Overview

Dataset statistics

Number of variables11
Number of observations26
Missing cells18
Missing cells (%)6.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory96.1 B

Variable types

Text7
Categorical1
Numeric3

Alerts

소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
사례팀명 has 1 (3.8%) missing valuesMissing
자원팀명 has 17 (65.4%) missing valuesMissing
시군명 has unique valuesUnique
센터명 has unique valuesUnique
전화번호 has unique valuesUnique
소재지우편번호 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique

Reproduction

Analysis started2024-04-29 13:19:14.684061
Analysis finished2024-04-29 13:19:17.751518
Duration3.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-04-29T22:19:17.880272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0769231
Min length3

Characters and Unicode

Total characters80
Distinct characters33
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

Unique26 ?
Unique (%)100.0%

Sample

1st row가평군
2nd row고양시
3rd row광명시
4th row광주시
5th row구리시
ValueCountFrequency (%)
가평군 1
 
3.8%
고양시 1
 
3.8%
포천시 1
 
3.8%
파주시 1
 
3.8%
이천시 1
 
3.8%
의왕시 1
 
3.8%
용인시 1
 
3.8%
연천군 1
 
3.8%
여주시 1
 
3.8%
양평군 1
 
3.8%
Other values (16) 16
61.5%
2024-04-29T22:19:18.181783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 24
30.0%
천 5
 
6.2%
주 5
 
6.2%
양 5
 
6.2%
군 4
 
5.0%
남 3
 
3.8%
포 3
 
3.8%
안 3
 
3.8%
광 2
 
2.5%
평 2
 
2.5%
Other values (23) 24
30.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 24
30.0%
천 5
 
6.2%
주 5
 
6.2%
양 5
 
6.2%
군 4
 
5.0%
남 3
 
3.8%
포 3
 
3.8%
안 3
 
3.8%
광 2
 
2.5%
평 2
 
2.5%
Other values (23) 24
30.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 24
30.0%
천 5
 
6.2%
주 5
 
6.2%
양 5
 
6.2%
군 4
 
5.0%
남 3
 
3.8%
포 3
 
3.8%
안 3
 
3.8%
광 2
 
2.5%
평 2
 
2.5%
Other values (23) 24
30.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 24
30.0%
천 5
 
6.2%
주 5
 
6.2%
양 5
 
6.2%
군 4
 
5.0%
남 3
 
3.8%
포 3
 
3.8%
안 3
 
3.8%
광 2
 
2.5%
평 2
 
2.5%
Other values (23) 24
30.0%

센터명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-04-29T22:19:18.354845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length9.2692308
Min length9

Characters and Unicode

Total characters241
Distinct characters44
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

Unique26 ?
Unique (%)100.0%

Sample

1st row가평군무한돌봄센터
2nd row고양시무한돌봄센터
3rd row광명시무한돌봄센터
4th row광주시무한돌봄센터
5th row구리시무한돌봄센터
ValueCountFrequency (%)
가평군무한돌봄센터 1
 
3.8%
고양시무한돌봄센터 1
 
3.8%
포천시무한돌봄센터 1
 
3.8%
파주시무한돌봄센터 1
 
3.8%
이천시무한돌봄센터 1
 
3.8%
의왕시무한돌봄센터 1
 
3.8%
용인시무한돌봄센터 1
 
3.8%
연천군무한돌봄센터 1
 
3.8%
여주시무한돌봄센터 1
 
3.8%
양평군무한돌봄센터 1
 
3.8%
Other values (16) 16
61.5%
2024-04-29T22:19:18.656654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
무 26
10.8%
한 26
10.8%
돌 26
10.8%
봄 26
10.8%
센 26
10.8%
터 26
10.8%
시 24
10.0%
천 5
 
2.1%
양 5
 
2.1%
주 5
 
2.1%
Other values (34) 46
19.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 241
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
무 26
10.8%
한 26
10.8%
돌 26
10.8%
봄 26
10.8%
센 26
10.8%
터 26
10.8%
시 24
10.0%
천 5
 
2.1%
양 5
 
2.1%
주 5
 
2.1%
Other values (34) 46
19.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 241
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
무 26
10.8%
한 26
10.8%
돌 26
10.8%
봄 26
10.8%
센 26
10.8%
터 26
10.8%
시 24
10.0%
천 5
 
2.1%
양 5
 
2.1%
주 5
 
2.1%
Other values (34) 46
19.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 241
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
무 26
10.8%
한 26
10.8%
돌 26
10.8%
봄 26
10.8%
센 26
10.8%
터 26
10.8%
시 24
10.0%
천 5
 
2.1%
양 5
 
2.1%
주 5
 
2.1%
Other values (34) 46
19.1%

전화번호
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-04-29T22:19:18.835241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.115385
Min length12

Characters and Unicode

Total characters315
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

Unique26 ?
Unique (%)100.0%

Sample

1st row031-580-2255
2nd row031-8075-3604
3rd row02-2680-6508
4th row031-760-5947
5th row031-550-8333
ValueCountFrequency (%)
031-580-2255 1
 
3.8%
031-8075-3604 1
 
3.8%
031-538-3077 1
 
3.8%
031-940-8581 1
 
3.8%
031-645-3529 1
 
3.8%
031-345-3936 1
 
3.8%
031-324-3855 1
 
3.8%
031-839-2461 1
 
3.8%
031-887-2888 1
 
3.8%
031-770-2143 1
 
3.8%
Other values (16) 16
61.5%
2024-04-29T22:19:19.150291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 52
16.5%
3 49
15.6%
0 47
14.9%
1 32
10.2%
8 29
9.2%
2 28
8.9%
5 26
8.3%
6 17
 
5.4%
7 13
 
4.1%
4 11
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 263
83.5%
Dash Punctuation 52
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 49
18.6%
0 47
17.9%
1 32
12.2%
8 29
11.0%
2 28
10.6%
5 26
9.9%
6 17
 
6.5%
7 13
 
4.9%
4 11
 
4.2%
9 11
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 315
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 52
16.5%
3 49
15.6%
0 47
14.9%
1 32
10.2%
8 29
9.2%
2 28
8.9%
5 26
8.3%
6 17
 
5.4%
7 13
 
4.1%
4 11
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 315
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 52
16.5%
3 49
15.6%
0 47
14.9%
1 32
10.2%
8 29
9.2%
2 28
8.9%
5 26
8.3%
6 17
 
5.4%
7 13
 
4.1%
4 11
 
3.5%

담당부서명
Categorical

Distinct11
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Memory size340.0 B
복지정책과
16 
찾아가는복지과
 
1
아동복지과
 
1
복지과
 
1
통합돌봄과
 
1
Other values (6)
6 

Length

Max length7
Median length5
Mean length5
Min length3

Unique

Unique10 ?
Unique (%)38.5%

Sample

1st row복지정책과
2nd row찾아가는복지과
3rd row복지정책과
4th row아동복지과
5th row복지정책과

Common Values

ValueCountFrequency (%)
복지정책과 16
61.5%
찾아가는복지과 1
 
3.8%
아동복지과 1
 
3.8%
복지과 1
 
3.8%
통합돌봄과 1
 
3.8%
복지협력과 1
 
3.8%
사회복지과 1
 
3.8%
지역돌봄과 1
 
3.8%
복지행정과 1
 
3.8%
복지정채과 1
 
3.8%

Length

2024-04-29T22:19:19.291879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
복지정책과 16
61.5%
찾아가는복지과 1
 
3.8%
아동복지과 1
 
3.8%
복지과 1
 
3.8%
통합돌봄과 1
 
3.8%
복지협력과 1
 
3.8%
사회복지과 1
 
3.8%
지역돌봄과 1
 
3.8%
복지행정과 1
 
3.8%
복지정채과 1
 
3.8%

사례팀명
Text

MISSING 

Distinct13
Distinct (%)52.0%
Missing1
Missing (%)3.8%
Memory size340.0 B
2024-04-29T22:19:19.438238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.48
Min length5

Characters and Unicode

Total characters137
Distinct characters29
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

Unique11 ?
Unique (%)44.0%

Sample

1st row희망나눔팀
2nd row희망복지정책팀
3rd row사례관리지원팀
4th row복지지원팀
5th row희망복지팀
ValueCountFrequency (%)
희망복지팀 12
48.0%
무한돌봄팀 2
 
8.0%
희망나눔팀 1
 
4.0%
희망복지정책팀 1
 
4.0%
사례관리지원팀 1
 
4.0%
복지지원팀 1
 
4.0%
통합돌봄팀 1
 
4.0%
사례관리팀 1
 
4.0%
휴먼복지지원팀 1
 
4.0%
무한돌봄센터팀 1
 
4.0%
Other values (3) 3
 
12.0%
2024-04-29T22:19:19.713170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
팀 25
18.2%
지 22
16.1%
복 18
13.1%
희 14
10.2%
망 14
10.2%
돌 4
 
2.9%
봄 4
 
2.9%
원 4
 
2.9%
무 3
 
2.2%
한 3
 
2.2%
Other values (19) 26
19.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
팀 25
18.2%
지 22
16.1%
복 18
13.1%
희 14
10.2%
망 14
10.2%
돌 4
 
2.9%
봄 4
 
2.9%
원 4
 
2.9%
무 3
 
2.2%
한 3
 
2.2%
Other values (19) 26
19.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
팀 25
18.2%
지 22
16.1%
복 18
13.1%
희 14
10.2%
망 14
10.2%
돌 4
 
2.9%
봄 4
 
2.9%
원 4
 
2.9%
무 3
 
2.2%
한 3
 
2.2%
Other values (19) 26
19.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
팀 25
18.2%
지 22
16.1%
복 18
13.1%
희 14
10.2%
망 14
10.2%
돌 4
 
2.9%
봄 4
 
2.9%
원 4
 
2.9%
무 3
 
2.2%
한 3
 
2.2%
Other values (19) 26
19.0%

자원팀명
Text

MISSING 

Distinct8
Distinct (%)88.9%
Missing17
Missing (%)65.4%
Memory size340.0 B
2024-04-29T22:19:19.862834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.8888889
Min length5

Characters and Unicode

Total characters53
Distinct characters23
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

Unique7 ?
Unique (%)77.8%

Sample

1st row찾아가는복지팀
2nd row나눔복지팀
3rd row복지조사관리팀
4th row융합서비스팀
5th row복지지원팀
ValueCountFrequency (%)
복지지원팀 2
22.2%
찾아가는복지팀 1
11.1%
나눔복지팀 1
11.1%
복지조사관리팀 1
11.1%
융합서비스팀 1
11.1%
복지자원관리팀 1
11.1%
복지자원팀 1
11.1%
안양형복지팀 1
11.1%
2024-04-29T22:19:20.137671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 10
18.9%
팀 9
17.0%
복 8
15.1%
원 4
 
7.5%
자 2
 
3.8%
관 2
 
3.8%
리 2
 
3.8%
융 1
 
1.9%
양 1
 
1.9%
안 1
 
1.9%
Other values (13) 13
24.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 10
18.9%
팀 9
17.0%
복 8
15.1%
원 4
 
7.5%
자 2
 
3.8%
관 2
 
3.8%
리 2
 
3.8%
융 1
 
1.9%
양 1
 
1.9%
안 1
 
1.9%
Other values (13) 13
24.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 10
18.9%
팀 9
17.0%
복 8
15.1%
원 4
 
7.5%
자 2
 
3.8%
관 2
 
3.8%
리 2
 
3.8%
융 1
 
1.9%
양 1
 
1.9%
안 1
 
1.9%
Other values (13) 13
24.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 10
18.9%
팀 9
17.0%
복 8
15.1%
원 4
 
7.5%
자 2
 
3.8%
관 2
 
3.8%
리 2
 
3.8%
융 1
 
1.9%
양 1
 
1.9%
안 1
 
1.9%
Other values (13) 13
24.5%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13503.5
Minimum10109
Maximum17586
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-04-29T22:19:20.275266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10109
5-th percentile10578
Q111608.5
median12844.5
Q315250.75
95-th percentile17289
Maximum17586
Range7477
Interquartile range (IQR)3642.25

Descriptive statistics

Standard deviation2274.6435
Coefficient of variation (CV)0.16844844
Kurtosis-1.0606029
Mean13503.5
Median Absolute Deviation (MAD)1700
Skewness0.373822
Sum351091
Variance5174002.9
MonotonicityNot monotonic
2024-04-29T22:19:20.384598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
12417 1
 
3.8%
17586 1
 
3.8%
12951 1
 
3.8%
11147 1
 
3.8%
10932 1
 
3.8%
17379 1
 
3.8%
16075 1
 
3.8%
17019 1
 
3.8%
11017 1
 
3.8%
12619 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
10109 1
3.8%
10460 1
3.8%
10932 1
3.8%
11017 1
3.8%
11147 1
3.8%
11317 1
3.8%
11498 1
3.8%
11940 1
3.8%
12232 1
3.8%
12417 1
3.8%
ValueCountFrequency (%)
17586 1
3.8%
17379 1
3.8%
17019 1
3.8%
16668 1
3.8%
16075 1
3.8%
15829 1
3.8%
15335 1
3.8%
14998 1
3.8%
14547 1
3.8%
14234 1
3.8%

소재지지번주소
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-04-29T22:19:20.611825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length31.5
Mean length28.346154
Min length17

Characters and Unicode

Total characters737
Distinct characters109
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

Unique26 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 보납로 31(가평군청,복지정책과)
2nd row경기도 고양시 덕양구 주교동 600번지 고양시청
3rd row경기도 광명시 철산동 222-1번지 광명시청 복지정책과
4th row경기도 광주시 송정동 570번지 광주시청 희망복지과
5th row경기도 구리시 수택동 848번지 행정복지센터 무한돌봄과
ValueCountFrequency (%)
경기도 26
 
17.0%
복지정책과 8
 
5.2%
희망복지과 2
 
1.3%
안양시청 1
 
0.7%
홍문동 1
 
0.7%
여주시 1
 
0.7%
행복돌봄과 1
 
0.7%
양평군청 1
 
0.7%
448-8번지 1
 
0.7%
양근리 1
 
0.7%
Other values (110) 110
71.9%
2024-04-29T22:19:20.974345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
 
17.2%
시 44
 
6.0%
지 42
 
5.7%
동 28
 
3.8%
경 26
 
3.5%
도 26
 
3.5%
기 26
 
3.5%
번 25
 
3.4%
청 21
 
2.8%
1 19
 
2.6%
Other values (99) 353
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 509
69.1%
Space Separator 127
 
17.2%
Decimal Number 86
 
11.7%
Dash Punctuation 10
 
1.4%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 44
 
8.6%
지 42
 
8.3%
동 28
 
5.5%
경 26
 
5.1%
도 26
 
5.1%
기 26
 
5.1%
번 25
 
4.9%
청 21
 
4.1%
과 16
 
3.1%
복 16
 
3.1%
Other values (84) 239
47.0%
Decimal Number
ValueCountFrequency (%)
1 19
22.1%
0 12
14.0%
2 11
12.8%
5 11
12.8%
4 9
10.5%
8 8
9.3%
3 6
 
7.0%
6 4
 
4.7%
9 4
 
4.7%
7 2
 
2.3%
Space Separator
ValueCountFrequency (%)
127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 509
69.1%
Common 228
30.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 44
 
8.6%
지 42
 
8.3%
동 28
 
5.5%
경 26
 
5.1%
도 26
 
5.1%
기 26
 
5.1%
번 25
 
4.9%
청 21
 
4.1%
과 16
 
3.1%
복 16
 
3.1%
Other values (84) 239
47.0%
Common
ValueCountFrequency (%)
127
55.7%
1 19
 
8.3%
0 12
 
5.3%
2 11
 
4.8%
5 11
 
4.8%
- 10
 
4.4%
4 9
 
3.9%
8 8
 
3.5%
3 6
 
2.6%
6 4
 
1.8%
Other values (5) 11
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 509
69.1%
ASCII 228
30.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
55.7%
1 19
 
8.3%
0 12
 
5.3%
2 11
 
4.8%
5 11
 
4.8%
- 10
 
4.4%
4 9
 
3.9%
8 8
 
3.5%
3 6
 
2.6%
6 4
 
1.8%
Other values (5) 11
 
4.8%
Hangul
ValueCountFrequency (%)
시 44
 
8.6%
지 42
 
8.3%
동 28
 
5.5%
경 26
 
5.1%
도 26
 
5.1%
기 26
 
5.1%
번 25
 
4.9%
청 21
 
4.1%
과 16
 
3.1%
복 16
 
3.1%
Other values (84) 239
47.0%

소재지도로명주소
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-04-29T22:19:21.216805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length35.5
Mean length28.923077
Min length13

Characters and Unicode

Total characters752
Distinct characters116
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 보납로 31(가평군청,복지정책과)
2nd row경기도 고양시 덕양구 고양시청로 10, 고양시청
3rd row경기도 광명시 시청로 20. 광명시청 복지정책과
4th row경기도 광주시 행정타운로 50(송정동, 광주시청 희망복지과)
5th row경기도 구리시 체육관로 74, 행정복지센터 무한돌봄과(수택동)
ValueCountFrequency (%)
경기도 26
 
17.4%
복지정책과 6
 
4.0%
시청로 3
 
2.0%
20 2
 
1.3%
양주시청 1
 
0.7%
부흥로 1
 
0.7%
1533 1
 
0.7%
남방동 1
 
0.7%
양평군 1
 
0.7%
안양시청 1
 
0.7%
Other values (106) 106
71.1%
2024-04-29T22:19:21.574268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
123
 
16.4%
시 51
 
6.8%
청 30
 
4.0%
경 27
 
3.6%
기 26
 
3.5%
도 26
 
3.5%
로 23
 
3.1%
) 18
 
2.4%
( 18
 
2.4%
지 17
 
2.3%
Other values (106) 393
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 509
67.7%
Space Separator 123
 
16.4%
Decimal Number 65
 
8.6%
Other Punctuation 19
 
2.5%
Close Punctuation 18
 
2.4%
Open Punctuation 18
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 51
 
10.0%
청 30
 
5.9%
경 27
 
5.3%
기 26
 
5.1%
도 26
 
5.1%
로 23
 
4.5%
지 17
 
3.3%
과 16
 
3.1%
복 16
 
3.1%
동 16
 
3.1%
Other values (91) 261
51.3%
Decimal Number
ValueCountFrequency (%)
1 15
23.1%
2 10
15.4%
0 10
15.4%
3 7
10.8%
9 6
 
9.2%
5 5
 
7.7%
7 5
 
7.7%
4 4
 
6.2%
8 2
 
3.1%
6 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 17
89.5%
. 2
 
10.5%
Space Separator
ValueCountFrequency (%)
123
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 509
67.7%
Common 243
32.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 51
 
10.0%
청 30
 
5.9%
경 27
 
5.3%
기 26
 
5.1%
도 26
 
5.1%
로 23
 
4.5%
지 17
 
3.3%
과 16
 
3.1%
복 16
 
3.1%
동 16
 
3.1%
Other values (91) 261
51.3%
Common
ValueCountFrequency (%)
123
50.6%
) 18
 
7.4%
( 18
 
7.4%
, 17
 
7.0%
1 15
 
6.2%
2 10
 
4.1%
0 10
 
4.1%
3 7
 
2.9%
9 6
 
2.5%
5 5
 
2.1%
Other values (5) 14
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 509
67.7%
ASCII 243
32.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
123
50.6%
) 18
 
7.4%
( 18
 
7.4%
, 17
 
7.0%
1 15
 
6.2%
2 10
 
4.1%
0 10
 
4.1%
3 7
 
2.9%
9 6
 
2.5%
5 5
 
2.1%
Other values (5) 14
 
5.8%
Hangul
ValueCountFrequency (%)
시 51
 
10.0%
청 30
 
5.9%
경 27
 
5.3%
기 26
 
5.1%
도 26
 
5.1%
로 23
 
4.5%
지 17
 
3.3%
과 16
 
3.1%
복 16
 
3.1%
동 16
 
3.1%
Other values (91) 261
51.3%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.519441
Minimum37.008436
Maximum38.096517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-04-29T22:19:21.698347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.008436
5-th percentile37.241653
Q137.349353
median37.485439
Q337.652981
95-th percentile37.901378
Maximum38.096517
Range1.0880802
Interquartile range (IQR)0.30362838

Descriptive statistics

Standard deviation0.25052125
Coefficient of variation (CV)0.006677105
Kurtosis-0.027243694
Mean37.519441
Median Absolute Deviation (MAD)0.15701107
Skewness0.40048317
Sum975.50546
Variance0.062760895
MonotonicityNot monotonic
2024-04-29T22:19:21.825206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
37.8312936704 1
 
3.8%
37.0084364158 1
 
3.8%
37.5392759713 1
 
3.8%
37.8946984341 1
 
3.8%
37.7594890632 1
 
3.8%
37.2721453977 1
 
3.8%
37.3452361445 1
 
3.8%
37.2407024165 1
 
3.8%
38.0965166652 1
 
3.8%
37.2982159296 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
37.0084364158 1
3.8%
37.2407024165 1
3.8%
37.2445060675 1
3.8%
37.2721453977 1
3.8%
37.2982159296 1
3.8%
37.322669894 1
3.8%
37.3452361445 1
3.8%
37.3617039781 1
3.8%
37.3802568167 1
3.8%
37.395206289 1
3.8%
ValueCountFrequency (%)
38.0965166652 1
3.8%
37.9036051104 1
3.8%
37.8946984341 1
3.8%
37.8312936704 1
3.8%
37.7860842773 1
3.8%
37.7594890632 1
3.8%
37.6584112959 1
3.8%
37.6366920245 1
3.8%
37.6148826054 1
3.8%
37.5914726758 1
3.8%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.0905
Minimum126.71569
Maximum127.63663
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-04-29T22:19:21.944659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.71569
5-th percentile126.76915
Q1126.88231
median127.06776
Q3127.21676
95-th percentile127.50408
Maximum127.63663
Range0.92093335
Interquartile range (IQR)0.33444261

Descriptive statistics

Standard deviation0.24818878
Coefficient of variation (CV)0.0019528507
Kurtosis-0.43376689
Mean127.0905
Median Absolute Deviation (MAD)0.16852308
Skewness0.46046253
Sum3304.353
Variance0.061597669
MonotonicityNot monotonic
2024-04-29T22:19:22.063885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
127.5097161526 1
 
3.8%
127.2792872356 1
 
3.8%
127.2145359087 1
 
3.8%
127.2003394909 1
 
3.8%
126.7805607607 1
 
3.8%
127.435042525 1
 
3.8%
126.9686952702 1
 
3.8%
127.1792150942 1
 
3.8%
127.0752280078 1
 
3.8%
127.6366282067 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
126.715694858 1
3.8%
126.7653515249 1
3.8%
126.7805607607 1
3.8%
126.8040790718 1
3.8%
126.8309421906 1
3.8%
126.8319654608 1
3.8%
126.8652005766 1
3.8%
126.9336513174 1
3.8%
126.9582878965 1
3.8%
126.9686952702 1
3.8%
ValueCountFrequency (%)
127.6366282067 1
3.8%
127.5097161526 1
3.8%
127.4871719211 1
3.8%
127.435042525 1
3.8%
127.2792872356 1
3.8%
127.2550789677 1
3.8%
127.2174958647 1
3.8%
127.2145359087 1
3.8%
127.2003394909 1
3.8%
127.1792150942 1
3.8%

Interactions

2024-04-29T22:19:17.195155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:19:16.634085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:19:16.957403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:19:17.280240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:19:16.793714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:19:17.044571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:19:17.357786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:19:16.877672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:19:17.118325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-29T22:19:22.149695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명센터명전화번호담당부서명사례팀명자원팀명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
센터명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
담당부서명1.0001.0001.0001.0000.0000.6720.4011.0001.0000.3920.000
사례팀명1.0001.0001.0000.0001.0001.0000.7671.0001.0000.0000.000
자원팀명1.0001.0001.0000.6721.0001.0001.0001.0001.0001.0000.802
소재지우편번호1.0001.0001.0000.4010.7671.0001.0001.0001.0000.4570.746
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
WGS84위도1.0001.0001.0000.3920.0001.0000.4571.0001.0001.0000.391
WGS84경도1.0001.0001.0000.0000.0000.8020.7461.0001.0000.3911.000
2024-04-29T22:19:22.276732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도담당부서명
소재지우편번호1.000-0.8800.1100.000
WGS84위도-0.8801.000-0.1000.098
WGS84경도0.110-0.1001.0000.000
담당부서명0.0000.0980.0001.000

Missing values

2024-04-29T22:19:17.456074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-29T22:19:17.591258image/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.
2024-04-29T22:19:17.703659image/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

시군명센터명전화번호담당부서명사례팀명자원팀명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
0가평군가평군무한돌봄센터031-580-2255복지정책과희망나눔팀<NA>12417경기도 가평군 가평읍 보납로 31(가평군청,복지정책과)경기도 가평군 가평읍 보납로 31(가평군청,복지정책과)37.831294127.509716
1고양시고양시무한돌봄센터031-8075-3604찾아가는복지과희망복지정책팀찾아가는복지팀10460경기도 고양시 덕양구 주교동 600번지 고양시청경기도 고양시 덕양구 고양시청로 10, 고양시청37.658411126.831965
2광명시광명시무한돌봄센터02-2680-6508복지정책과사례관리지원팀나눔복지팀14234경기도 광명시 철산동 222-1번지 광명시청 복지정책과경기도 광명시 시청로 20. 광명시청 복지정책과37.478975126.865201
3광주시광주시무한돌봄센터031-760-5947아동복지과복지지원팀<NA>12738경기도 광주시 송정동 570번지 광주시청 희망복지과경기도 광주시 행정타운로 50(송정동, 광주시청 희망복지과)37.42931127.255079
4구리시구리시무한돌봄센터031-550-8333복지정책과희망복지팀<NA>11940경기도 구리시 수택동 848번지 행정복지센터 무한돌봄과경기도 구리시 체육관로 74, 행정복지센터 무한돌봄과(수택동)37.591473127.138625
5군포시군포시무한돌봄센터031-390-0638복지정책과희망복지팀복지조사관리팀15829경기도 군포시 금정동 844번지 군포시청 복지정책과경기도 군포시 청백리길 6. 군포시청(복지정책과)37.361704126.933651
6김포시김포시무한돌봄센터031-980-2632복지과희망복지팀<NA>10109경기도 김포시 사우동 263-1번지 김포시청경기도 김포시 사우중로 1, (사우동, 김포시청)37.614883126.715695
7남양주시남양주시무한돌봄센터031-590-8856복지정책과통합돌봄팀융합서비스팀12232경기도 남양주시 금곡동 185-10번지 남양주시청제1청사 희망복지과경기도 남양주시 경춘로 1037 희망복지과(금곡동, 남양주시청제1청사)37.636692127.217496
8동두천시동두천시무한돌봄센터031-860-2362복지정책과희망복지팀복지지원팀11317경기도 동두천시 생연동 438번지 동두천시청 주민생활지원과경기도 동두천시 방죽로 23(동두천시청,주민생활지원과)37.903605127.060301
9부천시부천시무한돌봄센터032-625-9032통합돌봄과사례관리팀<NA>14547경기도 부천시 원미구 중동 1156번지경기도 부천시 원미구 길주로 21037.50358126.765352
시군명센터명전화번호담당부서명사례팀명자원팀명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
16양주시양주시무한돌봄센터031-8082-5752사회복지과무한돌봄팀<NA>11498경기도 양주시 남방동 1-1번지 양주시청경기도 양주시 부흥로 1533 (남방동) 양주시청37.786084127.0462
17양평군양평군무한돌봄센터031-770-2143지역돌봄과희망복지팀<NA>12554경기도 양평군 양평읍 양근리 448-8번지 양평군청 행복돌봄과경기도 양평군 양평읍 군청앞길 2, (양평군청 행복돌봄과)37.491902127.487172
18여주시여주시무한돌봄센터031-887-2888복지행정과희망복지팀<NA>12619경기도 여주시 홍문동 4번지 여주시청 무한돌봄센터경기도 여주시 세종로 1(홍문동) 여주시청 무한돌봄센터37.298216127.636628
19연천군연천군무한돌봄센터031-839-2461복지정채과희망복지팀<NA>11017경기도 연천군 연천읍 차탄리 290-1번지 복지지원과경기도 연천군 연천읍 연천로 220 복지지원과38.096517127.075228
20용인시용인시무한돌봄센터031-324-3855복지정책과나눔복지팀<NA>17019경기도 용인시 처인구 삼가동 556번지 용인시청 복지정책과경기도 용인시 처인구 중부대로 1199(삼가동, 용인시청 복지정책과)37.240702127.179215
21의왕시의왕시무한돌봄센터031-345-3936복지정책과청계복지관팀<NA>16075경기도 의왕시 고천동 171번지경기도 의왕시 시청로11(고천동)37.345236126.968695
22이천시이천시무한돌봄센터031-645-3529복지정책과희망복지팀<NA>17379경기도 이천시 중리동 490번지 이천시청 복지정책과경기도 이천시 부악로 40, 이천시청 복지정책과37.272145127.435043
23파주시파주시무한돌봄센터031-940-8581복지정책과맞춤형복지지원팀<NA>10932경기도 파주시 아동동 215-1번지 파주시청 복지정책과경기도 파주시 시청로 50, 파주시청 복지정책과37.759489126.780561
24포천시포천시무한돌봄센터031-538-3077시민복지과희망복지팀복지지원팀11147경기도 포천시 신읍동 58-2번지경기도 포천시 중앙로8737.894698127.200339
25하남시하남시무한돌봄센터031-790-5536복지정책과희망복지팀<NA>12951경기도 하남시 신장동 520번지 하남시청경기도 하남시 대청로 10(신장동) 하남시청37.539276127.214536