Overview

Dataset statistics

Number of variables9
Number of observations89
Missing cells12
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.6 KiB
Average record size in memory76.5 B

Variable types

Categorical2
Text4
Numeric3

Dataset

Description경기도 우수숙박시설 현황
Author경기관광공사
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=LU6OWRJ132QKLU6TASZX31096522&infSeq=1

Alerts

데이터기준일자 has constant value ""Constant
정제우편번호 is highly overall correlated with 정제WGS84위도 and 1 other fieldsHigh correlation
정제WGS84위도 is highly overall correlated with 정제우편번호 and 1 other fieldsHigh correlation
정제WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 정제우편번호 and 2 other fieldsHigh correlation
정제도로명주소 has 7 (7.9%) missing valuesMissing
정제우편번호 has 1 (1.1%) missing valuesMissing
정제WGS84위도 has 2 (2.2%) missing valuesMissing
정제WGS84경도 has 2 (2.2%) missing valuesMissing
업체명 has unique valuesUnique
정제지번주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:06:41.714945
Analysis finished2023-12-10 22:06:42.991548
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)23.6%
Missing0
Missing (%)0.0%
Memory size844.0 B
가평군
13 
수원시
13 
양평군
11 
파주시
8 
고양시
6 
Other values (16)
38 

Length

Max length4
Median length3
Mean length3.0224719
Min length3

Unique

Unique5 ?
Unique (%)5.6%

Sample

1st row파주시
2nd row용인시
3rd row안산시
4th row여주시
5th row고양시

Common Values

ValueCountFrequency (%)
가평군 13
14.6%
수원시 13
14.6%
양평군 11
12.4%
파주시 8
9.0%
고양시 6
 
6.7%
양주시 4
 
4.5%
안성시 4
 
4.5%
용인시 4
 
4.5%
화성시 4
 
4.5%
시흥시 4
 
4.5%
Other values (11) 18
20.2%

Length

2023-12-11T07:06:43.040778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가평군 13
14.6%
수원시 13
14.6%
양평군 11
12.4%
파주시 8
9.0%
고양시 6
 
6.7%
양주시 4
 
4.5%
안성시 4
 
4.5%
용인시 4
 
4.5%
화성시 4
 
4.5%
시흥시 4
 
4.5%
Other values (11) 18
20.2%

업체명
Text

UNIQUE 

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-11T07:06:43.258032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length21
Mean length6.1348315
Min length2

Characters and Unicode

Total characters546
Distinct characters193
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)100.0%

Sample

1st row소풍호텔
2nd row호텔리버
3rd row굿스테이안산호텔
4th row남강모텔
5th row호텔쉘
ValueCountFrequency (%)
펜션 4
 
3.5%
호텔 3
 
2.7%
the 2
 
1.8%
가평 2
 
1.8%
한옥펜션 2
 
1.8%
한옥 2
 
1.8%
아이리스 1
 
0.9%
춘화원한옥펜션 1
 
0.9%
신풍재 1
 
0.9%
아바타호텔 1
 
0.9%
Other values (94) 94
83.2%
2023-12-11T07:06:43.617616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 43
 
7.9%
호 30
 
5.5%
24
 
4.4%
션 24
 
4.4%
펜 24
 
4.4%
한 21
 
3.8%
옥 18
 
3.3%
스 16
 
2.9%
모 13
 
2.4%
리 9
 
1.6%
Other values (183) 324
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 464
85.0%
Uppercase Letter 43
 
7.9%
Space Separator 24
 
4.4%
Lowercase Letter 8
 
1.5%
Open Punctuation 3
 
0.5%
Close Punctuation 3
 
0.5%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 43
 
9.3%
호 30
 
6.5%
션 24
 
5.2%
펜 24
 
5.2%
한 21
 
4.5%
옥 18
 
3.9%
스 16
 
3.4%
모 13
 
2.8%
리 9
 
1.9%
이 8
 
1.7%
Other values (154) 258
55.6%
Uppercase Letter
ValueCountFrequency (%)
S 6
14.0%
E 6
14.0%
T 5
11.6%
H 4
9.3%
N 3
7.0%
O 3
7.0%
R 3
7.0%
I 3
7.0%
G 2
 
4.7%
A 1
 
2.3%
Other values (7) 7
16.3%
Lowercase Letter
ValueCountFrequency (%)
n 1
12.5%
d 1
12.5%
l 1
12.5%
a 1
12.5%
p 1
12.5%
o 1
12.5%
e 1
12.5%
h 1
12.5%
Space Separator
ValueCountFrequency (%)
24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 464
85.0%
Latin 51
 
9.3%
Common 31
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 43
 
9.3%
호 30
 
6.5%
션 24
 
5.2%
펜 24
 
5.2%
한 21
 
4.5%
옥 18
 
3.9%
스 16
 
3.4%
모 13
 
2.8%
리 9
 
1.9%
이 8
 
1.7%
Other values (154) 258
55.6%
Latin
ValueCountFrequency (%)
S 6
 
11.8%
E 6
 
11.8%
T 5
 
9.8%
H 4
 
7.8%
N 3
 
5.9%
O 3
 
5.9%
R 3
 
5.9%
I 3
 
5.9%
G 2
 
3.9%
A 1
 
2.0%
Other values (15) 15
29.4%
Common
ValueCountFrequency (%)
24
77.4%
( 3
 
9.7%
) 3
 
9.7%
2 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 464
85.0%
ASCII 82
 
15.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 43
 
9.3%
호 30
 
6.5%
션 24
 
5.2%
펜 24
 
5.2%
한 21
 
4.5%
옥 18
 
3.9%
스 16
 
3.4%
모 13
 
2.8%
리 9
 
1.9%
이 8
 
1.7%
Other values (154) 258
55.6%
ASCII
ValueCountFrequency (%)
24
29.3%
S 6
 
7.3%
E 6
 
7.3%
T 5
 
6.1%
H 4
 
4.9%
N 3
 
3.7%
O 3
 
3.7%
R 3
 
3.7%
I 3
 
3.7%
( 3
 
3.7%
Other values (19) 22
26.8%

전화번호
Text

Distinct72
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-11T07:06:43.805588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.224719
Min length11

Characters and Unicode

Total characters1088
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)79.8%

Sample

1st row031-944-7942
2nd row031-283-3601
3rd row031-408-8700
4th row031-886-0303
5th row031-972-0229
ValueCountFrequency (%)
18
 
20.2%
031-944-7942 1
 
1.1%
031-855-0282 1
 
1.1%
031-245-2456 1
 
1.1%
031-534-3833 1
 
1.1%
031-242-5897 1
 
1.1%
031-919-6761 1
 
1.1%
031-432-1000 1
 
1.1%
031-584-4661 1
 
1.1%
031-613-1758 1
 
1.1%
Other values (62) 62
69.7%
2023-12-11T07:06:44.118866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 198
18.2%
- 178
16.4%
3 130
11.9%
0 124
11.4%
1 122
11.2%
7 59
 
5.4%
8 53
 
4.9%
2 50
 
4.6%
5 50
 
4.6%
4 47
 
4.3%
Other values (2) 77
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 712
65.4%
Other Punctuation 198
 
18.2%
Dash Punctuation 178
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 130
18.3%
0 124
17.4%
1 122
17.1%
7 59
8.3%
8 53
7.4%
2 50
 
7.0%
5 50
 
7.0%
4 47
 
6.6%
6 42
 
5.9%
9 35
 
4.9%
Other Punctuation
ValueCountFrequency (%)
* 198
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1088
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 198
18.2%
- 178
16.4%
3 130
11.9%
0 124
11.4%
1 122
11.2%
7 59
 
5.4%
8 53
 
4.9%
2 50
 
4.6%
5 50
 
4.6%
4 47
 
4.3%
Other values (2) 77
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1088
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 198
18.2%
- 178
16.4%
3 130
11.9%
0 124
11.4%
1 122
11.2%
7 59
 
5.4%
8 53
 
4.9%
2 50
 
4.6%
5 50
 
4.6%
4 47
 
4.3%
Other values (2) 77
 
7.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size844.0 B
2021-03-05
89 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-03-05
2nd row2021-03-05
3rd row2021-03-05
4th row2021-03-05
5th row2021-03-05

Common Values

ValueCountFrequency (%)
2021-03-05 89
100.0%

Length

2023-12-11T07:06:44.227575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:06:44.303147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-03-05 89
100.0%

정제도로명주소
Text

MISSING 

Distinct82
Distinct (%)100.0%
Missing7
Missing (%)7.9%
Memory size844.0 B
2023-12-11T07:06:44.518420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length21.097561
Min length14

Characters and Unicode

Total characters1730
Distinct characters138
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

Unique82 ?
Unique (%)100.0%

Sample

1st row경기도 파주시 탄현면 요풍길 119-1
2nd row경기도 안산시 상록구 구룡로2길 20
3rd row경기도 여주시 강변북로 7
4th row경기도 파주시 광탄면 보광로 877
5th row경기도 수원시 팔달구 인계로166번길 24
ValueCountFrequency (%)
경기도 82
 
20.8%
가평군 11
 
2.8%
수원시 11
 
2.8%
양평군 11
 
2.8%
팔달구 9
 
2.3%
파주시 8
 
2.0%
서종면 5
 
1.3%
강하면 5
 
1.3%
고양시 5
 
1.3%
안성시 4
 
1.0%
Other values (192) 244
61.8%
2023-12-11T07:06:44.877614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
313
 
18.1%
경 83
 
4.8%
기 83
 
4.8%
도 82
 
4.7%
1 64
 
3.7%
시 63
 
3.6%
로 63
 
3.6%
길 50
 
2.9%
2 47
 
2.7%
4 44
 
2.5%
Other values (128) 838
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1054
60.9%
Decimal Number 336
 
19.4%
Space Separator 313
 
18.1%
Dash Punctuation 27
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 83
 
7.9%
기 83
 
7.9%
도 82
 
7.8%
시 63
 
6.0%
로 63
 
6.0%
길 50
 
4.7%
면 36
 
3.4%
번 29
 
2.8%
평 28
 
2.7%
양 26
 
2.5%
Other values (116) 511
48.5%
Decimal Number
ValueCountFrequency (%)
1 64
19.0%
2 47
14.0%
4 44
13.1%
3 42
12.5%
9 29
8.6%
0 25
 
7.4%
5 24
 
7.1%
8 21
 
6.2%
7 20
 
6.0%
6 20
 
6.0%
Space Separator
ValueCountFrequency (%)
313
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1054
60.9%
Common 676
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 83
 
7.9%
기 83
 
7.9%
도 82
 
7.8%
시 63
 
6.0%
로 63
 
6.0%
길 50
 
4.7%
면 36
 
3.4%
번 29
 
2.8%
평 28
 
2.7%
양 26
 
2.5%
Other values (116) 511
48.5%
Common
ValueCountFrequency (%)
313
46.3%
1 64
 
9.5%
2 47
 
7.0%
4 44
 
6.5%
3 42
 
6.2%
9 29
 
4.3%
- 27
 
4.0%
0 25
 
3.7%
5 24
 
3.6%
8 21
 
3.1%
Other values (2) 40
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1054
60.9%
ASCII 676
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
313
46.3%
1 64
 
9.5%
2 47
 
7.0%
4 44
 
6.5%
3 42
 
6.2%
9 29
 
4.3%
- 27
 
4.0%
0 25
 
3.7%
5 24
 
3.6%
8 21
 
3.1%
Other values (2) 40
 
5.9%
Hangul
ValueCountFrequency (%)
경 83
 
7.9%
기 83
 
7.9%
도 82
 
7.8%
시 63
 
6.0%
로 63
 
6.0%
길 50
 
4.7%
면 36
 
3.4%
번 29
 
2.8%
평 28
 
2.7%
양 26
 
2.5%
Other values (116) 511
48.5%

정제지번주소
Text

UNIQUE 

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-11T07:06:45.084553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length22.168539
Min length16

Characters and Unicode

Total characters1973
Distinct characters134
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

Unique89 ?
Unique (%)100.0%

Sample

1st row경기도 파주시 탄현면 성동리 476-1번지
2nd row경기도 용인시 기흥구 갈천로7번길 73
3rd row경기도 안산시 상록구 일동 120-5번지
4th row경기도 여주시 천송동 565번지
5th row경기도 고양시 덕양구 화중로 32-9
ValueCountFrequency (%)
경기도 89
 
20.6%
수원시 13
 
3.0%
가평군 13
 
3.0%
양평군 11
 
2.5%
팔달구 10
 
2.3%
파주시 8
 
1.8%
인계동 6
 
1.4%
고양시 6
 
1.4%
서종면 5
 
1.2%
강하면 5
 
1.2%
Other values (206) 267
61.7%
2023-12-11T07:06:45.393058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
344
 
17.4%
기 93
 
4.7%
도 90
 
4.6%
경 89
 
4.5%
번 86
 
4.4%
지 83
 
4.2%
1 81
 
4.1%
시 68
 
3.4%
- 68
 
3.4%
동 45
 
2.3%
Other values (124) 926
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1205
61.1%
Decimal Number 356
 
18.0%
Space Separator 344
 
17.4%
Dash Punctuation 68
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 93
 
7.7%
도 90
 
7.5%
경 89
 
7.4%
번 86
 
7.1%
지 83
 
6.9%
시 68
 
5.6%
동 45
 
3.7%
리 45
 
3.7%
면 39
 
3.2%
평 30
 
2.5%
Other values (112) 537
44.6%
Decimal Number
ValueCountFrequency (%)
1 81
22.8%
4 39
11.0%
2 39
11.0%
0 36
10.1%
3 35
9.8%
6 33
9.3%
8 27
 
7.6%
5 25
 
7.0%
7 23
 
6.5%
9 18
 
5.1%
Space Separator
ValueCountFrequency (%)
344
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1205
61.1%
Common 768
38.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 93
 
7.7%
도 90
 
7.5%
경 89
 
7.4%
번 86
 
7.1%
지 83
 
6.9%
시 68
 
5.6%
동 45
 
3.7%
리 45
 
3.7%
면 39
 
3.2%
평 30
 
2.5%
Other values (112) 537
44.6%
Common
ValueCountFrequency (%)
344
44.8%
1 81
 
10.5%
- 68
 
8.9%
4 39
 
5.1%
2 39
 
5.1%
0 36
 
4.7%
3 35
 
4.6%
6 33
 
4.3%
8 27
 
3.5%
5 25
 
3.3%
Other values (2) 41
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1205
61.1%
ASCII 768
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
344
44.8%
1 81
 
10.5%
- 68
 
8.9%
4 39
 
5.1%
2 39
 
5.1%
0 36
 
4.7%
3 35
 
4.6%
6 33
 
4.3%
8 27
 
3.5%
5 25
 
3.3%
Other values (2) 41
 
5.3%
Hangul
ValueCountFrequency (%)
기 93
 
7.7%
도 90
 
7.5%
경 89
 
7.4%
번 86
 
7.1%
지 83
 
6.9%
시 68
 
5.6%
동 45
 
3.7%
리 45
 
3.7%
면 39
 
3.2%
평 30
 
2.5%
Other values (112) 537
44.6%

정제우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct69
Distinct (%)78.4%
Missing1
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean13793.773
Minimum10029
Maximum18455
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size933.0 B
2023-12-11T07:06:45.513232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10029
5-th percentile10510
Q111522.75
median12575
Q316488
95-th percentile17929.95
Maximum18455
Range8426
Interquartile range (IQR)4965.25

Descriptive statistics

Standard deviation2590.1546
Coefficient of variation (CV)0.1877771
Kurtosis-1.3534378
Mean13793.773
Median Absolute Deviation (MAD)1872
Skewness0.34620682
Sum1213852
Variance6708900.9
MonotonicityNot monotonic
2023-12-11T07:06:45.632510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10862 3
 
3.4%
14966 3
 
3.4%
16489 3
 
3.4%
12575 3
 
3.4%
12500 2
 
2.2%
16251 2
 
2.2%
12458 2
 
2.2%
18455 2
 
2.2%
12639 2
 
2.2%
18450 2
 
2.2%
Other values (59) 64
71.9%
ValueCountFrequency (%)
10029 1
 
1.1%
10343 1
 
1.1%
10381 2
2.2%
10503 1
 
1.1%
10523 1
 
1.1%
10580 1
 
1.1%
10803 1
 
1.1%
10862 3
3.4%
10880 1
 
1.1%
10952 1
 
1.1%
ValueCountFrequency (%)
18455 2
2.2%
18450 2
2.2%
18141 1
1.1%
17538 1
1.1%
17537 1
1.1%
17534 1
1.1%
17523 1
1.1%
17384 1
1.1%
17369 1
1.1%
17142 1
1.1%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct87
Distinct (%)100.0%
Missing2
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean37.511256
Minimum36.958309
Maximum38.06355
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size933.0 B
2023-12-11T07:06:46.030138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.958309
5-th percentile37.158163
Q137.281024
median37.501231
Q337.739075
95-th percentile37.947638
Maximum38.06355
Range1.1052405
Interquartile range (IQR)0.45805088

Descriptive statistics

Standard deviation0.26521442
Coefficient of variation (CV)0.0070702623
Kurtosis-0.96623882
Mean37.511256
Median Absolute Deviation (MAD)0.2260922
Skewness0.01022257
Sum3263.4793
Variance0.070338688
MonotonicityNot monotonic
2023-12-11T07:06:46.145588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.2709709334 1
 
1.1%
37.5669750205 1
 
1.1%
37.9361886728 1
 
1.1%
37.2839274606 1
 
1.1%
37.6899509351 1
 
1.1%
37.3889417408 1
 
1.1%
37.2181942225 1
 
1.1%
37.2661734102 1
 
1.1%
37.2662533244 1
 
1.1%
37.502704585 1
 
1.1%
Other values (77) 77
86.5%
(Missing) 2
 
2.2%
ValueCountFrequency (%)
36.9583094447 1
1.1%
36.9625457911 1
1.1%
36.9999819825 1
1.1%
37.0502368544 1
1.1%
37.1449526867 1
1.1%
37.1889859721 1
1.1%
37.2011354005 1
1.1%
37.2011454311 1
1.1%
37.2181942225 1
1.1%
37.2182224268 1
1.1%
ValueCountFrequency (%)
38.0635499501 1
1.1%
37.983393664 1
1.1%
37.9560674269 1
1.1%
37.9553580315 1
1.1%
37.9525444767 1
1.1%
37.9361886728 1
1.1%
37.9015642932 1
1.1%
37.8940273925 1
1.1%
37.8235471067 1
1.1%
37.8041528545 1
1.1%

정제WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct87
Distinct (%)100.0%
Missing2
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean127.1203
Minimum126.58825
Maximum127.64895
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size933.0 B
2023-12-11T07:06:46.262337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.58825
5-th percentile126.70992
Q1126.91667
median127.06928
Q3127.39005
95-th percentile127.52296
Maximum127.64895
Range1.060706
Interquartile range (IQR)0.47338196

Descriptive statistics

Standard deviation0.27611238
Coefficient of variation (CV)0.0021720557
Kurtosis-1.1693898
Mean127.1203
Median Absolute Deviation (MAD)0.26623009
Skewness0.073503236
Sum11059.466
Variance0.076238044
MonotonicityNot monotonic
2023-12-11T07:06:46.382307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1072616102 1
 
1.1%
127.4168847471 1
 
1.1%
127.348678998 1
 
1.1%
127.0135396593 1
 
1.1%
126.7627682492 1
 
1.1%
126.7390098298 1
 
1.1%
127.0784895322 1
 
1.1%
127.0299961556 1
 
1.1%
127.0296911443 1
 
1.1%
126.763651746 1
 
1.1%
Other values (77) 77
86.5%
(Missing) 2
 
2.2%
ValueCountFrequency (%)
126.5882483286 1
1.1%
126.6820458015 1
1.1%
126.6876806658 1
1.1%
126.6876928223 1
1.1%
126.6974538634 1
1.1%
126.7390098298 1
1.1%
126.7402916543 1
1.1%
126.7409544855 1
1.1%
126.7433336421 1
1.1%
126.7487494672 1
1.1%
ValueCountFrequency (%)
127.6489542868 1
1.1%
127.6422669082 1
1.1%
127.5532901384 1
1.1%
127.5286740121 1
1.1%
127.5244234387 1
1.1%
127.5195600502 1
1.1%
127.5138750188 1
1.1%
127.4763698847 1
1.1%
127.4658304909 1
1.1%
127.4617510904 1
1.1%

Interactions

2023-12-11T07:06:42.534568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:42.146414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:42.341824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:42.594801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:42.211282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:42.405482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:42.661055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:42.275122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:06:42.469224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:06:46.462155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명업체명전화번호정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
시군명1.0001.0000.9371.0001.0000.9990.9450.915
업체명1.0001.0001.0001.0001.0001.0001.0001.000
전화번호0.9371.0001.0001.0001.0000.9640.0000.000
정제도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
정제지번주소1.0001.0001.0001.0001.0001.0001.0001.000
정제우편번호0.9991.0000.9641.0001.0001.0000.8910.904
정제WGS84위도0.9451.0000.0001.0001.0000.8911.0000.677
정제WGS84경도0.9151.0000.0001.0001.0000.9040.6771.000
2023-12-11T07:06:46.591865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정제우편번호정제WGS84위도정제WGS84경도시군명
정제우편번호1.000-0.8990.2500.867
정제WGS84위도-0.8991.000-0.0460.684
정제WGS84경도0.250-0.0461.0000.605
시군명0.8670.6840.6051.000

Missing values

2023-12-11T07:06:42.754417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:06:42.857430image/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.
2023-12-11T07:06:42.943490image/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

시군명업체명전화번호데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
0파주시소풍호텔031-944-79422021-03-05경기도 파주시 탄현면 요풍길 119-1경기도 파주시 탄현면 성동리 476-1번지1086237.784966126.682046
1용인시호텔리버031-283-36012021-03-05<NA>경기도 용인시 기흥구 갈천로7번길 731706437.270971127.107262
2안산시굿스테이안산호텔031-408-87002021-03-05경기도 안산시 상록구 구룡로2길 20경기도 안산시 상록구 일동 120-5번지1532637.310076126.868327
3여주시남강모텔031-886-03032021-03-05경기도 여주시 강변북로 7경기도 여주시 천송동 565번지1263937.300671127.648954
4고양시호텔쉘031-972-02292021-03-05<NA>경기도 고양시 덕양구 화중로 32-91050337.630363126.830619
5파주시유일레저031-948-61612021-03-05경기도 파주시 광탄면 보광로 877경기도 파주시 광탄면 마장리 86번지1095237.77285126.882862
6수원시뉴필모텔031-223-37652021-03-05경기도 수원시 팔달구 인계로166번길 24경기도 수원시 팔달구 인계동 1115-14번지1648837.265409127.035054
7고양시리젠트인호텔031-913-28532021-03-05경기도 고양시 일산서구 중앙로 1560-14경기도 고양시 일산서구 대화동 2208-4번지1038137.67646126.748749
8수원시호텔퍼시픽031-895-40452021-03-05경기도 수원시 팔달구 효원로235번길 38경기도 수원시 팔달구 인계동 1030-10번지1649037.264527127.028439
9양주시솔내음한옥펜션031-855-26342021-03-05경기도 양주시 장흥면 유원지로89번길 28-12경기도 양주시 장흥면 삼상리 118-2번지1152437.700396126.93763
시군명업체명전화번호데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
79안성시안성 호텔 수031-671-01472021-03-05경기도 안성시 금광면 삼흥로 102경기도 안성시 금광면 오흥리 883-1번지1753436.999982127.335506
80양평군양평밸리031-774-30002021-03-05경기도 양평군 양평읍 백안길60번길 14경기도 양평군 양평읍 백안리 산17-2번지1254937.496165127.51956
81파주시칼튼호텔031-942-39552021-03-05경기도 파주시 탄현면 성동로 34경기도 파주시 탄현면 성동리 679-1번지1086237.777443126.687693
82수원시엠모텔031-225-23472021-03-05경기도 수원시 팔달구 효원로291번길 22경기도 수원시 팔달구 인계동 1123-7번지1648837.262296127.034238
83의정부시S모텔031-826-20772021-03-05경기도 의정부시 시민로122번길 9-25경기도 의정부시 의정부동 132-11번지1169737.73775127.049446
84오산시스티플모텔031-377-59042021-03-05경기도 오산시 대원로38번길 15경기도 오산시 원동 768-12번지1814137.144953127.072872
85시흥시G모텔031-318-52502021-03-05경기도 시흥시 월곶중앙로58번길 30경기도 시흥시 월곶동 1003-13번지1496637.391018126.740954
86수원시그랜드모텔031-234-71312021-03-05<NA>경기도 수원시 권선구 권선로683번길 221657137.260301127.026649
87수원시수원호텔꼬모031-233-89662021-03-05경기도 수원시 팔달구 효원로219번길 46-14경기도 수원시 팔달구 인계동 1026-10번지1649037.264929127.027568
88시흥시체스모텔031-318-37412021-03-05경기도 시흥시 월곶중앙로14번길 42경기도 시흥시 월곶동 992-4번지1496837.39034126.743334