Overview

Dataset statistics

Number of variables56
Number of observations482
Missing cells39
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory214.3 KiB
Average record size in memory455.3 B

Variable types

Numeric7
Text5
Categorical42
DateTime2

Alerts

last_load_dttm has constant value ""Constant
sitepostno is highly imbalanced (72.2%)Imbalance
dcbymd is highly imbalanced (61.9%)Imbalance
trdstatenm is highly imbalanced (55.7%)Imbalance
dtlstatenm is highly imbalanced (63.4%)Imbalance
facilar is highly imbalanced (52.3%)Imbalance
regnsenm is highly imbalanced (51.7%)Imbalance
rdnpostno has 21 (4.4%) 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 11:38:32.166184
Analysis finished2024-04-16 11:38:33.195531
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct482
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean983.09959
Minimum1
Maximum3089
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:33.250552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.05
Q1121.25
median241.5
Q31956.5
95-th percentile3064.95
Maximum3089
Range3088
Interquartile range (IQR)1835.25

Descriptive statistics

Standard deviation1149.1954
Coefficient of variation (CV)1.1689512
Kurtosis-0.84980627
Mean983.09959
Median Absolute Deviation (MAD)206
Skewness0.90730909
Sum473854
Variance1320650.1
MonotonicityNot monotonic
2024-04-16T20:38:33.362610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
1981 1
 
0.2%
1415 1
 
0.2%
1301 1
 
0.2%
1299 1
 
0.2%
1286 1
 
0.2%
1285 1
 
0.2%
1235 1
 
0.2%
1234 1
 
0.2%
1233 1
 
0.2%
Other values (472) 472
97.9%
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 (%)
3089 1
0.2%
3088 1
0.2%
3087 1
0.2%
3086 1
0.2%
3085 1
0.2%
3084 1
0.2%
3083 1
0.2%
3082 1
0.2%
3081 1
0.2%
3080 1
0.2%

opnsfteamcode
Real number (ℝ)

Distinct15
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3319751
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:33.473901image/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 deviation40705.068
Coefficient of variation (CV)0.012261482
Kurtosis-0.47464617
Mean3319751
Median Absolute Deviation (MAD)30000
Skewness0.099215115
Sum1.60012 × 109
Variance1.6569025 × 109
MonotonicityNot monotonic
2024-04-16T20:38:33.576128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3330000 129
26.8%
3290000 86
17.8%
3250000 56
11.6%
3300000 29
 
6.0%
3320000 27
 
5.6%
3350000 26
 
5.4%
3400000 26
 
5.4%
3380000 21
 
4.4%
3310000 20
 
4.1%
3390000 15
 
3.1%
Other values (5) 47
 
9.8%
ValueCountFrequency (%)
3250000 56
11.6%
3260000 2
 
0.4%
3270000 9
 
1.9%
3290000 86
17.8%
3300000 29
 
6.0%
3310000 20
 
4.1%
3320000 27
 
5.6%
3330000 129
26.8%
3340000 13
 
2.7%
3350000 26
 
5.4%
ValueCountFrequency (%)
3400000 26
 
5.4%
3390000 15
 
3.1%
3380000 21
 
4.4%
3370000 9
 
1.9%
3360000 14
 
2.9%
3350000 26
 
5.4%
3340000 13
 
2.7%
3330000 129
26.8%
3320000 27
 
5.6%
3310000 20
 
4.1%

mgtno
Text

Distinct253
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-16T20:38:33.768442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters9640
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 (%)30.9%

Sample

1st rowCDFF4220002005000001
2nd rowCDFF4220002017000003
3rd rowCDFF4220002017000006
4th rowCDFF4220002017000005
5th rowCDFF4220001982000001
ValueCountFrequency (%)
cdff5211012020000001 18
 
3.7%
cdff5211012021000001 13
 
2.7%
cdff5211012019000001 12
 
2.5%
cdff5211012021000002 9
 
1.9%
cdff5211012020000002 9
 
1.9%
cdff5211042021000001 8
 
1.7%
cdff5211032020000001 8
 
1.7%
cdff5211032019000001 8
 
1.7%
cdff5211042019000001 6
 
1.2%
cdff5211012022000001 6
 
1.2%
Other values (243) 385
79.9%
2024-04-16T20:38:34.062701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4194
43.5%
2 1495
 
15.5%
F 964
 
10.0%
1 952
 
9.9%
C 482
 
5.0%
D 482
 
5.0%
4 393
 
4.1%
5 245
 
2.5%
9 135
 
1.4%
3 90
 
0.9%
Other values (3) 208
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7712
80.0%
Uppercase Letter 1928
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4194
54.4%
2 1495
 
19.4%
1 952
 
12.3%
4 393
 
5.1%
5 245
 
3.2%
9 135
 
1.8%
3 90
 
1.2%
7 84
 
1.1%
6 65
 
0.8%
8 59
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
F 964
50.0%
C 482
25.0%
D 482
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7712
80.0%
Latin 1928
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4194
54.4%
2 1495
 
19.4%
1 952
 
12.3%
4 393
 
5.1%
5 245
 
3.2%
9 135
 
1.8%
3 90
 
1.2%
7 84
 
1.1%
6 65
 
0.8%
8 59
 
0.8%
Latin
ValueCountFrequency (%)
F 964
50.0%
C 482
25.0%
D 482
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9640
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4194
43.5%
2 1495
 
15.5%
F 964
 
10.0%
1 952
 
9.9%
C 482
 
5.0%
D 482
 
5.0%
4 393
 
4.1%
5 245
 
2.5%
9 135
 
1.4%
3 90
 
0.9%
Other values (3) 208
 
2.2%

opnsvcid
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
03_13_02_P
302 
03_13_05_P
119 
03_13_01_P
31 
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
62.7%
03_13_05_P 119
 
24.7%
03_13_01_P 31
 
6.4%
03_13_03_P 22
 
4.6%
03_13_04_P 8
 
1.7%

Length

2024-04-16T20:38:34.185121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:34.264912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_13_02_p 302
62.7%
03_13_05_p 119
 
24.7%
03_13_01_p 31
 
6.4%
03_13_03_p 22
 
4.6%
03_13_04_p 8
 
1.7%

updategbn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
I
241 
U
241 

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 241
50.0%
U 241
50.0%

Length

2024-04-16T20:38:34.357721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:34.443538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 241
50.0%
u 241
50.0%
Distinct123
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2018-08-31 23:59:59
Maximum2022-01-28 02:40:00
2024-04-16T20:38:34.529696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:38:34.644283image/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 size3.9 KiB
영화상영관
205 
영화제작업
119 
<NA>
97 
영화배급업
31 
영화상영업
22 

Length

Max length5
Median length5
Mean length4.7987552
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
42.5%
영화제작업 119
24.7%
<NA> 97
20.1%
영화배급업 31
 
6.4%
영화상영업 22
 
4.6%
영화수입업 8
 
1.7%

Length

2024-04-16T20:38:34.764258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:34.863605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 205
42.5%
영화제작업 119
24.7%
na 97
20.1%
영화배급업 31
 
6.4%
영화상영업 22
 
4.6%
영화수입업 8
 
1.7%

bplcnm
Text

Distinct399
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-16T20:38:35.073311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length10.821577
Min length2

Characters and Unicode

Total characters5216
Distinct characters260
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

Unique356 ?
Unique (%)73.9%

Sample

1st row국도극장 예술관
2nd row롯데시네마 대영 제3관
3rd row롯데시네마 대영 제6관
4th row롯데시네마 대영 제5관
5th row메가박스 부산극장 1관
ValueCountFrequency (%)
롯데시네마 92
 
8.8%
메가박스 48
 
4.6%
cgv 41
 
3.9%
주식회사 40
 
3.8%
해운대 26
 
2.5%
서면 20
 
1.9%
센텀시티 19
 
1.8%
6관 16
 
1.5%
제3관 16
 
1.5%
4관 15
 
1.4%
Other values (250) 710
68.1%
2024-04-16T20:38:35.410170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
563
 
10.8%
329
 
6.3%
170
 
3.3%
154
 
3.0%
150
 
2.9%
143
 
2.7%
124
 
2.4%
C 111
 
2.1%
109
 
2.1%
108
 
2.1%
Other values (250) 3255
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3677
70.5%
Space Separator 563
 
10.8%
Uppercase Letter 441
 
8.5%
Decimal Number 293
 
5.6%
Close Punctuation 103
 
2.0%
Open Punctuation 103
 
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
 
8.9%
170
 
4.6%
154
 
4.2%
150
 
4.1%
143
 
3.9%
124
 
3.4%
109
 
3.0%
108
 
2.9%
107
 
2.9%
80
 
2.2%
Other values (201) 2203
59.9%
Uppercase Letter
ValueCountFrequency (%)
C 111
25.2%
G 89
20.2%
V 88
20.0%
N 24
 
5.4%
E 14
 
3.2%
O 12
 
2.7%
I 11
 
2.5%
M 10
 
2.3%
A 10
 
2.3%
U 10
 
2.3%
Other values (13) 62
14.1%
Decimal Number
ValueCountFrequency (%)
1 46
15.7%
2 44
15.0%
4 40
13.7%
3 34
11.6%
6 33
11.3%
5 32
10.9%
7 25
8.5%
9 17
 
5.8%
8 16
 
5.5%
0 6
 
2.0%
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 (%)
) 102
99.0%
] 1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 102
99.0%
[ 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
, 4
33.3%
Space Separator
ValueCountFrequency (%)
563
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3677
70.5%
Common 1075
 
20.6%
Latin 464
 
8.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
329
 
8.9%
170
 
4.6%
154
 
4.2%
150
 
4.1%
143
 
3.9%
124
 
3.4%
109
 
3.0%
108
 
2.9%
107
 
2.9%
80
 
2.2%
Other values (201) 2203
59.9%
Latin
ValueCountFrequency (%)
C 111
23.9%
G 89
19.2%
V 88
19.0%
N 24
 
5.2%
E 14
 
3.0%
O 12
 
2.6%
I 11
 
2.4%
M 10
 
2.2%
A 10
 
2.2%
U 10
 
2.2%
Other values (21) 85
18.3%
Common
ValueCountFrequency (%)
563
52.4%
) 102
 
9.5%
( 102
 
9.5%
1 46
 
4.3%
2 44
 
4.1%
4 40
 
3.7%
3 34
 
3.2%
6 33
 
3.1%
5 32
 
3.0%
7 25
 
2.3%
Other values (8) 54
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3677
70.5%
ASCII 1539
29.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
563
36.6%
C 111
 
7.2%
) 102
 
6.6%
( 102
 
6.6%
G 89
 
5.8%
V 88
 
5.7%
1 46
 
3.0%
2 44
 
2.9%
4 40
 
2.6%
3 34
 
2.2%
Other values (39) 320
20.8%
Hangul
ValueCountFrequency (%)
329
 
8.9%
170
 
4.6%
154
 
4.2%
150
 
4.1%
143
 
3.9%
124
 
3.4%
109
 
3.0%
108
 
2.9%
107
 
2.9%
80
 
2.2%
Other values (201) 2203
59.9%

sitepostno
Categorical

IMBALANCE 

Distinct16
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
370 
지번우편번호
90 
614845
 
4
600805
 
3
601060
 
3
Other values (11)
 
12

Length

Max length6
Median length4
Mean length4.4647303
Min length4

Unique

Unique10 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 370
76.8%
지번우편번호 90
 
18.7%
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

2024-04-16T20:38:35.527439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 370
76.8%
지번우편번호 90
 
18.7%
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%
Distinct160
Distinct (%)33.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-04-16T20:38:35.786789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length26.435685
Min length18

Characters and Unicode

Total characters12742
Distinct characters247
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

Unique76 ?
Unique (%)15.8%

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 482
 
20.2%
해운대구 129
 
5.4%
우동 95
 
4.0%
부산진구 86
 
3.6%
중구 56
 
2.3%
부전동 53
 
2.2%
43
 
1.8%
동래구 29
 
1.2%
전포동 27
 
1.1%
북구 27
 
1.1%
Other values (327) 1357
56.9%
2024-04-16T20:38:36.199252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2337
18.3%
672
 
5.3%
627
 
4.9%
521
 
4.1%
520
 
4.1%
488
 
3.8%
482
 
3.8%
1 478
 
3.8%
459
 
3.6%
- 409
 
3.2%
Other values (237) 5749
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7338
57.6%
Space Separator 2337
 
18.3%
Decimal Number 2188
 
17.2%
Dash Punctuation 409
 
3.2%
Other Punctuation 275
 
2.2%
Uppercase Letter 150
 
1.2%
Lowercase Letter 15
 
0.1%
Open Punctuation 12
 
0.1%
Close Punctuation 12
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
672
 
9.2%
627
 
8.5%
521
 
7.1%
520
 
7.1%
488
 
6.7%
482
 
6.6%
459
 
6.3%
208
 
2.8%
180
 
2.5%
172
 
2.3%
Other values (201) 3009
41.0%
Uppercase Letter
ValueCountFrequency (%)
K 35
23.3%
T 21
14.0%
S 19
12.7%
G 16
10.7%
B 11
 
7.3%
U 10
 
6.7%
H 10
 
6.7%
C 10
 
6.7%
Y 9
 
6.0%
N 8
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 478
21.8%
2 316
14.4%
6 228
10.4%
5 228
10.4%
4 201
9.2%
0 170
 
7.8%
8 159
 
7.3%
7 154
 
7.0%
3 142
 
6.5%
9 112
 
5.1%
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 (%)
* 242
88.0%
, 18
 
6.5%
& 15
 
5.5%
Space Separator
ValueCountFrequency (%)
2337
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 409
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7338
57.6%
Common 5239
41.1%
Latin 165
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
672
 
9.2%
627
 
8.5%
521
 
7.1%
520
 
7.1%
488
 
6.7%
482
 
6.6%
459
 
6.3%
208
 
2.8%
180
 
2.5%
172
 
2.3%
Other values (201) 3009
41.0%
Common
ValueCountFrequency (%)
2337
44.6%
1 478
 
9.1%
- 409
 
7.8%
2 316
 
6.0%
* 242
 
4.6%
6 228
 
4.4%
5 228
 
4.4%
4 201
 
3.8%
0 170
 
3.2%
8 159
 
3.0%
Other values (8) 471
 
9.0%
Latin
ValueCountFrequency (%)
K 35
21.2%
T 21
12.7%
S 19
11.5%
G 16
9.7%
B 11
 
6.7%
U 10
 
6.1%
H 10
 
6.1%
C 10
 
6.1%
Y 9
 
5.5%
N 8
 
4.8%
Other values (8) 16
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7338
57.6%
ASCII 5404
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2337
43.2%
1 478
 
8.8%
- 409
 
7.6%
2 316
 
5.8%
* 242
 
4.5%
6 228
 
4.2%
5 228
 
4.2%
4 201
 
3.7%
0 170
 
3.1%
8 159
 
2.9%
Other values (26) 636
 
11.8%
Hangul
ValueCountFrequency (%)
672
 
9.2%
627
 
8.5%
521
 
7.1%
520
 
7.1%
488
 
6.7%
482
 
6.6%
459
 
6.3%
208
 
2.8%
180
 
2.5%
172
 
2.3%
Other values (201) 3009
41.0%

rdnpostno
Text

MISSING 

Distinct91
Distinct (%)19.7%
Missing21
Missing (%)4.4%
Memory size3.9 KiB
2024-04-16T20:38:36.414772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0086768
Min length5

Characters and Unicode

Total characters2309
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

Unique36 ?
Unique (%)7.8%

Sample

1st row48947
2nd row48953
3rd row48953
4th row48953
5th row48947
ValueCountFrequency (%)
48947 49
 
10.6%
48058 49
 
10.6%
48953 20
 
4.3%
48059 16
 
3.5%
47296 16
 
3.5%
46726 14
 
3.0%
47299 12
 
2.6%
47288 12
 
2.6%
48944 11
 
2.4%
47285 11
 
2.4%
Other values (81) 251
54.4%
2024-04-16T20:38:36.736141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 600
26.0%
8 392
17.0%
7 239
 
10.4%
9 234
 
10.1%
5 170
 
7.4%
0 163
 
7.1%
2 160
 
6.9%
6 153
 
6.6%
1 99
 
4.3%
3 85
 
3.7%
Other values (7) 14
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2295
99.4%
Other Letter 14
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 600
26.1%
8 392
17.1%
7 239
 
10.4%
9 234
 
10.2%
5 170
 
7.4%
0 163
 
7.1%
2 160
 
7.0%
6 153
 
6.7%
1 99
 
4.3%
3 85
 
3.7%
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 2295
99.4%
Hangul 14
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
4 600
26.1%
8 392
17.1%
7 239
 
10.4%
9 234
 
10.2%
5 170
 
7.4%
0 163
 
7.1%
2 160
 
7.0%
6 153
 
6.7%
1 99
 
4.3%
3 85
 
3.7%
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 2295
99.4%
Hangul 14
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 600
26.1%
8 392
17.1%
7 239
 
10.4%
9 234
 
10.2%
5 170
 
7.4%
0 163
 
7.1%
2 160
 
7.0%
6 153
 
6.7%
1 99
 
4.3%
3 85
 
3.7%
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 

Distinct161
Distinct (%)33.8%
Missing6
Missing (%)1.2%
Memory size3.9 KiB
2024-04-16T20:38:36.977206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length33.283613
Min length22

Characters and Unicode

Total characters15843
Distinct characters277
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

Unique77 ?
Unique (%)16.2%

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 476
 
15.6%
해운대구 129
 
4.2%
부산진구 86
 
2.8%
우동 85
 
2.8%
중앙대로 54
 
1.8%
부전동 53
 
1.7%
중구 53
 
1.7%
해운대로 46
 
1.5%
43
 
1.4%
39 40
 
1.3%
Other values (424) 1994
65.2%
2024-04-16T20:38:37.352845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2608
 
16.5%
685
 
4.3%
634
 
4.0%
589
 
3.7%
532
 
3.4%
529
 
3.3%
476
 
3.0%
475
 
3.0%
( 466
 
2.9%
) 466
 
2.9%
Other values (267) 8383
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9376
59.2%
Space Separator 2608
 
16.5%
Decimal Number 1969
 
12.4%
Other Punctuation 739
 
4.7%
Open Punctuation 469
 
3.0%
Close Punctuation 469
 
3.0%
Uppercase Letter 159
 
1.0%
Dash Punctuation 26
 
0.2%
Lowercase Letter 16
 
0.1%
Math Symbol 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
685
 
7.3%
634
 
6.8%
589
 
6.3%
532
 
5.7%
529
 
5.6%
476
 
5.1%
475
 
5.1%
460
 
4.9%
381
 
4.1%
207
 
2.2%
Other values (226) 4408
47.0%
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%
U 10
 
6.3%
H 10
 
6.3%
Y 9
 
5.7%
N 8
 
5.0%
Other values (3) 9
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 375
19.0%
2 267
13.6%
0 222
11.3%
3 219
11.1%
6 171
8.7%
5 162
8.2%
7 157
8.0%
4 148
 
7.5%
9 125
 
6.3%
8 123
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 5
31.2%
o 3
18.8%
h 2
 
12.5%
r 2
 
12.5%
l 1
 
6.2%
p 1
 
6.2%
i 1
 
6.2%
v 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 422
57.1%
* 302
40.9%
& 15
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 466
99.4%
[ 3
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 466
99.4%
] 3
 
0.6%
Space Separator
ValueCountFrequency (%)
2608
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9376
59.2%
Common 6292
39.7%
Latin 175
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
685
 
7.3%
634
 
6.8%
589
 
6.3%
532
 
5.7%
529
 
5.6%
476
 
5.1%
475
 
5.1%
460
 
4.9%
381
 
4.1%
207
 
2.2%
Other values (226) 4408
47.0%
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%
U 10
 
5.7%
H 10
 
5.7%
Y 9
 
5.1%
N 8
 
4.6%
Other values (11) 25
14.3%
Common
ValueCountFrequency (%)
2608
41.4%
( 466
 
7.4%
) 466
 
7.4%
, 422
 
6.7%
1 375
 
6.0%
* 302
 
4.8%
2 267
 
4.2%
0 222
 
3.5%
3 219
 
3.5%
6 171
 
2.7%
Other values (10) 774
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9376
59.2%
ASCII 6467
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2608
40.3%
( 466
 
7.2%
) 466
 
7.2%
, 422
 
6.5%
1 375
 
5.8%
* 302
 
4.7%
2 267
 
4.1%
0 222
 
3.4%
3 219
 
3.4%
6 171
 
2.6%
Other values (31) 949
 
14.7%
Hangul
ValueCountFrequency (%)
685
 
7.3%
634
 
6.8%
589
 
6.3%
532
 
5.7%
529
 
5.6%
476
 
5.1%
475
 
5.1%
460
 
4.9%
381
 
4.1%
207
 
2.2%
Other values (226) 4408
47.0%

apvpermymd
Real number (ℝ)

Distinct159
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20121128
Minimum19451015
Maximum20220125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:37.695856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000529
Q120060740
median20150661
Q320200103
95-th percentile20211203
Maximum20220125
Range769110
Interquartile range (IQR)139363.5

Descriptive statistics

Standard deviation89624.784
Coefficient of variation (CV)0.0044542623
Kurtosis8.4522317
Mean20121128
Median Absolute Deviation (MAD)60048
Skewness-1.7775492
Sum9.6983839 × 109
Variance8.0326019 × 109
MonotonicityNot monotonic
2024-04-16T20:38:37.809458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211215 12
 
2.5%
20190315 12
 
2.5%
20000529 12
 
2.5%
20010609 11
 
2.3%
20140822 11
 
2.3%
20071204 10
 
2.1%
20021112 10
 
2.1%
20090302 10
 
2.1%
20210615 10
 
2.1%
20050307 10
 
2.1%
Other values (149) 374
77.6%
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 (%)
20220125 2
 
0.4%
20220119 1
 
0.2%
20220114 2
 
0.4%
20211231 2
 
0.4%
20211230 1
 
0.2%
20211224 2
 
0.4%
20211215 12
2.5%
20211210 2
 
0.4%
20211203 4
 
0.8%
20211116 1
 
0.2%

dcbymd
Categorical

IMBALANCE 

Distinct37
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
320 
폐업일자
85 
20170315
 
10
20160617
 
8
20110616
 
8
Other values (32)
51 

Length

Max length8
Median length4
Mean length4.6390041
Min length4

Unique

Unique24 ?
Unique (%)5.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 320
66.4%
폐업일자 85
 
17.6%
20170315 10
 
2.1%
20160617 8
 
1.7%
20110616 8
 
1.7%
20100806 7
 
1.5%
20001201 4
 
0.8%
20070725 3
 
0.6%
20200921 3
 
0.6%
20210806 3
 
0.6%
Other values (27) 31
 
6.4%

Length

2024-04-16T20:38:37.945291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 320
66.4%
폐업일자 85
 
17.6%
20170315 10
 
2.1%
20160617 8
 
1.7%
20110616 8
 
1.7%
20100806 7
 
1.5%
20001201 4
 
0.8%
20070725 3
 
0.6%
20200921 3
 
0.6%
20210806 3
 
0.6%
Other values (27) 31
 
6.4%

clgstdt
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
휴업시작일자
90 

Length

Max length6
Median length4
Mean length4.373444
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> 392
81.3%
휴업시작일자 90
 
18.7%

Length

2024-04-16T20:38:38.086467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:38.188657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
휴업시작일자 90
 
18.7%

clgenddt
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
휴업종료일자
90 

Length

Max length6
Median length4
Mean length4.373444
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> 392
81.3%
휴업종료일자 90
 
18.7%

Length

2024-04-16T20:38:38.293985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:38.381228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
휴업종료일자 90
 
18.7%

ropnymd
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
재개업일자
90 

Length

Max length5
Median length4
Mean length4.186722
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> 392
81.3%
재개업일자 90
 
18.7%

Length

2024-04-16T20:38:38.464864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:38.547622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
재개업일자 90
 
18.7%

trdstatenm
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
영업/정상
363 
03
56 
13
40 
폐업
 
13
제외/삭제/전출
 
8
Other values (2)
 
2

Length

Max length8
Median length5
Mean length4.3630705
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 363
75.3%
03 56
 
11.6%
13 40
 
8.3%
폐업 13
 
2.7%
제외/삭제/전출 8
 
1.7%
35 1
 
0.2%
<NA> 1
 
0.2%

Length

2024-04-16T20:38:38.632589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:38.725458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 363
75.3%
03 56
 
11.6%
13 40
 
8.3%
폐업 13
 
2.7%
제외/삭제/전출 8
 
1.7%
35 1
 
0.2%
na 1
 
0.2%

dtlstatenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
영업중
404 
폐업
69 
전출
 
8
직권말소
 
1

Length

Max length4
Median length3
Mean length2.8423237
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 404
83.8%
폐업 69
 
14.3%
전출 8
 
1.7%
직권말소 1
 
0.2%

Length

2024-04-16T20:38:38.827588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:38.917610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 404
83.8%
폐업 69
 
14.3%
전출 8
 
1.7%
직권말소 1
 
0.2%

x
Real number (ℝ)

MISSING 

Distinct129
Distinct (%)27.1%
Missing6
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean389541.53
Minimum373470.6
Maximum401669
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:39.024069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum373470.6
5-th percentile379270.62
Q1385622.78
median389097.8
Q3393724.66
95-th percentile398310.24
Maximum401669
Range28198.396
Interquartile range (IQR)8101.8747

Descriptive statistics

Standard deviation5887.1154
Coefficient of variation (CV)0.015112934
Kurtosis0.064756828
Mean389541.53
Median Absolute Deviation (MAD)4154.7931
Skewness-0.31312998
Sum1.8542177 × 108
Variance34658128
MonotonicityNot monotonic
2024-04-16T20:38:39.136796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393674.032955782 21
 
4.4%
388011.197829908 12
 
2.5%
387608.014165034 11
 
2.3%
385622.780457355 11
 
2.3%
387271.299492377 11
 
2.3%
396915.143441 10
 
2.1%
393952.264486105 10
 
2.1%
398310.243451 10
 
2.1%
394083.501537578 10
 
2.1%
387280.619672939 9
 
1.9%
Other values (119) 361
74.9%
ValueCountFrequency (%)
373470.60373869 7
1.5%
374253.112340712 7
1.5%
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
1.5%
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
2.1%
398275.475596001 1
 
0.2%
398269.05154158 7
1.5%

y
Real number (ℝ)

MISSING 

Distinct129
Distinct (%)27.1%
Missing6
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean187421.73
Minimum178757.42
Maximum204621.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:39.259494image/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 deviation5337.6411
Coefficient of variation (CV)0.028479307
Kurtosis1.73888
Mean187421.73
Median Absolute Deviation (MAD)2169.7385
Skewness0.86025675
Sum89212746
Variance28490413
MonotonicityNot monotonic
2024-04-16T20:38:39.372445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187973.297243244 21
 
4.4%
185310.70532509 12
 
2.5%
185703.079007724 11
 
2.3%
179452.224754792 11
 
2.3%
186099.137533193 11
 
2.3%
187480.443811 10
 
2.1%
187602.933160728 10
 
2.1%
188031.67198 10
 
2.1%
187707.586117775 10
 
2.1%
185679.050795793 9
 
1.9%
Other values (119) 361
74.9%
ValueCountFrequency (%)
178757.423271048 7
1.5%
178872.461747926 1
 
0.2%
178919.583231221 7
1.5%
179411.189506548 1
 
0.2%
179452.224754792 11
2.3%
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
1.7%
195029.489621392 1
 
0.2%
194992.355262 2
 
0.4%
194681.150958776 7
1.5%
194312.723690481 7
1.5%

lastmodts
Real number (ℝ)

Distinct379
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0193091 × 1013
Minimum2.0030127 × 1013
Maximum2.0220126 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:39.489169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030127 × 1013
5-th percentile2.0110616 × 1013
Q12.0190315 × 1013
median2.0210422 × 1013
Q32.0211215 × 1013
95-th percentile2.0211223 × 1013
Maximum2.0220126 × 1013
Range1.8999895 × 1011
Interquartile range (IQR)2.090002 × 1010

Descriptive statistics

Standard deviation3.3949427 × 1010
Coefficient of variation (CV)0.0016812397
Kurtosis7.0350304
Mean2.0193091 × 1013
Median Absolute Deviation (MAD)7.9902789 × 108
Skewness-2.5887978
Sum9.73307 × 1015
Variance1.1525636 × 1021
MonotonicityNot monotonic
2024-04-16T20:38:39.618208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211220133307 6
 
1.2%
20210421091411 5
 
1.0%
20211220133338 5
 
1.0%
20211216174849 5
 
1.0%
20190920121341 5
 
1.0%
20030127161348 4
 
0.8%
20211217153628 4
 
0.8%
20211220161532 4
 
0.8%
20191017170859 4
 
0.8%
20211220133308 4
 
0.8%
Other values (369) 436
90.5%
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 (%)
20220126114242 1
0.2%
20220126114036 1
0.2%
20220126113804 1
0.2%
20220126113514 1
0.2%
20220125161841 1
0.2%
20220125161622 1
0.2%
20220119101954 1
0.2%
20220114114313 2
0.4%
20220114112527 2
0.4%
20220105133816 1
0.2%

uptaenm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
업태구분명
90 

Length

Max length5
Median length4
Mean length4.186722
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> 392
81.3%
업태구분명 90
 
18.7%

Length

2024-04-16T20:38:39.730380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:39.809547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
업태구분명 90
 
18.7%

sitetel
Categorical

Distinct39
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
051-123-1234
193 
<NA>
77 
전화번호
49 
910-1411
 
12
070-7495-8542
 
11
Other values (34)
140 

Length

Max length13
Median length12
Mean length9.6887967
Min length4

Unique

Unique11 ?
Unique (%)2.3%

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 193
40.0%
<NA> 77
 
16.0%
전화번호 49
 
10.2%
910-1411 12
 
2.5%
070-7495-8542 11
 
2.3%
810-3941 11
 
2.3%
051-366-2200 9
 
1.9%
051-745-2883 8
 
1.7%
070-4159-8881 7
 
1.5%
051-581-5950 7
 
1.5%
Other values (29) 98
20.3%

Length

2024-04-16T20:38:39.898241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 193
40.0%
na 77
 
16.0%
전화번호 49
 
10.2%
910-1411 12
 
2.5%
070-7495-8542 11
 
2.3%
810-3941 11
 
2.3%
051-366-2200 9
 
1.9%
051-745-2883 8
 
1.7%
070-4159-8881 7
 
1.5%
051-581-5950 7
 
1.5%
Other values (29) 98
20.3%

bdngsrvnm
Categorical

Distinct7
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
285 
문화시설
88 
건물용도명
80 
근린생활시설
 
13
유통시설
 
9
Other values (2)
 
7

Length

Max length6
Median length4
Mean length4.1929461
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> 285
59.1%
문화시설 88
 
18.3%
건물용도명 80
 
16.6%
근린생활시설 13
 
2.7%
유통시설 9
 
1.9%
호텔 6
 
1.2%
사무실 1
 
0.2%

Length

2024-04-16T20:38:40.008988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:40.115305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 285
59.1%
문화시설 88
 
18.3%
건물용도명 80
 
16.6%
근린생활시설 13
 
2.7%
유통시설 9
 
1.9%
호텔 6
 
1.2%
사무실 1
 
0.2%

perplaformsenm
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
영화관
294 
<NA>
111 
공연장형태구분명
73 
자동차극장
 
4

Length

Max length8
Median length3
Mean length4.0041494
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화관 294
61.0%
<NA> 111
 
23.0%
공연장형태구분명 73
 
15.1%
자동차극장 4
 
0.8%

Length

2024-04-16T20:38:40.213309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:40.303122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화관 294
61.0%
na 111
 
23.0%
공연장형태구분명 73
 
15.1%
자동차극장 4
 
0.8%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
기존게임업외업종명
90 

Length

Max length9
Median length4
Mean length4.93361
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> 392
81.3%
기존게임업외업종명 90
 
18.7%

Length

2024-04-16T20:38:40.388913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:40.464545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
기존게임업외업종명 90
 
18.7%

noroomcnt
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
349 
노래방실수
67 
0
66 

Length

Max length5
Median length4
Mean length3.7282158
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> 349
72.4%
노래방실수 67
 
13.9%
0 66
 
13.7%

Length

2024-04-16T20:38:40.552387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:40.644840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 349
72.4%
노래방실수 67
 
13.9%
0 66
 
13.7%

culwrkrsenm
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
201 
영화상영관
196 
문화사업자구분명
85 

Length

Max length8
Median length5
Mean length5.1120332
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 201
41.7%
영화상영관 196
40.7%
문화사업자구분명 85
17.6%

Length

2024-04-16T20:38:40.758465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:40.841888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 201
41.7%
영화상영관 196
40.7%
문화사업자구분명 85
17.6%

culphyedcobnm
Categorical

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
영화상영관
302 
영화제작업
119 
영화배급업
31 
영화상영업
 
22
영화수입업
 
8

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 302
62.7%
영화제작업 119
 
24.7%
영화배급업 31
 
6.4%
영화상영업 22
 
4.6%
영화수입업 8
 
1.7%

Length

2024-04-16T20:38:40.927104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:41.007992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화상영관 302
62.7%
영화제작업 119
 
24.7%
영화배급업 31
 
6.4%
영화상영업 22
 
4.6%
영화수입업 8
 
1.7%

souarfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
90 

Length

Max length4
Median length4
Mean length3.439834
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> 392
81.3%
90
 
18.7%

Length

2024-04-16T20:38:41.098767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:41.179810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
90
 
18.7%

vdoretornm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
비디오재생기명
90 

Length

Max length7
Median length4
Mean length4.560166
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> 392
81.3%
비디오재생기명 90
 
18.7%

Length

2024-04-16T20:38:41.269503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:41.351857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
비디오재생기명 90
 
18.7%

emerstairyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
90 

Length

Max length4
Median length4
Mean length3.439834
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> 392
81.3%
90
 
18.7%

Length

2024-04-16T20:38:41.434064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:41.521035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
90
 
18.7%

emexyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
90 

Length

Max length4
Median length4
Mean length3.439834
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> 392
81.3%
90
 
18.7%

Length

2024-04-16T20:38:41.625880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:41.722137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
90
 
18.7%

firefacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
90 

Length

Max length4
Median length4
Mean length3.439834
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> 392
81.3%
90
 
18.7%

Length

2024-04-16T20:38:41.811365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:41.890773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
90
 
18.7%

facilar
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
343 
시설면적
67 
0
66 
1578.8
 
4
147.46
 
1

Length

Max length6
Median length4
Mean length3.6120332
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> 343
71.2%
시설면적 67
 
13.9%
0 66
 
13.7%
1578.8 4
 
0.8%
147.46 1
 
0.2%
181.3 1
 
0.2%

Length

2024-04-16T20:38:41.977073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:42.085629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 343
71.2%
시설면적 67
 
13.9%
0 66
 
13.7%
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 size3.9 KiB
<NA>
392 
90 

Length

Max length4
Median length4
Mean length3.439834
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> 392
81.3%
90
 
18.7%

Length

2024-04-16T20:38:42.190766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:42.276099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
90
 
18.7%

autochaairyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
90 

Length

Max length4
Median length4
Mean length3.439834
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> 392
81.3%
90
 
18.7%

Length

2024-04-16T20:38:42.368878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:42.456731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
90
 
18.7%

prvdgathinnm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
제공게임물명
90 

Length

Max length6
Median length4
Mean length4.373444
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> 392
81.3%
제공게임물명 90
 
18.7%

Length

2024-04-16T20:38:42.543808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:42.626451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
제공게임물명 90
 
18.7%

mnfactreartclcn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
제작취급품목내용
90 

Length

Max length8
Median length4
Mean length4.746888
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> 392
81.3%
제작취급품목내용 90
 
18.7%

Length

2024-04-16T20:38:42.711144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:42.792531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
제작취급품목내용 90
 
18.7%

lghtfacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
90 

Length

Max length4
Median length4
Mean length3.439834
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> 392
81.3%
90
 
18.7%

Length

2024-04-16T20:38:42.885788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:42.978868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
90
 
18.7%

lghtfacilinillu
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
349 
조명시설조도
67 
0
66 

Length

Max length6
Median length4
Mean length3.8672199
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> 349
72.4%
조명시설조도 67
 
13.9%
0 66
 
13.7%

Length

2024-04-16T20:38:43.064059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:43.142807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 349
72.4%
조명시설조도 67
 
13.9%
0 66
 
13.7%

nearenvnm
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
337 
주변환경명
84 
기타
 
32
유흥업소밀집지역
 
18
아파트지역
 
9

Length

Max length8
Median length4
Mean length4.2261411
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> 337
69.9%
주변환경명 84
 
17.4%
기타 32
 
6.6%
유흥업소밀집지역 18
 
3.7%
아파트지역 9
 
1.9%
학교정화(상대) 2
 
0.4%

Length

2024-04-16T20:38:43.478605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:43.561271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 337
69.9%
주변환경명 84
 
17.4%
기타 32
 
6.6%
유흥업소밀집지역 18
 
3.7%
아파트지역 9
 
1.9%
학교정화(상대 2
 
0.4%

jisgnumlay
Categorical

Distinct23
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
149 
지상층수
57 
10
43 
0
29 
7
28 
Other values (18)
176 

Length

Max length4
Median length2
Mean length2.5518672
Min length1

Unique

Unique4 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 149
30.9%
지상층수 57
 
11.8%
10 43
 
8.9%
0 29
 
6.0%
7 28
 
5.8%
9 27
 
5.6%
5 20
 
4.1%
8 19
 
3.9%
42 17
 
3.5%
13 15
 
3.1%
Other values (13) 78
16.2%

Length

2024-04-16T20:38:43.659240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 149
30.9%
지상층수 57
 
11.8%
10 43
 
8.9%
0 29
 
6.0%
7 28
 
5.8%
9 27
 
5.6%
5 20
 
4.1%
8 19
 
3.9%
42 17
 
3.5%
13 15
 
3.1%
Other values (13) 78
16.2%

regnsenm
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
324 
지역구분명
83 
일반상업지역
 
30
상업지역
 
16
중심상업지역
 
12
Other values (5)
 
17

Length

Max length6
Median length4
Mean length4.379668
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 324
67.2%
지역구분명 83
 
17.2%
일반상업지역 30
 
6.2%
상업지역 16
 
3.3%
중심상업지역 12
 
2.5%
녹지지역 8
 
1.7%
일반주거지역 4
 
0.8%
근린상업지역 3
 
0.6%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

Length

2024-04-16T20:38:43.764265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:43.866079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 324
67.2%
지역구분명 83
 
17.2%
일반상업지역 30
 
6.2%
상업지역 16
 
3.3%
중심상업지역 12
 
2.5%
녹지지역 8
 
1.7%
일반주거지역 4
 
0.8%
근린상업지역 3
 
0.6%
주거지역 1
 
0.2%
일반공업지역 1
 
0.2%

undernumlay
Categorical

Distinct12
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
157 
5
65 
지하층수
58 
2
53 
1
35 
Other values (7)
114 

Length

Max length4
Median length1
Mean length2.3423237
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 157
32.6%
5 65
13.5%
지하층수 58
 
12.0%
2 53
 
11.0%
1 35
 
7.3%
0 29
 
6.0%
3 24
 
5.0%
4 21
 
4.4%
6 20
 
4.1%
8 18
 
3.7%
Other values (2) 2
 
0.4%

Length

2024-04-16T20:38:43.996644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 157
32.6%
5 65
13.5%
지하층수 58
 
12.0%
2 53
 
11.0%
1 35
 
7.3%
0 29
 
6.0%
3 24
 
5.0%
4 21
 
4.4%
6 20
 
4.1%
8 18
 
3.7%
Other values (2) 2
 
0.4%

bgroomcnt
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
349 
청소년실수
67 
0
66 

Length

Max length5
Median length4
Mean length3.7282158
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> 349
72.4%
청소년실수 67
 
13.9%
0 66
 
13.7%

Length

2024-04-16T20:38:44.136612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:44.244658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 349
72.4%
청소년실수 67
 
13.9%
0 66
 
13.7%

bgroomyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
90 

Length

Max length4
Median length4
Mean length3.439834
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> 392
81.3%
90
 
18.7%

Length

2024-04-16T20:38:44.335549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:44.424239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
90
 
18.7%

totgasyscnt
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
349 
총게임기수
67 
0
66 

Length

Max length5
Median length4
Mean length3.7282158
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> 349
72.4%
총게임기수 67
 
13.9%
0 66
 
13.7%

Length

2024-04-16T20:38:44.534864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:44.628083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 349
72.4%
총게임기수 67
 
13.9%
0 66
 
13.7%

totnumlay
Categorical

Distinct20
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
235 
총층수
60 
0
35 
10
 
20
12
 
13
Other values (15)
119 

Length

Max length4
Median length3
Mean length2.9585062
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> 235
48.8%
총층수 60
 
12.4%
0 35
 
7.3%
10 20
 
4.1%
12 13
 
2.7%
6 12
 
2.5%
11 12
 
2.5%
9 12
 
2.5%
18 11
 
2.3%
19 10
 
2.1%
Other values (10) 62
 
12.9%

Length

2024-04-16T20:38:44.715452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 235
48.8%
총층수 60
 
12.4%
0 35
 
7.3%
10 20
 
4.1%
12 13
 
2.7%
6 12
 
2.5%
11 12
 
2.5%
9 12
 
2.5%
18 11
 
2.3%
19 10
 
2.1%
Other values (10) 62
 
12.9%

frstregts
Real number (ℝ)

Distinct159
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20121128
Minimum19451015
Maximum20220125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-04-16T20:38:44.823245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20000529
Q120060740
median20150661
Q320200103
95-th percentile20211203
Maximum20220125
Range769110
Interquartile range (IQR)139363.5

Descriptive statistics

Standard deviation89624.784
Coefficient of variation (CV)0.0044542623
Kurtosis8.4522317
Mean20121128
Median Absolute Deviation (MAD)60048
Skewness-1.7775492
Sum9.6983839 × 109
Variance8.0326019 × 109
MonotonicityNot monotonic
2024-04-16T20:38:44.944220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211215 12
 
2.5%
20190315 12
 
2.5%
20000529 12
 
2.5%
20010609 11
 
2.3%
20140822 11
 
2.3%
20071204 10
 
2.1%
20021112 10
 
2.1%
20090302 10
 
2.1%
20210615 10
 
2.1%
20050307 10
 
2.1%
Other values (149) 374
77.6%
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 (%)
20220125 2
 
0.4%
20220119 1
 
0.2%
20220114 2
 
0.4%
20211231 2
 
0.4%
20211230 1
 
0.2%
20211224 2
 
0.4%
20211215 12
2.5%
20211210 2
 
0.4%
20211203 4
 
0.8%
20211116 1
 
0.2%

pasgbreth
Categorical

Distinct19
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
216 
1
103 
통로너비
61 
0
57 
1.5
 
12
Other values (14)
33 

Length

Max length4
Median length4
Mean length2.9460581
Min length1

Unique

Unique8 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
44.8%
1 103
21.4%
통로너비 61
 
12.7%
0 57
 
11.8%
1.5 12
 
2.5%
1.2 7
 
1.5%
1.45 5
 
1.0%
1.3 4
 
0.8%
1.15 4
 
0.8%
1.7 3
 
0.6%
Other values (9) 10
 
2.1%

Length

2024-04-16T20:38:45.058434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 216
44.8%
1 103
21.4%
통로너비 61
 
12.7%
0 57
 
11.8%
1.5 12
 
2.5%
1.2 7
 
1.5%
1.45 5
 
1.0%
1.3 4
 
0.8%
1.15 4
 
0.8%
1.7 3
 
0.6%
Other values (9) 10
 
2.1%

speclghtyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
90 

Length

Max length4
Median length4
Mean length3.439834
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> 392
81.3%
90
 
18.7%

Length

2024-04-16T20:38:45.171962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:45.264504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
90
 
18.7%

cnvefacilyn
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
90 

Length

Max length4
Median length4
Mean length3.439834
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> 392
81.3%
90
 
18.7%

Length

2024-04-16T20:38:45.361816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:45.446990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
90
 
18.7%

actlnm
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
392 
품목명
90 

Length

Max length4
Median length4
Mean length3.813278
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> 392
81.3%
품목명 90
 
18.7%

Length

2024-04-16T20:38:45.524178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:38:45.599791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 392
81.3%
품목명 90
 
18.7%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2022-02-01 05:20:03
Maximum2022-02-01 05:20:03
2024-04-16T20:38:45.664806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:38:45.736491image/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>2022-02-01 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>2022-02-01 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>2022-02-01 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/정상영업중384985.448098179597.59295420211220135431업태구분명070-7438-5100건물용도명영화관기존게임업외업종명노래방실수문화사업자구분명영화상영관비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명6상업지역4청소년실수총게임기수총층수20170309통로너비품목명2022-02-01 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>2022-02-01 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>2022-02-01 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>2022-02-01 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>2022-02-01 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>2022-02-01 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>2022-02-01 05:20:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
47230163400000CDFF521101202100000103_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/정상영업중401170.585262195833.19932620210329113916업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210329통로너비품목명2022-02-01 05:20:03
47330173380000CDFF521101202100000203_13_05_PI2021-04-01 00:22:58.0영화제작업탄탄필름지번우편번호부산광역시 수영구 광안동 158-28 광안그린빌라 501호48296부산광역시 수영구 광안로49번길 40, 501호 (광안동, 광안그린빌라)20210330폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중392991.646291186220.25001820210330103227업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210330통로너비품목명2022-02-01 05:20:03
47430183330000CDFF521101202100000403_13_05_PU2021-04-29 02:40:00.0영화제작업공감지번우편번호부산광역시 해운대구 우동 1466-2 영상산업센터 902호48058부산광역시 해운대구 센텀서로 39, 영상산업센터 902호 (우동)20210405폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중393674.032956187973.29724320210427092012업태구분명070-4407-6252건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210405통로너비품목명2022-02-01 05:20:03
47530193360000CDFF521104202100000103_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/정상영업중374253.112341178757.42327120210611144411업태구분명070-4159-8881건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210512통로너비품목명2022-02-01 05:20:03
47630203330000CDFF521103202100000303_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/정상영업중393573.517297188018.68713820210513125315업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화배급업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210513통로너비품목명2022-02-01 05:20:03
47730213330000CDFF521101202100000503_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>2022-02-01 05:20:03
47830223250000CDFF521102202100000103_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>2022-02-01 05:20:03
47930233250000CDFF521103202100000103_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>2022-02-01 05:20:03
48030243250000CDFF521101202100000203_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>2022-02-01 05:20:03
48130253290000CDFF521104202100000103_13_03_PU2021-09-19 02:40:00.0영화상영업삼정프라퍼티 주식회사지번우편번호부산광역시 부산진구 부전동 227-2 삼정타워47296부산광역시 부산진구 중앙대로 672, 삼정타워 11층 (부전동)20210521폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중387608.014165185703.07900820210917145721업태구분명051-520-3766건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화상영업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210521통로너비품목명2022-02-01 05:20:03