Overview

Dataset statistics

Number of variables13
Number of observations303
Missing cells241
Missing cells (%)6.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.4 KiB
Average record size in memory109.4 B

Variable types

Categorical4
Text3
Numeric5
Boolean1

Dataset

Description다단계판매기타(복합등) 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=E73FPYX8HMQ9TTAV878B14541670&infSeq=1

Alerts

다중이용업소여부 has constant value ""Constant
위생업종명 is highly overall correlated with 소재지우편번호 and 7 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 4 other fieldsHigh correlation
영업상태명 is highly overall correlated with 폐업일자 and 2 other fieldsHigh correlation
위생업태명 is highly overall correlated with 소재지우편번호 and 7 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with WGS84경도 and 3 other fieldsHigh correlation
인허가일자 is highly overall correlated with 폐업일자 and 2 other fieldsHigh correlation
폐업일자 is highly overall correlated with 인허가일자 and 3 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 시군명 and 2 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
위생업종명 is highly imbalanced (87.9%)Imbalance
위생업태명 is highly imbalanced (87.9%)Imbalance
폐업일자 has 236 (77.9%) missing valuesMissing
다중이용업소여부 has 5 (1.7%) missing valuesMissing

Reproduction

Analysis started2023-12-10 22:01:25.498897
Analysis finished2023-12-10 22:01:28.921261
Duration3.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
고양시
109 
부천시
51 
수원시
49 
성남시
18 
포천시
11 
Other values (22)
65 

Length

Max length4
Median length3
Mean length3.0363036
Min length3

Unique

Unique8 ?
Unique (%)2.6%

Sample

1st row가평군
2nd row고양시
3rd row고양시
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
고양시 109
36.0%
부천시 51
16.8%
수원시 49
16.2%
성남시 18
 
5.9%
포천시 11
 
3.6%
광주시 9
 
3.0%
동두천시 6
 
2.0%
안양시 5
 
1.7%
이천시 5
 
1.7%
화성시 5
 
1.7%
Other values (17) 35
 
11.6%

Length

2023-12-11T07:01:28.981415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고양시 109
36.0%
부천시 51
16.8%
수원시 49
16.2%
성남시 18
 
5.9%
포천시 11
 
3.6%
광주시 9
 
3.0%
동두천시 6
 
2.0%
안양시 5
 
1.7%
이천시 5
 
1.7%
화성시 5
 
1.7%
Other values (17) 35
 
11.6%

사업장명
Text

Distinct292
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-11T07:01:29.214730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length7.0429043
Min length1

Characters and Unicode

Total characters2134
Distinct characters366
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

Unique285 ?
Unique (%)94.1%

Sample

1st row유니베라(가평현리점)
2nd row로스트월드
3rd row건국우유행신보급소
4th row비즈팜(Biz Pharm)
5th row삼성디엠에스
ValueCountFrequency (%)
주식회사 7
 
2.1%
애터미 5
 
1.5%
케어셀라 3
 
0.9%
주)정원에스와이 3
 
0.9%
톡진수원지사 2
 
0.6%
스킨앤바디 2
 
0.6%
허브디톡스 2
 
0.6%
건국패밀리생유산균 2
 
0.6%
건국우유 2
 
0.6%
다이어트 2
 
0.6%
Other values (308) 310
91.2%
2023-12-11T07:01:29.689253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 85
 
4.0%
스 84
 
3.9%
주 76
 
3.6%
( 70
 
3.3%
) 70
 
3.3%
사 41
 
1.9%
리 37
 
1.7%
37
 
1.7%
에 30
 
1.4%
인 27
 
1.3%
Other values (356) 1577
73.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1871
87.7%
Open Punctuation 70
 
3.3%
Close Punctuation 70
 
3.3%
Lowercase Letter 47
 
2.2%
Space Separator 37
 
1.7%
Uppercase Letter 23
 
1.1%
Decimal Number 10
 
0.5%
Other Punctuation 5
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 85
 
4.5%
스 84
 
4.5%
주 76
 
4.1%
사 41
 
2.2%
리 37
 
2.0%
에 30
 
1.6%
인 27
 
1.4%
점 27
 
1.4%
트 26
 
1.4%
유 25
 
1.3%
Other values (310) 1413
75.5%
Lowercase Letter
ValueCountFrequency (%)
s 5
10.6%
i 5
10.6%
a 4
 
8.5%
o 4
 
8.5%
n 4
 
8.5%
h 3
 
6.4%
r 3
 
6.4%
k 3
 
6.4%
t 2
 
4.3%
l 2
 
4.3%
Other values (10) 12
25.5%
Uppercase Letter
ValueCountFrequency (%)
S 5
21.7%
H 3
13.0%
J 2
 
8.7%
M 2
 
8.7%
E 2
 
8.7%
T 1
 
4.3%
D 1
 
4.3%
L 1
 
4.3%
A 1
 
4.3%
O 1
 
4.3%
Other values (4) 4
17.4%
Decimal Number
ValueCountFrequency (%)
4 4
40.0%
2 3
30.0%
3 1
 
10.0%
5 1
 
10.0%
6 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
, 1
 
20.0%
& 1
 
20.0%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Space Separator
ValueCountFrequency (%)
37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1871
87.7%
Common 193
 
9.0%
Latin 70
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 85
 
4.5%
스 84
 
4.5%
주 76
 
4.1%
사 41
 
2.2%
리 37
 
2.0%
에 30
 
1.6%
인 27
 
1.4%
점 27
 
1.4%
트 26
 
1.4%
유 25
 
1.3%
Other values (310) 1413
75.5%
Latin
ValueCountFrequency (%)
s 5
 
7.1%
i 5
 
7.1%
S 5
 
7.1%
a 4
 
5.7%
o 4
 
5.7%
n 4
 
5.7%
h 3
 
4.3%
r 3
 
4.3%
k 3
 
4.3%
H 3
 
4.3%
Other values (24) 31
44.3%
Common
ValueCountFrequency (%)
( 70
36.3%
) 70
36.3%
37
19.2%
4 4
 
2.1%
. 3
 
1.6%
2 3
 
1.6%
3 1
 
0.5%
5 1
 
0.5%
6 1
 
0.5%
- 1
 
0.5%
Other values (2) 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1871
87.7%
ASCII 263
 
12.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 85
 
4.5%
스 84
 
4.5%
주 76
 
4.1%
사 41
 
2.2%
리 37
 
2.0%
에 30
 
1.6%
인 27
 
1.4%
점 27
 
1.4%
트 26
 
1.4%
유 25
 
1.3%
Other values (310) 1413
75.5%
ASCII
ValueCountFrequency (%)
( 70
26.6%
) 70
26.6%
37
14.1%
s 5
 
1.9%
i 5
 
1.9%
S 5
 
1.9%
a 4
 
1.5%
o 4
 
1.5%
n 4
 
1.5%
4 4
 
1.5%
Other values (36) 55
20.9%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct210
Distinct (%)69.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean361867.33
Minimum10541
Maximum487871
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T07:01:29.846002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10541
5-th percentile14543
Q1410835
median412822
Q3443818
95-th percentile483020
Maximum487871
Range477330
Interquartile range (IQR)32983

Descriptive statistics

Standard deviation161831.31
Coefficient of variation (CV)0.44721173
Kurtosis0.83696935
Mean361867.33
Median Absolute Deviation (MAD)29055
Skewness-1.6399881
Sum1.096458 × 108
Variance2.6189374 × 1010
MonotonicityNot monotonic
2023-12-11T07:01:29.994809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
410837 16
 
5.3%
410835 8
 
2.6%
410811 5
 
1.7%
411838 5
 
1.7%
412070 5
 
1.7%
487823 5
 
1.7%
14544 4
 
1.3%
412827 4
 
1.3%
411848 4
 
1.3%
411805 3
 
1.0%
Other values (200) 244
80.5%
ValueCountFrequency (%)
10541 1
0.3%
12438 1
0.3%
14430 1
0.3%
14436 1
0.3%
14468 1
0.3%
14491 1
0.3%
14498 1
0.3%
14513 1
0.3%
14527 1
0.3%
14537 1
0.3%
ValueCountFrequency (%)
487871 1
 
0.3%
487829 1
 
0.3%
487823 5
1.7%
487020 3
1.0%
486903 1
 
0.3%
483120 1
 
0.3%
483030 2
 
0.7%
483020 3
1.0%
480799 1
 
0.3%
476893 1
 
0.3%

소재지도로명주소
Text

Distinct300
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-11T07:01:30.253430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length47
Mean length37.30033
Min length21

Characters and Unicode

Total characters11302
Distinct characters333
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)98.3%

Sample

1st row경기도 가평군 조종면 청군로 1183-1, 2층
2nd row경기도 고양시 일산서구 일현로 97-11, 108동 2404호 (탄현동, 일산두산위브더제니스)
3rd row경기도 고양시 덕양구 지도로42번길 5, 1층 일부(101)호 (토당동, 조화빌딩)
4th row경기도 고양시 덕양구 지도로125번길 23-16 (토당동,101호)
5th row경기도 고양시 일산서구 강성로 147, 310호 (주엽동, 동문시티프라자)
ValueCountFrequency (%)
경기도 303
 
13.0%
고양시 109
 
4.7%
부천시 51
 
2.2%
1층 50
 
2.1%
수원시 49
 
2.1%
덕양구 43
 
1.8%
일산동구 43
 
1.8%
2층 29
 
1.2%
일산서구 23
 
1.0%
3층 21
 
0.9%
Other values (992) 1609
69.1%
2023-12-11T07:01:30.723149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2028
 
17.9%
1 481
 
4.3%
동 430
 
3.8%
, 399
 
3.5%
2 314
 
2.8%
경 313
 
2.8%
도 312
 
2.8%
시 308
 
2.7%
기 306
 
2.7%
로 300
 
2.7%
Other values (323) 6111
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6197
54.8%
Space Separator 2028
 
17.9%
Decimal Number 1993
 
17.6%
Other Punctuation 400
 
3.5%
Close Punctuation 289
 
2.6%
Open Punctuation 289
 
2.6%
Dash Punctuation 65
 
0.6%
Uppercase Letter 38
 
0.3%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 430
 
6.9%
경 313
 
5.1%
도 312
 
5.0%
시 308
 
5.0%
기 306
 
4.9%
로 300
 
4.8%
호 219
 
3.5%
구 190
 
3.1%
양 189
 
3.0%
길 134
 
2.2%
Other values (290) 3496
56.4%
Uppercase Letter
ValueCountFrequency (%)
B 11
28.9%
A 6
15.8%
E 3
 
7.9%
C 3
 
7.9%
Y 2
 
5.3%
P 2
 
5.3%
L 2
 
5.3%
I 2
 
5.3%
S 1
 
2.6%
X 1
 
2.6%
Other values (5) 5
13.2%
Decimal Number
ValueCountFrequency (%)
1 481
24.1%
2 314
15.8%
0 263
13.2%
3 223
11.2%
4 169
 
8.5%
5 133
 
6.7%
6 130
 
6.5%
7 96
 
4.8%
9 95
 
4.8%
8 89
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 399
99.8%
& 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2028
100.0%
Close Punctuation
ValueCountFrequency (%)
) 289
100.0%
Open Punctuation
ValueCountFrequency (%)
( 289
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6197
54.8%
Common 5065
44.8%
Latin 40
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 430
 
6.9%
경 313
 
5.1%
도 312
 
5.0%
시 308
 
5.0%
기 306
 
4.9%
로 300
 
4.8%
호 219
 
3.5%
구 190
 
3.1%
양 189
 
3.0%
길 134
 
2.2%
Other values (290) 3496
56.4%
Common
ValueCountFrequency (%)
2028
40.0%
1 481
 
9.5%
, 399
 
7.9%
2 314
 
6.2%
) 289
 
5.7%
( 289
 
5.7%
0 263
 
5.2%
3 223
 
4.4%
4 169
 
3.3%
5 133
 
2.6%
Other values (7) 477
 
9.4%
Latin
ValueCountFrequency (%)
B 11
27.5%
A 6
15.0%
E 3
 
7.5%
C 3
 
7.5%
Y 2
 
5.0%
P 2
 
5.0%
e 2
 
5.0%
L 2
 
5.0%
I 2
 
5.0%
S 1
 
2.5%
Other values (6) 6
15.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6197
54.8%
ASCII 5105
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2028
39.7%
1 481
 
9.4%
, 399
 
7.8%
2 314
 
6.2%
) 289
 
5.7%
( 289
 
5.7%
0 263
 
5.2%
3 223
 
4.4%
4 169
 
3.3%
5 133
 
2.6%
Other values (23) 517
 
10.1%
Hangul
ValueCountFrequency (%)
동 430
 
6.9%
경 313
 
5.1%
도 312
 
5.0%
시 308
 
5.0%
기 306
 
4.9%
로 300
 
4.8%
호 219
 
3.5%
구 190
 
3.1%
양 189
 
3.0%
길 134
 
2.2%
Other values (290) 3496
56.4%

소재지지번주소
Text

Distinct295
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-11T07:01:30.932727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length27.924092
Min length17

Characters and Unicode

Total characters8461
Distinct characters299
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique289 ?
Unique (%)95.4%

Sample

1st row경기도 가평군 조종면 현리 477-316번지
2nd row경기도 고양시 일산서구 탄현동 1640번지 일산두산위브더제니스 108동 2404호
3rd row경기도 고양시 덕양구 토당동 875-2번지 조화빌딩
4th row경기도 고양시 덕양구 토당동 835-3번지 101호
5th row경기도 고양시 일산서구 주엽동 18-1번지 동문시티프라자 310호
ValueCountFrequency (%)
경기도 303
 
17.1%
고양시 109
 
6.1%
부천시 51
 
2.9%
수원시 49
 
2.8%
덕양구 43
 
2.4%
일산동구 43
 
2.4%
일산서구 23
 
1.3%
1층 19
 
1.1%
장항동 19
 
1.1%
성남시 18
 
1.0%
Other values (734) 1098
61.9%
2023-12-11T07:01:31.480662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1472
 
17.4%
동 377
 
4.5%
1 334
 
3.9%
지 332
 
3.9%
시 310
 
3.7%
경 307
 
3.6%
도 306
 
3.6%
기 306
 
3.6%
번 303
 
3.6%
2 206
 
2.4%
Other values (289) 4208
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5150
60.9%
Decimal Number 1588
 
18.8%
Space Separator 1472
 
17.4%
Dash Punctuation 203
 
2.4%
Uppercase Letter 22
 
0.3%
Other Punctuation 18
 
0.2%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 377
 
7.3%
지 332
 
6.4%
시 310
 
6.0%
경 307
 
6.0%
도 306
 
5.9%
기 306
 
5.9%
번 303
 
5.9%
구 192
 
3.7%
양 178
 
3.5%
고 116
 
2.3%
Other values (258) 2423
47.0%
Uppercase Letter
ValueCountFrequency (%)
B 6
27.3%
A 2
 
9.1%
Y 2
 
9.1%
E 2
 
9.1%
I 2
 
9.1%
C 2
 
9.1%
X 1
 
4.5%
O 1
 
4.5%
M 1
 
4.5%
P 1
 
4.5%
Other values (2) 2
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 334
21.0%
2 206
13.0%
3 180
11.3%
0 170
10.7%
4 141
8.9%
7 117
 
7.4%
5 116
 
7.3%
6 116
 
7.3%
8 115
 
7.2%
9 93
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 15
83.3%
& 2
 
11.1%
@ 1
 
5.6%
Space Separator
ValueCountFrequency (%)
1472
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 203
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5150
60.9%
Common 3288
38.9%
Latin 23
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 377
 
7.3%
지 332
 
6.4%
시 310
 
6.0%
경 307
 
6.0%
도 306
 
5.9%
기 306
 
5.9%
번 303
 
5.9%
구 192
 
3.7%
양 178
 
3.5%
고 116
 
2.3%
Other values (258) 2423
47.0%
Common
ValueCountFrequency (%)
1472
44.8%
1 334
 
10.2%
2 206
 
6.3%
- 203
 
6.2%
3 180
 
5.5%
0 170
 
5.2%
4 141
 
4.3%
7 117
 
3.6%
5 116
 
3.5%
6 116
 
3.5%
Other values (8) 233
 
7.1%
Latin
ValueCountFrequency (%)
B 6
26.1%
A 2
 
8.7%
Y 2
 
8.7%
E 2
 
8.7%
I 2
 
8.7%
C 2
 
8.7%
e 1
 
4.3%
X 1
 
4.3%
O 1
 
4.3%
M 1
 
4.3%
Other values (3) 3
13.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5150
60.9%
ASCII 3311
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1472
44.5%
1 334
 
10.1%
2 206
 
6.2%
- 203
 
6.1%
3 180
 
5.4%
0 170
 
5.1%
4 141
 
4.3%
7 117
 
3.5%
5 116
 
3.5%
6 116
 
3.5%
Other values (21) 256
 
7.7%
Hangul
ValueCountFrequency (%)
동 377
 
7.3%
지 332
 
6.4%
시 310
 
6.0%
경 307
 
6.0%
도 306
 
5.9%
기 306
 
5.9%
번 303
 
5.9%
구 192
 
3.7%
양 178
 
3.5%
고 116
 
2.3%
Other values (258) 2423
47.0%

인허가일자
Real number (ℝ)

HIGH CORRELATION 

Distinct243
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20163950
Minimum20040615
Maximum20180830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T07:01:31.604130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040615
5-th percentile20142006
Q120160122
median20170222
Q320180117
95-th percentile20180731
Maximum20180830
Range140215
Interquartile range (IQR)19995.5

Descriptive statistics

Standard deviation18949.655
Coefficient of variation (CV)0.00093977891
Kurtosis14.157756
Mean20163950
Median Absolute Deviation (MAD)9992
Skewness-3.0158507
Sum6.1096768 × 109
Variance3.5908941 × 108
MonotonicityNot monotonic
2023-12-11T07:01:31.730976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160722 4
 
1.3%
20180530 4
 
1.3%
20180103 3
 
1.0%
20180619 3
 
1.0%
20180126 3
 
1.0%
20180219 3
 
1.0%
20150811 3
 
1.0%
20151030 3
 
1.0%
20171214 3
 
1.0%
20180330 3
 
1.0%
Other values (233) 271
89.4%
ValueCountFrequency (%)
20040615 1
0.3%
20040616 1
0.3%
20080725 1
0.3%
20090109 1
0.3%
20090818 1
0.3%
20090820 1
0.3%
20100111 1
0.3%
20100812 1
0.3%
20110615 1
0.3%
20120309 1
0.3%
ValueCountFrequency (%)
20180830 1
0.3%
20180829 1
0.3%
20180827 2
0.7%
20180824 2
0.7%
20180820 1
0.3%
20180816 2
0.7%
20180813 1
0.3%
20180810 1
0.3%
20180809 1
0.3%
20180808 1
0.3%

영업상태명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
운영중
236 
폐업 등
67 

Length

Max length4
Median length3
Mean length3.2211221
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 236
77.9%
폐업 등 67
 
22.1%

Length

2023-12-11T07:01:31.866070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:01:31.953353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 236
63.8%
폐업 67
 
18.1%
등 67
 
18.1%

폐업일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct59
Distinct (%)88.1%
Missing236
Missing (%)77.9%
Infinite0
Infinite (%)0.0%
Mean20170717
Minimum20150515
Maximum20180831
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T07:01:32.055844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20150515
5-th percentile20151205
Q120170110
median20171010
Q320180130
95-th percentile20180783
Maximum20180831
Range30316
Interquartile range (IQR)10020

Descriptive statistics

Standard deviation8740.3193
Coefficient of variation (CV)0.00043331723
Kurtosis-0.11326929
Mean20170717
Median Absolute Deviation (MAD)9119
Skewness-0.70613651
Sum1.3514381 × 109
Variance76393181
MonotonicityNot monotonic
2023-12-11T07:01:32.189853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170628 3
 
1.0%
20170921 2
 
0.7%
20171218 2
 
0.7%
20170110 2
 
0.7%
20180410 2
 
0.7%
20171010 2
 
0.7%
20171226 2
 
0.7%
20171103 1
 
0.3%
20180814 1
 
0.3%
20170320 1
 
0.3%
Other values (49) 49
 
16.2%
(Missing) 236
77.9%
ValueCountFrequency (%)
20150515 1
0.3%
20150618 1
0.3%
20151120 1
0.3%
20151204 1
0.3%
20151208 1
0.3%
20160122 1
0.3%
20160212 1
0.3%
20160315 1
0.3%
20160620 1
0.3%
20160705 1
0.3%
ValueCountFrequency (%)
20180831 1
0.3%
20180817 1
0.3%
20180814 1
0.3%
20180807 1
0.3%
20180727 1
0.3%
20180629 1
0.3%
20180605 1
0.3%
20180604 1
0.3%
20180509 1
0.3%
20180426 1
0.3%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing5
Missing (%)1.7%
Memory size738.0 B
False
298 
(Missing)
 
5
ValueCountFrequency (%)
False 298
98.3%
(Missing) 5
 
1.7%
2023-12-11T07:01:32.291684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위생업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
건강기능식품일반판매업
298 
<NA>
 
5

Length

Max length11
Median length11
Mean length10.884488
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품일반판매업 298
98.3%
<NA> 5
 
1.7%

Length

2023-12-11T07:01:32.382434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:01:32.472099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품일반판매업 298
98.3%
na 5
 
1.7%

위생업태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
기타(복합 등)
298 
<NA>
 
5

Length

Max length8
Median length8
Mean length7.9339934
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타(복합 등)
2nd row기타(복합 등)
3rd row기타(복합 등)
4th row기타(복합 등)
5th row기타(복합 등)

Common Values

ValueCountFrequency (%)
기타(복합 등) 298
98.3%
<NA> 5
 
1.7%

Length

2023-12-11T07:01:32.571781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:01:32.686686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타(복합 298
49.6%
등 298
49.6%
na 5
 
0.8%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct291
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.517257
Minimum36.992413
Maximum38.025484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T07:01:32.814339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.992413
5-th percentile37.259133
Q137.366231
median37.506376
Q337.655851
95-th percentile37.829789
Maximum38.025484
Range1.0330711
Interquartile range (IQR)0.28961933

Descriptive statistics

Standard deviation0.18476639
Coefficient of variation (CV)0.0049248375
Kurtosis-0.45224439
Mean37.517257
Median Absolute Deviation (MAD)0.14900475
Skewness-0.090988664
Sum11367.729
Variance0.034138621
MonotonicityNot monotonic
2023-12-11T07:01:32.954513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3875738121 3
 
1.0%
37.6548220944 3
 
1.0%
37.6683555154 2
 
0.7%
37.6489256763 2
 
0.7%
37.2966577449 2
 
0.7%
37.5063755894 2
 
0.7%
37.663225235 2
 
0.7%
37.6547704839 2
 
0.7%
37.6616931899 2
 
0.7%
37.6553803425 2
 
0.7%
Other values (281) 281
92.7%
ValueCountFrequency (%)
36.9924129235 1
0.3%
36.9968025274 1
0.3%
37.0949286583 1
0.3%
37.1454761283 1
0.3%
37.1458598153 1
0.3%
37.1777501079 1
0.3%
37.2087055346 1
0.3%
37.2105046921 1
0.3%
37.2165813219 1
0.3%
37.2520153047 1
0.3%
ValueCountFrequency (%)
38.0254839768 1
0.3%
38.0034417157 1
0.3%
37.91540451 1
0.3%
37.9016944405 1
0.3%
37.8984375157 1
0.3%
37.8955750401 1
0.3%
37.8941658815 1
0.3%
37.8914072829 1
0.3%
37.8889916889 1
0.3%
37.8587961862 1
0.3%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct291
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.9302
Minimum126.5302
Maximum127.6283
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T07:01:33.123837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5302
5-th percentile126.75156
Q1126.77687
median126.86717
Q3127.04999
95-th percentile127.24604
Maximum127.6283
Range1.0981
Interquartile range (IQR)0.27312244

Descriptive statistics

Standard deviation0.18311883
Coefficient of variation (CV)0.0014426734
Kurtosis0.85323845
Mean126.9302
Median Absolute Deviation (MAD)0.10780547
Skewness1.0281675
Sum38459.852
Variance0.033532508
MonotonicityNot monotonic
2023-12-11T07:01:33.256627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1237232152 3
 
1.0%
126.7707679935 3
 
1.0%
126.765691892 2
 
0.7%
126.7792821649 2
 
0.7%
127.0054807148 2
 
0.7%
126.7525730276 2
 
0.7%
126.8903698833 2
 
0.7%
126.772627716 2
 
0.7%
126.7668912997 2
 
0.7%
126.7735967304 2
 
0.7%
Other values (281) 281
92.7%
ValueCountFrequency (%)
126.5302036856 1
0.3%
126.667362725 1
0.3%
126.687087405 1
0.3%
126.7024184505 1
0.3%
126.7220267648 1
0.3%
126.7235101621 1
0.3%
126.7393752543 1
0.3%
126.7441037261 1
0.3%
126.7470082329 1
0.3%
126.7479225208 1
0.3%
ValueCountFrequency (%)
127.6283036802 1
0.3%
127.5377343732 1
0.3%
127.49349504 1
0.3%
127.4876014788 1
0.3%
127.454900488 1
0.3%
127.4510639608 1
0.3%
127.4463383673 1
0.3%
127.4431234678 1
0.3%
127.4428756227 1
0.3%
127.351469644 1
0.3%

Interactions

2023-12-11T07:01:28.152215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:26.349342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:26.878499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:27.318386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:27.740455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:28.227468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:26.447173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:26.965806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:27.400951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:27.833856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:28.314262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:26.570397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:27.061281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:27.482524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:27.922415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:28.393049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:26.694112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:27.147171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:27.564638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:28.003687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:28.469105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:26.784820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:27.236005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:27.651486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:01:28.076932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:01:33.366983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명소재지우편번호인허가일자영업상태명폐업일자WGS84위도WGS84경도
시군명1.0001.0000.4980.1760.0000.9660.949
소재지우편번호1.0001.0000.3590.0000.0000.8740.803
인허가일자0.4980.3591.0000.3830.7540.2010.282
영업상태명0.1760.0000.3831.000NaN0.1300.161
폐업일자0.0000.0000.754NaN1.0000.0000.000
WGS84위도0.9660.8740.2010.1300.0001.0000.816
WGS84경도0.9490.8030.2820.1610.0000.8161.000
2023-12-11T07:01:33.512640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위생업종명시군명영업상태명위생업태명
위생업종명1.0001.0001.0001.000
시군명1.0001.0000.1441.000
영업상태명1.0000.1441.0001.000
위생업태명1.0001.0001.0001.000
2023-12-11T07:01:33.631561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호인허가일자폐업일자WGS84위도WGS84경도시군명영업상태명위생업종명위생업태명
소재지우편번호1.000-0.1900.022-0.2790.8580.9520.0001.0001.000
인허가일자-0.1901.0000.5310.125-0.1380.1540.3801.0001.000
폐업일자0.0220.5311.0000.1310.0480.0001.0001.0001.000
WGS84위도-0.2790.1250.1311.000-0.4180.7880.0981.0001.000
WGS84경도0.858-0.1380.048-0.4181.0000.7240.1211.0001.000
시군명0.9520.1540.0000.7880.7241.0000.1441.0001.000
영업상태명0.0000.3801.0000.0980.1210.1441.0001.0001.000
위생업종명1.0001.0001.0001.0001.0001.0001.0001.0001.000
위생업태명1.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-11T07:01:28.574459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:01:28.725968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T07:01:28.861197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명사업장명소재지우편번호소재지도로명주소소재지지번주소인허가일자영업상태명폐업일자다중이용업소여부위생업종명위생업태명WGS84위도WGS84경도
0가평군유니베라(가평현리점)12438경기도 가평군 조종면 청군로 1183-1, 2층경기도 가평군 조종면 현리 477-316번지20170613폐업 등20180129N건강기능식품일반판매업기타(복합 등)37.81084127.35147
1고양시로스트월드411797경기도 고양시 일산서구 일현로 97-11, 108동 2404호 (탄현동, 일산두산위브더제니스)경기도 고양시 일산서구 탄현동 1640번지 일산두산위브더제니스 108동 2404호20150528운영중<NA>N건강기능식품일반판매업기타(복합 등)37.692806126.762445
2고양시건국우유행신보급소412821경기도 고양시 덕양구 지도로42번길 5, 1층 일부(101)호 (토당동, 조화빌딩)경기도 고양시 덕양구 토당동 875-2번지 조화빌딩20180827운영중<NA>N건강기능식품일반판매업기타(복합 등)37.620967126.825026
3고양시비즈팜(Biz Pharm)412820경기도 고양시 덕양구 지도로125번길 23-16 (토당동,101호)경기도 고양시 덕양구 토당동 835-3번지 101호20080725운영중<NA>N건강기능식품일반판매업기타(복합 등)37.627185126.821808
4고양시삼성디엠에스411838경기도 고양시 일산서구 강성로 147, 310호 (주엽동, 동문시티프라자)경기도 고양시 일산서구 주엽동 18-1번지 동문시티프라자 310호20141106운영중<NA>N건강기능식품일반판매업기타(복합 등)37.671777126.759365
5고양시(주)유승씨앤씨412060경기도 고양시 덕양구 흥도로178번길 135, 코비빌딩 1,2층 (도내동)경기도 고양시 덕양구 도내동 290-10번지 코비빌딩20140207운영중<NA>N건강기능식품일반판매업기타(복합 등)37.623788126.865603
6고양시풀무원녹즙 일산서구지사411803경기도 고양시 일산서구 일산로636번길 23-3, 1층 (대화동)경기도 고양시 일산서구 대화동 2025-8번지 1층 우측20150102운영중<NA>N건강기능식품일반판매업기타(복합 등)37.682843126.75896
7고양시비에이블410837경기도 고양시 일산동구 정발산로 11, 501호 (장항동, 일호골든타워)경기도 고양시 일산동구 장항동 863-2번지 일호골든타워 501호20150202운영중<NA>N건강기능식품일반판매업기타(복합 등)37.656558126.770184
8고양시참좋은미디어410835경기도 고양시 일산동구 장백로 20, 102동 625호 (백석동, 동문굿모닝힐)경기도 고양시 일산동구 백석동 1302번지20150430운영중<NA>N건강기능식품일반판매업기타(복합 등)37.640688126.78979
9고양시케어셀라410330경기도 고양시 일산동구 숲속마을로 44, 103호 (풍동, 미래타워)경기도 고양시 일산동구 풍동 1280-1번지20170718운영중<NA>N건강기능식품일반판매업기타(복합 등)37.667409126.798254
시군명사업장명소재지우편번호소재지도로명주소소재지지번주소인허가일자영업상태명폐업일자다중이용업소여부위생업종명위생업태명WGS84위도WGS84경도
293포천시채심촌 산약초487829경기도 포천시 소흘읍 광릉수목원로 625, 다동 2층경기도 포천시 소흘읍 직동리 428-2번지 다동 2호20170206운영중<NA>N건강기능식품일반판매업기타(복합 등)37.768843127.164991
294포천시청인487823경기도 포천시 소흘읍 송우로 75, 106호경기도 포천시 소흘읍 송우리 729-3번지 106호20160113폐업 등20160620N건강기능식품일반판매업기타(복합 등)37.82979127.140625
295포천시포인홍삼유통480799경기도 포천시 영중면 호국로 2926, 1층경기도 포천시 영중면 양문리 832-13번지 , 1층20160719폐업 등20180124N건강기능식품일반판매업기타(복합 등)38.003442127.24727
296포천시케어셀라 체험샵487020경기도 포천시 호국로929번길 3, 가동 1층 (선단동)경기도 포천시 선단동 555-2번지 1층 ,가동20170822폐업 등20180807N건강기능식품일반판매업기타(복합 등)37.848718127.161948
297하남시주식회사 일양465818경기도 하남시 서하남로43번길 137, 3층 (감북동)경기도 하남시 감북동 261-9번지 3층20160525운영중<NA>N건강기능식품일반판매업기타(복합 등)37.521002127.152794
298화성시대지유통445380경기도 화성시 안녕북길 82, 지하1층 일부호 (안녕동)경기도 화성시 안녕동 188-255번지 지하1층 일부호20160808운영중<NA>N건강기능식품일반판매업기타(복합 등)37.210505126.980742
299화성시이니스트바이오제약(주)445937경기도 화성시 향남읍 제약공단2길 34-40, 1층 일부경기도 화성시 향남읍 상신리 900-2번지20180604운영중<NA>N건강기능식품일반판매업기타(복합 등)37.094929126.906397
300화성시건국패밀리생유산균445130경기도 화성시 동탄대로22길 9, 636동 11층 1102호 (영천동, 동탄역 센트럴 상록아파트)경기도 화성시 영천동 662번지 동탄역 센트럴 상록아파트 636동 1102호20160418운영중<NA>N건강기능식품일반판매업기타(복합 등)37.208706127.102862
301화성시(주)에이앤젬조인445902경기도 화성시 봉담읍 복만터길 14, 2층경기도 화성시 봉담읍 마하리 211번지20150520운영중<NA>N건강기능식품일반판매업기타(복합 등)37.17775126.943544
302화성시점핑다이어트445893경기도 화성시 봉담읍 동화길 91, 903호경기도 화성시 봉담읍 동화리 599-4번지 903호20160428운영중<NA>N건강기능식품일반판매업기타(복합 등)37.216581126.958858