Overview

Dataset statistics

Number of variables47
Number of observations4934
Missing cells7360
Missing cells (%)3.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 MiB
Average record size in memory382.0 B

Variable types

Numeric6
Text7
Categorical31
DateTime1
Boolean2

Alerts

opnsvcid has constant value ""Constant
multusnupsoyn has constant value ""Constant
balhansilyn has constant value ""Constant
last_load_dttm has constant value ""Constant
updategbn is highly imbalanced (68.3%)Imbalance
opnsvcnm is highly imbalanced (60.8%)Imbalance
clgstdt is highly imbalanced (91.7%)Imbalance
clgenddt is highly imbalanced (91.7%)Imbalance
ropnymd is highly imbalanced (91.7%)Imbalance
trdstatenm is highly imbalanced (51.9%)Imbalance
uptaenm is highly imbalanced (94.3%)Imbalance
sitetel is highly imbalanced (95.5%)Imbalance
bdngownsenm is highly imbalanced (60.4%)Imbalance
bdngunderflrcnt is highly imbalanced (53.2%)Imbalance
maneipcnt is highly imbalanced (80.8%)Imbalance
useunderendflr is highly imbalanced (60.1%)Imbalance
useunderstflr is highly imbalanced (50.9%)Imbalance
wmeipcnt is highly imbalanced (78.7%)Imbalance
sntuptaenm is highly imbalanced (94.3%)Imbalance
cndpermstymd is highly imbalanced (95.6%)Imbalance
cndpermntwhy is highly imbalanced (94.6%)Imbalance
cndpermendymd is highly imbalanced (95.6%)Imbalance
abedcnt is highly imbalanced (69.4%)Imbalance
rdnpostno has 2660 (53.9%) missing valuesMissing
rdnwhladdr has 2604 (52.8%) missing valuesMissing
dcbymd has 1441 (29.2%) missing valuesMissing
x has 314 (6.4%) missing valuesMissing
y has 314 (6.4%) missing valuesMissing
apvpermymd is highly skewed (γ1 = -26.90114143)Skewed
skey has unique valuesUnique

Reproduction

Analysis started2024-04-17 01:45:56.382054
Analysis finished2024-04-17 01:45:57.738772
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct4934
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2516.3581
Minimum1
Maximum7088
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.5 KiB
2024-04-17T10:45:57.793069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile247.65
Q11234.25
median2467.5
Q33700.75
95-th percentile4687.35
Maximum7088
Range7087
Interquartile range (IQR)2466.5

Descriptive statistics

Standard deviation1528.3714
Coefficient of variation (CV)0.60737435
Kurtosis-0.44251552
Mean2516.3581
Median Absolute Deviation (MAD)1233.5
Skewness0.32830608
Sum12415711
Variance2335919.1
MonotonicityNot monotonic
2024-04-17T10:45:57.906384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 1
 
< 0.1%
3289 1
 
< 0.1%
3296 1
 
< 0.1%
3295 1
 
< 0.1%
3294 1
 
< 0.1%
3293 1
 
< 0.1%
3292 1
 
< 0.1%
3291 1
 
< 0.1%
3290 1
 
< 0.1%
3287 1
 
< 0.1%
Other values (4924) 4924
99.8%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
7088 1
< 0.1%
7087 1
< 0.1%
7086 1
< 0.1%
7085 1
< 0.1%
7084 1
< 0.1%
7083 1
< 0.1%
7082 1
< 0.1%
7081 1
< 0.1%
7080 1
< 0.1%
7079 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3324452.8
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.5 KiB
2024-04-17T10:45:58.011007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3320000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation40372.963
Coefficient of variation (CV)0.012144243
Kurtosis-0.94067359
Mean3324452.8
Median Absolute Deviation (MAD)30000
Skewness0.062421579
Sum1.640285 × 1010
Variance1.6299762 × 109
MonotonicityNot monotonic
2024-04-17T10:45:58.106444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 514
10.4%
3340000 503
10.2%
3300000 418
 
8.5%
3320000 410
 
8.3%
3330000 393
 
8.0%
3350000 380
 
7.7%
3390000 336
 
6.8%
3370000 328
 
6.6%
3310000 323
 
6.5%
3380000 284
 
5.8%
Other values (6) 1045
21.2%
ValueCountFrequency (%)
3250000 166
 
3.4%
3260000 213
4.3%
3270000 257
5.2%
3280000 211
4.3%
3290000 514
10.4%
3300000 418
8.5%
3310000 323
6.5%
3320000 410
8.3%
3330000 393
8.0%
3340000 503
10.2%
ValueCountFrequency (%)
3400000 110
 
2.2%
3390000 336
6.8%
3380000 284
5.8%
3370000 328
6.6%
3360000 88
 
1.8%
3350000 380
7.7%
3340000 503
10.2%
3330000 393
8.0%
3320000 410
8.3%
3310000 323
6.5%

mgtno
Text

Distinct4897
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
2024-04-17T10:45:58.279278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters108548
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

Unique4875 ?
Unique (%)98.8%

Sample

1st row3250000-203-1980-00478
2nd row3250000-203-2005-00004
3rd row3250000-203-2005-00005
4th row3250000-203-1972-00443
5th row3250000-203-2005-00001
ValueCountFrequency (%)
3280000-203-2018-00003 3
 
0.1%
3390000-203-2017-00003 3
 
0.1%
3330000-203-2019-00002 3
 
0.1%
3290000-203-2020-00002 3
 
0.1%
3300000-203-2019-00008 3
 
0.1%
3290000-203-2020-00004 3
 
0.1%
3290000-203-2019-00008 3
 
0.1%
3290000-203-2019-00003 3
 
0.1%
3390000-203-2019-00006 3
 
0.1%
3340000-203-2019-00006 3
 
0.1%
Other values (4887) 4904
99.4%
2024-04-17T10:45:58.551723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43383
40.0%
3 15489
 
14.3%
- 14802
 
13.6%
2 10929
 
10.1%
1 6182
 
5.7%
9 6050
 
5.6%
8 2666
 
2.5%
7 2441
 
2.2%
4 2335
 
2.2%
6 2137
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93746
86.4%
Dash Punctuation 14802
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43383
46.3%
3 15489
 
16.5%
2 10929
 
11.7%
1 6182
 
6.6%
9 6050
 
6.5%
8 2666
 
2.8%
7 2441
 
2.6%
4 2335
 
2.5%
6 2137
 
2.3%
5 2134
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 14802
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108548
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43383
40.0%
3 15489
 
14.3%
- 14802
 
13.6%
2 10929
 
10.1%
1 6182
 
5.7%
9 6050
 
5.6%
8 2666
 
2.5%
7 2441
 
2.2%
4 2335
 
2.2%
6 2137
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108548
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43383
40.0%
3 15489
 
14.3%
- 14802
 
13.6%
2 10929
 
10.1%
1 6182
 
5.7%
9 6050
 
5.6%
8 2666
 
2.5%
7 2441
 
2.2%
4 2335
 
2.2%
6 2137
 
2.0%

opnsvcid
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
05_19_01_P
4934 

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 4934
100.0%

Length

2024-04-17T10:45:58.665197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:58.738732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 4934
100.0%

updategbn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
I
4651 
U
 
283

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 4651
94.3%
U 283
 
5.7%

Length

2024-04-17T10:45:58.812116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:58.886699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4651
94.3%
u 283
 
5.7%
Distinct268
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
Minimum2018-08-31 23:59:59
Maximum2021-04-01 00:22:58
2024-04-17T10:45:58.996813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T10:45:59.129282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

opnsvcnm
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4553 
이용업
 
381

Length

Max length4
Median length4
Mean length3.9227807
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4553
92.3%
이용업 381
 
7.7%

Length

2024-04-17T10:45:59.240141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:59.318047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4553
92.3%
이용업 381
 
7.7%

bplcnm
Text

Distinct3320
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
2024-04-17T10:45:59.532592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length4.7638833
Min length1

Characters and Unicode

Total characters23505
Distinct characters566
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2625 ?
Unique (%)53.2%

Sample

1st row태양탕구내
2nd row국사 이용원
3rd row녹수탕구내이용원
4th row부산호텔이용원
5th row터프가위 이용원
ValueCountFrequency (%)
이용원 364
 
6.4%
구내 53
 
0.9%
컷트실 50
 
0.9%
구내이용원 40
 
0.7%
현대 35
 
0.6%
우리 28
 
0.5%
제일 28
 
0.5%
태후사랑 25
 
0.4%
블루클럽 24
 
0.4%
구내이용 23
 
0.4%
Other values (3174) 5040
88.3%
2024-04-17T10:45:59.898915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2089
 
8.9%
2019
 
8.6%
1928
 
8.2%
977
 
4.2%
840
 
3.6%
789
 
3.4%
584
 
2.5%
477
 
2.0%
402
 
1.7%
392
 
1.7%
Other values (556) 13008
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22231
94.6%
Space Separator 789
 
3.4%
Uppercase Letter 158
 
0.7%
Lowercase Letter 133
 
0.6%
Close Punctuation 66
 
0.3%
Open Punctuation 66
 
0.3%
Decimal Number 36
 
0.2%
Other Punctuation 19
 
0.1%
Dash Punctuation 6
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2089
 
9.4%
2019
 
9.1%
1928
 
8.7%
977
 
4.4%
840
 
3.8%
584
 
2.6%
477
 
2.1%
402
 
1.8%
392
 
1.8%
342
 
1.5%
Other values (497) 12181
54.8%
Uppercase Letter
ValueCountFrequency (%)
B 20
12.7%
E 14
 
8.9%
O 14
 
8.9%
R 13
 
8.2%
H 12
 
7.6%
S 12
 
7.6%
M 8
 
5.1%
A 8
 
5.1%
T 7
 
4.4%
L 7
 
4.4%
Other values (12) 43
27.2%
Lowercase Letter
ValueCountFrequency (%)
e 18
13.5%
r 15
11.3%
s 11
8.3%
h 11
8.3%
i 10
 
7.5%
a 9
 
6.8%
b 9
 
6.8%
o 8
 
6.0%
k 8
 
6.0%
u 7
 
5.3%
Other values (8) 27
20.3%
Decimal Number
ValueCountFrequency (%)
2 11
30.6%
8 10
27.8%
1 8
22.2%
5 3
 
8.3%
9 2
 
5.6%
4 1
 
2.8%
3 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 9
47.4%
& 4
21.1%
, 2
 
10.5%
: 1
 
5.3%
# 1
 
5.3%
· 1
 
5.3%
' 1
 
5.3%
Space Separator
ValueCountFrequency (%)
789
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22228
94.6%
Common 983
 
4.2%
Latin 291
 
1.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2089
 
9.4%
2019
 
9.1%
1928
 
8.7%
977
 
4.4%
840
 
3.8%
584
 
2.6%
477
 
2.1%
402
 
1.8%
392
 
1.8%
342
 
1.5%
Other values (494) 12178
54.8%
Latin
ValueCountFrequency (%)
B 20
 
6.9%
e 18
 
6.2%
r 15
 
5.2%
E 14
 
4.8%
O 14
 
4.8%
R 13
 
4.5%
H 12
 
4.1%
S 12
 
4.1%
s 11
 
3.8%
h 11
 
3.8%
Other values (30) 151
51.9%
Common
ValueCountFrequency (%)
789
80.3%
) 66
 
6.7%
( 66
 
6.7%
2 11
 
1.1%
8 10
 
1.0%
. 9
 
0.9%
1 8
 
0.8%
- 6
 
0.6%
& 4
 
0.4%
5 3
 
0.3%
Other values (9) 11
 
1.1%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22228
94.6%
ASCII 1273
 
5.4%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2089
 
9.4%
2019
 
9.1%
1928
 
8.7%
977
 
4.4%
840
 
3.8%
584
 
2.6%
477
 
2.1%
402
 
1.8%
392
 
1.8%
342
 
1.5%
Other values (494) 12178
54.8%
ASCII
ValueCountFrequency (%)
789
62.0%
) 66
 
5.2%
( 66
 
5.2%
B 20
 
1.6%
e 18
 
1.4%
r 15
 
1.2%
E 14
 
1.1%
O 14
 
1.1%
R 13
 
1.0%
H 12
 
0.9%
Other values (48) 246
 
19.3%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
None
ValueCountFrequency (%)
· 1
100.0%

sitepostno
Real number (ℝ)

Distinct775
Distinct (%)15.8%
Missing24
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean610460.18
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.5 KiB
2024-04-17T10:46:00.017565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601812
Q1606064.25
median609854
Q3614827
95-th percentile617833
Maximum619953
Range19942
Interquartile range (IQR)8762.75

Descriptive statistics

Standard deviation5295.9277
Coefficient of variation (CV)0.0086753041
Kurtosis-1.0217951
Mean610460.18
Median Absolute Deviation (MAD)4960
Skewness-0.19058452
Sum2.9973595 × 109
Variance28046851
MonotonicityNot monotonic
2024-04-17T10:46:00.138326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
607833 33
 
0.7%
601829 28
 
0.6%
616801 28
 
0.6%
604851 27
 
0.5%
612847 27
 
0.5%
607826 24
 
0.5%
617818 24
 
0.5%
616807 23
 
0.5%
604813 22
 
0.4%
611803 22
 
0.4%
Other values (765) 4652
94.3%
(Missing) 24
 
0.5%
ValueCountFrequency (%)
600011 2
 
< 0.1%
600012 8
0.2%
600013 2
 
< 0.1%
600014 2
 
< 0.1%
600015 1
 
< 0.1%
600021 4
0.1%
600022 3
 
0.1%
600023 3
 
0.1%
600024 1
 
< 0.1%
600025 4
0.1%
ValueCountFrequency (%)
619953 3
 
0.1%
619952 6
0.1%
619951 5
 
0.1%
619950 1
 
< 0.1%
619913 3
 
0.1%
619912 5
 
0.1%
619911 6
0.1%
619906 9
0.2%
619905 14
0.3%
619904 2
 
< 0.1%
Distinct4307
Distinct (%)87.3%
Missing3
Missing (%)0.1%
Memory size38.7 KiB
2024-04-17T10:46:00.403142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length48
Mean length24.681201
Min length7

Characters and Unicode

Total characters121703
Distinct characters369
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3839 ?
Unique (%)77.9%

Sample

1st row부산광역시 중구 남포동6가 115-5번지 (지하1층)
2nd row부산광역시 중구 신창동1가 35-2번지 (2층)
3rd row부산광역시 중구 신창동2가 21-2번지 (2층)
4th row부산광역시 중구 동광동2가 12-1번지 외11필지
5th row부산광역시 중구 중앙동4가 78-20번지 (1층)
ValueCountFrequency (%)
부산광역시 4930
 
22.3%
t통b반 768
 
3.5%
부산진구 514
 
2.3%
사하구 505
 
2.3%
동래구 418
 
1.9%
북구 412
 
1.9%
해운대구 393
 
1.8%
금정구 380
 
1.7%
사상구 336
 
1.5%
연제구 326
 
1.5%
Other values (4652) 13135
59.4%
2024-04-17T10:46:00.976085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21990
18.1%
5852
 
4.8%
5805
 
4.8%
5801
 
4.8%
5101
 
4.2%
1 5088
 
4.2%
5063
 
4.2%
4980
 
4.1%
4956
 
4.1%
4936
 
4.1%
Other values (359) 52131
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69634
57.2%
Decimal Number 23491
 
19.3%
Space Separator 21990
 
18.1%
Dash Punctuation 4475
 
3.7%
Uppercase Letter 1586
 
1.3%
Open Punctuation 219
 
0.2%
Close Punctuation 218
 
0.2%
Other Punctuation 88
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5852
 
8.4%
5805
 
8.3%
5801
 
8.3%
5101
 
7.3%
5063
 
7.3%
4980
 
7.2%
4956
 
7.1%
4936
 
7.1%
4780
 
6.9%
955
 
1.4%
Other values (327) 21405
30.7%
Uppercase Letter
ValueCountFrequency (%)
B 788
49.7%
T 772
48.7%
A 11
 
0.7%
F 2
 
0.1%
G 2
 
0.1%
C 2
 
0.1%
S 2
 
0.1%
P 2
 
0.1%
L 2
 
0.1%
E 1
 
0.1%
Other values (2) 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 5088
21.7%
2 3176
13.5%
3 2717
11.6%
4 2243
9.5%
5 2187
9.3%
6 1728
 
7.4%
0 1715
 
7.3%
8 1661
 
7.1%
7 1611
 
6.9%
9 1365
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 76
86.4%
@ 6
 
6.8%
/ 3
 
3.4%
. 2
 
2.3%
& 1
 
1.1%
Space Separator
ValueCountFrequency (%)
21990
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4475
100.0%
Open Punctuation
ValueCountFrequency (%)
( 219
100.0%
Close Punctuation
ValueCountFrequency (%)
) 218
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69632
57.2%
Common 50483
41.5%
Latin 1586
 
1.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5852
 
8.4%
5805
 
8.3%
5801
 
8.3%
5101
 
7.3%
5063
 
7.3%
4980
 
7.2%
4956
 
7.1%
4936
 
7.1%
4780
 
6.9%
955
 
1.4%
Other values (326) 21403
30.7%
Common
ValueCountFrequency (%)
21990
43.6%
1 5088
 
10.1%
- 4475
 
8.9%
2 3176
 
6.3%
3 2717
 
5.4%
4 2243
 
4.4%
5 2187
 
4.3%
6 1728
 
3.4%
0 1715
 
3.4%
8 1661
 
3.3%
Other values (10) 3503
 
6.9%
Latin
ValueCountFrequency (%)
B 788
49.7%
T 772
48.7%
A 11
 
0.7%
F 2
 
0.1%
G 2
 
0.1%
C 2
 
0.1%
S 2
 
0.1%
P 2
 
0.1%
L 2
 
0.1%
E 1
 
0.1%
Other values (2) 2
 
0.1%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69632
57.2%
ASCII 52069
42.8%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21990
42.2%
1 5088
 
9.8%
- 4475
 
8.6%
2 3176
 
6.1%
3 2717
 
5.2%
4 2243
 
4.3%
5 2187
 
4.2%
6 1728
 
3.3%
0 1715
 
3.3%
8 1661
 
3.2%
Other values (22) 5089
 
9.8%
Hangul
ValueCountFrequency (%)
5852
 
8.4%
5805
 
8.3%
5801
 
8.3%
5101
 
7.3%
5063
 
7.3%
4980
 
7.2%
4956
 
7.1%
4936
 
7.1%
4780
 
6.9%
955
 
1.4%
Other values (326) 21403
30.7%
CJK
ValueCountFrequency (%)
2
100.0%

rdnpostno
Real number (ℝ)

MISSING 

Distinct1152
Distinct (%)50.7%
Missing2660
Missing (%)53.9%
Infinite0
Infinite (%)0.0%
Mean47830.927
Minimum46002
Maximum49525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.5 KiB
2024-04-17T10:46:01.101333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46243
Q147009
median47795
Q348735
95-th percentile49407
Maximum49525
Range3523
Interquartile range (IQR)1726

Descriptive statistics

Standard deviation1013.1272
Coefficient of variation (CV)0.021181425
Kurtosis-1.1215467
Mean47830.927
Median Absolute Deviation (MAD)800
Skewness0.021728746
Sum1.0876753 × 108
Variance1026426.8
MonotonicityNot monotonic
2024-04-17T10:46:01.219365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47709 13
 
0.3%
49256 12
 
0.2%
46219 9
 
0.2%
49476 9
 
0.2%
49228 8
 
0.2%
46321 7
 
0.1%
48099 7
 
0.1%
47603 7
 
0.1%
48445 7
 
0.1%
48501 7
 
0.1%
Other values (1142) 2188
44.3%
(Missing) 2660
53.9%
ValueCountFrequency (%)
46002 3
0.1%
46007 2
< 0.1%
46008 1
 
< 0.1%
46013 1
 
< 0.1%
46015 3
0.1%
46017 2
< 0.1%
46019 1
 
< 0.1%
46020 1
 
< 0.1%
46021 1
 
< 0.1%
46022 2
< 0.1%
ValueCountFrequency (%)
49525 1
 
< 0.1%
49524 2
 
< 0.1%
49522 2
 
< 0.1%
49521 1
 
< 0.1%
49518 5
0.1%
49516 1
 
< 0.1%
49515 4
0.1%
49514 1
 
< 0.1%
49511 6
0.1%
49509 1
 
< 0.1%

rdnwhladdr
Text

MISSING 

Distinct2210
Distinct (%)94.8%
Missing2604
Missing (%)52.8%
Memory size38.7 KiB
2024-04-17T10:46:01.510077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length54
Mean length28.683691
Min length17

Characters and Unicode

Total characters66833
Distinct characters390
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2114 ?
Unique (%)90.7%

Sample

1st row부산광역시 중구 자갈치로15번길 4, 지하1층 (남포동6가)
2nd row부산광역시 중구 광복로43번길 12, 2층 (신창동2가)
3rd row부산광역시 중구 중구로 90, 3층 (대청동4가)
4th row부산광역시 중구 동영로 18 (동광동5가)
5th row부산광역시 중구 동영로 11, 1층 (동광동5가)
ValueCountFrequency (%)
부산광역시 2330
 
17.9%
부산진구 277
 
2.1%
1층 273
 
2.1%
동래구 224
 
1.7%
사하구 220
 
1.7%
사상구 192
 
1.5%
금정구 183
 
1.4%
해운대구 178
 
1.4%
남구 163
 
1.3%
북구 154
 
1.2%
Other values (2612) 8793
67.7%
2024-04-17T10:46:01.917063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10661
 
16.0%
3026
 
4.5%
2852
 
4.3%
2810
 
4.2%
1 2511
 
3.8%
2443
 
3.7%
2437
 
3.6%
2414
 
3.6%
2334
 
3.5%
) 2298
 
3.4%
Other values (380) 33047
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39903
59.7%
Space Separator 10661
 
16.0%
Decimal Number 10163
 
15.2%
Close Punctuation 2298
 
3.4%
Open Punctuation 2298
 
3.4%
Other Punctuation 1045
 
1.6%
Dash Punctuation 424
 
0.6%
Uppercase Letter 39
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3026
 
7.6%
2852
 
7.1%
2810
 
7.0%
2443
 
6.1%
2437
 
6.1%
2414
 
6.0%
2334
 
5.8%
2248
 
5.6%
1269
 
3.2%
1203
 
3.0%
Other values (351) 16867
42.3%
Decimal Number
ValueCountFrequency (%)
1 2511
24.7%
2 1548
15.2%
3 1188
11.7%
4 869
 
8.6%
5 822
 
8.1%
0 714
 
7.0%
6 700
 
6.9%
7 657
 
6.5%
8 599
 
5.9%
9 555
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 19
48.7%
T 7
 
17.9%
A 6
 
15.4%
S 2
 
5.1%
C 1
 
2.6%
F 1
 
2.6%
P 1
 
2.6%
E 1
 
2.6%
K 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 1032
98.8%
@ 5
 
0.5%
/ 5
 
0.5%
. 2
 
0.2%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
10661
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2298
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2298
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 424
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39903
59.7%
Common 26891
40.2%
Latin 39
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3026
 
7.6%
2852
 
7.1%
2810
 
7.0%
2443
 
6.1%
2437
 
6.1%
2414
 
6.0%
2334
 
5.8%
2248
 
5.6%
1269
 
3.2%
1203
 
3.0%
Other values (351) 16867
42.3%
Common
ValueCountFrequency (%)
10661
39.6%
1 2511
 
9.3%
) 2298
 
8.5%
( 2298
 
8.5%
2 1548
 
5.8%
3 1188
 
4.4%
, 1032
 
3.8%
4 869
 
3.2%
5 822
 
3.1%
0 714
 
2.7%
Other values (10) 2950
 
11.0%
Latin
ValueCountFrequency (%)
B 19
48.7%
T 7
 
17.9%
A 6
 
15.4%
S 2
 
5.1%
C 1
 
2.6%
F 1
 
2.6%
P 1
 
2.6%
E 1
 
2.6%
K 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39903
59.7%
ASCII 26930
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10661
39.6%
1 2511
 
9.3%
) 2298
 
8.5%
( 2298
 
8.5%
2 1548
 
5.7%
3 1188
 
4.4%
, 1032
 
3.8%
4 869
 
3.2%
5 822
 
3.1%
0 714
 
2.7%
Other values (19) 2989
 
11.1%
Hangul
ValueCountFrequency (%)
3026
 
7.6%
2852
 
7.1%
2810
 
7.0%
2443
 
6.1%
2437
 
6.1%
2414
 
6.0%
2334
 
5.8%
2248
 
5.6%
1269
 
3.2%
1203
 
3.0%
Other values (351) 16867
42.3%

apvpermymd
Real number (ℝ)

SKEWED 

Distinct3633
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19959415
Minimum9710223
Maximum20210330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.5 KiB
2024-04-17T10:46:02.041011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9710223
5-th percentile19691176
Q119880109
median19980518
Q320060123
95-th percentile20171149
Maximum20210330
Range10500107
Interquartile range (IQR)180014

Descriptive statistics

Standard deviation201278.01
Coefficient of variation (CV)0.010084364
Kurtosis1362.133
Mean19959415
Median Absolute Deviation (MAD)90012
Skewness-26.901141
Sum9.8479755 × 1010
Variance4.0512838 × 1010
MonotonicityNot monotonic
2024-04-17T10:46:02.159127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19770830 35
 
0.7%
19660301 35
 
0.7%
20000420 19
 
0.4%
20020506 17
 
0.3%
20000623 13
 
0.3%
20030224 9
 
0.2%
19630630 9
 
0.2%
20030410 7
 
0.1%
19721129 7
 
0.1%
19630110 6
 
0.1%
Other values (3623) 4777
96.8%
ValueCountFrequency (%)
9710223 1
 
< 0.1%
19300722 1
 
< 0.1%
19610922 1
 
< 0.1%
19621202 1
 
< 0.1%
19630110 6
0.1%
19630522 1
 
< 0.1%
19630525 1
 
< 0.1%
19630529 4
0.1%
19630601 1
 
< 0.1%
19630622 1
 
< 0.1%
ValueCountFrequency (%)
20210330 1
 
< 0.1%
20210324 1
 
< 0.1%
20210318 1
 
< 0.1%
20210310 2
< 0.1%
20210309 1
 
< 0.1%
20210305 2
< 0.1%
20210304 1
 
< 0.1%
20210303 3
0.1%
20210302 1
 
< 0.1%
20210222 2
< 0.1%

dcbymd
Text

MISSING 

Distinct2166
Distinct (%)62.0%
Missing1441
Missing (%)29.2%
Memory size38.7 KiB
2024-04-17T10:46:02.412918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9507587
Min length4

Characters and Unicode

Total characters27772
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1538 ?
Unique (%)44.0%

Sample

1st row20180501
2nd row20121212
3rd row20151228
4th row20121212
5th row20080710
ValueCountFrequency (%)
20030715 58
 
1.7%
폐업일자 43
 
1.2%
20050214 41
 
1.2%
20031213 36
 
1.0%
20030305 33
 
0.9%
20020222 33
 
0.9%
20030221 32
 
0.9%
20030101 17
 
0.5%
20051011 16
 
0.5%
20061226 13
 
0.4%
Other values (2156) 3171
90.8%
2024-04-17T10:46:02.786639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9767
35.2%
2 5761
20.7%
1 4557
16.4%
3 1418
 
5.1%
5 1259
 
4.5%
9 1161
 
4.2%
4 1002
 
3.6%
7 948
 
3.4%
6 899
 
3.2%
8 828
 
3.0%
Other values (4) 172
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27600
99.4%
Other Letter 172
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9767
35.4%
2 5761
20.9%
1 4557
16.5%
3 1418
 
5.1%
5 1259
 
4.6%
9 1161
 
4.2%
4 1002
 
3.6%
7 948
 
3.4%
6 899
 
3.3%
8 828
 
3.0%
Other Letter
ValueCountFrequency (%)
43
25.0%
43
25.0%
43
25.0%
43
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27600
99.4%
Hangul 172
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9767
35.4%
2 5761
20.9%
1 4557
16.5%
3 1418
 
5.1%
5 1259
 
4.6%
9 1161
 
4.2%
4 1002
 
3.6%
7 948
 
3.4%
6 899
 
3.3%
8 828
 
3.0%
Hangul
ValueCountFrequency (%)
43
25.0%
43
25.0%
43
25.0%
43
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27600
99.4%
Hangul 172
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9767
35.4%
2 5761
20.9%
1 4557
16.5%
3 1418
 
5.1%
5 1259
 
4.6%
9 1161
 
4.2%
4 1002
 
3.6%
7 948
 
3.4%
6 899
 
3.3%
8 828
 
3.0%
Hangul
ValueCountFrequency (%)
43
25.0%
43
25.0%
43
25.0%
43
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4883 
휴업시작일자
 
51

Length

Max length6
Median length4
Mean length4.0206729
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4883
99.0%
휴업시작일자 51
 
1.0%

Length

2024-04-17T10:46:02.913163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:02.998290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4883
99.0%
휴업시작일자 51
 
1.0%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4883 
휴업종료일자
 
51

Length

Max length6
Median length4
Mean length4.0206729
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4883
99.0%
휴업종료일자 51
 
1.0%

Length

2024-04-17T10:46:03.106875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:03.202926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4883
99.0%
휴업종료일자 51
 
1.0%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4883 
재개업일자
 
51

Length

Max length5
Median length4
Mean length4.0103364
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4883
99.0%
재개업일자 51
 
1.0%

Length

2024-04-17T10:46:03.284719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:03.362543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4883
99.0%
재개업일자 51
 
1.0%

trdstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
02
3330 
01
1223 
영업/정상
 
257
폐업
 
119
영업상태
 
3

Length

Max length5
Median length2
Mean length2.1582894
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row02
2nd row02
3rd row02
4th row02
5th row02

Common Values

ValueCountFrequency (%)
02 3330
67.5%
01 1223
 
24.8%
영업/정상 257
 
5.2%
폐업 119
 
2.4%
영업상태 3
 
0.1%
<NA> 2
 
< 0.1%

Length

2024-04-17T10:46:03.441278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:03.524517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3330
67.5%
01 1223
 
24.8%
영업/정상 257
 
5.2%
폐업 119
 
2.4%
영업상태 3
 
0.1%
na 2
 
< 0.1%

dtlstatenm
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
폐업
3450 
영업
1484 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3450
69.9%
영업 1484
30.1%

Length

2024-04-17T10:46:03.614233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:03.685100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3450
69.9%
영업 1484
30.1%

x
Text

MISSING 

Distinct4009
Distinct (%)86.8%
Missing314
Missing (%)6.4%
Memory size38.7 KiB
2024-04-17T10:46:03.852910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.991558
Min length7

Characters and Unicode

Total characters92361
Distinct characters19
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3518 ?
Unique (%)76.1%

Sample

1st row384763.36249800000
2nd row385005.25775
3rd row385086.62014400000
4th row385447.404485
5th row385737.436336
ValueCountFrequency (%)
382169.305404 5
 
0.1%
389415.20340442 5
 
0.1%
387543.799105301 4
 
0.1%
379140.640735214 4
 
0.1%
400802.655281 4
 
0.1%
385892.507054 4
 
0.1%
384473.209419 4
 
0.1%
385517.559896 4
 
0.1%
385851.312113 4
 
0.1%
388076.092919 4
 
0.1%
Other values (3999) 4578
99.1%
2024-04-17T10:46:04.148542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20989
22.7%
0 14684
15.9%
3 9452
10.2%
8 7450
 
8.1%
9 6210
 
6.7%
7 4999
 
5.4%
1 4869
 
5.3%
5 4818
 
5.2%
6 4783
 
5.2%
2 4748
 
5.1%
Other values (9) 9359
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66734
72.3%
Space Separator 20989
 
22.7%
Other Punctuation 4617
 
5.0%
Other Letter 12
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Uppercase Letter 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14684
22.0%
3 9452
14.2%
8 7450
11.2%
9 6210
9.3%
7 4999
 
7.5%
1 4869
 
7.3%
5 4818
 
7.2%
6 4783
 
7.2%
2 4748
 
7.1%
4 4721
 
7.1%
Other Letter
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%
Space Separator
ValueCountFrequency (%)
20989
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4617
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 92346
> 99.9%
Hangul 12
 
< 0.1%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
20989
22.7%
0 14684
15.9%
3 9452
10.2%
8 7450
 
8.1%
9 6210
 
6.7%
7 4999
 
5.4%
1 4869
 
5.3%
5 4818
 
5.2%
6 4783
 
5.2%
2 4748
 
5.1%
Other values (4) 9344
10.1%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%
Latin
ValueCountFrequency (%)
X 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92349
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20989
22.7%
0 14684
15.9%
3 9452
10.2%
8 7450
 
8.1%
9 6210
 
6.7%
7 4999
 
5.4%
1 4869
 
5.3%
5 4818
 
5.2%
6 4783
 
5.2%
2 4748
 
5.1%
Other values (5) 9347
10.1%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%

y
Text

MISSING 

Distinct4009
Distinct (%)86.8%
Missing314
Missing (%)6.4%
Memory size38.7 KiB
2024-04-17T10:46:04.348071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.991558
Min length7

Characters and Unicode

Total characters92361
Distinct characters19
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3518 ?
Unique (%)76.1%

Sample

1st row179706.64036800000
2nd row179998.796394
3rd row180119.33406400000
4th row179824.590338
5th row180816.22011
ValueCountFrequency (%)
191928.498233 5
 
0.1%
193131.590860807 5
 
0.1%
185519.589265759 4
 
0.1%
180128.072887035 4
 
0.1%
189455.898675 4
 
0.1%
192110.101669 4
 
0.1%
179378.899808 4
 
0.1%
179676.666539 4
 
0.1%
181799.414753 4
 
0.1%
177016.065925 4
 
0.1%
Other values (3999) 4578
99.1%
2024-04-17T10:46:04.648745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20945
22.7%
0 14473
15.7%
1 9489
10.3%
8 7184
 
7.8%
9 6464
 
7.0%
7 5555
 
6.0%
2 4876
 
5.3%
3 4752
 
5.1%
4 4708
 
5.1%
6 4645
 
5.0%
Other values (9) 9270
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66778
72.3%
Space Separator 20945
 
22.7%
Other Punctuation 4617
 
5.0%
Other Letter 12
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Uppercase Letter 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14473
21.7%
1 9489
14.2%
8 7184
10.8%
9 6464
9.7%
7 5555
 
8.3%
2 4876
 
7.3%
3 4752
 
7.1%
4 4708
 
7.1%
6 4645
 
7.0%
5 4632
 
6.9%
Other Letter
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%
Space Separator
ValueCountFrequency (%)
20945
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4617
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 92346
> 99.9%
Hangul 12
 
< 0.1%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
20945
22.7%
0 14473
15.7%
1 9489
10.3%
8 7184
 
7.8%
9 6464
 
7.0%
7 5555
 
6.0%
2 4876
 
5.3%
3 4752
 
5.1%
4 4708
 
5.1%
6 4645
 
5.0%
Other values (4) 9255
10.0%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%
Latin
ValueCountFrequency (%)
Y 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92349
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20945
22.7%
0 14473
15.7%
1 9489
10.3%
8 7184
 
7.8%
9 6464
 
7.0%
7 5555
 
6.0%
2 4876
 
5.3%
3 4752
 
5.1%
4 4708
 
5.1%
6 4645
 
5.0%
Other values (5) 9258
10.0%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%

lastmodts
Real number (ℝ)

Distinct3209
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0088038 × 1013
Minimum1.9990218 × 1013
Maximum2.021033 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.5 KiB
2024-04-17T10:46:04.777157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile1.9990624 × 1013
Q12.0031002 × 1013
median2.0070831 × 1013
Q32.0131215 × 1013
95-th percentile2.0191116 × 1013
Maximum2.021033 × 1013
Range2.2011217 × 1011
Interquartile range (IQR)1.0021335 × 1011

Descriptive statistics

Standard deviation6.1719761 × 1010
Coefficient of variation (CV)0.0030724633
Kurtosis-1.152494
Mean2.0088038 × 1013
Median Absolute Deviation (MAD)4.0620142 × 1010
Skewness0.30893857
Sum9.9114381 × 1016
Variance3.8093289 × 1021
MonotonicityNot monotonic
2024-04-17T10:46:04.886638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030211000000 63
 
1.3%
20070501000000 54
 
1.1%
20031215000000 38
 
0.8%
20020424000000 38
 
0.8%
20030311000000 38
 
0.8%
20030502000000 37
 
0.7%
19990428000000 35
 
0.7%
20020423000000 34
 
0.7%
20060707000000 34
 
0.7%
20030318000000 33
 
0.7%
Other values (3199) 4530
91.8%
ValueCountFrequency (%)
19990218000000 1
 
< 0.1%
19990223000000 4
 
0.1%
19990224000000 1
 
< 0.1%
19990225000000 3
 
0.1%
19990302000000 11
0.2%
19990303000000 12
0.2%
19990304000000 20
0.4%
19990308000000 17
0.3%
19990309000000 5
 
0.1%
19990310000000 18
0.4%
ValueCountFrequency (%)
20210330165802 1
< 0.1%
20210329101926 1
< 0.1%
20210324102256 1
< 0.1%
20210322180239 1
< 0.1%
20210322165604 1
< 0.1%
20210318135628 1
< 0.1%
20210317154704 1
< 0.1%
20210317154655 1
< 0.1%
20210317144034 1
< 0.1%
20210317133229 1
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
일반이용업
4870 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0079043
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 4870
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-17T10:46:04.995942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:05.089013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4870
97.9%
이용업 40
 
0.8%
기타 40
 
0.8%
일반미용업 23
 
0.5%
na 1
 
< 0.1%

sitetel
Categorical

IMBALANCE 

Distinct37
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
051-123-1234
4815 
<NA>
 
65
전화번호
 
16
051 7526956
 
3
070 86729677
 
3
Other values (32)
 
32

Length

Max length12
Median length12
Mean length11.864005
Min length4

Unique

Unique32 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
051-123-1234 4815
97.6%
<NA> 65
 
1.3%
전화번호 16
 
0.3%
051 7526956 3
 
0.1%
070 86729677 3
 
0.1%
051 8070102 1
 
< 0.1%
051 243 3920 1
 
< 0.1%
051412 8217 1
 
< 0.1%
051803 9900 1
 
< 0.1%
051 896 7133 1
 
< 0.1%
Other values (27) 27
 
0.5%

Length

2024-04-17T10:46:05.187296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-123-1234 4815
96.6%
na 65
 
1.3%
051 30
 
0.6%
전화번호 16
 
0.3%
7526956 3
 
0.1%
070 3
 
0.1%
86729677 3
 
0.1%
807 2
 
< 0.1%
0885 1
 
< 0.1%
5142804 1
 
< 0.1%
Other values (45) 45
 
0.9%

bdngownsenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
3967 
임대
907 
건물소유구분명
 
38
자가
 
22

Length

Max length7
Median length4
Mean length3.6465343
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3967
80.4%
임대 907
 
18.4%
건물소유구분명 38
 
0.8%
자가 22
 
0.4%

Length

2024-04-17T10:46:05.293791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:05.370697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3967
80.4%
임대 907
 
18.4%
건물소유구분명 38
 
0.8%
자가 22
 
0.4%

bdngjisgflrcnt
Categorical

Distinct34
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
1766 
0
1181 
3
484 
4
421 
2
402 
Other values (29)
680 

Length

Max length6
Median length1
Mean length2.0944467
Min length1

Unique

Unique9 ?
Unique (%)0.2%

Sample

1st row1
2nd row3
3rd row4
4th row16
5th row6

Common Values

ValueCountFrequency (%)
<NA> 1766
35.8%
0 1181
23.9%
3 484
 
9.8%
4 421
 
8.5%
2 402
 
8.1%
5 237
 
4.8%
1 165
 
3.3%
6 84
 
1.7%
7 55
 
1.1%
8 28
 
0.6%
Other values (24) 111
 
2.2%

Length

2024-04-17T10:46:05.471641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1766
35.8%
0 1181
23.9%
3 484
 
9.8%
4 421
 
8.5%
2 402
 
8.1%
5 237
 
4.8%
1 165
 
3.3%
6 84
 
1.7%
7 55
 
1.1%
8 28
 
0.6%
Other values (24) 111
 
2.2%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
2282 
0
1670 
1
841 
2
 
87
3
 
22
Other values (7)
 
32

Length

Max length6
Median length1
Mean length2.3921767
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2282
46.3%
0 1670
33.8%
1 841
 
17.0%
2 87
 
1.8%
3 22
 
0.4%
5 15
 
0.3%
4 6
 
0.1%
6 4
 
0.1%
건물지하층수 4
 
0.1%
7 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2024-04-17T10:46:05.591256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2282
46.3%
0 1670
33.8%
1 841
 
17.0%
2 87
 
1.8%
3 22
 
0.4%
5 15
 
0.3%
4 6
 
0.1%
6 4
 
0.1%
건물지하층수 4
 
0.1%
7 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

maneipcnt
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4538 
0
 
357
1
 
32
남성종사자수
 
6
2
 
1

Length

Max length6
Median length4
Mean length3.765302
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4538
92.0%
0 357
 
7.2%
1 32
 
0.6%
남성종사자수 6
 
0.1%
2 1
 
< 0.1%

Length

2024-04-17T10:46:05.686203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:05.767744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4538
92.0%
0 357
 
7.2%
1 32
 
0.6%
남성종사자수 6
 
0.1%
2 1
 
< 0.1%

multusnupsoyn
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
False
4934 
ValueCountFrequency (%)
False 4934
100.0%
2024-04-17T10:46:05.833392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

balhansilyn
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
False
4934 
ValueCountFrequency (%)
False 4934
100.0%
2024-04-17T10:46:05.885889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

usejisgendflr
Categorical

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
2780 
1
752 
0
540 
2
466 
3
 
214
Other values (8)
 
182

Length

Max length6
Median length4
Mean length2.7182813
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row2
3rd row2
4th row3
5th row1

Common Values

ValueCountFrequency (%)
<NA> 2780
56.3%
1 752
 
15.2%
0 540
 
10.9%
2 466
 
9.4%
3 214
 
4.3%
4 81
 
1.6%
5 46
 
0.9%
사용끝지상층 27
 
0.5%
6 15
 
0.3%
7 7
 
0.1%
Other values (3) 6
 
0.1%

Length

2024-04-17T10:46:05.962193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2780
56.3%
1 752
 
15.2%
0 540
 
10.9%
2 466
 
9.4%
3 214
 
4.3%
4 81
 
1.6%
5 46
 
0.9%
사용끝지상층 27
 
0.5%
6 15
 
0.3%
7 7
 
0.1%
Other values (3) 6
 
0.1%

useunderendflr
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
3769 
0
855 
1
 
262
사용끝지하층
 
41
2
 
6

Length

Max length6
Median length4
Mean length3.3331982
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3769
76.4%
0 855
 
17.3%
1 262
 
5.3%
사용끝지하층 41
 
0.8%
2 6
 
0.1%
4 1
 
< 0.1%

Length

2024-04-17T10:46:06.059892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:06.143962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3769
76.4%
0 855
 
17.3%
1 262
 
5.3%
사용끝지하층 41
 
0.8%
2 6
 
0.1%
4 1
 
< 0.1%

usejisgstflr
Categorical

Distinct15
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
2158 
0
969 
1
857 
2
497 
3
253 
Other values (10)
 
200

Length

Max length7
Median length1
Mean length2.336441
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row2
3rd row2
4th row3
5th row1

Common Values

ValueCountFrequency (%)
<NA> 2158
43.7%
0 969
19.6%
1 857
 
17.4%
2 497
 
10.1%
3 253
 
5.1%
4 89
 
1.8%
5 56
 
1.1%
6 19
 
0.4%
사용시작지상층 19
 
0.4%
7 5
 
0.1%
Other values (5) 12
 
0.2%

Length

2024-04-17T10:46:06.239237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2158
43.7%
0 969
19.6%
1 857
 
17.4%
2 497
 
10.1%
3 253
 
5.1%
4 89
 
1.8%
5 56
 
1.1%
6 19
 
0.4%
사용시작지상층 19
 
0.4%
7 5
 
0.1%
Other values (5) 12
 
0.2%

useunderstflr
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
3112 
0
1462 
1
 
308
사용시작지하층
 
36
2
 
15

Length

Max length7
Median length4
Mean length2.9361573
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3112
63.1%
0 1462
29.6%
1 308
 
6.2%
사용시작지하층 36
 
0.7%
2 15
 
0.3%
22 1
 
< 0.1%

Length

2024-04-17T10:46:06.338086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:06.429631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3112
63.1%
0 1462
29.6%
1 308
 
6.2%
사용시작지하층 36
 
0.7%
2 15
 
0.3%
22 1
 
< 0.1%

washmccnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
3428 
0
1502 
세탁기수
 
4

Length

Max length4
Median length4
Mean length3.086745
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3428
69.5%
0 1502
30.4%
세탁기수 4
 
0.1%

Length

2024-04-17T10:46:06.526341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:06.608416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3428
69.5%
0 1502
30.4%
세탁기수 4
 
0.1%

yangsilcnt
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
2759 
0
2170 
양실수
 
4
38
 
1

Length

Max length4
Median length4
Mean length2.6793677
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2759
55.9%
0 2170
44.0%
양실수 4
 
0.1%
38 1
 
< 0.1%

Length

2024-04-17T10:46:06.693893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:06.777712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2759
55.9%
0 2170
44.0%
양실수 4
 
0.1%
38 1
 
< 0.1%

wmeipcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4549 
0
 
361
1
 
18
여성종사자수
 
6

Length

Max length6
Median length4
Mean length3.7719903
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4549
92.2%
0 361
 
7.3%
1 18
 
0.4%
여성종사자수 6
 
0.1%

Length

2024-04-17T10:46:06.863995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:06.938422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4549
92.2%
0 361
 
7.3%
1 18
 
0.4%
여성종사자수 6
 
0.1%

yoksilcnt
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
2759 
0
2170 
욕실수
 
4
2
 
1

Length

Max length4
Median length4
Mean length2.679165
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2759
55.9%
0 2170
44.0%
욕실수 4
 
0.1%
2 1
 
< 0.1%

Length

2024-04-17T10:46:07.023085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:07.106207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2759
55.9%
0 2170
44.0%
욕실수 4
 
0.1%
2 1
 
< 0.1%

sntuptaenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
일반이용업
4870 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0079043
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 4870
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-17T10:46:07.206433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:07.555260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4870
97.9%
이용업 40
 
0.8%
기타 40
 
0.8%
일반미용업 23
 
0.5%
na 1
 
< 0.1%

chaircnt
Categorical

Distinct17
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
2
1334 
3
887 
<NA>
613 
4
592 
0
339 
Other values (12)
1169 

Length

Max length4
Median length1
Mean length1.382651
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row4
3rd row2
4th row7
5th row4

Common Values

ValueCountFrequency (%)
2 1334
27.0%
3 887
18.0%
<NA> 613
12.4%
4 592
12.0%
0 339
 
6.9%
1 329
 
6.7%
5 264
 
5.4%
6 180
 
3.6%
7 171
 
3.5%
8 111
 
2.2%
Other values (7) 114
 
2.3%

Length

2024-04-17T10:46:07.637744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 1334
27.0%
3 887
18.0%
na 613
12.4%
4 592
12.0%
0 339
 
6.9%
1 329
 
6.7%
5 264
 
5.4%
6 180
 
3.6%
7 171
 
3.5%
8 111
 
2.2%
Other values (7) 114
 
2.3%

cndpermstymd
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4881 
조건부허가시작일자
 
51
20050520
 
1
20050414
 
1

Length

Max length9
Median length4
Mean length4.0533036
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row20050520
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4881
98.9%
조건부허가시작일자 51
 
1.0%
20050520 1
 
< 0.1%
20050414 1
 
< 0.1%

Length

2024-04-17T10:46:07.732895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:07.809421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4881
98.9%
조건부허가시작일자 51
 
1.0%
20050520 1
 
< 0.1%
20050414 1
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4882 
조건부허가신고사유
 
51
가설건축물
 
1

Length

Max length9
Median length4
Mean length4.0518849
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4882
98.9%
조건부허가신고사유 51
 
1.0%
가설건축물 1
 
< 0.1%

Length

2024-04-17T10:46:07.896324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:07.972214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4882
98.9%
조건부허가신고사유 51
 
1.0%
가설건축물 1
 
< 0.1%

cndpermendymd
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4881 
조건부허가종료일자
 
51
20060425
 
1
20050414
 
1

Length

Max length9
Median length4
Mean length4.0533036
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row20060425
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4881
98.9%
조건부허가종료일자 51
 
1.0%
20060425 1
 
< 0.1%
20050414 1
 
< 0.1%

Length

2024-04-17T10:46:08.055596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:08.143462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4881
98.9%
조건부허가종료일자 51
 
1.0%
20060425 1
 
< 0.1%
20050414 1
 
< 0.1%

abedcnt
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
3629 
0
1293 
2
 
4
침대수
 
4
3
 
2
Other values (2)
 
2

Length

Max length4
Median length4
Mean length3.2081475
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3629
73.6%
0 1293
 
26.2%
2 4
 
0.1%
침대수 4
 
0.1%
3 2
 
< 0.1%
1 1
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-17T10:46:08.238300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:08.334843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3629
73.6%
0 1293
 
26.2%
2 4
 
0.1%
침대수 4
 
0.1%
3 2
 
< 0.1%
1 1
 
< 0.1%
5 1
 
< 0.1%

hanshilcnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
2760 
0
2170 
한실수
 
4

Length

Max length4
Median length4
Mean length2.679773
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2760
55.9%
0 2170
44.0%
한실수 4
 
0.1%

Length

2024-04-17T10:46:08.430380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:08.524832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2760
55.9%
0 2170
44.0%
한실수 4
 
0.1%

rcvdryncnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
3611 
0
1319 
회수건조수
 
4

Length

Max length5
Median length4
Mean length3.1988245
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3611
73.2%
0 1319
 
26.7%
회수건조수 4
 
0.1%

Length

2024-04-17T10:46:08.637789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:08.744626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3611
73.2%
0 1319
 
26.7%
회수건조수 4
 
0.1%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
2021-04-01 05:25:03
4934 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-04-01 05:25:03
2nd row2021-04-01 05:25:03
3rd row2021-04-01 05:25:03
4th row2021-04-01 05:25:03
5th row2021-04-01 05:25:03

Common Values

ValueCountFrequency (%)
2021-04-01 05:25:03 4934
100.0%

Length

2024-04-17T10:46:08.824911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:46:08.893075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-04-01 4934
50.0%
05:25:03 4934
50.0%

Sample

skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
0532500003250000-203-1980-0047805_19_01_PI2018-08-31 23:59:59.0<NA>태양탕구내600046부산광역시 중구 남포동6가 115-5번지 (지하1층)48982부산광역시 중구 자갈치로15번길 4, 지하1층 (남포동6가)1980120220180501<NA><NA><NA>02폐업384763.36249800000179706.6403680000020180501090321일반이용업051-123-1234임대11<NA>NN010100<NA>0일반이용업2<NA><NA><NA>0002021-04-01 05:25:03
1632500003250000-203-2005-0000405_19_01_PI2018-08-31 23:59:59.0<NA>국사 이용원600061부산광역시 중구 신창동1가 35-2번지 (2층)<NA><NA>2005052020121212<NA><NA><NA>02폐업385005.25775179998.79639420050520000000일반이용업051-123-1234<NA>3<NA><NA>NN2<NA>2<NA><NA><NA><NA><NA>일반이용업420050520가설건축물20060425<NA><NA><NA>2021-04-01 05:25:03
2732500003250000-203-2005-0000505_19_01_PI2018-08-31 23:59:59.0<NA>녹수탕구내이용원600062부산광역시 중구 신창동2가 21-2번지 (2층)48947부산광역시 중구 광복로43번길 12, 2층 (신창동2가)2005053120151228<NA><NA><NA>02폐업385086.62014400000180119.3340640000020130208134228일반이용업051-123-1234<NA>41<NA>NN202000<NA>0일반이용업2<NA><NA><NA>0002021-04-01 05:25:03
3832500003250000-203-1972-0044305_19_01_PI2018-08-31 23:59:59.0<NA>부산호텔이용원600022부산광역시 중구 동광동2가 12-1번지 외11필지<NA><NA>1972103120121212<NA><NA><NA>02폐업385447.404485179824.59033820060306000000일반이용업051-123-1234임대161<NA>NN3<NA>3<NA><NA><NA><NA><NA>일반이용업7<NA><NA><NA><NA><NA><NA>2021-04-01 05:25:03
4932500003250000-203-2005-0000105_19_01_PI2018-08-31 23:59:59.0<NA>터프가위 이용원600816부산광역시 중구 중앙동4가 78-20번지 (1층)<NA><NA>2005011920080710<NA><NA><NA>02폐업385737.436336180816.2201120050119000000일반이용업051-123-1234<NA>61<NA>NN1<NA>1<NA><NA><NA><NA><NA>일반이용업4<NA><NA><NA><NA><NA><NA>2021-04-01 05:25:03
51032500003250000-203-2005-0000205_19_01_PI2018-08-31 23:59:59.0<NA>알지 이용원600816부산광역시 중구 중앙동4가 84-26번지 (지하1층)<NA><NA>2005031420060201<NA><NA><NA>02폐업385685.971895180523.35229820050314000000일반이용업051-123-1234<NA>51<NA>NN<NA>1<NA>1<NA><NA><NA><NA>일반이용업7<NA><NA><NA><NA><NA><NA>2021-04-01 05:25:03
61132500003250000-203-1989-0051705_19_01_PI2018-08-31 23:59:59.0<NA>남성H전문600800부산광역시 중구 대청동4가 85-1번지 (3층)48933부산광역시 중구 중구로 90, 3층 (대청동4가)19890928<NA><NA><NA><NA>01영업385152.87363900000180604.3028620000020171110105721일반이용업051-123-1234임대41<NA>NN303000<NA>0일반이용업2<NA><NA><NA>0002021-04-01 05:25:03
71232500003250000-203-2002-0001005_19_01_PI2018-08-31 23:59:59.0<NA>미도이용원600807부산광역시 중구 부평동2가 27-4번지<NA><NA>2002052320090805<NA><NA><NA>02폐업384647.050294179711.51617220070117000000일반이용업051-123-1234임대4<NA><NA>NN2<NA>2<NA><NA><NA><NA><NA>일반이용업6<NA><NA><NA><NA><NA><NA>2021-04-01 05:25:03
81332500003250000-203-1979-0046105_19_01_PI2018-08-31 23:59:59.0<NA>부남600025부산광역시 중구 동광동5가 12-165번지48921부산광역시 중구 동영로 18 (동광동5가)19790623<NA><NA><NA><NA>01영업385465.80651300000181014.9432670000020131230110555일반이용업051-123-1234임대31<NA>NN101000<NA>0일반이용업5<NA><NA><NA>0002021-04-01 05:25:03
91432500003250000-203-1979-0046205_19_01_PI2018-08-31 23:59:59.0<NA>부전600025부산광역시 중구 동광동5가 13-68번지 (1층)48918부산광역시 중구 동영로 11, 1층 (동광동5가)19791231<NA><NA><NA><NA>01영업385407.17813300000180988.5592120000020130208125257일반이용업051-123-1234임대10<NA>NN101000<NA>0일반이용업4<NA><NA><NA>0002021-04-01 05:25:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
4924708133800003380000-203-2021-0000105_19_01_PU2021-03-11 02:40:00.0이용업강남사우나이용원613807부산광역시 수영구 광안동 716-5 강남사우나48248부산광역시 수영구 광서로 33, 강남사우나 4층 (광안동)2021030520210309<NA><NA><NA>폐업폐업392251.396025486187062.88020845720210309132017일반이용업<NA><NA>000NN4<NA>4<NA>0000일반이용업1<NA><NA><NA>0002021-04-01 05:25:03
4925708233800003380000-203-2021-0000105_19_01_PU2021-03-11 02:40:00.0이용업강남사우나이용원613807부산광역시 수영구 광안동 716-5 강남사우나48248부산광역시 수영구 광서로 33, 강남사우나 4층 (광안동)2021030520210309<NA><NA><NA>폐업폐업392251.396025486187062.88020845720210309132017일반이용업<NA><NA>000NN4<NA>4<NA>0000일반이용업1<NA><NA><NA>0002021-04-01 05:25:03
4926708332800003280000-203-2021-0000305_19_01_PI2021-03-11 00:23:00.0이용업긱스(geeks)606042부산광역시 영도구 영선동2가 44-249056부산광역시 영도구 영선대로 67 (영선동2가)20210309폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업386100.884001403178372.43703474920210309111641일반이용업전화번호건물소유구분명000NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층0000일반이용업4조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-04-01 05:25:03
4927708432900003290000-203-2021-0000805_19_01_PI2021-03-12 00:23:00.0이용업태후사랑614882부산광역시 부산진구 양정동 406-6 부원맨숀47210부산광역시 부산진구 중앙대로941번길 11, 1층 13호 (양정동, 부원맨숀)20210310폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업388596.435735087188048.52433618920210310164736일반이용업전화번호건물소유구분명610NN1사용끝지하층1사용시작지하층0000일반이용업2조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-04-01 05:25:03
4928708532900003290000-203-2021-0000705_19_01_PI2021-03-12 00:23:00.0이용업가야남성컷트클럽614803부산광역시 부산진구 가야동 275-547330부산광역시 부산진구 가야대로588번길 15, B1층 호 (가야동)20210310<NA><NA><NA><NA>영업/정상영업385444.715910317185760.1511629520210310154649일반이용업<NA>임대210NN<NA>1<NA>10000일반이용업3<NA><NA><NA>0002021-04-01 05:25:03
4929708633100003310000-203-2021-0000105_19_01_PI2021-03-20 00:22:59.0이용업못골이용원608808부산광역시 남구 대연동 1378 못골대중사우나48445부산광역시 남구 못골번영로 6, 못골대중사우나 4층 (대연동)20210318폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업390356.030587687183836.08928744920210318135628일반이용업전화번호건물소유구분명000NN4사용끝지하층4사용시작지하층0000일반이용업2조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-04-01 05:25:03
4930708733500003350000-203-2021-0000405_19_01_PI2021-03-26 00:22:59.0이용업희망609847부산광역시 금정구 구서동 258-646243부산광역시 금정구 금강로 458, 1층 (구서동)20210324폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업390036.897951263196340.38717702820210324102256일반이용업전화번호건물소유구분명000NN1사용끝지하층1사용시작지하층0010일반이용업3조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-04-01 05:25:03
4931708833000003300000-203-2021-0000205_19_01_PI2021-04-01 00:22:58.0이용업레드폴바버샵607716부산광역시 동래구 온천동 502-3 롯데백화점47727부산광역시 동래구 중앙대로 1393, 롯데백화점 4층 (온천동)20210330폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업389097.800933845192260.81164826320210330165802일반이용업전화번호건물소유구분명건물지상층수건물지하층수남성종사자수NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층세탁기수양실수여성종사자수욕실수일반이용업의자수조건부허가시작일자조건부허가신고사유조건부허가종료일자침대수한실수회수건조수2021-04-01 05:25:03
4932707232900003290000-203-2021-0000405_19_01_PI2021-02-24 00:23:01.0이용업올멋614817부산광역시 부산진구 당감동 238-5347182부산광역시 부산진구 백양대로60번길 34, 1층 (당감동)20210222<NA><NA><NA><NA>영업/정상영업386028.073030716186868.3391381420210222104030일반이용업<NA>임대200NN1<NA>1<NA>0000일반이용업2<NA><NA><NA>0002021-04-01 05:25:03
4933707533700003370000-203-2021-0000105_19_01_PI2021-02-24 00:23:01.0이용업머스마611812부산광역시 연제구 연산동 488-3547570부산광역시 연제구 고분로242번길 34, 101호 (연산동)20210222<NA><NA><NA><NA>영업/정상영업391987.811458421189111.23857948920210222140400일반이용업<NA>임대400NN1<NA>1<NA>0000일반이용업2<NA><NA><NA>0002021-04-01 05:25:03