Overview

Dataset statistics

Number of variables47
Number of observations4938
Missing cells7420
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
Text8
Categorical30
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 (64.2%)Imbalance
opnsvcnm is highly imbalanced (57.1%)Imbalance
clgstdt is highly imbalanced (90.5%)Imbalance
clgenddt is highly imbalanced (90.5%)Imbalance
ropnymd is highly imbalanced (90.5%)Imbalance
trdstatenm is highly imbalanced (50.9%)Imbalance
uptaenm is highly imbalanced (94.3%)Imbalance
bdngownsenm is highly imbalanced (59.9%)Imbalance
bdngunderflrcnt is highly imbalanced (53.1%)Imbalance
maneipcnt is highly imbalanced (80.3%)Imbalance
useunderendflr is highly imbalanced (59.8%)Imbalance
useunderstflr is highly imbalanced (50.7%)Imbalance
wmeipcnt is highly imbalanced (78.2%)Imbalance
sntuptaenm is highly imbalanced (94.3%)Imbalance
cndpermstymd is highly imbalanced (95.0%)Imbalance
cndpermntwhy is highly imbalanced (93.8%)Imbalance
cndpermendymd is highly imbalanced (95.0%)Imbalance
abedcnt is highly imbalanced (69.1%)Imbalance
rdnpostno has 2660 (53.9%) missing valuesMissing
rdnwhladdr has 2604 (52.7%) missing valuesMissing
dcbymd has 1430 (29.0%) missing valuesMissing
x has 314 (6.4%) missing valuesMissing
y has 314 (6.4%) missing valuesMissing
sitetel has 71 (1.4%) missing valuesMissing
apvpermymd is highly skewed (γ1 = -26.86271738)Skewed
skey has unique valuesUnique

Reproduction

Analysis started2024-04-17 01:45:41.118562
Analysis finished2024-04-17 01:45:42.386576
Duration1.27 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct4938
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2520.0634
Minimum1
Maximum7092
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.5 KiB
2024-04-17T10:45:42.440730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile247.85
Q11235.25
median2469.5
Q33703.75
95-th percentile4691.15
Maximum7092
Range7091
Interquartile range (IQR)2468.5

Descriptive statistics

Standard deviation1533.2855
Coefficient of variation (CV)0.60843134
Kurtosis-0.41628296
Mean2520.0634
Median Absolute Deviation (MAD)1234.5
Skewness0.3391629
Sum12444073
Variance2350964.6
MonotonicityNot monotonic
2024-04-17T10:45:42.554181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 1
 
< 0.1%
3291 1
 
< 0.1%
3298 1
 
< 0.1%
3297 1
 
< 0.1%
3296 1
 
< 0.1%
3295 1
 
< 0.1%
3294 1
 
< 0.1%
3293 1
 
< 0.1%
3292 1
 
< 0.1%
3290 1
 
< 0.1%
Other values (4928) 4928
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 (%)
7092 1
< 0.1%
7091 1
< 0.1%
7090 1
< 0.1%
7089 1
< 0.1%
7088 1
< 0.1%
7087 1
< 0.1%
7086 1
< 0.1%
7085 1
< 0.1%
7084 1
< 0.1%
7083 1
< 0.1%

opnsfteamcode
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3324459.3
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.5 KiB
2024-04-17T10:45:42.663791image/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 deviation40393.563
Coefficient of variation (CV)0.012150416
Kurtosis-0.9414021
Mean3324459.3
Median Absolute Deviation (MAD)30000
Skewness0.06220914
Sum1.641618 × 1010
Variance1.6316399 × 109
MonotonicityNot monotonic
2024-04-17T10:45:42.760226image/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 419
8.5%
3320000 410
 
8.3%
3330000 393
 
8.0%
3350000 380
 
7.7%
3390000 338
 
6.8%
3370000 328
 
6.6%
3310000 323
 
6.5%
3380000 284
 
5.8%
Other values (6) 1046
21.2%
ValueCountFrequency (%)
3250000 167
 
3.4%
3260000 213
4.3%
3270000 257
5.2%
3280000 211
4.3%
3290000 514
10.4%
3300000 419
8.5%
3310000 323
6.5%
3320000 410
8.3%
3330000 393
8.0%
3340000 503
10.2%
ValueCountFrequency (%)
3400000 110
 
2.2%
3390000 338
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

Distinct4900
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
2024-04-17T10:45:42.937468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters108636
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

Unique4877 ?
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 (%)
3320000-203-2018-00006 3
 
0.1%
3290000-203-2020-00004 3
 
0.1%
3290000-203-2019-00008 3
 
0.1%
3390000-203-2019-00006 3
 
0.1%
3390000-203-2017-00003 3
 
0.1%
3260000-203-2019-00003 3
 
0.1%
3290000-203-2019-00003 3
 
0.1%
3340000-203-2019-00006 3
 
0.1%
3320000-203-2019-00001 3
 
0.1%
3340000-203-2019-00003 3
 
0.1%
Other values (4890) 4908
99.4%
2024-04-17T10:45:43.211570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43424
40.0%
3 15500
 
14.3%
- 14814
 
13.6%
2 10945
 
10.1%
1 6186
 
5.7%
9 6052
 
5.6%
8 2666
 
2.5%
7 2441
 
2.2%
4 2336
 
2.2%
6 2137
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93822
86.4%
Dash Punctuation 14814
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43424
46.3%
3 15500
 
16.5%
2 10945
 
11.7%
1 6186
 
6.6%
9 6052
 
6.5%
8 2666
 
2.8%
7 2441
 
2.6%
4 2336
 
2.5%
6 2137
 
2.3%
5 2135
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 14814
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108636
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43424
40.0%
3 15500
 
14.3%
- 14814
 
13.6%
2 10945
 
10.1%
1 6186
 
5.7%
9 6052
 
5.6%
8 2666
 
2.5%
7 2441
 
2.2%
4 2336
 
2.2%
6 2137
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108636
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43424
40.0%
3 15500
 
14.3%
- 14814
 
13.6%
2 10945
 
10.1%
1 6186
 
5.7%
9 6052
 
5.6%
8 2666
 
2.5%
7 2441
 
2.2%
4 2336
 
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
4938 

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 4938
100.0%

Length

2024-04-17T10:45:43.327441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:43.403779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 4938
100.0%

updategbn
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
I
4603 
U
 
335

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 4603
93.2%
U 335
 
6.8%

Length

2024-04-17T10:45:43.475567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:43.545950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4603
93.2%
u 335
 
6.8%

updatedt
Date

Distinct279
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
Minimum2018-08-31 23:59:59
Maximum2021-04-29 02:40:00
2024-04-17T10:45:43.632402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T10:45:43.740420image/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>
4505 
이용업
 
433

Length

Max length4
Median length4
Mean length3.9123127
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> 4505
91.2%
이용업 433
 
8.8%

Length

2024-04-17T10:45:43.845753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:43.926043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4505
91.2%
이용업 433
 
8.8%

bplcnm
Text

Distinct3324
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
2024-04-17T10:45:44.154310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length4.7673147
Min length1

Characters and Unicode

Total characters23541
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

Unique2629 ?
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 (3178) 5046
88.3%
2024-04-17T10:45:44.528050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 2090
 
8.9%
용 2019
 
8.6%
원 1928
 
8.2%
탕 977
 
4.2%
내 840
 
3.6%
791
 
3.4%
구 584
 
2.5%
성 480
 
2.0%
트 406
 
1.7%
대 391
 
1.7%
Other values (556) 13035
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22264
94.6%
Space Separator 791
 
3.4%
Uppercase Letter 158
 
0.7%
Lowercase Letter 133
 
0.6%
Open Punctuation 66
 
0.3%
Close Punctuation 66
 
0.3%
Decimal Number 37
 
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 (%)
이 2090
 
9.4%
용 2019
 
9.1%
원 1928
 
8.7%
탕 977
 
4.4%
내 840
 
3.8%
구 584
 
2.6%
성 480
 
2.2%
트 406
 
1.8%
대 391
 
1.8%
수 342
 
1.5%
Other values (497) 12207
54.8%
Uppercase Letter
ValueCountFrequency (%)
B 20
12.7%
O 14
 
8.9%
E 14
 
8.9%
R 13
 
8.2%
H 12
 
7.6%
S 12
 
7.6%
A 8
 
5.1%
M 8
 
5.1%
L 7
 
4.4%
P 7
 
4.4%
Other values (12) 43
27.2%
Lowercase Letter
ValueCountFrequency (%)
e 18
13.5%
r 15
11.3%
h 11
8.3%
s 11
8.3%
i 10
 
7.5%
b 9
 
6.8%
a 9
 
6.8%
o 8
 
6.0%
k 8
 
6.0%
n 7
 
5.3%
Other values (8) 27
20.3%
Decimal Number
ValueCountFrequency (%)
2 12
32.4%
8 10
27.0%
1 8
21.6%
5 3
 
8.1%
9 2
 
5.4%
4 1
 
2.7%
3 1
 
2.7%
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 (%)
791
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22261
94.6%
Common 986
 
4.2%
Latin 291
 
1.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 2090
 
9.4%
용 2019
 
9.1%
원 1928
 
8.7%
탕 977
 
4.4%
내 840
 
3.8%
구 584
 
2.6%
성 480
 
2.2%
트 406
 
1.8%
대 391
 
1.8%
수 342
 
1.5%
Other values (494) 12204
54.8%
Latin
ValueCountFrequency (%)
B 20
 
6.9%
e 18
 
6.2%
r 15
 
5.2%
O 14
 
4.8%
E 14
 
4.8%
R 13
 
4.5%
H 12
 
4.1%
S 12
 
4.1%
h 11
 
3.8%
s 11
 
3.8%
Other values (30) 151
51.9%
Common
ValueCountFrequency (%)
791
80.2%
( 66
 
6.7%
) 66
 
6.7%
2 12
 
1.2%
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 (%)
秀 1
33.3%
子 1
33.3%
男 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22261
94.6%
ASCII 1276
 
5.4%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 2090
 
9.4%
용 2019
 
9.1%
원 1928
 
8.7%
탕 977
 
4.4%
내 840
 
3.8%
구 584
 
2.6%
성 480
 
2.2%
트 406
 
1.8%
대 391
 
1.8%
수 342
 
1.5%
Other values (494) 12204
54.8%
ASCII
ValueCountFrequency (%)
791
62.0%
( 66
 
5.2%
) 66
 
5.2%
B 20
 
1.6%
e 18
 
1.4%
r 15
 
1.2%
O 14
 
1.1%
E 14
 
1.1%
R 13
 
1.0%
H 12
 
0.9%
Other values (48) 247
 
19.4%
CJK
ValueCountFrequency (%)
秀 1
33.3%
子 1
33.3%
男 1
33.3%
None
ValueCountFrequency (%)
· 1
100.0%

sitepostno
Real number (ℝ)

Distinct775
Distinct (%)15.8%
Missing24
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean610460.53
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.5 KiB
2024-04-17T10:45:44.645303image/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 deviation5298.0796
Coefficient of variation (CV)0.0086788241
Kurtosis-1.0219831
Mean610460.53
Median Absolute Deviation (MAD)4960
Skewness-0.19086712
Sum2.999803 × 109
Variance28069647
MonotonicityNot monotonic
2024-04-17T10:45:44.774462image/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%
617818 24
 
0.5%
607826 24
 
0.5%
616807 23
 
0.5%
604813 22
 
0.4%
611803 22
 
0.4%
Other values (765) 4656
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%

sitewhladdr
Text

Distinct4313
Distinct (%)87.4%
Missing3
Missing (%)0.1%
Memory size38.7 KiB
2024-04-17T10:45:45.027100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length48
Mean length24.66079
Min length7

Characters and Unicode

Total characters121701
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

Unique3846 ?
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 4934
 
22.3%
t통b반 768
 
3.5%
부산진구 514
 
2.3%
사하구 505
 
2.3%
동래구 419
 
1.9%
북구 412
 
1.9%
해운대구 393
 
1.8%
금정구 380
 
1.7%
사상구 338
 
1.5%
연제구 326
 
1.5%
Other values (4665) 13147
59.4%
2024-04-17T10:45:45.398775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22008
18.1%
산 5856
 
4.8%
부 5809
 
4.8%
동 5805
 
4.8%
광 5105
 
4.2%
1 5093
 
4.2%
구 5067
 
4.2%
시 4960
 
4.1%
역 4940
 
4.1%
지 4930
 
4.1%
Other values (359) 52128
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69589
57.2%
Decimal Number 23512
 
19.3%
Space Separator 22008
 
18.1%
Dash Punctuation 4479
 
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 (%)
산 5856
 
8.4%
부 5809
 
8.3%
동 5805
 
8.3%
광 5105
 
7.3%
구 5067
 
7.3%
시 4960
 
7.1%
역 4940
 
7.1%
지 4930
 
7.1%
번 4730
 
6.8%
사 957
 
1.4%
Other values (327) 21430
30.8%
Uppercase Letter
ValueCountFrequency (%)
B 788
49.7%
T 772
48.7%
A 11
 
0.7%
C 2
 
0.1%
S 2
 
0.1%
G 2
 
0.1%
F 2
 
0.1%
L 2
 
0.1%
P 2
 
0.1%
E 1
 
0.1%
Other values (2) 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 5093
21.7%
2 3174
13.5%
3 2722
11.6%
4 2247
9.6%
5 2189
9.3%
6 1731
 
7.4%
0 1716
 
7.3%
8 1662
 
7.1%
7 1610
 
6.8%
9 1368
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 76
86.4%
@ 6
 
6.8%
/ 3
 
3.4%
. 2
 
2.3%
& 1
 
1.1%
Space Separator
ValueCountFrequency (%)
22008
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4479
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 69587
57.2%
Common 50526
41.5%
Latin 1586
 
1.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 5856
 
8.4%
부 5809
 
8.3%
동 5805
 
8.3%
광 5105
 
7.3%
구 5067
 
7.3%
시 4960
 
7.1%
역 4940
 
7.1%
지 4930
 
7.1%
번 4730
 
6.8%
사 957
 
1.4%
Other values (326) 21428
30.8%
Common
ValueCountFrequency (%)
22008
43.6%
1 5093
 
10.1%
- 4479
 
8.9%
2 3174
 
6.3%
3 2722
 
5.4%
4 2247
 
4.4%
5 2189
 
4.3%
6 1731
 
3.4%
0 1716
 
3.4%
8 1662
 
3.3%
Other values (10) 3505
 
6.9%
Latin
ValueCountFrequency (%)
B 788
49.7%
T 772
48.7%
A 11
 
0.7%
C 2
 
0.1%
S 2
 
0.1%
G 2
 
0.1%
F 2
 
0.1%
L 2
 
0.1%
P 2
 
0.1%
E 1
 
0.1%
Other values (2) 2
 
0.1%
Han
ValueCountFrequency (%)
內 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69587
57.2%
ASCII 52112
42.8%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22008
42.2%
1 5093
 
9.8%
- 4479
 
8.6%
2 3174
 
6.1%
3 2722
 
5.2%
4 2247
 
4.3%
5 2189
 
4.2%
6 1731
 
3.3%
0 1716
 
3.3%
8 1662
 
3.2%
Other values (22) 5091
 
9.8%
Hangul
ValueCountFrequency (%)
산 5856
 
8.4%
부 5809
 
8.3%
동 5805
 
8.3%
광 5105
 
7.3%
구 5067
 
7.3%
시 4960
 
7.1%
역 4940
 
7.1%
지 4930
 
7.1%
번 4730
 
6.8%
사 957
 
1.4%
Other values (326) 21428
30.8%
CJK
ValueCountFrequency (%)
內 2
100.0%

rdnpostno
Real number (ℝ)

MISSING 

Distinct1152
Distinct (%)50.6%
Missing2660
Missing (%)53.9%
Infinite0
Infinite (%)0.0%
Mean47830.666
Minimum46002
Maximum49525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.5 KiB
2024-04-17T10:45:45.514409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46243
Q147008.25
median47794.5
Q348735
95-th percentile49407
Maximum49525
Range3523
Interquartile range (IQR)1726.75

Descriptive statistics

Standard deviation1012.8149
Coefficient of variation (CV)0.021175011
Kurtosis-1.1214373
Mean47830.666
Median Absolute Deviation (MAD)800
Skewness0.022584441
Sum1.0895826 × 108
Variance1025794
MonotonicityNot monotonic
2024-04-17T10:45:45.631315image/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%
49217 7
 
0.1%
48445 7
 
0.1%
48501 7
 
0.1%
Other values (1142) 2192
44.4%
(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 

Distinct2212
Distinct (%)94.8%
Missing2604
Missing (%)52.7%
Memory size38.7 KiB
2024-04-17T10:45:45.944879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length54
Mean length28.697087
Min length17

Characters and Unicode

Total characters66979
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 (%)90.6%

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 2334
 
17.9%
1층 278
 
2.1%
부산진구 277
 
2.1%
동래구 225
 
1.7%
사하구 220
 
1.7%
사상구 194
 
1.5%
금정구 183
 
1.4%
해운대구 178
 
1.4%
남구 163
 
1.3%
북구 154
 
1.2%
Other values (2612) 8810
67.7%
2024-04-17T10:45:46.356520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10686
 
16.0%
동 3031
 
4.5%
부 2856
 
4.3%
산 2814
 
4.2%
1 2517
 
3.8%
광 2447
 
3.7%
시 2441
 
3.6%
구 2419
 
3.6%
역 2338
 
3.5%
( 2302
 
3.4%
Other values (380) 33128
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39979
59.7%
Space Separator 10686
 
16.0%
Decimal Number 10192
 
15.2%
Open Punctuation 2302
 
3.4%
Close Punctuation 2302
 
3.4%
Other Punctuation 1051
 
1.6%
Dash Punctuation 426
 
0.6%
Uppercase Letter 39
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3031
 
7.6%
부 2856
 
7.1%
산 2814
 
7.0%
광 2447
 
6.1%
시 2441
 
6.1%
구 2419
 
6.1%
역 2338
 
5.8%
로 2252
 
5.6%
길 1273
 
3.2%
번 1207
 
3.0%
Other values (351) 16901
42.3%
Decimal Number
ValueCountFrequency (%)
1 2517
24.7%
2 1551
15.2%
3 1192
11.7%
4 875
 
8.6%
5 823
 
8.1%
0 717
 
7.0%
6 702
 
6.9%
7 658
 
6.5%
8 598
 
5.9%
9 559
 
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 (%)
, 1038
98.8%
/ 5
 
0.5%
@ 5
 
0.5%
. 2
 
0.2%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
10686
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2302
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2302
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 426
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39979
59.7%
Common 26961
40.3%
Latin 39
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3031
 
7.6%
부 2856
 
7.1%
산 2814
 
7.0%
광 2447
 
6.1%
시 2441
 
6.1%
구 2419
 
6.1%
역 2338
 
5.8%
로 2252
 
5.6%
길 1273
 
3.2%
번 1207
 
3.0%
Other values (351) 16901
42.3%
Common
ValueCountFrequency (%)
10686
39.6%
1 2517
 
9.3%
( 2302
 
8.5%
) 2302
 
8.5%
2 1551
 
5.8%
3 1192
 
4.4%
, 1038
 
3.9%
4 875
 
3.2%
5 823
 
3.1%
0 717
 
2.7%
Other values (10) 2958
 
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 39979
59.7%
ASCII 27000
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10686
39.6%
1 2517
 
9.3%
( 2302
 
8.5%
) 2302
 
8.5%
2 1551
 
5.7%
3 1192
 
4.4%
, 1038
 
3.8%
4 875
 
3.2%
5 823
 
3.0%
0 717
 
2.7%
Other values (19) 2997
 
11.1%
Hangul
ValueCountFrequency (%)
동 3031
 
7.6%
부 2856
 
7.1%
산 2814
 
7.0%
광 2447
 
6.1%
시 2441
 
6.1%
구 2419
 
6.1%
역 2338
 
5.8%
로 2252
 
5.6%
길 1273
 
3.2%
번 1207
 
3.0%
Other values (351) 16901
42.3%

apvpermymd
Real number (ℝ)

SKEWED 

Distinct3636
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19959619
Minimum9710223
Maximum20210421
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.5 KiB
2024-04-17T10:45:46.694534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9710223
5-th percentile19691192
Q119880119
median19980520
Q320060209
95-th percentile20171226
Maximum20210421
Range10500198
Interquartile range (IQR)180090.25

Descriptive statistics

Standard deviation201323.16
Coefficient of variation (CV)0.010086524
Kurtosis1359.913
Mean19959619
Median Absolute Deviation (MAD)90017
Skewness-26.862717
Sum9.8560596 × 1010
Variance4.0531016 × 1010
MonotonicityNot monotonic
2024-04-17T10:45:46.814230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19660301 35
 
0.7%
19770830 35
 
0.7%
20000420 19
 
0.4%
20020506 17
 
0.3%
20000623 13
 
0.3%
19630630 9
 
0.2%
20030224 9
 
0.2%
19721129 7
 
0.1%
20030410 7
 
0.1%
19630110 6
 
0.1%
Other values (3626) 4781
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 (%)
20210421 1
< 0.1%
20210419 1
< 0.1%
20210402 2
< 0.1%
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%

dcbymd
Text

MISSING 

Distinct2173
Distinct (%)61.9%
Missing1430
Missing (%)29.0%
Memory size38.7 KiB
2024-04-17T10:45:47.049762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9441277
Min length4

Characters and Unicode

Total characters27868
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

Unique1543 ?
Unique (%)44.0%

Sample

1st row20180501
2nd row20121212
3rd row20151228
4th row20121212
5th row20080710
ValueCountFrequency (%)
20030715 58
 
1.7%
폐업일자 49
 
1.4%
20050214 41
 
1.2%
20031213 36
 
1.0%
20020222 33
 
0.9%
20030305 33
 
0.9%
20030221 32
 
0.9%
20030101 17
 
0.5%
20051011 16
 
0.5%
20061226 13
 
0.4%
Other values (2163) 3180
90.6%
2024-04-17T10:45:47.415950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9788
35.1%
2 5786
20.8%
1 4570
16.4%
3 1419
 
5.1%
5 1259
 
4.5%
9 1163
 
4.2%
4 1011
 
3.6%
7 949
 
3.4%
6 899
 
3.2%
8 828
 
3.0%
Other values (4) 196
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27672
99.3%
Other Letter 196
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9788
35.4%
2 5786
20.9%
1 4570
16.5%
3 1419
 
5.1%
5 1259
 
4.5%
9 1163
 
4.2%
4 1011
 
3.7%
7 949
 
3.4%
6 899
 
3.2%
8 828
 
3.0%
Other Letter
ValueCountFrequency (%)
폐 49
25.0%
업 49
25.0%
일 49
25.0%
자 49
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27672
99.3%
Hangul 196
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9788
35.4%
2 5786
20.9%
1 4570
16.5%
3 1419
 
5.1%
5 1259
 
4.5%
9 1163
 
4.2%
4 1011
 
3.7%
7 949
 
3.4%
6 899
 
3.2%
8 828
 
3.0%
Hangul
ValueCountFrequency (%)
폐 49
25.0%
업 49
25.0%
일 49
25.0%
자 49
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27672
99.3%
Hangul 196
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9788
35.4%
2 5786
20.9%
1 4570
16.5%
3 1419
 
5.1%
5 1259
 
4.5%
9 1163
 
4.2%
4 1011
 
3.7%
7 949
 
3.4%
6 899
 
3.2%
8 828
 
3.0%
Hangul
ValueCountFrequency (%)
폐 49
25.0%
업 49
25.0%
일 49
25.0%
자 49
25.0%

clgstdt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4878 
휴업시작일자
 
60

Length

Max length6
Median length4
Mean length4.0243013
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> 4878
98.8%
휴업시작일자 60
 
1.2%

Length

2024-04-17T10:45:47.539921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:47.632351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4878
98.8%
휴업시작일자 60
 
1.2%

clgenddt
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4878 
휴업종료일자
 
60

Length

Max length6
Median length4
Mean length4.0243013
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> 4878
98.8%
휴업종료일자 60
 
1.2%

Length

2024-04-17T10:45:47.717558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:47.808964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4878
98.8%
휴업종료일자 60
 
1.2%

ropnymd
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4878 
재개업일자
 
60

Length

Max length5
Median length4
Mean length4.0121507
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> 4878
98.8%
재개업일자 60
 
1.2%

Length

2024-04-17T10:45:47.892161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:47.971505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4878
98.8%
재개업일자 60
 
1.2%

trdstatenm
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
02
3330 
01
1175 
영업/정상
 
300
폐업
 
128
영업상태
 
3

Length

Max length5
Median length2
Mean length2.1842851
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
02 3330
67.4%
01 1175
 
23.8%
영업/정상 300
 
6.1%
폐업 128
 
2.6%
영업상태 3
 
0.1%
<NA> 2
 
< 0.1%

Length

2024-04-17T10:45:48.051358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:48.137460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02 3330
67.4%
01 1175
 
23.8%
영업/정상 300
 
6.1%
폐업 128
 
2.6%
영업상태 3
 
0.1%
na 2
 
< 0.1%

dtlstatenm
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
폐업
3459 
영업
1479 

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 3459
70.0%
영업 1479
30.0%

Length

2024-04-17T10:45:48.224736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:48.296202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3459
70.0%
영업 1479
30.0%

x
Text

MISSING 

Distinct4015
Distinct (%)86.8%
Missing314
Missing (%)6.4%
Memory size38.7 KiB
2024-04-17T10:45:48.463479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.991566
Min length7

Characters and Unicode

Total characters92441
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

Unique3524 ?
Unique (%)76.2%

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%
384080.85541900000 4
 
0.1%
400804.64364100000 4
 
0.1%
383537.369514 4
 
0.1%
379140.640735214 4
 
0.1%
385851.312113 4
 
0.1%
383359.409731 4
 
0.1%
394263.364966 4
 
0.1%
392357.064184 4
 
0.1%
Other values (4005) 4582
99.1%
2024-04-17T10:45:48.754947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21106
22.8%
0 14456
15.6%
3 9461
10.2%
8 7478
 
8.1%
9 6238
 
6.7%
7 5017
 
5.4%
1 4903
 
5.3%
5 4841
 
5.2%
6 4792
 
5.2%
2 4771
 
5.2%
Other values (9) 9378
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66693
72.1%
Space Separator 21106
 
22.8%
Other Punctuation 4621
 
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 14456
21.7%
3 9461
14.2%
8 7478
11.2%
9 6238
9.4%
7 5017
 
7.5%
1 4903
 
7.4%
5 4841
 
7.3%
6 4792
 
7.2%
2 4771
 
7.2%
4 4736
 
7.1%
Other Letter
ValueCountFrequency (%)
좌 3
25.0%
표 3
25.0%
정 3
25.0%
보 3
25.0%
Space Separator
ValueCountFrequency (%)
21106
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4621
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 92426
> 99.9%
Hangul 12
 
< 0.1%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
21106
22.8%
0 14456
15.6%
3 9461
10.2%
8 7478
 
8.1%
9 6238
 
6.7%
7 5017
 
5.4%
1 4903
 
5.3%
5 4841
 
5.2%
6 4792
 
5.2%
2 4771
 
5.2%
Other values (4) 9363
10.1%
Hangul
ValueCountFrequency (%)
좌 3
25.0%
표 3
25.0%
정 3
25.0%
보 3
25.0%
Latin
ValueCountFrequency (%)
X 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92429
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21106
22.8%
0 14456
15.6%
3 9461
10.2%
8 7478
 
8.1%
9 6238
 
6.7%
7 5017
 
5.4%
1 4903
 
5.3%
5 4841
 
5.2%
6 4792
 
5.2%
2 4771
 
5.2%
Other values (5) 9366
10.1%
Hangul
ValueCountFrequency (%)
좌 3
25.0%
표 3
25.0%
정 3
25.0%
보 3
25.0%

y
Text

MISSING 

Distinct4015
Distinct (%)86.8%
Missing314
Missing (%)6.4%
Memory size38.7 KiB
2024-04-17T10:45:48.962054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.991566
Min length7

Characters and Unicode

Total characters92441
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

Unique3524 ?
Unique (%)76.2%

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%
179983.87155900000 4
 
0.1%
189454.38252300000 4
 
0.1%
195339.407375 4
 
0.1%
180128.072887035 4
 
0.1%
181799.414753 4
 
0.1%
180510.501555 4
 
0.1%
191382.712014 4
 
0.1%
185295.821253 4
 
0.1%
Other values (4005) 4582
99.1%
2024-04-17T10:45:49.266024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21057
22.8%
0 14255
15.4%
1 9512
10.3%
8 7210
 
7.8%
9 6485
 
7.0%
7 5573
 
6.0%
2 4903
 
5.3%
3 4761
 
5.2%
4 4727
 
5.1%
6 4671
 
5.1%
Other values (9) 9287
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66742
72.2%
Space Separator 21057
 
22.8%
Other Punctuation 4621
 
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 14255
21.4%
1 9512
14.3%
8 7210
10.8%
9 6485
9.7%
7 5573
 
8.4%
2 4903
 
7.3%
3 4761
 
7.1%
4 4727
 
7.1%
6 4671
 
7.0%
5 4645
 
7.0%
Other Letter
ValueCountFrequency (%)
좌 3
25.0%
표 3
25.0%
정 3
25.0%
보 3
25.0%
Space Separator
ValueCountFrequency (%)
21057
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4621
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 92426
> 99.9%
Hangul 12
 
< 0.1%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
21057
22.8%
0 14255
15.4%
1 9512
10.3%
8 7210
 
7.8%
9 6485
 
7.0%
7 5573
 
6.0%
2 4903
 
5.3%
3 4761
 
5.2%
4 4727
 
5.1%
6 4671
 
5.1%
Other values (4) 9272
10.0%
Hangul
ValueCountFrequency (%)
좌 3
25.0%
표 3
25.0%
정 3
25.0%
보 3
25.0%
Latin
ValueCountFrequency (%)
Y 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92429
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21057
22.8%
0 14255
15.4%
1 9512
10.3%
8 7210
 
7.8%
9 6485
 
7.0%
7 5573
 
6.0%
2 4903
 
5.3%
3 4761
 
5.2%
4 4727
 
5.1%
6 4671
 
5.1%
Other values (5) 9275
10.0%
Hangul
ValueCountFrequency (%)
좌 3
25.0%
표 3
25.0%
정 3
25.0%
보 3
25.0%

lastmodts
Real number (ℝ)

Distinct3221
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0089017 × 1013
Minimum1.9990218 × 1013
Maximum2.0210427 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.5 KiB
2024-04-17T10:45:49.400108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile1.9990624 × 1013
Q12.0031004 × 1013
median2.0071008 × 1013
Q32.0140203 × 1013
95-th percentile2.020032 × 1013
Maximum2.0210427 × 1013
Range2.2020911 × 1011
Interquartile range (IQR)1.0919911 × 1011

Descriptive statistics

Standard deviation6.2726282 × 1010
Coefficient of variation (CV)0.0031224166
Kurtosis-1.1471364
Mean2.0089017 × 1013
Median Absolute Deviation (MAD)4.0796646 × 1010
Skewness0.31992503
Sum9.9199568 × 1016
Variance3.9345865 × 1021
MonotonicityNot monotonic
2024-04-17T10:45:49.512654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030211000000 63
 
1.3%
20070501000000 54
 
1.1%
20030311000000 38
 
0.8%
20020424000000 38
 
0.8%
20031215000000 38
 
0.8%
20030502000000 37
 
0.7%
19990428000000 35
 
0.7%
20020423000000 34
 
0.7%
20030221000000 33
 
0.7%
20060707000000 33
 
0.7%
Other values (3211) 4535
91.8%
ValueCountFrequency (%)
19990218000000 1
 
< 0.1%
19990223000000 4
 
0.1%
19990224000000 1
 
< 0.1%
19990225000000 3
 
0.1%
19990302000000 10
0.2%
19990303000000 12
0.2%
19990304000000 20
0.4%
19990308000000 17
0.3%
19990309000000 5
 
0.1%
19990310000000 18
0.4%
ValueCountFrequency (%)
20210427114235 1
< 0.1%
20210427112748 1
< 0.1%
20210427102711 1
< 0.1%
20210422155504 1
< 0.1%
20210422092445 1
< 0.1%
20210421143244 1
< 0.1%
20210421105101 1
< 0.1%
20210419160700 1
< 0.1%
20210415164040 2
< 0.1%
20210413165730 1
< 0.1%

uptaenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
일반이용업
4874 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0078979
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 4874
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-17T10:45:49.622147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:49.709152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4874
97.9%
이용업 40
 
0.8%
기타 40
 
0.8%
일반미용업 23
 
0.5%
na 1
 
< 0.1%

sitetel
Text

MISSING 

Distinct78
Distinct (%)1.6%
Missing71
Missing (%)1.4%
Memory size38.7 KiB
2024-04-17T10:45:49.916154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.948839
Min length4

Characters and Unicode

Total characters58155
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)1.5%

Sample

1st row051-123-1234
2nd row051-123-1234
3rd row051-123-1234
4th row051-123-1234
5th row051-123-1234
ValueCountFrequency (%)
051-123-1234 4764
96.0%
051 58
 
1.2%
전화번호 23
 
0.5%
070 3
 
0.1%
86729677 3
 
0.1%
7526956 3
 
0.1%
051624 3
 
0.1%
896 2
 
< 0.1%
807 2
 
< 0.1%
051635 2
 
< 0.1%
Other values (98) 98
 
2.0%
2024-04-17T10:45:50.245815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14420
24.8%
2 9596
16.5%
3 9592
16.5%
- 9528
16.4%
5 4895
 
8.4%
0 4888
 
8.4%
4 4814
 
8.3%
96
 
0.2%
6 80
 
0.1%
7 60
 
0.1%
Other values (6) 186
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48439
83.3%
Dash Punctuation 9528
 
16.4%
Space Separator 96
 
0.2%
Other Letter 92
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14420
29.8%
2 9596
19.8%
3 9592
19.8%
5 4895
 
10.1%
0 4888
 
10.1%
4 4814
 
9.9%
6 80
 
0.2%
7 60
 
0.1%
9 49
 
0.1%
8 45
 
0.1%
Other Letter
ValueCountFrequency (%)
전 23
25.0%
화 23
25.0%
번 23
25.0%
호 23
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 9528
100.0%
Space Separator
ValueCountFrequency (%)
96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58063
99.8%
Hangul 92
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14420
24.8%
2 9596
16.5%
3 9592
16.5%
- 9528
16.4%
5 4895
 
8.4%
0 4888
 
8.4%
4 4814
 
8.3%
96
 
0.2%
6 80
 
0.1%
7 60
 
0.1%
Other values (2) 94
 
0.2%
Hangul
ValueCountFrequency (%)
전 23
25.0%
화 23
25.0%
번 23
25.0%
호 23
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58063
99.8%
Hangul 92
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14420
24.8%
2 9596
16.5%
3 9592
16.5%
- 9528
16.4%
5 4895
 
8.4%
0 4888
 
8.4%
4 4814
 
8.3%
96
 
0.2%
6 80
 
0.1%
7 60
 
0.1%
Other values (2) 94
 
0.2%
Hangul
ValueCountFrequency (%)
전 23
25.0%
화 23
25.0%
번 23
25.0%
호 23
25.0%

bdngownsenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
3962 
임대
908 
건물소유구분명
 
46
자가
 
22

Length

Max length7
Median length4
Mean length3.6512758
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> 3962
80.2%
임대 908
 
18.4%
건물소유구분명 46
 
0.9%
자가 22
 
0.4%

Length

2024-04-17T10:45:50.347754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:50.427031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3962
80.2%
임대 908
 
18.4%
건물소유구분명 46
 
0.9%
자가 22
 
0.4%

bdngjisgflrcnt
Categorical

Distinct34
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
1761 
0
1186 
3
484 
4
421 
2
404 
Other values (29)
682 

Length

Max length6
Median length1
Mean length2.0925476
Min length1

Unique

Unique9 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1761
35.7%
0 1186
24.0%
3 484
 
9.8%
4 421
 
8.5%
2 404
 
8.2%
5 237
 
4.8%
1 165
 
3.3%
6 84
 
1.7%
7 55
 
1.1%
8 28
 
0.6%
Other values (24) 113
 
2.3%

Length

2024-04-17T10:45:50.512987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1761
35.7%
0 1186
24.0%
3 484
 
9.8%
4 421
 
8.5%
2 404
 
8.2%
5 237
 
4.8%
1 165
 
3.3%
6 84
 
1.7%
7 55
 
1.1%
8 28
 
0.6%
Other values (24) 113
 
2.3%

bdngunderflrcnt
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
2277 
0
1676 
1
842 
2
 
87
3
 
22
Other values (7)
 
34

Length

Max length6
Median length1
Mean length2.3900365
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2277
46.1%
0 1676
33.9%
1 842
 
17.1%
2 87
 
1.8%
3 22
 
0.4%
5 15
 
0.3%
건물지하층수 6
 
0.1%
4 6
 
0.1%
6 4
 
0.1%
7 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2024-04-17T10:45:50.610888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2277
46.1%
0 1676
33.9%
1 842
 
17.1%
2 87
 
1.8%
3 22
 
0.4%
5 15
 
0.3%
건물지하층수 6
 
0.1%
4 6
 
0.1%
6 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>
4534 
0
 
360
1
 
32
남성종사자수
 
11
2
 
1

Length

Max length6
Median length4
Mean length3.7656946
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> 4534
91.8%
0 360
 
7.3%
1 32
 
0.6%
남성종사자수 11
 
0.2%
2 1
 
< 0.1%

Length

2024-04-17T10:45:50.708069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:50.801031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4534
91.8%
0 360
 
7.3%
1 32
 
0.6%
남성종사자수 11
 
0.2%
2 1
 
< 0.1%

multusnupsoyn
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
False
4938 
ValueCountFrequency (%)
False 4938
100.0%
2024-04-17T10:45:50.873364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

balhansilyn
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
False
4938 
ValueCountFrequency (%)
False 4938
100.0%
2024-04-17T10:45:50.927541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

usejisgendflr
Categorical

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
2775 
1
753 
0
546 
2
467 
3
 
214
Other values (8)
 
183

Length

Max length6
Median length4
Mean length2.7148643
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2775
56.2%
1 753
 
15.2%
0 546
 
11.1%
2 467
 
9.5%
3 214
 
4.3%
4 81
 
1.6%
5 46
 
0.9%
사용끝지상층 28
 
0.6%
6 15
 
0.3%
7 7
 
0.1%
Other values (3) 6
 
0.1%

Length

2024-04-17T10:45:51.002761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2775
56.2%
1 753
 
15.2%
0 546
 
11.1%
2 467
 
9.5%
3 214
 
4.3%
4 81
 
1.6%
5 46
 
0.9%
사용끝지상층 28
 
0.6%
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>
3763 
0
861 
1
 
262
사용끝지하층
 
45
2
 
6

Length

Max length6
Median length4
Mean length3.3317132
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> 3763
76.2%
0 861
 
17.4%
1 262
 
5.3%
사용끝지하층 45
 
0.9%
2 6
 
0.1%
4 1
 
< 0.1%

Length

2024-04-17T10:45:51.102027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:51.189554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3763
76.2%
0 861
 
17.4%
1 262
 
5.3%
사용끝지하층 45
 
0.9%
2 6
 
0.1%
4 1
 
< 0.1%

usejisgstflr
Categorical

Distinct15
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
2154 
0
973 
1
860 
2
498 
3
253 
Other values (10)
 
200

Length

Max length7
Median length1
Mean length2.3329283
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2154
43.6%
0 973
19.7%
1 860
 
17.4%
2 498
 
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

2024-04-17T10:45:51.285460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2154
43.6%
0 973
19.7%
1 860
 
17.4%
2 498
 
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>
3107 
0
1468 
1
 
308
사용시작지하층
 
39
2
 
15

Length

Max length7
Median length4
Mean length2.9351964
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> 3107
62.9%
0 1468
29.7%
1 308
 
6.2%
사용시작지하층 39
 
0.8%
2 15
 
0.3%
22 1
 
< 0.1%

Length

2024-04-17T10:45:51.400328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:51.505931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3107
62.9%
0 1468
29.7%
1 308
 
6.2%
사용시작지하층 39
 
0.8%
2 15
 
0.3%
22 1
 
< 0.1%

washmccnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
3422 
0
1508 
세탁기수
 
8

Length

Max length4
Median length4
Mean length3.0838396
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> 3422
69.3%
0 1508
30.5%
세탁기수 8
 
0.2%

Length

2024-04-17T10:45:51.606371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:51.686435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3422
69.3%
0 1508
30.5%
세탁기수 8
 
0.2%

yangsilcnt
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
2754 
0
2176 
양실수
 
7
38
 
1

Length

Max length4
Median length4
Mean length2.6761847
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> 2754
55.8%
0 2176
44.1%
양실수 7
 
0.1%
38 1
 
< 0.1%

Length

2024-04-17T10:45:51.774299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:51.854167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2754
55.8%
0 2176
44.1%
양실수 7
 
0.1%
38 1
 
< 0.1%

wmeipcnt
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4545 
0
 
364
1
 
18
여성종사자수
 
11

Length

Max length6
Median length4
Mean length3.7723775
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> 4545
92.0%
0 364
 
7.4%
1 18
 
0.4%
여성종사자수 11
 
0.2%

Length

2024-04-17T10:45:51.945045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:52.036812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4545
92.0%
0 364
 
7.4%
1 18
 
0.4%
여성종사자수 11
 
0.2%

yoksilcnt
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
2754 
0
2176 
욕실수
 
7
2
 
1

Length

Max length4
Median length4
Mean length2.6759822
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> 2754
55.8%
0 2176
44.1%
욕실수 7
 
0.1%
2 1
 
< 0.1%

Length

2024-04-17T10:45:52.124701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:52.214020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2754
55.8%
0 2176
44.1%
욕실수 7
 
0.1%
2 1
 
< 0.1%

sntuptaenm
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
일반이용업
4874 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0078979
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 4874
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-17T10:45:52.303911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:52.404892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4874
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
1336 
3
887 
<NA>
611 
4
593 
0
340 
Other values (12)
1171 

Length

Max length4
Median length1
Mean length1.381531
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
2 1336
27.1%
3 887
18.0%
<NA> 611
12.4%
4 593
12.0%
0 340
 
6.9%
1 329
 
6.7%
5 265
 
5.4%
6 180
 
3.6%
7 171
 
3.5%
8 111
 
2.2%
Other values (7) 115
 
2.3%

Length

2024-04-17T10:45:52.511007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 1336
27.1%
3 887
18.0%
na 611
12.4%
4 593
12.0%
0 340
 
6.9%
1 329
 
6.7%
5 265
 
5.4%
6 180
 
3.6%
7 171
 
3.5%
8 111
 
2.2%
Other values (7) 115
 
2.3%

cndpermstymd
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4876 
조건부허가시작일자
 
60
20050520
 
1
20050414
 
1

Length

Max length9
Median length4
Mean length4.0623734
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> 4876
98.7%
조건부허가시작일자 60
 
1.2%
20050520 1
 
< 0.1%
20050414 1
 
< 0.1%

Length

2024-04-17T10:45:52.611240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:52.687590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4876
98.7%
조건부허가시작일자 60
 
1.2%
20050520 1
 
< 0.1%
20050414 1
 
< 0.1%

cndpermntwhy
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4877 
조건부허가신고사유
 
60
가설건축물
 
1

Length

Max length9
Median length4
Mean length4.0609559
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> 4877
98.8%
조건부허가신고사유 60
 
1.2%
가설건축물 1
 
< 0.1%

Length

2024-04-17T10:45:52.772730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:52.848785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4877
98.8%
조건부허가신고사유 60
 
1.2%
가설건축물 1
 
< 0.1%

cndpermendymd
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
4876 
조건부허가종료일자
 
60
20060425
 
1
20050414
 
1

Length

Max length9
Median length4
Mean length4.0623734
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> 4876
98.7%
조건부허가종료일자 60
 
1.2%
20060425 1
 
< 0.1%
20050414 1
 
< 0.1%

Length

2024-04-17T10:45:52.935717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:53.016882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4876
98.7%
조건부허가종료일자 60
 
1.2%
20060425 1
 
< 0.1%
20050414 1
 
< 0.1%

abedcnt
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
3623 
0
1299 
침대수
 
8
2
 
4
3
 
2
Other values (2)
 
2

Length

Max length4
Median length4
Mean length3.2043337
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> 3623
73.4%
0 1299
 
26.3%
침대수 8
 
0.2%
2 4
 
0.1%
3 2
 
< 0.1%
1 1
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-17T10:45:53.108125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:53.202650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3623
73.4%
0 1299
 
26.3%
침대수 8
 
0.2%
2 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>
2755 
0
2176 
한실수
 
7

Length

Max length4
Median length4
Mean length2.6765897
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> 2755
55.8%
0 2176
44.1%
한실수 7
 
0.1%

Length

2024-04-17T10:45:53.306957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:53.384967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2755
55.8%
0 2176
44.1%
한실수 7
 
0.1%

rcvdryncnt
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
<NA>
3605 
0
1325 
회수건조수
 
8

Length

Max length5
Median length4
Mean length3.1966383
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> 3605
73.0%
0 1325
 
26.8%
회수건조수 8
 
0.2%

Length

2024-04-17T10:45:53.719368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:53.799552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3605
73.0%
0 1325
 
26.8%
회수건조수 8
 
0.2%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.7 KiB
2021-05-01 05:25:03
4938 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021-05-01 05:25:03 4938
100.0%

Length

2024-04-17T10:45:53.877481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:45:53.945637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-05-01 4938
50.0%
05:25:03 4938
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>0002021-05-01 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>2021-05-01 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>0002021-05-01 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>2021-05-01 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>2021-05-01 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>2021-05-01 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>0002021-05-01 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>2021-05-01 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>0002021-05-01 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>0002021-05-01 05:25:03
skeyopnsfteamcodemgtnoopnsvcidupdategbnupdatedtopnsvcnmbplcnmsitepostnositewhladdrrdnpostnordnwhladdrapvpermymddcbymdclgstdtclgenddtropnymdtrdstatenmdtlstatenmxylastmodtsuptaenmsitetelbdngownsenmbdngjisgflrcntbdngunderflrcntmaneipcntmultusnupsoynbalhansilynusejisgendflruseunderendflrusejisgstflruseunderstflrwashmccntyangsilcntwmeipcntyoksilcntsntuptaenmchaircntcndpermstymdcndpermntwhycndpermendymdabedcnthanshilcntrcvdryncntlast_load_dttm
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>0002021-05-01 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/정상영업390356.030587687183836.08928744920210318135628일반이용업전화번호건물소유구분명000NN4사용끝지하층4사용시작지하층0000일반이용업2조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-05-01 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/정상영업390036.897951263196340.38717702820210324102256일반이용업전화번호건물소유구분명000NN1사용끝지하층1사용시작지하층0010일반이용업3조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-05-01 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/정상영업389097.800933845192260.81164826320210330165802일반이용업전화번호건물소유구분명건물지상층수건물지하층수남성종사자수NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층세탁기수양실수여성종사자수욕실수일반이용업의자수조건부허가시작일자조건부허가신고사유조건부허가종료일자침대수한실수회수건조수2021-05-01 05:25:03
4932708933900003390000-203-2021-0000205_19_01_PU2021-04-17 02:40:00.0이용업포맨 남성컷트샵617836부산광역시 사상구 주례동 965-13 해물나라46993부산광역시 사상구 백양대로494번길 9-3, 1층 (주례동)20210402폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업381981.3566866185727.60063115120210415164040일반이용업전화번호건물소유구분명000NN00100000일반이용업4조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-05-01 05:25:03
4933709033900003390000-203-2021-0000205_19_01_PU2021-04-17 02:40:00.0이용업포맨 남성컷트샵617836부산광역시 사상구 주례동 965-13 해물나라46993부산광역시 사상구 백양대로494번길 9-3, 1층 (주례동)20210402폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업381981.3566866185727.60063115120210415164040일반이용업전화번호건물소유구분명000NN00100000일반이용업4조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-05-01 05:25:03
4934709133000003300000-203-2021-0000405_19_01_PI2021-04-21 00:22:58.0이용업또또남성컷트607830부산광역시 동래구 안락동 448-3847790부산광역시 동래구 안락로 72-1, 1층 (안락동)20210419폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업391621.925407303190927.85842312820210419160700일반이용업전화번호건물소유구분명건물지상층수건물지하층수남성종사자수NN사용끝지상층사용끝지하층사용시작지상층사용시작지하층세탁기수양실수여성종사자수욕실수일반이용업의자수조건부허가시작일자조건부허가신고사유조건부허가종료일자침대수한실수회수건조수2021-05-01 05:25:03
4935709232500003250000-203-2021-0000205_19_01_PI2021-04-23 00:22:58.0이용업남포이발컷트600045부산광역시 중구 남포동5가 39-648953부산광역시 중구 중구로 2, 2층 (남포동5가)20210421폐업일자휴업시작일자휴업종료일자재개업일자영업/정상영업384877.272223985179536.79460869520210421143244일반이용업전화번호건물소유구분명200NN2사용끝지하층2사용시작지하층0000일반이용업2조건부허가시작일자조건부허가신고사유조건부허가종료일자0002021-05-01 05:25:03
4936707232900003290000-203-2021-0000405_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>0002021-05-01 05:25:03
4937707533700003370000-203-2021-0000105_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>0002021-05-01 05:25:03