Overview

Dataset statistics

Number of variables81
Number of observations8580
Missing cells33864
Missing cells (%)4.9%
Duplicate rows357
Duplicate rows (%)4.2%
Total size in memory5.3 MiB
Average record size in memory650.0 B

Variable types

Unsupported4
Numeric2
Text12
Categorical62
DateTime1

Alerts

Dataset has 357 (4.2%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (89.1%)Imbalance
updategbn is highly imbalanced (54.3%)Imbalance
opnsvcnm is highly imbalanced (69.9%)Imbalance
clgstdt is highly imbalanced (95.3%)Imbalance
clgenddt is highly imbalanced (95.3%)Imbalance
ropnymd is highly imbalanced (85.2%)Imbalance
dtlstatenm is highly imbalanced (53.6%)Imbalance
stroomcnt is highly imbalanced (92.6%)Imbalance
bdngsrvnm is highly imbalanced (90.4%)Imbalance
bdngunderflrcnt is highly imbalanced (54.6%)Imbalance
cnstyarea is highly imbalanced (94.4%)Imbalance
svnsr is highly imbalanced (85.2%)Imbalance
plninsurstdt is highly imbalanced (85.2%)Imbalance
plninsurenddt is highly imbalanced (85.2%)Imbalance
maneipcnt is highly imbalanced (81.2%)Imbalance
playutscntdtl is highly imbalanced (85.2%)Imbalance
playfacilcnt is highly imbalanced (62.9%)Imbalance
multusnupsoyn is highly imbalanced (90.9%)Imbalance
stagear is highly imbalanced (86.0%)Imbalance
culwrkrsenm is highly imbalanced (85.2%)Imbalance
culphyedcobnm is highly imbalanced (85.8%)Imbalance
geicpfacilen is highly imbalanced (85.2%)Imbalance
balhansilyn is highly imbalanced (90.2%)Imbalance
bcfacilen is highly imbalanced (85.2%)Imbalance
insurorgnm is highly imbalanced (95.9%)Imbalance
insurstdt is highly imbalanced (85.2%)Imbalance
insurenddt is highly imbalanced (85.2%)Imbalance
afc is highly imbalanced (85.2%)Imbalance
useunderendflr is highly imbalanced (61.8%)Imbalance
useunderstflr is highly imbalanced (62.5%)Imbalance
shpinfo is highly imbalanced (85.2%)Imbalance
shpcnt is highly imbalanced (86.0%)Imbalance
shptottons is highly imbalanced (86.0%)Imbalance
infoben is highly imbalanced (85.2%)Imbalance
wmeipcnt is highly imbalanced (79.8%)Imbalance
engstntrnmaddr is highly imbalanced (94.7%)Imbalance
yoksilcnt is highly imbalanced (76.9%)Imbalance
dispenen is highly imbalanced (85.2%)Imbalance
capt is highly imbalanced (93.7%)Imbalance
mnfactreartclcn is highly imbalanced (85.2%)Imbalance
cndpermstymd is highly imbalanced (85.2%)Imbalance
cndpermntwhy is highly imbalanced (85.2%)Imbalance
cndpermendymd is highly imbalanced (85.2%)Imbalance
chaircnt is highly imbalanced (65.4%)Imbalance
nearenvnm is highly imbalanced (91.2%)Imbalance
jisgnumlay is highly imbalanced (92.0%)Imbalance
regnsenm is highly imbalanced (88.9%)Imbalance
undernumlay is highly imbalanced (91.6%)Imbalance
totnumlay is highly imbalanced (91.7%)Imbalance
meetsamtimesygstf is highly imbalanced (86.0%)Imbalance
sitepostno has 314 (3.7%) missing valuesMissing
rdnwhladdr has 2551 (29.7%) missing valuesMissing
dcbymd has 4415 (51.5%) missing valuesMissing
x has 386 (4.5%) missing valuesMissing
y has 389 (4.5%) missing valuesMissing
sitetel has 250 (2.9%) missing valuesMissing
facilscp has 8120 (94.6%) missing valuesMissing
facilar has 8120 (94.6%) missing valuesMissing
yangsilcnt has 921 (10.7%) missing valuesMissing
engstntrnmnm has 8341 (97.2%) 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
y is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 16:31:36.223679
Analysis finished2024-04-16 16:31:38.323734
Duration2.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size67.2 KiB

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3319031.1
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.5 KiB
2024-04-17T01:31:38.370197image/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 deviation42894.961
Coefficient of variation (CV)0.012923941
Kurtosis-0.97834041
Mean3319031.1
Median Absolute Deviation (MAD)30000
Skewness0.26131165
Sum2.846733 × 1010
Variance1.8399777 × 109
MonotonicityNot monotonic
2024-04-17T01:31:38.471003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1177
13.7%
3290000 1060
12.4%
3300000 893
10.4%
3390000 689
 
8.0%
3270000 655
 
7.6%
3320000 578
 
6.7%
3380000 512
 
6.0%
3250000 485
 
5.7%
3260000 407
 
4.7%
3370000 384
 
4.5%
Other values (6) 1737
20.2%
ValueCountFrequency (%)
3250000 485
5.7%
3260000 407
 
4.7%
3270000 655
7.6%
3280000 381
 
4.4%
3290000 1060
12.4%
3300000 893
10.4%
3310000 285
 
3.3%
3320000 578
6.7%
3330000 1177
13.7%
3340000 363
 
4.2%
ValueCountFrequency (%)
3400000 215
 
2.5%
3390000 689
8.0%
3380000 512
6.0%
3370000 384
 
4.5%
3360000 139
 
1.6%
3350000 354
 
4.1%
3340000 363
 
4.2%
3330000 1177
13.7%
3320000 578
6.7%
3310000 285
 
3.3%

mgtno
Text

Distinct4269
Distinct (%)49.8%
Missing3
Missing (%)< 0.1%
Memory size67.2 KiB
2024-04-17T01:31:38.662826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.906028
Min length20

Characters and Unicode

Total characters187888
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

Unique176 ?
Unique (%)2.1%

Sample

1st row3250000-201-2017-00002
2nd row3250000-201-2014-00001
3rd row3250000-214-2017-00003
4th row3250000-201-1971-00116
5th row3250000-201-2012-00005
ValueCountFrequency (%)
cdfi2262212019000001 15
 
0.2%
cdfi2262212018000001 12
 
0.1%
cdfi2262212015000001 12
 
0.1%
cdfi2262212017000001 11
 
0.1%
cdfi2260032021000001 11
 
0.1%
cdfi2262212015000002 11
 
0.1%
cdfi2262212016000001 11
 
0.1%
cdfi2262212020000001 10
 
0.1%
cdfi2262212016000002 10
 
0.1%
cdfi2262212014000001 9
 
0.1%
Other values (4259) 8465
98.7%
2024-04-17T01:31:38.966392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72343
38.5%
- 24522
 
13.1%
2 20322
 
10.8%
1 20262
 
10.8%
3 18328
 
9.8%
9 10164
 
5.4%
8 4990
 
2.7%
7 4877
 
2.6%
6 3759
 
2.0%
4 3651
 
1.9%
Other values (5) 4670
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 161754
86.1%
Dash Punctuation 24522
 
13.1%
Uppercase Letter 1612
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72343
44.7%
2 20322
 
12.6%
1 20262
 
12.5%
3 18328
 
11.3%
9 10164
 
6.3%
8 4990
 
3.1%
7 4877
 
3.0%
6 3759
 
2.3%
4 3651
 
2.3%
5 3058
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 403
25.0%
D 403
25.0%
F 403
25.0%
I 403
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 24522
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 186276
99.1%
Latin 1612
 
0.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72343
38.8%
- 24522
 
13.2%
2 20322
 
10.9%
1 20262
 
10.9%
3 18328
 
9.8%
9 10164
 
5.5%
8 4990
 
2.7%
7 4877
 
2.6%
6 3759
 
2.0%
4 3651
 
2.0%
Latin
ValueCountFrequency (%)
C 403
25.0%
D 403
25.0%
F 403
25.0%
I 403
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 187888
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72343
38.5%
- 24522
 
13.1%
2 20322
 
10.8%
1 20262
 
10.8%
3 18328
 
9.8%
9 10164
 
5.4%
8 4990
 
2.7%
7 4877
 
2.6%
6 3759
 
2.0%
4 3651
 
1.9%
Other values (5) 4670
 
2.5%

opnsvcid
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
03_11_03_P
8174 
03_11_04_P
 
293
03_11_01_P
 
94
03_11_05_P
 
9
03_11_02_P
 
3
Other values (3)
 
7

Length

Max length10
Median length10
Mean length9.9979021
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 8174
95.3%
03_11_04_P 293
 
3.4%
03_11_01_P 94
 
1.1%
03_11_05_P 9
 
0.1%
03_11_02_P 3
 
< 0.1%
03_11_06_P 3
 
< 0.1%
<NA> 3
 
< 0.1%
03_11_07_P 1
 
< 0.1%

Length

2024-04-17T01:31:39.278840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:39.380291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 8174
95.3%
03_11_04_p 293
 
3.4%
03_11_01_p 94
 
1.1%
03_11_05_p 9
 
0.1%
03_11_02_p 3
 
< 0.1%
03_11_06_p 3
 
< 0.1%
na 3
 
< 0.1%
03_11_07_p 1
 
< 0.1%

updategbn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
I
6872 
U
1705 
180000000
 
3

Length

Max length9
Median length1
Mean length1.0027972
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6872
80.1%
U 1705
 
19.9%
180000000 3
 
< 0.1%

Length

2024-04-17T01:31:39.518528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:39.624285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6872
80.1%
u 1705
 
19.9%
180000000 3
 
< 0.1%
Distinct376
Distinct (%)4.4%
Missing3
Missing (%)< 0.1%
Memory size67.2 KiB
Minimum2018-08-31 23:59:59
Maximum2022-02-28 02:40:00
2024-04-17T01:31:39.721727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:31:39.863075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
6760 
숙박업
1570 
외국인관광도시민박업
 
149
관광숙박업
 
94
한옥체험업
 
3
Other values (3)
 
4

Length

Max length10
Median length4
Mean length3.9335664
Min length3

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> 6760
78.8%
숙박업 1570
 
18.3%
외국인관광도시민박업 149
 
1.7%
관광숙박업 94
 
1.1%
한옥체험업 3
 
< 0.1%
자동차야영장업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

Length

2024-04-17T01:31:39.971676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:40.072459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6760
78.8%
숙박업 1570
 
18.3%
외국인관광도시민박업 149
 
1.7%
관광숙박업 94
 
1.1%
한옥체험업 3
 
< 0.1%
자동차야영장업 2
 
< 0.1%
일반야영장업 1
 
< 0.1%
관광펜션업 1
 
< 0.1%

bplcnm
Text

Distinct3466
Distinct (%)40.4%
Missing3
Missing (%)< 0.1%
Memory size67.2 KiB
2024-04-17T01:31:40.309694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length5.2308499
Min length1

Characters and Unicode

Total characters44865
Distinct characters652
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique348 ?
Unique (%)4.1%

Sample

1st row(주)아이에이치엠 호텔포레 프리미어 남포지점
2nd row호텔아벤트리부산
3rd row케이 칠구(K79)
4th row영하장
5th row누리게스트하우스 더셀프
ValueCountFrequency (%)
호텔 257
 
2.5%
모텔 182
 
1.8%
게스트하우스 120
 
1.2%
여관 82
 
0.8%
hotel 71
 
0.7%
부산 51
 
0.5%
house 48
 
0.5%
해운대 41
 
0.4%
여인숙 36
 
0.3%
35
 
0.3%
Other values (3579) 9381
91.0%
2024-04-17T01:31:40.704041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2952
 
6.6%
2019
 
4.5%
1789
 
4.0%
1744
 
3.9%
1719
 
3.8%
1532
 
3.4%
1436
 
3.2%
1273
 
2.8%
770
 
1.7%
770
 
1.7%
Other values (642) 28861
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37511
83.6%
Uppercase Letter 2544
 
5.7%
Space Separator 1744
 
3.9%
Lowercase Letter 1288
 
2.9%
Open Punctuation 551
 
1.2%
Close Punctuation 551
 
1.2%
Decimal Number 520
 
1.2%
Other Punctuation 104
 
0.2%
Dash Punctuation 29
 
0.1%
Letter Number 11
 
< 0.1%
Other values (4) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2952
 
7.9%
2019
 
5.4%
1789
 
4.8%
1719
 
4.6%
1532
 
4.1%
1436
 
3.8%
1273
 
3.4%
770
 
2.1%
770
 
2.1%
622
 
1.7%
Other values (562) 22629
60.3%
Uppercase Letter
ValueCountFrequency (%)
E 263
 
10.3%
O 251
 
9.9%
H 232
 
9.1%
T 207
 
8.1%
S 167
 
6.6%
A 155
 
6.1%
L 152
 
6.0%
N 129
 
5.1%
B 109
 
4.3%
U 99
 
3.9%
Other values (16) 780
30.7%
Lowercase Letter
ValueCountFrequency (%)
e 204
15.8%
o 144
11.2%
a 112
8.7%
s 111
8.6%
n 99
 
7.7%
u 95
 
7.4%
t 91
 
7.1%
h 59
 
4.6%
i 58
 
4.5%
l 58
 
4.5%
Other values (16) 257
20.0%
Decimal Number
ValueCountFrequency (%)
2 134
25.8%
1 71
13.7%
7 60
11.5%
5 60
11.5%
9 55
10.6%
0 42
 
8.1%
6 33
 
6.3%
3 28
 
5.4%
4 27
 
5.2%
8 10
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 57
54.8%
& 27
26.0%
' 9
 
8.7%
, 6
 
5.8%
; 2
 
1.9%
2
 
1.9%
: 1
 
1.0%
Letter Number
ValueCountFrequency (%)
7
63.6%
4
36.4%
Math Symbol
ValueCountFrequency (%)
2
50.0%
+ 2
50.0%
Space Separator
ValueCountFrequency (%)
1744
100.0%
Open Punctuation
ValueCountFrequency (%)
( 551
100.0%
Close Punctuation
ValueCountFrequency (%)
) 551
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Other Symbol
ValueCountFrequency (%)
6
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37509
83.6%
Latin 3843
 
8.6%
Common 3505
 
7.8%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2952
 
7.9%
2019
 
5.4%
1789
 
4.8%
1719
 
4.6%
1532
 
4.1%
1436
 
3.8%
1273
 
3.4%
770
 
2.1%
770
 
2.1%
622
 
1.7%
Other values (558) 22627
60.3%
Latin
ValueCountFrequency (%)
E 263
 
6.8%
O 251
 
6.5%
H 232
 
6.0%
T 207
 
5.4%
e 204
 
5.3%
S 167
 
4.3%
A 155
 
4.0%
L 152
 
4.0%
o 144
 
3.7%
N 129
 
3.4%
Other values (44) 1939
50.5%
Common
ValueCountFrequency (%)
1744
49.8%
( 551
 
15.7%
) 551
 
15.7%
2 134
 
3.8%
1 71
 
2.0%
7 60
 
1.7%
5 60
 
1.7%
. 57
 
1.6%
9 55
 
1.6%
0 42
 
1.2%
Other values (15) 180
 
5.1%
Han
ValueCountFrequency (%)
3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37503
83.6%
ASCII 7332
 
16.3%
Number Forms 11
 
< 0.1%
None 10
 
< 0.1%
CJK 8
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2952
 
7.9%
2019
 
5.4%
1789
 
4.8%
1719
 
4.6%
1532
 
4.1%
1436
 
3.8%
1273
 
3.4%
770
 
2.1%
770
 
2.1%
622
 
1.7%
Other values (557) 22621
60.3%
ASCII
ValueCountFrequency (%)
1744
23.8%
( 551
 
7.5%
) 551
 
7.5%
E 263
 
3.6%
O 251
 
3.4%
H 232
 
3.2%
T 207
 
2.8%
e 204
 
2.8%
S 167
 
2.3%
A 155
 
2.1%
Other values (64) 3007
41.0%
Number Forms
ValueCountFrequency (%)
7
63.6%
4
36.4%
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 

Distinct494
Distinct (%)6.0%
Missing314
Missing (%)3.7%
Memory size67.2 KiB
2024-04-17T01:31:40.997491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters49596
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.3%

Sample

1st row600045
2nd row600051
3rd row600092
4th row600806
5th row600012
ValueCountFrequency (%)
612821 318
 
3.8%
616801 254
 
3.1%
612040 219
 
2.6%
612847 186
 
2.3%
607833 175
 
2.1%
601829 145
 
1.8%
617807 136
 
1.6%
613828 131
 
1.6%
607831 126
 
1.5%
607842 114
 
1.4%
Other values (484) 6462
78.2%
2024-04-17T01:31:41.391283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 9884
19.9%
1 8093
16.3%
0 8038
16.2%
8 7952
16.0%
2 4329
8.7%
4 3463
 
7.0%
7 2603
 
5.2%
3 2463
 
5.0%
9 1413
 
2.8%
5 962
 
1.9%
Other values (5) 396
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49200
99.2%
Other Letter 396
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 9884
20.1%
1 8093
16.4%
0 8038
16.3%
8 7952
16.2%
2 4329
8.8%
4 3463
 
7.0%
7 2603
 
5.3%
3 2463
 
5.0%
9 1413
 
2.9%
5 962
 
2.0%
Other Letter
ValueCountFrequency (%)
132
33.3%
66
16.7%
66
16.7%
66
16.7%
66
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 49200
99.2%
Hangul 396
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
6 9884
20.1%
1 8093
16.4%
0 8038
16.3%
8 7952
16.2%
2 4329
8.8%
4 3463
 
7.0%
7 2603
 
5.3%
3 2463
 
5.0%
9 1413
 
2.9%
5 962
 
2.0%
Hangul
ValueCountFrequency (%)
132
33.3%
66
16.7%
66
16.7%
66
16.7%
66
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49200
99.2%
Hangul 396
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 9884
20.1%
1 8093
16.4%
0 8038
16.3%
8 7952
16.2%
2 4329
8.8%
4 3463
 
7.0%
7 2603
 
5.3%
3 2463
 
5.0%
9 1413
 
2.9%
5 962
 
2.0%
Hangul
ValueCountFrequency (%)
132
33.3%
66
16.7%
66
16.7%
66
16.7%
66
16.7%
Distinct4156
Distinct (%)48.5%
Missing5
Missing (%)0.1%
Memory size67.2 KiB
2024-04-17T01:31:41.692083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length43
Mean length23.295394
Min length13

Characters and Unicode

Total characters199758
Distinct characters309
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique281 ?
Unique (%)3.3%

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 8575
23.5%
해운대구 1177
 
3.2%
부산진구 1060
 
2.9%
동래구 893
 
2.4%
t통b반 868
 
2.4%
사상구 689
 
1.9%
동구 655
 
1.8%
온천동 644
 
1.8%
북구 582
 
1.6%
수영구 512
 
1.4%
Other values (4409) 20855
57.1%
2024-04-17T01:31:42.144129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36415
18.2%
10399
 
5.2%
10142
 
5.1%
10053
 
5.0%
8956
 
4.5%
8816
 
4.4%
1 8674
 
4.3%
8601
 
4.3%
8581
 
4.3%
- 7944
 
4.0%
Other values (299) 81177
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 112976
56.6%
Decimal Number 40087
 
20.1%
Space Separator 36415
 
18.2%
Dash Punctuation 7944
 
4.0%
Uppercase Letter 1780
 
0.9%
Other Punctuation 192
 
0.1%
Close Punctuation 124
 
0.1%
Open Punctuation 124
 
0.1%
Math Symbol 115
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10399
 
9.2%
10142
 
9.0%
10053
 
8.9%
8956
 
7.9%
8816
 
7.8%
8601
 
7.6%
8581
 
7.6%
7114
 
6.3%
6895
 
6.1%
1631
 
1.4%
Other values (267) 31788
28.1%
Uppercase Letter
ValueCountFrequency (%)
B 876
49.2%
T 869
48.8%
A 11
 
0.6%
K 5
 
0.3%
C 5
 
0.3%
O 3
 
0.2%
M 2
 
0.1%
S 2
 
0.1%
G 2
 
0.1%
E 2
 
0.1%
Other values (3) 3
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 8674
21.6%
2 5263
13.1%
3 4218
10.5%
4 4080
10.2%
5 3944
9.8%
0 3082
 
7.7%
6 3046
 
7.6%
7 2858
 
7.1%
8 2596
 
6.5%
9 2326
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 189
98.4%
. 2
 
1.0%
& 1
 
0.5%
Space Separator
ValueCountFrequency (%)
36415
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7944
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 112976
56.6%
Common 85001
42.6%
Latin 1781
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10399
 
9.2%
10142
 
9.0%
10053
 
8.9%
8956
 
7.9%
8816
 
7.8%
8601
 
7.6%
8581
 
7.6%
7114
 
6.3%
6895
 
6.1%
1631
 
1.4%
Other values (267) 31788
28.1%
Common
ValueCountFrequency (%)
36415
42.8%
1 8674
 
10.2%
- 7944
 
9.3%
2 5263
 
6.2%
3 4218
 
5.0%
4 4080
 
4.8%
5 3944
 
4.6%
0 3082
 
3.6%
6 3046
 
3.6%
7 2858
 
3.4%
Other values (8) 5477
 
6.4%
Latin
ValueCountFrequency (%)
B 876
49.2%
T 869
48.8%
A 11
 
0.6%
K 5
 
0.3%
C 5
 
0.3%
O 3
 
0.2%
M 2
 
0.1%
S 2
 
0.1%
G 2
 
0.1%
E 2
 
0.1%
Other values (4) 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 112976
56.6%
ASCII 86781
43.4%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36415
42.0%
1 8674
 
10.0%
- 7944
 
9.2%
2 5263
 
6.1%
3 4218
 
4.9%
4 4080
 
4.7%
5 3944
 
4.5%
0 3082
 
3.6%
6 3046
 
3.5%
7 2858
 
3.3%
Other values (21) 7257
 
8.4%
Hangul
ValueCountFrequency (%)
10399
 
9.2%
10142
 
9.0%
10053
 
8.9%
8956
 
7.9%
8816
 
7.8%
8601
 
7.6%
8581
 
7.6%
7114
 
6.3%
6895
 
6.1%
1631
 
1.4%
Other values (267) 31788
28.1%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct623
Distinct (%)7.3%
Missing37
Missing (%)0.4%
Memory size67.2 KiB
2024-04-17T01:31:42.402417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0004682
Min length5

Characters and Unicode

Total characters42719
Distinct characters17
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

Unique76 ?
Unique (%)0.9%

Sample

1st row48953
2nd row48947
3rd row48948
4th row48977
5th row48956
ValueCountFrequency (%)
48947 2928
34.3%
48094 184
 
2.2%
48095 131
 
1.5%
49269 99
 
1.2%
48072 91
 
1.1%
48303 90
 
1.1%
48093 86
 
1.0%
48073 83
 
1.0%
48283 82
 
1.0%
48055 79
 
0.9%
Other values (613) 4690
54.9%
2024-04-17T01:31:42.785922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 12854
30.1%
8 6825
16.0%
7 6031
14.1%
9 5680
13.3%
0 2353
 
5.5%
2 2224
 
5.2%
6 2092
 
4.9%
5 1788
 
4.2%
3 1680
 
3.9%
1 1178
 
2.8%
Other values (7) 14
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42705
> 99.9%
Other Letter 14
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 12854
30.1%
8 6825
16.0%
7 6031
14.1%
9 5680
13.3%
0 2353
 
5.5%
2 2224
 
5.2%
6 2092
 
4.9%
5 1788
 
4.2%
3 1680
 
3.9%
1 1178
 
2.8%
Other Letter
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 42705
> 99.9%
Hangul 14
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 12854
30.1%
8 6825
16.0%
7 6031
14.1%
9 5680
13.3%
0 2353
 
5.5%
2 2224
 
5.2%
6 2092
 
4.9%
5 1788
 
4.2%
3 1680
 
3.9%
1 1178
 
2.8%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42705
> 99.9%
Hangul 14
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 12854
30.1%
8 6825
16.0%
7 6031
14.1%
9 5680
13.3%
0 2353
 
5.5%
2 2224
 
5.2%
6 2092
 
4.9%
5 1788
 
4.2%
3 1680
 
3.9%
1 1178
 
2.8%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

rdnwhladdr
Text

MISSING 

Distinct3073
Distinct (%)51.0%
Missing2551
Missing (%)29.7%
Memory size67.2 KiB
2024-04-17T01:31:43.056614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length61
Mean length27.897495
Min length18

Characters and Unicode

Total characters168194
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

Unique339 ?
Unique (%)5.6%

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 6029
 
19.1%
해운대구 959
 
3.0%
부산진구 726
 
2.3%
동래구 607
 
1.9%
사상구 516
 
1.6%
동구 489
 
1.5%
온천동 422
 
1.3%
수영구 410
 
1.3%
중구 395
 
1.3%
부전동 385
 
1.2%
Other values (2625) 20636
65.4%
2024-04-17T01:31:43.471248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25545
 
15.2%
7828
 
4.7%
7435
 
4.4%
7099
 
4.2%
6768
 
4.0%
6406
 
3.8%
1 6396
 
3.8%
6166
 
3.7%
6035
 
3.6%
) 5909
 
3.5%
Other values (358) 82607
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 100113
59.5%
Decimal Number 27219
 
16.2%
Space Separator 25545
 
15.2%
Close Punctuation 5909
 
3.5%
Open Punctuation 5909
 
3.5%
Dash Punctuation 1808
 
1.1%
Other Punctuation 1327
 
0.8%
Math Symbol 269
 
0.2%
Uppercase Letter 91
 
0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7828
 
7.8%
7435
 
7.4%
7099
 
7.1%
6768
 
6.8%
6406
 
6.4%
6166
 
6.2%
6035
 
6.0%
5737
 
5.7%
4014
 
4.0%
3764
 
3.8%
Other values (320) 38861
38.8%
Uppercase Letter
ValueCountFrequency (%)
A 31
34.1%
B 21
23.1%
K 8
 
8.8%
O 5
 
5.5%
C 5
 
5.5%
E 3
 
3.3%
S 3
 
3.3%
U 2
 
2.2%
F 2
 
2.2%
G 2
 
2.2%
Other values (8) 9
 
9.9%
Decimal Number
ValueCountFrequency (%)
1 6396
23.5%
2 4144
15.2%
3 3056
11.2%
4 2319
 
8.5%
5 2197
 
8.1%
0 1963
 
7.2%
6 1943
 
7.1%
7 1872
 
6.9%
9 1714
 
6.3%
8 1615
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 1317
99.2%
. 9
 
0.7%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
25545
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5909
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5909
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1808
100.0%
Math Symbol
ValueCountFrequency (%)
~ 269
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 100113
59.5%
Common 67986
40.4%
Latin 95
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7828
 
7.8%
7435
 
7.4%
7099
 
7.1%
6768
 
6.8%
6406
 
6.4%
6166
 
6.2%
6035
 
6.0%
5737
 
5.7%
4014
 
4.0%
3764
 
3.8%
Other values (320) 38861
38.8%
Latin
ValueCountFrequency (%)
A 31
32.6%
B 21
22.1%
K 8
 
8.4%
O 5
 
5.3%
C 5
 
5.3%
3
 
3.2%
E 3
 
3.2%
S 3
 
3.2%
U 2
 
2.1%
F 2
 
2.1%
Other values (10) 12
 
12.6%
Common
ValueCountFrequency (%)
25545
37.6%
1 6396
 
9.4%
) 5909
 
8.7%
( 5909
 
8.7%
2 4144
 
6.1%
3 3056
 
4.5%
4 2319
 
3.4%
5 2197
 
3.2%
0 1963
 
2.9%
6 1943
 
2.9%
Other values (8) 8605
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 100113
59.5%
ASCII 68078
40.5%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25545
37.5%
1 6396
 
9.4%
) 5909
 
8.7%
( 5909
 
8.7%
2 4144
 
6.1%
3 3056
 
4.5%
4 2319
 
3.4%
5 2197
 
3.2%
0 1963
 
2.9%
6 1943
 
2.9%
Other values (27) 8697
 
12.8%
Hangul
ValueCountFrequency (%)
7828
 
7.8%
7435
 
7.4%
7099
 
7.1%
6768
 
6.8%
6406
 
6.4%
6166
 
6.2%
6035
 
6.0%
5737
 
5.7%
4014
 
4.0%
3764
 
3.8%
Other values (320) 38861
38.8%
Number Forms
ValueCountFrequency (%)
3
100.0%

apvpermymd
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size67.2 KiB

dcbymd
Text

MISSING 

Distinct1426
Distinct (%)34.2%
Missing4415
Missing (%)51.5%
Memory size67.2 KiB
2024-04-17T01:31:43.726638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8386555
Min length4

Characters and Unicode

Total characters32648
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

Unique49 ?
Unique (%)1.2%

Sample

1st row20140310
2nd row20121231
3rd row20171120
4th row20220224
5th row20210823
ValueCountFrequency (%)
20041022 180
 
4.3%
폐업일자 168
 
4.0%
20030122 64
 
1.5%
20120711 52
 
1.2%
20021024 38
 
0.9%
20030305 26
 
0.6%
20030101 24
 
0.6%
20030227 22
 
0.5%
20051117 20
 
0.5%
20030123 18
 
0.4%
Other values (1416) 3553
85.3%
2024-04-17T01:31:44.103320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10676
32.7%
2 6945
21.3%
1 5902
18.1%
3 1460
 
4.5%
9 1434
 
4.4%
7 1227
 
3.8%
4 1155
 
3.5%
6 1109
 
3.4%
5 1080
 
3.3%
8 988
 
3.0%
Other values (4) 672
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31976
97.9%
Other Letter 672
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10676
33.4%
2 6945
21.7%
1 5902
18.5%
3 1460
 
4.6%
9 1434
 
4.5%
7 1227
 
3.8%
4 1155
 
3.6%
6 1109
 
3.5%
5 1080
 
3.4%
8 988
 
3.1%
Other Letter
ValueCountFrequency (%)
168
25.0%
168
25.0%
168
25.0%
168
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31976
97.9%
Hangul 672
 
2.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10676
33.4%
2 6945
21.7%
1 5902
18.5%
3 1460
 
4.6%
9 1434
 
4.5%
7 1227
 
3.8%
4 1155
 
3.6%
6 1109
 
3.5%
5 1080
 
3.4%
8 988
 
3.1%
Hangul
ValueCountFrequency (%)
168
25.0%
168
25.0%
168
25.0%
168
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31976
97.9%
Hangul 672
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10676
33.4%
2 6945
21.7%
1 5902
18.5%
3 1460
 
4.6%
9 1434
 
4.5%
7 1227
 
3.8%
4 1155
 
3.6%
6 1109
 
3.5%
5 1080
 
3.4%
8 988
 
3.1%
Hangul
ValueCountFrequency (%)
168
25.0%
168
25.0%
168
25.0%
168
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8391 
휴업시작일자
 
178
20210916
 
2
20210528
 
2
20211129
 
1
Other values (6)
 
6

Length

Max length8
Median length4
Mean length4.04662
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> 8391
97.8%
휴업시작일자 178
 
2.1%
20210916 2
 
< 0.1%
20210528 2
 
< 0.1%
20211129 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20220118 1
 
< 0.1%
20211031 1
 
< 0.1%

Length

2024-04-17T01:31:44.231969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8391
97.8%
휴업시작일자 178
 
2.1%
20210916 2
 
< 0.1%
20210528 2
 
< 0.1%
20211129 1
 
< 0.1%
20160425 1
 
< 0.1%
20170413 1
 
< 0.1%
20180501 1
 
< 0.1%
20220118 1
 
< 0.1%
20211031 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8391 
휴업종료일자
 
178
20221130
 
2
20230131
 
2
20221128
 
1
Other values (6)
 
6

Length

Max length8
Median length4
Mean length4.04662
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> 8391
97.8%
휴업종료일자 178
 
2.1%
20221130 2
 
< 0.1%
20230131 2
 
< 0.1%
20221128 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20220630 1
 
< 0.1%
20220131 1
 
< 0.1%

Length

2024-04-17T01:31:44.337084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8391
97.8%
휴업종료일자 178
 
2.1%
20221130 2
 
< 0.1%
20230131 2
 
< 0.1%
20221128 1
 
< 0.1%
20180424 1
 
< 0.1%
20190501 1
 
< 0.1%
20190531 1
 
< 0.1%
20220630 1
 
< 0.1%
20220131 1
 
< 0.1%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
재개업일자
 
182

Length

Max length5
Median length4
Mean length4.0212121
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> 8398
97.9%
재개업일자 182
 
2.1%

Length

2024-04-17T01:31:44.441431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:44.535097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
재개업일자 182
 
2.1%

trdstatenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
02
3707 
01
2900 
영업/정상
1571 
폐업
 
240
13
 
96
Other values (4)
 
66

Length

Max length5
Median length2
Mean length2.5502331
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
02 3707
43.2%
01 2900
33.8%
영업/정상 1571
18.3%
폐업 240
 
2.8%
13 96
 
1.1%
03 53
 
0.6%
휴업 8
 
0.1%
<NA> 4
 
< 0.1%
31 1
 
< 0.1%

Length

2024-04-17T01:31:44.634679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:44.735294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3707
43.2%
01 2900
33.8%
영업/정상 1571
18.3%
폐업 240
 
2.8%
13 96
 
1.1%
03 53
 
0.6%
휴업 8
 
0.1%
na 4
 
< 0.1%
31 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
영업
4270 
폐업
3997 
영업중
 
298
휴업
 
11
<NA>
 
3

Length

Max length4
Median length2
Mean length2.0356643
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4270
49.8%
폐업 3997
46.6%
영업중 298
 
3.5%
휴업 11
 
0.1%
<NA> 3
 
< 0.1%
등록취소 1
 
< 0.1%

Length

2024-04-17T01:31:44.854269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:44.949903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4270
49.8%
폐업 3997
46.6%
영업중 298
 
3.5%
휴업 11
 
0.1%
na 3
 
< 0.1%
등록취소 1
 
< 0.1%

x
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing386
Missing (%)4.5%
Memory size67.2 KiB

y
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing389
Missing (%)4.5%
Memory size67.2 KiB

lastmodts
Real number (ℝ)

Distinct3756
Distinct (%)43.8%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0137338 × 1013
Minimum1.9990211 × 1013
Maximum2.0220226 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.5 KiB
2024-04-17T01:31:45.054614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0020204 × 1013
Q12.006071 × 1013
median2.0171127 × 1013
Q32.0180726 × 1013
95-th percentile2.0211216 × 1013
Maximum2.0220226 × 1013
Range2.3001519 × 1011
Interquartile range (IQR)1.2001616 × 1011

Descriptive statistics

Standard deviation7.1314232 × 1010
Coefficient of variation (CV)0.0035413933
Kurtosis-0.98890648
Mean2.0137338 × 1013
Median Absolute Deviation (MAD)3.948998 × 1010
Skewness-0.73480005
Sum1.7271795 × 1017
Variance5.0857197 × 1021
MonotonicityNot monotonic
2024-04-17T01:31:45.172522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19990428000000 62
 
0.7%
19990920000000 60
 
0.7%
20040902000000 60
 
0.7%
20030122000000 58
 
0.7%
20040203000000 50
 
0.6%
20030414000000 36
 
0.4%
20070531000000 36
 
0.4%
20020515000000 32
 
0.4%
19990308000000 32
 
0.4%
20030329000000 32
 
0.4%
Other values (3746) 8119
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 (%)
20220226191138 1
< 0.1%
20220226120043 1
< 0.1%
20220225175400 1
< 0.1%
20220225175343 1
< 0.1%
20220225140439 1
< 0.1%
20220224144751 2
< 0.1%
20220224115803 2
< 0.1%
20220224104958 2
< 0.1%
20220224103231 2
< 0.1%
20220223180238 2
< 0.1%

uptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
여관업
5223 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
513
일반호텔
 
488
Other values (4)
691 

Length

Max length8
Median length3
Mean length3.719697
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5223
60.9%
여인숙업 1076
 
12.5%
숙박업 기타 589
 
6.9%
숙박업(생활) 513
 
6.0%
일반호텔 488
 
5.7%
<NA> 343
 
4.0%
관광호텔 274
 
3.2%
업태구분명 65
 
0.8%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:31:45.292443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:45.391557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5223
57.0%
여인숙업 1076
 
11.7%
숙박업 589
 
6.4%
기타 589
 
6.4%
숙박업(생활 513
 
5.6%
일반호텔 488
 
5.3%
na 343
 
3.7%
관광호텔 274
 
3.0%
업태구분명 65
 
0.7%
휴양콘도미니엄업 9
 
0.1%

sitetel
Text

MISSING 

Distinct701
Distinct (%)8.4%
Missing250
Missing (%)2.9%
Memory size67.2 KiB
2024-04-17T01:31:45.612150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.823289
Min length4

Characters and Unicode

Total characters98488
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)0.7%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234
ValueCountFrequency (%)
051-123-1234 6896
68.2%
051 1250
 
12.4%
전화번호 78
 
0.8%
747 20
 
0.2%
070 20
 
0.2%
746 16
 
0.2%
806 11
 
0.1%
805 10
 
0.1%
755 9
 
0.1%
743 8
 
0.1%
Other values (823) 1793
 
17.7%
2024-04-17T01:31:45.951631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22978
23.3%
2 14904
15.1%
3 14842
15.1%
- 13846
14.1%
0 9355
9.5%
5 9175
 
9.3%
4 7902
 
8.0%
1796
 
1.8%
7 1093
 
1.1%
8 898
 
0.9%
Other values (6) 1699
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82534
83.8%
Dash Punctuation 13846
 
14.1%
Space Separator 1796
 
1.8%
Other Letter 312
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22978
27.8%
2 14904
18.1%
3 14842
18.0%
0 9355
11.3%
5 9175
 
11.1%
4 7902
 
9.6%
7 1093
 
1.3%
8 898
 
1.1%
6 846
 
1.0%
9 541
 
0.7%
Other Letter
ValueCountFrequency (%)
78
25.0%
78
25.0%
78
25.0%
78
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 13846
100.0%
Space Separator
ValueCountFrequency (%)
1796
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98176
99.7%
Hangul 312
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22978
23.4%
2 14904
15.2%
3 14842
15.1%
- 13846
14.1%
0 9355
9.5%
5 9175
 
9.3%
4 7902
 
8.0%
1796
 
1.8%
7 1093
 
1.1%
8 898
 
0.9%
Other values (2) 1387
 
1.4%
Hangul
ValueCountFrequency (%)
78
25.0%
78
25.0%
78
25.0%
78
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98176
99.7%
Hangul 312
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22978
23.4%
2 14904
15.2%
3 14842
15.1%
- 13846
14.1%
0 9355
9.5%
5 9175
 
9.3%
4 7902
 
8.0%
1796
 
1.8%
7 1093
 
1.1%
8 898
 
0.9%
Other values (2) 1387
 
1.4%
Hangul
ValueCountFrequency (%)
78
25.0%
78
25.0%
78
25.0%
78
25.0%

stroomcnt
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8231 
객실수
 
130
1
 
66
2
 
51
3
 
25
Other values (28)
 
77

Length

Max length4
Median length4
Mean length3.9129371
Min length1

Unique

Unique15 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8231
95.9%
객실수 130
 
1.5%
1 66
 
0.8%
2 51
 
0.6%
3 25
 
0.3%
0 11
 
0.1%
7 9
 
0.1%
5 6
 
0.1%
4 6
 
0.1%
6 6
 
0.1%
Other values (23) 39
 
0.5%

Length

2024-04-17T01:31:46.075680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8231
95.9%
객실수 130
 
1.5%
1 66
 
0.8%
2 51
 
0.6%
3 25
 
0.3%
0 11
 
0.1%
7 9
 
0.1%
5 6
 
0.1%
4 6
 
0.1%
6 6
 
0.1%
Other values (23) 39
 
0.5%

bdngownsenm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
6480 
자가
1175 
임대
775 
건물소유구분명
 
150

Length

Max length7
Median length4
Mean length3.5979021
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6480
75.5%
자가 1175
 
13.7%
임대 775
 
9.0%
건물소유구분명 150
 
1.7%

Length

2024-04-17T01:31:46.174807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:46.262288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6480
75.5%
자가 1175
 
13.7%
임대 775
 
9.0%
건물소유구분명 150
 
1.7%

bdngsrvnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8236 
건물용도명
 
149
단독주택
 
78
아파트
 
60
숙박시설
 
24
Other values (6)
 
33

Length

Max length15
Median length4
Mean length4.0170163
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> 8236
96.0%
건물용도명 149
 
1.7%
단독주택 78
 
0.9%
아파트 60
 
0.7%
숙박시설 24
 
0.3%
다세대주택 15
 
0.2%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 주택(공동주택적용) 4
 
< 0.1%
호텔 4
 
< 0.1%

Length

2024-04-17T01:31:46.360456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8236
95.9%
건물용도명 149
 
1.7%
단독주택 78
 
0.9%
아파트 60
 
0.7%
숙박시설 24
 
0.3%
다세대주택 15
 
0.2%
연립주택 5
 
0.1%
근린생활시설 4
 
< 0.1%
다가구용 4
 
< 0.1%
주택(공동주택적용 4
 
< 0.1%
Other values (2) 5
 
0.1%

bdngjisgflrcnt
Categorical

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
0
2547 
<NA>
1673 
4
874 
3
751 
5
601 
Other values (32)
2134 

Length

Max length6
Median length1
Mean length1.6677156
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2547
29.7%
<NA> 1673
19.5%
4 874
 
10.2%
3 751
 
8.8%
5 601
 
7.0%
2 424
 
4.9%
8 330
 
3.8%
6 306
 
3.6%
7 303
 
3.5%
9 199
 
2.3%
Other values (27) 572
 
6.7%

Length

2024-04-17T01:31:46.479501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2547
29.7%
na 1673
19.5%
4 874
 
10.2%
3 751
 
8.8%
5 601
 
7.0%
2 424
 
4.9%
8 330
 
3.8%
6 306
 
3.6%
7 303
 
3.5%
9 199
 
2.3%
Other values (27) 572
 
6.7%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
0
4457 
<NA>
2239 
1
1512 
2
 
200
건물지하층수
 
65
Other values (9)
 
107

Length

Max length6
Median length1
Mean length1.8214452
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4457
51.9%
<NA> 2239
26.1%
1 1512
 
17.6%
2 200
 
2.3%
건물지하층수 65
 
0.8%
4 36
 
0.4%
3 27
 
0.3%
5 19
 
0.2%
6 6
 
0.1%
8 6
 
0.1%
Other values (4) 13
 
0.2%

Length

2024-04-17T01:31:46.576985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4457
51.9%
na 2239
26.1%
1 1514
 
17.6%
2 200
 
2.3%
건물지하층수 65
 
0.8%
4 36
 
0.4%
3 27
 
0.3%
5 19
 
0.2%
6 6
 
0.1%
8 6
 
0.1%
Other values (3) 11
 
0.1%

cnstyarea
Categorical

IMBALANCE 

Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8312 
건축연면적
 
150
0
 
91
2282
 
3
20571
 
3
Other values (19)
 
21

Length

Max length5
Median length4
Mean length3.9840326
Min length1

Unique

Unique17 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8312
96.9%
건축연면적 150
 
1.7%
0 91
 
1.1%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
761 2
 
< 0.1%
451 2
 
< 0.1%
437 1
 
< 0.1%
132 1
 
< 0.1%
352 1
 
< 0.1%
Other values (14) 14
 
0.2%

Length

2024-04-17T01:31:46.679102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8312
96.9%
건축연면적 150
 
1.7%
0 91
 
1.1%
2282 3
 
< 0.1%
20571 3
 
< 0.1%
761 2
 
< 0.1%
451 2
 
< 0.1%
151 1
 
< 0.1%
85 1
 
< 0.1%
2971 1
 
< 0.1%
Other values (14) 14
 
0.2%

svnsr
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
기념품종류
 
182

Length

Max length5
Median length4
Mean length4.0212121
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> 8398
97.9%
기념품종류 182
 
2.1%

Length

2024-04-17T01:31:46.778670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:46.859666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
기념품종류 182
 
2.1%

plninsurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
기획여행보험시작일자
 
182

Length

Max length10
Median length4
Mean length4.1272727
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> 8398
97.9%
기획여행보험시작일자 182
 
2.1%

Length

2024-04-17T01:31:46.944330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:47.039708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
기획여행보험시작일자 182
 
2.1%

plninsurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
기획여행보험종료일자
 
182

Length

Max length10
Median length4
Mean length4.1272727
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> 8398
97.9%
기획여행보험종료일자 182
 
2.1%

Length

2024-04-17T01:31:47.133221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:47.218609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
기획여행보험종료일자 182
 
2.1%

maneipcnt
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
7452 
0
999 
남성종사자수
 
99
1
 
12
3
 
5
Other values (6)
 
13

Length

Max length6
Median length4
Mean length3.6634033
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> 7452
86.9%
0 999
 
11.6%
남성종사자수 99
 
1.2%
1 12
 
0.1%
3 5
 
0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
35 1
 
< 0.1%

Length

2024-04-17T01:31:47.575922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7452
86.9%
0 999
 
11.6%
남성종사자수 99
 
1.2%
1 12
 
0.1%
3 5
 
0.1%
2 4
 
< 0.1%
4 3
 
< 0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
35 1
 
< 0.1%

playutscntdtl
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
놀이기구수내역
 
182

Length

Max length7
Median length4
Mean length4.0636364
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> 8398
97.9%
놀이기구수내역 182
 
2.1%

Length

2024-04-17T01:31:47.679965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:47.765675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
놀이기구수내역 182
 
2.1%

playfacilcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
N
6893 
<NA>
1444 
놀이시설수
 
139
0
 
101
Y
 
3

Length

Max length5
Median length1
Mean length1.569697
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 6893
80.3%
<NA> 1444
 
16.8%
놀이시설수 139
 
1.6%
0 101
 
1.2%
Y 3
 
< 0.1%

Length

2024-04-17T01:31:47.869390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:47.972728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 6893
80.3%
na 1444
 
16.8%
놀이시설수 139
 
1.6%
0 101
 
1.2%
y 3
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
N
8384 
<NA>
 
133
 
52
Y
 
11

Length

Max length4
Median length1
Mean length1.0465035
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8384
97.7%
<NA> 133
 
1.6%
52
 
0.6%
Y 11
 
0.1%

Length

2024-04-17T01:31:48.072886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:48.171816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8384
97.7%
na 133
 
1.6%
52
 
0.6%
y 11
 
0.1%

stagear
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8325 
무대면적
 
154
0
 
101

Length

Max length4
Median length4
Mean length3.9646853
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> 8325
97.0%
무대면적 154
 
1.8%
0 101
 
1.2%

Length

2024-04-17T01:31:48.265586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:48.351171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8325
97.0%
무대면적 154
 
1.8%
0 101
 
1.2%

culwrkrsenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
문화사업자구분명
 
182

Length

Max length8
Median length4
Mean length4.0848485
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> 8398
97.9%
문화사업자구분명 182
 
2.1%

Length

2024-04-17T01:31:48.465457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:48.558849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
문화사업자구분명 182
 
2.1%

culphyedcobnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8063 
외국인관광 도시민박업
 
290
문화체육업종명
 
117
관광숙박업
 
94
자동차야영장업
 
9
Other values (3)
 
7

Length

Max length11
Median length4
Mean length4.2925408
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> 8063
94.0%
외국인관광 도시민박업 290
 
3.4%
문화체육업종명 117
 
1.4%
관광숙박업 94
 
1.1%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%

Length

2024-04-17T01:31:48.652229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:48.758584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8063
90.9%
외국인관광 290
 
3.3%
도시민박업 290
 
3.3%
문화체육업종명 117
 
1.3%
관광숙박업 94
 
1.1%
자동차야영장업 9
 
0.1%
관광펜션업 3
 
< 0.1%
한옥체험업 3
 
< 0.1%
일반야영장업 1
 
< 0.1%

geicpfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
 
182

Length

Max length4
Median length4
Mean length3.9363636
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> 8398
97.9%
182
 
2.1%

Length

2024-04-17T01:31:48.877505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:48.959755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
182
 
2.1%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
N
8371 
<NA>
 
133
 
52
Y
 
24

Length

Max length4
Median length1
Mean length1.0465035
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 8371
97.6%
<NA> 133
 
1.6%
52
 
0.6%
Y 24
 
0.3%

Length

2024-04-17T01:31:49.058180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:49.166114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 8371
97.6%
na 133
 
1.6%
52
 
0.6%
y 24
 
0.3%

bcfacilen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
 
182

Length

Max length4
Median length4
Mean length3.9363636
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> 8398
97.9%
182
 
2.1%

Length

2024-04-17T01:31:49.276491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:49.361273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
182
 
2.1%

insurorgnm
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8373 
보험기관명
 
179
현대해상
 
3
야영장사고배상책임보험
 
2
DB 손해보험
 
2
Other values (20)
 
21

Length

Max length22
Median length4
Mean length4.0414918
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> 8373
97.6%
보험기관명 179
 
2.1%
현대해상 3
 
< 0.1%
야영장사고배상책임보험 2
 
< 0.1%
DB 손해보험 2
 
< 0.1%
객실수/수용인원 : 2개/ 6명 2
 
< 0.1%
객실수/수용인원:1/2 1
 
< 0.1%
객실수/수용인원 : 3/8 1
 
< 0.1%
객실수/수용인원:2/6 1
 
< 0.1%
객실수/수용인원: 3/8 1
 
< 0.1%
Other values (15) 15
 
0.2%

Length

2024-04-17T01:31:49.459356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8373
97.4%
보험기관명 179
 
2.1%
객실수/수용인원 6
 
0.1%
5
 
0.1%
현대해상 3
 
< 0.1%
야영장사고배상책임보험 2
 
< 0.1%
db 2
 
< 0.1%
손해보험 2
 
< 0.1%
2개 2
 
< 0.1%
6명 2
 
< 0.1%
Other values (21) 22
 
0.3%

insurstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
보험시작일자
 
182

Length

Max length6
Median length4
Mean length4.0424242
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> 8398
97.9%
보험시작일자 182
 
2.1%

Length

2024-04-17T01:31:49.591218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:49.680271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
보험시작일자 182
 
2.1%

insurenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
보험종료일자
 
182

Length

Max length6
Median length4
Mean length4.0424242
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> 8398
97.9%
보험종료일자 182
 
2.1%

Length

2024-04-17T01:31:49.785859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:49.885246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
보험종료일자 182
 
2.1%

afc
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
부대시설내역
 
182

Length

Max length6
Median length4
Mean length4.0424242
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> 8398
97.9%
부대시설내역 182
 
2.1%

Length

2024-04-17T01:31:50.022422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:50.110106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
부대시설내역 182
 
2.1%

usejisgendflr
Categorical

Distinct36
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
2695 
0
1970 
4
766 
3
650 
5
475 
Other values (31)
2024 

Length

Max length6
Median length1
Mean length2.0219114
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2695
31.4%
0 1970
23.0%
4 766
 
8.9%
3 650
 
7.6%
5 475
 
5.5%
6 417
 
4.9%
2 391
 
4.6%
7 270
 
3.1%
8 261
 
3.0%
9 185
 
2.2%
Other values (26) 500
 
5.8%

Length

2024-04-17T01:31:50.216290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2695
31.4%
0 1970
23.0%
4 766
 
8.9%
3 650
 
7.6%
5 475
 
5.5%
6 417
 
4.9%
2 391
 
4.6%
7 270
 
3.1%
8 261
 
3.0%
9 185
 
2.2%
Other values (26) 500
 
5.8%

useunderendflr
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
0
4716 
<NA>
3582 
1
 
182
사용끝지하층
 
70
2
 
16
Other values (4)
 
14

Length

Max length6
Median length1
Mean length2.2933566
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4716
55.0%
<NA> 3582
41.7%
1 182
 
2.1%
사용끝지하층 70
 
0.8%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
19 1
 
< 0.1%

Length

2024-04-17T01:31:50.317255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:50.414186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4716
55.0%
na 3582
41.7%
1 182
 
2.1%
사용끝지하층 70
 
0.8%
2 16
 
0.2%
7 5
 
0.1%
4 4
 
< 0.1%
3 4
 
< 0.1%
19 1
 
< 0.1%

usejisgstflr
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
0
2459 
1
1919 
<NA>
1868 
2
1001 
3
517 
Other values (16)
816 

Length

Max length7
Median length1
Mean length1.7066434
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2459
28.7%
1 1919
22.4%
<NA> 1868
21.8%
2 1001
11.7%
3 517
 
6.0%
4 315
 
3.7%
5 191
 
2.2%
6 77
 
0.9%
사용시작지상층 67
 
0.8%
7 60
 
0.7%
Other values (11) 106
 
1.2%

Length

2024-04-17T01:31:50.539040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 2459
28.7%
1 1919
22.4%
na 1868
21.8%
2 1001
11.7%
3 517
 
6.0%
4 315
 
3.7%
5 191
 
2.2%
6 77
 
0.9%
사용시작지상층 67
 
0.8%
7 60
 
0.7%
Other values (11) 106
 
1.2%

useunderstflr
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
0
5653 
<NA>
2631 
1
 
215
사용시작지하층
 
68
4
 
8
Other values (3)
 
5

Length

Max length7
Median length1
Mean length1.9674825
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5653
65.9%
<NA> 2631
30.7%
1 215
 
2.5%
사용시작지하층 68
 
0.8%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:31:50.649913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:50.749546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5653
65.9%
na 2631
30.7%
1 215
 
2.5%
사용시작지하층 68
 
0.8%
4 8
 
0.1%
6 2
 
< 0.1%
2 2
 
< 0.1%
7 1
 
< 0.1%

shpinfo
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
선박제원
 
182

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> 8398
97.9%
선박제원 182
 
2.1%

Length

2024-04-17T01:31:50.846182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:50.930878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
선박제원 182
 
2.1%

shpcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8325 
선박척수
 
154
0
 
101

Length

Max length4
Median length4
Mean length3.9646853
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> 8325
97.0%
선박척수 154
 
1.8%
0 101
 
1.2%

Length

2024-04-17T01:31:51.017621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:51.110591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8325
97.0%
선박척수 154
 
1.8%
0 101
 
1.2%

shptottons
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8325 
선박총톤수
 
154
0
 
101

Length

Max length5
Median length4
Mean length3.982634
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> 8325
97.0%
선박총톤수 154
 
1.8%
0 101
 
1.2%

Length

2024-04-17T01:31:51.211268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:51.301443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8325
97.0%
선박총톤수 154
 
1.8%
0 101
 
1.2%

washmccnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
0
5032 
<NA>
3483 
세탁기수
 
65

Length

Max length4
Median length1
Mean length2.2405594
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5032
58.6%
<NA> 3483
40.6%
세탁기수 65
 
0.8%

Length

2024-04-17T01:31:51.392600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:51.478909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5032
58.6%
na 3483
40.6%
세탁기수 65
 
0.8%

facilscp
Text

MISSING 

Distinct158
Distinct (%)34.3%
Missing8120
Missing (%)94.6%
Memory size67.2 KiB
2024-04-17T01:31:51.712833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.9369565
Min length1

Characters and Unicode

Total characters1351
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

Unique84 ?
Unique (%)18.3%

Sample

1st row시설규모
2nd row시설규모
3rd row시설규모
4th row시설규모
5th row시설규모
ValueCountFrequency (%)
시설규모 123
26.7%
0 25
 
5.4%
85 16
 
3.5%
46 7
 
1.5%
57 6
 
1.3%
83 6
 
1.3%
60 6
 
1.3%
67 6
 
1.3%
599 6
 
1.3%
63 5
 
1.1%
Other values (148) 254
55.2%
2024-04-17T01:31:52.143198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 130
9.6%
123
9.1%
123
9.1%
123
9.1%
123
9.1%
5 106
 
7.8%
0 91
 
6.7%
8 88
 
6.5%
6 78
 
5.8%
2 76
 
5.6%
Other values (4) 290
21.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 859
63.6%
Other Letter 492
36.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 130
15.1%
5 106
12.3%
0 91
10.6%
8 88
10.2%
6 78
9.1%
2 76
8.8%
4 75
8.7%
7 73
8.5%
3 71
8.3%
9 71
8.3%
Other Letter
ValueCountFrequency (%)
123
25.0%
123
25.0%
123
25.0%
123
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 859
63.6%
Hangul 492
36.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 130
15.1%
5 106
12.3%
0 91
10.6%
8 88
10.2%
6 78
9.1%
2 76
8.8%
4 75
8.7%
7 73
8.5%
3 71
8.3%
9 71
8.3%
Hangul
ValueCountFrequency (%)
123
25.0%
123
25.0%
123
25.0%
123
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 859
63.6%
Hangul 492
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 130
15.1%
5 106
12.3%
0 91
10.6%
8 88
10.2%
6 78
9.1%
2 76
8.8%
4 75
8.7%
7 73
8.5%
3 71
8.3%
9 71
8.3%
Hangul
ValueCountFrequency (%)
123
25.0%
123
25.0%
123
25.0%
123
25.0%

facilar
Text

MISSING 

Distinct234
Distinct (%)50.9%
Missing8120
Missing (%)94.6%
Memory size67.2 KiB
2024-04-17T01:31:52.495549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.7
Min length1

Characters and Unicode

Total characters2162
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

Unique183 ?
Unique (%)39.8%

Sample

1st row시설면적
2nd row시설면적
3rd row시설면적
4th row시설면적
5th row시설면적
ValueCountFrequency (%)
시설면적 123
26.7%
0 25
 
5.4%
45.5 6
 
1.3%
598.73 6
 
1.3%
218.85 4
 
0.9%
62.58 4
 
0.9%
1497.35 3
 
0.7%
62.25 3
 
0.7%
8546.81 3
 
0.7%
59.4 3
 
0.7%
Other values (224) 280
60.9%
2024-04-17T01:31:52.943975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 285
13.2%
1 175
 
8.1%
4 171
 
7.9%
8 164
 
7.6%
5 144
 
6.7%
3 130
 
6.0%
2 130
 
6.0%
6 128
 
5.9%
123
 
5.7%
123
 
5.7%
Other values (5) 589
27.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1385
64.1%
Other Letter 492
 
22.8%
Other Punctuation 285
 
13.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 175
12.6%
4 171
12.3%
8 164
11.8%
5 144
10.4%
3 130
9.4%
2 130
9.4%
6 128
9.2%
9 123
8.9%
7 114
8.2%
0 106
7.7%
Other Letter
ValueCountFrequency (%)
123
25.0%
123
25.0%
123
25.0%
123
25.0%
Other Punctuation
ValueCountFrequency (%)
. 285
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1670
77.2%
Hangul 492
 
22.8%

Most frequent character per script

Common
ValueCountFrequency (%)
. 285
17.1%
1 175
10.5%
4 171
10.2%
8 164
9.8%
5 144
8.6%
3 130
7.8%
2 130
7.8%
6 128
7.7%
9 123
7.4%
7 114
 
6.8%
Hangul
ValueCountFrequency (%)
123
25.0%
123
25.0%
123
25.0%
123
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1670
77.2%
Hangul 492
 
22.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 285
17.1%
1 175
10.5%
4 171
10.2%
8 164
9.8%
5 144
8.6%
3 130
7.8%
2 130
7.8%
6 128
7.7%
9 123
7.4%
7 114
 
6.8%
Hangul
ValueCountFrequency (%)
123
25.0%
123
25.0%
123
25.0%
123
25.0%

infoben
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
 
182

Length

Max length4
Median length4
Mean length3.9363636
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> 8398
97.9%
182
 
2.1%

Length

2024-04-17T01:31:53.068898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:53.153507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
182
 
2.1%

yangsilcnt
Text

MISSING 

Distinct154
Distinct (%)2.0%
Missing921
Missing (%)10.7%
Memory size67.2 KiB
2024-04-17T01:31:53.326468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7438308
Min length1

Characters and Unicode

Total characters13356
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

Unique21 ?
Unique (%)0.3%

Sample

1st row107
2nd row81
3rd row16
4th row7
5th row5
ValueCountFrequency (%)
0 1042
 
13.6%
10 440
 
5.7%
18 370
 
4.8%
12 318
 
4.2%
14 314
 
4.1%
15 301
 
3.9%
13 248
 
3.2%
19 242
 
3.2%
16 221
 
2.9%
17 217
 
2.8%
Other values (144) 3946
51.5%
2024-04-17T01:31:53.756530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3439
25.7%
0 1930
14.5%
2 1884
14.1%
3 1358
 
10.2%
4 1046
 
7.8%
5 823
 
6.2%
8 815
 
6.1%
6 640
 
4.8%
9 623
 
4.7%
7 603
 
4.5%
Other values (3) 195
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13161
98.5%
Other Letter 195
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3439
26.1%
0 1930
14.7%
2 1884
14.3%
3 1358
 
10.3%
4 1046
 
7.9%
5 823
 
6.3%
8 815
 
6.2%
6 640
 
4.9%
9 623
 
4.7%
7 603
 
4.6%
Other Letter
ValueCountFrequency (%)
65
33.3%
65
33.3%
65
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13161
98.5%
Hangul 195
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3439
26.1%
0 1930
14.7%
2 1884
14.3%
3 1358
 
10.3%
4 1046
 
7.9%
5 823
 
6.3%
8 815
 
6.2%
6 640
 
4.9%
9 623
 
4.7%
7 603
 
4.6%
Hangul
ValueCountFrequency (%)
65
33.3%
65
33.3%
65
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13161
98.5%
Hangul 195
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3439
26.1%
0 1930
14.7%
2 1884
14.3%
3 1358
 
10.3%
4 1046
 
7.9%
5 823
 
6.3%
8 815
 
6.2%
6 640
 
4.9%
9 623
 
4.7%
7 603
 
4.6%
Hangul
ValueCountFrequency (%)
65
33.3%
65
33.3%
65
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
7454 
0
1005 
여성종사자수
 
99
2
 
6
1
 
6
Other values (4)
 
10

Length

Max length6
Median length4
Mean length3.6643357
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> 7454
86.9%
0 1005
 
11.7%
여성종사자수 99
 
1.2%
2 6
 
0.1%
1 6
 
0.1%
3 5
 
0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

Length

2024-04-17T01:31:53.908066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:54.052607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7454
86.9%
0 1005
 
11.7%
여성종사자수 99
 
1.2%
2 6
 
0.1%
1 6
 
0.1%
3 5
 
0.1%
15 2
 
< 0.1%
7 2
 
< 0.1%
35 1
 
< 0.1%

engstntrnmnm
Text

MISSING 

Distinct55
Distinct (%)23.0%
Missing8341
Missing (%)97.2%
Memory size67.2 KiB
2024-04-17T01:31:54.306575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length5
Mean length7.9874477
Min length4

Characters and Unicode

Total characters1909
Distinct characters60
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

Unique43 ?
Unique (%)18.0%

Sample

1st row영문상호명
2nd row영문상호명
3rd row영문상호명
4th row영문상호명
5th row영문상호명
ValueCountFrequency (%)
영문상호명 167
50.8%
house 31
 
9.4%
busan 9
 
2.7%
ocean 6
 
1.8%
hotel 6
 
1.8%
guest 5
 
1.5%
kim's 4
 
1.2%
suyeong 3
 
0.9%
in 3
 
0.9%
the 3
 
0.9%
Other values (66) 92
28.0%
2024-04-17T01:31:54.675707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
167
 
8.7%
167
 
8.7%
167
 
8.7%
167
 
8.7%
167
 
8.7%
e 99
 
5.2%
90
 
4.7%
o 84
 
4.4%
a 61
 
3.2%
n 58
 
3.0%
Other values (50) 682
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 835
43.7%
Lowercase Letter 643
33.7%
Uppercase Letter 315
 
16.5%
Space Separator 90
 
4.7%
Decimal Number 12
 
0.6%
Dash Punctuation 7
 
0.4%
Other Punctuation 7
 
0.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 39
12.4%
S 36
 
11.4%
E 31
 
9.8%
O 24
 
7.6%
U 21
 
6.7%
B 19
 
6.0%
Y 16
 
5.1%
A 14
 
4.4%
P 13
 
4.1%
R 12
 
3.8%
Other values (14) 90
28.6%
Lowercase Letter
ValueCountFrequency (%)
e 99
15.4%
o 84
13.1%
a 61
9.5%
n 58
9.0%
u 50
 
7.8%
s 42
 
6.5%
h 30
 
4.7%
t 28
 
4.4%
m 24
 
3.7%
i 24
 
3.7%
Other values (13) 143
22.2%
Other Letter
ValueCountFrequency (%)
167
20.0%
167
20.0%
167
20.0%
167
20.0%
167
20.0%
Decimal Number
ValueCountFrequency (%)
0 7
58.3%
2 3
25.0%
1 2
 
16.7%
Other Punctuation
ValueCountFrequency (%)
' 5
71.4%
& 1
 
14.3%
. 1
 
14.3%
Space Separator
ValueCountFrequency (%)
90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 958
50.2%
Hangul 835
43.7%
Common 116
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 99
 
10.3%
o 84
 
8.8%
a 61
 
6.4%
n 58
 
6.1%
u 50
 
5.2%
s 42
 
4.4%
H 39
 
4.1%
S 36
 
3.8%
E 31
 
3.2%
h 30
 
3.1%
Other values (37) 428
44.7%
Common
ValueCountFrequency (%)
90
77.6%
- 7
 
6.0%
0 7
 
6.0%
' 5
 
4.3%
2 3
 
2.6%
1 2
 
1.7%
& 1
 
0.9%
. 1
 
0.9%
Hangul
ValueCountFrequency (%)
167
20.0%
167
20.0%
167
20.0%
167
20.0%
167
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1074
56.3%
Hangul 835
43.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
167
20.0%
167
20.0%
167
20.0%
167
20.0%
167
20.0%
ASCII
ValueCountFrequency (%)
e 99
 
9.2%
90
 
8.4%
o 84
 
7.8%
a 61
 
5.7%
n 58
 
5.4%
u 50
 
4.7%
s 42
 
3.9%
H 39
 
3.6%
S 36
 
3.4%
E 31
 
2.9%
Other values (45) 484
45.1%

engstntrnmaddr
Categorical

IMBALANCE 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8344 
영문상호주소
 
167
Guesthouse for Foreign Tourists
 
23
Foreigner Tourism City home-stay Business
 
14
Guest House
 
4
Other values (16)
 
28

Length

Max length41
Median length4
Mean length4.2538462
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> 8344
97.2%
영문상호주소 167
 
1.9%
Guesthouse for Foreign Tourists 23
 
0.3%
Foreigner Tourism City home-stay Business 14
 
0.2%
Guest House 4
 
< 0.1%
Oversea Travel Business 3
 
< 0.1%
TOURIST ACCOMMODATION 3
 
< 0.1%
TOURIST ACCOMMODATION (hostel) 3
 
< 0.1%
Guesthouse for Foregin Tourists 3
 
< 0.1%
Entertainment Business for foreigner only 3
 
< 0.1%
Other values (11) 13
 
0.2%

Length

2024-04-17T01:31:54.815877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8344
95.1%
영문상호주소 167
 
1.9%
for 33
 
0.4%
guesthouse 29
 
0.3%
foreign 29
 
0.3%
tourists 29
 
0.3%
business 22
 
0.3%
foreigner 19
 
0.2%
home-stay 15
 
0.2%
city 14
 
0.2%
Other values (19) 74
 
0.8%

yoksilcnt
Categorical

IMBALANCE 

Distinct33
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
0
5876 
<NA>
2451 
욕실수
 
65
15
 
16
12
 
14
Other values (28)
 
158

Length

Max length4
Median length1
Mean length1.8914918
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5876
68.5%
<NA> 2451
28.6%
욕실수 65
 
0.8%
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

2024-04-17T01:31:54.956197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 5876
68.5%
na 2451
28.6%
욕실수 65
 
0.8%
15 16
 
0.2%
12 14
 
0.2%
18 12
 
0.1%
10 12
 
0.1%
14 10
 
0.1%
9 10
 
0.1%
8 10
 
0.1%
Other values (23) 104
 
1.2%

sntuptaenm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
여관업
5223 
여인숙업
1076 
숙박업 기타
589 
숙박업(생활)
 
513
일반호텔
 
488
Other values (4)
691 

Length

Max length8
Median length3
Mean length3.719697
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여관업 5223
60.9%
여인숙업 1076
 
12.5%
숙박업 기타 589
 
6.9%
숙박업(생활) 513
 
6.0%
일반호텔 488
 
5.7%
<NA> 343
 
4.0%
관광호텔 274
 
3.2%
위생업태명 65
 
0.8%
휴양콘도미니엄업 9
 
0.1%

Length

2024-04-17T01:31:55.064898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:55.162387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 5223
57.0%
여인숙업 1076
 
11.7%
숙박업 589
 
6.4%
기타 589
 
6.4%
숙박업(생활 513
 
5.6%
일반호텔 488
 
5.3%
na 343
 
3.7%
관광호텔 274
 
3.0%
위생업태명 65
 
0.7%
휴양콘도미니엄업 9
 
0.1%

dispenen
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
 
182

Length

Max length4
Median length4
Mean length3.9363636
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> 8398
97.9%
182
 
2.1%

Length

2024-04-17T01:31:55.293668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:55.376232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
182
 
2.1%

capt
Categorical

IMBALANCE 

Distinct45
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8258 
자본금
 
138
0
 
75
10000000
 
20
100000000
 
12
Other values (40)
 
77

Length

Max length10
Median length4
Mean length4.0134033
Min length1

Unique

Unique25 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8258
96.2%
자본금 138
 
1.6%
0 75
 
0.9%
10000000 20
 
0.2%
100000000 12
 
0.1%
200000000 7
 
0.1%
50000000 7
 
0.1%
20000000 5
 
0.1%
300000000 4
 
< 0.1%
5000000 4
 
< 0.1%
Other values (35) 50
 
0.6%

Length

2024-04-17T01:31:55.466849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8258
96.2%
자본금 138
 
1.6%
0 75
 
0.9%
10000000 20
 
0.2%
100000000 12
 
0.1%
200000000 7
 
0.1%
50000000 7
 
0.1%
20000000 5
 
0.1%
5000000 4
 
< 0.1%
300000000 4
 
< 0.1%
Other values (35) 50
 
0.6%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
제작취급품목내용
 
182

Length

Max length8
Median length4
Mean length4.0848485
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> 8398
97.9%
제작취급품목내용 182
 
2.1%

Length

2024-04-17T01:31:55.562387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:55.680239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
제작취급품목내용 182
 
2.1%

cndpermstymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
조건부허가시작일자
 
182

Length

Max length9
Median length4
Mean length4.1060606
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> 8398
97.9%
조건부허가시작일자 182
 
2.1%

Length

2024-04-17T01:31:55.788745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:55.894200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
조건부허가시작일자 182
 
2.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
조건부허가신고사유
 
182

Length

Max length9
Median length4
Mean length4.1060606
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> 8398
97.9%
조건부허가신고사유 182
 
2.1%

Length

2024-04-17T01:31:56.262910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:56.345134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
조건부허가신고사유 182
 
2.1%

cndpermendymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8398 
조건부허가종료일자
 
182

Length

Max length9
Median length4
Mean length4.1060606
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> 8398
97.9%
조건부허가종료일자 182
 
2.1%

Length

2024-04-17T01:31:56.442025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:56.533076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8398
97.9%
조건부허가종료일자 182
 
2.1%

chaircnt
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
4665 
0
3873 
좌석수
 
37
6
 
1
12
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length2.6398601
Min length1

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4665
54.4%
0 3873
45.1%
좌석수 37
 
0.4%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-17T01:31:56.636419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:56.796372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4665
54.4%
0 3873
45.1%
좌석수 37
 
0.4%
6 1
 
< 0.1%
12 1
 
< 0.1%
4 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%

nearenvnm
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8303 
주변환경명
 
163
주택가주변
 
40
아파트지역
 
32
기타
 
25
Other values (3)
 
17

Length

Max length8
Median length4
Mean length4.0294872
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> 8303
96.8%
주변환경명 163
 
1.9%
주택가주변 40
 
0.5%
아파트지역 32
 
0.4%
기타 25
 
0.3%
학교정화(상대) 14
 
0.2%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-17T01:31:56.984531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:57.109555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8303
96.8%
주변환경명 163
 
1.9%
주택가주변 40
 
0.5%
아파트지역 32
 
0.4%
기타 25
 
0.3%
학교정화(상대 14
 
0.2%
유흥업소밀집지역 2
 
< 0.1%
학교정화(절대 1
 
< 0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8224 
지상층수
 
138
0
 
62
2
 
35
4
 
19
Other values (22)
 
102

Length

Max length4
Median length4
Mean length3.9285548
Min length1

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8224
95.9%
지상층수 138
 
1.6%
0 62
 
0.7%
2 35
 
0.4%
4 19
 
0.2%
1 15
 
0.2%
3 15
 
0.2%
5 11
 
0.1%
6 8
 
0.1%
20 7
 
0.1%
Other values (17) 46
 
0.5%

Length

2024-04-17T01:31:57.245517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8224
95.9%
지상층수 138
 
1.6%
0 62
 
0.7%
2 35
 
0.4%
4 19
 
0.2%
1 15
 
0.2%
3 15
 
0.2%
5 11
 
0.1%
6 8
 
0.1%
20 7
 
0.1%
Other values (17) 46
 
0.5%

regnsenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8193 
지역구분명
 
141
일반주거지역
 
122
일반상업지역
 
44
준주거지역
 
33
Other values (5)
 
47

Length

Max length6
Median length4
Mean length4.0606061
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> 8193
95.5%
지역구분명 141
 
1.6%
일반주거지역 122
 
1.4%
일반상업지역 44
 
0.5%
준주거지역 33
 
0.4%
주거지역 31
 
0.4%
자연녹지지역 6
 
0.1%
상업지역 6
 
0.1%
녹지지역 3
 
< 0.1%
전용주거지역 1
 
< 0.1%

Length

2024-04-17T01:31:57.363153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:57.500169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8193
95.5%
지역구분명 141
 
1.6%
일반주거지역 122
 
1.4%
일반상업지역 44
 
0.5%
준주거지역 33
 
0.4%
주거지역 31
 
0.4%
자연녹지지역 6
 
0.1%
상업지역 6
 
0.1%
녹지지역 3
 
< 0.1%
전용주거지역 1
 
< 0.1%

undernumlay
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8285 
지하층수
 
144
0
 
94
1
 
29
2
 
21
Other values (5)
 
7

Length

Max length4
Median length4
Mean length3.9472028
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> 8285
96.6%
지하층수 144
 
1.7%
0 94
 
1.1%
1 29
 
0.3%
2 21
 
0.2%
3 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:31:57.617990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:57.720945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8285
96.6%
지하층수 144
 
1.7%
0 94
 
1.1%
1 29
 
0.3%
2 21
 
0.2%
3 3
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%

totnumlay
Categorical

IMBALANCE 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8217 
총층수
 
135
0
 
49
2
 
41
1
 
22
Other values (21)
 
116

Length

Max length4
Median length4
Mean length3.909324
Min length1

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8217
95.8%
총층수 135
 
1.6%
0 49
 
0.6%
2 41
 
0.5%
1 22
 
0.3%
4 21
 
0.2%
3 19
 
0.2%
5 16
 
0.2%
6 9
 
0.1%
20 7
 
0.1%
Other values (16) 44
 
0.5%

Length

2024-04-17T01:31:57.857394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8217
95.8%
총층수 135
 
1.6%
0 49
 
0.6%
2 41
 
0.5%
1 22
 
0.3%
4 21
 
0.2%
3 19
 
0.2%
5 16
 
0.2%
6 9
 
0.1%
20 7
 
0.1%
Other values (16) 44
 
0.5%

abedcnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
0
4988 
<NA>
3525 
침대수
 
65
41
 
2

Length

Max length4
Median length1
Mean length2.2479021
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4988
58.1%
<NA> 3525
41.1%
침대수 65
 
0.8%
41 2
 
< 0.1%

Length

2024-04-17T01:31:57.974551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:58.077223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4988
58.1%
na 3525
41.1%
침대수 65
 
0.8%
41 2
 
< 0.1%

hanshilcnt
Categorical

Distinct48
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
0
3769 
<NA>
1475 
2
 
326
10
 
310
3
 
266
Other values (43)
2434 

Length

Max length4
Median length1
Mean length1.6792541
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3769
43.9%
<NA> 1475
 
17.2%
2 326
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 262
 
3.1%
8 227
 
2.6%
4 201
 
2.3%
6 200
 
2.3%
9 197
 
2.3%
Other values (38) 1347
 
15.7%

Length

2024-04-17T01:31:58.221410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 3769
43.9%
na 1475
 
17.2%
2 326
 
3.8%
10 310
 
3.6%
3 266
 
3.1%
1 262
 
3.1%
8 227
 
2.6%
4 201
 
2.3%
6 200
 
2.3%
9 197
 
2.3%
Other values (38) 1347
 
15.7%

rcvdryncnt
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
0
4996 
<NA>
3519 
회수건조수
 
65

Length

Max length5
Median length1
Mean length2.2607226
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 4996
58.2%
<NA> 3519
41.0%
회수건조수 65
 
0.8%

Length

2024-04-17T01:31:58.357091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:58.497567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4996
58.2%
na 3519
41.0%
회수건조수 65
 
0.8%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
<NA>
8325 
회의실별동시수용인원
 
154
0
 
101

Length

Max length10
Median length4
Mean length4.0723776
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> 8325
97.0%
회의실별동시수용인원 154
 
1.8%
0 101
 
1.2%

Length

2024-04-17T01:31:58.644912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:58.744485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8325
97.0%
회의실별동시수용인원 154
 
1.8%
0 101
 
1.2%

last_load_dttm
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.2 KiB
2022-03-01 05:09:04
5055 
2022-03-01 05:09:03
3326 
2022-03-01 05:09:05
 
193
<NA>
 
6

Length

Max length19
Median length19
Mean length18.98951
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2022-03-01 05:09:04 5055
58.9%
2022-03-01 05:09:03 3326
38.8%
2022-03-01 05:09:05 193
 
2.2%
<NA> 6
 
0.1%

Length

2024-04-17T01:31:58.852008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:31:58.946296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-03-01 8574
50.0%
05:09:04 5055
29.5%
05:09:03 3326
 
19.4%
05:09:05 193
 
1.1%
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>2022-03-01 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>2022-03-01 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>2022-03-01 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>2022-03-01 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>2022-03-01 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>2022-03-01 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>2022-03-01 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>2022-03-01 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>2022-03-01 05:09:03
91132500003250000-201-1972-0000303_11_03_PU2022-02-25 02:40:00.0숙박업주식회사 경원건설 호텔노아600045부산광역시 중구 남포동5가 81-148983부산광역시 중구 자갈치로47번길 3-1 (남포동5가)19721010<NA><NA><NA><NA>영업/정상영업384966.283935179482.33662320220223180238관광호텔051 2464361<NA>자가<NA>91<NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9010<NA><NA><NA>0<NA><NA><NA>51<NA><NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>2022-03-01 05:09:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
85701302733600003360000-201-2021-0000103_11_03_PU2021-12-04 02:40:00.0숙박업신라스테이 서부산618200부산광역시 강서구 명지동 3595-1 신라스테이 서부산점46726부산광역시 강서구 명지국제7로 38, 신라스테이 서부산점 (명지동)20210331<NA><NA><NA><NA>영업/정상영업373665.73430842179173.52698928820211202090442관광호텔051 661 9000<NA><NA><NA>233<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0000<NA><NA><NA>0<NA><NA><NA>2910<NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>040<NA>2022-03-01 05:09:05
85711302833300003330000-214-2021-0000203_11_03_PI2021-04-02 00:22:59.0숙박업벨리아(BELLIA)612847부산광역시 해운대구 중동 1123 해운대푸르지오시티48099부산광역시 해운대구 해운대해변로298번길 29, 해운대푸르지오시티 (중동)20210331<NA><NA><NA><NA>영업/정상영업397359.716406649186807.81129899520210331103454숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>3<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>22737<NA><NA><NA>0<NA><NA><NA>300<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-03-01 05:09:05
85721302933800003380000-214-2021-0000403_11_03_PU2022-01-19 02:40:00.0숙박업위더스오션613805부산광역시 수영구 광안동 201-1 광안 지웰에스테이트 더 테라스48303부산광역시 수영구 광남로94번길 16, 광안 지웰에스테이트 더 테라스 3~19층 301호 등 66개호 (광안동)20210406<NA><NA><NA><NA>영업/정상영업392691.625721388185474.22691274120220117142044숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>19030<NA><NA><NA>0<NA><NA><NA>700<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-03-01 05:09:05
85731303033300003330000-214-2021-0000303_11_03_PU2022-01-11 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504686720220109123120숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5010<NA><NA><NA>0<NA><NA><NA>82<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-03-01 05:09:05
8574130313280000CDFI226221202100000103_11_04_PU2022-01-06 02:40:00.0외국인관광도시민박업윤슬가지번우편번호부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.397605613179078.07581929720220104140052업태구분명전화번호1건물소유구분명단독주택건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4545.45양실수여성종사자수YoonSeulgaGuesthouse for Foreign Tourists욕실수위생업태명200000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주택가주변1일반주거지역01침대수한실수회수건조수02022-03-01 05:09:05
85751303233300003330000-214-2021-0000303_11_03_PU2022-01-11 02:40:00.0숙박업지비그리다612040부산광역시 해운대구 송정동 159-1248073부산광역시 해운대구 송정중앙로6번길 94 (송정동)20210416<NA><NA><NA><NA>영업/정상영업400247.814972824188971.38504686720220109123120숙박업(생활)<NA><NA><NA><NA>50<NA><NA><NA><NA>1<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5010<NA><NA><NA>0<NA><NA><NA>82<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-03-01 05:09:05
8576130333280000CDFI226221202100000103_11_04_PU2022-01-06 02:40:00.0외국인관광도시민박업윤슬가지번우편번호부산광역시 영도구 청학동 398-1549031부산광역시 영도구 청학서로16번길 43-16 (청학동)20210415폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.397605613179078.07581929720220104140052업태구분명전화번호1건물소유구분명단독주택건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4545.45양실수여성종사자수YoonSeulgaGuesthouse for Foreign Tourists욕실수위생업태명200000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주택가주변1일반주거지역01침대수한실수회수건조수02022-03-01 05:09:05
8577130413330000CDFI226221201500002603_11_04_PI2021-05-26 00:22:56.0외국인관광도시민박업미포유<NA>부산광역시 해운대구 중동 946-1<NA>부산광역시 해운대구 달맞이길62번길 9-1 (중동)20150813<NA><NA><NA><NA>영업/정상영업중397758.722800944186726.05991974820210524093757<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2022-03-01 05:09:05
85781304233800003380000-214-2021-0000603_11_03_PU2021-06-27 02:40:00.0숙박업제이스테이 펜트하우스613805부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210526<NA><NA><NA><NA>영업/정상영업392732.161638137185542.45270223420210625155820숙박업(생활)<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>5050<NA><NA><NA>0<NA><NA><NA>40<NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-03-01 05:09:05
8579130433380000CDFI226003202100000303_11_01_PU2021-06-24 02:40:00.0관광숙박업제이스테이 펜트하우스지번우편번호부산광역시 수영구 광안동 200-448303부산광역시 수영구 광안해변로 179, 5층 (광안동)20210525폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392732.161638137185542.45270223420210622151628업태구분명전화번호4건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명관광숙박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수219218.85양실수여성종사자수영문상호명영문상호주소욕실수위생업태명125000000제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수지역구분명지하층수총층수침대수한실수회수건조수회의실별동시수용인원2022-03-01 05:09:05

Duplicate rows

Most frequently occurring

opnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrdcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmlastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
363330000CDFI226003201800000503_11_01_PU2019-04-14 02:40:00.0관광숙박업일로이리조트<NA>부산광역시 해운대구 송정동 809번지48073부산광역시 해운대구 송정구덕포길 130 (송정동)<NA><NA><NA><NA>영업/정상영업중20190412092534<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>관광숙박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>599598.73<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4주거지역<NA>4<NA><NA><NA><NA>2022-03-01 05:09:046
53250000CDFI226221201900000103_11_04_PU2021-05-05 02:40:00.0외국인관광도시민박업보수동방공호지번우편번호부산광역시 중구 보수동1가 116-15648967부산광역시 중구 책방골목길 13-11 (보수동1가)20210427휴업시작일자휴업종료일자재개업일자폐업폐업20210503101511업태구분명전화번호6건물소유구분명건물용도명건물지상층수건물지하층수건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역놀이시설수무대면적문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원선박척수선박총톤수세탁기수168167.82양실수여성종사자수영문상호명영문상호주소욕실수위생업태명자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자좌석수주변환경명지상층수일반상업지역지하층수3침대수한실수회수건조수회의실별동시수용인원2022-03-01 05:09:043
63250000CDFI226221201900000203_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/정상영업중20201031173301<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3838.18<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2022-03-01 05:09:043
1032700003270000-201-2019-0000303_11_03_PU2021-06-20 02:40:00.0숙박업대구여관601829부산광역시 동구 초량동 388-2 지하1층, 지상1~3층, 4층 일부48815부산광역시 동구 중앙대로221번길 14-5 (초량동)<NA><NA><NA><NA>영업/정상영업20210618100954여관업051 467 5401<NA>자가<NA>41<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4111<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>060<NA>2022-03-01 05:09:043
1132700003270000-201-2019-0000503_11_03_PU2022-01-14 02:40:00.0숙박업단테하우스601829부산광역시 동구 초량동 39948816부산광역시 동구 초량로13번길 58 (초량동)<NA><NA><NA><NA>영업/정상영업20220112091015여관업<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4010<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-03-01 05:09:043
143280000CDFI226221202000000103_11_04_PU2021-10-21 02:40:00.0외국인관광도시민박업오션하우스<NA>부산광역시 영도구 동삼동 1124 함지그린아파트49119부산광역시 영도구 함지로 8, 106동 1904호 (동삼동, 함지그린아파트)<NA><NA><NA><NA>영업/정상영업중20211019153414<NA><NA>2<NA>아파트<NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>00<NA>4645.5<NA><NA><NA>ocean houseGuesthouse for Foreign Tourists<NA><NA><NA>10000000<NA><NA><NA><NA>0아파트지역20일반주거지역220<NA><NA><NA>02022-03-01 05:09:043
153280000CDFI226221202000000203_11_04_PU2021-10-21 02:40:00.0외국인관광도시민박업에메랄드 오션뷰지번우편번호부산광역시 영도구 동삼동 1124 함지그린아파트49119부산광역시 영도구 함지로 8, 106동 1902호 (동삼동, 함지그린아파트)폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중20211019153331업태구분명전화번호1건물소유구분명아파트건물지상층수건물지하층수0기념품종류기획여행보험시작일자기획여행보험종료일자남성종사자수놀이기구수내역00문화사업자구분명외국인관광 도시민박업보험기관명보험시작일자보험종료일자부대시설내역사용끝지상층사용끝지하층사용시작지상층사용시작지하층선박제원00세탁기수4645.5양실수여성종사자수Emerald ocean viewGuesthouse for Foreign Tourists욕실수위생업태명0제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0아파트지역20주거지역220침대수한실수회수건조수02022-03-01 05:09:043
163280000CDFI226221202000000303_11_04_PU2021-11-26 02:40:00.0외국인관광도시민박업청학소담<NA>부산광역시 영도구 청학동 398-2049031부산광역시 영도구 청학서로16번길 43-14 (청학동)<NA><NA><NA><NA>영업/정상영업중20211124114259<NA><NA>1<NA>단독주택<NA><NA>0<NA><NA><NA><NA><NA>0<NA>0<NA>외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>00<NA>8080.1<NA><NA><NA>CheonghakSodamGuesthouse for Foreign Tourists<NA><NA><NA>200000000<NA><NA><NA><NA>0주택가주변0일반주거지역01<NA><NA><NA>02022-03-01 05:09:053
2232900003290000-201-2019-0000203_11_03_PU2020-12-15 02:40:00.0숙박업엑스모텔614846부산광역시 부산진구 부전동 226-547296부산광역시 부산진구 신천대로50번길 34, 6층~9층 (부전동)<NA><NA><NA><NA>영업/정상영업20201212162712일반호텔051 803 6996<NA><NA><NA>102<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9060<NA><NA><NA>0<NA><NA><NA>290<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-03-01 05:09:043
2332900003290000-201-2020-0000103_11_03_PU2020-12-15 02:40:00.0숙박업지지배614849부산광역시 부산진구 부전동 417-2547258부산광역시 부산진구 부전로 99-1, 3층 (부전동)<NA><NA><NA><NA>영업/정상영업20201212135845여관업051 806 7779<NA>자가<NA>41<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA>3<NA><NA><NA><NA>0<NA><NA><NA>60<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2022-03-01 05:09:043