Overview

Dataset statistics

Number of variables56
Number of observations404
Missing cells18
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory180.0 KiB
Average record size in memory456.3 B

Variable types

Numeric8
Text4
Categorical42
DateTime2

Alerts

last_load_dttm has constant value ""Constant
sitepostno is highly imbalanced (75.2%)Imbalance
dcbymd is highly imbalanced (66.7%)Imbalance
clgstdt is highly imbalanced (64.6%)Imbalance
clgenddt is highly imbalanced (64.6%)Imbalance
ropnymd is highly imbalanced (64.6%)Imbalance
dtlstatenm is highly imbalanced (66.3%)Imbalance
uptaenm is highly imbalanced (64.6%)Imbalance
sitetel is highly imbalanced (87.5%)Imbalance
bfgameocptectcobnm is highly imbalanced (64.6%)Imbalance
noroomcnt is highly imbalanced (64.6%)Imbalance
souarfacilyn is highly imbalanced (64.6%)Imbalance
vdoretornm is highly imbalanced (64.6%)Imbalance
emerstairyn is highly imbalanced (64.6%)Imbalance
emexyn is highly imbalanced (64.6%)Imbalance
firefacilyn is highly imbalanced (64.6%)Imbalance
facilar is highly imbalanced (79.2%)Imbalance
soundfacilyn is highly imbalanced (64.6%)Imbalance
autochaairyn is highly imbalanced (64.6%)Imbalance
prvdgathinnm is highly imbalanced (64.6%)Imbalance
mnfactreartclcn is highly imbalanced (64.6%)Imbalance
lghtfacilyn is highly imbalanced (64.6%)Imbalance
lghtfacilinillu is highly imbalanced (64.6%)Imbalance
nearenvnm is highly imbalanced (54.0%)Imbalance
regnsenm is highly imbalanced (56.0%)Imbalance
bgroomcnt is highly imbalanced (64.6%)Imbalance
bgroomyn is highly imbalanced (64.6%)Imbalance
totgasyscnt is highly imbalanced (64.6%)Imbalance
pasgbreth is highly imbalanced (53.4%)Imbalance
speclghtyn is highly imbalanced (64.6%)Imbalance
cnvefacilyn is highly imbalanced (64.6%)Imbalance
actlnm is highly imbalanced (64.6%)Imbalance
rdnwhladdr has 6 (1.5%) missing valuesMissing
x has 6 (1.5%) missing valuesMissing
y has 6 (1.5%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 11:41:22.567730
Analysis finished2024-04-16 11:41:23.502468
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct404
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean583.94802
Minimum1
Maximum2962
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:23.557718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.15
Q1101.75
median202.5
Q3804.5
95-th percentile2155.25
Maximum2962
Range2961
Interquartile range (IQR)702.75

Descriptive statistics

Standard deviation767.5875
Coefficient of variation (CV)1.3144792
Kurtosis1.193819
Mean583.94802
Median Absolute Deviation (MAD)130
Skewness1.5446433
Sum235915
Variance589190.57
MonotonicityStrictly increasing
2024-04-16T20:41:23.666842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
268 1
 
0.2%
475 1
 
0.2%
459 1
 
0.2%
345 1
 
0.2%
335 1
 
0.2%
325 1
 
0.2%
273 1
 
0.2%
272 1
 
0.2%
271 1
 
0.2%
Other values (394) 394
97.5%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
2962 1
0.2%
2958 1
0.2%
2955 1
0.2%
2953 1
0.2%
2952 1
0.2%
2900 1
0.2%
2897 1
0.2%
2846 1
0.2%
2786 1
0.2%
2650 1
0.2%

opnsfteamcode
Real number (ℝ)

Distinct14
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3317871.3
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:23.769386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13290000
median3330000
Q33330000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation40596.34
Coefficient of variation (CV)0.012235658
Kurtosis-0.36630197
Mean3317871.3
Median Absolute Deviation (MAD)30000
Skewness0.13602165
Sum1.34042 × 109
Variance1.6480628 × 109
MonotonicityNot monotonic
2024-04-16T20:41:23.876431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3330000 113
28.0%
3290000 73
18.1%
3250000 53
13.1%
3350000 26
 
6.4%
3300000 25
 
6.2%
3400000 22
 
5.4%
3320000 21
 
5.2%
3310000 18
 
4.5%
3390000 15
 
3.7%
3340000 13
 
3.2%
Other values (4) 25
 
6.2%
ValueCountFrequency (%)
3250000 53
13.1%
3260000 1
 
0.2%
3270000 5
 
1.2%
3290000 73
18.1%
3300000 25
 
6.2%
3310000 18
 
4.5%
3320000 21
 
5.2%
3330000 113
28.0%
3340000 13
 
3.2%
3350000 26
 
6.4%
ValueCountFrequency (%)
3400000 22
 
5.4%
3390000 15
 
3.7%
3380000 10
 
2.5%
3370000 9
 
2.2%
3350000 26
 
6.4%
3340000 13
 
3.2%
3330000 113
28.0%
3320000 21
 
5.2%
3310000 18
 
4.5%
3300000 25
 
6.2%

mgtno
Text

Distinct225
Distinct (%)55.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-16T20:41:24.076226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters8080
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique137 ?
Unique (%)33.9%

Sample

1st rowCDFF4220002005000001
2nd rowCDFF4220002017000003
3rd rowCDFF4220002017000006
4th rowCDFF4220002017000005
5th rowCDFF4220001982000001
ValueCountFrequency (%)
cdff5211012020000001 18
 
4.5%
cdff5211012019000001 12
 
3.0%
cdff5211012020000002 9
 
2.2%
cdff5211032020000001 8
 
2.0%
cdff5211032019000001 8
 
2.0%
cdff5211042019000001 6
 
1.5%
cdff5211042020000001 4
 
1.0%
cdff5211012020000004 4
 
1.0%
cdff4220002007000001 4
 
1.0%
cdff4220002006000007 4
 
1.0%
Other values (215) 327
80.9%
2024-04-16T20:41:24.385851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3611
44.7%
2 1215
 
15.0%
F 808
 
10.0%
1 687
 
8.5%
C 404
 
5.0%
D 404
 
5.0%
4 362
 
4.5%
5 183
 
2.3%
9 132
 
1.6%
7 82
 
1.0%
Other values (3) 192
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6464
80.0%
Uppercase Letter 1616
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3611
55.9%
2 1215
 
18.8%
1 687
 
10.6%
4 362
 
5.6%
5 183
 
2.8%
9 132
 
2.0%
7 82
 
1.3%
3 74
 
1.1%
6 61
 
0.9%
8 57
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
F 808
50.0%
C 404
25.0%
D 404
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6464
80.0%
Latin 1616
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3611
55.9%
2 1215
 
18.8%
1 687
 
10.6%
4 362
 
5.6%
5 183
 
2.8%
9 132
 
2.0%
7 82
 
1.3%
3 74
 
1.1%
6 61
 
0.9%
8 57
 
0.9%
Latin
ValueCountFrequency (%)
F 808
50.0%
C 404
25.0%
D 404
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8080
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3611
44.7%
2 1215
 
15.0%
F 808
 
10.0%
1 687
 
8.5%
C 404
 
5.0%
D 404
 
5.0%
4 362
 
4.5%
5 183
 
2.3%
9 132
 
1.6%
7 82
 
1.0%
Other values (3) 192
 
2.4%

opnsvcid
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
03_13_02_P
282 
03_13_05_P
78 
03_13_01_P
 
23
03_13_03_P
 
15
03_13_04_P
 
6

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03_13_02_P
2nd row03_13_02_P
3rd row03_13_02_P
4th row03_13_02_P
5th row03_13_02_P

Common Values

ValueCountFrequency (%)
03_13_02_P 282
69.8%
03_13_05_P 78
 
19.3%
03_13_01_P 23
 
5.7%
03_13_03_P 15
 
3.7%
03_13_04_P 6
 
1.5%

Length

2024-04-16T20:41:24.498986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:24.593993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_13_02_p 282
69.8%
03_13_05_p 78
 
19.3%
03_13_01_p 23
 
5.7%
03_13_03_p 15
 
3.7%
03_13_04_p 6
 
1.5%

updategbn
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
I
327 
U
77 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 327
80.9%
U 77
 
19.1%

Length

2024-04-16T20:41:24.691128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:24.771494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 327
80.9%
u 77
 
19.1%

updatedt
Date

Distinct80
Distinct (%)19.8%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-02-24 02:40:00
2024-04-16T20:41:24.862168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:41:24.982200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
220 
영화제작업
78 
영화상영관
62 
영화배급업
23 
영화상영업
 
15

Length

Max length5
Median length4
Mean length4.4554455
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 220
54.5%
영화제작업 78
 
19.3%
영화상영관 62
 
15.3%
영화배급업 23
 
5.7%
영화상영업 15
 
3.7%
영화수입업 6
 
1.5%

Length

2024-04-16T20:41:25.086479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:25.176407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 220
54.5%
영화제작업 78
 
19.3%
영화상영관 62
 
15.3%
영화배급업 23
 
5.7%
영화상영업 15
 
3.7%
영화수입업 6
 
1.5%

bplcnm
Text

Distinct344
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-16T20:41:25.360242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length20
Mean length10.903465
Min length2

Characters and Unicode

Total characters4405
Distinct characters244
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

Unique319 ?
Unique (%)79.0%

Sample

1st row국도극장 예술관
2nd row롯데시네마 대영 제3관
3rd row롯데시네마 대영 제6관
4th row롯데시네마 대영 제5관
5th row메가박스 부산극장 1관
ValueCountFrequency (%)
롯데시네마 85
 
9.5%
메가박스 48
 
5.4%
cgv 41
 
4.6%
주식회사 29
 
3.2%
해운대 26
 
2.9%
서면 20
 
2.2%
센텀시티 19
 
2.1%
제3관 15
 
1.7%
정관 15
 
1.7%
제2관 14
 
1.6%
Other values (204) 584
65.2%
2024-04-16T20:41:25.671884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
494
 
11.2%
관 305
 
6.9%
시 151
 
3.4%
제 143
 
3.2%
네 132
 
3.0%
마 121
 
2.7%
스 106
 
2.4%
롯 100
 
2.3%
데 100
 
2.3%
C 93
 
2.1%
Other values (234) 2660
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3043
69.1%
Space Separator 494
 
11.2%
Uppercase Letter 363
 
8.2%
Decimal Number 258
 
5.9%
Close Punctuation 89
 
2.0%
Open Punctuation 89
 
2.0%
Lowercase Letter 56
 
1.3%
Other Punctuation 12
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 305
 
10.0%
시 151
 
5.0%
제 143
 
4.7%
네 132
 
4.3%
마 121
 
4.0%
스 106
 
3.5%
롯 100
 
3.3%
데 100
 
3.3%
대 87
 
2.9%
주 86
 
2.8%
Other values (180) 1712
56.3%
Uppercase Letter
ValueCountFrequency (%)
C 93
25.6%
G 75
20.7%
V 74
20.4%
N 19
 
5.2%
E 11
 
3.0%
M 10
 
2.8%
A 8
 
2.2%
U 8
 
2.2%
O 8
 
2.2%
I 7
 
1.9%
Other values (11) 50
13.8%
Lowercase Letter
ValueCountFrequency (%)
c 8
14.3%
g 8
14.3%
v 8
14.3%
o 7
12.5%
d 6
10.7%
t 5
8.9%
l 3
 
5.4%
m 2
 
3.6%
i 2
 
3.6%
e 2
 
3.6%
Other values (5) 5
8.9%
Decimal Number
ValueCountFrequency (%)
1 44
17.1%
2 35
13.6%
4 33
12.8%
3 31
12.0%
6 30
11.6%
5 28
10.9%
7 24
9.3%
8 16
 
6.2%
9 12
 
4.7%
0 5
 
1.9%
Close Punctuation
ValueCountFrequency (%)
) 88
98.9%
] 1
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 88
98.9%
[ 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
, 4
33.3%
Space Separator
ValueCountFrequency (%)
494
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3043
69.1%
Common 943
 
21.4%
Latin 419
 
9.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 305
 
10.0%
시 151
 
5.0%
제 143
 
4.7%
네 132
 
4.3%
마 121
 
4.0%
스 106
 
3.5%
롯 100
 
3.3%
데 100
 
3.3%
대 87
 
2.9%
주 86
 
2.8%
Other values (180) 1712
56.3%
Latin
ValueCountFrequency (%)
C 93
22.2%
G 75
17.9%
V 74
17.7%
N 19
 
4.5%
E 11
 
2.6%
M 10
 
2.4%
c 8
 
1.9%
A 8
 
1.9%
g 8
 
1.9%
v 8
 
1.9%
Other values (26) 105
25.1%
Common
ValueCountFrequency (%)
494
52.4%
) 88
 
9.3%
( 88
 
9.3%
1 44
 
4.7%
2 35
 
3.7%
4 33
 
3.5%
3 31
 
3.3%
6 30
 
3.2%
5 28
 
3.0%
7 24
 
2.5%
Other values (8) 48
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3043
69.1%
ASCII 1362
30.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
494
36.3%
C 93
 
6.8%
) 88
 
6.5%
( 88
 
6.5%
G 75
 
5.5%
V 74
 
5.4%
1 44
 
3.2%
2 35
 
2.6%
4 33
 
2.4%
3 31
 
2.3%
Other values (44) 307
22.5%
Hangul
ValueCountFrequency (%)
관 305
 
10.0%
시 151
 
5.0%
제 143
 
4.7%
네 132
 
4.3%
마 121
 
4.0%
스 106
 
3.5%
롯 100
 
3.3%
데 100
 
3.3%
대 87
 
2.9%
주 86
 
2.8%
Other values (180) 1712
56.3%

sitepostno
Categorical

IMBALANCE 

Distinct18
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
345 
지번우편번호
 
27
607787
 
7
614845
 
4
601060
 
3
Other values (13)
 
18

Length

Max length6
Median length4
Mean length4.2920792
Min length4

Unique

Unique10 ?
Unique (%)2.5%

Sample

1st row600805
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 345
85.4%
지번우편번호 27
 
6.7%
607787 7
 
1.7%
614845 4
 
1.0%
601060 3
 
0.7%
608805 3
 
0.7%
600805 3
 
0.7%
600046 2
 
0.5%
612824 1
 
0.2%
613827 1
 
0.2%
Other values (8) 8
 
2.0%

Length

2024-04-16T20:41:25.790990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 345
85.4%
지번우편번호 27
 
6.7%
607787 7
 
1.7%
614845 4
 
1.0%
601060 3
 
0.7%
608805 3
 
0.7%
600805 3
 
0.7%
600046 2
 
0.5%
607833 1
 
0.2%
600801 1
 
0.2%
Other values (8) 8
 
2.0%

sitewhladdr
Text

Distinct128
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-16T20:41:26.296020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length27.292079
Min length18

Characters and Unicode

Total characters11026
Distinct characters219
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)15.6%

Sample

1st row부산광역시 중구 부평동1가 45-9번지
2nd row부산광역시 중구 남포동5가 12-1번지
3rd row부산광역시 중구 남포동5가 12-1번지
4th row부산광역시 중구 남포동5가 12-1번지
5th row부산광역시 중구 남포동5가 18-1번지
ValueCountFrequency (%)
부산광역시 404
 
20.3%
해운대구 113
 
5.7%
우동 85
 
4.3%
부산진구 73
 
3.7%
중구 53
 
2.7%
부전동 45
 
2.3%
전포동 27
 
1.4%
금정구 26
 
1.3%
동래구 25
 
1.3%
온천동 23
 
1.2%
Other values (278) 1114
56.0%
2024-04-16T20:41:26.697125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1949
 
17.7%
부 561
 
5.1%
산 518
 
4.7%
1 446
 
4.0%
시 439
 
4.0%
동 436
 
4.0%
광 406
 
3.7%
역 404
 
3.7%
구 383
 
3.5%
지 373
 
3.4%
Other values (209) 5111
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6546
59.4%
Decimal Number 2049
 
18.6%
Space Separator 1949
 
17.7%
Dash Punctuation 339
 
3.1%
Uppercase Letter 86
 
0.8%
Other Punctuation 26
 
0.2%
Open Punctuation 10
 
0.1%
Close Punctuation 10
 
0.1%
Math Symbol 6
 
0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 561
 
8.6%
산 518
 
7.9%
시 439
 
6.7%
동 436
 
6.7%
광 406
 
6.2%
역 404
 
6.2%
구 383
 
5.9%
지 373
 
5.7%
번 359
 
5.5%
대 149
 
2.3%
Other values (176) 2518
38.5%
Uppercase Letter
ValueCountFrequency (%)
K 22
25.6%
T 13
15.1%
S 12
14.0%
G 10
11.6%
C 8
 
9.3%
N 8
 
9.3%
B 4
 
4.7%
H 3
 
3.5%
U 3
 
3.5%
Y 2
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 446
21.8%
2 287
14.0%
5 216
10.5%
6 204
10.0%
4 183
8.9%
0 170
 
8.3%
7 164
 
8.0%
8 141
 
6.9%
3 127
 
6.2%
9 111
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
e 1
20.0%
v 1
20.0%
i 1
20.0%
o 1
20.0%
l 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 17
65.4%
& 9
34.6%
Space Separator
ValueCountFrequency (%)
1949
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 339
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6546
59.4%
Common 4389
39.8%
Latin 91
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 561
 
8.6%
산 518
 
7.9%
시 439
 
6.7%
동 436
 
6.7%
광 406
 
6.2%
역 404
 
6.2%
구 383
 
5.9%
지 373
 
5.7%
번 359
 
5.5%
대 149
 
2.3%
Other values (176) 2518
38.5%
Common
ValueCountFrequency (%)
1949
44.4%
1 446
 
10.2%
- 339
 
7.7%
2 287
 
6.5%
5 216
 
4.9%
6 204
 
4.6%
4 183
 
4.2%
0 170
 
3.9%
7 164
 
3.7%
8 141
 
3.2%
Other values (7) 290
 
6.6%
Latin
ValueCountFrequency (%)
K 22
24.2%
T 13
14.3%
S 12
13.2%
G 10
11.0%
C 8
 
8.8%
N 8
 
8.8%
B 4
 
4.4%
H 3
 
3.3%
U 3
 
3.3%
Y 2
 
2.2%
Other values (6) 6
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6546
59.4%
ASCII 4480
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1949
43.5%
1 446
 
10.0%
- 339
 
7.6%
2 287
 
6.4%
5 216
 
4.8%
6 204
 
4.6%
4 183
 
4.1%
0 170
 
3.8%
7 164
 
3.7%
8 141
 
3.1%
Other values (23) 381
 
8.5%
Hangul
ValueCountFrequency (%)
부 561
 
8.6%
산 518
 
7.9%
시 439
 
6.7%
동 436
 
6.7%
광 406
 
6.2%
역 404
 
6.2%
구 383
 
5.9%
지 373
 
5.7%
번 359
 
5.5%
대 149
 
2.3%
Other values (176) 2518
38.5%

rdnpostno
Real number (ℝ)

Distinct71
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47973.079
Minimum46015
Maximum49431
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:26.815351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46015
5-th percentile46083
Q147293
median48058
Q348947
95-th percentile48953
Maximum49431
Range3416
Interquartile range (IQR)1654

Descriptive statistics

Standard deviation911.47622
Coefficient of variation (CV)0.018999744
Kurtosis-0.66214842
Mean47973.079
Median Absolute Deviation (MAD)773
Skewness-0.51955568
Sum19381124
Variance830788.9
MonotonicityNot monotonic
2024-04-16T20:41:26.946231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48947 70
 
17.3%
48058 43
 
10.6%
48953 20
 
5.0%
48059 16
 
4.0%
47296 14
 
3.5%
47299 12
 
3.0%
48944 11
 
2.7%
47285 11
 
2.7%
47710 10
 
2.5%
46015 10
 
2.5%
Other values (61) 187
46.3%
ValueCountFrequency (%)
46015 10
2.5%
46024 6
1.5%
46083 6
1.5%
46251 1
 
0.2%
46259 1
 
0.2%
46291 6
1.5%
46321 1
 
0.2%
46527 9
2.2%
46548 9
2.2%
46560 1
 
0.2%
ValueCountFrequency (%)
49431 1
 
0.2%
49418 1
 
0.2%
49315 3
 
0.7%
49311 7
 
1.7%
49223 1
 
0.2%
48981 2
 
0.5%
48968 3
 
0.7%
48953 20
 
5.0%
48948 1
 
0.2%
48947 70
17.3%

rdnwhladdr
Text

MISSING 

Distinct126
Distinct (%)31.7%
Missing6
Missing (%)1.5%
Memory size3.3 KiB
2024-04-16T20:41:27.209686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length31.954774
Min length22

Characters and Unicode

Total characters12718
Distinct characters248
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)15.6%

Sample

1st row부산광역시 중구 중구로 13 (부평동1가)
2nd row부산광역시 중구 비프광장로 37, 6층 (남포동5가)
3rd row부산광역시 중구 비프광장로 37, 6층 (남포동5가)
4th row부산광역시 중구 비프광장로 37, 6층 (남포동5가)
5th row부산광역시 중구 비프광장로 36 (남포동5가)
ValueCountFrequency (%)
부산광역시 398
 
16.1%
해운대구 113
 
4.6%
우동 81
 
3.3%
부산진구 73
 
2.9%
중구 50
 
2.0%
중앙대로 48
 
1.9%
부전동 45
 
1.8%
해운대로 44
 
1.8%
6층 32
 
1.3%
39 31
 
1.3%
Other values (340) 1564
63.1%
2024-04-16T20:41:27.600123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2106
 
16.6%
부 571
 
4.5%
산 524
 
4.1%
동 496
 
3.9%
시 437
 
3.4%
광 433
 
3.4%
역 398
 
3.1%
로 392
 
3.1%
) 389
 
3.1%
( 389
 
3.1%
Other values (238) 6583
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7603
59.8%
Space Separator 2106
 
16.6%
Decimal Number 1770
 
13.9%
Close Punctuation 389
 
3.1%
Open Punctuation 389
 
3.1%
Other Punctuation 346
 
2.7%
Uppercase Letter 85
 
0.7%
Dash Punctuation 18
 
0.1%
Math Symbol 6
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 571
 
7.5%
산 524
 
6.9%
동 496
 
6.5%
시 437
 
5.7%
광 433
 
5.7%
역 398
 
5.2%
로 392
 
5.2%
구 384
 
5.1%
대 331
 
4.4%
운 185
 
2.4%
Other values (202) 3452
45.4%
Uppercase Letter
ValueCountFrequency (%)
K 22
25.9%
T 13
15.3%
S 12
14.1%
G 9
10.6%
N 7
 
8.2%
C 7
 
8.2%
B 4
 
4.7%
U 3
 
3.5%
H 3
 
3.5%
Y 2
 
2.4%
Other values (3) 3
 
3.5%
Decimal Number
ValueCountFrequency (%)
1 331
18.7%
2 236
13.3%
0 203
11.5%
3 178
10.1%
6 161
9.1%
4 158
8.9%
7 156
8.8%
5 148
8.4%
9 112
 
6.3%
8 87
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
l 1
16.7%
p 1
16.7%
e 1
16.7%
v 1
16.7%
i 1
16.7%
o 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 337
97.4%
& 9
 
2.6%
Space Separator
ValueCountFrequency (%)
2106
100.0%
Close Punctuation
ValueCountFrequency (%)
) 389
100.0%
Open Punctuation
ValueCountFrequency (%)
( 389
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7603
59.8%
Common 5024
39.5%
Latin 91
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 571
 
7.5%
산 524
 
6.9%
동 496
 
6.5%
시 437
 
5.7%
광 433
 
5.7%
역 398
 
5.2%
로 392
 
5.2%
구 384
 
5.1%
대 331
 
4.4%
운 185
 
2.4%
Other values (202) 3452
45.4%
Latin
ValueCountFrequency (%)
K 22
24.2%
T 13
14.3%
S 12
13.2%
G 9
9.9%
N 7
 
7.7%
C 7
 
7.7%
B 4
 
4.4%
U 3
 
3.3%
H 3
 
3.3%
Y 2
 
2.2%
Other values (9) 9
9.9%
Common
ValueCountFrequency (%)
2106
41.9%
) 389
 
7.7%
( 389
 
7.7%
, 337
 
6.7%
1 331
 
6.6%
2 236
 
4.7%
0 203
 
4.0%
3 178
 
3.5%
6 161
 
3.2%
4 158
 
3.1%
Other values (7) 536
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7603
59.8%
ASCII 5115
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2106
41.2%
) 389
 
7.6%
( 389
 
7.6%
, 337
 
6.6%
1 331
 
6.5%
2 236
 
4.6%
0 203
 
4.0%
3 178
 
3.5%
6 161
 
3.1%
4 158
 
3.1%
Other values (26) 627
 
12.3%
Hangul
ValueCountFrequency (%)
부 571
 
7.5%
산 524
 
6.9%
동 496
 
6.5%
시 437
 
5.7%
광 433
 
5.7%
역 398
 
5.2%
로 392
 
5.2%
구 384
 
5.1%
대 331
 
4.4%
운 185
 
2.4%
Other values (202) 3452
45.4%

apvpermymd
Real number (ℝ)

Distinct125
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20103414
Minimum19451015
Maximum20210203
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:27.728433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000516
Q120050111
median20090302
Q320190315
95-th percentile20200501
Maximum20210203
Range759188
Interquartile range (IQR)140204

Descriptive statistics

Standard deviation89193.511
Coefficient of variation (CV)0.0044367346
Kurtosis9.1667212
Mean20103414
Median Absolute Deviation (MAD)79693
Skewness-1.7507283
Sum8.1217791 × 109
Variance7.9554824 × 109
MonotonicityNot monotonic
2024-04-16T20:41:27.859804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190315 12
 
3.0%
20000529 12
 
3.0%
20140822 11
 
2.7%
20010609 11
 
2.7%
20090302 10
 
2.5%
20021112 10
 
2.5%
20050307 10
 
2.5%
20071204 10
 
2.5%
20080527 9
 
2.2%
20200103 9
 
2.2%
Other values (115) 300
74.3%
ValueCountFrequency (%)
19451015 1
0.2%
19591023 1
0.2%
19690925 1
0.2%
19820125 1
0.2%
19910826 1
0.2%
19930814 2
0.5%
19970308 1
0.2%
19980307 1
0.2%
19980319 1
0.2%
19980623 1
0.2%
ValueCountFrequency (%)
20210203 1
 
0.2%
20210202 4
1.0%
20210121 1
 
0.2%
20210120 1
 
0.2%
20210111 1
 
0.2%
20201228 1
 
0.2%
20201113 2
0.5%
20201111 1
 
0.2%
20201027 1
 
0.2%
20201026 1
 
0.2%

dcbymd
Categorical

IMBALANCE 

Distinct29
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
313 
폐업일자
 
27
20170315
 
10
20160617
 
8
20110616
 
8
Other values (24)
38 

Length

Max length8
Median length4
Mean length4.6336634
Min length4

Unique

Unique19 ?
Unique (%)4.7%

Sample

1st row20080501
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 313
77.5%
폐업일자 27
 
6.7%
20170315 10
 
2.5%
20160617 8
 
2.0%
20110616 8
 
2.0%
20100806 7
 
1.7%
20001201 4
 
1.0%
20200921 3
 
0.7%
20070725 3
 
0.7%
20160913 2
 
0.5%
Other values (19) 19
 
4.7%

Length

2024-04-16T20:41:28.008294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 313
77.5%
폐업일자 27
 
6.7%
20170315 10
 
2.5%
20160617 8
 
2.0%
20110616 8
 
2.0%
20100806 7
 
1.7%
20001201 4
 
1.0%
20200921 3
 
0.7%
20070725 3
 
0.7%
20160913 2
 
0.5%
Other values (19) 19
 
4.7%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
휴업시작일자
 
27

Length

Max length6
Median length4
Mean length4.1336634
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
휴업시작일자 27
 
6.7%

Length

2024-04-16T20:41:28.147338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:28.261929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
휴업시작일자 27
 
6.7%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
휴업종료일자
 
27

Length

Max length6
Median length4
Mean length4.1336634
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
휴업종료일자 27
 
6.7%

Length

2024-04-16T20:41:28.378524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:28.491991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
휴업종료일자 27
 
6.7%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
재개업일자
 
27

Length

Max length5
Median length4
Mean length4.0668317
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
재개업일자 27
 
6.7%

Length

2024-04-16T20:41:28.593861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:28.706716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
재개업일자 27
 
6.7%

trdstatenm
Categorical

Distinct7
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
영업/정상
174 
13
163 
03
56 
폐업
 
7
<NA>
 
2
Other values (2)
 
2

Length

Max length8
Median length2
Mean length3.3168317
Min length2

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row03
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row13

Common Values

ValueCountFrequency (%)
영업/정상 174
43.1%
13 163
40.3%
03 56
 
13.9%
폐업 7
 
1.7%
<NA> 2
 
0.5%
35 1
 
0.2%
제외/삭제/전출 1
 
0.2%

Length

2024-04-16T20:41:28.807976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:28.911773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 174
43.1%
13 163
40.3%
03 56
 
13.9%
폐업 7
 
1.7%
na 2
 
0.5%
35 1
 
0.2%
제외/삭제/전출 1
 
0.2%

dtlstatenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
영업중
339 
폐업
63 
직권말소
 
1
전출
 
1

Length

Max length4
Median length3
Mean length2.8440594
Min length2

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 339
83.9%
폐업 63
 
15.6%
직권말소 1
 
0.2%
전출 1
 
0.2%

Length

2024-04-16T20:41:29.038738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:29.157068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 339
83.9%
폐업 63
 
15.6%
직권말소 1
 
0.2%
전출 1
 
0.2%

x
Real number (ℝ)

MISSING 

Distinct106
Distinct (%)26.6%
Missing6
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean389928.83
Minimum377558
Maximum401504.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:29.254452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum377558
5-th percentile380757.33
Q1385761.58
median389668.23
Q3393952.26
95-th percentile398310.24
Maximum401504.79
Range23946.794
Interquartile range (IQR)8190.6894

Descriptive statistics

Standard deviation5284.4089
Coefficient of variation (CV)0.013552239
Kurtosis-0.63574737
Mean389928.83
Median Absolute Deviation (MAD)4045.4522
Skewness0.029142241
Sum1.5519168 × 108
Variance27924978
MonotonicityNot monotonic
2024-04-16T20:41:29.365300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393674.032955782 16
 
4.0%
387982.190387 14
 
3.5%
385622.780457355 11
 
2.7%
387443.214568 11
 
2.7%
388087.223988 11
 
2.7%
396915.143441 10
 
2.5%
394153.800755 10
 
2.5%
398310.243451 10
 
2.5%
382810.081755 9
 
2.2%
382956.05258 9
 
2.2%
Other values (96) 287
71.0%
ValueCountFrequency (%)
377557.995908 1
 
0.2%
378656.720935232 1
 
0.2%
379212.079721725 5
1.2%
379240.573215267 3
 
0.7%
379280.632039 2
 
0.5%
379546.541691789 1
 
0.2%
379635.65262 1
 
0.2%
380625.391364589 6
1.5%
380780.612775 7
1.7%
382810.081755 9
2.2%
ValueCountFrequency (%)
401504.790177 6
1.5%
400819.975248202 1
 
0.2%
398628.503470003 2
 
0.5%
398341.802637 7
1.7%
398310.243451 10
2.5%
398275.475596001 1
 
0.2%
398242.150343638 2
 
0.5%
398035.0 5
1.2%
398025.711375 6
1.5%
398024.244821605 5
1.2%

y
Real number (ℝ)

MISSING 

Distinct106
Distinct (%)26.6%
Missing6
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean187862.73
Minimum178872.46
Maximum204621.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:29.484834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum178872.46
5-th percentile179876.43
Q1185679.05
median187480.44
Q3190048.6
95-th percentile195491.52
Maximum204621.66
Range25749.194
Interquartile range (IQR)4369.5539

Descriptive statistics

Standard deviation5467.8142
Coefficient of variation (CV)0.029105369
Kurtosis1.5733541
Mean187862.73
Median Absolute Deviation (MAD)1855.9627
Skewness0.89058064
Sum74769367
Variance29896992
MonotonicityNot monotonic
2024-04-16T20:41:29.614879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187973.297243244 16
 
4.0%
186465.864259 14
 
3.5%
179452.224754792 11
 
2.7%
186484.775084 11
 
2.7%
185624.481146 11
 
2.7%
187480.443811 10
 
2.5%
188019.100861 10
 
2.5%
188031.67198 10
 
2.5%
192364.303125 9
 
2.2%
194992.355262 9
 
2.2%
Other values (96) 287
71.0%
ValueCountFrequency (%)
178872.461747926 1
 
0.2%
179411.189506548 1
 
0.2%
179452.224754792 11
2.7%
179597.592953541 6
1.5%
179823.23303496 1
 
0.2%
179885.813689 2
 
0.5%
179911.285409 5
1.2%
179919.437009 4
 
1.0%
179919.488084 8
2.0%
179957.089237 3
 
0.7%
ValueCountFrequency (%)
204621.655738547 5
1.2%
204597.0 5
1.2%
204401.691446 6
1.5%
196220.454694204 1
 
0.2%
195491.519782 8
2.0%
194992.355262 9
2.2%
194622.201131 7
1.7%
194428.696617 7
1.7%
193896.1715796 1
 
0.2%
193803.958512 1
 
0.2%

lastmodts
Real number (ℝ)

Distinct352
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.017621 × 1013
Minimum2.0030127 × 1013
Maximum2.0210222 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:29.729171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030127 × 1013
5-th percentile2.0110616 × 1013
Q12.017071 × 1013
median2.0180618 × 1013
Q32.0191115 × 1013
95-th percentile2.020092 × 1013
Maximum2.0210222 × 1013
Range1.8009502 × 1011
Interquartile range (IQR)2.0405039 × 1010

Descriptive statistics

Standard deviation3.1065871 × 1010
Coefficient of variation (CV)0.0015397278
Kurtosis6.8435377
Mean2.017621 × 1013
Median Absolute Deviation (MAD)1.0084035 × 1010
Skewness-2.4457247
Sum8.1511889 × 1015
Variance9.6508836 × 1020
MonotonicityNot monotonic
2024-04-16T20:41:29.847485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190920121341 5
 
1.2%
20030127161348 4
 
1.0%
20191017170859 4
 
1.0%
20200320103703 3
 
0.7%
20190315085722 3
 
0.7%
20200501151723 3
 
0.7%
20200501151929 3
 
0.7%
20190315161634 3
 
0.7%
20200921144254 3
 
0.7%
20200320175117 3
 
0.7%
Other values (342) 370
91.6%
ValueCountFrequency (%)
20030127161348 4
1.0%
20040731102817 1
 
0.2%
20050416094533 1
 
0.2%
20070725150334 1
 
0.2%
20070725150429 1
 
0.2%
20070725183312 1
 
0.2%
20071231132808 1
 
0.2%
20080506140353 1
 
0.2%
20080627132446 1
 
0.2%
20090622134847 1
 
0.2%
ValueCountFrequency (%)
20210222180618 1
0.2%
20210222180418 1
0.2%
20210216110123 1
0.2%
20210203130757 1
0.2%
20210202122837 1
0.2%
20210202122805 1
0.2%
20210202122737 1
0.2%
20210202122656 1
0.2%
20210121162622 1
0.2%
20210120155809 1
0.2%

uptaenm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
업태구분명
 
27

Length

Max length5
Median length4
Mean length4.0668317
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
업태구분명 27
 
6.7%

Length

2024-04-16T20:41:29.959726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:30.051736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
업태구분명 27
 
6.7%

sitetel
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
051-123-1234
387 
<NA>
 
9
전화번호
 
5
070-7728-6334
 
1
070-8899-7402
 
1

Length

Max length13
Median length12
Mean length11.727723
Min length4

Unique

Unique3 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
051-123-1234 387
95.8%
<NA> 9
 
2.2%
전화번호 5
 
1.2%
070-7728-6334 1
 
0.2%
070-8899-7402 1
 
0.2%
051-704-7125 1
 
0.2%

Length

2024-04-16T20:41:30.136956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:30.228698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-123-1234 387
95.8%
na 9
 
2.2%
전화번호 5
 
1.2%
070-7728-6334 1
 
0.2%
070-8899-7402 1
 
0.2%
051-704-7125 1
 
0.2%

bdngsrvnm
Categorical

Distinct7
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
272 
문화시설
82 
건물용도명
 
27
유통시설
 
9
근린생활시설
 
7
Other values (2)
 
7

Length

Max length6
Median length4
Mean length4.0693069
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 272
67.3%
문화시설 82
 
20.3%
건물용도명 27
 
6.7%
유통시설 9
 
2.2%
근린생활시설 7
 
1.7%
호텔 6
 
1.5%
사무실 1
 
0.2%

Length

2024-04-16T20:41:30.365739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:30.469162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 272
67.3%
문화시설 82
 
20.3%
건물용도명 27
 
6.7%
유통시설 9
 
2.2%
근린생활시설 7
 
1.7%
호텔 6
 
1.5%
사무실 1
 
0.2%

perplaformsenm
Categorical

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
영화관
275 
<NA>
100 
공연장형태구분명
 
26
자동차극장
 
3

Length

Max length8
Median length3
Mean length3.5841584
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화관 275
68.1%
<NA> 100
 
24.8%
공연장형태구분명 26
 
6.4%
자동차극장 3
 
0.7%

Length

2024-04-16T20:41:30.579012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:30.674918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화관 275
68.1%
na 100
 
24.8%
공연장형태구분명 26
 
6.4%
자동차극장 3
 
0.7%

bfgameocptectcobnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
기존게임업외업종명
 
27

Length

Max length9
Median length4
Mean length4.3341584
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
기존게임업외업종명 27
 
6.7%

Length

2024-04-16T20:41:30.782412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:30.870960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
기존게임업외업종명 27
 
6.7%

noroomcnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
노래방실수
 
27

Length

Max length5
Median length4
Mean length4.0668317
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
노래방실수 27
 
6.7%

Length

2024-04-16T20:41:30.976808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:31.059022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
노래방실수 27
 
6.7%

culwrkrsenm
Categorical

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
영화상영관
196 
<NA>
181 
문화사업자구분명
27 

Length

Max length8
Median length5
Mean length4.7524752
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화상영관 196
48.5%
<NA> 181
44.8%
문화사업자구분명 27
 
6.7%

Length

2024-04-16T20:41:31.156023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:31.267626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 196
48.5%
na 181
44.8%
문화사업자구분명 27
 
6.7%

culphyedcobnm
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
영화상영관
282 
영화제작업
78 
영화배급업
 
23
영화상영업
 
15
영화수입업
 
6

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화상영관 282
69.8%
영화제작업 78
 
19.3%
영화배급업 23
 
5.7%
영화상영업 15
 
3.7%
영화수입업 6
 
1.5%

Length

2024-04-16T20:41:31.356810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:31.447481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 282
69.8%
영화제작업 78
 
19.3%
영화배급업 23
 
5.7%
영화상영업 15
 
3.7%
영화수입업 6
 
1.5%

souarfacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
방
 
27

Length

Max length4
Median length4
Mean length3.799505
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
방 27
 
6.7%

Length

2024-04-16T20:41:31.564803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:31.660980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
방 27
 
6.7%

vdoretornm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
비디오재생기명
 
27

Length

Max length7
Median length4
Mean length4.200495
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
비디오재생기명 27
 
6.7%

Length

2024-04-16T20:41:31.748245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:31.834371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
비디오재생기명 27
 
6.7%

emerstairyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
비
 
27

Length

Max length4
Median length4
Mean length3.799505
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
비 27
 
6.7%

Length

2024-04-16T20:41:32.157004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:32.239451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
비 27
 
6.7%

emexyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
비
 
27

Length

Max length4
Median length4
Mean length3.799505
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
비 27
 
6.7%

Length

2024-04-16T20:41:32.335662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:32.432572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
비 27
 
6.7%

firefacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
소
 
27

Length

Max length4
Median length4
Mean length3.799505
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
소 27
 
6.7%

Length

2024-04-16T20:41:32.533800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:32.622000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
소 27
 
6.7%

facilar
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
371 
시설면적
 
27
1578.8
 
4
147.46
 
1
181.3
 
1

Length

Max length6
Median length4
Mean length4.0272277
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 371
91.8%
시설면적 27
 
6.7%
1578.8 4
 
1.0%
147.46 1
 
0.2%
181.3 1
 
0.2%

Length

2024-04-16T20:41:32.719136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:32.829499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 371
91.8%
시설면적 27
 
6.7%
1578.8 4
 
1.0%
147.46 1
 
0.2%
181.3 1
 
0.2%

soundfacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
음
 
27

Length

Max length4
Median length4
Mean length3.799505
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
음 27
 
6.7%

Length

2024-04-16T20:41:32.955426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:33.047426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
음 27
 
6.7%

autochaairyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
자
 
27

Length

Max length4
Median length4
Mean length3.799505
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
자 27
 
6.7%

Length

2024-04-16T20:41:33.141046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:33.233590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
자 27
 
6.7%

prvdgathinnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
제공게임물명
 
27

Length

Max length6
Median length4
Mean length4.1336634
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
제공게임물명 27
 
6.7%

Length

2024-04-16T20:41:33.329771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:33.436196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
제공게임물명 27
 
6.7%

mnfactreartclcn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
제작취급품목내용
 
27

Length

Max length8
Median length4
Mean length4.2673267
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
제작취급품목내용 27
 
6.7%

Length

2024-04-16T20:41:33.546268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:33.652982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
제작취급품목내용 27
 
6.7%

lghtfacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
조
 
27

Length

Max length4
Median length4
Mean length3.799505
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
조 27
 
6.7%

Length

2024-04-16T20:41:33.774644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:33.885497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
조 27
 
6.7%

lghtfacilinillu
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
조명시설조도
 
27

Length

Max length6
Median length4
Mean length4.1336634
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
조명시설조도 27
 
6.7%

Length

2024-04-16T20:41:34.005095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:34.108719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
조명시설조도 27
 
6.7%

nearenvnm
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
316 
기타
32 
주변환경명
 
27
유흥업소밀집지역
 
18
아파트지역
 
9

Length

Max length8
Median length4
Mean length4.1287129
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 316
78.2%
기타 32
 
7.9%
주변환경명 27
 
6.7%
유흥업소밀집지역 18
 
4.5%
아파트지역 9
 
2.2%
학교정화(상대) 2
 
0.5%

Length

2024-04-16T20:41:34.199451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:34.299705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 316
78.2%
기타 32
 
7.9%
주변환경명 27
 
6.7%
유흥업소밀집지역 18
 
4.5%
아파트지역 9
 
2.2%
학교정화(상대 2
 
0.5%

jisgnumlay
Categorical

Distinct21
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
151 
10
37 
7
28 
지상층수
26 
9
25 
Other values (16)
137 

Length

Max length4
Median length2
Mean length2.5915842
Min length1

Unique

Unique4 ?
Unique (%)1.0%

Sample

1st row4
2nd row6
3rd row6
4th row6
5th row6

Common Values

ValueCountFrequency (%)
<NA> 151
37.4%
10 37
 
9.2%
7 28
 
6.9%
지상층수 26
 
6.4%
9 25
 
6.2%
5 20
 
5.0%
8 19
 
4.7%
42 17
 
4.2%
12 15
 
3.7%
6 12
 
3.0%
Other values (11) 54
 
13.4%

Length

2024-04-16T20:41:34.413708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 151
37.4%
10 37
 
9.2%
7 28
 
6.9%
지상층수 26
 
6.4%
9 25
 
6.2%
5 20
 
5.0%
8 19
 
4.7%
42 17
 
4.2%
12 15
 
3.7%
6 12
 
3.0%
Other values (11) 54
 
13.4%

regnsenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
302 
일반상업지역
 
30
지역구분명
 
27
상업지역
 
16
중심상업지역
 
12
Other values (5)
 
17

Length

Max length6
Median length4
Mean length4.3143564
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 302
74.8%
일반상업지역 30
 
7.4%
지역구분명 27
 
6.7%
상업지역 16
 
4.0%
중심상업지역 12
 
3.0%
녹지지역 8
 
2.0%
일반주거지역 4
 
1.0%
근린상업지역 3
 
0.7%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

Length

2024-04-16T20:41:34.527145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:34.649589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 302
74.8%
일반상업지역 30
 
7.4%
지역구분명 27
 
6.7%
상업지역 16
 
4.0%
중심상업지역 12
 
3.0%
녹지지역 8
 
2.0%
일반주거지역 4
 
1.0%
근린상업지역 3
 
0.7%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

undernumlay
Categorical

Distinct11
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
160 
5
51 
2
47 
1
35 
지하층수
26 
Other values (6)
85 

Length

Max length4
Median length1
Mean length2.3861386
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 160
39.6%
5 51
 
12.6%
2 47
 
11.6%
1 35
 
8.7%
지하층수 26
 
6.4%
3 24
 
5.9%
4 21
 
5.2%
6 20
 
5.0%
8 18
 
4.5%
58 1
 
0.2%

Length

2024-04-16T20:41:34.795671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 160
39.6%
5 51
 
12.6%
2 47
 
11.6%
1 35
 
8.7%
지하층수 26
 
6.4%
3 24
 
5.9%
4 21
 
5.2%
6 20
 
5.0%
8 18
 
4.5%
58 1
 
0.2%

bgroomcnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
청소년실수
 
27

Length

Max length5
Median length4
Mean length4.0668317
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
청소년실수 27
 
6.7%

Length

2024-04-16T20:41:34.906477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:34.994897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
청소년실수 27
 
6.7%

bgroomyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
청
 
27

Length

Max length4
Median length4
Mean length3.799505
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
청 27
 
6.7%

Length

2024-04-16T20:41:35.085153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:35.171240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
청 27
 
6.7%

totgasyscnt
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
총게임기수
 
27

Length

Max length5
Median length4
Mean length4.0668317
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
총게임기수 27
 
6.7%

Length

2024-04-16T20:41:35.261063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:35.344433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
총게임기수 27
 
6.7%

totnumlay
Categorical

Distinct18
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
238 
총층수
26 
10
 
20
9
 
12
6
 
12
Other values (13)
96 

Length

Max length4
Median length4
Mean length3.1608911
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 238
58.9%
총층수 26
 
6.4%
10 20
 
5.0%
9 12
 
3.0%
6 12
 
3.0%
11 12
 
3.0%
18 11
 
2.7%
19 10
 
2.5%
15 9
 
2.2%
54 9
 
2.2%
Other values (8) 45
 
11.1%

Length

2024-04-16T20:41:35.431739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 238
58.9%
총층수 26
 
6.4%
10 20
 
5.0%
9 12
 
3.0%
6 12
 
3.0%
11 12
 
3.0%
18 11
 
2.7%
19 10
 
2.5%
54 9
 
2.2%
15 9
 
2.2%
Other values (8) 45
 
11.1%

frstregts
Real number (ℝ)

Distinct125
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20103414
Minimum19451015
Maximum20210203
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-16T20:41:35.533740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000516
Q120050111
median20090302
Q320190315
95-th percentile20200501
Maximum20210203
Range759188
Interquartile range (IQR)140204

Descriptive statistics

Standard deviation89193.511
Coefficient of variation (CV)0.0044367346
Kurtosis9.1667212
Mean20103414
Median Absolute Deviation (MAD)79693
Skewness-1.7507283
Sum8.1217791 × 109
Variance7.9554824 × 109
MonotonicityNot monotonic
2024-04-16T20:41:35.660435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190315 12
 
3.0%
20000529 12
 
3.0%
20140822 11
 
2.7%
20010609 11
 
2.7%
20090302 10
 
2.5%
20021112 10
 
2.5%
20050307 10
 
2.5%
20071204 10
 
2.5%
20080527 9
 
2.2%
20200103 9
 
2.2%
Other values (115) 300
74.3%
ValueCountFrequency (%)
19451015 1
0.2%
19591023 1
0.2%
19690925 1
0.2%
19820125 1
0.2%
19910826 1
0.2%
19930814 2
0.5%
19970308 1
0.2%
19980307 1
0.2%
19980319 1
0.2%
19980623 1
0.2%
ValueCountFrequency (%)
20210203 1
 
0.2%
20210202 4
1.0%
20210121 1
 
0.2%
20210120 1
 
0.2%
20210111 1
 
0.2%
20201228 1
 
0.2%
20201113 2
0.5%
20201111 1
 
0.2%
20201027 1
 
0.2%
20201026 1
 
0.2%

pasgbreth
Categorical

IMBALANCE 

Distinct18
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
231 
1
102 
통로너비
26 
1.5
 
12
1.2
 
7
Other values (13)
26 

Length

Max length4
Median length4
Mean length3.1732673
Min length1

Unique

Unique8 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 231
57.2%
1 102
25.2%
통로너비 26
 
6.4%
1.5 12
 
3.0%
1.2 7
 
1.7%
1.45 5
 
1.2%
1.15 4
 
1.0%
1.3 4
 
1.0%
1.7 3
 
0.7%
1.55 2
 
0.5%
Other values (8) 8
 
2.0%

Length

2024-04-16T20:41:35.794779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 231
57.2%
1 102
25.2%
통로너비 26
 
6.4%
1.5 12
 
3.0%
1.2 7
 
1.7%
1.45 5
 
1.2%
1.15 4
 
1.0%
1.3 4
 
1.0%
1.7 3
 
0.7%
1.55 2
 
0.5%
Other values (8) 8
 
2.0%

speclghtyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
특
 
27

Length

Max length4
Median length4
Mean length3.799505
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
특 27
 
6.7%

Length

2024-04-16T20:41:35.907378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:36.004664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
특 27
 
6.7%

cnvefacilyn
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
편
 
27

Length

Max length4
Median length4
Mean length3.799505
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
편 27
 
6.7%

Length

2024-04-16T20:41:36.090547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:36.175739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
편 27
 
6.7%

actlnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
377 
품목명
 
27

Length

Max length4
Median length4
Mean length3.9331683
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
93.3%
품목명 27
 
6.7%

Length

2024-04-16T20:41:36.269724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:36.354868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 377
93.3%
품목명 27
 
6.7%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2021-03-01 05:20:03
Maximum2021-03-01 05:20:03
2024-04-16T20:41:36.423415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:41:36.504592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
013250000CDFF422000200500000103_13_02_PI2018-08-31 23:59:59.0<NA>국도극장 예술관600805부산광역시 중구 부평동1가 45-9번지48947부산광역시 중구 중구로 13 (부평동1가)2005041520080501<NA><NA><NA>03폐업384872.100538179957.08923720080506140353<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4<NA><NA><NA><NA><NA><NA>20050415<NA><NA><NA><NA>2021-03-01 05:20:03
123250000CDFF422000201700000303_13_02_PU2020-01-19 02:40:00.0영화상영관롯데시네마 대영 제3관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448098179597.59295420200117162055<NA>051-123-1234<NA>영화관<NA><NA><NA>영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6상업지역4<NA><NA><NA><NA>20170309<NA><NA><NA><NA>2021-03-01 05:20:03
233250000CDFF422000201700000603_13_02_PU2020-01-19 02:40:00.0영화상영관롯데시네마 대영 제6관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448098179597.59295420200117162131<NA>051-123-1234<NA>영화관<NA><NA><NA>영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6상업지역4<NA><NA><NA><NA>20170309<NA><NA><NA><NA>2021-03-01 05:20:03
343250000CDFF422000201700000503_13_02_PU2020-01-19 02:40:00.0영화상영관롯데시네마 대영 제5관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448098179597.59295420200117162119<NA>051-123-1234<NA>영화관<NA><NA><NA>영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6상업지역4<NA><NA><NA><NA>20170309<NA><NA><NA><NA>2021-03-01 05:20:03
453250000CDFF422000198200000103_13_02_PI2018-08-31 23:59:59.0<NA>메가박스 부산극장 1관<NA>부산광역시 중구 남포동5가 18-1번지48947부산광역시 중구 비프광장로 36 (남포동5가)19820125<NA><NA><NA><NA>13영업중384992.283249179919.43700920180621102116<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>1<NA><NA><NA><NA>19820125<NA><NA><NA><NA>2021-03-01 05:20:03
563250000CDFF422000199300000103_13_02_PI2018-08-31 23:59:59.0<NA>메가박스 부산극장 2관<NA>부산광역시 중구 남포동5가 18-1번지48947부산광역시 중구 비프광장로 36 (남포동5가)19930814<NA><NA><NA><NA>13영업중384992.283249179919.43700920180621102237<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19930814<NA><NA><NA><NA>2021-03-01 05:20:03
673250000CDFF422000199300000203_13_02_PI2018-08-31 23:59:59.0<NA>메가박스 부산극장 3관<NA>부산광역시 중구 남포동5가 18-1번지48947부산광역시 중구 비프광장로 36 (남포동5가)19930814<NA><NA><NA><NA>13영업중384992.283249179919.43700920180621103110<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>1<NA><NA><NA><NA>19930814<NA><NA><NA><NA>2021-03-01 05:20:03
783250000CDFF422000199800000103_13_02_PI2018-08-31 23:59:59.0<NA>삼보극장600807부산광역시 중구 부평동2가 56번지48947<NA>1998030720070725<NA><NA><NA>03폐업<NA><NA>20070725183312<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19980307<NA><NA><NA><NA>2021-03-01 05:20:03
893250000CDFF422000199900000103_13_02_PI2018-08-31 23:59:59.0<NA>대영시네마 1관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37 (남포동5가)1999071620160617<NA><NA><NA>03폐업385057.258081179919.48808420160617104121<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1019990716<NA><NA><NA><NA>2021-03-01 05:20:03
9103250000CDFF422000199900000203_13_02_PI2018-08-31 23:59:59.0<NA>대영시네마 2관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37 (남포동5가)1999071620160617<NA><NA><NA>03폐업385057.258081179919.48808420160617104156<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>4<NA><NA><NA><NA>19990716<NA><NA><NA><NA>2021-03-01 05:20:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
39426503330000CDFF521101202000000703_13_05_PI2020-11-15 00:23:30.0영화제작업(주)시네포엠지번우편번호부산광역시 해운대구 우동 1460 센텀 T 타워 1203호48059부산광역시 해운대구 센텀중앙로 66, 센텀 T 타워 1203호 (우동)20201113폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393828.352613188165.14841920201113152652업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업방비디오재생기명비비소시설면적음자제공게임물명제작취급품목내용조조명시설조도주변환경명지상층수지역구분명지하층수청소년실수청총게임기수총층수20201113통로너비특편품목명2021-03-01 05:20:03
39527863330000CDFF521101202000000803_13_05_PI2020-12-30 00:23:06.0영화제작업주식회사 퍼플박스<NA>부산광역시 해운대구 우동 1466-1 부산문화콘텐츠컴플렉스 706호48058부산광역시 해운대구 수영강변대로 140, 부산문화콘텐츠컴플렉스 706호 (우동)20201228<NA><NA><NA><NA>영업/정상영업중393573.517297188018.68713820201228171145<NA>070-8899-7402<NA><NA><NA><NA><NA>영화제작업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20201228<NA><NA><NA><NA>2021-03-01 05:20:03
39628463340000CDFF521101202100000103_13_05_PI2021-01-13 00:23:04.0영화제작업키노스타지번우편번호부산광역시 사하구 신평동 599-849431부산광역시 사하구 하신번영로 173, 4층 (신평동)20210111폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중378656.720935179411.18950720210111180613업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업방비디오재생기명비비소시설면적음자제공게임물명제작취급품목내용조조명시설조도주변환경명지상층수지역구분명지하층수청소년실수청총게임기수총층수20210111통로너비특편품목명2021-03-01 05:20:03
39728973330000CDFF521103202100000103_13_01_PI2021-01-22 00:23:04.0영화배급업(주)시네포엠<NA>부산광역시 해운대구 우동 1460 센텀 T 타워 1203호48059부산광역시 해운대구 센텀중앙로 66, 센텀 T 타워 1203호 (우동)20210120<NA><NA><NA><NA>영업/정상영업중393828.352613188165.14841920210120155809<NA><NA><NA><NA><NA><NA><NA>영화배급업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20210120<NA><NA><NA><NA>2021-03-01 05:20:03
39829003250000CDFF521101202100000103_13_05_PI2021-01-23 00:23:11.0영화제작업주식회사 리멘<NA>부산광역시 중구 신창동1가 8-2 BNK부산은행 아트시네마 406호48948부산광역시 중구 광복중앙로 13, BNK부산은행 아트시네마 406호 (신창동1가)20210121<NA><NA><NA><NA>영업/정상영업중385096.938581179823.23303520210121162622<NA><NA><NA><NA><NA><NA><NA>영화제작업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20210121<NA><NA><NA><NA>2021-03-01 05:20:03
39929523330000CDFF521103202100000203_13_01_PI2021-02-04 00:23:03.0영화배급업주식회사 퍼니콘(FUNNYCON Co., Ltd.)지번우편번호부산광역시 해운대구 우동 1466-2 영상산업센터 1008호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 1008호 (우동)20210202폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393674.032956187973.29724320210202122656업태구분명051-704-7125건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화배급업방비디오재생기명비비소시설면적음자제공게임물명제작취급품목내용조조명시설조도주변환경명지상층수지역구분명지하층수청소년실수청총게임기수총층수20210202통로너비특편품목명2021-03-01 05:20:03
40029533330000CDFF521101202100000103_13_05_PI2021-02-04 00:23:03.0영화제작업주식회사 퍼니콘(FUNNYCON Co., Ltd.)<NA>부산광역시 해운대구 우동 1466-2 영상산업센터 1008호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 1008호 (우동)20210202<NA><NA><NA><NA>영업/정상영업중393674.032956187973.29724320210202122737<NA><NA><NA><NA><NA><NA><NA>영화제작업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20210202<NA><NA><NA><NA>2021-03-01 05:20:03
40129553330000CDFF521102202100000103_13_04_PI2021-02-04 00:23:03.0영화수입업주식회사 퍼니콘(FUNNYCON Co., Ltd.)<NA>부산광역시 해운대구 우동 1466-2 영상산업센터 1008호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 1008호 (우동)20210202<NA><NA><NA><NA>영업/정상영업중393674.032956187973.29724320210202122805<NA><NA><NA><NA><NA><NA><NA>영화수입업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20210202<NA><NA><NA><NA>2021-03-01 05:20:03
40229583330000CDFF521104202100000103_13_03_PI2021-02-04 00:23:03.0영화상영업주식회사 퍼니콘(FUNNYCON Co., Ltd.)<NA>부산광역시 해운대구 우동 1466-2 영상산업센터 1008호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 1008호 (우동)20210202<NA><NA><NA><NA>영업/정상영업중393674.032956187973.29724320210202122837<NA><NA><NA><NA><NA><NA><NA>영화상영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20210202<NA><NA><NA><NA>2021-03-01 05:20:03
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