Overview

Dataset statistics

Number of variables81
Number of observations8484
Missing cells25520
Missing cells (%)3.7%
Duplicate rows245
Duplicate rows (%)2.9%
Total size in memory5.3 MiB
Average record size in memory651.0 B

Variable types

Unsupported4
Numeric3
Text10
Categorical62
DateTime2

Alerts

Dataset has 245 (2.9%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (89.5%)Imbalance
updategbn is highly imbalanced (75.7%)Imbalance
opnsvcnm is highly imbalanced (81.3%)Imbalance
clgstdt is highly imbalanced (96.9%)Imbalance
clgenddt is highly imbalanced (96.8%)Imbalance
ropnymd is highly imbalanced (91.1%)Imbalance
trdstatenm is highly imbalanced (51.7%)Imbalance
dtlstatenm is highly imbalanced (54.1%)Imbalance
stroomcnt is highly imbalanced (95.3%)Imbalance
bdngsrvnm is highly imbalanced (92.5%)Imbalance
bdngunderflrcnt is highly imbalanced (55.3%)Imbalance
cnstyarea is highly imbalanced (97.1%)Imbalance
svnsr is highly imbalanced (91.1%)Imbalance
plninsurstdt is highly imbalanced (91.1%)Imbalance
plninsurenddt is highly imbalanced (91.1%)Imbalance
maneipcnt is highly imbalanced (87.6%)Imbalance
playutscntdtl is highly imbalanced (91.1%)Imbalance
playfacilcnt is highly imbalanced (80.6%)Imbalance
multusnupsoyn is highly imbalanced (95.1%)Imbalance
stagear is highly imbalanced (91.1%)Imbalance
culwrkrsenm is highly imbalanced (91.1%)Imbalance
culphyedcobnm is highly imbalanced (87.7%)Imbalance
geicpfacilen is highly imbalanced (91.1%)Imbalance
balhansilyn is highly imbalanced (94.3%)Imbalance
bcfacilen is highly imbalanced (91.1%)Imbalance
insurorgnm is highly imbalanced (97.2%)Imbalance
insurstdt is highly imbalanced (91.1%)Imbalance
insurenddt is highly imbalanced (91.1%)Imbalance
afc is highly imbalanced (91.1%)Imbalance
useunderendflr is highly imbalanced (64.0%)Imbalance
useunderstflr is highly imbalanced (63.0%)Imbalance
shpinfo is highly imbalanced (91.1%)Imbalance
shpcnt is highly imbalanced (91.1%)Imbalance
shptottons is highly imbalanced (91.1%)Imbalance
infoben is highly imbalanced (91.1%)Imbalance
wmeipcnt is highly imbalanced (86.7%)Imbalance
engstntrnmnm is highly imbalanced (96.7%)Imbalance
engstntrnmaddr is highly imbalanced (96.2%)Imbalance
yoksilcnt is highly imbalanced (77.2%)Imbalance
dispenen is highly imbalanced (91.1%)Imbalance
capt is highly imbalanced (96.0%)Imbalance
mnfactreartclcn is highly imbalanced (91.1%)Imbalance
cndpermstymd is highly imbalanced (94.2%)Imbalance
cndpermntwhy is highly imbalanced (91.1%)Imbalance
cndpermendymd is highly imbalanced (94.2%)Imbalance
chaircnt is highly imbalanced (66.5%)Imbalance
nearenvnm is highly imbalanced (93.4%)Imbalance
jisgnumlay is highly imbalanced (94.5%)Imbalance
regnsenm is highly imbalanced (90.8%)Imbalance
undernumlay is highly imbalanced (95.3%)Imbalance
totnumlay is highly imbalanced (94.3%)Imbalance
meetsamtimesygstf is highly imbalanced (91.1%)Imbalance
sitepostno has 293 (3.5%) missing valuesMissing
rdnwhladdr has 2549 (30.0%) missing valuesMissing
dcbymd has 4578 (54.0%) missing valuesMissing
x has 385 (4.5%) missing valuesMissing
y has 388 (4.6%) missing valuesMissing
sitetel has 96 (1.1%) missing valuesMissing
facilscp has 8147 (96.0%) missing valuesMissing
facilar has 8147 (96.0%) missing valuesMissing
yangsilcnt has 897 (10.6%) missing valuesMissing
skey is an unsupported type, check if it needs cleaning or further analysisUnsupported
rdnpostno is an unsupported type, check if it needs cleaning or further analysisUnsupported
apvpermymd is an unsupported type, check if it needs cleaning or further analysisUnsupported
x is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 16:35:30.266390
Analysis finished2024-04-16 16:35:33.242243
Duration2.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.4 KiB

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3318929.4
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.7 KiB
2024-04-17T01:35:33.282748image/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 deviation42882.132
Coefficient of variation (CV)0.012920471
Kurtosis-0.97799079
Mean3318929.4
Median Absolute Deviation (MAD)30000
Skewness0.2655391
Sum2.814784 × 1010
Variance1.8388772 × 109
MonotonicityNot monotonic
2024-04-17T01:35:33.373590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1138
13.4%
3290000 1059
12.5%
3300000 893
10.5%
3390000 688
8.1%
3270000 654
 
7.7%
3320000 578
 
6.8%
3380000 499
 
5.9%
3250000 478
 
5.6%
3260000 405
 
4.8%
3370000 383
 
4.5%
Other values (6) 1706
20.1%
ValueCountFrequency (%)
3250000 478
5.6%
3260000 405
 
4.8%
3270000 654
7.7%
3280000 365
 
4.3%
3290000 1059
12.5%
3300000 893
10.5%
3310000 285
 
3.4%
3320000 578
6.8%
3330000 1138
13.4%
3340000 358
 
4.2%
ValueCountFrequency (%)
3400000 207
 
2.4%
3390000 688
8.1%
3380000 499
5.9%
3370000 383
 
4.5%
3360000 138
 
1.6%
3350000 353
 
4.2%
3340000 358
 
4.2%
3330000 1138
13.4%
3320000 578
6.8%
3310000 285
 
3.4%

mgtno
Text

Distinct4204
Distinct (%)49.6%
Missing3
Missing (%)< 0.1%
Memory size66.4 KiB
2024-04-17T01:35:33.551295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.917227
Min length20

Characters and Unicode

Total characters185880
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

Unique126 ?
Unique (%)1.5%

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%
cdfi2262212016000001 11
 
0.1%
cdfi2262212020000001 10
 
0.1%
cdfi2262212016000002 10
 
0.1%
cdfi2260032020000001 9
 
0.1%
cdfi2262212017000002 9
 
0.1%
Other values (4194) 8371
98.7%
2024-04-17T01:35:33.845947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71580
38.5%
- 24390
 
13.1%
1 20064
 
10.8%
2 19879
 
10.7%
3 18214
 
9.8%
9 10161
 
5.5%
8 4973
 
2.7%
7 4871
 
2.6%
6 3697
 
2.0%
4 3606
 
1.9%
Other values (5) 4445
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160086
86.1%
Dash Punctuation 24390
 
13.1%
Uppercase Letter 1404
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71580
44.7%
1 20064
 
12.5%
2 19879
 
12.4%
3 18214
 
11.4%
9 10161
 
6.3%
8 4973
 
3.1%
7 4871
 
3.0%
6 3697
 
2.3%
4 3606
 
2.3%
5 3041
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 351
25.0%
D 351
25.0%
F 351
25.0%
I 351
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24390
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 184476
99.2%
Latin 1404
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 71580
38.8%
- 24390
 
13.2%
1 20064
 
10.9%
2 19879
 
10.8%
3 18214
 
9.9%
9 10161
 
5.5%
8 4973
 
2.7%
7 4871
 
2.6%
6 3697
 
2.0%
4 3606
 
2.0%
Latin
ValueCountFrequency (%)
C 351
25.0%
D 351
25.0%
F 351
25.0%
I 351
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 185880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 71580
38.5%
- 24390
 
13.1%
1 20064
 
10.8%
2 19879
 
10.7%
3 18214
 
9.8%
9 10161
 
5.5%
8 4973
 
2.7%
7 4871
 
2.6%
6 3697
 
2.0%
4 3606
 
1.9%
Other values (5) 4445
 
2.4%

opnsvcid
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
03_11_03_P
8130 
03_11_04_P
 
265
03_11_01_P
 
73
03_11_05_P
 
9
03_11_02_P
 
3
Other values (2)
 
4

Length

Max length10
Median length10
Mean length9.9978784
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 8130
95.8%
03_11_04_P 265
 
3.1%
03_11_01_P 73
 
0.9%
03_11_05_P 9
 
0.1%
03_11_02_P 3
 
< 0.1%
<NA> 3
 
< 0.1%
03_11_06_P 1
 
< 0.1%

Length

2024-04-17T01:35:33.996962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:34.095955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8130
95.8%
03_11_04_p 265
 
3.1%
03_11_01_p 73
 
0.9%
03_11_05_p 9
 
0.1%
03_11_02_p 3
 
< 0.1%
na 3
 
< 0.1%
03_11_06_p 1
 
< 0.1%

updategbn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
I
7853 
U
 
628
180000000
 
3

Length

Max length9
Median length1
Mean length1.0028289
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7853
92.6%
U 628
 
7.4%
180000000 3
 
< 0.1%

Length

2024-04-17T01:35:34.199078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:34.283522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7853
92.6%
u 628
 
7.4%
180000000 3
 
< 0.1%
Distinct228
Distinct (%)2.7%
Missing3
Missing (%)< 0.1%
Memory size66.4 KiB
Minimum2018-08-31 23:59:59
Maximum2021-06-01 02:40:00
2024-04-17T01:35:34.379570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:35:34.487210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
7731 
숙박업
 
582
외국인관광도시민박업
 
95
관광숙박업
 
73
자동차야영장업
 
1
Other values (2)
 
2

Length

Max length10
Median length4
Mean length4.0077793
Min length3

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7731
91.1%
숙박업 582
 
6.9%
외국인관광도시민박업 95
 
1.1%
관광숙박업 73
 
0.9%
자동차야영장업 1
 
< 0.1%
한옥체험업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

Length

2024-04-17T01:35:34.591010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:34.688419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7731
91.1%
숙박업 582
 
6.9%
외국인관광도시민박업 95
 
1.1%
관광숙박업 73
 
0.9%
자동차야영장업 1
 
< 0.1%
한옥체험업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

bplcnm
Text

Distinct3374
Distinct (%)39.8%
Missing3
Missing (%)< 0.1%
Memory size66.4 KiB
2024-04-17T01:35:34.951647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length36
Mean length5.1317062
Min length1

Characters and Unicode

Total characters43522
Distinct characters649
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

Unique296 ?
Unique (%)3.5%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 칠구(K79)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 234
 
2.3%
모텔 192
 
1.9%
게스트하우스 120
 
1.2%
여관 82
 
0.8%
hotel 61
 
0.6%
부산 51
 
0.5%
house 50
 
0.5%
해운대 39
 
0.4%
여인숙 36
 
0.4%
36
 
0.4%
Other values (3461) 9178
91.1%
2024-04-17T01:35:35.338033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2910
 
6.7%
2016
 
4.6%
1791
 
4.1%
1770
 
4.1%
1615
 
3.7%
1495
 
3.4%
1332
 
3.1%
1279
 
2.9%
768
 
1.8%
721
 
1.7%
Other values (639) 27825
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36663
84.2%
Uppercase Letter 2351
 
5.4%
Space Separator 1615
 
3.7%
Lowercase Letter 1212
 
2.8%
Decimal Number 515
 
1.2%
Open Punctuation 505
 
1.2%
Close Punctuation 505
 
1.2%
Other Punctuation 102
 
0.2%
Dash Punctuation 30
 
0.1%
Letter Number 10
 
< 0.1%
Other values (4) 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2910
 
7.9%
2016
 
5.5%
1791
 
4.9%
1770
 
4.8%
1495
 
4.1%
1332
 
3.6%
1279
 
3.5%
768
 
2.1%
721
 
2.0%
622
 
1.7%
Other values (559) 21959
59.9%
Uppercase Letter
ValueCountFrequency (%)
E 253
 
10.8%
O 220
 
9.4%
H 204
 
8.7%
T 173
 
7.4%
S 168
 
7.1%
A 133
 
5.7%
L 130
 
5.5%
N 112
 
4.8%
U 104
 
4.4%
M 92
 
3.9%
Other values (16) 762
32.4%
Lowercase Letter
ValueCountFrequency (%)
e 197
16.3%
o 144
11.9%
s 102
8.4%
a 97
8.0%
n 91
 
7.5%
u 91
 
7.5%
t 84
 
6.9%
h 59
 
4.9%
l 56
 
4.6%
i 52
 
4.3%
Other values (16) 239
19.7%
Decimal Number
ValueCountFrequency (%)
2 124
24.1%
1 70
13.6%
5 65
12.6%
7 58
11.3%
9 54
10.5%
6 39
 
7.6%
0 38
 
7.4%
3 34
 
6.6%
4 23
 
4.5%
8 10
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 57
55.9%
& 25
24.5%
' 9
 
8.8%
, 6
 
5.9%
2
 
2.0%
; 2
 
2.0%
: 1
 
1.0%
Letter Number
ValueCountFrequency (%)
6
60.0%
4
40.0%
Math Symbol
ValueCountFrequency (%)
+ 4
66.7%
2
33.3%
Space Separator
ValueCountFrequency (%)
1615
100.0%
Open Punctuation
ValueCountFrequency (%)
( 505
100.0%
Close Punctuation
ValueCountFrequency (%)
) 505
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
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 36661
84.2%
Latin 3573
 
8.2%
Common 3280
 
7.5%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2910
 
7.9%
2016
 
5.5%
1791
 
4.9%
1770
 
4.8%
1495
 
4.1%
1332
 
3.6%
1279
 
3.5%
768
 
2.1%
721
 
2.0%
622
 
1.7%
Other values (555) 21957
59.9%
Latin
ValueCountFrequency (%)
E 253
 
7.1%
O 220
 
6.2%
H 204
 
5.7%
e 197
 
5.5%
T 173
 
4.8%
S 168
 
4.7%
o 144
 
4.0%
A 133
 
3.7%
L 130
 
3.6%
N 112
 
3.1%
Other values (44) 1839
51.5%
Common
ValueCountFrequency (%)
1615
49.2%
( 505
 
15.4%
) 505
 
15.4%
2 124
 
3.8%
1 70
 
2.1%
5 65
 
2.0%
7 58
 
1.8%
. 57
 
1.7%
9 54
 
1.6%
6 39
 
1.2%
Other values (15) 188
 
5.7%
Han
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36655
84.2%
ASCII 6838
 
15.7%
None 10
 
< 0.1%
Number Forms 10
 
< 0.1%
CJK 8
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2910
 
7.9%
2016
 
5.5%
1791
 
4.9%
1770
 
4.8%
1495
 
4.1%
1332
 
3.6%
1279
 
3.5%
768
 
2.1%
721
 
2.0%
622
 
1.7%
Other values (554) 21951
59.9%
ASCII
ValueCountFrequency (%)
1615
23.6%
( 505
 
7.4%
) 505
 
7.4%
E 253
 
3.7%
O 220
 
3.2%
H 204
 
3.0%
e 197
 
2.9%
T 173
 
2.5%
S 168
 
2.5%
o 144
 
2.1%
Other values (64) 2854
41.7%
None
ValueCountFrequency (%)
6
60.0%
2
 
20.0%
2
 
20.0%
Number Forms
ValueCountFrequency (%)
6
60.0%
4
40.0%
CJK
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%
Punctuation
ValueCountFrequency (%)
1
100.0%

sitepostno
Text

MISSING 

Distinct492
Distinct (%)6.0%
Missing293
Missing (%)3.5%
Memory size66.4 KiB
2024-04-17T01:35:35.609313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters49146
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

Unique19 ?
Unique (%)0.2%

Sample

1st row600045
2nd row600051
3rd row600092
4th row600806
5th row600012
ValueCountFrequency (%)
612821 317
 
3.9%
616801 254
 
3.1%
612040 208
 
2.5%
612847 183
 
2.2%
607833 175
 
2.1%
601829 145
 
1.8%
617807 136
 
1.7%
613828 129
 
1.6%
607831 126
 
1.5%
607842 114
 
1.4%
Other values (482) 6404
78.2%
2024-04-17T01:35:35.996957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9833
20.0%
1 8031
16.3%
0 7982
16.2%
8 7927
16.1%
2 4290
8.7%
4 3439
 
7.0%
7 2596
 
5.3%
3 2458
 
5.0%
9 1403
 
2.9%
5 953
 
1.9%
Other values (5) 234
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48912
99.5%
Other Letter 234
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9833
20.1%
1 8031
16.4%
0 7982
16.3%
8 7927
16.2%
2 4290
8.8%
4 3439
 
7.0%
7 2596
 
5.3%
3 2458
 
5.0%
9 1403
 
2.9%
5 953
 
1.9%
Other Letter
ValueCountFrequency (%)
78
33.3%
39
16.7%
39
16.7%
39
16.7%
39
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 48912
99.5%
Hangul 234
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9833
20.1%
1 8031
16.4%
0 7982
16.3%
8 7927
16.2%
2 4290
8.8%
4 3439
 
7.0%
7 2596
 
5.3%
3 2458
 
5.0%
9 1403
 
2.9%
5 953
 
1.9%
Hangul
ValueCountFrequency (%)
78
33.3%
39
16.7%
39
16.7%
39
16.7%
39
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48912
99.5%
Hangul 234
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9833
20.1%
1 8031
16.4%
0 7982
16.3%
8 7927
16.2%
2 4290
8.8%
4 3439
 
7.0%
7 2596
 
5.3%
3 2458
 
5.0%
9 1403
 
2.9%
5 953
 
1.9%
Hangul
ValueCountFrequency (%)
78
33.3%
39
16.7%
39
16.7%
39
16.7%
39
16.7%
Distinct4060
Distinct (%)47.9%
Missing5
Missing (%)0.1%
Memory size66.4 KiB
2024-04-17T01:35:36.275371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length45
Mean length23.551362
Min length13

Characters and Unicode

Total characters199692
Distinct characters308
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

Unique248 ?
Unique (%)2.9%

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 8479
23.5%
해운대구 1138
 
3.2%
부산진구 1059
 
2.9%
동래구 893
 
2.5%
t통b반 868
 
2.4%
사상구 688
 
1.9%
동구 654
 
1.8%
온천동 644
 
1.8%
북구 582
 
1.6%
부전동 503
 
1.4%
Other values (4251) 20585
57.0%
2024-04-17T01:35:36.719056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36002
18.0%
10301
 
5.2%
10048
 
5.0%
9954
 
5.0%
8848
 
4.4%
8727
 
4.4%
1 8572
 
4.3%
8505
 
4.3%
8485
 
4.2%
8128
 
4.1%
Other values (298) 82122
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113778
57.0%
Decimal Number 39691
 
19.9%
Space Separator 36002
 
18.0%
Dash Punctuation 7876
 
3.9%
Uppercase Letter 1782
 
0.9%
Other Punctuation 196
 
0.1%
Close Punctuation 124
 
0.1%
Open Punctuation 124
 
0.1%
Math Symbol 115
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10301
 
9.1%
10048
 
8.8%
9954
 
8.7%
8848
 
7.8%
8727
 
7.7%
8505
 
7.5%
8485
 
7.5%
8128
 
7.1%
7916
 
7.0%
1577
 
1.4%
Other values (262) 31289
27.5%
Uppercase Letter
ValueCountFrequency (%)
B 875
49.1%
T 869
48.8%
A 11
 
0.6%
K 6
 
0.3%
C 5
 
0.3%
S 3
 
0.2%
O 3
 
0.2%
E 2
 
0.1%
G 2
 
0.1%
M 2
 
0.1%
Other values (4) 4
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 8572
21.6%
2 5208
13.1%
3 4176
10.5%
4 4036
10.2%
5 3914
9.9%
0 3056
 
7.7%
6 3028
 
7.6%
7 2838
 
7.2%
8 2565
 
6.5%
9 2298
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 193
98.5%
. 2
 
1.0%
& 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
i 1
33.3%
w 1
33.3%
Space Separator
ValueCountFrequency (%)
36002
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7876
100.0%
Close Punctuation
ValueCountFrequency (%)
) 124
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Math Symbol
ValueCountFrequency (%)
~ 115
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113778
57.0%
Common 84128
42.1%
Latin 1786
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10301
 
9.1%
10048
 
8.8%
9954
 
8.7%
8848
 
7.8%
8727
 
7.7%
8505
 
7.5%
8485
 
7.5%
8128
 
7.1%
7916
 
7.0%
1577
 
1.4%
Other values (262) 31289
27.5%
Common
ValueCountFrequency (%)
36002
42.8%
1 8572
 
10.2%
- 7876
 
9.4%
2 5208
 
6.2%
3 4176
 
5.0%
4 4036
 
4.8%
5 3914
 
4.7%
0 3056
 
3.6%
6 3028
 
3.6%
7 2838
 
3.4%
Other values (8) 5422
 
6.4%
Latin
ValueCountFrequency (%)
B 875
49.0%
T 869
48.7%
A 11
 
0.6%
K 6
 
0.3%
C 5
 
0.3%
S 3
 
0.2%
O 3
 
0.2%
E 2
 
0.1%
G 2
 
0.1%
M 2
 
0.1%
Other values (8) 8
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113778
57.0%
ASCII 85913
43.0%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36002
41.9%
1 8572
 
10.0%
- 7876
 
9.2%
2 5208
 
6.1%
3 4176
 
4.9%
4 4036
 
4.7%
5 3914
 
4.6%
0 3056
 
3.6%
6 3028
 
3.5%
7 2838
 
3.3%
Other values (25) 7207
 
8.4%
Hangul
ValueCountFrequency (%)
10301
 
9.1%
10048
 
8.8%
9954
 
8.7%
8848
 
7.8%
8727
 
7.7%
8505
 
7.5%
8485
 
7.5%
8128
 
7.1%
7916
 
7.0%
1577
 
1.4%
Other values (262) 31289
27.5%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Unsupported

REJECTED  UNSUPPORTED 

Missing14
Missing (%)0.2%
Memory size66.4 KiB

rdnwhladdr
Text

MISSING 

Distinct3010
Distinct (%)50.7%
Missing2549
Missing (%)30.0%
Memory size66.4 KiB
2024-04-17T01:35:36.994543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length61
Mean length27.849368
Min length5

Characters and Unicode

Total characters165286
Distinct characters369
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique292 ?
Unique (%)4.9%

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 5934
 
19.1%
해운대구 920
 
3.0%
부산진구 725
 
2.3%
동래구 607
 
2.0%
사상구 515
 
1.7%
동구 489
 
1.6%
온천동 422
 
1.4%
수영구 397
 
1.3%
중구 388
 
1.3%
부전동 385
 
1.2%
Other values (2576) 20225
65.2%
2024-04-17T01:35:37.393649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25072
 
15.2%
7727
 
4.7%
7338
 
4.4%
7002
 
4.2%
6645
 
4.0%
6310
 
3.8%
1 6299
 
3.8%
6065
 
3.7%
5940
 
3.6%
( 5824
 
3.5%
Other values (359) 81064
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 98348
59.5%
Decimal Number 26796
 
16.2%
Space Separator 25072
 
15.2%
Open Punctuation 5824
 
3.5%
Close Punctuation 5824
 
3.5%
Dash Punctuation 1798
 
1.1%
Other Punctuation 1272
 
0.8%
Math Symbol 252
 
0.2%
Uppercase Letter 93
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7727
 
7.9%
7338
 
7.5%
7002
 
7.1%
6645
 
6.8%
6310
 
6.4%
6065
 
6.2%
5940
 
6.0%
5660
 
5.8%
3957
 
4.0%
3721
 
3.8%
Other values (317) 37983
38.6%
Uppercase Letter
ValueCountFrequency (%)
A 30
32.3%
B 21
22.6%
K 9
 
9.7%
O 5
 
5.4%
C 5
 
5.4%
S 4
 
4.3%
E 3
 
3.2%
G 2
 
2.2%
U 2
 
2.2%
F 2
 
2.2%
Other values (9) 10
 
10.8%
Decimal Number
ValueCountFrequency (%)
1 6299
23.5%
2 4113
15.3%
3 3008
11.2%
4 2278
 
8.5%
5 2143
 
8.0%
0 1922
 
7.2%
6 1900
 
7.1%
7 1847
 
6.9%
9 1698
 
6.3%
8 1588
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
b 1
25.0%
i 1
25.0%
e 1
25.0%
w 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 1262
99.2%
. 9
 
0.7%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
25072
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5824
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5824
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1798
100.0%
Math Symbol
ValueCountFrequency (%)
~ 252
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 98348
59.5%
Common 66838
40.4%
Latin 100
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7727
 
7.9%
7338
 
7.5%
7002
 
7.1%
6645
 
6.8%
6310
 
6.4%
6065
 
6.2%
5940
 
6.0%
5660
 
5.8%
3957
 
4.0%
3721
 
3.8%
Other values (317) 37983
38.6%
Latin
ValueCountFrequency (%)
A 30
30.0%
B 21
21.0%
K 9
 
9.0%
O 5
 
5.0%
C 5
 
5.0%
S 4
 
4.0%
3
 
3.0%
E 3
 
3.0%
G 2
 
2.0%
U 2
 
2.0%
Other values (14) 16
16.0%
Common
ValueCountFrequency (%)
25072
37.5%
1 6299
 
9.4%
( 5824
 
8.7%
) 5824
 
8.7%
2 4113
 
6.2%
3 3008
 
4.5%
4 2278
 
3.4%
5 2143
 
3.2%
0 1922
 
2.9%
6 1900
 
2.8%
Other values (8) 8455
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 98348
59.5%
ASCII 66935
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25072
37.5%
1 6299
 
9.4%
( 5824
 
8.7%
) 5824
 
8.7%
2 4113
 
6.1%
3 3008
 
4.5%
4 2278
 
3.4%
5 2143
 
3.2%
0 1922
 
2.9%
6 1900
 
2.8%
Other values (31) 8552
 
12.8%
Hangul
ValueCountFrequency (%)
7727
 
7.9%
7338
 
7.5%
7002
 
7.1%
6645
 
6.8%
6310
 
6.4%
6065
 
6.2%
5940
 
6.0%
5660
 
5.8%
3957
 
4.0%
3721
 
3.8%
Other values (317) 37983
38.6%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.4 KiB

dcbymd
Text

MISSING 

Distinct1343
Distinct (%)34.4%
Missing4578
Missing (%)54.0%
Memory size66.4 KiB
2024-04-17T01:35:37.645599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9088582
Min length4

Characters and Unicode

Total characters30892
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

Unique32 ?
Unique (%)0.8%

Sample

1st row20140310
2nd row20121231
3rd row20171120
4th row20171107
5th row20120514
ValueCountFrequency (%)
20041022 180
 
4.6%
폐업일자 89
 
2.3%
20030122 64
 
1.6%
20120711 52
 
1.3%
20021024 38
 
1.0%
20030305 26
 
0.7%
20030101 24
 
0.6%
20030227 22
 
0.6%
20051117 20
 
0.5%
20030901 18
 
0.5%
Other values (1333) 3373
86.4%
2024-04-17T01:35:37.990154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10278
33.3%
2 6458
20.9%
1 5548
18.0%
3 1434
 
4.6%
9 1398
 
4.5%
7 1192
 
3.9%
4 1134
 
3.7%
6 1082
 
3.5%
5 1065
 
3.4%
8 947
 
3.1%
Other values (4) 356
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30536
98.8%
Other Letter 356
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10278
33.7%
2 6458
21.1%
1 5548
18.2%
3 1434
 
4.7%
9 1398
 
4.6%
7 1192
 
3.9%
4 1134
 
3.7%
6 1082
 
3.5%
5 1065
 
3.5%
8 947
 
3.1%
Other Letter
ValueCountFrequency (%)
89
25.0%
89
25.0%
89
25.0%
89
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30536
98.8%
Hangul 356
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10278
33.7%
2 6458
21.1%
1 5548
18.2%
3 1434
 
4.7%
9 1398
 
4.6%
7 1192
 
3.9%
4 1134
 
3.7%
6 1082
 
3.5%
5 1065
 
3.5%
8 947
 
3.1%
Hangul
ValueCountFrequency (%)
89
25.0%
89
25.0%
89
25.0%
89
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30536
98.8%
Hangul 356
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10278
33.7%
2 6458
21.1%
1 5548
18.2%
3 1434
 
4.7%
9 1398
 
4.6%
7 1192
 
3.9%
4 1134
 
3.7%
6 1082
 
3.5%
5 1065
 
3.5%
8 947
 
3.1%
Hangul
ValueCountFrequency (%)
89
25.0%
89
25.0%
89
25.0%
89
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8381 
휴업시작일자
 
94
20210528
 
2
20201012
 
1
20160608
 
1
Other values (5)
 
5

Length

Max length8
Median length4
Mean length4.0264026
Min length4

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8381
98.8%
휴업시작일자 94
 
1.1%
20210528 2
 
< 0.1%
20201012 1
 
< 0.1%
20160608 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20180719 1
 
< 0.1%
20201001 1
 
< 0.1%

Length

2024-04-17T01:35:38.132287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:38.233912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8381
98.8%
휴업시작일자 94
 
1.1%
20210528 2
 
< 0.1%
20201012 1
 
< 0.1%
20160608 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20180719 1
 
< 0.1%
20201001 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8381 
휴업종료일자
 
95
20230131
 
2
20170607
 
1
20180424
 
1
Other values (4)
 
4

Length

Max length8
Median length4
Mean length4.0261669
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> 8381
98.8%
휴업종료일자 95
 
1.1%
20230131 2
 
< 0.1%
20170607 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20181231 1
 
< 0.1%
20211001 1
 
< 0.1%

Length

2024-04-17T01:35:38.350560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:38.449933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8381
98.8%
휴업종료일자 95
 
1.1%
20230131 2
 
< 0.1%
20170607 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20181231 1
 
< 0.1%
20211001 1
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
재개업일자
 
95

Length

Max length5
Median length4
Mean length4.0111975
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> 8389
98.9%
재개업일자 95
 
1.1%

Length

2024-04-17T01:35:38.549223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:38.637289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
재개업일자 95
 
1.1%

trdstatenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
01
3844 
02
3709 
영업/정상
686 
13
 
121
폐업
 
60
Other values (4)
 
64

Length

Max length5
Median length2
Mean length2.2439887
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
01 3844
45.3%
02 3709
43.7%
영업/정상 686
 
8.1%
13 121
 
1.4%
폐업 60
 
0.7%
03 53
 
0.6%
<NA> 6
 
0.1%
휴업 4
 
< 0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:35:38.726874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:38.827701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01 3844
45.3%
02 3709
43.7%
영업/정상 686
 
8.1%
13 121
 
1.4%
폐업 60
 
0.7%
03 53
 
0.6%
na 6
 
0.1%
휴업 4
 
< 0.1%
31 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
영업
4379 
폐업
3817 
영업중
 
275
휴업
 
9
<NA>
 
3

Length

Max length4
Median length2
Mean length2.0333569
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4379
51.6%
폐업 3817
45.0%
영업중 275
 
3.2%
휴업 9
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:35:38.942044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:39.058003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4379
51.6%
폐업 3817
45.0%
영업중 275
 
3.2%
휴업 9
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing385
Missing (%)4.5%
Memory size66.4 KiB

y
Real number (ℝ)

MISSING 

Distinct3936
Distinct (%)48.6%
Missing388
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean186731.9
Minimum169998.58
Maximum209754.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.7 KiB
2024-04-17T01:35:39.168658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169998.58
5-th percentile178698.94
Q1182940.33
median186928.93
Q3189964.97
95-th percentile193848.76
Maximum209754.15
Range39755.577
Interquartile range (IQR)7024.6432

Descriptive statistics

Standard deviation5111.1671
Coefficient of variation (CV)0.027371686
Kurtosis0.081700102
Mean186731.9
Median Absolute Deviation (MAD)3576.2171
Skewness0.10926926
Sum1.5117815 × 109
Variance26124029
MonotonicityNot monotonic
2024-04-17T01:35:39.290796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185933.100965604 19
 
0.2%
176595.034934652 11
 
0.1%
187092.852201 10
 
0.1%
187269.854013 8
 
0.1%
186243.806655 8
 
0.1%
185542.452702234 8
 
0.1%
186655.373923053 8
 
0.1%
192327.468209 8
 
0.1%
186807.811298995 7
 
0.1%
187863.015365939 7
 
0.1%
Other values (3926) 8002
94.3%
(Missing) 388
 
4.6%
ValueCountFrequency (%)
169998.576608 2
< 0.1%
171461.496152 2
< 0.1%
174251.232048 2
< 0.1%
174413.752458 1
< 0.1%
174599.932466 2
< 0.1%
174999.02898 2
< 0.1%
175045.348943 2
< 0.1%
175046.263792 2
< 0.1%
175057.331511 2
< 0.1%
175075.261586 2
< 0.1%
ValueCountFrequency (%)
209754.153703 1
< 0.1%
207516.984282 2
< 0.1%
207378.835702 1
< 0.1%
206172.903942 2
< 0.1%
206065.80538 2
< 0.1%
205949.336131 2
< 0.1%
205793.809975 2
< 0.1%
205774.280535 2
< 0.1%
205756.904836 2
< 0.1%
205755.902784 2
< 0.1%

lastmodts
Real number (ℝ)

Distinct3675
Distinct (%)43.3%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0132184 × 1013
Minimum1.9990211 × 1013
Maximum2.0210528 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.7 KiB
2024-04-17T01:35:39.414849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0011011 × 1013
Q12.0060516 × 1013
median2.0171124 × 1013
Q32.0180517 × 1013
95-th percentile2.0210305 × 1013
Maximum2.0210528 × 1013
Range2.2031717 × 1011
Interquartile range (IQR)1.2000116 × 1011

Descriptive statistics

Standard deviation6.7499307 × 1010
Coefficient of variation (CV)0.003352806
Kurtosis-0.94343464
Mean2.0132184 × 1013
Median Absolute Deviation (MAD)9.7789276 × 109
Skewness-0.80795578
Sum1.7074105 × 1017
Variance4.5561565 × 1021
MonotonicityNot monotonic
2024-04-17T01:35:39.528512image/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%
20020515000000 32
 
0.4%
20030329000000 32
 
0.4%
19990308000000 32
 
0.4%
Other values (3665) 8023
94.6%
ValueCountFrequency (%)
19990211000000 2
 
< 0.1%
19990218000000 20
0.2%
19990223000000 2
 
< 0.1%
19990225000000 6
 
0.1%
19990302000000 4
 
< 0.1%
19990303000000 18
0.2%
19990308000000 32
0.4%
19990309000000 6
 
0.1%
19990310000000 2
 
< 0.1%
19990315000000 2
 
< 0.1%
ValueCountFrequency (%)
20210528171148 2
< 0.1%
20210528164049 2
< 0.1%
20210528161852 2
< 0.1%
20210528142314 2
< 0.1%
20210528134533 2
< 0.1%
20210528115539 2
< 0.1%
20210528113239 2
< 0.1%
20210527144331 2
< 0.1%
20210527133651 1
< 0.1%
20210527114524 2
< 0.1%

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
여관업
5265 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
487
일반호텔
 
432
Other values (4)
635 

Length

Max length8
Median length3
Mean length3.6990806
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5265
62.1%
여인숙업 1076
 
12.7%
숙박업 기타 589
 
6.9%
숙박업(생활) 487
 
5.7%
일반호텔 432
 
5.1%
<NA> 319
 
3.8%
관광호텔 270
 
3.2%
업태구분명 37
 
0.4%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:35:39.633426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:39.733172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5265
58.0%
여인숙업 1076
 
11.9%
숙박업 589
 
6.5%
기타 589
 
6.5%
숙박업(생활 487
 
5.4%
일반호텔 432
 
4.8%
na 319
 
3.5%
관광호텔 270
 
3.0%
업태구분명 37
 
0.4%
휴양콘도미니엄업 9
 
0.1%

sitetel
Text

MISSING 

Distinct221
Distinct (%)2.6%
Missing96
Missing (%)1.1%
Memory size66.4 KiB
2024-04-17T01:35:39.889908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.939914
Min length4

Characters and Unicode

Total characters100152
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

Unique24 ?
Unique (%)0.3%

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 7934
88.5%
051 389
 
4.3%
전화번호 35
 
0.4%
070 10
 
0.1%
731 6
 
0.1%
747 6
 
0.1%
803 5
 
0.1%
5500 5
 
0.1%
7779 5
 
0.1%
806 5
 
0.1%
Other values (284) 566
 
6.3%
2024-04-17T01:35:40.387926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24493
24.5%
2 16195
16.2%
3 16146
16.1%
- 15888
15.9%
0 8705
 
8.7%
5 8687
 
8.7%
4 8229
 
8.2%
582
 
0.6%
7 361
 
0.4%
8 274
 
0.3%
Other values (6) 592
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83542
83.4%
Dash Punctuation 15888
 
15.9%
Space Separator 582
 
0.6%
Other Letter 140
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24493
29.3%
2 16195
19.4%
3 16146
19.3%
0 8705
 
10.4%
5 8687
 
10.4%
4 8229
 
9.9%
7 361
 
0.4%
8 274
 
0.3%
6 268
 
0.3%
9 184
 
0.2%
Other Letter
ValueCountFrequency (%)
35
25.0%
35
25.0%
35
25.0%
35
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 15888
100.0%
Space Separator
ValueCountFrequency (%)
582
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 100012
99.9%
Hangul 140
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24493
24.5%
2 16195
16.2%
3 16146
16.1%
- 15888
15.9%
0 8705
 
8.7%
5 8687
 
8.7%
4 8229
 
8.2%
582
 
0.6%
7 361
 
0.4%
8 274
 
0.3%
Other values (2) 452
 
0.5%
Hangul
ValueCountFrequency (%)
35
25.0%
35
25.0%
35
25.0%
35
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100012
99.9%
Hangul 140
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24493
24.5%
2 16195
16.2%
3 16146
16.1%
- 15888
15.9%
0 8705
 
8.7%
5 8687
 
8.7%
4 8229
 
8.2%
582
 
0.6%
7 361
 
0.4%
8 274
 
0.3%
Other values (2) 452
 
0.5%
Hangul
ValueCountFrequency (%)
35
25.0%
35
25.0%
35
25.0%
35
25.0%

stroomcnt
Categorical

IMBALANCE 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8292 
객실수
 
74
1
 
31
2
 
27
3
 
19
Other values (22)
 
41

Length

Max length4
Median length4
Mean length3.9529703
Min length1

Unique

Unique13 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8292
97.7%
객실수 74
 
0.9%
1 31
 
0.4%
2 27
 
0.3%
3 19
 
0.2%
6 5
 
0.1%
7 5
 
0.1%
5 3
 
< 0.1%
33 3
 
< 0.1%
11 3
 
< 0.1%
Other values (17) 22
 
0.3%

Length

2024-04-17T01:35:40.484541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8292
97.7%
객실수 74
 
0.9%
1 31
 
0.4%
2 27
 
0.3%
3 19
 
0.2%
6 5
 
0.1%
7 5
 
0.1%
5 3
 
< 0.1%
33 3
 
< 0.1%
11 3
 
< 0.1%
Other values (17) 22
 
0.3%

bdngownsenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
6456 
자가
1175 
임대
773 
건물소유구분명
 
80

Length

Max length7
Median length4
Mean length3.5690712
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6456
76.1%
자가 1175
 
13.8%
임대 773
 
9.1%
건물소유구분명 80
 
0.9%

Length

2024-04-17T01:35:40.578163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:40.664875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6456
76.1%
자가 1175
 
13.8%
임대 773
 
9.1%
건물소유구분명 80
 
0.9%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8237 
건물용도명
 
78
단독주택
 
69
아파트
 
54
숙박시설
 
16
Other values (6)
 
30

Length

Max length15
Median length4
Mean length4.0091938
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> 8237
97.1%
건물용도명 78
 
0.9%
단독주택 69
 
0.8%
아파트 54
 
0.6%
숙박시설 16
 
0.2%
다세대주택 12
 
0.1%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 주택(공동주택적용) 4
 
< 0.1%
호텔 4
 
< 0.1%

Length

2024-04-17T01:35:40.761569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8237
97.0%
건물용도명 78
 
0.9%
단독주택 69
 
0.8%
아파트 54
 
0.6%
숙박시설 16
 
0.2%
다세대주택 12
 
0.1%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 4
 
< 0.1%
주택(공동주택적용 4
 
< 0.1%
Other values (2) 5
 
0.1%

bdngjisgflrcnt
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
2556 
<NA>
1655 
4
861 
3
749 
5
591 
Other values (30)
2072 

Length

Max length6
Median length1
Mean length1.6504008
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2556
30.1%
<NA> 1655
19.5%
4 861
 
10.1%
3 749
 
8.8%
5 591
 
7.0%
2 423
 
5.0%
8 319
 
3.8%
6 303
 
3.6%
7 302
 
3.6%
9 195
 
2.3%
Other values (25) 530
 
6.2%

Length

2024-04-17T01:35:40.861624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2556
30.1%
na 1655
19.5%
4 861
 
10.1%
3 749
 
8.8%
5 591
 
7.0%
2 423
 
5.0%
8 319
 
3.8%
6 303
 
3.6%
7 302
 
3.6%
9 195
 
2.3%
Other values (25) 530
 
6.2%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
4445 
<NA>
2221 
1
1484 
2
 
193
건물지하층수
 
37
Other values (9)
 
104

Length

Max length6
Median length1
Mean length1.8078736
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4445
52.4%
<NA> 2221
26.2%
1 1484
 
17.5%
2 193
 
2.3%
건물지하층수 37
 
0.4%
4 36
 
0.4%
3 27
 
0.3%
5 17
 
0.2%
8 6
 
0.1%
6 4
 
< 0.1%
Other values (4) 14
 
0.2%

Length

2024-04-17T01:35:40.987281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4445
52.4%
na 2221
26.2%
1 1486
 
17.5%
2 193
 
2.3%
건물지하층수 37
 
0.4%
4 36
 
0.4%
3 27
 
0.3%
5 17
 
0.2%
8 6
 
0.1%
6 4
 
< 0.1%
Other values (3) 12
 
0.1%

cnstyarea
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8374 
건축연면적
 
92
2282
 
3
20571
 
3
72
 
1
Other values (11)
 
11

Length

Max length5
Median length4
Mean length4.0100189
Min length2

Unique

Unique12 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8374
98.7%
건축연면적 92
 
1.1%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
72 1
 
< 0.1%
39 1
 
< 0.1%
85 1
 
< 0.1%
437 1
 
< 0.1%
132 1
 
< 0.1%
352 1
 
< 0.1%
Other values (6) 6
 
0.1%

Length

2024-04-17T01:35:41.119341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8374
98.7%
건축연면적 92
 
1.1%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
72 1
 
< 0.1%
39 1
 
< 0.1%
85 1
 
< 0.1%
437 1
 
< 0.1%
132 1
 
< 0.1%
352 1
 
< 0.1%
Other values (6) 6
 
0.1%

svnsr
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
기념품종류
 
95

Length

Max length5
Median length4
Mean length4.0111975
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> 8389
98.9%
기념품종류 95
 
1.1%

Length

2024-04-17T01:35:41.228184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:41.315165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
기념품종류 95
 
1.1%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
기획여행보험시작일자
 
95

Length

Max length10
Median length4
Mean length4.0671853
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> 8389
98.9%
기획여행보험시작일자 95
 
1.1%

Length

2024-04-17T01:35:41.400512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:41.484135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
기획여행보험시작일자 95
 
1.1%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
기획여행보험종료일자
 
95

Length

Max length10
Median length4
Mean length4.0671853
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> 8389
98.9%
기획여행보험종료일자 95
 
1.1%

Length

2024-04-17T01:35:41.569176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:41.657981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
기획여행보험종료일자 95
 
1.1%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
7892 
0
 
494
남성종사자수
 
68
1
 
12
3
 
5
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.8308581
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> 7892
93.0%
0 494
 
5.8%
남성종사자수 68
 
0.8%
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

2024-04-17T01:35:41.765901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7892
93.0%
0 494
 
5.8%
남성종사자수 68
 
0.8%
1 12
 
0.1%
3 5
 
0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
35 1
 
< 0.1%

playutscntdtl
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
놀이기구수내역
 
95

Length

Max length7
Median length4
Mean length4.0335926
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> 8389
98.9%
놀이기구수내역 95
 
1.1%

Length

2024-04-17T01:35:41.874117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:41.958991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
놀이기구수내역 95
 
1.1%

playfacilcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
N
7931 
<NA>
 
475
놀이시설수
 
75
Y
 
3

Length

Max length5
Median length1
Mean length1.2033239
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 7931
93.5%
<NA> 475
 
5.6%
놀이시설수 75
 
0.9%
Y 3
 
< 0.1%

Length

2024-04-17T01:35:42.052785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:42.159268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 7931
93.5%
na 475
 
5.6%
놀이시설수 75
 
0.9%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
N
8393 
<NA>
 
63
 
19
Y
 
9

Length

Max length4
Median length1
Mean length1.0222772
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8393
98.9%
<NA> 63
 
0.7%
19
 
0.2%
Y 9
 
0.1%

Length

2024-04-17T01:35:42.273865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:42.381645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8393
98.9%
na 63
 
0.7%
19
 
0.2%
y 9
 
0.1%

stagear
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
무대면적
 
95

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> 8389
98.9%
무대면적 95
 
1.1%

Length

2024-04-17T01:35:42.469983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:42.550720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
무대면적 95
 
1.1%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
문화사업자구분명
 
95

Length

Max length8
Median length4
Mean length4.0447902
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> 8389
98.9%
문화사업자구분명 95
 
1.1%

Length

2024-04-17T01:35:42.639383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:42.726068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
문화사업자구분명 95
 
1.1%

culphyedcobnm
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8078 
외국인관광 도시민박업
 
262
관광숙박업
 
73
문화체육업종명
 
58
자동차야영장업
 
9
Other values (2)
 
4

Length

Max length11
Median length4
Mean length4.2489392
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> 8078
95.2%
외국인관광 도시민박업 262
 
3.1%
관광숙박업 73
 
0.9%
문화체육업종명 58
 
0.7%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 1
 
< 0.1%

Length

2024-04-17T01:35:42.816365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:42.913604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8078
92.4%
외국인관광 262
 
3.0%
도시민박업 262
 
3.0%
관광숙박업 73
 
0.8%
문화체육업종명 58
 
0.7%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 1
 
< 0.1%

geicpfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
 
95

Length

Max length4
Median length4
Mean length3.9664074
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> 8389
98.9%
95
 
1.1%

Length

2024-04-17T01:35:43.020450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:43.103461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
95
 
1.1%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
N
8378 
<NA>
 
63
Y
 
24
 
19

Length

Max length4
Median length1
Mean length1.0222772
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8378
98.8%
<NA> 63
 
0.7%
Y 24
 
0.3%
19
 
0.2%

Length

2024-04-17T01:35:43.208353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:43.309932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8378
98.8%
na 63
 
0.7%
y 24
 
0.3%
19
 
0.2%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
 
95

Length

Max length4
Median length4
Mean length3.9664074
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> 8389
98.9%
95
 
1.1%

Length

2024-04-17T01:35:43.422984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:43.512528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
95
 
1.1%

insurorgnm
Categorical

IMBALANCE 

Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8368 
보험기관명
 
92
객실수/수용인원 : 2개/ 6명
 
2
DB 손해보험
 
2
객실수/수용인원:3/10
 
1
Other values (19)
 
19

Length

Max length22
Median length4
Mean length4.0308817
Min length2

Unique

Unique20 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8368
98.6%
보험기관명 92
 
1.1%
객실수/수용인원 : 2개/ 6명 2
 
< 0.1%
DB 손해보험 2
 
< 0.1%
객실수/수용인원:3/10 1
 
< 0.1%
객실수/수용인원:2/3 1
 
< 0.1%
객실수/수용인원:2/5 1
 
< 0.1%
객실수2/수용인원12 1
 
< 0.1%
객실수/수용인원 : 2개/10명 1
 
< 0.1%
객실수/수용인원 : 3/8 1
 
< 0.1%
Other values (14) 14
 
0.2%

Length

2024-04-17T01:35:43.607074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8368
98.4%
보험기관명 92
 
1.1%
객실수/수용인원 6
 
0.1%
5
 
0.1%
3/8 2
 
< 0.1%
2개 2
 
< 0.1%
6명 2
 
< 0.1%
db 2
 
< 0.1%
손해보험 2
 
< 0.1%
민박)객실3(20명 1
 
< 0.1%
Other values (21) 21
 
0.2%

insurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
보험시작일자
 
95

Length

Max length6
Median length4
Mean length4.0223951
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> 8389
98.9%
보험시작일자 95
 
1.1%

Length

2024-04-17T01:35:43.715325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:43.802710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
보험시작일자 95
 
1.1%

insurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
보험종료일자
 
95

Length

Max length6
Median length4
Mean length4.0223951
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> 8389
98.9%
보험종료일자 95
 
1.1%

Length

2024-04-17T01:35:43.896921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:43.983867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
보험종료일자 95
 
1.1%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
부대시설내역
 
95

Length

Max length6
Median length4
Mean length4.0223951
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> 8389
98.9%
부대시설내역 95
 
1.1%

Length

2024-04-17T01:35:44.079141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:44.166194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
부대시설내역 95
 
1.1%

usejisgendflr
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
2682 
0
1974 
4
755 
3
646 
5
468 
Other values (30)
1959 

Length

Max length6
Median length1
Mean length2.0095474
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2682
31.6%
0 1974
23.3%
4 755
 
8.9%
3 646
 
7.6%
5 468
 
5.5%
6 417
 
4.9%
2 387
 
4.6%
7 267
 
3.1%
8 253
 
3.0%
9 187
 
2.2%
Other values (25) 448
 
5.3%

Length

2024-04-17T01:35:44.255484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2682
31.6%
0 1974
23.3%
4 755
 
8.9%
3 646
 
7.6%
5 468
 
5.5%
6 417
 
4.9%
2 387
 
4.6%
7 267
 
3.1%
8 253
 
3.0%
9 187
 
2.2%
Other values (25) 448
 
5.3%

useunderendflr
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
4632 
<NA>
3597 
1
 
182
사용끝지하층
 
41
2
 
16
Other values (5)
 
16

Length

Max length6
Median length1
Mean length2.2964404
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4632
54.6%
<NA> 3597
42.4%
1 182
 
2.1%
사용끝지하층 41
 
0.5%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
10 2
 
< 0.1%
19 1
 
< 0.1%

Length

2024-04-17T01:35:44.365906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:44.493191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4632
54.6%
na 3597
42.4%
1 182
 
2.1%
사용끝지하층 41
 
0.5%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
10 2
 
< 0.1%
19 1
 
< 0.1%

usejisgstflr
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
2467 
1
1902 
<NA>
1854 
2
979 
3
506 
Other values (15)
776 

Length

Max length7
Median length1
Mean length1.688826
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2467
29.1%
1 1902
22.4%
<NA> 1854
21.9%
2 979
 
11.5%
3 506
 
6.0%
4 305
 
3.6%
5 197
 
2.3%
6 69
 
0.8%
7 59
 
0.7%
사용시작지상층 37
 
0.4%
Other values (10) 109
 
1.3%

Length

2024-04-17T01:35:44.606114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2467
29.1%
1 1902
22.4%
na 1854
21.9%
2 979
 
11.5%
3 506
 
6.0%
4 305
 
3.6%
5 197
 
2.3%
6 69
 
0.8%
7 59
 
0.7%
사용시작지상층 37
 
0.4%
Other values (10) 109
 
1.3%

useunderstflr
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
5571 
<NA>
2646 
1
 
213
사용시작지하층
 
41
4
 
8
Other values (3)
 
5

Length

Max length7
Median length1
Mean length1.9646393
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5571
65.7%
<NA> 2646
31.2%
1 213
 
2.5%
사용시작지하층 41
 
0.5%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:35:44.706745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:44.806065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5571
65.7%
na 2646
31.2%
1 213
 
2.5%
사용시작지하층 41
 
0.5%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

shpinfo
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
선박제원
 
95

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> 8389
98.9%
선박제원 95
 
1.1%

Length

2024-04-17T01:35:44.904062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:44.982652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
선박제원 95
 
1.1%

shpcnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
선박척수
 
95

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> 8389
98.9%
선박척수 95
 
1.1%

Length

2024-04-17T01:35:45.065240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:45.141834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
선박척수 95
 
1.1%

shptottons
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
선박총톤수
 
95

Length

Max length5
Median length4
Mean length4.0111975
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> 8389
98.9%
선박총톤수 95
 
1.1%

Length

2024-04-17T01:35:45.232254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:45.320676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
선박총톤수 95
 
1.1%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
4979 
<NA>
3468 
세탁기수
 
37

Length

Max length4
Median length1
Mean length2.2393918
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4979
58.7%
<NA> 3468
40.9%
세탁기수 37
 
0.4%

Length

2024-04-17T01:35:45.420784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:45.507256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4979
58.7%
na 3468
40.9%
세탁기수 37
 
0.4%

facilscp
Text

MISSING 

Distinct142
Distinct (%)42.1%
Missing8147
Missing (%)96.0%
Memory size66.4 KiB
2024-04-17T01:35:45.742257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.9109792
Min length2

Characters and Unicode

Total characters981
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

Unique77 ?
Unique (%)22.8%

Sample

1st row시설규모
2nd row시설규모
3rd row시설규모
4th row시설규모
5th row시설규모
ValueCountFrequency (%)
시설규모 64
 
19.0%
85 15
 
4.5%
46 7
 
2.1%
60 6
 
1.8%
83 6
 
1.8%
599 6
 
1.8%
63 5
 
1.5%
67 5
 
1.5%
84 4
 
1.2%
62 4
 
1.2%
Other values (132) 215
63.8%
2024-04-17T01:35:46.100011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 112
11.4%
5 86
 
8.8%
8 79
 
8.1%
2 70
 
7.1%
6 67
 
6.8%
9 67
 
6.8%
4 65
 
6.6%
7 65
 
6.6%
64
 
6.5%
64
 
6.5%
Other values (4) 242
24.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 725
73.9%
Other Letter 256
 
26.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 112
15.4%
5 86
11.9%
8 79
10.9%
2 70
9.7%
6 67
9.2%
9 67
9.2%
4 65
9.0%
7 65
9.0%
3 62
8.6%
0 52
7.2%
Other Letter
ValueCountFrequency (%)
64
25.0%
64
25.0%
64
25.0%
64
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 725
73.9%
Hangul 256
 
26.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 112
15.4%
5 86
11.9%
8 79
10.9%
2 70
9.7%
6 67
9.2%
9 67
9.2%
4 65
9.0%
7 65
9.0%
3 62
8.6%
0 52
7.2%
Hangul
ValueCountFrequency (%)
64
25.0%
64
25.0%
64
25.0%
64
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 725
73.9%
Hangul 256
 
26.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 112
15.4%
5 86
11.9%
8 79
10.9%
2 70
9.7%
6 67
9.2%
9 67
9.2%
4 65
9.0%
7 65
9.0%
3 62
8.6%
0 52
7.2%
Hangul
ValueCountFrequency (%)
64
25.0%
64
25.0%
64
25.0%
64
25.0%

facilar
Text

MISSING 

Distinct205
Distinct (%)60.8%
Missing8147
Missing (%)96.0%
Memory size66.4 KiB
2024-04-17T01:35:46.392501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.0089021
Min length2

Characters and Unicode

Total characters1688
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

Unique166 ?
Unique (%)49.3%

Sample

1st row시설면적
2nd row시설면적
3rd row시설면적
4th row시설면적
5th row시설면적
ValueCountFrequency (%)
시설면적 64
 
19.0%
45.5 6
 
1.8%
598.73 6
 
1.8%
218.85 4
 
1.2%
62.58 4
 
1.2%
337.46 3
 
0.9%
38.18 3
 
0.9%
84.59 3
 
0.9%
8546.81 3
 
0.9%
59.4 3
 
0.9%
Other values (195) 238
70.6%
2024-04-17T01:35:46.813355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 249
14.8%
1 157
9.3%
4 145
8.6%
8 143
8.5%
5 123
 
7.3%
2 114
 
6.8%
6 113
 
6.7%
3 112
 
6.6%
9 106
 
6.3%
7 103
 
6.1%
Other values (5) 323
19.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1183
70.1%
Other Letter 256
 
15.2%
Other Punctuation 249
 
14.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 157
13.3%
4 145
12.3%
8 143
12.1%
5 123
10.4%
2 114
9.6%
6 113
9.6%
3 112
9.5%
9 106
9.0%
7 103
8.7%
0 67
5.7%
Other Letter
ValueCountFrequency (%)
64
25.0%
64
25.0%
64
25.0%
64
25.0%
Other Punctuation
ValueCountFrequency (%)
. 249
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1432
84.8%
Hangul 256
 
15.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 249
17.4%
1 157
11.0%
4 145
10.1%
8 143
10.0%
5 123
8.6%
2 114
8.0%
6 113
7.9%
3 112
7.8%
9 106
7.4%
7 103
7.2%
Hangul
ValueCountFrequency (%)
64
25.0%
64
25.0%
64
25.0%
64
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1432
84.8%
Hangul 256
 
15.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 249
17.4%
1 157
11.0%
4 145
10.1%
8 143
10.0%
5 123
8.6%
2 114
8.0%
6 113
7.9%
3 112
7.8%
9 106
7.4%
7 103
7.2%
Hangul
ValueCountFrequency (%)
64
25.0%
64
25.0%
64
25.0%
64
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
 
95

Length

Max length4
Median length4
Mean length3.9664074
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> 8389
98.9%
95
 
1.1%

Length

2024-04-17T01:35:46.934504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:47.016441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
95
 
1.1%

yangsilcnt
Text

MISSING 

Distinct149
Distinct (%)2.0%
Missing897
Missing (%)10.6%
Memory size66.4 KiB
2024-04-17T01:35:47.160785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7395545
Min length1

Characters and Unicode

Total characters13198
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

Unique15 ?
Unique (%)0.2%

Sample

1st row107
2nd row81
3rd row16
4th row7
5th row5
ValueCountFrequency (%)
0 1041
 
13.7%
10 439
 
5.8%
18 368
 
4.9%
12 318
 
4.2%
14 314
 
4.1%
15 302
 
4.0%
13 248
 
3.3%
19 242
 
3.2%
17 222
 
2.9%
16 219
 
2.9%
Other values (139) 3874
51.1%
2024-04-17T01:35:47.483727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3433
26.0%
0 1920
14.5%
2 1872
14.2%
3 1342
 
10.2%
4 1038
 
7.9%
5 823
 
6.2%
8 812
 
6.2%
6 631
 
4.8%
9 615
 
4.7%
7 601
 
4.6%
Other values (3) 111
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13087
99.2%
Other Letter 111
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3433
26.2%
0 1920
14.7%
2 1872
14.3%
3 1342
 
10.3%
4 1038
 
7.9%
5 823
 
6.3%
8 812
 
6.2%
6 631
 
4.8%
9 615
 
4.7%
7 601
 
4.6%
Other Letter
ValueCountFrequency (%)
37
33.3%
37
33.3%
37
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13087
99.2%
Hangul 111
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3433
26.2%
0 1920
14.7%
2 1872
14.3%
3 1342
 
10.3%
4 1038
 
7.9%
5 823
 
6.3%
8 812
 
6.2%
6 631
 
4.8%
9 615
 
4.7%
7 601
 
4.6%
Hangul
ValueCountFrequency (%)
37
33.3%
37
33.3%
37
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13087
99.2%
Hangul 111
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3433
26.2%
0 1920
14.7%
2 1872
14.3%
3 1342
 
10.3%
4 1038
 
7.9%
5 823
 
6.3%
8 812
 
6.2%
6 631
 
4.8%
9 615
 
4.7%
7 601
 
4.6%
Hangul
ValueCountFrequency (%)
37
33.3%
37
33.3%
37
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
7894 
0
 
500
여성종사자수
 
68
2
 
6
1
 
6
Other values (4)
 
10

Length

Max length6
Median length4
Mean length3.831801
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> 7894
93.0%
0 500
 
5.9%
여성종사자수 68
 
0.8%
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

2024-04-17T01:35:47.592867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:47.684838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7894
93.0%
0 500
 
5.9%
여성종사자수 68
 
0.8%
2 6
 
0.1%
1 6
 
0.1%
3 5
 
0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

engstntrnmnm
Categorical

IMBALANCE 

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8334 
영문상호명
 
89
CheonghakSodam
 
3
Emerald ocean view
 
3
ocean house
 
3
Other values (41)
 
52

Length

Max length45
Median length4
Mean length4.094413
Min length4

Unique

Unique34 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8334
98.2%
영문상호명 89
 
1.0%
CheonghakSodam 3
 
< 0.1%
Emerald ocean view 3
 
< 0.1%
ocean house 3
 
< 0.1%
DYD COZY HOUSE 3
 
< 0.1%
H-avenue Hotel Gwanganlihaebyeon 3
 
< 0.1%
Brown-dot Hotel Suyeong 3
 
< 0.1%
BUSAN HAPPY HOUSE 3
 
< 0.1%
YoonSeulga 2
 
< 0.1%
Other values (36) 38
 
0.4%

Length

2024-04-17T01:35:48.043925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8334
97.3%
영문상호명 89
 
1.0%
house 29
 
0.3%
busan 9
 
0.1%
ocean 6
 
0.1%
hotel 6
 
0.1%
guest 5
 
0.1%
kim's 4
 
< 0.1%
brown-dot 3
 
< 0.1%
in 3
 
< 0.1%
Other values (55) 81
 
0.9%

engstntrnmaddr
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8337 
영문상호주소
 
89
Guesthouse for Foreign Tourists
 
15
Foreigner Tourism City home-stay Business
 
14
Guest House
 
4
Other values (15)
 
25

Length

Max length41
Median length4
Mean length4.2033239
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> 8337
98.3%
영문상호주소 89
 
1.0%
Guesthouse for Foreign Tourists 15
 
0.2%
Foreigner Tourism City home-stay Business 14
 
0.2%
Guest House 4
 
< 0.1%
Entertainment Business for foreigner only 3
 
< 0.1%
Oversea Travel Business 3
 
< 0.1%
TOURIST ACCOMMODATION 3
 
< 0.1%
TOURIST ACCOMMODATION (hostel) 3
 
< 0.1%
Hostel(Guesthouse) 2
 
< 0.1%
Other values (10) 11
 
0.1%

Length

2024-04-17T01:35:48.142744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8337
96.4%
영문상호주소 89
 
1.0%
for 22
 
0.3%
business 22
 
0.3%
foreign 21
 
0.2%
foreigner 19
 
0.2%
guesthouse 18
 
0.2%
tourists 18
 
0.2%
home-stay 15
 
0.2%
tourism 14
 
0.2%
Other values (18) 71
 
0.8%

yoksilcnt
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
5823 
<NA>
2436 
욕실수
 
37
15
 
16
12
 
14
Other values (28)
 
158

Length

Max length4
Median length1
Mean length1.8896747
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5823
68.6%
<NA> 2436
28.7%
욕실수 37
 
0.4%
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

2024-04-17T01:35:48.249939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 5823
68.6%
na 2436
28.7%
욕실수 37
 
0.4%
15 16
 
0.2%
12 14
 
0.2%
18 12
 
0.1%
10 12
 
0.1%
14 10
 
0.1%
9 10
 
0.1%
8 10
 
0.1%
Other values (23) 104
 
1.2%

sntuptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
여관업
5265 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
487
일반호텔
 
432
Other values (4)
635 

Length

Max length8
Median length3
Mean length3.6990806
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5265
62.1%
여인숙업 1076
 
12.7%
숙박업 기타 589
 
6.9%
숙박업(생활) 487
 
5.7%
일반호텔 432
 
5.1%
<NA> 319
 
3.8%
관광호텔 270
 
3.2%
위생업태명 37
 
0.4%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:35:48.352496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:48.471275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5265
58.0%
여인숙업 1076
 
11.9%
숙박업 589
 
6.5%
기타 589
 
6.5%
숙박업(생활 487
 
5.4%
일반호텔 432
 
4.8%
na 319
 
3.5%
관광호텔 270
 
3.0%
위생업태명 37
 
0.4%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
 
95

Length

Max length4
Median length4
Mean length3.9664074
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> 8389
98.9%
95
 
1.1%

Length

2024-04-17T01:35:48.588550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:48.672191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
95
 
1.1%

capt
Categorical

IMBALANCE 

Distinct40
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8311 
자본금
 
78
10000000
 
18
100000000
 
12
200000000
 
7
Other values (35)
 
58

Length

Max length10
Median length4
Mean length4.0397218
Min length3

Unique

Unique22 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8311
98.0%
자본금 78
 
0.9%
10000000 18
 
0.2%
100000000 12
 
0.1%
200000000 7
 
0.1%
50000000 5
 
0.1%
20000000 5
 
0.1%
300000000 4
 
< 0.1%
12500000 3
 
< 0.1%
12000000 3
 
< 0.1%
Other values (30) 38
 
0.4%

Length

2024-04-17T01:35:48.760950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8311
98.0%
자본금 78
 
0.9%
10000000 18
 
0.2%
100000000 12
 
0.1%
200000000 7
 
0.1%
50000000 5
 
0.1%
20000000 5
 
0.1%
300000000 4
 
< 0.1%
12500000 3
 
< 0.1%
12000000 3
 
< 0.1%
Other values (30) 38
 
0.4%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
제작취급품목내용
 
95

Length

Max length8
Median length4
Mean length4.0447902
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> 8389
98.9%
제작취급품목내용 95
 
1.1%

Length

2024-04-17T01:35:48.868571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:48.958977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
제작취급품목내용 95
 
1.1%

cndpermstymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8387 
조건부허가시작일자
 
95
20180202
 
2

Length

Max length9
Median length4
Mean length4.0569307
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> 8387
98.9%
조건부허가시작일자 95
 
1.1%
20180202 2
 
< 0.1%

Length

2024-04-17T01:35:49.053701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:49.142055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.9%
조건부허가시작일자 95
 
1.1%
20180202 2
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
조건부허가신고사유
 
95

Length

Max length9
Median length4
Mean length4.0559877
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> 8389
98.9%
조건부허가신고사유 95
 
1.1%

Length

2024-04-17T01:35:49.227693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:49.310577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
조건부허가신고사유 95
 
1.1%

cndpermendymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8387 
조건부허가종료일자
 
95
20190202
 
2

Length

Max length9
Median length4
Mean length4.0569307
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> 8387
98.9%
조건부허가종료일자 95
 
1.1%
20190202 2
 
< 0.1%

Length

2024-04-17T01:35:49.428192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:49.523875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.9%
조건부허가종료일자 95
 
1.1%
20190202 2
 
< 0.1%

chaircnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
5190 
0
3252 
좌석수
 
37
6
 
1
12
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length2.8440594
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5190
61.2%
0 3252
38.3%
좌석수 37
 
0.4%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-17T01:35:49.617597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:49.716232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5190
61.2%
0 3252
38.3%
좌석수 37
 
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 size66.4 KiB
<NA>
8299 
주변환경명
 
87
주택가주변
 
32
아파트지역
 
29
기타
 
22
Other values (3)
 
15

Length

Max length8
Median length4
Mean length4.0193305
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> 8299
97.8%
주변환경명 87
 
1.0%
주택가주변 32
 
0.4%
아파트지역 29
 
0.3%
기타 22
 
0.3%
학교정화(상대) 12
 
0.1%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-17T01:35:49.819855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:49.918950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8299
97.8%
주변환경명 87
 
1.0%
주택가주변 32
 
0.4%
아파트지역 29
 
0.3%
기타 22
 
0.3%
학교정화(상대 12
 
0.1%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대 1
 
< 0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8273 
지상층수
 
75
2
 
31
4
 
18
1
 
13
Other values (19)
 
74

Length

Max length4
Median length4
Mean length3.9561528
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8273
97.5%
지상층수 75
 
0.9%
2 31
 
0.4%
4 18
 
0.2%
1 13
 
0.2%
3 13
 
0.2%
5 8
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
19 6
 
0.1%
Other values (14) 33
 
0.4%

Length

2024-04-17T01:35:50.026274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8273
97.5%
지상층수 75
 
0.9%
2 31
 
0.4%
4 18
 
0.2%
1 13
 
0.2%
3 13
 
0.2%
5 8
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
19 6
 
0.1%
Other values (14) 33
 
0.4%

regnsenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8198 
일반주거지역
 
109
지역구분명
 
71
일반상업지역
 
37
주거지역
 
30
Other values (4)
 
39

Length

Max length6
Median length4
Mean length4.0469118
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> 8198
96.6%
일반주거지역 109
 
1.3%
지역구분명 71
 
0.8%
일반상업지역 37
 
0.4%
주거지역 30
 
0.4%
준주거지역 25
 
0.3%
상업지역 6
 
0.1%
자연녹지지역 5
 
0.1%
녹지지역 3
 
< 0.1%

Length

2024-04-17T01:35:50.137758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:50.248139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8198
96.6%
일반주거지역 109
 
1.3%
지역구분명 71
 
0.8%
일반상업지역 37
 
0.4%
주거지역 30
 
0.4%
준주거지역 25
 
0.3%
상업지역 6
 
0.1%
자연녹지지역 5
 
0.1%
녹지지역 3
 
< 0.1%

undernumlay
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8345 
지하층수
 
79
1
 
26
2
 
20
0
 
9
Other values (4)
 
5

Length

Max length4
Median length4
Mean length3.9787836
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8345
98.4%
지하층수 79
 
0.9%
1 26
 
0.3%
2 20
 
0.2%
0 9
 
0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:35:50.357280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:50.465440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8345
98.4%
지하층수 79
 
0.9%
1 26
 
0.3%
2 20
 
0.2%
0 9
 
0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

totnumlay
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8260 
총층수
 
71
2
 
36
4
 
20
1
 
18
Other values (20)
 
79

Length

Max length4
Median length4
Mean length3.9417727
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> 8260
97.4%
총층수 71
 
0.8%
2 36
 
0.4%
4 20
 
0.2%
1 18
 
0.2%
3 17
 
0.2%
5 12
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
11 6
 
0.1%
Other values (15) 30
 
0.4%

Length

2024-04-17T01:35:50.591100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8260
97.4%
총층수 71
 
0.8%
2 36
 
0.4%
4 20
 
0.2%
1 18
 
0.2%
3 17
 
0.2%
5 12
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
11 6
 
0.1%
Other values (15) 30
 
0.4%

abedcnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
4933 
<NA>
3512 
침대수
 
37
41
 
2

Length

Max length4
Median length1
Mean length2.2508251
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4933
58.1%
<NA> 3512
41.4%
침대수 37
 
0.4%
41 2
 
< 0.1%

Length

2024-04-17T01:35:50.691911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:50.781734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4933
58.1%
na 3512
41.4%
침대수 37
 
0.4%
41 2
 
< 0.1%

hanshilcnt
Categorical

Distinct48
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
3715 
<NA>
1458 
2
 
326
10
 
310
3
 
268
Other values (43)
2407 

Length

Max length4
Median length1
Mean length1.6743281
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3715
43.8%
<NA> 1458
 
17.2%
2 326
 
3.8%
10 310
 
3.7%
3 268
 
3.2%
1 262
 
3.1%
8 226
 
2.7%
4 203
 
2.4%
6 200
 
2.4%
9 197
 
2.3%
Other values (38) 1319
 
15.5%

Length

2024-04-17T01:35:50.882764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3715
43.8%
na 1458
 
17.2%
2 326
 
3.8%
10 310
 
3.7%
3 268
 
3.2%
1 262
 
3.1%
8 226
 
2.7%
4 203
 
2.4%
6 200
 
2.4%
9 197
 
2.3%
Other values (38) 1319
 
15.5%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
0
4941 
<NA>
3506 
회수건조수
 
37

Length

Max length5
Median length1
Mean length2.25719
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4941
58.2%
<NA> 3506
41.3%
회수건조수 37
 
0.4%

Length

2024-04-17T01:35:50.986607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:51.075820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4941
58.2%
na 3506
41.3%
회수건조수 37
 
0.4%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
8389 
회의실별동시수용인원
 
95

Length

Max length10
Median length4
Mean length4.0671853
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> 8389
98.9%
회의실별동시수용인원 95
 
1.1%

Length

2024-04-17T01:35:51.165106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:51.248167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8389
98.9%
회의실별동시수용인원 95
 
1.1%
Distinct2
Distinct (%)< 0.1%
Missing6
Missing (%)0.1%
Memory size66.4 KiB
Minimum2021-06-01 05:09:03
Maximum2021-06-01 05:09:04
2024-04-17T01:35:51.327252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:35:51.414742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 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>2021-06-01 05:09:03
91132500003250000-201-1972-0000303_11_03_PI2018-08-31 23:59:59.0<NA>주식회사 경원건설 호텔노아600045부산광역시 중구 남포동5가 81-1번지48983부산광역시 중구 자갈치로47번길 3-1 (남포동5가)19721010<NA><NA><NA><NA>01영업385043.08817179794.6106720171220145009관광호텔051-123-1234<NA>자가<NA>91<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9010<NA><NA><NA>0<NA><NA><NA>51<NA><NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>2021-06-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
84741302733600003360000-201-2021-0000103_11_03_PU2021-04-21 02:40:00.0숙박업신라스테이 서부산618200부산광역시 강서구 명지동 3595-1 신라스테이 서부산점46726.0부산광역시 강서구 명지국제7로 38, 신라스테이 서부산점 (명지동)20210331<NA><NA><NA><NA>영업/정상영업373665.73430842179173.52698920210419165344관광호텔051 661 9000<NA><NA><NA>233<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>2910<NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>040<NA>2021-06-01 05:09:04
84751302833300003330000-214-2021-0000203_11_03_PI2021-04-02 00:22:59.0숙박업벨리아(BELLIA)612847부산광역시 해운대구 중동 1123 해운대푸르지오시티48099.0부산광역시 해운대구 해운대해변로298번길 29, 해운대푸르지오시티 (중동)20210331<NA><NA><NA><NA>영업/정상영업397359.716406649186807.81129920210331103454숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>3<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>22737<NA><NA><NA>0<NA><NA><NA>300<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-06-01 05:09:04
84761302933800003380000-214-2021-0000403_11_03_PU2021-05-01 02:40:00.0숙박업위더스오션613805부산광역시 수영구 광안동 201-1 광안 지웰에스테이트 더 테라스48303.0부산광역시 수영구 광남로94번길 16, 광안 지웰에스테이트 더 테라스 3~19층 305호 외 33개호 (광안동)20210406<NA><NA><NA><NA>영업/정상영업392691.625721388185474.22691320210429170842숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>19030<NA><NA><NA>0<NA><NA><NA>340<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-06-01 05:09:04
84771303033300003330000-214-2021-0000303_11_03_PU2021-04-21 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073.0부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504720210419133601숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5<NA>1<NA><NA><NA><NA>0<NA><NA><NA>82<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-06-01 05:09:04
8478130313280000CDFI226221202100000103_11_04_PI2021-04-18 00:22:58.0외국인관광도시민박업윤슬가<NA>부산광역시 영도구 청학동 398-1549031.0부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415<NA><NA><NA><NA>영업/정상영업중387608.397605613179078.07581920210416160045<NA><NA><NA><NA>단독주택<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4545.45<NA><NA><NA>YoonSeulgaGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA><NA>주택가주변1일반주거지역<NA>1<NA><NA><NA><NA>2021-06-01 05:09:04
84791303233300003330000-214-2021-0000303_11_03_PU2021-04-21 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073.0부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504720210419133601숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5<NA>1<NA><NA><NA><NA>0<NA><NA><NA>82<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-06-01 05:09:04
8480130333280000CDFI226221202100000103_11_04_PI2021-04-18 00:22:58.0외국인관광도시민박업윤슬가<NA>부산광역시 영도구 청학동 398-1549031.0부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415<NA><NA><NA><NA>영업/정상영업중387608.397605613179078.07581920210416160045<NA><NA><NA><NA>단독주택<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4545.45<NA><NA><NA>YoonSeulgaGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA><NA>주택가주변1일반주거지역<NA>1<NA><NA><NA><NA>2021-06-01 05:09:04
8481130413330000CDFI226221201500002603_11_04_PI2021-05-26 00:22:56.0외국인관광도시민박업미포유<NA>부산광역시 해운대구 중동 946-1NaN부산광역시 해운대구 달맞이길62번길 9-1 (중동)20150813<NA><NA><NA><NA>영업/정상영업중397758.722800944186726.0599220210524093757<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-06-01 05:09:04
84821304233800003380000-214-2021-0000603_11_03_PI2021-05-28 00:22:55.0숙박업제이스테이 펜트하우스613805부산광역시 수영구 광안동 200-448303.0부산광역시 수영구 광안해변로 179, 5층 (광안동)20210526폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업392732.161638137185542.45270220210526143114숙박업(생활)전화번호객실수건물소유구분명건물용도명00건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자0놀이기구수내역놀이시설수N무대면적문화사업자구분명문화체육업종명N보험기관명보험시작일자보험종료일자부대시설내역5사용끝지하층5사용시작지하층선박제원선박척수선박총톤수0시설규모시설면적40영문상호명영문상호주소0숙박업(생활)자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주변환경명지상층수지역구분명지하층수총층수000회의실별동시수용인원2021-06-01 05:09:04
8483130433380000CDFI226003202100000303_11_01_PI2021-05-28 00:22:55.0관광숙박업제이스테이 펜트하우스<NA>부산광역시 수영구 광안동 200-448303.0부산광역시 수영구 광안해변로 179, 5층 (광안동)20210525<NA><NA><NA><NA>영업/정상영업중392732.161638137185542.45270220210526133221<NA><NA><NA><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>219218.85<NA><NA><NA><NA><NA><NA><NA><NA>125000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-06-01 05:09:04

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnwhladdrdcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
283330000CDFI226003201800000503_11_01_PU2019-04-14 02:40:00.0관광숙박업일로이리조트<NA>부산광역시 해운대구 송정동 809번지부산광역시 해운대구 송정구덕포길 130 (송정동)<NA><NA><NA><NA>영업/정상영업중187863.01536620190412092534<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>관광숙박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>599598.73<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4주거지역<NA>4<NA><NA><NA><NA>2021-06-01 05:09:046
23250000CDFI226221201900000103_11_04_PU2021-05-05 02:40:00.0외국인관광도시민박업보수동방공호지번우편번호부산광역시 중구 보수동1가 116-156부산광역시 중구 책방골목길 13-11 (보수동1가)20210427휴업시작일자휴업종료일자재개업일자폐업폐업180168.55870820210503101511업태구분명전화번호6건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수168167.82양실수여성종사자수영문상호명영문상호주소욕실수위생업태명자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수일반상업지역지하층수3침대수한실수회수건조수회의실별동시수용인원2021-06-01 05:09:043
33250000CDFI226221201900000203_11_04_PU2020-11-03 02:40:00.0외국인관광도시민박업제이온게스트하우스<NA>부산광역시 중구 부평동2가 21-8부산광역시 중구 중구로29번길 38, 4층 (부평동2가)<NA><NA><NA><NA>영업/정상영업중179818.66105720201031173301<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3838.18<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-06-01 05:09:043
732700003270000-201-2019-0000303_11_03_PI2019-06-23 02:21:37.0숙박업대구여관601829부산광역시 동구 초량동 388-2번지 지하1층, 지상1~3층, 4층 일부부산광역시 동구 중앙대로221번길 14-5 (초량동)<NA><NA><NA><NA>영업/정상영업181704.05848320190621114502여관업051-123-1234<NA>자가<NA>41<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4111<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>060<NA>2021-06-01 05:09:043
832700003270000-201-2019-0000503_11_03_PU2020-10-29 02:40:00.0숙박업단테하우스B601829부산광역시 동구 초량동 399부산광역시 동구 초량로13번길 58 (초량동)<NA><NA><NA><NA>영업/정상영업181627.55533520201027175551여관업<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4010<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-06-01 05:09:043
103280000CDFI226221202000000103_11_04_PU2021-05-23 02:40:00.0외국인관광도시민박업오션하우스지번우편번호부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1904호 (동삼동, 함지그린아파트)폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중176595.03493520210521172412업태구분명전화번호2건물소유구분명아파트건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수4645.5양실수여성종사자수ocean houseGuesthouse for Foreign Tourists욕실수위생업태명10000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수아파트지역20일반주거지역220침대수한실수회수건조수회의실별동시수용인원2021-06-01 05:09:043
113280000CDFI226221202000000203_11_04_PU2021-03-28 02:40:00.0외국인관광도시민박업에메랄드 오션뷰<NA>부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1902호 (동삼동, 함지그린아파트)<NA><NA><NA><NA>영업/정상영업중176595.03493520210326105821<NA><NA>1<NA>아파트<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>4645.5<NA><NA><NA>Emerald ocean viewGuesthouse for Foreign Tourists<NA><NA><NA><NA><NA><NA><NA><NA><NA>아파트지역20주거지역220<NA><NA><NA><NA>2021-06-01 05:09:043
123280000CDFI226221202000000303_11_04_PU2021-05-29 02:40:00.0외국인관광도시민박업청학소담<NA>부산광역시 영도구 청학동 398-20부산광역시 영도구 청학서로16번길 43-14 (청학동)<NA><NA><NA><NA>영업/정상영업중179086.90220320210527105330<NA><NA>1<NA>단독주택<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>8080.1<NA><NA><NA>CheonghakSodamGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA><NA>주택가주변<NA>일반주거지역<NA>1<NA><NA><NA><NA>2021-06-01 05:09:043
1732900003290000-201-2019-0000203_11_03_PU2020-12-15 02:40:00.0숙박업엑스모텔614846부산광역시 부산진구 부전동 226-5부산광역시 부산진구 신천대로50번길 34, 6층~9층 (부전동)<NA><NA><NA><NA>영업/정상영업185627.12814620201212162712일반호텔051 803 6996<NA><NA><NA>102<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9060<NA><NA><NA>0<NA><NA><NA>290<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-06-01 05:09:043
1832900003290000-201-2020-0000103_11_03_PU2020-12-15 02:40:00.0숙박업지지배614849부산광역시 부산진구 부전동 417-25부산광역시 부산진구 부전로 99-1, 3층 (부전동)<NA><NA><NA><NA>영업/정상영업186361.92755720201212135845여관업051 806 7779<NA>자가<NA>41<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA>3<NA><NA><NA><NA>0<NA><NA><NA>60<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-06-01 05:09:043