Overview

Dataset statistics

Number of variables56
Number of observations495
Missing cells41
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory220.1 KiB
Average record size in memory455.3 B

Variable types

Numeric7
Text5
Categorical43
DateTime1

Alerts

last_load_dttm has constant value ""Constant
sitepostno is highly imbalanced (72.1%)Imbalance
dcbymd is highly imbalanced (62.0%)Imbalance
trdstatenm is highly imbalanced (55.8%)Imbalance
dtlstatenm is highly imbalanced (63.5%)Imbalance
facilar is highly imbalanced (51.1%)Imbalance
regnsenm is highly imbalanced (51.8%)Imbalance
rdnpostno has 21 (4.2%) missing valuesMissing
rdnwhladdr has 6 (1.2%) missing valuesMissing
x has 6 (1.2%) missing valuesMissing
y has 6 (1.2%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 11:36:39.241369
Analysis finished2024-04-16 11:36:40.092588
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct495
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1038.5899
Minimum1
Maximum3102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-16T20:36:40.147842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.7
Q1124.5
median248
Q32045
95-th percentile3077.3
Maximum3102
Range3101
Interquartile range (IQR)1920.5

Descriptive statistics

Standard deviation1183.3402
Coefficient of variation (CV)1.1393719
Kurtosis-1.0377172
Mean1038.5899
Median Absolute Deviation (MAD)218
Skewness0.81811649
Sum514102
Variance1400293.9
MonotonicityNot monotonic
2024-04-16T20:36:40.277683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
1285 1
 
0.2%
1542 1
 
0.2%
1525 1
 
0.2%
1523 1
 
0.2%
1477 1
 
0.2%
1459 1
 
0.2%
1453 1
 
0.2%
1443 1
 
0.2%
1427 1
 
0.2%
Other values (485) 485
98.0%
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 (%)
3102 1
0.2%
3101 1
0.2%
3100 1
0.2%
3099 1
0.2%
3098 1
0.2%
3097 1
0.2%
3096 1
0.2%
3095 1
0.2%
3094 1
0.2%
3093 1
0.2%

opnsfteamcode
Real number (ℝ)

Distinct15
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3320444.4
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-16T20:36:40.413207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13290000
median3330000
Q33340000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation40809.179
Coefficient of variation (CV)0.012290276
Kurtosis-0.51365192
Mean3320444.4
Median Absolute Deviation (MAD)30000
Skewness0.0837672
Sum1.64362 × 109
Variance1.6653891 × 109
MonotonicityNot monotonic
2024-04-16T20:36:40.510750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3330000 130
26.3%
3290000 88
17.8%
3250000 56
11.3%
3300000 30
 
6.1%
3350000 28
 
5.7%
3320000 27
 
5.5%
3380000 27
 
5.5%
3400000 26
 
5.3%
3310000 21
 
4.2%
3390000 15
 
3.0%
Other values (5) 47
 
9.5%
ValueCountFrequency (%)
3250000 56
11.3%
3260000 2
 
0.4%
3270000 9
 
1.8%
3290000 88
17.8%
3300000 30
 
6.1%
3310000 21
 
4.2%
3320000 27
 
5.5%
3330000 130
26.3%
3340000 13
 
2.6%
3350000 28
 
5.7%
ValueCountFrequency (%)
3400000 26
 
5.3%
3390000 15
 
3.0%
3380000 27
 
5.5%
3370000 9
 
1.8%
3360000 14
 
2.8%
3350000 28
 
5.7%
3340000 13
 
2.6%
3330000 130
26.3%
3320000 27
 
5.5%
3310000 21
 
4.2%

mgtno
Text

Distinct256
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-16T20:36:40.703390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters9900
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

Unique149 ?
Unique (%)30.1%

Sample

1st rowCDFF4220002005000001
2nd rowCDFF4220002017000003
3rd rowCDFF4220002017000006
4th rowCDFF4220002017000005
5th rowCDFF4220001982000001
ValueCountFrequency (%)
cdff5211012020000001 18
 
3.6%
cdff5211012021000001 13
 
2.6%
cdff5211012019000001 12
 
2.4%
cdff5211012020000002 9
 
1.8%
cdff5211012021000002 9
 
1.8%
cdff5211012022000001 8
 
1.6%
cdff5211032020000001 8
 
1.6%
cdff5211042021000001 8
 
1.6%
cdff5211032019000001 8
 
1.6%
cdff5211012022000002 6
 
1.2%
Other values (246) 396
80.0%
2024-04-16T20:36:40.999762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4285
43.3%
2 1552
 
15.7%
1 993
 
10.0%
F 990
 
10.0%
C 495
 
5.0%
D 495
 
5.0%
4 394
 
4.0%
5 259
 
2.6%
9 135
 
1.4%
3 94
 
0.9%
Other values (3) 208
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7920
80.0%
Uppercase Letter 1980
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4285
54.1%
2 1552
 
19.6%
1 993
 
12.5%
4 394
 
5.0%
5 259
 
3.3%
9 135
 
1.7%
3 94
 
1.2%
7 84
 
1.1%
6 65
 
0.8%
8 59
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
F 990
50.0%
C 495
25.0%
D 495
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7920
80.0%
Latin 1980
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4285
54.1%
2 1552
 
19.6%
1 993
 
12.5%
4 394
 
5.0%
5 259
 
3.3%
9 135
 
1.7%
3 94
 
1.2%
7 84
 
1.1%
6 65
 
0.8%
8 59
 
0.7%
Latin
ValueCountFrequency (%)
F 990
50.0%
C 495
25.0%
D 495
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4285
43.3%
2 1552
 
15.7%
1 993
 
10.0%
F 990
 
10.0%
C 495
 
5.0%
D 495
 
5.0%
4 394
 
4.0%
5 259
 
2.6%
9 135
 
1.4%
3 94
 
0.9%
Other values (3) 208
 
2.1%

opnsvcid
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
03_13_02_P
302 
03_13_05_P
131 
03_13_01_P
32 
03_13_03_P
 
22
03_13_04_P
 
8

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 302
61.0%
03_13_05_P 131
26.5%
03_13_01_P 32
 
6.5%
03_13_03_P 22
 
4.4%
03_13_04_P 8
 
1.6%

Length

2024-04-16T20:36:41.118645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:41.201697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_13_02_p 302
61.0%
03_13_05_p 131
26.5%
03_13_01_p 32
 
6.5%
03_13_03_p 22
 
4.4%
03_13_04_p 8
 
1.6%

updategbn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
U
252 
I
243 

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 (%)
U 252
50.9%
I 243
49.1%

Length

2024-04-16T20:36:41.290788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:41.365774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 252
50.9%
i 243
49.1%
Distinct133
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2018-08-31 23:59:59
Maximum2022-04-29 00:22:33
2024-04-16T20:36:41.462466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:36:41.582250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
영화상영관
205 
영화제작업
131 
<NA>
97 
영화배급업
32 
영화상영업
22 

Length

Max length5
Median length5
Mean length4.8040404
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화상영관 205
41.4%
영화제작업 131
26.5%
<NA> 97
19.6%
영화배급업 32
 
6.5%
영화상영업 22
 
4.4%
영화수입업 8
 
1.6%

Length

2024-04-16T20:36:41.695536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:41.776371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 205
41.4%
영화제작업 131
26.5%
na 97
19.6%
영화배급업 32
 
6.5%
영화상영업 22
 
4.4%
영화수입업 8
 
1.6%

bplcnm
Text

Distinct408
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-16T20:36:41.970238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length10.793939
Min length2

Characters and Unicode

Total characters5343
Distinct characters271
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

Unique361 ?
Unique (%)72.9%

Sample

1st row국도극장 예술관
2nd row롯데시네마 대영 제3관
3rd row롯데시네마 대영 제6관
4th row롯데시네마 대영 제5관
5th row메가박스 부산극장 1관
ValueCountFrequency (%)
롯데시네마 92
 
8.7%
메가박스 48
 
4.5%
주식회사 42
 
4.0%
cgv 41
 
3.9%
해운대 26
 
2.4%
서면 20
 
1.9%
센텀시티 19
 
1.8%
제3관 16
 
1.5%
6관 16
 
1.5%
정관 15
 
1.4%
Other values (261) 728
68.5%
2024-04-16T20:36:42.320270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
570
 
10.7%
329
 
6.2%
170
 
3.2%
154
 
2.9%
150
 
2.8%
145
 
2.7%
132
 
2.5%
C 111
 
2.1%
111
 
2.1%
108
 
2.0%
Other values (261) 3363
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3771
70.6%
Space Separator 570
 
10.7%
Uppercase Letter 457
 
8.6%
Decimal Number 299
 
5.6%
Close Punctuation 105
 
2.0%
Open Punctuation 105
 
2.0%
Lowercase Letter 23
 
0.4%
Other Punctuation 12
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
329
 
8.7%
170
 
4.5%
154
 
4.1%
150
 
4.0%
145
 
3.8%
132
 
3.5%
111
 
2.9%
108
 
2.9%
107
 
2.8%
81
 
2.1%
Other values (212) 2284
60.6%
Uppercase Letter
ValueCountFrequency (%)
C 111
24.3%
G 90
19.7%
V 88
19.3%
N 26
 
5.7%
O 16
 
3.5%
E 15
 
3.3%
I 13
 
2.8%
M 12
 
2.6%
A 11
 
2.4%
T 10
 
2.2%
Other values (13) 65
14.2%
Decimal Number
ValueCountFrequency (%)
1 48
16.1%
2 44
14.7%
4 40
13.4%
3 34
11.4%
6 33
11.0%
5 32
10.7%
7 25
8.4%
8 18
 
6.0%
9 17
 
5.7%
0 8
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
o 7
30.4%
d 5
21.7%
t 4
17.4%
m 3
13.0%
g 1
 
4.3%
i 1
 
4.3%
l 1
 
4.3%
s 1
 
4.3%
Close Punctuation
ValueCountFrequency (%)
) 104
99.0%
] 1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 104
99.0%
[ 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
, 4
33.3%
Space Separator
ValueCountFrequency (%)
570
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3771
70.6%
Common 1092
 
20.4%
Latin 480
 
9.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
329
 
8.7%
170
 
4.5%
154
 
4.1%
150
 
4.0%
145
 
3.8%
132
 
3.5%
111
 
2.9%
108
 
2.9%
107
 
2.8%
81
 
2.1%
Other values (212) 2284
60.6%
Latin
ValueCountFrequency (%)
C 111
23.1%
G 90
18.8%
V 88
18.3%
N 26
 
5.4%
O 16
 
3.3%
E 15
 
3.1%
I 13
 
2.7%
M 12
 
2.5%
A 11
 
2.3%
T 10
 
2.1%
Other values (21) 88
18.3%
Common
ValueCountFrequency (%)
570
52.2%
) 104
 
9.5%
( 104
 
9.5%
1 48
 
4.4%
2 44
 
4.0%
4 40
 
3.7%
3 34
 
3.1%
6 33
 
3.0%
5 32
 
2.9%
7 25
 
2.3%
Other values (8) 58
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3771
70.6%
ASCII 1572
29.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
570
36.3%
C 111
 
7.1%
) 104
 
6.6%
( 104
 
6.6%
G 90
 
5.7%
V 88
 
5.6%
1 48
 
3.1%
2 44
 
2.8%
4 40
 
2.5%
3 34
 
2.2%
Other values (39) 339
21.6%
Hangul
ValueCountFrequency (%)
329
 
8.7%
170
 
4.5%
154
 
4.1%
150
 
4.0%
145
 
3.8%
132
 
3.5%
111
 
2.9%
108
 
2.9%
107
 
2.8%
81
 
2.1%
Other values (212) 2284
60.6%

sitepostno
Categorical

IMBALANCE 

Distinct16
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
377 
지번우편번호
96 
614845
 
4
600805
 
3
601060
 
3
Other values (11)
 
12

Length

Max length6
Median length4
Mean length4.4767677
Min length4

Unique

Unique10 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 377
76.2%
지번우편번호 96
 
19.4%
614845 4
 
0.8%
600805 3
 
0.6%
601060 3
 
0.6%
600046 2
 
0.4%
600807 1
 
0.2%
600801 1
 
0.2%
600045 1
 
0.2%
614847 1
 
0.2%
Other values (6) 6
 
1.2%

Length

2024-04-16T20:36:42.496609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 377
76.2%
지번우편번호 96
 
19.4%
614845 4
 
0.8%
600805 3
 
0.6%
601060 3
 
0.6%
600046 2
 
0.4%
600807 1
 
0.2%
600801 1
 
0.2%
600045 1
 
0.2%
614847 1
 
0.2%
Other values (6) 6
 
1.2%
Distinct170
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-16T20:36:42.767927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length26.464646
Min length18

Characters and Unicode

Total characters13100
Distinct characters252
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

Unique82 ?
Unique (%)16.6%

Sample

1st row부산광역시 중구 부평동1가 45-9번지
2nd row부산광역시 중구 남포동5가 12-1
3rd row부산광역시 중구 남포동5가 12-1
4th row부산광역시 중구 남포동5가 12-1
5th row부산광역시 중구 남포동5가 18-1번지
ValueCountFrequency (%)
부산광역시 495
 
20.2%
해운대구 130
 
5.3%
우동 96
 
3.9%
부산진구 88
 
3.6%
60
 
2.4%
중구 56
 
2.3%
부전동 53
 
2.2%
동래구 30
 
1.2%
금정구 28
 
1.1%
수영구 27
 
1.1%
Other values (334) 1388
56.6%
2024-04-16T20:36:43.099904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2402
18.3%
691
 
5.3%
644
 
4.9%
534
 
4.1%
534
 
4.1%
506
 
3.9%
497
 
3.8%
472
 
3.6%
1 471
 
3.6%
- 421
 
3.2%
Other values (242) 5928
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7554
57.7%
Space Separator 2402
 
18.3%
Decimal Number 2157
 
16.5%
Dash Punctuation 421
 
3.2%
Other Punctuation 371
 
2.8%
Uppercase Letter 150
 
1.1%
Lowercase Letter 15
 
0.1%
Close Punctuation 12
 
0.1%
Open Punctuation 12
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
691
 
9.1%
644
 
8.5%
534
 
7.1%
534
 
7.1%
506
 
6.7%
497
 
6.6%
472
 
6.2%
208
 
2.8%
179
 
2.4%
177
 
2.3%
Other values (206) 3112
41.2%
Uppercase Letter
ValueCountFrequency (%)
K 35
23.3%
T 21
14.0%
S 19
12.7%
G 16
10.7%
B 11
 
7.3%
C 10
 
6.7%
U 10
 
6.7%
H 10
 
6.7%
Y 9
 
6.0%
N 8
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 471
21.8%
2 313
14.5%
5 227
10.5%
6 221
10.2%
4 198
9.2%
0 164
 
7.6%
8 156
 
7.2%
7 153
 
7.1%
3 142
 
6.6%
9 112
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
e 5
33.3%
o 3
20.0%
h 2
 
13.3%
r 2
 
13.3%
l 1
 
6.7%
i 1
 
6.7%
v 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
* 338
91.1%
, 18
 
4.9%
& 15
 
4.0%
Space Separator
ValueCountFrequency (%)
2402
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 421
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7554
57.7%
Common 5381
41.1%
Latin 165
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
691
 
9.1%
644
 
8.5%
534
 
7.1%
534
 
7.1%
506
 
6.7%
497
 
6.6%
472
 
6.2%
208
 
2.8%
179
 
2.4%
177
 
2.3%
Other values (206) 3112
41.2%
Common
ValueCountFrequency (%)
2402
44.6%
1 471
 
8.8%
- 421
 
7.8%
* 338
 
6.3%
2 313
 
5.8%
5 227
 
4.2%
6 221
 
4.1%
4 198
 
3.7%
0 164
 
3.0%
8 156
 
2.9%
Other values (8) 470
 
8.7%
Latin
ValueCountFrequency (%)
K 35
21.2%
T 21
12.7%
S 19
11.5%
G 16
9.7%
B 11
 
6.7%
C 10
 
6.1%
U 10
 
6.1%
H 10
 
6.1%
Y 9
 
5.5%
N 8
 
4.8%
Other values (8) 16
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7554
57.7%
ASCII 5546
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2402
43.3%
1 471
 
8.5%
- 421
 
7.6%
* 338
 
6.1%
2 313
 
5.6%
5 227
 
4.1%
6 221
 
4.0%
4 198
 
3.6%
0 164
 
3.0%
8 156
 
2.8%
Other values (26) 635
 
11.4%
Hangul
ValueCountFrequency (%)
691
 
9.1%
644
 
8.5%
534
 
7.1%
534
 
7.1%
506
 
6.7%
497
 
6.6%
472
 
6.2%
208
 
2.8%
179
 
2.4%
177
 
2.3%
Other values (206) 3112
41.2%

rdnpostno
Text

MISSING 

Distinct99
Distinct (%)20.9%
Missing21
Missing (%)4.2%
Memory size4.0 KiB
2024-04-16T20:36:43.325846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0084388
Min length5

Characters and Unicode

Total characters2374
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)8.4%

Sample

1st row48947
2nd row48953
3rd row48953
4th row48953
5th row48947
ValueCountFrequency (%)
48947 49
 
10.3%
48058 49
 
10.3%
48953 20
 
4.2%
48059 16
 
3.4%
47296 16
 
3.4%
46726 14
 
3.0%
47299 12
 
2.5%
47288 12
 
2.5%
48944 11
 
2.3%
47285 11
 
2.3%
Other values (89) 264
55.7%
2024-04-16T20:36:43.672857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 618
26.0%
8 402
16.9%
7 244
 
10.3%
9 239
 
10.1%
5 172
 
7.2%
2 171
 
7.2%
0 165
 
7.0%
6 158
 
6.7%
1 101
 
4.3%
3 90
 
3.8%
Other values (7) 14
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2360
99.4%
Other Letter 14
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 618
26.2%
8 402
17.0%
7 244
 
10.3%
9 239
 
10.1%
5 172
 
7.3%
2 171
 
7.2%
0 165
 
7.0%
6 158
 
6.7%
1 101
 
4.3%
3 90
 
3.8%
Other Letter
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2360
99.4%
Hangul 14
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
4 618
26.2%
8 402
17.0%
7 244
 
10.3%
9 239
 
10.1%
5 172
 
7.3%
2 171
 
7.2%
0 165
 
7.0%
6 158
 
6.7%
1 101
 
4.3%
3 90
 
3.8%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2360
99.4%
Hangul 14
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 618
26.2%
8 402
17.0%
7 244
 
10.3%
9 239
 
10.1%
5 172
 
7.3%
2 171
 
7.2%
0 165
 
7.0%
6 158
 
6.7%
1 101
 
4.3%
3 90
 
3.8%
Hangul
ValueCountFrequency (%)
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%
2
14.3%

rdnwhladdr
Text

MISSING 

Distinct171
Distinct (%)35.0%
Missing6
Missing (%)1.2%
Memory size4.0 KiB
2024-04-16T20:36:43.933232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length33.417178
Min length22

Characters and Unicode

Total characters16341
Distinct characters282
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

Unique82 ?
Unique (%)16.8%

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 489
 
15.5%
해운대구 130
 
4.1%
부산진구 88
 
2.8%
우동 86
 
2.7%
60
 
1.9%
중앙대로 56
 
1.8%
중구 53
 
1.7%
부전동 53
 
1.7%
해운대로 46
 
1.5%
43
 
1.4%
Other values (438) 2046
65.0%
2024-04-16T20:36:44.303488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2686
 
16.4%
704
 
4.3%
651
 
4.0%
605
 
3.7%
548
 
3.4%
545
 
3.3%
491
 
3.0%
488
 
3.0%
( 479
 
2.9%
) 479
 
2.9%
Other values (272) 8665
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9663
59.1%
Space Separator 2686
 
16.4%
Decimal Number 1947
 
11.9%
Other Punctuation 867
 
5.3%
Open Punctuation 482
 
2.9%
Close Punctuation 482
 
2.9%
Uppercase Letter 159
 
1.0%
Dash Punctuation 27
 
0.2%
Lowercase Letter 16
 
0.1%
Math Symbol 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
704
 
7.3%
651
 
6.7%
605
 
6.3%
548
 
5.7%
545
 
5.6%
491
 
5.1%
488
 
5.1%
474
 
4.9%
390
 
4.0%
212
 
2.2%
Other values (231) 4555
47.1%
Uppercase Letter
ValueCountFrequency (%)
K 35
22.0%
T 21
13.2%
S 19
11.9%
G 15
9.4%
B 12
 
7.5%
C 11
 
6.9%
H 10
 
6.3%
U 10
 
6.3%
Y 9
 
5.7%
N 8
 
5.0%
Other values (3) 9
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 371
19.1%
2 266
13.7%
0 216
11.1%
3 215
11.0%
6 170
8.7%
5 162
8.3%
7 157
8.1%
4 148
 
7.6%
9 122
 
6.3%
8 120
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 5
31.2%
o 3
18.8%
h 2
 
12.5%
r 2
 
12.5%
p 1
 
6.2%
l 1
 
6.2%
i 1
 
6.2%
v 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 442
51.0%
* 410
47.3%
& 15
 
1.7%
Open Punctuation
ValueCountFrequency (%)
( 479
99.4%
[ 3
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 479
99.4%
] 3
 
0.6%
Space Separator
ValueCountFrequency (%)
2686
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9663
59.1%
Common 6503
39.8%
Latin 175
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
704
 
7.3%
651
 
6.7%
605
 
6.3%
548
 
5.7%
545
 
5.6%
491
 
5.1%
488
 
5.1%
474
 
4.9%
390
 
4.0%
212
 
2.2%
Other values (231) 4555
47.1%
Latin
ValueCountFrequency (%)
K 35
20.0%
T 21
12.0%
S 19
10.9%
G 15
8.6%
B 12
 
6.9%
C 11
 
6.3%
H 10
 
5.7%
U 10
 
5.7%
Y 9
 
5.1%
N 8
 
4.6%
Other values (11) 25
14.3%
Common
ValueCountFrequency (%)
2686
41.3%
( 479
 
7.4%
) 479
 
7.4%
, 442
 
6.8%
* 410
 
6.3%
1 371
 
5.7%
2 266
 
4.1%
0 216
 
3.3%
3 215
 
3.3%
6 170
 
2.6%
Other values (10) 769
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9663
59.1%
ASCII 6678
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2686
40.2%
( 479
 
7.2%
) 479
 
7.2%
, 442
 
6.6%
* 410
 
6.1%
1 371
 
5.6%
2 266
 
4.0%
0 216
 
3.2%
3 215
 
3.2%
6 170
 
2.5%
Other values (31) 944
 
14.1%
Hangul
ValueCountFrequency (%)
704
 
7.3%
651
 
6.7%
605
 
6.3%
548
 
5.7%
545
 
5.6%
491
 
5.1%
488
 
5.1%
474
 
4.9%
390
 
4.0%
212
 
2.2%
Other values (231) 4555
47.1%

apvpermymd
Real number (ℝ)

Distinct168
Distinct (%)33.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20123615
Minimum19451015
Maximum20220427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-16T20:36:44.421764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000529
Q120060825
median20160317
Q320200304
95-th percentile20211215
Maximum20220427
Range769412
Interquartile range (IQR)139479

Descriptive statistics

Standard deviation89763.103
Coefficient of variation (CV)0.0044605855
Kurtosis8.30868
Mean20123615
Median Absolute Deviation (MAD)50893
Skewness-1.7729232
Sum9.9611892 × 109
Variance8.0574146 × 109
MonotonicityNot monotonic
2024-04-16T20:36:44.563940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211215 12
 
2.4%
20000529 12
 
2.4%
20190315 12
 
2.4%
20010609 11
 
2.2%
20140822 11
 
2.2%
20050307 10
 
2.0%
20071204 10
 
2.0%
20210615 10
 
2.0%
20021112 10
 
2.0%
20090302 10
 
2.0%
Other values (158) 387
78.2%
ValueCountFrequency (%)
19451015 1
0.2%
19591023 1
0.2%
19690925 1
0.2%
19820125 1
0.2%
19910826 1
0.2%
19930814 2
0.4%
19970308 1
0.2%
19980307 1
0.2%
19980319 1
0.2%
19980623 1
0.2%
ValueCountFrequency (%)
20220427 2
0.4%
20220426 1
0.2%
20220405 2
0.4%
20220325 2
0.4%
20220322 1
0.2%
20220318 2
0.4%
20220302 1
0.2%
20220208 1
0.2%
20220125 2
0.4%
20220119 1
0.2%

dcbymd
Categorical

IMBALANCE 

Distinct39
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
325 
폐업일자
91 
20170315
 
10
20160617
 
8
20110616
 
8
Other values (34)
53 

Length

Max length8
Median length4
Mean length4.6383838
Min length4

Unique

Unique26 ?
Unique (%)5.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 325
65.7%
폐업일자 91
 
18.4%
20170315 10
 
2.0%
20160617 8
 
1.6%
20110616 8
 
1.6%
20100806 7
 
1.4%
20001201 4
 
0.8%
20070725 3
 
0.6%
20211217 3
 
0.6%
20200921 3
 
0.6%
Other values (29) 33
 
6.7%

Length

2024-04-16T20:36:44.693833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 325
65.7%
폐업일자 91
 
18.4%
20170315 10
 
2.0%
20160617 8
 
1.6%
20110616 8
 
1.6%
20100806 7
 
1.4%
20001201 4
 
0.8%
20070725 3
 
0.6%
20211217 3
 
0.6%
20200921 3
 
0.6%
Other values (29) 33
 
6.7%

clgstdt
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
휴업시작일자
96 

Length

Max length6
Median length4
Mean length4.3878788
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
휴업시작일자 96
 
19.4%

Length

2024-04-16T20:36:44.799407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:44.882166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
휴업시작일자 96
 
19.4%

clgenddt
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
휴업종료일자
96 

Length

Max length6
Median length4
Mean length4.3878788
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
휴업종료일자 96
 
19.4%

Length

2024-04-16T20:36:44.977847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:45.062765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
휴업종료일자 96
 
19.4%

ropnymd
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
재개업일자
96 

Length

Max length5
Median length4
Mean length4.1939394
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
재개업일자 96
 
19.4%

Length

2024-04-16T20:36:45.150604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:45.225595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
재개업일자 96
 
19.4%

trdstatenm
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
영업/정상
374 
03
56 
13
40 
폐업
 
15
제외/삭제/전출
 
8
Other values (2)
 
2

Length

Max length8
Median length5
Mean length4.3676768
Min length2

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 374
75.6%
03 56
 
11.3%
13 40
 
8.1%
폐업 15
 
3.0%
제외/삭제/전출 8
 
1.6%
35 1
 
0.2%
<NA> 1
 
0.2%

Length

2024-04-16T20:36:45.310954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:45.402220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 374
75.6%
03 56
 
11.3%
13 40
 
8.1%
폐업 15
 
3.0%
제외/삭제/전출 8
 
1.6%
35 1
 
0.2%
na 1
 
0.2%

dtlstatenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
영업중
415 
폐업
71 
전출
 
8
직권말소
 
1

Length

Max length4
Median length3
Mean length2.8424242
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 415
83.8%
폐업 71
 
14.3%
전출 8
 
1.6%
직권말소 1
 
0.2%

Length

2024-04-16T20:36:45.503710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:45.593451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 415
83.8%
폐업 71
 
14.3%
전출 8
 
1.6%
직권말소 1
 
0.2%

x
Real number (ℝ)

MISSING 

Distinct138
Distinct (%)28.2%
Missing6
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean389594.83
Minimum373470.6
Maximum401669
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-16T20:36:45.688141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum373470.6
5-th percentile379280.63
Q1385622.78
median389691.84
Q3393674.03
95-th percentile398310.24
Maximum401669
Range28198.396
Interquartile range (IQR)8051.2525

Descriptive statistics

Standard deviation5829.329
Coefficient of variation (CV)0.014962542
Kurtosis0.12034248
Mean389594.83
Median Absolute Deviation (MAD)4032.814
Skewness-0.33604509
Sum1.9051187 × 108
Variance33981077
MonotonicityNot monotonic
2024-04-16T20:36:45.802956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393674.032955782 21
 
4.2%
388011.197829908 12
 
2.4%
387608.014165034 11
 
2.2%
385622.780457355 11
 
2.2%
387271.299492377 11
 
2.2%
396915.143441 10
 
2.0%
393952.264486105 10
 
2.0%
398310.243451 10
 
2.0%
394083.501537578 10
 
2.0%
387280.619672939 9
 
1.8%
Other values (128) 374
75.6%
ValueCountFrequency (%)
373470.60373869 7
1.4%
374253.112340712 7
1.4%
377557.995908 1
 
0.2%
378656.720935232 1
 
0.2%
379212.079721725 5
1.0%
379240.573215267 3
0.6%
379280.632039 2
 
0.4%
379546.541691789 1
 
0.2%
379635.65262 1
 
0.2%
380509.783073762 7
1.4%
ValueCountFrequency (%)
401669.0 6
1.2%
401646.70301259 3
 
0.6%
401170.585261685 1
 
0.2%
400819.975248202 1
 
0.2%
398757.078098629 1
 
0.2%
398628.503470003 2
 
0.4%
398330.516530402 2
 
0.4%
398310.243451 10
2.0%
398275.475596001 1
 
0.2%
398269.05154158 7
1.4%

y
Real number (ℝ)

MISSING 

Distinct138
Distinct (%)28.2%
Missing6
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean187422.57
Minimum178757.42
Maximum204621.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-16T20:36:45.932566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum178757.42
5-th percentile179452.22
Q1185310.71
median187480.44
Q3189911.43
95-th percentile195491.52
Maximum204621.66
Range25864.232
Interquartile range (IQR)4600.7252

Descriptive statistics

Standard deviation5292.0027
Coefficient of variation (CV)0.028235675
Kurtosis1.7839018
Mean187422.57
Median Absolute Deviation (MAD)2169.7385
Skewness0.86617659
Sum91649634
Variance28005293
MonotonicityNot monotonic
2024-04-16T20:36:46.047018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187973.297243244 21
 
4.2%
185310.70532509 12
 
2.4%
185703.079007724 11
 
2.2%
179452.224754792 11
 
2.2%
186099.137533193 11
 
2.2%
187480.443811 10
 
2.0%
187602.933160728 10
 
2.0%
188031.67198 10
 
2.0%
187707.586117775 10
 
2.0%
185679.050795793 9
 
1.8%
Other values (128) 374
75.6%
ValueCountFrequency (%)
178757.423271048 7
1.4%
178872.461747926 1
 
0.2%
178919.583231221 7
1.4%
179411.189506548 1
 
0.2%
179452.224754792 11
2.2%
179597.592953541 6
1.2%
179823.23303496 4
 
0.8%
179885.813689 2
 
0.4%
179911.285409 5
1.0%
179919.437009 4
 
0.8%
ValueCountFrequency (%)
204621.655738547 5
1.0%
204597.0 5
1.0%
204401.691446 6
1.2%
196220.454694204 1
 
0.2%
195833.199326362 1
 
0.2%
195491.519782 8
1.6%
195029.489621392 1
 
0.2%
194992.355262 2
 
0.4%
194681.150958776 7
1.4%
194312.723690481 7
1.4%

lastmodts
Real number (ℝ)

Distinct390
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.019393 × 1013
Minimum2.0030127 × 1013
Maximum2.0220427 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-16T20:36:46.173873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030127 × 1013
5-th percentile2.0110616 × 1013
Q12.0190318 × 1013
median2.0210422 × 1013
Q32.0211216 × 1013
95-th percentile2.0220126 × 1013
Maximum2.0220427 × 1013
Range1.903 × 1011
Interquartile range (IQR)2.0898002 × 1010

Descriptive statistics

Standard deviation3.3854519 × 1010
Coefficient of variation (CV)0.0016764701
Kurtosis7.1487429
Mean2.019393 × 1013
Median Absolute Deviation (MAD)7.99937 × 108
Skewness-2.5982659
Sum9.9959954 × 1015
Variance1.1461285 × 1021
MonotonicityNot monotonic
2024-04-16T20:36:46.521037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211220133307 6
 
1.2%
20211220133338 5
 
1.0%
20190920121341 5
 
1.0%
20210421091411 5
 
1.0%
20211216174849 5
 
1.0%
20191017170859 4
 
0.8%
20211217153628 4
 
0.8%
20211220133308 4
 
0.8%
20211220161532 4
 
0.8%
20030127161348 4
 
0.8%
Other values (380) 449
90.7%
ValueCountFrequency (%)
20030127161348 4
0.8%
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 (%)
20220427164939 1
0.2%
20220427161558 1
0.2%
20220426065808 1
0.2%
20220425110619 1
0.2%
20220405100600 1
0.2%
20220405095644 1
0.2%
20220325104350 2
0.4%
20220318084652 2
0.4%
20220314135813 1
0.2%
20220311093350 2
0.4%

uptaenm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
업태구분명
96 

Length

Max length5
Median length4
Mean length4.1939394
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
업태구분명 96
 
19.4%

Length

2024-04-16T20:36:46.642328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:46.732663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
업태구분명 96
 
19.4%

sitetel
Categorical

Distinct42
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
051-123-1234
192 
<NA>
80 
전화번호
56 
910-1411
 
12
070-7495-8542
 
11
Other values (37)
144 

Length

Max length13
Median length12
Mean length9.589899
Min length4

Unique

Unique13 ?
Unique (%)2.6%

Sample

1st row051-123-1234
2nd row070-7438-5100
3rd row070-7438-5100
4th row070-7438-5100
5th row051-123-1234

Common Values

ValueCountFrequency (%)
051-123-1234 192
38.8%
<NA> 80
16.2%
전화번호 56
 
11.3%
910-1411 12
 
2.4%
070-7495-8542 11
 
2.2%
810-3941 11
 
2.2%
051-366-2200 9
 
1.8%
051-745-2883 8
 
1.6%
051-507-0202 7
 
1.4%
364-0480 7
 
1.4%
Other values (32) 102
20.6%

Length

2024-04-16T20:36:46.818520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 192
38.8%
na 80
16.2%
전화번호 56
 
11.3%
910-1411 12
 
2.4%
070-7495-8542 11
 
2.2%
810-3941 11
 
2.2%
051-366-2200 9
 
1.8%
051-745-2883 8
 
1.6%
051-581-5950 7
 
1.4%
070-7465-3972 7
 
1.4%
Other values (32) 102
20.6%

bdngsrvnm
Categorical

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
292 
문화시설
88 
건물용도명
86 
근린생활시설
 
13
유통시설
 
9
Other values (2)
 
7

Length

Max length6
Median length4
Mean length4.2
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 292
59.0%
문화시설 88
 
17.8%
건물용도명 86
 
17.4%
근린생활시설 13
 
2.6%
유통시설 9
 
1.8%
호텔 6
 
1.2%
사무실 1
 
0.2%

Length

2024-04-16T20:36:46.920993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:47.017410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 292
59.0%
문화시설 88
 
17.8%
건물용도명 86
 
17.4%
근린생활시설 13
 
2.6%
유통시설 9
 
1.8%
호텔 6
 
1.2%
사무실 1
 
0.2%

perplaformsenm
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
영화관
294 
<NA>
118 
공연장형태구분명
79 
자동차극장
 
4

Length

Max length8
Median length3
Mean length4.0525253
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화관 294
59.4%
<NA> 118
23.8%
공연장형태구분명 79
 
16.0%
자동차극장 4
 
0.8%

Length

2024-04-16T20:36:47.119934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:47.209433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화관 294
59.4%
na 118
23.8%
공연장형태구분명 79
 
16.0%
자동차극장 4
 
0.8%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
기존게임업외업종명
96 

Length

Max length9
Median length4
Mean length4.969697
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
기존게임업외업종명 96
 
19.4%

Length

2024-04-16T20:36:47.303560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:47.386351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
기존게임업외업종명 96
 
19.4%

noroomcnt
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
351 
0
78 
노래방실수
66 

Length

Max length5
Median length4
Mean length3.6606061
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 351
70.9%
0 78
 
15.8%
노래방실수 66
 
13.3%

Length

2024-04-16T20:36:47.475390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:47.563602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 351
70.9%
0 78
 
15.8%
노래방실수 66
 
13.3%

culwrkrsenm
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
208 
영화상영관
196 
문화사업자구분명
91 

Length

Max length8
Median length5
Mean length5.1313131
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 208
42.0%
영화상영관 196
39.6%
문화사업자구분명 91
18.4%

Length

2024-04-16T20:36:47.655630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:47.752003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 208
42.0%
영화상영관 196
39.6%
문화사업자구분명 91
18.4%

culphyedcobnm
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
영화상영관
302 
영화제작업
129 
영화배급업
32 
영화상영업
 
22
영화수입업
 
8

Length

Max length5
Median length5
Mean length4.9959596
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화상영관 302
61.0%
영화제작업 129
26.1%
영화배급업 32
 
6.5%
영화상영업 22
 
4.4%
영화수입업 8
 
1.6%
<NA> 2
 
0.4%

Length

2024-04-16T20:36:47.845415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:47.936120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 302
61.0%
영화제작업 129
26.1%
영화배급업 32
 
6.5%
영화상영업 22
 
4.4%
영화수입업 8
 
1.6%
na 2
 
0.4%

souarfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
96 

Length

Max length4
Median length4
Mean length3.4181818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
96
 
19.4%

Length

2024-04-16T20:36:48.052294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:48.134983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
96
 
19.4%

vdoretornm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
비디오재생기명
96 

Length

Max length7
Median length4
Mean length4.5818182
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
비디오재생기명 96
 
19.4%

Length

2024-04-16T20:36:48.219980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:48.296947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
비디오재생기명 96
 
19.4%

emerstairyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
96 

Length

Max length4
Median length4
Mean length3.4181818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
96
 
19.4%

Length

2024-04-16T20:36:48.389235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:48.492368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
96
 
19.4%

emexyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
96 

Length

Max length4
Median length4
Mean length3.4181818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
96
 
19.4%

Length

2024-04-16T20:36:48.589144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:48.673374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
96
 
19.4%

firefacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
96 

Length

Max length4
Median length4
Mean length3.4181818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
96
 
19.4%

Length

2024-04-16T20:36:48.761003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:48.837172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
96
 
19.4%

facilar
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
345 
0
78 
시설면적
66 
1578.8
 
4
147.46
 
1

Length

Max length6
Median length4
Mean length3.5494949
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 345
69.7%
0 78
 
15.8%
시설면적 66
 
13.3%
1578.8 4
 
0.8%
147.46 1
 
0.2%
181.3 1
 
0.2%

Length

2024-04-16T20:36:48.918562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:49.000430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 345
69.7%
0 78
 
15.8%
시설면적 66
 
13.3%
1578.8 4
 
0.8%
147.46 1
 
0.2%
181.3 1
 
0.2%

soundfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
96 

Length

Max length4
Median length4
Mean length3.4181818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
96
 
19.4%

Length

2024-04-16T20:36:49.095867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:49.187365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
96
 
19.4%

autochaairyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
96 

Length

Max length4
Median length4
Mean length3.4181818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
96
 
19.4%

Length

2024-04-16T20:36:49.272773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:49.364209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
96
 
19.4%

prvdgathinnm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
제공게임물명
96 

Length

Max length6
Median length4
Mean length4.3878788
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
제공게임물명 96
 
19.4%

Length

2024-04-16T20:36:49.453995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:49.542760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
제공게임물명 96
 
19.4%

mnfactreartclcn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
제작취급품목내용
96 

Length

Max length8
Median length4
Mean length4.7757576
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
제작취급품목내용 96
 
19.4%

Length

2024-04-16T20:36:49.643003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:49.730067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
제작취급품목내용 96
 
19.4%

lghtfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
96 

Length

Max length4
Median length4
Mean length3.4181818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
96
 
19.4%

Length

2024-04-16T20:36:49.819422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:49.898521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
96
 
19.4%

lghtfacilinillu
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
351 
0
78 
조명시설조도
66 

Length

Max length6
Median length4
Mean length3.7939394
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 351
70.9%
0 78
 
15.8%
조명시설조도 66
 
13.3%

Length

2024-04-16T20:36:49.982600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:50.068012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 351
70.9%
0 78
 
15.8%
조명시설조도 66
 
13.3%

nearenvnm
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
344 
주변환경명
90 
기타
 
32
유흥업소밀집지역
 
18
아파트지역
 
9

Length

Max length8
Median length4
Mean length4.2323232
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 344
69.5%
주변환경명 90
 
18.2%
기타 32
 
6.5%
유흥업소밀집지역 18
 
3.6%
아파트지역 9
 
1.8%
학교정화(상대) 2
 
0.4%

Length

2024-04-16T20:36:50.162643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:50.256201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 344
69.5%
주변환경명 90
 
18.2%
기타 32
 
6.5%
유흥업소밀집지역 18
 
3.6%
아파트지역 9
 
1.8%
학교정화(상대 2
 
0.4%

jisgnumlay
Categorical

Distinct23
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
151 
지상층수
56 
10
43 
0
41 
7
28 
Other values (18)
176 

Length

Max length4
Median length2
Mean length2.5171717
Min length1

Unique

Unique4 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 151
30.5%
지상층수 56
 
11.3%
10 43
 
8.7%
0 41
 
8.3%
7 28
 
5.7%
9 27
 
5.5%
5 20
 
4.0%
8 19
 
3.8%
42 17
 
3.4%
13 15
 
3.0%
Other values (13) 78
15.8%

Length

2024-04-16T20:36:50.354787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 151
30.5%
지상층수 56
 
11.3%
10 43
 
8.7%
0 41
 
8.3%
7 28
 
5.7%
9 27
 
5.5%
5 20
 
4.0%
8 19
 
3.8%
42 17
 
3.4%
13 15
 
3.0%
Other values (13) 78
15.8%

regnsenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
331 
지역구분명
89 
일반상업지역
 
30
상업지역
 
16
중심상업지역
 
12
Other values (5)
 
17

Length

Max length6
Median length4
Mean length4.3818182
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 331
66.9%
지역구분명 89
 
18.0%
일반상업지역 30
 
6.1%
상업지역 16
 
3.2%
중심상업지역 12
 
2.4%
녹지지역 8
 
1.6%
일반주거지역 4
 
0.8%
근린상업지역 3
 
0.6%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

Length

2024-04-16T20:36:50.473345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:50.574460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 331
66.9%
지역구분명 89
 
18.0%
일반상업지역 30
 
6.1%
상업지역 16
 
3.2%
중심상업지역 12
 
2.4%
녹지지역 8
 
1.6%
일반주거지역 4
 
0.8%
근린상업지역 3
 
0.6%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

undernumlay
Categorical

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
159 
5
65 
지하층수
57 
2
53 
0
41 
Other values (7)
120 

Length

Max length4
Median length1
Mean length2.3131313
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 159
32.1%
5 65
13.1%
지하층수 57
 
11.5%
2 53
 
10.7%
0 41
 
8.3%
1 35
 
7.1%
3 24
 
4.8%
4 21
 
4.2%
6 20
 
4.0%
8 18
 
3.6%
Other values (2) 2
 
0.4%

Length

2024-04-16T20:36:50.694793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 159
32.1%
5 65
13.1%
지하층수 57
 
11.5%
2 53
 
10.7%
0 41
 
8.3%
1 35
 
7.1%
3 24
 
4.8%
4 21
 
4.2%
6 20
 
4.0%
8 18
 
3.6%
Other values (2) 2
 
0.4%

bgroomcnt
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
351 
0
78 
청소년실수
66 

Length

Max length5
Median length4
Mean length3.6606061
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 351
70.9%
0 78
 
15.8%
청소년실수 66
 
13.3%

Length

2024-04-16T20:36:50.817038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:50.901514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 351
70.9%
0 78
 
15.8%
청소년실수 66
 
13.3%

bgroomyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
96 

Length

Max length4
Median length4
Mean length3.4181818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
96
 
19.4%

Length

2024-04-16T20:36:50.992860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:51.069987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
96
 
19.4%

totgasyscnt
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
351 
0
78 
총게임기수
66 

Length

Max length5
Median length4
Mean length3.6606061
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 351
70.9%
0 78
 
15.8%
총게임기수 66
 
13.3%

Length

2024-04-16T20:36:51.159174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:51.247988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 351
70.9%
0 78
 
15.8%
총게임기수 66
 
13.3%

totnumlay
Categorical

Distinct20
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
237 
총층수
59 
0
47 
10
 
20
12
 
13
Other values (15)
119 

Length

Max length4
Median length3
Mean length2.9151515
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 237
47.9%
총층수 59
 
11.9%
0 47
 
9.5%
10 20
 
4.0%
12 13
 
2.6%
6 12
 
2.4%
11 12
 
2.4%
9 12
 
2.4%
18 11
 
2.2%
19 10
 
2.0%
Other values (10) 62
 
12.5%

Length

2024-04-16T20:36:51.339675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 237
47.9%
총층수 59
 
11.9%
0 47
 
9.5%
10 20
 
4.0%
12 13
 
2.6%
6 12
 
2.4%
11 12
 
2.4%
9 12
 
2.4%
18 11
 
2.2%
19 10
 
2.0%
Other values (10) 62
 
12.5%

frstregts
Real number (ℝ)

Distinct167
Distinct (%)33.9%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean20123222
Minimum19451015
Maximum20220426
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-16T20:36:51.446393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000529
Q120060825
median20151020
Q320200225
95-th percentile20211215
Maximum20220426
Range769411
Interquartile range (IQR)139400

Descriptive statistics

Standard deviation89732.455
Coefficient of variation (CV)0.0044591495
Kurtosis8.3337551
Mean20123222
Median Absolute Deviation (MAD)59806
Skewness-1.7739259
Sum9.9207484 × 109
Variance8.0519135 × 109
MonotonicityNot monotonic
2024-04-16T20:36:51.568544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000529 12
 
2.4%
20211215 12
 
2.4%
20190315 12
 
2.4%
20010609 11
 
2.2%
20140822 11
 
2.2%
20071204 10
 
2.0%
20050307 10
 
2.0%
20021112 10
 
2.0%
20210615 10
 
2.0%
20090302 10
 
2.0%
Other values (157) 385
77.8%
ValueCountFrequency (%)
19451015 1
0.2%
19591023 1
0.2%
19690925 1
0.2%
19820125 1
0.2%
19910826 1
0.2%
19930814 2
0.4%
19970308 1
0.2%
19980307 1
0.2%
19980319 1
0.2%
19980623 1
0.2%
ValueCountFrequency (%)
20220426 1
0.2%
20220405 2
0.4%
20220325 2
0.4%
20220322 1
0.2%
20220318 2
0.4%
20220302 1
0.2%
20220208 1
0.2%
20220125 2
0.4%
20220119 1
0.2%
20220114 2
0.4%

pasgbreth
Categorical

Distinct19
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
218 
1
103 
0
69 
통로너비
60 
1.5
 
12
Other values (14)
33 

Length

Max length4
Median length4
Mean length2.9010101
Min length1

Unique

Unique8 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 218
44.0%
1 103
20.8%
0 69
 
13.9%
통로너비 60
 
12.1%
1.5 12
 
2.4%
1.2 7
 
1.4%
1.45 5
 
1.0%
1.3 4
 
0.8%
1.15 4
 
0.8%
1.7 3
 
0.6%
Other values (9) 10
 
2.0%

Length

2024-04-16T20:36:51.689121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 218
44.0%
1 103
20.8%
0 69
 
13.9%
통로너비 60
 
12.1%
1.5 12
 
2.4%
1.2 7
 
1.4%
1.45 5
 
1.0%
1.3 4
 
0.8%
1.15 4
 
0.8%
1.7 3
 
0.6%
Other values (9) 10
 
2.0%

speclghtyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
96 

Length

Max length4
Median length4
Mean length3.4181818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
96
 
19.4%

Length

2024-04-16T20:36:51.791112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:51.876654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
96
 
19.4%

cnvefacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
96 

Length

Max length4
Median length4
Mean length3.4181818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
96
 
19.4%

Length

2024-04-16T20:36:51.970967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:52.051172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
96
 
19.4%

actlnm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
399 
품목명
96 

Length

Max length4
Median length4
Mean length3.8060606
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 399
80.6%
품목명 96
 
19.4%

Length

2024-04-16T20:36:52.131224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:52.213383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 399
80.6%
품목명 96
 
19.4%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2022-05-01 05:20:03
495 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-05-01 05:20:03
2nd row2022-05-01 05:20:03
3rd row2022-05-01 05:20:03
4th row2022-05-01 05:20:03
5th row2022-05-01 05:20:03

Common Values

ValueCountFrequency (%)
2022-05-01 05:20:03 495
100.0%

Length

2024-04-16T20:36:52.310050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:36:52.387143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-05-01 495
50.0%
05:20:03 495
50.0%

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>2022-05-01 05:20:03
123250000CDFF422000201700000303_13_02_PU2021-12-22 02:40:00.0영화상영관롯데시네마 대영 제3관<NA>부산광역시 중구 남포동5가 12-148953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448098179597.59295420211220135303<NA>070-7438-5100<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>2022-05-01 05:20:03
233250000CDFF422000201700000603_13_02_PU2021-12-22 02:40:00.0영화상영관롯데시네마 대영 제6관<NA>부산광역시 중구 남포동5가 12-148953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448098179597.59295420211220135540<NA>070-7438-5100<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>2022-05-01 05:20:03
343250000CDFF422000201700000503_13_02_PU2021-12-22 02:40:00.0영화상영관롯데시네마 대영 제5관지번우편번호부산광역시 중구 남포동5가 12-148953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중384985.448098179597.59295420211220135431업태구분명070-7438-5100건물용도명영화관기존게임업외업종명노래방실수문화사업자구분명영화상영관비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명6상업지역4청소년실수총게임기수총층수20170309통로너비품목명2022-05-01 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>2022-05-01 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>2022-05-01 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>2022-05-01 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>2022-05-01 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>2022-05-01 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>2022-05-01 05:20:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
48530163400000CDFF521101202100000103_13_05_PI2021-03-31 00:22:59.0영화제작업필름상가509호지번우편번호부산광역시 기장군 기장읍 대라리 1000 월가 아델리스 아파트 304호46067부산광역시 기장군 기장읍 차성남로 23, 304호 (월가 아델리스 아파트)20210329폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중401170.585262195833.19932620210329113916업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210329통로너비품목명2022-05-01 05:20:03
48630173380000CDFF521101202100000203_13_05_PI2021-04-01 00:22:58.0영화제작업탄탄필름지번우편번호부산광역시 수영구 광안동 158-28 광안그린빌라 501호48296부산광역시 수영구 광안로49번길 40, 501호 (광안동, 광안그린빌라)20210330폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392991.646291186220.25001820210330103227업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210330통로너비품목명2022-05-01 05:20:03
48730183330000CDFF521101202100000403_13_05_PU2021-04-29 02:40:00.0영화제작업공감지번우편번호부산광역시 해운대구 우동 1466-2 영상산업센터 902호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 902호 (우동)20210405폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393674.032956187973.29724320210427092012업태구분명070-4407-6252건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210405통로너비품목명2022-05-01 05:20:03
48830193360000CDFF521104202100000103_13_03_PU2021-06-13 02:40:00.0영화상영업롯데시네마 부산 명지점지번우편번호부산광역시 강서구 명지동 3432-346726부산광역시 강서구 명지국제6로 107, 부산명지 대방디엠시티 센텀오션 2차 2층 (명지동)20210512폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중374253.112341178757.42327120210611144411업태구분명070-4159-8881건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210512통로너비품목명2022-05-01 05:20:03
48930203330000CDFF521103202100000303_13_01_PI2021-05-15 00:22:56.0영화배급업주식회사 엠앤미디어지번우편번호부산광역시 해운대구 우동 1466-1 부산문화콘텐츠컴플렉스 5층 부산콘텐츠코리아랩48058부산광역시 해운대구 수영강변대로 140, 부산문화콘텐츠컴플렉스 5층 부산콘텐츠코리아랩 (우동)20210513폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393573.517297188018.68713820210513125315업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화배급업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210513통로너비품목명2022-05-01 05:20:03
49030213330000CDFF521101202100000503_13_05_PI2021-05-15 00:22:56.0영화제작업주식회사 엠앤미디어<NA>부산광역시 해운대구 우동 1466-1 부산문화콘텐츠컴플렉스 5층 부산콘텐츠코리아랩48058부산광역시 해운대구 수영강변대로 140, 부산문화콘텐츠컴플렉스 5층 부산콘텐츠코리아랩 (우동)20210513<NA><NA><NA><NA>영업/정상영업중393573.517297188018.68713820210513125158<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>20210513<NA><NA><NA><NA>2022-05-01 05:20:03
49130223250000CDFF521102202100000103_13_04_PI2021-05-15 00:22:56.0영화수입업주식회사 라라아비스<NA>부산광역시 중구 신창동1가 8-248948부산광역시 중구 광복중앙로 13, 4층 6호 (신창동1가)20161013<NA><NA><NA><NA>영업/정상영업중385096.938581179823.23303520210513163139<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>20161013<NA><NA><NA><NA>2022-05-01 05:20:03
49230233250000CDFF521103202100000103_13_01_PI2021-05-15 00:22:56.0영화배급업주식회사 라라아비스<NA>부산광역시 중구 신창동1가 8-248948부산광역시 중구 광복중앙로 13, 4층 6호 (신창동1가)20161013<NA><NA><NA><NA>영업/정상영업중385096.938581179823.23303520210513163400<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>20161013<NA><NA><NA><NA>2022-05-01 05:20:03
49330243250000CDFF521101202100000203_13_05_PI2021-05-15 00:22:56.0영화제작업주식회사 라라아비스<NA>부산광역시 중구 신창동1가 8-248948부산광역시 중구 광복중앙로 13, 4층 6호 (신창동1가)20161013<NA><NA><NA><NA>영업/정상영업중385096.938581179823.23303520210513162803<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>20161013<NA><NA><NA><NA>2022-05-01 05:20:03
49430253290000CDFF521104202100000103_13_03_PU2021-09-19 02:40:00.0영화상영업삼정프라퍼티 주식회사지번우편번호부산광역시 부산진구 부전동 227-2 삼정타워47296부산광역시 부산진구 중앙대로 672, 삼정타워 11층 (부전동)20210521폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.014165185703.07900820210917145721업태구분명051-520-3766건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210521통로너비품목명2022-05-01 05:20:03