Overview

Dataset statistics

Number of variables40
Number of observations100
Missing cells31
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.9 KiB
Average record size in memory326.3 B

Variable types

Numeric4
Categorical29
Text7

Alerts

svc_id has constant value ""Constant
cltur_bsnm_se_nm has constant value ""Constant
cltur_phstrn_induty_nm has constant value ""Constant
sfrnd_code is highly imbalanced (89.8%)Imbalance
sfrnd_code_nm is highly imbalanced (89.8%)Imbalance
data_updt_se is highly imbalanced (85.9%)Imbalance
data_updt_de is highly imbalanced (89.8%)Imbalance
svc_id_nm is highly imbalanced (85.9%)Imbalance
last_updt_de is highly imbalanced (91.9%)Imbalance
cfr_envrn_nm is highly imbalanced (76.3%)Imbalance
area_se_nm is highly imbalanced (67.2%)Imbalance
clsbiz_de has 31 (31.0%) missing valuesMissing
skey has unique valuesUnique
person_prmisn_no has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:48:46.853663
Analysis finished2023-12-10 09:48:48.311796
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:48:48.470188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-10T18:48:48.804417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

sfrnd_code
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
3250000
98 
4200000
 
1
3290000
 
1

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row4200000
2nd row3250000
3rd row3250000
4th row3250000
5th row3250000

Common Values

ValueCountFrequency (%)
3250000 98
98.0%
4200000 1
 
1.0%
3290000 1
 
1.0%

Length

2023-12-10T18:48:49.035591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:49.193069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3250000 98
98.0%
4200000 1
 
1.0%
3290000 1
 
1.0%

sfrnd_code_nm
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
부산 중구
98 
강원 강릉시
 
1
부산 부산진구
 
1

Length

Max length7
Median length5
Mean length5.03
Min length5

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row강원 강릉시
2nd row부산 중구
3rd row부산 중구
4th row부산 중구
5th row부산 중구

Common Values

ValueCountFrequency (%)
부산 중구 98
98.0%
강원 강릉시 1
 
1.0%
부산 부산진구 1
 
1.0%

Length

2023-12-10T18:48:49.387499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:49.624373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산 99
49.5%
중구 98
49.0%
강원 1
 
0.5%
강릉시 1
 
0.5%
부산진구 1
 
0.5%

person_prmisn_no
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:48:49.958963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters2000
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

Unique100 ?
Unique (%)100.0%

Sample

1st rowCDFF3242052019000002
2nd rowCDFF3242052003000006
3rd rowCDFF3242052003000007
4th rowCDFF3242052003000008
5th rowCDFF3242052004000001
ValueCountFrequency (%)
cdff3242052019000002 1
 
1.0%
cdff3242052001000005 1
 
1.0%
cdff3242052002000021 1
 
1.0%
cdff3242052002000020 1
 
1.0%
cdff3242052001000017 1
 
1.0%
cdff3242052001000016 1
 
1.0%
cdff3242052001000014 1
 
1.0%
cdff3242052001000013 1
 
1.0%
cdff3242052001000009 1
 
1.0%
cdff3242052001000008 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:48:50.555683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 730
36.5%
2 344
17.2%
F 200
 
10.0%
3 132
 
6.6%
4 114
 
5.7%
5 113
 
5.7%
C 100
 
5.0%
D 100
 
5.0%
1 81
 
4.0%
9 49
 
2.5%
Other values (3) 37
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1600
80.0%
Uppercase Letter 400
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 730
45.6%
2 344
21.5%
3 132
 
8.2%
4 114
 
7.1%
5 113
 
7.1%
1 81
 
5.1%
9 49
 
3.1%
6 16
 
1.0%
7 12
 
0.8%
8 9
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
F 200
50.0%
C 100
25.0%
D 100
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1600
80.0%
Latin 400
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 730
45.6%
2 344
21.5%
3 132
 
8.2%
4 114
 
7.1%
5 113
 
7.1%
1 81
 
5.1%
9 49
 
3.1%
6 16
 
1.0%
7 12
 
0.8%
8 9
 
0.6%
Latin
ValueCountFrequency (%)
F 200
50.0%
C 100
25.0%
D 100
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 730
36.5%
2 344
17.2%
F 200
 
10.0%
3 132
 
6.6%
4 114
 
5.7%
5 113
 
5.7%
C 100
 
5.0%
D 100
 
5.0%
1 81
 
4.0%
9 49
 
2.5%
Other values (3) 37
 
1.8%

svc_id
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
03_09_01_P
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03_09_01_P
2nd row03_09_01_P
3rd row03_09_01_P
4th row03_09_01_P
5th row03_09_01_P

Common Values

ValueCountFrequency (%)
03_09_01_P 100
100.0%

Length

2023-12-10T18:48:51.005476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:51.178624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_09_01_p 100
100.0%

data_updt_se
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
I
98 
U
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 98
98.0%
U 2
 
2.0%

Length

2023-12-10T18:48:51.361182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:51.510414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 98
98.0%
u 2
 
2.0%

data_updt_de
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2019-11-12 AM 12:59:59
98 
2011-11-12 AM 12:59:59
 
1
2019-11-12 AM 12:40:00
 
1

Length

Max length22
Median length22
Mean length22
Min length22

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row2019-11-12 AM 12:59:59
2nd row2019-11-12 AM 12:59:59
3rd row2019-11-12 AM 12:59:59
4th row2019-11-12 AM 12:59:59
5th row2019-11-12 AM 12:59:59

Common Values

ValueCountFrequency (%)
2019-11-12 AM 12:59:59 98
98.0%
2011-11-12 AM 12:59:59 1
 
1.0%
2019-11-12 AM 12:40:00 1
 
1.0%

Length

2023-12-10T18:48:51.731886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:51.941373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
am 100
33.3%
2019-11-12 99
33.0%
12:59:59 99
33.0%
2011-11-12 1
 
0.3%
12:40:00 1
 
0.3%

svc_id_nm
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
98 
노래연습장업
 
2

Length

Max length6
Median length1
Mean length1.1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row노래연습장업
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 98
98.0%
노래연습장업 2
 
2.0%

Length

2023-12-10T18:48:52.150748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:52.310416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
98
98.0%
노래연습장업 2
 
2.0%
Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:48:52.870317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length14
Mean length5.54
Min length1

Characters and Unicode

Total characters554
Distinct characters155
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

Unique96 ?
Unique (%)96.0%

Sample

1st row인싸코인노래연습장
2nd row호심
3rd row진양
4th row도깨비노래연습장
5th row남포노래연습장
ValueCountFrequency (%)
노래연습장 11
 
8.9%
동전노래연습장 4
 
3.3%
오디션 3
 
2.4%
앵콜 2
 
1.6%
남포노래연습장 2
 
1.6%
동전 2
 
1.6%
2
 
1.6%
샤본 1
 
0.8%
자이안트 1
 
0.8%
누브노래연습장 1
 
0.8%
Other values (94) 94
76.4%
2023-12-10T18:48:53.527294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
8.3%
46
 
8.3%
46
 
8.3%
45
 
8.1%
45
 
8.1%
23
 
4.2%
15
 
2.7%
13
 
2.3%
8
 
1.4%
7
 
1.3%
Other values (145) 260
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 495
89.4%
Uppercase Letter 25
 
4.5%
Space Separator 23
 
4.2%
Decimal Number 5
 
0.9%
Close Punctuation 2
 
0.4%
Other Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
46
 
9.3%
46
 
9.3%
46
 
9.3%
45
 
9.1%
45
 
9.1%
15
 
3.0%
13
 
2.6%
8
 
1.6%
7
 
1.4%
6
 
1.2%
Other values (126) 218
44.0%
Uppercase Letter
ValueCountFrequency (%)
S 3
12.0%
C 3
12.0%
O 3
12.0%
Y 2
8.0%
R 2
8.0%
D 2
8.0%
T 2
8.0%
V 2
8.0%
I 2
8.0%
K 1
 
4.0%
Other values (3) 3
12.0%
Decimal Number
ValueCountFrequency (%)
2 4
80.0%
3 1
 
20.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 495
89.4%
Common 34
 
6.1%
Latin 25
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
46
 
9.3%
46
 
9.3%
46
 
9.3%
45
 
9.1%
45
 
9.1%
15
 
3.0%
13
 
2.6%
8
 
1.6%
7
 
1.4%
6
 
1.2%
Other values (126) 218
44.0%
Latin
ValueCountFrequency (%)
S 3
12.0%
C 3
12.0%
O 3
12.0%
Y 2
8.0%
R 2
8.0%
D 2
8.0%
T 2
8.0%
V 2
8.0%
I 2
8.0%
K 1
 
4.0%
Other values (3) 3
12.0%
Common
ValueCountFrequency (%)
23
67.6%
2 4
 
11.8%
) 2
 
5.9%
. 2
 
5.9%
( 2
 
5.9%
3 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 495
89.4%
ASCII 59
 
10.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
46
 
9.3%
46
 
9.3%
46
 
9.3%
45
 
9.1%
45
 
9.1%
15
 
3.0%
13
 
2.6%
8
 
1.6%
7
 
1.4%
6
 
1.2%
Other values (126) 218
44.0%
ASCII
ValueCountFrequency (%)
23
39.0%
2 4
 
6.8%
S 3
 
5.1%
C 3
 
5.1%
O 3
 
5.1%
) 2
 
3.4%
. 2
 
3.4%
( 2
 
3.4%
Y 2
 
3.4%
R 2
 
3.4%
Other values (9) 13
22.0%

lnm_zip
Categorical

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
53 
600060
 
5
600046
 
5
600092
 
4
600805
 
4
Other values (17)
29 

Length

Max length6
Median length1
Mean length3.35
Min length1

Unique

Unique9 ?
Unique (%)9.0%

Sample

1st row-
2nd row600023
3rd row600046
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 53
53.0%
600060 5
 
5.0%
600046 5
 
5.0%
600092 4
 
4.0%
600805 4
 
4.0%
600807 4
 
4.0%
600814 3
 
3.0%
600045 3
 
3.0%
600025 2
 
2.0%
600044 2
 
2.0%
Other values (12) 15
 
15.0%

Length

2023-12-10T18:48:53.763481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
53
53.0%
600046 5
 
5.0%
600060 5
 
5.0%
600092 4
 
4.0%
600805 4
 
4.0%
600807 4
 
4.0%
600814 3
 
3.0%
600045 3
 
3.0%
600806 2
 
2.0%
600013 2
 
2.0%
Other values (12) 15
 
15.0%
Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:48:54.251100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length20.95
Min length18

Characters and Unicode

Total characters2095
Distinct characters48
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)86.0%

Sample

1st row강원도 강릉시 교동 1841-2번지
2nd row부산광역시 중구 동광동3가 21-1번지
3rd row부산광역시 중구 남포동6가 6번지
4th row부산광역시 중구 부평동2가 22-3번지
5th row부산광역시 중구 남포동2가 21-1번지
ValueCountFrequency (%)
부산광역시 99
24.3%
중구 98
24.1%
남포동5가 12
 
2.9%
남포동2가 11
 
2.7%
부평동1가 9
 
2.2%
남포동6가 9
 
2.2%
부평동2가 9
 
2.2%
영주동 7
 
1.7%
남포동3가 6
 
1.5%
대청동2가 5
 
1.2%
Other values (114) 142
34.9%
2023-12-10T18:48:55.038651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
307
 
14.7%
119
 
5.7%
106
 
5.1%
106
 
5.1%
105
 
5.0%
104
 
5.0%
100
 
4.8%
100
 
4.8%
100
 
4.8%
99
 
4.7%
Other values (38) 849
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1306
62.3%
Decimal Number 393
 
18.8%
Space Separator 307
 
14.7%
Dash Punctuation 89
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
119
9.1%
106
 
8.1%
106
 
8.1%
105
 
8.0%
104
 
8.0%
100
 
7.7%
100
 
7.7%
100
 
7.7%
99
 
7.6%
99
 
7.6%
Other values (26) 268
20.5%
Decimal Number
ValueCountFrequency (%)
2 97
24.7%
1 90
22.9%
3 54
13.7%
4 34
 
8.7%
5 33
 
8.4%
6 31
 
7.9%
7 18
 
4.6%
8 14
 
3.6%
0 11
 
2.8%
9 11
 
2.8%
Space Separator
ValueCountFrequency (%)
307
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1306
62.3%
Common 789
37.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
119
9.1%
106
 
8.1%
106
 
8.1%
105
 
8.0%
104
 
8.0%
100
 
7.7%
100
 
7.7%
100
 
7.7%
99
 
7.6%
99
 
7.6%
Other values (26) 268
20.5%
Common
ValueCountFrequency (%)
307
38.9%
2 97
 
12.3%
1 90
 
11.4%
- 89
 
11.3%
3 54
 
6.8%
4 34
 
4.3%
5 33
 
4.2%
6 31
 
3.9%
7 18
 
2.3%
8 14
 
1.8%
Other values (2) 22
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1306
62.3%
ASCII 789
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
307
38.9%
2 97
 
12.3%
1 90
 
11.4%
- 89
 
11.3%
3 54
 
6.8%
4 34
 
4.3%
5 33
 
4.2%
6 31
 
3.9%
7 18
 
2.3%
8 14
 
1.8%
Other values (2) 22
 
2.8%
Hangul
ValueCountFrequency (%)
119
9.1%
106
 
8.1%
106
 
8.1%
105
 
8.0%
104
 
8.0%
100
 
7.7%
100
 
7.7%
100
 
7.7%
99
 
7.6%
99
 
7.6%
Other values (26) 268
20.5%

rn_zip
Categorical

Distinct28
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
49 
48953
18 
48980
 
4
600045
 
2
48981
 
2
Other values (23)
25 

Length

Max length6
Median length5
Mean length3.17
Min length1

Unique

Unique21 ?
Unique (%)21.0%

Sample

1st row25511
2nd row-
3rd row-
4th row48977
5th row48953

Common Values

ValueCountFrequency (%)
- 49
49.0%
48953 18
 
18.0%
48980 4
 
4.0%
600045 2
 
2.0%
48981 2
 
2.0%
48956 2
 
2.0%
48983 2
 
2.0%
600042 1
 
1.0%
48954 1
 
1.0%
600031 1
 
1.0%
Other values (18) 18
 
18.0%

Length

2023-12-10T18:48:55.287140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
49
49.0%
48953 18
 
18.0%
48980 4
 
4.0%
600045 2
 
2.0%
48981 2
 
2.0%
48956 2
 
2.0%
48983 2
 
2.0%
600046 1
 
1.0%
600074 1
 
1.0%
48978 1
 
1.0%
Other values (18) 18
 
18.0%
Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:48:56.106833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length25.39
Min length1

Characters and Unicode

Total characters2539
Distinct characters72
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

Unique96 ?
Unique (%)96.0%

Sample

1st row강원도 강릉시 솔올로 51, 4층 (교동)
2nd row부산광역시 중구 백산길 18 (동광동3가)
3rd row-
4th row부산광역시 중구 중구로29번길 30-1 (부평동2가)
5th row부산광역시 중구 남포길 22-2 (남포동2가)
ValueCountFrequency (%)
중구 95
19.2%
부산광역시 95
19.2%
비프광장로 12
 
2.4%
남포동5가 12
 
2.4%
남포길 11
 
2.2%
남포동2가 10
 
2.0%
부평동2가 9
 
1.8%
부평동1가 9
 
1.8%
중구로 8
 
1.6%
영주동 7
 
1.4%
Other values (136) 228
46.0%
2023-12-10T18:48:56.984119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
441
 
17.4%
134
 
5.3%
126
 
5.0%
116
 
4.6%
116
 
4.6%
103
 
4.1%
) 96
 
3.8%
( 96
 
3.8%
96
 
3.8%
96
 
3.8%
Other values (62) 1119
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1476
58.1%
Space Separator 441
 
17.4%
Decimal Number 378
 
14.9%
Close Punctuation 96
 
3.8%
Open Punctuation 96
 
3.8%
Dash Punctuation 39
 
1.5%
Other Punctuation 12
 
0.5%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
134
 
9.1%
126
 
8.5%
116
 
7.9%
116
 
7.9%
103
 
7.0%
96
 
6.5%
96
 
6.5%
95
 
6.4%
88
 
6.0%
81
 
5.5%
Other values (46) 425
28.8%
Decimal Number
ValueCountFrequency (%)
1 84
22.2%
2 69
18.3%
3 57
15.1%
4 44
11.6%
5 36
9.5%
9 20
 
5.3%
6 19
 
5.0%
7 18
 
4.8%
8 16
 
4.2%
0 15
 
4.0%
Space Separator
ValueCountFrequency (%)
441
100.0%
Close Punctuation
ValueCountFrequency (%)
) 96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1476
58.1%
Common 1062
41.8%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
134
 
9.1%
126
 
8.5%
116
 
7.9%
116
 
7.9%
103
 
7.0%
96
 
6.5%
96
 
6.5%
95
 
6.4%
88
 
6.0%
81
 
5.5%
Other values (46) 425
28.8%
Common
ValueCountFrequency (%)
441
41.5%
) 96
 
9.0%
( 96
 
9.0%
1 84
 
7.9%
2 69
 
6.5%
3 57
 
5.4%
4 44
 
4.1%
- 39
 
3.7%
5 36
 
3.4%
9 20
 
1.9%
Other values (5) 80
 
7.5%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1476
58.1%
ASCII 1063
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
441
41.5%
) 96
 
9.0%
( 96
 
9.0%
1 84
 
7.9%
2 69
 
6.5%
3 57
 
5.4%
4 44
 
4.1%
- 39
 
3.7%
5 36
 
3.4%
9 20
 
1.9%
Other values (6) 81
 
7.6%
Hangul
ValueCountFrequency (%)
134
 
9.1%
126
 
8.5%
116
 
7.9%
116
 
7.9%
103
 
7.0%
96
 
6.5%
96
 
6.5%
95
 
6.4%
88
 
6.0%
81
 
5.5%
Other values (46) 425
28.8%

person_prmisn_de
Real number (ℝ)

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20028558
Minimum19920930
Maximum20190805
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:48:57.269073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19920930
5-th percentile19949723
Q120000628
median20020310
Q320030113
95-th percentile20160834
Maximum20190805
Range269875
Interquartile range (IQR)29485.25

Descriptive statistics

Standard deviation58895.02
Coefficient of variation (CV)0.0029405521
Kurtosis1.1875357
Mean20028558
Median Absolute Deviation (MAD)10648.5
Skewness1.1624651
Sum2.0028558 × 109
Variance3.4686234 × 109
MonotonicityNot monotonic
2023-12-10T18:48:57.552909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000628 2
 
2.0%
20000608 2
 
2.0%
20011203 2
 
2.0%
20001130 2
 
2.0%
20030327 1
 
1.0%
20020906 1
 
1.0%
20020201 1
 
1.0%
20020307 1
 
1.0%
20011222 1
 
1.0%
20010423 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
19920930 1
1.0%
19930310 1
1.0%
19930907 1
1.0%
19930916 1
1.0%
19931005 1
1.0%
19950708 1
1.0%
19951128 1
1.0%
19960424 1
1.0%
19960808 1
1.0%
19970312 1
1.0%
ValueCountFrequency (%)
20190805 1
1.0%
20170707 1
1.0%
20170324 1
1.0%
20161118 1
1.0%
20160922 1
1.0%
20160829 1
1.0%
20160627 1
1.0%
20160429 1
1.0%
20160129 1
1.0%
20151008 1
1.0%

clsbiz_de
Text

MISSING 

Distinct61
Distinct (%)88.4%
Missing31
Missing (%)31.0%
Memory size932.0 B
2023-12-10T18:48:57.997012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8985507
Min length1

Characters and Unicode

Total characters545
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)82.6%

Sample

1st row-
2nd row20040901
3rd row20050216
4th row20071116
5th row20070227
ValueCountFrequency (%)
20100219 5
 
7.2%
20090526 3
 
4.3%
20090507 2
 
2.9%
20120207 2
 
2.9%
20051223 1
 
1.4%
20080502 1
 
1.4%
20120918 1
 
1.4%
20020905 1
 
1.4%
20070515 1
 
1.4%
1
 
1.4%
Other values (51) 51
73.9%
2023-12-10T18:48:58.617384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 197
36.1%
2 126
23.1%
1 81
14.9%
9 27
 
5.0%
8 23
 
4.2%
5 22
 
4.0%
7 21
 
3.9%
6 20
 
3.7%
4 14
 
2.6%
3 13
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 544
99.8%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 197
36.2%
2 126
23.2%
1 81
14.9%
9 27
 
5.0%
8 23
 
4.2%
5 22
 
4.0%
7 21
 
3.9%
6 20
 
3.7%
4 14
 
2.6%
3 13
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 545
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 197
36.1%
2 126
23.1%
1 81
14.9%
9 27
 
5.0%
8 23
 
4.2%
5 22
 
4.0%
7 21
 
3.9%
6 20
 
3.7%
4 14
 
2.6%
3 13
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 545
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 197
36.1%
2 126
23.1%
1 81
14.9%
9 27
 
5.0%
8 23
 
4.2%
5 22
 
4.0%
7 21
 
3.9%
6 20
 
3.7%
4 14
 
2.6%
3 13
 
2.4%

engl_sttus
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
3
61 
13
29 
35
영업/정상
 
2
30
 
1

Length

Max length5
Median length1
Mean length1.45
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row영업/정상
2nd row3
3rd row3
4th row13
5th row13

Common Values

ValueCountFrequency (%)
3 61
61.0%
13 29
29.0%
35 7
 
7.0%
영업/정상 2
 
2.0%
30 1
 
1.0%

Length

2023-12-10T18:48:58.876435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:59.067267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 61
61.0%
13 29
29.0%
35 7
 
7.0%
영업/정상 2
 
2.0%
30 1
 
1.0%
Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
폐업
61 
영업중
31 
직권말소
허가취소
 
1

Length

Max length4
Median length2
Mean length2.47
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 61
61.0%
영업중 31
31.0%
직권말소 7
 
7.0%
허가취소 1
 
1.0%

Length

2023-12-10T18:48:59.281376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:59.488561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 61
61.0%
영업중 31
31.0%
직권말소 7
 
7.0%
허가취소 1
 
1.0%

xcnts
Real number (ℝ)

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean377205.91
Minimum1
Maximum385752.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:48:59.716346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile384523.25
Q1384842.75
median385060.23
Q3385231.56
95-th percentile385634.17
Maximum385752.13
Range385751.13
Interquartile range (IQR)388.80493

Descriptive statistics

Standard deviation54194.46
Coefficient of variation (CV)0.14367341
Kurtosis47.281596
Mean377205.91
Median Absolute Deviation (MAD)196.23015
Skewness-6.9478163
Sum37720591
Variance2.9370394 × 109
MonotonicityNot monotonic
2023-12-10T18:49:00.389492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
384974.6987 2
 
2.0%
1.0 2
 
2.0%
385201.5093 2
 
2.0%
385613.9251 2
 
2.0%
385182.1989 2
 
2.0%
384968.9732 2
 
2.0%
385006.6262 2
 
2.0%
365429.2312 1
 
1.0%
385150.1068 1
 
1.0%
384883.7358 1
 
1.0%
Other values (83) 83
83.0%
ValueCountFrequency (%)
1.0 2
2.0%
365429.2312 1
1.0%
384329.0808 1
1.0%
384496.8171 1
1.0%
384524.6421 1
1.0%
384692.5723 1
1.0%
384710.5133 1
1.0%
384725.4439 1
1.0%
384745.0845 1
1.0%
384752.3182 1
1.0%
ValueCountFrequency (%)
385752.1288 1
1.0%
385735.2699 1
1.0%
385711.431 1
1.0%
385705.258 1
1.0%
385687.9386 1
1.0%
385631.3425 1
1.0%
385613.9251 2
2.0%
385607.6126 1
1.0%
385604.6085 1
1.0%
385581.7788 1
1.0%

ydnts
Real number (ℝ)

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean179528.27
Minimum1
Maximum475456.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:49:00.777403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile179740.32
Q1179913.39
median179983.54
Q3180305.35
95-th percentile181319.39
Maximum475456.19
Range475455.19
Interquartile range (IQR)391.95867

Descriptive statistics

Standard deviation39195.558
Coefficient of variation (CV)0.21832527
Kurtosis41.226505
Mean179528.27
Median Absolute Deviation (MAD)153.4978
Skewness2.455116
Sum17952827
Variance1.5362918 × 109
MonotonicityNot monotonic
2023-12-10T18:49:01.101931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
179960.282 2
 
2.0%
1.0 2
 
2.0%
180344.6317 2
 
2.0%
181138.8437 2
 
2.0%
179955.9715 2
 
2.0%
179927.5014 2
 
2.0%
179877.8597 2
 
2.0%
475456.191 1
 
1.0%
179929.3322 1
 
1.0%
179976.4411 1
 
1.0%
Other values (83) 83
83.0%
ValueCountFrequency (%)
1.0 2
2.0%
179541.0559 1
1.0%
179663.5489 1
1.0%
179667.3795 1
1.0%
179744.1621 1
1.0%
179770.9899 1
1.0%
179787.8979 1
1.0%
179791.5818 1
1.0%
179816.0845 1
1.0%
179820.7719 1
1.0%
ValueCountFrequency (%)
475456.191 1
1.0%
181524.5461 1
1.0%
181456.6651 1
1.0%
181354.4362 1
1.0%
181328.3628 1
1.0%
181318.9137 1
1.0%
181283.1093 1
1.0%
181138.8437 2
2.0%
180988.9823 1
1.0%
180794.7413 1
1.0%

last_updt_de
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20200617
99 
-
 
1

Length

Max length8
Median length8
Mean length7.93
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row-
2nd row20200617
3rd row20200617
4th row20200617
5th row20200617

Common Values

ValueCountFrequency (%)
20200617 99
99.0%
- 1
 
1.0%

Length

2023-12-10T18:49:01.347011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:01.507853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200617 99
99.0%
1
 
1.0%

telno
Text

Distinct85
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:49:01.858865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length8
Mean length7.41
Min length1

Characters and Unicode

Total characters741
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)84.0%

Sample

1st row-
2nd row245-8214
3rd row242-8089
4th row253-6777
5th row-
ValueCountFrequency (%)
16
 
16.0%
246-6647 1
 
1.0%
241-3628 1
 
1.0%
243-8012 1
 
1.0%
246-9967 1
 
1.0%
245-9029 1
 
1.0%
242-5011 1
 
1.0%
245-4796 1
 
1.0%
241-2338 1
 
1.0%
248-3298 1
 
1.0%
Other values (75) 75
75.0%
2023-12-10T18:49:02.490717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 109
14.7%
- 107
14.4%
4 103
13.9%
6 75
10.1%
5 69
9.3%
3 54
7.3%
8 53
7.2%
0 48
6.5%
7 43
 
5.8%
1 42
 
5.7%
Other values (2) 38
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 629
84.9%
Dash Punctuation 107
 
14.4%
Other Punctuation 5
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 109
17.3%
4 103
16.4%
6 75
11.9%
5 69
11.0%
3 54
8.6%
8 53
8.4%
0 48
7.6%
7 43
 
6.8%
1 42
 
6.7%
9 33
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 107
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 741
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 109
14.7%
- 107
14.4%
4 103
13.9%
6 75
10.1%
5 69
9.3%
3 54
7.3%
8 53
7.2%
0 48
6.5%
7 43
 
5.8%
1 42
 
5.7%
Other values (2) 38
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 741
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 109
14.7%
- 107
14.4%
4 103
13.9%
6 75
10.1%
5 69
9.3%
3 54
7.3%
8 53
7.2%
0 48
6.5%
7 43
 
5.8%
1 42
 
5.7%
Other values (2) 38
 
5.1%

buld_prpos_nm
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
근린생활시설
68 
-
32 

Length

Max length6
Median length6
Mean length4.4
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd row근린생활시설
3rd row근린생활시설
4th row근린생활시설
5th row근린생활시설

Common Values

ValueCountFrequency (%)
근린생활시설 68
68.0%
- 32
32.0%

Length

2023-12-10T18:49:02.739314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:02.893216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
근린생활시설 68
68.0%
32
32.0%

sngrum_sil_co
Categorical

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
5
17 
6
10
4
7
Other values (17)
49 

Length

Max length2
Median length1
Mean length1.39
Min length1

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row28
2nd row3
3rd row5
4th row5
5th row9

Common Values

ValueCountFrequency (%)
5 17
17.0%
6 9
 
9.0%
10 9
 
9.0%
4 8
 
8.0%
7 8
 
8.0%
8 8
 
8.0%
9 6
 
6.0%
11 6
 
6.0%
12 3
 
3.0%
- 3
 
3.0%
Other values (12) 23
23.0%

Length

2023-12-10T18:49:03.080617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5 17
17.0%
10 9
 
9.0%
6 9
 
9.0%
4 8
 
8.0%
7 8
 
8.0%
8 8
 
8.0%
9 6
 
6.0%
11 6
 
6.0%
19 3
 
3.0%
28 3
 
3.0%
Other values (12) 23
23.0%

cltur_bsnm_se_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
유통관련업
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통관련업 100
100.0%

Length

2023-12-10T18:49:03.277511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:03.422206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통관련업 100
100.0%

cltur_phstrn_induty_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
노래연습장업
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노래연습장업 100
100.0%

Length

2023-12-10T18:49:03.615916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:03.761593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노래연습장업 100
100.0%

sdfcl_at
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
N
67 
Y
30 
-
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd rowY
3rd rowN
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
N 67
67.0%
Y 30
30.0%
- 3
 
3.0%

Length

2023-12-10T18:49:03.935386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:04.091536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 67
67.0%
y 30
30.0%
3
 
3.0%

emgnc_stairs_at
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
N
68 
Y
29 
-
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd rowN
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
N 68
68.0%
Y 29
29.0%
- 3
 
3.0%

Length

2023-12-10T18:49:04.277537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:04.442709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 68
68.0%
y 29
29.0%
3
 
3.0%

ency_at
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
N
66 
Y
32 
-
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd rowY
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
N 66
66.0%
Y 32
32.0%
- 2
 
2.0%

Length

2023-12-10T18:49:04.620941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:04.799606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 66
66.0%
y 32
32.0%
2
 
2.0%
Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:49:05.265097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.2
Min length1

Characters and Unicode

Total characters520
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)96.0%

Sample

1st row225.59
2nd row114.05
3rd row121.68
4th row130.81
5th row159.77
ValueCountFrequency (%)
210.54 2
 
2.0%
319.37 2
 
2.0%
57.8 1
 
1.0%
139.95 1
 
1.0%
88.46 1
 
1.0%
115.7 1
 
1.0%
320.8 1
 
1.0%
283.02 1
 
1.0%
171.57 1
 
1.0%
103.58 1
 
1.0%
Other values (88) 88
88.0%
2023-12-10T18:49:06.325723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 95
18.3%
. 95
18.3%
3 50
9.6%
2 47
9.0%
5 45
8.7%
7 41
7.9%
8 36
 
6.9%
4 32
 
6.2%
6 30
 
5.8%
9 27
 
5.2%
Other values (2) 22
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 424
81.5%
Other Punctuation 95
 
18.3%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 95
22.4%
3 50
11.8%
2 47
11.1%
5 45
10.6%
7 41
9.7%
8 36
 
8.5%
4 32
 
7.5%
6 30
 
7.1%
9 27
 
6.4%
0 21
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 95
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 520
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 95
18.3%
. 95
18.3%
3 50
9.6%
2 47
9.0%
5 45
8.7%
7 41
7.9%
8 36
 
6.9%
4 32
 
6.2%
6 30
 
5.8%
9 27
 
5.2%
Other values (2) 22
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 520
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 95
18.3%
. 95
18.3%
3 50
9.6%
2 47
9.0%
5 45
8.7%
7 41
7.9%
8 36
 
6.9%
4 32
 
6.2%
6 30
 
5.8%
9 27
 
5.2%
Other values (2) 22
 
4.2%

atmc_ventl_at
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
N
67 
Y
23 
-
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd rowY
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
N 67
67.0%
Y 23
 
23.0%
- 10
 
10.0%

Length

2023-12-10T18:49:06.759217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:06.946393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 67
67.0%
y 23
 
23.0%
10
 
10.0%

lght_fclty_dgree
Categorical

Distinct28
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
65 
42
 
5
48
 
2
44
 
2
41
 
2
Other values (23)
24 

Length

Max length5
Median length1
Mean length1.59
Min length1

Unique

Unique22 ?
Unique (%)22.0%

Sample

1st row-
2nd row40
3rd row44
4th row38
5th row80

Common Values

ValueCountFrequency (%)
- 65
65.0%
42 5
 
5.0%
48 2
 
2.0%
44 2
 
2.0%
41 2
 
2.0%
43 2
 
2.0%
40 1
 
1.0%
38 1
 
1.0%
80 1
 
1.0%
45 1
 
1.0%
Other values (18) 18
 
18.0%

Length

2023-12-10T18:49:07.185373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
65
65.0%
42 5
 
5.0%
48 2
 
2.0%
44 2
 
2.0%
41 2
 
2.0%
43 2
 
2.0%
178.5 1
 
1.0%
54.2 1
 
1.0%
37.5 1
 
1.0%
64 1
 
1.0%
Other values (18) 18
 
18.0%

cfr_envrn_nm
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
93 
유흥업소밀집지역
 
3
기타
 
2
학교정화(상대)
 
2

Length

Max length8
Median length1
Mean length1.37
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd row기타
3rd row-
4th row-
5th row유흥업소밀집지역

Common Values

ValueCountFrequency (%)
- 93
93.0%
유흥업소밀집지역 3
 
3.0%
기타 2
 
2.0%
학교정화(상대) 2
 
2.0%

Length

2023-12-10T18:49:07.440579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:07.634074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
93
93.0%
유흥업소밀집지역 3
 
3.0%
기타 2
 
2.0%
학교정화(상대 2
 
2.0%

ground_floor_co
Categorical

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
41 
2
21 
3
19 
4
5
Other values (4)

Length

Max length2
Median length1
Mean length1.01
Min length1

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row-
2nd row1
3rd row-
4th row2
5th row-

Common Values

ValueCountFrequency (%)
- 41
41.0%
2 21
21.0%
3 19
19.0%
4 7
 
7.0%
5 6
 
6.0%
1 3
 
3.0%
15 1
 
1.0%
7 1
 
1.0%
6 1
 
1.0%

Length

2023-12-10T18:49:07.871129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:08.122230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41
41.0%
2 21
21.0%
3 19
19.0%
4 7
 
7.0%
5 6
 
6.0%
1 3
 
3.0%
15 1
 
1.0%
7 1
 
1.0%
6 1
 
1.0%

area_se_nm
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
87 
일반상업지역
 
7
상업지역
 
4
일반주거지역
 
1
근린상업지역
 
1

Length

Max length6
Median length1
Mean length1.57
Min length1

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row-
2nd row일반상업지역
3rd row-
4th row-
5th row상업지역

Common Values

ValueCountFrequency (%)
- 87
87.0%
일반상업지역 7
 
7.0%
상업지역 4
 
4.0%
일반주거지역 1
 
1.0%
근린상업지역 1
 
1.0%

Length

2023-12-10T18:49:08.363734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:08.571905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
87
87.0%
일반상업지역 7
 
7.0%
상업지역 4
 
4.0%
일반주거지역 1
 
1.0%
근린상업지역 1
 
1.0%

undgrnd_floor_co
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
71 
1
29 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd row-
3rd row1
4th row-
5th row1

Common Values

ValueCountFrequency (%)
- 71
71.0%
1 29
29.0%

Length

2023-12-10T18:49:08.781967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:08.986924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
71
71.0%
1 29
29.0%

yngbgs_sil_co
Categorical

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
43 
1
3
2
7
Other values (18)
33 

Length

Max length2
Median length1
Mean length1.18
Min length1

Unique

Unique9 ?
Unique (%)9.0%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row7

Common Values

ValueCountFrequency (%)
- 43
43.0%
1 9
 
9.0%
3 5
 
5.0%
2 5
 
5.0%
7 5
 
5.0%
4 4
 
4.0%
6 3
 
3.0%
9 3
 
3.0%
8 3
 
3.0%
12 3
 
3.0%
Other values (13) 17
 
17.0%

Length

2023-12-10T18:49:09.185565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
43
43.0%
1 9
 
9.0%
3 5
 
5.0%
2 5
 
5.0%
7 5
 
5.0%
4 4
 
4.0%
6 3
 
3.0%
9 3
 
3.0%
8 3
 
3.0%
12 3
 
3.0%
Other values (13) 17
 
17.0%

yngbgs_sil_at
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Y
54 
N
26 
-
20 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowN
3rd rowN
4th row-
5th rowY

Common Values

ValueCountFrequency (%)
Y 54
54.0%
N 26
26.0%
- 20
 
20.0%

Length

2023-12-10T18:49:09.382004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:09.555128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 54
54.0%
n 26
26.0%
20
 
20.0%

tot_floor_co
Categorical

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
43 
5
18 
6
12 
4
10 
3
Other values (6)

Length

Max length2
Median length1
Mean length1.02
Min length1

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row-
2nd row3
3rd row6
4th row5
5th row4

Common Values

ValueCountFrequency (%)
- 43
43.0%
5 18
18.0%
6 12
 
12.0%
4 10
 
10.0%
3 8
 
8.0%
2 2
 
2.0%
7 2
 
2.0%
8 2
 
2.0%
10 1
 
1.0%
11 1
 
1.0%

Length

2023-12-10T18:49:09.763303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
43
43.0%
5 18
18.0%
6 12
 
12.0%
4 10
 
10.0%
3 8
 
8.0%
2 2
 
2.0%
7 2
 
2.0%
8 2
 
2.0%
10 1
 
1.0%
11 1
 
1.0%

passway_bt
Categorical

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
-
63 
1.3
1.2
 
5
1.5
 
4
1.4
 
3
Other values (12)
16 

Length

Max length4
Median length1
Mean length1.72
Min length1

Unique

Unique8 ?
Unique (%)8.0%

Sample

1st row-
2nd row1.3
3rd row1.2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
- 63
63.0%
1.3 9
 
9.0%
1.2 5
 
5.0%
1.5 4
 
4.0%
1.4 3
 
3.0%
1.1 2
 
2.0%
1.6 2
 
2.0%
1 2
 
2.0%
1.25 2
 
2.0%
1.28 1
 
1.0%
Other values (7) 7
 
7.0%

Length

2023-12-10T18:49:10.082173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
63
63.0%
1.3 9
 
9.0%
1.2 5
 
5.0%
1.5 4
 
4.0%
1.4 3
 
3.0%
1 2
 
2.0%
1.25 2
 
2.0%
1.6 2
 
2.0%
1.1 2
 
2.0%
1.28 1
 
1.0%
Other values (7) 7
 
7.0%

spcl_lght_at
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
N
55 
Y
30 
-
15 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd rowY
3rd rowY
4th rowY
5th rowY

Common Values

ValueCountFrequency (%)
N 55
55.0%
Y 30
30.0%
- 15
 
15.0%

Length

2023-12-10T18:49:10.320553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:49:10.642428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 55
55.0%
y 30
30.0%
15
 
15.0%

Sample

skeysfrnd_codesfrnd_code_nmperson_prmisn_nosvc_iddata_updt_sedata_updt_desvc_id_nmbplc_nmlnm_ziplnm_adresrn_ziprdnmadrperson_prmisn_declsbiz_deengl_sttusdetail_engl_sttusxcntsydntslast_updt_detelnobuld_prpos_nmsngrum_sil_cocltur_bsnm_se_nmcltur_phstrn_induty_nmsdfcl_atemgnc_stairs_atency_atfclty_aratmc_ventl_atlght_fclty_dgreecfr_envrn_nmground_floor_coarea_se_nmundgrnd_floor_coyngbgs_sil_coyngbgs_sil_attot_floor_copassway_btspcl_lght_at
014200000강원 강릉시CDFF324205201900000203_09_01_PU2019-11-12 AM 12:59:59노래연습장업인싸코인노래연습장-강원도 강릉시 교동 1841-2번지25511강원도 강릉시 솔올로 51, 4층 (교동)20190805-영업/정상영업중365429.2312475456.191---28유통관련업노래연습장업---225.59-------Y---
123250000부산 중구CDFF324205200300000603_09_01_PI2019-11-12 AM 12:59:59-호심600023부산광역시 중구 동광동3가 21-1번지-부산광역시 중구 백산길 18 (동광동3가)20030417200409013폐업385501.4819180233.23320200617245-8214근린생활시설3유통관련업노래연습장업YNY114.05Y40기타1일반상업지역--N31.3Y
233250000부산 중구CDFF324205200300000703_09_01_PI2019-11-12 AM 12:59:59-진양600046부산광역시 중구 남포동6가 6번지--20030702200502163폐업1.01.020200617242-8089근린생활시설5유통관련업노래연습장업NYY121.68Y44---1-N61.2Y
343250000부산 중구CDFF324205200300000803_09_01_PI2019-11-12 AM 12:59:59-도깨비노래연습장-부산광역시 중구 부평동2가 22-3번지48977부산광역시 중구 중구로29번길 30-1 (부평동2가)20031215<NA>13영업중384754.7092180131.918720200617253-6777근린생활시설5유통관련업노래연습장업YYY130.81Y38-2----51Y
453250000부산 중구CDFF324205200400000103_09_01_PI2019-11-12 AM 12:59:59-남포노래연습장-부산광역시 중구 남포동2가 21-1번지48953부산광역시 중구 남포길 22-2 (남포동2가)20040527<NA>13영업중385220.7239179923.532420200617-근린생활시설9유통관련업노래연습장업YYY159.77Y80유흥업소밀집지역-상업지역17Y41Y
563250000부산 중구CDFF324205200500000103_09_01_PI2019-11-12 AM 12:59:59-열창노래연습장600045부산광역시 중구 남포동5가 90번지-부산광역시 중구 자갈치로37번길 4-1 (남포동5가)20050223<NA>30허가취소384971.191179770.989920200617254-6210근린생활시설-유통관련업노래연습장업NNN138.28N--4-1-N5-N
673250000부산 중구CDFF324205200600000103_09_01_PI2019-11-12 AM 12:59:59-GIV 노래연습장600092부산광역시 중구 대청동2가 34-1번지-부산광역시 중구 광복중앙로 28-1 (대청동2가)20060405200711163폐업385198.6002180287.488420200617256-3535근린생활시설-유통관련업노래연습장업NNN206.85N-학교정화(상대)5상업지역1-N6-N
783250000부산 중구CDFF324205200200000903_09_01_PI2019-11-12 AM 12:59:59-600060부산광역시 중구 신창동1가 36-6번지-부산광역시 중구 광복중앙로33번길 7-2 (신창동1가)20020802200702273폐업385094.0738180302.163620200617247-4896-4유통관련업노래연습장업NNN41.5N--1---N2-N
893250000부산 중구CDFF324205200200001003_09_01_PI2019-11-12 AM 12:59:59-금호노래연습장-부산광역시 중구 영주동 161번지48917부산광역시 중구 영주로 51-1 (영주동)20020131<NA>13영업중385130.5655181318.913720200617442-6622근린생활시설14유통관련업노래연습장업NNN258.7N---일반주거지역1--3-N
9103250000부산 중구CDFF324205200200001103_09_01_PI2011-11-12 AM 12:59:59-라이브-부산광역시 중구 창선동1가 6-1번지600051부산광역시 중구 광복로55번길 8 (창선동1가)200206042012020735직권말소385175.3352180057.558820200617242-8896근린생활시설14유통관련업노래연습장업NNN177.7N--4--14Y5-N
skeysfrnd_codesfrnd_code_nmperson_prmisn_nosvc_iddata_updt_sedata_updt_desvc_id_nmbplc_nmlnm_ziplnm_adresrn_ziprdnmadrperson_prmisn_declsbiz_deengl_sttusdetail_engl_sttusxcntsydntslast_updt_detelnobuld_prpos_nmsngrum_sil_cocltur_bsnm_se_nmcltur_phstrn_induty_nmsdfcl_atemgnc_stairs_atency_atfclty_aratmc_ventl_atlght_fclty_dgreecfr_envrn_nmground_floor_coarea_se_nmundgrnd_floor_coyngbgs_sil_coyngbgs_sil_attot_floor_copassway_btspcl_lght_at
90913250000부산 중구CDFF324205199200000103_09_01_PI2019-11-12 AM 12:59:59-남포노래연습장-부산광역시 중구 남포동5가 50-2번지 2층48983부산광역시 중구 자갈치로47번길 5 (남포동5가)19920930<NA>13영업중385035.6443179816.084520200617254-3485근린생활시설11유통관련업노래연습장업NNN136.9N--2------N
91923250000부산 중구CDFF324205199300000103_09_01_PI2019-11-12 AM 12:59:59-일신600100부산광역시 중구 대창동2가 14-4번지-부산광역시 중구 중앙대로 147 (대창동2가)19930916200411053폐업385752.1288181283.109320200617463-1094-8유통관련업노래연습장업NNN76.4N------N--N
92933250000부산 중구CDFF324205199300000203_09_01_PI2019-11-12 AM 12:59:59-상록-부산광역시 중구 보수동3가 5-21번지 지하1층600083부산광역시 중구 보수대로106번길 5 (보수동3가)199303102010021935직권말소384329.0808180631.273720200617253-2853-9유통관련업노래연습장업NNN143.5N----1----N
93943250000부산 중구CDFF324205199300000303_09_01_PI2019-11-12 AM 12:59:59-재미나-부산광역시 중구 영주동 743-24번지-부산광역시 중구 중구로 162 (영주동)19930907200206173폐업385613.9251181138.843720200617469-8222-6유통관련업노래연습장업NNN87N---------N
94953250000부산 중구CDFF324205199500000103_09_01_PI2019-11-12 AM 12:59:59-다영600023부산광역시 중구 동광동3가 17-2번지-부산광역시 중구 중앙대로41번길 14-1 (동광동3가)19950708200312013폐업385534.5158180211.580720200617245-9399-5유통관련업노래연습장업NNN106.7N------N--N
95963250000부산 중구CDFF324205199500000203_09_01_PI2019-11-12 AM 12:59:59-이스트600022부산광역시 중구 동광동2가 11-67번지-부산광역시 중구 광복로85번길 11 (동광동2가)19951128200209173폐업385508.0835180032.175320200617245-5400-5유통관련업노래연습장업NNN191.4N------N--N
96973250000부산 중구CDFF324205199600000103_09_01_PI2019-11-12 AM 12:59:59-도레미600013부산광역시 중구 중앙동3가 10-6번지-부산광역시 중구 대청로141번길 6 (중앙동3가)19960808200703143폐업385581.7788180461.600620200617469-0349근린생활시설5유통관련업노래연습장업NNN87.3N--2---N4-N
97983250000부산 중구CDFF324205199600000203_09_01_PI2019-11-12 AM 12:59:59-신천지600046부산광역시 중구 남포동6가 3번지-부산광역시 중구 자갈치로 33 (남포동6가)19960424200905263폐업384912.1479179744.162120200617245-8860-5유통관련업노래연습장업NNN56.2N------N--N
98993250000부산 중구CDFF324205199700000103_09_01_PI2019-11-12 AM 12:59:59-앵콜노래연습장-부산광역시 중구 영주동 14-2번지 지하1층48911부산광역시 중구 초량중로 7-1 (영주동)19970312<NA>13영업중385631.3425181524.546120200617463-5776-7유통관련업노래연습장업NNN78.6N----1----N
991003250000부산 중구CDFF324205200200000403_09_01_PI2019-11-12 AM 12:59:59-송송600807부산광역시 중구 부평동2가 47번지-부산광역시 중구 보수대로24번길 4-2 (부평동2가)20020603200412303폐업384692.5723179942.831620200617257-0370-15유통관련업노래연습장업NNN115.2N--1---N--N