Overview

Dataset statistics

Number of variables81
Number of observations8504
Missing cells25516
Missing cells (%)3.7%
Duplicate rows355
Duplicate rows (%)4.2%
Total size in memory5.3 MiB
Average record size in memory650.0 B

Variable types

Unsupported5
Numeric2
Text10
Categorical62
DateTime2

Alerts

Dataset has 355 (4.2%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (89.9%)Imbalance
updategbn is highly imbalanced (67.6%)Imbalance
opnsvcnm is highly imbalanced (78.0%)Imbalance
clgstdt is highly imbalanced (96.4%)Imbalance
clgenddt is highly imbalanced (96.3%)Imbalance
ropnymd is highly imbalanced (89.5%)Imbalance
dtlstatenm is highly imbalanced (53.9%)Imbalance
stroomcnt is highly imbalanced (94.8%)Imbalance
bdngsrvnm is highly imbalanced (92.1%)Imbalance
bdngunderflrcnt is highly imbalanced (55.0%)Imbalance
cnstyarea is highly imbalanced (96.6%)Imbalance
svnsr is highly imbalanced (89.5%)Imbalance
plninsurstdt is highly imbalanced (89.5%)Imbalance
plninsurenddt is highly imbalanced (89.5%)Imbalance
maneipcnt is highly imbalanced (86.5%)Imbalance
playutscntdtl is highly imbalanced (89.5%)Imbalance
playfacilcnt is highly imbalanced (76.4%)Imbalance
multusnupsoyn is highly imbalanced (94.1%)Imbalance
stagear is highly imbalanced (92.8%)Imbalance
culwrkrsenm is highly imbalanced (89.5%)Imbalance
culphyedcobnm is highly imbalanced (87.9%)Imbalance
geicpfacilen is highly imbalanced (89.5%)Imbalance
balhansilyn is highly imbalanced (93.4%)Imbalance
bcfacilen is highly imbalanced (89.5%)Imbalance
insurorgnm is highly imbalanced (96.9%)Imbalance
insurstdt is highly imbalanced (89.5%)Imbalance
insurenddt is highly imbalanced (89.5%)Imbalance
afc is highly imbalanced (89.5%)Imbalance
useunderendflr is highly imbalanced (63.7%)Imbalance
useunderstflr is highly imbalanced (62.7%)Imbalance
shpinfo is highly imbalanced (89.5%)Imbalance
shpcnt is highly imbalanced (92.8%)Imbalance
shptottons is highly imbalanced (92.8%)Imbalance
infoben is highly imbalanced (89.5%)Imbalance
wmeipcnt is highly imbalanced (85.5%)Imbalance
engstntrnmnm is highly imbalanced (96.4%)Imbalance
engstntrnmaddr is highly imbalanced (95.8%)Imbalance
yoksilcnt is highly imbalanced (77.1%)Imbalance
dispenen is highly imbalanced (89.5%)Imbalance
capt is highly imbalanced (95.6%)Imbalance
mnfactreartclcn is highly imbalanced (89.5%)Imbalance
cndpermstymd is highly imbalanced (89.5%)Imbalance
cndpermntwhy is highly imbalanced (89.5%)Imbalance
cndpermendymd is highly imbalanced (89.5%)Imbalance
chaircnt is highly imbalanced (65.9%)Imbalance
nearenvnm is highly imbalanced (92.9%)Imbalance
jisgnumlay is highly imbalanced (94.2%)Imbalance
regnsenm is highly imbalanced (90.3%)Imbalance
undernumlay is highly imbalanced (94.6%)Imbalance
totnumlay is highly imbalanced (93.9%)Imbalance
meetsamtimesygstf is highly imbalanced (92.8%)Imbalance
sitepostno has 292 (3.4%) missing valuesMissing
rdnwhladdr has 2550 (30.0%) missing valuesMissing
dcbymd has 4548 (53.5%) missing valuesMissing
x has 384 (4.5%) missing valuesMissing
y has 387 (4.6%) missing valuesMissing
sitetel has 121 (1.4%) missing valuesMissing
facilscp has 8148 (95.8%) missing valuesMissing
facilar has 8148 (95.8%) missing valuesMissing
yangsilcnt has 895 (10.5%) missing valuesMissing
skey is an unsupported type, check if it needs cleaning or further analysisUnsupported
rdnpostno is an unsupported type, check if it needs cleaning or further analysisUnsupported
apvpermymd is an unsupported type, check if it needs cleaning or further analysisUnsupported
x is an unsupported type, check if it needs cleaning or further analysisUnsupported
y is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 16:34:39.757175
Analysis finished2024-04-16 16:34:42.425434
Duration2.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.6 KiB

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3318954.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.9 KiB
2024-04-17T01:34:42.472823image/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 deviation42897.968
Coefficient of variation (CV)0.012925146
Kurtosis-0.97837856
Mean3318954.2
Median Absolute Deviation (MAD)30000
Skewness0.26488399
Sum2.821443 × 1010
Variance1.8402357 × 109
MonotonicityNot monotonic
2024-04-17T01:34:42.576457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1146
13.5%
3290000 1059
12.5%
3300000 893
10.5%
3390000 688
8.1%
3270000 655
 
7.7%
3320000 578
 
6.8%
3380000 502
 
5.9%
3250000 480
 
5.6%
3260000 405
 
4.8%
3370000 383
 
4.5%
Other values (6) 1712
20.1%
ValueCountFrequency (%)
3250000 480
5.6%
3260000 405
 
4.8%
3270000 655
7.7%
3280000 368
 
4.3%
3290000 1059
12.5%
3300000 893
10.5%
3310000 285
 
3.4%
3320000 578
6.8%
3330000 1146
13.5%
3340000 358
 
4.2%
ValueCountFrequency (%)
3400000 210
 
2.5%
3390000 688
8.1%
3380000 502
5.9%
3370000 383
 
4.5%
3360000 138
 
1.6%
3350000 353
 
4.2%
3340000 358
 
4.2%
3330000 1146
13.5%
3320000 578
6.8%
3310000 285
 
3.4%

mgtno
Text

Distinct4216
Distinct (%)49.6%
Missing3
Missing (%)< 0.1%
Memory size66.6 KiB
2024-04-17T01:34:42.765963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.914598
Min length20

Characters and Unicode

Total characters186296
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

Unique134 ?
Unique (%)1.6%

Sample

1st row3250000-201-2017-00002
2nd row3250000-201-2014-00001
3rd row3250000-214-2017-00003
4th row3250000-201-1971-00116
5th row3250000-201-2012-00005
ValueCountFrequency (%)
cdfi2262212019000001 15
 
0.2%
cdfi2262212018000001 12
 
0.1%
cdfi2262212015000001 12
 
0.1%
cdfi2262212015000002 11
 
0.1%
cdfi2262212016000001 11
 
0.1%
cdfi2262212017000001 11
 
0.1%
cdfi2262212016000002 10
 
0.1%
cdfi2262212020000001 10
 
0.1%
cdfi2262212017000002 9
 
0.1%
cdfi2260032020000001 9
 
0.1%
Other values (4206) 8391
98.7%
2024-04-17T01:34:43.090821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71739
38.5%
- 24414
 
13.1%
1 20106
 
10.8%
2 19969
 
10.7%
3 18239
 
9.8%
9 10161
 
5.5%
8 4974
 
2.7%
7 4872
 
2.6%
6 3709
 
2.0%
4 3617
 
1.9%
Other values (5) 4496
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160430
86.1%
Dash Punctuation 24414
 
13.1%
Uppercase Letter 1452
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71739
44.7%
1 20106
 
12.5%
2 19969
 
12.4%
3 18239
 
11.4%
9 10161
 
6.3%
8 4974
 
3.1%
7 4872
 
3.0%
6 3709
 
2.3%
4 3617
 
2.3%
5 3044
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 363
25.0%
D 363
25.0%
F 363
25.0%
I 363
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24414
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 184844
99.2%
Latin 1452
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 71739
38.8%
- 24414
 
13.2%
1 20106
 
10.9%
2 19969
 
10.8%
3 18239
 
9.9%
9 10161
 
5.5%
8 4974
 
2.7%
7 4872
 
2.6%
6 3709
 
2.0%
4 3617
 
2.0%
Latin
ValueCountFrequency (%)
C 363
25.0%
D 363
25.0%
F 363
25.0%
I 363
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 186296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 71739
38.5%
- 24414
 
13.1%
1 20106
 
10.8%
2 19969
 
10.7%
3 18239
 
9.8%
9 10161
 
5.5%
8 4974
 
2.7%
7 4872
 
2.6%
6 3709
 
2.0%
4 3617
 
1.9%
Other values (5) 4496
 
2.4%

opnsvcid
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
03_11_03_P
8138 
03_11_04_P
 
270
03_11_01_P
 
78
03_11_05_P
 
9
03_11_02_P
 
3
Other values (3)
 
6

Length

Max length10
Median length10
Mean length9.9978833
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 8138
95.7%
03_11_04_P 270
 
3.2%
03_11_01_P 78
 
0.9%
03_11_05_P 9
 
0.1%
03_11_02_P 3
 
< 0.1%
<NA> 3
 
< 0.1%
03_11_06_P 2
 
< 0.1%
03_11_07_P 1
 
< 0.1%

Length

2024-04-17T01:34:43.219616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:43.323095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8138
95.7%
03_11_04_p 270
 
3.2%
03_11_01_p 78
 
0.9%
03_11_05_p 9
 
0.1%
03_11_02_p 3
 
< 0.1%
na 3
 
< 0.1%
03_11_06_p 2
 
< 0.1%
03_11_07_p 1
 
< 0.1%

updategbn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
I
7541 
U
960 
180000000
 
3

Length

Max length9
Median length1
Mean length1.0028222
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7541
88.7%
U 960
 
11.3%
180000000 3
 
< 0.1%

Length

2024-04-17T01:34:43.443044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:43.534207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7541
88.7%
u 960
 
11.3%
180000000 3
 
< 0.1%
Distinct264
Distinct (%)3.1%
Missing3
Missing (%)< 0.1%
Memory size66.6 KiB
Minimum2018-08-31 23:59:59
Maximum2021-08-01 02:40:00
2024-04-17T01:34:43.633267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:34:43.753508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
7427 
숙박업
890 
외국인관광도시민박업
 
104
관광숙박업
 
78
한옥체험업
 
2
Other values (3)
 
3

Length

Max length10
Median length4
Mean length3.9788335
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> 7427
87.3%
숙박업 890
 
10.5%
외국인관광도시민박업 104
 
1.2%
관광숙박업 78
 
0.9%
한옥체험업 2
 
< 0.1%
자동차야영장업 1
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

Length

2024-04-17T01:34:43.884552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:43.988611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7427
87.3%
숙박업 890
 
10.5%
외국인관광도시민박업 104
 
1.2%
관광숙박업 78
 
0.9%
한옥체험업 2
 
< 0.1%
자동차야영장업 1
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

bplcnm
Text

Distinct3394
Distinct (%)39.9%
Missing3
Missing (%)< 0.1%
Memory size66.6 KiB
2024-04-17T01:34:44.250313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length5.1729208
Min length1

Characters and Unicode

Total characters43975
Distinct characters652
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

Unique306 ?
Unique (%)3.6%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 칠구(K79)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 241
 
2.4%
모텔 188
 
1.9%
게스트하우스 120
 
1.2%
여관 82
 
0.8%
hotel 65
 
0.6%
부산 51
 
0.5%
house 48
 
0.5%
해운대 39
 
0.4%
36
 
0.4%
여인숙 36
 
0.4%
Other values (3490) 9237
91.1%
2024-04-17T01:34:44.638849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2928
 
6.7%
2009
 
4.6%
1791
 
4.1%
1752
 
4.0%
1659
 
3.8%
1515
 
3.4%
1370
 
3.1%
1275
 
2.9%
766
 
1.7%
741
 
1.7%
Other values (642) 28169
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36960
84.0%
Uppercase Letter 2408
 
5.5%
Space Separator 1659
 
3.8%
Lowercase Letter 1216
 
2.8%
Decimal Number 528
 
1.2%
Open Punctuation 524
 
1.2%
Close Punctuation 524
 
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 (%)
2928
 
7.9%
2009
 
5.4%
1791
 
4.8%
1752
 
4.7%
1515
 
4.1%
1370
 
3.7%
1275
 
3.4%
766
 
2.1%
741
 
2.0%
622
 
1.7%
Other values (562) 22191
60.0%
Uppercase Letter
ValueCountFrequency (%)
E 254
 
10.5%
O 231
 
9.6%
H 215
 
8.9%
T 190
 
7.9%
S 169
 
7.0%
A 142
 
5.9%
L 138
 
5.7%
N 116
 
4.8%
U 101
 
4.2%
B 95
 
3.9%
Other values (16) 757
31.4%
Lowercase Letter
ValueCountFrequency (%)
e 197
16.2%
o 143
11.8%
s 101
8.3%
a 98
8.1%
n 90
 
7.4%
u 90
 
7.4%
t 85
 
7.0%
h 59
 
4.9%
l 58
 
4.8%
i 53
 
4.4%
Other values (16) 242
19.9%
Decimal Number
ValueCountFrequency (%)
2 130
24.6%
1 73
13.8%
5 66
12.5%
7 60
11.4%
9 59
11.2%
0 40
 
7.6%
6 35
 
6.6%
3 30
 
5.7%
4 25
 
4.7%
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 (%)
1659
100.0%
Open Punctuation
ValueCountFrequency (%)
( 524
100.0%
Close Punctuation
ValueCountFrequency (%)
) 524
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 36958
84.0%
Latin 3634
 
8.3%
Common 3375
 
7.7%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2928
 
7.9%
2009
 
5.4%
1791
 
4.8%
1752
 
4.7%
1515
 
4.1%
1370
 
3.7%
1275
 
3.4%
766
 
2.1%
741
 
2.0%
622
 
1.7%
Other values (558) 22189
60.0%
Latin
ValueCountFrequency (%)
E 254
 
7.0%
O 231
 
6.4%
H 215
 
5.9%
e 197
 
5.4%
T 190
 
5.2%
S 169
 
4.7%
o 143
 
3.9%
A 142
 
3.9%
L 138
 
3.8%
N 116
 
3.2%
Other values (44) 1839
50.6%
Common
ValueCountFrequency (%)
1659
49.2%
( 524
 
15.5%
) 524
 
15.5%
2 130
 
3.9%
1 73
 
2.2%
5 66
 
2.0%
7 60
 
1.8%
9 59
 
1.7%
. 57
 
1.7%
0 40
 
1.2%
Other values (15) 183
 
5.4%
Han
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36952
84.0%
ASCII 6994
 
15.9%
None 10
 
< 0.1%
Number Forms 10
 
< 0.1%
CJK 8
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2928
 
7.9%
2009
 
5.4%
1791
 
4.8%
1752
 
4.7%
1515
 
4.1%
1370
 
3.7%
1275
 
3.5%
766
 
2.1%
741
 
2.0%
622
 
1.7%
Other values (557) 22183
60.0%
ASCII
ValueCountFrequency (%)
1659
23.7%
( 524
 
7.5%
) 524
 
7.5%
E 254
 
3.6%
O 231
 
3.3%
H 215
 
3.1%
e 197
 
2.8%
T 190
 
2.7%
S 169
 
2.4%
o 143
 
2.0%
Other values (64) 2888
41.3%
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%
Missing292
Missing (%)3.4%
Memory size66.6 KiB
2024-04-17T01:34:44.933797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters49272
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 212
 
2.6%
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) 6421
78.2%
2024-04-17T01:34:45.307310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9840
20.0%
1 8037
16.3%
0 7995
16.2%
8 7929
16.1%
2 4293
8.7%
4 3444
 
7.0%
7 2596
 
5.3%
3 2461
 
5.0%
9 1405
 
2.9%
5 954
 
1.9%
Other values (5) 318
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48954
99.4%
Other Letter 318
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9840
20.1%
1 8037
16.4%
0 7995
16.3%
8 7929
16.2%
2 4293
8.8%
4 3444
 
7.0%
7 2596
 
5.3%
3 2461
 
5.0%
9 1405
 
2.9%
5 954
 
1.9%
Other Letter
ValueCountFrequency (%)
106
33.3%
53
16.7%
53
16.7%
53
16.7%
53
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 48954
99.4%
Hangul 318
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9840
20.1%
1 8037
16.4%
0 7995
16.3%
8 7929
16.2%
2 4293
8.8%
4 3444
 
7.0%
7 2596
 
5.3%
3 2461
 
5.0%
9 1405
 
2.9%
5 954
 
1.9%
Hangul
ValueCountFrequency (%)
106
33.3%
53
16.7%
53
16.7%
53
16.7%
53
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48954
99.4%
Hangul 318
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9840
20.1%
1 8037
16.4%
0 7995
16.3%
8 7929
16.2%
2 4293
8.8%
4 3444
 
7.0%
7 2596
 
5.3%
3 2461
 
5.0%
9 1405
 
2.9%
5 954
 
1.9%
Hangul
ValueCountFrequency (%)
106
33.3%
53
16.7%
53
16.7%
53
16.7%
53
16.7%
Distinct4083
Distinct (%)48.0%
Missing5
Missing (%)0.1%
Memory size66.6 KiB
2024-04-17T01:34:45.627830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length45
Mean length23.47888
Min length13

Characters and Unicode

Total characters199547
Distinct characters309
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique254 ?
Unique (%)3.0%

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 8499
23.5%
해운대구 1146
 
3.2%
부산진구 1059
 
2.9%
동래구 893
 
2.5%
t통b반 868
 
2.4%
사상구 688
 
1.9%
동구 655
 
1.8%
온천동 644
 
1.8%
북구 582
 
1.6%
부전동 503
 
1.4%
Other values (4288) 20648
57.1%
2024-04-17T01:34:46.110820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36094
18.1%
10321
 
5.2%
10066
 
5.0%
9974
 
5.0%
8873
 
4.4%
8744
 
4.4%
1 8591
 
4.3%
8525
 
4.3%
8505
 
4.3%
- 7894
 
4.0%
Other values (299) 81960
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113443
56.9%
Decimal Number 39770
 
19.9%
Space Separator 36094
 
18.1%
Dash Punctuation 7894
 
4.0%
Uppercase Letter 1783
 
0.9%
Other Punctuation 196
 
0.1%
Open Punctuation 124
 
0.1%
Close Punctuation 124
 
0.1%
Math Symbol 115
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10321
 
9.1%
10066
 
8.9%
9974
 
8.8%
8873
 
7.8%
8744
 
7.7%
8525
 
7.5%
8505
 
7.5%
7814
 
6.9%
7599
 
6.7%
1589
 
1.4%
Other values (263) 31433
27.7%
Uppercase Letter
ValueCountFrequency (%)
B 876
49.1%
T 869
48.7%
A 11
 
0.6%
K 6
 
0.3%
C 5
 
0.3%
S 3
 
0.2%
O 3
 
0.2%
G 2
 
0.1%
E 2
 
0.1%
M 2
 
0.1%
Other values (4) 4
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 8591
21.6%
2 5215
13.1%
3 4188
10.5%
4 4049
10.2%
5 3922
9.9%
0 3059
 
7.7%
6 3029
 
7.6%
7 2845
 
7.2%
8 2573
 
6.5%
9 2299
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 193
98.5%
. 2
 
1.0%
& 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
w 1
33.3%
e 1
33.3%
i 1
33.3%
Space Separator
ValueCountFrequency (%)
36094
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7894
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 124
100.0%
Math Symbol
ValueCountFrequency (%)
~ 115
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113443
56.9%
Common 84317
42.3%
Latin 1787
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10321
 
9.1%
10066
 
8.9%
9974
 
8.8%
8873
 
7.8%
8744
 
7.7%
8525
 
7.5%
8505
 
7.5%
7814
 
6.9%
7599
 
6.7%
1589
 
1.4%
Other values (263) 31433
27.7%
Common
ValueCountFrequency (%)
36094
42.8%
1 8591
 
10.2%
- 7894
 
9.4%
2 5215
 
6.2%
3 4188
 
5.0%
4 4049
 
4.8%
5 3922
 
4.7%
0 3059
 
3.6%
6 3029
 
3.6%
7 2845
 
3.4%
Other values (8) 5431
 
6.4%
Latin
ValueCountFrequency (%)
B 876
49.0%
T 869
48.6%
A 11
 
0.6%
K 6
 
0.3%
C 5
 
0.3%
S 3
 
0.2%
O 3
 
0.2%
G 2
 
0.1%
E 2
 
0.1%
M 2
 
0.1%
Other values (8) 8
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113443
56.9%
ASCII 86103
43.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36094
41.9%
1 8591
 
10.0%
- 7894
 
9.2%
2 5215
 
6.1%
3 4188
 
4.9%
4 4049
 
4.7%
5 3922
 
4.6%
0 3059
 
3.6%
6 3029
 
3.5%
7 2845
 
3.3%
Other values (25) 7217
 
8.4%
Hangul
ValueCountFrequency (%)
10321
 
9.1%
10066
 
8.9%
9974
 
8.8%
8873
 
7.8%
8744
 
7.7%
8525
 
7.5%
8505
 
7.5%
7814
 
6.9%
7599
 
6.7%
1589
 
1.4%
Other values (263) 31433
27.7%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Unsupported

REJECTED  UNSUPPORTED 

Missing17
Missing (%)0.2%
Memory size66.6 KiB

rdnwhladdr
Text

MISSING 

Distinct3024
Distinct (%)50.8%
Missing2550
Missing (%)30.0%
Memory size66.6 KiB
2024-04-17T01:34:46.415790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length62
Mean length27.86211
Min length5

Characters and Unicode

Total characters165891
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

Unique305 ?
Unique (%)5.1%

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 5953
 
19.1%
해운대구 928
 
3.0%
부산진구 725
 
2.3%
동래구 607
 
2.0%
사상구 515
 
1.7%
동구 489
 
1.6%
온천동 422
 
1.4%
수영구 400
 
1.3%
중구 390
 
1.3%
부전동 385
 
1.2%
Other values (2583) 20302
65.2%
2024-04-17T01:34:46.848492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25162
 
15.2%
7744
 
4.7%
7359
 
4.4%
7021
 
4.2%
6673
 
4.0%
6326
 
3.8%
1 6313
 
3.8%
6084
 
3.7%
5959
 
3.6%
( 5839
 
3.5%
Other values (359) 81411
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 98728
59.5%
Decimal Number 26879
 
16.2%
Space Separator 25162
 
15.2%
Open Punctuation 5839
 
3.5%
Close Punctuation 5839
 
3.5%
Dash Punctuation 1801
 
1.1%
Other Punctuation 1284
 
0.8%
Math Symbol 258
 
0.2%
Uppercase Letter 94
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7744
 
7.8%
7359
 
7.5%
7021
 
7.1%
6673
 
6.8%
6326
 
6.4%
6084
 
6.2%
5959
 
6.0%
5676
 
5.7%
3973
 
4.0%
3734
 
3.8%
Other values (317) 38179
38.7%
Uppercase Letter
ValueCountFrequency (%)
A 30
31.9%
B 22
23.4%
K 9
 
9.6%
C 5
 
5.3%
O 5
 
5.3%
S 4
 
4.3%
E 3
 
3.2%
F 2
 
2.1%
U 2
 
2.1%
G 2
 
2.1%
Other values (9) 10
 
10.6%
Decimal Number
ValueCountFrequency (%)
1 6313
23.5%
2 4111
15.3%
3 3024
11.3%
4 2290
 
8.5%
5 2148
 
8.0%
0 1926
 
7.2%
6 1910
 
7.1%
7 1857
 
6.9%
9 1703
 
6.3%
8 1597
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
b 1
25.0%
w 1
25.0%
e 1
25.0%
i 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 1274
99.2%
. 9
 
0.7%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
25162
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5839
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5839
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1801
100.0%
Math Symbol
ValueCountFrequency (%)
~ 258
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 98728
59.5%
Common 67062
40.4%
Latin 101
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7744
 
7.8%
7359
 
7.5%
7021
 
7.1%
6673
 
6.8%
6326
 
6.4%
6084
 
6.2%
5959
 
6.0%
5676
 
5.7%
3973
 
4.0%
3734
 
3.8%
Other values (317) 38179
38.7%
Latin
ValueCountFrequency (%)
A 30
29.7%
B 22
21.8%
K 9
 
8.9%
C 5
 
5.0%
O 5
 
5.0%
S 4
 
4.0%
E 3
 
3.0%
3
 
3.0%
F 2
 
2.0%
U 2
 
2.0%
Other values (14) 16
15.8%
Common
ValueCountFrequency (%)
25162
37.5%
1 6313
 
9.4%
( 5839
 
8.7%
) 5839
 
8.7%
2 4111
 
6.1%
3 3024
 
4.5%
4 2290
 
3.4%
5 2148
 
3.2%
0 1926
 
2.9%
6 1910
 
2.8%
Other values (8) 8500
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 98728
59.5%
ASCII 67160
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25162
37.5%
1 6313
 
9.4%
( 5839
 
8.7%
) 5839
 
8.7%
2 4111
 
6.1%
3 3024
 
4.5%
4 2290
 
3.4%
5 2148
 
3.2%
0 1926
 
2.9%
6 1910
 
2.8%
Other values (31) 8598
 
12.8%
Hangul
ValueCountFrequency (%)
7744
 
7.8%
7359
 
7.5%
7021
 
7.1%
6673
 
6.8%
6326
 
6.4%
6084
 
6.2%
5959
 
6.0%
5676
 
5.7%
3973
 
4.0%
3734
 
3.8%
Other values (317) 38179
38.7%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.6 KiB

dcbymd
Text

MISSING 

Distinct1356
Distinct (%)34.3%
Missing4548
Missing (%)53.5%
Memory size66.6 KiB
2024-04-17T01:34:47.101488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8897877
Min length4

Characters and Unicode

Total characters31212
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

Unique34 ?
Unique (%)0.9%

Sample

1st row20140310
2nd row20121231
3rd row20171120
4th row20171107
5th row20120514
ValueCountFrequency (%)
20041022 180
 
4.6%
폐업일자 109
 
2.8%
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%
20030123 18
 
0.5%
Other values (1346) 3403
86.0%
2024-04-17T01:34:47.454799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10358
33.2%
2 6528
20.9%
1 5589
17.9%
3 1434
 
4.6%
9 1403
 
4.5%
7 1213
 
3.9%
4 1136
 
3.6%
6 1093
 
3.5%
5 1070
 
3.4%
8 952
 
3.1%
Other values (4) 436
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30776
98.6%
Other Letter 436
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10358
33.7%
2 6528
21.2%
1 5589
18.2%
3 1434
 
4.7%
9 1403
 
4.6%
7 1213
 
3.9%
4 1136
 
3.7%
6 1093
 
3.6%
5 1070
 
3.5%
8 952
 
3.1%
Other Letter
ValueCountFrequency (%)
109
25.0%
109
25.0%
109
25.0%
109
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30776
98.6%
Hangul 436
 
1.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10358
33.7%
2 6528
21.2%
1 5589
18.2%
3 1434
 
4.7%
9 1403
 
4.6%
7 1213
 
3.9%
4 1136
 
3.7%
6 1093
 
3.6%
5 1070
 
3.5%
8 952
 
3.1%
Hangul
ValueCountFrequency (%)
109
25.0%
109
25.0%
109
25.0%
109
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30776
98.6%
Hangul 436
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10358
33.7%
2 6528
21.2%
1 5589
18.2%
3 1434
 
4.7%
9 1403
 
4.6%
7 1213
 
3.9%
4 1136
 
3.7%
6 1093
 
3.6%
5 1070
 
3.5%
8 952
 
3.1%
Hangul
ValueCountFrequency (%)
109
25.0%
109
25.0%
109
25.0%
109
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8378 
휴업시작일자
 
117
20210528
 
2
20201012
 
1
20160608
 
1
Other values (5)
 
5

Length

Max length8
Median length4
Mean length4.0317498
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> 8378
98.5%
휴업시작일자 117
 
1.4%
20210528 2
 
< 0.1%
20201012 1
 
< 0.1%
20160608 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20210701 1
 
< 0.1%
20201001 1
 
< 0.1%

Length

2024-04-17T01:34:47.589894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:47.708939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8378
98.5%
휴업시작일자 117
 
1.4%
20210528 2
 
< 0.1%
20201012 1
 
< 0.1%
20160608 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20210701 1
 
< 0.1%
20201001 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8379 
휴업종료일자
 
117
20230131
 
2
20170607
 
1
20180424
 
1
Other values (4)
 
4

Length

Max length8
Median length4
Mean length4.0312794
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> 8379
98.5%
휴업종료일자 117
 
1.4%
20230131 2
 
< 0.1%
20170607 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20211231 1
 
< 0.1%
20211001 1
 
< 0.1%

Length

2024-04-17T01:34:47.864297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:47.979125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8379
98.5%
휴업종료일자 117
 
1.4%
20230131 2
 
< 0.1%
20170607 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20211231 1
 
< 0.1%
20211001 1
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
재개업일자
 
117

Length

Max length5
Median length4
Mean length4.0137582
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
98.6%
재개업일자 117
 
1.4%

Length

2024-04-17T01:34:48.094206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:48.205090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
재개업일자 117
 
1.4%

trdstatenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
02
3708 
01
3544 
영업/정상
979 
13
 
118
폐업
 
90
Other values (4)
 
65

Length

Max length5
Median length2
Mean length2.346778
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
02 3708
43.6%
01 3544
41.7%
영업/정상 979
 
11.5%
13 118
 
1.4%
폐업 90
 
1.1%
03 53
 
0.6%
<NA> 6
 
0.1%
휴업 5
 
0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:34:48.320334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:48.447448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3708
43.6%
01 3544
41.7%
영업/정상 979
 
11.5%
13 118
 
1.4%
폐업 90
 
1.1%
03 53
 
0.6%
na 6
 
0.1%
휴업 5
 
0.1%
31 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
영업
4362 
폐업
3847 
영업중
 
282
휴업
 
9
<NA>
 
3

Length

Max length4
Median length2
Mean length2.0341016
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4362
51.3%
폐업 3847
45.2%
영업중 282
 
3.3%
휴업 9
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:34:48.605412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:48.708220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4362
51.3%
폐업 3847
45.2%
영업중 282
 
3.3%
휴업 9
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing384
Missing (%)4.5%
Memory size66.6 KiB

y
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing387
Missing (%)4.6%
Memory size66.6 KiB

lastmodts
Real number (ℝ)

Distinct3693
Distinct (%)43.4%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0133597 × 1013
Minimum1.9990211 × 1013
Maximum2.021073 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.9 KiB
2024-04-17T01:34:48.821127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0011011 × 1013
Q12.0060601 × 1013
median2.0171124 × 1013
Q32.0180625 × 1013
95-th percentile2.0210528 × 1013
Maximum2.021073 × 1013
Range2.2051915 × 1011
Interquartile range (IQR)1.200241 × 1011

Descriptive statistics

Standard deviation6.8630836 × 1010
Coefficient of variation (CV)0.0034087718
Kurtosis-0.95766929
Mean2.0133597 × 1013
Median Absolute Deviation (MAD)2.0007972 × 1010
Skewness-0.78011959
Sum1.7115571 × 1017
Variance4.7101917 × 1021
MonotonicityNot monotonic
2024-04-17T01:34:48.974666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19990428000000 62
 
0.7%
20040902000000 60
 
0.7%
19990920000000 60
 
0.7%
20030122000000 58
 
0.7%
20040203000000 50
 
0.6%
20030414000000 36
 
0.4%
20070531000000 36
 
0.4%
19990308000000 32
 
0.4%
20020515000000 32
 
0.4%
20030329000000 32
 
0.4%
Other values (3683) 8043
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 (%)
20210730154118 1
< 0.1%
20210730151930 2
< 0.1%
20210730145700 1
< 0.1%
20210730142315 1
< 0.1%
20210730140152 2
< 0.1%
20210730134502 2
< 0.1%
20210730115140 2
< 0.1%
20210730113130 1
< 0.1%
20210730112104 2
< 0.1%
20210730094231 2
< 0.1%

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
여관업
5245 
여인숙업
1076 
숙박업 기타
591 
숙박업(생활)
 
491
일반호텔
 
453
Other values (4)
648 

Length

Max length8
Median length3
Mean length3.7056679
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5245
61.7%
여인숙업 1076
 
12.7%
숙박업 기타 591
 
6.9%
숙박업(생활) 491
 
5.8%
일반호텔 453
 
5.3%
<NA> 317
 
3.7%
관광호텔 271
 
3.2%
업태구분명 51
 
0.6%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:34:49.113124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:49.210430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5245
57.7%
여인숙업 1076
 
11.8%
숙박업 591
 
6.5%
기타 591
 
6.5%
숙박업(생활 491
 
5.4%
일반호텔 453
 
5.0%
na 317
 
3.5%
관광호텔 271
 
3.0%
업태구분명 51
 
0.6%
휴양콘도미니엄업 9
 
0.1%

sitetel
Text

MISSING 

Distinct373
Distinct (%)4.4%
Missing121
Missing (%)1.4%
Memory size66.6 KiB
2024-04-17T01:34:49.379200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.904688
Min length4

Characters and Unicode

Total characters99797
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

Unique29 ?
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 7615
81.3%
051 679
 
7.2%
전화번호 48
 
0.5%
070 12
 
0.1%
806 9
 
0.1%
741 8
 
0.1%
746 8
 
0.1%
747 8
 
0.1%
803 7
 
0.1%
714 6
 
0.1%
Other values (461) 970
 
10.4%
2024-04-17T01:34:49.693671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24053
24.1%
2 15837
15.9%
3 15740
15.8%
- 15253
15.3%
0 8916
 
8.9%
5 8864
 
8.9%
4 8148
 
8.2%
993
 
1.0%
7 591
 
0.6%
8 488
 
0.5%
Other values (6) 914
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83359
83.5%
Dash Punctuation 15253
 
15.3%
Space Separator 993
 
1.0%
Other Letter 192
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24053
28.9%
2 15837
19.0%
3 15740
18.9%
0 8916
 
10.7%
5 8864
 
10.6%
4 8148
 
9.8%
7 591
 
0.7%
8 488
 
0.6%
6 436
 
0.5%
9 286
 
0.3%
Other Letter
ValueCountFrequency (%)
48
25.0%
48
25.0%
48
25.0%
48
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 15253
100.0%
Space Separator
ValueCountFrequency (%)
993
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99605
99.8%
Hangul 192
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24053
24.1%
2 15837
15.9%
3 15740
15.8%
- 15253
15.3%
0 8916
 
9.0%
5 8864
 
8.9%
4 8148
 
8.2%
993
 
1.0%
7 591
 
0.6%
8 488
 
0.5%
Other values (2) 722
 
0.7%
Hangul
ValueCountFrequency (%)
48
25.0%
48
25.0%
48
25.0%
48
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99605
99.8%
Hangul 192
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24053
24.1%
2 15837
15.9%
3 15740
15.8%
- 15253
15.3%
0 8916
 
9.0%
5 8864
 
8.9%
4 8148
 
8.2%
993
 
1.0%
7 591
 
0.6%
8 488
 
0.5%
Other values (2) 722
 
0.7%
Hangul
ValueCountFrequency (%)
48
25.0%
48
25.0%
48
25.0%
48
25.0%

stroomcnt
Categorical

IMBALANCE 

Distinct30
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8282 
객실수
 
84
1
 
40
2
 
30
3
 
19
Other values (25)
 
49

Length

Max length4
Median length4
Mean length3.9452023
Min length1

Unique

Unique15 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8282
97.4%
객실수 84
 
1.0%
1 40
 
0.5%
2 30
 
0.4%
3 19
 
0.2%
6 6
 
0.1%
7 5
 
0.1%
11 3
 
< 0.1%
4 3
 
< 0.1%
49 3
 
< 0.1%
Other values (20) 29
 
0.3%

Length

2024-04-17T01:34:49.810540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8282
97.4%
객실수 84
 
1.0%
1 40
 
0.5%
2 30
 
0.4%
3 19
 
0.2%
6 6
 
0.1%
7 5
 
0.1%
33 3
 
< 0.1%
0 3
 
< 0.1%
30 3
 
< 0.1%
Other values (20) 29
 
0.3%

bdngownsenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
6456 
자가
1175 
임대
773 
건물소유구분명
 
100

Length

Max length7
Median length4
Mean length3.5771402
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6456
75.9%
자가 1175
 
13.8%
임대 773
 
9.1%
건물소유구분명 100
 
1.2%

Length

2024-04-17T01:34:49.915318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:50.023191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6456
75.9%
자가 1175
 
13.8%
임대 773
 
9.1%
건물소유구분명 100
 
1.2%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8241 
건물용도명
 
87
단독주택
 
72
아파트
 
54
숙박시설
 
18
Other values (6)
 
32

Length

Max length15
Median length4
Mean length4.0104657
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8241
96.9%
건물용도명 87
 
1.0%
단독주택 72
 
0.8%
아파트 54
 
0.6%
숙박시설 18
 
0.2%
다세대주택 14
 
0.2%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 주택(공동주택적용) 4
 
< 0.1%
호텔 4
 
< 0.1%

Length

2024-04-17T01:34:50.389762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8241
96.9%
건물용도명 87
 
1.0%
단독주택 72
 
0.8%
아파트 54
 
0.6%
숙박시설 18
 
0.2%
다세대주택 14
 
0.2%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 4
 
< 0.1%
주택(공동주택적용 4
 
< 0.1%
Other values (2) 5
 
0.1%

bdngjisgflrcnt
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
0
2552 
<NA>
1651 
4
867 
3
749 
5
592 
Other values (30)
2093 

Length

Max length6
Median length1
Mean length1.6559266
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2552
30.0%
<NA> 1651
19.4%
4 867
 
10.2%
3 749
 
8.8%
5 592
 
7.0%
2 423
 
5.0%
8 321
 
3.8%
7 303
 
3.6%
6 303
 
3.6%
9 197
 
2.3%
Other values (25) 546
 
6.4%

Length

2024-04-17T01:34:50.501364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2552
30.0%
na 1651
19.4%
4 867
 
10.2%
3 749
 
8.8%
5 592
 
7.0%
2 423
 
5.0%
8 321
 
3.8%
6 303
 
3.6%
7 303
 
3.6%
9 197
 
2.3%
Other values (25) 546
 
6.4%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
0
4442 
<NA>
2217 
1
1493 
2
 
197
건물지하층수
 
51
Other values (9)
 
104

Length

Max length6
Median length1
Mean length1.812794
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4442
52.2%
<NA> 2217
26.1%
1 1493
 
17.6%
2 197
 
2.3%
건물지하층수 51
 
0.6%
4 36
 
0.4%
3 27
 
0.3%
5 17
 
0.2%
8 6
 
0.1%
6 4
 
< 0.1%
Other values (4) 14
 
0.2%

Length

2024-04-17T01:34:50.601383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4442
52.2%
na 2217
26.1%
1 1495
 
17.6%
2 197
 
2.3%
건물지하층수 51
 
0.6%
4 36
 
0.4%
3 27
 
0.3%
5 17
 
0.2%
8 6
 
0.1%
6 4
 
< 0.1%
Other values (3) 12
 
0.1%

cnstyarea
Categorical

IMBALANCE 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8369 
건축연면적
 
106
0
 
10
20571
 
3
2282
 
3
Other values (13)
 
13

Length

Max length5
Median length4
Mean length4.0081138
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> 8369
98.4%
건축연면적 106
 
1.2%
0 10
 
0.1%
20571 3
 
< 0.1%
2282 3
 
< 0.1%
352 1
 
< 0.1%
72 1
 
< 0.1%
39 1
 
< 0.1%
85 1
 
< 0.1%
437 1
 
< 0.1%
Other values (8) 8
 
0.1%

Length

2024-04-17T01:34:50.710256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8369
98.4%
건축연면적 106
 
1.2%
0 10
 
0.1%
20571 3
 
< 0.1%
2282 3
 
< 0.1%
530 1
 
< 0.1%
2038 1
 
< 0.1%
13440 1
 
< 0.1%
2971 1
 
< 0.1%
984 1
 
< 0.1%
Other values (8) 8
 
0.1%

svnsr
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
기념품종류
 
117

Length

Max length5
Median length4
Mean length4.0137582
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
98.6%
기념품종류 117
 
1.4%

Length

2024-04-17T01:34:50.814468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:50.896442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
기념품종류 117
 
1.4%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
기획여행보험시작일자
 
117

Length

Max length10
Median length4
Mean length4.0825494
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
98.6%
기획여행보험시작일자 117
 
1.4%

Length

2024-04-17T01:34:50.988089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:51.071291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
기획여행보험시작일자 117
 
1.4%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
기획여행보험종료일자
 
117

Length

Max length10
Median length4
Mean length4.0825494
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
98.6%
기획여행보험종료일자 117
 
1.4%

Length

2024-04-17T01:34:51.174911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:51.270240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
기획여행보험종료일자 117
 
1.4%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
7837 
0
 
554
남성종사자수
 
83
1
 
12
3
 
5
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.8136171
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> 7837
92.2%
0 554
 
6.5%
남성종사자수 83
 
1.0%
1 12
 
0.1%
3 5
 
0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
35 1
 
< 0.1%

Length

2024-04-17T01:34:51.364479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7837
92.2%
0 554
 
6.5%
남성종사자수 83
 
1.0%
1 12
 
0.1%
3 5
 
0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
35 1
 
< 0.1%

playutscntdtl
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
놀이기구수내역
 
117

Length

Max length7
Median length4
Mean length4.0412747
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
98.6%
놀이기구수내역 117
 
1.4%

Length

2024-04-17T01:34:51.470319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:51.555120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
놀이기구수내역 117
 
1.4%

playfacilcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
N
7612 
<NA>
788 
놀이시설수
 
90
0
 
11
Y
 
3

Length

Max length5
Median length1
Mean length1.3203198
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 7612
89.5%
<NA> 788
 
9.3%
놀이시설수 90
 
1.1%
0 11
 
0.1%
Y 3
 
< 0.1%

Length

2024-04-17T01:34:51.657544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:51.759997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 7612
89.5%
na 788
 
9.3%
놀이시설수 90
 
1.1%
0 11
 
0.1%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
N
8391 
<NA>
 
69
 
33
Y
 
11

Length

Max length4
Median length1
Mean length1.0243415
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8391
98.7%
<NA> 69
 
0.8%
33
 
0.4%
Y 11
 
0.1%

Length

2024-04-17T01:34:51.860433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:51.952270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8391
98.7%
na 69
 
0.8%
33
 
0.4%
y 11
 
0.1%

stagear
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8383 
무대면적
 
110
0
 
11

Length

Max length4
Median length4
Mean length3.9961195
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> 8383
98.6%
무대면적 110
 
1.3%
0 11
 
0.1%

Length

2024-04-17T01:34:52.045404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:52.132202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8383
98.6%
무대면적 110
 
1.3%
0 11
 
0.1%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
문화사업자구분명
 
117

Length

Max length8
Median length4
Mean length4.0550329
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
98.6%
문화사업자구분명 117
 
1.4%

Length

2024-04-17T01:34:52.227542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:52.319157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
문화사업자구분명 117
 
1.4%

culphyedcobnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8078 
외국인관광 도시민박업
 
267
관광숙박업
 
78
문화체육업종명
 
66
자동차야영장업
 
9
Other values (3)
 
6

Length

Max length11
Median length4
Mean length4.2562324
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
95.0%
외국인관광 도시민박업 267
 
3.1%
관광숙박업 78
 
0.9%
문화체육업종명 66
 
0.8%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%

Length

2024-04-17T01:34:52.424963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:52.559521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8078
92.1%
외국인관광 267
 
3.0%
도시민박업 267
 
3.0%
관광숙박업 78
 
0.9%
문화체육업종명 66
 
0.8%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%

geicpfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
 
117

Length

Max length4
Median length4
Mean length3.9587253
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> 8387
98.6%
117
 
1.4%

Length

2024-04-17T01:34:52.678425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:52.777306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
117
 
1.4%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
N
8378 
<NA>
 
69
 
33
Y
 
24

Length

Max length4
Median length1
Mean length1.0243415
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8378
98.5%
<NA> 69
 
0.8%
33
 
0.4%
Y 24
 
0.3%

Length

2024-04-17T01:34:52.868494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:52.955003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8378
98.5%
na 69
 
0.8%
33
 
0.4%
y 24
 
0.3%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
 
117

Length

Max length4
Median length4
Mean length3.9587253
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> 8387
98.6%
117
 
1.4%

Length

2024-04-17T01:34:53.049037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:53.145543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
117
 
1.4%

insurorgnm
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8365 
보험기관명
 
114
DB 손해보험
 
2
객실수/수용인원 : 2개/ 6명
 
2
객실수/수용인원:1/2
 
1
Other values (20)
 
20

Length

Max length22
Median length4
Mean length4.033396
Min length2

Unique

Unique21 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8365
98.4%
보험기관명 114
 
1.3%
DB 손해보험 2
 
< 0.1%
객실수/수용인원 : 2개/ 6명 2
 
< 0.1%
객실수/수용인원:1/2 1
 
< 0.1%
영업배상책임보험 증권 1
 
< 0.1%
객실수/수용인원 : 3/8 1
 
< 0.1%
객실수/수용인원:2/6 1
 
< 0.1%
객실수/수용인원: 3/8 1
 
< 0.1%
객실수/수용인원:2/3 1
 
< 0.1%
Other values (15) 15
 
0.2%

Length

2024-04-17T01:34:53.283090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8365
98.1%
보험기관명 114
 
1.3%
객실수/수용인원 6
 
0.1%
5
 
0.1%
db 2
 
< 0.1%
손해보험 2
 
< 0.1%
2개 2
 
< 0.1%
6명 2
 
< 0.1%
3/8 2
 
< 0.1%
농협손해보험주식회사 1
 
< 0.1%
Other values (22) 22
 
0.3%

insurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
보험시작일자
 
117

Length

Max length6
Median length4
Mean length4.0275165
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
98.6%
보험시작일자 117
 
1.4%

Length

2024-04-17T01:34:53.398553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:53.492780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
보험시작일자 117
 
1.4%

insurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
보험종료일자
 
117

Length

Max length6
Median length4
Mean length4.0275165
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
98.6%
보험종료일자 117
 
1.4%

Length

2024-04-17T01:34:53.587089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:53.700050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
보험종료일자 117
 
1.4%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
부대시설내역
 
117

Length

Max length6
Median length4
Mean length4.0275165
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
98.6%
부대시설내역 117
 
1.4%

Length

2024-04-17T01:34:53.801045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:53.888556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
부대시설내역 117
 
1.4%

usejisgendflr
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
2677 
0
1967 
4
762 
3
646 
5
470 
Other values (30)
1982 

Length

Max length6
Median length1
Mean length2.0137582
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2677
31.5%
0 1967
23.1%
4 762
 
9.0%
3 646
 
7.6%
5 470
 
5.5%
6 417
 
4.9%
2 389
 
4.6%
7 266
 
3.1%
8 258
 
3.0%
9 189
 
2.2%
Other values (25) 463
 
5.4%

Length

2024-04-17T01:34:53.976421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2677
31.5%
0 1967
23.1%
4 762
 
9.0%
3 646
 
7.6%
5 470
 
5.5%
6 417
 
4.9%
2 389
 
4.6%
7 266
 
3.1%
8 258
 
3.0%
9 189
 
2.2%
Other values (25) 463
 
5.4%

useunderendflr
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
0
4644 
<NA>
3591 
1
 
182
사용끝지하층
 
55
2
 
16
Other values (5)
 
16

Length

Max length6
Median length1
Mean length2.2995061
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4644
54.6%
<NA> 3591
42.2%
1 182
 
2.1%
사용끝지하층 55
 
0.6%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
10 2
 
< 0.1%
19 1
 
< 0.1%

Length

2024-04-17T01:34:54.083845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:54.191323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4644
54.6%
na 3591
42.2%
1 182
 
2.1%
사용끝지하층 55
 
0.6%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
10 2
 
< 0.1%
19 1
 
< 0.1%

usejisgstflr
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
0
2460 
1
1906 
<NA>
1849 
2
987 
3
510 
Other values (15)
792 

Length

Max length7
Median length1
Mean length1.696731
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2460
28.9%
1 1906
22.4%
<NA> 1849
21.7%
2 987
11.6%
3 510
 
6.0%
4 306
 
3.6%
5 195
 
2.3%
6 70
 
0.8%
7 59
 
0.7%
사용시작지상층 53
 
0.6%
Other values (10) 109
 
1.3%

Length

2024-04-17T01:34:54.309150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2460
28.9%
1 1906
22.4%
na 1849
21.7%
2 987
11.6%
3 510
 
6.0%
4 306
 
3.6%
5 195
 
2.3%
6 70
 
0.8%
7 59
 
0.7%
사용시작지상층 53
 
0.6%
Other values (10) 109
 
1.3%

useunderstflr
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
0
5583 
<NA>
2640 
1
 
215
사용시작지하층
 
53
4
 
8
Other values (3)
 
5

Length

Max length7
Median length1
Mean length1.9687206
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5583
65.7%
<NA> 2640
31.0%
1 215
 
2.5%
사용시작지하층 53
 
0.6%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:34:54.413197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:54.515753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5583
65.7%
na 2640
31.0%
1 215
 
2.5%
사용시작지하층 53
 
0.6%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

shpinfo
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
선박제원
 
117

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> 8387
98.6%
선박제원 117
 
1.4%

Length

2024-04-17T01:34:54.625154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:54.724274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
선박제원 117
 
1.4%

shpcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8383 
선박척수
 
110
0
 
11

Length

Max length4
Median length4
Mean length3.9961195
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> 8383
98.6%
선박척수 110
 
1.3%
0 11
 
0.1%

Length

2024-04-17T01:34:54.819611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:54.916748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8383
98.6%
선박척수 110
 
1.3%
0 11
 
0.1%

shptottons
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8383 
선박총톤수
 
110
0
 
11

Length

Max length5
Median length4
Mean length4.0090546
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> 8383
98.6%
선박총톤수 110
 
1.3%
0 11
 
0.1%

Length

2024-04-17T01:34:55.015760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:55.124411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8383
98.6%
선박총톤수 110
 
1.3%
0 11
 
0.1%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
0
4989 
<NA>
3464 
세탁기수
 
51

Length

Max length4
Median length1
Mean length2.2400047
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4989
58.7%
<NA> 3464
40.7%
세탁기수 51
 
0.6%

Length

2024-04-17T01:34:55.231085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:55.336278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4989
58.7%
na 3464
40.7%
세탁기수 51
 
0.6%

facilscp
Text

MISSING 

Distinct148
Distinct (%)41.6%
Missing8148
Missing (%)95.8%
Memory size66.6 KiB
2024-04-17T01:34:55.576788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.9269663
Min length2

Characters and Unicode

Total characters1042
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

Unique83 ?
Unique (%)23.3%

Sample

1st row시설규모
2nd row시설규모
3rd row시설규모
4th row시설규모
5th row시설규모
ValueCountFrequency (%)
시설규모 73
 
20.5%
85 16
 
4.5%
46 7
 
2.0%
67 6
 
1.7%
83 6
 
1.7%
60 6
 
1.7%
599 6
 
1.7%
62 5
 
1.4%
63 5
 
1.4%
57 4
 
1.1%
Other values (138) 222
62.4%
2024-04-17T01:34:55.995791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 113
10.8%
5 91
 
8.7%
8 81
 
7.8%
73
 
7.0%
73
 
7.0%
73
 
7.0%
73
 
7.0%
6 72
 
6.9%
2 72
 
6.9%
9 69
 
6.6%
Other values (4) 252
24.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 750
72.0%
Other Letter 292
 
28.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 113
15.1%
5 91
12.1%
8 81
10.8%
6 72
9.6%
2 72
9.6%
9 69
9.2%
4 67
8.9%
7 67
8.9%
3 65
8.7%
0 53
7.1%
Other Letter
ValueCountFrequency (%)
73
25.0%
73
25.0%
73
25.0%
73
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 750
72.0%
Hangul 292
 
28.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 113
15.1%
5 91
12.1%
8 81
10.8%
6 72
9.6%
2 72
9.6%
9 69
9.2%
4 67
8.9%
7 67
8.9%
3 65
8.7%
0 53
7.1%
Hangul
ValueCountFrequency (%)
73
25.0%
73
25.0%
73
25.0%
73
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 750
72.0%
Hangul 292
 
28.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 113
15.1%
5 91
12.1%
8 81
10.8%
6 72
9.6%
2 72
9.6%
9 69
9.2%
4 67
8.9%
7 67
8.9%
3 65
8.7%
0 53
7.1%
Hangul
ValueCountFrequency (%)
73
25.0%
73
25.0%
73
25.0%
73
25.0%

facilar
Text

MISSING 

Distinct215
Distinct (%)60.4%
Missing8148
Missing (%)95.8%
Memory size66.6 KiB
2024-04-17T01:34:56.307700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.988764
Min length2

Characters and Unicode

Total characters1776
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique176 ?
Unique (%)49.4%

Sample

1st row시설면적
2nd row시설면적
3rd row시설면적
4th row시설면적
5th row시설면적
ValueCountFrequency (%)
시설면적 73
 
20.5%
45.5 6
 
1.7%
598.73 6
 
1.7%
218.85 4
 
1.1%
62.58 4
 
1.1%
337.46 3
 
0.8%
38.18 3
 
0.8%
84.59 3
 
0.8%
8546.81 3
 
0.8%
59.4 3
 
0.8%
Other values (205) 248
69.7%
2024-04-17T01:34:56.754041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 258
14.5%
1 159
9.0%
8 149
8.4%
4 149
8.4%
5 128
 
7.2%
2 123
 
6.9%
6 118
 
6.6%
3 116
 
6.5%
9 110
 
6.2%
7 105
 
5.9%
Other values (5) 361
20.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1226
69.0%
Other Letter 292
 
16.4%
Other Punctuation 258
 
14.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 159
13.0%
8 149
12.2%
4 149
12.2%
5 128
10.4%
2 123
10.0%
6 118
9.6%
3 116
9.5%
9 110
9.0%
7 105
8.6%
0 69
5.6%
Other Letter
ValueCountFrequency (%)
73
25.0%
73
25.0%
73
25.0%
73
25.0%
Other Punctuation
ValueCountFrequency (%)
. 258
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1484
83.6%
Hangul 292
 
16.4%

Most frequent character per script

Common
ValueCountFrequency (%)
. 258
17.4%
1 159
10.7%
8 149
10.0%
4 149
10.0%
5 128
8.6%
2 123
8.3%
6 118
8.0%
3 116
7.8%
9 110
7.4%
7 105
7.1%
Hangul
ValueCountFrequency (%)
73
25.0%
73
25.0%
73
25.0%
73
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1484
83.6%
Hangul 292
 
16.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 258
17.4%
1 159
10.7%
8 149
10.0%
4 149
10.0%
5 128
8.6%
2 123
8.3%
6 118
8.0%
3 116
7.8%
9 110
7.4%
7 105
7.1%
Hangul
ValueCountFrequency (%)
73
25.0%
73
25.0%
73
25.0%
73
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
 
117

Length

Max length4
Median length4
Mean length3.9587253
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> 8387
98.6%
117
 
1.4%

Length

2024-04-17T01:34:56.884747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:56.976105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
117
 
1.4%

yangsilcnt
Text

MISSING 

Distinct148
Distinct (%)1.9%
Missing895
Missing (%)10.5%
Memory size66.6 KiB
2024-04-17T01:34:57.163706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7417532
Min length1

Characters and Unicode

Total characters13253
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

Unique14 ?
Unique (%)0.2%

Sample

1st row107
2nd row81
3rd row16
4th row7
5th row5
ValueCountFrequency (%)
0 1041
 
13.7%
10 439
 
5.8%
18 368
 
4.8%
12 318
 
4.2%
14 314
 
4.1%
15 302
 
4.0%
13 248
 
3.3%
19 242
 
3.2%
16 221
 
2.9%
17 220
 
2.9%
Other values (138) 3896
51.2%
2024-04-17T01:34:57.469668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3429
25.9%
0 1920
14.5%
2 1872
14.1%
3 1339
 
10.1%
4 1043
 
7.9%
5 822
 
6.2%
8 817
 
6.2%
6 641
 
4.8%
9 618
 
4.7%
7 599
 
4.5%
Other values (3) 153
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13100
98.8%
Other Letter 153
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3429
26.2%
0 1920
14.7%
2 1872
14.3%
3 1339
 
10.2%
4 1043
 
8.0%
5 822
 
6.3%
8 817
 
6.2%
6 641
 
4.9%
9 618
 
4.7%
7 599
 
4.6%
Other Letter
ValueCountFrequency (%)
51
33.3%
51
33.3%
51
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13100
98.8%
Hangul 153
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3429
26.2%
0 1920
14.7%
2 1872
14.3%
3 1339
 
10.2%
4 1043
 
8.0%
5 822
 
6.3%
8 817
 
6.2%
6 641
 
4.9%
9 618
 
4.7%
7 599
 
4.6%
Hangul
ValueCountFrequency (%)
51
33.3%
51
33.3%
51
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13100
98.8%
Hangul 153
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3429
26.2%
0 1920
14.7%
2 1872
14.3%
3 1339
 
10.2%
4 1043
 
8.0%
5 822
 
6.3%
8 817
 
6.2%
6 641
 
4.9%
9 618
 
4.7%
7 599
 
4.6%
Hangul
ValueCountFrequency (%)
51
33.3%
51
33.3%
51
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
7839 
0
 
560
여성종사자수
 
83
2
 
6
1
 
6
Other values (4)
 
10

Length

Max length6
Median length4
Mean length3.8145579
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> 7839
92.2%
0 560
 
6.6%
여성종사자수 83
 
1.0%
2 6
 
0.1%
1 6
 
0.1%
3 5
 
0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

Length

2024-04-17T01:34:57.593941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:57.705614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7839
92.2%
0 560
 
6.6%
여성종사자수 83
 
1.0%
2 6
 
0.1%
1 6
 
0.1%
3 5
 
0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

engstntrnmnm
Categorical

IMBALANCE 

Distinct50
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8336 
영문상호명
 
103
CheonghakSodam
 
3
Emerald ocean view
 
3
ocean house
 
3
Other values (45)
 
56

Length

Max length45
Median length4
Mean length4.0978363
Min length4

Unique

Unique38 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8336
98.0%
영문상호명 103
 
1.2%
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 (40) 42
 
0.5%

Length

2024-04-17T01:34:57.818115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8336
97.0%
영문상호명 103
 
1.2%
house 30
 
0.3%
busan 9
 
0.1%
ocean 6
 
0.1%
hotel 6
 
0.1%
guest 5
 
0.1%
kim's 4
 
< 0.1%
dyd 3
 
< 0.1%
emerald 3
 
< 0.1%
Other values (59) 85
 
1.0%

engstntrnmaddr
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8339 
영문상호주소
 
103
Guesthouse for Foreign Tourists
 
19
Foreigner Tourism City home-stay Business
 
14
Guest House
 
4
Other values (15)
 
25

Length

Max length41
Median length4
Mean length4.2188382
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> 8339
98.1%
영문상호주소 103
 
1.2%
Guesthouse for Foreign Tourists 19
 
0.2%
Foreigner Tourism City home-stay Business 14
 
0.2%
Guest House 4
 
< 0.1%
Entertainment Business for foreigner only 3
 
< 0.1%
Oversea Travel Business 3
 
< 0.1%
TOURIST ACCOMMODATION 3
 
< 0.1%
TOURIST ACCOMMODATION (hostel) 3
 
< 0.1%
Entertainment Business for Foreigner only 2
 
< 0.1%
Other values (10) 11
 
0.1%

Length

2024-04-17T01:34:58.189628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8339
96.1%
영문상호주소 103
 
1.2%
for 26
 
0.3%
foreign 25
 
0.3%
guesthouse 22
 
0.3%
tourists 22
 
0.3%
business 22
 
0.3%
foreigner 19
 
0.2%
home-stay 15
 
0.2%
tourism 14
 
0.2%
Other values (18) 71
 
0.8%

yoksilcnt
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
0
5833 
<NA>
2432 
욕실수
 
51
15
 
16
12
 
14
Other values (28)
 
158

Length

Max length4
Median length1
Mean length1.8894638
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5833
68.6%
<NA> 2432
28.6%
욕실수 51
 
0.6%
15 16
 
0.2%
12 14
 
0.2%
18 12
 
0.1%
10 12
 
0.1%
14 10
 
0.1%
22 10
 
0.1%
9 10
 
0.1%
Other values (23) 104
 
1.2%

Length

2024-04-17T01:34:58.321851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 5833
68.6%
na 2432
28.6%
욕실수 51
 
0.6%
15 16
 
0.2%
12 14
 
0.2%
18 12
 
0.1%
10 12
 
0.1%
14 10
 
0.1%
9 10
 
0.1%
8 10
 
0.1%
Other values (23) 104
 
1.2%

sntuptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
여관업
5245 
여인숙업
1076 
숙박업 기타
591 
숙박업(생활)
 
491
일반호텔
 
453
Other values (4)
648 

Length

Max length8
Median length3
Mean length3.7056679
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5245
61.7%
여인숙업 1076
 
12.7%
숙박업 기타 591
 
6.9%
숙박업(생활) 491
 
5.8%
일반호텔 453
 
5.3%
<NA> 317
 
3.7%
관광호텔 271
 
3.2%
위생업태명 51
 
0.6%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:34:58.452575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:58.566939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5245
57.7%
여인숙업 1076
 
11.8%
숙박업 591
 
6.5%
기타 591
 
6.5%
숙박업(생활 491
 
5.4%
일반호텔 453
 
5.0%
na 317
 
3.5%
관광호텔 271
 
3.0%
위생업태명 51
 
0.6%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
 
117

Length

Max length4
Median length4
Mean length3.9587253
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> 8387
98.6%
117
 
1.4%

Length

2024-04-17T01:34:58.707445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:58.795199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
117
 
1.4%

capt
Categorical

IMBALANCE 

Distinct42
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8307 
자본금
 
91
10000000
 
18
100000000
 
12
200000000
 
7
Other values (37)
 
69

Length

Max length10
Median length4
Mean length4.0380997
Min length1

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> 8307
97.7%
자본금 91
 
1.1%
10000000 18
 
0.2%
100000000 12
 
0.1%
200000000 7
 
0.1%
0 7
 
0.1%
50000000 6
 
0.1%
20000000 5
 
0.1%
300000000 4
 
< 0.1%
12500000 3
 
< 0.1%
Other values (32) 44
 
0.5%

Length

2024-04-17T01:34:58.885557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8307
97.7%
자본금 91
 
1.1%
10000000 18
 
0.2%
100000000 12
 
0.1%
200000000 7
 
0.1%
0 7
 
0.1%
50000000 6
 
0.1%
20000000 5
 
0.1%
300000000 4
 
< 0.1%
12500000 3
 
< 0.1%
Other values (32) 44
 
0.5%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
제작취급품목내용
 
117

Length

Max length8
Median length4
Mean length4.0550329
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
98.6%
제작취급품목내용 117
 
1.4%

Length

2024-04-17T01:34:58.985812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:59.077067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
제작취급품목내용 117
 
1.4%

cndpermstymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
조건부허가시작일자
 
117

Length

Max length9
Median length4
Mean length4.0687912
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
98.6%
조건부허가시작일자 117
 
1.4%

Length

2024-04-17T01:34:59.169811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:59.272853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
조건부허가시작일자 117
 
1.4%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
조건부허가신고사유
 
117

Length

Max length9
Median length4
Mean length4.0687912
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
98.6%
조건부허가신고사유 117
 
1.4%

Length

2024-04-17T01:34:59.380113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:59.489803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
조건부허가신고사유 117
 
1.4%

cndpermendymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8387 
조건부허가종료일자
 
117

Length

Max length9
Median length4
Mean length4.0687912
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
98.6%
조건부허가종료일자 117
 
1.4%

Length

2024-04-17T01:34:59.612987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:59.710613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8387
98.6%
조건부허가종료일자 117
 
1.4%

chaircnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
5034 
0
3421 
좌석수
 
44
6
 
1
12
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length2.7863358
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5034
59.2%
0 3421
40.2%
좌석수 44
 
0.5%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-17T01:34:59.825612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:34:59.968282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5034
59.2%
0 3421
40.2%
좌석수 44
 
0.5%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

nearenvnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8301 
주변환경명
 
99
주택가주변
 
36
아파트지역
 
29
기타
 
24
Other values (3)
 
15

Length

Max length8
Median length4
Mean length4.0206961
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> 8301
97.6%
주변환경명 99
 
1.2%
주택가주변 36
 
0.4%
아파트지역 29
 
0.3%
기타 24
 
0.3%
학교정화(상대) 12
 
0.1%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-17T01:35:00.087633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:00.198527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8301
97.6%
주변환경명 99
 
1.2%
주택가주변 36
 
0.4%
아파트지역 29
 
0.3%
기타 24
 
0.3%
학교정화(상대 12
 
0.1%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대 1
 
< 0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8272 
지상층수
 
87
2
 
31
4
 
19
1
 
15
Other values (21)
 
80

Length

Max length4
Median length4
Mean length3.9531985
Min length1

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> 8272
97.3%
지상층수 87
 
1.0%
2 31
 
0.4%
4 19
 
0.2%
1 15
 
0.2%
3 13
 
0.2%
5 9
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
11 6
 
0.1%
Other values (16) 38
 
0.4%

Length

2024-04-17T01:35:00.311438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8272
97.3%
지상층수 87
 
1.0%
2 31
 
0.4%
4 19
 
0.2%
1 15
 
0.2%
3 13
 
0.2%
5 9
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
11 6
 
0.1%
Other values (16) 38
 
0.4%

regnsenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8199 
일반주거지역
 
113
지역구분명
 
82
일반상업지역
 
37
주거지역
 
31
Other values (4)
 
42

Length

Max length6
Median length4
Mean length4.0493885
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> 8199
96.4%
일반주거지역 113
 
1.3%
지역구분명 82
 
1.0%
일반상업지역 37
 
0.4%
주거지역 31
 
0.4%
준주거지역 28
 
0.3%
상업지역 6
 
0.1%
자연녹지지역 5
 
0.1%
녹지지역 3
 
< 0.1%

Length

2024-04-17T01:35:00.414654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:00.526448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8199
96.4%
일반주거지역 113
 
1.3%
지역구분명 82
 
1.0%
일반상업지역 37
 
0.4%
주거지역 31
 
0.4%
준주거지역 28
 
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 size66.6 KiB
<NA>
8341 
지하층수
 
94
1
 
28
2
 
21
0
 
15
Other values (4)
 
5

Length

Max length4
Median length4
Mean length3.9756585
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> 8341
98.1%
지하층수 94
 
1.1%
1 28
 
0.3%
2 21
 
0.2%
0 15
 
0.2%
3 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:35:00.661869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:00.789486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8341
98.1%
지하층수 94
 
1.1%
1 28
 
0.3%
2 21
 
0.2%
0 15
 
0.2%
3 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%

totnumlay
Categorical

IMBALANCE 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8259 
총층수
 
83
2
 
37
4
 
21
1
 
19
Other values (21)
 
85

Length

Max length4
Median length4
Mean length3.9373236
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> 8259
97.1%
총층수 83
 
1.0%
2 37
 
0.4%
4 21
 
0.2%
1 19
 
0.2%
3 17
 
0.2%
5 12
 
0.1%
6 8
 
0.1%
20 7
 
0.1%
11 6
 
0.1%
Other values (16) 35
 
0.4%

Length

2024-04-17T01:35:00.904696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8259
97.1%
총층수 83
 
1.0%
2 37
 
0.4%
4 21
 
0.2%
1 19
 
0.2%
3 17
 
0.2%
5 12
 
0.1%
6 8
 
0.1%
20 7
 
0.1%
11 6
 
0.1%
Other values (16) 35
 
0.4%

abedcnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
0
4943 
<NA>
3508 
침대수
 
51
41
 
2

Length

Max length4
Median length1
Mean length2.2497648
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4943
58.1%
<NA> 3508
41.3%
침대수 51
 
0.6%
41 2
 
< 0.1%

Length

2024-04-17T01:35:01.009410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:01.107291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4943
58.1%
na 3508
41.3%
침대수 51
 
0.6%
41 2
 
< 0.1%

hanshilcnt
Categorical

Distinct48
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
0
3723 
<NA>
1456 
2
 
328
10
 
310
3
 
266
Other values (43)
2421 

Length

Max length4
Median length1
Mean length1.6753293
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3723
43.8%
<NA> 1456
 
17.1%
2 328
 
3.9%
10 310
 
3.6%
3 266
 
3.1%
1 262
 
3.1%
8 226
 
2.7%
4 203
 
2.4%
6 200
 
2.4%
9 197
 
2.3%
Other values (38) 1333
 
15.7%

Length

2024-04-17T01:35:01.211821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3723
43.8%
na 1456
 
17.1%
2 328
 
3.9%
10 310
 
3.6%
3 266
 
3.1%
1 262
 
3.1%
8 226
 
2.7%
4 203
 
2.4%
6 200
 
2.4%
9 197
 
2.3%
Other values (38) 1333
 
15.7%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
0
4951 
<NA>
3502 
회수건조수
 
51

Length

Max length5
Median length1
Mean length2.2594073
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4951
58.2%
<NA> 3502
41.2%
회수건조수 51
 
0.6%

Length

2024-04-17T01:35:01.335485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:01.442904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4951
58.2%
na 3502
41.2%
회수건조수 51
 
0.6%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
<NA>
8383 
회의실별동시수용인원
 
110
0
 
11

Length

Max length10
Median length4
Mean length4.07373
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> 8383
98.6%
회의실별동시수용인원 110
 
1.3%
0 11
 
0.1%

Length

2024-04-17T01:35:01.550058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:35:01.642178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8383
98.6%
회의실별동시수용인원 110
 
1.3%
0 11
 
0.1%
Distinct3
Distinct (%)< 0.1%
Missing6
Missing (%)0.1%
Memory size66.6 KiB
Minimum2021-08-01 05:09:03
Maximum2021-08-01 05:09:05
2024-04-17T01:35:01.723592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:35:01.822418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
0232500003250000-201-2017-0000203_11_03_PI2018-08-31 23:59:59.0<NA>(주)아이에이치엠 호텔포레 프리미어 남포지점600045부산광역시 중구 남포동5가 8-1번지48953.0부산광역시 중구 구덕로 54-1 (남포동5가)20170213<NA><NA><NA><NA>01영업385079.145433179894.98255720171123163559일반호텔051-123-1234<NA>임대<NA>162<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>14040<NA><NA><NA>0<NA><NA><NA>1070<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:03
1332500003250000-201-2014-0000103_11_03_PI2018-08-31 23:59:59.0<NA>호텔아벤트리부산600051부산광역시 중구 창선동1가 12-1번지48947.0부산광역시 중구 광복로39번길 6 (창선동1가)20140318<NA><NA><NA><NA>01영업385065.851535180046.79139420180727133623일반호텔051-123-1234<NA>자가<NA>84<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>8060<NA><NA><NA>0<NA><NA><NA>81<NA><NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:03
2432500003250000-214-2017-0000303_11_03_PI2018-08-31 23:59:59.0<NA>케이 칠구(K79)600092부산광역시 중구 대청동2가 23-3번지48948.0부산광역시 중구 광복로49번길 38 (대청동2가)20170731<NA><NA><NA><NA>01영업385140.157403180362.44609920180814140805숙박업(생활)051-123-1234<NA><NA><NA>51<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>3010<NA><NA><NA>0<NA><NA><NA>160<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:03
3532500003250000-201-1971-0011603_11_03_PI2018-08-31 23:59:59.0<NA>영하장600806부산광역시 중구 부평동2가 24-3번지48977.0부산광역시 중구 중구로23번길 34 (부평동2가)1971080720140310<NA><NA><NA>02폐업384736.73365180083.04251420121015144713여관업051-123-1234<NA>임대<NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>7<NA><NA><NA><NA>여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3<NA><NA>2021-08-01 05:09:03
4632500003250000-201-2012-0000503_11_03_PI2018-08-31 23:59:59.0<NA>누리게스트하우스 더셀프600012부산광역시 중구 중앙동2가 52-2번지48956.0부산광역시 중구 중앙대로49번길 13 (중앙동2가)2012112720121231<NA><NA><NA>02폐업385546.889042180289.00649820121127133856숙박업 기타051-123-1234<NA>임대<NA>50<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>2<NA>2<NA><NA><NA><NA>0<NA><NA><NA>5<NA><NA><NA>0숙박업 기타<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:03
5732500003250000-201-1988-0006903_11_03_PI2018-08-31 23:59:59.0<NA>야(Ya)600083부산광역시 중구 보수동3가 5-21번지48947.0부산광역시 중구 보수대로106번길 5 (보수동3가)1988012620171120<NA><NA><NA>02폐업384329.080801180631.27368220171120143429여관업051-123-1234<NA>임대<NA>00<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>10<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>020<NA>2021-08-01 05:09:03
6832500003250000-201-1970-0011603_11_03_PI2018-08-31 23:59:59.0<NA>세피아600071부산광역시 중구 부평동1가 41-7번지 ,848980.0부산광역시 중구 광복로12번길 7-5 (부평동1가, 41-7,8)19700828<NA><NA><NA><NA>01영업384788.862125179954.32496120180727110634여관업051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>16<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>020<NA>2021-08-01 05:09:03
7932500003250000-201-2007-0000203_11_03_PI2018-08-31 23:59:59.0<NA>식스나인모텔600046부산광역시 중구 남포동6가 29번지 (8~11층)48982.0부산광역시 중구 자갈치로 21 (남포동6가)20070712<NA><NA><NA><NA>01영업384804.909084179701.53297720180502092950여관업051-123-1234<NA>자가<NA>101<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>11080<NA><NA><NA>0<NA><NA><NA>25<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:03
81032500003250000-201-1971-0011703_11_03_PI2018-08-31 23:59:59.0<NA>동산장모텔600033부산광역시 중구 광복동3가 5-20번지48949.0부산광역시 중구 광복로67번길 30-22 (광복동3가)19710315<NA><NA><NA><NA>01영업385245.417649180087.31460420180727170224여관업051-123-1234<NA><NA><NA>30<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>4<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>080<NA>2021-08-01 05:09:03
91132500003250000-201-1972-0000303_11_03_PI2018-08-31 23:59:59.0<NA>주식회사 경원건설 호텔노아600045부산광역시 중구 남포동5가 81-1번지48983.0부산광역시 중구 자갈치로47번길 3-1 (남포동5가)19721010<NA><NA><NA><NA>01영업385043.08817179794.6106720171220145009관광호텔051-123-1234<NA>자가<NA>91<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9010<NA><NA><NA>0<NA><NA><NA>51<NA><NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>2021-08-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
84941302733600003360000-201-2021-0000103_11_03_PU2021-04-21 02:40:00.0숙박업신라스테이 서부산618200부산광역시 강서구 명지동 3595-1 신라스테이 서부산점46726부산광역시 강서구 명지국제7로 38, 신라스테이 서부산점 (명지동)20210331<NA><NA><NA><NA>영업/정상영업373665.73430842179173.52698928820210419165344관광호텔051 661 9000<NA><NA><NA>233<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>2910<NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>040<NA>2021-08-01 05:09:05
84951302833300003330000-214-2021-0000203_11_03_PI2021-04-02 00:22:59.0숙박업벨리아(BELLIA)612847부산광역시 해운대구 중동 1123 해운대푸르지오시티48099부산광역시 해운대구 해운대해변로298번길 29, 해운대푸르지오시티 (중동)20210331<NA><NA><NA><NA>영업/정상영업397359.716406649186807.81129899520210331103454숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>3<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>22737<NA><NA><NA>0<NA><NA><NA>300<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:05
84961302933800003380000-214-2021-0000403_11_03_PU2021-05-01 02:40:00.0숙박업위더스오션613805부산광역시 수영구 광안동 201-1 광안 지웰에스테이트 더 테라스48303부산광역시 수영구 광남로94번길 16, 광안 지웰에스테이트 더 테라스 3~19층 305호 외 33개호 (광안동)20210406<NA><NA><NA><NA>영업/정상영업392691.625721388185474.22691274120210429170842숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>19030<NA><NA><NA>0<NA><NA><NA>340<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:05
84971303033300003330000-214-2021-0000303_11_03_PU2021-04-21 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504686720210419133601숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5<NA>1<NA><NA><NA><NA>0<NA><NA><NA>82<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:05
8498130313280000CDFI226221202100000103_11_04_PU2021-06-23 02:40:00.0외국인관광도시민박업윤슬가<NA>부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415<NA><NA><NA><NA>영업/정상영업중387608.397605613179078.07581929720210621140737<NA><NA>1<NA>단독주택<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4545.45<NA><NA><NA>YoonSeulgaGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA><NA>주택가주변1일반주거지역<NA>1<NA><NA><NA><NA>2021-08-01 05:09:05
84991303233300003330000-214-2021-0000303_11_03_PU2021-04-21 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504686720210419133601숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5<NA>1<NA><NA><NA><NA>0<NA><NA><NA>82<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:05
8500130333280000CDFI226221202100000103_11_04_PU2021-06-23 02:40:00.0외국인관광도시민박업윤슬가<NA>부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415<NA><NA><NA><NA>영업/정상영업중387608.397605613179078.07581929720210621140737<NA><NA>1<NA>단독주택<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4545.45<NA><NA><NA>YoonSeulgaGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA><NA>주택가주변1일반주거지역<NA>1<NA><NA><NA><NA>2021-08-01 05:09:05
8501130413330000CDFI226221201500002603_11_04_PI2021-05-26 00:22:56.0외국인관광도시민박업미포유<NA>부산광역시 해운대구 중동 946-1NaN부산광역시 해운대구 달맞이길62번길 9-1 (중동)20150813<NA><NA><NA><NA>영업/정상영업중397758.722800944186726.05991974820210524093757<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-08-01 05:09:05
85021304233800003380000-214-2021-0000603_11_03_PU2021-06-27 02:40:00.0숙박업제이스테이 펜트하우스613805부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210526<NA><NA><NA><NA>영업/정상영업392732.161638137185542.45270223420210625155820숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5050<NA><NA><NA>0<NA><NA><NA>40<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:05
8503130433380000CDFI226003202100000303_11_01_PU2021-06-24 02:40:00.0관광숙박업제이스테이 펜트하우스지번우편번호부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210525폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392732.161638137185542.45270223420210622151628업태구분명전화번호4건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명관광숙박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수219218.85양실수여성종사자수영문상호명영문상호주소욕실수위생업태명125000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수지역구분명지하층수총층수침대수한실수회수건조수회의실별동시수용인원2021-08-01 05:09:05

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnwhladdrdcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmlastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
1593330000CDFI226003201800000503_11_01_PU2019-04-14 02:40:00.0관광숙박업일로이리조트<NA>부산광역시 해운대구 송정동 809번지부산광역시 해운대구 송정구덕포길 130 (송정동)<NA><NA><NA><NA>영업/정상영업중20190412092534<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>관광숙박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>599598.73<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4주거지역<NA>4<NA><NA><NA><NA>2021-08-01 05:09:046
33250000CDFI226221201900000103_11_04_PU2021-05-05 02:40:00.0외국인관광도시민박업보수동방공호지번우편번호부산광역시 중구 보수동1가 116-156부산광역시 중구 책방골목길 13-11 (보수동1가)20210427휴업시작일자휴업종료일자재개업일자폐업폐업20210503101511업태구분명전화번호6건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수168167.82양실수여성종사자수영문상호명영문상호주소욕실수위생업태명자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수일반상업지역지하층수3침대수한실수회수건조수회의실별동시수용인원2021-08-01 05:09:053
43250000CDFI226221201900000203_11_04_PU2020-11-03 02:40:00.0외국인관광도시민박업제이온게스트하우스<NA>부산광역시 중구 부평동2가 21-8부산광역시 중구 중구로29번길 38, 4층 (부평동2가)<NA><NA><NA><NA>영업/정상영업중20201031173301<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3838.18<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-08-01 05:09:053
832700003270000-201-2019-0000303_11_03_PU2021-06-20 02:40:00.0숙박업대구여관601829부산광역시 동구 초량동 388-2 지하1층, 지상1~3층, 4층 일부부산광역시 동구 중앙대로221번길 14-5 (초량동)<NA><NA><NA><NA>영업/정상영업20210618100954여관업051 467 5401<NA>자가<NA>41<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4111<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>060<NA>2021-08-01 05:09:053
932700003270000-201-2019-0000503_11_03_PU2020-10-29 02:40:00.0숙박업단테하우스B601829부산광역시 동구 초량동 399부산광역시 동구 초량로13번길 58 (초량동)<NA><NA><NA><NA>영업/정상영업20201027175551여관업<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4010<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:053
103280000CDFI226221202000000103_11_04_PU2021-05-23 02:40:00.0외국인관광도시민박업오션하우스지번우편번호부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1904호 (동삼동, 함지그린아파트)폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중20210521172412업태구분명전화번호2건물소유구분명아파트건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수4645.5양실수여성종사자수ocean houseGuesthouse for Foreign Tourists욕실수위생업태명10000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수아파트지역20일반주거지역220침대수한실수회수건조수회의실별동시수용인원2021-08-01 05:09:053
113280000CDFI226221202000000203_11_04_PU2021-07-19 02:40:00.0외국인관광도시민박업에메랄드 오션뷰지번우편번호부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1902호 (동삼동, 함지그린아파트)폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중20210717123956업태구분명전화번호1건물소유구분명아파트건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4645.5양실수여성종사자수Emerald ocean viewGuesthouse for Foreign Tourists욕실수위생업태명0제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0아파트지역20주거지역220침대수한실수회수건조수02021-08-01 05:09:053
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/정상영업중20210527105330<NA><NA>1<NA>단독주택<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>8080.1<NA><NA><NA>CheonghakSodamGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA><NA>주택가주변<NA>일반주거지역<NA>1<NA><NA><NA><NA>2021-08-01 05:09:053
1632900003290000-201-2019-0000203_11_03_PU2020-12-15 02:40:00.0숙박업엑스모텔614846부산광역시 부산진구 부전동 226-5부산광역시 부산진구 신천대로50번길 34, 6층~9층 (부전동)<NA><NA><NA><NA>영업/정상영업20201212162712일반호텔051 803 6996<NA><NA><NA>102<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9060<NA><NA><NA>0<NA><NA><NA>290<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:053
1732900003290000-201-2020-0000103_11_03_PU2020-12-15 02:40:00.0숙박업지지배614849부산광역시 부산진구 부전동 417-25부산광역시 부산진구 부전로 99-1, 3층 (부전동)<NA><NA><NA><NA>영업/정상영업20201212135845여관업051 806 7779<NA>자가<NA>41<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA>3<NA><NA><NA><NA>0<NA><NA><NA>60<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-08-01 05:09:053