Overview

Dataset statistics

Number of variables81
Number of observations8619
Missing cells34059
Missing cells (%)4.9%
Duplicate rows575
Duplicate rows (%)6.7%
Total size in memory5.3 MiB
Average record size in memory650.0 B

Variable types

Unsupported4
Numeric2
Text12
Categorical62
DateTime1

Alerts

Dataset has 575 (6.7%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (88.8%)Imbalance
updategbn is highly imbalanced (51.9%)Imbalance
opnsvcnm is highly imbalanced (68.3%)Imbalance
clgstdt is highly imbalanced (95.3%)Imbalance
clgenddt is highly imbalanced (95.3%)Imbalance
ropnymd is highly imbalanced (85.8%)Imbalance
dtlstatenm is highly imbalanced (53.4%)Imbalance
stroomcnt is highly imbalanced (92.4%)Imbalance
bdngsrvnm is highly imbalanced (90.4%)Imbalance
bdngunderflrcnt is highly imbalanced (54.5%)Imbalance
cnstyarea is highly imbalanced (94.4%)Imbalance
svnsr is highly imbalanced (85.8%)Imbalance
plninsurstdt is highly imbalanced (85.8%)Imbalance
plninsurenddt is highly imbalanced (85.8%)Imbalance
maneipcnt is highly imbalanced (80.2%)Imbalance
playutscntdtl is highly imbalanced (85.8%)Imbalance
playfacilcnt is highly imbalanced (60.4%)Imbalance
multusnupsoyn is highly imbalanced (90.0%)Imbalance
stagear is highly imbalanced (85.3%)Imbalance
culwrkrsenm is highly imbalanced (85.8%)Imbalance
culphyedcobnm is highly imbalanced (85.6%)Imbalance
geicpfacilen is highly imbalanced (85.8%)Imbalance
balhansilyn is highly imbalanced (89.3%)Imbalance
bcfacilen is highly imbalanced (85.8%)Imbalance
insurorgnm is highly imbalanced (96.0%)Imbalance
insurstdt is highly imbalanced (85.8%)Imbalance
insurenddt is highly imbalanced (85.8%)Imbalance
afc is highly imbalanced (85.8%)Imbalance
useunderendflr is highly imbalanced (61.9%)Imbalance
useunderstflr is highly imbalanced (62.6%)Imbalance
shpinfo is highly imbalanced (85.8%)Imbalance
shpcnt is highly imbalanced (85.3%)Imbalance
shptottons is highly imbalanced (85.3%)Imbalance
infoben is highly imbalanced (85.8%)Imbalance
wmeipcnt is highly imbalanced (78.7%)Imbalance
engstntrnmaddr is highly imbalanced (94.7%)Imbalance
yoksilcnt is highly imbalanced (77.0%)Imbalance
dispenen is highly imbalanced (85.8%)Imbalance
capt is highly imbalanced (93.5%)Imbalance
mnfactreartclcn is highly imbalanced (85.8%)Imbalance
cndpermstymd is highly imbalanced (85.8%)Imbalance
cndpermntwhy is highly imbalanced (85.8%)Imbalance
cndpermendymd is highly imbalanced (85.8%)Imbalance
chaircnt is highly imbalanced (65.4%)Imbalance
nearenvnm is highly imbalanced (91.4%)Imbalance
jisgnumlay is highly imbalanced (91.8%)Imbalance
regnsenm is highly imbalanced (89.4%)Imbalance
undernumlay is highly imbalanced (91.3%)Imbalance
totnumlay is highly imbalanced (91.6%)Imbalance
meetsamtimesygstf is highly imbalanced (85.3%)Imbalance
sitepostno has 334 (3.9%) missing valuesMissing
rdnwhladdr has 2551 (29.6%) missing valuesMissing
dcbymd has 4414 (51.2%) missing valuesMissing
x has 392 (4.5%) missing valuesMissing
y has 395 (4.6%) missing valuesMissing
sitetel has 297 (3.4%) missing valuesMissing
facilscp has 8147 (94.5%) missing valuesMissing
facilar has 8147 (94.5%) missing valuesMissing
yangsilcnt has 938 (10.9%) missing valuesMissing
engstntrnmnm has 8380 (97.2%) missing valuesMissing
skey 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 16:30:17.810170
Analysis finished2024-04-16 16:30:20.142939
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size67.5 KiB

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3319063.4
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.9 KiB
2024-04-17T01:30:20.184335image/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 deviation42893.518
Coefficient of variation (CV)0.01292338
Kurtosis-0.97711667
Mean3319063.4
Median Absolute Deviation (MAD)30000
Skewness0.2607515
Sum2.859705 × 1010
Variance1.8398539 × 109
MonotonicityNot monotonic
2024-04-17T01:30:20.280563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1195
13.9%
3290000 1062
12.3%
3300000 893
10.4%
3390000 689
 
8.0%
3270000 657
 
7.6%
3320000 578
 
6.7%
3380000 513
 
6.0%
3250000 487
 
5.7%
3260000 407
 
4.7%
3280000 387
 
4.5%
Other values (6) 1748
20.3%
ValueCountFrequency (%)
3250000 487
5.7%
3260000 407
 
4.7%
3270000 657
7.6%
3280000 387
 
4.5%
3290000 1062
12.3%
3300000 893
10.4%
3310000 285
 
3.3%
3320000 578
6.7%
3330000 1195
13.9%
3340000 363
 
4.2%
ValueCountFrequency (%)
3400000 220
 
2.6%
3390000 689
8.0%
3380000 513
6.0%
3370000 386
 
4.5%
3360000 140
 
1.6%
3350000 354
 
4.1%
3340000 363
 
4.2%
3330000 1195
13.9%
3320000 578
6.7%
3310000 285
 
3.3%

mgtno
Text

Distinct4297
Distinct (%)49.9%
Missing3
Missing (%)< 0.1%
Memory size67.5 KiB
2024-04-17T01:30:20.462858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.903435
Min length20

Characters and Unicode

Total characters188720
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

Unique198 ?
Unique (%)2.3%

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%
cdfi2262212017000001 11
 
0.1%
cdfi2262212015000002 11
 
0.1%
cdfi2260032021000001 11
 
0.1%
cdfi2262212016000001 11
 
0.1%
cdfi2262212020000001 10
 
0.1%
cdfi2262212016000002 10
 
0.1%
cdfi2262212017000002 9
 
0.1%
Other values (4287) 8504
98.7%
2024-04-17T01:30:20.764699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72685
38.5%
- 24600
 
13.0%
2 20516
 
10.9%
1 20305
 
10.8%
3 18397
 
9.7%
9 10166
 
5.4%
8 4992
 
2.6%
7 4882
 
2.6%
6 3774
 
2.0%
4 3674
 
1.9%
Other values (5) 4729
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 162456
86.1%
Dash Punctuation 24600
 
13.0%
Uppercase Letter 1664
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72685
44.7%
2 20516
 
12.6%
1 20305
 
12.5%
3 18397
 
11.3%
9 10166
 
6.3%
8 4992
 
3.1%
7 4882
 
3.0%
6 3774
 
2.3%
4 3674
 
2.3%
5 3065
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 416
25.0%
D 416
25.0%
F 416
25.0%
I 416
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24600
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 187056
99.1%
Latin 1664
 
0.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72685
38.9%
- 24600
 
13.2%
2 20516
 
11.0%
1 20305
 
10.9%
3 18397
 
9.8%
9 10166
 
5.4%
8 4992
 
2.7%
7 4882
 
2.6%
6 3774
 
2.0%
4 3674
 
2.0%
Latin
ValueCountFrequency (%)
C 416
25.0%
D 416
25.0%
F 416
25.0%
I 416
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 188720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72685
38.5%
- 24600
 
13.0%
2 20516
 
10.9%
1 20305
 
10.8%
3 18397
 
9.7%
9 10166
 
5.4%
8 4992
 
2.6%
7 4882
 
2.6%
6 3774
 
2.0%
4 3674
 
1.9%
Other values (5) 4729
 
2.5%

opnsvcid
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
03_11_03_P
8200 
03_11_04_P
 
299
03_11_01_P
 
101
03_11_05_P
 
9
03_11_02_P
 
3
Other values (3)
 
7

Length

Max length10
Median length10
Mean length9.9979116
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 8200
95.1%
03_11_04_P 299
 
3.5%
03_11_01_P 101
 
1.2%
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

2024-04-17T01:30:20.897772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:21.007290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8200
95.1%
03_11_04_p 299
 
3.5%
03_11_01_p 101
 
1.2%
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 size67.5 KiB
I
6730 
U
1886 
180000000
 
3

Length

Max length9
Median length1
Mean length1.0027845
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6730
78.1%
U 1886
 
21.9%
180000000 3
 
< 0.1%

Length

2024-04-17T01:30:21.122249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:21.211807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6730
78.1%
u 1886
 
21.9%
180000000 3
 
< 0.1%
Distinct425
Distinct (%)4.9%
Missing3
Missing (%)< 0.1%
Memory size67.5 KiB
Minimum2018-08-31 23:59:59
Maximum2022-05-29 02:40:00
2024-04-17T01:30:21.303770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:30:21.416362image/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 size67.5 KiB
<NA>
6611 
숙박업
1740 
외국인관광도시민박업
 
159
관광숙박업
 
101
자동차야영장업
 
3
Other values (3)
 
5

Length

Max length10
Median length4
Mean length3.9222648
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> 6611
76.7%
숙박업 1740
 
20.2%
외국인관광도시민박업 159
 
1.8%
관광숙박업 101
 
1.2%
자동차야영장업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

Length

2024-04-17T01:30:21.538589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:21.654311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6611
76.7%
숙박업 1740
 
20.2%
외국인관광도시민박업 159
 
1.8%
관광숙박업 101
 
1.2%
자동차야영장업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

bplcnm
Text

Distinct3500
Distinct (%)40.6%
Missing3
Missing (%)< 0.1%
Memory size67.5 KiB
2024-04-17T01:30:21.898061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length5.253598
Min length1

Characters and Unicode

Total characters45265
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

Unique366 ?
Unique (%)4.2%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 칠구(K79)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 266
 
2.6%
모텔 183
 
1.8%
게스트하우스 117
 
1.1%
여관 82
 
0.8%
hotel 71
 
0.7%
부산 51
 
0.5%
house 48
 
0.5%
해운대 41
 
0.4%
39
 
0.4%
여인숙 36
 
0.3%
Other values (3613) 9447
91.0%
2024-04-17T01:30:22.291043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2967
 
6.6%
2019
 
4.5%
1789
 
4.0%
1782
 
3.9%
1720
 
3.8%
1545
 
3.4%
1460
 
3.2%
1273
 
2.8%
783
 
1.7%
767
 
1.7%
Other values (643) 29160
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37791
83.5%
Uppercase Letter 2583
 
5.7%
Space Separator 1782
 
3.9%
Lowercase Letter 1318
 
2.9%
Open Punctuation 555
 
1.2%
Close Punctuation 555
 
1.2%
Decimal Number 516
 
1.1%
Other Punctuation 113
 
0.2%
Dash Punctuation 29
 
0.1%
Letter Number 11
 
< 0.1%
Other values (4) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2967
 
7.9%
2019
 
5.3%
1789
 
4.7%
1720
 
4.6%
1545
 
4.1%
1460
 
3.9%
1273
 
3.4%
783
 
2.1%
767
 
2.0%
622
 
1.6%
Other values (563) 22846
60.5%
Uppercase Letter
ValueCountFrequency (%)
E 269
 
10.4%
O 254
 
9.8%
H 236
 
9.1%
T 209
 
8.1%
S 165
 
6.4%
A 159
 
6.2%
L 158
 
6.1%
N 128
 
5.0%
B 109
 
4.2%
U 99
 
3.8%
Other values (16) 797
30.9%
Lowercase Letter
ValueCountFrequency (%)
e 210
15.9%
o 147
11.2%
a 111
8.4%
s 111
8.4%
n 105
 
8.0%
u 95
 
7.2%
t 94
 
7.1%
h 65
 
4.9%
i 58
 
4.4%
l 58
 
4.4%
Other values (16) 264
20.0%
Decimal Number
ValueCountFrequency (%)
2 130
25.2%
1 72
14.0%
7 60
11.6%
5 58
11.2%
9 55
10.7%
0 43
 
8.3%
6 33
 
6.4%
3 28
 
5.4%
4 27
 
5.2%
8 10
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 65
57.5%
& 27
23.9%
' 9
 
8.0%
, 7
 
6.2%
; 2
 
1.8%
2
 
1.8%
: 1
 
0.9%
Letter Number
ValueCountFrequency (%)
7
63.6%
4
36.4%
Math Symbol
ValueCountFrequency (%)
2
50.0%
+ 2
50.0%
Space Separator
ValueCountFrequency (%)
1782
100.0%
Open Punctuation
ValueCountFrequency (%)
( 555
100.0%
Close Punctuation
ValueCountFrequency (%)
) 555
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Other Symbol
ValueCountFrequency (%)
6
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37791
83.5%
Latin 3912
 
8.6%
Common 3556
 
7.9%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2967
 
7.9%
2019
 
5.3%
1789
 
4.7%
1720
 
4.6%
1545
 
4.1%
1460
 
3.9%
1273
 
3.4%
783
 
2.1%
767
 
2.0%
622
 
1.6%
Other values (560) 22846
60.5%
Latin
ValueCountFrequency (%)
E 269
 
6.9%
O 254
 
6.5%
H 236
 
6.0%
e 210
 
5.4%
T 209
 
5.3%
S 165
 
4.2%
A 159
 
4.1%
L 158
 
4.0%
o 147
 
3.8%
N 128
 
3.3%
Other values (44) 1977
50.5%
Common
ValueCountFrequency (%)
1782
50.1%
( 555
 
15.6%
) 555
 
15.6%
2 130
 
3.7%
1 72
 
2.0%
. 65
 
1.8%
7 60
 
1.7%
5 58
 
1.6%
9 55
 
1.5%
0 43
 
1.2%
Other values (15) 181
 
5.1%
Han
ValueCountFrequency (%)
3
50.0%
1
 
16.7%
1
 
16.7%
1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37785
83.5%
ASCII 7452
 
16.5%
Number Forms 11
 
< 0.1%
None 10
 
< 0.1%
CJK 6
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2967
 
7.9%
2019
 
5.3%
1789
 
4.7%
1720
 
4.6%
1545
 
4.1%
1460
 
3.9%
1273
 
3.4%
783
 
2.1%
767
 
2.0%
622
 
1.6%
Other values (559) 22840
60.4%
ASCII
ValueCountFrequency (%)
1782
23.9%
( 555
 
7.4%
) 555
 
7.4%
E 269
 
3.6%
O 254
 
3.4%
H 236
 
3.2%
e 210
 
2.8%
T 209
 
2.8%
S 165
 
2.2%
A 159
 
2.1%
Other values (64) 3058
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
50.0%
1
 
16.7%
1
 
16.7%
1
 
16.7%
Punctuation
ValueCountFrequency (%)
1
100.0%

sitepostno
Text

MISSING 

Distinct495
Distinct (%)6.0%
Missing334
Missing (%)3.9%
Memory size67.5 KiB
2024-04-17T01:30:22.580925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters49710
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 318
 
3.8%
616801 254
 
3.1%
612040 224
 
2.7%
612847 189
 
2.3%
607833 175
 
2.1%
601829 145
 
1.8%
617807 136
 
1.6%
613828 131
 
1.6%
607831 126
 
1.5%
607842 114
 
1.4%
Other values (485) 6473
78.1%
2024-04-17T01:30:23.215985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9912
19.9%
1 8115
16.3%
0 8068
16.2%
8 7965
16.0%
2 4348
8.7%
4 3481
 
7.0%
7 2613
 
5.3%
3 2465
 
5.0%
9 1420
 
2.9%
5 963
 
1.9%
Other values (5) 360
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49350
99.3%
Other Letter 360
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9912
20.1%
1 8115
16.4%
0 8068
16.3%
8 7965
16.1%
2 4348
8.8%
4 3481
 
7.1%
7 2613
 
5.3%
3 2465
 
5.0%
9 1420
 
2.9%
5 963
 
2.0%
Other Letter
ValueCountFrequency (%)
120
33.3%
60
16.7%
60
16.7%
60
16.7%
60
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 49350
99.3%
Hangul 360
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9912
20.1%
1 8115
16.4%
0 8068
16.3%
8 7965
16.1%
2 4348
8.8%
4 3481
 
7.1%
7 2613
 
5.3%
3 2465
 
5.0%
9 1420
 
2.9%
5 963
 
2.0%
Hangul
ValueCountFrequency (%)
120
33.3%
60
16.7%
60
16.7%
60
16.7%
60
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49350
99.3%
Hangul 360
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9912
20.1%
1 8115
16.4%
0 8068
16.3%
8 7965
16.1%
2 4348
8.8%
4 3481
 
7.1%
7 2613
 
5.3%
3 2465
 
5.0%
9 1420
 
2.9%
5 963
 
2.0%
Hangul
ValueCountFrequency (%)
120
33.3%
60
16.7%
60
16.7%
60
16.7%
60
16.7%
Distinct4180
Distinct (%)48.5%
Missing5
Missing (%)0.1%
Memory size67.5 KiB
2024-04-17T01:30:23.484905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length43
Mean length23.261899
Min length13

Characters and Unicode

Total characters200378
Distinct characters312
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

Unique292 ?
Unique (%)3.4%

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 8614
23.5%
해운대구 1195
 
3.3%
부산진구 1062
 
2.9%
동래구 893
 
2.4%
t통b반 868
 
2.4%
사상구 689
 
1.9%
동구 657
 
1.8%
온천동 644
 
1.8%
북구 582
 
1.6%
수영구 513
 
1.4%
Other values (4453) 20986
57.2%
2024-04-17T01:30:23.880684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36608
18.3%
10442
 
5.2%
10179
 
5.1%
10096
 
5.0%
8996
 
4.5%
8850
 
4.4%
1 8717
 
4.4%
8652
 
4.3%
8620
 
4.3%
- 7967
 
4.0%
Other values (302) 81251
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113204
56.5%
Decimal Number 40259
 
20.1%
Space Separator 36608
 
18.3%
Dash Punctuation 7967
 
4.0%
Uppercase Letter 1784
 
0.9%
Other Punctuation 194
 
0.1%
Close Punctuation 122
 
0.1%
Open Punctuation 122
 
0.1%
Math Symbol 117
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10442
 
9.2%
10179
 
9.0%
10096
 
8.9%
8996
 
7.9%
8850
 
7.8%
8652
 
7.6%
8620
 
7.6%
6950
 
6.1%
6725
 
5.9%
1651
 
1.5%
Other values (269) 32043
28.3%
Uppercase Letter
ValueCountFrequency (%)
B 876
49.1%
T 869
48.7%
A 11
 
0.6%
C 5
 
0.3%
K 5
 
0.3%
M 4
 
0.2%
O 3
 
0.2%
G 2
 
0.1%
E 2
 
0.1%
S 2
 
0.1%
Other values (4) 5
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 8717
21.7%
2 5288
13.1%
3 4238
10.5%
4 4102
10.2%
5 3963
9.8%
0 3088
 
7.7%
6 3061
 
7.6%
7 2866
 
7.1%
8 2598
 
6.5%
9 2338
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 191
98.5%
. 2
 
1.0%
& 1
 
0.5%
Space Separator
ValueCountFrequency (%)
36608
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7967
100.0%
Close Punctuation
ValueCountFrequency (%)
) 122
100.0%
Open Punctuation
ValueCountFrequency (%)
( 122
100.0%
Math Symbol
ValueCountFrequency (%)
~ 117
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113204
56.5%
Common 85389
42.6%
Latin 1785
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10442
 
9.2%
10179
 
9.0%
10096
 
8.9%
8996
 
7.9%
8850
 
7.8%
8652
 
7.6%
8620
 
7.6%
6950
 
6.1%
6725
 
5.9%
1651
 
1.5%
Other values (269) 32043
28.3%
Common
ValueCountFrequency (%)
36608
42.9%
1 8717
 
10.2%
- 7967
 
9.3%
2 5288
 
6.2%
3 4238
 
5.0%
4 4102
 
4.8%
5 3963
 
4.6%
0 3088
 
3.6%
6 3061
 
3.6%
7 2866
 
3.4%
Other values (8) 5491
 
6.4%
Latin
ValueCountFrequency (%)
B 876
49.1%
T 869
48.7%
A 11
 
0.6%
C 5
 
0.3%
K 5
 
0.3%
M 4
 
0.2%
O 3
 
0.2%
G 2
 
0.1%
E 2
 
0.1%
S 2
 
0.1%
Other values (5) 6
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113204
56.5%
ASCII 87173
43.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36608
42.0%
1 8717
 
10.0%
- 7967
 
9.1%
2 5288
 
6.1%
3 4238
 
4.9%
4 4102
 
4.7%
5 3963
 
4.5%
0 3088
 
3.5%
6 3061
 
3.5%
7 2866
 
3.3%
Other values (22) 7275
 
8.3%
Hangul
ValueCountFrequency (%)
10442
 
9.2%
10179
 
9.0%
10096
 
8.9%
8996
 
7.9%
8850
 
7.8%
8652
 
7.6%
8620
 
7.6%
6950
 
6.1%
6725
 
5.9%
1651
 
1.5%
Other values (269) 32043
28.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct625
Distinct (%)7.3%
Missing44
Missing (%)0.5%
Memory size67.5 KiB
2024-04-17T01:30:24.122595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0004665
Min length5

Characters and Unicode

Total characters42879
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)0.9%

Sample

1st row48953
2nd row48947
3rd row48948
4th row48977
5th row48956
ValueCountFrequency (%)
48947 2920
34.1%
48094 184
 
2.1%
48095 132
 
1.5%
49269 99
 
1.2%
48072 91
 
1.1%
48303 91
 
1.1%
48073 87
 
1.0%
48093 86
 
1.0%
48283 82
 
1.0%
48055 79
 
0.9%
Other values (615) 4724
55.1%
2024-04-17T01:30:24.516569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 12888
30.1%
8 6849
16.0%
7 6042
14.1%
9 5686
13.3%
0 2396
 
5.6%
2 2232
 
5.2%
6 2105
 
4.9%
5 1794
 
4.2%
3 1690
 
3.9%
1 1183
 
2.8%
Other values (7) 14
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42865
> 99.9%
Other Letter 14
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 12888
30.1%
8 6849
16.0%
7 6042
14.1%
9 5686
13.3%
0 2396
 
5.6%
2 2232
 
5.2%
6 2105
 
4.9%
5 1794
 
4.2%
3 1690
 
3.9%
1 1183
 
2.8%
Other Letter
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 42865
> 99.9%
Hangul 14
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 12888
30.1%
8 6849
16.0%
7 6042
14.1%
9 5686
13.3%
0 2396
 
5.6%
2 2232
 
5.2%
6 2105
 
4.9%
5 1794
 
4.2%
3 1690
 
3.9%
1 1183
 
2.8%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42865
> 99.9%
Hangul 14
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 12888
30.1%
8 6849
16.0%
7 6042
14.1%
9 5686
13.3%
0 2396
 
5.6%
2 2232
 
5.2%
6 2105
 
4.9%
5 1794
 
4.2%
3 1690
 
3.9%
1 1183
 
2.8%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

rdnwhladdr
Text

MISSING 

Distinct3101
Distinct (%)51.1%
Missing2551
Missing (%)29.6%
Memory size67.5 KiB
2024-04-17T01:30:24.778044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length66
Mean length27.93408
Min length18

Characters and Unicode

Total characters169504
Distinct characters368
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

Unique361 ?
Unique (%)5.9%

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 6068
 
19.1%
해운대구 977
 
3.1%
부산진구 728
 
2.3%
동래구 607
 
1.9%
사상구 516
 
1.6%
동구 491
 
1.5%
온천동 422
 
1.3%
수영구 411
 
1.3%
중구 397
 
1.2%
부전동 387
 
1.2%
Other values (2660) 20825
65.4%
2024-04-17T01:30:25.187098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25761
 
15.2%
7872
 
4.6%
7483
 
4.4%
7147
 
4.2%
6815
 
4.0%
6440
 
3.8%
1 6439
 
3.8%
6213
 
3.7%
6074
 
3.6%
( 5941
 
3.5%
Other values (358) 83319
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 100874
59.5%
Decimal Number 27434
 
16.2%
Space Separator 25761
 
15.2%
Open Punctuation 5941
 
3.5%
Close Punctuation 5941
 
3.5%
Dash Punctuation 1818
 
1.1%
Other Punctuation 1355
 
0.8%
Math Symbol 281
 
0.2%
Uppercase Letter 95
 
0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7872
 
7.8%
7483
 
7.4%
7147
 
7.1%
6815
 
6.8%
6440
 
6.4%
6213
 
6.2%
6074
 
6.0%
5775
 
5.7%
4028
 
4.0%
3777
 
3.7%
Other values (319) 39250
38.9%
Uppercase Letter
ValueCountFrequency (%)
A 31
32.6%
B 21
22.1%
K 8
 
8.4%
C 5
 
5.3%
O 5
 
5.3%
M 4
 
4.2%
E 3
 
3.2%
S 3
 
3.2%
U 2
 
2.1%
G 2
 
2.1%
Other values (9) 11
 
11.6%
Decimal Number
ValueCountFrequency (%)
1 6439
23.5%
2 4182
15.2%
3 3081
11.2%
4 2345
 
8.5%
5 2213
 
8.1%
0 1981
 
7.2%
6 1952
 
7.1%
7 1889
 
6.9%
9 1728
 
6.3%
8 1624
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 1345
99.3%
. 9
 
0.7%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
25761
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5941
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5941
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1818
100.0%
Math Symbol
ValueCountFrequency (%)
~ 281
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 100874
59.5%
Common 68531
40.4%
Latin 99
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7872
 
7.8%
7483
 
7.4%
7147
 
7.1%
6815
 
6.8%
6440
 
6.4%
6213
 
6.2%
6074
 
6.0%
5775
 
5.7%
4028
 
4.0%
3777
 
3.7%
Other values (319) 39250
38.9%
Latin
ValueCountFrequency (%)
A 31
31.3%
B 21
21.2%
K 8
 
8.1%
C 5
 
5.1%
O 5
 
5.1%
M 4
 
4.0%
3
 
3.0%
E 3
 
3.0%
S 3
 
3.0%
U 2
 
2.0%
Other values (11) 14
14.1%
Common
ValueCountFrequency (%)
25761
37.6%
1 6439
 
9.4%
( 5941
 
8.7%
) 5941
 
8.7%
2 4182
 
6.1%
3 3081
 
4.5%
4 2345
 
3.4%
5 2213
 
3.2%
0 1981
 
2.9%
6 1952
 
2.8%
Other values (8) 8695
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 100874
59.5%
ASCII 68627
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25761
37.5%
1 6439
 
9.4%
( 5941
 
8.7%
) 5941
 
8.7%
2 4182
 
6.1%
3 3081
 
4.5%
4 2345
 
3.4%
5 2213
 
3.2%
0 1981
 
2.9%
6 1952
 
2.8%
Other values (28) 8791
 
12.8%
Hangul
ValueCountFrequency (%)
7872
 
7.8%
7483
 
7.4%
7147
 
7.1%
6815
 
6.8%
6440
 
6.4%
6213
 
6.2%
6074
 
6.0%
5775
 
5.7%
4028
 
4.0%
3777
 
3.7%
Other values (319) 39250
38.9%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size67.5 KiB

dcbymd
Text

MISSING 

Distinct1446
Distinct (%)34.4%
Missing4414
Missing (%)51.2%
Memory size67.5 KiB
2024-04-17T01:30:25.434516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8478002
Min length4

Characters and Unicode

Total characters33000
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

Unique50 ?
Unique (%)1.2%

Sample

1st row20140310
2nd row20121231
3rd row20171120
4th row20220224
5th row20210823
ValueCountFrequency (%)
20041022 180
 
4.3%
폐업일자 160
 
3.8%
20030122 64
 
1.5%
20120711 52
 
1.2%
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 (1436) 3601
85.6%
2024-04-17T01:30:25.798964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10780
32.7%
2 7115
21.6%
1 5926
18.0%
3 1477
 
4.5%
9 1437
 
4.4%
7 1231
 
3.7%
4 1178
 
3.6%
6 1113
 
3.4%
5 1100
 
3.3%
8 1003
 
3.0%
Other values (4) 640
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32360
98.1%
Other Letter 640
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10780
33.3%
2 7115
22.0%
1 5926
18.3%
3 1477
 
4.6%
9 1437
 
4.4%
7 1231
 
3.8%
4 1178
 
3.6%
6 1113
 
3.4%
5 1100
 
3.4%
8 1003
 
3.1%
Other Letter
ValueCountFrequency (%)
160
25.0%
160
25.0%
160
25.0%
160
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32360
98.1%
Hangul 640
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10780
33.3%
2 7115
22.0%
1 5926
18.3%
3 1477
 
4.6%
9 1437
 
4.4%
7 1231
 
3.8%
4 1178
 
3.6%
6 1113
 
3.4%
5 1100
 
3.4%
8 1003
 
3.1%
Hangul
ValueCountFrequency (%)
160
25.0%
160
25.0%
160
25.0%
160
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32360
98.1%
Hangul 640
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10780
33.3%
2 7115
22.0%
1 5926
18.3%
3 1477
 
4.6%
9 1437
 
4.4%
7 1231
 
3.8%
4 1178
 
3.6%
6 1113
 
3.4%
5 1100
 
3.4%
8 1003
 
3.1%
Hangul
ValueCountFrequency (%)
160
25.0%
160
25.0%
160
25.0%
160
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8439 
휴업시작일자
 
170
20210916
 
2
20210528
 
2
20211129
 
1
Other values (5)
 
5

Length

Max length8
Median length4
Mean length4.0440886
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> 8439
97.9%
휴업시작일자 170
 
2.0%
20210916 2
 
< 0.1%
20210528 2
 
< 0.1%
20211129 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20220118 1
 
< 0.1%
20211031 1
 
< 0.1%

Length

2024-04-17T01:30:25.926676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:26.030919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8439
97.9%
휴업시작일자 170
 
2.0%
20210916 2
 
< 0.1%
20210528 2
 
< 0.1%
20211129 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20220118 1
 
< 0.1%
20211031 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8439 
휴업종료일자
 
170
20221130
 
2
20230131
 
2
20221128
 
1
Other values (5)
 
5

Length

Max length8
Median length4
Mean length4.0440886
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> 8439
97.9%
휴업종료일자 170
 
2.0%
20221130 2
 
< 0.1%
20230131 2
 
< 0.1%
20221128 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20220630 1
 
< 0.1%
20220131 1
 
< 0.1%

Length

2024-04-17T01:30:26.148166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:26.252697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8439
97.9%
휴업종료일자 170
 
2.0%
20221130 2
 
< 0.1%
20230131 2
 
< 0.1%
20221128 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20220630 1
 
< 0.1%
20220131 1
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
재개업일자
 
174

Length

Max length5
Median length4
Mean length4.020188
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> 8445
98.0%
재개업일자 174
 
2.0%

Length

2024-04-17T01:30:26.385138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:26.487506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
재개업일자 174
 
2.0%

trdstatenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
02
3707 
01
2756 
영업/정상
1712 
폐업
 
288
13
 
91
Other values (4)
 
65

Length

Max length5
Median length2
Mean length2.596821
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
02 3707
43.0%
01 2756
32.0%
영업/정상 1712
19.9%
폐업 288
 
3.3%
13 91
 
1.1%
03 53
 
0.6%
휴업 7
 
0.1%
<NA> 4
 
< 0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:30:26.596756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:26.709110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3707
43.0%
01 2756
32.0%
영업/정상 1712
19.9%
폐업 288
 
3.3%
13 91
 
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 size67.5 KiB
영업
4249 
폐업
4045 
영업중
 
311
휴업
 
10
<NA>
 
3

Length

Max length4
Median length2
Mean length2.0370113
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4249
49.3%
폐업 4045
46.9%
영업중 311
 
3.6%
휴업 10
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:30:26.824278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:26.925937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4249
49.3%
폐업 4045
46.9%
영업중 311
 
3.6%
휴업 10
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing392
Missing (%)4.5%
Memory size67.5 KiB

y
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing395
Missing (%)4.6%
Memory size67.5 KiB

lastmodts
Real number (ℝ)

Distinct3789
Distinct (%)44.0%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0138691 × 1013
Minimum1.9990211 × 1013
Maximum2.0220527 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.9 KiB
2024-04-17T01:30:27.069136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0020207 × 1013
Q12.0060809 × 1013
median2.0171127 × 1013
Q32.018081 × 1013
95-th percentile2.0220204 × 1013
Maximum2.0220527 × 1013
Range2.3031617 × 1011
Interquartile range (IQR)1.2000113 × 1011

Descriptive statistics

Standard deviation7.2219998 × 1010
Coefficient of variation (CV)0.0035861316
Kurtosis-0.99504957
Mean2.0138691 × 1013
Median Absolute Deviation (MAD)3.9680447 × 1010
Skewness-0.72090233
Sum1.7351496 × 1017
Variance5.215728 × 1021
MonotonicityNot monotonic
2024-04-17T01:30:27.187673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19990428000000 62
 
0.7%
19990920000000 60
 
0.7%
20040902000000 60
 
0.7%
20030122000000 58
 
0.7%
20040203000000 50
 
0.6%
20070531000000 36
 
0.4%
20030414000000 36
 
0.4%
20030329000000 32
 
0.4%
20020515000000 32
 
0.4%
20040427000000 32
 
0.4%
Other values (3779) 8158
94.7%
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 (%)
20220527173115 2
< 0.1%
20220527162744 2
< 0.1%
20220527152929 3
< 0.1%
20220527135101 2
< 0.1%
20220527111550 1
 
< 0.1%
20220525180346 1
 
< 0.1%
20220525170349 2
< 0.1%
20220525153538 2
< 0.1%
20220525141337 2
< 0.1%
20220525133133 2
< 0.1%

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
여관업
5219 
여인숙업
1076 
숙박업 기타
591 
숙박업(생활)
527 
일반호텔
 
500
Other values (4)
706 

Length

Max length8
Median length3
Mean length3.7260703
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5219
60.6%
여인숙업 1076
 
12.5%
숙박업 기타 591
 
6.9%
숙박업(생활) 527
 
6.1%
일반호텔 500
 
5.8%
<NA> 362
 
4.2%
관광호텔 276
 
3.2%
업태구분명 59
 
0.7%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:30:27.344736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:27.442298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5219
56.7%
여인숙업 1076
 
11.7%
숙박업 591
 
6.4%
기타 591
 
6.4%
숙박업(생활 527
 
5.7%
일반호텔 500
 
5.4%
na 362
 
3.9%
관광호텔 276
 
3.0%
업태구분명 59
 
0.6%
휴양콘도미니엄업 9
 
0.1%

sitetel
Text

MISSING 

Distinct787
Distinct (%)9.5%
Missing297
Missing (%)3.4%
Memory size67.5 KiB
2024-04-17T01:30:27.659504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.81615
Min length4

Characters and Unicode

Total characters98334
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

Unique71 ?
Unique (%)0.9%

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 6725
65.2%
051 1397
 
13.5%
전화번호 73
 
0.7%
070 24
 
0.2%
747 20
 
0.2%
746 18
 
0.2%
744 12
 
0.1%
806 11
 
0.1%
743 10
 
0.1%
728 10
 
0.1%
Other values (922) 2013
 
19.5%
2024-04-17T01:30:28.011763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22754
23.1%
2 14683
14.9%
3 14626
14.9%
- 13532
13.8%
0 9492
9.7%
5 9291
9.4%
4 7852
 
8.0%
2008
 
2.0%
7 1247
 
1.3%
8 999
 
1.0%
Other values (6) 1850
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82502
83.9%
Dash Punctuation 13532
 
13.8%
Space Separator 2008
 
2.0%
Other Letter 292
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22754
27.6%
2 14683
17.8%
3 14626
17.7%
0 9492
11.5%
5 9291
11.3%
4 7852
 
9.5%
7 1247
 
1.5%
8 999
 
1.2%
6 957
 
1.2%
9 601
 
0.7%
Other Letter
ValueCountFrequency (%)
73
25.0%
73
25.0%
73
25.0%
73
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 13532
100.0%
Space Separator
ValueCountFrequency (%)
2008
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98042
99.7%
Hangul 292
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22754
23.2%
2 14683
15.0%
3 14626
14.9%
- 13532
13.8%
0 9492
9.7%
5 9291
9.5%
4 7852
 
8.0%
2008
 
2.0%
7 1247
 
1.3%
8 999
 
1.0%
Other values (2) 1558
 
1.6%
Hangul
ValueCountFrequency (%)
73
25.0%
73
25.0%
73
25.0%
73
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98042
99.7%
Hangul 292
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22754
23.2%
2 14683
15.0%
3 14626
14.9%
- 13532
13.8%
0 9492
9.7%
5 9291
9.5%
4 7852
 
8.0%
2008
 
2.0%
7 1247
 
1.3%
8 999
 
1.0%
Other values (2) 1558
 
1.6%
Hangul
ValueCountFrequency (%)
73
25.0%
73
25.0%
73
25.0%
73
25.0%

stroomcnt
Categorical

IMBALANCE 

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8246 
객실수
 
127
1
 
71
2
 
54
3
 
26
Other values (32)
 
95

Length

Max length4
Median length4
Mean length3.9048614
Min length1

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> 8246
95.7%
객실수 127
 
1.5%
1 71
 
0.8%
2 54
 
0.6%
3 26
 
0.3%
0 17
 
0.2%
7 15
 
0.2%
4 8
 
0.1%
6 6
 
0.1%
5 6
 
0.1%
Other values (27) 43
 
0.5%

Length

2024-04-17T01:30:28.120146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8246
95.7%
객실수 127
 
1.5%
1 71
 
0.8%
2 54
 
0.6%
3 26
 
0.3%
0 17
 
0.2%
7 15
 
0.2%
4 8
 
0.1%
6 6
 
0.1%
5 6
 
0.1%
Other values (27) 43
 
0.5%

bdngownsenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
6526 
자가
1176 
임대
775 
건물소유구분명
 
142

Length

Max length7
Median length4
Mean length3.596705
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6526
75.7%
자가 1176
 
13.6%
임대 775
 
9.0%
건물소유구분명 142
 
1.6%

Length

2024-04-17T01:30:28.218439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:28.318917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6526
75.7%
자가 1176
 
13.6%
임대 775
 
9.0%
건물소유구분명 142
 
1.6%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8278 
건물용도명
 
143
단독주택
 
78
아파트
 
60
숙박시설
 
26
Other values (6)
 
34

Length

Max length15
Median length4
Mean length4.0160111
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> 8278
96.0%
건물용도명 143
 
1.7%
단독주택 78
 
0.9%
아파트 60
 
0.7%
숙박시설 26
 
0.3%
다세대주택 15
 
0.2%
연립주택 5
 
0.1%
호텔 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 주택(공동주택적용) 4
 
< 0.1%

Length

2024-04-17T01:30:28.438100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8278
96.0%
건물용도명 143
 
1.7%
단독주택 78
 
0.9%
아파트 60
 
0.7%
숙박시설 26
 
0.3%
다세대주택 15
 
0.2%
연립주택 5
 
0.1%
호텔 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 4
 
< 0.1%
Other values (2) 5
 
0.1%

bdngjisgflrcnt
Categorical

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
0
2553 
<NA>
1692 
4
874 
3
751 
5
603 
Other values (32)
2146 

Length

Max length6
Median length1
Mean length1.6692192
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2553
29.6%
<NA> 1692
19.6%
4 874
 
10.1%
3 751
 
8.7%
5 603
 
7.0%
2 425
 
4.9%
8 330
 
3.8%
6 309
 
3.6%
7 303
 
3.5%
9 201
 
2.3%
Other values (27) 578
 
6.7%

Length

2024-04-17T01:30:28.549662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2553
29.6%
na 1692
19.6%
4 874
 
10.1%
3 751
 
8.7%
5 603
 
7.0%
2 425
 
4.9%
8 330
 
3.8%
6 309
 
3.6%
7 303
 
3.5%
9 201
 
2.3%
Other values (27) 578
 
6.7%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
0
4467 
<NA>
2256 
1
1523 
2
 
200
건물지하층수
 
59
Other values (9)
 
114

Length

Max length6
Median length1
Mean length1.8201648
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4467
51.8%
<NA> 2256
26.2%
1 1523
 
17.7%
2 200
 
2.3%
건물지하층수 59
 
0.7%
4 36
 
0.4%
3 27
 
0.3%
5 24
 
0.3%
6 6
 
0.1%
8 6
 
0.1%
Other values (4) 15
 
0.2%

Length

2024-04-17T01:30:28.653462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4467
51.8%
na 2256
26.2%
1 1525
 
17.7%
2 200
 
2.3%
건물지하층수 59
 
0.7%
4 36
 
0.4%
3 27
 
0.3%
5 24
 
0.3%
6 6
 
0.1%
8 6
 
0.1%
Other values (3) 13
 
0.2%

cnstyarea
Categorical

IMBALANCE 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8337 
건축연면적
 
147
0
 
105
2282
 
3
20571
 
3
Other values (22)
 
24

Length

Max length5
Median length4
Mean length3.9788839
Min length1

Unique

Unique20 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8337
96.7%
건축연면적 147
 
1.7%
0 105
 
1.2%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
761 2
 
< 0.1%
451 2
 
< 0.1%
2606 1
 
< 0.1%
72 1
 
< 0.1%
39 1
 
< 0.1%
Other values (17) 17
 
0.2%

Length

2024-04-17T01:30:28.764611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8337
96.7%
건축연면적 147
 
1.7%
0 105
 
1.2%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
761 2
 
< 0.1%
451 2
 
< 0.1%
984 1
 
< 0.1%
2971 1
 
< 0.1%
870 1
 
< 0.1%
Other values (17) 17
 
0.2%

svnsr
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
기념품종류
 
174

Length

Max length5
Median length4
Mean length4.020188
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> 8445
98.0%
기념품종류 174
 
2.0%

Length

2024-04-17T01:30:28.864281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:28.949544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
기념품종류 174
 
2.0%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
기획여행보험시작일자
 
174

Length

Max length10
Median length4
Mean length4.1211277
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> 8445
98.0%
기획여행보험시작일자 174
 
2.0%

Length

2024-04-17T01:30:29.048709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:29.136123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
기획여행보험시작일자 174
 
2.0%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
기획여행보험종료일자
 
174

Length

Max length10
Median length4
Mean length4.1211277
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> 8445
98.0%
기획여행보험종료일자 174
 
2.0%

Length

2024-04-17T01:30:29.228844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:29.317450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
기획여행보험종료일자 174
 
2.0%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
7365 
0
1133 
남성종사자수
 
91
1
 
12
3
 
5
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.6164288
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> 7365
85.5%
0 1133
 
13.1%
남성종사자수 91
 
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

2024-04-17T01:30:29.420407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7365
85.5%
0 1133
 
13.1%
남성종사자수 91
 
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 size67.5 KiB
<NA>
8445 
놀이기구수내역
 
174

Length

Max length7
Median length4
Mean length4.0605639
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> 8445
98.0%
놀이기구수내역 174
 
2.0%

Length

2024-04-17T01:30:29.540646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:29.629913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
놀이기구수내역 174
 
2.0%

playfacilcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
N
6722 
<NA>
1635 
놀이시설수
 
138
0
 
121
Y
 
3

Length

Max length5
Median length1
Mean length1.6331361
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 6722
78.0%
<NA> 1635
 
19.0%
놀이시설수 138
 
1.6%
0 121
 
1.4%
Y 3
 
< 0.1%

Length

2024-04-17T01:30:29.724812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:29.816685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 6722
78.0%
na 1635
 
19.0%
놀이시설수 138
 
1.6%
0 121
 
1.4%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
N
8395 
<NA>
 
166
 
47
Y
 
11

Length

Max length4
Median length1
Mean length1.0577793
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8395
97.4%
<NA> 166
 
1.9%
47
 
0.5%
Y 11
 
0.1%

Length

2024-04-17T01:30:29.909052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:29.993769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8395
97.4%
na 166
 
1.9%
47
 
0.5%
y 11
 
0.1%

stagear
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8347 
무대면적
 
151
0
 
121

Length

Max length4
Median length4
Mean length3.9578837
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> 8347
96.8%
무대면적 151
 
1.8%
0 121
 
1.4%

Length

2024-04-17T01:30:30.107279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:30.209485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8347
96.8%
무대면적 151
 
1.8%
0 121
 
1.4%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
문화사업자구분명
 
174

Length

Max length8
Median length4
Mean length4.0807518
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> 8445
98.0%
문화사업자구분명 174
 
2.0%

Length

2024-04-17T01:30:30.305044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:30.391727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
문화사업자구분명 174
 
2.0%

culphyedcobnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8091 
외국인관광 도시민박업
 
296
문화체육업종명
 
115
관광숙박업
 
101
자동차야영장업
 
9
Other values (3)
 
7

Length

Max length11
Median length4
Mean length4.2962061
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> 8091
93.9%
외국인관광 도시민박업 296
 
3.4%
문화체육업종명 115
 
1.3%
관광숙박업 101
 
1.2%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%

Length

2024-04-17T01:30:30.495975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:30.604304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8091
90.8%
외국인관광 296
 
3.3%
도시민박업 296
 
3.3%
문화체육업종명 115
 
1.3%
관광숙박업 101
 
1.1%
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 size67.5 KiB
<NA>
8445 
 
174

Length

Max length4
Median length4
Mean length3.9394361
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> 8445
98.0%
174
 
2.0%

Length

2024-04-17T01:30:30.709617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:30.795036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
174
 
2.0%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
N
8382 
<NA>
 
166
 
47
Y
 
24

Length

Max length4
Median length1
Mean length1.0577793
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8382
97.3%
<NA> 166
 
1.9%
47
 
0.5%
Y 24
 
0.3%

Length

2024-04-17T01:30:30.890218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:31.265561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8382
97.3%
na 166
 
1.9%
47
 
0.5%
y 24
 
0.3%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
 
174

Length

Max length4
Median length4
Mean length3.9394361
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> 8445
98.0%
174
 
2.0%

Length

2024-04-17T01:30:31.368300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:31.459726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
174
 
2.0%

insurorgnm
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8420 
보험기관명
 
171
현대해상
 
3
야영장사고배상책임보험
 
2
DB 손해보험
 
2
Other values (20)
 
21

Length

Max length22
Median length4
Mean length4.0403759
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> 8420
97.7%
보험기관명 171
 
2.0%
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

2024-04-17T01:30:31.557578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8420
97.5%
보험기관명 171
 
2.0%
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 size67.5 KiB
<NA>
8445 
보험시작일자
 
174

Length

Max length6
Median length4
Mean length4.0403759
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> 8445
98.0%
보험시작일자 174
 
2.0%

Length

2024-04-17T01:30:31.667709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:31.754839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
보험시작일자 174
 
2.0%

insurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
보험종료일자
 
174

Length

Max length6
Median length4
Mean length4.0403759
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> 8445
98.0%
보험종료일자 174
 
2.0%

Length

2024-04-17T01:30:31.845166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:31.944319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
보험종료일자 174
 
2.0%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
부대시설내역
 
174

Length

Max length6
Median length4
Mean length4.0403759
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> 8445
98.0%
부대시설내역 174
 
2.0%

Length

2024-04-17T01:30:32.046247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:32.145134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
부대시설내역 174
 
2.0%

usejisgendflr
Categorical

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
2715 
0
1977 
4
766 
3
650 
5
481 
Other values (32)
2030 

Length

Max length6
Median length1
Mean length2.0216963
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2715
31.5%
0 1977
22.9%
4 766
 
8.9%
3 650
 
7.5%
5 481
 
5.6%
6 417
 
4.8%
2 391
 
4.5%
7 270
 
3.1%
8 261
 
3.0%
9 185
 
2.1%
Other values (27) 506
 
5.9%

Length

2024-04-17T01:30:32.234562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2715
31.5%
0 1977
22.9%
4 766
 
8.9%
3 650
 
7.5%
5 481
 
5.6%
6 417
 
4.8%
2 391
 
4.5%
7 270
 
3.1%
8 261
 
3.0%
9 185
 
2.1%
Other values (27) 506
 
5.9%

useunderendflr
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
0
4746 
<NA>
3594 
1
 
186
사용끝지하층
 
63
2
 
16
Other values (4)
 
14

Length

Max length6
Median length1
Mean length2.2876204
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4746
55.1%
<NA> 3594
41.7%
1 186
 
2.2%
사용끝지하층 63
 
0.7%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
19 1
 
< 0.1%

Length

2024-04-17T01:30:32.335614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:32.440031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4746
55.1%
na 3594
41.7%
1 186
 
2.2%
사용끝지하층 63
 
0.7%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
19 1
 
< 0.1%

usejisgstflr
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
0
2461 
1
1922 
<NA>
1887 
2
1009 
3
522 
Other values (16)
818 

Length

Max length7
Median length1
Mean length1.7059984
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2461
28.6%
1 1922
22.3%
<NA> 1887
21.9%
2 1009
11.7%
3 522
 
6.1%
4 319
 
3.7%
5 193
 
2.2%
6 77
 
0.9%
사용시작지상층 61
 
0.7%
7 61
 
0.7%
Other values (11) 107
 
1.2%

Length

2024-04-17T01:30:32.554757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2461
28.6%
1 1922
22.3%
na 1887
21.9%
2 1009
11.7%
3 522
 
6.1%
4 319
 
3.7%
5 193
 
2.2%
6 77
 
0.9%
사용시작지상층 61
 
0.7%
7 61
 
0.7%
Other values (11) 107
 
1.2%

useunderstflr
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
0
5683 
<NA>
2643 
1
 
219
사용시작지하층
 
61
4
 
8
Other values (3)
 
5

Length

Max length7
Median length1
Mean length1.9624086
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5683
65.9%
<NA> 2643
30.7%
1 219
 
2.5%
사용시작지하층 61
 
0.7%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:30:32.657434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:32.760274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5683
65.9%
na 2643
30.7%
1 219
 
2.5%
사용시작지하층 61
 
0.7%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

shpinfo
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
선박제원
 
174

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> 8445
98.0%
선박제원 174
 
2.0%

Length

2024-04-17T01:30:32.859972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:32.963833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
선박제원 174
 
2.0%

shpcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8347 
선박척수
 
151
0
 
121

Length

Max length4
Median length4
Mean length3.9578837
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> 8347
96.8%
선박척수 151
 
1.8%
0 121
 
1.4%

Length

2024-04-17T01:30:33.048394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:33.134204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8347
96.8%
선박척수 151
 
1.8%
0 121
 
1.4%

shptottons
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8347 
선박총톤수
 
151
0
 
121

Length

Max length5
Median length4
Mean length3.9754032
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> 8347
96.8%
선박총톤수 151
 
1.8%
0 121
 
1.4%

Length

2024-04-17T01:30:33.243006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:33.334421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8347
96.8%
선박총톤수 151
 
1.8%
0 121
 
1.4%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
0
5066 
<NA>
3494 
세탁기수
 
59

Length

Max length4
Median length1
Mean length2.2366864
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5066
58.8%
<NA> 3494
40.5%
세탁기수 59
 
0.7%

Length

2024-04-17T01:30:33.435701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:33.535877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5066
58.8%
na 3494
40.5%
세탁기수 59
 
0.7%

facilscp
Text

MISSING 

Distinct163
Distinct (%)34.5%
Missing8147
Missing (%)94.5%
Memory size67.5 KiB
2024-04-17T01:30:33.783869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.9152542
Min length1

Characters and Unicode

Total characters1376
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

Unique86 ?
Unique (%)18.2%

Sample

1st row시설규모
2nd row시설규모
3rd row시설규모
4th row시설규모
5th row시설규모
ValueCountFrequency (%)
시설규모 121
25.6%
0 27
 
5.7%
85 16
 
3.4%
46 7
 
1.5%
60 6
 
1.3%
67 6
 
1.3%
83 6
 
1.3%
599 6
 
1.3%
57 6
 
1.3%
62 5
 
1.1%
Other values (153) 266
56.4%
2024-04-17T01:30:34.172003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 131
9.5%
121
8.8%
121
8.8%
121
8.8%
121
8.8%
5 109
 
7.9%
0 95
 
6.9%
8 90
 
6.5%
6 90
 
6.5%
2 78
 
5.7%
Other values (4) 299
21.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 892
64.8%
Other Letter 484
35.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 131
14.7%
5 109
12.2%
0 95
10.7%
8 90
10.1%
6 90
10.1%
2 78
8.7%
4 77
8.6%
7 76
8.5%
3 73
8.2%
9 73
8.2%
Other Letter
ValueCountFrequency (%)
121
25.0%
121
25.0%
121
25.0%
121
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 892
64.8%
Hangul 484
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 131
14.7%
5 109
12.2%
0 95
10.7%
8 90
10.1%
6 90
10.1%
2 78
8.7%
4 77
8.6%
7 76
8.5%
3 73
8.2%
9 73
8.2%
Hangul
ValueCountFrequency (%)
121
25.0%
121
25.0%
121
25.0%
121
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 892
64.8%
Hangul 484
35.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 131
14.7%
5 109
12.2%
0 95
10.7%
8 90
10.1%
6 90
10.1%
2 78
8.7%
4 77
8.6%
7 76
8.5%
3 73
8.2%
9 73
8.2%
Hangul
ValueCountFrequency (%)
121
25.0%
121
25.0%
121
25.0%
121
25.0%

facilar
Text

MISSING 

Distinct244
Distinct (%)51.7%
Missing8147
Missing (%)94.5%
Memory size67.5 KiB
2024-04-17T01:30:34.488623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.6991525
Min length1

Characters and Unicode

Total characters2218
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

Unique191 ?
Unique (%)40.5%

Sample

1st row시설면적
2nd row시설면적
3rd row시설면적
4th row시설면적
5th row시설면적
ValueCountFrequency (%)
시설면적 121
25.6%
0 27
 
5.7%
598.73 6
 
1.3%
45.5 6
 
1.3%
218.85 4
 
0.8%
62.58 4
 
0.8%
83.36 3
 
0.6%
167.82 3
 
0.6%
392.02 3
 
0.6%
38.18 3
 
0.6%
Other values (234) 292
61.9%
2024-04-17T01:30:34.922651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 296
13.3%
1 177
 
8.0%
4 174
 
7.8%
8 171
 
7.7%
5 152
 
6.9%
6 139
 
6.3%
2 135
 
6.1%
3 134
 
6.0%
9 129
 
5.8%
121
 
5.5%
Other values (5) 590
26.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1438
64.8%
Other Letter 484
 
21.8%
Other Punctuation 296
 
13.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 177
12.3%
4 174
12.1%
8 171
11.9%
5 152
10.6%
6 139
9.7%
2 135
9.4%
3 134
9.3%
9 129
9.0%
7 117
8.1%
0 110
7.6%
Other Letter
ValueCountFrequency (%)
121
25.0%
121
25.0%
121
25.0%
121
25.0%
Other Punctuation
ValueCountFrequency (%)
. 296
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1734
78.2%
Hangul 484
 
21.8%

Most frequent character per script

Common
ValueCountFrequency (%)
. 296
17.1%
1 177
10.2%
4 174
10.0%
8 171
9.9%
5 152
8.8%
6 139
8.0%
2 135
7.8%
3 134
7.7%
9 129
7.4%
7 117
 
6.7%
Hangul
ValueCountFrequency (%)
121
25.0%
121
25.0%
121
25.0%
121
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1734
78.2%
Hangul 484
 
21.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 296
17.1%
1 177
10.2%
4 174
10.0%
8 171
9.9%
5 152
8.8%
6 139
8.0%
2 135
7.8%
3 134
7.7%
9 129
7.4%
7 117
 
6.7%
Hangul
ValueCountFrequency (%)
121
25.0%
121
25.0%
121
25.0%
121
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
 
174

Length

Max length4
Median length4
Mean length3.9394361
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> 8445
98.0%
174
 
2.0%

Length

2024-04-17T01:30:35.058537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:35.155972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
174
 
2.0%

yangsilcnt
Text

MISSING 

Distinct155
Distinct (%)2.0%
Missing938
Missing (%)10.9%
Memory size67.5 KiB
2024-04-17T01:30:35.337862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7427418
Min length1

Characters and Unicode

Total characters13386
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

Unique22 ?
Unique (%)0.3%

Sample

1st row107
2nd row81
3rd row16
4th row7
5th row5
ValueCountFrequency (%)
0 1045
 
13.6%
10 440
 
5.7%
18 370
 
4.8%
12 318
 
4.1%
14 316
 
4.1%
15 301
 
3.9%
13 248
 
3.2%
19 242
 
3.2%
16 222
 
2.9%
17 217
 
2.8%
Other values (145) 3962
51.6%
2024-04-17T01:30:35.632227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3449
25.8%
0 1934
14.4%
2 1894
14.1%
3 1365
 
10.2%
4 1055
 
7.9%
5 827
 
6.2%
8 816
 
6.1%
6 641
 
4.8%
9 624
 
4.7%
7 604
 
4.5%
Other values (3) 177
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13209
98.7%
Other Letter 177
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3449
26.1%
0 1934
14.6%
2 1894
14.3%
3 1365
 
10.3%
4 1055
 
8.0%
5 827
 
6.3%
8 816
 
6.2%
6 641
 
4.9%
9 624
 
4.7%
7 604
 
4.6%
Other Letter
ValueCountFrequency (%)
59
33.3%
59
33.3%
59
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13209
98.7%
Hangul 177
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3449
26.1%
0 1934
14.6%
2 1894
14.3%
3 1365
 
10.3%
4 1055
 
8.0%
5 827
 
6.3%
8 816
 
6.2%
6 641
 
4.9%
9 624
 
4.7%
7 604
 
4.6%
Hangul
ValueCountFrequency (%)
59
33.3%
59
33.3%
59
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13209
98.7%
Hangul 177
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3449
26.1%
0 1934
14.6%
2 1894
14.3%
3 1365
 
10.3%
4 1055
 
8.0%
5 827
 
6.3%
8 816
 
6.2%
6 641
 
4.9%
9 624
 
4.7%
7 604
 
4.6%
Hangul
ValueCountFrequency (%)
59
33.3%
59
33.3%
59
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
7367 
0
1139 
여성종사자수
 
91
2
 
6
1
 
6
Other values (4)
 
10

Length

Max length6
Median length4
Mean length3.617357
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> 7367
85.5%
0 1139
 
13.2%
여성종사자수 91
 
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

2024-04-17T01:30:35.747142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:35.868858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7367
85.5%
0 1139
 
13.2%
여성종사자수 91
 
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 

Distinct59
Distinct (%)24.7%
Missing8380
Missing (%)97.2%
Memory size67.5 KiB
2024-04-17T01:30:36.074039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length5
Mean length8.1841004
Min length4

Characters and Unicode

Total characters1956
Distinct characters60
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

Unique46 ?
Unique (%)19.2%

Sample

1st row영문상호명
2nd row영문상호명
3rd row영문상호명
4th row영문상호명
5th row영문상호명
ValueCountFrequency (%)
영문상호명 162
48.1%
house 31
 
9.2%
busan 9
 
2.7%
ocean 6
 
1.8%
hotel 6
 
1.8%
guest 5
 
1.5%
kim's 4
 
1.2%
in 4
 
1.2%
suyeong 3
 
0.9%
the 3
 
0.9%
Other values (75) 104
30.9%
2024-04-17T01:30:36.380091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
 
8.3%
162
 
8.3%
162
 
8.3%
162
 
8.3%
162
 
8.3%
e 109
 
5.6%
98
 
5.0%
o 87
 
4.4%
a 65
 
3.3%
n 64
 
3.3%
Other values (50) 723
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 810
41.4%
Lowercase Letter 693
35.4%
Uppercase Letter 329
16.8%
Space Separator 98
 
5.0%
Decimal Number 12
 
0.6%
Dash Punctuation 7
 
0.4%
Other Punctuation 7
 
0.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 40
12.2%
S 37
 
11.2%
E 31
 
9.4%
O 24
 
7.3%
U 22
 
6.7%
B 19
 
5.8%
A 17
 
5.2%
Y 17
 
5.2%
P 14
 
4.3%
N 13
 
4.0%
Other values (14) 95
28.9%
Lowercase Letter
ValueCountFrequency (%)
e 109
15.7%
o 87
12.6%
a 65
9.4%
n 64
 
9.2%
u 51
 
7.4%
s 43
 
6.2%
h 31
 
4.5%
t 29
 
4.2%
r 27
 
3.9%
i 27
 
3.9%
Other values (13) 160
23.1%
Other Letter
ValueCountFrequency (%)
162
20.0%
162
20.0%
162
20.0%
162
20.0%
162
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 (%)
98
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1022
52.2%
Hangul 810
41.4%
Common 124
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 109
 
10.7%
o 87
 
8.5%
a 65
 
6.4%
n 64
 
6.3%
u 51
 
5.0%
s 43
 
4.2%
H 40
 
3.9%
S 37
 
3.6%
E 31
 
3.0%
h 31
 
3.0%
Other values (37) 464
45.4%
Common
ValueCountFrequency (%)
98
79.0%
0 7
 
5.6%
- 7
 
5.6%
' 5
 
4.0%
2 3
 
2.4%
1 2
 
1.6%
& 1
 
0.8%
. 1
 
0.8%
Hangul
ValueCountFrequency (%)
162
20.0%
162
20.0%
162
20.0%
162
20.0%
162
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1146
58.6%
Hangul 810
41.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
162
20.0%
162
20.0%
162
20.0%
162
20.0%
162
20.0%
ASCII
ValueCountFrequency (%)
e 109
 
9.5%
98
 
8.6%
o 87
 
7.6%
a 65
 
5.7%
n 64
 
5.6%
u 51
 
4.5%
s 43
 
3.8%
H 40
 
3.5%
S 37
 
3.2%
E 31
 
2.7%
Other values (45) 521
45.5%

engstntrnmaddr
Categorical

IMBALANCE 

Distinct22
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8383 
영문상호주소
 
162
Guesthouse for Foreign Tourists
 
23
Foreigner Tourism City home-stay Business
 
14
Guesthouse for Foregin Tourists
 
5
Other values (17)
 
32

Length

Max length41
Median length4
Mean length4.2675484
Min length4

Unique

Unique9 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8383
97.3%
영문상호주소 162
 
1.9%
Guesthouse for Foreign Tourists 23
 
0.3%
Foreigner Tourism City home-stay Business 14
 
0.2%
Guesthouse for Foregin Tourists 5
 
0.1%
Guest House 4
 
< 0.1%
Entertainment Business for foreigner only 3
 
< 0.1%
Foreign tourist city guest house 3
 
< 0.1%
Oversea Travel Business 3
 
< 0.1%
TOURIST ACCOMMODATION 3
 
< 0.1%
Other values (12) 16
 
0.2%

Length

2024-04-17T01:30:36.504382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8383
94.9%
영문상호주소 162
 
1.8%
for 35
 
0.4%
foreign 32
 
0.4%
guesthouse 31
 
0.4%
tourists 31
 
0.4%
business 22
 
0.2%
foreigner 19
 
0.2%
city 17
 
0.2%
home-stay 15
 
0.2%
Other values (19) 85
 
1.0%

yoksilcnt
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
0
5910 
<NA>
2462 
욕실수
 
59
15
 
16
12
 
14
Other values (28)
 
158

Length

Max length4
Median length1
Mean length1.8898944
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5910
68.6%
<NA> 2462
28.6%
욕실수 59
 
0.7%
15 16
 
0.2%
12 14
 
0.2%
18 12
 
0.1%
10 12
 
0.1%
14 10
 
0.1%
22 10
 
0.1%
9 10
 
0.1%
Other values (23) 104
 
1.2%

Length

2024-04-17T01:30:36.638734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 5910
68.6%
na 2462
28.6%
욕실수 59
 
0.7%
15 16
 
0.2%
12 14
 
0.2%
18 12
 
0.1%
10 12
 
0.1%
14 10
 
0.1%
9 10
 
0.1%
8 10
 
0.1%
Other values (23) 104
 
1.2%

sntuptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
여관업
5219 
여인숙업
1076 
숙박업 기타
591 
숙박업(생활)
527 
일반호텔
 
500
Other values (4)
706 

Length

Max length8
Median length3
Mean length3.7260703
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5219
60.6%
여인숙업 1076
 
12.5%
숙박업 기타 591
 
6.9%
숙박업(생활) 527
 
6.1%
일반호텔 500
 
5.8%
<NA> 362
 
4.2%
관광호텔 276
 
3.2%
위생업태명 59
 
0.7%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:30:36.748308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:36.847348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5219
56.7%
여인숙업 1076
 
11.7%
숙박업 591
 
6.4%
기타 591
 
6.4%
숙박업(생활 527
 
5.7%
일반호텔 500
 
5.4%
na 362
 
3.9%
관광호텔 276
 
3.0%
위생업태명 59
 
0.6%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
 
174

Length

Max length4
Median length4
Mean length3.9394361
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> 8445
98.0%
174
 
2.0%

Length

2024-04-17T01:30:36.963052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:37.056247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
174
 
2.0%

capt
Categorical

IMBALANCE 

Distinct48
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8281 
자본금
 
135
0
 
88
10000000
 
20
100000000
 
12
Other values (43)
 
83

Length

Max length10
Median length4
Mean length4.0124144
Min length1

Unique

Unique27 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8281
96.1%
자본금 135
 
1.6%
0 88
 
1.0%
10000000 20
 
0.2%
100000000 12
 
0.1%
50000000 8
 
0.1%
200000000 7
 
0.1%
20000000 5
 
0.1%
150000000 4
 
< 0.1%
5000000 4
 
< 0.1%
Other values (38) 55
 
0.6%

Length

2024-04-17T01:30:37.142136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8281
96.1%
자본금 135
 
1.6%
0 88
 
1.0%
10000000 20
 
0.2%
100000000 12
 
0.1%
50000000 8
 
0.1%
200000000 7
 
0.1%
20000000 5
 
0.1%
300000000 4
 
< 0.1%
5000000 4
 
< 0.1%
Other values (38) 55
 
0.6%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
제작취급품목내용
 
174

Length

Max length8
Median length4
Mean length4.0807518
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> 8445
98.0%
제작취급품목내용 174
 
2.0%

Length

2024-04-17T01:30:37.240594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:37.343035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
제작취급품목내용 174
 
2.0%

cndpermstymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
조건부허가시작일자
 
174

Length

Max length9
Median length4
Mean length4.1009398
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> 8445
98.0%
조건부허가시작일자 174
 
2.0%

Length

2024-04-17T01:30:37.432776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:37.516363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
조건부허가시작일자 174
 
2.0%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
조건부허가신고사유
 
174

Length

Max length9
Median length4
Mean length4.1009398
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> 8445
98.0%
조건부허가신고사유 174
 
2.0%

Length

2024-04-17T01:30:37.610250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:37.694794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
조건부허가신고사유 174
 
2.0%

cndpermendymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8445 
조건부허가종료일자
 
174

Length

Max length9
Median length4
Mean length4.1009398
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> 8445
98.0%
조건부허가종료일자 174
 
2.0%

Length

2024-04-17T01:30:37.780730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:37.858891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8445
98.0%
조건부허가종료일자 174
 
2.0%

chaircnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
4583 
0
3995 
좌석수
 
36
6
 
1
12
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length2.6036663
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4583
53.2%
0 3995
46.4%
좌석수 36
 
0.4%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-17T01:30:37.948360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:38.042949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4583
53.2%
0 3995
46.4%
좌석수 36
 
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 size67.5 KiB
<NA>
8349 
주변환경명
 
155
주택가주변
 
40
아파트지역
 
32
기타
 
26
Other values (3)
 
17

Length

Max length8
Median length4
Mean length4.0281935
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> 8349
96.9%
주변환경명 155
 
1.8%
주택가주변 40
 
0.5%
아파트지역 32
 
0.4%
기타 26
 
0.3%
학교정화(상대) 14
 
0.2%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-17T01:30:38.153025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:38.255548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8349
96.9%
주변환경명 155
 
1.8%
주택가주변 40
 
0.5%
아파트지역 32
 
0.4%
기타 26
 
0.3%
학교정화(상대 14
 
0.2%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대 1
 
< 0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8250 
지상층수
 
136
0
 
71
2
 
36
4
 
19
Other values (23)
 
107

Length

Max length4
Median length4
Mean length3.9240051
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> 8250
95.7%
지상층수 136
 
1.6%
0 71
 
0.8%
2 36
 
0.4%
4 19
 
0.2%
1 16
 
0.2%
3 15
 
0.2%
5 11
 
0.1%
6 8
 
0.1%
20 7
 
0.1%
Other values (18) 50
 
0.6%

Length

2024-04-17T01:30:38.365584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8250
95.7%
지상층수 136
 
1.6%
0 71
 
0.8%
2 36
 
0.4%
4 19
 
0.2%
1 16
 
0.2%
3 15
 
0.2%
5 11
 
0.1%
6 8
 
0.1%
20 7
 
0.1%
Other values (18) 50
 
0.6%

regnsenm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8232 
지역구분명
 
134
일반주거지역
 
125
일반상업지역
 
46
준주거지역
 
34
Other values (6)
 
48

Length

Max length6
Median length4
Mean length4.0607959
Min length4

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> 8232
95.5%
지역구분명 134
 
1.6%
일반주거지역 125
 
1.5%
일반상업지역 46
 
0.5%
준주거지역 34
 
0.4%
주거지역 31
 
0.4%
자연녹지지역 6
 
0.1%
상업지역 6
 
0.1%
녹지지역 3
 
< 0.1%
관리지역 1
 
< 0.1%

Length

2024-04-17T01:30:38.468250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8232
95.5%
지역구분명 134
 
1.6%
일반주거지역 125
 
1.5%
일반상업지역 46
 
0.5%
준주거지역 34
 
0.4%
주거지역 31
 
0.4%
자연녹지지역 6
 
0.1%
상업지역 6
 
0.1%
녹지지역 3
 
< 0.1%
관리지역 1
 
< 0.1%

undernumlay
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8309 
지하층수
 
142
0
 
108
1
 
31
2
 
22
Other values (5)
 
7

Length

Max length4
Median length4
Mean length3.9415245
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> 8309
96.4%
지하층수 142
 
1.6%
0 108
 
1.3%
1 31
 
0.4%
2 22
 
0.3%
3 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:30:38.569093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:38.668864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8309
96.4%
지하층수 142
 
1.6%
0 108
 
1.3%
1 31
 
0.4%
2 22
 
0.3%
3 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%

totnumlay
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8244 
총층수
 
133
0
 
55
2
 
44
1
 
23
Other values (23)
 
120

Length

Max length4
Median length4
Mean length3.9054415
Min length1

Unique

Unique8 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8244
95.6%
총층수 133
 
1.5%
0 55
 
0.6%
2 44
 
0.5%
1 23
 
0.3%
4 21
 
0.2%
3 19
 
0.2%
5 16
 
0.2%
6 9
 
0.1%
20 7
 
0.1%
Other values (18) 48
 
0.6%

Length

2024-04-17T01:30:38.774503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8244
95.6%
총층수 133
 
1.5%
0 55
 
0.6%
2 44
 
0.5%
1 23
 
0.3%
4 21
 
0.2%
3 19
 
0.2%
5 16
 
0.2%
6 9
 
0.1%
20 7
 
0.1%
Other values (18) 48
 
0.6%

abedcnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
0
5022 
<NA>
3536 
침대수
 
59
41
 
2

Length

Max length4
Median length1
Mean length2.244692
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5022
58.3%
<NA> 3536
41.0%
침대수 59
 
0.7%
41 2
 
< 0.1%

Length

2024-04-17T01:30:38.871147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:38.958811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5022
58.3%
na 3536
41.0%
침대수 59
 
0.7%
41 2
 
< 0.1%

hanshilcnt
Categorical

Distinct49
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
0
3792 
<NA>
1492 
2
 
327
10
 
310
3
 
266
Other values (44)
2432 

Length

Max length4
Median length1
Mean length1.6809375
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3792
44.0%
<NA> 1492
 
17.3%
2 327
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 264
 
3.1%
8 227
 
2.6%
4 201
 
2.3%
6 200
 
2.3%
9 197
 
2.3%
Other values (39) 1343
 
15.6%

Length

2024-04-17T01:30:39.327535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3792
44.0%
na 1492
 
17.3%
2 327
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 264
 
3.1%
8 227
 
2.6%
4 201
 
2.3%
6 200
 
2.3%
9 197
 
2.3%
Other values (39) 1343
 
15.6%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
0
5030 
<NA>
3530 
회수건조수
 
59

Length

Max length5
Median length1
Mean length2.2560622
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5030
58.4%
<NA> 3530
41.0%
회수건조수 59
 
0.7%

Length

2024-04-17T01:30:39.459582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:39.553624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5030
58.4%
na 3530
41.0%
회수건조수 59
 
0.7%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
<NA>
8347 
회의실별동시수용인원
 
151
0
 
121

Length

Max length10
Median length4
Mean length4.0630003
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> 8347
96.8%
회의실별동시수용인원 151
 
1.8%
0 121
 
1.4%

Length

2024-04-17T01:30:39.646212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:39.753311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8347
96.8%
회의실별동시수용인원 151
 
1.8%
0 121
 
1.4%

last_load_dttm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.5 KiB
2022-06-01 05:09:04
5058 
2022-06-01 05:09:03
2851 
2022-06-01 05:09:05
704 
<NA>
 
6

Length

Max length19
Median length19
Mean length18.989558
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-06-01 05:09:03
2nd row2022-06-01 05:09:03
3rd row2022-06-01 05:09:03
4th row2022-06-01 05:09:03
5th row2022-06-01 05:09:03

Common Values

ValueCountFrequency (%)
2022-06-01 05:09:04 5058
58.7%
2022-06-01 05:09:03 2851
33.1%
2022-06-01 05:09:05 704
 
8.2%
<NA> 6
 
0.1%

Length

2024-04-17T01:30:39.857589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:30:39.948318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-06-01 8613
50.0%
05:09:04 5058
29.4%
05:09:03 2851
 
16.5%
05:09:05 704
 
4.1%
na 6
 
< 0.1%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
0232500003250000-201-2017-0000203_11_03_PI2018-08-31 23:59:59.0<NA>(주)아이에이치엠 호텔포레 프리미어 남포지점600045부산광역시 중구 남포동5가 8-1번지48953부산광역시 중구 구덕로 54-1 (남포동5가)20170213<NA><NA><NA><NA>01영업385079.145433179894.98255720171123163559일반호텔051-123-1234<NA>임대<NA>162<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>14040<NA><NA><NA>0<NA><NA><NA>1070<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-06-01 05:09:03
1332500003250000-201-2014-0000103_11_03_PI2018-08-31 23:59:59.0<NA>호텔아벤트리부산600051부산광역시 중구 창선동1가 12-1번지48947부산광역시 중구 광복로39번길 6 (창선동1가)20140318<NA><NA><NA><NA>01영업385065.851535180046.79139420180727133623일반호텔051-123-1234<NA>자가<NA>84<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>8060<NA><NA><NA>0<NA><NA><NA>81<NA><NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-06-01 05:09:03
2432500003250000-214-2017-0000303_11_03_PI2018-08-31 23:59:59.0<NA>케이 칠구(K79)600092부산광역시 중구 대청동2가 23-3번지48948부산광역시 중구 광복로49번길 38 (대청동2가)20170731<NA><NA><NA><NA>01영업385140.157403180362.44609920180814140805숙박업(생활)051-123-1234<NA><NA><NA>51<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>3010<NA><NA><NA>0<NA><NA><NA>160<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-06-01 05:09:03
3532500003250000-201-1971-0011603_11_03_PI2018-08-31 23:59:59.0<NA>영하장600806부산광역시 중구 부평동2가 24-3번지48977부산광역시 중구 중구로23번길 34 (부평동2가)1971080720140310<NA><NA><NA>02폐업384736.73365180083.04251420121015144713여관업051-123-1234<NA>임대<NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>7<NA><NA><NA><NA>여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3<NA><NA>2022-06-01 05:09:03
4632500003250000-201-2012-0000503_11_03_PI2018-08-31 23:59:59.0<NA>누리게스트하우스 더셀프600012부산광역시 중구 중앙동2가 52-2번지48956부산광역시 중구 중앙대로49번길 13 (중앙동2가)2012112720121231<NA><NA><NA>02폐업385546.889042180289.00649820121127133856숙박업 기타051-123-1234<NA>임대<NA>50<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>2<NA>2<NA><NA><NA><NA>0<NA><NA><NA>5<NA><NA><NA>0숙박업 기타<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-06-01 05:09:03
5732500003250000-201-1988-0006903_11_03_PI2018-08-31 23:59:59.0<NA>야(Ya)600083부산광역시 중구 보수동3가 5-21번지48947부산광역시 중구 보수대로106번길 5 (보수동3가)1988012620171120<NA><NA><NA>02폐업384329.080801180631.27368220171120143429여관업051-123-1234<NA>임대<NA>00<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>10<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>020<NA>2022-06-01 05:09:03
6832500003250000-201-1970-0011603_11_03_PI2018-08-31 23:59:59.0<NA>세피아600071부산광역시 중구 부평동1가 41-7번지 ,848980부산광역시 중구 광복로12번길 7-5 (부평동1가, 41-7,8)19700828<NA><NA><NA><NA>01영업384788.862125179954.32496120180727110634여관업051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>16<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>020<NA>2022-06-01 05:09:03
7932500003250000-201-2007-0000203_11_03_PI2018-08-31 23:59:59.0<NA>식스나인모텔600046부산광역시 중구 남포동6가 29번지 (8~11층)48982부산광역시 중구 자갈치로 21 (남포동6가)20070712<NA><NA><NA><NA>01영업384804.909084179701.53297720180502092950여관업051-123-1234<NA>자가<NA>101<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>11080<NA><NA><NA>0<NA><NA><NA>25<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-06-01 05:09:03
81032500003250000-201-1971-0011703_11_03_PI2018-08-31 23:59:59.0<NA>동산장모텔600033부산광역시 중구 광복동3가 5-20번지48949부산광역시 중구 광복로67번길 30-22 (광복동3가)19710315<NA><NA><NA><NA>01영업385245.417649180087.31460420180727170224여관업051-123-1234<NA><NA><NA>30<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>4<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>080<NA>2022-06-01 05:09:03
91132500003250000-201-1972-0000303_11_03_PU2022-02-25 02:40:00.0숙박업주식회사 경원건설 호텔노아600045부산광역시 중구 남포동5가 81-148983부산광역시 중구 자갈치로47번길 3-1 (남포동5가)19721010<NA><NA><NA><NA>영업/정상영업384966.283935179482.33662320220223180238관광호텔051 2464361<NA>자가<NA>91<NA><NA><NA><NA><NA><NA><NA>N<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>2022-06-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
86091302733600003360000-201-2021-0000103_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>2022-06-01 05:09:05
86101302833300003330000-214-2021-0000203_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>2022-06-01 05:09:05
86111302933800003380000-214-2021-0000403_11_03_PU2022-05-28 02:40:00.0숙박업위더스오션613805부산광역시 수영구 광안동 201-1 광안 지웰에스테이트 더 테라스48303부산광역시 수영구 광남로94번길 16, 광안 지웰에스테이트 더 테라스 3~19층 301호 등 70개소 (광안동)20210406<NA><NA><NA><NA>영업/정상영업392691.625721388185474.22691274120220525180346숙박업(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>700<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-06-01 05:09:05
86121303033300003330000-214-2021-0000303_11_03_PU2022-01-11 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504686720220109123120숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5010<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>2022-06-01 05:09:05
8613130313280000CDFI226221202100000103_11_04_PU2022-01-06 02:40:00.0외국인관광도시민박업윤슬가지번우편번호부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.397605613179078.07581929720220104140052업태구분명전화번호1건물소유구분명단독주택건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4545.45양실수여성종사자수YoonSeulgaGuesthouse for Foreign Tourists욕실수위생업태명200000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주택가주변1일반주거지역01침대수한실수회수건조수02022-06-01 05:09:05
86141303233300003330000-214-2021-0000303_11_03_PU2022-01-11 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504686720220109123120숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5010<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>2022-06-01 05:09:05
8615130333280000CDFI226221202100000103_11_04_PU2022-01-06 02:40:00.0외국인관광도시민박업윤슬가지번우편번호부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.397605613179078.07581929720220104140052업태구분명전화번호1건물소유구분명단독주택건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4545.45양실수여성종사자수YoonSeulgaGuesthouse for Foreign Tourists욕실수위생업태명200000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주택가주변1일반주거지역01침대수한실수회수건조수02022-06-01 05:09:05
8616130413330000CDFI226221201500002603_11_04_PI2021-05-26 00:22:56.0외국인관광도시민박업미포유<NA>부산광역시 해운대구 중동 946-1<NA>부산광역시 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>2022-06-01 05:09:05
86171304233800003380000-214-2021-0000603_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>2022-06-01 05:09:05
8618130433380000CDFI226003202100000303_11_01_PU2021-06-24 02:40:00.0관광숙박업제이스테이 펜트하우스지번우편번호부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210525폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392732.161638137185542.45270223420210622151628업태구분명전화번호4건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명관광숙박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수219218.85양실수여성종사자수영문상호명영문상호주소욕실수위생업태명125000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수지역구분명지하층수총층수침대수한실수회수건조수회의실별동시수용인원2022-06-01 05:09:05

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrdcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmlastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
383330000CDFI226003201800000503_11_01_PU2022-05-06 02:40:00.0관광숙박업일로이풀빌라<NA>부산광역시 해운대구 송정동 80948073부산광역시 해운대구 송정구덕포길 130 (송정동)<NA><NA><NA><NA>영업/정상영업중20220504133213<NA>051-704-78887<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>관광숙박업<NA><NA><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>2022-06-01 05:09:046
53250000CDFI226221201900000103_11_04_PU2021-05-05 02:40:00.0외국인관광도시민박업보수동방공호지번우편번호부산광역시 중구 보수동1가 116-15648967부산광역시 중구 책방골목길 13-11 (보수동1가)20210427휴업시작일자휴업종료일자재개업일자폐업폐업20210503101511업태구분명전화번호6건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수168167.82양실수여성종사자수영문상호명영문상호주소욕실수위생업태명자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수일반상업지역지하층수3침대수한실수회수건조수회의실별동시수용인원2022-06-01 05:09:053
63250000CDFI226221201900000203_11_04_PU2020-11-03 02:40:00.0외국인관광도시민박업제이온게스트하우스<NA>부산광역시 중구 부평동2가 21-848977부산광역시 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>2022-06-01 05:09:053
1032700003270000-201-2019-0000303_11_03_PU2021-06-20 02:40:00.0숙박업대구여관601829부산광역시 동구 초량동 388-2 지하1층, 지상1~3층, 4층 일부48815부산광역시 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>2022-06-01 05:09:053
1132700003270000-201-2019-0000503_11_03_PU2022-01-14 02:40:00.0숙박업단테하우스601829부산광역시 동구 초량동 39948816부산광역시 동구 초량로13번길 58 (초량동)<NA><NA><NA><NA>영업/정상영업20220112091015여관업<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>2022-06-01 05:09:053
133280000CDFI226221202000000103_11_04_PU2021-10-21 02:40:00.0외국인관광도시민박업오션하우스<NA>부산광역시 영도구 동삼동 1124 함지그린아파트49119부산광역시 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>02022-06-01 05:09:053
143280000CDFI226221202000000203_11_04_PU2021-10-21 02:40:00.0외국인관광도시민박업에메랄드 오션뷰지번우편번호부산광역시 영도구 동삼동 1124 함지그린아파트49119부산광역시 영도구 함지로 8, 106동 1902호 (동삼동, 함지그린아파트)폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중20211019153331업태구분명전화번호1건물소유구분명아파트건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4645.5양실수여성종사자수Emerald ocean viewGuesthouse for Foreign Tourists욕실수위생업태명0제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0아파트지역20주거지역220침대수한실수회수건조수02022-06-01 05:09:053
153280000CDFI226221202000000303_11_04_PU2021-11-26 02:40:00.0외국인관광도시민박업청학소담<NA>부산광역시 영도구 청학동 398-2049031부산광역시 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>02022-06-01 05:09:053
2132900003290000-201-2019-0000203_11_03_PU2020-12-15 02:40:00.0숙박업엑스모텔614846부산광역시 부산진구 부전동 226-547296부산광역시 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>2022-06-01 05:09:053
2232900003290000-201-2020-0000103_11_03_PU2020-12-15 02:40:00.0숙박업지지배614849부산광역시 부산진구 부전동 417-2547258부산광역시 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>2022-06-01 05:09:053