Overview

Dataset statistics

Number of variables34
Number of observations100
Missing cells325
Missing cells (%)9.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.4 KiB
Average record size in memory291.3 B

Variable types

Numeric10
Categorical15
Text4
DateTime1
Unsupported2
Boolean2

Alerts

svc_id has constant value ""Constant
svc_id_nm has constant value ""Constant
bizcnd_se_nm has constant value ""Constant
male_enfsn_co has constant value ""Constant
multi_use_bssh_at has constant value ""Constant
pyrxia_room_at has constant value ""Constant
female_enfsn_co has constant value ""Constant
snitat_biznd_nm has constant value ""Constant
sfrnd_code is highly imbalanced (80.6%)Imbalance
sfrnd_code_nm is highly imbalanced (80.6%)Imbalance
data_updt_se is highly imbalanced (67.3%)Imbalance
rdnmadr has 38 (38.0%) missing valuesMissing
person_prmisn_de has 100 (100.0%) missing valuesMissing
clsbiz_de has 100 (100.0%) missing valuesMissing
xcnts has 6 (6.0%) missing valuesMissing
ydnts has 6 (6.0%) missing valuesMissing
telno has 20 (20.0%) missing valuesMissing
buld_ground_floor_co has 7 (7.0%) missing valuesMissing
pyrxia_room_at has 4 (4.0%) missing valuesMissing
use_end_ground_floor has 20 (20.0%) missing valuesMissing
use_begin_ground_floor has 17 (17.0%) missing valuesMissing
chair_co has 7 (7.0%) missing valuesMissing
skey has unique valuesUnique
person_prmisn_no has unique valuesUnique
person_prmisn_de is an unsupported type, check if it needs cleaning or further analysisUnsupported
clsbiz_de is an unsupported type, check if it needs cleaning or further analysisUnsupported
buld_ground_floor_co has 5 (5.0%) zerosZeros
use_end_ground_floor has 19 (19.0%) zerosZeros
use_begin_ground_floor has 20 (20.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:13:04.086956
Analysis finished2023-12-10 10:13:04.926977
Duration0.84 seconds
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%
Mean195.97
Minimum1
Maximum4864
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:05.073044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.95
Q127.75
median53.5
Q378.25
95-th percentile98.05
Maximum4864
Range4863
Interquartile range (IQR)50.5

Descriptive statistics

Standard deviation825.37499
Coefficient of variation (CV)4.2117415
Kurtosis29.82106
Mean195.97
Median Absolute Deviation (MAD)25.5
Skewness5.5842339
Sum19597
Variance681243.87
MonotonicityNot monotonic
2023-12-10T19:13:05.310483image/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%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
9 1
1.0%
10 1
1.0%
11 1
1.0%
12 1
1.0%
ValueCountFrequency (%)
4864 1
1.0%
4863 1
1.0%
4862 1
1.0%
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%

sfrnd_code
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
3250000
97 
3400000
 
3

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3250000
2nd row3400000
3rd row3250000
4th row3250000
5th row3250000

Common Values

ValueCountFrequency (%)
3250000 97
97.0%
3400000 3
 
3.0%

Length

2023-12-10T19:13:05.531123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:05.692085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3250000 97
97.0%
3400000 3
 
3.0%

sfrnd_code_nm
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
부산광역시 중구
97 
부산광역시 기장군
 
3

Length

Max length9
Median length8
Mean length8.03
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 중구
2nd row부산광역시 기장군
3rd row부산광역시 중구
4th row부산광역시 중구
5th row부산광역시 중구

Common Values

ValueCountFrequency (%)
부산광역시 중구 97
97.0%
부산광역시 기장군 3
 
3.0%

Length

2023-12-10T19:13:05.875171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:06.058734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 100
50.0%
중구 97
48.5%
기장군 3
 
1.5%

person_prmisn_no
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:13:06.353134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2200
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

Unique100 ?
Unique (%)100.0%

Sample

1st row3250000-203-2003-00003
2nd row3400000-203-1990-00288
3rd row3250000-203-1969-00485
4th row3250000-203-1974-00486
5th row3250000-203-2008-00007
ValueCountFrequency (%)
3250000-203-2003-00003 1
 
1.0%
3250000-203-1985-00494 1
 
1.0%
3250000-203-1985-00496 1
 
1.0%
3250000-203-2006-00005 1
 
1.0%
3250000-203-1995-00552 1
 
1.0%
3250000-203-2006-00001 1
 
1.0%
3250000-203-2006-00008 1
 
1.0%
3250000-203-1976-00502 1
 
1.0%
3250000-203-1983-00476 1
 
1.0%
3250000-203-1976-00450 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:13:06.940145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 883
40.1%
- 300
 
13.6%
2 270
 
12.3%
3 225
 
10.2%
5 156
 
7.1%
9 100
 
4.5%
1 95
 
4.3%
4 59
 
2.7%
8 46
 
2.1%
7 34
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1900
86.4%
Dash Punctuation 300
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 883
46.5%
2 270
 
14.2%
3 225
 
11.8%
5 156
 
8.2%
9 100
 
5.3%
1 95
 
5.0%
4 59
 
3.1%
8 46
 
2.4%
7 34
 
1.8%
6 32
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 300
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2200
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 883
40.1%
- 300
 
13.6%
2 270
 
12.3%
3 225
 
10.2%
5 156
 
7.1%
9 100
 
4.5%
1 95
 
4.3%
4 59
 
2.7%
8 46
 
2.1%
7 34
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 883
40.1%
- 300
 
13.6%
2 270
 
12.3%
3 225
 
10.2%
5 156
 
7.1%
9 100
 
4.5%
1 95
 
4.3%
4 59
 
2.7%
8 46
 
2.1%
7 34
 
1.5%

svc_id
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
05_19_01_P
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05_19_01_P
2nd row05_19_01_P
3rd row05_19_01_P
4th row05_19_01_P
5th row05_19_01_P

Common Values

ValueCountFrequency (%)
05_19_01_P 100
100.0%

Length

2023-12-10T19:13:07.210807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:07.387573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 100
100.0%

data_updt_se
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
I
94 
U
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 94
94.0%
U 6
 
6.0%

Length

2023-12-10T19:13:07.619859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:07.837976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 94
94.0%
u 6
 
6.0%

data_updt_de
Date

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2018-08-31 11:59:59
Maximum2020-08-28 02:40:00
2023-12-10T19:13:07.984737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:13:08.185600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

svc_id_nm
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이용업 100
100.0%

Length

2023-12-10T19:13:08.437236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:08.626348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용업 100
100.0%

bplc_nm
Text

Distinct94
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:13:09.058759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.78
Min length1

Characters and Unicode

Total characters478
Distinct characters110
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)88.0%

Sample

1st row종 이용원
2nd row대우이용원
3rd row아파트
4th row미진
5th row양신탕구내이용원
ValueCountFrequency (%)
이용원 9
 
8.0%
용두산 3
 
2.7%
천목사우나이용원 2
 
1.8%
대림이용원 2
 
1.8%
두원 2
 
1.8%
양신탕구내이용원 2
 
1.8%
유정탕구내 2
 
1.8%
부천탕구내이용원 2
 
1.8%
복 1
 
0.9%
창성 1
 
0.9%
Other values (87) 87
77.0%
2023-12-10T19:13:09.933054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 45
 
9.4%
용 45
 
9.4%
이 42
 
8.8%
내 24
 
5.0%
구 23
 
4.8%
탕 23
 
4.8%
13
 
2.7%
성 12
 
2.5%
수 9
 
1.9%
양 8
 
1.7%
Other values (100) 234
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 462
96.7%
Space Separator 13
 
2.7%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 45
 
9.7%
용 45
 
9.7%
이 42
 
9.1%
내 24
 
5.2%
구 23
 
5.0%
탕 23
 
5.0%
성 12
 
2.6%
수 9
 
1.9%
양 8
 
1.7%
대 8
 
1.7%
Other values (96) 223
48.3%
Space Separator
ValueCountFrequency (%)
13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
H 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 462
96.7%
Common 15
 
3.1%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 45
 
9.7%
용 45
 
9.7%
이 42
 
9.1%
내 24
 
5.2%
구 23
 
5.0%
탕 23
 
5.0%
성 12
 
2.6%
수 9
 
1.9%
양 8
 
1.7%
대 8
 
1.7%
Other values (96) 223
48.3%
Common
ValueCountFrequency (%)
13
86.7%
( 1
 
6.7%
) 1
 
6.7%
Latin
ValueCountFrequency (%)
H 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 462
96.7%
ASCII 16
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 45
 
9.7%
용 45
 
9.7%
이 42
 
9.1%
내 24
 
5.2%
구 23
 
5.0%
탕 23
 
5.0%
성 12
 
2.6%
수 9
 
1.9%
양 8
 
1.7%
대 8
 
1.7%
Other values (96) 223
48.3%
ASCII
ValueCountFrequency (%)
13
81.2%
( 1
 
6.2%
) 1
 
6.2%
H 1
 
6.2%

lnm_zip
Real number (ℝ)

Distinct37
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean600943.99
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:10.272382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile600012
Q1600045
median600096.5
Q3600807
95-th percentile600817.1
Maximum619953
Range19942
Interquartile range (IQR)762

Descriptive statistics

Standard deviation3372.3488
Coefficient of variation (CV)0.0056117522
Kurtosis29.122264
Mean600943.99
Median Absolute Deviation (MAD)79
Skewness5.489629
Sum60094399
Variance11372736
MonotonicityNot monotonic
2023-12-10T19:13:10.575816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
600811 7
 
7.0%
600110 7
 
7.0%
600046 5
 
5.0%
600012 5
 
5.0%
600045 5
 
5.0%
600807 5
 
5.0%
600804 5
 
5.0%
600074 4
 
4.0%
600817 4
 
4.0%
600042 4
 
4.0%
Other values (27) 49
49.0%
ValueCountFrequency (%)
600011 2
 
2.0%
600012 5
5.0%
600014 1
 
1.0%
600021 3
3.0%
600022 2
 
2.0%
600023 1
 
1.0%
600024 1
 
1.0%
600025 3
3.0%
600041 1
 
1.0%
600042 4
4.0%
ValueCountFrequency (%)
619953 1
 
1.0%
619905 1
 
1.0%
619873 1
 
1.0%
600819 2
 
2.0%
600817 4
4.0%
600816 3
3.0%
600815 2
 
2.0%
600811 7
7.0%
600808 2
 
2.0%
600807 5
5.0%

lnm_adres
Text

Distinct94
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:13:11.200858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length33
Mean length25.3
Min length19

Characters and Unicode

Total characters2530
Distinct characters71
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

Unique89 ?
Unique (%)89.0%

Sample

1st row부산광역시 중구 중앙동1가 22-23번지
2nd row부산광역시 기장군 장안읍 좌천리 203-3번지 T통B반
3rd row부산광역시 중구 영주동 151-7번지 (1층)
4th row부산광역시 중구 영주동 278-18번지 (1층)
5th row부산광역시 중구 부평동1가 27-1번지
ValueCountFrequency (%)
부산광역시 100
20.5%
중구 97
19.9%
영주동 14
 
2.9%
2층 13
 
2.7%
지하1층 12
 
2.5%
1층 10
 
2.1%
중앙동4가 10
 
2.1%
부평동2가 7
 
1.4%
보수동1가 7
 
1.4%
외 6
 
1.2%
Other values (142) 211
43.3%
2023-12-10T19:13:12.008815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
387
 
15.3%
1 132
 
5.2%
부 120
 
4.7%
지 119
 
4.7%
중 114
 
4.5%
광 113
 
4.5%
동 112
 
4.4%
2 110
 
4.3%
시 100
 
4.0%
역 100
 
4.0%
Other values (61) 1123
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1415
55.9%
Decimal Number 521
 
20.6%
Space Separator 387
 
15.3%
Dash Punctuation 92
 
3.6%
Close Punctuation 43
 
1.7%
Open Punctuation 43
 
1.7%
Other Punctuation 24
 
0.9%
Uppercase Letter 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 120
 
8.5%
지 119
 
8.4%
중 114
 
8.1%
광 113
 
8.0%
동 112
 
7.9%
시 100
 
7.1%
역 100
 
7.1%
산 100
 
7.1%
번 98
 
6.9%
구 97
 
6.9%
Other values (44) 342
24.2%
Decimal Number
ValueCountFrequency (%)
1 132
25.3%
2 110
21.1%
3 63
12.1%
4 47
 
9.0%
5 45
 
8.6%
6 33
 
6.3%
7 26
 
5.0%
9 23
 
4.4%
8 21
 
4.0%
0 21
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
60.0%
T 2
40.0%
Space Separator
ValueCountFrequency (%)
387
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1415
55.9%
Common 1110
43.9%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 120
 
8.5%
지 119
 
8.4%
중 114
 
8.1%
광 113
 
8.0%
동 112
 
7.9%
시 100
 
7.1%
역 100
 
7.1%
산 100
 
7.1%
번 98
 
6.9%
구 97
 
6.9%
Other values (44) 342
24.2%
Common
ValueCountFrequency (%)
387
34.9%
1 132
 
11.9%
2 110
 
9.9%
- 92
 
8.3%
3 63
 
5.7%
4 47
 
4.2%
5 45
 
4.1%
) 43
 
3.9%
( 43
 
3.9%
6 33
 
3.0%
Other values (5) 115
 
10.4%
Latin
ValueCountFrequency (%)
B 3
60.0%
T 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1415
55.9%
ASCII 1115
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
387
34.7%
1 132
 
11.8%
2 110
 
9.9%
- 92
 
8.3%
3 63
 
5.7%
4 47
 
4.2%
5 45
 
4.0%
) 43
 
3.9%
( 43
 
3.9%
6 33
 
3.0%
Other values (7) 120
 
10.8%
Hangul
ValueCountFrequency (%)
부 120
 
8.5%
지 119
 
8.4%
중 114
 
8.1%
광 113
 
8.0%
동 112
 
7.9%
시 100
 
7.1%
역 100
 
7.1%
산 100
 
7.1%
번 98
 
6.9%
구 97
 
6.9%
Other values (44) 342
24.2%

rdnmadr
Text

MISSING 

Distinct61
Distinct (%)98.4%
Missing38
Missing (%)38.0%
Memory size932.0 B
2023-12-10T19:13:12.644598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length30
Min length21

Characters and Unicode

Total characters1860
Distinct characters83
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)96.8%

Sample

1st row부산광역시 중구 해관로 22-1 (중앙동1가)
2nd row부산광역시 중구 영주로 62, 1층 (영주동)
3rd row부산광역시 중구 동영로73번길 1, 1층 (영주동)
4th row부산광역시 중구 중구로33번길 22 (부평동1가)
5th row부산광역시 중구 중구로29번길 20, 2층 (부평동1가, 외 1필지)
ValueCountFrequency (%)
부산광역시 62
 
16.9%
중구 60
 
16.4%
2층 12
 
3.3%
지하1층 12
 
3.3%
1층 11
 
3.0%
영주동 8
 
2.2%
중앙동4가 6
 
1.6%
남포동6가 5
 
1.4%
중구로 5
 
1.4%
동영로 4
 
1.1%
Other values (120) 181
49.5%
2023-12-10T19:13:13.544681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
304
 
16.3%
1 94
 
5.1%
중 83
 
4.5%
부 74
 
4.0%
구 74
 
4.0%
광 73
 
3.9%
동 70
 
3.8%
2 69
 
3.7%
역 62
 
3.3%
시 62
 
3.3%
Other values (73) 895
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1031
55.4%
Decimal Number 328
 
17.6%
Space Separator 304
 
16.3%
Close Punctuation 60
 
3.2%
Open Punctuation 60
 
3.2%
Other Punctuation 57
 
3.1%
Dash Punctuation 20
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 83
 
8.1%
부 74
 
7.2%
구 74
 
7.2%
광 73
 
7.1%
동 70
 
6.8%
역 62
 
6.0%
시 62
 
6.0%
산 62
 
6.0%
로 58
 
5.6%
가 52
 
5.0%
Other values (58) 361
35.0%
Decimal Number
ValueCountFrequency (%)
1 94
28.7%
2 69
21.0%
3 46
14.0%
4 41
12.5%
5 23
 
7.0%
6 17
 
5.2%
8 11
 
3.4%
9 10
 
3.0%
7 9
 
2.7%
0 8
 
2.4%
Space Separator
ValueCountFrequency (%)
304
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Other Punctuation
ValueCountFrequency (%)
, 57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1031
55.4%
Common 829
44.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 83
 
8.1%
부 74
 
7.2%
구 74
 
7.2%
광 73
 
7.1%
동 70
 
6.8%
역 62
 
6.0%
시 62
 
6.0%
산 62
 
6.0%
로 58
 
5.6%
가 52
 
5.0%
Other values (58) 361
35.0%
Common
ValueCountFrequency (%)
304
36.7%
1 94
 
11.3%
2 69
 
8.3%
) 60
 
7.2%
( 60
 
7.2%
, 57
 
6.9%
3 46
 
5.5%
4 41
 
4.9%
5 23
 
2.8%
- 20
 
2.4%
Other values (5) 55
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1031
55.4%
ASCII 829
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
304
36.7%
1 94
 
11.3%
2 69
 
8.3%
) 60
 
7.2%
( 60
 
7.2%
, 57
 
6.9%
3 46
 
5.5%
4 41
 
4.9%
5 23
 
2.8%
- 20
 
2.4%
Other values (5) 55
 
6.6%
Hangul
ValueCountFrequency (%)
중 83
 
8.1%
부 74
 
7.2%
구 74
 
7.2%
광 73
 
7.1%
동 70
 
6.8%
역 62
 
6.0%
시 62
 
6.0%
산 62
 
6.0%
로 58
 
5.6%
가 52
 
5.0%
Other values (58) 361
35.0%

person_prmisn_de
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

clsbiz_de
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

engl_sttus
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
폐업
60 
영업/정상
40 

Length

Max length5
Median length2
Mean length3.2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 60
60.0%
영업/정상 40
40.0%

Length

2023-12-10T19:13:13.846417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:14.051052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 60
60.0%
영업/정상 40
40.0%

detail_engl_sttus
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
폐업
60 
영업
40 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 60
60.0%
영업 40
40.0%

Length

2023-12-10T19:13:14.231316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:14.436596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 60
60.0%
영업 40
40.0%

xcnts
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)79.8%
Missing6
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean385359.31
Minimum384269.37
Maximum401617.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:14.796418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum384269.37
5-th percentile384398.16
Q1384698.9
median385083
Q3385497.26
95-th percentile385759.65
Maximum401617.56
Range17348.189
Interquartile range (IQR)798.36238

Descriptive statistics

Standard deviation1981.8102
Coefficient of variation (CV)0.0051427593
Kurtosis53.235793
Mean385359.31
Median Absolute Deviation (MAD)414.19855
Skewness6.990149
Sum36223775
Variance3927571.5
MonotonicityNot monotonic
2023-12-10T19:13:15.073310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
385316.674026245 3
 
3.0%
385364.139160371 3
 
3.0%
385517.559896349 3
 
3.0%
384380.762745833 3
 
3.0%
384728.430348184 3
 
3.0%
385015.384999651 2
 
2.0%
385508.413954577 2
 
2.0%
384615.3144212 2
 
2.0%
384856.568228363 2
 
2.0%
384969.91342527 2
 
2.0%
Other values (65) 69
69.0%
(Missing) 6
 
6.0%
ValueCountFrequency (%)
384269.368239152 1
 
1.0%
384283.686492926 1
 
1.0%
384380.762745833 3
3.0%
384407.525465206 1
 
1.0%
384454.178374824 1
 
1.0%
384480.960659264 1
 
1.0%
384506.317967696 1
 
1.0%
384523.423921873 2
2.0%
384542.121201746 1
 
1.0%
384544.708039828 1
 
1.0%
ValueCountFrequency (%)
401617.557302013 1
1.0%
394117.140328901 1
1.0%
385825.756707547 2
2.0%
385793.299310018 1
1.0%
385741.524981409 1
1.0%
385735.376259052 1
1.0%
385704.287614749 1
1.0%
385685.21954645 1
1.0%
385683.589345804 1
1.0%
385632.365526707 1
1.0%

ydnts
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)79.8%
Missing6
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean180553.89
Minimum179391.53
Maximum202127.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:15.420962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum179391.53
5-th percentile179478.21
Q1179737.18
median179955.77
Q3180658.67
95-th percentile181102.84
Maximum202127.11
Range22735.579
Interquartile range (IQR)921.48821

Descriptive statistics

Standard deviation2849.0401
Coefficient of variation (CV)0.015779445
Kurtosis45.386455
Mean180553.89
Median Absolute Deviation (MAD)379.72676
Skewness6.6195859
Sum16972065
Variance8117029.4
MonotonicityNot monotonic
2023-12-10T19:13:15.825938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180977.867377644 3
 
3.0%
179562.815862117 3
 
3.0%
179676.666538806 3
 
3.0%
179907.143964003 3
 
3.0%
179877.329958975 3
 
3.0%
179808.355520845 2
 
2.0%
179934.600251496 2
 
2.0%
179748.447306371 2
 
2.0%
179733.426954037 2
 
2.0%
180996.784424076 2
 
2.0%
Other values (65) 69
69.0%
(Missing) 6
 
6.0%
ValueCountFrequency (%)
179391.528210828 1
1.0%
179395.986370534 1
1.0%
179432.734579543 1
1.0%
179453.398252904 1
1.0%
179469.679502888 1
1.0%
179482.807870709 1
1.0%
179490.560472097 1
1.0%
179494.036404419 1
1.0%
179532.62384963 1
1.0%
179539.723961796 1
1.0%
ValueCountFrequency (%)
202127.107015021 1
1.0%
196326.970885559 1
1.0%
181175.647616445 1
1.0%
181146.093577037 1
1.0%
181106.197122183 1
1.0%
181101.034719319 1
1.0%
181072.468071507 1
1.0%
181066.382096046 1
1.0%
180996.784424076 2
2.0%
180987.169145877 2
2.0%

last_updt_de
Real number (ℝ)

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0114292 × 1013
Minimum1.9990809 × 1013
Maximum2.0200826 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:16.144181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990809 × 1013
5-th percentile2.0030612 × 1013
Q12.0070978 × 1013
median2.0130208 × 1013
Q32.0160731 × 1013
95-th percentile2.0181475 × 1013
Maximum2.0200826 × 1013
Range2.100171 × 1011
Interquartile range (IQR)8.9752812 × 1010

Descriptive statistics

Standard deviation5.3091705 × 1010
Coefficient of variation (CV)0.0026395015
Kurtosis-0.99690044
Mean2.0114292 × 1013
Median Absolute Deviation (MAD)4.0804014 × 1010
Skewness-0.38372375
Sum2.0114292 × 1015
Variance2.8187291 × 1021
MonotonicityNot monotonic
2023-12-10T19:13:16.880219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030614000000 8
 
8.0%
20030612000000 2
 
2.0%
20030609000000 2
 
2.0%
20180531110625 1
 
1.0%
20180501090321 1
 
1.0%
20050507000000 1
 
1.0%
20130208130240 1
 
1.0%
20130208134503 1
 
1.0%
20060522000000 1
 
1.0%
20061127000000 1
 
1.0%
Other values (81) 81
81.0%
ValueCountFrequency (%)
19990809000000 1
 
1.0%
20030527000000 1
 
1.0%
20030529000000 1
 
1.0%
20030609000000 2
 
2.0%
20030612000000 2
 
2.0%
20030614000000 8
8.0%
20041126000000 1
 
1.0%
20041230000000 1
 
1.0%
20050507000000 1
 
1.0%
20050520000000 1
 
1.0%
ValueCountFrequency (%)
20200826100317 1
1.0%
20200707131927 1
1.0%
20191121213913 1
1.0%
20191113100011 1
1.0%
20190312105700 1
1.0%
20181010140044 1
1.0%
20180730133943 1
1.0%
20180627110337 1
1.0%
20180531110625 1
1.0%
20180501090321 1
1.0%

bizcnd_se_nm
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 100
100.0%

Length

2023-12-10T19:13:17.169994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:17.385350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 100
100.0%

telno
Real number (ℝ)

MISSING 

Distinct74
Distinct (%)92.5%
Missing20
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean4.4957446 × 108
Minimum2426848
Maximum5.1727416 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:17.667089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2426848
5-th percentile2554350.4
Q15.1244743 × 108
median5.1248644 × 108
Q35.1462666 × 108
95-th percentile5.146985 × 108
Maximum5.1727416 × 108
Range5.1484731 × 108
Interquartile range (IQR)2179222.8

Descriptive statistics

Standard deviation1.69637 × 108
Coefficient of variation (CV)0.37732794
Kurtosis3.4270733
Mean4.4957446 × 108
Median Absolute Deviation (MAD)76045
Skewness-2.3111777
Sum3.5965957 × 1010
Variance2.8776713 × 1016
MonotonicityNot monotonic
2023-12-10T19:13:17.932184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
512542442 3
 
3.0%
512572828 2
 
2.0%
514626807 2
 
2.0%
512427007 2
 
2.0%
512456345 2
 
2.0%
2465684 1
 
1.0%
512448542 1
 
1.0%
512475341 1
 
1.0%
512557727 1
 
1.0%
512413503 1
 
1.0%
Other values (64) 64
64.0%
(Missing) 20
 
20.0%
ValueCountFrequency (%)
2426848 1
1.0%
2451624 1
1.0%
2465684 1
1.0%
2546834 1
1.0%
2554746 1
1.0%
4657015 1
1.0%
4663494 1
1.0%
4665208 1
1.0%
4692041 1
1.0%
4694750 1
1.0%
ValueCountFrequency (%)
517274161 1
1.0%
516273530 1
1.0%
515092161 1
1.0%
514699464 1
1.0%
514698444 1
1.0%
514695333 1
1.0%
514694487 1
1.0%
514675173 1
1.0%
514657840 1
1.0%
514655552 1
1.0%

buld_posesn_se_nm
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
임대
76 
<NA>
24 

Length

Max length4
Median length2
Mean length2.48
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
임대 76
76.0%
<NA> 24
 
24.0%

Length

2023-12-10T19:13:18.200146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:18.368556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임대 76
76.0%
na 24
 
24.0%

buld_ground_floor_co
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)12.9%
Missing7
Missing (%)7.0%
Infinite0
Infinite (%)0.0%
Mean3.9139785
Minimum0
Maximum19
Zeros5
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:18.564824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.6
Q12
median4
Q34
95-th percentile9
Maximum19
Range19
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.1195593
Coefficient of variation (CV)0.79703026
Kurtosis11.105855
Mean3.9139785
Median Absolute Deviation (MAD)1
Skewness2.8083967
Sum364
Variance9.7316503
MonotonicityNot monotonic
2023-12-10T19:13:18.784106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
4 28
28.0%
3 19
19.0%
5 12
12.0%
1 10
 
10.0%
2 9
 
9.0%
0 5
 
5.0%
9 3
 
3.0%
6 2
 
2.0%
19 2
 
2.0%
10 1
 
1.0%
Other values (2) 2
 
2.0%
(Missing) 7
 
7.0%
ValueCountFrequency (%)
0 5
 
5.0%
1 10
 
10.0%
2 9
 
9.0%
3 19
19.0%
4 28
28.0%
5 12
12.0%
6 2
 
2.0%
7 1
 
1.0%
9 3
 
3.0%
10 1
 
1.0%
ValueCountFrequency (%)
19 2
 
2.0%
13 1
 
1.0%
10 1
 
1.0%
9 3
 
3.0%
7 1
 
1.0%
6 2
 
2.0%
5 12
12.0%
4 28
28.0%
3 19
19.0%
2 9
 
9.0%

buld_undgrnd_floor_co
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
45 
<NA>
24 
0
24 
2
5 
3
 
2

Length

Max length4
Median length1
Mean length1.72
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
1 45
45.0%
<NA> 24
24.0%
0 24
24.0%
2 5
 
5.0%
3 2
 
2.0%

Length

2023-12-10T19:13:18.996711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:19.164580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 45
45.0%
na 24
24.0%
0 24
24.0%
2 5
 
5.0%
3 2
 
2.0%

male_enfsn_co
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T19:13:19.345412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:19.496044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

multi_use_bssh_at
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
100 
ValueCountFrequency (%)
False 100
100.0%
2023-12-10T19:13:19.619518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

pyrxia_room_at
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.0%
Missing4
Missing (%)4.0%
Memory size332.0 B
False
96 
(Missing)
 
4
ValueCountFrequency (%)
False 96
96.0%
(Missing) 4
 
4.0%
2023-12-10T19:13:19.744571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

use_end_ground_floor
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)8.8%
Missing20
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean1.5
Minimum0
Maximum8
Zeros19
Zeros (%)19.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:19.902332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3.05
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3501055
Coefficient of variation (CV)0.90007032
Kurtosis6.1681756
Mean1.5
Median Absolute Deviation (MAD)1
Skewness1.7725744
Sum120
Variance1.8227848
MonotonicityNot monotonic
2023-12-10T19:13:20.100975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 27
27.0%
1 23
23.0%
0 19
19.0%
3 7
 
7.0%
5 2
 
2.0%
4 1
 
1.0%
8 1
 
1.0%
(Missing) 20
20.0%
ValueCountFrequency (%)
0 19
19.0%
1 23
23.0%
2 27
27.0%
3 7
 
7.0%
4 1
 
1.0%
5 2
 
2.0%
8 1
 
1.0%
ValueCountFrequency (%)
8 1
 
1.0%
5 2
 
2.0%
4 1
 
1.0%
3 7
 
7.0%
2 27
27.0%
1 23
23.0%
0 19
19.0%

use_end_undgrnd_floor
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
38 
0
36 
1
26 

Length

Max length4
Median length1
Mean length2.14
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 38
38.0%
0 36
36.0%
1 26
26.0%

Length

2023-12-10T19:13:20.348045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:20.553102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 38
38.0%
0 36
36.0%
1 26
26.0%

use_begin_ground_floor
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)8.4%
Missing17
Missing (%)17.0%
Infinite0
Infinite (%)0.0%
Mean1.5060241
Minimum0
Maximum8
Zeros20
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:20.739673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3468436
Coefficient of variation (CV)0.89430414
Kurtosis5.9032377
Mean1.5060241
Median Absolute Deviation (MAD)1
Skewness1.7054588
Sum125
Variance1.8139877
MonotonicityNot monotonic
2023-12-10T19:13:20.940114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 28
28.0%
1 23
23.0%
0 20
20.0%
3 8
 
8.0%
5 2
 
2.0%
4 1
 
1.0%
8 1
 
1.0%
(Missing) 17
17.0%
ValueCountFrequency (%)
0 20
20.0%
1 23
23.0%
2 28
28.0%
3 8
 
8.0%
4 1
 
1.0%
5 2
 
2.0%
8 1
 
1.0%
ValueCountFrequency (%)
8 1
 
1.0%
5 2
 
2.0%
4 1
 
1.0%
3 8
 
8.0%
2 28
28.0%
1 23
23.0%
0 20
20.0%

female_enfsn_co
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T19:13:21.196676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:21.374322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

snitat_biznd_nm
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 100
100.0%

Length

2023-12-10T19:13:21.549736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:21.747949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 100
100.0%

chair_co
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)11.8%
Missing7
Missing (%)7.0%
Infinite0
Infinite (%)0.0%
Mean3.8602151
Minimum0
Maximum10
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:13:22.066401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.6
Q12
median3
Q35
95-th percentile8.4
Maximum10
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3846948
Coefficient of variation (CV)0.61776218
Kurtosis0.22782647
Mean3.8602151
Median Absolute Deviation (MAD)1
Skewness1.009709
Sum359
Variance5.6867695
MonotonicityNot monotonic
2023-12-10T19:13:22.491605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 35
35.0%
4 13
 
13.0%
3 11
 
11.0%
6 10
 
10.0%
5 6
 
6.0%
8 5
 
5.0%
10 4
 
4.0%
1 4
 
4.0%
7 3
 
3.0%
0 1
 
1.0%
(Missing) 7
 
7.0%
ValueCountFrequency (%)
0 1
 
1.0%
1 4
 
4.0%
2 35
35.0%
3 11
 
11.0%
4 13
 
13.0%
5 6
 
6.0%
6 10
 
10.0%
7 3
 
3.0%
8 5
 
5.0%
9 1
 
1.0%
ValueCountFrequency (%)
10 4
 
4.0%
9 1
 
1.0%
8 5
 
5.0%
7 3
 
3.0%
6 10
 
10.0%
5 6
 
6.0%
4 13
 
13.0%
3 11
 
11.0%
2 35
35.0%
1 4
 
4.0%

bedd_co
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
66 
<NA>
34 

Length

Max length4
Median length1
Mean length2.02
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 66
66.0%
<NA> 34
34.0%

Length

2023-12-10T19:13:22.771686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:13:22.955485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 66
66.0%
na 34
34.0%

Sample

skeysfrnd_codesfrnd_code_nmperson_prmisn_nosvc_iddata_updt_sedata_updt_desvc_id_nmbplc_nmlnm_ziplnm_adresrdnmadrperson_prmisn_declsbiz_deengl_sttusdetail_engl_sttusxcntsydntslast_updt_debizcnd_se_nmtelnobuld_posesn_se_nmbuld_ground_floor_cobuld_undgrnd_floor_comale_enfsn_comulti_use_bssh_atpyrxia_room_atuse_end_ground_flooruse_end_undgrnd_flooruse_begin_ground_floorfemale_enfsn_cosnitat_biznd_nmchair_cobedd_co
013250000부산광역시 중구3250000-203-2003-0000305_19_01_PI2018-08-31 11:59:59.0이용업종 이용원600011부산광역시 중구 중앙동1가 22-23번지부산광역시 중구 해관로 22-1 (중앙동1가)<NA><NA>영업/정상영업385566.02033179863.35218120130208134015일반이용업2426848임대510NN0100일반이용업40
148623400000부산광역시 기장군3400000-203-1990-0028805_19_01_PI2018-08-31 11:59:59.0이용업대우이용원619953부산광역시 기장군 장안읍 좌천리 203-3번지 T통B반<NA><NA><NA>영업/정상영업<NA><NA>20041230000000일반이용업517274161<NA><NA><NA>0NN<NA><NA><NA>0일반이용업<NA><NA>
233250000부산광역시 중구3250000-203-1969-0048505_19_01_PI2018-08-31 11:59:59.0이용업아파트600110부산광역시 중구 영주동 151-7번지 (1층)부산광역시 중구 영주로 62, 1층 (영주동)<NA><NA>영업/정상영업385032.70417181175.64761620130208115140일반이용업514629497임대200NN1010일반이용업30
343250000부산광역시 중구3250000-203-1974-0048605_19_01_PI2018-08-31 11:59:59.0이용업미진600110부산광역시 중구 영주동 278-18번지 (1층)부산광역시 중구 동영로73번길 1, 1층 (영주동)<NA><NA>영업/정상영업385176.475635181066.38209620130208124508일반이용업4665208임대100NN1010일반이용업40
453250000부산광역시 중구3250000-203-2008-0000705_19_01_PI2018-08-31 11:59:59.0이용업양신탕구내이용원600804부산광역시 중구 부평동1가 27-1번지부산광역시 중구 중구로33번길 22 (부평동1가)<NA><NA>영업/정상영업384728.430348179877.32995920130208135011일반이용업512567085<NA>000NN0000일반이용업20
563250000부산광역시 중구3250000-203-2012-0000305_19_01_PI2018-08-31 11:59:59.0이용업국사이용원600804부산광역시 중구 부평동1가 29-30번지 외 1필지 (2층)부산광역시 중구 중구로29번길 20, 2층 (부평동1가, 외 1필지)<NA><NA>영업/정상영업384733.730546179820.20718620130208135410일반이용업512572828임대410NN2020일반이용업30
673250000부산광역시 중구3250000-203-1968-0046005_19_01_PI2018-08-31 11:59:59.0이용업삼화600024부산광역시 중구 동광동4가 16-1번지 ,18-1(2층)부산광역시 중구 광복로97번길 25-1 (동광동2가)<NA><NA>영업/정상영업385441.079235179872.78586520131230105103일반이용업514625861임대400NN2020일반이용업60
748633400000부산광역시 기장군3400000-203-2009-0000505_19_01_PU2019-11-23 02:40:00.0이용업서울이용원619905부산광역시 기장군 기장읍 동부리 273-1번지부산광역시 기장군 기장읍 차성로322번길 36<NA><NA>영업/정상영업401617.557302196326.97088620191121213913일반이용업<NA>임대000NN1010일반이용업20
893250000부산광역시 중구3250000-203-1979-0047205_19_01_PI2018-08-31 11:59:59.0이용업금성600800부산광역시 중구 대청동4가 63-11번지 (2층)부산광역시 중구 대청북길17번길 41-3, 2층 (대청동4가)<NA><NA>영업/정상영업385042.318024180533.35910520130208125346일반이용업514694487임대410NN2020일반이용업30
9103250000부산광역시 중구3250000-203-1966-0048405_19_01_PI2018-08-31 11:59:59.0이용업중부산세무서구내600803부산광역시 중구 보수동1가 52-1번지부산광역시 중구 보수대로140번길 81, 1층 (보수동1가)<NA><NA>영업/정상영업384580.2671180348.6688620171115091630일반이용업512547767임대100NN1010일반이용업40
skeysfrnd_codesfrnd_code_nmperson_prmisn_nosvc_iddata_updt_sedata_updt_desvc_id_nmbplc_nmlnm_ziplnm_adresrdnmadrperson_prmisn_declsbiz_deengl_sttusdetail_engl_sttusxcntsydntslast_updt_debizcnd_se_nmtelnobuld_posesn_se_nmbuld_ground_floor_cobuld_undgrnd_floor_comale_enfsn_comulti_use_bssh_atpyrxia_room_atuse_end_ground_flooruse_end_undgrnd_flooruse_begin_ground_floorfemale_enfsn_cosnitat_biznd_nmchair_cobedd_co
90913250000부산광역시 중구3250000-203-2013-0000305_19_01_PI2018-08-31 11:59:59.0이용업신천지이용원600046부산광역시 중구 남포동6가 3번지 신천지 B-200(지하1층)부산광역시 중구 자갈치로 33 (남포동6가)<NA><NA>폐업폐업384836.914456179432.7345820170405140832일반이용업<NA><NA>910NN<NA>1<NA>0일반이용업30
91923250000부산광역시 중구3250000-203-2016-0000305_19_01_PI2018-08-31 11:59:59.0이용업녹수탕 구내 이용원600062부산광역시 중구 신창동2가 21-2번지부산광역시 중구 광복로43번길 12 (신창동2가)<NA><NA>폐업폐업385015.385179808.35552120160704123227일반이용업<NA><NA><NA><NA>0NN<NA><NA><NA>0일반이용업<NA><NA>
92933250000부산광역시 중구3250000-203-2006-0000605_19_01_PI2018-08-31 11:59:59.0이용업태평양이용원600808부산광역시 중구 부평동3가 25-1번지 (1층)부산광역시 중구 흑교로25번길 6, 1층 (부평동3가)<NA><NA>영업/정상영업384544.70804179973.71407820171012144237일반이용업512557888임대410NN1010일반이용업30
93943250000부산광역시 중구3250000-203-2006-0000405_19_01_PI2018-08-31 11:59:59.0이용업강강600817부산광역시 중구 중앙동4가 81-17번지 (2층)부산광역시 중구 충장대로5번길 32, 2층 (중앙동4가)<NA><NA>영업/정상영업385685.219546180664.24749120170718144740일반이용업<NA>임대510NN2020일반이용업30
94953250000부산광역시 중구3250000-203-1989-0051705_19_01_PI2018-08-31 11:59:59.0이용업남성H전문600800부산광역시 중구 대청동4가 85-1번지 (3층)부산광역시 중구 중구로 90, 3층 (대청동4가)<NA><NA>영업/정상영업385079.664368180294.01910420171110105721일반이용업514655552임대410NN3030일반이용업20
95963250000부산광역시 중구3250000-203-1979-0046105_19_01_PI2018-08-31 11:59:59.0이용업부남600025부산광역시 중구 동광동5가 12-165번지부산광역시 중구 동영로 18 (동광동5가)<NA><NA>영업/정상영업385393.497592180704.3542820131230110555일반이용업514699464임대310NN1010일반이용업50
96973250000부산광역시 중구3250000-203-1979-0046205_19_01_PI2018-08-31 11:59:59.0이용업부전600025부산광역시 중구 동광동5가 13-68번지 (1층)부산광역시 중구 동영로 11, 1층 (동광동5가)<NA><NA>영업/정상영업385334.516493180678.92415620130208125257일반이용업4694750임대100NN1010일반이용업40
97983250000부산광역시 중구3250000-203-1970-0045905_19_01_PI2018-08-31 11:59:59.0이용업광미이용원600101부산광역시 중구 대창동1가 51번지 외 2필지(5층)부산광역시 중구 해관로 89, 5층 (대창동1가, 외 2필지)<NA><NA>영업/정상영업385507.64053180548.79261220130208115354일반이용업514626258임대1310NN5050일반이용업20
98993250000부산광역시 중구3250000-203-2020-0000105_19_01_PU2020-07-09 02:40:00.0이용업두원600811부산광역시 중구 영주동 526-49 두원베스피아부산광역시 중구 동영로 46, 두원베스피아 (영주동)<NA><NA>폐업폐업385316.674026180977.86737820200707131927일반이용업<NA><NA>410NN<NA>1<NA>0일반이용업20
991003250000부산광역시 중구3250000-203-1994-0054405_19_01_PI2018-08-31 11:59:59.0이용업용두산600022부산광역시 중구 동광동2가 17-26번지<NA><NA><NA>폐업폐업385389.409543179854.6555520030614000000일반이용업512478091임대9<NA>0NN1<NA>10일반이용업6<NA>