Overview

Dataset statistics

Number of variables14
Number of observations28
Missing cells72
Missing cells (%)18.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory121.7 B

Variable types

Text4
DateTime2
Categorical3
Unsupported2
Numeric3

Dataset

Description휴게음식점(관광호텔) 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=QM8T7VZ0EDGJXD70W5NV13412431&infSeq=1

Alerts

위생업태명 has constant value ""Constant
영업상태명 is highly overall correlated with 위생업종명High correlation
위생업종명 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 위생업종명High correlation
폐업일자 has 13 (46.4%) missing valuesMissing
다중이용업소여부 has 28 (100.0%) missing valuesMissing
총시설규모(㎡) has 28 (100.0%) missing valuesMissing
소재지도로명주소 has 1 (3.6%) missing valuesMissing
WGS84위도 has 1 (3.6%) missing valuesMissing
WGS84경도 has 1 (3.6%) missing valuesMissing
소재지지번주소 has unique valuesUnique
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 20:38:19.044009
Analysis finished2024-05-10 20:38:24.613888
Duration5.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct18
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-10T20:38:24.800709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0357143
Min length3

Characters and Unicode

Total characters85
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)42.9%

Sample

1st row가평군
2nd row가평군
3rd row고양시
4th row과천시
5th row군포시
ValueCountFrequency (%)
평택시 4
14.3%
성남시 4
14.3%
가평군 2
 
7.1%
하남시 2
 
7.1%
파주시 2
 
7.1%
부천시 2
 
7.1%
고양시 1
 
3.6%
안산시 1
 
3.6%
이천시 1
 
3.6%
양주시 1
 
3.6%
Other values (8) 8
28.6%
2024-05-10T20:38:25.574913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 27
31.8%
남 7
 
8.2%
평 6
 
7.1%
성 5
 
5.9%
천 4
 
4.7%
양 4
 
4.7%
택 4
 
4.7%
주 4
 
4.7%
군 3
 
3.5%
파 2
 
2.4%
Other values (14) 19
22.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 85
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 27
31.8%
남 7
 
8.2%
평 6
 
7.1%
성 5
 
5.9%
천 4
 
4.7%
양 4
 
4.7%
택 4
 
4.7%
주 4
 
4.7%
군 3
 
3.5%
파 2
 
2.4%
Other values (14) 19
22.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 85
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 27
31.8%
남 7
 
8.2%
평 6
 
7.1%
성 5
 
5.9%
천 4
 
4.7%
양 4
 
4.7%
택 4
 
4.7%
주 4
 
4.7%
군 3
 
3.5%
파 2
 
2.4%
Other values (14) 19
22.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 85
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 27
31.8%
남 7
 
8.2%
평 6
 
7.1%
성 5
 
5.9%
천 4
 
4.7%
양 4
 
4.7%
택 4
 
4.7%
주 4
 
4.7%
군 3
 
3.5%
파 2
 
2.4%
Other values (14) 19
22.4%

사업장명
Text

Distinct23
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-10T20:38:26.057493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length7.2857143
Min length2

Characters and Unicode

Total characters204
Distinct characters88
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)64.3%

Sample

1st row가평관광호텔휴게실
2nd row가평관광호텔휴게실
3rd row미소떡볶이
4th row과천관광호텔
5th row미니스톱금정점
ValueCountFrequency (%)
가평관광호텔휴게실 2
 
6.1%
호텔야자 2
 
6.1%
위례점 2
 
6.1%
비젼 2
 
6.1%
로망스 2
 
6.1%
파비아관광호텔커피숍 2
 
6.1%
카페루앤비안산일동점 1
 
3.0%
주)호텔 1
 
3.0%
호텔소그노커피숍 1
 
3.0%
가보호텔레스토랑 1
 
3.0%
Other values (17) 17
51.5%
2024-05-10T20:38:26.944134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
호 16
 
7.8%
텔 15
 
7.4%
관 9
 
4.4%
광 9
 
4.4%
스 6
 
2.9%
이 6
 
2.9%
커 5
 
2.5%
점 5
 
2.5%
5
 
2.5%
비 5
 
2.5%
Other values (78) 123
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 193
94.6%
Space Separator 5
 
2.5%
Close Punctuation 3
 
1.5%
Open Punctuation 3
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 16
 
8.3%
텔 15
 
7.8%
관 9
 
4.7%
광 9
 
4.7%
스 6
 
3.1%
이 6
 
3.1%
커 5
 
2.6%
점 5
 
2.6%
비 5
 
2.6%
피 5
 
2.6%
Other values (75) 112
58.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 193
94.6%
Common 11
 
5.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 16
 
8.3%
텔 15
 
7.8%
관 9
 
4.7%
광 9
 
4.7%
스 6
 
3.1%
이 6
 
3.1%
커 5
 
2.6%
점 5
 
2.6%
비 5
 
2.6%
피 5
 
2.6%
Other values (75) 112
58.0%
Common
ValueCountFrequency (%)
5
45.5%
) 3
27.3%
( 3
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 193
94.6%
ASCII 11
 
5.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
호 16
 
8.3%
텔 15
 
7.8%
관 9
 
4.7%
광 9
 
4.7%
스 6
 
3.1%
이 6
 
3.1%
커 5
 
2.6%
점 5
 
2.6%
비 5
 
2.6%
피 5
 
2.6%
Other values (75) 112
58.0%
ASCII
ValueCountFrequency (%)
5
45.5%
) 3
27.3%
( 3
27.3%

인허가일자
Date

Distinct23
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum1986-10-21 00:00:00
Maximum2023-01-19 00:00:00
2024-05-10T20:38:27.453808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:28.013070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

영업상태명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
폐업 등
13 
운영중
7 
영업
6 
폐업
2 

Length

Max length4
Median length3
Mean length3.1785714
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 등 13
46.4%
운영중 7
25.0%
영업 6
21.4%
폐업 2
 
7.1%

Length

2024-05-10T20:38:28.346201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T20:38:28.773988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 15
36.6%
등 13
31.7%
운영중 7
17.1%
영업 6
 
14.6%

폐업일자
Date

MISSING 

Distinct15
Distinct (%)100.0%
Missing13
Missing (%)46.4%
Memory size356.0 B
Minimum2003-01-20 00:00:00
Maximum2023-02-23 00:00:00
2024-05-10T20:38:29.086356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:29.427745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

다중이용업소여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

총시설규모(㎡)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

위생업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
휴게음식점
20 
<NA>
8 

Length

Max length5
Median length5
Mean length4.7142857
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
휴게음식점 20
71.4%
<NA> 8
 
28.6%

Length

2024-05-10T20:38:29.793919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T20:38:30.111864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴게음식점 20
71.4%
na 8
 
28.6%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
관광호텔
28 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광호텔 28
100.0%

Length

2024-05-10T20:38:30.448142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T20:38:30.742753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광호텔 28
100.0%

소재지도로명주소
Text

MISSING 

Distinct23
Distinct (%)85.2%
Missing1
Missing (%)3.6%
Memory size356.0 B
2024-05-10T20:38:31.176205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length37
Mean length30.888889
Min length13

Characters and Unicode

Total characters834
Distinct characters113
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)70.4%

Sample

1st row경기도 가평군 가평읍 보납로34번길 16 (,406-1)
2nd row경기도 가평군 가평읍 보납로34번길 16 (,406-1)
3rd row경기도 고양시 일산동구 일산로 208, 106호 (마두동, 한일파킹타운)
4th row경기도 과천시 별양상가1로 30 (별양동, 과천관광호텔 1층)
5th row경기도 군포시 금정로 9
ValueCountFrequency (%)
경기도 27
 
15.3%
1층 7
 
4.0%
평택시 4
 
2.3%
일부호 4
 
2.3%
성남시 4
 
2.3%
수정구 3
 
1.7%
1층일부 3
 
1.7%
탄현면 2
 
1.1%
하남시 2
 
1.1%
심곡동 2
 
1.1%
Other values (96) 118
67.0%
2024-05-10T20:38:32.196983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
 
17.9%
1 42
 
5.0%
경 28
 
3.4%
도 28
 
3.4%
기 28
 
3.4%
시 26
 
3.1%
로 26
 
3.1%
동 24
 
2.9%
) 23
 
2.8%
, 23
 
2.8%
Other values (103) 437
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 461
55.3%
Space Separator 149
 
17.9%
Decimal Number 141
 
16.9%
Close Punctuation 23
 
2.8%
Other Punctuation 23
 
2.8%
Open Punctuation 23
 
2.8%
Dash Punctuation 12
 
1.4%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 28
 
6.1%
도 28
 
6.1%
기 28
 
6.1%
시 26
 
5.6%
로 26
 
5.6%
동 24
 
5.2%
층 15
 
3.3%
일 14
 
3.0%
호 14
 
3.0%
부 12
 
2.6%
Other values (86) 246
53.4%
Decimal Number
ValueCountFrequency (%)
1 42
29.8%
0 18
12.8%
3 17
12.1%
6 12
 
8.5%
9 11
 
7.8%
4 10
 
7.1%
7 10
 
7.1%
5 10
 
7.1%
2 8
 
5.7%
8 3
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
149
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 461
55.3%
Common 371
44.5%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 28
 
6.1%
도 28
 
6.1%
기 28
 
6.1%
시 26
 
5.6%
로 26
 
5.6%
동 24
 
5.2%
층 15
 
3.3%
일 14
 
3.0%
호 14
 
3.0%
부 12
 
2.6%
Other values (86) 246
53.4%
Common
ValueCountFrequency (%)
149
40.2%
1 42
 
11.3%
) 23
 
6.2%
, 23
 
6.2%
( 23
 
6.2%
0 18
 
4.9%
3 17
 
4.6%
6 12
 
3.2%
- 12
 
3.2%
9 11
 
3.0%
Other values (5) 41
 
11.1%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 461
55.3%
ASCII 373
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
149
39.9%
1 42
 
11.3%
) 23
 
6.2%
, 23
 
6.2%
( 23
 
6.2%
0 18
 
4.8%
3 17
 
4.6%
6 12
 
3.2%
- 12
 
3.2%
9 11
 
2.9%
Other values (7) 43
 
11.5%
Hangul
ValueCountFrequency (%)
경 28
 
6.1%
도 28
 
6.1%
기 28
 
6.1%
시 26
 
5.6%
로 26
 
5.6%
동 24
 
5.2%
층 15
 
3.3%
일 14
 
3.0%
호 14
 
3.0%
부 12
 
2.6%
Other values (86) 246
53.4%

소재지지번주소
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-10T20:38:32.764255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length29.5
Mean length28.428571
Min length19

Characters and Unicode

Total characters796
Distinct characters105
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 읍내리 403 ,406-1
2nd row경기도 가평군 가평읍 읍내리 403번지 ,406-1
3rd row경기도 고양시 일산동구 마두동 729번지 한일파킹타운 106호
4th row경기도 과천시 별양동 1-8번지 과천관광호텔 1층
5th row경기도 군포시 금정동 79-7번지 (1층)
ValueCountFrequency (%)
경기도 28
 
16.2%
1층 10
 
5.8%
평택시 4
 
2.3%
성남시 4
 
2.3%
신장동 4
 
2.3%
1층일부 3
 
1.7%
수정구 3
 
1.7%
일부 2
 
1.2%
901호 2
 
1.2%
9층 2
 
1.2%
Other values (95) 111
64.2%
2024-05-10T20:38:33.713058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
152
 
19.1%
1 43
 
5.4%
동 30
 
3.8%
기 29
 
3.6%
- 28
 
3.5%
경 28
 
3.5%
도 28
 
3.5%
시 27
 
3.4%
9 24
 
3.0%
지 24
 
3.0%
Other values (95) 383
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 443
55.7%
Decimal Number 155
 
19.5%
Space Separator 152
 
19.1%
Dash Punctuation 28
 
3.5%
Close Punctuation 7
 
0.9%
Open Punctuation 7
 
0.9%
Other Punctuation 3
 
0.4%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 30
 
6.8%
기 29
 
6.5%
경 28
 
6.3%
도 28
 
6.3%
시 27
 
6.1%
지 24
 
5.4%
번 20
 
4.5%
층 18
 
4.1%
호 12
 
2.7%
일 11
 
2.5%
Other values (79) 216
48.8%
Decimal Number
ValueCountFrequency (%)
1 43
27.7%
9 24
15.5%
0 14
 
9.0%
2 14
 
9.0%
3 13
 
8.4%
6 12
 
7.7%
4 11
 
7.1%
7 11
 
7.1%
5 8
 
5.2%
8 5
 
3.2%
Space Separator
ValueCountFrequency (%)
152
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 443
55.7%
Common 352
44.2%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 30
 
6.8%
기 29
 
6.5%
경 28
 
6.3%
도 28
 
6.3%
시 27
 
6.1%
지 24
 
5.4%
번 20
 
4.5%
층 18
 
4.1%
호 12
 
2.7%
일 11
 
2.5%
Other values (79) 216
48.8%
Common
ValueCountFrequency (%)
152
43.2%
1 43
 
12.2%
- 28
 
8.0%
9 24
 
6.8%
0 14
 
4.0%
2 14
 
4.0%
3 13
 
3.7%
6 12
 
3.4%
4 11
 
3.1%
7 11
 
3.1%
Other values (5) 30
 
8.5%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 443
55.7%
ASCII 353
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
152
43.1%
1 43
 
12.2%
- 28
 
7.9%
9 24
 
6.8%
0 14
 
4.0%
2 14
 
4.0%
3 13
 
3.7%
6 12
 
3.4%
4 11
 
3.1%
7 11
 
3.1%
Other values (6) 31
 
8.8%
Hangul
ValueCountFrequency (%)
동 30
 
6.8%
기 29
 
6.5%
경 28
 
6.3%
도 28
 
6.3%
시 27
 
6.1%
지 24
 
5.4%
번 20
 
4.5%
층 18
 
4.1%
호 12
 
2.7%
일 11
 
2.5%
Other values (79) 216
48.8%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14197.071
Minimum10090
Maximum18326
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-10T20:38:34.039999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10090
5-th percentile10572.75
Q112419
median13741.5
Q316000.25
95-th percentile17901.9
Maximum18326
Range8236
Interquartile range (IQR)3581.25

Descriptive statistics

Standard deviation2490.5092
Coefficient of variation (CV)0.17542415
Kurtosis-0.99300511
Mean14197.071
Median Absolute Deviation (MAD)1624.5
Skewness0.17823298
Sum397518
Variance6202636.2
MonotonicityNot monotonic
2024-05-10T20:38:34.313475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
12419 2
 
7.1%
12950 2
 
7.1%
14643 2
 
7.1%
13646 2
 
7.1%
10862 2
 
7.1%
14032 1
 
3.6%
18326 1
 
3.6%
17885 1
 
3.6%
17911 1
 
3.6%
17760 1
 
3.6%
Other values (13) 13
46.4%
ValueCountFrequency (%)
10090 1
3.6%
10417 1
3.6%
10862 2
7.1%
11419 1
3.6%
12077 1
3.6%
12419 2
7.1%
12950 2
7.1%
13320 1
3.6%
13553 1
3.6%
13646 2
7.1%
ValueCountFrequency (%)
18326 1
3.6%
17911 1
3.6%
17885 1
3.6%
17761 1
3.6%
17760 1
3.6%
17372 1
3.6%
16565 1
3.6%
15812 1
3.6%
15326 1
3.6%
15015 1
3.6%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)81.5%
Missing1
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean37.43897
Minimum36.992813
Maximum37.829382
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-10T20:38:34.610038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.992813
5-th percentile37.017915
Q137.293007
median37.436237
Q337.590208
95-th percentile37.827745
Maximum37.829382
Range0.83656913
Interquartile range (IQR)0.29720175

Descriptive statistics

Standard deviation0.24843529
Coefficient of variation (CV)0.0066357405
Kurtosis-0.61781693
Mean37.43897
Median Absolute Deviation (MAD)0.16014505
Skewness-0.068401001
Sum1010.8522
Variance0.061720092
MonotonicityNot monotonic
2024-05-10T20:38:34.879865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
37.8293823547 2
 
7.1%
37.5401379753 2
 
7.1%
37.4850443392 2
 
7.1%
37.4649011867 2
 
7.1%
37.7768226788 2
 
7.1%
37.8239243974 1
 
3.6%
37.2037378362 1
 
3.6%
36.9930645038 1
 
3.6%
36.9928132283 1
 
3.6%
37.0788607336 1
 
3.6%
Other values (12) 12
42.9%
ValueCountFrequency (%)
36.9928132283 1
3.6%
36.9930645038 1
3.6%
37.0759010707 1
3.6%
37.0788607336 1
3.6%
37.2037378362 1
3.6%
37.2569451732 1
3.6%
37.2760922522 1
3.6%
37.3099210506 1
3.6%
37.3474977419 1
3.6%
37.3673951526 1
3.6%
ValueCountFrequency (%)
37.8293823547 2
7.1%
37.8239243974 1
3.6%
37.7768226788 2
7.1%
37.6549584323 1
3.6%
37.6402788189 1
3.6%
37.5401379753 2
7.1%
37.4850443392 2
7.1%
37.4649011867 2
7.1%
37.4362372982 1
3.6%
37.4282707107 1
3.6%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)81.5%
Missing1
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean127.02087
Minimum126.68465
Maximum127.51477
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-10T20:38:35.194307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.68465
5-th percentile126.68787
Q1126.82911
median127.02151
Q3127.13476
95-th percentile127.49568
Maximum127.51477
Range0.83011777
Interquartile range (IQR)0.30565501

Descriptive statistics

Standard deviation0.23681441
Coefficient of variation (CV)0.0018643739
Kurtosis-0.056124781
Mean127.02087
Median Absolute Deviation (MAD)0.1191432
Skewness0.46897399
Sum3429.5636
Variance0.056081063
MonotonicityNot monotonic
2024-05-10T20:38:35.459898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
127.5147727 2
 
7.1%
127.2131742808 2
 
7.1%
126.7866959484 2
 
7.1%
127.1406487769 2
 
7.1%
126.687869943 2
 
7.1%
126.9834737019 1
 
3.6%
126.9834143949 1
 
3.6%
127.1128869548 1
 
3.6%
127.0864905344 1
 
3.6%
127.0509333216 1
 
3.6%
Other values (12) 12
42.9%
ValueCountFrequency (%)
126.6846549268 1
3.6%
126.687869943 2
7.1%
126.6889381821 1
3.6%
126.7866959484 2
7.1%
126.7901638014 1
3.6%
126.8680465894 1
3.6%
126.9301580258 1
3.6%
126.9438855374 1
3.6%
126.9834143949 1
3.6%
126.9834737019 1
3.6%
ValueCountFrequency (%)
127.5147727 2
7.1%
127.4511242582 1
3.6%
127.2131742808 2
7.1%
127.1406487769 2
7.1%
127.1288716424 1
3.6%
127.1128869548 1
3.6%
127.1044439782 1
3.6%
127.0864905344 1
3.6%
127.0549220525 1
3.6%
127.0509333216 1
3.6%

Interactions

2024-05-10T20:38:22.347906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:20.404796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:21.462183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:22.600899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:20.705731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:21.771452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:22.902386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:21.068955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:38:22.033768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T20:38:35.707807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업장명인허가일자영업상태명폐업일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
시군명1.0001.0001.0000.0001.0001.0001.0000.9880.9460.987
사업장명1.0001.0001.0000.0001.0001.0001.0001.0001.0001.000
인허가일자1.0001.0001.0000.7721.0001.0001.0001.0001.0001.000
영업상태명0.0000.0000.7721.0001.0000.0001.0000.0000.0000.585
폐업일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0000.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호0.9881.0001.0000.0001.0001.0001.0001.0000.7060.795
WGS84위도0.9461.0001.0000.0001.0001.0001.0000.7061.0000.679
WGS84경도0.9871.0001.0000.5851.0001.0001.0000.7950.6791.000
2024-05-10T20:38:36.022711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명위생업종명
영업상태명1.0001.000
위생업종명1.0001.000
2024-05-10T20:38:36.219088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도영업상태명위생업종명
소재지우편번호1.000-0.9200.1160.0001.000
WGS84위도-0.9201.000-0.0540.0001.000
WGS84경도0.116-0.0541.0000.2461.000
영업상태명0.0000.0000.2461.0001.000
위생업종명1.0001.0001.0001.0001.000

Missing values

2024-05-10T20:38:23.346677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T20:38:24.064273image/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.
2024-05-10T20:38:24.446474image/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
0가평군가평관광호텔휴게실1994-09-03영업<NA><NA><NA><NA>관광호텔경기도 가평군 가평읍 보납로34번길 16 (,406-1)경기도 가평군 가평읍 읍내리 403 ,406-11241937.829382127.514773
1가평군가평관광호텔휴게실19940903운영중<NA><NA><NA>휴게음식점관광호텔경기도 가평군 가평읍 보납로34번길 16 (,406-1)경기도 가평군 가평읍 읍내리 403번지 ,406-11241937.829382127.514773
2고양시미소떡볶이20120530폐업 등20130226<NA><NA>휴게음식점관광호텔경기도 고양시 일산동구 일산로 208, 106호 (마두동, 한일파킹타운)경기도 고양시 일산동구 마두동 729번지 한일파킹타운 106호1041737.654958126.790164
3과천시과천관광호텔19980608폐업 등20101202<NA><NA>휴게음식점관광호텔경기도 과천시 별양상가1로 30 (별양동, 과천관광호텔 1층)경기도 과천시 별양동 1-8번지 과천관광호텔 1층1383737.428271126.993336
4군포시미니스톱금정점20020522폐업 등20030701<NA><NA>휴게음식점관광호텔경기도 군포시 금정로 9경기도 군포시 금정동 79-7번지 (1층)1581237.367395126.943886
5김포시모닝스타2020-04-17영업<NA><NA><NA><NA>관광호텔경기도 김포시 태장로795번길 147, 1층 일부호 (장기동)경기도 김포시 장기동 2011-3 1층일부호1009037.640279126.684655
6남양주시리바쉬관광호텔(그릴)19940930폐업 등20030120<NA><NA>휴게음식점관광호텔<NA>경기도 남양주시 별내면 청학리 71-3번지12077<NA><NA>
7부천시파비아관광호텔커피숍19871224영업<NA><NA><NA><NA>관광호텔경기도 부천시 부일로 510 (심곡동, 1층일부)경기도 부천시 심곡동 139-14 1층일부1464337.485044126.786696
8부천시파비아관광호텔커피숍1987-12-24폐업2022-07-06<NA><NA><NA>관광호텔경기도 부천시 원미구 부일로 510 (심곡동, 1층일부)경기도 부천시 원미구 심곡동 139-14 1층일부1464337.485044126.786696
9성남시호텔야자 위례점2017-10-19영업<NA><NA><NA><NA>관광호텔경기도 성남시 수정구 위례광장로 9-10, 9층 901호 일부호 (창곡동, 아롬타워)경기도 성남시 수정구 창곡동 561-2 아롬타워 9층 901호 일부1364637.464901127.140649
시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
18이천시잼글20140912운영중<NA><NA><NA>휴게음식점관광호텔경기도 이천시 중리천로115번길 45, A동 2층 (안흥동)경기도 이천시 안흥동 408-1번지 외2필지(2층) A동1737237.276092127.451124
19파주시비젼20161222영업<NA><NA><NA><NA>관광호텔경기도 파주시 탄현면 성동로 36-30, 1층경기도 파주시 탄현면 성동리 679-6 1층1086237.776823126.68787
20파주시비젼20161222운영중<NA><NA><NA>휴게음식점관광호텔경기도 파주시 탄현면 성동로 36-30, 1층경기도 파주시 탄현면 성동리 679-6번지 1층1086237.776823126.68787
21평택시경기관광호텔 선라이즈20031120폐업 등20060118<NA><NA>휴게음식점관광호텔경기도 평택시 탄현로 261경기도 평택시 신장동 240-3번지 (1층)1776137.075901127.054922
22평택시아시아커피샵20041026폐업 등20100818<NA><NA>휴게음식점관광호텔경기도 평택시 신장로 33경기도 평택시 신장동 297-61번지 외 9필지1776037.078861127.050933
23평택시(주)호성평택관광호텔휴게실19901215폐업 등20151222<NA><NA>휴게음식점관광호텔경기도 평택시 평택1로 7 (평택동)경기도 평택시 평택동 62-10번지1791136.992813127.086491
24평택시가보호텔레스토랑19980612폐업 등20061018<NA><NA>휴게음식점관광호텔경기도 평택시 평택5로76번길 18-10경기도 평택시 비전동 845-1번지1788536.993065127.112887
25하남시로망스2002-06-26영업<NA><NA><NA><NA>관광호텔경기도 하남시 하남대로776번길 14-30 (신장동,(동서울호텔내 1층))경기도 하남시 신장동 519-9 (동서울호텔내 1층)1295037.540138127.213174
26하남시로망스20020626운영중<NA><NA><NA>휴게음식점관광호텔경기도 하남시 하남대로776번길 14-30 (신장동,(동서울호텔내 1층))경기도 하남시 신장동 519-9번지 (동서울호텔내 1층)1295037.540138127.213174
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