Overview

Dataset statistics

Number of variables81
Number of observations8648
Missing cells38663
Missing cells (%)5.5%
Duplicate rows470
Duplicate rows (%)5.4%
Total size in memory5.4 MiB
Average record size in memory650.0 B

Variable types

Unsupported6
Numeric2
Text11
Categorical61
DateTime1

Alerts

Dataset has 470 (5.4%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (88.6%)Imbalance
opnsvcnm is highly imbalanced (66.4%)Imbalance
clgstdt is highly imbalanced (95.5%)Imbalance
clgenddt is highly imbalanced (95.5%)Imbalance
ropnymd is highly imbalanced (86.5%)Imbalance
dtlstatenm is highly imbalanced (53.2%)Imbalance
stroomcnt is highly imbalanced (92.1%)Imbalance
bdngsrvnm is highly imbalanced (90.5%)Imbalance
bdngunderflrcnt is highly imbalanced (54.6%)Imbalance
cnstyarea is highly imbalanced (94.2%)Imbalance
svnsr is highly imbalanced (86.5%)Imbalance
plninsurstdt is highly imbalanced (86.5%)Imbalance
plninsurenddt is highly imbalanced (86.5%)Imbalance
maneipcnt is highly imbalanced (78.8%)Imbalance
playutscntdtl is highly imbalanced (86.5%)Imbalance
playfacilcnt is highly imbalanced (57.8%)Imbalance
multusnupsoyn is highly imbalanced (89.4%)Imbalance
stagear is highly imbalanced (84.6%)Imbalance
culwrkrsenm is highly imbalanced (86.5%)Imbalance
culphyedcobnm is highly imbalanced (85.5%)Imbalance
geicpfacilen is highly imbalanced (86.5%)Imbalance
balhansilyn is highly imbalanced (88.8%)Imbalance
bcfacilen is highly imbalanced (86.5%)Imbalance
insurorgnm is highly imbalanced (96.2%)Imbalance
insurstdt is highly imbalanced (86.5%)Imbalance
insurenddt is highly imbalanced (86.5%)Imbalance
afc is highly imbalanced (86.5%)Imbalance
useunderendflr is highly imbalanced (62.1%)Imbalance
useunderstflr is highly imbalanced (62.8%)Imbalance
shpinfo is highly imbalanced (86.5%)Imbalance
shpcnt is highly imbalanced (84.6%)Imbalance
shptottons is highly imbalanced (84.6%)Imbalance
infoben is highly imbalanced (86.5%)Imbalance
wmeipcnt is highly imbalanced (77.1%)Imbalance
engstntrnmaddr is highly imbalanced (94.8%)Imbalance
yoksilcnt is highly imbalanced (77.1%)Imbalance
dispenen is highly imbalanced (86.5%)Imbalance
capt is highly imbalanced (93.3%)Imbalance
mnfactreartclcn is highly imbalanced (86.5%)Imbalance
cndpermstymd is highly imbalanced (86.5%)Imbalance
cndpermntwhy is highly imbalanced (86.5%)Imbalance
cndpermendymd is highly imbalanced (86.5%)Imbalance
nearenvnm is highly imbalanced (91.5%)Imbalance
jisgnumlay is highly imbalanced (91.6%)Imbalance
regnsenm is highly imbalanced (89.3%)Imbalance
undernumlay is highly imbalanced (91.0%)Imbalance
totnumlay is highly imbalanced (91.4%)Imbalance
meetsamtimesygstf is highly imbalanced (84.6%)Imbalance
sitepostno has 355 (4.1%) missing valuesMissing
rdnwhladdr has 2551 (29.5%) missing valuesMissing
dcbymd has 4362 (50.4%) missing valuesMissing
x has 394 (4.6%) missing valuesMissing
y has 397 (4.6%) missing valuesMissing
sitetel has 359 (4.2%) missing valuesMissing
facilscp has 8167 (94.4%) missing valuesMissing
facilar has 8167 (94.4%) missing valuesMissing
yangsilcnt has 958 (11.1%) missing valuesMissing
engstntrnmnm has 8414 (97.3%) missing valuesMissing
chaircnt has 4472 (51.7%) 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
chaircnt is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 16:28:59.096037
Analysis finished2024-04-16 16:29:01.417852
Duration2.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size67.7 KiB

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3319117.4
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.1 KiB
2024-04-17T01:29:01.459885image/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 deviation42921.651
Coefficient of variation (CV)0.012931646
Kurtosis-0.97822037
Mean3319117.4
Median Absolute Deviation (MAD)30000
Skewness0.26032845
Sum2.869377 × 1010
Variance1.8422681 × 109
MonotonicityNot monotonic
2024-04-17T01:29:01.553786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1204
13.9%
3290000 1063
12.3%
3300000 893
10.3%
3390000 689
 
8.0%
3270000 659
 
7.6%
3320000 578
 
6.7%
3380000 517
 
6.0%
3250000 488
 
5.6%
3260000 407
 
4.7%
3280000 392
 
4.5%
Other values (6) 1755
20.3%
ValueCountFrequency (%)
3250000 488
5.6%
3260000 407
 
4.7%
3270000 659
7.6%
3280000 392
 
4.5%
3290000 1063
12.3%
3300000 893
10.3%
3310000 285
 
3.3%
3320000 578
6.7%
3330000 1204
13.9%
3340000 363
 
4.2%
ValueCountFrequency (%)
3400000 226
 
2.6%
3390000 689
8.0%
3380000 517
6.0%
3370000 386
 
4.5%
3360000 140
 
1.6%
3350000 355
 
4.1%
3340000 363
 
4.2%
3330000 1204
13.9%
3320000 578
6.7%
3310000 285
 
3.3%

mgtno
Text

Distinct4317
Distinct (%)49.9%
Missing3
Missing (%)< 0.1%
Memory size67.7 KiB
2024-04-17T01:29:01.733217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.900521
Min length20

Characters and Unicode

Total characters189330
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

Unique215 ?
Unique (%)2.5%

Sample

1st row3250000-201-2017-00002
2nd row3250000-201-2014-00001
3rd row3250000-214-2017-00003
4th row3250000-201-1971-00116
5th row3250000-201-2012-00005
ValueCountFrequency (%)
cdfi2262212019000001 15
 
0.2%
cdfi2262212018000001 12
 
0.1%
cdfi2262212015000001 12
 
0.1%
cdfi2262212015000002 11
 
0.1%
cdfi2260032021000001 11
 
0.1%
cdfi2262212017000001 11
 
0.1%
cdfi2262212016000001 11
 
0.1%
cdfi2262212020000001 10
 
0.1%
cdfi2262212016000002 10
 
0.1%
cdfi2262212014000001 9
 
0.1%
Other values (4307) 8533
98.7%
2024-04-17T01:29:02.072300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72926
38.5%
- 24645
 
13.0%
2 20675
 
10.9%
1 20332
 
10.7%
3 18431
 
9.7%
9 10169
 
5.4%
8 4999
 
2.6%
7 4884
 
2.6%
6 3791
 
2.0%
4 3688
 
1.9%
Other values (5) 4790
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 162965
86.1%
Dash Punctuation 24645
 
13.0%
Uppercase Letter 1720
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72926
44.7%
2 20675
 
12.7%
1 20332
 
12.5%
3 18431
 
11.3%
9 10169
 
6.2%
8 4999
 
3.1%
7 4884
 
3.0%
6 3791
 
2.3%
4 3688
 
2.3%
5 3070
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 430
25.0%
D 430
25.0%
F 430
25.0%
I 430
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24645
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 187610
99.1%
Latin 1720
 
0.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72926
38.9%
- 24645
 
13.1%
2 20675
 
11.0%
1 20332
 
10.8%
3 18431
 
9.8%
9 10169
 
5.4%
8 4999
 
2.7%
7 4884
 
2.6%
6 3791
 
2.0%
4 3688
 
2.0%
Latin
ValueCountFrequency (%)
C 430
25.0%
D 430
25.0%
F 430
25.0%
I 430
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 189330
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72926
38.5%
- 24645
 
13.0%
2 20675
 
10.9%
1 20332
 
10.7%
3 18431
 
9.7%
9 10169
 
5.4%
8 4999
 
2.6%
7 4884
 
2.6%
6 3791
 
2.0%
4 3688
 
1.9%
Other values (5) 4790
 
2.5%

opnsvcid
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
03_11_03_P
8215 
03_11_04_P
 
308
03_11_01_P
 
106
03_11_05_P
 
9
03_11_02_P
 
3
Other values (3)
 
7

Length

Max length10
Median length10
Mean length9.9979186
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 8215
95.0%
03_11_04_P 308
 
3.6%
03_11_01_P 106
 
1.2%
03_11_05_P 9
 
0.1%
03_11_02_P 3
 
< 0.1%
03_11_06_P 3
 
< 0.1%
<NA> 3
 
< 0.1%
03_11_07_P 1
 
< 0.1%

Length

2024-04-17T01:29:02.204162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:02.329699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8215
95.0%
03_11_04_p 308
 
3.6%
03_11_01_p 106
 
1.2%
03_11_05_p 9
 
0.1%
03_11_02_p 3
 
< 0.1%
03_11_06_p 3
 
< 0.1%
na 3
 
< 0.1%
03_11_07_p 1
 
< 0.1%

updategbn
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
I
6521 
U
2124 
180000000
 
3

Length

Max length9
Median length1
Mean length1.0027752
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6521
75.4%
U 2124
 
24.6%
180000000 3
 
< 0.1%

Length

2024-04-17T01:29:02.452133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:02.559143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6521
75.4%
u 2124
 
24.6%
180000000 3
 
< 0.1%
Distinct469
Distinct (%)5.4%
Missing3
Missing (%)< 0.1%
Memory size67.7 KiB
Minimum2018-08-31 23:59:59
Maximum2022-09-01 02:40:00
2024-04-17T01:29:02.661551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:29:02.790749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
6403 
숙박업
1961 
외국인관광도시민박업
 
170
관광숙박업
 
106
자동차야영장업
 
3
Other values (3)
 
5

Length

Max length10
Median length4
Mean length3.9051804
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6403
74.0%
숙박업 1961
 
22.7%
외국인관광도시민박업 170
 
2.0%
관광숙박업 106
 
1.2%
자동차야영장업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

Length

2024-04-17T01:29:02.960016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:03.080266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6403
74.0%
숙박업 1961
 
22.7%
외국인관광도시민박업 170
 
2.0%
관광숙박업 106
 
1.2%
자동차야영장업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

bplcnm
Text

Distinct3528
Distinct (%)40.8%
Missing3
Missing (%)< 0.1%
Memory size67.7 KiB
2024-04-17T01:29:03.390751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length5.2719491
Min length1

Characters and Unicode

Total characters45576
Distinct characters655
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

Unique388 ?
Unique (%)4.5%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 친구(K친구)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 280
 
2.7%
모텔 183
 
1.8%
게스트하우스 119
 
1.1%
여관 82
 
0.8%
hotel 73
 
0.7%
부산 54
 
0.5%
house 49
 
0.5%
해운대 41
 
0.4%
37
 
0.4%
여인숙 36
 
0.3%
Other values (3647) 9485
90.9%
2024-04-17T01:29:03.794000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2983
 
6.5%
2016
 
4.4%
1811
 
4.0%
1781
 
3.9%
1717
 
3.8%
1559
 
3.4%
1488
 
3.3%
1274
 
2.8%
788
 
1.7%
762
 
1.7%
Other values (645) 29397
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38015
83.4%
Uppercase Letter 2614
 
5.7%
Space Separator 1811
 
4.0%
Lowercase Letter 1335
 
2.9%
Close Punctuation 559
 
1.2%
Open Punctuation 559
 
1.2%
Decimal Number 515
 
1.1%
Other Punctuation 115
 
0.3%
Dash Punctuation 32
 
0.1%
Letter Number 9
 
< 0.1%
Other values (4) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2983
 
7.8%
2016
 
5.3%
1781
 
4.7%
1717
 
4.5%
1559
 
4.1%
1488
 
3.9%
1274
 
3.4%
788
 
2.1%
762
 
2.0%
624
 
1.6%
Other values (565) 23023
60.6%
Uppercase Letter
ValueCountFrequency (%)
E 271
 
10.4%
O 254
 
9.7%
H 244
 
9.3%
T 210
 
8.0%
S 165
 
6.3%
L 164
 
6.3%
A 160
 
6.1%
N 131
 
5.0%
B 111
 
4.2%
U 100
 
3.8%
Other values (16) 804
30.8%
Lowercase Letter
ValueCountFrequency (%)
e 212
15.9%
o 154
11.5%
s 112
8.4%
n 110
8.2%
a 109
8.2%
u 95
 
7.1%
t 92
 
6.9%
h 63
 
4.7%
i 62
 
4.6%
l 58
 
4.3%
Other values (16) 268
20.1%
Decimal Number
ValueCountFrequency (%)
2 130
25.2%
1 71
13.8%
7 60
11.7%
5 58
11.3%
9 53
10.3%
0 42
 
8.2%
6 33
 
6.4%
4 28
 
5.4%
3 28
 
5.4%
8 12
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 67
58.3%
& 27
23.5%
' 9
 
7.8%
, 7
 
6.1%
; 2
 
1.7%
2
 
1.7%
: 1
 
0.9%
Letter Number
ValueCountFrequency (%)
5
55.6%
4
44.4%
Math Symbol
ValueCountFrequency (%)
2
50.0%
+ 2
50.0%
Space Separator
ValueCountFrequency (%)
1811
100.0%
Close Punctuation
ValueCountFrequency (%)
) 559
100.0%
Open Punctuation
ValueCountFrequency (%)
( 559
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
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 38015
83.4%
Latin 3958
 
8.7%
Common 3597
 
7.9%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2983
 
7.8%
2016
 
5.3%
1781
 
4.7%
1717
 
4.5%
1559
 
4.1%
1488
 
3.9%
1274
 
3.4%
788
 
2.1%
762
 
2.0%
624
 
1.6%
Other values (562) 23023
60.6%
Latin
ValueCountFrequency (%)
E 271
 
6.8%
O 254
 
6.4%
H 244
 
6.2%
e 212
 
5.4%
T 210
 
5.3%
S 165
 
4.2%
L 164
 
4.1%
A 160
 
4.0%
o 154
 
3.9%
N 131
 
3.3%
Other values (44) 1993
50.4%
Common
ValueCountFrequency (%)
1811
50.3%
) 559
 
15.5%
( 559
 
15.5%
2 130
 
3.6%
1 71
 
2.0%
. 67
 
1.9%
7 60
 
1.7%
5 58
 
1.6%
9 53
 
1.5%
0 42
 
1.2%
Other values (15) 187
 
5.2%
Han
ValueCountFrequency (%)
3
50.0%
1
 
16.7%
1
 
16.7%
1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38009
83.4%
ASCII 7541
 
16.5%
None 10
 
< 0.1%
Number Forms 9
 
< 0.1%
CJK 6
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2983
 
7.8%
2016
 
5.3%
1781
 
4.7%
1717
 
4.5%
1559
 
4.1%
1488
 
3.9%
1274
 
3.4%
788
 
2.1%
762
 
2.0%
624
 
1.6%
Other values (561) 23017
60.6%
ASCII
ValueCountFrequency (%)
1811
24.0%
) 559
 
7.4%
( 559
 
7.4%
E 271
 
3.6%
O 254
 
3.4%
H 244
 
3.2%
e 212
 
2.8%
T 210
 
2.8%
S 165
 
2.2%
L 164
 
2.2%
Other values (64) 3092
41.0%
None
ValueCountFrequency (%)
6
60.0%
2
 
20.0%
2
 
20.0%
Number Forms
ValueCountFrequency (%)
5
55.6%
4
44.4%
CJK
ValueCountFrequency (%)
3
50.0%
1
 
16.7%
1
 
16.7%
1
 
16.7%
Punctuation
ValueCountFrequency (%)
1
100.0%

sitepostno
Text

MISSING 

Distinct495
Distinct (%)6.0%
Missing355
Missing (%)4.1%
Memory size67.7 KiB
2024-04-17T01:29:04.169946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters49758
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.3%

Sample

1st row600045
2nd row600051
3rd row600092
4th row600806
5th row600012
ValueCountFrequency (%)
612821 319
 
3.8%
616801 254
 
3.1%
612040 226
 
2.7%
612847 189
 
2.3%
607833 175
 
2.1%
601829 145
 
1.7%
617807 136
 
1.6%
613828 131
 
1.6%
607831 126
 
1.5%
607842 114
 
1.4%
Other values (485) 6478
78.1%
2024-04-17T01:29:04.570948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9927
20.0%
1 8125
16.3%
0 8087
16.3%
8 7975
16.0%
2 4355
8.8%
4 3486
 
7.0%
7 2615
 
5.3%
3 2467
 
5.0%
9 1427
 
2.9%
5 964
 
1.9%
Other values (5) 330
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49428
99.3%
Other Letter 330
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9927
20.1%
1 8125
16.4%
0 8087
16.4%
8 7975
16.1%
2 4355
8.8%
4 3486
 
7.1%
7 2615
 
5.3%
3 2467
 
5.0%
9 1427
 
2.9%
5 964
 
2.0%
Other Letter
ValueCountFrequency (%)
110
33.3%
55
16.7%
55
16.7%
55
16.7%
55
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 49428
99.3%
Hangul 330
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9927
20.1%
1 8125
16.4%
0 8087
16.4%
8 7975
16.1%
2 4355
8.8%
4 3486
 
7.1%
7 2615
 
5.3%
3 2467
 
5.0%
9 1427
 
2.9%
5 964
 
2.0%
Hangul
ValueCountFrequency (%)
110
33.3%
55
16.7%
55
16.7%
55
16.7%
55
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49428
99.3%
Hangul 330
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9927
20.1%
1 8125
16.4%
0 8087
16.4%
8 7975
16.1%
2 4355
8.8%
4 3486
 
7.1%
7 2615
 
5.3%
3 2467
 
5.0%
9 1427
 
2.9%
5 964
 
2.0%
Hangul
ValueCountFrequency (%)
110
33.3%
55
16.7%
55
16.7%
55
16.7%
55
16.7%
Distinct4212
Distinct (%)48.7%
Missing5
Missing (%)0.1%
Memory size67.7 KiB
2024-04-17T01:29:04.848133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length43
Mean length23.216244
Min length13

Characters and Unicode

Total characters200658
Distinct characters313
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique307 ?
Unique (%)3.6%

Sample

1st row부산광역시 중구 남포동5가 8-1번지
2nd row부산광역시 중구 창선동1가 12-1번지
3rd row부산광역시 중구 대청동2가 23-3
4th row부산광역시 중구 부평동2가 24-3번지
5th row부산광역시 중구 중앙동2가 52-2번지
ValueCountFrequency (%)
부산광역시 8643
23.5%
해운대구 1204
 
3.3%
부산진구 1063
 
2.9%
동래구 893
 
2.4%
t통b반 868
 
2.4%
사상구 689
 
1.9%
동구 659
 
1.8%
온천동 644
 
1.7%
북구 582
 
1.6%
수영구 517
 
1.4%
Other values (4495) 21085
57.2%
2024-04-17T01:29:05.275819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36750
18.3%
10474
 
5.2%
10210
 
5.1%
10127
 
5.0%
9028
 
4.5%
8874
 
4.4%
1 8739
 
4.4%
8685
 
4.3%
8649
 
4.3%
- 7986
 
4.0%
Other values (303) 81136
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113181
56.4%
Decimal Number 40398
 
20.1%
Space Separator 36750
 
18.3%
Dash Punctuation 7986
 
4.0%
Uppercase Letter 1785
 
0.9%
Other Punctuation 195
 
0.1%
Open Punctuation 122
 
0.1%
Close Punctuation 122
 
0.1%
Math Symbol 118
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10474
 
9.3%
10210
 
9.0%
10127
 
8.9%
9028
 
8.0%
8874
 
7.8%
8685
 
7.7%
8649
 
7.6%
6735
 
6.0%
6510
 
5.8%
1666
 
1.5%
Other values (270) 32223
28.5%
Uppercase Letter
ValueCountFrequency (%)
B 876
49.1%
T 869
48.7%
A 12
 
0.7%
K 5
 
0.3%
C 5
 
0.3%
M 4
 
0.2%
O 3
 
0.2%
G 2
 
0.1%
E 2
 
0.1%
S 2
 
0.1%
Other values (4) 5
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 8739
21.6%
2 5303
13.1%
3 4255
10.5%
4 4111
10.2%
5 3978
9.8%
0 3099
 
7.7%
6 3073
 
7.6%
7 2884
 
7.1%
8 2605
 
6.4%
9 2351
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 192
98.5%
. 2
 
1.0%
& 1
 
0.5%
Space Separator
ValueCountFrequency (%)
36750
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7986
100.0%
Open Punctuation
ValueCountFrequency (%)
( 122
100.0%
Close Punctuation
ValueCountFrequency (%)
) 122
100.0%
Math Symbol
ValueCountFrequency (%)
~ 118
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113181
56.4%
Common 85691
42.7%
Latin 1786
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10474
 
9.3%
10210
 
9.0%
10127
 
8.9%
9028
 
8.0%
8874
 
7.8%
8685
 
7.7%
8649
 
7.6%
6735
 
6.0%
6510
 
5.8%
1666
 
1.5%
Other values (270) 32223
28.5%
Common
ValueCountFrequency (%)
36750
42.9%
1 8739
 
10.2%
- 7986
 
9.3%
2 5303
 
6.2%
3 4255
 
5.0%
4 4111
 
4.8%
5 3978
 
4.6%
0 3099
 
3.6%
6 3073
 
3.6%
7 2884
 
3.4%
Other values (8) 5513
 
6.4%
Latin
ValueCountFrequency (%)
B 876
49.0%
T 869
48.7%
A 12
 
0.7%
K 5
 
0.3%
C 5
 
0.3%
M 4
 
0.2%
O 3
 
0.2%
G 2
 
0.1%
E 2
 
0.1%
S 2
 
0.1%
Other values (5) 6
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113181
56.4%
ASCII 87476
43.6%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36750
42.0%
1 8739
 
10.0%
- 7986
 
9.1%
2 5303
 
6.1%
3 4255
 
4.9%
4 4111
 
4.7%
5 3978
 
4.5%
0 3099
 
3.5%
6 3073
 
3.5%
7 2884
 
3.3%
Other values (22) 7298
 
8.3%
Hangul
ValueCountFrequency (%)
10474
 
9.3%
10210
 
9.0%
10127
 
8.9%
9028
 
8.0%
8874
 
7.8%
8685
 
7.7%
8649
 
7.6%
6735
 
6.0%
6510
 
5.8%
1666
 
1.5%
Other values (270) 32223
28.5%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Unsupported

REJECTED  UNSUPPORTED 

Missing47
Missing (%)0.5%
Memory size67.7 KiB

rdnwhladdr
Text

MISSING 

Distinct3125
Distinct (%)51.3%
Missing2551
Missing (%)29.5%
Memory size67.7 KiB
2024-04-17T01:29:05.551185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length61
Mean length27.954896
Min length18

Characters and Unicode

Total characters170441
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

Unique383 ?
Unique (%)6.3%

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 6097
 
19.0%
해운대구 986
 
3.1%
부산진구 729
 
2.3%
동래구 607
 
1.9%
사상구 516
 
1.6%
동구 493
 
1.5%
온천동 422
 
1.3%
수영구 415
 
1.3%
중구 398
 
1.2%
부전동 388
 
1.2%
Other values (2681) 20961
65.5%
2024-04-17T01:29:05.983768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25915
 
15.2%
7912
 
4.6%
7517
 
4.4%
7180
 
4.2%
6855
 
4.0%
1 6472
 
3.8%
6467
 
3.8%
6244
 
3.7%
6103
 
3.6%
) 5964
 
3.5%
Other values (359) 83812
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 101423
59.5%
Decimal Number 27581
 
16.2%
Space Separator 25915
 
15.2%
Close Punctuation 5964
 
3.5%
Open Punctuation 5964
 
3.5%
Dash Punctuation 1826
 
1.1%
Other Punctuation 1384
 
0.8%
Math Symbol 284
 
0.2%
Uppercase Letter 96
 
0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7912
 
7.8%
7517
 
7.4%
7180
 
7.1%
6855
 
6.8%
6467
 
6.4%
6244
 
6.2%
6103
 
6.0%
5798
 
5.7%
4043
 
4.0%
3786
 
3.7%
Other values (320) 39518
39.0%
Uppercase Letter
ValueCountFrequency (%)
A 32
33.3%
B 21
21.9%
K 8
 
8.3%
O 5
 
5.2%
C 5
 
5.2%
M 4
 
4.2%
E 3
 
3.1%
S 3
 
3.1%
J 2
 
2.1%
G 2
 
2.1%
Other values (9) 11
 
11.5%
Decimal Number
ValueCountFrequency (%)
1 6472
23.5%
2 4191
15.2%
3 3100
11.2%
4 2367
 
8.6%
5 2224
 
8.1%
0 1991
 
7.2%
6 1957
 
7.1%
7 1905
 
6.9%
9 1738
 
6.3%
8 1636
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 1374
99.3%
. 9
 
0.7%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
25915
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5964
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5964
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1826
100.0%
Math Symbol
ValueCountFrequency (%)
~ 284
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 101423
59.5%
Common 68918
40.4%
Latin 100
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7912
 
7.8%
7517
 
7.4%
7180
 
7.1%
6855
 
6.8%
6467
 
6.4%
6244
 
6.2%
6103
 
6.0%
5798
 
5.7%
4043
 
4.0%
3786
 
3.7%
Other values (320) 39518
39.0%
Latin
ValueCountFrequency (%)
A 32
32.0%
B 21
21.0%
K 8
 
8.0%
O 5
 
5.0%
C 5
 
5.0%
M 4
 
4.0%
E 3
 
3.0%
3
 
3.0%
S 3
 
3.0%
J 2
 
2.0%
Other values (11) 14
14.0%
Common
ValueCountFrequency (%)
25915
37.6%
1 6472
 
9.4%
) 5964
 
8.7%
( 5964
 
8.7%
2 4191
 
6.1%
3 3100
 
4.5%
4 2367
 
3.4%
5 2224
 
3.2%
0 1991
 
2.9%
6 1957
 
2.8%
Other values (8) 8773
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 101423
59.5%
ASCII 69015
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25915
37.5%
1 6472
 
9.4%
) 5964
 
8.6%
( 5964
 
8.6%
2 4191
 
6.1%
3 3100
 
4.5%
4 2367
 
3.4%
5 2224
 
3.2%
0 1991
 
2.9%
6 1957
 
2.8%
Other values (28) 8870
 
12.9%
Hangul
ValueCountFrequency (%)
7912
 
7.8%
7517
 
7.4%
7180
 
7.1%
6855
 
6.8%
6467
 
6.4%
6244
 
6.2%
6103
 
6.0%
5798
 
5.7%
4043
 
4.0%
3786
 
3.7%
Other values (320) 39518
39.0%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size67.7 KiB

dcbymd
Text

MISSING 

Distinct1476
Distinct (%)34.4%
Missing4362
Missing (%)50.4%
Memory size67.7 KiB
2024-04-17T01:29:06.265618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8609426
Min length4

Characters and Unicode

Total characters33692
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

Unique52 ?
Unique (%)1.2%

Sample

1st row20140310
2nd row20121231
3rd row20171120
4th row20220224
5th row20210823
ValueCountFrequency (%)
20041022 180
 
4.2%
폐업일자 149
 
3.5%
20030122 64
 
1.5%
20120711 52
 
1.2%
20021024 38
 
0.9%
20030305 26
 
0.6%
20030101 24
 
0.6%
20030227 22
 
0.5%
20051117 20
 
0.5%
20030901 18
 
0.4%
Other values (1466) 3693
86.2%
2024-04-17T01:29:06.616661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11015
32.7%
2 7421
22.0%
1 5960
17.7%
3 1487
 
4.4%
9 1454
 
4.3%
7 1278
 
3.8%
4 1180
 
3.5%
6 1162
 
3.4%
5 1113
 
3.3%
8 1026
 
3.0%
Other values (4) 596
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33096
98.2%
Other Letter 596
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11015
33.3%
2 7421
22.4%
1 5960
18.0%
3 1487
 
4.5%
9 1454
 
4.4%
7 1278
 
3.9%
4 1180
 
3.6%
6 1162
 
3.5%
5 1113
 
3.4%
8 1026
 
3.1%
Other Letter
ValueCountFrequency (%)
149
25.0%
149
25.0%
149
25.0%
149
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33096
98.2%
Hangul 596
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11015
33.3%
2 7421
22.4%
1 5960
18.0%
3 1487
 
4.5%
9 1454
 
4.4%
7 1278
 
3.9%
4 1180
 
3.6%
6 1162
 
3.5%
5 1113
 
3.4%
8 1026
 
3.1%
Hangul
ValueCountFrequency (%)
149
25.0%
149
25.0%
149
25.0%
149
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33096
98.2%
Hangul 596
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11015
33.3%
2 7421
22.4%
1 5960
18.0%
3 1487
 
4.5%
9 1454
 
4.4%
7 1278
 
3.9%
4 1180
 
3.6%
6 1162
 
3.5%
5 1113
 
3.4%
8 1026
 
3.1%
Hangul
ValueCountFrequency (%)
149
25.0%
149
25.0%
149
25.0%
149
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8478 
휴업시작일자
 
160
20210916
 
2
20210528
 
2
20211129
 
1
Other values (5)
 
5

Length

Max length8
Median length4
Mean length4.0416281
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> 8478
98.0%
휴업시작일자 160
 
1.9%
20210916 2
 
< 0.1%
20210528 2
 
< 0.1%
20211129 1
 
< 0.1%
20220728 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20211031 1
 
< 0.1%

Length

2024-04-17T01:29:06.779416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:06.895641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8478
98.0%
휴업시작일자 160
 
1.9%
20210916 2
 
< 0.1%
20210528 2
 
< 0.1%
20211129 1
 
< 0.1%
20220728 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20211031 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8478 
휴업종료일자
 
160
20221130
 
2
20230131
 
2
20221128
 
1
Other values (5)
 
5

Length

Max length8
Median length4
Mean length4.0416281
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> 8478
98.0%
휴업종료일자 160
 
1.9%
20221130 2
 
< 0.1%
20230131 2
 
< 0.1%
20221128 1
 
< 0.1%
20230727 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20220131 1
 
< 0.1%

Length

2024-04-17T01:29:07.027369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:07.155500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8478
98.0%
휴업종료일자 160
 
1.9%
20221130 2
 
< 0.1%
20230131 2
 
< 0.1%
20221128 1
 
< 0.1%
20230727 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20220131 1
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
재개업일자
 
163

Length

Max length5
Median length4
Mean length4.0188483
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> 8485
98.1%
재개업일자 163
 
1.9%

Length

2024-04-17T01:29:07.281916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:07.361128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
재개업일자 163
 
1.9%

trdstatenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
02
3707 
01
2550 
영업/정상
1857 
폐업
380 
13
 
89
Other values (4)
 
65

Length

Max length5
Median length2
Mean length2.6451203
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row01
2nd row01
3rd row영업/정상
4th row02
5th row02

Common Values

ValueCountFrequency (%)
02 3707
42.9%
01 2550
29.5%
영업/정상 1857
21.5%
폐업 380
 
4.4%
13 89
 
1.0%
03 53
 
0.6%
휴업 7
 
0.1%
<NA> 4
 
< 0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:29:07.455919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:07.560976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3707
42.9%
01 2550
29.5%
영업/정상 1857
21.5%
폐업 380
 
4.4%
13 89
 
1.0%
03 53
 
0.6%
휴업 7
 
0.1%
na 4
 
< 0.1%
31 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
영업
4176 
폐업
4137 
영업중
 
321
휴업
 
10
<NA>
 
3

Length

Max length4
Median length2
Mean length2.0380435
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4176
48.3%
폐업 4137
47.8%
영업중 321
 
3.7%
휴업 10
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:29:07.702804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:07.806757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4176
48.3%
폐업 4137
47.8%
영업중 321
 
3.7%
휴업 10
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing394
Missing (%)4.6%
Memory size67.7 KiB

y
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing397
Missing (%)4.6%
Memory size67.7 KiB

lastmodts
Real number (ℝ)

Distinct3816
Distinct (%)44.1%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0140243 × 1013
Minimum1.9990211 × 1013
Maximum2.022083 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.1 KiB
2024-04-17T01:29:08.213922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0020207 × 1013
Q12.0061025 × 1013
median2.0171129 × 1013
Q32.0200211 × 1013
95-th percentile2.0220608 × 1013
Maximum2.022083 × 1013
Range2.3061914 × 1011
Interquartile range (IQR)1.3918614 × 1011

Descriptive statistics

Standard deviation7.33207 × 1010
Coefficient of variation (CV)0.0036405072
Kurtosis-1.0088705
Mean2.0140243 × 1013
Median Absolute Deviation (MAD)3.9987969 × 1010
Skewness-0.70649563
Sum1.741124 × 1017
Variance5.3759251 × 1021
MonotonicityNot monotonic
2024-04-17T01:29:08.350597image/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%
20070531000000 36
 
0.4%
20030414000000 36
 
0.4%
20040427000000 32
 
0.4%
20020515000000 32
 
0.4%
20030329000000 32
 
0.4%
Other values (3806) 8187
94.7%
ValueCountFrequency (%)
19990211000000 2
 
< 0.1%
19990218000000 20
0.2%
19990223000000 2
 
< 0.1%
19990225000000 6
 
0.1%
19990302000000 4
 
< 0.1%
19990303000000 18
0.2%
19990308000000 32
0.4%
19990309000000 6
 
0.1%
19990310000000 2
 
< 0.1%
19990315000000 2
 
< 0.1%
ValueCountFrequency (%)
20220830140506 2
< 0.1%
20220830131159 2
< 0.1%
20220830115205 2
< 0.1%
20220830093759 2
< 0.1%
20220829142229 2
< 0.1%
20220826170600 2
< 0.1%
20220826165331 1
< 0.1%
20220826151758 2
< 0.1%
20220826135050 2
< 0.1%
20220826124820 1
< 0.1%

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
여관업
5211 
여인숙업
1076 
숙박업 기타
592 
숙박업(생활)
534 
일반호텔
 
514
Other values (4)
721 

Length

Max length8
Median length3
Mean length3.7298797
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5211
60.3%
여인숙업 1076
 
12.4%
숙박업 기타 592
 
6.8%
숙박업(생활) 534
 
6.2%
일반호텔 514
 
5.9%
<NA> 382
 
4.4%
관광호텔 277
 
3.2%
업태구분명 53
 
0.6%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:29:08.459836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:08.565877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5211
56.4%
여인숙업 1076
 
11.6%
숙박업 592
 
6.4%
기타 592
 
6.4%
숙박업(생활 534
 
5.8%
일반호텔 514
 
5.6%
na 382
 
4.1%
관광호텔 277
 
3.0%
업태구분명 53
 
0.6%
휴양콘도미니엄업 9
 
0.1%

sitetel
Text

MISSING 

Distinct883
Distinct (%)10.7%
Missing359
Missing (%)4.2%
Memory size67.7 KiB
2024-04-17T01:29:08.801988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.807335
Min length4

Characters and Unicode

Total characters97871
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

Unique78 ?
Unique (%)0.9%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051 242 8279
4th row051-123-1234
5th row051-123-1234
ValueCountFrequency (%)
051-123-1234 6510
61.9%
051 1565
 
14.9%
전화번호 66
 
0.6%
070 27
 
0.3%
746 20
 
0.2%
747 20
 
0.2%
744 12
 
0.1%
806 11
 
0.1%
743 10
 
0.1%
751 10
 
0.1%
Other values (1030) 2273
 
21.6%
2024-04-17T01:29:09.150224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22424
22.9%
2 14415
14.7%
3 14361
14.7%
- 13108
13.4%
0 9623
9.8%
5 9482
9.7%
4 7783
 
8.0%
2262
 
2.3%
7 1362
 
1.4%
8 1111
 
1.1%
Other values (6) 1940
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82237
84.0%
Dash Punctuation 13108
 
13.4%
Space Separator 2262
 
2.3%
Other Letter 264
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22424
27.3%
2 14415
17.5%
3 14361
17.5%
0 9623
11.7%
5 9482
11.5%
4 7783
 
9.5%
7 1362
 
1.7%
8 1111
 
1.4%
6 1027
 
1.2%
9 649
 
0.8%
Other Letter
ValueCountFrequency (%)
66
25.0%
66
25.0%
66
25.0%
66
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 13108
100.0%
Space Separator
ValueCountFrequency (%)
2262
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97607
99.7%
Hangul 264
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22424
23.0%
2 14415
14.8%
3 14361
14.7%
- 13108
13.4%
0 9623
9.9%
5 9482
9.7%
4 7783
 
8.0%
2262
 
2.3%
7 1362
 
1.4%
8 1111
 
1.1%
Other values (2) 1676
 
1.7%
Hangul
ValueCountFrequency (%)
66
25.0%
66
25.0%
66
25.0%
66
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97607
99.7%
Hangul 264
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22424
23.0%
2 14415
14.8%
3 14361
14.7%
- 13108
13.4%
0 9623
9.9%
5 9482
9.7%
4 7783
 
8.0%
2262
 
2.3%
7 1362
 
1.4%
8 1111
 
1.1%
Other values (2) 1676
 
1.7%
Hangul
ValueCountFrequency (%)
66
25.0%
66
25.0%
66
25.0%
66
25.0%

stroomcnt
Categorical

IMBALANCE 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8261 
객실수
 
122
1
 
72
2
 
57
3
 
28
Other values (33)
 
108

Length

Max length4
Median length4
Mean length3.89963
Min length1

Unique

Unique18 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8261
95.5%
객실수 122
 
1.4%
1 72
 
0.8%
2 57
 
0.7%
3 28
 
0.3%
0 25
 
0.3%
7 15
 
0.2%
4 8
 
0.1%
6 7
 
0.1%
5 6
 
0.1%
Other values (28) 47
 
0.5%

Length

2024-04-17T01:29:09.261484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8261
95.5%
객실수 122
 
1.4%
1 72
 
0.8%
2 57
 
0.7%
3 28
 
0.3%
0 25
 
0.3%
7 15
 
0.2%
4 8
 
0.1%
6 7
 
0.1%
5 6
 
0.1%
Other values (28) 47
 
0.5%

bdngownsenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
6561 
자가
1178 
임대
778 
건물소유구분명
 
131

Length

Max length7
Median length4
Mean length3.5930851
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6561
75.9%
자가 1178
 
13.6%
임대 778
 
9.0%
건물소유구분명 131
 
1.5%

Length

2024-04-17T01:29:09.362560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:09.469141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6561
75.9%
자가 1178
 
13.6%
임대 778
 
9.0%
건물소유구분명 131
 
1.5%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8309 
건물용도명
 
137
단독주택
 
79
아파트
 
61
숙박시설
 
26
Other values (6)
 
36

Length

Max length15
Median length4
Mean length4.0146855
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> 8309
96.1%
건물용도명 137
 
1.6%
단독주택 79
 
0.9%
아파트 61
 
0.7%
숙박시설 26
 
0.3%
다세대주택 15
 
0.2%
호텔 7
 
0.1%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 주택(공동주택적용) 4
 
< 0.1%

Length

2024-04-17T01:29:09.568709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8309
96.0%
건물용도명 137
 
1.6%
단독주택 79
 
0.9%
아파트 61
 
0.7%
숙박시설 26
 
0.3%
다세대주택 15
 
0.2%
호텔 7
 
0.1%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 4
 
< 0.1%
Other values (2) 5
 
0.1%

bdngjisgflrcnt
Categorical

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
0
2561 
<NA>
1710 
4
875 
3
753 
5
607 
Other values (33)
2142 

Length

Max length6
Median length1
Mean length1.6699815
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2561
29.6%
<NA> 1710
19.8%
4 875
 
10.1%
3 753
 
8.7%
5 607
 
7.0%
2 425
 
4.9%
8 330
 
3.8%
6 307
 
3.5%
7 305
 
3.5%
9 201
 
2.3%
Other values (28) 574
 
6.6%

Length

2024-04-17T01:29:09.665810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2561
29.6%
na 1710
19.8%
4 875
 
10.1%
3 753
 
8.7%
5 607
 
7.0%
2 425
 
4.9%
8 330
 
3.8%
6 307
 
3.5%
7 305
 
3.5%
9 201
 
2.3%
Other values (28) 574
 
6.6%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
0
4479 
<NA>
2274 
1
1528 
2
 
200
건물지하층수
 
53
Other values (9)
 
114

Length

Max length6
Median length1
Mean length1.8201896
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4479
51.8%
<NA> 2274
26.3%
1 1528
 
17.7%
2 200
 
2.3%
건물지하층수 53
 
0.6%
4 36
 
0.4%
3 27
 
0.3%
5 24
 
0.3%
6 6
 
0.1%
8 6
 
0.1%
Other values (4) 15
 
0.2%

Length

2024-04-17T01:29:09.764796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4479
51.8%
na 2274
26.3%
1 1530
 
17.7%
2 200
 
2.3%
건물지하층수 53
 
0.6%
4 36
 
0.4%
3 27
 
0.3%
5 24
 
0.3%
6 6
 
0.1%
8 6
 
0.1%
Other values (3) 13
 
0.2%

cnstyarea
Categorical

IMBALANCE 

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8351 
건축연면적
 
142
0
 
122
2282
 
3
20571
 
3
Other values (24)
 
27

Length

Max length5
Median length4
Mean length3.9722479
Min length1

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> 8351
96.6%
건축연면적 142
 
1.6%
0 122
 
1.4%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
761 2
 
< 0.1%
451 2
 
< 0.1%
2267 2
 
< 0.1%
132 1
 
< 0.1%
2038 1
 
< 0.1%
Other values (19) 19
 
0.2%

Length

2024-04-17T01:29:09.871102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8351
96.6%
건축연면적 142
 
1.6%
0 122
 
1.4%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
761 2
 
< 0.1%
451 2
 
< 0.1%
2267 2
 
< 0.1%
155 1
 
< 0.1%
2606 1
 
< 0.1%
Other values (19) 19
 
0.2%

svnsr
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
기념품종류
 
163

Length

Max length5
Median length4
Mean length4.0188483
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> 8485
98.1%
기념품종류 163
 
1.9%

Length

2024-04-17T01:29:09.973861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:10.070080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
기념품종류 163
 
1.9%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
기획여행보험시작일자
 
163

Length

Max length10
Median length4
Mean length4.1130897
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> 8485
98.1%
기획여행보험시작일자 163
 
1.9%

Length

2024-04-17T01:29:10.190959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:10.279872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
기획여행보험시작일자 163
 
1.9%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
기획여행보험종료일자
 
163

Length

Max length10
Median length4
Mean length4.1130897
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> 8485
98.1%
기획여행보험종료일자 163
 
1.9%

Length

2024-04-17T01:29:10.383030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:10.465919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
기획여행보험종료일자 163
 
1.9%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
7221 
0
1312 
남성종사자수
 
85
1
 
12
3
 
5
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.5542322
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> 7221
83.5%
0 1312
 
15.2%
남성종사자수 85
 
1.0%
1 12
 
0.1%
3 5
 
0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
35 1
 
< 0.1%

Length

2024-04-17T01:29:10.558796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7221
83.5%
0 1312
 
15.2%
남성종사자수 85
 
1.0%
1 12
 
0.1%
3 5
 
0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
35 1
 
< 0.1%

playutscntdtl
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
놀이기구수내역
 
163

Length

Max length7
Median length4
Mean length4.0565449
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> 8485
98.1%
놀이기구수내역 163
 
1.9%

Length

2024-04-17T01:29:10.670761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:10.757480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
놀이기구수내역 163
 
1.9%

playfacilcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
N
6507 
<NA>
1864 
0
 
142
놀이시설수
 
132
Y
 
3

Length

Max length5
Median length1
Mean length1.7076781
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 6507
75.2%
<NA> 1864
 
21.6%
0 142
 
1.6%
놀이시설수 132
 
1.5%
Y 3
 
< 0.1%

Length

2024-04-17T01:29:10.852256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:10.962571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 6507
75.2%
na 1864
 
21.6%
0 142
 
1.6%
놀이시설수 132
 
1.5%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
N
8403 
<NA>
 
193
 
41
Y
 
11

Length

Max length4
Median length1
Mean length1.0669519
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8403
97.2%
<NA> 193
 
2.2%
41
 
0.5%
Y 11
 
0.1%

Length

2024-04-17T01:29:11.064298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:11.152438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8403
97.2%
na 193
 
2.2%
41
 
0.5%
y 11
 
0.1%

stagear
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8361 
무대면적
 
145
0
 
142

Length

Max length4
Median length4
Mean length3.9507401
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> 8361
96.7%
무대면적 145
 
1.7%
0 142
 
1.6%

Length

2024-04-17T01:29:11.251460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:11.342572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8361
96.7%
무대면적 145
 
1.7%
0 142
 
1.6%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
문화사업자구분명
 
163

Length

Max length8
Median length4
Mean length4.0753932
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> 8485
98.1%
문화사업자구분명 163
 
1.9%

Length

2024-04-17T01:29:11.437550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:11.531191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
문화사업자구분명 163
 
1.9%

culphyedcobnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8112 
외국인관광 도시민박업
 
304
문화체육업종명
 
110
관광숙박업
 
106
자동차야영장업
 
9
Other values (3)
 
7

Length

Max length11
Median length4
Mean length4.3005319
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> 8112
93.8%
외국인관광 도시민박업 304
 
3.5%
문화체육업종명 110
 
1.3%
관광숙박업 106
 
1.2%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%

Length

2024-04-17T01:29:11.626655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:11.731789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8112
90.6%
외국인관광 304
 
3.4%
도시민박업 304
 
3.4%
문화체육업종명 110
 
1.2%
관광숙박업 106
 
1.2%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%

geicpfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
 
163

Length

Max length4
Median length4
Mean length3.9434551
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> 8485
98.1%
163
 
1.9%

Length

2024-04-17T01:29:11.833134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:11.916089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
163
 
1.9%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
N
8390 
<NA>
 
193
 
41
Y
 
24

Length

Max length4
Median length1
Mean length1.0669519
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8390
97.0%
<NA> 193
 
2.2%
41
 
0.5%
Y 24
 
0.3%

Length

2024-04-17T01:29:12.001771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:12.092421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8390
97.0%
na 193
 
2.2%
41
 
0.5%
y 24
 
0.3%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
 
163

Length

Max length4
Median length4
Mean length3.9434551
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> 8485
98.1%
163
 
1.9%

Length

2024-04-17T01:29:12.188704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:12.287613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
163
 
1.9%

insurorgnm
Categorical

IMBALANCE 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8458 
보험기관명
 
161
현대해상
 
3
야영장사고배상책임보험
 
2
DB 손해보험
 
2
Other values (21)
 
22

Length

Max length22
Median length4
Mean length4.0393154
Min length2

Unique

Unique20 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8458
97.8%
보험기관명 161
 
1.9%
현대해상 3
 
< 0.1%
야영장사고배상책임보험 2
 
< 0.1%
DB 손해보험 2
 
< 0.1%
객실수/수용인원 : 2개/ 6명 2
 
< 0.1%
객실수/수용인원 : 2개/4명 1
 
< 0.1%
서울보증보험 1
 
< 0.1%
객실수/수용인원 : 3/8 1
 
< 0.1%
객실수/수용인원:2/6 1
 
< 0.1%
Other values (16) 16
 
0.2%

Length

2024-04-17T01:29:12.412878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8458
97.6%
보험기관명 161
 
1.9%
객실수/수용인원 6
 
0.1%
5
 
0.1%
현대해상 3
 
< 0.1%
야영장사고배상책임보험 2
 
< 0.1%
db 2
 
< 0.1%
손해보험 2
 
< 0.1%
2개 2
 
< 0.1%
6명 2
 
< 0.1%
Other values (22) 23
 
0.3%

insurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
보험시작일자
 
163

Length

Max length6
Median length4
Mean length4.0376966
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> 8485
98.1%
보험시작일자 163
 
1.9%

Length

2024-04-17T01:29:12.535761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:12.625663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
보험시작일자 163
 
1.9%

insurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
보험종료일자
 
163

Length

Max length6
Median length4
Mean length4.0376966
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> 8485
98.1%
보험종료일자 163
 
1.9%

Length

2024-04-17T01:29:12.718871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:12.807242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
보험종료일자 163
 
1.9%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
부대시설내역
 
163

Length

Max length6
Median length4
Mean length4.0376966
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> 8485
98.1%
부대시설내역 163
 
1.9%

Length

2024-04-17T01:29:12.898774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:12.983951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
부대시설내역 163
 
1.9%

usejisgendflr
Categorical

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
2731 
0
1980 
4
767 
3
658 
5
480 
Other values (32)
2032 

Length

Max length6
Median length1
Mean length2.0209297
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2731
31.6%
0 1980
22.9%
4 767
 
8.9%
3 658
 
7.6%
5 480
 
5.6%
6 417
 
4.8%
2 391
 
4.5%
7 272
 
3.1%
8 262
 
3.0%
9 185
 
2.1%
Other values (27) 505
 
5.8%

Length

2024-04-17T01:29:13.072569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2731
31.6%
0 1980
22.9%
4 767
 
8.9%
3 658
 
7.6%
5 480
 
5.6%
6 417
 
4.8%
2 391
 
4.5%
7 272
 
3.1%
8 262
 
3.0%
9 185
 
2.1%
Other values (27) 505
 
5.8%

useunderendflr
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
0
4769 
<NA>
3604 
1
 
188
사용끝지하층
 
57
2
 
16
Other values (4)
 
14

Length

Max length6
Median length1
Mean length2.2833025
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4769
55.1%
<NA> 3604
41.7%
1 188
 
2.2%
사용끝지하층 57
 
0.7%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
19 1
 
< 0.1%

Length

2024-04-17T01:29:13.172895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:13.266546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4769
55.1%
na 3604
41.7%
1 188
 
2.2%
사용끝지하층 57
 
0.7%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
19 1
 
< 0.1%

usejisgstflr
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
0
2463 
1
1931 
<NA>
1903 
2
1010 
3
528 
Other values (16)
813 

Length

Max length7
Median length1
Mean length1.7051341
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2463
28.5%
1 1931
22.3%
<NA> 1903
22.0%
2 1010
11.7%
3 528
 
6.1%
4 320
 
3.7%
5 194
 
2.2%
6 77
 
0.9%
7 61
 
0.7%
사용시작지상층 55
 
0.6%
Other values (11) 106
 
1.2%

Length

2024-04-17T01:29:13.374471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2463
28.5%
1 1931
22.3%
na 1903
22.0%
2 1010
11.7%
3 528
 
6.1%
4 320
 
3.7%
5 194
 
2.2%
6 77
 
0.9%
7 61
 
0.7%
사용시작지상층 55
 
0.6%
Other values (11) 106
 
1.2%

useunderstflr
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
0
5706 
<NA>
2653 
1
 
221
사용시작지하층
 
55
4
 
8
Other values (3)
 
5

Length

Max length7
Median length1
Mean length1.9584875
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5706
66.0%
<NA> 2653
30.7%
1 221
 
2.6%
사용시작지하층 55
 
0.6%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:29:13.476902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:13.580300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5706
66.0%
na 2653
30.7%
1 221
 
2.6%
사용시작지하층 55
 
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 size67.7 KiB
<NA>
8485 
선박제원
 
163

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> 8485
98.1%
선박제원 163
 
1.9%

Length

2024-04-17T01:29:13.689746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:13.770726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
선박제원 163
 
1.9%

shpcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8361 
선박척수
 
145
0
 
142

Length

Max length4
Median length4
Mean length3.9507401
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> 8361
96.7%
선박척수 145
 
1.7%
0 142
 
1.6%

Length

2024-04-17T01:29:13.855121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:13.940742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8361
96.7%
선박척수 145
 
1.7%
0 142
 
1.6%

shptottons
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8361 
선박총톤수
 
145
0
 
142

Length

Max length5
Median length4
Mean length3.9675069
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> 8361
96.7%
선박총톤수 145
 
1.7%
0 142
 
1.6%

Length

2024-04-17T01:29:14.037323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:14.130343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8361
96.7%
선박총톤수 145
 
1.7%
0 142
 
1.6%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
0
5085 
<NA>
3510 
세탁기수
 
53

Length

Max length4
Median length1
Mean length2.2360083
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5085
58.8%
<NA> 3510
40.6%
세탁기수 53
 
0.6%

Length

2024-04-17T01:29:14.221265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:14.600293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5085
58.8%
na 3510
40.6%
세탁기수 53
 
0.6%

facilscp
Text

MISSING 

Distinct166
Distinct (%)34.5%
Missing8167
Missing (%)94.4%
Memory size67.7 KiB
2024-04-17T01:29:14.853544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.8773389
Min length1

Characters and Unicode

Total characters1384
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

Unique88 ?
Unique (%)18.3%

Sample

1st row시설규모
2nd row시설규모
3rd row시설규모
4th row시설규모
5th row시설규모
ValueCountFrequency (%)
시설규모 116
24.1%
0 33
 
6.9%
85 17
 
3.5%
57 7
 
1.5%
46 7
 
1.5%
60 6
 
1.2%
599 6
 
1.2%
67 6
 
1.2%
63 6
 
1.2%
83 6
 
1.2%
Other values (156) 271
56.3%
2024-04-17T01:29:15.241078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 133
9.6%
116
 
8.4%
116
 
8.4%
116
 
8.4%
116
 
8.4%
5 111
 
8.0%
0 101
 
7.3%
6 94
 
6.8%
8 91
 
6.6%
2 83
 
6.0%
Other values (4) 307
22.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 920
66.5%
Other Letter 464
33.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 133
14.5%
5 111
12.1%
0 101
11.0%
6 94
10.2%
8 91
9.9%
2 83
9.0%
7 80
8.7%
4 78
8.5%
3 75
8.2%
9 74
8.0%
Other Letter
ValueCountFrequency (%)
116
25.0%
116
25.0%
116
25.0%
116
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 920
66.5%
Hangul 464
33.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 133
14.5%
5 111
12.1%
0 101
11.0%
6 94
10.2%
8 91
9.9%
2 83
9.0%
7 80
8.7%
4 78
8.5%
3 75
8.2%
9 74
8.0%
Hangul
ValueCountFrequency (%)
116
25.0%
116
25.0%
116
25.0%
116
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 920
66.5%
Hangul 464
33.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 133
14.5%
5 111
12.1%
0 101
11.0%
6 94
10.2%
8 91
9.9%
2 83
9.0%
7 80
8.7%
4 78
8.5%
3 75
8.2%
9 74
8.0%
Hangul
ValueCountFrequency (%)
116
25.0%
116
25.0%
116
25.0%
116
25.0%

facilar
Text

MISSING 

Distinct249
Distinct (%)51.8%
Missing8167
Missing (%)94.4%
Memory size67.7 KiB
2024-04-17T01:29:15.594696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.6777547
Min length1

Characters and Unicode

Total characters2250
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

Unique194 ?
Unique (%)40.3%

Sample

1st row시설면적
2nd row시설면적
3rd row시설면적
4th row시설면적
5th row시설면적
ValueCountFrequency (%)
시설면적 116
 
24.1%
0 33
 
6.9%
45.5 6
 
1.2%
598.73 6
 
1.2%
218.85 4
 
0.8%
62.58 4
 
0.8%
2281.67 3
 
0.6%
167.82 3
 
0.6%
84.99 3
 
0.6%
392.02 3
 
0.6%
Other values (239) 300
62.4%
2024-04-17T01:29:16.059835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 304
13.5%
1 181
 
8.0%
4 175
 
7.8%
8 172
 
7.6%
5 154
 
6.8%
6 149
 
6.6%
2 141
 
6.3%
3 140
 
6.2%
9 134
 
6.0%
7 119
 
5.3%
Other values (5) 581
25.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1482
65.9%
Other Letter 464
 
20.6%
Other Punctuation 304
 
13.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 181
12.2%
4 175
11.8%
8 172
11.6%
5 154
10.4%
6 149
10.1%
2 141
9.5%
3 140
9.4%
9 134
9.0%
7 119
8.0%
0 117
7.9%
Other Letter
ValueCountFrequency (%)
116
25.0%
116
25.0%
116
25.0%
116
25.0%
Other Punctuation
ValueCountFrequency (%)
. 304
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1786
79.4%
Hangul 464
 
20.6%

Most frequent character per script

Common
ValueCountFrequency (%)
. 304
17.0%
1 181
10.1%
4 175
9.8%
8 172
9.6%
5 154
8.6%
6 149
8.3%
2 141
7.9%
3 140
7.8%
9 134
7.5%
7 119
 
6.7%
Hangul
ValueCountFrequency (%)
116
25.0%
116
25.0%
116
25.0%
116
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1786
79.4%
Hangul 464
 
20.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 304
17.0%
1 181
10.1%
4 175
9.8%
8 172
9.6%
5 154
8.6%
6 149
8.3%
2 141
7.9%
3 140
7.8%
9 134
7.5%
7 119
 
6.7%
Hangul
ValueCountFrequency (%)
116
25.0%
116
25.0%
116
25.0%
116
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
 
163

Length

Max length4
Median length4
Mean length3.9434551
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> 8485
98.1%
163
 
1.9%

Length

2024-04-17T01:29:16.184005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:16.267468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
163
 
1.9%

yangsilcnt
Text

MISSING 

Distinct160
Distinct (%)2.1%
Missing958
Missing (%)11.1%
Memory size67.7 KiB
2024-04-17T01:29:16.436018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7420026
Min length1

Characters and Unicode

Total characters13396
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

Unique28 ?
Unique (%)0.4%

Sample

1st row107
2nd row81
3rd row16
4th row7
5th row5
ValueCountFrequency (%)
0 1046
 
13.6%
10 440
 
5.7%
18 370
 
4.8%
12 318
 
4.1%
14 316
 
4.1%
15 301
 
3.9%
13 248
 
3.2%
19 242
 
3.1%
16 222
 
2.9%
17 217
 
2.8%
Other values (150) 3970
51.6%
2024-04-17T01:29:16.744988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3454
25.8%
0 1942
14.5%
2 1893
14.1%
3 1372
 
10.2%
4 1057
 
7.9%
5 826
 
6.2%
8 816
 
6.1%
6 639
 
4.8%
9 626
 
4.7%
7 612
 
4.6%
Other values (3) 159
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13237
98.8%
Other Letter 159
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3454
26.1%
0 1942
14.7%
2 1893
14.3%
3 1372
 
10.4%
4 1057
 
8.0%
5 826
 
6.2%
8 816
 
6.2%
6 639
 
4.8%
9 626
 
4.7%
7 612
 
4.6%
Other Letter
ValueCountFrequency (%)
53
33.3%
53
33.3%
53
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13237
98.8%
Hangul 159
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3454
26.1%
0 1942
14.7%
2 1893
14.3%
3 1372
 
10.4%
4 1057
 
8.0%
5 826
 
6.2%
8 816
 
6.2%
6 639
 
4.8%
9 626
 
4.7%
7 612
 
4.6%
Hangul
ValueCountFrequency (%)
53
33.3%
53
33.3%
53
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13237
98.8%
Hangul 159
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3454
26.1%
0 1942
14.7%
2 1893
14.3%
3 1372
 
10.4%
4 1057
 
8.0%
5 826
 
6.2%
8 816
 
6.2%
6 639
 
4.8%
9 626
 
4.7%
7 612
 
4.6%
Hangul
ValueCountFrequency (%)
53
33.3%
53
33.3%
53
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
7221 
0
1320 
여성종사자수
 
85
2
 
6
1
 
6
Other values (4)
 
10

Length

Max length6
Median length4
Mean length3.5544635
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> 7221
83.5%
0 1320
 
15.3%
여성종사자수 85
 
1.0%
2 6
 
0.1%
1 6
 
0.1%
3 5
 
0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

Length

2024-04-17T01:29:16.857535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:16.964577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7221
83.5%
0 1320
 
15.3%
여성종사자수 85
 
1.0%
2 6
 
0.1%
1 6
 
0.1%
3 5
 
0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

engstntrnmnm
Text

MISSING 

Distinct62
Distinct (%)26.5%
Missing8414
Missing (%)97.3%
Memory size67.7 KiB
2024-04-17T01:29:17.193848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length5
Mean length8.2863248
Min length4

Characters and Unicode

Total characters1939
Distinct characters61
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)20.9%

Sample

1st row영문상호명
2nd row영문상호명
3rd row영문상호명
4th row영문상호명
5th row영문상호명
ValueCountFrequency (%)
영문상호명 154
46.2%
house 31
 
9.3%
busan 9
 
2.7%
ocean 6
 
1.8%
hotel 6
 
1.8%
guest 5
 
1.5%
in 4
 
1.2%
kim's 4
 
1.2%
suyeong 3
 
0.9%
the 3
 
0.9%
Other values (79) 108
32.4%
2024-04-17T01:29:17.544306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
154
 
7.9%
154
 
7.9%
154
 
7.9%
154
 
7.9%
154
 
7.9%
e 112
 
5.8%
99
 
5.1%
o 90
 
4.6%
a 65
 
3.4%
n 64
 
3.3%
Other values (51) 739
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 770
39.7%
Lowercase Letter 706
36.4%
Uppercase Letter 336
17.3%
Space Separator 99
 
5.1%
Decimal Number 14
 
0.7%
Dash Punctuation 7
 
0.4%
Other Punctuation 7
 
0.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 40
11.9%
S 38
 
11.3%
E 32
 
9.5%
O 24
 
7.1%
U 22
 
6.5%
B 19
 
5.7%
A 18
 
5.4%
Y 17
 
5.1%
P 15
 
4.5%
R 14
 
4.2%
Other values (14) 97
28.9%
Lowercase Letter
ValueCountFrequency (%)
e 112
15.9%
o 90
12.7%
a 65
9.2%
n 64
 
9.1%
u 51
 
7.2%
s 44
 
6.2%
h 31
 
4.4%
t 30
 
4.2%
r 29
 
4.1%
i 28
 
4.0%
Other values (13) 162
22.9%
Other Letter
ValueCountFrequency (%)
154
20.0%
154
20.0%
154
20.0%
154
20.0%
154
20.0%
Decimal Number
ValueCountFrequency (%)
0 8
57.1%
2 3
 
21.4%
1 2
 
14.3%
4 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
' 5
71.4%
& 1
 
14.3%
. 1
 
14.3%
Space Separator
ValueCountFrequency (%)
99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1042
53.7%
Hangul 770
39.7%
Common 127
 
6.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 112
 
10.7%
o 90
 
8.6%
a 65
 
6.2%
n 64
 
6.1%
u 51
 
4.9%
s 44
 
4.2%
H 40
 
3.8%
S 38
 
3.6%
E 32
 
3.1%
h 31
 
3.0%
Other values (37) 475
45.6%
Common
ValueCountFrequency (%)
99
78.0%
0 8
 
6.3%
- 7
 
5.5%
' 5
 
3.9%
2 3
 
2.4%
1 2
 
1.6%
& 1
 
0.8%
. 1
 
0.8%
4 1
 
0.8%
Hangul
ValueCountFrequency (%)
154
20.0%
154
20.0%
154
20.0%
154
20.0%
154
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1169
60.3%
Hangul 770
39.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
154
20.0%
154
20.0%
154
20.0%
154
20.0%
154
20.0%
ASCII
ValueCountFrequency (%)
e 112
 
9.6%
99
 
8.5%
o 90
 
7.7%
a 65
 
5.6%
n 64
 
5.5%
u 51
 
4.4%
s 44
 
3.8%
H 40
 
3.4%
S 38
 
3.3%
E 32
 
2.7%
Other values (46) 534
45.7%

engstntrnmaddr
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8417 
영문상호주소
 
154
Guesthouse for Foreign Tourists
 
23
Foreigner Tourism City home-stay Business
 
14
Foreign tourist city guest house
 
5
Other values (18)
 
35

Length

Max length41
Median length4
Mean length4.2747456
Min length4

Unique

Unique10 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8417
97.3%
영문상호주소 154
 
1.8%
Guesthouse for Foreign Tourists 23
 
0.3%
Foreigner Tourism City home-stay Business 14
 
0.2%
Foreign tourist city guest house 5
 
0.1%
Guesthouse for Foregin Tourists 5
 
0.1%
Guest House 4
 
< 0.1%
TOURIST ACCOMMODATION (hostel) 3
 
< 0.1%
Entertainment Business for foreigner only 3
 
< 0.1%
Oversea Travel Business 3
 
< 0.1%
Other values (13) 17
 
0.2%

Length

2024-04-17T01:29:17.684920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8417
94.9%
영문상호주소 154
 
1.7%
for 35
 
0.4%
foreign 34
 
0.4%
guesthouse 31
 
0.3%
tourists 31
 
0.3%
business 22
 
0.2%
foreigner 19
 
0.2%
city 19
 
0.2%
home-stay 15
 
0.2%
Other values (21) 95
 
1.1%

yoksilcnt
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
0
5929 
<NA>
2478 
욕실수
 
53
15
 
16
12
 
14
Other values (28)
 
158

Length

Max length4
Median length1
Mean length1.8910731
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5929
68.6%
<NA> 2478
28.7%
욕실수 53
 
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

2024-04-17T01:29:17.805311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 5929
68.6%
na 2478
28.7%
욕실수 53
 
0.6%
15 16
 
0.2%
12 14
 
0.2%
18 12
 
0.1%
10 12
 
0.1%
14 10
 
0.1%
9 10
 
0.1%
8 10
 
0.1%
Other values (23) 104
 
1.2%

sntuptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
여관업
5213 
여인숙업
1076 
숙박업 기타
592 
숙박업(생활)
534 
일반호텔
 
512
Other values (4)
721 

Length

Max length8
Median length3
Mean length3.7296485
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5213
60.3%
여인숙업 1076
 
12.4%
숙박업 기타 592
 
6.8%
숙박업(생활) 534
 
6.2%
일반호텔 512
 
5.9%
<NA> 382
 
4.4%
관광호텔 277
 
3.2%
위생업태명 53
 
0.6%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:29:17.920278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:18.037899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5213
56.4%
여인숙업 1076
 
11.6%
숙박업 592
 
6.4%
기타 592
 
6.4%
숙박업(생활 534
 
5.8%
일반호텔 512
 
5.5%
na 382
 
4.1%
관광호텔 277
 
3.0%
위생업태명 53
 
0.6%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
 
163

Length

Max length4
Median length4
Mean length3.9434551
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> 8485
98.1%
163
 
1.9%

Length

2024-04-17T01:29:18.201487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:18.328433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
163
 
1.9%

capt
Categorical

IMBALANCE 

Distinct48
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8299 
자본금
 
130
0
 
101
10000000
 
21
100000000
 
12
Other values (43)
 
85

Length

Max length10
Median length4
Mean length4.0098289
Min length1

Unique

Unique27 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8299
96.0%
자본금 130
 
1.5%
0 101
 
1.2%
10000000 21
 
0.2%
100000000 12
 
0.1%
50000000 8
 
0.1%
200000000 7
 
0.1%
20000000 6
 
0.1%
150000000 4
 
< 0.1%
5000000 4
 
< 0.1%
Other values (38) 56
 
0.6%

Length

2024-04-17T01:29:18.450420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8299
96.0%
자본금 130
 
1.5%
0 101
 
1.2%
10000000 21
 
0.2%
100000000 12
 
0.1%
50000000 8
 
0.1%
200000000 7
 
0.1%
20000000 6
 
0.1%
300000000 4
 
< 0.1%
5000000 4
 
< 0.1%
Other values (38) 56
 
0.6%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
제작취급품목내용
 
163

Length

Max length8
Median length4
Mean length4.0753932
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> 8485
98.1%
제작취급품목내용 163
 
1.9%

Length

2024-04-17T01:29:18.576041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:18.696084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
제작취급품목내용 163
 
1.9%

cndpermstymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
조건부허가시작일자
 
163

Length

Max length9
Median length4
Mean length4.0942414
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> 8485
98.1%
조건부허가시작일자 163
 
1.9%

Length

2024-04-17T01:29:18.801006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:18.892050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
조건부허가시작일자 163
 
1.9%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
조건부허가신고사유
 
163

Length

Max length9
Median length4
Mean length4.0942414
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> 8485
98.1%
조건부허가신고사유 163
 
1.9%

Length

2024-04-17T01:29:19.004183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:19.100218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
조건부허가신고사유 163
 
1.9%

cndpermendymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8485 
조건부허가종료일자
 
163

Length

Max length9
Median length4
Mean length4.0942414
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> 8485
98.1%
조건부허가종료일자 163
 
1.9%

Length

2024-04-17T01:29:19.189236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:19.270499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8485
98.1%
조건부허가종료일자 163
 
1.9%

chaircnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4472
Missing (%)51.7%
Memory size67.7 KiB

nearenvnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8385 
주변환경명
 
148
주택가주변
 
40
아파트지역
 
32
기타
 
26
Other values (3)
 
17

Length

Max length8
Median length4
Mean length4.0272895
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> 8385
97.0%
주변환경명 148
 
1.7%
주택가주변 40
 
0.5%
아파트지역 32
 
0.4%
기타 26
 
0.3%
학교정화(상대) 14
 
0.2%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-17T01:29:19.362927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:19.489206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8385
97.0%
주변환경명 148
 
1.7%
주택가주변 40
 
0.5%
아파트지역 32
 
0.4%
기타 26
 
0.3%
학교정화(상대 14
 
0.2%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대 1
 
< 0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8266 
지상층수
 
131
0
 
86
2
 
36
4
 
19
Other values (23)
 
110

Length

Max length4
Median length4
Mean length3.918247
Min length1

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8266
95.6%
지상층수 131
 
1.5%
0 86
 
1.0%
2 36
 
0.4%
4 19
 
0.2%
1 17
 
0.2%
3 15
 
0.2%
5 11
 
0.1%
6 8
 
0.1%
11 8
 
0.1%
Other values (18) 51
 
0.6%

Length

2024-04-17T01:29:19.601045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8266
95.6%
지상층수 131
 
1.5%
0 86
 
1.0%
2 36
 
0.4%
4 19
 
0.2%
1 17
 
0.2%
3 15
 
0.2%
5 11
 
0.1%
6 8
 
0.1%
11 8
 
0.1%
Other values (18) 51
 
0.6%

regnsenm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8259 
일반주거지역
 
129
지역구분명
 
128
일반상업지역
 
46
준주거지역
 
37
Other values (6)
 
49

Length

Max length6
Median length4
Mean length4.0611702
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8259
95.5%
일반주거지역 129
 
1.5%
지역구분명 128
 
1.5%
일반상업지역 46
 
0.5%
준주거지역 37
 
0.4%
주거지역 32
 
0.4%
자연녹지지역 6
 
0.1%
상업지역 6
 
0.1%
녹지지역 3
 
< 0.1%
관리지역 1
 
< 0.1%

Length

2024-04-17T01:29:19.706387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8259
95.5%
일반주거지역 129
 
1.5%
지역구분명 128
 
1.5%
일반상업지역 46
 
0.5%
준주거지역 37
 
0.4%
주거지역 32
 
0.4%
자연녹지지역 6
 
0.1%
상업지역 6
 
0.1%
녹지지역 3
 
< 0.1%
관리지역 1
 
< 0.1%

undernumlay
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8324 
지하층수
 
137
0
 
125
1
 
33
2
 
22
Other values (5)
 
7

Length

Max length4
Median length4
Mean length3.9351295
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8324
96.3%
지하층수 137
 
1.6%
0 125
 
1.4%
1 33
 
0.4%
2 22
 
0.3%
3 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:29:19.806602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:19.916651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8324
96.3%
지하층수 137
 
1.6%
0 125
 
1.4%
1 33
 
0.4%
2 22
 
0.3%
3 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%

totnumlay
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8261 
총층수
 
128
0
 
67
2
 
44
1
 
24
Other values (23)
 
124

Length

Max length4
Median length4
Mean length3.9006707
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> 8261
95.5%
총층수 128
 
1.5%
0 67
 
0.8%
2 44
 
0.5%
1 24
 
0.3%
4 22
 
0.3%
3 20
 
0.2%
5 16
 
0.2%
6 9
 
0.1%
20 7
 
0.1%
Other values (18) 50
 
0.6%

Length

2024-04-17T01:29:20.024271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8261
95.5%
총층수 128
 
1.5%
0 67
 
0.8%
2 44
 
0.5%
1 24
 
0.3%
4 22
 
0.3%
3 20
 
0.2%
5 16
 
0.2%
6 9
 
0.1%
20 7
 
0.1%
Other values (18) 50
 
0.6%

abedcnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
0
5041 
<NA>
3552 
침대수
 
53
41
 
2

Length

Max length4
Median length1
Mean length2.2446809
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5041
58.3%
<NA> 3552
41.1%
침대수 53
 
0.6%
41 2
 
< 0.1%

Length

2024-04-17T01:29:20.127879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:20.215689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5041
58.3%
na 3552
41.1%
침대수 53
 
0.6%
41 2
 
< 0.1%

hanshilcnt
Categorical

Distinct49
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
0
3810 
<NA>
1510 
2
 
327
10
 
310
3
 
266
Other values (44)
2425 

Length

Max length4
Median length1
Mean length1.6838575
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3810
44.1%
<NA> 1510
 
17.5%
2 327
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 264
 
3.1%
8 227
 
2.6%
4 201
 
2.3%
6 198
 
2.3%
9 197
 
2.3%
Other values (39) 1338
 
15.5%

Length

2024-04-17T01:29:20.311699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3810
44.1%
na 1510
 
17.5%
2 327
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 264
 
3.1%
8 227
 
2.6%
4 201
 
2.3%
6 198
 
2.3%
9 197
 
2.3%
Other values (39) 1338
 
15.5%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
0
5049 
<NA>
3546 
회수건조수
 
53

Length

Max length5
Median length1
Mean length2.2546253
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5049
58.4%
<NA> 3546
41.0%
회수건조수 53
 
0.6%

Length

2024-04-17T01:29:20.415081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:20.523095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5049
58.4%
na 3546
41.0%
회수건조수 53
 
0.6%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
<NA>
8361 
회의실별동시수용인원
 
145
0
 
142

Length

Max length10
Median length4
Mean length4.0513414
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> 8361
96.7%
회의실별동시수용인원 145
 
1.7%
0 142
 
1.6%

Length

2024-04-17T01:29:20.648924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:20.773045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8361
96.7%
회의실별동시수용인원 145
 
1.7%
0 142
 
1.6%

last_load_dttm
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.7 KiB
2022-09-01 05:09:04
5032 
2022-09-01 05:09:03
3610 
<NA>
 
6

Length

Max length19
Median length19
Mean length18.989593
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2022-09-01 05:09:04 5032
58.2%
2022-09-01 05:09:03 3610
41.7%
<NA> 6
 
0.1%

Length

2024-04-17T01:29:20.867149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:29:20.953250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-01 8642
50.0%
05:09:04 5032
29.1%
05:09:03 3610
20.9%
na 6
 
< 0.1%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
0232500003250000-201-2017-0000203_11_03_PI2018-08-31 23:59:59.0<NA>(주)아이에이치엠 호텔포레 프리미어 남포지점600045부산광역시 중구 남포동5가 8-1번지48953.0부산광역시 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>0.0<NA><NA><NA><NA><NA>000<NA>2022-09-01 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>0.0<NA><NA><NA><NA><NA>000<NA>2022-09-01 05:09:03
2432500003250000-214-2017-0000303_11_03_PU2022-07-29 02:40:00.0숙박업케이 친구(K친구)600092부산광역시 중구 대청동2가 23-348948.0부산광역시 중구 광복로49번길 38 (대청동2가)20170731<NA><NA><NA><NA>영업/정상영업385067.377686180051.52191420220727113013숙박업(생활)051 242 8279<NA><NA><NA>51<NA><NA><NA><NA>0<NA><NA>N<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>0.0<NA><NA><NA><NA><NA>000<NA>2022-09-01 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>NaN<NA><NA><NA><NA><NA><NA>3<NA><NA>2022-09-01 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>0.0<NA><NA><NA><NA><NA>000<NA>2022-09-01 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>0.0<NA><NA><NA><NA><NA>020<NA>2022-09-01 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>0.0<NA><NA><NA><NA><NA>020<NA>2022-09-01 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>0.0<NA><NA><NA><NA><NA>000<NA>2022-09-01 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>0.0<NA><NA><NA><NA><NA>080<NA>2022-09-01 05:09:03
91132500003250000-201-1972-0000303_11_03_PU2022-02-25 02:40:00.0숙박업주식회사 경원건설 호텔노아600045부산광역시 중구 남포동5가 81-148983.0부산광역시 중구 자갈치로47번길 3-1 (남포동5가)19721010<NA><NA><NA><NA>영업/정상영업384966.283935179482.33662320220223180238관광호텔051 2464361<NA>자가<NA>91<NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9010<NA><NA><NA>0<NA><NA><NA>51<NA><NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA>0<NA>0<NA>2022-09-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
86381302733600003360000-201-2021-0000103_11_03_PU2021-12-04 02:40:00.0숙박업신라스테이 서부산618200부산광역시 강서구 명지동 3595-1 신라스테이 서부산점46726부산광역시 강서구 명지국제7로 38, 신라스테이 서부산점 (명지동)20210331<NA><NA><NA><NA>영업/정상영업373665.73430842179173.52698928820211202090442관광호텔051 661 9000<NA><NA><NA>233<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>2910<NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>040<NA>2022-09-01 05:09:04
86391302833300003330000-214-2021-0000203_11_03_PI2021-04-02 00:22:59.0숙박업벨리아(BELLIA)612847부산광역시 해운대구 중동 1123 해운대푸르지오시티48099부산광역시 해운대구 해운대해변로298번길 29, 해운대푸르지오시티 (중동)20210331<NA><NA><NA><NA>영업/정상영업397359.716406649186807.81129899520210331103454숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>3<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>22737<NA><NA><NA>0<NA><NA><NA>300<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-09-01 05:09:04
86401302933800003380000-214-2021-0000403_11_03_PU2022-05-28 02:40:00.0숙박업위더스오션613805부산광역시 수영구 광안동 201-1 광안 지웰에스테이트 더 테라스48303부산광역시 수영구 광남로94번길 16, 광안 지웰에스테이트 더 테라스 3~19층 301호 등 70개소 (광안동)20210406<NA><NA><NA><NA>영업/정상영업392691.625721388185474.22691274120220525180346숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>19030<NA><NA><NA>0<NA><NA><NA>700<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-09-01 05:09:04
86411303033300003330000-214-2021-0000303_11_03_PU2022-06-26 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504686720220624125511숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5010<NA><NA><NA>0<NA><NA><NA>82<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-09-01 05:09:04
8642130313280000CDFI226221202100000103_11_04_PU2022-01-06 02:40:00.0외국인관광도시민박업윤슬가지번우편번호부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.397605613179078.07581929720220104140052업태구분명전화번호1건물소유구분명단독주택건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4545.45양실수여성종사자수YoonSeulgaGuesthouse for Foreign Tourists욕실수위생업태명200000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주택가주변1일반주거지역01침대수한실수회수건조수02022-09-01 05:09:04
86431303233300003330000-214-2021-0000303_11_03_PU2022-06-26 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504686720220624125511숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5010<NA><NA><NA>0<NA><NA><NA>82<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-09-01 05:09:04
8644130333280000CDFI226221202100000103_11_04_PU2022-01-06 02:40:00.0외국인관광도시민박업윤슬가지번우편번호부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.397605613179078.07581929720220104140052업태구분명전화번호1건물소유구분명단독주택건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4545.45양실수여성종사자수YoonSeulgaGuesthouse for Foreign Tourists욕실수위생업태명200000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주택가주변1일반주거지역01침대수한실수회수건조수02022-09-01 05:09:04
8645130413330000CDFI226221201500002603_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>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2022-09-01 05:09:04
86461304233800003380000-214-2021-0000603_11_03_PU2021-06-27 02:40:00.0숙박업제이스테이 펜트하우스613805부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210526<NA><NA><NA><NA>영업/정상영업392732.161638137185542.45270223420210625155820숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5050<NA><NA><NA>0<NA><NA><NA>40<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-09-01 05:09:04
8647130433380000CDFI226003202100000303_11_01_PU2021-06-24 02:40:00.0관광숙박업제이스테이 펜트하우스지번우편번호부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210525폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392732.161638137185542.45270223420210622151628업태구분명전화번호4건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명관광숙박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수219218.85양실수여성종사자수영문상호명영문상호주소욕실수위생업태명125000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수지역구분명지하층수총층수침대수한실수회수건조수회의실별동시수용인원2022-09-01 05:09:04

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnwhladdrdcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmlastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
473330000CDFI226003201800000503_11_01_PU2022-05-06 02:40:00.0관광숙박업일로이풀빌라<NA>부산광역시 해운대구 송정동 809부산광역시 해운대구 송정구덕포길 130 (송정동)<NA><NA><NA><NA>영업/정상영업중20220504133213<NA>051-704-78887<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>관광숙박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>599598.73<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4주거지역<NA>4<NA><NA><NA><NA>2022-09-01 05:09:046
53250000CDFI226221201900000103_11_04_PU2021-05-05 02:40:00.0외국인관광도시민박업보수동방공호지번우편번호부산광역시 중구 보수동1가 116-156부산광역시 중구 책방골목길 13-11 (보수동1가)20210427휴업시작일자휴업종료일자재개업일자폐업폐업20210503101511업태구분명전화번호6건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수168167.82양실수여성종사자수영문상호명영문상호주소욕실수위생업태명자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자주변환경명지상층수일반상업지역지하층수3침대수한실수회수건조수회의실별동시수용인원2022-09-01 05:09:043
63250000CDFI226221201900000203_11_04_PU2020-11-03 02:40:00.0외국인관광도시민박업제이온게스트하우스<NA>부산광역시 중구 부평동2가 21-8부산광역시 중구 중구로29번길 38, 4층 (부평동2가)<NA><NA><NA><NA>영업/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>2022-09-01 05:09:043
1032700003270000-201-2019-0000303_11_03_PU2021-06-20 02:40:00.0숙박업대구여관601829부산광역시 동구 초량동 388-2 지하1층, 지상1~3층, 4층 일부부산광역시 동구 중앙대로221번길 14-5 (초량동)<NA><NA><NA><NA>영업/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><NA><NA><NA><NA><NA>060<NA>2022-09-01 05:09:043
1132700003270000-201-2019-0000503_11_03_PU2022-01-14 02:40:00.0숙박업단테하우스601829부산광역시 동구 초량동 399부산광역시 동구 초량로13번길 58 (초량동)<NA><NA><NA><NA>영업/정상영업20220112091015여관업<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4010<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000<NA>2022-09-01 05:09:043
153280000CDFI226221202000000103_11_04_PU2022-07-12 02:40:00.0외국인관광도시민박업오션하우스<NA>부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1904호 (동삼동, 함지그린아파트)<NA><NA><NA><NA>영업/정상영업중20220707134035<NA><NA>2<NA>아파트<NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>00<NA>4645.5<NA><NA><NA>ocean houseGuesthouse for Foreign Tourists<NA><NA><NA>10000000<NA><NA><NA><NA>아파트지역20일반주거지역220<NA><NA><NA>02022-09-01 05:09:043
163280000CDFI226221202000000203_11_04_PU2022-06-08 02:40:00.0외국인관광도시민박업에메랄드 오션뷰<NA>부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1902호 (동삼동, 함지그린아파트)<NA><NA><NA><NA>영업/정상영업중20220603103741<NA><NA>1<NA>아파트<NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>00<NA>4645.5<NA><NA><NA>Emerald ocean viewGuesthouse for Foreign Tourists<NA><NA><NA>0<NA><NA><NA><NA>아파트지역20주거지역220<NA><NA><NA>02022-09-01 05:09:043
173280000CDFI226221202000000303_11_04_PU2021-11-26 02:40:00.0외국인관광도시민박업청학소담<NA>부산광역시 영도구 청학동 398-20부산광역시 영도구 청학서로16번길 43-14 (청학동)<NA><NA><NA><NA>영업/정상영업중20211124114259<NA><NA>1<NA>단독주택<NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>00<NA>8080.1<NA><NA><NA>CheonghakSodamGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA>주택가주변0일반주거지역01<NA><NA><NA>02022-09-01 05:09:043
2432900003290000-201-2019-0000203_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><NA><NA><NA><NA><NA>000<NA>2022-09-01 05:09:043
2532900003290000-201-2020-0000103_11_03_PU2022-08-11 02:40:00.0숙박업모과나무 서면점614849부산광역시 부산진구 부전동 417-25부산광역시 부산진구 부전로 99-1, 3층 (부전동)<NA><NA><NA><NA>영업/정상영업20220809144642여관업051 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><NA><NA><NA><NA><NA>000<NA>2022-09-01 05:09:043