Overview

Dataset statistics

Number of variables37
Number of observations10000
Missing cells81696
Missing cells (%)22.1%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory3.1 MiB
Average record size in memory327.0 B

Variable types

Categorical15
Text7
DateTime1
Unsupported1
Numeric11
Boolean2

Alerts

발한실여부 has constant value ""Constant
Dataset has 1 (< 0.1%) duplicate rowsDuplicates
사용시작지하층수 is highly imbalanced (53.8%)Imbalance
사용끝지하층수 is highly imbalanced (54.0%)Imbalance
조건부허가시작일자 is highly imbalanced (99.7%)Imbalance
조건부허가종료일자 is highly imbalanced (99.7%)Imbalance
다중이용업소여부 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 6706 (67.1%) missing valuesMissing
소재지시설전화번호 has 8518 (85.2%) missing valuesMissing
소재지면적정보 has 4528 (45.3%) missing valuesMissing
도로명우편번호 has 4587 (45.9%) missing valuesMissing
X좌표값 has 4699 (47.0%) missing valuesMissing
Y좌표값 has 4699 (47.0%) missing valuesMissing
건물지상층수 has 4561 (45.6%) missing valuesMissing
건물지하층수 has 4596 (46.0%) missing valuesMissing
사용시작지상층수 has 4681 (46.8%) missing valuesMissing
사용끝지상층수 has 4701 (47.0%) missing valuesMissing
발한실여부 has 4539 (45.4%) missing valuesMissing
조건부허가신고사유 has 9993 (99.9%) missing valuesMissing
여성종사자수 has 4745 (47.4%) missing valuesMissing
소재지면적정보 is highly skewed (γ1 = 73.33518335)Skewed
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적정보 has 453 (4.5%) zerosZeros
건물지상층수 has 4435 (44.4%) zerosZeros
건물지하층수 has 4995 (50.0%) zerosZeros
사용시작지상층수 has 2772 (27.7%) zerosZeros
사용끝지상층수 has 3012 (30.1%) zerosZeros
여성종사자수 has 5017 (50.2%) zerosZeros

Reproduction

Analysis started2023-12-10 23:00:46.603072
Analysis finished2023-12-10 23:00:49.260686
Duration2.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원시
1264 
부천시
866 
고양시
765 
성남시
734 
화성시
 
534
Other values (27)
5837 

Length

Max length4
Median length3
Mean length3.0807
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양주시
2nd row성남시
3rd row안양시
4th row고양시
5th row광주시

Common Values

ValueCountFrequency (%)
수원시 1264
 
12.6%
부천시 866
 
8.7%
고양시 765
 
7.6%
성남시 734
 
7.3%
화성시 534
 
5.3%
안산시 533
 
5.3%
용인시 513
 
5.1%
안양시 509
 
5.1%
양주시 491
 
4.9%
평택시 449
 
4.5%
Other values (22) 3342
33.4%

Length

2023-12-11T08:00:49.333821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 1264
 
12.6%
부천시 866
 
8.7%
고양시 765
 
7.6%
성남시 734
 
7.3%
화성시 534
 
5.3%
안산시 533
 
5.3%
용인시 513
 
5.1%
안양시 509
 
5.1%
양주시 491
 
4.9%
평택시 449
 
4.5%
Other values (22) 3342
33.4%

사업장명
Text

Distinct8908
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:00:49.628473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length6.7053
Min length1

Characters and Unicode

Total characters67053
Distinct characters927
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8251 ?
Unique (%)82.5%

Sample

1st row도노헤어룸
2nd row에스더 피부샵
3rd row시선살롱
4th row스킨아트 에스테틱
5th row피부사랑 에스테틱
ValueCountFrequency (%)
에스테틱 145
 
1.1%
헤어 103
 
0.8%
스킨케어 83
 
0.7%
hair 75
 
0.6%
네일 74
 
0.6%
nail 59
 
0.5%
뷰티 49
 
0.4%
피부관리실 47
 
0.4%
피부관리 44
 
0.3%
더 41
 
0.3%
Other values (9336) 11992
94.3%
2023-12-11T08:00:50.099180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 2895
 
4.3%
2716
 
4.1%
어 2458
 
3.7%
헤 1670
 
2.5%
리 1390
 
2.1%
이 1297
 
1.9%
피 1286
 
1.9%
킨 1151
 
1.7%
티 1131
 
1.7%
부 1126
 
1.7%
Other values (917) 49933
74.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54176
80.8%
Lowercase Letter 3883
 
5.8%
Uppercase Letter 3208
 
4.8%
Space Separator 2716
 
4.1%
Close Punctuation 1006
 
1.5%
Open Punctuation 1005
 
1.5%
Other Punctuation 631
 
0.9%
Decimal Number 362
 
0.5%
Dash Punctuation 40
 
0.1%
Connector Punctuation 13
 
< 0.1%
Other values (4) 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 2895
 
5.3%
어 2458
 
4.5%
헤 1670
 
3.1%
리 1390
 
2.6%
이 1297
 
2.4%
피 1286
 
2.4%
킨 1151
 
2.1%
티 1131
 
2.1%
부 1126
 
2.1%
미 1102
 
2.0%
Other values (826) 38670
71.4%
Lowercase Letter
ValueCountFrequency (%)
a 487
12.5%
e 436
11.2%
i 385
9.9%
n 315
 
8.1%
o 306
 
7.9%
l 273
 
7.0%
r 211
 
5.4%
s 202
 
5.2%
h 182
 
4.7%
u 171
 
4.4%
Other values (16) 915
23.6%
Uppercase Letter
ValueCountFrequency (%)
A 295
 
9.2%
S 249
 
7.8%
N 246
 
7.7%
O 218
 
6.8%
E 218
 
6.8%
I 203
 
6.3%
H 193
 
6.0%
B 185
 
5.8%
L 164
 
5.1%
R 148
 
4.6%
Other values (16) 1089
33.9%
Other Punctuation
ValueCountFrequency (%)
& 252
39.9%
, 103
16.3%
. 101
16.0%
# 76
 
12.0%
' 45
 
7.1%
: 32
 
5.1%
＆ 6
 
1.0%
; 4
 
0.6%
· 4
 
0.6%
? 2
 
0.3%
Other values (4) 6
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 73
20.2%
2 64
17.7%
0 56
15.5%
5 35
9.7%
3 35
9.7%
4 29
 
8.0%
8 25
 
6.9%
9 16
 
4.4%
6 15
 
4.1%
7 14
 
3.9%
Math Symbol
ValueCountFrequency (%)
+ 5
71.4%
> 1
 
14.3%
< 1
 
14.3%
Modifier Symbol
ValueCountFrequency (%)
˚ 2
50.0%
´ 1
25.0%
` 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 1002
99.6%
] 4
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 1001
99.6%
[ 4
 
0.4%
Space Separator
ValueCountFrequency (%)
2716
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 13
100.0%
Other Number
ValueCountFrequency (%)
₂ 1
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54107
80.7%
Latin 7091
 
10.6%
Common 5786
 
8.6%
Han 69
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 2895
 
5.4%
어 2458
 
4.5%
헤 1670
 
3.1%
리 1390
 
2.6%
이 1297
 
2.4%
피 1286
 
2.4%
킨 1151
 
2.1%
티 1131
 
2.1%
부 1126
 
2.1%
미 1102
 
2.0%
Other values (812) 38601
71.3%
Latin
ValueCountFrequency (%)
a 487
 
6.9%
e 436
 
6.1%
i 385
 
5.4%
n 315
 
4.4%
o 306
 
4.3%
A 295
 
4.2%
l 273
 
3.8%
S 249
 
3.5%
N 246
 
3.5%
O 218
 
3.1%
Other values (42) 3881
54.7%
Common
ValueCountFrequency (%)
2716
46.9%
) 1002
 
17.3%
( 1001
 
17.3%
& 252
 
4.4%
, 103
 
1.8%
. 101
 
1.7%
# 76
 
1.3%
1 73
 
1.3%
2 64
 
1.1%
0 56
 
1.0%
Other values (29) 342
 
5.9%
Han
ValueCountFrequency (%)
美 49
71.0%
愛 5
 
7.2%
人 3
 
4.3%
秀 2
 
2.9%
林 1
 
1.4%
水 1
 
1.4%
家 1
 
1.4%
眞 1
 
1.4%
白 1
 
1.4%
粧 1
 
1.4%
Other values (4) 4
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54103
80.7%
ASCII 12862
 
19.2%
CJK 69
 
0.1%
None 13
 
< 0.1%
Compat Jamo 4
 
< 0.1%
Modifier Letters 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 2895
 
5.4%
어 2458
 
4.5%
헤 1670
 
3.1%
리 1390
 
2.6%
이 1297
 
2.4%
피 1286
 
2.4%
킨 1151
 
2.1%
티 1131
 
2.1%
부 1126
 
2.1%
미 1102
 
2.0%
Other values (810) 38597
71.3%
ASCII
ValueCountFrequency (%)
2716
21.1%
) 1002
 
7.8%
( 1001
 
7.8%
a 487
 
3.8%
e 436
 
3.4%
i 385
 
3.0%
n 315
 
2.4%
o 306
 
2.4%
A 295
 
2.3%
l 273
 
2.1%
Other values (75) 5646
43.9%
CJK
ValueCountFrequency (%)
美 49
71.0%
愛 5
 
7.2%
人 3
 
4.3%
秀 2
 
2.9%
林 1
 
1.4%
水 1
 
1.4%
家 1
 
1.4%
眞 1
 
1.4%
白 1
 
1.4%
粧 1
 
1.4%
Other values (4) 4
 
5.8%
None
ValueCountFrequency (%)
＆ 6
46.2%
· 4
30.8%
´ 1
 
7.7%
₂ 1
 
7.7%
° 1
 
7.7%
Compat Jamo
ValueCountFrequency (%)
ㄱ 2
50.0%
ㅋ 2
50.0%
Modifier Letters
ValueCountFrequency (%)
˚ 2
100.0%

인허가일자
Date

Distinct3644
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1977-08-10 00:00:00
Maximum2023-12-06 00:00:00
2023-12-11T08:00:50.268006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:00:50.451149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

영업상태구분코드
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4523 
1
4287 
2
1190 

Length

Max length4
Median length1
Mean length2.3569
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4523
45.2%
1 4287
42.9%
2 1190
 
11.9%

Length

2023-12-11T08:00:50.811792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:00:50.917145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4523
45.2%
1 4287
42.9%
2 1190
 
11.9%

영업상태명
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업
4287 
운영중
2419 
폐업 등
2104 
폐업
1190 

Length

Max length4
Median length2
Mean length2.6627
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업
2nd row폐업 등
3rd row영업
4th row운영중
5th row운영중

Common Values

ValueCountFrequency (%)
영업 4287
42.9%
운영중 2419
24.2%
폐업 등 2104
21.0%
폐업 1190
 
11.9%

Length

2023-12-11T08:00:51.077624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:00:51.218229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4287
35.4%
폐업 3294
27.2%
운영중 2419
20.0%
등 2104
17.4%

폐업일자
Text

MISSING 

Distinct1497
Distinct (%)45.4%
Missing6706
Missing (%)67.1%
Memory size156.2 KiB
2023-12-11T08:00:51.548459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.7216151
Min length5

Characters and Unicode

Total characters28729
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

Unique789 ?
Unique (%)24.0%

Sample

1st row20101110
2nd row20180802
3rd row20150130
4th row20130507
5th row20150826
ValueCountFrequency (%)
2023-08-31 17
 
0.5%
2023-03-31 16
 
0.5%
2023-07-31 15
 
0.5%
2023-10-05 14
 
0.4%
2023-10-04 14
 
0.4%
2023-08-28 14
 
0.4%
2023-05-30 14
 
0.4%
2023-11-30 13
 
0.4%
2023-10-24 13
 
0.4%
2023-07-03 13
 
0.4%
Other values (1487) 3151
95.7%
2023-12-11T08:00:52.069927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7431
25.9%
2 6474
22.5%
1 5107
17.8%
- 2380
 
8.3%
3 2296
 
8.0%
7 953
 
3.3%
6 894
 
3.1%
5 872
 
3.0%
4 869
 
3.0%
8 862
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26349
91.7%
Dash Punctuation 2380
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7431
28.2%
2 6474
24.6%
1 5107
19.4%
3 2296
 
8.7%
7 953
 
3.6%
6 894
 
3.4%
5 872
 
3.3%
4 869
 
3.3%
8 862
 
3.3%
9 591
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 2380
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28729
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7431
25.9%
2 6474
22.5%
1 5107
17.8%
- 2380
 
8.3%
3 2296
 
8.0%
7 953
 
3.3%
6 894
 
3.1%
5 872
 
3.0%
4 869
 
3.0%
8 862
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28729
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7431
25.9%
2 6474
22.5%
1 5107
17.8%
- 2380
 
8.3%
3 2296
 
8.0%
7 953
 
3.3%
6 894
 
3.1%
5 872
 
3.0%
4 869
 
3.0%
8 862
 
3.0%

소재지시설전화번호
Text

MISSING 

Distinct1460
Distinct (%)98.5%
Missing8518
Missing (%)85.2%
Memory size156.2 KiB
2023-12-11T08:00:52.455340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.394062
Min length7

Characters and Unicode

Total characters16886
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

Unique1439 ?
Unique (%)97.1%

Sample

1st row031 8653111
2nd row031 425 0340
3rd row031 7110057
4th row02 5043629
5th row031 834 2943
ValueCountFrequency (%)
031 1141
31.8%
032 80
 
2.2%
070 35
 
1.0%
02 35
 
1.0%
381 10
 
0.3%
866 9
 
0.3%
846 8
 
0.2%
653 7
 
0.2%
323 7
 
0.2%
212 6
 
0.2%
Other values (1816) 2252
62.7%
2023-12-11T08:00:52.961027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2477
14.7%
0 2419
14.3%
1 2173
12.9%
2146
12.7%
2 1451
8.6%
8 1232
7.3%
7 1155
6.8%
6 1116
6.6%
5 1009
6.0%
9 880
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14740
87.3%
Space Separator 2146
 
12.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2477
16.8%
0 2419
16.4%
1 2173
14.7%
2 1451
9.8%
8 1232
8.4%
7 1155
7.8%
6 1116
7.6%
5 1009
6.8%
9 880
 
6.0%
4 828
 
5.6%
Space Separator
ValueCountFrequency (%)
2146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16886
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 2477
14.7%
0 2419
14.3%
1 2173
12.9%
2146
12.7%
2 1451
8.6%
8 1232
7.3%
7 1155
6.8%
6 1116
6.6%
5 1009
6.0%
9 880
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 2477
14.7%
0 2419
14.3%
1 2173
12.9%
2146
12.7%
2 1451
8.6%
8 1232
7.3%
7 1155
6.8%
6 1116
6.6%
5 1009
6.0%
9 880
 
5.2%

소재지면적정보
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct2910
Distinct (%)53.2%
Missing4528
Missing (%)45.3%
Infinite0
Infinite (%)0.0%
Mean52.417038
Minimum0
Maximum42008
Zeros453
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:00:53.131505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q122.2
median34.23
Q352.8
95-th percentile125.4
Maximum42008
Range42008
Interquartile range (IQR)30.6

Descriptive statistics

Standard deviation568.92152
Coefficient of variation (CV)10.853752
Kurtosis5409.0163
Mean52.417038
Median Absolute Deviation (MAD)14.28
Skewness73.335183
Sum286826.03
Variance323671.7
MonotonicityNot monotonic
2023-12-11T08:00:53.266539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 453
 
4.5%
33.0 53
 
0.5%
30.0 40
 
0.4%
36.0 28
 
0.3%
20.0 27
 
0.3%
40.0 24
 
0.2%
35.0 22
 
0.2%
27.0 20
 
0.2%
32.0 20
 
0.2%
45.0 19
 
0.2%
Other values (2900) 4766
47.7%
(Missing) 4528
45.3%
ValueCountFrequency (%)
0.0 453
4.5%
1.6 1
 
< 0.1%
2.24 1
 
< 0.1%
3.0 2
 
< 0.1%
3.3 2
 
< 0.1%
3.34 1
 
< 0.1%
3.5 1
 
< 0.1%
3.7 1
 
< 0.1%
3.75 1
 
< 0.1%
3.96 1
 
< 0.1%
ValueCountFrequency (%)
42008.0 1
< 0.1%
735.86 1
< 0.1%
601.17 1
< 0.1%
538.26 1
< 0.1%
439.85 1
< 0.1%
389.62 1
< 0.1%
365.18 1
< 0.1%
364.0 1
< 0.1%
349.2 1
< 0.1%
327.0 1
< 0.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1879
Distinct (%)34.7%
Missing4587
Missing (%)45.9%
Infinite0
Infinite (%)0.0%
Mean14356.279
Minimum7428
Maximum31513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:00:53.428024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7428
5-th percentile10362
Q111813
median14544
Q316546
95-th percentile18379
Maximum31513
Range24085
Interquartile range (IQR)4733

Descriptive statistics

Standard deviation2590.8546
Coefficient of variation (CV)0.18046839
Kurtosis-0.8954029
Mean14356.279
Median Absolute Deviation (MAD)2160
Skewness-0.017259027
Sum77710540
Variance6712527.6
MonotonicityNot monotonic
2023-12-11T08:00:53.556613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11473 71
 
0.7%
12913 43
 
0.4%
15011 37
 
0.4%
11476 36
 
0.4%
10071 35
 
0.4%
11444 33
 
0.3%
16509 33
 
0.3%
14637 32
 
0.3%
14544 31
 
0.3%
11813 31
 
0.3%
Other values (1869) 5031
50.3%
(Missing) 4587
45.9%
ValueCountFrequency (%)
7428 1
 
< 0.1%
7584 1
 
< 0.1%
10011 2
< 0.1%
10018 2
< 0.1%
10019 4
< 0.1%
10024 1
 
< 0.1%
10031 3
< 0.1%
10039 1
 
< 0.1%
10056 1
 
< 0.1%
10059 2
< 0.1%
ValueCountFrequency (%)
31513 1
 
< 0.1%
22657 1
 
< 0.1%
18617 1
 
< 0.1%
18611 4
< 0.1%
18606 9
0.1%
18603 1
 
< 0.1%
18602 2
 
< 0.1%
18600 2
 
< 0.1%
18598 1
 
< 0.1%
18594 4
< 0.1%

소재지도로명주소
Text

Distinct9658
Distinct (%)97.2%
Missing68
Missing (%)0.7%
Memory size156.2 KiB
2023-12-11T08:00:53.885860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length61
Mean length36.500403
Min length14

Characters and Unicode

Total characters362522
Distinct characters684
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9402 ?
Unique (%)94.7%

Sample

1st row경기도 양주시 옥정동로5다길 5-13, 1층 일부 (옥정동)
2nd row경기도 성남시 분당구 성남대로916번길 7
3rd row경기도 안양시 동안구 시민대로 317, 대한스마트타워 지상1층 118호 (관양동)
4th row경기도 고양시 덕양구 충경로 44 (행신동,대명프라자 304호)
5th row경기도 광주시 중앙로 147, 2층 (경안동)
ValueCountFrequency (%)
경기도 9928
 
13.3%
1층 2227
 
3.0%
2층 1285
 
1.7%
수원시 1261
 
1.7%
부천시 860
 
1.2%
고양시 763
 
1.0%
성남시 733
 
1.0%
영통구 661
 
0.9%
일부 622
 
0.8%
일부호 620
 
0.8%
Other values (11437) 55645
74.6%
2023-12-11T08:00:54.387420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64710
 
17.8%
1 15809
 
4.4%
동 12405
 
3.4%
, 11158
 
3.1%
시 10905
 
3.0%
2 10821
 
3.0%
경 10343
 
2.9%
기 10308
 
2.8%
도 10268
 
2.8%
로 9601
 
2.6%
Other values (674) 196194
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 200769
55.4%
Space Separator 64710
 
17.8%
Decimal Number 63044
 
17.4%
Other Punctuation 11231
 
3.1%
Close Punctuation 9415
 
2.6%
Open Punctuation 9415
 
2.6%
Dash Punctuation 2324
 
0.6%
Uppercase Letter 1356
 
0.4%
Lowercase Letter 170
 
< 0.1%
Letter Number 44
 
< 0.1%
Other values (3) 44
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 12405
 
6.2%
시 10905
 
5.4%
경 10343
 
5.2%
기 10308
 
5.1%
도 10268
 
5.1%
로 9601
 
4.8%
호 7431
 
3.7%
층 5571
 
2.8%
구 4734
 
2.4%
길 4262
 
2.1%
Other values (598) 114941
57.3%
Uppercase Letter
ValueCountFrequency (%)
B 331
24.4%
A 205
15.1%
C 94
 
6.9%
I 93
 
6.9%
S 69
 
5.1%
L 64
 
4.7%
E 58
 
4.3%
K 42
 
3.1%
D 42
 
3.1%
W 36
 
2.7%
Other values (15) 322
23.7%
Lowercase Letter
ValueCountFrequency (%)
e 54
31.8%
l 14
 
8.2%
a 12
 
7.1%
r 11
 
6.5%
o 10
 
5.9%
k 9
 
5.3%
t 9
 
5.3%
s 8
 
4.7%
h 8
 
4.7%
i 7
 
4.1%
Other values (11) 28
16.5%
Decimal Number
ValueCountFrequency (%)
1 15809
25.1%
2 10821
17.2%
0 7965
12.6%
3 6871
10.9%
4 4868
 
7.7%
5 4273
 
6.8%
6 3614
 
5.7%
7 3311
 
5.3%
8 2955
 
4.7%
9 2557
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 11158
99.4%
. 44
 
0.4%
@ 16
 
0.1%
/ 6
 
0.1%
& 5
 
< 0.1%
: 1
 
< 0.1%
# 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 27
61.4%
Ⅲ 9
 
20.5%
Ⅰ 4
 
9.1%
Ⅳ 2
 
4.5%
Ⅴ 2
 
4.5%
Math Symbol
ValueCountFrequency (%)
~ 41
97.6%
∏ 1
 
2.4%
Space Separator
ValueCountFrequency (%)
64710
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9415
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9415
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2324
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 200767
55.4%
Common 160183
44.2%
Latin 1570
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 12405
 
6.2%
시 10905
 
5.4%
경 10343
 
5.2%
기 10308
 
5.1%
도 10268
 
5.1%
로 9601
 
4.8%
호 7431
 
3.7%
층 5571
 
2.8%
구 4734
 
2.4%
길 4262
 
2.1%
Other values (596) 114939
57.2%
Latin
ValueCountFrequency (%)
B 331
21.1%
A 205
 
13.1%
C 94
 
6.0%
I 93
 
5.9%
S 69
 
4.4%
L 64
 
4.1%
E 58
 
3.7%
e 54
 
3.4%
K 42
 
2.7%
D 42
 
2.7%
Other values (41) 518
33.0%
Common
ValueCountFrequency (%)
64710
40.4%
1 15809
 
9.9%
, 11158
 
7.0%
2 10821
 
6.8%
) 9415
 
5.9%
( 9415
 
5.9%
0 7965
 
5.0%
3 6871
 
4.3%
4 4868
 
3.0%
5 4273
 
2.7%
Other values (15) 14878
 
9.3%
Han
ValueCountFrequency (%)
眞 1
50.0%
愛 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 200767
55.4%
ASCII 161708
44.6%
Number Forms 44
 
< 0.1%
CJK 2
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64710
40.0%
1 15809
 
9.8%
, 11158
 
6.9%
2 10821
 
6.7%
) 9415
 
5.8%
( 9415
 
5.8%
0 7965
 
4.9%
3 6871
 
4.2%
4 4868
 
3.0%
5 4273
 
2.6%
Other values (60) 16403
 
10.1%
Hangul
ValueCountFrequency (%)
동 12405
 
6.2%
시 10905
 
5.4%
경 10343
 
5.2%
기 10308
 
5.1%
도 10268
 
5.1%
로 9601
 
4.8%
호 7431
 
3.7%
층 5571
 
2.8%
구 4734
 
2.4%
길 4262
 
2.1%
Other values (596) 114939
57.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 27
61.4%
Ⅲ 9
 
20.5%
Ⅰ 4
 
9.1%
Ⅳ 2
 
4.5%
Ⅴ 2
 
4.5%
Math Operators
ValueCountFrequency (%)
∏ 1
100.0%
CJK
ValueCountFrequency (%)
眞 1
50.0%
愛 1
50.0%

소재지지번주소
Text

Distinct9406
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:00:54.762041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length55
Mean length29.006
Min length4

Characters and Unicode

Total characters290060
Distinct characters652
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8999 ?
Unique (%)90.0%

Sample

1st row경기도 양주시 옥정동 1081-5 1층 일부
2nd row경기도 성남시 분당구 야탑동 366-3번지 서일빌딩 207호
3rd row경기도 안양시 동안구 관양동 1746-2 대한스마트타워 118호
4th row경기도 고양시 덕양구 행신동 761번지 대명프라자 304호
5th row경기도 광주시 경안동 74-25번지
ValueCountFrequency (%)
경기도 9995
 
16.3%
수원시 1264
 
2.1%
1층 961
 
1.6%
부천시 866
 
1.4%
고양시 765
 
1.2%
성남시 734
 
1.2%
영통구 662
 
1.1%
일부 631
 
1.0%
2층 564
 
0.9%
화성시 534
 
0.9%
Other values (12736) 44343
72.3%
2023-12-11T08:00:55.313974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55509
 
19.1%
1 13589
 
4.7%
동 11584
 
4.0%
시 10701
 
3.7%
기 10308
 
3.6%
도 10239
 
3.5%
경 10098
 
3.5%
2 8016
 
2.8%
- 7556
 
2.6%
0 6951
 
2.4%
Other values (642) 145509
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 164281
56.6%
Decimal Number 59524
 
20.5%
Space Separator 55510
 
19.1%
Dash Punctuation 7556
 
2.6%
Uppercase Letter 1076
 
0.4%
Open Punctuation 649
 
0.2%
Close Punctuation 648
 
0.2%
Other Punctuation 590
 
0.2%
Lowercase Letter 149
 
0.1%
Letter Number 43
 
< 0.1%
Other values (3) 34
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 11584
 
7.1%
시 10701
 
6.5%
기 10308
 
6.3%
도 10239
 
6.2%
경 10098
 
6.1%
지 5991
 
3.6%
호 5120
 
3.1%
구 4665
 
2.8%
번 4538
 
2.8%
양 3053
 
1.9%
Other values (566) 87984
53.6%
Uppercase Letter
ValueCountFrequency (%)
B 207
19.2%
A 155
14.4%
I 84
 
7.8%
C 71
 
6.6%
S 60
 
5.6%
L 58
 
5.4%
E 49
 
4.6%
D 42
 
3.9%
K 36
 
3.3%
W 32
 
3.0%
Other values (15) 282
26.2%
Lowercase Letter
ValueCountFrequency (%)
e 50
33.6%
a 12
 
8.1%
l 12
 
8.1%
r 10
 
6.7%
h 8
 
5.4%
t 8
 
5.4%
k 7
 
4.7%
c 6
 
4.0%
i 6
 
4.0%
o 6
 
4.0%
Other values (11) 24
16.1%
Decimal Number
ValueCountFrequency (%)
1 13589
22.8%
2 8016
13.5%
0 6951
11.7%
3 6110
10.3%
4 5144
 
8.6%
5 4672
 
7.8%
6 4277
 
7.2%
7 3881
 
6.5%
8 3653
 
6.1%
9 3231
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 511
86.6%
. 45
 
7.6%
@ 20
 
3.4%
/ 9
 
1.5%
& 4
 
0.7%
: 1
 
0.2%
Letter Number
ValueCountFrequency (%)
Ⅱ 27
62.8%
Ⅲ 8
 
18.6%
Ⅴ 4
 
9.3%
Ⅰ 3
 
7.0%
Ⅳ 1
 
2.3%
Space Separator
ValueCountFrequency (%)
55509
> 99.9%
　 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 31
96.9%
∏ 1
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 7556
100.0%
Open Punctuation
ValueCountFrequency (%)
( 649
100.0%
Close Punctuation
ValueCountFrequency (%)
) 648
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 164280
56.6%
Common 124511
42.9%
Latin 1268
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 11584
 
7.1%
시 10701
 
6.5%
기 10308
 
6.3%
도 10239
 
6.2%
경 10098
 
6.1%
지 5991
 
3.6%
호 5120
 
3.1%
구 4665
 
2.8%
번 4538
 
2.8%
양 3053
 
1.9%
Other values (565) 87983
53.6%
Latin
ValueCountFrequency (%)
B 207
16.3%
A 155
 
12.2%
I 84
 
6.6%
C 71
 
5.6%
S 60
 
4.7%
L 58
 
4.6%
e 50
 
3.9%
E 49
 
3.9%
D 42
 
3.3%
K 36
 
2.8%
Other values (41) 456
36.0%
Common
ValueCountFrequency (%)
55509
44.6%
1 13589
 
10.9%
2 8016
 
6.4%
- 7556
 
6.1%
0 6951
 
5.6%
3 6110
 
4.9%
4 5144
 
4.1%
5 4672
 
3.8%
6 4277
 
3.4%
7 3881
 
3.1%
Other values (15) 8806
 
7.1%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 164279
56.6%
ASCII 125734
43.3%
Number Forms 43
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Math Operators 1
 
< 0.1%
CJK 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55509
44.1%
1 13589
 
10.8%
2 8016
 
6.4%
- 7556
 
6.0%
0 6951
 
5.5%
3 6110
 
4.9%
4 5144
 
4.1%
5 4672
 
3.7%
6 4277
 
3.4%
7 3881
 
3.1%
Other values (59) 10029
 
8.0%
Hangul
ValueCountFrequency (%)
동 11584
 
7.1%
시 10701
 
6.5%
기 10308
 
6.3%
도 10239
 
6.2%
경 10098
 
6.1%
지 5991
 
3.6%
호 5120
 
3.1%
구 4665
 
2.8%
번 4538
 
2.8%
양 3053
 
1.9%
Other values (564) 87982
53.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 27
62.8%
Ⅲ 8
 
18.6%
Ⅴ 4
 
9.3%
Ⅰ 3
 
7.0%
Ⅳ 1
 
2.3%
Compat Jamo
ValueCountFrequency (%)
ㅎ 1
100.0%
Math Operators
ValueCountFrequency (%)
∏ 1
100.0%
CJK
ValueCountFrequency (%)
愛 1
100.0%
None
ValueCountFrequency (%)
　 1
100.0%

소재지우편번호
Text

Distinct2443
Distinct (%)24.4%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-11T08:00:55.688870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.3614446
Min length5

Characters and Unicode

Total characters63589
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

Unique947 ?
Unique (%)9.5%

Sample

1st row482-130
2nd row463827
3rd row431-060
4th row412220
5th row464801
ValueCountFrequency (%)
482-130 133
 
1.3%
443-270 106
 
1.1%
445160 81
 
0.8%
465-150 77
 
0.8%
482-050 71
 
0.7%
443-400 68
 
0.7%
410837 60
 
0.6%
482-060 55
 
0.6%
410-837 53
 
0.5%
415-080 52
 
0.5%
Other values (2433) 9240
92.4%
2023-12-11T08:00:56.198845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 14617
23.0%
8 7772
12.2%
0 7265
11.4%
1 6878
10.8%
2 5075
 
8.0%
3 4886
 
7.7%
- 4758
 
7.5%
5 4236
 
6.7%
6 3570
 
5.6%
7 2656
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58831
92.5%
Dash Punctuation 4758
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 14617
24.8%
8 7772
13.2%
0 7265
12.3%
1 6878
11.7%
2 5075
 
8.6%
3 4886
 
8.3%
5 4236
 
7.2%
6 3570
 
6.1%
7 2656
 
4.5%
9 1876
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 4758
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63589
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 14617
23.0%
8 7772
12.2%
0 7265
11.4%
1 6878
10.8%
2 5075
 
8.0%
3 4886
 
7.7%
- 4758
 
7.5%
5 4236
 
6.7%
6 3570
 
5.6%
7 2656
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63589
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 14617
23.0%
8 7772
12.2%
0 7265
11.4%
1 6878
10.8%
2 5075
 
8.0%
3 4886
 
7.7%
- 4758
 
7.5%
5 4236
 
6.7%
6 3570
 
5.6%
7 2656
 
4.2%

WGS84위도
Real number (ℝ)

Distinct7238
Distinct (%)72.6%
Missing35
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean37.435061
Minimum36.782665
Maximum38.158609
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:00:56.358535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.782665
5-th percentile37.079352
Q137.282
median37.395646
Q337.622942
95-th percentile37.816763
Maximum38.158609
Range1.3759441
Interquartile range (IQR)0.34094212

Descriptive statistics

Standard deviation0.21186297
Coefficient of variation (CV)0.0056594796
Kurtosis-0.52962522
Mean37.435061
Median Absolute Deviation (MAD)0.12998868
Skewness0.19030512
Sum373040.39
Variance0.044885917
MonotonicityNot monotonic
2023-12-11T08:00:56.507365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4853661029 29
 
0.3%
37.3923317778 20
 
0.2%
37.2819999319 20
 
0.2%
37.5051300224 18
 
0.2%
37.3186720112 13
 
0.1%
37.2915837894 13
 
0.1%
37.3613295298 12
 
0.1%
37.3941527748 12
 
0.1%
37.5041102158 12
 
0.1%
37.6087490072 11
 
0.1%
Other values (7228) 9805
98.0%
(Missing) 35
 
0.4%
ValueCountFrequency (%)
36.7826649744 1
< 0.1%
36.9430828013 1
< 0.1%
36.9587665345 1
< 0.1%
36.9591575959 1
< 0.1%
36.9597520347 1
< 0.1%
36.9598214981 1
< 0.1%
36.9603843188 2
< 0.1%
36.9605133359 1
< 0.1%
36.9624069212 1
< 0.1%
36.9644518722 1
< 0.1%
ValueCountFrequency (%)
38.1586090441 1
< 0.1%
38.0997438001 1
< 0.1%
38.0988563659 1
< 0.1%
38.0912697166 1
< 0.1%
38.0894446557 1
< 0.1%
38.089154984 1
< 0.1%
38.04214687 1
< 0.1%
38.0329498273 1
< 0.1%
38.0291556424 1
< 0.1%
38.0287320503 1
< 0.1%

WGS84경도
Real number (ℝ)

Distinct7238
Distinct (%)72.6%
Missing35
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean126.99248
Minimum126.55544
Maximum127.65125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:00:56.673215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55544
5-th percentile126.73705
Q1126.83082
median127.03565
Q3127.10614
95-th percentile127.25667
Maximum127.65125
Range1.0958132
Interquartile range (IQR)0.27532683

Descriptive statistics

Standard deviation0.18112747
Coefficient of variation (CV)0.001426285
Kurtosis0.58311097
Mean126.99248
Median Absolute Deviation (MAD)0.10758509
Skewness0.43479766
Sum1265480
Variance0.03280716
MonotonicityNot monotonic
2023-12-11T08:00:56.802991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7803021466 29
 
0.3%
126.9565123356 20
 
0.2%
127.0575579762 20
 
0.2%
126.7537281611 18
 
0.2%
126.8364965083 13
 
0.1%
127.0485551442 13
 
0.1%
127.105560326 12
 
0.1%
126.9644638738 12
 
0.1%
126.7752346544 12
 
0.1%
127.1589920361 11
 
0.1%
Other values (7228) 9805
98.0%
(Missing) 35
 
0.4%
ValueCountFrequency (%)
126.5554354776 1
 
< 0.1%
126.5649396805 1
 
< 0.1%
126.5834037736 1
 
< 0.1%
126.5841675178 1
 
< 0.1%
126.5927922822 3
< 0.1%
126.5940538809 2
< 0.1%
126.5958031627 1
 
< 0.1%
126.5965892909 2
< 0.1%
126.5973215677 1
 
< 0.1%
126.5976057487 2
< 0.1%
ValueCountFrequency (%)
127.6512486669 1
 
< 0.1%
127.6497639185 1
 
< 0.1%
127.6488912206 1
 
< 0.1%
127.6485268246 1
 
< 0.1%
127.6482480426 2
< 0.1%
127.6470072724 1
 
< 0.1%
127.6458851503 2
< 0.1%
127.6432635465 1
 
< 0.1%
127.6426790522 1
 
< 0.1%
127.6416386992 3
< 0.1%

업태구분명정보
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4523 
일반미용업
2719 
피부미용업
1287 
네일아트업
1015 
메이크업업
 
411
Other values (2)
 
45

Length

Max length6
Median length5
Mean length4.5346
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4523
45.2%
일반미용업 2719
27.2%
피부미용업 1287
 
12.9%
네일아트업 1015
 
10.2%
메이크업업 411
 
4.1%
기타 44
 
0.4%
미용업 기타 1
 
< 0.1%

Length

2023-12-11T08:00:56.954815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:00:57.065235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4523
45.2%
일반미용업 2719
27.2%
피부미용업 1287
 
12.9%
네일아트업 1015
 
10.1%
메이크업업 411
 
4.1%
기타 45
 
0.4%
미용업 1
 
< 0.1%

X좌표값
Real number (ℝ)

MISSING 

Distinct3984
Distinct (%)75.2%
Missing4699
Missing (%)47.0%
Infinite0
Infinite (%)0.0%
Mean199834.94
Minimum160741.87
Maximum257717.91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:00:57.220859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum160741.87
5-th percentile176413.41
Q1185115.72
median203941.79
Q3208811.04
95-th percentile222756.37
Maximum257717.91
Range96976.043
Interquartile range (IQR)23695.317

Descriptive statistics

Standard deviation16015.87
Coefficient of variation (CV)0.080145494
Kurtosis0.73902019
Mean199834.94
Median Absolute Deviation (MAD)8327.9337
Skewness0.35992625
Sum1.059325 × 109
Variance2.5650808 × 108
MonotonicityNot monotonic
2023-12-11T08:00:57.379279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180483.202220306 28
 
0.3%
205026.079641798 22
 
0.2%
204219.521658448 15
 
0.1%
196080.532197962 13
 
0.1%
180055.338981845 13
 
0.1%
204977.175329834 10
 
0.1%
176072.60072494 10
 
0.1%
179427.40778259 10
 
0.1%
213941.170509698 9
 
0.1%
209258.186310397 9
 
0.1%
Other values (3974) 5162
51.6%
(Missing) 4699
47.0%
ValueCountFrequency (%)
160741.869208895 1
< 0.1%
163173.767767807 1
< 0.1%
164005.287807315 1
< 0.1%
164104.282468862 2
< 0.1%
164279.70241321 1
< 0.1%
164356.39726346 1
< 0.1%
164446.767685534 1
< 0.1%
164466.752054693 1
< 0.1%
164562.022750105 1
< 0.1%
164652.919954456 1
< 0.1%
ValueCountFrequency (%)
257717.912489153 1
< 0.1%
257423.487878228 1
< 0.1%
257406.362654 1
< 0.1%
257292.779340695 1
< 0.1%
257189.696962984 2
< 0.1%
256813.796166822 2
< 0.1%
256791.054956366 1
< 0.1%
256732.402523507 1
< 0.1%
256724.101322993 2
< 0.1%
256610.411591591 2
< 0.1%

Y좌표값
Real number (ℝ)

MISSING 

Distinct3984
Distinct (%)75.2%
Missing4699
Missing (%)47.0%
Infinite0
Infinite (%)0.0%
Mean437603.17
Minimum364582.18
Maximum517330.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:00:57.504363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum364582.18
5-th percentile395861.99
Q1419057.01
median432715.71
Q3460148.44
95-th percentile479795.48
Maximum517330.25
Range152748.07
Interquartile range (IQR)41091.43

Descriptive statistics

Standard deviation25064.189
Coefficient of variation (CV)0.057276069
Kurtosis-0.74862764
Mean437603.17
Median Absolute Deviation (MAD)16062.353
Skewness0.18755814
Sum2.3197344 × 109
Variance6.2821358 × 108
MonotonicityNot monotonic
2023-12-11T08:00:57.639866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442608.40965091 28
 
0.3%
420062.878231009 22
 
0.2%
421105.173167299 15
 
0.1%
432244.867412549 13
 
0.1%
444675.457254185 13
 
0.1%
420627.234160383 10
 
0.1%
429602.843996773 10
 
0.1%
444580.076928048 10
 
0.1%
456267.182532575 9
 
0.1%
477061.318061355 9
 
0.1%
Other values (3974) 5162
51.6%
(Missing) 4699
47.0%
ValueCountFrequency (%)
364582.184571225 1
< 0.1%
382424.45801559 1
< 0.1%
384132.753148783 1
< 0.1%
384252.034045157 1
< 0.1%
384325.774886246 1
< 0.1%
384760.3030791 1
< 0.1%
384791.555113728 1
< 0.1%
384993.37806625 1
< 0.1%
386256.250095257 1
< 0.1%
386287.834502281 1
< 0.1%
ValueCountFrequency (%)
517330.2541113 1
< 0.1%
510769.611376078 1
< 0.1%
510672.313478556 1
< 0.1%
509626.568633858 1
< 0.1%
504436.376951031 1
< 0.1%
503351.516780245 1
< 0.1%
502630.308521877 1
< 0.1%
495141.057622823 1
< 0.1%
494919.503726598 1
< 0.1%
494813.508919827 1
< 0.1%

위생업태명정보
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4523 
일반미용업
2191 
피부미용업
1026 
네일미용업
706 
종합미용업
 
439
Other values (14)
1115 

Length

Max length23
Median length19
Mean length5.467
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4523
45.2%
일반미용업 2191
21.9%
피부미용업 1026
 
10.3%
네일미용업 706
 
7.1%
종합미용업 439
 
4.4%
화장ㆍ분장 미용업 273
 
2.7%
피부미용업, 네일미용업 146
 
1.5%
네일미용업, 화장ㆍ분장 미용업 142
 
1.4%
피부미용업, 화장ㆍ분장 미용업 127
 
1.3%
미용업 117
 
1.2%
Other values (9) 310
 
3.1%

Length

2023-12-11T08:00:57.790797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4523
38.7%
일반미용업 2424
20.8%
피부미용업 1454
 
12.5%
네일미용업 1177
 
10.1%
미용업 886
 
7.6%
화장ㆍ분장 769
 
6.6%
종합미용업 439
 
3.8%
미용업(피부 2
 
< 0.1%
미용업(손톱ㆍ발톱 1
 
< 0.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)0.5%
Missing4561
Missing (%)45.6%
Infinite0
Infinite (%)0.0%
Mean0.75068946
Minimum0
Maximum73
Zeros4435
Zeros (%)44.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:00:57.925271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum73
Range73
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.438502
Coefficient of variation (CV)3.2483498
Kurtosis186.26703
Mean0.75068946
Median Absolute Deviation (MAD)0
Skewness9.4918553
Sum4083
Variance5.9462918
MonotonicityNot monotonic
2023-12-11T08:00:58.060894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 4435
44.4%
1 202
 
2.0%
3 188
 
1.9%
2 185
 
1.8%
4 152
 
1.5%
5 92
 
0.9%
8 37
 
0.4%
6 34
 
0.3%
7 29
 
0.3%
10 25
 
0.2%
Other values (16) 60
 
0.6%
(Missing) 4561
45.6%
ValueCountFrequency (%)
0 4435
44.4%
1 202
 
2.0%
2 185
 
1.8%
3 188
 
1.9%
4 152
 
1.5%
5 92
 
0.9%
6 34
 
0.3%
7 29
 
0.3%
8 37
 
0.4%
9 17
 
0.2%
ValueCountFrequency (%)
73 1
 
< 0.1%
39 2
< 0.1%
37 1
 
< 0.1%
26 2
< 0.1%
23 1
 
< 0.1%
22 1
 
< 0.1%
21 1
 
< 0.1%
20 2
< 0.1%
17 1
 
< 0.1%
16 3
< 0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.2%
Missing4596
Missing (%)46.0%
Infinite0
Infinite (%)0.0%
Mean0.14156181
Minimum0
Maximum10
Zeros4995
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:00:58.171780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.61607578
Coefficient of variation (CV)4.3519915
Kurtosis49.050637
Mean0.14156181
Median Absolute Deviation (MAD)0
Skewness6.1704234
Sum765
Variance0.37954936
MonotonicityNot monotonic
2023-12-11T08:00:58.275895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 4995
50.0%
1 239
 
2.4%
2 72
 
0.7%
3 45
 
0.4%
4 34
 
0.3%
5 12
 
0.1%
7 3
 
< 0.1%
6 2
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 4596
46.0%
ValueCountFrequency (%)
0 4995
50.0%
1 239
 
2.4%
2 72
 
0.7%
3 45
 
0.4%
4 34
 
0.3%
5 12
 
0.1%
6 2
 
< 0.1%
7 3
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
8 1
 
< 0.1%
7 3
 
< 0.1%
6 2
 
< 0.1%
5 12
 
0.1%
4 34
 
0.3%
3 45
 
0.4%
2 72
 
0.7%
1 239
 
2.4%
0 4995
50.0%

사용시작지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)0.3%
Missing4681
Missing (%)46.8%
Infinite0
Infinite (%)0.0%
Mean0.90186125
Minimum0
Maximum71
Zeros2772
Zeros (%)27.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:00:58.403008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum71
Range71
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.704405
Coefficient of variation (CV)1.889875
Kurtosis544.95474
Mean0.90186125
Median Absolute Deviation (MAD)0
Skewness14.892916
Sum4797
Variance2.9049965
MonotonicityNot monotonic
2023-12-11T08:00:58.525918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 2772
27.7%
1 1470
 
14.7%
2 611
 
6.1%
3 216
 
2.2%
4 106
 
1.1%
5 55
 
0.5%
6 31
 
0.3%
8 19
 
0.2%
7 19
 
0.2%
10 8
 
0.1%
Other values (7) 12
 
0.1%
(Missing) 4681
46.8%
ValueCountFrequency (%)
0 2772
27.7%
1 1470
14.7%
2 611
 
6.1%
3 216
 
2.2%
4 106
 
1.1%
5 55
 
0.5%
6 31
 
0.3%
7 19
 
0.2%
8 19
 
0.2%
9 3
 
< 0.1%
ValueCountFrequency (%)
71 1
 
< 0.1%
16 1
 
< 0.1%
15 1
 
< 0.1%
14 2
 
< 0.1%
13 2
 
< 0.1%
12 2
 
< 0.1%
10 8
0.1%
9 3
 
< 0.1%
8 19
0.2%
7 19
0.2%

사용끝지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.3%
Missing4701
Missing (%)47.0%
Infinite0
Infinite (%)0.0%
Mean0.80637856
Minimum0
Maximum16
Zeros3012
Zeros (%)30.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:00:58.635731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum16
Range16
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3644453
Coefficient of variation (CV)1.6920654
Kurtosis18.171766
Mean0.80637856
Median Absolute Deviation (MAD)0
Skewness3.3290726
Sum4273
Variance1.8617109
MonotonicityNot monotonic
2023-12-11T08:00:58.956678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 3012
30.1%
1 1302
 
13.0%
2 558
 
5.6%
3 202
 
2.0%
4 98
 
1.0%
5 45
 
0.4%
6 29
 
0.3%
8 19
 
0.2%
7 19
 
0.2%
10 5
 
0.1%
Other values (6) 10
 
0.1%
(Missing) 4701
47.0%
ValueCountFrequency (%)
0 3012
30.1%
1 1302
13.0%
2 558
 
5.6%
3 202
 
2.0%
4 98
 
1.0%
5 45
 
0.4%
6 29
 
0.3%
7 19
 
0.2%
8 19
 
0.2%
9 3
 
< 0.1%
ValueCountFrequency (%)
16 1
 
< 0.1%
15 1
 
< 0.1%
14 2
 
< 0.1%
13 1
 
< 0.1%
12 2
 
< 0.1%
10 5
 
0.1%
9 3
 
< 0.1%
8 19
0.2%
7 19
0.2%
6 29
0.3%

사용시작지하층수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5088 
<NA>
4821 
1
 
72
2
 
17
3
 
2

Length

Max length4
Median length1
Mean length2.4463
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5088
50.9%
<NA> 4821
48.2%
1 72
 
0.7%
2 17
 
0.2%
3 2
 
< 0.1%

Length

2023-12-11T08:00:59.107568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:00:59.229276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5088
50.9%
na 4821
48.2%
1 72
 
0.7%
2 17
 
0.2%
3 2
 
< 0.1%

사용끝지하층수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5090 
<NA>
4827 
1
 
67
2
 
14
3
 
2

Length

Max length4
Median length1
Mean length2.4481
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5090
50.9%
<NA> 4827
48.3%
1 67
 
0.7%
2 14
 
0.1%
3 2
 
< 0.1%

Length

2023-12-11T08:00:59.326461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:00:59.415425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5090
50.9%
na 4827
48.3%
1 67
 
0.7%
2 14
 
0.1%
3 2
 
< 0.1%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5397 
<NA>
4603 

Length

Max length4
Median length1
Mean length2.3809
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5397
54.0%
<NA> 4603
46.0%

Length

2023-12-11T08:00:59.510564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:00:59.594355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5397
54.0%
na 4603
46.0%

양실수
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5396 
<NA>
4603 
19
 
1

Length

Max length4
Median length1
Mean length2.381
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5396
54.0%
<NA> 4603
46.0%
19 1
 
< 0.1%

Length

2023-12-11T08:00:59.682975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:00:59.776301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5396
54.0%
na 4603
46.0%
19 1
 
< 0.1%

욕실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5397 
<NA>
4603 

Length

Max length4
Median length1
Mean length2.3809
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5397
54.0%
<NA> 4603
46.0%

Length

2023-12-11T08:00:59.869725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:00:59.948222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5397
54.0%
na 4603
46.0%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing4539
Missing (%)45.4%
Memory size97.7 KiB
False
5461 
(Missing)
4539 
ValueCountFrequency (%)
False 5461
54.6%
(Missing) 4539
45.4%
2023-12-11T08:01:00.033497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

조건부허가신고사유
Text

MISSING 

Distinct6
Distinct (%)85.7%
Missing9993
Missing (%)99.9%
Memory size156.2 KiB
2023-12-11T08:01:00.193359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length30
Mean length30
Min length8

Characters and Unicode

Total characters210
Distinct characters74
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)71.4%

Sample

1st row국유재산 유상 사용허가서 기간에 따라 조건부 기간 설정
2nd row공유미용실 기간: 2023. 4.5. ~ 2025. 4. 4. 장소:B04 (공유면적 241.37㎡)
3rd row체류기간 연장 시 보고 바람
4th row산업통상자원부(확인서-23호)규제특례확인서에 따라, 조성아헤어와 공동영업장 사용
5th row2층은 영업면적에서 제외
ValueCountFrequency (%)
따라 3
 
7.7%
산업통상자원부(확인서-23호)규제특례확인서에 2
 
5.1%
사용 2
 
5.1%
기간 2
 
5.1%
4 2
 
5.1%
공동영업장 2
 
5.1%
조성아헤어와 2
 
5.1%
체류기간내 1
 
2.6%
제외 1
 
2.6%
영업면적에서 1
 
2.6%
Other values (21) 21
53.8%
2023-12-11T08:01:00.473439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
 
15.2%
2 8
 
3.8%
. 7
 
3.3%
서 6
 
2.9%
업 6
 
2.9%
4 5
 
2.4%
기 5
 
2.4%
간 5
 
2.4%
장 4
 
1.9%
3 4
 
1.9%
Other values (64) 128
61.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 132
62.9%
Space Separator 32
 
15.2%
Decimal Number 24
 
11.4%
Other Punctuation 11
 
5.2%
Close Punctuation 3
 
1.4%
Open Punctuation 3
 
1.4%
Dash Punctuation 2
 
1.0%
Other Symbol 1
 
0.5%
Uppercase Letter 1
 
0.5%
Math Symbol 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 6
 
4.5%
업 6
 
4.5%
기 5
 
3.8%
간 5
 
3.8%
장 4
 
3.0%
영 4
 
3.0%
인 4
 
3.0%
확 4
 
3.0%
유 4
 
3.0%
용 4
 
3.0%
Other values (47) 86
65.2%
Decimal Number
ValueCountFrequency (%)
2 8
33.3%
4 5
20.8%
3 4
16.7%
0 3
 
12.5%
5 2
 
8.3%
7 1
 
4.2%
1 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 7
63.6%
: 2
 
18.2%
, 2
 
18.2%
Space Separator
ValueCountFrequency (%)
32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 132
62.9%
Common 77
36.7%
Latin 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 6
 
4.5%
업 6
 
4.5%
기 5
 
3.8%
간 5
 
3.8%
장 4
 
3.0%
영 4
 
3.0%
인 4
 
3.0%
확 4
 
3.0%
유 4
 
3.0%
용 4
 
3.0%
Other values (47) 86
65.2%
Common
ValueCountFrequency (%)
32
41.6%
2 8
 
10.4%
. 7
 
9.1%
4 5
 
6.5%
3 4
 
5.2%
0 3
 
3.9%
) 3
 
3.9%
( 3
 
3.9%
: 2
 
2.6%
5 2
 
2.6%
Other values (6) 8
 
10.4%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 132
62.9%
ASCII 77
36.7%
CJK Compat 1
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
41.6%
2 8
 
10.4%
. 7
 
9.1%
4 5
 
6.5%
3 4
 
5.2%
0 3
 
3.9%
) 3
 
3.9%
( 3
 
3.9%
: 2
 
2.6%
5 2
 
2.6%
Other values (6) 8
 
10.4%
Hangul
ValueCountFrequency (%)
서 6
 
4.5%
업 6
 
4.5%
기 5
 
3.8%
간 5
 
3.8%
장 4
 
3.0%
영 4
 
3.0%
인 4
 
3.0%
확 4
 
3.0%
유 4
 
3.0%
용 4
 
3.0%
Other values (47) 86
65.2%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9994 
20230127
 
2
20210715
 
1
20230921
 
1
20220712
 
1

Length

Max length8
Median length4
Mean length4.0024
Min length4

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9994
99.9%
20230127 2
 
< 0.1%
20210715 1
 
< 0.1%
20230921 1
 
< 0.1%
20220712 1
 
< 0.1%
20220829 1
 
< 0.1%

Length

2023-12-11T08:01:00.590620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:01:00.721744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9994
99.9%
20230127 2
 
< 0.1%
20210715 1
 
< 0.1%
20230921 1
 
< 0.1%
20220712 1
 
< 0.1%
20220829 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9994 
20250131
 
2
20240714
 
1
20261030
 
1
20240226
 
1

Length

Max length8
Median length4
Mean length4.0024
Min length4

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9994
99.9%
20250131 2
 
< 0.1%
20240714 1
 
< 0.1%
20261030 1
 
< 0.1%
20240226 1
 
< 0.1%
20230428 1
 
< 0.1%

Length

2023-12-11T08:01:00.845382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:01:00.957555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9994
99.9%
20250131 2
 
< 0.1%
20240714 1
 
< 0.1%
20261030 1
 
< 0.1%
20240226 1
 
< 0.1%
20230428 1
 
< 0.1%

세탁기수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5391 
<NA>
4609 

Length

Max length4
Median length1
Mean length2.3827
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5391
53.9%
<NA> 4609
46.1%

Length

2023-12-11T08:01:01.066085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:01:01.155569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5391
53.9%
na 4609
46.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.1%
Missing4745
Missing (%)47.4%
Infinite0
Infinite (%)0.0%
Mean0.053472883
Minimum0
Maximum6
Zeros5017
Zeros (%)50.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:01:01.230812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.28205231
Coefficient of variation (CV)5.2746793
Kurtosis119.60641
Mean0.053472883
Median Absolute Deviation (MAD)0
Skewness8.6311651
Sum281
Variance0.079553506
MonotonicityNot monotonic
2023-12-11T08:01:01.319955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 5017
50.2%
1 212
 
2.1%
2 18
 
0.2%
3 4
 
< 0.1%
6 2
 
< 0.1%
5 1
 
< 0.1%
4 1
 
< 0.1%
(Missing) 4745
47.4%
ValueCountFrequency (%)
0 5017
50.2%
1 212
 
2.1%
2 18
 
0.2%
3 4
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 2
 
< 0.1%
ValueCountFrequency (%)
6 2
 
< 0.1%
5 1
 
< 0.1%
4 1
 
< 0.1%
3 4
 
< 0.1%
2 18
 
0.2%
1 212
 
2.1%
0 5017
50.2%

남성종사자수
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5230 
<NA>
4752 
1
 
17
2
 
1

Length

Max length4
Median length1
Mean length2.4256
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5230
52.3%
<NA> 4752
47.5%
1 17
 
0.2%
2 1
 
< 0.1%

Length

2023-12-11T08:01:01.425868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:01:01.512589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5230
52.3%
na 4752
47.5%
1 17
 
0.2%
2 1
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5382 
<NA>
4618 

Length

Max length4
Median length1
Mean length2.3854
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5382
53.8%
<NA> 4618
46.2%

Length

2023-12-11T08:01:01.606775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:01:01.685968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5382
53.8%
na 4618
46.2%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size97.7 KiB
False
9996 
True
 
3
(Missing)
 
1
ValueCountFrequency (%)
False 9996
> 99.9%
True 3
 
< 0.1%
(Missing) 1
 
< 0.1%
2023-12-11T08:01:01.762178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값위생업태명정보건물지상층수건물지하층수사용시작지상층수사용끝지상층수사용시작지하층수사용끝지하층수한실수양실수욕실수발한실여부조건부허가신고사유조건부허가시작일자조건부허가종료일자세탁기수여성종사자수남성종사자수회수건조수다중이용업소여부
12421양주시도노헤어룸2021-06-08<NA>1영업<NA>031 865311119.011476경기도 양주시 옥정동로5다길 5-13, 1층 일부 (옥정동)경기도 양주시 옥정동 1081-5 1층 일부482-13037.815448127.097976일반미용업208558.135407479214.939132일반미용업001100000N<NA><NA><NA>0000N
6891성남시에스더 피부샵20090623<NA><NA>폐업 등20101110<NA><NA><NA>경기도 성남시 분당구 성남대로916번길 7경기도 성남시 분당구 야탑동 366-3번지 서일빌딩 207호46382737.411155127.129866<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
11529안양시시선살롱2020-03-30<NA>1영업<NA>031 425 034041.5814055경기도 안양시 동안구 시민대로 317, 대한스마트타워 지상1층 118호 (관양동)경기도 안양시 동안구 관양동 1746-2 대한스마트타워 118호431-06037.396266126.965375일반미용업196877.232291432687.63583일반미용업000000000N<NA><NA><NA>0000N
524고양시스킨아트 에스테틱20110706<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 덕양구 충경로 44 (행신동,대명프라자 304호)경기도 고양시 덕양구 행신동 761번지 대명프라자 304호41222037.615297126.83447<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
2030광주시피부사랑 에스테틱20180823<NA><NA>운영중<NA><NA><NA><NA>경기도 광주시 중앙로 147, 2층 (경안동)경기도 광주시 경안동 74-25번지46480137.412837127.256895<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
18334화성시뷰티렉스20100108<NA><NA>폐업 등20180802<NA><NA><NA>경기도 화성시 향남읍 향남로 392 (우성메디피아 6층 606호)경기도 화성시 향남읍 행정리 487-6번지 우성메디피아 6층 606호44592637.130023126.92149<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
16337평택시이엠씨헤어2023-07-28<NA>1영업<NA><NA>47.3618008경기도 평택시 고덕갈평6길 25, 고덕로자벨1 주건축물제1동 317호 (고덕동)경기도 평택시 고덕동 1887-31800837.057306127.048237일반미용업204219.321571395067.783815일반미용업003300000N<NA><NA><NA>0000N
1522광명시태후사랑2016-07-15<NA>1영업<NA><NA>11.2214291경기도 광명시 광명로831번길 14, 1층 일부호 (광명동)경기도 광명시 광명동 347-1423-81637.473964126.850213일반미용업186681.576766441319.520337일반미용업00<NA><NA><NA><NA>000N<NA><NA><NA>0000N
5909성남시에이바헤어 분당수내역점2016-01-25<NA>1영업<NA>031 7110057135.4513595경기도 성남시 분당구 백현로101번길 20 (수내동, 그린프라자빌딩 202호)경기도 성남시 분당구 수내동 19-2 그린프라자빌딩 202호463-82537.377264127.113078일반미용업209944.170274430582.126594일반미용업002200000N<NA><NA><NA>0000N
13565오산시스킨시아20130830<NA><NA>폐업 등20150130<NA><NA><NA>경기도 오산시 대원로 72, 1층 107호 (원동)경기도 오산시 원동 815-9번지 1층 107호44706037.146119127.076458<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값위생업태명정보건물지상층수건물지하층수사용시작지상층수사용끝지상층수사용시작지하층수사용끝지하층수한실수양실수욕실수발한실여부조건부허가신고사유조건부허가시작일자조건부허가종료일자세탁기수여성종사자수남성종사자수회수건조수다중이용업소여부
13208양평군미앤미20100408<NA><NA>폐업 등20111130<NA><NA><NA>경기도 양평군 양평읍 시민로 15경기도 양평군 양평읍 양근리 206-5번지 (2층)47680237.489829127.49336<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
11584안양시네일하이(nail hi)2021-04-15<NA>1영업<NA><NA>10.814070경기도 안양시 동안구 귀인로 253, 초원대원아파트 대원종합상가 지상1층 114호 (평촌동)경기도 안양시 동안구 평촌동 898-6 초원대원아파트 대원종합상가 114호431-74337.387673126.966611네일아트업196990.897868431833.592864네일미용업000000000N<NA><NA><NA>0000N
14049용인시프리티(Pretty)피부관리20110506<NA><NA>운영중<NA><NA><NA><NA>경기도 용인시 수지구 현암로 136 (죽전동,세종프라자 302호)경기도 용인시 수지구 죽전동 1191-1번지 세종프라자 302호44880837.33151127.124409<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
13145양평군소연헤어2023-11-01<NA>1영업<NA><NA>30.3612571경기도 양평군 강상면 강남로 762, 1층경기도 양평군 강상면 병산리 88-2476-91337.492798127.462692일반미용업240861.031384443501.612616일반미용업001100000N<NA><NA><NA>0000N
3662남양주시동네미용실2023-04-26<NA>1영업<NA><NA>47.4912141경기도 남양주시 천마산로14번길 9, 1층 일부 (호평동)경기도 남양주시 호평동 405-36 1층 일부472-12037.663622127.248653일반미용업221869.734521462386.437102일반미용업000000000N<NA><NA><NA>0000N
17384하남시뷰티관리실20090714<NA><NA>폐업 등20100127<NA><NA><NA>경기도 하남시 신장로 156경기도 하남시 덕풍동 394-1번지 하남프라자 105호46581337.53993127.201946<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
15129의정부시오헤어(O hair)2016-09-28<NA>2폐업2023-05-01031 837 2235128.0<NA>경기도 의정부시 평화로 381, 203, 204호 (호원동)경기도 의정부시 호원동 414-9 203호480-86737.725982127.047872일반미용업204148.651582469280.659192일반미용업002200000N<NA><NA><NA>0100N
18202화성시윤힐링스킨케어2022-03-07<NA>2폐업2023-08-16<NA>82.0818611경기도 화성시 향남읍 상신하길로298번길 7-11, 1동 3층 304호경기도 화성시 향남읍 하길리 1472-4445-93837.115523126.911234피부미용업192039.632638401532.373074피부미용업003300000N<NA><NA><NA>0000N
8344수원시올라운드뷰티(Allround-beauty)2023-04-18<NA>1영업<NA><NA>44.5916471경기도 수원시 팔달구 중부대로 110, 한라시그마팰리스 2층 211호 (인계동)경기도 수원시 팔달구 인계동 206 한라시그마팰리스442-82737.277409127.028742네일아트업202484.290248419497.969593피부미용업, 네일미용업2652200000N<NA><NA><NA>0000N
15335의정부시프린세스 스킨케어20110309<NA><NA>폐업 등20121213<NA><NA><NA><NA>경기도 의정부시 호원동 467-8번지 롯데상가동 203호48085637.702484127.047799<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N

Duplicate rows

Most frequently occurring

시군명사업장명인허가일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값위생업태명정보건물지상층수건물지하층수사용시작지상층수사용끝지상층수사용시작지하층수사용끝지하층수한실수양실수욕실수발한실여부조건부허가신고사유조건부허가시작일자조건부허가종료일자세탁기수여성종사자수남성종사자수회수건조수다중이용업소여부# duplicates
0화성시시선에스테틱20160620<NA>폐업 등20170911<NA><NA><NA>경기도 화성시 동탄솔빛로 52, 105일부호 (반송동, 금탑프라자)경기도 화성시 반송동 217-5번지 금탑프라자 105일부호44516037.193352127.073636<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N3