Overview

Dataset statistics

Number of variables9
Number of observations86
Missing cells91
Missing cells (%)11.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory76.5 B

Variable types

Categorical1
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 28 (32.6%) missing valuesMissing
정제도로명주소 has 1 (1.2%) missing valuesMissing
정제지번주소 has 6 (7.0%) missing valuesMissing
정제우편번호 has 18 (20.9%) missing valuesMissing
정제WGS84위도 has 19 (22.1%) missing valuesMissing
정제WGS84경도 has 19 (22.1%) missing valuesMissing
위치명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:00:35.009118
Analysis finished2023-12-10 21:00:37.544519
Duration2.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)33.7%
Missing0
Missing (%)0.0%
Memory size820.0 B
수원시
10 
이천시
8 
평택시
7 
부천시
6 
용인시
 
5
Other values (24)
50 

Length

Max length4
Median length3
Mean length3.0348837
Min length3

Unique

Unique11 ?
Unique (%)12.8%

Sample

1st row이천시
2nd row고양시
3rd row여주시
4th row수원시
5th row파주시

Common Values

ValueCountFrequency (%)
수원시 10
 
11.6%
이천시 8
 
9.3%
평택시 7
 
8.1%
부천시 6
 
7.0%
용인시 5
 
5.8%
안산시 5
 
5.8%
파주시 4
 
4.7%
고양시 3
 
3.5%
안성시 3
 
3.5%
광명시 3
 
3.5%
Other values (19) 32
37.2%

Length

2023-12-11T06:00:37.639520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 10
 
11.6%
이천시 8
 
9.3%
평택시 7
 
8.1%
부천시 6
 
7.0%
용인시 5
 
5.8%
안산시 5
 
5.8%
파주시 4
 
4.7%
하남시 3
 
3.5%
가평군 3
 
3.5%
성남시 3
 
3.5%
Other values (19) 32
37.2%

위치명
Text

UNIQUE 

Distinct86
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size820.0 B
2023-12-11T06:00:37.937799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length6.9186047
Min length3

Characters and Unicode

Total characters595
Distinct characters182
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)100.0%

Sample

1st row송파결정유연구소
2nd row풍동 애니골
3rd row여주프리미엄아울렛
4th row롯데몰(수원)
5th row롯데프리미엄아울렛(파주점)
ValueCountFrequency (%)
음식문화거리 2
 
1.9%
송파결정유연구소 1
 
1.0%
지동시장 1
 
1.0%
청평5일장 1
 
1.0%
강원반찬 1
 
1.0%
모란민속5일장 1
 
1.0%
마도농산물재래시장 1
 
1.0%
자연을담은떡 1
 
1.0%
가평5일장 1
 
1.0%
먹거리촌 1
 
1.0%
Other values (93) 93
89.4%
2023-12-11T06:00:38.512536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 34
 
5.7%
리 29
 
4.9%
시 26
 
4.4%
거 18
 
3.0%
18
 
3.0%
동 10
 
1.7%
아 10
 
1.7%
문 10
 
1.7%
미 10
 
1.7%
화 9
 
1.5%
Other values (172) 421
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 556
93.4%
Space Separator 18
 
3.0%
Decimal Number 11
 
1.8%
Close Punctuation 5
 
0.8%
Open Punctuation 5
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 34
 
6.1%
리 29
 
5.2%
시 26
 
4.7%
거 18
 
3.2%
동 10
 
1.8%
아 10
 
1.8%
문 10
 
1.8%
미 10
 
1.8%
화 9
 
1.6%
통 9
 
1.6%
Other values (164) 391
70.3%
Decimal Number
ValueCountFrequency (%)
5 6
54.5%
1 2
 
18.2%
2 1
 
9.1%
8 1
 
9.1%
7 1
 
9.1%
Space Separator
ValueCountFrequency (%)
18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 556
93.4%
Common 39
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 34
 
6.1%
리 29
 
5.2%
시 26
 
4.7%
거 18
 
3.2%
동 10
 
1.8%
아 10
 
1.8%
문 10
 
1.8%
미 10
 
1.8%
화 9
 
1.6%
통 9
 
1.6%
Other values (164) 391
70.3%
Common
ValueCountFrequency (%)
18
46.2%
5 6
 
15.4%
) 5
 
12.8%
( 5
 
12.8%
1 2
 
5.1%
2 1
 
2.6%
8 1
 
2.6%
7 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 556
93.4%
ASCII 39
 
6.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 34
 
6.1%
리 29
 
5.2%
시 26
 
4.7%
거 18
 
3.2%
동 10
 
1.8%
아 10
 
1.8%
문 10
 
1.8%
미 10
 
1.8%
화 9
 
1.6%
통 9
 
1.6%
Other values (164) 391
70.3%
ASCII
ValueCountFrequency (%)
18
46.2%
5 6
 
15.4%
) 5
 
12.8%
( 5
 
12.8%
1 2
 
5.1%
2 1
 
2.6%
8 1
 
2.6%
7 1
 
2.6%

전화번호
Text

MISSING 

Distinct57
Distinct (%)98.3%
Missing28
Missing (%)32.6%
Memory size820.0 B
2023-12-11T06:00:38.893795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.189655
Min length11

Characters and Unicode

Total characters707
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

Unique56 ?
Unique (%)96.6%

Sample

1st row031-633-6587
2nd row031-907-6080
3rd row031-8067-4000
4th row031-960-2500
5th row031-1644-4001
ValueCountFrequency (%)
031-8045-5591 2
 
3.4%
031-777-2500 1
 
1.7%
031-633-6587 1
 
1.7%
031-580-2114 1
 
1.7%
031-8016-0101 1
 
1.7%
031-461-8021 1
 
1.7%
031-8064-2500 1
 
1.7%
031-228-2765 1
 
1.7%
031-820-2321 1
 
1.7%
02-503-2132 1
 
1.7%
Other values (47) 47
81.0%
2023-12-11T06:00:39.432498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 118
16.7%
- 116
16.4%
3 92
13.0%
1 86
12.2%
2 57
8.1%
8 46
 
6.5%
6 46
 
6.5%
5 40
 
5.7%
4 38
 
5.4%
7 31
 
4.4%
Other values (2) 37
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 580
82.0%
Dash Punctuation 116
 
16.4%
Other Punctuation 11
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 118
20.3%
3 92
15.9%
1 86
14.8%
2 57
9.8%
8 46
 
7.9%
6 46
 
7.9%
5 40
 
6.9%
4 38
 
6.6%
7 31
 
5.3%
9 26
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%
Other Punctuation
ValueCountFrequency (%)
* 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 707
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 118
16.7%
- 116
16.4%
3 92
13.0%
1 86
12.2%
2 57
8.1%
8 46
 
6.5%
6 46
 
6.5%
5 40
 
5.7%
4 38
 
5.4%
7 31
 
4.4%
Other values (2) 37
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 707
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 118
16.7%
- 116
16.4%
3 92
13.0%
1 86
12.2%
2 57
8.1%
8 46
 
6.5%
6 46
 
6.5%
5 40
 
5.7%
4 38
 
5.4%
7 31
 
4.4%
Other values (2) 37
 
5.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size820.0 B
Minimum2021-03-05 00:00:00
Maximum2021-03-05 00:00:00
2023-12-11T06:00:39.585577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:39.706027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

정제도로명주소
Text

MISSING 

Distinct84
Distinct (%)98.8%
Missing1
Missing (%)1.2%
Memory size820.0 B
2023-12-11T06:00:39.990978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length27
Mean length21.329412
Min length12

Characters and Unicode

Total characters1813
Distinct characters189
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)97.6%

Sample

1st row경기도 이천시 신둔면 둔터로58
2nd row경기도 고양시 일산동구 애니골길 15-46 (풍동,오푸스하임)
3rd row경기도 여주시 명품로 360
4th row경기도 수원시 권선구 세화로 134 (서둔동)
5th row경기도 파주시 회동길 390
ValueCountFrequency (%)
경기도 85
 
20.5%
수원시 10
 
2.4%
이천시 8
 
1.9%
일원 7
 
1.7%
평택시 7
 
1.7%
팔달구 6
 
1.4%
부천시 6
 
1.4%
안산시 5
 
1.2%
용인시 5
 
1.2%
파주시 4
 
1.0%
Other values (229) 271
65.5%
2023-12-11T06:00:40.553034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
330
 
18.2%
기 89
 
4.9%
경 88
 
4.9%
도 87
 
4.8%
시 85
 
4.7%
1 59
 
3.3%
로 57
 
3.1%
동 40
 
2.2%
2 39
 
2.2%
3 36
 
2.0%
Other values (179) 903
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1166
64.3%
Space Separator 330
 
18.2%
Decimal Number 274
 
15.1%
Dash Punctuation 15
 
0.8%
Close Punctuation 11
 
0.6%
Open Punctuation 11
 
0.6%
Other Punctuation 5
 
0.3%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 89
 
7.6%
경 88
 
7.5%
도 87
 
7.5%
시 85
 
7.3%
로 57
 
4.9%
동 40
 
3.4%
길 33
 
2.8%
구 32
 
2.7%
천 28
 
2.4%
번 27
 
2.3%
Other values (162) 600
51.5%
Decimal Number
ValueCountFrequency (%)
1 59
21.5%
2 39
14.2%
3 36
13.1%
6 25
9.1%
7 23
 
8.4%
4 23
 
8.4%
0 22
 
8.0%
5 22
 
8.0%
9 15
 
5.5%
8 10
 
3.6%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
· 1
 
20.0%
Space Separator
ValueCountFrequency (%)
330
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1166
64.3%
Common 646
35.6%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 89
 
7.6%
경 88
 
7.5%
도 87
 
7.5%
시 85
 
7.3%
로 57
 
4.9%
동 40
 
3.4%
길 33
 
2.8%
구 32
 
2.7%
천 28
 
2.4%
번 27
 
2.3%
Other values (162) 600
51.5%
Common
ValueCountFrequency (%)
330
51.1%
1 59
 
9.1%
2 39
 
6.0%
3 36
 
5.6%
6 25
 
3.9%
7 23
 
3.6%
4 23
 
3.6%
0 22
 
3.4%
5 22
 
3.4%
- 15
 
2.3%
Other values (6) 52
 
8.0%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1166
64.3%
ASCII 646
35.6%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
330
51.1%
1 59
 
9.1%
2 39
 
6.0%
3 36
 
5.6%
6 25
 
3.9%
7 23
 
3.6%
4 23
 
3.6%
0 22
 
3.4%
5 22
 
3.4%
- 15
 
2.3%
Other values (6) 52
 
8.0%
Hangul
ValueCountFrequency (%)
기 89
 
7.6%
경 88
 
7.5%
도 87
 
7.5%
시 85
 
7.3%
로 57
 
4.9%
동 40
 
3.4%
길 33
 
2.8%
구 32
 
2.7%
천 28
 
2.4%
번 27
 
2.3%
Other values (162) 600
51.5%
None
ValueCountFrequency (%)
· 1
100.0%

정제지번주소
Text

MISSING 

Distinct79
Distinct (%)98.8%
Missing6
Missing (%)7.0%
Memory size820.0 B
2023-12-11T06:00:40.937653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length21.4875
Min length12

Characters and Unicode

Total characters1719
Distinct characters156
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)97.5%

Sample

1st row경기도 이천시 신둔면 수남리 175-1번지
2nd row경기도 고양시 일산동구 풍동 1127-13번지 오푸스하임
3rd row경기도 여주시 상거동 460번지
4th row경기도 수원시 권선구 서둔동 381번지
5th row경기도 파주시 문발동 645번지
ValueCountFrequency (%)
경기도 80
 
20.6%
수원시 10
 
2.6%
일원 9
 
2.3%
이천시 8
 
2.1%
부천시 6
 
1.5%
평택시 6
 
1.5%
팔달구 6
 
1.5%
안산시 5
 
1.3%
용인시 5
 
1.3%
파주시 4
 
1.0%
Other values (211) 250
64.3%
2023-12-11T06:00:41.506756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
309
 
18.0%
기 83
 
4.8%
도 81
 
4.7%
경 80
 
4.7%
시 77
 
4.5%
동 75
 
4.4%
지 70
 
4.1%
1 67
 
3.9%
번 64
 
3.7%
- 40
 
2.3%
Other values (146) 773
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1096
63.8%
Space Separator 309
 
18.0%
Decimal Number 269
 
15.6%
Dash Punctuation 40
 
2.3%
Other Punctuation 4
 
0.2%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 83
 
7.6%
도 81
 
7.4%
경 80
 
7.3%
시 77
 
7.0%
동 75
 
6.8%
지 70
 
6.4%
번 64
 
5.8%
구 28
 
2.6%
원 24
 
2.2%
리 23
 
2.1%
Other values (131) 491
44.8%
Decimal Number
ValueCountFrequency (%)
1 67
24.9%
3 35
13.0%
2 32
11.9%
4 26
 
9.7%
7 24
 
8.9%
5 20
 
7.4%
6 19
 
7.1%
0 18
 
6.7%
8 16
 
5.9%
9 12
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
· 1
 
25.0%
Space Separator
ValueCountFrequency (%)
309
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1096
63.8%
Common 622
36.2%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 83
 
7.6%
도 81
 
7.4%
경 80
 
7.3%
시 77
 
7.0%
동 75
 
6.8%
지 70
 
6.4%
번 64
 
5.8%
구 28
 
2.6%
원 24
 
2.2%
리 23
 
2.1%
Other values (131) 491
44.8%
Common
ValueCountFrequency (%)
309
49.7%
1 67
 
10.8%
- 40
 
6.4%
3 35
 
5.6%
2 32
 
5.1%
4 26
 
4.2%
7 24
 
3.9%
5 20
 
3.2%
6 19
 
3.1%
0 18
 
2.9%
Other values (4) 32
 
5.1%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1096
63.8%
ASCII 622
36.2%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
309
49.7%
1 67
 
10.8%
- 40
 
6.4%
3 35
 
5.6%
2 32
 
5.1%
4 26
 
4.2%
7 24
 
3.9%
5 20
 
3.2%
6 19
 
3.1%
0 18
 
2.9%
Other values (4) 32
 
5.1%
Hangul
ValueCountFrequency (%)
기 83
 
7.6%
도 81
 
7.4%
경 80
 
7.3%
시 77
 
7.0%
동 75
 
6.8%
지 70
 
6.4%
번 64
 
5.8%
구 28
 
2.6%
원 24
 
2.2%
리 23
 
2.1%
Other values (131) 491
44.8%
None
ValueCountFrequency (%)
· 1
100.0%

정제우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct65
Distinct (%)95.6%
Missing18
Missing (%)20.9%
Infinite0
Infinite (%)0.0%
Mean14989.221
Minimum10301
Maximum18550
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-11T06:00:41.685435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10301
5-th percentile10836.65
Q112907.75
median15610
Q317127
95-th percentile17861.35
Maximum18550
Range8249
Interquartile range (IQR)4219.25

Descriptive statistics

Standard deviation2400.6015
Coefficient of variation (CV)0.16015519
Kurtosis-1.0754235
Mean14989.221
Median Absolute Deviation (MAD)1785
Skewness-0.4570165
Sum1019267
Variance5762887.7
MonotonicityNot monotonic
2023-12-11T06:00:41.884235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16245 2
 
2.3%
17758 2
 
2.3%
17308 2
 
2.3%
13814 1
 
1.2%
12453 1
 
1.2%
13305 1
 
1.2%
16314 1
 
1.2%
12419 1
 
1.2%
17368 1
 
1.2%
16243 1
 
1.2%
Other values (55) 55
64.0%
(Missing) 18
 
20.9%
ValueCountFrequency (%)
10301 1
1.2%
10401 1
1.2%
10450 1
1.2%
10823 1
1.2%
10862 1
1.2%
10881 1
1.2%
11154 1
1.2%
11324 1
1.2%
11695 1
1.2%
11928 1
1.2%
ValueCountFrequency (%)
18550 1
1.2%
18136 1
1.2%
18105 1
1.2%
17917 1
1.2%
17758 2
2.3%
17731 1
1.2%
17592 1
1.2%
17581 1
1.2%
17519 1
1.2%
17420 1
1.2%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct67
Distinct (%)100.0%
Missing19
Missing (%)22.1%
Infinite0
Infinite (%)0.0%
Mean37.378596
Minimum36.991901
Maximum37.892609
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-11T06:00:42.094119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.991901
5-th percentile37.069034
Q137.265351
median37.300141
Q337.516435
95-th percentile37.76037
Maximum37.892609
Range0.90070799
Interquartile range (IQR)0.25108456

Descriptive statistics

Standard deviation0.21511584
Coefficient of variation (CV)0.0057550542
Kurtosis-0.24360139
Mean37.378596
Median Absolute Deviation (MAD)0.12668427
Skewness0.49700197
Sum2504.3659
Variance0.046274826
MonotonicityNot monotonic
2023-12-11T06:00:42.273354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.2923502729 1
 
1.2%
37.2779218633 1
 
1.2%
37.2760247294 1
 
1.2%
37.6774461802 1
 
1.2%
37.7346061435 1
 
1.2%
37.4418010319 1
 
1.2%
37.2062122346 1
 
1.2%
37.8297608931 1
 
1.2%
37.6719264532 1
 
1.2%
37.4533593074 1
 
1.2%
Other values (57) 57
66.3%
(Missing) 19
 
22.1%
ValueCountFrequency (%)
36.9919006082 1
1.2%
37.0065594739 1
1.2%
37.0066256944 1
1.2%
37.0660526248 1
1.2%
37.0759902563 1
1.2%
37.0805105741 1
1.2%
37.0807604823 1
1.2%
37.114866575 1
1.2%
37.1510943316 1
1.2%
37.188316862 1
1.2%
ValueCountFrequency (%)
37.8926085954 1
1.2%
37.8567241041 1
1.2%
37.8297608931 1
1.2%
37.7693560552 1
1.2%
37.7394019398 1
1.2%
37.7346061435 1
1.2%
37.7177916524 1
1.2%
37.6774461802 1
1.2%
37.6719264532 1
1.2%
37.6613265499 1
1.2%

정제WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct67
Distinct (%)100.0%
Missing19
Missing (%)22.1%
Infinite0
Infinite (%)0.0%
Mean127.0876
Minimum126.69378
Maximum127.65455
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size906.0 B
2023-12-11T06:00:42.538307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.69378
5-th percentile126.74498
Q1126.85991
median127.05272
Q3127.2696
95-th percentile127.50806
Maximum127.65455
Range0.96077038
Interquartile range (IQR)0.40968856

Descriptive statistics

Standard deviation0.25675063
Coefficient of variation (CV)0.002020265
Kurtosis-0.73568214
Mean127.0876
Median Absolute Deviation (MAD)0.21607233
Skewness0.3898359
Sum8514.8693
Variance0.065920884
MonotonicityNot monotonic
2023-12-11T06:00:42.824997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9993262623 1
 
1.2%
127.0195905812 1
 
1.2%
127.0207757343 1
 
1.2%
127.4921184686 1
 
1.2%
127.415880581 1
 
1.2%
127.1324842649 1
 
1.2%
126.7790840043 1
 
1.2%
127.5148864119 1
 
1.2%
126.789514607 1
 
1.2%
127.0026644711 1
 
1.2%
Other values (57) 57
66.3%
(Missing) 19
 
22.1%
ValueCountFrequency (%)
126.693779466 1
1.2%
126.6965126169 1
1.2%
126.73689981 1
1.2%
126.7370588161 1
1.2%
126.7634622698 1
1.2%
126.7688109747 1
1.2%
126.7710277905 1
1.2%
126.7790840043 1
1.2%
126.7799409281 1
1.2%
126.7839477675 1
1.2%
ValueCountFrequency (%)
127.6545498438 1
1.2%
127.630760159 1
1.2%
127.6136549141 1
1.2%
127.5148864119 1
1.2%
127.4921184686 1
1.2%
127.4454921657 1
1.2%
127.4403595125 1
1.2%
127.423386291 1
1.2%
127.415880581 1
1.2%
127.4121079852 1
1.2%

Interactions

2023-12-11T06:00:36.316634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:35.645957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:35.952242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:36.426375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:35.738043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:36.062626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:36.553194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:35.840706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:36.198906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:00:42.928941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명위치명전화번호정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
시군명1.0001.0001.0001.0001.0001.0000.9620.965
위치명1.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
정제도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
정제지번주소1.0001.0001.0001.0001.0001.0001.0001.000
정제우편번호1.0001.0001.0001.0001.0001.0000.8710.899
정제WGS84위도0.9621.0001.0001.0001.0000.8711.0000.708
정제WGS84경도0.9651.0001.0001.0001.0000.8990.7081.000
2023-12-11T06:00:43.084584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정제우편번호정제WGS84위도정제WGS84경도시군명
정제우편번호1.000-0.9070.2040.861
정제WGS84위도-0.9071.000-0.2420.694
정제WGS84경도0.204-0.2421.0000.705
시군명0.8610.6940.7051.000

Missing values

2023-12-11T06:00:36.718351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:00:37.203747image/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.
2023-12-11T06:00:37.414334image/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

시군명위치명전화번호데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
0이천시송파결정유연구소031-633-65872021-03-05경기도 이천시 신둔면 둔터로58경기도 이천시 신둔면 수남리 175-1번지1730737.287932127.400631
1고양시풍동 애니골031-907-60802021-03-05경기도 고양시 일산동구 애니골길 15-46 (풍동,오푸스하임)경기도 고양시 일산동구 풍동 1127-13번지 오푸스하임1030137.671926126.789515
2여주시여주프리미엄아울렛<NA>2021-03-05경기도 여주시 명품로 360경기도 여주시 상거동 460번지1264637.245211127.613655
3수원시롯데몰(수원)031-8067-40002021-03-05경기도 수원시 권선구 세화로 134 (서둔동)경기도 수원시 권선구 서둔동 381번지1662137.264101126.997371
4파주시롯데프리미엄아울렛(파주점)031-960-25002021-03-05경기도 파주시 회동길 390경기도 파주시 문발동 645번지1088137.717792126.693779
5파주시파주프리미엄아울렛031-1644-40012021-03-05경기도 파주시 탄현면 필승로 200경기도 파주시 탄현면 법흥리 1790-8번지1086237.769356126.696513
6광주시곤지암 도자공원031-799-15002021-03-05경기도 광주시 곤지암읍 경충대로 727경기도 광주시 곤지암읍 삼리 72-1번지1280537.35028127.33479
7고양시라페스타031-920-96002021-03-05경기도 고양시 일산동구 무궁화로 32-34경기도 고양시 일산동구 장항동 764번지1040137.661327126.768811
8이천시토월도요031-638-33902021-03-05경기도 이천시 경충대로2993번길 28경기도 이천시 사음동 537-1번지1730837.294747127.412108
9이천시장호원재래시장<NA>2021-03-05경기도 이천시 장호원읍 서동대로8965번길 36경기도 이천시 장호원읍 오남리 3-38번지1742037.114867127.63076
시군명위치명전화번호데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
76하남시하남덕풍전통재래시장031-794-37532021-03-05경기도 하남시 신장로154번길 57경기도 하남시 덕풍동 326-9번지1296737.541818127.203523
77하남시신장전통재래시장031-794-46262021-03-05경기도 하남시 신장1로3번길 42경기도 하남시 신장동 429-1번지1295837.53786127.207014
78수원시광교카페거리<NA>2021-03-05경기도 수원시 영통구 센트럴파크로127번길 51경기도 수원시 영통구 이의동 1311번지1650637.294398127.053717
79이천시이진상회070-8888-88822021-03-05경기도 이천시 마장면 서이천로 656경기도 이천시 마장면 장암리 325번지1738337.279323127.400078
80수원시28청춘청년몰031-242-60902021-03-05경기도 수원시 팔달구 수원천로255번길 6경기도 수원시 팔달구 영동 8번지1626237.276891127.018717
81의정부시의정부 제일전통시장031-846-26172021-03-05경기도 의정부시 태평로73번길 20경기도 의정부시 의정부동 160번지1169537.739402127.050117
82안산시댕이골 전통음식거리***-****-****2021-03-05경기도 안산시 상록구 석호공원로2길 16-1 (사동)경기도 안산시 상록구 사동 산62-3번지1558237.300094126.849342
83안산시다문화거리031-1666-12342021-03-05경기도 안산시 단원구 다문화길 16 일원경기도 안산시 단원구 원곡동 795번지 일원1539337.32943126.790608
84이천시롯데프리미엄아울렛(이천점)031-777-25002021-03-05경기도 이천시 호법면 프리미엄아울렛로 177-74경기도 이천시 호법면 단천리 864번지1738437.242321127.399992
85이천시수안도예명품관031-633-27242021-03-05경기도 이천시 경충대로 3052경기도 이천시 사음동 629-10번지1730837.300017127.408367