Overview

Dataset statistics

Number of variables81
Number of observations10000
Missing cells88847
Missing cells (%)11.0%
Duplicate rows561
Duplicate rows (%)5.6%
Total size in memory6.3 MiB
Average record size in memory657.0 B

Variable types

Unsupported3
Text20
Categorical56
DateTime1
Numeric1

Alerts

Dataset has 561 (5.6%) duplicate rowsDuplicates
opnsvcid is highly imbalanced (61.8%)Imbalance
updategbn is highly imbalanced (79.0%)Imbalance
clgstdt is highly imbalanced (93.5%)Imbalance
clgenddt is highly imbalanced (93.5%)Imbalance
ropnymd is highly imbalanced (84.7%)Imbalance
trdstatenm is highly imbalanced (50.2%)Imbalance
dtlstatenm is highly imbalanced (54.5%)Imbalance
bdngownsenm is highly imbalanced (51.9%)Imbalance
bdngsrvnm is highly imbalanced (81.0%)Imbalance
bdngunderflrcnt is highly imbalanced (55.0%)Imbalance
svnsr is highly imbalanced (84.7%)Imbalance
plninsurstdt is highly imbalanced (84.7%)Imbalance
plninsurenddt is highly imbalanced (84.7%)Imbalance
maneipcnt is highly imbalanced (76.2%)Imbalance
playutscntdtl is highly imbalanced (84.7%)Imbalance
playfacilcnt is highly imbalanced (83.8%)Imbalance
multusnupsoyn is highly imbalanced (89.8%)Imbalance
stagear is highly imbalanced (84.7%)Imbalance
culwrkrsenm is highly imbalanced (84.7%)Imbalance
culphyedcobnm is highly imbalanced (61.5%)Imbalance
geicpfacilen is highly imbalanced (84.7%)Imbalance
balhansilyn is highly imbalanced (90.4%)Imbalance
bcfacilen is highly imbalanced (84.7%)Imbalance
insurstdt is highly imbalanced (84.7%)Imbalance
insurenddt is highly imbalanced (84.7%)Imbalance
afc is highly imbalanced (84.7%)Imbalance
useunderendflr is highly imbalanced (61.6%)Imbalance
useunderstflr is highly imbalanced (58.3%)Imbalance
shpinfo is highly imbalanced (84.7%)Imbalance
shpcnt is highly imbalanced (84.7%)Imbalance
shptottons is highly imbalanced (87.7%)Imbalance
infoben is highly imbalanced (84.7%)Imbalance
wmeipcnt is highly imbalanced (74.5%)Imbalance
yoksilcnt is highly imbalanced (75.4%)Imbalance
dispenen is highly imbalanced (84.7%)Imbalance
mnfactreartclcn is highly imbalanced (84.7%)Imbalance
cndpermstymd is highly imbalanced (93.0%)Imbalance
cndpermntwhy is highly imbalanced (92.1%)Imbalance
cndpermendymd is highly imbalanced (93.0%)Imbalance
chaircnt is highly imbalanced (65.0%)Imbalance
nearenvnm is highly imbalanced (81.2%)Imbalance
jisgnumlay is highly imbalanced (83.9%)Imbalance
regnsenm is highly imbalanced (77.7%)Imbalance
undernumlay is highly imbalanced (85.6%)Imbalance
totnumlay is highly imbalanced (83.1%)Imbalance
abedcnt is highly imbalanced (51.2%)Imbalance
meetsamtimesygstf is highly imbalanced (84.7%)Imbalance
sitepostno has 1867 (18.7%) missing valuesMissing
rdnwhladdr has 2106 (21.1%) missing valuesMissing
dcbymd has 6582 (65.8%) missing valuesMissing
x has 462 (4.6%) missing valuesMissing
y has 466 (4.7%) missing valuesMissing
sitetel has 329 (3.3%) missing valuesMissing
stroomcnt has 9235 (92.3%) missing valuesMissing
cnstyarea has 9478 (94.8%) missing valuesMissing
insurorgnm has 9308 (93.1%) missing valuesMissing
facilscp has 8156 (81.6%) missing valuesMissing
facilar has 8156 (81.6%) missing valuesMissing
yangsilcnt has 2345 (23.4%) missing valuesMissing
engstntrnmnm has 9164 (91.6%) missing valuesMissing
engstntrnmaddr has 9166 (91.7%) missing valuesMissing
capt has 9191 (91.9%) missing valuesMissing
hanshilcnt has 2794 (27.9%) missing valuesMissing
skey is an unsupported type, check if it needs cleaning or further analysisUnsupported
opnsfteamcode is an unsupported type, check if it needs cleaning or further analysisUnsupported
rdnpostno is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 16:37:46.288802
Analysis finished2024-04-16 16:37:49.754082
Duration3.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size156.2 KiB

opnsfteamcode
Unsupported

REJECTED  UNSUPPORTED 

Missing4
Missing (%)< 0.1%
Memory size156.2 KiB

mgtno
Text

Distinct5548
Distinct (%)55.5%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-17T01:37:49.884506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.579032
Min length20

Characters and Unicode

Total characters215704
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

Unique2602 ?
Unique (%)26.0%

Sample

1st row3290000-201-2001-00621
2nd row3390000-201-2001-00051
3rd row3290000-201-1977-02426
4th row3270000-201-1968-00014
5th row4270000-201-2019-00001
ValueCountFrequency (%)
cdfi2262132019000001 69
 
0.7%
cdfi2262132020000001 66
 
0.7%
cdfi2262212019000001 63
 
0.6%
cdfi2260032019000001 62
 
0.6%
cdfi2262212020000001 61
 
0.6%
cdfi2260032020000001 58
 
0.6%
cdfi2262132019000002 44
 
0.4%
cdfi3261132019000001 42
 
0.4%
cdfi2262212019000003 40
 
0.4%
cdfi2262142019000001 37
 
0.4%
Other values (5538) 9454
94.6%
2024-04-17T01:37:50.184969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 83170
38.6%
2 28290
 
13.1%
- 23676
 
11.0%
1 22868
 
10.6%
3 16613
 
7.7%
9 10122
 
4.7%
6 5295
 
2.5%
4 4991
 
2.3%
8 4664
 
2.2%
7 4187
 
1.9%
Other values (5) 11828
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 183612
85.1%
Dash Punctuation 23676
 
11.0%
Uppercase Letter 8416
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 83170
45.3%
2 28290
 
15.4%
1 22868
 
12.5%
3 16613
 
9.0%
9 10122
 
5.5%
6 5295
 
2.9%
4 4991
 
2.7%
8 4664
 
2.5%
7 4187
 
2.3%
5 3412
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
C 2104
25.0%
D 2104
25.0%
F 2104
25.0%
I 2104
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 23676
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 207288
96.1%
Latin 8416
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 83170
40.1%
2 28290
 
13.6%
- 23676
 
11.4%
1 22868
 
11.0%
3 16613
 
8.0%
9 10122
 
4.9%
6 5295
 
2.6%
4 4991
 
2.4%
8 4664
 
2.3%
7 4187
 
2.0%
Latin
ValueCountFrequency (%)
C 2104
25.0%
D 2104
25.0%
F 2104
25.0%
I 2104
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 215704
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 83170
38.6%
2 28290
 
13.1%
- 23676
 
11.0%
1 22868
 
10.6%
3 16613
 
7.7%
9 10122
 
4.7%
6 5295
 
2.5%
4 4991
 
2.3%
8 4664
 
2.2%
7 4187
 
1.9%
Other values (5) 11828
 
5.5%

opnsvcid
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
03_11_03_P
7891 
03_11_04_P
923 
03_11_07_P
 
376
03_11_01_P
 
344
03_11_06_P
 
224
Other values (4)
 
242

Length

Max length10
Median length10
Mean length9.9974
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 7891
78.9%
03_11_04_P 923
 
9.2%
03_11_07_P 376
 
3.8%
03_11_01_P 344
 
3.4%
03_11_06_P 224
 
2.2%
03_11_02_P 142
 
1.4%
03_11_05_P 95
 
0.9%
<NA> 4
 
< 0.1%
opnSvcId 1
 
< 0.1%

Length

2024-04-17T01:37:50.314734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:50.413603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 7891
78.9%
03_11_04_p 923
 
9.2%
03_11_07_p 376
 
3.8%
03_11_01_p 344
 
3.4%
03_11_06_p 224
 
2.2%
03_11_02_p 142
 
1.4%
03_11_05_p 95
 
0.9%
na 4
 
< 0.1%
opnsvcid 1
 
< 0.1%

updategbn
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
8956 
U
1039 
<NA>
 
2
180000000
 
2
u
 
1

Length

Max length9
Median length1
Mean length1.0022
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 8956
89.6%
U 1039
 
10.4%
<NA> 2
 
< 0.1%
180000000 2
 
< 0.1%
u 1
 
< 0.1%

Length

2024-04-17T01:37:50.528320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:50.618522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 8956
89.6%
u 1040
 
10.4%
na 2
 
< 0.1%
180000000 2
 
< 0.1%
Distinct870
Distinct (%)8.7%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-03 02:40:00
2024-04-17T01:37:50.710804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T01:37:50.851749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6395 
숙박업
1653 
외국인관광도시민박업
777 
일반야영장업
 
376
관광숙박업
 
344
Other values (4)
 
455

Length

Max length10
Median length4
Mean length4.4741
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6395
63.9%
숙박업 1653
 
16.5%
외국인관광도시민박업 777
 
7.8%
일반야영장업 376
 
3.8%
관광숙박업 344
 
3.4%
한옥체험업 224
 
2.2%
관광펜션업 141
 
1.4%
자동차야영장업 89
 
0.9%
opnSvcNm 1
 
< 0.1%

Length

2024-04-17T01:37:50.985934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:51.087902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6395
63.9%
숙박업 1653
 
16.5%
외국인관광도시민박업 777
 
7.8%
일반야영장업 376
 
3.8%
관광숙박업 344
 
3.4%
한옥체험업 224
 
2.2%
관광펜션업 141
 
1.4%
자동차야영장업 89
 
0.9%
opnsvcnm 1
 
< 0.1%

bplcnm
Text

Distinct5585
Distinct (%)55.9%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-17T01:37:51.369743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length35
Mean length5.8661465
Min length1

Characters and Unicode

Total characters58638
Distinct characters841
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2932 ?
Unique (%)29.3%

Sample

1st rowV(브이)모텔
2nd row동산여인숙
3rd row이화장
4th row본역여인숙
5th row(주)다움 수피움
ValueCountFrequency (%)
호텔 263
 
2.1%
게스트하우스 167
 
1.3%
모텔 146
 
1.1%
house 145
 
1.1%
하우스 80
 
0.6%
여관 67
 
0.5%
펜션 60
 
0.5%
호스텔 60
 
0.5%
hotel 55
 
0.4%
캠핑장 54
 
0.4%
Other values (5918) 11718
91.4%
2024-04-17T01:37:51.789281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2983
 
5.1%
2834
 
4.8%
2248
 
3.8%
1975
 
3.4%
1632
 
2.8%
1562
 
2.7%
1497
 
2.6%
1080
 
1.8%
1006
 
1.7%
988
 
1.7%
Other values (831) 40833
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47172
80.4%
Uppercase Letter 3210
 
5.5%
Lowercase Letter 2932
 
5.0%
Space Separator 2834
 
4.8%
Decimal Number 911
 
1.6%
Open Punctuation 662
 
1.1%
Close Punctuation 662
 
1.1%
Other Punctuation 165
 
0.3%
Dash Punctuation 57
 
0.1%
Letter Number 16
 
< 0.1%
Other values (5) 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2983
 
6.3%
2248
 
4.8%
1975
 
4.2%
1632
 
3.5%
1562
 
3.3%
1497
 
3.2%
1080
 
2.3%
1006
 
2.1%
988
 
2.1%
893
 
1.9%
Other values (743) 31308
66.4%
Lowercase Letter
ValueCountFrequency (%)
e 429
14.6%
o 363
12.4%
s 311
10.6%
u 249
8.5%
a 232
 
7.9%
n 182
 
6.2%
t 174
 
5.9%
h 152
 
5.2%
i 128
 
4.4%
l 122
 
4.2%
Other values (16) 590
20.1%
Uppercase Letter
ValueCountFrequency (%)
H 320
 
10.0%
O 281
 
8.8%
E 277
 
8.6%
S 237
 
7.4%
A 214
 
6.7%
T 208
 
6.5%
L 153
 
4.8%
U 147
 
4.6%
N 140
 
4.4%
B 137
 
4.3%
Other values (16) 1096
34.1%
Decimal Number
ValueCountFrequency (%)
1 196
21.5%
2 194
21.3%
3 94
10.3%
0 86
9.4%
7 77
 
8.5%
5 77
 
8.5%
9 61
 
6.7%
6 54
 
5.9%
4 44
 
4.8%
8 28
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 53
32.1%
' 48
29.1%
& 45
27.3%
: 5
 
3.0%
, 5
 
3.0%
; 3
 
1.8%
# 2
 
1.2%
2
 
1.2%
· 1
 
0.6%
@ 1
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 659
99.5%
2
 
0.3%
[ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 659
99.5%
2
 
0.3%
] 1
 
0.2%
Letter Number
ValueCountFrequency (%)
11
68.8%
5
31.2%
Math Symbol
ValueCountFrequency (%)
+ 5
83.3%
1
 
16.7%
Space Separator
ValueCountFrequency (%)
2834
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Other Symbol
ValueCountFrequency (%)
5
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47155
80.4%
Latin 6158
 
10.5%
Common 5303
 
9.0%
Han 22
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2983
 
6.3%
2248
 
4.8%
1975
 
4.2%
1632
 
3.5%
1562
 
3.3%
1497
 
3.2%
1080
 
2.3%
1006
 
2.1%
988
 
2.1%
893
 
1.9%
Other values (729) 31291
66.4%
Latin
ValueCountFrequency (%)
e 429
 
7.0%
o 363
 
5.9%
H 320
 
5.2%
s 311
 
5.1%
O 281
 
4.6%
E 277
 
4.5%
u 249
 
4.0%
S 237
 
3.8%
a 232
 
3.8%
A 214
 
3.5%
Other values (44) 3245
52.7%
Common
ValueCountFrequency (%)
2834
53.4%
( 659
 
12.4%
) 659
 
12.4%
1 196
 
3.7%
2 194
 
3.7%
3 94
 
1.8%
0 86
 
1.6%
7 77
 
1.5%
5 77
 
1.5%
9 61
 
1.2%
Other values (23) 366
 
6.9%
Han
ValueCountFrequency (%)
3
13.6%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (5) 5
22.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47150
80.4%
ASCII 11436
 
19.5%
CJK 21
 
< 0.1%
Number Forms 16
 
< 0.1%
None 13
 
< 0.1%
Punctuation 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2983
 
6.3%
2248
 
4.8%
1975
 
4.2%
1632
 
3.5%
1562
 
3.3%
1497
 
3.2%
1080
 
2.3%
1006
 
2.1%
988
 
2.1%
893
 
1.9%
Other values (728) 31286
66.4%
ASCII
ValueCountFrequency (%)
2834
24.8%
( 659
 
5.8%
) 659
 
5.8%
e 429
 
3.8%
o 363
 
3.2%
H 320
 
2.8%
s 311
 
2.7%
O 281
 
2.5%
E 277
 
2.4%
u 249
 
2.2%
Other values (69) 5054
44.2%
Number Forms
ValueCountFrequency (%)
11
68.8%
5
31.2%
None
ValueCountFrequency (%)
5
38.5%
2
 
15.4%
2
 
15.4%
2
 
15.4%
· 1
 
7.7%
1
 
7.7%
CJK
ValueCountFrequency (%)
3
14.3%
2
9.5%
2
9.5%
2
9.5%
2
9.5%
2
9.5%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
Other values (4) 4
19.0%
Punctuation
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

sitepostno
Text

MISSING 

Distinct1188
Distinct (%)14.6%
Missing1867
Missing (%)18.7%
Memory size156.2 KiB
2024-04-17T01:37:52.078638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.0004918
Min length6

Characters and Unicode

Total characters48802
Distinct characters22
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique501 ?
Unique (%)6.2%

Sample

1st row614849
2nd row617807
3rd row614849
4th row601830
5th row230902
ValueCountFrequency (%)
612821 252
 
3.1%
지번우편번호 227
 
2.8%
616801 194
 
2.4%
612040 169
 
2.1%
612847 138
 
1.7%
607833 131
 
1.6%
601829 109
 
1.3%
617807 106
 
1.3%
613828 103
 
1.3%
607831 102
 
1.3%
Other values (1178) 6602
81.2%
2024-04-17T01:37:52.490907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 8338
17.1%
0 7648
15.7%
8 7363
15.1%
1 7154
14.7%
2 4330
8.9%
4 3598
7.4%
7 2764
 
5.7%
3 2718
 
5.6%
9 1784
 
3.7%
5 1733
 
3.6%
Other values (12) 1372
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47430
97.2%
Other Letter 1362
 
2.8%
Lowercase Letter 8
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 8338
17.6%
0 7648
16.1%
8 7363
15.5%
1 7154
15.1%
2 4330
9.1%
4 3598
7.6%
7 2764
 
5.8%
3 2718
 
5.7%
9 1784
 
3.8%
5 1733
 
3.7%
Other Letter
ValueCountFrequency (%)
454
33.3%
227
16.7%
227
16.7%
227
16.7%
227
16.7%
Lowercase Letter
ValueCountFrequency (%)
s 2
25.0%
t 2
25.0%
o 2
25.0%
i 1
12.5%
e 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
N 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47430
97.2%
Hangul 1362
 
2.8%
Latin 10
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
6 8338
17.6%
0 7648
16.1%
8 7363
15.5%
1 7154
15.1%
2 4330
9.1%
4 3598
7.6%
7 2764
 
5.8%
3 2718
 
5.7%
9 1784
 
3.8%
5 1733
 
3.7%
Latin
ValueCountFrequency (%)
s 2
20.0%
t 2
20.0%
o 2
20.0%
i 1
10.0%
e 1
10.0%
P 1
10.0%
N 1
10.0%
Hangul
ValueCountFrequency (%)
454
33.3%
227
16.7%
227
16.7%
227
16.7%
227
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47440
97.2%
Hangul 1362
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 8338
17.6%
0 7648
16.1%
8 7363
15.5%
1 7154
15.1%
2 4330
9.1%
4 3598
7.6%
7 2764
 
5.8%
3 2718
 
5.7%
9 1784
 
3.8%
5 1733
 
3.7%
Other values (7) 10
 
< 0.1%
Hangul
ValueCountFrequency (%)
454
33.3%
227
16.7%
227
16.7%
227
16.7%
227
16.7%
Distinct6244
Distinct (%)62.5%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-17T01:37:52.800431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length71
Mean length24.030215
Min length11

Characters and Unicode

Total characters240182
Distinct characters542
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3225 ?
Unique (%)32.3%

Sample

1st row부산광역시 부산진구 부전동 398-2번지
2nd row부산광역시 사상구 괘법동 545-12번지
3rd row부산광역시 부산진구 부전동 402-2번지
4th row부산광역시 동구 초량동 564-0번지
5th row강원도 영월군 상동읍 내덕리 산 10번지 숯치유센터
ValueCountFrequency (%)
부산광역시 6622
 
14.8%
해운대구 889
 
2.0%
부산진구 817
 
1.8%
서울특별시 707
 
1.6%
동래구 701
 
1.6%
t통b반 682
 
1.5%
중구 569
 
1.3%
사상구 551
 
1.2%
동구 534
 
1.2%
북구 519
 
1.2%
Other values (8385) 32235
71.9%
2024-04-17T01:37:53.248533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44406
 
18.5%
10112
 
4.2%
1 9954
 
4.1%
9403
 
3.9%
9208
 
3.8%
9046
 
3.8%
- 8964
 
3.7%
8529
 
3.6%
8233
 
3.4%
8184
 
3.4%
Other values (532) 114143
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137681
57.3%
Decimal Number 46535
 
19.4%
Space Separator 44406
 
18.5%
Dash Punctuation 8964
 
3.7%
Uppercase Letter 1523
 
0.6%
Other Punctuation 428
 
0.2%
Math Symbol 232
 
0.1%
Open Punctuation 150
 
0.1%
Close Punctuation 150
 
0.1%
Lowercase Letter 110
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10112
 
7.3%
9403
 
6.8%
9208
 
6.7%
9046
 
6.6%
8529
 
6.2%
8233
 
6.0%
8184
 
5.9%
7372
 
5.4%
6993
 
5.1%
2765
 
2.0%
Other values (470) 57836
42.0%
Uppercase Letter
ValueCountFrequency (%)
B 705
46.3%
T 688
45.2%
C 21
 
1.4%
A 18
 
1.2%
O 11
 
0.7%
K 10
 
0.7%
S 9
 
0.6%
E 8
 
0.5%
R 7
 
0.5%
L 7
 
0.5%
Other values (11) 39
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
e 16
14.5%
l 11
10.0%
n 10
9.1%
i 9
8.2%
o 9
8.2%
t 9
8.2%
h 8
7.3%
u 8
7.3%
d 7
 
6.4%
a 5
 
4.5%
Other values (8) 18
16.4%
Decimal Number
ValueCountFrequency (%)
1 9954
21.4%
2 6211
13.3%
3 5171
11.1%
4 4646
10.0%
5 4286
9.2%
0 3589
 
7.7%
6 3571
 
7.7%
7 3331
 
7.2%
8 2991
 
6.4%
9 2785
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 384
89.7%
25
 
5.8%
. 13
 
3.0%
& 6
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 149
99.3%
[ 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 149
99.3%
] 1
 
0.7%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
44406
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8964
100.0%
Math Symbol
ValueCountFrequency (%)
~ 232
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137679
57.3%
Common 100865
42.0%
Latin 1636
 
0.7%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10112
 
7.3%
9403
 
6.8%
9208
 
6.7%
9046
 
6.6%
8529
 
6.2%
8233
 
6.0%
8184
 
5.9%
7372
 
5.4%
6993
 
5.1%
2765
 
2.0%
Other values (469) 57834
42.0%
Latin
ValueCountFrequency (%)
B 705
43.1%
T 688
42.1%
C 21
 
1.3%
A 18
 
1.1%
e 16
 
1.0%
O 11
 
0.7%
l 11
 
0.7%
K 10
 
0.6%
n 10
 
0.6%
i 9
 
0.6%
Other values (31) 137
 
8.4%
Common
ValueCountFrequency (%)
44406
44.0%
1 9954
 
9.9%
- 8964
 
8.9%
2 6211
 
6.2%
3 5171
 
5.1%
4 4646
 
4.6%
5 4286
 
4.2%
0 3589
 
3.6%
6 3571
 
3.5%
7 3331
 
3.3%
Other values (11) 6736
 
6.7%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137679
57.3%
ASCII 102473
42.7%
None 25
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44406
43.3%
1 9954
 
9.7%
- 8964
 
8.7%
2 6211
 
6.1%
3 5171
 
5.0%
4 4646
 
4.5%
5 4286
 
4.2%
0 3589
 
3.5%
6 3571
 
3.5%
7 3331
 
3.3%
Other values (49) 8344
 
8.1%
Hangul
ValueCountFrequency (%)
10112
 
7.3%
9403
 
6.8%
9208
 
6.7%
9046
 
6.6%
8529
 
6.2%
8233
 
6.0%
8184
 
5.9%
7372
 
5.4%
6993
 
5.1%
2765
 
2.0%
Other values (469) 57834
42.0%
None
ValueCountFrequency (%)
25
100.0%
CJK
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%

rdnpostno
Unsupported

REJECTED  UNSUPPORTED 

Missing17
Missing (%)0.2%
Memory size156.2 KiB

rdnwhladdr
Text

MISSING 

Distinct5210
Distinct (%)66.0%
Missing2106
Missing (%)21.1%
Memory size156.2 KiB
2024-04-17T01:37:53.556228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length71
Mean length28.03395
Min length1

Characters and Unicode

Total characters221300
Distinct characters618
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2949 ?
Unique (%)37.4%

Sample

1st row부산광역시 부산진구 서면문화로 30-8 (부전동)
2nd row부산광역시 사상구 광장로87번길 13 (괘법동)
3rd row부산광역시 부산진구 새싹로29번길 10-7 (부전동)
4th row부산광역시 동구 대영로243번길 52 (초량동)
5th row강원도 영월군 상동읍 선바위길 94, 숯치유센터
ValueCountFrequency (%)
부산광역시 4632
 
10.8%
해운대구 716
 
1.7%
서울특별시 707
 
1.6%
부산진구 557
 
1.3%
중구 500
 
1.2%
동래구 473
 
1.1%
경기도 464
 
1.1%
사상구 417
 
1.0%
동구 401
 
0.9%
강원도 390
 
0.9%
Other values (6897) 33791
78.5%
2024-04-17T01:37:53.989220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35155
 
15.9%
8651
 
3.9%
1 8444
 
3.8%
7284
 
3.3%
6818
 
3.1%
( 6436
 
2.9%
) 6436
 
2.9%
6335
 
2.9%
6309
 
2.9%
2 5995
 
2.7%
Other values (608) 123437
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 129430
58.5%
Decimal Number 36930
 
16.7%
Space Separator 35155
 
15.9%
Open Punctuation 6439
 
2.9%
Close Punctuation 6439
 
2.9%
Other Punctuation 3137
 
1.4%
Dash Punctuation 2904
 
1.3%
Math Symbol 502
 
0.2%
Uppercase Letter 245
 
0.1%
Lowercase Letter 115
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8651
 
6.7%
7284
 
5.6%
6818
 
5.3%
6335
 
4.9%
6309
 
4.9%
5934
 
4.6%
5652
 
4.4%
5226
 
4.0%
4995
 
3.9%
3429
 
2.6%
Other values (541) 68797
53.2%
Uppercase Letter
ValueCountFrequency (%)
A 48
19.6%
B 43
17.6%
C 29
11.8%
O 13
 
5.3%
K 13
 
5.3%
E 12
 
4.9%
D 10
 
4.1%
S 10
 
4.1%
L 8
 
3.3%
G 7
 
2.9%
Other values (12) 52
21.2%
Lowercase Letter
ValueCountFrequency (%)
e 17
14.8%
n 11
9.6%
l 11
9.6%
u 9
7.8%
o 9
7.8%
d 8
 
7.0%
i 8
 
7.0%
h 8
 
7.0%
t 8
 
7.0%
a 5
 
4.3%
Other values (9) 21
18.3%
Decimal Number
ValueCountFrequency (%)
1 8444
22.9%
2 5995
16.2%
3 4233
11.5%
4 3204
 
8.7%
5 2815
 
7.6%
0 2785
 
7.5%
6 2595
 
7.0%
7 2469
 
6.7%
9 2247
 
6.1%
8 2143
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 3060
97.5%
32
 
1.0%
: 21
 
0.7%
. 15
 
0.5%
& 6
 
0.2%
* 2
 
0.1%
/ 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 6436
> 99.9%
[ 3
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 6436
> 99.9%
] 3
 
< 0.1%
Letter Number
ValueCountFrequency (%)
2
50.0%
2
50.0%
Space Separator
ValueCountFrequency (%)
35155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2904
100.0%
Math Symbol
ValueCountFrequency (%)
~ 502
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 129428
58.5%
Common 91506
41.3%
Latin 364
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8651
 
6.7%
7284
 
5.6%
6818
 
5.3%
6335
 
4.9%
6309
 
4.9%
5934
 
4.6%
5652
 
4.4%
5226
 
4.0%
4995
 
3.9%
3429
 
2.6%
Other values (540) 68795
53.2%
Latin
ValueCountFrequency (%)
A 48
 
13.2%
B 43
 
11.8%
C 29
 
8.0%
e 17
 
4.7%
O 13
 
3.6%
K 13
 
3.6%
E 12
 
3.3%
n 11
 
3.0%
l 11
 
3.0%
D 10
 
2.7%
Other values (33) 157
43.1%
Common
ValueCountFrequency (%)
35155
38.4%
1 8444
 
9.2%
( 6436
 
7.0%
) 6436
 
7.0%
2 5995
 
6.6%
3 4233
 
4.6%
4 3204
 
3.5%
, 3060
 
3.3%
- 2904
 
3.2%
5 2815
 
3.1%
Other values (14) 12824
 
14.0%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 129428
58.5%
ASCII 91834
41.5%
None 32
 
< 0.1%
Number Forms 4
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35155
38.3%
1 8444
 
9.2%
( 6436
 
7.0%
) 6436
 
7.0%
2 5995
 
6.5%
3 4233
 
4.6%
4 3204
 
3.5%
, 3060
 
3.3%
- 2904
 
3.2%
5 2815
 
3.1%
Other values (54) 13152
 
14.3%
Hangul
ValueCountFrequency (%)
8651
 
6.7%
7284
 
5.6%
6818
 
5.3%
6335
 
4.9%
6309
 
4.9%
5934
 
4.6%
5652
 
4.4%
5226
 
4.0%
4995
 
3.9%
3429
 
2.6%
Other values (540) 68795
53.2%
None
ValueCountFrequency (%)
32
100.0%
CJK
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
2
50.0%
2
50.0%
Distinct3623
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T01:37:54.279312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.999
Min length4

Characters and Unicode

Total characters79990
Distinct characters28
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique949 ?
Unique (%)9.5%

Sample

1st row20010801
2nd row19801122
3rd row19771201
4th row19680109
5th row20190215
ValueCountFrequency (%)
20190705 29
 
0.3%
20191213 26
 
0.3%
20200403 25
 
0.2%
20190712 25
 
0.2%
20190927 25
 
0.2%
20191227 25
 
0.2%
20181207 24
 
0.2%
20190614 24
 
0.2%
20190329 24
 
0.2%
20190531 24
 
0.2%
Other values (3613) 9749
97.5%
2024-04-17T01:37:54.692366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20574
25.7%
1 17354
21.7%
2 13773
17.2%
9 9157
11.4%
8 4579
 
5.7%
7 4031
 
5.0%
3 3032
 
3.8%
6 2681
 
3.4%
4 2467
 
3.1%
5 2312
 
2.9%
Other values (18) 30
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79960
> 99.9%
Other Letter 20
 
< 0.1%
Lowercase Letter 8
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20574
25.7%
1 17354
21.7%
2 13773
17.2%
9 9157
11.5%
8 4579
 
5.7%
7 4031
 
5.0%
3 3032
 
3.8%
6 2681
 
3.4%
4 2467
 
3.1%
5 2312
 
2.9%
Other Letter
ValueCountFrequency (%)
4
20.0%
4
20.0%
3
15.0%
3
15.0%
2
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
m 2
25.0%
a 1
12.5%
p 1
12.5%
v 1
12.5%
e 1
12.5%
r 1
12.5%
d 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
Y 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79960
> 99.9%
Hangul 20
 
< 0.1%
Latin 10
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20574
25.7%
1 17354
21.7%
2 13773
17.2%
9 9157
11.5%
8 4579
 
5.7%
7 4031
 
5.0%
3 3032
 
3.8%
6 2681
 
3.4%
4 2467
 
3.1%
5 2312
 
2.9%
Hangul
ValueCountFrequency (%)
4
20.0%
4
20.0%
3
15.0%
3
15.0%
2
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Latin
ValueCountFrequency (%)
m 2
20.0%
a 1
10.0%
p 1
10.0%
v 1
10.0%
P 1
10.0%
e 1
10.0%
r 1
10.0%
Y 1
10.0%
d 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79970
> 99.9%
Hangul 20
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20574
25.7%
1 17354
21.7%
2 13773
17.2%
9 9157
11.5%
8 4579
 
5.7%
7 4031
 
5.0%
3 3032
 
3.8%
6 2681
 
3.4%
4 2467
 
3.1%
5 2312
 
2.9%
Other values (9) 10
 
< 0.1%
Hangul
ValueCountFrequency (%)
4
20.0%
4
20.0%
3
15.0%
3
15.0%
2
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%

dcbymd
Text

MISSING 

Distinct1316
Distinct (%)38.5%
Missing6582
Missing (%)65.8%
Memory size156.2 KiB
2024-04-17T01:37:54.952971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.533938
Min length1

Characters and Unicode

Total characters25751
Distinct characters19
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique403 ?
Unique (%)11.8%

Sample

1st row20150702
2nd row20041022
3rd row19940926
4th row20161019
5th row폐업일자
ValueCountFrequency (%)
폐업일자 396
 
11.6%
20041022 138
 
4.0%
20030122 50
 
1.5%
20120711 41
 
1.2%
20021024 29
 
0.8%
20030305 19
 
0.6%
20051117 16
 
0.5%
20030227 16
 
0.5%
20030101 15
 
0.4%
20030123 14
 
0.4%
Other values (1306) 2684
78.5%
2024-04-17T01:37:55.345373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8165
31.7%
2 5127
19.9%
1 4369
17.0%
9 1121
 
4.4%
3 1078
 
4.2%
7 940
 
3.7%
4 885
 
3.4%
6 859
 
3.3%
5 857
 
3.3%
8 760
 
3.0%
Other values (9) 1590
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24161
93.8%
Other Letter 1584
 
6.2%
Lowercase Letter 5
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8165
33.8%
2 5127
21.2%
1 4369
18.1%
9 1121
 
4.6%
3 1078
 
4.5%
7 940
 
3.9%
4 885
 
3.7%
6 859
 
3.6%
5 857
 
3.5%
8 760
 
3.1%
Other Letter
ValueCountFrequency (%)
396
25.0%
396
25.0%
396
25.0%
396
25.0%
Lowercase Letter
ValueCountFrequency (%)
d 2
40.0%
c 1
20.0%
b 1
20.0%
m 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
Y 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24161
93.8%
Hangul 1584
 
6.2%
Latin 6
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8165
33.8%
2 5127
21.2%
1 4369
18.1%
9 1121
 
4.6%
3 1078
 
4.5%
7 940
 
3.9%
4 885
 
3.7%
6 859
 
3.6%
5 857
 
3.5%
8 760
 
3.1%
Latin
ValueCountFrequency (%)
d 2
33.3%
c 1
16.7%
b 1
16.7%
Y 1
16.7%
m 1
16.7%
Hangul
ValueCountFrequency (%)
396
25.0%
396
25.0%
396
25.0%
396
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24167
93.8%
Hangul 1584
 
6.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8165
33.8%
2 5127
21.2%
1 4369
18.1%
9 1121
 
4.6%
3 1078
 
4.5%
7 940
 
3.9%
4 885
 
3.7%
6 859
 
3.6%
5 857
 
3.5%
8 760
 
3.1%
Other values (5) 6
 
< 0.1%
Hangul
ValueCountFrequency (%)
396
25.0%
396
25.0%
396
25.0%
396
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9586 
휴업시작일자
 
398
20200806
 
2
20160608
 
1
20200825
 
1
Other values (12)
 
12

Length

Max length8
Median length4
Mean length4.0845
Min length1

Unique

Unique14 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9586
95.9%
휴업시작일자 398
 
4.0%
20200806 2
 
< 0.1%
20160608 1
 
< 0.1%
20200825 1
 
< 0.1%
20170413 1
 
< 0.1%
clgStdt 1
 
< 0.1%
20160425 1
 
< 0.1%
2 1
 
< 0.1%
20200123 1
 
< 0.1%
Other values (7) 7
 
0.1%

Length

2024-04-17T01:37:55.466949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9586
95.9%
휴업시작일자 398
 
4.0%
20200806 2
 
< 0.1%
20191101 1
 
< 0.1%
20200301 1
 
< 0.1%
20201201 1
 
< 0.1%
20201001 1
 
< 0.1%
20180719 1
 
< 0.1%
1 1
 
< 0.1%
2 1
 
< 0.1%
Other values (7) 7
 
0.1%

clgenddt
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9588 
휴업종료일자
 
398
20211231
 
1
20210206
 
1
20190501
 
1
Other values (11)
 
11

Length

Max length8
Median length4
Mean length4.0852
Min length4

Unique

Unique14 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9588
95.9%
휴업종료일자 398
 
4.0%
20211231 1
 
< 0.1%
20210206 1
 
< 0.1%
20190501 1
 
< 0.1%
clgEnddt 1
 
< 0.1%
20180424 1
 
< 0.1%
20201101 1
 
< 0.1%
20170607 1
 
< 0.1%
20210430 1
 
< 0.1%
Other values (6) 6
 
0.1%

Length

2024-04-17T01:37:55.586189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9588
95.9%
휴업종료일자 398
 
4.0%
20211231 1
 
< 0.1%
20210206 1
 
< 0.1%
20190501 1
 
< 0.1%
clgenddt 1
 
< 0.1%
20180424 1
 
< 0.1%
20201101 1
 
< 0.1%
20170607 1
 
< 0.1%
20210430 1
 
< 0.1%
Other values (6) 6
 
0.1%

ropnymd
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
재개업일자
 
398
ropnYmd
 
1

Length

Max length7
Median length4
Mean length4.0401
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> 9601
96.0%
재개업일자 398
 
4.0%
ropnYmd 1
 
< 0.1%

Length

2024-04-17T01:37:55.696331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:56.008574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
재개업일자 398
 
4.0%
ropnymd 1
 
< 0.1%

trdstatenm
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업/정상
3476 
01
3335 
02
2907 
13
 
104
폐업
 
73
Other values (7)
 
105

Length

Max length14
Median length2
Mean length3.0566
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 3476
34.8%
01 3335
33.4%
02 2907
29.1%
13 104
 
1.0%
폐업 73
 
0.7%
03 44
 
0.4%
<NA> 43
 
0.4%
휴업 9
 
0.1%
영업상태 4
 
< 0.1%
취소/말소/만료/정지/중지 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2024-04-17T01:37:56.090834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영업/정상 3476
34.8%
01 3335
33.4%
02 2907
29.1%
13 104
 
1.0%
폐업 73
 
0.7%
03 44
 
0.4%
na 43
 
0.4%
휴업 9
 
0.1%
영업상태 4
 
< 0.1%
취소/말소/만료/정지/중지 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업
4959 
폐업
3020 
영업중
1998 
휴업
 
13
<NA>
 
4
Other values (5)
 
6

Length

Max length10
Median length2
Mean length2.2026
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4959
49.6%
폐업 3020
30.2%
영업중 1998
20.0%
휴업 13
 
0.1%
<NA> 4
 
< 0.1%
등록취소 2
 
< 0.1%
직권말소 1
 
< 0.1%
dtlStateNm 1
 
< 0.1%
?????? 1
 
< 0.1%
지정취소 1
 
< 0.1%

Length

2024-04-17T01:37:56.200211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:56.299556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4959
49.6%
폐업 3020
30.2%
영업중 1998
20.0%
휴업 13
 
0.1%
na 4
 
< 0.1%
등록취소 2
 
< 0.1%
직권말소 1
 
< 0.1%
dtlstatenm 1
 
< 0.1%
?????? 1
 
< 0.1%
지정취소 1
 
< 0.1%

x
Text

MISSING 

Distinct5889
Distinct (%)61.7%
Missing462
Missing (%)4.6%
Memory size156.2 KiB
2024-04-17T01:37:56.509340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.958062
Min length1

Characters and Unicode

Total characters190360
Distinct characters22
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2949 ?
Unique (%)30.9%

Sample

1st row387384.16195800000
2nd row380916.26538200000
3rd row387365.40938900000
4th row385844.32781200000
5th row360583
ValueCountFrequency (%)
좌표정보(x 29
 
0.3%
393521.998603867 12
 
0.1%
397447.054868 11
 
0.1%
414007.31124689 10
 
0.1%
397816.16252117 9
 
0.1%
388014.370428964 9
 
0.1%
269061.383127 8
 
0.1%
382472.003431 8
 
0.1%
397287.76503000000 7
 
0.1%
205271.275273064 7
 
0.1%
Other values (5880) 9432
98.8%
2024-04-17T01:37:56.863418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37954
19.9%
0 31710
16.7%
3 16786
8.8%
8 14779
 
7.8%
9 12919
 
6.8%
1 11715
 
6.2%
7 11096
 
5.8%
6 11075
 
5.8%
2 11047
 
5.8%
4 10953
 
5.8%
Other values (12) 20326
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 142706
75.0%
Space Separator 37954
 
19.9%
Other Punctuation 9485
 
5.0%
Other Letter 116
 
0.1%
Close Punctuation 29
 
< 0.1%
Uppercase Letter 29
 
< 0.1%
Open Punctuation 29
 
< 0.1%
Dash Punctuation 11
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31710
22.2%
3 16786
11.8%
8 14779
10.4%
9 12919
9.1%
1 11715
 
8.2%
7 11096
 
7.8%
6 11075
 
7.8%
2 11047
 
7.7%
4 10953
 
7.7%
5 10626
 
7.4%
Other Letter
ValueCountFrequency (%)
29
25.0%
29
25.0%
29
25.0%
29
25.0%
Other Punctuation
ValueCountFrequency (%)
. 9477
99.9%
: 8
 
0.1%
Space Separator
ValueCountFrequency (%)
37954
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 190214
99.9%
Hangul 116
 
0.1%
Latin 30
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
37954
20.0%
0 31710
16.7%
3 16786
8.8%
8 14779
 
7.8%
9 12919
 
6.8%
1 11715
 
6.2%
7 11096
 
5.8%
6 11075
 
5.8%
2 11047
 
5.8%
4 10953
 
5.8%
Other values (6) 20180
10.6%
Hangul
ValueCountFrequency (%)
29
25.0%
29
25.0%
29
25.0%
29
25.0%
Latin
ValueCountFrequency (%)
X 29
96.7%
x 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 190244
99.9%
Hangul 116
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37954
20.0%
0 31710
16.7%
3 16786
8.8%
8 14779
 
7.8%
9 12919
 
6.8%
1 11715
 
6.2%
7 11096
 
5.8%
6 11075
 
5.8%
2 11047
 
5.8%
4 10953
 
5.8%
Other values (8) 20210
10.6%
Hangul
ValueCountFrequency (%)
29
25.0%
29
25.0%
29
25.0%
29
25.0%

y
Text

MISSING 

Distinct5888
Distinct (%)61.8%
Missing466
Missing (%)4.7%
Memory size156.2 KiB
2024-04-17T01:37:57.079479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.958464
Min length1

Characters and Unicode

Total characters190284
Distinct characters22
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2949 ?
Unique (%)30.9%

Sample

1st row186756.31881800000
2nd row186993.18035300000
3rd row186836.54127200000
4th row181681.83686200000
5th row405735
ValueCountFrequency (%)
좌표정보(y 29
 
0.3%
185933.100965604 12
 
0.1%
187092.852201 11
 
0.1%
306334.983198896 10
 
0.1%
176595.034934652 9
 
0.1%
259272.14964063 9
 
0.1%
192327.468209 8
 
0.1%
135486.237452 8
 
0.1%
408011.516423623 7
 
0.1%
187269.85401300000 7
 
0.1%
Other values (5878) 9424
98.8%
2024-04-17T01:37:57.385024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37812
19.9%
0 31402
16.5%
1 17273
9.1%
8 14229
 
7.5%
9 12511
 
6.6%
4 12170
 
6.4%
7 11445
 
6.0%
2 11133
 
5.9%
3 10972
 
5.8%
6 10825
 
5.7%
Other values (12) 20512
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 142673
75.0%
Space Separator 37812
 
19.9%
Other Punctuation 9477
 
5.0%
Other Letter 116
 
0.1%
Dash Punctuation 104
 
0.1%
Close Punctuation 43
 
< 0.1%
Uppercase Letter 29
 
< 0.1%
Open Punctuation 29
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31402
22.0%
1 17273
12.1%
8 14229
10.0%
9 12511
 
8.8%
4 12170
 
8.5%
7 11445
 
8.0%
2 11133
 
7.8%
3 10972
 
7.7%
6 10825
 
7.6%
5 10713
 
7.5%
Other Letter
ValueCountFrequency (%)
29
25.0%
29
25.0%
29
25.0%
29
25.0%
Close Punctuation
ValueCountFrequency (%)
) 29
67.4%
] 14
32.6%
Space Separator
ValueCountFrequency (%)
37812
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9477
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Lowercase Letter
ValueCountFrequency (%)
y 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 190138
99.9%
Hangul 116
 
0.1%
Latin 30
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
37812
19.9%
0 31402
16.5%
1 17273
9.1%
8 14229
 
7.5%
9 12511
 
6.6%
4 12170
 
6.4%
7 11445
 
6.0%
2 11133
 
5.9%
3 10972
 
5.8%
6 10825
 
5.7%
Other values (6) 20366
10.7%
Hangul
ValueCountFrequency (%)
29
25.0%
29
25.0%
29
25.0%
29
25.0%
Latin
ValueCountFrequency (%)
Y 29
96.7%
y 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 190168
99.9%
Hangul 116
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37812
19.9%
0 31402
16.5%
1 17273
9.1%
8 14229
 
7.5%
9 12511
 
6.6%
4 12170
 
6.4%
7 11445
 
6.0%
2 11133
 
5.9%
3 10972
 
5.8%
6 10825
 
5.7%
Other values (8) 20396
10.7%
Hangul
ValueCountFrequency (%)
29
25.0%
29
25.0%
29
25.0%
29
25.0%

lastmodts
Real number (ℝ)

Distinct6057
Distinct (%)60.6%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.0151976 × 1013
Minimum1.9990211 × 1013
Maximum2.0210101 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T01:37:57.517904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990211 × 1013
5-th percentile2.0021022 × 1013
Q12.0141021 × 1013
median2.0180501 × 1013
Q32.0190621 × 1013
95-th percentile2.0200929 × 1013
Maximum2.0210101 × 1013
Range2.1989015 × 1011
Interquartile range (IQR)4.9599712 × 1010

Descriptive statistics

Standard deviation6.1594436 × 1010
Coefficient of variation (CV)0.0030564961
Kurtosis0.40404523
Mean2.0151976 × 1013
Median Absolute Deviation (MAD)1.0292982 × 1010
Skewness-1.3953272
Sum2.0143915 × 1017
Variance3.7938746 × 1021
MonotonicityNot monotonic
2024-04-17T01:37:57.637293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19990428000000 49
 
0.5%
19990920000000 47
 
0.5%
20040902000000 47
 
0.5%
20030122000000 46
 
0.5%
20040203000000 41
 
0.4%
20070531000000 28
 
0.3%
20030414000000 27
 
0.3%
19990308000000 26
 
0.3%
20040427000000 26
 
0.3%
20030329000000 25
 
0.2%
Other values (6047) 9634
96.3%
ValueCountFrequency (%)
19990211000000 2
 
< 0.1%
19990218000000 13
0.1%
19990223000000 2
 
< 0.1%
19990225000000 4
 
< 0.1%
19990302000000 3
 
< 0.1%
19990303000000 11
0.1%
19990308000000 26
0.3%
19990309000000 4
 
< 0.1%
19990310000000 2
 
< 0.1%
19990315000000 2
 
< 0.1%
ValueCountFrequency (%)
20210101150205 2
< 0.1%
20201231172220 1
< 0.1%
20201231164730 1
< 0.1%
20201231153518 1
< 0.1%
20201231151448 1
< 0.1%
20201231150759 1
< 0.1%
20201231114928 1
< 0.1%
20201231111548 1
< 0.1%
20201230174952 1
< 0.1%
20201230164543 1
< 0.1%

uptaenm
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
여관업
4333 
<NA>
1883 
숙박업(생활)
1193 
여인숙업
858 
숙박업 기타
642 
Other values (5)
1091 

Length

Max length8
Median length7
Mean length4.0831
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row여관업
2nd row여인숙업
3rd row여관업
4th row여인숙업
5th row숙박업 기타

Common Values

ValueCountFrequency (%)
여관업 4333
43.3%
<NA> 1883
18.8%
숙박업(생활) 1193
 
11.9%
여인숙업 858
 
8.6%
숙박업 기타 642
 
6.4%
일반호텔 522
 
5.2%
관광호텔 324
 
3.2%
업태구분명 226
 
2.3%
휴양콘도미니엄업 18
 
0.2%
uptaeNm 1
 
< 0.1%

Length

2024-04-17T01:37:57.750888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:57.856376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 4333
40.7%
na 1883
17.7%
숙박업(생활 1193
 
11.2%
여인숙업 858
 
8.1%
숙박업 642
 
6.0%
기타 642
 
6.0%
일반호텔 522
 
4.9%
관광호텔 324
 
3.0%
업태구분명 226
 
2.1%
휴양콘도미니엄업 18
 
0.2%

sitetel
Text

MISSING 

Distinct124
Distinct (%)1.3%
Missing329
Missing (%)3.3%
Memory size156.2 KiB
2024-04-17T01:37:58.028564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.963706
Min length4

Characters and Unicode

Total characters115701
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

Unique98 ?
Unique (%)1.0%

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 9481
96.2%
전화번호 38
 
0.4%
051 16
 
0.2%
061 12
 
0.1%
033 12
 
0.1%
041 9
 
0.1%
052 8
 
0.1%
055 7
 
0.1%
032 7
 
0.1%
054 6
 
0.1%
Other values (185) 263
 
2.7%
2024-04-17T01:37:58.270443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 28598
24.7%
3 19133
16.5%
2 19100
16.5%
- 19033
16.5%
0 9831
 
8.5%
5 9646
 
8.3%
4 9585
 
8.3%
189
 
0.2%
6 128
 
0.1%
7 115
 
0.1%
Other values (6) 343
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96327
83.3%
Dash Punctuation 19033
 
16.5%
Space Separator 189
 
0.2%
Other Letter 152
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 28598
29.7%
3 19133
19.9%
2 19100
19.8%
0 9831
 
10.2%
5 9646
 
10.0%
4 9585
 
10.0%
6 128
 
0.1%
7 115
 
0.1%
9 101
 
0.1%
8 90
 
0.1%
Other Letter
ValueCountFrequency (%)
38
25.0%
38
25.0%
38
25.0%
38
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 19033
100.0%
Space Separator
ValueCountFrequency (%)
189
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 115549
99.9%
Hangul 152
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 28598
24.7%
3 19133
16.6%
2 19100
16.5%
- 19033
16.5%
0 9831
 
8.5%
5 9646
 
8.3%
4 9585
 
8.3%
189
 
0.2%
6 128
 
0.1%
7 115
 
0.1%
Other values (2) 191
 
0.2%
Hangul
ValueCountFrequency (%)
38
25.0%
38
25.0%
38
25.0%
38
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 115549
99.9%
Hangul 152
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 28598
24.7%
3 19133
16.6%
2 19100
16.5%
- 19033
16.5%
0 9831
 
8.5%
5 9646
 
8.3%
4 9585
 
8.3%
189
 
0.2%
6 128
 
0.1%
7 115
 
0.1%
Other values (2) 191
 
0.2%
Hangul
ValueCountFrequency (%)
38
25.0%
38
25.0%
38
25.0%
38
25.0%

stroomcnt
Text

MISSING 

Distinct63
Distinct (%)8.2%
Missing9235
Missing (%)92.3%
Memory size156.2 KiB
2024-04-17T01:37:58.436023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length2.1058824
Min length1

Characters and Unicode

Total characters1611
Distinct characters20
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)4.3%

Sample

1st row객실수
2nd row객실수
3rd row객실수
4th row객실수
5th row2
ValueCountFrequency (%)
객실수 361
47.2%
1 122
 
15.9%
2 104
 
13.6%
3 32
 
4.2%
5 14
 
1.8%
4 13
 
1.7%
7 8
 
1.0%
8 8
 
1.0%
33 5
 
0.7%
49 5
 
0.7%
Other values (53) 93
 
12.2%
2024-04-17T01:37:58.732294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
361
22.4%
361
22.4%
361
22.4%
1 162
10.1%
2 129
 
8.0%
3 65
 
4.0%
4 43
 
2.7%
5 31
 
1.9%
0 30
 
1.9%
8 17
 
1.1%
Other values (10) 51
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1083
67.2%
Decimal Number 519
32.2%
Lowercase Letter 8
 
0.5%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 162
31.2%
2 129
24.9%
3 65
12.5%
4 43
 
8.3%
5 31
 
6.0%
0 30
 
5.8%
8 17
 
3.3%
9 16
 
3.1%
7 15
 
2.9%
6 11
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
t 2
25.0%
o 2
25.0%
s 1
12.5%
r 1
12.5%
m 1
12.5%
n 1
12.5%
Other Letter
ValueCountFrequency (%)
361
33.3%
361
33.3%
361
33.3%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1083
67.2%
Common 519
32.2%
Latin 9
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 162
31.2%
2 129
24.9%
3 65
12.5%
4 43
 
8.3%
5 31
 
6.0%
0 30
 
5.8%
8 17
 
3.3%
9 16
 
3.1%
7 15
 
2.9%
6 11
 
2.1%
Latin
ValueCountFrequency (%)
t 2
22.2%
o 2
22.2%
s 1
11.1%
r 1
11.1%
m 1
11.1%
C 1
11.1%
n 1
11.1%
Hangul
ValueCountFrequency (%)
361
33.3%
361
33.3%
361
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1083
67.2%
ASCII 528
32.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
361
33.3%
361
33.3%
361
33.3%
ASCII
ValueCountFrequency (%)
1 162
30.7%
2 129
24.4%
3 65
12.3%
4 43
 
8.1%
5 31
 
5.9%
0 30
 
5.7%
8 17
 
3.2%
9 16
 
3.0%
7 15
 
2.8%
6 11
 
2.1%
Other values (7) 9
 
1.7%

bdngownsenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7640 
자가
1332 
임대
 
696
건물소유구분명
 
331
bdngOwnSeNm
 
1

Length

Max length11
Median length4
Mean length3.6944
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7640
76.4%
자가 1332
 
13.3%
임대 696
 
7.0%
건물소유구분명 331
 
3.3%
bdngOwnSeNm 1
 
< 0.1%

Length

2024-04-17T01:37:58.840548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:37:58.938068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7640
76.4%
자가 1332
 
13.3%
임대 696
 
7.0%
건물소유구분명 331
 
3.3%
bdngownsenm 1
 
< 0.1%

bdngsrvnm
Categorical

IMBALANCE 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8869 
건물용도명
 
298
단독주택
 
287
숙박시설
 
214
아파트
 
76
Other values (16)
 
256

Length

Max length15
Median length4
Mean length4.0806
Min length2

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8869
88.7%
건물용도명 298
 
3.0%
단독주택 287
 
2.9%
숙박시설 214
 
2.1%
아파트 76
 
0.8%
기타 62
 
0.6%
다가구용 주택(공동주택적용) 62
 
0.6%
호텔 46
 
0.5%
근린생활시설 31
 
0.3%
다세대주택 17
 
0.2%
Other values (11) 38
 
0.4%

Length

2024-04-17T01:37:59.055111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8869
88.1%
건물용도명 298
 
3.0%
단독주택 287
 
2.9%
숙박시설 214
 
2.1%
아파트 76
 
0.8%
기타 62
 
0.6%
다가구용 62
 
0.6%
주택(공동주택적용 62
 
0.6%
호텔 46
 
0.5%
근린생활시설 31
 
0.3%
Other values (12) 55
 
0.5%

bdngjisgflrcnt
Categorical

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
2937 
0
2555 
3
800 
4
799 
2
577 
Other values (35)
2332 

Length

Max length10
Median length1
Mean length2.0336
Min length1

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row2
3rd row3
4th row0
5th row2

Common Values

ValueCountFrequency (%)
<NA> 2937
29.4%
0 2555
25.6%
3 800
 
8.0%
4 799
 
8.0%
2 577
 
5.8%
5 542
 
5.4%
6 280
 
2.8%
8 270
 
2.7%
7 267
 
2.7%
건물지상층수 230
 
2.3%
Other values (30) 743
 
7.4%

Length

2024-04-17T01:37:59.188796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2937
29.4%
0 2555
25.6%
3 800
 
8.0%
4 799
 
8.0%
2 577
 
5.8%
5 542
 
5.4%
6 280
 
2.8%
8 270
 
2.7%
7 267
 
2.7%
건물지상층수 230
 
2.3%
Other values (30) 743
 
7.4%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
4660 
<NA>
3405 
1
1357 
건물지하층수
 
230
2
 
198
Other values (11)
 
150

Length

Max length10
Median length1
Mean length2.1386
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4660
46.6%
<NA> 3405
34.1%
1 1357
 
13.6%
건물지하층수 230
 
2.3%
2 198
 
2.0%
3 47
 
0.5%
4 43
 
0.4%
5 22
 
0.2%
8 9
 
0.1%
6 8
 
0.1%
Other values (6) 21
 
0.2%

Length

2024-04-17T01:37:59.285885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 4660
46.6%
na 3405
34.1%
1 1359
 
13.6%
건물지하층수 230
 
2.3%
2 198
 
2.0%
3 47
 
0.5%
4 43
 
0.4%
5 22
 
0.2%
8 9
 
0.1%
6 8
 
0.1%
Other values (5) 19
 
0.2%

cnstyarea
Text

MISSING 

Distinct106
Distinct (%)20.3%
Missing9478
Missing (%)94.8%
Memory size156.2 KiB
2024-04-17T01:37:59.501237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.5344828
Min length2

Characters and Unicode

Total characters2367
Distinct characters23
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)15.3%

Sample

1st row건축연면적
2nd row건축연면적
3rd row건축연면적
4th row건축연면적
5th row건축연면적
ValueCountFrequency (%)
건축연면적 382
73.2%
184 3
 
0.6%
1400 3
 
0.6%
248 3
 
0.6%
1844 3
 
0.6%
83 3
 
0.6%
421 3
 
0.6%
2282 3
 
0.6%
75 3
 
0.6%
105 3
 
0.6%
Other values (96) 113
 
21.6%
2024-04-17T01:37:59.832187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
382
16.1%
382
16.1%
382
16.1%
382
16.1%
382
16.1%
1 80
 
3.4%
2 71
 
3.0%
4 47
 
2.0%
0 46
 
1.9%
8 44
 
1.9%
Other values (13) 169
7.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1910
80.7%
Decimal Number 448
 
18.9%
Lowercase Letter 8
 
0.3%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 80
17.9%
2 71
15.8%
4 47
10.5%
0 46
10.3%
8 44
9.8%
3 39
8.7%
9 36
8.0%
7 31
 
6.9%
5 27
 
6.0%
6 27
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
25.0%
c 1
12.5%
n 1
12.5%
s 1
12.5%
t 1
12.5%
r 1
12.5%
e 1
12.5%
Other Letter
ValueCountFrequency (%)
382
20.0%
382
20.0%
382
20.0%
382
20.0%
382
20.0%
Uppercase Letter
ValueCountFrequency (%)
Y 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1910
80.7%
Common 448
 
18.9%
Latin 9
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 80
17.9%
2 71
15.8%
4 47
10.5%
0 46
10.3%
8 44
9.8%
3 39
8.7%
9 36
8.0%
7 31
 
6.9%
5 27
 
6.0%
6 27
 
6.0%
Latin
ValueCountFrequency (%)
a 2
22.2%
c 1
11.1%
n 1
11.1%
s 1
11.1%
t 1
11.1%
Y 1
11.1%
r 1
11.1%
e 1
11.1%
Hangul
ValueCountFrequency (%)
382
20.0%
382
20.0%
382
20.0%
382
20.0%
382
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1910
80.7%
ASCII 457
 
19.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
382
20.0%
382
20.0%
382
20.0%
382
20.0%
382
20.0%
ASCII
ValueCountFrequency (%)
1 80
17.5%
2 71
15.5%
4 47
10.3%
0 46
10.1%
8 44
9.6%
3 39
8.5%
9 36
7.9%
7 31
 
6.8%
5 27
 
5.9%
6 27
 
5.9%
Other values (8) 9
 
2.0%

svnsr
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
기념품종류
 
398
svnSr
 
1

Length

Max length5
Median length4
Mean length4.0399
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> 9601
96.0%
기념품종류 398
 
4.0%
svnSr 1
 
< 0.1%

Length

2024-04-17T01:37:59.955650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:00.045963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
기념품종류 398
 
4.0%
svnsr 1
 
< 0.1%

plninsurstdt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
기획여행보험시작일자
 
398
plnInsurStdt
 
1

Length

Max length12
Median length4
Mean length4.2396
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> 9601
96.0%
기획여행보험시작일자 398
 
4.0%
plnInsurStdt 1
 
< 0.1%

Length

2024-04-17T01:38:00.149839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:00.251247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
기획여행보험시작일자 398
 
4.0%
plninsurstdt 1
 
< 0.1%

plninsurenddt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
기획여행보험종료일자
 
398
plnInsurEnddt
 
1

Length

Max length13
Median length4
Mean length4.2397
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> 9601
96.0%
기획여행보험종료일자 398
 
4.0%
plnInsurEnddt 1
 
< 0.1%

Length

2024-04-17T01:38:00.342911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:00.425003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
기획여행보험종료일자 398
 
4.0%
plninsurenddt 1
 
< 0.1%

maneipcnt
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7964 
0
1656 
남성종사자수
 
232
1
 
111
2
 
12
Other values (10)
 
25

Length

Max length9
Median length4
Mean length3.5066
Min length1

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7964
79.6%
0 1656
 
16.6%
남성종사자수 232
 
2.3%
1 111
 
1.1%
2 12
 
0.1%
5 6
 
0.1%
3 5
 
0.1%
4 5
 
0.1%
10 3
 
< 0.1%
8 1
 
< 0.1%
Other values (5) 5
 
0.1%

Length

2024-04-17T01:38:00.525685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7964
79.6%
0 1656
 
16.6%
남성종사자수 232
 
2.3%
1 111
 
1.1%
2 12
 
0.1%
5 6
 
0.1%
3 5
 
< 0.1%
4 5
 
< 0.1%
10 3
 
< 0.1%
8 1
 
< 0.1%
Other values (5) 5
 
< 0.1%

playutscntdtl
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
놀이기구수내역
 
398
playUtsCntDtl
 
1

Length

Max length13
Median length4
Mean length4.1203
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> 9601
96.0%
놀이기구수내역 398
 
4.0%
playUtsCntDtl 1
 
< 0.1%

Length

2024-04-17T01:38:00.644240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:00.725305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
놀이기구수내역 398
 
4.0%
playutscntdtl 1
 
< 0.1%

playfacilcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
N
9479 
<NA>
 
460
놀이시설수
 
59
Y
 
2

Length

Max length5
Median length1
Mean length1.1616
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 9479
94.8%
<NA> 460
 
4.6%
놀이시설수 59
 
0.6%
Y 2
 
< 0.1%

Length

2024-04-17T01:38:00.816740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:00.916513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 9479
94.8%
na 460
 
4.6%
놀이시설수 59
 
0.6%
y 2
 
< 0.1%

multusnupsoyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
N
9729 
<NA>
 
220
Y
 
27
 
24

Length

Max length4
Median length1
Mean length1.066
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 9729
97.3%
<NA> 220
 
2.2%
Y 27
 
0.3%
24
 
0.2%

Length

2024-04-17T01:38:01.025881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:01.118575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 9729
97.3%
na 220
 
2.2%
y 27
 
0.3%
24
 
0.2%

stagear
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
무대면적
 
398
stageAr
 
1

Length

Max length7
Median length4
Mean length4.0003
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> 9601
96.0%
무대면적 398
 
4.0%
stageAr 1
 
< 0.1%

Length

2024-04-17T01:38:01.211750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:01.312487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
무대면적 398
 
4.0%
stagear 1
 
< 0.1%

culwrkrsenm
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
문화사업자구분명
 
398
culWrkrSeNm
 
1

Length

Max length11
Median length4
Mean length4.1599
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> 9601
96.0%
문화사업자구분명 398
 
4.0%
culWrkrSeNm 1
 
< 0.1%

Length

2024-04-17T01:38:01.414800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:01.505077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
문화사업자구분명 398
 
4.0%
culwrkrsenm 1
 
< 0.1%

culphyedcobnm
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7727 
외국인관광 도시민박업
919 
일반야영장업
 
376
관광숙박업
 
344
한옥체험업
 
216
Other values (6)
 
418

Length

Max length14
Median length4
Mean length4.8735
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7727
77.3%
외국인관광 도시민박업 919
 
9.2%
일반야영장업 376
 
3.8%
관광숙박업 344
 
3.4%
한옥체험업 216
 
2.2%
문화체육업종명 172
 
1.7%
관광펜션업 142
 
1.4%
자동차야영장업 95
 
0.9%
한옥체험업(구) 7
 
0.1%
culPhyedCobNm 1
 
< 0.1%

Length

2024-04-17T01:38:01.614768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7727
70.8%
외국인관광 919
 
8.4%
도시민박업 919
 
8.4%
일반야영장업 376
 
3.4%
관광숙박업 344
 
3.2%
한옥체험업 216
 
2.0%
문화체육업종명 172
 
1.6%
관광펜션업 142
 
1.3%
자동차야영장업 95
 
0.9%
한옥체험업(구 7
 
0.1%
Other values (3) 3
 
< 0.1%

geicpfacilen
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
 
398
g
 
1

Length

Max length4
Median length4
Mean length3.8803
Min length1

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> 9601
96.0%
398
 
4.0%
g 1
 
< 0.1%

Length

2024-04-17T01:38:01.709266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:01.815319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
398
 
4.0%
g 1
 
< 0.1%

balhansilyn
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
N
9741 
<NA>
 
220
 
24
Y
 
15

Length

Max length4
Median length1
Mean length1.066
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 9741
97.4%
<NA> 220
 
2.2%
24
 
0.2%
Y 15
 
0.1%

Length

2024-04-17T01:38:01.908849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:02.001342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 9741
97.4%
na 220
 
2.2%
24
 
0.2%
y 15
 
0.1%

bcfacilen
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
 
398
b
 
1

Length

Max length4
Median length4
Mean length3.8803
Min length1

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> 9601
96.0%
398
 
4.0%
b 1
 
< 0.1%

Length

2024-04-17T01:38:02.105549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:02.190143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
398
 
4.0%
b 1
 
< 0.1%

insurorgnm
Text

MISSING 

Distinct89
Distinct (%)12.9%
Missing9308
Missing (%)93.1%
Memory size156.2 KiB
2024-04-17T01:38:02.390122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length5
Mean length5.8511561
Min length2

Characters and Unicode

Total characters4049
Distinct characters98
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)7.4%

Sample

1st row객실수/수용인원:2/5
2nd row2실(8명)
3rd row보험기관명
4th row보험기관명
5th row보험기관명
ValueCountFrequency (%)
보험기관명 379
52.9%
1실(4명 44
 
6.1%
2실(6명 23
 
3.2%
1실(2명 21
 
2.9%
1실(3명 17
 
2.4%
2실(8명 15
 
2.1%
2실(4명 13
 
1.8%
2실(5명 11
 
1.5%
현대해상화재보험 9
 
1.3%
객실 9
 
1.3%
Other values (86) 176
24.5%
2024-04-17T01:38:02.774414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
599
14.8%
436
10.8%
429
10.6%
379
9.4%
379
9.4%
246
 
6.1%
( 230
 
5.7%
) 230
 
5.7%
1 146
 
3.6%
2 136
 
3.4%
Other values (88) 839
20.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2984
73.7%
Decimal Number 521
 
12.9%
Open Punctuation 230
 
5.7%
Close Punctuation 230
 
5.7%
Other Punctuation 33
 
0.8%
Space Separator 25
 
0.6%
Uppercase Letter 18
 
0.4%
Lowercase Letter 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
599
20.1%
436
14.6%
429
14.4%
379
12.7%
379
12.7%
246
8.2%
42
 
1.4%
32
 
1.1%
30
 
1.0%
29
 
1.0%
Other values (59) 383
12.8%
Decimal Number
ValueCountFrequency (%)
1 146
28.0%
2 136
26.1%
4 76
14.6%
6 42
 
8.1%
3 41
 
7.9%
5 27
 
5.2%
8 27
 
5.2%
0 13
 
2.5%
7 10
 
1.9%
9 3
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
r 2
25.0%
i 1
12.5%
m 1
12.5%
g 1
12.5%
u 1
12.5%
s 1
12.5%
n 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
B 8
44.4%
K 5
27.8%
D 3
 
16.7%
N 1
 
5.6%
O 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/ 19
57.6%
: 9
27.3%
4
 
12.1%
, 1
 
3.0%
Open Punctuation
ValueCountFrequency (%)
( 230
100.0%
Close Punctuation
ValueCountFrequency (%)
) 230
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2984
73.7%
Common 1039
 
25.7%
Latin 26
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
599
20.1%
436
14.6%
429
14.4%
379
12.7%
379
12.7%
246
8.2%
42
 
1.4%
32
 
1.1%
30
 
1.0%
29
 
1.0%
Other values (59) 383
12.8%
Common
ValueCountFrequency (%)
( 230
22.1%
) 230
22.1%
1 146
14.1%
2 136
13.1%
4 76
 
7.3%
6 42
 
4.0%
3 41
 
3.9%
5 27
 
2.6%
8 27
 
2.6%
25
 
2.4%
Other values (7) 59
 
5.7%
Latin
ValueCountFrequency (%)
B 8
30.8%
K 5
19.2%
D 3
 
11.5%
r 2
 
7.7%
i 1
 
3.8%
m 1
 
3.8%
N 1
 
3.8%
g 1
 
3.8%
O 1
 
3.8%
u 1
 
3.8%
Other values (2) 2
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2984
73.7%
ASCII 1061
 
26.2%
None 4
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
599
20.1%
436
14.6%
429
14.4%
379
12.7%
379
12.7%
246
8.2%
42
 
1.4%
32
 
1.1%
30
 
1.0%
29
 
1.0%
Other values (59) 383
12.8%
ASCII
ValueCountFrequency (%)
( 230
21.7%
) 230
21.7%
1 146
13.8%
2 136
12.8%
4 76
 
7.2%
6 42
 
4.0%
3 41
 
3.9%
5 27
 
2.5%
8 27
 
2.5%
25
 
2.4%
Other values (18) 81
 
7.6%
None
ValueCountFrequency (%)
4
100.0%

insurstdt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
보험시작일자
 
398
insurStdt
 
1

Length

Max length9
Median length4
Mean length4.0801
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> 9601
96.0%
보험시작일자 398
 
4.0%
insurStdt 1
 
< 0.1%

Length

2024-04-17T01:38:02.903126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:02.988946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
보험시작일자 398
 
4.0%
insurstdt 1
 
< 0.1%

insurenddt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
보험종료일자
 
398
insurEnddt
 
1

Length

Max length10
Median length4
Mean length4.0802
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> 9601
96.0%
보험종료일자 398
 
4.0%
insurEnddt 1
 
< 0.1%

Length

2024-04-17T01:38:03.082911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:03.167832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
보험종료일자 398
 
4.0%
insurenddt 1
 
< 0.1%

afc
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
부대시설내역
 
398
afc
 
1

Length

Max length6
Median length4
Mean length4.0795
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9601
96.0%
부대시설내역 398
 
4.0%
afc 1
 
< 0.1%

Length

2024-04-17T01:38:03.272454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:03.354212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
부대시설내역 398
 
4.0%
afc 1
 
< 0.1%

usejisgendflr
Categorical

Distinct39
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
3968 
0
1714 
3
757 
4
730 
2
590 
Other values (34)
2241 

Length

Max length10
Median length1
Mean length2.363
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3968
39.7%
0 1714
17.1%
3 757
 
7.6%
4 730
 
7.3%
2 590
 
5.9%
5 436
 
4.4%
6 354
 
3.5%
사용끝지상층 267
 
2.7%
7 249
 
2.5%
8 225
 
2.2%
Other values (29) 710
 
7.1%

Length

2024-04-17T01:38:03.453350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3968
39.7%
0 1714
17.1%
3 757
 
7.6%
4 730
 
7.3%
2 590
 
5.9%
5 436
 
4.4%
6 354
 
3.5%
사용끝지상층 267
 
2.7%
7 249
 
2.5%
8 225
 
2.2%
Other values (29) 710
 
7.1%

useunderendflr
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5253 
0
4080 
사용끝지하층
 
371
1
 
233
2
 
33
Other values (7)
 
30

Length

Max length10
Median length4
Mean length2.7626
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5253
52.5%
0 4080
40.8%
사용끝지하층 371
 
3.7%
1 233
 
2.3%
2 33
 
0.3%
3 14
 
0.1%
4 7
 
0.1%
7 3
 
< 0.1%
10 2
 
< 0.1%
6 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2024-04-17T01:38:03.552807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5253
52.5%
0 4080
40.8%
사용끝지하층 371
 
3.7%
1 233
 
2.3%
2 33
 
0.3%
3 14
 
0.1%
4 7
 
0.1%
7 3
 
< 0.1%
10 2
 
< 0.1%
6 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

usejisgstflr
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
3273 
1
2232 
0
2076 
2
978 
3
478 
Other values (16)
963 

Length

Max length10
Median length1
Mean length2.1436
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row3
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3273
32.7%
1 2232
22.3%
0 2076
20.8%
2 978
 
9.8%
3 478
 
4.8%
4 277
 
2.8%
사용시작지상층 259
 
2.6%
5 175
 
1.8%
6 83
 
0.8%
7 63
 
0.6%
Other values (11) 106
 
1.1%

Length

2024-04-17T01:38:03.646993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3273
32.7%
1 2232
22.3%
0 2076
20.8%
2 978
 
9.8%
3 478
 
4.8%
4 277
 
2.8%
사용시작지상층 259
 
2.6%
5 175
 
1.8%
6 83
 
0.8%
7 63
 
0.6%
Other values (11) 106
 
1.1%

useunderstflr
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
4810 
<NA>
4489 
사용시작지하층
 
363
1
 
311
4
 
8
Other values (5)
 
19

Length

Max length10
Median length1
Mean length2.5654
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 4810
48.1%
<NA> 4489
44.9%
사용시작지하층 363
 
3.6%
1 311
 
3.1%
4 8
 
0.1%
2 7
 
0.1%
3 5
 
0.1%
6 4
 
< 0.1%
5 2
 
< 0.1%
useUnderSt 1
 
< 0.1%

Length

2024-04-17T01:38:03.746034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:04.114155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4810
48.1%
na 4489
44.9%
사용시작지하층 363
 
3.6%
1 311
 
3.1%
4 8
 
0.1%
2 7
 
0.1%
3 5
 
< 0.1%
6 4
 
< 0.1%
5 2
 
< 0.1%
useunderst 1
 
< 0.1%

shpinfo
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
선박제원
 
398
shpInfo
 
1

Length

Max length7
Median length4
Mean length4.0003
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> 9601
96.0%
선박제원 398
 
4.0%
shpInfo 1
 
< 0.1%

Length

2024-04-17T01:38:04.221169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:04.315287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
선박제원 398
 
4.0%
shpinfo 1
 
< 0.1%

shpcnt
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
선박척수
 
398
shpCnt
 
1

Length

Max length6
Median length4
Mean length4.0002
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> 9601
96.0%
선박척수 398
 
4.0%
shpCnt 1
 
< 0.1%

Length

2024-04-17T01:38:04.427109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:04.513830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
선박척수 398
 
4.0%
shpcnt 1
 
< 0.1%

shptottons
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9599 
선박총톤수
 
398
1
 
2
shpTotTons
 
1

Length

Max length10
Median length4
Mean length4.0398
Min length1

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> 9599
96.0%
선박총톤수 398
 
4.0%
1 2
 
< 0.1%
shpTotTons 1
 
< 0.1%

Length

2024-04-17T01:38:04.595001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:04.684318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9599
96.0%
선박총톤수 398
 
4.0%
1 2
 
< 0.1%
shptottons 1
 
< 0.1%

washmccnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5378 
<NA>
4391 
세탁기수
 
230
washmcCnt
 
1

Length

Max length9
Median length1
Mean length2.3871
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5378
53.8%
<NA> 4391
43.9%
세탁기수 230
 
2.3%
washmcCnt 1
 
< 0.1%

Length

2024-04-17T01:38:04.800691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:04.918190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5378
53.8%
na 4391
43.9%
세탁기수 230
 
2.3%
washmccnt 1
 
< 0.1%

facilscp
Text

MISSING 

Distinct602
Distinct (%)32.6%
Missing8156
Missing (%)81.6%
Memory size156.2 KiB
2024-04-17T01:38:05.227378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length2.9788503
Min length1

Characters and Unicode

Total characters5493
Distinct characters21
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique331 ?
Unique (%)18.0%

Sample

1st row95
2nd row93
3rd row71
4th row시설규모
5th row500
ValueCountFrequency (%)
시설규모 224
 
12.1%
85 29
 
1.6%
83 27
 
1.5%
60 22
 
1.2%
61 21
 
1.1%
59 19
 
1.0%
50 17
 
0.9%
65 17
 
0.9%
46 15
 
0.8%
49 15
 
0.8%
Other values (592) 1438
78.0%
2024-04-17T01:38:05.656683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 751
13.7%
5 483
8.8%
2 476
8.7%
4 474
8.6%
6 442
8.0%
3 436
7.9%
9 419
7.6%
8 403
7.3%
0 367
6.7%
7 338
 
6.2%
Other values (11) 904
16.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4589
83.5%
Other Letter 896
 
16.3%
Lowercase Letter 7
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 751
16.4%
5 483
10.5%
2 476
10.4%
4 474
10.3%
6 442
9.6%
3 436
9.5%
9 419
9.1%
8 403
8.8%
0 367
8.0%
7 338
7.4%
Lowercase Letter
ValueCountFrequency (%)
c 2
28.6%
f 1
14.3%
a 1
14.3%
i 1
14.3%
l 1
14.3%
p 1
14.3%
Other Letter
ValueCountFrequency (%)
224
25.0%
224
25.0%
224
25.0%
224
25.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4589
83.5%
Hangul 896
 
16.3%
Latin 8
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 751
16.4%
5 483
10.5%
2 476
10.4%
4 474
10.3%
6 442
9.6%
3 436
9.5%
9 419
9.1%
8 403
8.8%
0 367
8.0%
7 338
7.4%
Latin
ValueCountFrequency (%)
c 2
25.0%
f 1
12.5%
a 1
12.5%
i 1
12.5%
l 1
12.5%
S 1
12.5%
p 1
12.5%
Hangul
ValueCountFrequency (%)
224
25.0%
224
25.0%
224
25.0%
224
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4597
83.7%
Hangul 896
 
16.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 751
16.3%
5 483
10.5%
2 476
10.4%
4 474
10.3%
6 442
9.6%
3 436
9.5%
9 419
9.1%
8 403
8.8%
0 367
8.0%
7 338
7.4%
Other values (7) 8
 
0.2%
Hangul
ValueCountFrequency (%)
224
25.0%
224
25.0%
224
25.0%
224
25.0%

facilar
Text

MISSING 

Distinct1135
Distinct (%)61.6%
Missing8156
Missing (%)81.6%
Memory size156.2 KiB
2024-04-17T01:38:05.947811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.8492408
Min length1

Characters and Unicode

Total characters8942
Distinct characters22
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique841 ?
Unique (%)45.6%

Sample

1st row95.07
2nd row92.52
3rd row70.9
4th row시설면적
5th row499.87
ValueCountFrequency (%)
시설면적 224
 
12.1%
1544.48 6
 
0.3%
59.5 6
 
0.3%
74.74 6
 
0.3%
184.08 6
 
0.3%
598.73 5
 
0.3%
45.5 5
 
0.3%
70 5
 
0.3%
49.59 5
 
0.3%
58.5 5
 
0.3%
Other values (1125) 1571
85.2%
2024-04-17T01:38:06.391896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1221
13.7%
1 932
10.4%
4 776
8.7%
5 737
8.2%
2 728
8.1%
6 706
7.9%
8 684
7.6%
9 669
7.5%
3 612
6.8%
7 523
 
5.8%
Other values (12) 1354
15.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6818
76.2%
Other Punctuation 1221
 
13.7%
Other Letter 896
 
10.0%
Lowercase Letter 6
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 932
13.7%
4 776
11.4%
5 737
10.8%
2 728
10.7%
6 706
10.4%
8 684
10.0%
9 669
9.8%
3 612
9.0%
7 523
7.7%
0 451
6.6%
Lowercase Letter
ValueCountFrequency (%)
f 1
16.7%
a 1
16.7%
c 1
16.7%
i 1
16.7%
l 1
16.7%
r 1
16.7%
Other Letter
ValueCountFrequency (%)
224
25.0%
224
25.0%
224
25.0%
224
25.0%
Other Punctuation
ValueCountFrequency (%)
. 1221
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8039
89.9%
Hangul 896
 
10.0%
Latin 7
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1221
15.2%
1 932
11.6%
4 776
9.7%
5 737
9.2%
2 728
9.1%
6 706
8.8%
8 684
8.5%
9 669
8.3%
3 612
7.6%
7 523
6.5%
Latin
ValueCountFrequency (%)
f 1
14.3%
a 1
14.3%
c 1
14.3%
i 1
14.3%
l 1
14.3%
A 1
14.3%
r 1
14.3%
Hangul
ValueCountFrequency (%)
224
25.0%
224
25.0%
224
25.0%
224
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8046
90.0%
Hangul 896
 
10.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1221
15.2%
1 932
11.6%
4 776
9.6%
5 737
9.2%
2 728
9.0%
6 706
8.8%
8 684
8.5%
9 669
8.3%
3 612
7.6%
7 523
6.5%
Other values (8) 458
 
5.7%
Hangul
ValueCountFrequency (%)
224
25.0%
224
25.0%
224
25.0%
224
25.0%

infoben
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
 
398
i
 
1

Length

Max length4
Median length4
Mean length3.8803
Min length1

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> 9601
96.0%
398
 
4.0%
i 1
 
< 0.1%

Length

2024-04-17T01:38:06.511570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:06.610736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
398
 
4.0%
i 1
 
< 0.1%

yangsilcnt
Text

MISSING 

Distinct215
Distinct (%)2.8%
Missing2345
Missing (%)23.4%
Memory size156.2 KiB
2024-04-17T01:38:06.781368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length1.736904
Min length1

Characters and Unicode

Total characters13296
Distinct characters22
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)0.8%

Sample

1st row30
2nd row14
3rd row10
4th row0
5th row3
ValueCountFrequency (%)
0 1011
 
13.2%
10 377
 
4.9%
18 297
 
3.9%
12 281
 
3.7%
14 276
 
3.6%
15 259
 
3.4%
8 245
 
3.2%
양실수 230
 
3.0%
19 221
 
2.9%
13 205
 
2.7%
Other values (205) 4253
55.6%
2024-04-17T01:38:07.081328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3129
23.5%
0 1830
13.8%
2 1827
13.7%
3 1293
9.7%
4 1018
 
7.7%
5 812
 
6.1%
8 810
 
6.1%
6 644
 
4.8%
9 621
 
4.7%
7 612
 
4.6%
Other values (12) 700
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12596
94.7%
Other Letter 690
 
5.2%
Lowercase Letter 9
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3129
24.8%
0 1830
14.5%
2 1827
14.5%
3 1293
10.3%
4 1018
 
8.1%
5 812
 
6.4%
8 810
 
6.4%
6 644
 
5.1%
9 621
 
4.9%
7 612
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
n 2
22.2%
y 1
11.1%
a 1
11.1%
g 1
11.1%
s 1
11.1%
i 1
11.1%
l 1
11.1%
t 1
11.1%
Other Letter
ValueCountFrequency (%)
230
33.3%
230
33.3%
230
33.3%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12596
94.7%
Hangul 690
 
5.2%
Latin 10
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3129
24.8%
0 1830
14.5%
2 1827
14.5%
3 1293
10.3%
4 1018
 
8.1%
5 812
 
6.4%
8 810
 
6.4%
6 644
 
5.1%
9 621
 
4.9%
7 612
 
4.9%
Latin
ValueCountFrequency (%)
n 2
20.0%
y 1
10.0%
a 1
10.0%
g 1
10.0%
s 1
10.0%
i 1
10.0%
l 1
10.0%
C 1
10.0%
t 1
10.0%
Hangul
ValueCountFrequency (%)
230
33.3%
230
33.3%
230
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12606
94.8%
Hangul 690
 
5.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3129
24.8%
0 1830
14.5%
2 1827
14.5%
3 1293
10.3%
4 1018
 
8.1%
5 812
 
6.4%
8 810
 
6.4%
6 644
 
5.1%
9 621
 
4.9%
7 612
 
4.9%
Other values (9) 10
 
0.1%
Hangul
ValueCountFrequency (%)
230
33.3%
230
33.3%
230
33.3%

wmeipcnt
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7965 
0
1688 
여성종사자수
 
232
1
 
75
2
 
18
Other values (7)
 
22

Length

Max length8
Median length4
Mean length3.5065
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7965
79.7%
0 1688
 
16.9%
여성종사자수 232
 
2.3%
1 75
 
0.8%
2 18
 
0.2%
3 9
 
0.1%
7 4
 
< 0.1%
5 3
 
< 0.1%
15 2
 
< 0.1%
4 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2024-04-17T01:38:07.204010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7965
79.7%
0 1688
 
16.9%
여성종사자수 232
 
2.3%
1 75
 
0.8%
2 18
 
0.2%
3 9
 
0.1%
7 4
 
< 0.1%
5 3
 
< 0.1%
15 2
 
< 0.1%
4 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

engstntrnmnm
Text

MISSING 

Distinct366
Distinct (%)43.8%
Missing9164
Missing (%)91.6%
Memory size156.2 KiB
2024-04-17T01:38:07.523382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length49
Mean length10.041866
Min length2

Characters and Unicode

Total characters8395
Distinct characters75
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

Unique291 ?
Unique (%)34.8%

Sample

1st rowJunho Guesthouse
2nd row영문상호명
3rd row영문상호명
4th row영문상호명
5th row영문상호명
ValueCountFrequency (%)
영문상호명 353
24.7%
house 153
 
10.7%
guesthouse 57
 
4.0%
hotel 31
 
2.2%
guest 20
 
1.4%
stay 17
 
1.2%
pension 12
 
0.8%
seoul 10
 
0.7%
the 8
 
0.6%
hostel 8
 
0.6%
Other values (479) 763
53.3%
2024-04-17T01:38:07.962784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
596
 
7.1%
e 579
 
6.9%
o 501
 
6.0%
s 398
 
4.7%
u 356
 
4.2%
353
 
4.2%
353
 
4.2%
353
 
4.2%
353
 
4.2%
353
 
4.2%
Other values (65) 4200
50.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3844
45.8%
Uppercase Letter 2057
24.5%
Other Letter 1765
21.0%
Space Separator 596
 
7.1%
Decimal Number 69
 
0.8%
Other Punctuation 49
 
0.6%
Dash Punctuation 11
 
0.1%
Letter Number 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 579
15.1%
o 501
13.0%
s 398
10.4%
u 356
9.3%
n 297
7.7%
a 277
 
7.2%
h 200
 
5.2%
t 189
 
4.9%
i 180
 
4.7%
g 153
 
4.0%
Other values (16) 714
18.6%
Uppercase Letter
ValueCountFrequency (%)
H 243
 
11.8%
S 206
 
10.0%
O 189
 
9.2%
E 176
 
8.6%
U 120
 
5.8%
A 119
 
5.8%
N 113
 
5.5%
T 95
 
4.6%
G 93
 
4.5%
M 84
 
4.1%
Other values (15) 619
30.1%
Decimal Number
ValueCountFrequency (%)
2 17
24.6%
3 14
20.3%
1 12
17.4%
5 8
11.6%
4 6
 
8.7%
0 5
 
7.2%
6 5
 
7.2%
7 2
 
2.9%
Other Letter
ValueCountFrequency (%)
353
20.0%
353
20.0%
353
20.0%
353
20.0%
353
20.0%
Other Punctuation
ValueCountFrequency (%)
' 30
61.2%
. 11
 
22.4%
, 4
 
8.2%
& 2
 
4.1%
: 2
 
4.1%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
596
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5903
70.3%
Hangul 1765
 
21.0%
Common 727
 
8.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 579
 
9.8%
o 501
 
8.5%
s 398
 
6.7%
u 356
 
6.0%
n 297
 
5.0%
a 277
 
4.7%
H 243
 
4.1%
S 206
 
3.5%
h 200
 
3.4%
t 189
 
3.2%
Other values (43) 2657
45.0%
Common
ValueCountFrequency (%)
596
82.0%
' 30
 
4.1%
2 17
 
2.3%
3 14
 
1.9%
1 12
 
1.7%
. 11
 
1.5%
- 11
 
1.5%
5 8
 
1.1%
4 6
 
0.8%
0 5
 
0.7%
Other values (7) 17
 
2.3%
Hangul
ValueCountFrequency (%)
353
20.0%
353
20.0%
353
20.0%
353
20.0%
353
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6628
79.0%
Hangul 1765
 
21.0%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
596
 
9.0%
e 579
 
8.7%
o 501
 
7.6%
s 398
 
6.0%
u 356
 
5.4%
n 297
 
4.5%
a 277
 
4.2%
H 243
 
3.7%
S 206
 
3.1%
h 200
 
3.0%
Other values (58) 2975
44.9%
Hangul
ValueCountFrequency (%)
353
20.0%
353
20.0%
353
20.0%
353
20.0%
353
20.0%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%

engstntrnmaddr
Text

MISSING 

Distinct69
Distinct (%)8.3%
Missing9166
Missing (%)91.7%
Memory size156.2 KiB
2024-04-17T01:38:08.138260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length55
Mean length22.252998
Min length5

Characters and Unicode

Total characters18559
Distinct characters55
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)4.0%

Sample

1st rowURBAN HOMESTAY FOR FOREIGN TOURISTS
2nd row영문상호주소
3rd row영문상호주소
4th row영문상호주소
5th row영문상호주소
ValueCountFrequency (%)
영문상호주소 354
13.6%
for 324
12.5%
foreign 301
11.6%
tourists 297
11.4%
urban 296
11.4%
homestay 234
9.0%
business 108
 
4.2%
tourist 64
 
2.5%
private 45
 
1.7%
room 45
 
1.7%
Other values (59) 533
20.5%
2024-04-17T01:38:08.455616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1767
 
9.5%
O 992
 
5.3%
R 941
 
5.1%
T 869
 
4.7%
o 759
 
4.1%
S 742
 
4.0%
s 737
 
4.0%
r 732
 
3.9%
e 674
 
3.6%
i 624
 
3.4%
Other values (45) 9722
52.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 8046
43.4%
Lowercase Letter 6554
35.3%
Other Letter 2124
 
11.4%
Space Separator 1767
 
9.5%
Dash Punctuation 25
 
0.1%
Open Punctuation 21
 
0.1%
Close Punctuation 21
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 992
12.3%
R 941
11.7%
T 869
10.8%
S 742
9.2%
U 558
 
6.9%
F 517
 
6.4%
I 504
 
6.3%
E 497
 
6.2%
A 497
 
6.2%
N 482
 
6.0%
Other values (12) 1447
18.0%
Lowercase Letter
ValueCountFrequency (%)
o 759
11.6%
s 737
11.2%
r 732
11.2%
e 674
10.3%
i 624
9.5%
n 588
9.0%
t 477
7.3%
u 369
 
5.6%
a 346
 
5.3%
m 195
 
3.0%
Other values (12) 1053
16.1%
Other Letter
ValueCountFrequency (%)
354
16.7%
354
16.7%
354
16.7%
354
16.7%
354
16.7%
354
16.7%
Space Separator
ValueCountFrequency (%)
1767
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14600
78.7%
Hangul 2124
 
11.4%
Common 1835
 
9.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 992
 
6.8%
R 941
 
6.4%
T 869
 
6.0%
o 759
 
5.2%
S 742
 
5.1%
s 737
 
5.0%
r 732
 
5.0%
e 674
 
4.6%
i 624
 
4.3%
n 588
 
4.0%
Other values (34) 6942
47.5%
Hangul
ValueCountFrequency (%)
354
16.7%
354
16.7%
354
16.7%
354
16.7%
354
16.7%
354
16.7%
Common
ValueCountFrequency (%)
1767
96.3%
- 25
 
1.4%
( 21
 
1.1%
) 21
 
1.1%
& 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16435
88.6%
Hangul 2124
 
11.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1767
 
10.8%
O 992
 
6.0%
R 941
 
5.7%
T 869
 
5.3%
o 759
 
4.6%
S 742
 
4.5%
s 737
 
4.5%
r 732
 
4.5%
e 674
 
4.1%
i 624
 
3.8%
Other values (39) 7598
46.2%
Hangul
ValueCountFrequency (%)
354
16.7%
354
16.7%
354
16.7%
354
16.7%
354
16.7%
354
16.7%

yoksilcnt
Categorical

IMBALANCE 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6047 
<NA>
3574 
욕실수
 
230
12
 
14
10
 
12
Other values (29)
 
123

Length

Max length9
Median length1
Mean length2.1317
Min length1

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 6047
60.5%
<NA> 3574
35.7%
욕실수 230
 
2.3%
12 14
 
0.1%
10 12
 
0.1%
15 11
 
0.1%
9 10
 
0.1%
18 10
 
0.1%
8 9
 
0.1%
14 8
 
0.1%
Other values (24) 75
 
0.8%

Length

2024-04-17T01:38:08.576221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 6047
60.5%
na 3574
35.7%
욕실수 230
 
2.3%
12 14
 
0.1%
10 12
 
0.1%
15 11
 
0.1%
9 10
 
0.1%
18 10
 
0.1%
8 9
 
0.1%
14 8
 
0.1%
Other values (24) 75
 
0.8%

sntuptaenm
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
여관업
4333 
<NA>
1884 
숙박업(생활)
1192 
여인숙업
858 
숙박업 기타
642 
Other values (5)
1091 

Length

Max length10
Median length8
Mean length4.0831
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row여관업
2nd row여인숙업
3rd row여관업
4th row여인숙업
5th row숙박업 기타

Common Values

ValueCountFrequency (%)
여관업 4333
43.3%
<NA> 1884
18.8%
숙박업(생활) 1192
 
11.9%
여인숙업 858
 
8.6%
숙박업 기타 642
 
6.4%
일반호텔 522
 
5.2%
관광호텔 324
 
3.2%
위생업태명 226
 
2.3%
휴양콘도미니엄업 18
 
0.2%
sntUptaeNm 1
 
< 0.1%

Length

2024-04-17T01:38:08.681971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:08.796016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 4333
40.7%
na 1884
17.7%
숙박업(생활 1192
 
11.2%
여인숙업 858
 
8.1%
숙박업 642
 
6.0%
기타 642
 
6.0%
일반호텔 522
 
4.9%
관광호텔 324
 
3.0%
위생업태명 226
 
2.1%
휴양콘도미니엄업 18
 
0.2%

dispenen
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
 
398
d
 
1

Length

Max length4
Median length4
Mean length3.8803
Min length1

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> 9601
96.0%
398
 
4.0%
d 1
 
< 0.1%

Length

2024-04-17T01:38:08.930163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:09.065125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
398
 
4.0%
d 1
 
< 0.1%

capt
Text

MISSING 

Distinct112
Distinct (%)13.8%
Missing9191
Missing (%)91.9%
Memory size156.2 KiB
2024-04-17T01:38:09.264264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.2027194
Min length1

Characters and Unicode

Total characters5018
Distinct characters17
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)8.0%

Sample

1st row자본금
2nd row자본금
3rd row9500000000
4th row자본금
5th row자본금
ValueCountFrequency (%)
자본금 334
41.3%
10000000 51
 
6.3%
50000000 49
 
6.1%
30000000 37
 
4.6%
20000000 34
 
4.2%
100000000 34
 
4.2%
200000000 22
 
2.7%
5000000 18
 
2.2%
15000000 16
 
2.0%
500000000 12
 
1.5%
Other values (102) 202
25.0%
2024-04-17T01:38:09.600595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3282
65.4%
334
 
6.7%
334
 
6.7%
334
 
6.7%
1 176
 
3.5%
5 166
 
3.3%
2 133
 
2.7%
3 99
 
2.0%
6 37
 
0.7%
8 35
 
0.7%
Other values (7) 88
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4012
80.0%
Other Letter 1002
 
20.0%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3282
81.8%
1 176
 
4.4%
5 166
 
4.1%
2 133
 
3.3%
3 99
 
2.5%
6 37
 
0.9%
8 35
 
0.9%
4 32
 
0.8%
7 27
 
0.7%
9 25
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
c 1
25.0%
a 1
25.0%
p 1
25.0%
t 1
25.0%
Other Letter
ValueCountFrequency (%)
334
33.3%
334
33.3%
334
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4012
80.0%
Hangul 1002
 
20.0%
Latin 4
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3282
81.8%
1 176
 
4.4%
5 166
 
4.1%
2 133
 
3.3%
3 99
 
2.5%
6 37
 
0.9%
8 35
 
0.9%
4 32
 
0.8%
7 27
 
0.7%
9 25
 
0.6%
Latin
ValueCountFrequency (%)
c 1
25.0%
a 1
25.0%
p 1
25.0%
t 1
25.0%
Hangul
ValueCountFrequency (%)
334
33.3%
334
33.3%
334
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4016
80.0%
Hangul 1002
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3282
81.7%
1 176
 
4.4%
5 166
 
4.1%
2 133
 
3.3%
3 99
 
2.5%
6 37
 
0.9%
8 35
 
0.9%
4 32
 
0.8%
7 27
 
0.7%
9 25
 
0.6%
Other values (4) 4
 
0.1%
Hangul
ValueCountFrequency (%)
334
33.3%
334
33.3%
334
33.3%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
제작취급품목내용
 
398
mnfacTreArtclCn
 
1

Length

Max length15
Median length4
Mean length4.1603
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> 9601
96.0%
제작취급품목내용 398
 
4.0%
mnfacTreArtclCn 1
 
< 0.1%

Length

2024-04-17T01:38:09.714293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:09.792533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
제작취급품목내용 398
 
4.0%
mnfactreartclcn 1
 
< 0.1%

cndpermstymd
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9591 
조건부허가시작일자
 
396
20180202
 
2
20201120
 
2
20201028
 
1
Other values (8)
 
8

Length

Max length12
Median length4
Mean length4.2036
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> 9591
95.9%
조건부허가시작일자 396
 
4.0%
20180202 2
 
< 0.1%
20201120 2
 
< 0.1%
20201028 1
 
< 0.1%
20200909 1
 
< 0.1%
cndPermStYmd 1
 
< 0.1%
20181221 1
 
< 0.1%
20201126 1
 
< 0.1%
20200818 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

Length

2024-04-17T01:38:09.883227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9591
95.9%
조건부허가시작일자 396
 
4.0%
20180202 2
 
< 0.1%
20201120 2
 
< 0.1%
20201028 1
 
< 0.1%
20200909 1
 
< 0.1%
cndpermstymd 1
 
< 0.1%
20181221 1
 
< 0.1%
20201126 1
 
< 0.1%
20200818 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9597 
조건부허가신고사유
 
396
cndPermNtWhy
 
1
객실 수 : 80개소
 
1
약정서 이행
 
1
Other values (4)
 
4

Length

Max length37
Median length4
Mean length4.2067
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> 9597
96.0%
조건부허가신고사유 396
 
4.0%
cndPermNtWhy 1
 
< 0.1%
객실 수 : 80개소 1
 
< 0.1%
약정서 이행 1
 
< 0.1%
위탁기간 1
 
< 0.1%
임대차 계약기간(2020.06.30~2022.06.30) 동안 운영 1
 
< 0.1%
공유재산 대부계약체결 기간 기한설정 1
 
< 0.1%
가평군 뮤직빌리지 사무 위.수탁 협약 (숙박업) 1
 
< 0.1%

Length

2024-04-17T01:38:09.993526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:10.087901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9597
95.8%
조건부허가신고사유 396
 
4.0%
협약 1
 
< 0.1%
위.수탁 1
 
< 0.1%
사무 1
 
< 0.1%
뮤직빌리지 1
 
< 0.1%
가평군 1
 
< 0.1%
기한설정 1
 
< 0.1%
기간 1
 
< 0.1%
대부계약체결 1
 
< 0.1%
Other values (14) 14
 
0.1%

cndpermendymd
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9591 
조건부허가종료일자
 
396
20190202
 
2
20221031
 
2
20251014
 
1
Other values (8)
 
8

Length

Max length13
Median length4
Mean length4.2037
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> 9591
95.9%
조건부허가종료일자 396
 
4.0%
20190202 2
 
< 0.1%
20221031 2
 
< 0.1%
20251014 1
 
< 0.1%
20210725 1
 
< 0.1%
cndPermEndYmd 1
 
< 0.1%
20201220 1
 
< 0.1%
20221021 1
 
< 0.1%
20220630 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

Length

2024-04-17T01:38:10.198630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9591
95.9%
조건부허가종료일자 396
 
4.0%
20190202 2
 
< 0.1%
20221031 2
 
< 0.1%
20251014 1
 
< 0.1%
20210725 1
 
< 0.1%
cndpermendymd 1
 
< 0.1%
20201220 1
 
< 0.1%
20221021 1
 
< 0.1%
20220630 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

chaircnt
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5921 
0
3843 
좌석수
 
230
3
 
1
chairCnt
 
1
Other values (4)
 
4

Length

Max length8
Median length4
Mean length2.8231
Min length1

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5921
59.2%
0 3843
38.4%
좌석수 230
 
2.3%
3 1
 
< 0.1%
chairCnt 1
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
2 1
 
< 0.1%
12 1
 
< 0.1%

Length

2024-04-17T01:38:10.323478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:10.437813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5921
59.2%
0 3843
38.4%
좌석수 230
 
2.3%
3 1
 
< 0.1%
chaircnt 1
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
2 1
 
< 0.1%
12 1
 
< 0.1%

nearenvnm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9131 
주변환경명
 
330
기타
 
312
주택가주변
 
134
학교정화(상대)
 
49
Other values (4)
 
44

Length

Max length9
Median length4
Mean length4.0102
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> 9131
91.3%
주변환경명 330
 
3.3%
기타 312
 
3.1%
주택가주변 134
 
1.3%
학교정화(상대) 49
 
0.5%
아파트지역 37
 
0.4%
유흥업소밀집지역 4
 
< 0.1%
학교정화(절대) 2
 
< 0.1%
nearEnvNm 1
 
< 0.1%

Length

2024-04-17T01:38:10.545842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:10.643351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9131
91.3%
주변환경명 330
 
3.3%
기타 312
 
3.1%
주택가주변 134
 
1.3%
학교정화(상대 49
 
0.5%
아파트지역 37
 
0.4%
유흥업소밀집지역 4
 
< 0.1%
학교정화(절대 2
 
< 0.1%
nearenvnm 1
 
< 0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8976 
지상층수
 
296
2
 
184
1
 
181
3
 
110
Other values (26)
 
253

Length

Max length10
Median length4
Mean length3.7908
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> 8976
89.8%
지상층수 296
 
3.0%
2 184
 
1.8%
1 181
 
1.8%
3 110
 
1.1%
4 74
 
0.7%
5 28
 
0.3%
6 22
 
0.2%
10 19
 
0.2%
9 18
 
0.2%
Other values (21) 92
 
0.9%

Length

2024-04-17T01:38:10.760678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8976
89.8%
지상층수 296
 
3.0%
2 184
 
1.8%
1 181
 
1.8%
3 110
 
1.1%
4 74
 
0.7%
5 28
 
0.3%
6 22
 
0.2%
10 19
 
0.2%
9 18
 
0.2%
Other values (21) 92
 
0.9%

regnsenm
Categorical

IMBALANCE 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8714 
일반주거지역
 
315
지역구분명
 
275
관리지역
 
247
자연녹지지역
 
137
Other values (13)
 
312

Length

Max length8
Median length4
Mean length4.1535
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8714
87.1%
일반주거지역 315
 
3.1%
지역구분명 275
 
2.8%
관리지역 247
 
2.5%
자연녹지지역 137
 
1.4%
일반상업지역 104
 
1.0%
주거지역 82
 
0.8%
준주거지역 46
 
0.5%
상업지역 18
 
0.2%
보전녹지지역 15
 
0.1%
Other values (8) 47
 
0.5%

Length

2024-04-17T01:38:10.871073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8714
87.1%
일반주거지역 315
 
3.1%
지역구분명 275
 
2.8%
관리지역 247
 
2.5%
자연녹지지역 137
 
1.4%
일반상업지역 104
 
1.0%
주거지역 82
 
0.8%
준주거지역 46
 
0.5%
상업지역 18
 
0.2%
보전녹지지역 15
 
0.1%
Other values (8) 47
 
0.5%

undernumlay
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9310 
지하층수
 
334
1
 
195
0
 
79
2
 
43
Other values (6)
 
39

Length

Max length10
Median length4
Mean length3.8941
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9310
93.1%
지하층수 334
 
3.3%
1 195
 
1.9%
0 79
 
0.8%
2 43
 
0.4%
3 17
 
0.2%
4 10
 
0.1%
5 7
 
0.1%
6 3
 
< 0.1%
7 1
 
< 0.1%

Length

2024-04-17T01:38:10.982946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9310
93.1%
지하층수 334
 
3.3%
1 195
 
1.9%
0 79
 
0.8%
2 43
 
0.4%
3 17
 
0.2%
4 10
 
0.1%
5 7
 
0.1%
6 3
 
< 0.1%
7 1
 
< 0.1%

totnumlay
Categorical

IMBALANCE 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8905 
총층수
 
290
1
 
218
2
 
187
3
 
142
Other values (27)
 
258

Length

Max length9
Median length4
Mean length3.7389
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> 8905
89.0%
총층수 290
 
2.9%
1 218
 
2.2%
2 187
 
1.9%
3 142
 
1.4%
4 65
 
0.7%
5 46
 
0.5%
6 29
 
0.3%
8 12
 
0.1%
7 12
 
0.1%
Other values (22) 94
 
0.9%

Length

2024-04-17T01:38:11.098825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8905
89.0%
총층수 290
 
2.9%
1 218
 
2.2%
2 187
 
1.9%
3 142
 
1.4%
4 65
 
0.7%
5 46
 
0.5%
6 29
 
0.3%
8 12
 
0.1%
7 12
 
0.1%
Other values (22) 94
 
0.9%

abedcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5341 
<NA>
4426 
침대수
 
230
41
 
2
abedCnt
 
1

Length

Max length7
Median length1
Mean length2.3746
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5341
53.4%
<NA> 4426
44.3%
침대수 230
 
2.3%
41 2
 
< 0.1%
abedCnt 1
 
< 0.1%

Length

2024-04-17T01:38:11.211218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:11.297359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5341
53.4%
na 4426
44.3%
침대수 230
 
2.3%
41 2
 
< 0.1%
abedcnt 1
 
< 0.1%

hanshilcnt
Text

MISSING 

Distinct54
Distinct (%)0.7%
Missing2794
Missing (%)27.9%
Memory size156.2 KiB
2024-04-17T01:38:11.419869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length1
Mean length1.2212046
Min length1

Characters and Unicode

Total characters8800
Distinct characters21
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.1%

Sample

1st row1
2nd row0
3rd row0
4th row16
5th row2
ValueCountFrequency (%)
0 3961
55.0%
2 301
 
4.2%
1 275
 
3.8%
10 273
 
3.8%
3 259
 
3.6%
한실수 230
 
3.2%
8 214
 
3.0%
4 199
 
2.8%
6 174
 
2.4%
5 174
 
2.4%
Other values (44) 1146
 
15.9%
2024-04-17T01:38:11.672397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4278
48.6%
1 1349
 
15.3%
2 580
 
6.6%
3 388
 
4.4%
4 314
 
3.6%
8 269
 
3.1%
5 263
 
3.0%
6 252
 
2.9%
230
 
2.6%
230
 
2.6%
Other values (11) 647
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8100
92.0%
Other Letter 690
 
7.8%
Lowercase Letter 9
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4278
52.8%
1 1349
 
16.7%
2 580
 
7.2%
3 388
 
4.8%
4 314
 
3.9%
8 269
 
3.3%
5 263
 
3.2%
6 252
 
3.1%
9 218
 
2.7%
7 189
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
h 2
22.2%
n 2
22.2%
a 1
11.1%
s 1
11.1%
i 1
11.1%
l 1
11.1%
t 1
11.1%
Other Letter
ValueCountFrequency (%)
230
33.3%
230
33.3%
230
33.3%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8100
92.0%
Hangul 690
 
7.8%
Latin 10
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4278
52.8%
1 1349
 
16.7%
2 580
 
7.2%
3 388
 
4.8%
4 314
 
3.9%
8 269
 
3.3%
5 263
 
3.2%
6 252
 
3.1%
9 218
 
2.7%
7 189
 
2.3%
Latin
ValueCountFrequency (%)
h 2
20.0%
n 2
20.0%
a 1
10.0%
s 1
10.0%
i 1
10.0%
l 1
10.0%
C 1
10.0%
t 1
10.0%
Hangul
ValueCountFrequency (%)
230
33.3%
230
33.3%
230
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8110
92.2%
Hangul 690
 
7.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4278
52.7%
1 1349
 
16.6%
2 580
 
7.2%
3 388
 
4.8%
4 314
 
3.9%
8 269
 
3.3%
5 263
 
3.2%
6 252
 
3.1%
9 218
 
2.7%
7 189
 
2.3%
Other values (8) 10
 
0.1%
Hangul
ValueCountFrequency (%)
230
33.3%
230
33.3%
230
33.3%

rcvdryncnt
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5348 
<NA>
4421 
회수건조수
 
230
rcvDrynCnt
 
1

Length

Max length10
Median length1
Mean length2.4192
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5348
53.5%
<NA> 4421
44.2%
회수건조수 230
 
2.3%
rcvDrynCnt 1
 
< 0.1%

Length

2024-04-17T01:38:11.793019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:11.883395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5348
53.5%
na 4421
44.2%
회수건조수 230
 
2.3%
rcvdryncnt 1
 
< 0.1%

meetsamtimesygstf
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9601 
회의실별동시수용인원
 
398
meetSamTim
 
1

Length

Max length10
Median length4
Mean length4.2394
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> 9601
96.0%
회의실별동시수용인원 398
 
4.0%
meetSamTim 1
 
< 0.1%

Length

2024-04-17T01:38:11.976569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:12.058336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9601
96.0%
회의실별동시수용인원 398
 
4.0%
meetsamtim 1
 
< 0.1%

last_load_dttm
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-01-04 19:48:52
4196 
2021-01-04 19:48:51
2989 
2021-01-04 19:48:54
2173 
2021-01-04 19:48:53
634 
<NA>
 
8

Length

Max length19
Median length19
Mean length18.988
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-01-04 19:48:51
2nd row2021-01-04 19:48:52
3rd row2021-01-04 19:48:52
4th row2021-01-04 19:48:51
5th row2021-01-04 19:48:52

Common Values

ValueCountFrequency (%)
2021-01-04 19:48:52 4196
42.0%
2021-01-04 19:48:51 2989
29.9%
2021-01-04 19:48:54 2173
21.7%
2021-01-04 19:48:53 634
 
6.3%
<NA> 8
 
0.1%

Length

2024-04-17T01:38:12.147279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T01:38:12.239067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-01-04 9992
50.0%
19:48:52 4196
21.0%
19:48:51 2989
 
15.0%
19:48:54 2173
 
10.9%
19:48:53 634
 
3.2%
na 8
 
< 0.1%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
96496332900003290000-201-2001-0062103_11_03_PI2018-08-31 23:59:59.0<NA>V(브이)모텔614849부산광역시 부산진구 부전동 398-2번지47256부산광역시 부산진구 서면문화로 30-8 (부전동)20010801<NA><NA><NA><NA>01영업387384.16195800000186756.3188180000020180710111025여관업051-123-1234<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>30<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>010<NA>2021-01-04 19:48:51
7646764633900003390000-201-2001-0005103_11_03_PI2018-08-31 23:59:59.0<NA>동산여인숙617807부산광역시 사상구 괘법동 545-12번지46968부산광역시 사상구 광장로87번길 13 (괘법동)19801122<NA><NA><NA><NA>01영업380916.26538200000186993.1803530000020180705112614여인숙업051-123-1234<NA><NA><NA>20<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>14<NA><NA><NA>0여인숙업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000<NA>2021-01-04 19:48:52
5277527732900003290000-201-1977-0242603_11_03_PI2018-08-31 23:59:59.0<NA>이화장614849부산광역시 부산진구 부전동 402-2번지47256부산광역시 부산진구 새싹로29번길 10-7 (부전동)19771201<NA><NA><NA><NA>01영업387365.40938900000186836.5412720000020180307093845여관업051-123-1234<NA><NA><NA>30<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>0030<NA><NA><NA>0<NA><NA><NA>10<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000<NA>2021-01-04 19:48:52
48848932700003270000-201-1968-0001403_11_03_PI2018-08-31 23:59:59.0<NA>본역여인숙601830부산광역시 동구 초량동 564-0번지48818부산광역시 동구 대영로243번길 52 (초량동)19680109<NA><NA><NA><NA>01영업385844.32781200000181681.8368620000020180725172004여인숙업051-123-1234<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>0<NA><NA><NA>0여인숙업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>0160<NA>2021-01-04 19:48:51
890088994270000.04270000-201-2019-0000103_11_03_PI2019-02-17 02:21:23.0숙박업(주)다움 수피움230902강원도 영월군 상동읍 내덕리 산 10번지 숯치유센터26248강원도 영월군 상동읍 선바위길 94, 숯치유센터20190215<NA><NA><NA><NA>영업/정상영업36058340573520190215111821숙박업 기타051-123-1234<NA>임대<NA>20<NA><NA><NA><NA>2<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA>32<NA><NA>0숙박업 기타<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>020<NA>2021-01-04 19:48:52
989798964640000.04660000-201-2019-0000203_11_03_PI2019-07-10 02:21:55.0숙박업더그레이호텔561302전라북도 전주시 덕진구 송천동2가 1333-7번지55149전라북도 전주시 덕진구 세병서로 18-6 (송천동2가)20190708<NA><NA><NA><NA>영업/정상영업<NA><NA>20190708154031일반호텔051-123-1234<NA><NA><NA>00<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA>00<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-01-04 19:48:53
806480633290000CDFI226221201500000203_11_04_PI2018-08-31 23:59:59.0<NA>Yun's House614832부산광역시 부산진구 범천동 1080-121번지48947부산광역시 부산진구 신암로185번길 32 (범천동)20150701<NA><NA><NA><NA>13영업중386427.77178700000186216.9214390000020160503133728<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>외국인관광 도시민박업<NA>N<NA>객실수/수용인원:2/5<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>9595.07<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 19:48:52
2611261533300003330000-201-1996-0012503_11_03_PI2018-08-31 23:59:59.0<NA>니나인모텔612040부산광역시 해운대구 송정동 297-22번지48072부산광역시 해운대구 송정해변로 32 (송정동)19961224<NA><NA><NA><NA>01영업400636.15064500000189378.5042910000020171127104711여관업051-123-1234<NA>자가<NA>81<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>8030<NA><NA><NA>0<NA><NA><NA>29<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-01-04 19:48:51
932393223720000.03720000-201-2019-0000303_11_03_PI2019-04-24 02:20:29.0숙박업머큐어 앰배서더 호텔 울산683260울산광역시 북구 산하동 509-1번지 블루마시티KCC스위첸 201동 지상5~11층44264울산광역시 북구 강동산하2로 7, 블루마시티KCC스위첸 201동 지상5~11층 (산하동)20190422<NA><NA><NA><NA>영업/정상영업421088.091554398238936.94377729920190422140808일반호텔051-123-1234<NA><NA><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><NA><NA><NA><NA><NA>일반호텔<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 19:48:53
3331333433700003370000-201-1998-0026203_11_03_PI2018-08-31 23:59:59.0<NA>BNB(비앤비)611822부산광역시 연제구 연산동 746-1번지 T통B반47576부산광역시 연제구 월드컵대로114번길 15 (연산동)19980706<NA><NA><NA><NA>01영업389743.69698000000189621.6429300000020180726140847여관업051-123-1234<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>34<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-01-04 19:48:51
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm
12114121314860000.0CDFI226213202000000203_11_07_PI2020-08-12 00:23:31.0일반야영장업(주)온어스빌리지 야영장<NA>전라남도 곡성군 옥과면 합강리 499-157508전라남도 곡성군 옥과면 월파로 295, 곡성자연생태체험관20200810<NA><NA><NA><NA>영업/정상영업중215374.314867201963.21675220200810172129<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>일반야영장업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>82648264<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 19:48:54
4569456632700003270000-201-1992-0023703_11_03_PI2018-08-31 23:59:59.0<NA>귀빈모텔601829부산광역시 동구 초량동 505-1번지48816부산광역시 동구 초량로13번길 77 (초량동)19920519<NA><NA><NA><NA>01영업385865.05258800000181833.5425130000020180710152743여관업051-123-1234<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>18<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>090<NA>2021-01-04 19:48:52
1687168633000003300000-201-1998-0023703_11_03_PI2018-08-31 23:59:59.0<NA>광혜여관607833부산광역시 동래구 온천동 212-14번지48947<NA>1998121620030122<NA><NA><NA>02폐업389596.112288193385.42561720030122000000여관업051-123-1234<NA><NA><NA>00<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA>18<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA>2021-01-04 19:48:51
933093293380000.0CDFI226221201900000303_11_04_PI2019-04-25 02:20:42.0외국인관광도시민박업광안사계<NA>부산광역시 수영구 광안동 189-11번지48302부산광역시 수영구 남천바다로21번길 13-1, 1층 (광안동)20190423<NA><NA><NA><NA>영업/정상영업중392494.744403632185452.44694899420190423153519<NA>051-123-12342<NA>단독주택<NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>외국인관광 도시민박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>9191.24<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>일반주거지역<NA><NA><NA><NA><NA><NA>2021-01-04 19:48:53
3856385533900003390000-201-2001-0003903_11_03_PI2018-08-31 23:59:59.0<NA>별장여관617800부산광역시 사상구 감전동 105-12번지46982부산광역시 사상구 사상로161번길 55-1 (감전동)19820217<NA><NA><NA><NA>01영업380975.56200000000186381.6268310000020180329153918여관업051-123-1234<NA><NA><NA>30<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>3010<NA><NA><NA>0<NA><NA><NA>14<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-01-04 19:48:52
6988699333500003350000-201-1981-0105203_11_03_PI2018-08-31 23:59:59.0<NA>서동온천609830부산광역시 금정구 서동 338-2번지46320부산광역시 금정구 서동시장뒷길 1319811228<NA><NA><NA><NA>01영업391443.43940300000193028.9127440000020180511092835여관업051-123-1234<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>10<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>000<NA>2021-01-04 19:48:52
6974697933500003350000-201-1973-0104003_11_03_PI2018-08-31 23:59:59.0<NA>제일여인숙609827부산광역시 금정구 서동 302-31번지46318부산광역시 금정구 서동시장뒷길 43 (서동)19730403<NA><NA><NA><NA>01영업391406.66766300000193150.0047560000020180718150620여인숙업051-123-1234<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>0<NA><NA><NA>0여인숙업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0110<NA>2021-01-04 19:48:52
812381213330000CDFI226221201600000603_11_04_PI2018-08-31 23:59:59.0<NA>리얼 센텀하우스<NA>부산광역시 해운대구 재송동48050부산광역시 해운대구 센텀중앙로 145, 102동 1102호 (재송동, 더샵센텀파크1차아파트)20161014<NA><NA><NA><NA>13영업중393456.04268000000189209.2668350000020161014163844<NA>051-123-1234<NA><NA>아파트<NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>외국인관광 도시민박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>165165<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>아파트지역<NA>일반상업지역<NA><NA><NA><NA><NA><NA>2021-01-04 19:48:52
1522152033000003300000-201-1994-0022403_11_03_PI2018-08-31 23:59:59.0<NA>한빛장607832부산광역시 동래구 온천동 135-19번지47703부산광역시 동래구 금강로131번길 5 (온천동)19940117<NA><NA><NA><NA>01영업389400.51972700000193549.4400440000020171122151538여관업051-123-1234<NA><NA><NA>60<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>6030<NA><NA><NA>0<NA><NA><NA>9<NA><NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>030<NA>2021-01-04 19:48:51
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>02폐업384736.73365000000180083.0425140000020121015144713여관업051-123-1234<NA>임대<NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>7<NA><NA><NA><NA>여관업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3<NA><NA>2021-01-04 19:48:51

Duplicate rows

Most frequently occurring

mgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelstroomcntbdngownsenmbdngsrvnmbdngjisgflrcntbdngunderflrcntcnstyareasvnsrplninsurstdtplninsurenddtmaneipcntplayutscntdtlplayfacilcntmultusnupsoynstagearculwrkrsenmculphyedcobnmgeicpfacilenbalhansilynbcfacileninsurorgnminsurstdtinsurenddtafcusejisgendflruseunderendflrusejisgstflruseunderstflrshpinfoshpcntshptottonswashmccntfacilscpfacilarinfobenyangsilcntwmeipcntengstntrnmnmengstntrnmaddryoksilcntsntuptaenmdispenencaptmnfactreartclcncndpermstymdcndpermntwhycndpermendymdchaircntnearenvnmjisgnumlayregnsenmundernumlaytotnumlayabedcnthanshilcntrcvdryncntmeetsamtimesygstflast_load_dttm# duplicates
1864810000-214-2018-0004903_11_03_PU2018-10-21 02:36:21.0숙박업다올550833전라남도 여수시 돌산읍 우두리 1128-6번지전라남도 여수시 돌산읍 강남3길 73-2120181017<NA><NA><NA><NA><NA>영업269061.383127135486.23745220181019093755숙박업(생활)051-123-1234<NA>자가<NA>30<NA><NA><NA><NA><NA><NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>3010<NA><NA><NA>0<NA><NA><NA>3<NA><NA><NA>0숙박업(생활)<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>010<NA>2021-01-04 19:48:525
271CDFI226003201800000503_11_01_PU2019-04-14 02:40:00.0관광숙박업일로이리조트<NA>부산광역시 해운대구 송정동 809번지부산광역시 해운대구 송정구덕포길 130 (송정동)20181017<NA><NA><NA><NA>영업/정상영업중400102.463000748187863.01536593920190412092534<NA>051-123-1234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NN<NA><NA>관광숙박업<NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>599598.73<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4주거지역<NA>4<NA><NA><NA><NA>2021-01-04 19:48:525
03000000-214-2020-0000403_11_03_PU2020-08-07 02:40:00.0숙박업오라카이 인사동 스위츠110320서울특별시 종로구 낙원동 272 로담코 인사빌딩서울특별시 종로구 인사동4길 18, 로담코 인사빌딩 (낙원동)20200717<NA><NA><NA><NA>영업/정상영업198811.497417806452301.90778071720200805162817숙박업(생활)051-123-1234<NA><NA><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>213<NA><NA><NA><NA>숙박업(생활)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2021-01-04 19:48:543
33010000-201-2019-0001303_11_03_PU2019-12-25 02:40:00.0숙박업모헤닉 호텔 서울 명동100011서울특별시 중구 충무로1가 24-1번지 밀레오레 명동서울특별시 중구 퇴계로 115, 4-17층 (충무로1가)20191220<NA><NA><NA><NA>영업/정상영업198562.632745775450975.11640604820191223091326일반호텔051-123-1234<NA><NA><NA>00<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>17040<NA><NA><NA>0<NA><NA><NA>1170<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-01-04 19:48:543
63180000-201-2020-0000103_11_03_PI2020-06-21 00:23:27.0숙박업서울H150103서울특별시 영등포구 양평동3가 30-3번지서울특별시 영등포구 양산로1길 13 (양평동3가)20200619<NA><NA><NA><NA>영업/정상영업189758.735655025447157.13085801620200619110709관광호텔051-123-1234<NA>자가<NA>81<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>8111<NA><NA><NA>0<NA><NA><NA>00<NA><NA>0관광호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>0330<NA>2021-01-04 19:48:543
83230000-201-2019-0000303_11_03_PI2019-12-22 00:23:25.0숙박업호텔 더 캐슬(방이1)138827서울특별시 송파구 방이동 36-17번지 호텔 더 캐슬서울특별시 송파구 올림픽로32길 7, 호텔 더 캐슬 (방이동)20191220폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업209573.227434185445919.35224310620191220121509관광호텔051-123-1234객실수자가건물용도명00건축연면적기념품종류기획여행보험시작일자기획여행보험종료일자0놀이기구수내역NN무대면적문화사업자구분명문화체육업종명N보험기관명보험시작일자보험종료일자부대시설내역16사용끝지하층1사용시작지하층선박제원선박척수선박총톤수0시설규모시설면적630영문상호명영문상호주소0관광호텔자본금제작취급품목내용조건부허가시작일자조건부허가신고사유조건부허가종료일자0주변환경명지상층수지역구분명지하층수총층수000회의실별동시수용인원2021-01-04 19:48:543
143270000-201-2019-0000503_11_03_PU2020-10-29 02:40:00.0숙박업단테하우스B601829부산광역시 동구 초량동 399부산광역시 동구 초량로13번길 58 (초량동)20191025<NA><NA><NA><NA>영업/정상영업385810.401120568181627.55533489420201027175551여관업<NA><NA><NA><NA>00<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>4010<NA><NA><NA>0<NA><NA><NA>110<NA><NA>0여관업<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-01-04 19:48:543
173290000-201-2019-0000203_11_03_PU2020-12-15 02:40:00.0숙박업엑스모텔614846부산광역시 부산진구 부전동 226-5부산광역시 부산진구 신천대로50번길 34, 6층~9층 (부전동)20190705<NA><NA><NA><NA>영업/정상영업387652.201879265185627.12814592320201212162712일반호텔051 803 6996<NA><NA><NA>102<NA><NA><NA><NA>0<NA><NA>N<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>9060<NA><NA><NA>0<NA><NA><NA>290<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-01-04 19:48:533
193330000-201-2018-0001103_11_03_PI2018-12-15 02:20:16.0숙박업베이몬드호텔612821부산광역시 해운대구 우동 648-8번지부산광역시 해운대구 해운대해변로209번가길 27 (우동)20181213<NA><NA><NA><NA>영업/정상영업396446.063994506186617.52221071320181214133722일반호텔051-123-1234<NA><NA><NA>122<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>12211<NA><NA><NA>0<NA><NA><NA>670<NA><NA>0일반호텔<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>000<NA>2021-01-04 19:48:523
203330000-201-2019-0000203_11_03_PI2019-04-28 02:20:33.0숙박업해운대비치612846부산광역시 해운대구 중동 1010번지부산광역시 해운대구 달맞이길62번길 53, 6~7층 (중동)20190426<NA><NA><NA><NA>영업/정상영업397923.757629367186430.66364418520190426095714숙박업 기타051-123-1234<NA><NA><NA>00<NA><NA><NA><NA>0<NA>NN<NA><NA><NA><NA>N<NA><NA><NA><NA><NA>7<NA>6<NA><NA><NA><NA>0<NA><NA><NA>80<NA><NA>0숙박업 기타<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA>0120<NA>2021-01-04 19:48:533