Overview

Dataset statistics

Number of variables11
Number of observations114
Missing cells240
Missing cells (%)19.1%
Duplicate rows1
Duplicate rows (%)0.9%
Total size in memory10.5 KiB
Average record size in memory94.2 B

Variable types

Categorical2
Text4
Numeric3
Unsupported2

Dataset

Description경기도_노인돌봄서비스 수행기관 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=AOY7I1SKRJ7IM0ZJQSN528372736&infSeq=1

Alerts

서비스구분명 has constant value ""Constant
Dataset has 1 (0.9%) duplicate rowsDuplicates
우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 우편번호 and 2 other fieldsHigh correlation
도로명주소 has 6 (5.3%) missing valuesMissing
우편번호 has 2 (1.8%) missing valuesMissing
팩스번호 has 114 (100.0%) missing valuesMissing
비고 has 114 (100.0%) missing valuesMissing
WGS84위도 has 2 (1.8%) missing valuesMissing
WGS84경도 has 2 (1.8%) missing valuesMissing
팩스번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 22:13:46.468901
Analysis finished2023-12-10 22:13:48.101655
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)27.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
수원시
10 
고양시
10 
용인시
9 
성남시
8 
안산시
 
7
Other values (26)
70 

Length

Max length4
Median length3
Mean length3.0789474
Min length3

Unique

Unique5 ?
Unique (%)4.4%

Sample

1st row용인시
2nd row수원시
3rd row여주시
4th row여주시
5th row시흥시

Common Values

ValueCountFrequency (%)
수원시 10
 
8.8%
고양시 10
 
8.8%
용인시 9
 
7.9%
성남시 8
 
7.0%
안산시 7
 
6.1%
부천시 6
 
5.3%
남양주시 4
 
3.5%
파주시 4
 
3.5%
양주시 4
 
3.5%
안양시 4
 
3.5%
Other values (21) 48
42.1%

Length

2023-12-11T07:13:48.156821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 10
 
8.8%
고양시 10
 
8.8%
용인시 9
 
7.9%
성남시 8
 
7.0%
안산시 7
 
6.1%
부천시 6
 
5.3%
남양주시 4
 
3.5%
파주시 4
 
3.5%
양주시 4
 
3.5%
안양시 4
 
3.5%
Other values (21) 48
42.1%

서비스구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
노인돌봄서비스
114 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노인돌봄서비스 114
100.0%

Length

2023-12-11T07:13:48.255082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:13:48.337127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인돌봄서비스 114
100.0%

기관명
Text

Distinct112
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T07:13:48.529784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length10.026316
Min length5

Characters and Unicode

Total characters1143
Distinct characters174
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)96.5%

Sample

1st row(사)여럿이함께 푸드뱅크
2nd rowSK청솔노인복지관
3rd row가남반석재가노인지원서비스센터
4th row강북권역 노인맞춤돌봄서비스센터
5th row거모종합사회복지관
ValueCountFrequency (%)
재가노인지원서비스센터 3
 
2.3%
노인(종합)복지관 2
 
1.5%
열린노인복지센터 2
 
1.5%
노인맞춤돌봄서비스센터 2
 
1.5%
사회적협동조합 2
 
1.5%
양주시 2
 
1.5%
용인시수지노인복지관 1
 
0.8%
용인대학교 1
 
0.8%
사회봉사센터 1
 
0.8%
용인시기흥노인복지관 1
 
0.8%
Other values (113) 113
86.9%
2023-12-11T07:13:48.873632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 102
 
8.9%
복 89
 
7.8%
인 82
 
7.2%
관 78
 
6.8%
노 74
 
6.5%
합 47
 
4.1%
종 42
 
3.7%
사 31
 
2.7%
시 31
 
2.7%
터 30
 
2.6%
Other values (164) 537
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1116
97.6%
Space Separator 16
 
1.4%
Open Punctuation 3
 
0.3%
Close Punctuation 3
 
0.3%
Decimal Number 3
 
0.3%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 102
 
9.1%
복 89
 
8.0%
인 82
 
7.3%
관 78
 
7.0%
노 74
 
6.6%
합 47
 
4.2%
종 42
 
3.8%
사 31
 
2.8%
시 31
 
2.8%
터 30
 
2.7%
Other values (156) 510
45.7%
Decimal Number
ValueCountFrequency (%)
4 1
33.3%
7 1
33.3%
9 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1116
97.6%
Common 25
 
2.2%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 102
 
9.1%
복 89
 
8.0%
인 82
 
7.3%
관 78
 
7.0%
노 74
 
6.6%
합 47
 
4.2%
종 42
 
3.8%
사 31
 
2.8%
시 31
 
2.8%
터 30
 
2.7%
Other values (156) 510
45.7%
Common
ValueCountFrequency (%)
16
64.0%
( 3
 
12.0%
) 3
 
12.0%
4 1
 
4.0%
7 1
 
4.0%
9 1
 
4.0%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1116
97.6%
ASCII 27
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 102
 
9.1%
복 89
 
8.0%
인 82
 
7.3%
관 78
 
7.0%
노 74
 
6.6%
합 47
 
4.2%
종 42
 
3.8%
사 31
 
2.8%
시 31
 
2.8%
터 30
 
2.7%
Other values (156) 510
45.7%
ASCII
ValueCountFrequency (%)
16
59.3%
( 3
 
11.1%
) 3
 
11.1%
4 1
 
3.7%
7 1
 
3.7%
9 1
 
3.7%
S 1
 
3.7%
K 1
 
3.7%

도로명주소
Text

MISSING 

Distinct106
Distinct (%)98.1%
Missing6
Missing (%)5.3%
Memory size1.0 KiB
2023-12-11T07:13:49.124890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length19.324074
Min length14

Characters and Unicode

Total characters2087
Distinct characters164
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

Unique104 ?
Unique (%)96.3%

Sample

1st row경기도 용인시 수지구 죽전로 150
2nd row경기도 수원시 장안구 장안로 174
3rd row경기도 여주시 가남읍 은봉길 116-29
4th row경기도 여주시 세종로 319-1
5th row경기도 시흥시 군자로466번길 37
ValueCountFrequency (%)
경기도 108
 
21.8%
수원시 9
 
1.8%
용인시 9
 
1.8%
성남시 8
 
1.6%
안산시 7
 
1.4%
고양시 7
 
1.4%
부천시 6
 
1.2%
덕양구 5
 
1.0%
의정부시 4
 
0.8%
기흥구 4
 
0.8%
Other values (249) 329
66.3%
2023-12-11T07:13:49.529244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
388
18.6%
경 114
 
5.5%
기 114
 
5.5%
도 108
 
5.2%
시 108
 
5.2%
로 103
 
4.9%
1 71
 
3.4%
구 49
 
2.3%
길 45
 
2.2%
3 44
 
2.1%
Other values (154) 943
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1308
62.7%
Space Separator 388
 
18.6%
Decimal Number 380
 
18.2%
Dash Punctuation 11
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 114
 
8.7%
기 114
 
8.7%
도 108
 
8.3%
시 108
 
8.3%
로 103
 
7.9%
구 49
 
3.7%
길 45
 
3.4%
번 38
 
2.9%
양 31
 
2.4%
안 24
 
1.8%
Other values (142) 574
43.9%
Decimal Number
ValueCountFrequency (%)
1 71
18.7%
3 44
11.6%
2 44
11.6%
6 34
8.9%
4 34
8.9%
5 34
8.9%
7 32
8.4%
0 31
8.2%
9 29
7.6%
8 27
 
7.1%
Space Separator
ValueCountFrequency (%)
388
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1308
62.7%
Common 779
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 114
 
8.7%
기 114
 
8.7%
도 108
 
8.3%
시 108
 
8.3%
로 103
 
7.9%
구 49
 
3.7%
길 45
 
3.4%
번 38
 
2.9%
양 31
 
2.4%
안 24
 
1.8%
Other values (142) 574
43.9%
Common
ValueCountFrequency (%)
388
49.8%
1 71
 
9.1%
3 44
 
5.6%
2 44
 
5.6%
6 34
 
4.4%
4 34
 
4.4%
5 34
 
4.4%
7 32
 
4.1%
0 31
 
4.0%
9 29
 
3.7%
Other values (2) 38
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1308
62.7%
ASCII 779
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
388
49.8%
1 71
 
9.1%
3 44
 
5.6%
2 44
 
5.6%
6 34
 
4.4%
4 34
 
4.4%
5 34
 
4.4%
7 32
 
4.1%
0 31
 
4.0%
9 29
 
3.7%
Other values (2) 38
 
4.9%
Hangul
ValueCountFrequency (%)
경 114
 
8.7%
기 114
 
8.7%
도 108
 
8.3%
시 108
 
8.3%
로 103
 
7.9%
구 49
 
3.7%
길 45
 
3.4%
번 38
 
2.9%
양 31
 
2.4%
안 24
 
1.8%
Other values (142) 574
43.9%

지번주소
Text

Distinct112
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T07:13:49.813294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length34
Mean length22.394737
Min length15

Characters and Unicode

Total characters2553
Distinct characters182
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)96.5%

Sample

1st row경기도 용인시 수지구 죽전동 1328-3번지 단대프라자Ⅲ 403호
2nd row경기도 수원시 장안구 정자동 286번지
3rd row경기도 여주시 가남읍 은봉리 538-3번지
4th row경기도 여주시 교동 45-20번지
5th row경기도 시흥시 거모동 1738-9번지 4층
ValueCountFrequency (%)
경기도 114
 
20.5%
수원시 10
 
1.8%
고양시 10
 
1.8%
용인시 9
 
1.6%
성남시 8
 
1.4%
안산시 7
 
1.3%
부천시 6
 
1.1%
덕양구 5
 
0.9%
안양시 4
 
0.7%
기흥구 4
 
0.7%
Other values (296) 379
68.2%
2023-12-11T07:13:50.220740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
442
 
17.3%
지 120
 
4.7%
시 118
 
4.6%
기 118
 
4.6%
경 114
 
4.5%
도 114
 
4.5%
번 111
 
4.3%
동 103
 
4.0%
1 78
 
3.1%
2 75
 
2.9%
Other values (172) 1160
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1590
62.3%
Decimal Number 453
 
17.7%
Space Separator 442
 
17.3%
Dash Punctuation 64
 
2.5%
Uppercase Letter 2
 
0.1%
Letter Number 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 120
 
7.5%
시 118
 
7.4%
기 118
 
7.4%
경 114
 
7.2%
도 114
 
7.2%
번 111
 
7.0%
동 103
 
6.5%
구 52
 
3.3%
양 36
 
2.3%
산 29
 
1.8%
Other values (156) 675
42.5%
Decimal Number
ValueCountFrequency (%)
1 78
17.2%
2 75
16.6%
3 52
11.5%
4 41
9.1%
5 40
8.8%
0 36
7.9%
8 36
7.9%
7 34
7.5%
6 34
7.5%
9 27
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
442
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1590
62.3%
Common 960
37.6%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 120
 
7.5%
시 118
 
7.4%
기 118
 
7.4%
경 114
 
7.2%
도 114
 
7.2%
번 111
 
7.0%
동 103
 
6.5%
구 52
 
3.3%
양 36
 
2.3%
산 29
 
1.8%
Other values (156) 675
42.5%
Common
ValueCountFrequency (%)
442
46.0%
1 78
 
8.1%
2 75
 
7.8%
- 64
 
6.7%
3 52
 
5.4%
4 41
 
4.3%
5 40
 
4.2%
0 36
 
3.8%
8 36
 
3.8%
7 34
 
3.5%
Other values (3) 62
 
6.5%
Latin
ValueCountFrequency (%)
C 1
33.3%
Ⅲ 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1590
62.3%
ASCII 962
37.7%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
442
45.9%
1 78
 
8.1%
2 75
 
7.8%
- 64
 
6.7%
3 52
 
5.4%
4 41
 
4.3%
5 40
 
4.2%
0 36
 
3.7%
8 36
 
3.7%
7 34
 
3.5%
Other values (5) 64
 
6.7%
Hangul
ValueCountFrequency (%)
지 120
 
7.5%
시 118
 
7.4%
기 118
 
7.4%
경 114
 
7.2%
도 114
 
7.2%
번 111
 
7.0%
동 103
 
6.5%
구 52
 
3.3%
양 36
 
2.3%
산 29
 
1.8%
Other values (156) 675
42.5%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%

우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct109
Distinct (%)97.3%
Missing2
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean13997.554
Minimum10032
Maximum18590
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:13:50.350364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10032
5-th percentile10426.4
Q111800
median13956.5
Q316274.75
95-th percentile17785.35
Maximum18590
Range8558
Interquartile range (IQR)4474.75

Descriptive statistics

Standard deviation2470.0749
Coefficient of variation (CV)0.17646476
Kurtosis-1.2367944
Mean13997.554
Median Absolute Deviation (MAD)2237
Skewness0.098516933
Sum1567726
Variance6101270.2
MonotonicityNot monotonic
2023-12-11T07:13:50.474580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18590 2
 
1.8%
12790 2
 
1.8%
11508 2
 
1.8%
18120 1
 
0.9%
14566 1
 
0.9%
10469 1
 
0.9%
10873 1
 
0.9%
17019 1
 
0.9%
16835 1
 
0.9%
16959 1
 
0.9%
Other values (99) 99
86.8%
(Missing) 2
 
1.8%
ValueCountFrequency (%)
10032 1
0.9%
10111 1
0.9%
10378 1
0.9%
10382 1
0.9%
10388 1
0.9%
10400 1
0.9%
10448 1
0.9%
10469 1
0.9%
10470 1
0.9%
10486 1
0.9%
ValueCountFrequency (%)
18590 2
1.8%
18501 1
0.9%
18131 1
0.9%
18120 1
0.9%
17853 1
0.9%
17730 1
0.9%
17591 1
0.9%
17521 1
0.9%
17420 1
0.9%
17375 1
0.9%

전화번호
Text

Distinct112
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T07:13:51.109139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.087719
Min length11

Characters and Unicode

Total characters1378
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

Unique110 ?
Unique (%)96.5%

Sample

1st row031-283-0873
2nd row031-546-8987
3rd row031-884-8359
4th row031-883-9101
5th row031-493-6350
ValueCountFrequency (%)
031-943-0730 2
 
1.8%
031-829-2091 2
 
1.8%
031-283-0873 1
 
0.9%
031-201-8310 1
 
0.9%
032-667-0261 1
 
0.9%
031-966-4007 1
 
0.9%
031-334-9301 1
 
0.9%
031-270-0036 1
 
0.9%
031-284-8852 1
 
0.9%
031-8020-3413 1
 
0.9%
Other values (102) 102
89.5%
2023-12-11T07:13:51.941337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 240
17.4%
- 228
16.5%
3 187
13.6%
1 156
11.3%
8 99
7.2%
2 85
 
6.2%
7 80
 
5.8%
9 78
 
5.7%
5 78
 
5.7%
6 75
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1150
83.5%
Dash Punctuation 228
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 240
20.9%
3 187
16.3%
1 156
13.6%
8 99
8.6%
2 85
 
7.4%
7 80
 
7.0%
9 78
 
6.8%
5 78
 
6.8%
6 75
 
6.5%
4 72
 
6.3%
Dash Punctuation
ValueCountFrequency (%)
- 228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1378
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 240
17.4%
- 228
16.5%
3 187
13.6%
1 156
11.3%
8 99
7.2%
2 85
 
6.2%
7 80
 
5.8%
9 78
 
5.7%
5 78
 
5.7%
6 75
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1378
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 240
17.4%
- 228
16.5%
3 187
13.6%
1 156
11.3%
8 99
7.2%
2 85
 
6.2%
7 80
 
5.8%
9 78
 
5.7%
5 78
 
5.7%
6 75
 
5.4%

팩스번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing114
Missing (%)100.0%
Memory size1.1 KiB

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing114
Missing (%)100.0%
Memory size1.1 KiB

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct110
Distinct (%)98.2%
Missing2
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean37.460351
Minimum37.001368
Maximum38.103506
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:13:52.121402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.001368
5-th percentile37.128216
Q137.29313
median37.40685
Q337.646184
95-th percentile37.851322
Maximum38.103506
Range1.1021379
Interquartile range (IQR)0.35305393

Descriptive statistics

Standard deviation0.22764704
Coefficient of variation (CV)0.0060770129
Kurtosis-0.28682371
Mean37.460351
Median Absolute Deviation (MAD)0.13686541
Skewness0.44533438
Sum4195.5593
Variance0.051823174
MonotonicityNot monotonic
2023-12-11T07:13:52.308530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.1282159918 2
 
1.8%
37.8021908161 2
 
1.8%
37.2506946278 1
 
0.9%
37.4967307599 1
 
0.9%
37.6515843289 1
 
0.9%
37.7292152721 1
 
0.9%
37.2409283699 1
 
0.9%
37.3222450318 1
 
0.9%
37.2878686917 1
 
0.9%
37.2278791869 1
 
0.9%
Other values (100) 100
87.7%
(Missing) 2
 
1.8%
ValueCountFrequency (%)
37.0013678105 1
0.9%
37.004372045 1
0.9%
37.0657588099 1
0.9%
37.0657848904 1
0.9%
37.1154447219 1
0.9%
37.1282159918 2
1.8%
37.1575867433 1
0.9%
37.1599685291 1
0.9%
37.1704840136 1
0.9%
37.1863479304 1
0.9%
ValueCountFrequency (%)
38.1035057227 1
0.9%
38.0057091103 1
0.9%
37.9051489094 1
0.9%
37.9050478228 1
0.9%
37.9047627073 1
0.9%
37.8567487942 1
0.9%
37.8468825356 1
0.9%
37.8381451088 1
0.9%
37.8021908161 2
1.8%
37.8014591158 1
0.9%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct110
Distinct (%)98.2%
Missing2
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean127.03631
Minimum126.6069
Maximum127.64064
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:13:52.462477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.6069
5-th percentile126.75201
Q1126.84641
median127.0298
Q3127.14803
95-th percentile127.46399
Maximum127.64064
Range1.0337346
Interquartile range (IQR)0.30161354

Descriptive statistics

Standard deviation0.21867851
Coefficient of variation (CV)0.0017213858
Kurtosis0.39374709
Mean127.03631
Median Absolute Deviation (MAD)0.15083639
Skewness0.6954741
Sum14228.067
Variance0.04782029
MonotonicityNot monotonic
2023-12-11T07:13:52.598877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9374448187 2
 
1.8%
127.0016068883 2
 
1.8%
127.0773388139 1
 
0.9%
126.7875124505 1
 
0.9%
126.8328655054 1
 
0.9%
126.7252938339 1
 
0.9%
127.1761248957 1
 
0.9%
127.097401236 1
 
0.9%
127.1116977163 1
 
0.9%
127.1707247457 1
 
0.9%
Other values (100) 100
87.7%
(Missing) 2
 
1.8%
ValueCountFrequency (%)
126.6069018961 1
0.9%
126.7226202082 1
0.9%
126.7252938339 1
0.9%
126.7375199634 1
0.9%
126.7455759437 1
0.9%
126.7481458171 1
0.9%
126.755164903 1
0.9%
126.7604466371 1
0.9%
126.7622484517 1
0.9%
126.7627581092 1
0.9%
ValueCountFrequency (%)
127.6406364705 1
0.9%
127.6383689142 1
0.9%
127.6296355522 1
0.9%
127.5493023699 1
0.9%
127.546133394 1
0.9%
127.4912334922 1
0.9%
127.441692757 1
0.9%
127.4288728301 1
0.9%
127.4243423168 1
0.9%
127.3889531625 1
0.9%

Interactions

2023-12-11T07:13:47.420812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:46.899329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:47.167964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:47.545359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:46.982400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:47.246658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:47.657526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:47.073668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:47.332163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:13:52.700775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명우편번호WGS84위도WGS84경도
시군명1.0000.9910.9740.936
우편번호0.9911.0000.9200.703
WGS84위도0.9740.9201.0000.532
WGS84경도0.9360.7030.5321.000
2023-12-11T07:13:52.792215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호WGS84위도WGS84경도시군명
우편번호1.000-0.8940.1710.823
WGS84위도-0.8941.000-0.2080.739
WGS84경도0.171-0.2081.0000.614
시군명0.8230.7390.6141.000

Missing values

2023-12-11T07:13:47.763422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:13:47.904398image/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.
2023-12-11T07:13:48.048385image/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

시군명서비스구분명기관명도로명주소지번주소우편번호전화번호팩스번호비고WGS84위도WGS84경도
0용인시노인돌봄서비스(사)여럿이함께 푸드뱅크경기도 용인시 수지구 죽전로 150경기도 용인시 수지구 죽전동 1328-3번지 단대프라자Ⅲ 403호16889031-283-0873<NA><NA>37.323929127.1243
1수원시노인돌봄서비스SK청솔노인복지관경기도 수원시 장안구 장안로 174경기도 수원시 장안구 정자동 286번지16340031-546-8987<NA><NA>37.298985126.997296
2여주시노인돌봄서비스가남반석재가노인지원서비스센터경기도 여주시 가남읍 은봉길 116-29경기도 여주시 가남읍 은봉리 538-3번지12663031-884-8359<NA><NA>37.186348127.549302
3여주시노인돌봄서비스강북권역 노인맞춤돌봄서비스센터경기도 여주시 세종로 319-1경기도 여주시 교동 45-20번지12651031-883-9101<NA><NA>37.269099127.638369
4시흥시노인돌봄서비스거모종합사회복지관경기도 시흥시 군자로466번길 37경기도 시흥시 거모동 1738-9번지 4층15070031-493-6350<NA><NA>37.34485126.781307
5구리시노인돌봄서비스경기구리지역자활센터경기도 구리시 동구릉로136번길 90경기도 구리시 인창동 127번지 청과물동 A동 206호11916031-567-6668<NA><NA>37.610332127.145445
6부천시노인돌봄서비스경기부천나눔지역자활센터경기도 부천시 경인로224번길 36경기도 부천시 심곡본동 662-4번지14713032-323-9946<NA><NA>37.481623126.779942
7시흥시노인돌봄서비스경기시흥작은자리지역자활센터경기도 시흥시 비둘기공원7길 33경기도 시흥시 대야동 543-1번지 7층14912031-313-2733<NA><NA>37.443006126.792759
8부천시노인돌봄서비스고강종합사회복지관경기도 부천시 고리울로 79경기도 부천시 고강동 324-4번지14409032-677-9090<NA><NA>37.527055126.824843
9과천시노인돌봄서비스과천시노인복지관경기도 과천시 문원로 57경기도 과천시 문원동 15-168번지1382802-502-8500<NA><NA>37.428064127.004199
시군명서비스구분명기관명도로명주소지번주소우편번호전화번호팩스번호비고WGS84위도WGS84경도
104시흥시노인돌봄서비스함현상생종합사회복지관경기도 시흥시 함송로29번길 67경기도 시흥시 정왕동 1878-11번지15017031-434-8040<NA><NA>37.364271126.73752
105남양주시노인돌봄서비스해피누리노인복지관경기도 남양주시 호평로 6경기도 남양주시 호평동 625번지 주평강교회 502호12149031-590-3021<NA><NA>37.655466127.240518
106화성시노인돌봄서비스화성시남부노인복지관경기도 화성시 향남읍 토성로 37-22경기도 화성시 향남읍 행정리 29-2번지18590070-4881-8950<NA><NA>37.128216126.937445
107화성시노인돌봄서비스화성시동탄노인복지관경기도 화성시 동탄대로8길 36경기도 화성시 산척동 726번지 화성시동탄호수공원 어울림센터 C동 1층18501031-8077-1885<NA><NA>37.170484127.110463
108화성시노인돌봄서비스화성시서부노인복지관<NA>경기도 화성시 남양읍 시청로<NA>070-4832-6454<NA><NA><NA><NA>
109화성시노인돌봄서비스화성시서부종합사회복지관경기도 화성시 향남읍 토성로 37-22경기도 화성시 향남읍 행정리 29-2번지18590070-4422-3666<NA><NA>37.128216126.937445
110성남시노인돌봄서비스황송노인종합복지관경기도 성남시 중원구 금상로 132경기도 성남시 중원구 상대원동 279-7번지13208031-731-5520<NA><NA>37.441639127.169146
111수원시노인돌봄서비스효경의손길 재가노인지원서비스센터경기도 수원시 장안구 경수대로754번길 26-17경기도 수원시 장안구 연무동 256-2번지16221031-252-0078<NA><NA>37.29165127.024005
112고양시노인돌봄서비스효샘재가노인지원서비스센터경기도 고양시 덕양구 토당로104번길 18경기도 고양시 덕양구 토당동 295-2번지 마을회관 1층10508031-970-0361<NA><NA>37.623966126.818347
113고양시노인돌봄서비스흰돌종합사회복지관<NA>경기도 고양시 일산동구 백석동 1343번지 흰돌마을4단지아파트10448031-905-3400<NA><NA>37.642721126.784556

Duplicate rows

Most frequently occurring

시군명서비스구분명기관명도로명주소지번주소우편번호전화번호WGS84위도WGS84경도# duplicates
0양주시노인돌봄서비스열린노인복지센터경기도 양주시 백석읍 고릉말로 26경기도 양주시 백석읍 방성리 115-2번지 2층11508031-829-209137.802191127.0016072