Overview

Dataset statistics

Number of variables14
Number of observations2272
Missing cells7810
Missing cells (%)24.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory261.9 KiB
Average record size in memory118.1 B

Variable types

Text5
DateTime1
Categorical2
Unsupported3
Numeric3

Dataset

Description일반음식점(뷔페식) 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=X2LJ4G8SAPCP97BD28XO13529150&infSeq=1

Alerts

위생업태명 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
폐업일자 has 679 (29.9%) missing valuesMissing
다중이용업소여부 has 2272 (100.0%) missing valuesMissing
총시설규모(㎡) has 2272 (100.0%) missing valuesMissing
위생업종명 has 2272 (100.0%) missing valuesMissing
소재지도로명주소 has 141 (6.2%) missing valuesMissing
소재지우편번호 has 69 (3.0%) missing valuesMissing
WGS84위도 has 52 (2.3%) missing valuesMissing
WGS84경도 has 52 (2.3%) 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
위생업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 22:02:08.500763
Analysis finished2023-12-10 22:02:11.028653
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct55
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size17.9 KiB
2023-12-11T07:02:11.153877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9225352
Min length3

Characters and Unicode

Total characters8912
Distinct characters39
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.2%

Sample

1st row가평군
2nd row가평군
3rd row가평군
4th row가평군
5th row가평군
ValueCountFrequency (%)
평택시 225
 
9.9%
부천시 205
 
9.0%
고양시 203
 
8.9%
성남시 174
 
7.7%
수원시 167
 
7.4%
안산시 142
 
6.2%
안양시 116
 
5.1%
이천시 111
 
4.9%
김포시 107
 
4.7%
용인시 93
 
4.1%
Other values (21) 729
32.1%
2023-12-11T07:02:11.447447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 2320
26.0%
1918
21.5%
양 429
 
4.8%
천 376
 
4.2%
안 301
 
3.4%
부 280
 
3.1%
남 274
 
3.1%
성 271
 
3.0%
평 244
 
2.7%
택 225
 
2.5%
Other values (29) 2274
25.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6994
78.5%
Space Separator 1918
 
21.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2320
33.2%
양 429
 
6.1%
천 376
 
5.4%
안 301
 
4.3%
부 280
 
4.0%
남 274
 
3.9%
성 271
 
3.9%
평 244
 
3.5%
택 225
 
3.2%
주 205
 
2.9%
Other values (28) 2069
29.6%
Space Separator
ValueCountFrequency (%)
1918
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6994
78.5%
Common 1918
 
21.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2320
33.2%
양 429
 
6.1%
천 376
 
5.4%
안 301
 
4.3%
부 280
 
4.0%
남 274
 
3.9%
성 271
 
3.9%
평 244
 
3.5%
택 225
 
3.2%
주 205
 
2.9%
Other values (28) 2069
29.6%
Common
ValueCountFrequency (%)
1918
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6994
78.5%
ASCII 1918
 
21.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 2320
33.2%
양 429
 
6.1%
천 376
 
5.4%
안 301
 
4.3%
부 280
 
4.0%
남 274
 
3.9%
성 271
 
3.9%
평 244
 
3.5%
택 225
 
3.2%
주 205
 
2.9%
Other values (28) 2069
29.6%
ASCII
ValueCountFrequency (%)
1918
100.0%

사업장명
Text

Distinct2116
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size17.9 KiB
2023-12-11T07:02:11.684232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length7.0255282
Min length1

Characters and Unicode

Total characters15962
Distinct characters654
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2002 ?
Unique (%)88.1%

Sample

1st row뚱이네집보리밥뷔페
2nd row벨리웨딩홀
3rd row가평컨벤션뷔페식당
4th row가평제일부페
5th row귀빈연회뷔페
ValueCountFrequency (%)
한식뷔페 31
 
1.2%
주식회사 22
 
0.8%
한식부페 19
 
0.7%
쿠우쿠우 16
 
0.6%
부페 14
 
0.5%
뷔페 12
 
0.4%
애슐리퀸즈 11
 
0.4%
계절밥상 7
 
0.3%
컨벤션 7
 
0.3%
서울부페 7
 
0.3%
Other values (2239) 2523
94.5%
2023-12-11T07:02:12.039568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
페 1211
 
7.6%
부 896
 
5.6%
식 614
 
3.8%
한 539
 
3.4%
398
 
2.5%
뷔 369
 
2.3%
스 368
 
2.3%
웨 268
 
1.7%
딩 263
 
1.6%
점 258
 
1.6%
Other values (644) 10778
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14602
91.5%
Space Separator 398
 
2.5%
Close Punctuation 221
 
1.4%
Open Punctuation 216
 
1.4%
Uppercase Letter 195
 
1.2%
Decimal Number 152
 
1.0%
Lowercase Letter 109
 
0.7%
Other Punctuation 54
 
0.3%
Dash Punctuation 9
 
0.1%
Letter Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
페 1211
 
8.3%
부 896
 
6.1%
식 614
 
4.2%
한 539
 
3.7%
뷔 369
 
2.5%
스 368
 
2.5%
웨 268
 
1.8%
딩 263
 
1.8%
점 258
 
1.8%
이 253
 
1.7%
Other values (578) 9563
65.5%
Uppercase Letter
ValueCountFrequency (%)
N 18
 
9.2%
A 17
 
8.7%
W 14
 
7.2%
C 13
 
6.7%
S 11
 
5.6%
O 11
 
5.6%
L 11
 
5.6%
J 10
 
5.1%
B 10
 
5.1%
E 10
 
5.1%
Other values (14) 70
35.9%
Lowercase Letter
ValueCountFrequency (%)
e 19
17.4%
n 12
11.0%
h 10
 
9.2%
i 9
 
8.3%
t 9
 
8.3%
p 5
 
4.6%
o 5
 
4.6%
a 5
 
4.6%
r 4
 
3.7%
y 4
 
3.7%
Other values (10) 27
24.8%
Decimal Number
ValueCountFrequency (%)
2 40
26.3%
1 35
23.0%
0 20
13.2%
3 16
 
10.5%
9 12
 
7.9%
5 10
 
6.6%
4 8
 
5.3%
8 6
 
3.9%
6 3
 
2.0%
7 2
 
1.3%
Other Punctuation
ValueCountFrequency (%)
& 26
48.1%
. 15
27.8%
, 8
 
14.8%
' 3
 
5.6%
/ 1
 
1.9%
· 1
 
1.9%
Letter Number
ValueCountFrequency (%)
Ⅰ 3
50.0%
Ⅱ 3
50.0%
Space Separator
ValueCountFrequency (%)
398
100.0%
Close Punctuation
ValueCountFrequency (%)
) 221
100.0%
Open Punctuation
ValueCountFrequency (%)
( 216
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14600
91.5%
Common 1050
 
6.6%
Latin 310
 
1.9%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
페 1211
 
8.3%
부 896
 
6.1%
식 614
 
4.2%
한 539
 
3.7%
뷔 369
 
2.5%
스 368
 
2.5%
웨 268
 
1.8%
딩 263
 
1.8%
점 258
 
1.8%
이 253
 
1.7%
Other values (576) 9561
65.5%
Latin
ValueCountFrequency (%)
e 19
 
6.1%
N 18
 
5.8%
A 17
 
5.5%
W 14
 
4.5%
C 13
 
4.2%
n 12
 
3.9%
S 11
 
3.5%
O 11
 
3.5%
L 11
 
3.5%
J 10
 
3.2%
Other values (36) 174
56.1%
Common
ValueCountFrequency (%)
398
37.9%
) 221
21.0%
( 216
20.6%
2 40
 
3.8%
1 35
 
3.3%
& 26
 
2.5%
0 20
 
1.9%
3 16
 
1.5%
. 15
 
1.4%
9 12
 
1.1%
Other values (10) 51
 
4.9%
Han
ValueCountFrequency (%)
秀 1
50.0%
愛 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14600
91.5%
ASCII 1353
 
8.5%
Number Forms 6
 
< 0.1%
CJK 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
페 1211
 
8.3%
부 896
 
6.1%
식 614
 
4.2%
한 539
 
3.7%
뷔 369
 
2.5%
스 368
 
2.5%
웨 268
 
1.8%
딩 263
 
1.8%
점 258
 
1.8%
이 253
 
1.7%
Other values (576) 9561
65.5%
ASCII
ValueCountFrequency (%)
398
29.4%
) 221
16.3%
( 216
16.0%
2 40
 
3.0%
1 35
 
2.6%
& 26
 
1.9%
0 20
 
1.5%
e 19
 
1.4%
N 18
 
1.3%
A 17
 
1.3%
Other values (53) 343
25.4%
Number Forms
ValueCountFrequency (%)
Ⅰ 3
50.0%
Ⅱ 3
50.0%
CJK
ValueCountFrequency (%)
秀 1
50.0%
愛 1
50.0%
None
ValueCountFrequency (%)
· 1
100.0%

인허가일자
Date

Distinct1928
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size17.9 KiB
Minimum1977-03-10 00:00:00
Maximum2023-11-13 00:00:00
2023-12-11T07:02:12.354714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:02:12.475800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.9 KiB
폐업
1593 
영업
679 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1593
70.1%
영업 679
29.9%

Length

2023-12-11T07:02:12.591951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:12.672051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1593
70.1%
영업 679
29.9%

폐업일자
Text

MISSING 

Distinct1331
Distinct (%)83.6%
Missing679
Missing (%)29.9%
Memory size17.9 KiB
2023-12-11T07:02:12.965218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.0401758
Min length8

Characters and Unicode

Total characters12808
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

Unique1120 ?
Unique (%)70.3%

Sample

1st row20110502
2nd row20100518
3rd row20100326
4th row20080707
5th row2023-01-30
ValueCountFrequency (%)
20130909 4
 
0.3%
20151023 4
 
0.3%
20070809 4
 
0.3%
20161121 4
 
0.3%
19981130 4
 
0.3%
20221230 4
 
0.3%
20151005 4
 
0.3%
20180214 4
 
0.3%
20171121 4
 
0.3%
20170105 3
 
0.2%
Other values (1321) 1554
97.6%
2023-12-11T07:02:13.400997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4165
32.5%
2 2954
23.1%
1 2359
18.4%
9 625
 
4.9%
3 511
 
4.0%
8 478
 
3.7%
6 433
 
3.4%
7 416
 
3.2%
5 408
 
3.2%
4 395
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12744
99.5%
Dash Punctuation 64
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4165
32.7%
2 2954
23.2%
1 2359
18.5%
9 625
 
4.9%
3 511
 
4.0%
8 478
 
3.8%
6 433
 
3.4%
7 416
 
3.3%
5 408
 
3.2%
4 395
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12808
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4165
32.5%
2 2954
23.1%
1 2359
18.4%
9 625
 
4.9%
3 511
 
4.0%
8 478
 
3.7%
6 433
 
3.4%
7 416
 
3.2%
5 408
 
3.2%
4 395
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12808
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4165
32.5%
2 2954
23.1%
1 2359
18.4%
9 625
 
4.9%
3 511
 
4.0%
8 478
 
3.7%
6 433
 
3.4%
7 416
 
3.2%
5 408
 
3.2%
4 395
 
3.1%

다중이용업소여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2272
Missing (%)100.0%
Memory size20.1 KiB

총시설규모(㎡)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2272
Missing (%)100.0%
Memory size20.1 KiB

위생업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2272
Missing (%)100.0%
Memory size20.1 KiB

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.9 KiB
뷔페식
2272 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
뷔페식 2272
100.0%

Length

2023-12-11T07:02:13.521865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:02:13.598773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
뷔페식 2272
100.0%

소재지도로명주소
Text

MISSING 

Distinct2062
Distinct (%)96.8%
Missing141
Missing (%)6.2%
Memory size17.9 KiB
2023-12-11T07:02:13.890283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length96
Median length65
Mean length30.106053
Min length13

Characters and Unicode

Total characters64156
Distinct characters518
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2005 ?
Unique (%)94.1%

Sample

1st row경기도 가평군 청평면 시장중앙로3번길 7, 1층
2nd row경기도 가평군 가평읍 광장로 9, 1층
3rd row경기도 가평군 가평읍 보납로 41
4th row경기도 가평군 가평읍 경춘로 2176
5th row경기도 가평군 가평읍 가화로 138
ValueCountFrequency (%)
경기도 2131
 
15.8%
1층 325
 
2.4%
평택시 213
 
1.6%
고양시 195
 
1.4%
부천시 188
 
1.4%
성남시 171
 
1.3%
2층 166
 
1.2%
수원시 156
 
1.2%
안산시 129
 
1.0%
안양시 107
 
0.8%
Other values (3570) 9686
71.9%
2023-12-11T07:02:14.385362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11372
 
17.7%
1 2854
 
4.4%
경 2264
 
3.5%
시 2264
 
3.5%
기 2219
 
3.5%
도 2198
 
3.4%
로 2012
 
3.1%
, 1967
 
3.1%
2 1831
 
2.9%
동 1697
 
2.6%
Other values (508) 33478
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35602
55.5%
Decimal Number 11664
 
18.2%
Space Separator 11372
 
17.7%
Other Punctuation 1982
 
3.1%
Open Punctuation 1355
 
2.1%
Close Punctuation 1354
 
2.1%
Dash Punctuation 400
 
0.6%
Uppercase Letter 294
 
0.5%
Math Symbol 113
 
0.2%
Lowercase Letter 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 2264
 
6.4%
시 2264
 
6.4%
기 2219
 
6.2%
도 2198
 
6.2%
로 2012
 
5.7%
동 1697
 
4.8%
층 1026
 
2.9%
구 924
 
2.6%
호 724
 
2.0%
길 699
 
2.0%
Other values (453) 19575
55.0%
Uppercase Letter
ValueCountFrequency (%)
B 91
31.0%
A 40
13.6%
C 25
 
8.5%
F 16
 
5.4%
T 13
 
4.4%
R 11
 
3.7%
D 10
 
3.4%
I 10
 
3.4%
M 10
 
3.4%
K 10
 
3.4%
Other values (15) 58
19.7%
Decimal Number
ValueCountFrequency (%)
1 2854
24.5%
2 1831
15.7%
0 1352
11.6%
3 1171
10.0%
4 923
 
7.9%
5 842
 
7.2%
6 753
 
6.5%
7 695
 
6.0%
8 664
 
5.7%
9 579
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
a 5
33.3%
l 4
26.7%
b 1
 
6.7%
i 1
 
6.7%
v 1
 
6.7%
t 1
 
6.7%
s 1
 
6.7%
e 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 1967
99.2%
. 12
 
0.6%
/ 2
 
0.1%
: 1
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
40.0%
Ⅲ 2
40.0%
Ⅱ 1
20.0%
Space Separator
ValueCountFrequency (%)
11372
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1355
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1354
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 400
100.0%
Math Symbol
ValueCountFrequency (%)
~ 113
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35599
55.5%
Common 28240
44.0%
Latin 314
 
0.5%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 2264
 
6.4%
시 2264
 
6.4%
기 2219
 
6.2%
도 2198
 
6.2%
로 2012
 
5.7%
동 1697
 
4.8%
층 1026
 
2.9%
구 924
 
2.6%
호 724
 
2.0%
길 699
 
2.0%
Other values (450) 19572
55.0%
Latin
ValueCountFrequency (%)
B 91
29.0%
A 40
12.7%
C 25
 
8.0%
F 16
 
5.1%
T 13
 
4.1%
R 11
 
3.5%
D 10
 
3.2%
I 10
 
3.2%
M 10
 
3.2%
K 10
 
3.2%
Other values (26) 78
24.8%
Common
ValueCountFrequency (%)
11372
40.3%
1 2854
 
10.1%
, 1967
 
7.0%
2 1831
 
6.5%
( 1355
 
4.8%
) 1354
 
4.8%
0 1352
 
4.8%
3 1171
 
4.1%
4 923
 
3.3%
5 842
 
3.0%
Other values (9) 3219
 
11.4%
Han
ValueCountFrequency (%)
內 1
33.3%
堂 1
33.3%
美 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35599
55.5%
ASCII 28549
44.5%
Number Forms 5
 
< 0.1%
CJK 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11372
39.8%
1 2854
 
10.0%
, 1967
 
6.9%
2 1831
 
6.4%
( 1355
 
4.7%
) 1354
 
4.7%
0 1352
 
4.7%
3 1171
 
4.1%
4 923
 
3.2%
5 842
 
2.9%
Other values (42) 3528
 
12.4%
Hangul
ValueCountFrequency (%)
경 2264
 
6.4%
시 2264
 
6.4%
기 2219
 
6.2%
도 2198
 
6.2%
로 2012
 
5.7%
동 1697
 
4.8%
층 1026
 
2.9%
구 924
 
2.6%
호 724
 
2.0%
길 699
 
2.0%
Other values (450) 19572
55.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
40.0%
Ⅲ 2
40.0%
Ⅱ 1
20.0%
CJK
ValueCountFrequency (%)
內 1
33.3%
堂 1
33.3%
美 1
33.3%

소재지지번주소
Text

Distinct2226
Distinct (%)98.0%
Missing1
Missing (%)< 0.1%
Memory size17.9 KiB
2023-12-11T07:02:14.664185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length103
Median length63
Mean length28.116689
Min length13

Characters and Unicode

Total characters63853
Distinct characters499
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2188 ?
Unique (%)96.3%

Sample

1st row경기도 가평군 청평면 청평리 429-8 1층
2nd row경기도 가평군 가평읍 대곡리 258-2 1층
3rd row경기도 가평군 가평읍 읍내리 426-6번지
4th row경기도 가평군 가평읍 대곡리 107번지
5th row경기도 가평군 가평읍 읍내리 443-17번지 외3필지
ValueCountFrequency (%)
경기도 2272
 
17.1%
1층 230
 
1.7%
평택시 225
 
1.7%
부천시 205
 
1.5%
고양시 205
 
1.5%
성남시 174
 
1.3%
수원시 167
 
1.3%
안산시 142
 
1.1%
2층 139
 
1.0%
안양시 116
 
0.9%
Other values (3987) 9450
70.9%
2023-12-11T07:02:15.087957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11251
 
17.6%
1 3148
 
4.9%
시 2370
 
3.7%
도 2325
 
3.6%
기 2319
 
3.6%
경 2287
 
3.6%
동 2254
 
3.5%
2 1957
 
3.1%
지 1836
 
2.9%
- 1797
 
2.8%
Other values (489) 32309
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35226
55.2%
Decimal Number 13948
 
21.8%
Space Separator 11251
 
17.6%
Dash Punctuation 1797
 
2.8%
Other Punctuation 743
 
1.2%
Uppercase Letter 289
 
0.5%
Open Punctuation 237
 
0.4%
Close Punctuation 236
 
0.4%
Math Symbol 105
 
0.2%
Lowercase Letter 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2370
 
6.7%
도 2325
 
6.6%
기 2319
 
6.6%
경 2287
 
6.5%
동 2254
 
6.4%
지 1836
 
5.2%
번 1331
 
3.8%
층 983
 
2.8%
구 972
 
2.8%
호 723
 
2.1%
Other values (429) 17826
50.6%
Uppercase Letter
ValueCountFrequency (%)
B 87
30.1%
A 41
14.2%
C 24
 
8.3%
F 19
 
6.6%
T 11
 
3.8%
D 10
 
3.5%
R 10
 
3.5%
E 10
 
3.5%
I 10
 
3.5%
K 9
 
3.1%
Other values (15) 58
20.1%
Decimal Number
ValueCountFrequency (%)
1 3148
22.6%
2 1957
14.0%
0 1469
10.5%
3 1428
10.2%
4 1263
9.1%
5 1158
 
8.3%
6 1007
 
7.2%
7 915
 
6.6%
8 854
 
6.1%
9 749
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
l 5
31.2%
a 4
25.0%
x 1
 
6.2%
i 1
 
6.2%
v 1
 
6.2%
t 1
 
6.2%
s 1
 
6.2%
e 1
 
6.2%
p 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 680
91.5%
. 59
 
7.9%
/ 2
 
0.3%
: 1
 
0.1%
@ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 102
97.1%
> 1
 
1.0%
< 1
 
1.0%
∼ 1
 
1.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
40.0%
Ⅲ 2
40.0%
Ⅱ 1
20.0%
Space Separator
ValueCountFrequency (%)
11251
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1797
100.0%
Open Punctuation
ValueCountFrequency (%)
( 237
100.0%
Close Punctuation
ValueCountFrequency (%)
) 236
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35223
55.2%
Common 28317
44.3%
Latin 310
 
0.5%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2370
 
6.7%
도 2325
 
6.6%
기 2319
 
6.6%
경 2287
 
6.5%
동 2254
 
6.4%
지 1836
 
5.2%
번 1331
 
3.8%
층 983
 
2.8%
구 972
 
2.8%
호 723
 
2.1%
Other values (426) 17823
50.6%
Latin
ValueCountFrequency (%)
B 87
28.1%
A 41
13.2%
C 24
 
7.7%
F 19
 
6.1%
T 11
 
3.5%
D 10
 
3.2%
R 10
 
3.2%
E 10
 
3.2%
I 10
 
3.2%
K 9
 
2.9%
Other values (27) 79
25.5%
Common
ValueCountFrequency (%)
11251
39.7%
1 3148
 
11.1%
2 1957
 
6.9%
- 1797
 
6.3%
0 1469
 
5.2%
3 1428
 
5.0%
4 1263
 
4.5%
5 1158
 
4.1%
6 1007
 
3.6%
7 915
 
3.2%
Other values (13) 2924
 
10.3%
Han
ValueCountFrequency (%)
內 1
33.3%
堂 1
33.3%
美 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35223
55.2%
ASCII 28621
44.8%
Number Forms 5
 
< 0.1%
CJK 3
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11251
39.3%
1 3148
 
11.0%
2 1957
 
6.8%
- 1797
 
6.3%
0 1469
 
5.1%
3 1428
 
5.0%
4 1263
 
4.4%
5 1158
 
4.0%
6 1007
 
3.5%
7 915
 
3.2%
Other values (46) 3228
 
11.3%
Hangul
ValueCountFrequency (%)
시 2370
 
6.7%
도 2325
 
6.6%
기 2319
 
6.6%
경 2287
 
6.5%
동 2254
 
6.4%
지 1836
 
5.2%
번 1331
 
3.8%
층 983
 
2.8%
구 972
 
2.8%
호 723
 
2.1%
Other values (426) 17823
50.6%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
40.0%
Ⅲ 2
40.0%
Ⅱ 1
20.0%
CJK
ValueCountFrequency (%)
內 1
33.3%
堂 1
33.3%
美 1
33.3%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1170
Distinct (%)53.1%
Missing69
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean14390.041
Minimum10008
Maximum18631
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.1 KiB
2023-12-11T07:02:15.221341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10008
5-th percentile10223.1
Q112068
median14548
Q316705
95-th percentile17940.5
Maximum18631
Range8623
Interquartile range (IQR)4637

Descriptive statistics

Standard deviation2608.5651
Coefficient of variation (CV)0.18127572
Kurtosis-1.2096267
Mean14390.041
Median Absolute Deviation (MAD)2372
Skewness-0.18589861
Sum31701261
Variance6804611.7
MonotonicityNot monotonic
2023-12-11T07:02:15.360933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15865 19
 
0.8%
10500 16
 
0.7%
16491 15
 
0.7%
14623 14
 
0.6%
17823 14
 
0.6%
14637 13
 
0.6%
15360 13
 
0.6%
13506 11
 
0.5%
15361 11
 
0.5%
11651 11
 
0.5%
Other values (1160) 2066
90.9%
(Missing) 69
 
3.0%
ValueCountFrequency (%)
10008 1
 
< 0.1%
10010 4
0.2%
10012 3
0.1%
10014 1
 
< 0.1%
10016 1
 
< 0.1%
10017 1
 
< 0.1%
10018 4
0.2%
10019 1
 
< 0.1%
10020 1
 
< 0.1%
10022 1
 
< 0.1%
ValueCountFrequency (%)
18631 1
< 0.1%
18606 1
< 0.1%
18600 2
0.1%
18595 1
< 0.1%
18592 1
< 0.1%
18591 1
< 0.1%
18584 1
< 0.1%
18583 1
< 0.1%
18581 1
< 0.1%
18566 1
< 0.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1870
Distinct (%)84.2%
Missing52
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean37.416049
Minimum36.938069
Maximum38.100818
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.1 KiB
2023-12-11T07:02:15.487090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.938069
5-th percentile37.018434
Q137.275028
median37.39692
Q337.615456
95-th percentile37.763426
Maximum38.100818
Range1.1627496
Interquartile range (IQR)0.34042732

Descriptive statistics

Standard deviation0.22511103
Coefficient of variation (CV)0.0060164298
Kurtosis-0.56450382
Mean37.416049
Median Absolute Deviation (MAD)0.1393676
Skewness0.049888264
Sum83063.629
Variance0.050674976
MonotonicityNot monotonic
2023-12-11T07:02:15.634672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7379636094 8
 
0.4%
37.4752632034 6
 
0.3%
37.4855857173 5
 
0.2%
37.2531386864 5
 
0.2%
37.4895874749 5
 
0.2%
37.3035437598 5
 
0.2%
37.5064035555 5
 
0.2%
37.3492781995 5
 
0.2%
37.4888795916 5
 
0.2%
37.3981473497 4
 
0.2%
Other values (1860) 2167
95.4%
(Missing) 52
 
2.3%
ValueCountFrequency (%)
36.9380686213 1
< 0.1%
36.945223949 1
< 0.1%
36.9490609097 1
< 0.1%
36.9490753931 1
< 0.1%
36.9496981424 1
< 0.1%
36.9574798842 1
< 0.1%
36.9578869316 1
< 0.1%
36.9590716413 1
< 0.1%
36.9673346487 1
< 0.1%
36.9745997142 1
< 0.1%
ValueCountFrequency (%)
38.1008182395 1
< 0.1%
38.0301930006 1
< 0.1%
38.0278453361 1
< 0.1%
38.0099820185 2
0.1%
38.0095705436 1
< 0.1%
37.9623080117 1
< 0.1%
37.9601657398 1
< 0.1%
37.9593737477 1
< 0.1%
37.9558654465 1
< 0.1%
37.9548322926 1
< 0.1%

WGS84경도
Real number (ℝ)

MISSING 

Distinct1870
Distinct (%)84.2%
Missing52
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean126.98925
Minimum126.53664
Maximum127.75414
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.1 KiB
2023-12-11T07:02:15.781044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53664
5-th percentile126.72496
Q1126.80809
median126.99159
Q3127.11203
95-th percentile127.43628
Maximum127.75414
Range1.2174942
Interquartile range (IQR)0.30393866

Descriptive statistics

Standard deviation0.20967803
Coefficient of variation (CV)0.0016511479
Kurtosis0.19765918
Mean126.98925
Median Absolute Deviation (MAD)0.15233595
Skewness0.60161633
Sum281916.13
Variance0.043964878
MonotonicityNot monotonic
2023-12-11T07:02:15.947643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0440650026 8
 
0.4%
126.8671319861 6
 
0.3%
126.7823247232 5
 
0.2%
127.4425351446 5
 
0.2%
126.7546293907 5
 
0.2%
127.0075005776 5
 
0.2%
126.754145423 5
 
0.2%
127.1083218741 5
 
0.2%
126.7552924952 5
 
0.2%
126.9226440821 4
 
0.2%
Other values (1860) 2167
95.4%
(Missing) 52
 
2.3%
ValueCountFrequency (%)
126.5366429773 1
< 0.1%
126.554339608 1
< 0.1%
126.5643533231 1
< 0.1%
126.5646611537 1
< 0.1%
126.5696711291 1
< 0.1%
126.5718713729 1
< 0.1%
126.5732823136 1
< 0.1%
126.5742569717 1
< 0.1%
126.5752057511 1
< 0.1%
126.5762435159 1
< 0.1%
ValueCountFrequency (%)
127.7541371773 1
 
< 0.1%
127.6493588717 1
 
< 0.1%
127.6428772979 3
0.1%
127.6367504612 1
 
< 0.1%
127.6362086004 2
0.1%
127.635598597 1
 
< 0.1%
127.6353944158 1
 
< 0.1%
127.6353050456 1
 
< 0.1%
127.634413427 1
 
< 0.1%
127.6324848981 1
 
< 0.1%

Interactions

2023-12-11T07:02:10.271112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:02:09.685900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:02:09.975001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:02:10.371891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:02:09.769303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:02:10.070115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:02:10.473238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:02:09.862497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:02:10.153584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:02:16.033282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명소재지우편번호WGS84위도WGS84경도
시군명1.0000.5010.9930.9720.957
영업상태명0.5011.0000.2740.2520.247
소재지우편번호0.9930.2741.0000.9290.871
WGS84위도0.9720.2520.9291.0000.704
WGS84경도0.9570.2470.8710.7041.000
2023-12-11T07:02:16.126877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도영업상태명
소재지우편번호1.000-0.9230.3570.209
WGS84위도-0.9231.000-0.3780.193
WGS84경도0.357-0.3781.0000.189
영업상태명0.2090.1930.1891.000

Missing values

2023-12-11T07:02:10.617001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:02:10.799396image/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.
2023-12-11T07:02:10.935618image/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
0가평군뚱이네집보리밥뷔페20200624영업<NA><NA><NA><NA>뷔페식경기도 가평군 청평면 시장중앙로3번길 7, 1층경기도 가평군 청평면 청평리 429-8 1층1245337.735833127.416969
1가평군벨리웨딩홀20021202영업<NA><NA><NA><NA>뷔페식경기도 가평군 가평읍 광장로 9, 1층경기도 가평군 가평읍 대곡리 258-2 1층1241637.825994127.510909
2가평군가평컨벤션뷔페식당20090515폐업20110502<NA><NA><NA>뷔페식경기도 가평군 가평읍 보납로 41경기도 가평군 가평읍 읍내리 426-6번지1241237.831446127.515034
3가평군가평제일부페19960924폐업20100518<NA><NA><NA>뷔페식경기도 가평군 가평읍 경춘로 2176경기도 가평군 가평읍 대곡리 107번지1242137.81954127.513373
4가평군귀빈연회뷔페20051117폐업20100326<NA><NA><NA>뷔페식경기도 가평군 가평읍 가화로 138경기도 가평군 가평읍 읍내리 443-17번지 외3필지1241237.831789127.51275
5가평군백두산20060704폐업20080707<NA><NA><NA>뷔페식경기도 가평군 가평읍 가화로 183경기도 가평군 가평읍 읍내리 681-1번지1241337.835458127.510217
6고양시풍성한 한식뷔페2023-03-08영업<NA><NA><NA><NA>뷔페식경기도 고양시 일산동구 일산로 142, 유니테크빌벤처타운 101(일부)호 (백석동)경기도 고양시 일산동구 백석동 1141-2 유니테크빌벤처타운 101(일부)호1044237.649905126.793681
7고양시예은출장부페2005-02-28영업<NA><NA><NA><NA>뷔페식경기도 고양시 덕양구 충장로350번길 175-15, 1층 (성사동)경기도 고양시 덕양구 성사동 149-5 1층1048037.640634126.84746
8고양시(주)이랜드이츠 애슐리퀸즈 벨라시타일산점2023-06-26영업<NA><NA><NA><NA>뷔페식경기도 고양시 일산동구 강송로 33, 지하1층 일부호 (백석동, 일산 요진 와이시티)경기도 고양시 일산동구 백석동 1237 일산 요진 와이시티 지하1층 일부호(A-B130호)1045037.641454126.791301
9고양시셰프스키친(Chef's Kitchen)2013-03-06영업<NA><NA><NA><NA>뷔페식경기도 고양시 일산동구 태극로 20, 204호 (장항동)경기도 고양시 일산동구 장항동 17561039437.661907126.750767
시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
2262화성시남양한정식부페20061212폐업20151005<NA><NA><NA>뷔페식경기도 화성시 남양읍 남양시장로66번길 9-15 (남양동)경기도 화성시 남양읍 남양리 12321826137.209347126.818105
2263화성시두성웨딩홀부페20031031폐업20151005<NA><NA><NA>뷔페식<NA>경기도 화성시 남양읍 남양리 1627-1 외 2필지<NA>37.209685126.823662
2264화성시파티벨동탄점20110307폐업20160203<NA><NA><NA>뷔페식경기도 화성시 동탄지성로 11, 208,209,210호 (반송동, 동탄SR GOLD PLAZA (201, 202, 203, 204, 207)경기도 화성시 반송동 93-2 (201, 202, 203, 204, 207, 208, 209, 210호)1845437.204518127.072785
2265화성시링팡도넛츠&카페20100806폐업20150330<NA><NA><NA>뷔페식경기도 화성시 남양읍 남양시장로66번길 10-7 (남양동)경기도 화성시 남양읍 남양리 1170 청남빌딩 2층1826137.20791126.816022
2266화성시만석한식부페20101021폐업20150828<NA><NA><NA>뷔페식경기도 화성시 장안면 꽃밭길 3경기도 화성시 장안면 수촌리 741858137.09259126.862294
2267화성시한올웨딩부페한식19971230폐업20061004<NA><NA><NA>뷔페식<NA>경기도 화성시 향남읍 하길리 1-1<NA>37.116953126.903216
2268화성시노나식당20151029폐업20160830<NA><NA><NA>뷔페식경기도 화성시 삼성1로 150, 103호 (석우동)경기도 화성시 석우동 31-6 103호1845037.217364127.078359
2269화성시전원농장19950408폐업20070601<NA><NA><NA>뷔페식<NA>경기도 화성시 남양읍 남양리 381-2<NA>37.203021126.797939
2270화성시피에스타920130925폐업20181226<NA><NA><NA>뷔페식경기도 화성시 향남읍 향남로 430-16 (향남 중흥에스스퀘어 2차 2층 201~210호)경기도 화성시 향남읍 행정리 472-2 향남 중흥에스스퀘어 2차 2층 201~210호1859137.133042126.923066
2271화성시전주한중식부페20150616폐업20170601<NA><NA><NA>뷔페식경기도 화성시 동탄면 동탄대로22길 587, 301,302호<NA><NA><NA><NA>