Overview

Dataset statistics

Number of variables13
Number of observations29
Missing cells4
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory112.6 B

Variable types

Text6
Categorical3
Numeric4

Dataset

Description시설명,시설코드,시설종류명(시설유형),시설종류상세명(시설종류),자치구(시)구분,시설장명,시군구코드,시군구명,시설주소,정원(수용인원),현인원,전화번호,우편번호
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-20437/S/1/datasetView.do

Alerts

시설종류상세명(시설종류) has constant value ""Constant
자치구(시)구분 has constant value ""Constant
시군구코드 is highly overall correlated with 우편번호High correlation
정원(수용인원) is highly overall correlated with 현인원High correlation
현인원 is highly overall correlated with 정원(수용인원)High correlation
우편번호 is highly overall correlated with 시군구코드 and 1 other fieldsHigh correlation
시설종류명(시설유형) is highly overall correlated with 우편번호High correlation
정원(수용인원) has 1 (3.4%) missing valuesMissing
현인원 has 3 (10.3%) missing valuesMissing
시설코드 has unique valuesUnique
시설주소 has unique valuesUnique

Reproduction

Analysis started2024-05-10 23:59:52.981288
Analysis finished2024-05-11 00:00:04.832055
Duration11.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-05-11T00:00:05.208432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length5.1724138
Min length3

Characters and Unicode

Total characters150
Distinct characters79
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)86.2%

Sample

1st row동광모자원
2nd row성심모자원
3rd row영락모자원
4th row창신모자원
5th row평화모자원
ValueCountFrequency (%)
한남하우스 2
 
6.2%
꿈나무 2
 
6.2%
구세군디딤돌 1
 
3.1%
center 1
 
3.1%
vine 1
 
3.1%
상담소 1
 
3.1%
한부모가족 1
 
3.1%
이주배경 1
 
3.1%
도담하우스 1
 
3.1%
열린집 1
 
3.1%
Other values (20) 20
62.5%
2024-05-11T00:00:06.212862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 7
 
4.7%
모 7
 
4.7%
자 7
 
4.7%
리 5
 
3.3%
애 5
 
3.3%
란 5
 
3.3%
마 4
 
2.7%
세 4
 
2.7%
한 4
 
2.7%
스 4
 
2.7%
Other values (69) 98
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
91.3%
Lowercase Letter 8
 
5.3%
Space Separator 3
 
2.0%
Uppercase Letter 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 7
 
5.1%
모 7
 
5.1%
자 7
 
5.1%
리 5
 
3.6%
애 5
 
3.6%
란 5
 
3.6%
마 4
 
2.9%
세 4
 
2.9%
한 4
 
2.9%
스 4
 
2.9%
Other values (61) 85
62.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
37.5%
n 2
25.0%
t 1
 
12.5%
r 1
 
12.5%
i 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
V 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137
91.3%
Latin 10
 
6.7%
Common 3
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 7
 
5.1%
모 7
 
5.1%
자 7
 
5.1%
리 5
 
3.6%
애 5
 
3.6%
란 5
 
3.6%
마 4
 
2.9%
세 4
 
2.9%
한 4
 
2.9%
스 4
 
2.9%
Other values (61) 85
62.0%
Latin
ValueCountFrequency (%)
e 3
30.0%
n 2
20.0%
C 1
 
10.0%
t 1
 
10.0%
r 1
 
10.0%
V 1
 
10.0%
i 1
 
10.0%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137
91.3%
ASCII 13
 
8.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 7
 
5.1%
모 7
 
5.1%
자 7
 
5.1%
리 5
 
3.6%
애 5
 
3.6%
란 5
 
3.6%
마 4
 
2.9%
세 4
 
2.9%
한 4
 
2.9%
스 4
 
2.9%
Other values (61) 85
62.0%
ASCII
ValueCountFrequency (%)
3
23.1%
e 3
23.1%
n 2
15.4%
C 1
 
7.7%
t 1
 
7.7%
r 1
 
7.7%
V 1
 
7.7%
i 1
 
7.7%

시설코드
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-05-11T00:00:06.772098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters145
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st rowD0001
2nd rowD0002
3rd rowD0003
4th rowD0004
5th rowD0005
ValueCountFrequency (%)
d0001 1
 
3.4%
d0113 1
 
3.4%
d1038 1
 
3.4%
d1034 1
 
3.4%
d1031 1
 
3.4%
d1029 1
 
3.4%
d1025 1
 
3.4%
d1023 1
 
3.4%
d1020 1
 
3.4%
d1018 1
 
3.4%
Other values (19) 19
65.5%
2024-05-11T00:00:07.707982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 55
37.9%
1 31
21.4%
D 29
20.0%
3 7
 
4.8%
2 6
 
4.1%
4 5
 
3.4%
9 4
 
2.8%
5 3
 
2.1%
8 3
 
2.1%
6 1
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 116
80.0%
Uppercase Letter 29
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 55
47.4%
1 31
26.7%
3 7
 
6.0%
2 6
 
5.2%
4 5
 
4.3%
9 4
 
3.4%
5 3
 
2.6%
8 3
 
2.6%
6 1
 
0.9%
7 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
D 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 116
80.0%
Latin 29
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 55
47.4%
1 31
26.7%
3 7
 
6.0%
2 6
 
5.2%
4 5
 
4.3%
9 4
 
3.4%
5 3
 
2.6%
8 3
 
2.6%
6 1
 
0.9%
7 1
 
0.9%
Latin
ValueCountFrequency (%)
D 29
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 145
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 55
37.9%
1 31
21.4%
D 29
20.0%
3 7
 
4.8%
2 6
 
4.1%
4 5
 
3.4%
9 4
 
2.8%
5 3
 
2.1%
8 3
 
2.1%
6 1
 
0.7%

시설종류명(시설유형)
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
(한부모가족) 미혼모자가족복지시설(공동생활지원형)
13 
(한부모가족) 모자가족복지시설(기본생활지원형)
6 
(한부모가족) 미혼모자가족복지시설(기본생활지원형)
6 
(한부모가족) 미혼모자가족복지시설(미혼모공동생활지원형)
 
1
(한부모가족) 부자가족복지시설(공동생활지원형)
 
1
Other values (2)
2 

Length

Max length30
Median length27
Mean length26.241379
Min length18

Unique

Unique4 ?
Unique (%)13.8%

Sample

1st row(한부모가족) 모자가족복지시설(기본생활지원형)
2nd row(한부모가족) 모자가족복지시설(기본생활지원형)
3rd row(한부모가족) 모자가족복지시설(기본생활지원형)
4th row(한부모가족) 모자가족복지시설(기본생활지원형)
5th row(한부모가족) 모자가족복지시설(기본생활지원형)

Common Values

ValueCountFrequency (%)
(한부모가족) 미혼모자가족복지시설(공동생활지원형) 13
44.8%
(한부모가족) 모자가족복지시설(기본생활지원형) 6
20.7%
(한부모가족) 미혼모자가족복지시설(기본생활지원형) 6
20.7%
(한부모가족) 미혼모자가족복지시설(미혼모공동생활지원형) 1
 
3.4%
(한부모가족) 부자가족복지시설(공동생활지원형) 1
 
3.4%
(한부모가족) 부자가족복지시설(기본생활지원형) 1
 
3.4%
(한부모가족) 한부모가족복지상담소 1
 
3.4%

Length

2024-05-11T00:00:08.319824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:00:08.941896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한부모가족 29
50.0%
미혼모자가족복지시설(공동생활지원형 13
22.4%
모자가족복지시설(기본생활지원형 6
 
10.3%
미혼모자가족복지시설(기본생활지원형 6
 
10.3%
미혼모자가족복지시설(미혼모공동생활지원형 1
 
1.7%
부자가족복지시설(공동생활지원형 1
 
1.7%
부자가족복지시설(기본생활지원형 1
 
1.7%
한부모가족복지상담소 1
 
1.7%

시설종류상세명(시설종류)
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
한부모가족복지시설
29 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한부모가족복지시설 29
100.0%

Length

2024-05-11T00:00:09.464416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:00:09.736063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한부모가족복지시설 29
100.0%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
자치구
29 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자치구 29
100.0%

Length

2024-05-11T00:00:10.128488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:00:10.415276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 29
100.0%

시설장명
Text

Distinct26
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-05-11T00:00:10.879728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters87
Distinct characters46
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

Unique23 ?
Unique (%)79.3%

Sample

1st row배경희
2nd row임한길
3rd row이호진
4th row권명식
5th row변혜란
ValueCountFrequency (%)
박현주 2
 
6.9%
추남숙 2
 
6.9%
박미자 2
 
6.9%
배경희 1
 
3.4%
김지현 1
 
3.4%
이순희 1
 
3.4%
서인숙 1
 
3.4%
안경천 1
 
3.4%
정용순 1
 
3.4%
표승희 1
 
3.4%
Other values (16) 16
55.2%
2024-05-11T00:00:12.546259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
현 7
 
8.0%
박 4
 
4.6%
이 4
 
4.6%
김 4
 
4.6%
경 4
 
4.6%
숙 4
 
4.6%
희 3
 
3.4%
정 3
 
3.4%
권 3
 
3.4%
영 3
 
3.4%
Other values (36) 48
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
현 7
 
8.0%
박 4
 
4.6%
이 4
 
4.6%
김 4
 
4.6%
경 4
 
4.6%
숙 4
 
4.6%
희 3
 
3.4%
정 3
 
3.4%
권 3
 
3.4%
영 3
 
3.4%
Other values (36) 48
55.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
현 7
 
8.0%
박 4
 
4.6%
이 4
 
4.6%
김 4
 
4.6%
경 4
 
4.6%
숙 4
 
4.6%
희 3
 
3.4%
정 3
 
3.4%
권 3
 
3.4%
영 3
 
3.4%
Other values (36) 48
55.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
현 7
 
8.0%
박 4
 
4.6%
이 4
 
4.6%
김 4
 
4.6%
경 4
 
4.6%
숙 4
 
4.6%
희 3
 
3.4%
정 3
 
3.4%
권 3
 
3.4%
영 3
 
3.4%
Other values (36) 48
55.2%

시군구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1425 × 109
Minimum1.111 × 109
Maximum1.171 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-05-11T00:00:13.294127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111 × 109
5-th percentile1.117 × 109
Q11.138 × 109
median1.144 × 109
Q31.15 × 109
95-th percentile1.1578 × 109
Maximum1.171 × 109
Range60000000
Interquartile range (IQR)12000000

Descriptive statistics

Standard deviation13759412
Coefficient of variation (CV)0.012043249
Kurtosis0.35058138
Mean1.1425 × 109
Median Absolute Deviation (MAD)6000000
Skewness-0.644103
Sum3.31325 × 1010
Variance1.8932143 × 1014
MonotonicityNot monotonic
2024-05-11T00:00:13.712471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1150000000 5
17.2%
1141000000 4
13.8%
1144000000 4
13.8%
1153000000 3
10.3%
1117000000 2
 
6.9%
1129000000 2
 
6.9%
1135000000 1
 
3.4%
1111000000 1
 
3.4%
1138000000 1
 
3.4%
1159000000 1
 
3.4%
Other values (5) 5
17.2%
ValueCountFrequency (%)
1111000000 1
 
3.4%
1117000000 2
 
6.9%
1120000000 1
 
3.4%
1129000000 2
 
6.9%
1135000000 1
 
3.4%
1138000000 1
 
3.4%
1141000000 4
13.8%
1144000000 4
13.8%
1147000000 1
 
3.4%
1150000000 5
17.2%
ValueCountFrequency (%)
1171000000 1
 
3.4%
1159000000 1
 
3.4%
1156000000 1
 
3.4%
1154500000 1
 
3.4%
1153000000 3
10.3%
1150000000 5
17.2%
1147000000 1
 
3.4%
1144000000 4
13.8%
1141000000 4
13.8%
1138000000 1
 
3.4%

시군구명
Text

Distinct15
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-05-11T00:00:14.347665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.1724138
Min length3

Characters and Unicode

Total characters92
Distinct characters26
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

Unique9 ?
Unique (%)31.0%

Sample

1st row노원구
2nd row용산구
3rd row성북구
4th row구로구
5th row구로구
ValueCountFrequency (%)
강서구 5
17.2%
서대문구 4
13.8%
마포구 4
13.8%
구로구 3
10.3%
용산구 2
 
6.9%
성북구 2
 
6.9%
노원구 1
 
3.4%
종로구 1
 
3.4%
은평구 1
 
3.4%
동작구 1
 
3.4%
Other values (5) 5
17.2%
2024-05-11T00:00:15.753946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 32
34.8%
서 9
 
9.8%
강 5
 
5.4%
포 5
 
5.4%
대 4
 
4.3%
문 4
 
4.3%
마 4
 
4.3%
로 4
 
4.3%
성 3
 
3.3%
북 2
 
2.2%
Other values (16) 20
21.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 32
34.8%
서 9
 
9.8%
강 5
 
5.4%
포 5
 
5.4%
대 4
 
4.3%
문 4
 
4.3%
마 4
 
4.3%
로 4
 
4.3%
성 3
 
3.3%
북 2
 
2.2%
Other values (16) 20
21.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 32
34.8%
서 9
 
9.8%
강 5
 
5.4%
포 5
 
5.4%
대 4
 
4.3%
문 4
 
4.3%
마 4
 
4.3%
로 4
 
4.3%
성 3
 
3.3%
북 2
 
2.2%
Other values (16) 20
21.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 32
34.8%
서 9
 
9.8%
강 5
 
5.4%
포 5
 
5.4%
대 4
 
4.3%
문 4
 
4.3%
마 4
 
4.3%
로 4
 
4.3%
성 3
 
3.3%
북 2
 
2.2%
Other values (16) 20
21.7%

시설주소
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-05-11T00:00:16.596526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length35
Mean length30.206897
Min length21

Characters and Unicode

Total characters876
Distinct characters118
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row서울특별시 노원구 덕릉로 623-1 덕릉로 623-1 (중계동)
2nd row서울특별시 용산구 새창로12길 11-3성심모자원
3rd row서울특별시 성북구 솔샘로5길 47 (정릉동)
4th row서울특별시 구로구 오류로8나길 28창신모자원
5th row서울특별시 구로구 안양천로539길 18고척동
ValueCountFrequency (%)
서울특별시 29
 
19.1%
강서구 5
 
3.3%
마포구 4
 
2.6%
서대문구 4
 
2.6%
구로구 3
 
2.0%
623-1 2
 
1.3%
용산구 2
 
1.3%
성북구 2
 
1.3%
덕릉로 2
 
1.3%
공항동 2
 
1.3%
Other values (96) 97
63.8%
2024-05-11T00:00:18.107762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
123
 
14.0%
서 41
 
4.7%
구 34
 
3.9%
로 31
 
3.5%
1 30
 
3.4%
시 30
 
3.4%
2 30
 
3.4%
특 29
 
3.3%
별 29
 
3.3%
울 29
 
3.3%
Other values (108) 470
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 501
57.2%
Decimal Number 171
 
19.5%
Space Separator 123
 
14.0%
Close Punctuation 21
 
2.4%
Open Punctuation 21
 
2.4%
Dash Punctuation 20
 
2.3%
Other Punctuation 18
 
2.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 41
 
8.2%
구 34
 
6.8%
로 31
 
6.2%
시 30
 
6.0%
특 29
 
5.8%
별 29
 
5.8%
울 29
 
5.8%
동 28
 
5.6%
길 24
 
4.8%
호 9
 
1.8%
Other values (89) 217
43.3%
Decimal Number
ValueCountFrequency (%)
1 30
17.5%
2 30
17.5%
3 28
16.4%
4 20
11.7%
0 16
9.4%
5 14
8.2%
6 12
 
7.0%
8 12
 
7.0%
7 7
 
4.1%
9 2
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 20
95.2%
] 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 20
95.2%
[ 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 17
94.4%
. 1
 
5.6%
Space Separator
ValueCountFrequency (%)
123
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 501
57.2%
Common 374
42.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 41
 
8.2%
구 34
 
6.8%
로 31
 
6.2%
시 30
 
6.0%
특 29
 
5.8%
별 29
 
5.8%
울 29
 
5.8%
동 28
 
5.6%
길 24
 
4.8%
호 9
 
1.8%
Other values (89) 217
43.3%
Common
ValueCountFrequency (%)
123
32.9%
1 30
 
8.0%
2 30
 
8.0%
3 28
 
7.5%
) 20
 
5.3%
( 20
 
5.3%
- 20
 
5.3%
4 20
 
5.3%
, 17
 
4.5%
0 16
 
4.3%
Other values (8) 50
13.4%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 501
57.2%
ASCII 375
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
123
32.8%
1 30
 
8.0%
2 30
 
8.0%
3 28
 
7.5%
) 20
 
5.3%
( 20
 
5.3%
- 20
 
5.3%
4 20
 
5.3%
, 17
 
4.5%
0 16
 
4.3%
Other values (9) 51
13.6%
Hangul
ValueCountFrequency (%)
서 41
 
8.2%
구 34
 
6.8%
로 31
 
6.2%
시 30
 
6.0%
특 29
 
5.8%
별 29
 
5.8%
울 29
 
5.8%
동 28
 
5.6%
길 24
 
4.8%
호 9
 
1.8%
Other values (89) 217
43.3%

정원(수용인원)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)46.4%
Missing1
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean26.785714
Minimum10
Maximum65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-05-11T00:00:18.626374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10
Q110
median20
Q342.5
95-th percentile60
Maximum65
Range55
Interquartile range (IQR)32.5

Descriptive statistics

Standard deviation19.794045
Coefficient of variation (CV)0.73897769
Kurtosis-0.93401888
Mean26.785714
Median Absolute Deviation (MAD)10
Skewness0.83808859
Sum750
Variance391.80423
MonotonicityNot monotonic
2024-05-11T00:00:19.008489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
10 10
34.5%
20 4
 
13.8%
60 3
 
10.3%
12 2
 
6.9%
55 1
 
3.4%
40 1
 
3.4%
65 1
 
3.4%
50 1
 
3.4%
35 1
 
3.4%
52 1
 
3.4%
Other values (3) 3
 
10.3%
ValueCountFrequency (%)
10 10
34.5%
12 2
 
6.9%
15 1
 
3.4%
20 4
 
13.8%
24 1
 
3.4%
30 1
 
3.4%
35 1
 
3.4%
40 1
 
3.4%
50 1
 
3.4%
52 1
 
3.4%
ValueCountFrequency (%)
65 1
 
3.4%
60 3
10.3%
55 1
 
3.4%
52 1
 
3.4%
50 1
 
3.4%
40 1
 
3.4%
35 1
 
3.4%
30 1
 
3.4%
24 1
 
3.4%
20 4
13.8%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)73.1%
Missing3
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean19.807692
Minimum4
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-05-11T00:00:19.445293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4.5
Q18
median12
Q329.75
95-th percentile49.5
Maximum60
Range56
Interquartile range (IQR)21.75

Descriptive statistics

Standard deviation16.007546
Coefficient of variation (CV)0.80814797
Kurtosis0.22977321
Mean19.807692
Median Absolute Deviation (MAD)7
Skewness1.0917217
Sum515
Variance256.24154
MonotonicityNot monotonic
2024-05-11T00:00:19.927529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
10 3
 
10.3%
6 3
 
10.3%
8 2
 
6.9%
4 2
 
6.9%
9 2
 
6.9%
22 1
 
3.4%
20 1
 
3.4%
24 1
 
3.4%
15 1
 
3.4%
36 1
 
3.4%
Other values (9) 9
31.0%
(Missing) 3
 
10.3%
ValueCountFrequency (%)
4 2
6.9%
6 3
10.3%
7 1
 
3.4%
8 2
6.9%
9 2
6.9%
10 3
10.3%
14 1
 
3.4%
15 1
 
3.4%
20 1
 
3.4%
22 1
 
3.4%
ValueCountFrequency (%)
60 1
3.4%
50 1
3.4%
48 1
3.4%
39 1
3.4%
36 1
3.4%
33 1
3.4%
31 1
3.4%
26 1
3.4%
24 1
3.4%
22 1
3.4%

전화번호
Text

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-05-11T00:00:20.524373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10.793103
Min length9

Characters and Unicode

Total characters313
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

Unique25 ?
Unique (%)86.2%

Sample

1st row02-930-5782
2nd row02-712-5287
3rd row02-941-1970
4th row02-2612-7142
5th row02-2614-4303
ValueCountFrequency (%)
0226618805 2
 
6.9%
07089550804 2
 
6.9%
02-930-5782 1
 
3.4%
070-7547-8895 1
 
3.4%
0226710693 1
 
3.4%
027927937 1
 
3.4%
02-449-8893 1
 
3.4%
02-563-7420 1
 
3.4%
02-333-4725 1
 
3.4%
02-711-4725 1
 
3.4%
Other values (17) 17
58.6%
2024-05-11T00:00:21.793572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 52
16.6%
0 47
15.0%
- 38
12.1%
3 27
8.6%
7 25
8.0%
5 24
7.7%
4 23
7.3%
6 20
 
6.4%
1 20
 
6.4%
9 19
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 275
87.9%
Dash Punctuation 38
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 52
18.9%
0 47
17.1%
3 27
9.8%
7 25
9.1%
5 24
8.7%
4 23
8.4%
6 20
 
7.3%
1 20
 
7.3%
9 19
 
6.9%
8 18
 
6.5%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 313
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 52
16.6%
0 47
15.0%
- 38
12.1%
3 27
8.6%
7 25
8.0%
5 24
7.7%
4 23
7.3%
6 20
 
6.4%
1 20
 
6.4%
9 19
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 313
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 52
16.6%
0 47
15.0%
- 38
12.1%
3 27
8.6%
7 25
8.0%
5 24
7.7%
4 23
7.3%
6 20
 
6.4%
1 20
 
6.4%
9 19
 
6.1%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20413.034
Minimum1707
Maximum158600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-05-11T00:00:22.381637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1707
5-th percentile2828.4
Q13745
median4708
Q37722
95-th percentile149149.4
Maximum158600
Range156893
Interquartile range (IQR)3977

Descriptive statistics

Standard deviation45266.131
Coefficient of variation (CV)2.2175111
Kurtosis6.1586892
Mean20413.034
Median Absolute Deviation (MAD)2000
Skewness2.7665736
Sum591978
Variance2.0490226 × 109
MonotonicityNot monotonic
2024-05-11T00:00:22.886950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
7645 2
 
6.9%
3745 2
 
6.9%
1707 1
 
3.4%
3424 1
 
3.4%
8269 1
 
3.4%
7222 1
 
3.4%
158600 1
 
3.4%
5732 1
 
3.4%
8644 1
 
3.4%
4008 1
 
3.4%
Other values (17) 17
58.6%
ValueCountFrequency (%)
1707 1
3.4%
2708 1
3.4%
3009 1
3.4%
3424 1
3.4%
3640 1
3.4%
3721 1
3.4%
3745 2
6.9%
4002 1
3.4%
4008 1
3.4%
4044 1
3.4%
ValueCountFrequency (%)
158600 1
3.4%
157829 1
3.4%
136130 1
3.4%
8644 1
3.4%
8343 1
3.4%
8269 1
3.4%
8220 1
3.4%
7722 1
3.4%
7689 1
3.4%
7645 2
6.9%

Interactions

2024-05-11T00:00:01.759501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:59:57.260182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:59:58.861752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:00:00.248725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:00:02.090096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:59:57.721688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:59:59.236228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:00:00.643807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:00:02.409784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:59:58.121577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:59:59.567092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:00:01.191983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:00:02.866953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:59:58.456466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:59:59.862929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:00:01.474939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T00:00:23.215852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명시설코드시설종류명(시설유형)시설장명시군구코드시군구명시설주소정원(수용인원)현인원전화번호우편번호
시설명1.0001.0001.0001.0000.9760.9631.0001.0001.0001.0001.000
시설코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시설종류명(시설유형)1.0001.0001.0000.9840.4960.7181.0000.0000.7491.0000.707
시설장명1.0001.0000.9841.0000.9810.9761.0000.6980.9651.0001.000
시군구코드0.9761.0000.4960.9811.0001.0001.0000.7710.6120.9760.287
시군구명0.9631.0000.7180.9761.0001.0001.0000.0000.6780.9630.513
시설주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
정원(수용인원)1.0001.0000.0000.6980.7710.0001.0001.0000.8531.0000.000
현인원1.0001.0000.7490.9650.6120.6781.0000.8531.0001.0000.000
전화번호1.0001.0001.0001.0000.9760.9631.0001.0001.0001.0001.000
우편번호1.0001.0000.7071.0000.2870.5131.0000.0000.0001.0001.000
2024-05-11T00:00:23.545924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구코드정원(수용인원)현인원우편번호시설종류명(시설유형)
시군구코드1.000-0.436-0.2240.5990.221
정원(수용인원)-0.4361.0000.837-0.2290.000
현인원-0.2240.8371.0000.0300.450
우편번호0.599-0.2290.0301.0000.574
시설종류명(시설유형)0.2210.0000.4500.5741.000

Missing values

2024-05-11T00:00:03.284937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T00:00:04.198297image/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.
2024-05-11T00:00:04.673730image/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

시설명시설코드시설종류명(시설유형)시설종류상세명(시설종류)자치구(시)구분시설장명시군구코드시군구명시설주소정원(수용인원)현인원전화번호우편번호
0동광모자원D0001(한부모가족) 모자가족복지시설(기본생활지원형)한부모가족복지시설자치구배경희1135000000노원구서울특별시 노원구 덕릉로 623-1 덕릉로 623-1 (중계동)552602-930-57821707
1성심모자원D0002(한부모가족) 모자가족복지시설(기본생활지원형)한부모가족복지시설자치구임한길1117000000용산구서울특별시 용산구 새창로12길 11-3성심모자원403602-712-52874356
2영락모자원D0003(한부모가족) 모자가족복지시설(기본생활지원형)한부모가족복지시설자치구이호진1129000000성북구서울특별시 성북구 솔샘로5길 47 (정릉동)653902-941-19702708
3창신모자원D0004(한부모가족) 모자가족복지시설(기본생활지원형)한부모가족복지시설자치구권명식1153000000구로구서울특별시 구로구 오류로8나길 28창신모자원606002-2612-71428343
4평화모자원D0005(한부모가족) 모자가족복지시설(기본생활지원형)한부모가족복지시설자치구변혜란1153000000구로구서울특별시 구로구 안양천로539길 18고척동603302-2614-43038220
5해오름빌D0006(한부모가족) 모자가족복지시설(기본생활지원형)한부모가족복지시설자치구권수정1117000000용산구서울특별시 용산구 신흥로26길 21-3(용산동2가)503102-754-57024337
6구세군두리홈D0009(한부모가족) 미혼모자가족복지시설(기본생활지원형)한부모가족복지시설자치구추남숙1141000000서대문구서울특별시 서대문구 독립문로8길 41(천연동)35220236357223745
7애란원D0010(한부모가족) 미혼모자가족복지시설(기본생활지원형)한부모가족복지시설자치구강영실1141000000서대문구서울특별시 서대문구 연대동문길 138(대신동)52200239347253721
8애란모자의집D0011(한부모가족) 미혼모자가족복지시설(공동생활지원형)한부모가족복지시설자치구권지현1141000000서대문구서울특별시 서대문구 홍제내4길 9-7(홍제동)242402-391-47253640
9마음자리D0081(한부모가족) 미혼모자가족복지시설(기본생활지원형)한부모가족복지시설자치구윤해경1150000000강서구서울특별시 강서구 화곡로53나길 53-0201502-2691-43657689
시설명시설코드시설종류명(시설유형)시설종류상세명(시설종류)자치구(시)구분시설장명시군구코드시군구명시설주소정원(수용인원)현인원전화번호우편번호
19선재누리D1017(한부모가족) 부자가족복지시설(기본생활지원형)한부모가족복지시설자치구최삼열1120000000성동구서울특별시 성동구 무학로4길21 (도선동, 선재누리)604802-6959-68584708
20마포애란원D1018(한부모가족) 미혼모자가족복지시설(기본생활지원형)한부모가족복지시설자치구이숙영1144000000마포구서울특별시 마포구 새창로4나길5 (도화동)12802-711-47254169
21애란영스빌D1020(한부모가족) 미혼모자가족복지시설(공동생활지원형)한부모가족복지시설자치구표승희1144000000마포구서울특별시 마포구 희우정로20길 44-13 (망원동, 진성파크빌)20602-333-47254008
22열린집D1023(한부모가족) 미혼모자가족복지시설(공동생활지원형)한부모가족복지시설자치구정용순1154500000금천구서울특별시 금천구 금하로 714-20602호 (시흥동, 드림하우스)12402-563-74208644
23도담하우스D1025(한부모가족) 미혼모자가족복지시설(기본생활지원형)한부모가족복지시설자치구안경천1171000000송파구서울특별시 송파구 성내천로23가길 6-4 (마천동)101002-449-88935732
24이주배경 한부모가족 상담소D1029(한부모가족) 한부모가족복지상담소한부모가족복지시설자치구서인숙1147000000양천구서울특별시 양천구 월정로48길 15-2, 1.2층 (신월동)<NA>50027927937158600
25Vine CenterD1031(한부모가족) 미혼모자가족복지시설(기본생활지원형)한부모가족복지시설자치구이순희1156000000영등포구서울특별시 영등포구 양평로12가길 8 (당산동6가)10802267106937222
26한남하우스D1034(한부모가족) 미혼모자가족복지시설(공동생활지원형)한부모가족복지시설자치구박현주1150000000강서구서울특별시 강서구 방화대로6가길 34, 3층 302호, 4층 (공항동)10<NA>02266188057645
27꿈나무D1038(한부모가족) 미혼모자가족복지시설(공동생활지원형)한부모가족복지시설자치구박미자1153000000구로구서울특별시 구로구 고척로6길33, B동 201호 (오류동, 로하스빌)10<NA>070895508048269
28한남하우스D1040(한부모가족) 미혼모자가족복지시설(공동생활지원형)한부모가족복지시설자치구박현주1150000000강서구서울특별시 강서구 방화대로6가길34, 4,5층 (공항동)10<NA>02266188057645