Overview

Dataset statistics

Number of variables81
Number of observations8656
Missing cells38690
Missing cells (%)5.5%
Duplicate rows1499
Duplicate rows (%)17.3%
Total size in memory5.4 MiB
Average record size in memory649.0 B

Variable types

Unsupported5
Numeric1
Text12
Categorical61
DateTime2

Alerts

Dataset has 1499 (17.3%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (88.5%)Imbalance
opnsvcnm is highly imbalanced (66.0%)Imbalance
clgstdt is highly imbalanced (95.6%)Imbalance
clgenddt is highly imbalanced (95.6%)Imbalance
ropnymd is highly imbalanced (86.8%)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 (86.8%)Imbalance
plninsurstdt is highly imbalanced (86.8%)Imbalance
plninsurenddt is highly imbalanced (86.8%)Imbalance
maneipcnt is highly imbalanced (78.6%)Imbalance
playutscntdtl is highly imbalanced (86.8%)Imbalance
playfacilcnt is highly imbalanced (57.2%)Imbalance
multusnupsoyn is highly imbalanced (89.3%)Imbalance
stagear is highly imbalanced (84.4%)Imbalance
culwrkrsenm is highly imbalanced (86.8%)Imbalance
culphyedcobnm is highly imbalanced (85.5%)Imbalance
geicpfacilen is highly imbalanced (86.8%)Imbalance
balhansilyn is highly imbalanced (88.6%)Imbalance
bcfacilen is highly imbalanced (86.8%)Imbalance
insurorgnm is highly imbalanced (96.2%)Imbalance
insurstdt is highly imbalanced (91.4%)Imbalance
insurenddt is highly imbalanced (91.4%)Imbalance
afc is highly imbalanced (86.8%)Imbalance
useunderendflr is highly imbalanced (62.0%)Imbalance
useunderstflr is highly imbalanced (62.8%)Imbalance
shpinfo is highly imbalanced (86.8%)Imbalance
shpcnt is highly imbalanced (84.4%)Imbalance
shptottons is highly imbalanced (84.4%)Imbalance
infoben is highly imbalanced (86.8%)Imbalance
wmeipcnt is highly imbalanced (76.9%)Imbalance
engstntrnmaddr is highly imbalanced (94.9%)Imbalance
yoksilcnt is highly imbalanced (77.1%)Imbalance
dispenen is highly imbalanced (86.8%)Imbalance
capt is highly imbalanced (93.3%)Imbalance
mnfactreartclcn is highly imbalanced (86.8%)Imbalance
cndpermstymd is highly imbalanced (86.8%)Imbalance
cndpermntwhy is highly imbalanced (86.8%)Imbalance
cndpermendymd is highly imbalanced (86.8%)Imbalance
nearenvnm is highly imbalanced (91.6%)Imbalance
jisgnumlay is highly imbalanced (91.6%)Imbalance
regnsenm is highly imbalanced (89.4%)Imbalance
undernumlay is highly imbalanced (91.0%)Imbalance
totnumlay is highly imbalanced (91.4%)Imbalance
meetsamtimesygstf is highly imbalanced (84.4%)Imbalance
sitepostno has 362 (4.2%) missing valuesMissing
rdnwhladdr has 2551 (29.5%) missing valuesMissing
dcbymd has 4356 (50.3%) missing valuesMissing
x has 394 (4.6%) missing valuesMissing
y has 397 (4.6%) missing valuesMissing
sitetel has 380 (4.4%) missing valuesMissing
facilscp has 8175 (94.4%) missing valuesMissing
facilar has 8175 (94.4%) missing valuesMissing
yangsilcnt has 963 (11.1%) missing valuesMissing
engstntrnmnm has 8427 (97.4%) missing valuesMissing
chaircnt has 4443 (51.3%) 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
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 16:23:43.297453
Analysis finished2024-04-16 16:23:46.259219
Duration2.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size67.8 KiB

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3319124
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.2 KiB
2024-04-17T01:23:46.301360image/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 deviation42916.341
Coefficient of variation (CV)0.01293002
Kurtosis-0.97809037
Mean3319124
Median Absolute Deviation (MAD)30000
Skewness0.26017577
Sum2.872038 × 1010
Variance1.8418123 × 109
MonotonicityNot monotonic
2024-04-17T01:23:46.397982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1205
13.9%
3290000 1064
12.3%
3300000 893
10.3%
3390000 689
 
8.0%
3270000 660
 
7.6%
3320000 581
 
6.7%
3380000 519
 
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 660
7.6%
3280000 392
 
4.5%
3290000 1064
12.3%
3300000 893
10.3%
3310000 285
 
3.3%
3320000 581
6.7%
3330000 1205
13.9%
3340000 363
 
4.2%
ValueCountFrequency (%)
3400000 226
 
2.6%
3390000 689
8.0%
3380000 519
6.0%
3370000 386
 
4.5%
3360000 140
 
1.6%
3350000 355
 
4.1%
3340000 363
 
4.2%
3330000 1205
13.9%
3320000 581
6.7%
3310000 285
 
3.3%

mgtno
Text

Distinct4320
Distinct (%)49.9%
Missing3
Missing (%)< 0.1%
Memory size67.8 KiB
2024-04-17T01:23:46.582584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.899688
Min length20

Characters and Unicode

Total characters189498
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

Unique217 ?
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%
cdfi2262212017000001 11
 
0.1%
cdfi2262212016000001 11
 
0.1%
cdfi2262212015000002 11
 
0.1%
cdfi2260032021000001 11
 
0.1%
cdfi2262212016000002 10
 
0.1%
cdfi2262212020000001 10
 
0.1%
cdfi2262212014000001 9
 
0.1%
Other values (4310) 8541
98.7%
2024-04-17T01:23:46.869457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72994
38.5%
- 24657
 
13.0%
2 20715
 
10.9%
1 20342
 
10.7%
3 18444
 
9.7%
9 10169
 
5.4%
8 5001
 
2.6%
7 4884
 
2.6%
6 3795
 
2.0%
4 3691
 
1.9%
Other values (5) 4806
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 163105
86.1%
Dash Punctuation 24657
 
13.0%
Uppercase Letter 1736
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72994
44.8%
2 20715
 
12.7%
1 20342
 
12.5%
3 18444
 
11.3%
9 10169
 
6.2%
8 5001
 
3.1%
7 4884
 
3.0%
6 3795
 
2.3%
4 3691
 
2.3%
5 3070
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 434
25.0%
D 434
25.0%
F 434
25.0%
I 434
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24657
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 187762
99.1%
Latin 1736
 
0.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72994
38.9%
- 24657
 
13.1%
2 20715
 
11.0%
1 20342
 
10.8%
3 18444
 
9.8%
9 10169
 
5.4%
8 5001
 
2.7%
7 4884
 
2.6%
6 3795
 
2.0%
4 3691
 
2.0%
Latin
ValueCountFrequency (%)
C 434
25.0%
D 434
25.0%
F 434
25.0%
I 434
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 189498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72994
38.5%
- 24657
 
13.0%
2 20715
 
10.9%
1 20342
 
10.7%
3 18444
 
9.7%
9 10169
 
5.4%
8 5001
 
2.6%
7 4884
 
2.6%
6 3795
 
2.0%
4 3691
 
1.9%
Other values (5) 4806
 
2.5%

opnsvcid
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
03_11_03_P
8219 
03_11_04_P
 
309
03_11_01_P
 
109
03_11_05_P
 
9
03_11_02_P
 
3
Other values (3)
 
7

Length

Max length10
Median length10
Mean length9.9979205
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 8219
95.0%
03_11_04_P 309
 
3.6%
03_11_01_P 109
 
1.3%
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

2024-04-17T01:23:46.983549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:47.077351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8219
95.0%
03_11_04_p 309
 
3.6%
03_11_01_p 109
 
1.3%
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 size67.8 KiB
I
6476 
U
2177 
180000000
 
3

Length

Max length9
Median length1
Mean length1.0027726
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6476
74.8%
U 2177
 
25.2%
180000000 3
 
< 0.1%

Length

2024-04-17T01:23:47.184885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:47.271601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6476
74.8%
u 2177
 
25.2%
180000000 3
 
< 0.1%
Distinct485
Distinct (%)5.6%
Missing3
Missing (%)< 0.1%
Memory size67.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-06-10 02:40:00
2024-04-17T01:23:47.378179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:23:47.522614image/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 size67.8 KiB
<NA>
6353 
숙박업
2013 
외국인관광도시민박업
 
173
관광숙박업
 
109
자동차야영장업
 
3
Other values (3)
 
5

Length

Max length10
Median length4
Mean length3.9016867
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> 6353
73.4%
숙박업 2013
 
23.3%
외국인관광도시민박업 173
 
2.0%
관광숙박업 109
 
1.3%
자동차야영장업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

Length

2024-04-17T01:23:47.642229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:47.757209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6353
73.4%
숙박업 2013
 
23.3%
외국인관광도시민박업 173
 
2.0%
관광숙박업 109
 
1.3%
자동차야영장업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

bplcnm
Text

Distinct3536
Distinct (%)40.9%
Missing3
Missing (%)< 0.1%
Memory size67.8 KiB
2024-04-17T01:23:48.236503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length5.2760892
Min length1

Characters and Unicode

Total characters45654
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

Unique393 ?
Unique (%)4.5%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 친구(K친구)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 282
 
2.7%
모텔 181
 
1.7%
게스트하우스 117
 
1.1%
여관 82
 
0.8%
hotel 75
 
0.7%
부산 54
 
0.5%
house 49
 
0.5%
해운대 41
 
0.4%
37
 
0.4%
여인숙 36
 
0.3%
Other values (3654) 9504
90.9%
2024-04-17T01:23:48.611610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2988
 
6.5%
2016
 
4.4%
1822
 
4.0%
1781
 
3.9%
1715
 
3.8%
1564
 
3.4%
1495
 
3.3%
1274
 
2.8%
784
 
1.7%
760
 
1.7%
Other values (645) 29455
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38050
83.3%
Uppercase Letter 2648
 
5.8%
Space Separator 1822
 
4.0%
Lowercase Letter 1339
 
2.9%
Close Punctuation 558
 
1.2%
Open Punctuation 558
 
1.2%
Decimal Number 513
 
1.1%
Other Punctuation 113
 
0.2%
Dash Punctuation 32
 
0.1%
Letter Number 9
 
< 0.1%
Other values (4) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2988
 
7.9%
2016
 
5.3%
1781
 
4.7%
1715
 
4.5%
1564
 
4.1%
1495
 
3.9%
1274
 
3.3%
784
 
2.1%
760
 
2.0%
626
 
1.6%
Other values (565) 23047
60.6%
Uppercase Letter
ValueCountFrequency (%)
E 279
 
10.5%
O 258
 
9.7%
H 248
 
9.4%
T 216
 
8.2%
S 167
 
6.3%
L 166
 
6.3%
A 160
 
6.0%
N 133
 
5.0%
B 113
 
4.3%
U 100
 
3.8%
Other values (16) 808
30.5%
Lowercase Letter
ValueCountFrequency (%)
e 212
15.8%
o 155
11.6%
s 113
8.4%
n 110
8.2%
a 109
8.1%
u 95
 
7.1%
t 93
 
6.9%
h 63
 
4.7%
i 62
 
4.6%
l 58
 
4.3%
Other values (16) 269
20.1%
Decimal Number
ValueCountFrequency (%)
2 130
25.3%
1 69
13.5%
7 60
11.7%
5 58
11.3%
9 53
10.3%
0 42
 
8.2%
6 33
 
6.4%
4 28
 
5.5%
3 28
 
5.5%
8 12
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 65
57.5%
& 27
23.9%
' 9
 
8.0%
, 7
 
6.2%
; 2
 
1.8%
2
 
1.8%
: 1
 
0.9%
Letter Number
ValueCountFrequency (%)
5
55.6%
4
44.4%
Math Symbol
ValueCountFrequency (%)
2
50.0%
+ 2
50.0%
Space Separator
ValueCountFrequency (%)
1822
100.0%
Close Punctuation
ValueCountFrequency (%)
) 558
100.0%
Open Punctuation
ValueCountFrequency (%)
( 558
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 38050
83.3%
Latin 3996
 
8.8%
Common 3602
 
7.9%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2988
 
7.9%
2016
 
5.3%
1781
 
4.7%
1715
 
4.5%
1564
 
4.1%
1495
 
3.9%
1274
 
3.3%
784
 
2.1%
760
 
2.0%
626
 
1.6%
Other values (562) 23047
60.6%
Latin
ValueCountFrequency (%)
E 279
 
7.0%
O 258
 
6.5%
H 248
 
6.2%
T 216
 
5.4%
e 212
 
5.3%
S 167
 
4.2%
L 166
 
4.2%
A 160
 
4.0%
o 155
 
3.9%
N 133
 
3.3%
Other values (44) 2002
50.1%
Common
ValueCountFrequency (%)
1822
50.6%
) 558
 
15.5%
( 558
 
15.5%
2 130
 
3.6%
1 69
 
1.9%
. 65
 
1.8%
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 38044
83.3%
ASCII 7584
 
16.6%
None 10
 
< 0.1%
Number Forms 9
 
< 0.1%
CJK 6
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2988
 
7.9%
2016
 
5.3%
1781
 
4.7%
1715
 
4.5%
1564
 
4.1%
1495
 
3.9%
1274
 
3.3%
784
 
2.1%
760
 
2.0%
626
 
1.6%
Other values (561) 23041
60.6%
ASCII
ValueCountFrequency (%)
1822
24.0%
) 558
 
7.4%
( 558
 
7.4%
E 279
 
3.7%
O 258
 
3.4%
H 248
 
3.3%
T 216
 
2.8%
e 212
 
2.8%
S 167
 
2.2%
L 166
 
2.2%
Other values (64) 3100
40.9%
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 

Distinct499
Distinct (%)6.0%
Missing362
Missing (%)4.2%
Memory size67.8 KiB
2024-04-17T01:23:48.908431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0009646
Min length6

Characters and Unicode

Total characters49772
Distinct characters16
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

Unique23 ?
Unique (%)0.3%

Sample

1st row600045
2nd row600051
3rd row600092
4th row600806
5th row600012
ValueCountFrequency (%)
612821 319
 
3.8%
616801 256
 
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 (489) 6477
78.1%
2024-04-17T01:23:49.308204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9933
20.0%
1 8131
16.3%
0 8091
16.3%
8 7979
16.0%
2 4357
8.8%
4 3487
 
7.0%
7 2615
 
5.3%
3 2468
 
5.0%
9 1427
 
2.9%
5 964
 
1.9%
Other values (6) 320
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49452
99.4%
Other Letter 312
 
0.6%
Dash Punctuation 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9933
20.1%
1 8131
16.4%
0 8091
16.4%
8 7979
16.1%
2 4357
8.8%
4 3487
 
7.1%
7 2615
 
5.3%
3 2468
 
5.0%
9 1427
 
2.9%
5 964
 
1.9%
Other Letter
ValueCountFrequency (%)
104
33.3%
52
16.7%
52
16.7%
52
16.7%
52
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49460
99.4%
Hangul 312
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9933
20.1%
1 8131
16.4%
0 8091
16.4%
8 7979
16.1%
2 4357
8.8%
4 3487
 
7.1%
7 2615
 
5.3%
3 2468
 
5.0%
9 1427
 
2.9%
5 964
 
1.9%
Hangul
ValueCountFrequency (%)
104
33.3%
52
16.7%
52
16.7%
52
16.7%
52
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49460
99.4%
Hangul 312
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9933
20.1%
1 8131
16.4%
0 8091
16.4%
8 7979
16.1%
2 4357
8.8%
4 3487
 
7.1%
7 2615
 
5.3%
3 2468
 
5.0%
9 1427
 
2.9%
5 964
 
1.9%
Hangul
ValueCountFrequency (%)
104
33.3%
52
16.7%
52
16.7%
52
16.7%
52
16.7%
Distinct4223
Distinct (%)48.8%
Missing5
Missing (%)0.1%
Memory size67.8 KiB
2024-04-17T01:23:49.602013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length43
Mean length23.204947
Min length13

Characters and Unicode

Total characters200746
Distinct characters314
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

Unique314 ?
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 8651
23.5%
해운대구 1205
 
3.3%
부산진구 1064
 
2.9%
동래구 893
 
2.4%
t통b반 868
 
2.4%
사상구 689
 
1.9%
동구 660
 
1.8%
온천동 644
 
1.7%
북구 585
 
1.6%
수영구 519
 
1.4%
Other values (4508) 21106
57.2%
2024-04-17T01:23:50.033264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36787
18.3%
10484
 
5.2%
10219
 
5.1%
10136
 
5.0%
9037
 
4.5%
8885
 
4.4%
1 8750
 
4.4%
8693
 
4.3%
8657
 
4.3%
- 7993
 
4.0%
Other values (304) 81105
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113181
56.4%
Decimal Number 40442
 
20.1%
Space Separator 36787
 
18.3%
Dash Punctuation 7993
 
4.0%
Uppercase Letter 1785
 
0.9%
Other Punctuation 195
 
0.1%
Close Punctuation 122
 
0.1%
Open Punctuation 122
 
0.1%
Math Symbol 118
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10484
 
9.3%
10219
 
9.0%
10136
 
9.0%
9037
 
8.0%
8885
 
7.9%
8693
 
7.7%
8657
 
7.6%
6681
 
5.9%
6456
 
5.7%
1667
 
1.5%
Other values (271) 32266
28.5%
Uppercase Letter
ValueCountFrequency (%)
B 876
49.1%
T 869
48.7%
A 12
 
0.7%
C 5
 
0.3%
K 5
 
0.3%
M 4
 
0.2%
O 3
 
0.2%
G 2
 
0.1%
E 2
 
0.1%
S 2
 
0.1%
Other values (4) 5
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 8750
21.6%
2 5311
13.1%
3 4257
10.5%
4 4112
10.2%
5 3980
9.8%
0 3106
 
7.7%
6 3081
 
7.6%
7 2885
 
7.1%
8 2606
 
6.4%
9 2354
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 192
98.5%
. 2
 
1.0%
& 1
 
0.5%
Space Separator
ValueCountFrequency (%)
36787
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7993
100.0%
Close Punctuation
ValueCountFrequency (%)
) 122
100.0%
Open 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 85779
42.7%
Latin 1786
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10484
 
9.3%
10219
 
9.0%
10136
 
9.0%
9037
 
8.0%
8885
 
7.9%
8693
 
7.7%
8657
 
7.6%
6681
 
5.9%
6456
 
5.7%
1667
 
1.5%
Other values (271) 32266
28.5%
Common
ValueCountFrequency (%)
36787
42.9%
1 8750
 
10.2%
- 7993
 
9.3%
2 5311
 
6.2%
3 4257
 
5.0%
4 4112
 
4.8%
5 3980
 
4.6%
0 3106
 
3.6%
6 3081
 
3.6%
7 2885
 
3.4%
Other values (8) 5517
 
6.4%
Latin
ValueCountFrequency (%)
B 876
49.0%
T 869
48.7%
A 12
 
0.7%
C 5
 
0.3%
K 5
 
0.3%
M 4
 
0.2%
O 3
 
0.2%
G 2
 
0.1%
E 2
 
0.1%
S 2
 
0.1%
Other values (5) 6
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113181
56.4%
ASCII 87564
43.6%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36787
42.0%
1 8750
 
10.0%
- 7993
 
9.1%
2 5311
 
6.1%
3 4257
 
4.9%
4 4112
 
4.7%
5 3980
 
4.5%
0 3106
 
3.5%
6 3081
 
3.5%
7 2885
 
3.3%
Other values (22) 7302
 
8.3%
Hangul
ValueCountFrequency (%)
10484
 
9.3%
10219
 
9.0%
10136
 
9.0%
9037
 
8.0%
8885
 
7.9%
8693
 
7.7%
8657
 
7.6%
6681
 
5.9%
6456
 
5.7%
1667
 
1.5%
Other values (271) 32266
28.5%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Unsupported

REJECTED  UNSUPPORTED 

Missing47
Missing (%)0.5%
Memory size67.8 KiB

rdnwhladdr
Text

MISSING 

Distinct3132
Distinct (%)51.3%
Missing2551
Missing (%)29.5%
Memory size67.8 KiB
2024-04-17T01:23:50.298502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length61
Mean length27.95905
Min length18

Characters and Unicode

Total characters170690
Distinct characters370
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

Unique388 ?
Unique (%)6.4%

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 6105
 
19.0%
해운대구 987
 
3.1%
부산진구 730
 
2.3%
동래구 607
 
1.9%
사상구 516
 
1.6%
동구 494
 
1.5%
온천동 422
 
1.3%
수영구 417
 
1.3%
중구 398
 
1.2%
부전동 389
 
1.2%
Other values (2685) 20993
65.5%
2024-04-17T01:23:50.712696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25953
 
15.2%
7924
 
4.6%
7527
 
4.4%
7189
 
4.2%
6864
 
4.0%
1 6482
 
3.8%
6478
 
3.8%
6252
 
3.7%
6111
 
3.6%
) 5972
 
3.5%
Other values (360) 83938
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 101567
59.5%
Decimal Number 27620
 
16.2%
Space Separator 25953
 
15.2%
Close Punctuation 5972
 
3.5%
Open Punctuation 5972
 
3.5%
Dash Punctuation 1831
 
1.1%
Other Punctuation 1392
 
0.8%
Math Symbol 283
 
0.2%
Uppercase Letter 96
 
0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7924
 
7.8%
7527
 
7.4%
7189
 
7.1%
6864
 
6.8%
6478
 
6.4%
6252
 
6.2%
6111
 
6.0%
5806
 
5.7%
4047
 
4.0%
3790
 
3.7%
Other values (321) 39579
39.0%
Uppercase Letter
ValueCountFrequency (%)
A 32
33.3%
B 21
21.9%
K 8
 
8.3%
C 5
 
5.2%
O 5
 
5.2%
M 4
 
4.2%
E 3
 
3.1%
S 3
 
3.1%
U 2
 
2.1%
F 2
 
2.1%
Other values (9) 11
 
11.5%
Decimal Number
ValueCountFrequency (%)
1 6482
23.5%
2 4192
15.2%
3 3109
11.3%
4 2368
 
8.6%
5 2227
 
8.1%
0 1989
 
7.2%
6 1963
 
7.1%
7 1909
 
6.9%
9 1742
 
6.3%
8 1639
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 1382
99.3%
. 9
 
0.6%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
25953
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5972
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5972
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1831
100.0%
Math Symbol
ValueCountFrequency (%)
~ 283
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 101567
59.5%
Common 69023
40.4%
Latin 100
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7924
 
7.8%
7527
 
7.4%
7189
 
7.1%
6864
 
6.8%
6478
 
6.4%
6252
 
6.2%
6111
 
6.0%
5806
 
5.7%
4047
 
4.0%
3790
 
3.7%
Other values (321) 39579
39.0%
Latin
ValueCountFrequency (%)
A 32
32.0%
B 21
21.0%
K 8
 
8.0%
C 5
 
5.0%
O 5
 
5.0%
M 4
 
4.0%
E 3
 
3.0%
3
 
3.0%
S 3
 
3.0%
U 2
 
2.0%
Other values (11) 14
14.0%
Common
ValueCountFrequency (%)
25953
37.6%
1 6482
 
9.4%
) 5972
 
8.7%
( 5972
 
8.7%
2 4192
 
6.1%
3 3109
 
4.5%
4 2368
 
3.4%
5 2227
 
3.2%
0 1989
 
2.9%
6 1963
 
2.8%
Other values (8) 8796
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 101567
59.5%
ASCII 69120
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25953
37.5%
1 6482
 
9.4%
) 5972
 
8.6%
( 5972
 
8.6%
2 4192
 
6.1%
3 3109
 
4.5%
4 2368
 
3.4%
5 2227
 
3.2%
0 1989
 
2.9%
6 1963
 
2.8%
Other values (28) 8893
 
12.9%
Hangul
ValueCountFrequency (%)
7924
 
7.8%
7527
 
7.4%
7189
 
7.1%
6864
 
6.8%
6478
 
6.4%
6252
 
6.2%
6111
 
6.0%
5806
 
5.7%
4047
 
4.0%
3790
 
3.7%
Other values (321) 39579
39.0%
Number Forms
ValueCountFrequency (%)
3
100.0%
Distinct3532
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
2024-04-17T01:23:50.959692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.0008087
Min length5

Characters and Unicode

Total characters69255
Distinct characters16
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

Unique277 ?
Unique (%)3.2%

Sample

1st row20170213
2nd row20140318
3rd row20170731
4th row19710807
5th row20121127
ValueCountFrequency (%)
19630110 16
 
0.2%
20010927 14
 
0.2%
20010616 12
 
0.1%
20010206 12
 
0.1%
20020126 12
 
0.1%
20011130 12
 
0.1%
20030908 10
 
0.1%
20010727 10
 
0.1%
20030819 10
 
0.1%
20030410 10
 
0.1%
Other values (3522) 8538
98.6%
2024-04-17T01:23:51.314387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15758
22.8%
1 15692
22.7%
2 9389
13.6%
9 9014
13.0%
8 4778
 
6.9%
7 4209
 
6.1%
3 2902
 
4.2%
6 2810
 
4.1%
4 2398
 
3.5%
5 2274
 
3.3%
Other values (6) 31
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69224
> 99.9%
Dash Punctuation 16
 
< 0.1%
Other Letter 15
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15758
22.8%
1 15692
22.7%
2 9389
13.6%
9 9014
13.0%
8 4778
 
6.9%
7 4209
 
6.1%
3 2902
 
4.2%
6 2810
 
4.1%
4 2398
 
3.5%
5 2274
 
3.3%
Other Letter
ValueCountFrequency (%)
3
20.0%
3
20.0%
3
20.0%
3
20.0%
3
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69240
> 99.9%
Hangul 15
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15758
22.8%
1 15692
22.7%
2 9389
13.6%
9 9014
13.0%
8 4778
 
6.9%
7 4209
 
6.1%
3 2902
 
4.2%
6 2810
 
4.1%
4 2398
 
3.5%
5 2274
 
3.3%
Hangul
ValueCountFrequency (%)
3
20.0%
3
20.0%
3
20.0%
3
20.0%
3
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69240
> 99.9%
Hangul 15
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15758
22.8%
1 15692
22.7%
2 9389
13.6%
9 9014
13.0%
8 4778
 
6.9%
7 4209
 
6.1%
3 2902
 
4.2%
6 2810
 
4.1%
4 2398
 
3.5%
5 2274
 
3.3%
Hangul
ValueCountFrequency (%)
3
20.0%
3
20.0%
3
20.0%
3
20.0%
3
20.0%

dcbymd
Text

MISSING 

Distinct1481
Distinct (%)34.4%
Missing4356
Missing (%)50.3%
Memory size67.8 KiB
2024-04-17T01:23:51.574026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8660465
Min length4

Characters and Unicode

Total characters33824
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 144
 
3.3%
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%
20030123 18
 
0.4%
Other values (1471) 3712
86.3%
2024-04-17T01:23:51.973579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11057
32.7%
2 7478
22.1%
1 5977
17.7%
3 1498
 
4.4%
9 1473
 
4.4%
7 1280
 
3.8%
4 1180
 
3.5%
6 1164
 
3.4%
5 1115
 
3.3%
8 1026
 
3.0%
Other values (4) 576
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33248
98.3%
Other Letter 576
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11057
33.3%
2 7478
22.5%
1 5977
18.0%
3 1498
 
4.5%
9 1473
 
4.4%
7 1280
 
3.8%
4 1180
 
3.5%
6 1164
 
3.5%
5 1115
 
3.4%
8 1026
 
3.1%
Other Letter
ValueCountFrequency (%)
144
25.0%
144
25.0%
144
25.0%
144
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33248
98.3%
Hangul 576
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11057
33.3%
2 7478
22.5%
1 5977
18.0%
3 1498
 
4.5%
9 1473
 
4.4%
7 1280
 
3.8%
4 1180
 
3.5%
6 1164
 
3.5%
5 1115
 
3.4%
8 1026
 
3.1%
Hangul
ValueCountFrequency (%)
144
25.0%
144
25.0%
144
25.0%
144
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33248
98.3%
Hangul 576
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11057
33.3%
2 7478
22.5%
1 5977
18.0%
3 1498
 
4.5%
9 1473
 
4.4%
7 1280
 
3.8%
4 1180
 
3.5%
6 1164
 
3.5%
5 1115
 
3.4%
8 1026
 
3.1%
Hangul
ValueCountFrequency (%)
144
25.0%
144
25.0%
144
25.0%
144
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8491 
휴업시작일자
 
155
20210916
 
2
20210528
 
2
20211129
 
1
Other values (5)
 
5

Length

Max length8
Median length4
Mean length4.0404344
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> 8491
98.1%
휴업시작일자 155
 
1.8%
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

2024-04-17T01:23:52.128211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:52.240769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8491
98.1%
휴업시작일자 155
 
1.8%
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 size67.8 KiB
<NA>
8491 
휴업종료일자
 
155
20221130
 
2
20230131
 
2
20221128
 
1
Other values (5)
 
5

Length

Max length8
Median length4
Mean length4.0404344
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> 8491
98.1%
휴업종료일자 155
 
1.8%
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

2024-04-17T01:23:52.384821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:52.502969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8491
98.1%
휴업종료일자 155
 
1.8%
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 size67.8 KiB
<NA>
8498 
재개업일자
 
158

Length

Max length5
Median length4
Mean length4.0182532
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> 8498
98.2%
재개업일자 158
 
1.8%

Length

2024-04-17T01:23:52.610810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:52.690020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
재개업일자 158
 
1.8%

trdstatenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
02
3707 
01
2502 
영업/정상
1896 
폐업
399 
13
 
87
Other values (4)
 
65

Length

Max length5
Median length2
Mean length2.6580407
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
02 3707
42.8%
01 2502
28.9%
영업/정상 1896
21.9%
폐업 399
 
4.6%
13 87
 
1.0%
03 53
 
0.6%
휴업 7
 
0.1%
<NA> 4
 
< 0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:23:52.781034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:52.881289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3707
42.8%
01 2502
28.9%
영업/정상 1896
21.9%
폐업 399
 
4.6%
13 87
 
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 size67.8 KiB
영업
4161 
폐업
4156 
영업중
 
325
휴업
 
10
<NA>
 
3

Length

Max length4
Median length2
Mean length2.0384704
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4161
48.1%
폐업 4156
48.0%
영업중 325
 
3.8%
휴업 10
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:23:52.993671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:53.089345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4161
48.1%
폐업 4156
48.0%
영업중 325
 
3.8%
휴업 10
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing394
Missing (%)4.6%
Memory size67.8 KiB

y
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing397
Missing (%)4.6%
Memory size67.8 KiB
Distinct3823
Distinct (%)44.2%
Missing3
Missing (%)< 0.1%
Memory size67.8 KiB
Minimum1999-02-11 00:00:00
Maximum2023-06-08 16:07:46
2024-04-17T01:23:53.189389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:23:53.302831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
여관업
5203 
여인숙업
1076 
숙박업 기타
592 
숙박업(생활)
536 
일반호텔
522 
Other values (4)
727 

Length

Max length8
Median length3
Mean length3.7316312
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5203
60.1%
여인숙업 1076
 
12.4%
숙박업 기타 592
 
6.8%
숙박업(생활) 536
 
6.2%
일반호텔 522
 
6.0%
<NA> 387
 
4.5%
관광호텔 279
 
3.2%
업태구분명 52
 
0.6%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:23:53.416515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:53.524681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5203
56.3%
여인숙업 1076
 
11.6%
숙박업 592
 
6.4%
기타 592
 
6.4%
숙박업(생활 536
 
5.8%
일반호텔 522
 
5.6%
na 387
 
4.2%
관광호텔 279
 
3.0%
업태구분명 52
 
0.6%
휴양콘도미니엄업 9
 
0.1%

sitetel
Text

MISSING 

Distinct904
Distinct (%)10.9%
Missing380
Missing (%)4.4%
Memory size67.8 KiB
2024-04-17T01:23:53.779423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.804616
Min length4

Characters and Unicode

Total characters97695
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 6456
61.1%
051 1607
 
15.2%
전화번호 65
 
0.6%
070 27
 
0.3%
746 22
 
0.2%
747 20
 
0.2%
744 14
 
0.1%
731 12
 
0.1%
806 11
 
0.1%
743 10
 
0.1%
Other values (1052) 2323
 
22.0%
2024-04-17T01:23:54.138602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22328
22.9%
2 14332
14.7%
3 14288
14.6%
- 13000
13.3%
0 9637
9.9%
5 9522
9.7%
4 7759
 
7.9%
2318
 
2.4%
7 1398
 
1.4%
8 1135
 
1.2%
Other values (6) 1978
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82117
84.1%
Dash Punctuation 13000
 
13.3%
Space Separator 2318
 
2.4%
Other Letter 260
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22328
27.2%
2 14332
17.5%
3 14288
17.4%
0 9637
11.7%
5 9522
11.6%
4 7759
 
9.4%
7 1398
 
1.7%
8 1135
 
1.4%
6 1053
 
1.3%
9 665
 
0.8%
Other Letter
ValueCountFrequency (%)
65
25.0%
65
25.0%
65
25.0%
65
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 13000
100.0%
Space Separator
ValueCountFrequency (%)
2318
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97435
99.7%
Hangul 260
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22328
22.9%
2 14332
14.7%
3 14288
14.7%
- 13000
13.3%
0 9637
9.9%
5 9522
9.8%
4 7759
 
8.0%
2318
 
2.4%
7 1398
 
1.4%
8 1135
 
1.2%
Other values (2) 1718
 
1.8%
Hangul
ValueCountFrequency (%)
65
25.0%
65
25.0%
65
25.0%
65
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97435
99.7%
Hangul 260
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22328
22.9%
2 14332
14.7%
3 14288
14.7%
- 13000
13.3%
0 9637
9.9%
5 9522
9.8%
4 7759
 
8.0%
2318
 
2.4%
7 1398
 
1.4%
8 1135
 
1.2%
Other values (2) 1718
 
1.8%
Hangul
ValueCountFrequency (%)
65
25.0%
65
25.0%
65
25.0%
65
25.0%

stroomcnt
Categorical

IMBALANCE 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8268 
객실수
 
118
1
 
72
2
 
58
0
 
29
Other values (33)
 
111

Length

Max length4
Median length4
Mean length3.8984519
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> 8268
95.5%
객실수 118
 
1.4%
1 72
 
0.8%
2 58
 
0.7%
0 29
 
0.3%
3 28
 
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

2024-04-17T01:23:54.277604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8268
95.5%
객실수 118
 
1.4%
1 72
 
0.8%
2 58
 
0.7%
0 29
 
0.3%
3 28
 
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 size67.8 KiB
<NA>
6574 
자가
1178 
임대
778 
건물소유구분명
 
126

Length

Max length7
Median length4
Mean length3.5917283
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6574
75.9%
자가 1178
 
13.6%
임대 778
 
9.0%
건물소유구분명 126
 
1.5%

Length

2024-04-17T01:23:54.402151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:54.497645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6574
75.9%
자가 1178
 
13.6%
임대 778
 
9.0%
건물소유구분명 126
 
1.5%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8319 
건물용도명
 
133
단독주택
 
80
아파트
 
61
숙박시설
 
27
Other values (6)
 
36

Length

Max length15
Median length4
Mean length4.0142098
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> 8319
96.1%
건물용도명 133
 
1.5%
단독주택 80
 
0.9%
아파트 61
 
0.7%
숙박시설 27
 
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

2024-04-17T01:23:54.604791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8319
96.1%
건물용도명 133
 
1.5%
단독주택 80
 
0.9%
아파트 61
 
0.7%
숙박시설 27
 
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 size67.8 KiB
0
2556 
<NA>
1715 
4
875 
3
753 
5
609 
Other values (33)
2148 

Length

Max length6
Median length1
Mean length1.6707486
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2556
29.5%
<NA> 1715
19.8%
4 875
 
10.1%
3 753
 
8.7%
5 609
 
7.0%
2 425
 
4.9%
8 330
 
3.8%
6 309
 
3.6%
7 305
 
3.5%
9 203
 
2.3%
Other values (28) 576
 
6.7%

Length

2024-04-17T01:23:54.712478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2556
29.5%
na 1715
19.8%
4 875
 
10.1%
3 753
 
8.7%
5 609
 
7.0%
2 425
 
4.9%
8 330
 
3.8%
6 309
 
3.6%
7 305
 
3.5%
9 203
 
2.3%
Other values (28) 576
 
6.7%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
0
4475 
<NA>
2279 
1
1532 
2
 
204
건물지하층수
 
52
Other values (9)
 
114

Length

Max length6
Median length1
Mean length1.8205869
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4475
51.7%
<NA> 2279
26.3%
1 1532
 
17.7%
2 204
 
2.4%
건물지하층수 52
 
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

2024-04-17T01:23:54.812747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4475
51.7%
na 2279
26.3%
1 1534
 
17.7%
2 204
 
2.4%
건물지하층수 52
 
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 size67.8 KiB
<NA>
8355 
건축연면적
 
138
0
 
130
2282
 
3
20571
 
3
Other values (24)
 
27

Length

Max length5
Median length4
Mean length3.9690388
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> 8355
96.5%
건축연면적 138
 
1.6%
0 130
 
1.5%
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

2024-04-17T01:23:54.920102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8355
96.5%
건축연면적 138
 
1.6%
0 130
 
1.5%
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 size67.8 KiB
<NA>
8498 
기념품종류
 
158

Length

Max length5
Median length4
Mean length4.0182532
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> 8498
98.2%
기념품종류 158
 
1.8%

Length

2024-04-17T01:23:55.045536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:55.139045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
기념품종류 158
 
1.8%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8498 
기획여행보험시작일자
 
158

Length

Max length10
Median length4
Mean length4.1095194
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> 8498
98.2%
기획여행보험시작일자 158
 
1.8%

Length

2024-04-17T01:23:55.223008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:55.306106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
기획여행보험시작일자 158
 
1.8%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8498 
기획여행보험종료일자
 
158

Length

Max length10
Median length4
Mean length4.1095194
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> 8498
98.2%
기획여행보험종료일자 158
 
1.8%

Length

2024-04-17T01:23:55.407293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:55.501121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
기획여행보험종료일자 158
 
1.8%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
7188 
0
1358 
남성종사자수
 
80
1
 
12
3
 
5
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.5375462
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> 7188
83.0%
0 1358
 
15.7%
남성종사자수 80
 
0.9%
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

2024-04-17T01:23:55.590265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7188
83.0%
0 1358
 
15.7%
남성종사자수 80
 
0.9%
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 size67.8 KiB
<NA>
8498 
놀이기구수내역
 
158

Length

Max length7
Median length4
Mean length4.0547597
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> 8498
98.2%
놀이기구수내역 158
 
1.8%

Length

2024-04-17T01:23:55.697094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:55.841912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
놀이기구수내역 158
 
1.8%

playfacilcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
N
6453 
<NA>
1921 
0
 
151
놀이시설수
 
128
Y
 
3

Length

Max length5
Median length1
Mean length1.7249307
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 6453
74.5%
<NA> 1921
 
22.2%
0 151
 
1.7%
놀이시설수 128
 
1.5%
Y 3
 
< 0.1%

Length

2024-04-17T01:23:55.945375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:56.042627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 6453
74.5%
na 1921
 
22.2%
0 151
 
1.7%
놀이시설수 128
 
1.5%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
N
8405 
<NA>
 
200
 
40
Y
 
11

Length

Max length4
Median length1
Mean length1.0693161
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8405
97.1%
<NA> 200
 
2.3%
40
 
0.5%
Y 11
 
0.1%

Length

2024-04-17T01:23:56.138515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:56.233127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8405
97.1%
na 200
 
2.3%
40
 
0.5%
y 11
 
0.1%

stagear
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8364 
0
 
151
무대면적
 
141

Length

Max length4
Median length4
Mean length3.9476664
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> 8364
96.6%
0 151
 
1.7%
무대면적 141
 
1.6%

Length

2024-04-17T01:23:56.590111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:56.669722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8364
96.6%
0 151
 
1.7%
무대면적 141
 
1.6%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8498 
문화사업자구분명
 
158

Length

Max length8
Median length4
Mean length4.0730129
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> 8498
98.2%
문화사업자구분명 158
 
1.8%

Length

2024-04-17T01:23:56.762696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:56.849910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
문화사업자구분명 158
 
1.8%

culphyedcobnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8120 
외국인관광 도시민박업
 
305
관광숙박업
 
109
문화체육업종명
 
106
자동차야영장업
 
9
Other values (3)
 
7

Length

Max length11
Median length4
Mean length4.3000231
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> 8120
93.8%
외국인관광 도시민박업 305
 
3.5%
관광숙박업 109
 
1.3%
문화체육업종명 106
 
1.2%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%

Length

2024-04-17T01:23:56.943942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:57.049763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8120
90.6%
외국인관광 305
 
3.4%
도시민박업 305
 
3.4%
관광숙박업 109
 
1.2%
문화체육업종명 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 size67.8 KiB
<NA>
8498 
 
158

Length

Max length4
Median length4
Mean length3.9452403
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> 8498
98.2%
158
 
1.8%

Length

2024-04-17T01:23:57.157548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:57.238426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
158
 
1.8%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
N
8392 
<NA>
 
200
 
40
Y
 
24

Length

Max length4
Median length1
Mean length1.0693161
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8392
97.0%
<NA> 200
 
2.3%
40
 
0.5%
Y 24
 
0.3%

Length

2024-04-17T01:23:57.324332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:57.434206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8392
97.0%
na 200
 
2.3%
40
 
0.5%
y 24
 
0.3%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8498 
 
158

Length

Max length4
Median length4
Mean length3.9452403
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> 8498
98.2%
158
 
1.8%

Length

2024-04-17T01:23:57.547989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:57.637621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
158
 
1.8%

insurorgnm
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8469 
보험기관명
 
156
현대해상
 
3
DB 손해보험
 
2
야영장사고배상책임보험
 
2
Other values (23)
 
24

Length

Max length22
Median length4
Mean length4.0393946
Min length2

Unique

Unique22 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8469
97.8%
보험기관명 156
 
1.8%
현대해상 3
 
< 0.1%
DB 손해보험 2
 
< 0.1%
야영장사고배상책임보험 2
 
< 0.1%
객실수/수용인원 : 2개/ 6명 2
 
< 0.1%
객실수/수용인원 : 2개/4명 1
 
< 0.1%
재난배상책임보험 1
 
< 0.1%
서울보증보험 1
 
< 0.1%
객실수/수용인원 : 3/8 1
 
< 0.1%
Other values (18) 18
 
0.2%

Length

2024-04-17T01:23:57.734134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8469
97.6%
보험기관명 156
 
1.8%
객실수/수용인원 6
 
0.1%
5
 
0.1%
현대해상 3
 
< 0.1%
db 2
 
< 0.1%
손해보험 2
 
< 0.1%
야영장사고배상책임보험 2
 
< 0.1%
2개 2
 
< 0.1%
6명 2
 
< 0.1%
Other values (24) 25
 
0.3%

insurstdt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8495 
보험시작일자
 
158
20220422
 
3

Length

Max length8
Median length4
Mean length4.0378928
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> 8495
98.1%
보험시작일자 158
 
1.8%
20220422 3
 
< 0.1%

Length

2024-04-17T01:23:57.854965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:57.983161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8495
98.1%
보험시작일자 158
 
1.8%
20220422 3
 
< 0.1%

insurenddt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8495 
보험종료일자
 
158
20230422
 
3

Length

Max length8
Median length4
Mean length4.0378928
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> 8495
98.1%
보험종료일자 158
 
1.8%
20230422 3
 
< 0.1%

Length

2024-04-17T01:23:58.080668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:58.178158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8495
98.1%
보험종료일자 158
 
1.8%
20230422 3
 
< 0.1%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8498 
부대시설내역
 
158

Length

Max length6
Median length4
Mean length4.0365065
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> 8498
98.2%
부대시설내역 158
 
1.8%

Length

2024-04-17T01:23:58.288341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:58.438708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
부대시설내역 158
 
1.8%

usejisgendflr
Categorical

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
2736 
0
1971 
4
767 
3
660 
5
485 
Other values (32)
2037 

Length

Max length6
Median length1
Mean length2.0211414
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2736
31.6%
0 1971
22.8%
4 767
 
8.9%
3 660
 
7.6%
5 485
 
5.6%
6 419
 
4.8%
2 391
 
4.5%
7 273
 
3.2%
8 262
 
3.0%
9 187
 
2.2%
Other values (27) 505
 
5.8%

Length

2024-04-17T01:23:58.538952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2736
31.6%
0 1971
22.8%
4 767
 
8.9%
3 660
 
7.6%
5 485
 
5.6%
6 419
 
4.8%
2 391
 
4.5%
7 273
 
3.2%
8 262
 
3.0%
9 187
 
2.2%
Other values (27) 505
 
5.8%

useunderendflr
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
0
4776 
<NA>
3604 
1
 
188
사용끝지하층
 
56
2
 
18
Other values (4)
 
14

Length

Max length6
Median length1
Mean length2.2815388
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4776
55.2%
<NA> 3604
41.6%
1 188
 
2.2%
사용끝지하층 56
 
0.6%
2 18
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
19 1
 
< 0.1%

Length

2024-04-17T01:23:58.635096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:58.731773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4776
55.2%
na 3604
41.6%
1 188
 
2.2%
사용끝지하층 56
 
0.6%
2 18
 
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 size67.8 KiB
0
2454 
1
1938 
<NA>
1908 
2
1012 
3
528 
Other values (16)
816 

Length

Max length7
Median length1
Mean length1.7055222
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2454
28.4%
1 1938
22.4%
<NA> 1908
22.0%
2 1012
11.7%
3 528
 
6.1%
4 323
 
3.7%
5 194
 
2.2%
6 77
 
0.9%
7 62
 
0.7%
사용시작지상층 54
 
0.6%
Other values (11) 106
 
1.2%

Length

2024-04-17T01:23:58.839447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2454
28.4%
1 1938
22.4%
na 1908
22.0%
2 1012
11.7%
3 528
 
6.1%
4 323
 
3.7%
5 194
 
2.2%
6 77
 
0.9%
7 62
 
0.7%
사용시작지상층 54
 
0.6%
Other values (11) 106
 
1.2%

useunderstflr
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
0
5713 
<NA>
2653 
1
 
223
사용시작지하층
 
54
4
 
8
Other values (3)
 
5

Length

Max length7
Median length1
Mean length1.9569085
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5713
66.0%
<NA> 2653
30.6%
1 223
 
2.6%
사용시작지하층 54
 
0.6%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:23:58.942368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:59.054254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5713
66.0%
na 2653
30.6%
1 223
 
2.6%
사용시작지하층 54
 
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 size67.8 KiB
<NA>
8498 
선박제원
 
158

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> 8498
98.2%
선박제원 158
 
1.8%

Length

2024-04-17T01:23:59.153217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:59.233311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
선박제원 158
 
1.8%

shpcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8364 
0
 
151
선박척수
 
141

Length

Max length4
Median length4
Mean length3.9476664
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> 8364
96.6%
0 151
 
1.7%
선박척수 141
 
1.6%

Length

2024-04-17T01:23:59.324270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:59.423809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8364
96.6%
0 151
 
1.7%
선박척수 141
 
1.6%

shptottons
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8364 
0
 
151
선박총톤수
 
141

Length

Max length5
Median length4
Mean length3.9639556
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> 8364
96.6%
0 151
 
1.7%
선박총톤수 141
 
1.6%

Length

2024-04-17T01:23:59.522667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:59.617606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8364
96.6%
0 151
 
1.7%
선박총톤수 141
 
1.6%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
0
5089 
<NA>
3515 
세탁기수
 
52

Length

Max length4
Median length1
Mean length2.2362523
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5089
58.8%
<NA> 3515
40.6%
세탁기수 52
 
0.6%

Length

2024-04-17T01:23:59.728026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:23:59.831441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5089
58.8%
na 3515
40.6%
세탁기수 52
 
0.6%

facilscp
Text

MISSING 

Distinct167
Distinct (%)34.7%
Missing8175
Missing (%)94.4%
Memory size67.8 KiB
2024-04-17T01:24:00.097696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.8544699
Min length1

Characters and Unicode

Total characters1373
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

Unique89 ?
Unique (%)18.5%

Sample

1st row시설규모
2nd row시설규모
3rd row시설규모
4th row시설규모
5th row시설규모
ValueCountFrequency (%)
시설규모 112
23.3%
0 36
 
7.5%
85 17
 
3.5%
57 7
 
1.5%
46 7
 
1.5%
63 6
 
1.2%
67 6
 
1.2%
83 6
 
1.2%
60 6
 
1.2%
599 6
 
1.2%
Other values (157) 272
56.5%
2024-04-17T01:24:00.498354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 133
9.7%
112
 
8.2%
112
 
8.2%
112
 
8.2%
112
 
8.2%
5 112
 
8.2%
0 104
 
7.6%
6 94
 
6.8%
8 92
 
6.7%
2 83
 
6.0%
Other values (4) 307
22.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 925
67.4%
Other Letter 448
32.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 133
14.4%
5 112
12.1%
0 104
11.2%
6 94
10.2%
8 92
9.9%
2 83
9.0%
7 80
8.6%
4 78
8.4%
3 75
8.1%
9 74
8.0%
Other Letter
ValueCountFrequency (%)
112
25.0%
112
25.0%
112
25.0%
112
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 925
67.4%
Hangul 448
32.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 133
14.4%
5 112
12.1%
0 104
11.2%
6 94
10.2%
8 92
9.9%
2 83
9.0%
7 80
8.6%
4 78
8.4%
3 75
8.1%
9 74
8.0%
Hangul
ValueCountFrequency (%)
112
25.0%
112
25.0%
112
25.0%
112
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 925
67.4%
Hangul 448
32.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 133
14.4%
5 112
12.1%
0 104
11.2%
6 94
10.2%
8 92
9.9%
2 83
9.0%
7 80
8.6%
4 78
8.4%
3 75
8.1%
9 74
8.0%
Hangul
ValueCountFrequency (%)
112
25.0%
112
25.0%
112
25.0%
112
25.0%

facilar
Text

MISSING 

Distinct250
Distinct (%)52.0%
Missing8175
Missing (%)94.4%
Memory size67.8 KiB
2024-04-17T01:24:00.839671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.6611227
Min length1

Characters and Unicode

Total characters2242
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

Unique195 ?
Unique (%)40.5%

Sample

1st row시설면적
2nd row시설면적
3rd row시설면적
4th row시설면적
5th row시설면적
ValueCountFrequency (%)
시설면적 112
 
23.3%
0 36
 
7.5%
598.73 6
 
1.2%
45.5 6
 
1.2%
218.85 4
 
0.8%
62.58 4
 
0.8%
84.59 3
 
0.6%
2281.67 3
 
0.6%
392.02 3
 
0.6%
38.18 3
 
0.6%
Other values (240) 301
62.6%
2024-04-17T01:24:01.286982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 305
13.6%
1 182
 
8.1%
4 176
 
7.9%
8 173
 
7.7%
5 155
 
6.9%
6 149
 
6.6%
2 141
 
6.3%
3 140
 
6.2%
9 134
 
6.0%
0 120
 
5.4%
Other values (5) 567
25.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1489
66.4%
Other Letter 448
 
20.0%
Other Punctuation 305
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 182
12.2%
4 176
11.8%
8 173
11.6%
5 155
10.4%
6 149
10.0%
2 141
9.5%
3 140
9.4%
9 134
9.0%
0 120
8.1%
7 119
8.0%
Other Letter
ValueCountFrequency (%)
112
25.0%
112
25.0%
112
25.0%
112
25.0%
Other Punctuation
ValueCountFrequency (%)
. 305
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1794
80.0%
Hangul 448
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 305
17.0%
1 182
10.1%
4 176
9.8%
8 173
9.6%
5 155
8.6%
6 149
8.3%
2 141
7.9%
3 140
7.8%
9 134
7.5%
0 120
 
6.7%
Hangul
ValueCountFrequency (%)
112
25.0%
112
25.0%
112
25.0%
112
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1794
80.0%
Hangul 448
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 305
17.0%
1 182
10.1%
4 176
9.8%
8 173
9.6%
5 155
8.6%
6 149
8.3%
2 141
7.9%
3 140
7.8%
9 134
7.5%
0 120
 
6.7%
Hangul
ValueCountFrequency (%)
112
25.0%
112
25.0%
112
25.0%
112
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8498 
 
158

Length

Max length4
Median length4
Mean length3.9452403
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> 8498
98.2%
158
 
1.8%

Length

2024-04-17T01:24:01.408941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:01.502185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
158
 
1.8%

yangsilcnt
Text

MISSING 

Distinct159
Distinct (%)2.1%
Missing963
Missing (%)11.1%
Memory size67.8 KiB
2024-04-17T01:24:01.660313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7417132
Min length1

Characters and Unicode

Total characters13399
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

Unique27 ?
Unique (%)0.4%

Sample

1st row107
2nd row81
3rd row16
4th row7
5th row5
ValueCountFrequency (%)
0 1045
 
13.6%
10 440
 
5.7%
18 370
 
4.8%
12 318
 
4.1%
14 316
 
4.1%
15 301
 
3.9%
13 248
 
3.2%
19 242
 
3.1%
16 222
 
2.9%
17 217
 
2.8%
Other values (149) 3974
51.7%
2024-04-17T01:24:01.950500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3456
25.8%
0 1942
14.5%
2 1899
14.2%
3 1372
 
10.2%
4 1059
 
7.9%
5 823
 
6.1%
8 814
 
6.1%
6 640
 
4.8%
9 626
 
4.7%
7 612
 
4.6%
Other values (3) 156
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13243
98.8%
Other Letter 156
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3456
26.1%
0 1942
14.7%
2 1899
14.3%
3 1372
 
10.4%
4 1059
 
8.0%
5 823
 
6.2%
8 814
 
6.1%
6 640
 
4.8%
9 626
 
4.7%
7 612
 
4.6%
Other Letter
ValueCountFrequency (%)
52
33.3%
52
33.3%
52
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13243
98.8%
Hangul 156
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3456
26.1%
0 1942
14.7%
2 1899
14.3%
3 1372
 
10.4%
4 1059
 
8.0%
5 823
 
6.2%
8 814
 
6.1%
6 640
 
4.8%
9 626
 
4.7%
7 612
 
4.6%
Hangul
ValueCountFrequency (%)
52
33.3%
52
33.3%
52
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13243
98.8%
Hangul 156
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3456
26.1%
0 1942
14.7%
2 1899
14.3%
3 1372
 
10.4%
4 1059
 
8.0%
5 823
 
6.2%
8 814
 
6.1%
6 640
 
4.8%
9 626
 
4.7%
7 612
 
4.6%
Hangul
ValueCountFrequency (%)
52
33.3%
52
33.3%
52
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
7188 
0
1366 
여성종사자수
 
80
2
 
6
1
 
6
Other values (4)
 
10

Length

Max length6
Median length4
Mean length3.5377773
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> 7188
83.0%
0 1366
 
15.8%
여성종사자수 80
 
0.9%
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

2024-04-17T01:24:02.111598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:02.223970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7188
83.0%
0 1366
 
15.8%
여성종사자수 80
 
0.9%
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 (%)27.1%
Missing8427
Missing (%)97.4%
Memory size67.8 KiB
2024-04-17T01:24:02.428697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length5
Mean length8.3580786
Min length4

Characters and Unicode

Total characters1914
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 (%)21.4%

Sample

1st row영문상호명
2nd row영문상호명
3rd row영문상호명
4th row영문상호명
5th row영문상호명
ValueCountFrequency (%)
영문상호명 149
45.4%
house 31
 
9.5%
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
32.9%
2024-04-17T01:24:02.797212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
 
7.8%
149
 
7.8%
149
 
7.8%
149
 
7.8%
149
 
7.8%
e 112
 
5.9%
99
 
5.2%
o 90
 
4.7%
a 65
 
3.4%
n 64
 
3.3%
Other values (51) 739
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 745
38.9%
Lowercase Letter 706
36.9%
Uppercase Letter 336
17.6%
Space Separator 99
 
5.2%
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 (%)
149
20.0%
149
20.0%
149
20.0%
149
20.0%
149
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
54.4%
Hangul 745
38.9%
Common 127
 
6.6%

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 (%)
149
20.0%
149
20.0%
149
20.0%
149
20.0%
149
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1169
61.1%
Hangul 745
38.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
149
20.0%
149
20.0%
149
20.0%
149
20.0%
149
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 size67.8 KiB
<NA>
8430 
영문상호주소
 
149
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 length4.2733364
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> 8430
97.4%
영문상호주소 149
 
1.7%
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

2024-04-17T01:24:02.920651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8430
94.9%
영문상호주소 149
 
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 size67.8 KiB
0
5933 
<NA>
2483 
욕실수
 
52
15
 
16
12
 
14
Other values (28)
 
158

Length

Max length4
Median length1
Mean length1.8917514
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5933
68.5%
<NA> 2483
28.7%
욕실수 52
 
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

2024-04-17T01:24:03.033046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 5933
68.5%
na 2483
28.7%
욕실수 52
 
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 size67.8 KiB
여관업
5205 
여인숙업
1076 
숙박업 기타
592 
숙박업(생활)
536 
일반호텔
 
520
Other values (4)
727 

Length

Max length8
Median length3
Mean length3.7314002
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5205
60.1%
여인숙업 1076
 
12.4%
숙박업 기타 592
 
6.8%
숙박업(생활) 536
 
6.2%
일반호텔 520
 
6.0%
<NA> 387
 
4.5%
관광호텔 279
 
3.2%
위생업태명 52
 
0.6%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:24:03.133260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:03.239524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5205
56.3%
여인숙업 1076
 
11.6%
숙박업 592
 
6.4%
기타 592
 
6.4%
숙박업(생활 536
 
5.8%
일반호텔 520
 
5.6%
na 387
 
4.2%
관광호텔 279
 
3.0%
위생업태명 52
 
0.6%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8498 
 
158

Length

Max length4
Median length4
Mean length3.9452403
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> 8498
98.2%
158
 
1.8%

Length

2024-04-17T01:24:03.373685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:03.460068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
158
 
1.8%

capt
Categorical

IMBALANCE 

Distinct48
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8305 
자본금
 
126
0
 
104
10000000
 
21
100000000
 
13
Other values (43)
 
87

Length

Max length10
Median length4
Mean length4.0106285
Min length1

Unique

Unique26 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8305
95.9%
자본금 126
 
1.5%
0 104
 
1.2%
10000000 21
 
0.2%
100000000 13
 
0.2%
200000000 8
 
0.1%
50000000 8
 
0.1%
20000000 6
 
0.1%
5000000 4
 
< 0.1%
300000000 4
 
< 0.1%
Other values (38) 57
 
0.7%

Length

2024-04-17T01:24:03.542764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8305
95.9%
자본금 126
 
1.5%
0 104
 
1.2%
10000000 21
 
0.2%
100000000 13
 
0.2%
200000000 8
 
0.1%
50000000 8
 
0.1%
20000000 6
 
0.1%
150000000 4
 
< 0.1%
300000000 4
 
< 0.1%
Other values (38) 57
 
0.7%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8498 
제작취급품목내용
 
158

Length

Max length8
Median length4
Mean length4.0730129
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> 8498
98.2%
제작취급품목내용 158
 
1.8%

Length

2024-04-17T01:24:03.652171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:03.737449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
제작취급품목내용 158
 
1.8%

cndpermstymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8498 
조건부허가시작일자
 
158

Length

Max length9
Median length4
Mean length4.0912662
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> 8498
98.2%
조건부허가시작일자 158
 
1.8%

Length

2024-04-17T01:24:03.842773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:03.934382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
조건부허가시작일자 158
 
1.8%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8498 
조건부허가신고사유
 
158

Length

Max length9
Median length4
Mean length4.0912662
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> 8498
98.2%
조건부허가신고사유 158
 
1.8%

Length

2024-04-17T01:24:04.019326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:04.105690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
조건부허가신고사유 158
 
1.8%

cndpermendymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8498 
조건부허가종료일자
 
158

Length

Max length9
Median length4
Mean length4.0912662
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> 8498
98.2%
조건부허가종료일자 158
 
1.8%

Length

2024-04-17T01:24:04.229247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:04.607416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8498
98.2%
조건부허가종료일자 158
 
1.8%

chaircnt
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4443
Missing (%)51.3%
Memory size67.8 KiB

nearenvnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8396 
주변환경명
 
144
주택가주변
 
40
아파트지역
 
32
기타
 
26
Other values (3)
 
18

Length

Max length8
Median length4
Mean length4.0272643
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> 8396
97.0%
주변환경명 144
 
1.7%
주택가주변 40
 
0.5%
아파트지역 32
 
0.4%
기타 26
 
0.3%
학교정화(상대) 15
 
0.2%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-17T01:24:04.710681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:04.814088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8396
97.0%
주변환경명 144
 
1.7%
주택가주변 40
 
0.5%
아파트지역 32
 
0.4%
기타 26
 
0.3%
학교정화(상대 15
 
0.2%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대 1
 
< 0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8274 
지상층수
 
127
0
 
88
2
 
37
4
 
19
Other values (23)
 
111

Length

Max length4
Median length4
Mean length3.9169362
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> 8274
95.6%
지상층수 127
 
1.5%
0 88
 
1.0%
2 37
 
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) 52
 
0.6%

Length

2024-04-17T01:24:04.919880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8274
95.6%
지상층수 127
 
1.5%
0 88
 
1.0%
2 37
 
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) 52
 
0.6%

regnsenm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8269 
일반주거지역
 
130
지역구분명
 
124
일반상업지역
 
47
준주거지역
 
37
Other values (6)
 
49

Length

Max length6
Median length4
Mean length4.0611137
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> 8269
95.5%
일반주거지역 130
 
1.5%
지역구분명 124
 
1.4%
일반상업지역 47
 
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

2024-04-17T01:24:05.030696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8269
95.5%
일반주거지역 130
 
1.5%
지역구분명 124
 
1.4%
일반상업지역 47
 
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 size67.8 KiB
<NA>
8330 
지하층수
 
133
0
 
130
1
 
33
2
 
23
Other values (5)
 
7

Length

Max length4
Median length4
Mean length3.93311
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> 8330
96.2%
지하층수 133
 
1.5%
0 130
 
1.5%
1 33
 
0.4%
2 23
 
0.3%
3 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:24:05.158733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:05.273546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8330
96.2%
지하층수 133
 
1.5%
0 130
 
1.5%
1 33
 
0.4%
2 23
 
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 size67.8 KiB
<NA>
8269 
총층수
 
124
0
 
69
2
 
45
1
 
24
Other values (23)
 
125

Length

Max length4
Median length4
Mean length3.8999538
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> 8269
95.5%
총층수 124
 
1.4%
0 69
 
0.8%
2 45
 
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) 51
 
0.6%

Length

2024-04-17T01:24:05.383911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8269
95.5%
총층수 124
 
1.4%
0 69
 
0.8%
2 45
 
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) 51
 
0.6%

abedcnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
0
5045 
<NA>
3557 
침대수
 
52
41
 
2

Length

Max length4
Median length1
Mean length2.2450323
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5045
58.3%
<NA> 3557
41.1%
침대수 52
 
0.6%
41 2
 
< 0.1%

Length

2024-04-17T01:24:05.506367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:05.594505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5045
58.3%
na 3557
41.1%
침대수 52
 
0.6%
41 2
 
< 0.1%

hanshilcnt
Categorical

Distinct49
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
0
3816 
<NA>
1515 
2
 
327
10
 
310
3
 
266
Other values (44)
2422 

Length

Max length4
Median length1
Mean length1.6844963
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3816
44.1%
<NA> 1515
 
17.5%
2 327
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 264
 
3.0%
8 227
 
2.6%
4 201
 
2.3%
6 198
 
2.3%
9 197
 
2.3%
Other values (39) 1335
 
15.4%

Length

2024-04-17T01:24:05.693107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3816
44.1%
na 1515
 
17.5%
2 327
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 264
 
3.0%
8 227
 
2.6%
4 201
 
2.3%
6 198
 
2.3%
9 197
 
2.3%
Other values (39) 1335
 
15.4%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
0
5053 
<NA>
3551 
회수건조수
 
52

Length

Max length5
Median length1
Mean length2.2547366
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5053
58.4%
<NA> 3551
41.0%
회수건조수 52
 
0.6%

Length

2024-04-17T01:24:05.798027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:05.904990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5053
58.4%
na 3551
41.0%
회수건조수 52
 
0.6%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
<NA>
8364 
0
 
151
회의실별동시수용인원
 
141

Length

Max length10
Median length4
Mean length4.045402
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> 8364
96.6%
0 151
 
1.7%
회의실별동시수용인원 141
 
1.6%

Length

2024-04-17T01:24:06.011356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:06.099612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8364
96.6%
0 151
 
1.7%
회의실별동시수용인원 141
 
1.6%

last_load_dttm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
2023-09-01 05:09:04
5434 
2023-09-01 05:09:05
3127 
2023-09-01 05:09:03
 
89
<NA>
 
6

Length

Max length19
Median length19
Mean length18.989603
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-01 05:09:03
2nd row2023-09-01 05:09:03
3rd row2023-09-01 05:09:03
4th row2023-09-01 05:09:03
5th row2023-09-01 05:09:03

Common Values

ValueCountFrequency (%)
2023-09-01 05:09:04 5434
62.8%
2023-09-01 05:09:05 3127
36.1%
2023-09-01 05:09:03 89
 
1.0%
<NA> 6
 
0.1%

Length

2024-04-17T01:24:06.234263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:24:06.354517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-01 8650
50.0%
05:09:04 5434
31.4%
05:09:05 3127
 
18.1%
05:09:03 89
 
0.5%
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>2023-09-01 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>2023-09-01 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>2023-09-01 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>2023-09-01 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>2023-09-01 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>2023-09-01 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>2023-09-01 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>2023-09-01 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>2023-09-01 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>2023-09-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
86461302833300003330000-214-2021-0000203_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>2023-09-01 05:09:05
86471302933800003380000-214-2021-0000403_11_03_PU2022-09-22 02:40:00.0숙박업위더스오션613805부산광역시 수영구 광안동 201-1 광안 지웰에스테이트 더 테라스48303부산광역시 수영구 광남로94번길 16, 광안 지웰에스테이트 더 테라스 301호 외 73객실호 (광안동)20210406<NA><NA><NA><NA>영업/정상영업392691.625721388185474.22691274120220920135633숙박업(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>730<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2023-09-01 05:09:05
86481303033300003330000-214-2021-0000303_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>2023-09-01 05:09:05
8649130313280000CDFI226221202100000103_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 Tourists욕실수위생업태명200000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주택가주변1일반주거지역01침대수한실수회수건조수02023-09-01 05:09:05
86501303233300003330000-214-2021-0000303_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>2023-09-01 05:09:05
8651130333280000CDFI226221202100000103_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 Tourists욕실수위생업태명200000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주택가주변1일반주거지역01침대수한실수회수건조수02023-09-01 05:09:05
8652130413330000CDFI226221201500002603_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>2023-09-01 05:09:05
86531304233800003380000-214-2021-0000603_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>2023-09-01 05:09:05
8654130433380000CDFI226003202100000303_11_01_PU2021-06-24 02:40:00.0관광숙박업제이스테이 펜트하우스지번우편번호부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210525폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392732.161638137185542.45270223420210622151628업태구분명전화번호4건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명관광숙박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수219218.85양실수여성종사자수영문상호명영문상호주소욕실수위생업태명125000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수지역구분명지하층수총층수침대수한실수회수건조수회의실별동시수용인원2023-09-01 05:09:05
86551322633300003330000-214-2023-0001003_11_03_PI2023-06-10 00:19:49숙박업stov(스토브)612-040부산광역시 해운대구 송정동 159-1648073부산광역시 해운대구 송정중앙로6번길 76, 1층 (송정동)2023-06-08<NA><NA><NA><NA>영업/정상영업400288.929265345189048.342998382023-06-08 11:27:53숙박업(생활)<NA><NA><NA><NA>10<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>1010<NA><NA><NA>0<NA><NA><NA>10<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2023-09-01 05:09:05

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmlastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
14543330000CDFI226003201800000503_11_01_PU2022-05-06 02:40:00.0관광숙박업일로이풀빌라<NA>부산광역시 해운대구 송정동 809부산광역시 해운대구 송정구덕포길 130 (송정동)20181017<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>2023-09-01 05:09:045
1423250000CDFI226221201900000103_11_04_PU2021-05-05 02:40:00.0외국인관광도시민박업보수동방공호지번우편번호부산광역시 중구 보수동1가 116-156부산광역시 중구 책방골목길 13-11 (보수동1가)2019021520210427휴업시작일자휴업종료일자재개업일자폐업폐업20210503101511업태구분명전화번호6건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수168167.82양실수여성종사자수영문상호명영문상호주소욕실수위생업태명자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자주변환경명지상층수일반상업지역지하층수3침대수한실수회수건조수회의실별동시수용인원2023-09-01 05:09:053
1433250000CDFI226221201900000203_11_04_PU2020-11-03 02:40:00.0외국인관광도시민박업제이온게스트하우스<NA>부산광역시 중구 부평동2가 21-8부산광역시 중구 중구로29번길 38, 4층 (부평동2가)20190628<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>2023-09-01 05:09:053
64432700003270000-201-2019-0000303_11_03_PU2021-06-20 02:40:00.0숙박업대구여관601829부산광역시 동구 초량동 388-2 지하1층, 지상1~3층, 4층 일부부산광역시 동구 중앙대로221번길 14-5 (초량동)20190621<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>2023-09-01 05:09:053
64532700003270000-201-2019-0000503_11_03_PU2022-01-14 02:40:00.0숙박업단테하우스601829부산광역시 동구 초량동 399부산광역시 동구 초량로13번길 58 (초량동)20191025<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>2023-09-01 05:09:053
8243280000CDFI226221202000000103_11_04_PU2022-07-12 02:40:00.0외국인관광도시민박업오션하우스<NA>부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1904호 (동삼동, 함지그린아파트)20200313<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>02023-09-01 05:09:053
8253280000CDFI226221202000000203_11_04_PU2022-06-08 02:40:00.0외국인관광도시민박업에메랄드 오션뷰<NA>부산광역시 영도구 동삼동 1124 함지그린아파트부산광역시 영도구 함지로 8, 106동 1902호 (동삼동, 함지그린아파트)20200320<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>02023-09-01 05:09:053
8263280000CDFI226221202000000303_11_04_PU2021-11-26 02:40:00.0외국인관광도시민박업청학소담<NA>부산광역시 영도구 청학동 398-20부산광역시 영도구 청학서로16번길 43-14 (청학동)20200515<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>02023-09-01 05:09:053
133032900003290000-201-2019-0000203_11_03_PU2022-09-25 02:40:00.0숙박업엑스모텔614846부산광역시 부산진구 부전동 226-5부산광역시 부산진구 신천대로50번길 34, 6층~9층 (부전동)20190705<NA><NA><NA><NA>영업/정상영업20220923142047일반호텔051 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>2023-09-01 05:09:053
133132900003290000-201-2020-0000103_11_03_PU2022-08-11 02:40:00.0숙박업모과나무 서면점614849부산광역시 부산진구 부전동 417-25부산광역시 부산진구 부전로 99-1, 3층 (부전동)20200221<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>2023-09-01 05:09:053