Overview

Dataset statistics

Number of variables56
Number of observations2935
Missing cells2684
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory454.0 B

Variable types

Numeric6
Text8
Categorical41
DateTime1

Alerts

last_load_dttm has constant value ""Constant
sitepostno is highly imbalanced (80.8%)Imbalance
clgstdt is highly imbalanced (56.3%)Imbalance
clgenddt is highly imbalanced (56.3%)Imbalance
trdstatenm is highly imbalanced (71.3%)Imbalance
dtlstatenm is highly imbalanced (80.7%)Imbalance
bdngsrvnm is highly imbalanced (59.5%)Imbalance
facilar is highly imbalanced (71.9%)Imbalance
nearenvnm is highly imbalanced (61.1%)Imbalance
jisgnumlay is highly imbalanced (50.5%)Imbalance
regnsenm is highly imbalanced (63.6%)Imbalance
undernumlay is highly imbalanced (50.7%)Imbalance
totnumlay is highly imbalanced (59.3%)Imbalance
pasgbreth is highly imbalanced (72.7%)Imbalance
dcbymd has 2190 (74.6%) missing valuesMissing
x has 100 (3.4%) missing valuesMissing
y has 100 (3.4%) missing valuesMissing
sitetel has 284 (9.7%) missing valuesMissing
skey has unique valuesUnique

Reproduction

Analysis started2024-04-16 11:41:38.603885
Analysis finished2024-04-16 11:41:40.210303
Duration1.61 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct2935
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1474.1881
Minimum1
Maximum2947
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-16T20:41:40.266904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile147.7
Q1737.5
median1473
Q32212.5
95-th percentile2800.3
Maximum2947
Range2946
Interquartile range (IQR)1475

Descriptive statistics

Standard deviation851.58707
Coefficient of variation (CV)0.57766515
Kurtosis-1.2015019
Mean1474.1881
Median Absolute Deviation (MAD)738
Skewness0.00081959591
Sum4326742
Variance725200.54
MonotonicityNot monotonic
2024-04-16T20:41:40.379543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1959 1
 
< 0.1%
1961 1
 
< 0.1%
1963 1
 
< 0.1%
1964 1
 
< 0.1%
1965 1
 
< 0.1%
1970 1
 
< 0.1%
1971 1
 
< 0.1%
1972 1
 
< 0.1%
1967 1
 
< 0.1%
Other values (2925) 2925
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2947 1
< 0.1%
2946 1
< 0.1%
2945 1
< 0.1%
2944 1
< 0.1%
2943 1
< 0.1%
2942 1
< 0.1%
2941 1
< 0.1%
2940 1
< 0.1%
2939 1
< 0.1%
2938 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct159
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3624489.6
Minimum3000000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-16T20:41:40.507471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3020000
Q13160000
median3270000
Q33880000
95-th percentile5450000
Maximum6520000
Range3520000
Interquartile range (IQR)720000

Descriptive statistics

Standard deviation743864.2
Coefficient of variation (CV)0.20523281
Kurtosis3.0385948
Mean3624489.6
Median Absolute Deviation (MAD)180000
Skewness1.8627669
Sum1.0637877 × 1010
Variance5.5333395 × 1011
MonotonicityNot monotonic
2024-04-16T20:41:40.627171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3220000 321
 
10.9%
3130000 195
 
6.6%
3210000 163
 
5.6%
3330000 109
 
3.7%
3290000 73
 
2.5%
3030000 71
 
2.4%
3000000 70
 
2.4%
3020000 63
 
2.1%
3120000 62
 
2.1%
4050000 61
 
2.1%
Other values (149) 1747
59.5%
ValueCountFrequency (%)
3000000 70
2.4%
3010000 50
1.7%
3020000 63
2.1%
3030000 71
2.4%
3040000 35
1.2%
3050000 25
 
0.9%
3060000 16
 
0.5%
3070000 20
 
0.7%
3080000 4
 
0.1%
3090000 9
 
0.3%
ValueCountFrequency (%)
6520000 4
 
0.1%
6510000 33
1.1%
5710000 18
0.6%
5690000 11
 
0.4%
5680000 8
 
0.3%
5670000 18
0.6%
5600000 20
0.7%
5590000 13
 
0.4%
5540000 4
 
0.1%
5530000 12
 
0.4%

mgtno
Text

Distinct592
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
2024-04-16T20:41:40.814654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters58700
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

Unique279 ?
Unique (%)9.5%

Sample

1st rowCDFF4220002005000001
2nd rowCDFF4220002017000003
3rd rowCDFF4220002017000006
4th rowCDFF4220002017000005
5th rowCDFF4220001982000001
ValueCountFrequency (%)
cdff5211012019000001 111
 
3.8%
cdff5211012020000001 95
 
3.2%
cdff5211012019000002 77
 
2.6%
cdff5211032020000001 68
 
2.3%
cdff5211012020000002 66
 
2.2%
cdff5211042020000001 66
 
2.2%
cdff5211032019000001 58
 
2.0%
cdff4220002020000001 54
 
1.8%
cdff5211012019000003 50
 
1.7%
cdff5211022020000001 50
 
1.7%
Other values (582) 2240
76.3%
2024-04-16T20:41:41.120642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22946
39.1%
2 8818
 
15.0%
1 8341
 
14.2%
F 5870
 
10.0%
C 2935
 
5.0%
D 2935
 
5.0%
5 2425
 
4.1%
4 1355
 
2.3%
9 1308
 
2.2%
3 853
 
1.5%
Other values (3) 914
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46960
80.0%
Uppercase Letter 11740
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22946
48.9%
2 8818
 
18.8%
1 8341
 
17.8%
5 2425
 
5.2%
4 1355
 
2.9%
9 1308
 
2.8%
3 853
 
1.8%
8 425
 
0.9%
6 261
 
0.6%
7 228
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
F 5870
50.0%
C 2935
25.0%
D 2935
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46960
80.0%
Latin 11740
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22946
48.9%
2 8818
 
18.8%
1 8341
 
17.8%
5 2425
 
5.2%
4 1355
 
2.9%
9 1308
 
2.8%
3 853
 
1.8%
8 425
 
0.9%
6 261
 
0.6%
7 228
 
0.5%
Latin
ValueCountFrequency (%)
F 5870
50.0%
C 2935
25.0%
D 2935
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22946
39.1%
2 8818
 
15.0%
1 8341
 
14.2%
F 5870
 
10.0%
C 2935
 
5.0%
D 2935
 
5.0%
5 2425
 
4.1%
4 1355
 
2.3%
9 1308
 
2.2%
3 853
 
1.5%
Other values (3) 914
 
1.6%

opnsvcid
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
03_13_05_P
1243 
03_13_02_P
799 
03_13_01_P
431 
03_13_04_P
248 
03_13_03_P
214 

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_05_P 1243
42.4%
03_13_02_P 799
27.2%
03_13_01_P 431
 
14.7%
03_13_04_P 248
 
8.4%
03_13_03_P 214
 
7.3%

Length

2024-04-16T20:41:41.242007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:41.339621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_13_05_p 1243
42.4%
03_13_02_p 799
27.2%
03_13_01_p 431
 
14.7%
03_13_04_p 248
 
8.4%
03_13_03_p 214
 
7.3%

updategbn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
I
2297 
U
638 

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 2297
78.3%
U 638
 
21.7%

Length

2024-04-16T20:41:41.448115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:41.542299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2297
78.3%
u 638
 
21.7%
Distinct664
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-31 02:40:00
2024-04-16T20:41:41.643549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T20:41:41.760869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
영화제작업
1243 
영화상영관
579 
영화배급업
431 
영화수입업
248 
<NA>
220 

Length

Max length5
Median length5
Mean length4.9250426
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화제작업 1243
42.4%
영화상영관 579
19.7%
영화배급업 431
 
14.7%
영화수입업 248
 
8.4%
<NA> 220
 
7.5%
영화상영업 214
 
7.3%

Length

2024-04-16T20:41:41.883233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:41.975841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화제작업 1243
42.4%
영화상영관 579
19.7%
영화배급업 431
 
14.7%
영화수입업 248
 
8.4%
na 220
 
7.5%
영화상영업 214
 
7.3%

bplcnm
Text

Distinct1801
Distinct (%)61.4%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
2024-04-16T20:41:42.118938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length28
Mean length10.415673
Min length2

Characters and Unicode

Total characters30570
Distinct characters642
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1234 ?
Unique (%)42.0%

Sample

1st row국도극장 예술관
2nd row롯데시네마 대영 제3관
3rd row롯데시네마 대영 제6관
4th row롯데시네마 대영 제5관
5th row메가박스 부산극장 1관
ValueCountFrequency (%)
주식회사 729
 
13.4%
롯데시네마 188
 
3.4%
cgv 130
 
2.4%
1관 95
 
1.7%
2관 93
 
1.7%
87
 
1.6%
메가박스 79
 
1.4%
3관 61
 
1.1%
4관 57
 
1.0%
메가박스중앙(주 54
 
1.0%
Other values (1542) 3880
71.2%
2024-04-16T20:41:42.405514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2520
 
8.2%
1568
 
5.1%
1034
 
3.4%
962
 
3.1%
) 917
 
3.0%
( 900
 
2.9%
889
 
2.9%
795
 
2.6%
750
 
2.5%
723
 
2.4%
Other values (632) 19512
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23390
76.5%
Space Separator 2520
 
8.2%
Uppercase Letter 1441
 
4.7%
Close Punctuation 918
 
3.0%
Open Punctuation 901
 
2.9%
Decimal Number 860
 
2.8%
Lowercase Letter 477
 
1.6%
Other Punctuation 40
 
0.1%
Other Symbol 18
 
0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1568
 
6.7%
1034
 
4.4%
962
 
4.1%
889
 
3.8%
795
 
3.4%
750
 
3.2%
723
 
3.1%
407
 
1.7%
406
 
1.7%
396
 
1.7%
Other values (561) 15460
66.1%
Uppercase Letter
ValueCountFrequency (%)
C 311
21.6%
G 279
19.4%
V 262
18.2%
E 60
 
4.2%
A 57
 
4.0%
M 49
 
3.4%
S 38
 
2.6%
O 38
 
2.6%
I 37
 
2.6%
N 34
 
2.4%
Other values (16) 276
19.2%
Lowercase Letter
ValueCountFrequency (%)
e 49
 
10.3%
i 41
 
8.6%
o 39
 
8.2%
m 32
 
6.7%
a 32
 
6.7%
t 31
 
6.5%
r 30
 
6.3%
l 26
 
5.5%
n 26
 
5.5%
s 25
 
5.2%
Other values (12) 146
30.6%
Decimal Number
ValueCountFrequency (%)
1 174
20.2%
2 156
18.1%
3 113
13.1%
4 99
11.5%
5 89
10.3%
6 86
10.0%
7 58
 
6.7%
8 37
 
4.3%
9 31
 
3.6%
0 17
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 23
57.5%
, 7
 
17.5%
& 6
 
15.0%
" 2
 
5.0%
: 2
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 917
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 900
99.9%
[ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2520
100.0%
Other Symbol
ValueCountFrequency (%)
18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23408
76.6%
Common 5244
 
17.2%
Latin 1918
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1568
 
6.7%
1034
 
4.4%
962
 
4.1%
889
 
3.8%
795
 
3.4%
750
 
3.2%
723
 
3.1%
407
 
1.7%
406
 
1.7%
396
 
1.7%
Other values (562) 15478
66.1%
Latin
ValueCountFrequency (%)
C 311
16.2%
G 279
 
14.5%
V 262
 
13.7%
E 60
 
3.1%
A 57
 
3.0%
e 49
 
2.6%
M 49
 
2.6%
i 41
 
2.1%
o 39
 
2.0%
S 38
 
2.0%
Other values (38) 733
38.2%
Common
ValueCountFrequency (%)
2520
48.1%
) 917
 
17.5%
( 900
 
17.2%
1 174
 
3.3%
2 156
 
3.0%
3 113
 
2.2%
4 99
 
1.9%
5 89
 
1.7%
6 86
 
1.6%
7 58
 
1.1%
Other values (12) 132
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23390
76.5%
ASCII 7162
 
23.4%
None 18
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2520
35.2%
) 917
 
12.8%
( 900
 
12.6%
C 311
 
4.3%
G 279
 
3.9%
V 262
 
3.7%
1 174
 
2.4%
2 156
 
2.2%
3 113
 
1.6%
4 99
 
1.4%
Other values (60) 1431
20.0%
Hangul
ValueCountFrequency (%)
1568
 
6.7%
1034
 
4.4%
962
 
4.1%
889
 
3.8%
795
 
3.4%
750
 
3.2%
723
 
3.1%
407
 
1.7%
406
 
1.7%
396
 
1.7%
Other values (561) 15460
66.1%
None
ValueCountFrequency (%)
18
100.0%

sitepostno
Categorical

IMBALANCE 

Distinct19
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2363 
지번우편번호
539 
607787
 
7
614845
 
4
601060
 
3
Other values (14)
 
19

Length

Max length6
Median length4
Mean length4.3897785
Min length4

Unique

Unique11 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2363
80.5%
지번우편번호 539
 
18.4%
607787 7
 
0.2%
614845 4
 
0.1%
601060 3
 
0.1%
608805 3
 
0.1%
600805 3
 
0.1%
600046 2
 
0.1%
612821 1
 
< 0.1%
600807 1
 
< 0.1%
Other values (9) 9
 
0.3%

Length

2024-04-16T20:41:42.525572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2363
80.5%
지번우편번호 539
 
18.4%
607787 7
 
0.2%
614845 4
 
0.1%
601060 3
 
0.1%
608805 3
 
0.1%
600805 3
 
0.1%
600046 2
 
0.1%
614847 1
 
< 0.1%
600045 1
 
< 0.1%
Other values (9) 9
 
0.3%
Distinct1288
Distinct (%)43.9%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
2024-04-16T20:41:42.753093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length42
Mean length27.178876
Min length15

Characters and Unicode

Total characters79770
Distinct characters532
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique709 ?
Unique (%)24.2%

Sample

1st row부산광역시 중구 부평동1가 45-9번지
2nd row부산광역시 중구 남포동5가 12-1번지
3rd row부산광역시 중구 남포동5가 12-1번지
4th row부산광역시 중구 남포동5가 12-1번지
5th row부산광역시 중구 남포동5가 18-1번지
ValueCountFrequency (%)
서울특별시 1414
 
9.3%
경기도 508
 
3.4%
부산광역시 399
 
2.6%
강남구 321
 
2.1%
마포구 195
 
1.3%
서초구 164
 
1.1%
중구 141
 
0.9%
해운대구 109
 
0.7%
논현동 105
 
0.7%
경상남도 89
 
0.6%
Other values (3021) 11688
77.2%
2024-04-16T20:41:43.139770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14777
 
18.5%
3112
 
3.9%
1 3039
 
3.8%
2975
 
3.7%
2420
 
3.0%
2201
 
2.8%
- 2171
 
2.7%
2006
 
2.5%
1959
 
2.5%
2 1861
 
2.3%
Other values (522) 43249
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47762
59.9%
Space Separator 14777
 
18.5%
Decimal Number 13972
 
17.5%
Dash Punctuation 2171
 
2.7%
Uppercase Letter 753
 
0.9%
Lowercase Letter 126
 
0.2%
Other Punctuation 57
 
0.1%
Math Symbol 50
 
0.1%
Close Punctuation 47
 
0.1%
Open Punctuation 47
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3112
 
6.5%
2975
 
6.2%
2420
 
5.1%
2201
 
4.6%
2006
 
4.2%
1959
 
4.1%
1506
 
3.2%
1466
 
3.1%
1465
 
3.1%
1039
 
2.2%
Other values (463) 27613
57.8%
Uppercase Letter
ValueCountFrequency (%)
C 64
 
8.5%
E 62
 
8.2%
B 56
 
7.4%
A 54
 
7.2%
T 49
 
6.5%
K 47
 
6.2%
G 41
 
5.4%
S 40
 
5.3%
L 38
 
5.0%
V 36
 
4.8%
Other values (15) 266
35.3%
Lowercase Letter
ValueCountFrequency (%)
i 22
17.5%
e 22
17.5%
n 13
10.3%
c 13
10.3%
t 13
10.3%
y 9
7.1%
l 7
 
5.6%
r 6
 
4.8%
a 6
 
4.8%
z 3
 
2.4%
Other values (5) 12
9.5%
Decimal Number
ValueCountFrequency (%)
1 3039
21.8%
2 1861
13.3%
3 1393
10.0%
0 1268
9.1%
5 1260
9.0%
4 1235
8.8%
6 1163
 
8.3%
7 1019
 
7.3%
9 902
 
6.5%
8 832
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 38
66.7%
& 19
33.3%
Letter Number
ValueCountFrequency (%)
5
62.5%
3
37.5%
Space Separator
ValueCountFrequency (%)
14777
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2171
100.0%
Math Symbol
ValueCountFrequency (%)
~ 50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47762
59.9%
Common 31121
39.0%
Latin 887
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3112
 
6.5%
2975
 
6.2%
2420
 
5.1%
2201
 
4.6%
2006
 
4.2%
1959
 
4.1%
1506
 
3.2%
1466
 
3.1%
1465
 
3.1%
1039
 
2.2%
Other values (463) 27613
57.8%
Latin
ValueCountFrequency (%)
C 64
 
7.2%
E 62
 
7.0%
B 56
 
6.3%
A 54
 
6.1%
T 49
 
5.5%
K 47
 
5.3%
G 41
 
4.6%
S 40
 
4.5%
L 38
 
4.3%
V 36
 
4.1%
Other values (32) 400
45.1%
Common
ValueCountFrequency (%)
14777
47.5%
1 3039
 
9.8%
- 2171
 
7.0%
2 1861
 
6.0%
3 1393
 
4.5%
0 1268
 
4.1%
5 1260
 
4.0%
4 1235
 
4.0%
6 1163
 
3.7%
7 1019
 
3.3%
Other values (7) 1935
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47762
59.9%
ASCII 32000
40.1%
Number Forms 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14777
46.2%
1 3039
 
9.5%
- 2171
 
6.8%
2 1861
 
5.8%
3 1393
 
4.4%
0 1268
 
4.0%
5 1260
 
3.9%
4 1235
 
3.9%
6 1163
 
3.6%
7 1019
 
3.2%
Other values (47) 2814
 
8.8%
Hangul
ValueCountFrequency (%)
3112
 
6.5%
2975
 
6.2%
2420
 
5.1%
2201
 
4.6%
2006
 
4.2%
1959
 
4.1%
1506
 
3.2%
1466
 
3.1%
1465
 
3.1%
1039
 
2.2%
Other values (463) 27613
57.8%
Number Forms
ValueCountFrequency (%)
5
62.5%
3
37.5%

rdnpostno
Real number (ℝ)

Distinct996
Distinct (%)33.9%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean20224.122
Minimum1096
Maximum63627
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-16T20:41:43.260193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1096
5-th percentile3182
Q16018
median10494
Q337024
95-th percentile54654
Maximum63627
Range62531
Interquartile range (IQR)31006

Descriptive statistics

Standard deviation18884.052
Coefficient of variation (CV)0.933739
Kurtosis-0.86056193
Mean20224.122
Median Absolute Deviation (MAD)6450
Skewness0.860609
Sum59337575
Variance3.5660741 × 108
MonotonicityNot monotonic
2024-04-16T20:41:43.368504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48947 77
 
2.6%
48058 39
 
1.3%
34913 24
 
0.8%
7567 24
 
0.8%
6040 23
 
0.8%
10881 22
 
0.7%
6627 22
 
0.7%
44249 21
 
0.7%
3993 21
 
0.7%
48953 20
 
0.7%
Other values (986) 2641
90.0%
ValueCountFrequency (%)
1096 1
 
< 0.1%
1170 3
0.1%
1318 1
 
< 0.1%
1320 1
 
< 0.1%
1337 1
 
< 0.1%
1361 1
 
< 0.1%
1379 1
 
< 0.1%
1400 1
 
< 0.1%
1410 1
 
< 0.1%
1422 1
 
< 0.1%
ValueCountFrequency (%)
63627 1
 
< 0.1%
63595 1
 
< 0.1%
63580 1
 
< 0.1%
63558 1
 
< 0.1%
63343 1
 
< 0.1%
63316 15
0.5%
63270 3
 
0.1%
63217 3
 
0.1%
63208 4
 
0.1%
63207 1
 
< 0.1%
Distinct1328
Distinct (%)45.4%
Missing8
Missing (%)0.3%
Memory size23.1 KiB
2024-04-16T20:41:43.633481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length50
Mean length34.981551
Min length5

Characters and Unicode

Total characters102391
Distinct characters568
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique732 ?
Unique (%)25.0%

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 (%)
서울특별시 1413
 
7.0%
경기도 506
 
2.5%
부산광역시 393
 
1.9%
강남구 321
 
1.6%
2층 226
 
1.1%
마포구 194
 
1.0%
3층 173
 
0.9%
서초구 164
 
0.8%
4층 141
 
0.7%
중구 138
 
0.7%
Other values (3526) 16517
81.8%
2024-04-16T20:41:44.047125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17289
 
16.9%
1 3800
 
3.7%
3613
 
3.5%
3008
 
2.9%
, 2991
 
2.9%
2906
 
2.8%
) 2680
 
2.6%
( 2680
 
2.6%
2 2470
 
2.4%
2460
 
2.4%
Other values (558) 58494
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58205
56.8%
Space Separator 17289
 
16.9%
Decimal Number 16889
 
16.5%
Other Punctuation 3010
 
2.9%
Close Punctuation 2680
 
2.6%
Open Punctuation 2680
 
2.6%
Uppercase Letter 852
 
0.8%
Dash Punctuation 531
 
0.5%
Lowercase Letter 135
 
0.1%
Math Symbol 112
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3613
 
6.2%
3008
 
5.2%
2906
 
5.0%
2460
 
4.2%
2060
 
3.5%
1521
 
2.6%
1466
 
2.5%
1464
 
2.5%
1401
 
2.4%
1377
 
2.4%
Other values (496) 36929
63.4%
Uppercase Letter
ValueCountFrequency (%)
B 96
 
11.3%
C 82
 
9.6%
E 69
 
8.1%
A 65
 
7.6%
K 51
 
6.0%
T 50
 
5.9%
G 46
 
5.4%
S 40
 
4.7%
V 40
 
4.7%
L 38
 
4.5%
Other values (16) 275
32.3%
Lowercase Letter
ValueCountFrequency (%)
e 22
16.3%
i 22
16.3%
c 15
11.1%
n 13
9.6%
t 13
9.6%
y 9
6.7%
l 7
 
5.2%
a 6
 
4.4%
r 6
 
4.4%
b 6
 
4.4%
Other values (7) 16
11.9%
Decimal Number
ValueCountFrequency (%)
1 3800
22.5%
2 2470
14.6%
0 2164
12.8%
3 1857
11.0%
4 1446
 
8.6%
5 1402
 
8.3%
6 1005
 
6.0%
7 988
 
5.8%
9 903
 
5.3%
8 854
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 2991
99.4%
& 19
 
0.6%
Letter Number
ValueCountFrequency (%)
5
62.5%
3
37.5%
Space Separator
ValueCountFrequency (%)
17289
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2680
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2680
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 531
100.0%
Math Symbol
ValueCountFrequency (%)
~ 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58205
56.8%
Common 43191
42.2%
Latin 995
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3613
 
6.2%
3008
 
5.2%
2906
 
5.0%
2460
 
4.2%
2060
 
3.5%
1521
 
2.6%
1466
 
2.5%
1464
 
2.5%
1401
 
2.4%
1377
 
2.4%
Other values (496) 36929
63.4%
Latin
ValueCountFrequency (%)
B 96
 
9.6%
C 82
 
8.2%
E 69
 
6.9%
A 65
 
6.5%
K 51
 
5.1%
T 50
 
5.0%
G 46
 
4.6%
S 40
 
4.0%
V 40
 
4.0%
L 38
 
3.8%
Other values (35) 418
42.0%
Common
ValueCountFrequency (%)
17289
40.0%
1 3800
 
8.8%
, 2991
 
6.9%
) 2680
 
6.2%
( 2680
 
6.2%
2 2470
 
5.7%
0 2164
 
5.0%
3 1857
 
4.3%
4 1446
 
3.3%
5 1402
 
3.2%
Other values (7) 4412
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58205
56.8%
ASCII 44178
43.1%
Number Forms 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17289
39.1%
1 3800
 
8.6%
, 2991
 
6.8%
) 2680
 
6.1%
( 2680
 
6.1%
2 2470
 
5.6%
0 2164
 
4.9%
3 1857
 
4.2%
4 1446
 
3.3%
5 1402
 
3.2%
Other values (50) 5399
 
12.2%
Hangul
ValueCountFrequency (%)
3613
 
6.2%
3008
 
5.2%
2906
 
5.0%
2460
 
4.2%
2060
 
3.5%
1521
 
2.6%
1466
 
2.5%
1464
 
2.5%
1401
 
2.4%
1377
 
2.4%
Other values (496) 36929
63.4%
Number Forms
ValueCountFrequency (%)
5
62.5%
3
37.5%

apvpermymd
Real number (ℝ)

Distinct662
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20179055
Minimum19451015
Maximum22030212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-16T20:41:44.169406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20061023
Q120181220
median20190725
Q320200422
95-th percentile20201230
Maximum22030212
Range2579197
Interquartile range (IQR)19202.5

Descriptive statistics

Standard deviation58874.221
Coefficient of variation (CV)0.0029175907
Kurtosis347.49396
Mean20179055
Median Absolute Deviation (MAD)9602
Skewness8.2033031
Sum5.9225525 × 1010
Variance3.4661739 × 109
MonotonicityNot monotonic
2024-04-16T20:41:44.288842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190412 30
 
1.0%
20190315 30
 
1.0%
20190503 27
 
0.9%
20200214 26
 
0.9%
20200221 26
 
0.9%
20181207 25
 
0.9%
20181025 24
 
0.8%
20190322 24
 
0.8%
20190125 24
 
0.8%
20190111 24
 
0.8%
Other values (652) 2675
91.1%
ValueCountFrequency (%)
19451015 1
< 0.1%
19591023 1
< 0.1%
19690925 1
< 0.1%
19820125 1
< 0.1%
19910826 1
< 0.1%
19930814 2
0.1%
19970308 1
< 0.1%
19980307 1
< 0.1%
19980319 1
< 0.1%
19980623 1
< 0.1%
ValueCountFrequency (%)
22030212 1
 
< 0.1%
20210129 10
0.3%
20210128 8
0.3%
20210127 10
0.3%
20210126 1
 
< 0.1%
20210125 3
 
0.1%
20210122 8
0.3%
20210121 2
 
0.1%
20210120 4
 
0.1%
20210119 6
0.2%

dcbymd
Text

MISSING 

Distinct92
Distinct (%)12.3%
Missing2190
Missing (%)74.6%
Memory size23.1 KiB
2024-04-16T20:41:44.510766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length5.1167785
Min length4

Characters and Unicode

Total characters3812
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)7.0%

Sample

1st row20080501
2nd row20070725
3rd row20160617
4th row20160617
5th row20160617
ValueCountFrequency (%)
폐업일자 537
72.1%
20200805 12
 
1.6%
20170315 10
 
1.3%
20210119 10
 
1.3%
20200211 8
 
1.1%
20160617 8
 
1.1%
20110616 8
 
1.1%
20100806 7
 
0.9%
20200907 6
 
0.8%
20200713 5
 
0.7%
Other values (82) 134
 
18.0%
2024-04-16T20:41:44.855570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 584
15.3%
537
14.1%
537
14.1%
537
14.1%
537
14.1%
2 430
11.3%
1 293
7.7%
9 73
 
1.9%
6 69
 
1.8%
7 62
 
1.6%
Other values (4) 153
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2148
56.3%
Decimal Number 1664
43.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 584
35.1%
2 430
25.8%
1 293
17.6%
9 73
 
4.4%
6 69
 
4.1%
7 62
 
3.7%
3 46
 
2.8%
5 43
 
2.6%
8 34
 
2.0%
4 30
 
1.8%
Other Letter
ValueCountFrequency (%)
537
25.0%
537
25.0%
537
25.0%
537
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2148
56.3%
Common 1664
43.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 584
35.1%
2 430
25.8%
1 293
17.6%
9 73
 
4.4%
6 69
 
4.1%
7 62
 
3.7%
3 46
 
2.8%
5 43
 
2.6%
8 34
 
2.0%
4 30
 
1.8%
Hangul
ValueCountFrequency (%)
537
25.0%
537
25.0%
537
25.0%
537
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2148
56.3%
ASCII 1664
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 584
35.1%
2 430
25.8%
1 293
17.6%
9 73
 
4.4%
6 69
 
4.1%
7 62
 
3.7%
3 46
 
2.8%
5 43
 
2.6%
8 34
 
2.0%
4 30
 
1.8%
Hangul
ValueCountFrequency (%)
537
25.0%
537
25.0%
537
25.0%
537
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2394 
휴업시작일자
540 
20200210
 
1

Length

Max length8
Median length4
Mean length4.3693356
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2394
81.6%
휴업시작일자 540
 
18.4%
20200210 1
 
< 0.1%

Length

2024-04-16T20:41:44.980706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:45.073010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2394
81.6%
휴업시작일자 540
 
18.4%
20200210 1
 
< 0.1%

clgenddt
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2394 
휴업종료일자
540 
20210131
 
1

Length

Max length8
Median length4
Mean length4.3693356
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2394
81.6%
휴업종료일자 540
 
18.4%
20210131 1
 
< 0.1%

Length

2024-04-16T20:41:45.176827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:45.280098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2394
81.6%
휴업종료일자 540
 
18.4%
20210131 1
 
< 0.1%

ropnymd
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
재개업일자
540 

Length

Max length5
Median length4
Mean length4.1839864
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
재개업일자 540
 
18.4%

Length

2024-04-16T20:41:45.383949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:45.479186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
재개업일자 540
 
18.4%

trdstatenm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
영업/정상
2518 
13
 
163
제외/삭제/전출
 
100
03
 
56
폐업
 
52
Other values (4)
 
46

Length

Max length8
Median length5
Mean length4.8081772
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 2518
85.8%
13 163
 
5.6%
제외/삭제/전출 100
 
3.4%
03 56
 
1.9%
폐업 52
 
1.8%
<NA> 36
 
1.2%
영업상태 8
 
0.3%
35 1
 
< 0.1%
휴업 1
 
< 0.1%

Length

2024-04-16T20:41:45.583083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:45.685882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 2518
85.8%
13 163
 
5.6%
제외/삭제/전출 100
 
3.4%
03 56
 
1.9%
폐업 52
 
1.8%
na 36
 
1.2%
영업상태 8
 
0.3%
35 1
 
< 0.1%
휴업 1
 
< 0.1%

dtlstatenm
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
영업중
2725 
폐업
 
108
전출
 
100
직권말소
 
1
휴업
 
1

Length

Max length4
Median length3
Mean length2.9291312
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 2725
92.8%
폐업 108
 
3.7%
전출 100
 
3.4%
직권말소 1
 
< 0.1%
휴업 1
 
< 0.1%

Length

2024-04-16T20:41:45.798934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:45.910918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 2725
92.8%
폐업 108
 
3.7%
전출 100
 
3.4%
직권말소 1
 
< 0.1%
휴업 1
 
< 0.1%

x
Text

MISSING 

Distinct1157
Distinct (%)40.8%
Missing100
Missing (%)3.4%
Memory size23.1 KiB
2024-04-16T20:41:46.084475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.940388
Min length7

Characters and Unicode

Total characters56531
Distinct characters19
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique584 ?
Unique (%)20.6%

Sample

1st row384872.10053800000
2nd row384985.448097939
3rd row384985.448097939
4th row384985.448097939
5th row384992.28324900000
ValueCountFrequency (%)
187210.917773717 24
 
0.8%
238010.315065 24
 
0.8%
413436.345603296 21
 
0.7%
213057.927567229 19
 
0.7%
195858.214517145 18
 
0.6%
168216.577756851 15
 
0.5%
387982.19038700000 14
 
0.5%
좌표정보(x 13
 
0.5%
205013.09097466 12
 
0.4%
197257.765183997 12
 
0.4%
Other values (1147) 2663
93.9%
2024-04-16T20:41:46.360559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12515
22.1%
0 4990
 
8.8%
2 4855
 
8.6%
1 4723
 
8.4%
3 4369
 
7.7%
9 4215
 
7.5%
8 3785
 
6.7%
7 3742
 
6.6%
5 3733
 
6.6%
6 3386
 
6.0%
Other values (9) 6218
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41135
72.8%
Space Separator 12515
 
22.1%
Other Punctuation 2790
 
4.9%
Other Letter 52
 
0.1%
Open Punctuation 13
 
< 0.1%
Uppercase Letter 13
 
< 0.1%
Close Punctuation 13
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4990
12.1%
2 4855
11.8%
1 4723
11.5%
3 4369
10.6%
9 4215
10.2%
8 3785
9.2%
7 3742
9.1%
5 3733
9.1%
6 3386
8.2%
4 3337
8.1%
Other Letter
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Space Separator
ValueCountFrequency (%)
12515
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2790
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56466
99.9%
Hangul 52
 
0.1%
Latin 13
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
12515
22.2%
0 4990
 
8.8%
2 4855
 
8.6%
1 4723
 
8.4%
3 4369
 
7.7%
9 4215
 
7.5%
8 3785
 
6.7%
7 3742
 
6.6%
5 3733
 
6.6%
6 3386
 
6.0%
Other values (4) 6153
10.9%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Latin
ValueCountFrequency (%)
X 13
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56479
99.9%
Hangul 52
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12515
22.2%
0 4990
 
8.8%
2 4855
 
8.6%
1 4723
 
8.4%
3 4369
 
7.7%
9 4215
 
7.5%
8 3785
 
6.7%
7 3742
 
6.6%
5 3733
 
6.6%
6 3386
 
6.0%
Other values (5) 6166
10.9%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%

y
Text

MISSING 

Distinct1157
Distinct (%)40.8%
Missing100
Missing (%)3.4%
Memory size23.1 KiB
2024-04-16T20:41:46.796927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.940388
Min length7

Characters and Unicode

Total characters56531
Distinct characters21
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique584 ?
Unique (%)20.6%

Sample

1st row179957.08923700000
2nd row179597.592953541
3rd row179597.592953541
4th row179597.592953541
5th row179919.43700900000
ValueCountFrequency (%)
450631.435497518 24
 
0.8%
314178.057844 24
 
0.8%
233285.560332478 21
 
0.7%
421057.235457141 19
 
0.7%
419228.504806355 18
 
0.6%
431393.9120421 15
 
0.5%
186465.86425900000 14
 
0.5%
좌표정보(y 13
 
0.5%
420324.083289569 12
 
0.4%
447772.298383734 12
 
0.4%
Other values (1147) 2663
93.9%
2024-04-16T20:41:47.078632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12464
22.0%
4 6727
11.9%
0 4267
 
7.5%
1 4188
 
7.4%
5 4036
 
7.1%
8 3882
 
6.9%
3 3802
 
6.7%
2 3720
 
6.6%
6 3572
 
6.3%
7 3505
 
6.2%
Other values (11) 6368
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41176
72.8%
Space Separator 12464
 
22.0%
Other Punctuation 2790
 
4.9%
Other Letter 52
 
0.1%
Close Punctuation 15
 
< 0.1%
Open Punctuation 13
 
< 0.1%
Uppercase Letter 13
 
< 0.1%
Dash Punctuation 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 6727
16.3%
0 4267
10.4%
1 4188
10.2%
5 4036
9.8%
8 3882
9.4%
3 3802
9.2%
2 3720
9.0%
6 3572
8.7%
7 3505
8.5%
9 3477
8.4%
Other Letter
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Close Punctuation
ValueCountFrequency (%)
) 13
86.7%
] 2
 
13.3%
Space Separator
ValueCountFrequency (%)
12464
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2790
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56466
99.9%
Hangul 52
 
0.1%
Latin 13
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
12464
22.1%
4 6727
11.9%
0 4267
 
7.6%
1 4188
 
7.4%
5 4036
 
7.1%
8 3882
 
6.9%
3 3802
 
6.7%
2 3720
 
6.6%
6 3572
 
6.3%
7 3505
 
6.2%
Other values (6) 6303
11.2%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%
Latin
ValueCountFrequency (%)
Y 13
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56479
99.9%
Hangul 52
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12464
22.1%
4 6727
11.9%
0 4267
 
7.6%
1 4188
 
7.4%
5 4036
 
7.1%
8 3882
 
6.9%
3 3802
 
6.7%
2 3720
 
6.6%
6 3572
 
6.3%
7 3505
 
6.2%
Other values (7) 6316
11.2%
Hangul
ValueCountFrequency (%)
13
25.0%
13
25.0%
13
25.0%
13
25.0%

lastmodts
Real number (ℝ)

Distinct2258
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0193588 × 1013
Minimum2.0030127 × 1013
Maximum2.0210129 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-16T20:41:47.198874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030127 × 1013
5-th percentile2.0180611 × 1013
Q12.0190421 × 1013
median2.0200115 × 1013
Q32.0200821 × 1013
95-th percentile2.0210108 × 1013
Maximum2.0210129 × 1013
Range1.8000202 × 1011
Interquartile range (IQR)1.0400587 × 1010

Descriptive statistics

Standard deviation1.498144 × 1010
Coefficient of variation (CV)0.00074189096
Kurtosis40.812063
Mean2.0193588 × 1013
Median Absolute Deviation (MAD)8.9871399 × 109
Skewness-5.1756713
Sum5.9268181 × 1016
Variance2.2444356 × 1020
MonotonicityNot monotonic
2024-04-16T20:41:47.330259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190418131529 6
 
0.2%
20190920121341 5
 
0.2%
20191218104848 4
 
0.1%
20201023135809 4
 
0.1%
20200918104840 4
 
0.1%
20191017170859 4
 
0.1%
20030127161348 4
 
0.1%
20190227142751 4
 
0.1%
20200626160214 3
 
0.1%
20200629141616 3
 
0.1%
Other values (2248) 2894
98.6%
ValueCountFrequency (%)
20030127161348 4
0.1%
20040731102817 1
 
< 0.1%
20050416094533 1
 
< 0.1%
20070725150334 1
 
< 0.1%
20070725150429 1
 
< 0.1%
20070725183312 1
 
< 0.1%
20071231132808 1
 
< 0.1%
20080506140353 1
 
< 0.1%
20080627132446 1
 
< 0.1%
20090622134847 1
 
< 0.1%
ValueCountFrequency (%)
20210129182619 1
 
< 0.1%
20210129135407 3
0.1%
20210129111857 2
0.1%
20210129110840 2
0.1%
20210129110359 2
0.1%
20210129095751 2
0.1%
20210129094446 2
0.1%
20210128174538 1
 
< 0.1%
20210128172645 1
 
< 0.1%
20210128170213 1
 
< 0.1%

uptaenm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
업태구분명
540 

Length

Max length5
Median length4
Mean length4.1839864
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
업태구분명 540
 
18.4%

Length

2024-04-16T20:41:47.451610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:47.531294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
업태구분명 540
 
18.4%

sitetel
Text

MISSING 

Distinct86
Distinct (%)3.2%
Missing284
Missing (%)9.7%
Memory size23.1 KiB
2024-04-16T20:41:47.653516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.750283
Min length4

Characters and Unicode

Total characters31150
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)1.4%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234
ValueCountFrequency (%)
051-123-1234 2368
89.3%
전화번호 67
 
2.5%
032-832-0510 15
 
0.6%
063-653-7057 9
 
0.3%
02-971-6602 8
 
0.3%
070-4268-7168 7
 
0.3%
02-3017-3666 6
 
0.2%
15440070 6
 
0.2%
028580819 6
 
0.2%
0230173666 6
 
0.2%
Other values (76) 153
 
5.8%
2024-04-16T20:41:47.894958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7307
23.5%
- 5085
16.3%
3 4995
16.0%
2 4932
15.8%
0 2848
 
9.1%
5 2591
 
8.3%
4 2491
 
8.0%
7 219
 
0.7%
6 186
 
0.6%
8 120
 
0.4%
Other values (5) 376
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25797
82.8%
Dash Punctuation 5085
 
16.3%
Other Letter 268
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7307
28.3%
3 4995
19.4%
2 4932
19.1%
0 2848
 
11.0%
5 2591
 
10.0%
4 2491
 
9.7%
7 219
 
0.8%
6 186
 
0.7%
8 120
 
0.5%
9 108
 
0.4%
Other Letter
ValueCountFrequency (%)
67
25.0%
67
25.0%
67
25.0%
67
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 5085
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30882
99.1%
Hangul 268
 
0.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7307
23.7%
- 5085
16.5%
3 4995
16.2%
2 4932
16.0%
0 2848
 
9.2%
5 2591
 
8.4%
4 2491
 
8.1%
7 219
 
0.7%
6 186
 
0.6%
8 120
 
0.4%
Hangul
ValueCountFrequency (%)
67
25.0%
67
25.0%
67
25.0%
67
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30882
99.1%
Hangul 268
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7307
23.7%
- 5085
16.5%
3 4995
16.2%
2 4932
16.0%
0 2848
 
9.2%
5 2591
 
8.4%
4 2491
 
8.1%
7 219
 
0.7%
6 186
 
0.6%
8 120
 
0.4%
Hangul
ValueCountFrequency (%)
67
25.0%
67
25.0%
67
25.0%
67
25.0%

bdngsrvnm
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2057 
건물용도명
504 
문화시설
314 
근린생활시설
 
42
유통시설
 
9
Other values (4)
 
9

Length

Max length6
Median length4
Mean length4.1959114
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2057
70.1%
건물용도명 504
 
17.2%
문화시설 314
 
10.7%
근린생활시설 42
 
1.4%
유통시설 9
 
0.3%
호텔 6
 
0.2%
사무실 1
 
< 0.1%
기타 1
 
< 0.1%
식품위생시설 1
 
< 0.1%

Length

2024-04-16T20:41:48.012301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:48.132409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2057
70.1%
건물용도명 504
 
17.2%
문화시설 314
 
10.7%
근린생활시설 42
 
1.4%
유통시설 9
 
0.3%
호텔 6
 
0.2%
사무실 1
 
< 0.1%
기타 1
 
< 0.1%
식품위생시설 1
 
< 0.1%

perplaformsenm
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
1678 
영화관
778 
공연장형태구분명
462 
자동차극장
 
17

Length

Max length8
Median length4
Mean length4.3703578
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1678
57.2%
영화관 778
26.5%
공연장형태구분명 462
 
15.7%
자동차극장 17
 
0.6%

Length

2024-04-16T20:41:48.269511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:48.373201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1678
57.2%
영화관 778
26.5%
공연장형태구분명 462
 
15.7%
자동차극장 17
 
0.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
기존게임업외업종명
540 

Length

Max length9
Median length4
Mean length4.9199319
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
기존게임업외업종명 540
 
18.4%

Length

2024-04-16T20:41:48.487263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:48.581781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
기존게임업외업종명 540
 
18.4%

noroomcnt
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
노래방실수
540 

Length

Max length5
Median length4
Mean length4.1839864
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
노래방실수 540
 
18.4%

Length

2024-04-16T20:41:48.672737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:48.754211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
노래방실수 540
 
18.4%

culwrkrsenm
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2199 
문화사업자구분명
539 
영화상영관
 
197

Length

Max length8
Median length4
Mean length4.8017036
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2199
74.9%
문화사업자구분명 539
 
18.4%
영화상영관 197
 
6.7%

Length

2024-04-16T20:41:48.845835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:48.934766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2199
74.9%
문화사업자구분명 539
 
18.4%
영화상영관 197
 
6.7%

culphyedcobnm
Categorical

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
영화제작업
1243 
영화상영관
799 
영화배급업
431 
영화수입업
248 
영화상영업
213 

Length

Max length5
Median length5
Mean length4.9996593
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영화제작업 1243
42.4%
영화상영관 799
27.2%
영화배급업 431
 
14.7%
영화수입업 248
 
8.4%
영화상영업 213
 
7.3%
<NA> 1
 
< 0.1%

Length

2024-04-16T20:41:49.020389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:49.124165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화제작업 1243
42.4%
영화상영관 799
27.2%
영화배급업 431
 
14.7%
영화수입업 248
 
8.4%
영화상영업 213
 
7.3%
na 1
 
< 0.1%

souarfacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
540 

Length

Max length4
Median length4
Mean length3.4480409
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
540
 
18.4%

Length

2024-04-16T20:41:49.228614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:49.316308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
540
 
18.4%

vdoretornm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
비디오재생기명
540 

Length

Max length7
Median length4
Mean length4.5519591
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
비디오재생기명 540
 
18.4%

Length

2024-04-16T20:41:49.412618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:49.504856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
비디오재생기명 540
 
18.4%

emerstairyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
540 

Length

Max length4
Median length4
Mean length3.4480409
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
540
 
18.4%

Length

2024-04-16T20:41:49.604768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:49.709294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
540
 
18.4%

emexyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
540 

Length

Max length4
Median length4
Mean length3.4480409
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
540
 
18.4%

Length

2024-04-16T20:41:49.815418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:49.917465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
540
 
18.4%

firefacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
540 

Length

Max length4
Median length4
Mean length3.4480409
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
540
 
18.4%

Length

2024-04-16T20:41:50.021401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:50.121953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
540
 
18.4%

facilar
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2386 
시설면적
539 
1578.8
 
4
0
 
4
147.46
 
1

Length

Max length6
Median length4
Mean length3.9996593
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2386
81.3%
시설면적 539
 
18.4%
1578.8 4
 
0.1%
0 4
 
0.1%
147.46 1
 
< 0.1%
181.3 1
 
< 0.1%

Length

2024-04-16T20:41:50.228232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:50.331857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2386
81.3%
시설면적 539
 
18.4%
1578.8 4
 
0.1%
0 4
 
0.1%
147.46 1
 
< 0.1%
181.3 1
 
< 0.1%

soundfacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
540 

Length

Max length4
Median length4
Mean length3.4480409
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
540
 
18.4%

Length

2024-04-16T20:41:50.432092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:50.512753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
540
 
18.4%

autochaairyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
540 

Length

Max length4
Median length4
Mean length3.4480409
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
540
 
18.4%

Length

2024-04-16T20:41:50.600813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:50.681416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
540
 
18.4%

prvdgathinnm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
제공게임물명
540 

Length

Max length6
Median length4
Mean length4.3679727
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
제공게임물명 540
 
18.4%

Length

2024-04-16T20:41:50.771820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:50.865605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
제공게임물명 540
 
18.4%

mnfactreartclcn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
제작취급품목내용
540 

Length

Max length8
Median length4
Mean length4.7359455
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
제작취급품목내용 540
 
18.4%

Length

2024-04-16T20:41:50.977000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:51.066766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
제작취급품목내용 540
 
18.4%

lghtfacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
540 

Length

Max length4
Median length4
Mean length3.4480409
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
540
 
18.4%

Length

2024-04-16T20:41:51.154645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:51.234641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
540
 
18.4%

lghtfacilinillu
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
조명시설조도
540 

Length

Max length6
Median length4
Mean length4.3679727
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
조명시설조도 540
 
18.4%

Length

2024-04-16T20:41:51.329926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:51.425636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
조명시설조도 540
 
18.4%

nearenvnm
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2213 
주변환경명
521 
기타
 
156
유흥업소밀집지역
 
25
아파트지역
 
9
Other values (2)
 
11

Length

Max length8
Median length4
Mean length4.116184
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2213
75.4%
주변환경명 521
 
17.8%
기타 156
 
5.3%
유흥업소밀집지역 25
 
0.9%
아파트지역 9
 
0.3%
주택가주변 7
 
0.2%
학교정화(상대) 4
 
0.1%

Length

2024-04-16T20:41:51.514619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:51.606723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2213
75.4%
주변환경명 521
 
17.8%
기타 156
 
5.3%
유흥업소밀집지역 25
 
0.9%
아파트지역 9
 
0.3%
주택가주변 7
 
0.2%
학교정화(상대 4
 
0.1%

jisgnumlay
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
1790 
지상층수
474 
10
 
120
7
 
72
9
 
65
Other values (18)
414 

Length

Max length4
Median length4
Mean length3.4051107
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1790
61.0%
지상층수 474
 
16.1%
10 120
 
4.1%
7 72
 
2.5%
9 65
 
2.2%
2 56
 
1.9%
8 53
 
1.8%
5 43
 
1.5%
3 33
 
1.1%
4 33
 
1.1%
Other values (13) 196
 
6.7%

Length

2024-04-16T20:41:51.710425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1790
61.0%
지상층수 474
 
16.1%
10 120
 
4.1%
7 72
 
2.5%
9 65
 
2.2%
2 56
 
1.9%
8 53
 
1.8%
5 43
 
1.5%
3 33
 
1.1%
4 33
 
1.1%
Other values (13) 196
 
6.7%

regnsenm
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2128 
지역구분명
512 
일반상업지역
 
99
준주거지역
 
53
상업지역
 
50
Other values (9)
 
93

Length

Max length6
Median length4
Mean length4.3097104
Min length4

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2128
72.5%
지역구분명 512
 
17.4%
일반상업지역 99
 
3.4%
준주거지역 53
 
1.8%
상업지역 50
 
1.7%
일반주거지역 24
 
0.8%
중심상업지역 24
 
0.8%
자연녹지지역 17
 
0.6%
주거지역 10
 
0.3%
녹지지역 8
 
0.3%
Other values (4) 10
 
0.3%

Length

2024-04-16T20:41:51.816430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2128
72.5%
지역구분명 512
 
17.4%
일반상업지역 99
 
3.4%
준주거지역 53
 
1.8%
상업지역 50
 
1.7%
일반주거지역 24
 
0.8%
중심상업지역 24
 
0.8%
자연녹지지역 17
 
0.6%
주거지역 10
 
0.3%
녹지지역 8
 
0.3%
Other values (4) 10
 
0.3%

undernumlay
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
1846 
지하층수
501 
3
 
148
2
 
114
1
 
111
Other values (9)
215 

Length

Max length4
Median length4
Mean length3.4
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1846
62.9%
지하층수 501
 
17.1%
3 148
 
5.0%
2 114
 
3.9%
1 111
 
3.8%
5 81
 
2.8%
6 52
 
1.8%
4 33
 
1.1%
7 25
 
0.9%
8 18
 
0.6%
Other values (4) 6
 
0.2%

Length

2024-04-16T20:41:51.921665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1846
62.9%
지하층수 501
 
17.1%
3 148
 
5.0%
2 114
 
3.9%
1 111
 
3.8%
5 81
 
2.8%
6 52
 
1.8%
4 33
 
1.1%
7 25
 
0.9%
8 18
 
0.6%
Other values (4) 6
 
0.2%

bgroomcnt
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
청소년실수
540 

Length

Max length5
Median length4
Mean length4.1839864
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
청소년실수 540
 
18.4%

Length

2024-04-16T20:41:52.021184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:52.107303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
청소년실수 540
 
18.4%

bgroomyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
540 

Length

Max length4
Median length4
Mean length3.4480409
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
540
 
18.4%

Length

2024-04-16T20:41:52.203590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:52.291323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
540
 
18.4%

totgasyscnt
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
총게임기수
540 

Length

Max length5
Median length4
Mean length4.1839864
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
총게임기수 540
 
18.4%

Length

2024-04-16T20:41:52.380347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:52.463990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
총게임기수 540
 
18.4%

totnumlay
Categorical

IMBALANCE 

Distinct28
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
1960 
총층수
485 
11
 
61
3
 
57
10
 
47
Other values (23)
325 

Length

Max length4
Median length4
Mean length3.4391823
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1960
66.8%
총층수 485
 
16.5%
11 61
 
2.1%
3 57
 
1.9%
10 47
 
1.6%
13 45
 
1.5%
14 32
 
1.1%
2 32
 
1.1%
15 21
 
0.7%
9 20
 
0.7%
Other values (18) 175
 
6.0%

Length

2024-04-16T20:41:52.547401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1960
66.8%
총층수 485
 
16.5%
11 61
 
2.1%
3 57
 
1.9%
10 47
 
1.6%
13 45
 
1.5%
14 32
 
1.1%
2 32
 
1.1%
15 21
 
0.7%
9 20
 
0.7%
Other values (18) 175
 
6.0%

frstregts
Real number (ℝ)

Distinct662
Distinct (%)22.6%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean20179044
Minimum19451015
Maximum22030212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.9 KiB
2024-04-16T20:41:52.654373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19451015
5-th percentile20061023
Q120181220
median20190724
Q320200422
95-th percentile20201229
Maximum22030212
Range2579197
Interquartile range (IQR)19202

Descriptive statistics

Standard deviation58881.462
Coefficient of variation (CV)0.002917951
Kurtosis347.44715
Mean20179044
Median Absolute Deviation (MAD)9601
Skewness8.2035647
Sum5.9205315 × 1010
Variance3.4670266 × 109
MonotonicityNot monotonic
2024-04-16T20:41:52.786507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190412 30
 
1.0%
20190315 30
 
1.0%
20190503 27
 
0.9%
20200214 26
 
0.9%
20200221 26
 
0.9%
20181207 25
 
0.9%
20181025 24
 
0.8%
20190322 24
 
0.8%
20190125 24
 
0.8%
20190111 24
 
0.8%
Other values (652) 2674
91.1%
ValueCountFrequency (%)
19451015 1
< 0.1%
19591023 1
< 0.1%
19690925 1
< 0.1%
19820125 1
< 0.1%
19910826 1
< 0.1%
19930814 2
0.1%
19970308 1
< 0.1%
19980307 1
< 0.1%
19980319 1
< 0.1%
19980623 1
< 0.1%
ValueCountFrequency (%)
22030212 1
 
< 0.1%
20210129 10
0.3%
20210128 8
0.3%
20210127 10
0.3%
20210126 1
 
< 0.1%
20210125 3
 
0.1%
20210122 8
0.3%
20210121 2
 
0.1%
20210120 3
 
0.1%
20210119 6
0.2%

pasgbreth
Categorical

IMBALANCE 

Distinct28
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2154 
통로너비
527 
1
 
145
1.2
 
19
1050
 
12
Other values (23)
 
78

Length

Max length5
Median length4
Mean length3.8320273
Min length1

Unique

Unique10 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2154
73.4%
통로너비 527
 
18.0%
1 145
 
4.9%
1.2 19
 
0.6%
1050 12
 
0.4%
1.5 12
 
0.4%
1.3 10
 
0.3%
1.1 9
 
0.3%
1.08 9
 
0.3%
1.45 5
 
0.2%
Other values (18) 33
 
1.1%

Length

2024-04-16T20:41:52.902355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2154
73.4%
통로너비 527
 
18.0%
1 145
 
4.9%
1.2 19
 
0.6%
1050 12
 
0.4%
1.5 12
 
0.4%
1.3 10
 
0.3%
1.1 9
 
0.3%
1.08 9
 
0.3%
1.45 5
 
0.2%
Other values (18) 33
 
1.1%

speclghtyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
540 

Length

Max length4
Median length4
Mean length3.4480409
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
540
 
18.4%

Length

2024-04-16T20:41:53.253497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:53.339124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
540
 
18.4%

cnvefacilyn
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
540 

Length

Max length4
Median length4
Mean length3.4480409
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
540
 
18.4%

Length

2024-04-16T20:41:53.437503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:53.523750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
540
 
18.4%

actlnm
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
<NA>
2395 
품목명
540 

Length

Max length4
Median length4
Mean length3.8160136
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2395
81.6%
품목명 540
 
18.4%

Length

2024-04-16T20:41:53.605955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:53.686275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2395
81.6%
품목명 540
 
18.4%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
2021-02-01 05:20:03
2935 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-02-01 05:20:03
2nd row2021-02-01 05:20:03
3rd row2021-02-01 05:20:03
4th row2021-02-01 05:20:03
5th row2021-02-01 05:20:03

Common Values

ValueCountFrequency (%)
2021-02-01 05:20:03 2935
100.0%

Length

2024-04-16T20:41:53.768742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T20:41:53.850122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-02-01 2935
50.0%
05:20:03 2935
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>03폐업384872.10053800000179957.0892370000020080506140353<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>4<NA><NA><NA><NA><NA><NA>20050415<NA><NA><NA><NA>2021-02-01 05:20:03
123250000CDFF422000201700000303_13_02_PU2020-01-19 02:40:00.0영화상영관롯데시네마 대영 제3관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448097939179597.59295354120200117162055<NA>051-123-1234<NA>영화관<NA><NA><NA>영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6상업지역4<NA><NA><NA><NA>20170309<NA><NA><NA><NA>2021-02-01 05:20:03
233250000CDFF422000201700000603_13_02_PU2020-01-19 02:40:00.0영화상영관롯데시네마 대영 제6관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448097939179597.59295354120200117162131<NA>051-123-1234<NA>영화관<NA><NA><NA>영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6상업지역4<NA><NA><NA><NA>20170309<NA><NA><NA><NA>2021-02-01 05:20:03
343250000CDFF422000201700000503_13_02_PU2020-01-19 02:40:00.0영화상영관롯데시네마 대영 제5관<NA>부산광역시 중구 남포동5가 12-1번지48953부산광역시 중구 비프광장로 37, 6층 (남포동5가)20170309<NA><NA><NA><NA>영업/정상영업중384985.448097939179597.59295354120200117162119<NA>051-123-1234<NA>영화관<NA><NA><NA>영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6상업지역4<NA><NA><NA><NA>20170309<NA><NA><NA><NA>2021-02-01 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>13영업중384992.28324900000179919.4370090000020180621102116<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>1<NA><NA><NA><NA>19820125<NA><NA><NA><NA>2021-02-01 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>13영업중384992.28324900000179919.4370090000020180621102237<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19930814<NA><NA><NA><NA>2021-02-01 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>13영업중384992.28324900000179919.4370090000020180621103110<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>1<NA><NA><NA><NA>19930814<NA><NA><NA><NA>2021-02-01 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>2021-02-01 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>03폐업385057.25808100000179919.4880840000020160617104121<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1019990716<NA><NA><NA><NA>2021-02-01 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>03폐업385057.25808100000179919.4880840000020160617104156<NA>051-123-1234<NA>영화관<NA><NA>영화상영관영화상영관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6<NA>4<NA><NA><NA><NA>19990716<NA><NA><NA><NA>2021-02-01 05:20:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngsrvnmperplaformsenmbfgameocptectcobnmnoroomcntculwrkrsenmculphyedcobnmsouarfacilynvdoretornmemerstairynemexynfirefacilynfacilarsoundfacilynautochaairynprvdgathinnmmnfactreartclcnlghtfacilynlghtfacilinillunearenvnmjisgnumlayregnsenmundernumlaybgroomcntbgroomyntotgasyscnttotnumlayfrstregtspasgbrethspeclghtyncnvefacilynactlnmlast_load_dttm
292529383220000CDFF521101202100001903_13_05_PI2021-01-31 00:23:03.0영화제작업(주)에스팀지번우편번호서울특별시 강남구 신사동 595-66024서울특별시 강남구 논현로168길 40 (신사동)20210129폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중202691.183508103446770.34157298420210129111857업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210129통로너비품목명2021-02-01 05:20:03
292629394590000CDFF521103202100000103_13_01_PI2021-01-31 00:23:03.0영화배급업청양영상미디어<NA>충청남도 청양군 청양읍 읍내리 191-5 청양군문화체육센타33330충청남도 청양군 청양읍 칠갑산로 221, 청양군문화체육센타 3층20210129<NA><NA><NA><NA>영업/정상영업중182102.166268327860.01457120210129094446<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>20210129<NA><NA><NA><NA>2021-02-01 05:20:03
292729403780000CDFF521101202100000403_13_05_PI2021-01-31 00:23:03.0영화제작업주식회사 보이스프로덕션<NA>경기도 성남시 분당구 야탑동 525 탑마을경남아너스빌 711동 1902호13519경기도 성남시 분당구 판교로 519, 711동 1902호 (야탑동, 탑마을경남아너스빌)20210129<NA><NA><NA><NA>영업/정상영업중211609.222087618433918.50424955820210129095751<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>20210129<NA><NA><NA><NA>2021-02-01 05:20:03
292829413860000CDFF521101202100000203_13_05_PI2021-01-31 00:23:03.0영화제작업주식회사 타임픽서<NA>경기도 부천시 상동 529-214505경기도 부천시 길주로 1, 한국만화영상진흥원 비지니스센터 311호 (상동)20210129<NA><NA><NA><NA>영업/정상영업중177525.457142467445566.11631285420210129110359<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>20210129<NA><NA><NA><NA>2021-02-01 05:20:03
292929424060000CDFF521101202100000303_13_05_PI2021-01-31 00:23:03.0영화제작업오토마타 공작소<NA>경기도 파주시 월롱면 덕은리 1041-310844경기도 파주시 월롱면 옥돌내길 178-920210129<NA><NA><NA><NA>영업/정상영업중180558.362491819478836.09393683120210129110840<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>20210129<NA><NA><NA><NA>2021-02-01 05:20:03
293029433220000CDFF521101202100001903_13_05_PI2021-01-31 00:23:03.0영화제작업(주)에스팀지번우편번호서울특별시 강남구 신사동 595-66024서울특별시 강남구 논현로168길 40 (신사동)20210129폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업중202691.183508103446770.34157298420210129111857업태구분명전화번호건물용도명공연장형태구분명기존게임업외업종명노래방실수문화사업자구분명영화제작업비디오재생기명시설면적제공게임물명제작취급품목내용조명시설조도주변환경명지상층수지역구분명지하층수청소년실수총게임기수총층수20210129통로너비품목명2021-02-01 05:20:03
293129444590000CDFF521103202100000103_13_01_PI2021-01-31 00:23:03.0영화배급업청양영상미디어<NA>충청남도 청양군 청양읍 읍내리 191-5 청양군문화체육센타33330충청남도 청양군 청양읍 칠갑산로 221, 청양군문화체육센타 3층20210129<NA><NA><NA><NA>영업/정상영업중182102.166268327860.01457120210129094446<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>20210129<NA><NA><NA><NA>2021-02-01 05:20:03
293229453780000CDFF521101202100000403_13_05_PI2021-01-31 00:23:03.0영화제작업주식회사 보이스프로덕션<NA>경기도 성남시 분당구 야탑동 525 탑마을경남아너스빌 711동 1902호13519경기도 성남시 분당구 판교로 519, 711동 1902호 (야탑동, 탑마을경남아너스빌)20210129<NA><NA><NA><NA>영업/정상영업중211609.222087618433918.50424955820210129095751<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>20210129<NA><NA><NA><NA>2021-02-01 05:20:03
293329463860000CDFF521101202100000203_13_05_PI2021-01-31 00:23:03.0영화제작업주식회사 타임픽서<NA>경기도 부천시 상동 529-214505경기도 부천시 길주로 1, 한국만화영상진흥원 비지니스센터 311호 (상동)20210129<NA><NA><NA><NA>영업/정상영업중177525.457142467445566.11631285420210129110359<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>20210129<NA><NA><NA><NA>2021-02-01 05:20:03
293429474060000CDFF521101202100000303_13_05_PI2021-01-31 00:23:03.0영화제작업오토마타 공작소<NA>경기도 파주시 월롱면 덕은리 1041-310844경기도 파주시 월롱면 옥돌내길 178-920210129<NA><NA><NA><NA>영업/정상영업중180558.362491819478836.09393683120210129110840<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>20210129<NA><NA><NA><NA>2021-02-01 05:20:03