Overview

Dataset statistics

Number of variables81
Number of observations8461
Missing cells33966
Missing cells (%)5.0%
Duplicate rows243
Duplicate rows (%)2.9%
Total size in memory5.3 MiB
Average record size in memory652.0 B

Variable types

Unsupported3
Numeric4
Text10
Categorical63
DateTime1

Alerts

Dataset has 243 (2.9%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (89.9%)Imbalance
updategbn is highly imbalanced (88.2%)Imbalance
opnsvcnm is highly imbalanced (86.8%)Imbalance
clgstdt is highly imbalanced (98.6%)Imbalance
clgenddt is highly imbalanced (98.6%)Imbalance
ropnymd is highly imbalanced (96.9%)Imbalance
trdstatenm is highly imbalanced (56.9%)Imbalance
dtlstatenm is highly imbalanced (54.2%)Imbalance
sitetel is highly imbalanced (96.9%)Imbalance
stroomcnt is highly imbalanced (96.3%)Imbalance
bdngsrvnm is highly imbalanced (94.2%)Imbalance
bdngunderflrcnt is highly imbalanced (55.7%)Imbalance
cnstyarea is highly imbalanced (98.6%)Imbalance
svnsr is highly imbalanced (96.9%)Imbalance
plninsurstdt is highly imbalanced (96.9%)Imbalance
plninsurenddt is highly imbalanced (96.9%)Imbalance
maneipcnt is highly imbalanced (88.9%)Imbalance
playutscntdtl is highly imbalanced (96.9%)Imbalance
playfacilcnt is highly imbalanced (94.0%)Imbalance
multusnupsoyn is highly imbalanced (96.8%)Imbalance
stagear is highly imbalanced (96.9%)Imbalance
culwrkrsenm is highly imbalanced (96.9%)Imbalance
culphyedcobnm is highly imbalanced (89.7%)Imbalance
geicpfacilen is highly imbalanced (96.9%)Imbalance
balhansilyn is highly imbalanced (96.0%)Imbalance
bcfacilen is highly imbalanced (96.9%)Imbalance
insurorgnm is highly imbalanced (98.5%)Imbalance
insurstdt is highly imbalanced (96.9%)Imbalance
insurenddt is highly imbalanced (96.9%)Imbalance
afc is highly imbalanced (96.9%)Imbalance
useunderendflr is highly imbalanced (64.5%)Imbalance
useunderstflr is highly imbalanced (63.5%)Imbalance
shpinfo is highly imbalanced (96.9%)Imbalance
shpcnt is highly imbalanced (96.9%)Imbalance
shptottons is highly imbalanced (96.9%)Imbalance
infoben is highly imbalanced (96.9%)Imbalance
wmeipcnt is highly imbalanced (88.1%)Imbalance
engstntrnmaddr is highly imbalanced (97.5%)Imbalance
yoksilcnt is highly imbalanced (77.5%)Imbalance
dispenen is highly imbalanced (96.9%)Imbalance
capt is highly imbalanced (97.1%)Imbalance
mnfactreartclcn is highly imbalanced (96.9%)Imbalance
cndpermstymd is highly imbalanced (97.8%)Imbalance
cndpermntwhy is highly imbalanced (96.9%)Imbalance
cndpermendymd is highly imbalanced (97.8%)Imbalance
chaircnt is highly imbalanced (67.5%)Imbalance
nearenvnm is highly imbalanced (95.4%)Imbalance
jisgnumlay is highly imbalanced (95.8%)Imbalance
regnsenm is highly imbalanced (92.6%)Imbalance
undernumlay is highly imbalanced (96.9%)Imbalance
totnumlay is highly imbalanced (95.5%)Imbalance
meetsamtimesygstf is highly imbalanced (96.9%)Imbalance
sitepostno has 299 (3.5%) missing valuesMissing
rdnwhladdr has 2550 (30.1%) missing valuesMissing
dcbymd has 4665 (55.1%) missing valuesMissing
x has 385 (4.6%) missing valuesMissing
y has 388 (4.6%) missing valuesMissing
facilscp has 8188 (96.8%) missing valuesMissing
facilar has 8188 (96.8%) missing valuesMissing
yangsilcnt has 900 (10.6%) missing valuesMissing
engstntrnmnm has 8378 (99.0%) missing valuesMissing
skey is an unsupported type, check if it needs cleaning or further analysisUnsupported
apvpermymd is an unsupported type, check if it needs cleaning or further analysisUnsupported
x is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 16:36:47.158460
Analysis finished2024-04-16 16:36:49.351548
Duration2.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.2 KiB

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3318885.1
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.5 KiB
2024-04-17T01:36:49.398214image/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 deviation42883.237
Coefficient of variation (CV)0.012920977
Kurtosis-0.97678458
Mean3318885.1
Median Absolute Deviation (MAD)30000
Skewness0.2669751
Sum2.807113 × 1010
Variance1.838972 × 109
MonotonicityNot monotonic
2024-04-17T01:36:49.504657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1130
13.4%
3290000 1059
12.5%
3300000 893
10.6%
3390000 688
8.1%
3270000 652
 
7.7%
3320000 578
 
6.8%
3380000 493
 
5.8%
3250000 478
 
5.6%
3260000 405
 
4.8%
3370000 383
 
4.5%
Other values (6) 1699
20.1%
ValueCountFrequency (%)
3250000 478
5.6%
3260000 405
 
4.8%
3270000 652
7.7%
3280000 362
 
4.3%
3290000 1059
12.5%
3300000 893
10.6%
3310000 284
 
3.4%
3320000 578
6.8%
3330000 1130
13.4%
3340000 357
 
4.2%
ValueCountFrequency (%)
3400000 206
 
2.4%
3390000 688
8.1%
3380000 493
5.8%
3370000 383
 
4.5%
3360000 137
 
1.6%
3350000 353
 
4.2%
3340000 357
 
4.2%
3330000 1130
13.4%
3320000 578
6.8%
3310000 284
 
3.4%

mgtno
Text

Distinct4190
Distinct (%)49.5%
Missing3
Missing (%)< 0.1%
Memory size66.2 KiB
2024-04-17T01:36:49.686947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.920312
Min length20

Characters and Unicode

Total characters185402
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

Unique117 ?
Unique (%)1.4%

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%
cdfi2262212016000001 11
 
0.1%
cdfi2262212015000002 11
 
0.1%
cdfi2262212017000001 11
 
0.1%
cdfi2262212016000002 10
 
0.1%
cdfi2262212020000001 10
 
0.1%
cdfi2262212017000002 9
 
0.1%
cdfi2260032020000001 9
 
0.1%
Other values (4180) 8348
98.7%
2024-04-17T01:36:49.998017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71403
38.5%
- 24363
 
13.1%
1 20013
 
10.8%
2 19776
 
10.7%
3 18186
 
9.8%
9 10160
 
5.5%
8 4969
 
2.7%
7 4870
 
2.6%
6 3678
 
2.0%
4 3597
 
1.9%
Other values (5) 4387
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 159691
86.1%
Dash Punctuation 24363
 
13.1%
Uppercase Letter 1348
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71403
44.7%
1 20013
 
12.5%
2 19776
 
12.4%
3 18186
 
11.4%
9 10160
 
6.4%
8 4969
 
3.1%
7 4870
 
3.0%
6 3678
 
2.3%
4 3597
 
2.3%
5 3039
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 337
25.0%
D 337
25.0%
F 337
25.0%
I 337
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24363
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 184054
99.3%
Latin 1348
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 71403
38.8%
- 24363
 
13.2%
1 20013
 
10.9%
2 19776
 
10.7%
3 18186
 
9.9%
9 10160
 
5.5%
8 4969
 
2.7%
7 4870
 
2.6%
6 3678
 
2.0%
4 3597
 
2.0%
Latin
ValueCountFrequency (%)
C 337
25.0%
D 337
25.0%
F 337
25.0%
I 337
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 185402
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 71403
38.5%
- 24363
 
13.1%
1 20013
 
10.8%
2 19776
 
10.7%
3 18186
 
9.8%
9 10160
 
5.5%
8 4969
 
2.7%
7 4870
 
2.6%
6 3678
 
2.0%
4 3597
 
1.9%
Other values (5) 4387
 
2.4%

opnsvcid
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
03_11_03_P
8121 
03_11_04_P
 
257
03_11_01_P
 
68
03_11_05_P
 
9
<NA>
 
3
Other values (2)
 
3

Length

Max length10
Median length10
Mean length9.9978726
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 8121
96.0%
03_11_04_P 257
 
3.0%
03_11_01_P 68
 
0.8%
03_11_05_P 9
 
0.1%
<NA> 3
 
< 0.1%
03_11_02_P 2
 
< 0.1%
03_11_06_P 1
 
< 0.1%

Length

2024-04-17T01:36:50.111843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:50.206392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8121
96.0%
03_11_04_p 257
 
3.0%
03_11_01_p 68
 
0.8%
03_11_05_p 9
 
0.1%
na 3
 
< 0.1%
03_11_02_p 2
 
< 0.1%
03_11_06_p 1
 
< 0.1%

updategbn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
I
8224 
U
 
234
180000000
 
3

Length

Max length9
Median length1
Mean length1.0028365
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 8224
97.2%
U 234
 
2.8%
180000000 3
 
< 0.1%

Length

2024-04-17T01:36:50.327957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:50.429313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 8224
97.2%
u 234
 
2.8%
180000000 3
 
< 0.1%
Distinct166
Distinct (%)2.0%
Missing3
Missing (%)< 0.1%
Memory size66.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-02-28 02:40:00
2024-04-17T01:36:50.524709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:36:50.650985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8114 
숙박업
 
195
외국인관광도시민박업
 
83
관광숙박업
 
68
한옥체험업
 
1

Length

Max length10
Median length4
Mean length4.0439664
Min length3

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> 8114
95.9%
숙박업 195
 
2.3%
외국인관광도시민박업 83
 
1.0%
관광숙박업 68
 
0.8%
한옥체험업 1
 
< 0.1%

Length

2024-04-17T01:36:50.783839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:50.881475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8114
95.9%
숙박업 195
 
2.3%
외국인관광도시민박업 83
 
1.0%
관광숙박업 68
 
0.8%
한옥체험업 1
 
< 0.1%

bplcnm
Text

Distinct3350
Distinct (%)39.6%
Missing3
Missing (%)< 0.1%
Memory size66.2 KiB
2024-04-17T01:36:51.127199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length5.100733
Min length1

Characters and Unicode

Total characters43142
Distinct characters645
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

Unique284 ?
Unique (%)3.4%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 칠구(K79)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 239
 
2.4%
모텔 188
 
1.9%
게스트하우스 122
 
1.2%
여관 82
 
0.8%
hotel 57
 
0.6%
house 50
 
0.5%
부산 50
 
0.5%
해운대 39
 
0.4%
여인숙 36
 
0.4%
32
 
0.3%
Other values (3433) 9125
91.1%
2024-04-17T01:36:51.517512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2897
 
6.7%
2022
 
4.7%
1797
 
4.2%
1792
 
4.2%
1579
 
3.7%
1486
 
3.4%
1298
 
3.0%
1284
 
3.0%
768
 
1.8%
715
 
1.7%
Other values (635) 27504
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36427
84.4%
Uppercase Letter 2255
 
5.2%
Space Separator 1579
 
3.7%
Lowercase Letter 1204
 
2.8%
Decimal Number 521
 
1.2%
Close Punctuation 500
 
1.2%
Open Punctuation 500
 
1.2%
Other Punctuation 104
 
0.2%
Dash Punctuation 28
 
0.1%
Letter Number 10
 
< 0.1%
Other values (4) 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2897
 
8.0%
2022
 
5.6%
1797
 
4.9%
1792
 
4.9%
1486
 
4.1%
1298
 
3.6%
1284
 
3.5%
768
 
2.1%
715
 
2.0%
622
 
1.7%
Other values (555) 21746
59.7%
Uppercase Letter
ValueCountFrequency (%)
E 232
 
10.3%
O 214
 
9.5%
H 196
 
8.7%
T 165
 
7.3%
S 162
 
7.2%
L 126
 
5.6%
A 124
 
5.5%
N 102
 
4.5%
U 100
 
4.4%
M 88
 
3.9%
Other values (16) 746
33.1%
Lowercase Letter
ValueCountFrequency (%)
e 199
16.5%
o 144
12.0%
s 102
8.5%
a 95
 
7.9%
n 91
 
7.6%
u 91
 
7.6%
t 82
 
6.8%
h 57
 
4.7%
l 54
 
4.5%
i 50
 
4.2%
Other values (16) 239
19.9%
Decimal Number
ValueCountFrequency (%)
2 120
23.0%
1 78
15.0%
5 63
12.1%
7 60
11.5%
9 54
10.4%
6 41
 
7.9%
0 40
 
7.7%
3 36
 
6.9%
4 19
 
3.6%
8 10
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 59
56.7%
& 25
24.0%
' 9
 
8.7%
, 6
 
5.8%
; 2
 
1.9%
2
 
1.9%
: 1
 
1.0%
Letter Number
ValueCountFrequency (%)
6
60.0%
4
40.0%
Math Symbol
ValueCountFrequency (%)
+ 4
66.7%
2
33.3%
Space Separator
ValueCountFrequency (%)
1579
100.0%
Close Punctuation
ValueCountFrequency (%)
) 500
100.0%
Open Punctuation
ValueCountFrequency (%)
( 500
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Other Symbol
ValueCountFrequency (%)
6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36425
84.4%
Latin 3469
 
8.0%
Common 3240
 
7.5%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2897
 
8.0%
2022
 
5.6%
1797
 
4.9%
1792
 
4.9%
1486
 
4.1%
1298
 
3.6%
1284
 
3.5%
768
 
2.1%
715
 
2.0%
622
 
1.7%
Other values (551) 21744
59.7%
Latin
ValueCountFrequency (%)
E 232
 
6.7%
O 214
 
6.2%
e 199
 
5.7%
H 196
 
5.7%
T 165
 
4.8%
S 162
 
4.7%
o 144
 
4.2%
L 126
 
3.6%
A 124
 
3.6%
N 102
 
2.9%
Other values (44) 1805
52.0%
Common
ValueCountFrequency (%)
1579
48.7%
) 500
 
15.4%
( 500
 
15.4%
2 120
 
3.7%
1 78
 
2.4%
5 63
 
1.9%
7 60
 
1.9%
. 59
 
1.8%
9 54
 
1.7%
6 41
 
1.3%
Other values (15) 186
 
5.7%
Han
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36419
84.4%
ASCII 6694
 
15.5%
Number Forms 10
 
< 0.1%
None 10
 
< 0.1%
CJK 8
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2897
 
8.0%
2022
 
5.6%
1797
 
4.9%
1792
 
4.9%
1486
 
4.1%
1298
 
3.6%
1284
 
3.5%
768
 
2.1%
715
 
2.0%
622
 
1.7%
Other values (550) 21738
59.7%
ASCII
ValueCountFrequency (%)
1579
23.6%
) 500
 
7.5%
( 500
 
7.5%
E 232
 
3.5%
O 214
 
3.2%
e 199
 
3.0%
H 196
 
2.9%
T 165
 
2.5%
S 162
 
2.4%
o 144
 
2.2%
Other values (64) 2803
41.9%
Number Forms
ValueCountFrequency (%)
6
60.0%
4
40.0%
None
ValueCountFrequency (%)
6
60.0%
2
 
20.0%
2
 
20.0%
CJK
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%
Punctuation
ValueCountFrequency (%)
1
100.0%

sitepostno
Text

MISSING 

Distinct492
Distinct (%)6.0%
Missing299
Missing (%)3.5%
Memory size66.2 KiB
2024-04-17T01:36:51.786574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters48972
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)0.2%

Sample

1st row600045
2nd row600051
3rd row600092
4th row600806
5th row600012
ValueCountFrequency (%)
612821 317
 
3.9%
616801 254
 
3.1%
612040 206
 
2.5%
612847 182
 
2.2%
607833 175
 
2.1%
601829 144
 
1.8%
617807 136
 
1.7%
613828 128
 
1.6%
607831 126
 
1.5%
607842 114
 
1.4%
Other values (482) 6380
78.2%
2024-04-17T01:36:52.174194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9822
20.1%
1 8020
16.4%
0 7971
16.3%
8 7920
16.2%
2 4283
8.7%
4 3436
 
7.0%
7 2594
 
5.3%
3 2455
 
5.0%
9 1401
 
2.9%
5 950
 
1.9%
Other values (5) 120
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48852
99.8%
Other Letter 120
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9822
20.1%
1 8020
16.4%
0 7971
16.3%
8 7920
16.2%
2 4283
8.8%
4 3436
 
7.0%
7 2594
 
5.3%
3 2455
 
5.0%
9 1401
 
2.9%
5 950
 
1.9%
Other Letter
ValueCountFrequency (%)
40
33.3%
20
16.7%
20
16.7%
20
16.7%
20
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 48852
99.8%
Hangul 120
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9822
20.1%
1 8020
16.4%
0 7971
16.3%
8 7920
16.2%
2 4283
8.8%
4 3436
 
7.0%
7 2594
 
5.3%
3 2455
 
5.0%
9 1401
 
2.9%
5 950
 
1.9%
Hangul
ValueCountFrequency (%)
40
33.3%
20
16.7%
20
16.7%
20
16.7%
20
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48852
99.8%
Hangul 120
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9822
20.1%
1 8020
16.4%
0 7971
16.3%
8 7920
16.2%
2 4283
8.8%
4 3436
 
7.0%
7 2594
 
5.3%
3 2455
 
5.0%
9 1401
 
2.9%
5 950
 
1.9%
Hangul
ValueCountFrequency (%)
40
33.3%
20
16.7%
20
16.7%
20
16.7%
20
16.7%
Distinct4032
Distinct (%)47.7%
Missing5
Missing (%)0.1%
Memory size66.2 KiB
2024-04-17T01:36:52.468422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length45
Mean length23.642266
Min length13

Characters and Unicode

Total characters199919
Distinct characters307
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

Unique241 ?
Unique (%)2.9%

Sample

1st row부산광역시 중구 남포동5가 8-1번지
2nd row부산광역시 중구 창선동1가 12-1번지
3rd row부산광역시 중구 대청동2가 23-3번지
4th row부산광역시 중구 부평동2가 24-3번지
5th row부산광역시 중구 중앙동2가 52-2번지
ValueCountFrequency (%)
부산광역시 8456
23.5%
해운대구 1130
 
3.1%
부산진구 1059
 
2.9%
동래구 893
 
2.5%
t통b반 868
 
2.4%
사상구 688
 
1.9%
동구 652
 
1.8%
온천동 644
 
1.8%
북구 582
 
1.6%
부전동 503
 
1.4%
Other values (4197) 20508
57.0%
2024-04-17T01:36:52.924011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35893
18.0%
10277
 
5.1%
10023
 
5.0%
9930
 
5.0%
8821
 
4.4%
8705
 
4.4%
1 8543
 
4.3%
8524
 
4.3%
8480
 
4.2%
8462
 
4.2%
Other values (297) 82261
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 114232
57.1%
Decimal Number 39590
 
19.8%
Space Separator 35893
 
18.0%
Dash Punctuation 7858
 
3.9%
Uppercase Letter 1782
 
0.9%
Other Punctuation 197
 
0.1%
Close Punctuation 124
 
0.1%
Open Punctuation 124
 
0.1%
Math Symbol 115
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10277
 
9.0%
10023
 
8.8%
9930
 
8.7%
8821
 
7.7%
8705
 
7.6%
8524
 
7.5%
8480
 
7.4%
8462
 
7.4%
8316
 
7.3%
1565
 
1.4%
Other values (261) 31129
27.3%
Uppercase Letter
ValueCountFrequency (%)
B 875
49.1%
T 869
48.8%
A 11
 
0.6%
K 6
 
0.3%
C 5
 
0.3%
O 3
 
0.2%
S 3
 
0.2%
E 2
 
0.1%
G 2
 
0.1%
M 2
 
0.1%
Other values (4) 4
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 8543
21.6%
2 5195
13.1%
3 4169
10.5%
4 4029
10.2%
5 3899
9.8%
0 3046
 
7.7%
6 3024
 
7.6%
7 2836
 
7.2%
8 2561
 
6.5%
9 2288
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 194
98.5%
. 2
 
1.0%
& 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
i 1
33.3%
e 1
33.3%
w 1
33.3%
Space Separator
ValueCountFrequency (%)
35893
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7858
100.0%
Close Punctuation
ValueCountFrequency (%)
) 124
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Math Symbol
ValueCountFrequency (%)
~ 115
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 114232
57.1%
Common 83901
42.0%
Latin 1786
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10277
 
9.0%
10023
 
8.8%
9930
 
8.7%
8821
 
7.7%
8705
 
7.6%
8524
 
7.5%
8480
 
7.4%
8462
 
7.4%
8316
 
7.3%
1565
 
1.4%
Other values (261) 31129
27.3%
Common
ValueCountFrequency (%)
35893
42.8%
1 8543
 
10.2%
- 7858
 
9.4%
2 5195
 
6.2%
3 4169
 
5.0%
4 4029
 
4.8%
5 3899
 
4.6%
0 3046
 
3.6%
6 3024
 
3.6%
7 2836
 
3.4%
Other values (8) 5409
 
6.4%
Latin
ValueCountFrequency (%)
B 875
49.0%
T 869
48.7%
A 11
 
0.6%
K 6
 
0.3%
C 5
 
0.3%
O 3
 
0.2%
S 3
 
0.2%
E 2
 
0.1%
G 2
 
0.1%
M 2
 
0.1%
Other values (8) 8
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 114232
57.1%
ASCII 85686
42.9%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35893
41.9%
1 8543
 
10.0%
- 7858
 
9.2%
2 5195
 
6.1%
3 4169
 
4.9%
4 4029
 
4.7%
5 3899
 
4.6%
0 3046
 
3.6%
6 3024
 
3.5%
7 2836
 
3.3%
Other values (25) 7194
 
8.4%
Hangul
ValueCountFrequency (%)
10277
 
9.0%
10023
 
8.8%
9930
 
8.7%
8821
 
7.7%
8705
 
7.6%
8524
 
7.5%
8480
 
7.4%
8462
 
7.4%
8316
 
7.3%
1565
 
1.4%
Other values (261) 31129
27.3%
Number Forms
ValueCountFrequency (%)
1
100.0%

rdnpostno
Real number (ℝ)

Distinct605
Distinct (%)7.2%
Missing5
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean48270.557
Minimum46023
Maximum49527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.5 KiB
2024-04-17T01:36:53.049726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46023
5-th percentile46503
Q147708
median48795
Q348947
95-th percentile49253
Maximum49527
Range3504
Interquartile range (IQR)1239

Descriptive statistics

Standard deviation875.76048
Coefficient of variation (CV)0.018142747
Kurtosis-0.45972112
Mean48270.557
Median Absolute Deviation (MAD)459
Skewness-0.84527957
Sum4.0817583 × 108
Variance766956.41
MonotonicityNot monotonic
2024-04-17T01:36:53.190717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48947 2946
34.8%
48094 184
 
2.2%
48095 128
 
1.5%
49269 98
 
1.2%
48072 89
 
1.1%
48093 85
 
1.0%
48303 82
 
1.0%
48055 79
 
0.9%
48283 73
 
0.9%
48816 66
 
0.8%
Other values (595) 4626
54.7%
ValueCountFrequency (%)
46023 4
 
< 0.1%
46027 16
0.2%
46028 1
 
< 0.1%
46032 2
 
< 0.1%
46033 2
 
< 0.1%
46036 4
 
< 0.1%
46044 21
0.2%
46050 1
 
< 0.1%
46056 8
 
0.1%
46057 14
0.2%
ValueCountFrequency (%)
49527 2
 
< 0.1%
49524 14
0.2%
49523 6
0.1%
49520 1
 
< 0.1%
49511 2
 
< 0.1%
49509 6
0.1%
49482 2
 
< 0.1%
49476 2
 
< 0.1%
49475 4
 
< 0.1%
49474 2
 
< 0.1%

rdnwhladdr
Text

MISSING 

Distinct2995
Distinct (%)50.7%
Missing2550
Missing (%)30.1%
Memory size66.2 KiB
2024-04-17T01:36:53.439002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length58
Mean length27.820842
Min length18

Characters and Unicode

Total characters164449
Distinct characters368
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique286 ?
Unique (%)4.8%

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 5911
 
19.2%
해운대구 912
 
3.0%
부산진구 725
 
2.4%
동래구 607
 
2.0%
사상구 515
 
1.7%
동구 487
 
1.6%
온천동 422
 
1.4%
수영구 391
 
1.3%
중구 388
 
1.3%
부전동 385
 
1.2%
Other values (2558) 20108
65.2%
2024-04-17T01:36:53.846512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24940
 
15.2%
7696
 
4.7%
7316
 
4.4%
6978
 
4.2%
6612
 
4.0%
6288
 
3.8%
1 6278
 
3.8%
6041
 
3.7%
5917
 
3.6%
) 5804
 
3.5%
Other values (358) 80579
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 97846
59.5%
Decimal Number 26661
 
16.2%
Space Separator 24940
 
15.2%
Close Punctuation 5804
 
3.5%
Open Punctuation 5804
 
3.5%
Dash Punctuation 1796
 
1.1%
Other Punctuation 1256
 
0.8%
Math Symbol 246
 
0.1%
Uppercase Letter 89
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7696
 
7.9%
7316
 
7.5%
6978
 
7.1%
6612
 
6.8%
6288
 
6.4%
6041
 
6.2%
5917
 
6.0%
5637
 
5.8%
3939
 
4.0%
3705
 
3.8%
Other values (316) 37717
38.5%
Uppercase Letter
ValueCountFrequency (%)
A 28
31.5%
B 19
21.3%
K 9
 
10.1%
C 5
 
5.6%
O 5
 
5.6%
S 4
 
4.5%
E 3
 
3.4%
F 2
 
2.2%
G 2
 
2.2%
U 2
 
2.2%
Other values (9) 10
 
11.2%
Decimal Number
ValueCountFrequency (%)
1 6278
23.5%
2 4095
15.4%
3 2986
11.2%
4 2271
 
8.5%
5 2132
 
8.0%
0 1912
 
7.2%
6 1890
 
7.1%
7 1829
 
6.9%
9 1688
 
6.3%
8 1580
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
b 1
25.0%
e 1
25.0%
w 1
25.0%
i 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 1246
99.2%
. 9
 
0.7%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
24940
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5804
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5804
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1796
100.0%
Math Symbol
ValueCountFrequency (%)
~ 246
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 97846
59.5%
Common 66507
40.4%
Latin 96
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7696
 
7.9%
7316
 
7.5%
6978
 
7.1%
6612
 
6.8%
6288
 
6.4%
6041
 
6.2%
5917
 
6.0%
5637
 
5.8%
3939
 
4.0%
3705
 
3.8%
Other values (316) 37717
38.5%
Latin
ValueCountFrequency (%)
A 28
29.2%
B 19
19.8%
K 9
 
9.4%
C 5
 
5.2%
O 5
 
5.2%
S 4
 
4.2%
3
 
3.1%
E 3
 
3.1%
F 2
 
2.1%
G 2
 
2.1%
Other values (14) 16
16.7%
Common
ValueCountFrequency (%)
24940
37.5%
1 6278
 
9.4%
) 5804
 
8.7%
( 5804
 
8.7%
2 4095
 
6.2%
3 2986
 
4.5%
4 2271
 
3.4%
5 2132
 
3.2%
0 1912
 
2.9%
6 1890
 
2.8%
Other values (8) 8395
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 97846
59.5%
ASCII 66600
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24940
37.4%
1 6278
 
9.4%
) 5804
 
8.7%
( 5804
 
8.7%
2 4095
 
6.1%
3 2986
 
4.5%
4 2271
 
3.4%
5 2132
 
3.2%
0 1912
 
2.9%
6 1890
 
2.8%
Other values (31) 8488
 
12.7%
Hangul
ValueCountFrequency (%)
7696
 
7.9%
7316
 
7.5%
6978
 
7.1%
6612
 
6.8%
6288
 
6.4%
6041
 
6.2%
5917
 
6.0%
5637
 
5.8%
3939
 
4.0%
3705
 
3.8%
Other values (316) 37717
38.5%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size66.2 KiB

dcbymd
Text

MISSING 

Distinct1321
Distinct (%)34.8%
Missing4665
Missing (%)55.1%
Memory size66.2 KiB
2024-04-17T01:36:54.109441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.971549
Min length4

Characters and Unicode

Total characters30260
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

Unique30 ?
Unique (%)0.8%

Sample

1st row20140310
2nd row20121231
3rd row20171120
4th row20171107
5th row20120514
ValueCountFrequency (%)
20041022 180
 
4.7%
20030122 64
 
1.7%
20120711 52
 
1.4%
20021024 38
 
1.0%
폐업일자 27
 
0.7%
20030305 26
 
0.7%
20030101 24
 
0.6%
20030227 22
 
0.6%
20051117 20
 
0.5%
20030123 18
 
0.5%
Other values (1311) 3325
87.6%
2024-04-17T01:36:54.479118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10169
33.6%
2 6331
20.9%
1 5481
18.1%
3 1403
 
4.6%
9 1392
 
4.6%
7 1185
 
3.9%
4 1116
 
3.7%
6 1075
 
3.6%
5 1057
 
3.5%
8 943
 
3.1%
Other values (4) 108
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30152
99.6%
Other Letter 108
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10169
33.7%
2 6331
21.0%
1 5481
18.2%
3 1403
 
4.7%
9 1392
 
4.6%
7 1185
 
3.9%
4 1116
 
3.7%
6 1075
 
3.6%
5 1057
 
3.5%
8 943
 
3.1%
Other Letter
ValueCountFrequency (%)
27
25.0%
27
25.0%
27
25.0%
27
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30152
99.6%
Hangul 108
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10169
33.7%
2 6331
21.0%
1 5481
18.2%
3 1403
 
4.7%
9 1392
 
4.6%
7 1185
 
3.9%
4 1116
 
3.7%
6 1075
 
3.6%
5 1057
 
3.5%
8 943
 
3.1%
Hangul
ValueCountFrequency (%)
27
25.0%
27
25.0%
27
25.0%
27
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30152
99.6%
Hangul 108
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10169
33.7%
2 6331
21.0%
1 5481
18.2%
3 1403
 
4.7%
9 1392
 
4.6%
7 1185
 
3.9%
4 1116
 
3.7%
6 1075
 
3.6%
5 1057
 
3.5%
8 943
 
3.1%
Hangul
ValueCountFrequency (%)
27
25.0%
27
25.0%
27
25.0%
27
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8427 
휴업시작일자
 
27
20200120
 
1
20160608
 
1
20160425
 
1
Other values (4)
 
4

Length

Max length8
Median length4
Mean length4.0096915
Min length4

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8427
99.6%
휴업시작일자 27
 
0.3%
20200120 1
 
< 0.1%
20160608 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20180719 1
 
< 0.1%
20201001 1
 
< 0.1%

Length

2024-04-17T01:36:54.612088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:54.714256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8427
99.6%
휴업시작일자 27
 
0.3%
20200120 1
 
< 0.1%
20160608 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20180719 1
 
< 0.1%
20201001 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8427 
휴업종료일자
 
27
20220119
 
1
20170607
 
1
20180424
 
1
Other values (4)
 
4

Length

Max length8
Median length4
Mean length4.0096915
Min length4

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8427
99.6%
휴업종료일자 27
 
0.3%
20220119 1
 
< 0.1%
20170607 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20181231 1
 
< 0.1%
20211001 1
 
< 0.1%

Length

2024-04-17T01:36:54.839804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:55.234467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8427
99.6%
휴업종료일자 27
 
0.3%
20220119 1
 
< 0.1%
20170607 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20181231 1
 
< 0.1%
20211001 1
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
재개업일자
 
27

Length

Max length5
Median length4
Mean length4.0031911
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> 8434
99.7%
재개업일자 27
 
0.3%

Length

2024-04-17T01:36:55.348369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:55.436172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
재개업일자 27
 
0.3%

trdstatenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
01
4220 
02
3711 
영업/정상
 
332
13
 
126
03
 
53
Other values (4)
 
19

Length

Max length5
Median length2
Mean length2.1191349
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
01 4220
49.9%
02 3711
43.9%
영업/정상 332
 
3.9%
13 126
 
1.5%
03 53
 
0.6%
폐업 10
 
0.1%
<NA> 6
 
0.1%
휴업 2
 
< 0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:36:55.542210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:55.668166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01 4220
49.9%
02 3711
43.9%
영업/정상 332
 
3.9%
13 126
 
1.5%
03 53
 
0.6%
폐업 10
 
0.1%
na 6
 
0.1%
휴업 2
 
< 0.1%
31 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
영업
4407 
폐업
3769 
영업중
 
274
휴업
 
7
<NA>
 
3

Length

Max length4
Median length2
Mean length2.0333294
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4407
52.1%
폐업 3769
44.5%
영업중 274
 
3.2%
휴업 7
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:36:55.803267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:55.944854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4407
52.1%
폐업 3769
44.5%
영업중 274
 
3.2%
휴업 7
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing385
Missing (%)4.6%
Memory size66.2 KiB

y
Real number (ℝ)

MISSING 

Distinct3917
Distinct (%)48.5%
Missing388
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean186751.68
Minimum169998.58
Maximum209754.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.5 KiB
2024-04-17T01:36:56.075205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169998.58
5-th percentile178709.42
Q1182942.11
median186964.84
Q3189982.56
95-th percentile193852.39
Maximum209754.15
Range39755.577
Interquartile range (IQR)7040.4539

Descriptive statistics

Standard deviation5113.5766
Coefficient of variation (CV)0.02738169
Kurtosis0.083138547
Mean186751.68
Median Absolute Deviation (MAD)3603.0502
Skewness0.10828113
Sum1.5076463 × 109
Variance26148666
MonotonicityNot monotonic
2024-04-17T01:36:56.224506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185933.100965604 16
 
0.2%
187092.852201 16
 
0.2%
176595.034934652 11
 
0.1%
187269.854013 8
 
0.1%
186965.399683 8
 
0.1%
192327.468209 8
 
0.1%
186243.806655 8
 
0.1%
189143.147865081 7
 
0.1%
187863.015365939 7
 
0.1%
192061.533055 6
 
0.1%
Other values (3907) 7978
94.3%
(Missing) 388
 
4.6%
ValueCountFrequency (%)
169998.576608 2
< 0.1%
171461.496152 2
< 0.1%
174251.232048 2
< 0.1%
174413.752458 1
< 0.1%
174599.932466 2
< 0.1%
174999.02898 2
< 0.1%
175045.348943 2
< 0.1%
175046.263792 2
< 0.1%
175057.331511 2
< 0.1%
175075.261586 2
< 0.1%
ValueCountFrequency (%)
209754.153703 1
< 0.1%
207516.984282 2
< 0.1%
207378.835702 1
< 0.1%
206172.903942 2
< 0.1%
206065.80538 2
< 0.1%
205949.336131 2
< 0.1%
205793.809975 2
< 0.1%
205774.280535 2
< 0.1%
205756.904836 2
< 0.1%
205755.902784 2
< 0.1%

lastmodts
Real number (ℝ)

Distinct3656
Distinct (%)43.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0130392 × 1013
Minimum1.9990211 × 1013
Maximum2.0210226 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.5 KiB
2024-04-17T01:36:56.372225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0011004 × 1013
Q12.0060509 × 1013
median2.0171124 × 1013
Q32.0180427 × 1013
95-th percentile2.0180828 × 1013
Maximum2.0210226 × 1013
Range2.2001517 × 1011
Interquartile range (IQR)1.1991811 × 1011

Descriptive statistics

Standard deviation6.6007648 × 1010
Coefficient of variation (CV)0.0032790046
Kurtosis-0.92962543
Mean2.0130392 × 1013
Median Absolute Deviation (MAD)9.6070658 × 109
Skewness-0.85236398
Sum1.7026286 × 1017
Variance4.3570096 × 1021
MonotonicityNot monotonic
2024-04-17T01:36:56.505436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19990428000000 62
 
0.7%
20040902000000 60
 
0.7%
19990920000000 60
 
0.7%
20030122000000 58
 
0.7%
20040203000000 50
 
0.6%
20070531000000 36
 
0.4%
20030414000000 36
 
0.4%
20030329000000 32
 
0.4%
20020515000000 32
 
0.4%
19990308000000 32
 
0.4%
Other values (3646) 8000
94.6%
ValueCountFrequency (%)
19990211000000 2
 
< 0.1%
19990218000000 20
0.2%
19990223000000 2
 
< 0.1%
19990225000000 6
 
0.1%
19990302000000 4
 
< 0.1%
19990303000000 18
0.2%
19990308000000 32
0.4%
19990309000000 6
 
0.1%
19990310000000 2
 
< 0.1%
19990315000000 2
 
< 0.1%
ValueCountFrequency (%)
20210226172612 2
< 0.1%
20210226155259 2
< 0.1%
20210226143241 2
< 0.1%
20210226105722 2
< 0.1%
20210225131251 2
< 0.1%
20210224185325 1
< 0.1%
20210224180723 1
< 0.1%
20210224180651 1
< 0.1%
20210224165055 2
< 0.1%
20210224152248 2
< 0.1%

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
여관업
5281 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
480
일반호텔
 
415
Other values (4)
620 

Length

Max length8
Median length3
Mean length3.6918804
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5281
62.4%
여인숙업 1076
 
12.7%
숙박업 기타 589
 
7.0%
숙박업(생활) 480
 
5.7%
일반호텔 415
 
4.9%
<NA> 322
 
3.8%
관광호텔 269
 
3.2%
업태구분명 20
 
0.2%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:36:56.626332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:56.760265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5281
58.4%
여인숙업 1076
 
11.9%
숙박업 589
 
6.5%
기타 589
 
6.5%
숙박업(생활 480
 
5.3%
일반호텔 415
 
4.6%
na 322
 
3.6%
관광호텔 269
 
3.0%
업태구분명 20
 
0.2%
휴양콘도미니엄업 9
 
0.1%

sitetel
Categorical

IMBALANCE 

Distinct44
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
051-123-1234
8336 
<NA>
 
58
051 806 7779
 
3
051 803 6996
 
3
051 7846654
 
2
Other values (39)
 
59

Length

Max length12
Median length12
Mean length11.93996
Min length4

Unique

Unique19 ?
Unique (%)0.2%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234

Common Values

ValueCountFrequency (%)
051-123-1234 8336
98.5%
<NA> 58
 
0.7%
051 806 7779 3
 
< 0.1%
051 803 6996 3
 
< 0.1%
051 7846654 2
 
< 0.1%
051 808 9096 2
 
< 0.1%
051 819 8231 2
 
< 0.1%
070 77493650 2
 
< 0.1%
051 8181654 2
 
< 0.1%
051 321 1220 2
 
< 0.1%
Other values (34) 49
 
0.6%

Length

2024-04-17T01:36:56.886761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 8336
97.6%
na 58
 
0.7%
051 52
 
0.6%
802 4
 
< 0.1%
070 4
 
< 0.1%
7779 3
 
< 0.1%
803 3
 
< 0.1%
6996 3
 
< 0.1%
806 3
 
< 0.1%
7602100 2
 
< 0.1%
Other values (52) 77
 
0.9%

stroomcnt
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8328 
1
 
31
2
 
27
3
 
19
객실수
 
18
Other values (20)
 
38

Length

Max length4
Median length4
Mean length3.9602884
Min length1

Unique

Unique12 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8328
98.4%
1 31
 
0.4%
2 27
 
0.3%
3 19
 
0.2%
객실수 18
 
0.2%
7 5
 
0.1%
6 5
 
0.1%
5 3
 
< 0.1%
11 3
 
< 0.1%
49 3
 
< 0.1%
Other values (15) 19
 
0.2%

Length

2024-04-17T01:36:57.016918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8328
98.4%
1 31
 
0.4%
2 27
 
0.3%
3 19
 
0.2%
객실수 18
 
0.2%
7 5
 
0.1%
6 5
 
0.1%
5 3
 
< 0.1%
11 3
 
< 0.1%
49 3
 
< 0.1%
Other values (15) 19
 
0.2%

bdngownsenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
6486 
자가
1175 
임대
773 
건물소유구분명
 
27

Length

Max length7
Median length4
Mean length3.5491077
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6486
76.7%
자가 1175
 
13.9%
임대 773
 
9.1%
건물소유구분명 27
 
0.3%

Length

2024-04-17T01:36:57.131610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:57.229807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6486
76.7%
자가 1175
 
13.9%
임대 773
 
9.1%
건물소유구분명 27
 
0.3%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8281 
단독주택
 
65
아파트
 
53
건물용도명
 
17
숙박시설
 
16
Other values (6)
 
29

Length

Max length15
Median length4
Mean length4.0023638
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> 8281
97.9%
단독주택 65
 
0.8%
아파트 53
 
0.6%
건물용도명 17
 
0.2%
숙박시설 16
 
0.2%
다세대주택 12
 
0.1%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 주택(공동주택적용) 4
 
< 0.1%
호텔 3
 
< 0.1%

Length

2024-04-17T01:36:57.327540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8281
97.8%
단독주택 65
 
0.8%
아파트 53
 
0.6%
건물용도명 17
 
0.2%
숙박시설 16
 
0.2%
다세대주택 12
 
0.1%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 4
 
< 0.1%
주택(공동주택적용 4
 
< 0.1%
Other values (2) 4
 
< 0.1%

bdngjisgflrcnt
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
0
2558 
<NA>
1658 
4
859 
3
749 
5
587 
Other values (30)
2050 

Length

Max length6
Median length1
Mean length1.64295
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2558
30.2%
<NA> 1658
19.6%
4 859
 
10.2%
3 749
 
8.9%
5 587
 
6.9%
2 423
 
5.0%
8 319
 
3.8%
6 303
 
3.6%
7 299
 
3.5%
9 195
 
2.3%
Other values (25) 511
 
6.0%

Length

2024-04-17T01:36:57.435170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2558
30.2%
na 1658
19.6%
4 859
 
10.2%
3 749
 
8.9%
5 587
 
6.9%
2 423
 
5.0%
8 319
 
3.8%
6 303
 
3.6%
7 299
 
3.5%
9 195
 
2.3%
Other values (25) 511
 
6.0%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
0
4445 
<NA>
2224 
1
1476 
2
 
193
4
 
36
Other values (9)
 
87

Length

Max length6
Median length1
Mean length1.8010873
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4445
52.5%
<NA> 2224
26.3%
1 1476
 
17.4%
2 193
 
2.3%
4 36
 
0.4%
3 26
 
0.3%
건물지하층수 20
 
0.2%
5 17
 
0.2%
8 6
 
0.1%
6 4
 
< 0.1%
Other values (4) 14
 
0.2%

Length

2024-04-17T01:36:57.541347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4445
52.5%
na 2224
26.3%
1 1478
 
17.5%
2 193
 
2.3%
4 36
 
0.4%
3 26
 
0.3%
건물지하층수 20
 
0.2%
5 17
 
0.2%
8 6
 
0.1%
6 4
 
< 0.1%
Other values (3) 12
 
0.1%

cnstyarea
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8420 
건축연면적
 
24
2282
 
3
20571
 
3
72
 
1
Other values (10)
 
10

Length

Max length5
Median length4
Mean length4.0020092
Min length2

Unique

Unique11 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8420
99.5%
건축연면적 24
 
0.3%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
72 1
 
< 0.1%
39 1
 
< 0.1%
85 1
 
< 0.1%
437 1
 
< 0.1%
132 1
 
< 0.1%
352 1
 
< 0.1%
Other values (5) 5
 
0.1%

Length

2024-04-17T01:36:57.648561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8420
99.5%
건축연면적 24
 
0.3%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
72 1
 
< 0.1%
39 1
 
< 0.1%
85 1
 
< 0.1%
437 1
 
< 0.1%
132 1
 
< 0.1%
352 1
 
< 0.1%
Other values (5) 5
 
0.1%

svnsr
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
기념품종류
 
27

Length

Max length5
Median length4
Mean length4.0031911
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> 8434
99.7%
기념품종류 27
 
0.3%

Length

2024-04-17T01:36:57.746255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:57.826164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
기념품종류 27
 
0.3%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
기획여행보험시작일자
 
27

Length

Max length10
Median length4
Mean length4.0191467
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> 8434
99.7%
기획여행보험시작일자 27
 
0.3%

Length

2024-04-17T01:36:57.933337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:58.021594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
기획여행보험시작일자 27
 
0.3%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
기획여행보험종료일자
 
27

Length

Max length10
Median length4
Mean length4.0191467
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> 8434
99.7%
기획여행보험종료일자 27
 
0.3%

Length

2024-04-17T01:36:58.116653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:58.240072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
기획여행보험종료일자 27
 
0.3%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
7923 
0
 
489
남성종사자수
 
22
1
 
10
3
 
4
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.8223614
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> 7923
93.6%
0 489
 
5.8%
남성종사자수 22
 
0.3%
1 10
 
0.1%
3 4
 
< 0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
35 1
 
< 0.1%

Length

2024-04-17T01:36:58.356010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7923
93.6%
0 489
 
5.8%
남성종사자수 22
 
0.3%
1 10
 
0.1%
3 4
 
< 0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
35 1
 
< 0.1%

playutscntdtl
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
놀이기구수내역
 
27

Length

Max length7
Median length4
Mean length4.0095733
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> 8434
99.7%
놀이기구수내역 27
 
0.3%

Length

2024-04-17T01:36:58.473105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:58.594480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
놀이기구수내역 27
 
0.3%

playfacilcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
N
8333 
<NA>
 
118
놀이시설수
 
7
Y
 
3

Length

Max length5
Median length1
Mean length1.0451483
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8333
98.5%
<NA> 118
 
1.4%
놀이시설수 7
 
0.1%
Y 3
 
< 0.1%

Length

2024-04-17T01:36:58.711595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:58.832973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8333
98.5%
na 118
 
1.4%
놀이시설수 7
 
0.1%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
N
8403 
<NA>
 
47
Y
 
9
 
2

Length

Max length4
Median length1
Mean length1.0166647
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8403
99.3%
<NA> 47
 
0.6%
Y 9
 
0.1%
2
 
< 0.1%

Length

2024-04-17T01:36:58.958693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:59.066833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8403
99.3%
na 47
 
0.6%
y 9
 
0.1%
2
 
< 0.1%

stagear
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
무대면적
 
27

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> 8434
99.7%
무대면적 27
 
0.3%

Length

2024-04-17T01:36:59.156118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:59.236087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
무대면적 27
 
0.3%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
문화사업자구분명
 
27

Length

Max length8
Median length4
Mean length4.0127644
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> 8434
99.7%
문화사업자구분명 27
 
0.3%

Length

2024-04-17T01:36:59.336139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:59.443130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
문화사업자구분명 27
 
0.3%

culphyedcobnm
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8117 
외국인관광 도시민박업
 
257
관광숙박업
 
68
자동차야영장업
 
9
문화체육업종명
 
7
Other values (2)
 
3

Length

Max length11
Median length4
Mean length4.2266872
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> 8117
95.9%
외국인관광 도시민박업 257
 
3.0%
관광숙박업 68
 
0.8%
자동차야영장업 9
 
0.1%
문화체육업종명 7
 
0.1%
관광펜션업 2
 
< 0.1%
한옥체험업 1
 
< 0.1%

Length

2024-04-17T01:36:59.543363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:59.638962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8117
93.1%
외국인관광 257
 
2.9%
도시민박업 257
 
2.9%
관광숙박업 68
 
0.8%
자동차야영장업 9
 
0.1%
문화체육업종명 7
 
0.1%
관광펜션업 2
 
< 0.1%
한옥체험업 1
 
< 0.1%

geicpfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
 
27

Length

Max length4
Median length4
Mean length3.9904267
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> 8434
99.7%
27
 
0.3%

Length

2024-04-17T01:36:59.742760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:36:59.829450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
27
 
0.3%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
N
8388 
<NA>
 
47
Y
 
24
 
2

Length

Max length4
Median length1
Mean length1.0166647
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8388
99.1%
<NA> 47
 
0.6%
Y 24
 
0.3%
2
 
< 0.1%

Length

2024-04-17T01:36:59.923761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:00.018243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8388
99.1%
na 47
 
0.6%
y 24
 
0.3%
2
 
< 0.1%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
 
27

Length

Max length4
Median length4
Mean length3.9904267
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> 8434
99.7%
27
 
0.3%

Length

2024-04-17T01:37:00.114914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:00.201125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
27
 
0.3%

insurorgnm
Categorical

IMBALANCE 

Distinct22
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8413 
보험기관명
 
27
객실수/수용인원 : 2개/ 6명
 
2
객실 1개/4인
 
1
객실수/수용인원 : 3/8
 
1
Other values (17)
 
17

Length

Max length22
Median length4
Mean length4.0217468
Min length2

Unique

Unique19 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8413
99.4%
보험기관명 27
 
0.3%
객실수/수용인원 : 2개/ 6명 2
 
< 0.1%
객실 1개/4인 1
 
< 0.1%
객실수/수용인원 : 3/8 1
 
< 0.1%
객실수/수용인원:2/6 1
 
< 0.1%
객실수/수용인원: 3/8 1
 
< 0.1%
객실수/수용인원:2/3 1
 
< 0.1%
객실수/수용인원:2/5 1
 
< 0.1%
객실수2/수용인원12 1
 
< 0.1%
Other values (12) 12
 
0.1%

Length

2024-04-17T01:37:00.309808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8413
99.2%
보험기관명 27
 
0.3%
객실수/수용인원 6
 
0.1%
5
 
0.1%
2개 2
 
< 0.1%
6명 2
 
< 0.1%
3/8 2
 
< 0.1%
객실수 1
 
< 0.1%
객실수/수용인원:1/2 1
 
< 0.1%
동부 1
 
< 0.1%
Other values (17) 17
 
0.2%

insurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
보험시작일자
 
27

Length

Max length6
Median length4
Mean length4.0063822
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> 8434
99.7%
보험시작일자 27
 
0.3%

Length

2024-04-17T01:37:00.435807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:00.542901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
보험시작일자 27
 
0.3%

insurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
보험종료일자
 
27

Length

Max length6
Median length4
Mean length4.0063822
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> 8434
99.7%
보험종료일자 27
 
0.3%

Length

2024-04-17T01:37:00.654426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:00.752691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
보험종료일자 27
 
0.3%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
부대시설내역
 
27

Length

Max length6
Median length4
Mean length4.0063822
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> 8434
99.7%
부대시설내역 27
 
0.3%

Length

2024-04-17T01:37:00.892067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:01.014775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
부대시설내역 27
 
0.3%

usejisgendflr
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
2685 
0
1981 
4
751 
3
646 
5
465 
Other values (30)
1933 

Length

Max length6
Median length1
Mean length2.0028365
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2685
31.7%
0 1981
23.4%
4 751
 
8.9%
3 646
 
7.6%
5 465
 
5.5%
6 417
 
4.9%
2 387
 
4.6%
7 262
 
3.1%
8 253
 
3.0%
9 187
 
2.2%
Other values (25) 427
 
5.0%

Length

2024-04-17T01:37:01.151052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2685
31.7%
0 1981
23.4%
4 751
 
8.9%
3 646
 
7.6%
5 465
 
5.5%
6 417
 
4.9%
2 387
 
4.6%
7 262
 
3.1%
8 253
 
3.0%
9 187
 
2.2%
Other values (25) 427
 
5.0%

useunderendflr
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
0
4621 
<NA>
3607 
1
 
180
사용끝지하층
 
22
2
 
16
Other values (5)
 
15

Length

Max length6
Median length1
Mean length2.2922822
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4621
54.6%
<NA> 3607
42.6%
1 180
 
2.1%
사용끝지하층 22
 
0.3%
2 16
 
0.2%
4 4
 
< 0.1%
7 4
 
< 0.1%
3 4
 
< 0.1%
10 2
 
< 0.1%
19 1
 
< 0.1%

Length

2024-04-17T01:37:01.254758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:01.358318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4621
54.6%
na 3607
42.6%
1 180
 
2.1%
사용끝지하층 22
 
0.3%
2 16
 
0.2%
4 4
 
< 0.1%
7 4
 
< 0.1%
3 4
 
< 0.1%
10 2
 
< 0.1%
19 1
 
< 0.1%

usejisgstflr
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
0
2474 
1
1896 
<NA>
1857 
2
978 
3
498 
Other values (15)
758 

Length

Max length7
Median length1
Mean length1.6797069
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2474
29.2%
1 1896
22.4%
<NA> 1857
21.9%
2 978
 
11.6%
3 498
 
5.9%
4 305
 
3.6%
5 196
 
2.3%
6 69
 
0.8%
7 59
 
0.7%
8 34
 
0.4%
Other values (10) 95
 
1.1%

Length

2024-04-17T01:37:01.475236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2474
29.2%
1 1896
22.4%
na 1857
21.9%
2 978
 
11.6%
3 498
 
5.9%
4 305
 
3.6%
5 196
 
2.3%
6 69
 
0.8%
7 59
 
0.7%
8 34
 
0.4%
Other values (10) 95
 
1.1%

useunderstflr
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
0
5558 
<NA>
2656 
1
 
211
사용시작지하층
 
22
4
 
8
Other values (3)
 
6

Length

Max length7
Median length1
Mean length1.9573336
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5558
65.7%
<NA> 2656
31.4%
1 211
 
2.5%
사용시작지하층 22
 
0.3%
4 8
 
0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
2 2
 
< 0.1%

Length

2024-04-17T01:37:01.580482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:02.023698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5558
65.7%
na 2656
31.4%
1 211
 
2.5%
사용시작지하층 22
 
0.3%
4 8
 
0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
2 2
 
< 0.1%

shpinfo
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
선박제원
 
27

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> 8434
99.7%
선박제원 27
 
0.3%

Length

2024-04-17T01:37:02.142363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:02.227881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
선박제원 27
 
0.3%

shpcnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
선박척수
 
27

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> 8434
99.7%
선박척수 27
 
0.3%

Length

2024-04-17T01:37:02.343738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:02.429003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
선박척수 27
 
0.3%

shptottons
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
선박총톤수
 
27

Length

Max length5
Median length4
Mean length4.0031911
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> 8434
99.7%
선박총톤수 27
 
0.3%

Length

2024-04-17T01:37:02.513804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:02.603391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
선박총톤수 27
 
0.3%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
0
4968 
<NA>
3473 
세탁기수
 
20

Length

Max length4
Median length1
Mean length2.2385061
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4968
58.7%
<NA> 3473
41.0%
세탁기수 20
 
0.2%

Length

2024-04-17T01:37:02.695382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:02.781847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4968
58.7%
na 3473
41.0%
세탁기수 20
 
0.2%

facilscp
Text

MISSING 

Distinct139
Distinct (%)50.9%
Missing8188
Missing (%)96.8%
Memory size66.2 KiB
2024-04-17T01:37:03.023426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.6959707
Min length2

Characters and Unicode

Total characters736
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

Unique78 ?
Unique (%)28.6%

Sample

1st row시설규모
2nd row599
3rd row599
4th row599
5th row599
ValueCountFrequency (%)
85 15
 
5.5%
시설규모 9
 
3.3%
46 7
 
2.6%
599 6
 
2.2%
60 6
 
2.2%
83 6
 
2.2%
63 5
 
1.8%
67 5
 
1.8%
80 4
 
1.5%
57 4
 
1.5%
Other values (129) 206
75.5%
2024-04-17T01:37:03.411052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 110
14.9%
8 79
10.7%
5 79
10.7%
2 69
9.4%
6 67
9.1%
9 63
8.6%
4 62
8.4%
7 62
8.4%
3 59
8.0%
0 50
6.8%
Other values (4) 36
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 700
95.1%
Other Letter 36
 
4.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 110
15.7%
8 79
11.3%
5 79
11.3%
2 69
9.9%
6 67
9.6%
9 63
9.0%
4 62
8.9%
7 62
8.9%
3 59
8.4%
0 50
7.1%
Other Letter
ValueCountFrequency (%)
9
25.0%
9
25.0%
9
25.0%
9
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 700
95.1%
Hangul 36
 
4.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 110
15.7%
8 79
11.3%
5 79
11.3%
2 69
9.9%
6 67
9.6%
9 63
9.0%
4 62
8.9%
7 62
8.9%
3 59
8.4%
0 50
7.1%
Hangul
ValueCountFrequency (%)
9
25.0%
9
25.0%
9
25.0%
9
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 700
95.1%
Hangul 36
 
4.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 110
15.7%
8 79
11.3%
5 79
11.3%
2 69
9.9%
6 67
9.6%
9 63
9.0%
4 62
8.9%
7 62
8.9%
3 59
8.4%
0 50
7.1%
Hangul
ValueCountFrequency (%)
9
25.0%
9
25.0%
9
25.0%
9
25.0%

facilar
Text

MISSING 

Distinct200
Distinct (%)73.3%
Missing8188
Missing (%)96.8%
Memory size66.2 KiB
2024-04-17T01:37:03.747468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.1868132
Min length2

Characters and Unicode

Total characters1416
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

Unique164 ?
Unique (%)60.1%

Sample

1st row시설면적
2nd row598.73
3rd row598.73
4th row598.73
5th row598.73
ValueCountFrequency (%)
시설면적 9
 
3.3%
598.73 6
 
2.2%
45.5 6
 
2.2%
62.58 4
 
1.5%
57.09 3
 
1.1%
1497.35 3
 
1.1%
392.02 3
 
1.1%
83.36 3
 
1.1%
337.46 3
 
1.1%
8546.81 3
 
1.1%
Other values (190) 230
84.2%
2024-04-17T01:37:04.214731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 240
16.9%
1 154
10.9%
8 139
9.8%
4 136
9.6%
5 114
8.1%
6 112
7.9%
2 111
7.8%
3 107
7.6%
9 103
7.3%
7 99
7.0%
Other values (5) 101
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1140
80.5%
Other Punctuation 240
 
16.9%
Other Letter 36
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 154
13.5%
8 139
12.2%
4 136
11.9%
5 114
10.0%
6 112
9.8%
2 111
9.7%
3 107
9.4%
9 103
9.0%
7 99
8.7%
0 65
5.7%
Other Letter
ValueCountFrequency (%)
9
25.0%
9
25.0%
9
25.0%
9
25.0%
Other Punctuation
ValueCountFrequency (%)
. 240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1380
97.5%
Hangul 36
 
2.5%

Most frequent character per script

Common
ValueCountFrequency (%)
. 240
17.4%
1 154
11.2%
8 139
10.1%
4 136
9.9%
5 114
8.3%
6 112
8.1%
2 111
8.0%
3 107
7.8%
9 103
7.5%
7 99
7.2%
Hangul
ValueCountFrequency (%)
9
25.0%
9
25.0%
9
25.0%
9
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1380
97.5%
Hangul 36
 
2.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 240
17.4%
1 154
11.2%
8 139
10.1%
4 136
9.9%
5 114
8.3%
6 112
8.1%
2 111
8.0%
3 107
7.8%
9 103
7.5%
7 99
7.2%
Hangul
ValueCountFrequency (%)
9
25.0%
9
25.0%
9
25.0%
9
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
 
27

Length

Max length4
Median length4
Mean length3.9904267
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> 8434
99.7%
27
 
0.3%

Length

2024-04-17T01:37:04.346037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:04.468604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
27
 
0.3%

yangsilcnt
Text

MISSING 

Distinct148
Distinct (%)2.0%
Missing900
Missing (%)10.6%
Memory size66.2 KiB
2024-04-17T01:37:04.632055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7368073
Min length1

Characters and Unicode

Total characters13132
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)0.2%

Sample

1st row107
2nd row81
3rd row16
4th row7
5th row5
ValueCountFrequency (%)
0 1042
 
13.8%
10 437
 
5.8%
18 368
 
4.9%
12 318
 
4.2%
14 314
 
4.2%
15 302
 
4.0%
13 248
 
3.3%
19 242
 
3.2%
17 222
 
2.9%
16 219
 
2.9%
Other values (138) 3849
50.9%
2024-04-17T01:37:04.953312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3428
26.1%
0 1919
14.6%
2 1873
14.3%
3 1337
 
10.2%
4 1039
 
7.9%
5 820
 
6.2%
8 811
 
6.2%
6 631
 
4.8%
9 611
 
4.7%
7 603
 
4.6%
Other values (3) 60
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13072
99.5%
Other Letter 60
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3428
26.2%
0 1919
14.7%
2 1873
14.3%
3 1337
 
10.2%
4 1039
 
7.9%
5 820
 
6.3%
8 811
 
6.2%
6 631
 
4.8%
9 611
 
4.7%
7 603
 
4.6%
Other Letter
ValueCountFrequency (%)
20
33.3%
20
33.3%
20
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13072
99.5%
Hangul 60
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3428
26.2%
0 1919
14.7%
2 1873
14.3%
3 1337
 
10.2%
4 1039
 
7.9%
5 820
 
6.3%
8 811
 
6.2%
6 631
 
4.8%
9 611
 
4.7%
7 603
 
4.6%
Hangul
ValueCountFrequency (%)
20
33.3%
20
33.3%
20
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13072
99.5%
Hangul 60
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3428
26.2%
0 1919
14.7%
2 1873
14.3%
3 1337
 
10.2%
4 1039
 
7.9%
5 820
 
6.3%
8 811
 
6.2%
6 631
 
4.8%
9 611
 
4.7%
7 603
 
4.6%
Hangul
ValueCountFrequency (%)
20
33.3%
20
33.3%
20
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
7925 
0
 
494
여성종사자수
 
22
1
 
6
3
 
5
Other values (4)
 
9

Length

Max length6
Median length4
Mean length3.8233069
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> 7925
93.7%
0 494
 
5.8%
여성종사자수 22
 
0.3%
1 6
 
0.1%
3 5
 
0.1%
2 4
 
< 0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

Length

2024-04-17T01:37:05.071115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:05.190929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7925
93.7%
0 494
 
5.8%
여성종사자수 22
 
0.3%
1 6
 
0.1%
3 5
 
0.1%
2 4
 
< 0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

engstntrnmnm
Text

MISSING 

Distinct44
Distinct (%)53.0%
Missing8378
Missing (%)99.0%
Memory size66.2 KiB
2024-04-17T01:37:05.409206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length23
Mean length12.722892
Min length4

Characters and Unicode

Total characters1056
Distinct characters57
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

Unique34 ?
Unique (%)41.0%

Sample

1st row영문상호명
2nd row영문상호명
3rd rowPARKVILL
4th rowMonohouse Busan
5th rowDal guesthouse
ValueCountFrequency (%)
house 29
 
17.3%
영문상호명 24
 
14.3%
busan 9
 
5.4%
ocean 6
 
3.6%
hotel 6
 
3.6%
guest 5
 
3.0%
kim's 4
 
2.4%
cheonghaksodam 3
 
1.8%
happy 3
 
1.8%
suyeong 3
 
1.8%
Other values (53) 76
45.2%
2024-04-17T01:37:05.731554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
85
 
8.0%
e 83
 
7.9%
o 67
 
6.3%
a 52
 
4.9%
n 49
 
4.6%
u 45
 
4.3%
s 37
 
3.5%
H 36
 
3.4%
S 32
 
3.0%
E 30
 
2.8%
Other values (47) 540
51.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 544
51.5%
Uppercase Letter 291
27.6%
Other Letter 120
 
11.4%
Space Separator 85
 
8.0%
Dash Punctuation 7
 
0.7%
Other Punctuation 7
 
0.7%
Decimal Number 2
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 36
12.4%
S 32
 
11.0%
E 30
 
10.3%
O 22
 
7.6%
U 20
 
6.9%
B 17
 
5.8%
A 14
 
4.8%
Y 13
 
4.5%
P 13
 
4.5%
G 12
 
4.1%
Other values (14) 82
28.2%
Lowercase Letter
ValueCountFrequency (%)
e 83
15.3%
o 67
12.3%
a 52
9.6%
n 49
9.0%
u 45
 
8.3%
s 37
 
6.8%
t 27
 
5.0%
h 26
 
4.8%
m 23
 
4.2%
l 21
 
3.9%
Other values (12) 114
21.0%
Other Letter
ValueCountFrequency (%)
24
20.0%
24
20.0%
24
20.0%
24
20.0%
24
20.0%
Other Punctuation
ValueCountFrequency (%)
' 5
71.4%
& 1
 
14.3%
. 1
 
14.3%
Space Separator
ValueCountFrequency (%)
85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Decimal Number
ValueCountFrequency (%)
2 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 835
79.1%
Hangul 120
 
11.4%
Common 101
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 83
 
9.9%
o 67
 
8.0%
a 52
 
6.2%
n 49
 
5.9%
u 45
 
5.4%
s 37
 
4.4%
H 36
 
4.3%
S 32
 
3.8%
E 30
 
3.6%
t 27
 
3.2%
Other values (36) 377
45.1%
Common
ValueCountFrequency (%)
85
84.2%
- 7
 
6.9%
' 5
 
5.0%
2 2
 
2.0%
& 1
 
1.0%
. 1
 
1.0%
Hangul
ValueCountFrequency (%)
24
20.0%
24
20.0%
24
20.0%
24
20.0%
24
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 936
88.6%
Hangul 120
 
11.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
85
 
9.1%
e 83
 
8.9%
o 67
 
7.2%
a 52
 
5.6%
n 49
 
5.2%
u 45
 
4.8%
s 37
 
4.0%
H 36
 
3.8%
S 32
 
3.4%
E 30
 
3.2%
Other values (42) 420
44.9%
Hangul
ValueCountFrequency (%)
24
20.0%
24
20.0%
24
20.0%
24
20.0%
24
20.0%

engstntrnmaddr
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8381 
영문상호주소
 
24
Foreigner Tourism City home-stay Business
 
14
Guesthouse for Foreign Tourists
 
13
Guest House
 
4
Other values (15)
 
25

Length

Max length41
Median length4
Mean length4.1821298
Min length4

Unique

Unique9 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8381
99.1%
영문상호주소 24
 
0.3%
Foreigner Tourism City home-stay Business 14
 
0.2%
Guesthouse for Foreign Tourists 13
 
0.2%
Guest House 4
 
< 0.1%
Entertainment Business for foreigner only 3
 
< 0.1%
TOURIST ACCOMMODATION (hostel) 3
 
< 0.1%
TOURIST ACCOMMODATION 3
 
< 0.1%
Oversea Travel Business 3
 
< 0.1%
Entertainment Business for Foreigner only 2
 
< 0.1%
Other values (10) 11
 
0.1%

Length

2024-04-17T01:37:05.864697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8381
97.3%
영문상호주소 24
 
0.3%
business 22
 
0.3%
for 20
 
0.2%
foreigner 19
 
0.2%
foreign 19
 
0.2%
guesthouse 16
 
0.2%
tourists 16
 
0.2%
home-stay 15
 
0.2%
tourism 14
 
0.2%
Other values (18) 71
 
0.8%

yoksilcnt
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
0
5812 
<NA>
2441 
욕실수
 
20
15
 
16
12
 
14
Other values (28)
 
158

Length

Max length4
Median length1
Mean length1.8898475
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5812
68.7%
<NA> 2441
28.9%
욕실수 20
 
0.2%
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

2024-04-17T01:37:05.990156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 5812
68.7%
na 2441
28.9%
욕실수 20
 
0.2%
15 16
 
0.2%
12 14
 
0.2%
18 12
 
0.1%
10 12
 
0.1%
14 10
 
0.1%
9 10
 
0.1%
8 10
 
0.1%
Other values (23) 104
 
1.2%

sntuptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
여관업
5281 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
480
일반호텔
 
415
Other values (4)
620 

Length

Max length8
Median length3
Mean length3.6918804
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5281
62.4%
여인숙업 1076
 
12.7%
숙박업 기타 589
 
7.0%
숙박업(생활) 480
 
5.7%
일반호텔 415
 
4.9%
<NA> 322
 
3.8%
관광호텔 269
 
3.2%
위생업태명 20
 
0.2%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:37:06.103339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:06.224590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5281
58.4%
여인숙업 1076
 
11.9%
숙박업 589
 
6.5%
기타 589
 
6.5%
숙박업(생활 480
 
5.3%
일반호텔 415
 
4.6%
na 322
 
3.6%
관광호텔 269
 
3.0%
위생업태명 20
 
0.2%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
 
27

Length

Max length4
Median length4
Mean length3.9904267
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> 8434
99.7%
27
 
0.3%

Length

2024-04-17T01:37:06.346554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:06.444672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
27
 
0.3%

capt
Categorical

IMBALANCE 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8356 
10000000
 
18
자본금
 
15
100000000
 
12
200000000
 
5
Other values (33)
 
55

Length

Max length10
Median length4
Mean length4.0449119
Min length3

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> 8356
98.8%
10000000 18
 
0.2%
자본금 15
 
0.2%
100000000 12
 
0.1%
200000000 5
 
0.1%
20000000 5
 
0.1%
50000000 5
 
0.1%
300000000 4
 
< 0.1%
12000000 3
 
< 0.1%
12500000 3
 
< 0.1%
Other values (28) 35
 
0.4%

Length

2024-04-17T01:37:06.563714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8356
98.8%
10000000 18
 
0.2%
자본금 15
 
0.2%
100000000 12
 
0.1%
200000000 5
 
0.1%
20000000 5
 
0.1%
50000000 5
 
0.1%
300000000 4
 
< 0.1%
12000000 3
 
< 0.1%
12500000 3
 
< 0.1%
Other values (28) 35
 
0.4%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
제작취급품목내용
 
27

Length

Max length8
Median length4
Mean length4.0127644
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> 8434
99.7%
제작취급품목내용 27
 
0.3%

Length

2024-04-17T01:37:06.682584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:06.783946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
제작취급품목내용 27
 
0.3%

cndpermstymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8432 
조건부허가시작일자
 
27
20180202
 
2

Length

Max length9
Median length4
Mean length4.0169011
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> 8432
99.7%
조건부허가시작일자 27
 
0.3%
20180202 2
 
< 0.1%

Length

2024-04-17T01:37:06.880352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:06.973776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8432
99.7%
조건부허가시작일자 27
 
0.3%
20180202 2
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
조건부허가신고사유
 
27

Length

Max length9
Median length4
Mean length4.0159556
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> 8434
99.7%
조건부허가신고사유 27
 
0.3%

Length

2024-04-17T01:37:07.069782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:07.165400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
조건부허가신고사유 27
 
0.3%

cndpermendymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8432 
조건부허가종료일자
 
27
20190202
 
2

Length

Max length9
Median length4
Mean length4.0169011
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> 8432
99.7%
조건부허가종료일자 27
 
0.3%
20190202 2
 
< 0.1%

Length

2024-04-17T01:37:07.285582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:07.367434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8432
99.7%
조건부허가종료일자 27
 
0.3%
20190202 2
 
< 0.1%

chaircnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
5383 
0
3053 
좌석수
 
20
6
 
1
12
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length2.9134854
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5383
63.6%
0 3053
36.1%
좌석수 20
 
0.2%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-17T01:37:07.466891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:07.596675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5383
63.6%
0 3053
36.1%
좌석수 20
 
0.2%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

nearenvnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8344 
주택가주변
 
29
아파트지역
 
28
주변환경명
 
24
기타
 
21
Other values (3)
 
15

Length

Max length8
Median length4
Mean length4.0117007
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> 8344
98.6%
주택가주변 29
 
0.3%
아파트지역 28
 
0.3%
주변환경명 24
 
0.3%
기타 21
 
0.2%
학교정화(상대) 12
 
0.1%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-17T01:37:07.740962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:07.850046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8344
98.6%
주택가주변 29
 
0.3%
아파트지역 28
 
0.3%
주변환경명 24
 
0.3%
기타 21
 
0.2%
학교정화(상대 12
 
0.1%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대 1
 
< 0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8316 
2
 
31
4
 
17
3
 
13
지상층수
 
13
Other values (18)
 
71

Length

Max length4
Median length4
Mean length3.9573336
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> 8316
98.3%
2 31
 
0.4%
4 17
 
0.2%
3 13
 
0.2%
지상층수 13
 
0.2%
1 11
 
0.1%
5 8
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
19 6
 
0.1%
Other values (13) 32
 
0.4%

Length

2024-04-17T01:37:07.981830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8316
98.3%
2 31
 
0.4%
4 17
 
0.2%
3 13
 
0.2%
지상층수 13
 
0.2%
1 11
 
0.1%
5 8
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
19 6
 
0.1%
Other values (13) 32
 
0.4%

regnsenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8239 
일반주거지역
 
104
일반상업지역
 
35
주거지역
 
30
준주거지역
 
25
Other values (4)
 
28

Length

Max length6
Median length4
Mean length4.0385297
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> 8239
97.4%
일반주거지역 104
 
1.2%
일반상업지역 35
 
0.4%
주거지역 30
 
0.4%
준주거지역 25
 
0.3%
지역구분명 15
 
0.2%
상업지역 6
 
0.1%
자연녹지지역 4
 
< 0.1%
녹지지역 3
 
< 0.1%

Length

2024-04-17T01:37:08.092900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:08.196151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8239
97.4%
일반주거지역 104
 
1.2%
일반상업지역 35
 
0.4%
주거지역 30
 
0.4%
준주거지역 25
 
0.3%
지역구분명 15
 
0.2%
상업지역 6
 
0.1%
자연녹지지역 4
 
< 0.1%
녹지지역 3
 
< 0.1%

undernumlay
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8386 
1
 
26
2
 
20
지하층수
 
16
0
 
9
Other values (3)
 
4

Length

Max length4
Median length4
Mean length3.9790805
Min length1

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> 8386
99.1%
1 26
 
0.3%
2 20
 
0.2%
지하층수 16
 
0.2%
0 9
 
0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-17T01:37:08.322937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:08.423615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8386
99.1%
1 26
 
0.3%
2 20
 
0.2%
지하층수 16
 
0.2%
0 9
 
0.1%
3 2
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%

totnumlay
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8300 
2
 
36
4
 
19
3
 
17
1
 
16
Other values (20)
 
73

Length

Max length4
Median length4
Mean length3.9501241
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> 8300
98.1%
2 36
 
0.4%
4 19
 
0.2%
3 17
 
0.2%
1 16
 
0.2%
총층수 13
 
0.2%
5 11
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
11 6
 
0.1%
Other values (15) 29
 
0.3%

Length

2024-04-17T01:37:08.528440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8300
98.1%
2 36
 
0.4%
4 19
 
0.2%
3 17
 
0.2%
1 16
 
0.2%
총층수 13
 
0.2%
5 11
 
0.1%
6 7
 
0.1%
20 7
 
0.1%
11 6
 
0.1%
Other values (15) 29
 
0.3%

abedcnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
0
4922 
<NA>
3517 
침대수
 
20
41
 
2

Length

Max length4
Median length1
Mean length2.2519797
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4922
58.2%
<NA> 3517
41.6%
침대수 20
 
0.2%
41 2
 
< 0.1%

Length

2024-04-17T01:37:08.661287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:08.756381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4922
58.2%
na 3517
41.6%
침대수 20
 
0.2%
41 2
 
< 0.1%

hanshilcnt
Categorical

Distinct48
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
0
3705 
<NA>
1463 
2
 
326
10
 
310
3
 
268
Other values (43)
2389 

Length

Max length4
Median length1
Mean length1.6739156
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3705
43.8%
<NA> 1463
 
17.3%
2 326
 
3.9%
10 310
 
3.7%
3 268
 
3.2%
1 262
 
3.1%
8 226
 
2.7%
4 202
 
2.4%
6 200
 
2.4%
9 197
 
2.3%
Other values (38) 1302
 
15.4%

Length

2024-04-17T01:37:08.853752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3705
43.8%
na 1463
 
17.3%
2 326
 
3.9%
10 310
 
3.7%
3 268
 
3.2%
1 262
 
3.1%
8 226
 
2.7%
4 202
 
2.4%
6 200
 
2.4%
9 197
 
2.3%
Other values (38) 1302
 
15.4%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
0
4930 
<NA>
3511 
회수건조수
 
20

Length

Max length5
Median length1
Mean length2.2543435
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4930
58.3%
<NA> 3511
41.5%
회수건조수 20
 
0.2%

Length

2024-04-17T01:37:08.966258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:09.057386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4930
58.3%
na 3511
41.5%
회수건조수 20
 
0.2%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
<NA>
8434 
회의실별동시수용인원
 
27

Length

Max length10
Median length4
Mean length4.0191467
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> 8434
99.7%
회의실별동시수용인원 27
 
0.3%

Length

2024-04-17T01:37:09.172782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:09.289608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8434
99.7%
회의실별동시수용인원 27
 
0.3%

last_load_dttm
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.2 KiB
2021-03-01 05:09:04
5214 
2021-03-01 05:09:03
3241 
<NA>
 
6

Length

Max length19
Median length19
Mean length18.989363
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-03-01 05:09:03
2nd row2021-03-01 05:09:03
3rd row2021-03-01 05:09:03
4th row2021-03-01 05:09:03
5th row2021-03-01 05:09:03

Common Values

ValueCountFrequency (%)
2021-03-01 05:09:04 5214
61.6%
2021-03-01 05:09:03 3241
38.3%
<NA> 6
 
0.1%

Length

2024-04-17T01:37:09.415089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:09.515473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-03-01 8455
50.0%
05:09:04 5214
30.8%
05:09:03 3241
 
19.2%
na 6
 
< 0.1%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
0232500003250000-201-2017-0000203_11_03_PI2018-08-31 23:59:59.0<NA>(주)아이에이치엠 호텔포레 프리미어 남포지점600045부산광역시 중구 남포동5가 8-1번지48953부산광역시 중구 구덕로 54-1 (남포동5가)20170213<NA><NA><NA><NA>01영업385079.145433179894.98255720171123163559일반호텔051-123-1234<NA>임대<NA>162<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>14040<NA><NA><NA>0<NA><NA><NA>1070<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:03
1332500003250000-201-2014-0000103_11_03_PI2018-08-31 23:59:59.0<NA>호텔아벤트리부산600051부산광역시 중구 창선동1가 12-1번지48947부산광역시 중구 광복로39번길 6 (창선동1가)20140318<NA><NA><NA><NA>01영업385065.851535180046.79139420180727133623일반호텔051-123-1234<NA>자가<NA>84<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>8060<NA><NA><NA>0<NA><NA><NA>81<NA><NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:03
2432500003250000-214-2017-0000303_11_03_PI2018-08-31 23:59:59.0<NA>케이 칠구(K79)600092부산광역시 중구 대청동2가 23-3번지48948부산광역시 중구 광복로49번길 38 (대청동2가)20170731<NA><NA><NA><NA>01영업385140.157403180362.44609920180814140805숙박업(생활)051-123-1234<NA><NA><NA>51<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>3010<NA><NA><NA>0<NA><NA><NA>160<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:03
3532500003250000-201-1971-0011603_11_03_PI2018-08-31 23:59:59.0<NA>영하장600806부산광역시 중구 부평동2가 24-3번지48977부산광역시 중구 중구로23번길 34 (부평동2가)1971080720140310<NA><NA><NA>02폐업384736.73365180083.04251420121015144713여관업051-123-1234<NA>임대<NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>7<NA><NA><NA><NA>여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3<NA><NA>2021-03-01 05:09:03
4632500003250000-201-2012-0000503_11_03_PI2018-08-31 23:59:59.0<NA>누리게스트하우스 더셀프600012부산광역시 중구 중앙동2가 52-2번지48956부산광역시 중구 중앙대로49번길 13 (중앙동2가)2012112720121231<NA><NA><NA>02폐업385546.889042180289.00649820121127133856숙박업 기타051-123-1234<NA>임대<NA>50<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>2<NA>2<NA><NA><NA><NA>0<NA><NA><NA>5<NA><NA><NA>0숙박업 기타<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:03
5732500003250000-201-1988-0006903_11_03_PI2018-08-31 23:59:59.0<NA>야(Ya)600083부산광역시 중구 보수동3가 5-21번지48947부산광역시 중구 보수대로106번길 5 (보수동3가)1988012620171120<NA><NA><NA>02폐업384329.080801180631.27368220171120143429여관업051-123-1234<NA>임대<NA>00<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>10<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>020<NA>2021-03-01 05:09:03
6832500003250000-201-1970-0011603_11_03_PI2018-08-31 23:59:59.0<NA>세피아600071부산광역시 중구 부평동1가 41-7번지 ,848980부산광역시 중구 광복로12번길 7-5 (부평동1가, 41-7,8)19700828<NA><NA><NA><NA>01영업384788.862125179954.32496120180727110634여관업051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>16<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>020<NA>2021-03-01 05:09:03
7932500003250000-201-2007-0000203_11_03_PI2018-08-31 23:59:59.0<NA>식스나인모텔600046부산광역시 중구 남포동6가 29번지 (8~11층)48982부산광역시 중구 자갈치로 21 (남포동6가)20070712<NA><NA><NA><NA>01영업384804.909084179701.53297720180502092950여관업051-123-1234<NA>자가<NA>101<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>11080<NA><NA><NA>0<NA><NA><NA>25<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:03
81032500003250000-201-1971-0011703_11_03_PI2018-08-31 23:59:59.0<NA>동산장모텔600033부산광역시 중구 광복동3가 5-20번지48949부산광역시 중구 광복로67번길 30-22 (광복동3가)19710315<NA><NA><NA><NA>01영업385245.417649180087.31460420180727170224여관업051-123-1234<NA><NA><NA>30<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>4<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>080<NA>2021-03-01 05:09:03
91132500003250000-201-1972-0000303_11_03_PI2018-08-31 23:59:59.0<NA>주식회사 경원건설 호텔노아600045부산광역시 중구 남포동5가 81-1번지48983부산광역시 중구 자갈치로47번길 3-1 (남포동5가)19721010<NA><NA><NA><NA>01영업385043.08817179794.6106720171220145009관광호텔051-123-1234<NA>자가<NA>91<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9010<NA><NA><NA>0<NA><NA><NA>51<NA><NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>2021-03-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
84511275532500003250000-201-2020-0000603_11_03_PI2020-12-25 00:23:06.0숙박업라운지26호텔600045부산광역시 중구 남포동5가 86-2 LOUNGE 26 호텔48983부산광역시 중구 자갈치로47번길 5-13, LOUNGE 26 호텔 (남포동5가)20201223<NA><NA><NA><NA>영업/정상영업384924.795038687179469.84667520201223105033일반호텔051 245 5145<NA><NA><NA>81<NA><NA><NA><NA>0<NA><NA>Y<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA>81<NA><NA><NA>0<NA><NA><NA>260<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:04
84521280033800003380000-214-2021-0000103_11_03_PI2021-01-08 00:23:04.0숙박업주식회사 그랜드 테라스613805부산광역시 수영구 광안동 201-1 광안 지웰에스테이트 더 테라스48303부산광역시 수영구 광남로94번길 16, 광안 지웰에스테이트 더 테라스 303호외50호 (광안동)20210106<NA><NA><NA><NA>영업/정상영업392691.625721388185474.22691320210106162012숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA>510<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:04
84531283932500003250000-214-2021-0000103_11_03_PI2021-01-16 00:23:15.0숙박업수민600102부산광역시 중구 대창동2가 30-748924부산광역시 중구 동광길 178 (대창동2가)20210114<NA><NA><NA><NA>영업/정상영업385652.758867696180919.59314220210114114132숙박업(생활)<NA><NA><NA><NA>60<NA><NA><NA><NA>0<NA><NA>Y<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>6<NA>1<NA><NA><NA><NA>0<NA><NA><NA>180<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:04
84541289433300003330000-214-2021-0000103_11_03_PI2021-01-24 00:23:04.0숙박업에이치 스테이 호텔612821부산광역시 해운대구 우동 539-10 해운대 라뮤에뜨48094부산광역시 해운대구 해운대로 620, 해운대 라뮤에뜨 (우동)20210122<NA><NA><NA><NA>영업/정상영업396596.443478014186999.88452720210122133657숙박업(생활)051 7602100<NA><NA><NA>420<NA><NA><NA><NA>2<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>39<NA>7<NA><NA><NA><NA>0<NA><NA><NA>301<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:04
84551290433300003330000-214-2021-0000103_11_03_PI2021-01-24 00:23:04.0숙박업에이치 스테이 호텔612821부산광역시 해운대구 우동 539-10 해운대 라뮤에뜨48094부산광역시 해운대구 해운대로 620, 해운대 라뮤에뜨 (우동)20210122<NA><NA><NA><NA>영업/정상영업396596.443478014186999.88452720210122133657숙박업(생활)051 7602100<NA><NA><NA>420<NA><NA><NA><NA>2<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>39<NA>7<NA><NA><NA><NA>0<NA><NA><NA>301<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:04
8456129553390000CDFI226003202100000103_11_01_PU2021-02-18 02:40:00.0관광숙박업ND1226 HOTEL<NA>부산광역시 사상구 괘법동 517-146960부산광역시 사상구 낙동대로 1226 (괘법동)20210205<NA><NA><NA><NA>영업/정상영업중380057.991425369187370.83623620210216161824<NA><NA>32<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><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 05:09:04
8457129583390000CDFI226003202100000103_11_01_PU2021-02-18 02:40:00.0관광숙박업ND1226 HOTEL<NA>부산광역시 사상구 괘법동 517-146960부산광역시 사상구 낙동대로 1226 (괘법동)20210205<NA><NA><NA><NA>영업/정상영업중380057.991425369187370.83623620210216161824<NA><NA>32<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><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 05:09:04
8458129623380000CDFI226003202100000103_11_01_PI2021-02-10 00:23:02.0관광숙박업광안273<NA>부산광역시 수영구 민락동 176-1448286부산광역시 수영구 광안해변로 273, 2~4층 (민락동)20210208<NA><NA><NA><NA>영업/정상영업중393429.955148773186148.12377420210208173959<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>관광숙박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>311310.57<NA><NA><NA><NA><NA><NA><NA><NA>10000000<NA><NA><NA><NA><NA><NA><NA><NA><NA>4<NA><NA><NA><NA>2021-03-01 05:09:04
84591299833800003380000-214-2021-0000303_11_03_PI2021-02-19 00:23:01.0숙박업주식회사이너플랜613805부산광역시 수영구 광안동 202-1848303부산광역시 수영구 남천바다로33번길 35, 401~405,501~505,601~605,701~705,801~805호 4~8층 (광안동)20210217폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업392654.443900347185470.14027720210217121659숙박업(생활)070 46552587객실수건물소유구분명건물용도명00건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자0놀이기구수내역놀이시설수N무대면적문화사업자구분명문화체육업종명N보험기관명보험시작일자보험종료일자부대시설내역8040선박제원선박척수선박총톤수0시설규모시설면적250영문상호명영문상호주소0숙박업(생활)자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주변환경명지상층수지역구분명지하층수총층수000회의실별동시수용인원2021-03-01 05:09:04
8460130233330000CDFI226221201500002403_11_04_PI2021-02-25 00:23:01.0외국인관광도시민박업마망하우스<NA>부산광역시 해운대구 우동<NA>부산광역시 해운대구 해운대로 428, 119동 4층 403호 (우동, 동부올림픽타운)20151007<NA><NA><NA><NA>영업/정상영업중395088.21080900000187543.08045620210223162649<NA><NA><NA><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><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>10000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 05:09:04

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrdcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
263330000CDFI226003201800000503_11_01_PU2019-04-14 02:40:00.0관광숙박업일로이리조트<NA>부산광역시 해운대구 송정동 809번지48073부산광역시 해운대구 송정구덕포길 130 (송정동)<NA><NA><NA><NA>영업/정상영업중187863.01536620190412092534<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>관광숙박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>599598.73<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4주거지역<NA>4<NA><NA><NA><NA>2021-03-01 05:09:046
23250000CDFI226221201900000103_11_04_PU2020-11-03 02:40:00.0외국인관광도시민박업보수동방공호<NA>부산광역시 중구 보수동1가 116-15648967부산광역시 중구 책방골목길 13-11 (보수동1가)<NA><NA><NA><NA>영업/정상영업중180168.55870820201031173213<NA><NA>6<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>168167.82<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>일반상업지역<NA>3<NA><NA><NA><NA>2021-03-01 05:09:043
33250000CDFI226221201900000203_11_04_PU2020-11-03 02:40:00.0외국인관광도시민박업제이온게스트하우스<NA>부산광역시 중구 부평동2가 21-848977부산광역시 중구 중구로29번길 38, 4층 (부평동2가)<NA><NA><NA><NA>영업/정상영업중179818.66105720201031173301<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3838.18<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-03-01 05:09:043
732700003270000-201-2019-0000303_11_03_PI2019-06-23 02:21:37.0숙박업대구여관601829부산광역시 동구 초량동 388-2번지 지하1층, 지상1~3층, 4층 일부48815부산광역시 동구 중앙대로221번길 14-5 (초량동)<NA><NA><NA><NA>영업/정상영업181704.05848320190621114502여관업051-123-1234<NA>자가<NA>41<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4111<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>060<NA>2021-03-01 05:09:043
832700003270000-201-2019-0000503_11_03_PU2020-10-29 02:40:00.0숙박업단테하우스B601829부산광역시 동구 초량동 39948816부산광역시 동구 초량로13번길 58 (초량동)<NA><NA><NA><NA>영업/정상영업181627.55533520201027175551여관업<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4010<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:043
103280000CDFI226221202000000103_11_04_PU2020-03-21 02:40:00.0외국인관광도시민박업오션하우스<NA>부산광역시 영도구 동삼동 1124번지 함지그린아파트49119부산광역시 영도구 함지로 8, 106동 1904호 (동삼동, 함지그린아파트)<NA><NA><NA><NA>영업/정상영업중176595.03493520200319142335<NA>051-123-12342<NA>아파트<NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>외국인관광 도시민박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4645.5<NA><NA><NA>ocean houseGuesthouse for Foreign Tourists<NA><NA><NA>10000000<NA><NA><NA><NA><NA>아파트지역20일반주거지역220<NA><NA><NA><NA>2021-03-01 05:09:043
113280000CDFI226221202000000203_11_04_PU2020-03-25 02:40:00.0외국인관광도시민박업에메랄드 오션뷰<NA>부산광역시 영도구 동삼동 1124번지 함지그린아파트49119부산광역시 영도구 함지로 8, 106동 1902호 (동삼동, 함지그린아파트)<NA><NA><NA><NA>영업/정상영업중176595.03493520200323102518<NA>051-123-12341<NA>아파트<NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>외국인관광 도시민박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4645.5<NA><NA><NA>Emerald ocean viewGuesthouse for Foreign Tourists<NA><NA><NA><NA><NA><NA><NA><NA><NA>아파트지역20주거지역220<NA><NA><NA><NA>2021-03-01 05:09:043
123280000CDFI226221202000000303_11_04_PU2020-06-07 02:40:00.0외국인관광도시민박업청학소담<NA>부산광역시 영도구 청학동 398-20번지49031부산광역시 영도구 청학서로16번길 43-14 (청학동)<NA><NA><NA><NA>영업/정상영업중179086.90220320200605103404<NA>051-123-12341<NA>단독주택<NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>외국인관광 도시민박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>8080.1<NA><NA><NA>CheonghakSodamGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA><NA>주택가주변<NA>일반주거지역<NA>1<NA><NA><NA><NA>2021-03-01 05:09:043
1632900003290000-201-2019-0000203_11_03_PU2020-12-15 02:40:00.0숙박업엑스모텔614846부산광역시 부산진구 부전동 226-547296부산광역시 부산진구 신천대로50번길 34, 6층~9층 (부전동)<NA><NA><NA><NA>영업/정상영업185627.12814620201212162712일반호텔051 803 6996<NA><NA><NA>102<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9060<NA><NA><NA>0<NA><NA><NA>290<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:043
1732900003290000-201-2020-0000103_11_03_PU2020-12-15 02:40:00.0숙박업지지배614849부산광역시 부산진구 부전동 417-2547258부산광역시 부산진구 부전로 99-1, 3층 (부전동)<NA><NA><NA><NA>영업/정상영업186361.92755720201212135845여관업051 806 7779<NA>자가<NA>41<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA>3<NA><NA><NA><NA>0<NA><NA><NA>60<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-03-01 05:09:043