Overview

Dataset statistics

Number of variables14
Number of observations658
Missing cells1815
Missing cells (%)19.7%
Duplicate rows1
Duplicate rows (%)0.2%
Total size in memory75.3 KiB
Average record size in memory117.2 B

Variable types

Categorical4
Text3
DateTime2
Unsupported2
Numeric3

Dataset

Description휴게음식점(아이스크림) 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=5BW6XGSJK25CYFGNEA7B14623624&infSeq=1

Alerts

위생업태명 has constant value ""Constant
Dataset has 1 (0.2%) duplicate rowsDuplicates
영업상태명 is highly overall correlated with 위생업종명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
위생업종명 is highly overall correlated with 소재지우편번호 and 4 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with WGS84위도 and 2 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
폐업일자 has 476 (72.3%) missing valuesMissing
다중이용업소여부 has 658 (100.0%) missing valuesMissing
총시설규모(㎡) has 658 (100.0%) missing valuesMissing
소재지도로명주소 has 11 (1.7%) missing valuesMissing
다중이용업소여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총시설규모(㎡) is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-10 20:23:48.814013
Analysis finished2024-05-10 20:23:54.828932
Duration6.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
고양시
64 
성남시
59 
부천시
54 
수원시
50 
용인시
50 
Other values (26)
381 

Length

Max length4
Median length3
Mean length3.0987842
Min length3

Unique

Unique3 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
고양시 64
 
9.7%
성남시 59
 
9.0%
부천시 54
 
8.2%
수원시 50
 
7.6%
용인시 50
 
7.6%
화성시 38
 
5.8%
김포시 32
 
4.9%
남양주시 30
 
4.6%
의정부시 28
 
4.3%
평택시 28
 
4.3%
Other values (21) 225
34.2%

Length

2024-05-10T20:23:55.055340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고양시 64
 
9.7%
성남시 59
 
9.0%
부천시 54
 
8.2%
수원시 50
 
7.6%
용인시 50
 
7.6%
화성시 38
 
5.8%
김포시 32
 
4.9%
남양주시 30
 
4.6%
의정부시 28
 
4.3%
평택시 28
 
4.3%
Other values (21) 225
34.2%

사업장명
Text

Distinct553
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-10T20:23:55.604322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length23
Mean length10.486322
Min length2

Characters and Unicode

Total characters6900
Distinct characters440
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

Unique476 ?
Unique (%)72.3%

Sample

1st row배스킨라빈스
2nd row배스킨라빈스 고양스타필드점
3rd row배스킨라빈스 킨텍스역점
4th row스쿱스젤라또 고양지축점
5th row에밀리아 젤라또 일산동국대병원점
ValueCountFrequency (%)
배스킨라빈스 125
 
12.1%
베스킨라빈스 29
 
2.8%
설빙 13
 
1.3%
요거트아이스크림의정석 12
 
1.2%
바세츠아이스크림 10
 
1.0%
아이스크림 9
 
0.9%
정석 7
 
0.7%
하남점 7
 
0.7%
요거트월드 6
 
0.6%
백미당 6
 
0.6%
Other values (636) 805
78.2%
2024-05-10T20:23:56.829704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 695
 
10.1%
점 397
 
5.8%
371
 
5.4%
라 321
 
4.7%
킨 253
 
3.7%
빈 248
 
3.6%
배 198
 
2.9%
이 165
 
2.4%
아 139
 
2.0%
( 104
 
1.5%
Other values (430) 4009
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5926
85.9%
Space Separator 371
 
5.4%
Lowercase Letter 195
 
2.8%
Uppercase Letter 126
 
1.8%
Open Punctuation 104
 
1.5%
Close Punctuation 104
 
1.5%
Decimal Number 52
 
0.8%
Other Punctuation 19
 
0.3%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 695
 
11.7%
점 397
 
6.7%
라 321
 
5.4%
킨 253
 
4.3%
빈 248
 
4.2%
배 198
 
3.3%
이 165
 
2.8%
아 139
 
2.3%
크 99
 
1.7%
트 81
 
1.4%
Other values (368) 3330
56.2%
Lowercase Letter
ValueCountFrequency (%)
e 31
15.9%
a 18
 
9.2%
s 17
 
8.7%
i 16
 
8.2%
o 15
 
7.7%
r 14
 
7.2%
t 12
 
6.2%
n 10
 
5.1%
m 8
 
4.1%
c 7
 
3.6%
Other values (13) 47
24.1%
Uppercase Letter
ValueCountFrequency (%)
G 18
14.3%
A 14
11.1%
K 11
 
8.7%
D 10
 
7.9%
O 9
 
7.1%
L 8
 
6.3%
E 6
 
4.8%
C 6
 
4.8%
R 6
 
4.8%
I 5
 
4.0%
Other values (12) 33
26.2%
Decimal Number
ValueCountFrequency (%)
1 18
34.6%
3 13
25.0%
2 8
15.4%
5 4
 
7.7%
4 4
 
7.7%
0 2
 
3.8%
7 1
 
1.9%
8 1
 
1.9%
6 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
& 8
42.1%
. 6
31.6%
' 3
 
15.8%
, 2
 
10.5%
Space Separator
ValueCountFrequency (%)
371
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5926
85.9%
Common 653
 
9.5%
Latin 321
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 695
 
11.7%
점 397
 
6.7%
라 321
 
5.4%
킨 253
 
4.3%
빈 248
 
4.2%
배 198
 
3.3%
이 165
 
2.8%
아 139
 
2.3%
크 99
 
1.7%
트 81
 
1.4%
Other values (368) 3330
56.2%
Latin
ValueCountFrequency (%)
e 31
 
9.7%
G 18
 
5.6%
a 18
 
5.6%
s 17
 
5.3%
i 16
 
5.0%
o 15
 
4.7%
A 14
 
4.4%
r 14
 
4.4%
t 12
 
3.7%
K 11
 
3.4%
Other values (35) 155
48.3%
Common
ValueCountFrequency (%)
371
56.8%
( 104
 
15.9%
) 104
 
15.9%
1 18
 
2.8%
3 13
 
2.0%
& 8
 
1.2%
2 8
 
1.2%
. 6
 
0.9%
5 4
 
0.6%
4 4
 
0.6%
Other values (7) 13
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5926
85.9%
ASCII 974
 
14.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 695
 
11.7%
점 397
 
6.7%
라 321
 
5.4%
킨 253
 
4.3%
빈 248
 
4.2%
배 198
 
3.3%
이 165
 
2.8%
아 139
 
2.3%
크 99
 
1.7%
트 81
 
1.4%
Other values (368) 3330
56.2%
ASCII
ValueCountFrequency (%)
371
38.1%
( 104
 
10.7%
) 104
 
10.7%
e 31
 
3.2%
1 18
 
1.8%
G 18
 
1.8%
a 18
 
1.8%
s 17
 
1.7%
i 16
 
1.6%
o 15
 
1.5%
Other values (52) 262
26.9%

인허가일자
Date

Distinct500
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
Minimum1995-05-22 00:00:00
Maximum2024-04-30 00:00:00
2024-05-10T20:23:57.247061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:23:57.683371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
영업
311 
운영중
165 
폐업
104 
폐업 등
78 

Length

Max length4
Median length2
Mean length2.4878419
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 311
47.3%
운영중 165
25.1%
폐업 104
 
15.8%
폐업 등 78
 
11.9%

Length

2024-05-10T20:23:58.162985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T20:23:58.578759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 311
42.3%
폐업 182
24.7%
운영중 165
22.4%
등 78
 
10.6%

폐업일자
Date

MISSING 

Distinct164
Distinct (%)90.1%
Missing476
Missing (%)72.3%
Memory size5.3 KiB
Minimum2015-06-08 00:00:00
Maximum2024-03-18 00:00:00
2024-05-10T20:23:58.943334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:23:59.371667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

다중이용업소여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing658
Missing (%)100.0%
Memory size5.9 KiB

총시설규모(㎡)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing658
Missing (%)100.0%
Memory size5.9 KiB

위생업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
415 
휴게음식점
243 

Length

Max length5
Median length4
Mean length4.3693009
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 415
63.1%
휴게음식점 243
36.9%

Length

2024-05-10T20:23:59.791276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T20:24:00.119565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 415
63.1%
휴게음식점 243
36.9%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
아이스크림
658 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아이스크림 658
100.0%

Length

2024-05-10T20:24:00.468784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T20:24:00.782824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아이스크림 658
100.0%

소재지도로명주소
Text

MISSING 

Distinct595
Distinct (%)92.0%
Missing11
Missing (%)1.7%
Memory size5.3 KiB
2024-05-10T20:24:01.205799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length53
Mean length38.931994
Min length18

Characters and Unicode

Total characters25189
Distinct characters445
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique545 ?
Unique (%)84.2%

Sample

1st row경기도 가평군 조종면 조종희망로 14
2nd row경기도 고양시 덕양구 고양대로 1955, 스타필드고양쇼핑몰동 1(일부)층 (동산동)
3rd row경기도 고양시 일산서구 킨텍스로 240, 181,182호 (대화동, 킨텍스 꿈에그린)
4th row경기도 고양시 덕양구 안진2길 9, 1층 일부호 (지축동)
5th row경기도 고양시 일산동구 위시티로 25, 부경빌딩 1층 102(일부)호 (식사동)
ValueCountFrequency (%)
경기도 647
 
12.5%
1층 279
 
5.4%
일부호 64
 
1.2%
고양시 64
 
1.2%
성남시 59
 
1.1%
부천시 54
 
1.0%
일부 50
 
1.0%
용인시 50
 
1.0%
수원시 49
 
0.9%
지하1층 42
 
0.8%
Other values (1636) 3832
73.8%
2024-05-10T20:24:02.020568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4548
 
18.1%
1 1372
 
5.4%
, 829
 
3.3%
동 815
 
3.2%
시 722
 
2.9%
기 692
 
2.7%
경 681
 
2.7%
도 677
 
2.7%
로 642
 
2.5%
) 633
 
2.5%
Other values (435) 13578
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14272
56.7%
Space Separator 4548
 
18.1%
Decimal Number 3977
 
15.8%
Other Punctuation 845
 
3.4%
Close Punctuation 633
 
2.5%
Open Punctuation 633
 
2.5%
Uppercase Letter 148
 
0.6%
Dash Punctuation 98
 
0.4%
Lowercase Letter 26
 
0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 815
 
5.7%
시 722
 
5.1%
기 692
 
4.8%
경 681
 
4.8%
도 677
 
4.7%
로 642
 
4.5%
층 477
 
3.3%
호 466
 
3.3%
구 324
 
2.3%
부 320
 
2.2%
Other values (378) 8456
59.2%
Uppercase Letter
ValueCountFrequency (%)
A 25
16.9%
B 22
14.9%
E 14
9.5%
T 12
 
8.1%
K 10
 
6.8%
C 10
 
6.8%
F 6
 
4.1%
L 6
 
4.1%
I 5
 
3.4%
P 5
 
3.4%
Other values (14) 33
22.3%
Lowercase Letter
ValueCountFrequency (%)
e 5
19.2%
a 3
11.5%
r 3
11.5%
l 2
 
7.7%
k 2
 
7.7%
s 2
 
7.7%
q 2
 
7.7%
u 2
 
7.7%
m 1
 
3.8%
h 1
 
3.8%
Other values (3) 3
11.5%
Decimal Number
ValueCountFrequency (%)
1 1372
34.5%
0 513
 
12.9%
2 479
 
12.0%
3 328
 
8.2%
5 276
 
6.9%
4 247
 
6.2%
7 219
 
5.5%
6 191
 
4.8%
9 178
 
4.5%
8 174
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 829
98.1%
. 15
 
1.8%
& 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 6
85.7%
+ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
4548
100.0%
Close Punctuation
ValueCountFrequency (%)
) 633
100.0%
Open Punctuation
ValueCountFrequency (%)
( 633
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 98
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14272
56.7%
Common 10741
42.6%
Latin 176
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 815
 
5.7%
시 722
 
5.1%
기 692
 
4.8%
경 681
 
4.8%
도 677
 
4.7%
로 642
 
4.5%
층 477
 
3.3%
호 466
 
3.3%
구 324
 
2.3%
부 320
 
2.2%
Other values (378) 8456
59.2%
Latin
ValueCountFrequency (%)
A 25
14.2%
B 22
 
12.5%
E 14
 
8.0%
T 12
 
6.8%
K 10
 
5.7%
C 10
 
5.7%
F 6
 
3.4%
L 6
 
3.4%
e 5
 
2.8%
I 5
 
2.8%
Other values (28) 61
34.7%
Common
ValueCountFrequency (%)
4548
42.3%
1 1372
 
12.8%
, 829
 
7.7%
) 633
 
5.9%
( 633
 
5.9%
0 513
 
4.8%
2 479
 
4.5%
3 328
 
3.1%
5 276
 
2.6%
4 247
 
2.3%
Other values (9) 883
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14272
56.7%
ASCII 10915
43.3%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4548
41.7%
1 1372
 
12.6%
, 829
 
7.6%
) 633
 
5.8%
( 633
 
5.8%
0 513
 
4.7%
2 479
 
4.4%
3 328
 
3.0%
5 276
 
2.5%
4 247
 
2.3%
Other values (46) 1057
 
9.7%
Hangul
ValueCountFrequency (%)
동 815
 
5.7%
시 722
 
5.1%
기 692
 
4.8%
경 681
 
4.8%
도 677
 
4.7%
로 642
 
4.5%
층 477
 
3.3%
호 466
 
3.3%
구 324
 
2.3%
부 320
 
2.2%
Other values (378) 8456
59.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

소재지지번주소
Text

Distinct635
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-10T20:24:02.565976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length46
Mean length30.112462
Min length14

Characters and Unicode

Total characters19814
Distinct characters405
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique617 ?
Unique (%)93.8%

Sample

1st row경기도 가평군 조종면 현리 410-25번지
2nd row경기도 고양시 덕양구 동산동 370 스타필드고양쇼핑몰동 1층일부
3rd row경기도 고양시 일산서구 대화동 2603 킨텍스 꿈에그린 181,1호
4th row경기도 고양시 덕양구 지축동 0
5th row경기도 고양시 일산동구 식사동 662-26 부경빌딩 102일부호
ValueCountFrequency (%)
경기도 658
 
15.6%
1층 121
 
2.9%
고양시 64
 
1.5%
성남시 59
 
1.4%
일부 57
 
1.4%
부천시 54
 
1.3%
용인시 50
 
1.2%
수원시 50
 
1.2%
화성시 38
 
0.9%
지하1층 33
 
0.8%
Other values (1465) 3035
71.9%
2024-05-10T20:24:03.601763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3896
 
19.7%
1 1057
 
5.3%
동 746
 
3.8%
시 717
 
3.6%
기 697
 
3.5%
도 683
 
3.4%
경 669
 
3.4%
- 406
 
2.0%
0 406
 
2.0%
2 394
 
2.0%
Other values (395) 10143
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11473
57.9%
Space Separator 3896
 
19.7%
Decimal Number 3736
 
18.9%
Dash Punctuation 406
 
2.0%
Uppercase Letter 111
 
0.6%
Other Punctuation 93
 
0.5%
Open Punctuation 34
 
0.2%
Close Punctuation 34
 
0.2%
Lowercase Letter 24
 
0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 746
 
6.5%
시 717
 
6.2%
기 697
 
6.1%
도 683
 
6.0%
경 669
 
5.8%
지 380
 
3.3%
구 323
 
2.8%
호 288
 
2.5%
번 244
 
2.1%
부 244
 
2.1%
Other values (340) 6482
56.5%
Uppercase Letter
ValueCountFrequency (%)
B 19
17.1%
A 18
16.2%
T 9
 
8.1%
E 9
 
8.1%
F 7
 
6.3%
K 7
 
6.3%
C 6
 
5.4%
I 5
 
4.5%
L 4
 
3.6%
G 4
 
3.6%
Other values (14) 23
20.7%
Lowercase Letter
ValueCountFrequency (%)
e 5
20.8%
r 3
12.5%
a 3
12.5%
u 2
 
8.3%
q 2
 
8.3%
s 2
 
8.3%
l 2
 
8.3%
f 1
 
4.2%
m 1
 
4.2%
h 1
 
4.2%
Other values (2) 2
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 1057
28.3%
0 406
 
10.9%
2 394
 
10.5%
6 318
 
8.5%
3 303
 
8.1%
5 289
 
7.7%
4 274
 
7.3%
7 250
 
6.7%
8 241
 
6.5%
9 204
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 77
82.8%
. 13
 
14.0%
& 3
 
3.2%
Space Separator
ValueCountFrequency (%)
3896
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 406
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11473
57.9%
Common 8204
41.4%
Latin 137
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 746
 
6.5%
시 717
 
6.2%
기 697
 
6.1%
도 683
 
6.0%
경 669
 
5.8%
지 380
 
3.3%
구 323
 
2.8%
호 288
 
2.5%
번 244
 
2.1%
부 244
 
2.1%
Other values (340) 6482
56.5%
Latin
ValueCountFrequency (%)
B 19
 
13.9%
A 18
 
13.1%
T 9
 
6.6%
E 9
 
6.6%
F 7
 
5.1%
K 7
 
5.1%
C 6
 
4.4%
I 5
 
3.6%
e 5
 
3.6%
L 4
 
2.9%
Other values (27) 48
35.0%
Common
ValueCountFrequency (%)
3896
47.5%
1 1057
 
12.9%
- 406
 
4.9%
0 406
 
4.9%
2 394
 
4.8%
6 318
 
3.9%
3 303
 
3.7%
5 289
 
3.5%
4 274
 
3.3%
7 250
 
3.0%
Other values (8) 611
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11473
57.9%
ASCII 8339
42.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3896
46.7%
1 1057
 
12.7%
- 406
 
4.9%
0 406
 
4.9%
2 394
 
4.7%
6 318
 
3.8%
3 303
 
3.6%
5 289
 
3.5%
4 274
 
3.3%
7 250
 
3.0%
Other values (44) 746
 
8.9%
Hangul
ValueCountFrequency (%)
동 746
 
6.5%
시 717
 
6.2%
기 697
 
6.1%
도 683
 
6.0%
경 669
 
5.8%
지 380
 
3.3%
구 323
 
2.8%
호 288
 
2.5%
번 244
 
2.1%
부 244
 
2.1%
Other values (340) 6482
56.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct422
Distinct (%)64.3%
Missing2
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean14085.518
Minimum10031
Maximum18611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-10T20:24:03.985548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10031
5-th percentile10226
Q111812.25
median13992
Q316579.75
95-th percentile18321.75
Maximum18611
Range8580
Interquartile range (IQR)4767.5

Descriptive statistics

Standard deviation2621.9129
Coefficient of variation (CV)0.18614245
Kurtosis-1.2287525
Mean14085.518
Median Absolute Deviation (MAD)2404.5
Skewness0.092674454
Sum9240100
Variance6874427.3
MonotonicityNot monotonic
2024-05-10T20:24:04.387593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10390 14
 
2.1%
14546 13
 
2.0%
10135 10
 
1.5%
10595 9
 
1.4%
12942 9
 
1.4%
16896 6
 
0.9%
18476 6
 
0.9%
11695 5
 
0.8%
13640 5
 
0.8%
11813 5
 
0.8%
Other values (412) 574
87.2%
ValueCountFrequency (%)
10031 1
 
0.2%
10062 1
 
0.2%
10071 4
0.6%
10077 1
 
0.2%
10082 2
0.3%
10083 1
 
0.2%
10088 1
 
0.2%
10089 3
0.5%
10090 1
 
0.2%
10102 1
 
0.2%
ValueCountFrequency (%)
18611 2
 
0.3%
18567 1
 
0.2%
18498 1
 
0.2%
18497 1
 
0.2%
18480 1
 
0.2%
18479 1
 
0.2%
18478 4
0.6%
18476 6
0.9%
18472 1
 
0.2%
18471 1
 
0.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct498
Distinct (%)76.3%
Missing5
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean37.449795
Minimum36.963544
Maximum38.017232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-10T20:24:04.819812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.963544
5-th percentile37.101976
Q137.285718
median37.436496
Q337.637827
95-th percentile37.760775
Maximum38.017232
Range1.0536879
Interquartile range (IQR)0.35210883

Descriptive statistics

Standard deviation0.21012824
Coefficient of variation (CV)0.0056109316
Kurtosis-0.53966606
Mean37.449795
Median Absolute Deviation (MAD)0.16730141
Skewness-0.026587953
Sum24454.716
Variance0.044153878
MonotonicityNot monotonic
2024-05-10T20:24:05.393237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5043171668 12
 
1.8%
37.5972979801 9
 
1.4%
37.545418129 9
 
1.4%
37.6470962619 9
 
1.4%
37.6690309166 6
 
0.9%
37.3250031722 6
 
0.9%
37.7379343921 5
 
0.8%
37.2303018745 4
 
0.6%
37.6646740405 4
 
0.6%
37.653754696 4
 
0.6%
Other values (488) 585
88.9%
(Missing) 5
 
0.8%
ValueCountFrequency (%)
36.963544108 1
0.2%
36.9789601868 1
0.2%
36.9877046831 1
0.2%
36.9908799936 1
0.2%
36.9919006082 2
0.3%
36.9919640634 1
0.2%
36.9926673663 1
0.2%
36.9945235041 2
0.3%
36.9946458119 1
0.2%
36.995560236 2
0.3%
ValueCountFrequency (%)
38.0172319589 1
0.2%
37.9546894423 1
0.2%
37.9319559282 1
0.2%
37.9022799551 1
0.2%
37.8995288907 1
0.2%
37.8978700393 1
0.2%
37.8954318909 1
0.2%
37.8940634432 1
0.2%
37.8927661327 1
0.2%
37.8926917176 1
0.2%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct498
Distinct (%)76.3%
Missing5
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean127.00433
Minimum126.59836
Maximum127.61365
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-10T20:24:05.769215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.59836
5-th percentile126.73866
Q1126.83252
median127.0469
Q3127.11859
95-th percentile127.29003
Maximum127.61365
Range1.0152926
Interquartile range (IQR)0.28606773

Descriptive statistics

Standard deviation0.18644918
Coefficient of variation (CV)0.0014680537
Kurtosis-0.33820097
Mean127.00433
Median Absolute Deviation (MAD)0.12426124
Skewness0.14721422
Sum82933.827
Variance0.034763296
MonotonicityNot monotonic
2024-05-10T20:24:06.175654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7620745903 12
 
1.8%
126.7852858447 9
 
1.4%
127.2237611843 9
 
1.4%
126.8948092677 9
 
1.4%
126.7456041294 6
 
0.9%
127.1081092919 6
 
0.9%
127.045835705 5
 
0.8%
127.0815447612 4
 
0.6%
126.7422467741 4
 
0.6%
126.7686925095 4
 
0.6%
Other values (488) 585
88.9%
(Missing) 5
 
0.8%
ValueCountFrequency (%)
126.598362339 1
0.2%
126.6245167276 2
0.3%
126.6255457011 1
0.2%
126.6275344505 1
0.2%
126.6282980439 1
0.2%
126.6629337542 2
0.3%
126.6682393692 1
0.2%
126.6734726532 1
0.2%
126.6774205372 1
0.2%
126.6778611238 1
0.2%
ValueCountFrequency (%)
127.6136549141 1
0.2%
127.5940296441 1
0.2%
127.4927264866 1
0.2%
127.4922306247 1
0.2%
127.4910519874 1
0.2%
127.4885608293 1
0.2%
127.4794525517 1
0.2%
127.4570572516 1
0.2%
127.4509085413 1
0.2%
127.4506680271 1
0.2%

Interactions

2024-05-10T20:23:52.518373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:23:50.783355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:23:51.716929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:23:52.751636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:23:51.062812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:23:52.036001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:23:53.099972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:23:51.427063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:23:52.292336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T20:24:06.427750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명소재지우편번호WGS84위도WGS84경도
시군명1.0000.2840.9910.9730.942
영업상태명0.2841.0000.2340.1610.157
소재지우편번호0.9910.2341.0000.9360.871
WGS84위도0.9730.1610.9361.0000.656
WGS84경도0.9420.1570.8710.6561.000
2024-05-10T20:24:06.634058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명시군명위생업종명
영업상태명1.0000.1471.000
시군명0.1471.0001.000
위생업종명1.0001.0001.000
2024-05-10T20:24:06.862164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명영업상태명위생업종명
소재지우편번호1.000-0.9060.2820.9140.1401.000
WGS84위도-0.9061.000-0.2700.8140.0961.000
WGS84경도0.282-0.2701.0000.6970.0941.000
시군명0.9140.8140.6971.0000.1471.000
영업상태명0.1400.0960.0940.1471.0001.000
위생업종명1.0001.0001.0001.0001.0001.000

Missing values

2024-05-10T20:23:53.487845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T20:23:54.101794image/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.
2024-05-10T20:23:54.532266image/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

시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0가평군배스킨라빈스20170314운영중<NA><NA><NA>휴게음식점아이스크림경기도 가평군 조종면 조종희망로 14경기도 가평군 조종면 현리 410-25번지1243837.818184127.350251
1고양시배스킨라빈스 고양스타필드점2019-06-27영업<NA><NA><NA><NA>아이스크림경기도 고양시 덕양구 고양대로 1955, 스타필드고양쇼핑몰동 1(일부)층 (동산동)경기도 고양시 덕양구 동산동 370 스타필드고양쇼핑몰동 1층일부1059537.647096126.894809
2고양시배스킨라빈스 킨텍스역점20210419영업<NA><NA><NA><NA>아이스크림경기도 고양시 일산서구 킨텍스로 240, 181,182호 (대화동, 킨텍스 꿈에그린)경기도 고양시 일산서구 대화동 2603 킨텍스 꿈에그린 181,1호1039137.665708126.750377
3고양시스쿱스젤라또 고양지축점20220718영업<NA><NA><NA><NA>아이스크림경기도 고양시 덕양구 안진2길 9, 1층 일부호 (지축동)경기도 고양시 덕양구 지축동 01058537.647811126.913224
4고양시에밀리아 젤라또 일산동국대병원점2023-02-03영업<NA><NA><NA><NA>아이스크림경기도 고양시 일산동구 위시티로 25, 부경빌딩 1층 102(일부)호 (식사동)경기도 고양시 일산동구 식사동 662-26 부경빌딩 102일부호1032537.675479126.807885
5고양시설빙 고양벨라시타점2022-09-08영업<NA><NA><NA><NA>아이스크림경기도 고양시 일산동구 강송로 33, 1층 일부호 (백석동, 일산 요진 와이시티)경기도 고양시 일산동구 백석동 1237 일산 요진 와이시티 1층 일부호 A-1203호1045037.641454126.791301
6고양시어더아사 화정역점2023-07-24영업<NA><NA><NA><NA>아이스크림경기도 고양시 덕양구 화신로272번길 58, 영프라자빌딩 1층 114호 (화정동)경기도 고양시 덕양구 화정동 972 영프라자빌딩1050037.633662126.832108
7고양시이케아아이스크림샵2020-11-09영업<NA><NA><NA><NA>아이스크림경기도 고양시 덕양구 권율대로 420, 이케아 고양점 3층 일부호 (도내동)경기도 고양시 덕양구 도내동 1003 이케아 고양점1055137.629588126.863106
8고양시베스킨라빈스2015-11-03영업<NA><NA><NA><NA>아이스크림경기도 고양시 덕양구 도래울로 105, 1층 106호 (도내동, 아카메디)경기도 고양시 덕양구 도내동 957 아카메디 1층 106호1055137.635077126.871469
9고양시설빙행신점2020-09-24영업<NA><NA><NA><NA>아이스크림경기도 고양시 덕양구 무원로6번길 20, M타워 2층 204호 (행신동)경기도 고양시 덕양구 행신동 707-3 M타워 204호1052337.613427126.833705
시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
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649화성시배스킨라빈스(화성안녕점)20170912운영중<NA><NA><NA>휴게음식점아이스크림경기도 화성시 용주로 9, 1층 일부호 (안녕동)경기도 화성시 안녕동 10-56번지 1층일부호1836037.20538127.015791
650화성시베스킨라빈스 동탄영천점20160215운영중<NA><NA><NA>휴게음식점아이스크림경기도 화성시 동탄순환대로 685, 106호 (영천동)경기도 화성시 영천동 651-1465번지 106호1847237.205965127.110923
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