시 중구 자갈치로 21 (남포동6가)20070712<NA><NA><NA><NA>01영업384804.909084179701.53297720180502092950여관업051-123-1234<NA>자가<NA>101<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>11080<NA><NA><NA>0<NA><NA><NA>25<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:03
81032500003250000-201-1971-0011703_11_03_PI2018-08-31 23:59:59.0<NA>동산장모텔600033부산광역시 중구 광복동3가 5-20번지48949.0부산광역시 중구 광복로67번길 30-22 (광복동3가)19710315<NA><NA><NA><NA>01영업385245.417649180087.31460420180727170224여관업051-123-1234<NA><NA><NA>30<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>4<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>080<NA>2022-01-01 05:09:03
91132500003250000-201-1972-0000303_11_03_PI2018-08-31 23:59:59.0<NA>주식회사 경원건설 호텔노아600045부산광역시 중구 남포동5가 81-1번지48983.0부산광역시 중구 자갈치로47번길 3-1 (남포동5가)19721010<NA><NA><NA><NA>01영업385043.08817179794.6106720171220145009관광호텔051-123-1234<NA>자가<NA>91<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9010<NA><NA><NA>0<NA><NA><NA>51<NA><NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>2022-01-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
85501302733600003360000-201-2021-0000103_11_03_PU2021-12-04 02:40:00.0숙박업신라스테이 서부산618200부산광역시 강서구 명지동 3595-1 신라스테이 서부산점46726부산광역시 강서구 명지국제7로 38, 신라스테이 서부산점 (명지동)20210331<NA><NA><NA><NA>영업/정상영업373665.73430842179173.52698928820211202090442관광호텔051 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>2022-01-01 05:09:05
85511302833300003330000-214-2021-0000203_11_03_PI2021-04-02 00:22:59.0숙박업벨리아(BELLIA)612847부산광역시 해운대구 중동 1123 해운대푸르지오시티48099부산광역시 해운대구 해운대해변로298번길 29, 해운대푸르지오시티 (중동)20210331<NA><NA><NA><NA>영업/정상영업397359.716406649186807.81129899520210331103454숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>3<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>22737<NA><NA><NA>0<NA><NA><NA>300<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:05
85521302933800003380000-214-2021-0000403_11_03_PU2021-12-19 02:40:00.0숙박업위더스오션613805부산광역시 수영구 광안동 201-1 광안 지웰에스테이트 더 테라스48303부산광역시 수영구 광남로94번길 16, 광안 지웰에스테이트 더 테라스 3~19층 305호 등 69개호 (광안동)20210406<NA><NA><NA><NA>영업/정상영업392691.625721388185474.22691274120211217161517숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>19030<NA><NA><NA>0<NA><NA><NA>340<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:05
85531303033300003330000-214-2021-0000303_11_03_PU2021-04-21 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504686720210419133601숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5<NA>1<NA><NA><NA><NA>0<NA><NA><NA>82<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:05
8554130313280000CDFI226221202100000103_11_04_PU2021-10-02 02:40:00.0외국인관광도시민박업윤슬가지번우편번호부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.397605613179078.07581929720210930170851업태구분명전화번호1건물소유구분명단독주택건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4545.45양실수여성종사자수YoonSeulgaGuesthouse for Foreign Tourists욕실수위생업태명200000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주택가주변1일반주거지역01침대수한실수회수건조수02022-01-01 05:09:05
85551303233300003330000-214-2021-0000303_11_03_PU2021-04-21 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504686720210419133601숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5<NA>1<NA><NA><NA><NA>0<NA><NA><NA>82<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:05
8556130333280000CDFI226221202100000103_11_04_PU2021-10-02 02:40:00.0외국인관광도시민박업윤슬가지번우편번호부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.397605613179078.07581929720210930170851업태구분명전화번호1건물소유구분명단독주택건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4545.45양실수여성종사자수YoonSeulgaGuesthouse for Foreign Tourists욕실수위생업태명200000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주택가주변1일반주거지역01침대수한실수회수건조수02022-01-01 05:09:05
8557130413330000CDFI226221201500002603_11_04_PI2021-05-26 00:22:56.0외국인관광도시민박업미포유<NA>부산광역시 해운대구 중동 946-1NaN부산광역시 해운대구 달맞이길62번길 9-1 (중동)20150813<NA><NA><NA><NA>영업/정상영업중397758.722800944186726.05991974820210524093757<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2022-01-01 05:09:05
85581304233800003380000-214-2021-0000603_11_03_PU2021-06-27 02:40:00.0숙박업제이스테이 펜트하우스613805부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210526<NA><NA><NA><NA>영업/정상영업392732.161638137185542.45270223420210625155820숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5050<NA><NA><NA>0<NA><NA><NA>40<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:05
8559130433380000CDFI226003202100000303_11_01_PU2021-06-24 02:40:00.0관광숙박업제이스테이 펜트하우스지번우편번호부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210525폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392732.161638137185542.45270223420210622151628업태구분명전화번호4건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명관광숙박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수219218.85양실수여성종사자수영문상호명영문상호주소욕실수위생업태명125000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수지역구분명지하층수총층수침대수한실수회수건조수회의실별동시수용인원2022-01-01 05:09:05

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnwhladdrdcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmlastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
3203330000CDFI226003201800000503_11_01_PU2019-04-14 02:40:00.0관광숙박업일로이리조트<NA>부산광역시 해운대구 송정동 809번지부산광역시 해운대구 송정구덕포길 130 (송정동)<NA><NA><NA><NA>영업/정상영업중20190412092534<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>관광숙박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>599598.73<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4주거지역<NA>4<NA><NA><NA><NA>2022-01-01 05:09:046
53250000CDFI226221201900000103_11_04_PU2021-05-05 02:40:00.0외국인관광도시민박업보수동방공호지번우편번호부산광역시 중구 보수동1가 116-156부산광역시 중구 책방골목길 13-11 (보수동1가)20210427휴업시작일자휴업종료일자재개업일자폐업폐업20210503101511업태구분명전화번호6건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수168167.82양실수여성종사자수영문상호명영문상호주소욕실수위생업태명자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수일반상업지역지하층수3침대수한실수회수건조수회의실별동시수용인원2022-01-01 05:09:053
63250000CDFI226221201900000203_11_04_PU2020-11-03 02:40:00.0외국인관광도시민박업제이온게스트하우스<NA>부산광역시 중구 부평동2가 21-8부산광역시 중구 중구로29번길 38, 4층 (부평동2가)<NA><NA><NA><NA>영업/정상영업중20201031173301<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3838.18<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2022-01-01 05:09:053
1032700003270000-201-2019-0000303_11_03_PU2021-06-20 02:40:00.0숙박업대구여관601829부산광역시 동구 초량동 388-2 지하1층, 지상1~3층, 4층 일부부산광역시 동구 중앙대로221번길 14-5 (초량동)<NA><NA><NA><NA>영업/정상영업20210618100954여관업051 467 5401<NA>자가<NA>41<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4111<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>060<NA>2022-01-01 05:09:053
1132700003270000-201-2019-0000503_11_03_PU2020-10-29 02:40:00.0숙박업단테하우스B601829부산광역시 동구 초량동 399부산광역시 동구 초량로13번길 58 (초량동)<NA><NA><NA><NA>영업/정상영업20201027175551여관업<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4010<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:053
133280000CDFI226221202000000103_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/정상영업중20211019153414<NA><NA>2<NA>아파트<NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>00<NA>4645.5<NA><NA><NA>ocean houseGuesthouse for Foreign Tourists<NA><NA><NA>10000000<NA><NA><NA><NA>0아파트지역20일반주거지역220<NA><NA><NA>02022-01-01 05:09:053
143280000CDFI226221202000000203_11_04_PU2021-10-21 02:40:00.0외국인관광도시민박업에메랄드 오션뷰지번우편번호부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1902호 (동삼동, 함지그린아파트)폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중20211019153331업태구분명전화번호1건물소유구분명아파트건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4645.5양실수여성종사자수Emerald ocean viewGuesthouse for Foreign Tourists욕실수위생업태명0제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0아파트지역20주거지역220침대수한실수회수건조수02022-01-01 05:09:053
153280000CDFI226221202000000303_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/정상영업중20211124114259<NA><NA>1<NA>단독주택<NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>00<NA>8080.1<NA><NA><NA>CheonghakSodamGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA>0주택가주변0일반주거지역01<NA><NA><NA>02022-01-01 05:09:053
1932900003290000-201-2019-0000203_11_03_PU2020-12-15 02:40:00.0숙박업엑스모텔614846부산광역시 부산진구 부전동 226-5부산광역시 부산진구 신천대로50번길 34, 6층~9층 (부전동)<NA><NA><NA><NA>영업/정상영업20201212162712일반호텔051 803 6996<NA><NA><NA>102<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9060<NA><NA><NA>0<NA><NA><NA>290<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:053
2032900003290000-201-2020-0000103_11_03_PU2020-12-15 02:40:00.0숙박업지지배614849부산광역시 부산진구 부전동 417-25부산광역시 부산진구 부전로 99-1, 3층 (부전동)<NA><NA><NA><NA>영업/정상영업20201212135845여관업051 806 7779<NA>자가<NA>41<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA>3<NA><NA><NA><NA>0<NA><NA><NA>60<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-01-01 05:09:053