Overview

Dataset statistics

Number of variables10
Number of observations98
Missing cells33
Missing cells (%)3.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.1 KiB
Average record size in memory84.3 B

Variable types

Categorical2
Text4
DateTime1
Numeric3

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
전화번호 has 1 (1.0%) missing valuesMissing
정제지번주소 has 4 (4.1%) missing valuesMissing
정제우편번호 has 8 (8.2%) missing valuesMissing
정제WGS84위도 has 10 (10.2%) missing valuesMissing
정제WGS84경도 has 10 (10.2%) missing valuesMissing
명소명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:36:34.769938
Analysis finished2023-12-10 21:36:37.290984
Duration2.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Memory size916.0 B
용인시
9 
파주시
8 
고양시
7 
포천시
 
6
가평군
 
6
Other values (26)
62 

Length

Max length4
Median length3
Mean length3.0714286
Min length3

Unique

Unique10 ?
Unique (%)10.2%

Sample

1st row포천시
2nd row포천시
3rd row하남시
4th row화성시
5th row화성시

Common Values

ValueCountFrequency (%)
용인시 9
 
9.2%
파주시 8
 
8.2%
고양시 7
 
7.1%
포천시 6
 
6.1%
가평군 6
 
6.1%
양평군 6
 
6.1%
여주시 5
 
5.1%
남양주시 5
 
5.1%
과천시 4
 
4.1%
안산시 4
 
4.1%
Other values (21) 38
38.8%

Length

2023-12-11T06:36:37.381964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용인시 9
 
9.2%
파주시 8
 
8.2%
고양시 7
 
7.1%
포천시 6
 
6.1%
가평군 6
 
6.1%
양평군 6
 
6.1%
여주시 5
 
5.1%
남양주시 5
 
5.1%
안성시 4
 
4.1%
안산시 4
 
4.1%
Other values (21) 38
38.8%

명소명
Text

UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
2023-12-11T06:36:37.708972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length5.7653061
Min length3

Characters and Unicode

Total characters565
Distinct characters200
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

Unique98 ?
Unique (%)100.0%

Sample

1st row산정호수
2nd row포천아트밸리
3rd row미사리경정공원
4th row용주사
5th row제부도
ValueCountFrequency (%)
산정호수 1
 
0.9%
모란장 1
 
0.9%
다문화특구 1
 
0.9%
오이도 1
 
0.9%
갯골생태공원 1
 
0.9%
수원화성 1
 
0.9%
한국잡월드 1
 
0.9%
한국만화박물관 1
 
0.9%
소요산 1
 
0.9%
축령산자연휴양림 1
 
0.9%
Other values (103) 103
91.2%
2023-12-11T06:36:38.228877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 18
 
3.2%
산 16
 
2.8%
관 15
 
2.7%
15
 
2.7%
리 14
 
2.5%
도 11
 
1.9%
물 11
 
1.9%
마 10
 
1.8%
수 10
 
1.8%
사 10
 
1.8%
Other values (190) 435
77.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 544
96.3%
Space Separator 15
 
2.7%
Open Punctuation 3
 
0.5%
Close Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 18
 
3.3%
산 16
 
2.9%
관 15
 
2.8%
리 14
 
2.6%
도 11
 
2.0%
물 11
 
2.0%
마 10
 
1.8%
수 10
 
1.8%
사 10
 
1.8%
지 10
 
1.8%
Other values (185) 419
77.0%
Open Punctuation
ValueCountFrequency (%)
( 2
66.7%
[ 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 2
66.7%
] 1
33.3%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 544
96.3%
Common 21
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 18
 
3.3%
산 16
 
2.9%
관 15
 
2.8%
리 14
 
2.6%
도 11
 
2.0%
물 11
 
2.0%
마 10
 
1.8%
수 10
 
1.8%
사 10
 
1.8%
지 10
 
1.8%
Other values (185) 419
77.0%
Common
ValueCountFrequency (%)
15
71.4%
( 2
 
9.5%
) 2
 
9.5%
[ 1
 
4.8%
] 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 544
96.3%
ASCII 21
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 18
 
3.3%
산 16
 
2.9%
관 15
 
2.8%
리 14
 
2.6%
도 11
 
2.0%
물 11
 
2.0%
마 10
 
1.8%
수 10
 
1.8%
사 10
 
1.8%
지 10
 
1.8%
Other values (185) 419
77.0%
ASCII
ValueCountFrequency (%)
15
71.4%
( 2
 
9.5%
) 2
 
9.5%
[ 1
 
4.8%
] 1
 
4.8%

전화번호
Text

MISSING 

Distinct96
Distinct (%)99.0%
Missing1
Missing (%)1.0%
Memory size916.0 B
2023-12-11T06:36:38.513733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.113402
Min length11

Characters and Unicode

Total characters1175
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

Unique95 ?
Unique (%)97.9%

Sample

1st row031-532-6135
2nd row031-538-3485
3rd row031-790-8883
4th row031-234-0040
5th row031-369-1673
ValueCountFrequency (%)
031-1644-4001 2
 
2.1%
031-538-3342 1
 
1.0%
031-310-2903 1
 
1.0%
031-488-6900 1
 
1.0%
031-228-4480 1
 
1.0%
031-1644-1333 1
 
1.0%
032-310-3090 1
 
1.0%
031-860-2065 1
 
1.0%
031-592-0681 1
 
1.0%
031-579-0605 1
 
1.0%
Other values (86) 86
88.7%
2023-12-11T06:36:38.916915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 221
18.8%
- 194
16.5%
3 160
13.6%
1 148
12.6%
8 80
 
6.8%
5 72
 
6.1%
2 68
 
5.8%
6 67
 
5.7%
7 61
 
5.2%
4 53
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 981
83.5%
Dash Punctuation 194
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 221
22.5%
3 160
16.3%
1 148
15.1%
8 80
 
8.2%
5 72
 
7.3%
2 68
 
6.9%
6 67
 
6.8%
7 61
 
6.2%
4 53
 
5.4%
9 51
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 194
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 221
18.8%
- 194
16.5%
3 160
13.6%
1 148
12.6%
8 80
 
6.8%
5 72
 
6.1%
2 68
 
5.8%
6 67
 
5.7%
7 61
 
5.2%
4 53
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 221
18.8%
- 194
16.5%
3 160
13.6%
1 148
12.6%
8 80
 
6.8%
5 72
 
6.1%
2 68
 
5.8%
6 67
 
5.7%
7 61
 
5.2%
4 53
 
4.5%

부가정보
Categorical

Distinct40
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Memory size916.0 B
무료
48 
<NA>
12 
최초 1시간 경형 500원, 중·소형 1,100원, 대형 2,000원
 
1
경차 1,000원, 소형 2,000원 중형 3,000원, 대형 5,000원
 
1
유료주차, 소형 4,000원, 대형 10,000원
 
1
Other values (35)
35 

Length

Max length78
Median length2
Mean length13.622449
Min length2

Unique

Unique38 ?
Unique (%)38.8%

Sample

1st row경차 2,000원, 소형 5,000원, 중형 10,000원
2nd row무료
3rd row유료주차, 소형 4,000원, 대형 10,000원
4th row무료
5th row<NA>

Common Values

ValueCountFrequency (%)
무료 48
49.0%
<NA> 12
 
12.2%
최초 1시간 경형 500원, 중·소형 1,100원, 대형 2,000원 1
 
1.0%
경차 1,000원, 소형 2,000원 중형 3,000원, 대형 5,000원 1
 
1.0%
유료주차, 소형 4,000원, 대형 10,000원 1
 
1.0%
이용요금 별도문의 1
 
1.0%
소형차 1,000원 중,대형차 3,000원 버스 5,000원 1
 
1.0%
경차 1,500원, 중·소형 3,000원, 대형 5,000원 1
 
1.0%
무료(입장권에포함) 1
 
1.0%
소형차 2,000원/중형차 3,000원/대형차 4,000원 1
 
1.0%
Other values (30) 30
30.6%

Length

2023-12-11T06:36:39.088321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
무료 54
 
19.8%
na 12
 
4.4%
2,000원 11
 
4.0%
대형 10
 
3.7%
3,000원 8
 
2.9%
소형 8
 
2.9%
1,000원 7
 
2.6%
5,000원 7
 
2.6%
이후 6
 
2.2%
경차 6
 
2.2%
Other values (97) 144
52.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
Minimum2021-03-05 00:00:00
Maximum2021-03-05 00:00:00
2023-12-11T06:36:39.200787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:39.281992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

정제도로명주소
Text

Distinct97
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
2023-12-11T06:36:39.520860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length29
Mean length20.928571
Min length11

Characters and Unicode

Total characters2051
Distinct characters184
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)98.0%

Sample

1st row경기도 포천시 영북면 산정호수로411번길 89
2nd row경기도 포천시 신북면 아트밸리로 234
3rd row경기도 하남시 미사대로 505
4th row경기도 화성시 용주로 136
5th row경기도 화성시 서신면 제부리 산12
ValueCountFrequency (%)
경기도 99
 
19.9%
용인시 9
 
1.8%
파주시 8
 
1.6%
가평군 7
 
1.4%
고양시 7
 
1.4%
양평군 6
 
1.2%
포천시 6
 
1.2%
여주시 5
 
1.0%
남양주시 5
 
1.0%
처인구 4
 
0.8%
Other values (274) 341
68.6%
2023-12-11T06:36:39.915846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
399
19.5%
도 104
 
5.1%
기 104
 
5.1%
경 101
 
4.9%
시 86
 
4.2%
1 68
 
3.3%
로 67
 
3.3%
면 46
 
2.2%
2 46
 
2.2%
3 38
 
1.9%
Other values (174) 992
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1294
63.1%
Space Separator 399
 
19.5%
Decimal Number 324
 
15.8%
Dash Punctuation 21
 
1.0%
Close Punctuation 5
 
0.2%
Open Punctuation 5
 
0.2%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 104
 
8.0%
기 104
 
8.0%
경 101
 
7.8%
시 86
 
6.6%
로 67
 
5.2%
면 46
 
3.6%
양 32
 
2.5%
길 31
 
2.4%
주 29
 
2.2%
구 26
 
2.0%
Other values (158) 668
51.6%
Decimal Number
ValueCountFrequency (%)
1 68
21.0%
2 46
14.2%
3 38
11.7%
9 27
 
8.3%
5 27
 
8.3%
4 26
 
8.0%
7 24
 
7.4%
6 24
 
7.4%
8 23
 
7.1%
0 21
 
6.5%
Other Punctuation
ValueCountFrequency (%)
/ 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
399
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1294
63.1%
Common 757
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 104
 
8.0%
기 104
 
8.0%
경 101
 
7.8%
시 86
 
6.6%
로 67
 
5.2%
면 46
 
3.6%
양 32
 
2.5%
길 31
 
2.4%
주 29
 
2.2%
구 26
 
2.0%
Other values (158) 668
51.6%
Common
ValueCountFrequency (%)
399
52.7%
1 68
 
9.0%
2 46
 
6.1%
3 38
 
5.0%
9 27
 
3.6%
5 27
 
3.6%
4 26
 
3.4%
7 24
 
3.2%
6 24
 
3.2%
8 23
 
3.0%
Other values (6) 55
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1294
63.1%
ASCII 757
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
399
52.7%
1 68
 
9.0%
2 46
 
6.1%
3 38
 
5.0%
9 27
 
3.6%
5 27
 
3.6%
4 26
 
3.4%
7 24
 
3.2%
6 24
 
3.2%
8 23
 
3.0%
Other values (6) 55
 
7.3%
Hangul
ValueCountFrequency (%)
도 104
 
8.0%
기 104
 
8.0%
경 101
 
7.8%
시 86
 
6.6%
로 67
 
5.2%
면 46
 
3.6%
양 32
 
2.5%
길 31
 
2.4%
주 29
 
2.2%
구 26
 
2.0%
Other values (158) 668
51.6%

정제지번주소
Text

MISSING 

Distinct92
Distinct (%)97.9%
Missing4
Missing (%)4.1%
Memory size916.0 B
2023-12-11T06:36:40.249256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length21.425532
Min length11

Characters and Unicode

Total characters2014
Distinct characters155
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)96.8%

Sample

1st row경기도 포천시 영북면 산정리 191-1번지
2nd row경기도 포천시 신북면 기지리 282번지
3rd row경기도 하남시 신장동 281번지
4th row경기도 화성시 송산동 188번지
5th row경기도 화성시 서신면 제부리 산12
ValueCountFrequency (%)
경기도 95
 
20.6%
용인시 9
 
2.0%
파주시 8
 
1.7%
가평군 7
 
1.5%
포천시 6
 
1.3%
양평군 6
 
1.3%
처인구 5
 
1.1%
남양주시 5
 
1.1%
여주시 5
 
1.1%
고양시 5
 
1.1%
Other values (249) 310
67.2%
2023-12-11T06:36:40.754662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
367
 
18.2%
기 100
 
5.0%
도 99
 
4.9%
경 95
 
4.7%
지 84
 
4.2%
시 82
 
4.1%
번 81
 
4.0%
1 57
 
2.8%
리 52
 
2.6%
동 51
 
2.5%
Other values (145) 946
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1302
64.6%
Space Separator 367
 
18.2%
Decimal Number 298
 
14.8%
Dash Punctuation 44
 
2.2%
Open Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 100
 
7.7%
도 99
 
7.6%
경 95
 
7.3%
지 84
 
6.5%
시 82
 
6.3%
번 81
 
6.2%
리 52
 
4.0%
동 51
 
3.9%
면 46
 
3.5%
양 28
 
2.2%
Other values (130) 584
44.9%
Decimal Number
ValueCountFrequency (%)
1 57
19.1%
2 42
14.1%
3 39
13.1%
4 30
10.1%
6 27
9.1%
8 23
7.7%
7 22
 
7.4%
5 22
 
7.4%
9 21
 
7.0%
0 15
 
5.0%
Space Separator
ValueCountFrequency (%)
367
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1302
64.6%
Common 712
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 100
 
7.7%
도 99
 
7.6%
경 95
 
7.3%
지 84
 
6.5%
시 82
 
6.3%
번 81
 
6.2%
리 52
 
4.0%
동 51
 
3.9%
면 46
 
3.5%
양 28
 
2.2%
Other values (130) 584
44.9%
Common
ValueCountFrequency (%)
367
51.5%
1 57
 
8.0%
- 44
 
6.2%
2 42
 
5.9%
3 39
 
5.5%
4 30
 
4.2%
6 27
 
3.8%
8 23
 
3.2%
7 22
 
3.1%
5 22
 
3.1%
Other values (5) 39
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1302
64.6%
ASCII 712
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
367
51.5%
1 57
 
8.0%
- 44
 
6.2%
2 42
 
5.9%
3 39
 
5.5%
4 30
 
4.2%
6 27
 
3.8%
8 23
 
3.2%
7 22
 
3.1%
5 22
 
3.1%
Other values (5) 39
 
5.5%
Hangul
ValueCountFrequency (%)
기 100
 
7.7%
도 99
 
7.6%
경 95
 
7.3%
지 84
 
6.5%
시 82
 
6.3%
번 81
 
6.2%
리 52
 
4.0%
동 51
 
3.9%
면 46
 
3.5%
양 28
 
2.2%
Other values (130) 584
44.9%

정제우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct83
Distinct (%)92.2%
Missing8
Missing (%)8.2%
Infinite0
Infinite (%)0.0%
Mean13682.167
Minimum10000
Maximum18556
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2023-12-11T06:36:40.900174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile10481.9
Q111477.75
median12641
Q316036.75
95-th percentile17950.4
Maximum18556
Range8556
Interquartile range (IQR)4559

Descriptive statistics

Standard deviation2566.3387
Coefficient of variation (CV)0.18756815
Kurtosis-1.1617813
Mean13682.167
Median Absolute Deviation (MAD)1657
Skewness0.48962152
Sum1231395
Variance6586094.1
MonotonicityNot monotonic
2023-12-11T06:36:41.049726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12636 2
 
2.0%
13829 2
 
2.0%
10862 2
 
2.0%
17072 2
 
2.0%
11027 2
 
2.0%
11103 2
 
2.0%
12456 2
 
2.0%
12510 1
 
1.0%
11307 1
 
1.0%
11519 1
 
1.0%
Other values (73) 73
74.5%
(Missing) 8
 
8.2%
ValueCountFrequency (%)
10000 1
1.0%
10273 1
1.0%
10292 1
1.0%
10392 1
1.0%
10400 1
1.0%
10582 1
1.0%
10800 1
1.0%
10808 1
1.0%
10858 1
1.0%
10862 2
2.0%
ValueCountFrequency (%)
18556 1
1.0%
18553 1
1.0%
18347 1
1.0%
18118 1
1.0%
17972 1
1.0%
17924 1
1.0%
17524 1
1.0%
17509 1
1.0%
17508 1
1.0%
17500 1
1.0%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct87
Distinct (%)98.9%
Missing10
Missing (%)10.2%
Infinite0
Infinite (%)0.0%
Mean37.509498
Minimum36.914829
Maximum38.093863
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2023-12-11T06:36:41.187639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.914829
5-th percentile37.056496
Q137.273984
median37.513987
Q337.73407
95-th percentile37.993844
Maximum38.093863
Range1.1790349
Interquartile range (IQR)0.46008596

Descriptive statistics

Standard deviation0.28841742
Coefficient of variation (CV)0.0076891839
Kurtosis-0.84476521
Mean37.509498
Median Absolute Deviation (MAD)0.23157822
Skewness0.14043131
Sum3300.8358
Variance0.083184611
MonotonicityNot monotonic
2023-12-11T06:36:41.329803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.2682000947 2
 
2.0%
38.0938634487 1
 
1.0%
37.7152481121 1
 
1.0%
37.2197885275 1
 
1.0%
37.3897919258 1
 
1.0%
37.2807973662 1
 
1.0%
37.3784854065 1
 
1.0%
37.5086718515 1
 
1.0%
37.946522172 1
 
1.0%
37.7547771162 1
 
1.0%
Other values (77) 77
78.6%
(Missing) 10
 
10.2%
ValueCountFrequency (%)
36.9148285364 1
1.0%
37.0168049528 1
1.0%
37.0263280823 1
1.0%
37.0312945714 1
1.0%
37.0407249537 1
1.0%
37.0857838483 1
1.0%
37.1160239256 1
1.0%
37.1194420569 1
1.0%
37.148425197 1
1.0%
37.1662479454 1
1.0%
ValueCountFrequency (%)
38.0938634487 1
1.0%
38.0895926653 1
1.0%
38.0688767268 1
1.0%
38.011592569 1
1.0%
38.0088794383 1
1.0%
37.9659224212 1
1.0%
37.946522172 1
1.0%
37.9433116584 1
1.0%
37.9234463151 1
1.0%
37.9059943775 1
1.0%

정제WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct87
Distinct (%)98.9%
Missing10
Missing (%)10.2%
Infinite0
Infinite (%)0.0%
Mean127.13644
Minimum126.53089
Maximum127.68816
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2023-12-11T06:36:41.476057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53089
5-th percentile126.6826
Q1126.91806
median127.11588
Q3127.32221
95-th percentile127.63005
Maximum127.68816
Range1.1572633
Interquartile range (IQR)0.40415728

Descriptive statistics

Standard deviation0.28731616
Coefficient of variation (CV)0.0022599041
Kurtosis-0.80590984
Mean127.13644
Median Absolute Deviation (MAD)0.20560187
Skewness-0.024362142
Sum11188.007
Variance0.082550576
MonotonicityNot monotonic
2023-12-11T06:36:41.634892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1089114049 2
 
2.0%
127.3208416203 1
 
1.0%
127.4904238916 1
 
1.0%
126.6023925616 1
 
1.0%
126.7812507272 1
 
1.0%
127.0151841956 1
 
1.0%
127.106340222 1
 
1.0%
126.7437361036 1
 
1.0%
127.0693437436 1
 
1.0%
127.3132455526 1
 
1.0%
Other values (77) 77
78.6%
(Missing) 10
 
10.2%
ValueCountFrequency (%)
126.5308936298 1
1.0%
126.6023925616 1
1.0%
126.6771018353 1
1.0%
126.6779036739 1
1.0%
126.6812725007 1
1.0%
126.6850635963 1
1.0%
126.692875166 1
1.0%
126.6965126169 1
1.0%
126.7437361036 1
1.0%
126.7490079227 1
1.0%
ValueCountFrequency (%)
127.6881568938 1
1.0%
127.659948866 1
1.0%
127.6545498438 1
1.0%
127.6541067136 1
1.0%
127.6388838916 1
1.0%
127.6136549141 1
1.0%
127.5839371818 1
1.0%
127.5704624053 1
1.0%
127.5352125186 1
1.0%
127.4911984972 1
1.0%

Interactions

2023-12-11T06:36:36.545966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:35.982192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:36.234260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:36.650655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:36.059601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:36.318149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:36.733074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:36.141575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:36:36.419963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:36:41.727926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명명소명전화번호부가정보정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
시군명1.0001.0000.9960.8911.0001.0000.9990.9250.915
명소명1.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호0.9961.0001.0001.0000.9990.9970.9760.9530.911
부가정보0.8911.0001.0001.0001.0000.0000.7160.0000.000
정제도로명주소1.0001.0000.9991.0001.0001.0001.0001.0001.000
정제지번주소1.0001.0000.9970.0001.0001.0001.0000.9750.967
정제우편번호0.9991.0000.9760.7161.0001.0001.0000.8830.837
정제WGS84위도0.9251.0000.9530.0001.0000.9750.8831.0000.330
정제WGS84경도0.9151.0000.9110.0001.0000.9670.8370.3301.000
2023-12-11T06:36:41.862880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부가정보시군명
부가정보1.0000.350
시군명0.3501.000
2023-12-11T06:36:41.955625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정제우편번호정제WGS84위도정제WGS84경도시군명부가정보
정제우편번호1.000-0.9130.1300.8150.263
정제WGS84위도-0.9131.000-0.1310.5610.000
정제WGS84경도0.130-0.1311.0000.5390.000
시군명0.8150.5610.5391.0000.350
부가정보0.2630.0000.0000.3501.000

Missing values

2023-12-11T06:36:36.876022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:36:37.083361image/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.
2023-12-11T06:36:37.213182image/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

시군명명소명전화번호부가정보데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
0포천시산정호수031-532-6135경차 2,000원, 소형 5,000원, 중형 10,000원2021-03-05경기도 포천시 영북면 산정호수로411번길 89경기도 포천시 영북면 산정리 191-1번지1110338.068877127.322117
1포천시포천아트밸리031-538-3485무료2021-03-05경기도 포천시 신북면 아트밸리로 234경기도 포천시 신북면 기지리 282번지1113937.923446127.236496
2하남시미사리경정공원031-790-8883유료주차, 소형 4,000원, 대형 10,000원2021-03-05경기도 하남시 미사대로 505경기도 하남시 신장동 281번지1290037.553631127.213247
3화성시용주사031-234-0040무료2021-03-05경기도 화성시 용주로 136경기도 화성시 송산동 188번지1834737.211783127.005618
4화성시제부도031-369-1673<NA>2021-03-05경기도 화성시 서신면 제부리 산12경기도 화성시 서신면 제부리 산1218553<NA><NA>
5용인시에버랜드031-320-5000무료2021-03-05경기도 용인시 처인구 포곡읍 에버랜드로 199경기도 용인시 처인구 포곡읍 전대리 310번지1702337.28996127.216586
6가평군캠프통아일랜드031-585-6000이용요금 별도문의2021-03-05경기도 가평군 청평면 호반로 976경기도 가평군 청평면 고성리 761-5번지1245637.710561127.484434
7양평군용문사031-773-3797소형차 1,000원 중,대형차 3,000원 버스 5,000원2021-03-05경기도 양평군 용문면 용문산로 782경기도 양평군 용문면 신점리 618번지1251037.550236127.570462
8양평군중미산자연휴양림031-771-7166경차 1,500원, 중·소형 3,000원, 대형 5,000원2021-03-05경기도 양평군 옥천면 중미산로 1152경기도 양평군 옥천면 신복리 산172-19번지1250537.58323127.458513
9여주시신륵사031-885-2505무료2021-03-05경기도 여주시 여주읍 신륵사길 73 (천송동 282)경기도 여주시 천송동 282번지1263637.297421127.659949
시군명명소명전화번호부가정보데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
88용인시와우정사031-332-2472무료2021-03-05경기도 용인시 해곡동 43 연화산 와우정사경기도 용인시 처인구 해곡동 43 연화산 와우정사1714237.179031127.274105
89의정부시원도봉산031-828-4572하단2021-03-05경기도 의정부시 망월로28번길 51-97경기도 의정부시 호원동 229-104번지1164537.705474127.037843
90용인시한국민속촌031-288-0000대형 3,000원 소형 2,000원2021-03-05경기도 용인시 기흥구 민속촌로 90경기도 용인시 기흥구 보라동 35번지1707537.260919127.120813
91이천시이천세계도자센터(이천세라피아)031-645-0730무료2021-03-05경기도 이천시 경충대로 2697번길 167-29경기도 이천시 관고동 432-3번지1737937.274069127.425927
92파주시자운서원031-958-1749무료2021-03-05경기도 파주시 법원읍 동문리 산 5-1경기도 파주시 법원읍 동문리 산 5-1<NA>37.867297126.872006
93파주시판문점<NA><NA>2021-03-05경기도 파주시 군내면 대성동길 184-11경기도 파주시 군내면 조산리 382번지1080037.943312126.677904
94파주시파주출판도시031-955-5959무료2021-03-05경기도 파주시 문발로 312경기도 파주시 문발동 637-1번지1088137.720616126.692875
95파주시헤이리예술마을031-946-8551헤이리예술마을 곳곳에 주차장 있음2021-03-05경기도 파주시 탄현면 법흥리경기도 파주시 탄현면 법흥리<NA><NA><NA>
96평택시바람새마을031-663-5453무료2021-03-05경기도 평택시 고덕면 궁리 496번지경기도 평택시 고덕면 궁리 496번지1792437.016805127.020599
97포천시전통 술 박물관 산사원031-531-9300무료2021-03-05경기도 포천시 화현면 화현리 512번지경기도 포천시 화현면 화현리 512번지1112337.905994127.309906