Overview

Dataset statistics

Number of variables13
Number of observations935
Missing cells410
Missing cells (%)3.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory97.8 KiB
Average record size in memory107.1 B

Variable types

Text6
Categorical4
Numeric3

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-20420/S/1/datasetView.do

Alerts

시설종류상세명(시설종류) has constant value ""Constant
자치구(시)구분 has constant value ""Constant
시군구코드 is highly overall correlated with 시군구명High correlation
정원(수용인원) is highly overall correlated with 현인원High correlation
현인원 is highly overall correlated with 정원(수용인원)High correlation
시군구명 is highly overall correlated with 시군구코드High correlation
시설종류명(시설유형) is highly imbalanced (52.9%)Imbalance
정원(수용인원) has 51 (5.5%) missing valuesMissing
현인원 has 350 (37.4%) missing valuesMissing
시설코드 has unique valuesUnique

Reproduction

Analysis started2024-04-18 07:08:40.832807
Analysis finished2024-04-18 07:08:42.867040
Duration2.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct811
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2024-04-18T16:08:43.101824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length10.882353
Min length2

Characters and Unicode

Total characters10175
Distinct characters407
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique706 ?
Unique (%)75.5%

Sample

1st row구세군서울후생원
2nd row남산원
3rd row송죽원
4th row강동꿈마을
5th row리라아동복지관
ValueCountFrequency (%)
우리동네키움센터 140
 
10.3%
지역아동센터 43
 
3.2%
서울특별시 22
 
1.6%
송파키움센터 18
 
1.3%
중구 15
 
1.1%
아이휴센터 13
 
1.0%
학교돌봄터(중구형 8
 
0.6%
초등돌봄 8
 
0.6%
서대문구 7
 
0.5%
강북구 7
 
0.5%
Other values (864) 1074
79.3%
2024-04-18T16:08:43.551735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 886
 
8.7%
터 821
 
8.1%
센 767
 
7.5%
아 639
 
6.3%
지 587
 
5.8%
역 533
 
5.2%
422
 
4.1%
리 220
 
2.2%
키 192
 
1.9%
움 190
 
1.9%
Other values (397) 4918
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9405
92.4%
Space Separator 422
 
4.1%
Decimal Number 210
 
2.1%
Open Punctuation 49
 
0.5%
Close Punctuation 49
 
0.5%
Uppercase Letter 19
 
0.2%
Lowercase Letter 9
 
0.1%
Math Symbol 6
 
0.1%
Other Punctuation 5
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 886
 
9.4%
터 821
 
8.7%
센 767
 
8.2%
아 639
 
6.8%
지 587
 
6.2%
역 533
 
5.7%
리 220
 
2.3%
키 192
 
2.0%
움 190
 
2.0%
우 186
 
2.0%
Other values (358) 4384
46.6%
Uppercase Letter
ValueCountFrequency (%)
S 4
21.1%
O 3
15.8%
L 2
10.5%
C 2
10.5%
U 1
 
5.3%
H 1
 
5.3%
V 1
 
5.3%
I 1
 
5.3%
E 1
 
5.3%
A 1
 
5.3%
Other values (2) 2
10.5%
Decimal Number
ValueCountFrequency (%)
1 60
28.6%
2 41
19.5%
3 28
13.3%
5 21
 
10.0%
4 18
 
8.6%
6 13
 
6.2%
7 11
 
5.2%
8 8
 
3.8%
9 5
 
2.4%
0 5
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
e 3
33.3%
l 2
22.2%
i 1
 
11.1%
n 1
 
11.1%
d 1
 
11.1%
h 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
: 1
20.0%
, 1
20.0%
. 1
20.0%
' 1
20.0%
& 1
20.0%
Math Symbol
ValueCountFrequency (%)
> 3
50.0%
< 3
50.0%
Space Separator
ValueCountFrequency (%)
422
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9404
92.4%
Common 742
 
7.3%
Latin 28
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 886
 
9.4%
터 821
 
8.7%
센 767
 
8.2%
아 639
 
6.8%
지 587
 
6.2%
역 533
 
5.7%
리 220
 
2.3%
키 192
 
2.0%
움 190
 
2.0%
우 186
 
2.0%
Other values (357) 4383
46.6%
Common
ValueCountFrequency (%)
422
56.9%
1 60
 
8.1%
( 49
 
6.6%
) 49
 
6.6%
2 41
 
5.5%
3 28
 
3.8%
5 21
 
2.8%
4 18
 
2.4%
6 13
 
1.8%
7 11
 
1.5%
Other values (11) 30
 
4.0%
Latin
ValueCountFrequency (%)
S 4
14.3%
O 3
 
10.7%
e 3
 
10.7%
L 2
 
7.1%
C 2
 
7.1%
l 2
 
7.1%
U 1
 
3.6%
H 1
 
3.6%
V 1
 
3.6%
i 1
 
3.6%
Other values (8) 8
28.6%
Han
ValueCountFrequency (%)
來 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9404
92.4%
ASCII 770
 
7.6%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 886
 
9.4%
터 821
 
8.7%
센 767
 
8.2%
아 639
 
6.8%
지 587
 
6.2%
역 533
 
5.7%
리 220
 
2.3%
키 192
 
2.0%
움 190
 
2.0%
우 186
 
2.0%
Other values (357) 4383
46.6%
ASCII
ValueCountFrequency (%)
422
54.8%
1 60
 
7.8%
( 49
 
6.4%
) 49
 
6.4%
2 41
 
5.3%
3 28
 
3.6%
5 21
 
2.7%
4 18
 
2.3%
6 13
 
1.7%
7 11
 
1.4%
Other values (29) 58
 
7.5%
CJK
ValueCountFrequency (%)
來 1
100.0%

시설코드
Text

UNIQUE 

Distinct935
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2024-04-18T16:08:43.892033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0352941
Min length5

Characters and Unicode

Total characters4708
Distinct characters15
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

Unique935 ?
Unique (%)100.0%

Sample

1st rowB0001
2nd rowB0002
3rd rowB0003
4th rowB0006
5th rowB0009
ValueCountFrequency (%)
b0001 1
 
0.1%
k0935 1
 
0.1%
k1034 1
 
0.1%
k0903 1
 
0.1%
k0911 1
 
0.1%
k0915 1
 
0.1%
k0918 1
 
0.1%
k0920 1
 
0.1%
k0925 1
 
0.1%
k0927 1
 
0.1%
Other values (925) 925
98.9%
2024-04-18T16:08:44.317056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 578
12.3%
0 537
11.4%
K 459
9.7%
B 441
9.4%
2 433
9.2%
9 356
7.6%
3 353
7.5%
4 350
7.4%
8 327
6.9%
5 289
6.1%
Other values (5) 585
12.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3773
80.1%
Uppercase Letter 935
 
19.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 578
15.3%
0 537
14.2%
2 433
11.5%
9 356
9.4%
3 353
9.4%
4 350
9.3%
8 327
8.7%
5 289
7.7%
6 287
7.6%
7 263
7.0%
Uppercase Letter
ValueCountFrequency (%)
K 459
49.1%
B 441
47.2%
F 33
 
3.5%
P 1
 
0.1%
X 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3773
80.1%
Latin 935
 
19.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 578
15.3%
0 537
14.2%
2 433
11.5%
9 356
9.4%
3 353
9.4%
4 350
9.3%
8 327
8.7%
5 289
7.7%
6 287
7.6%
7 263
7.0%
Latin
ValueCountFrequency (%)
K 459
49.1%
B 441
47.2%
F 33
 
3.5%
P 1
 
0.1%
X 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4708
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 578
12.3%
0 537
11.4%
K 459
9.7%
B 441
9.4%
2 433
9.2%
9 356
7.6%
3 353
7.5%
4 350
7.4%
8 327
6.9%
5 289
6.1%
Other values (5) 585
12.4%

시설종류명(시설유형)
Categorical

IMBALANCE 

Distinct13
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
(아동) 지역아동센터
555 
(아동) 다함께돌봄센터
216 
(아동) 공동생활가정
84 
(아동) 아동양육시설
 
44
(아동) 지역아동센터(지역아동복지센터)
 
14
Other values (8)
 
22

Length

Max length21
Median length11
Mean length11.404278
Min length10

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row(아동) 아동양육시설
2nd row(아동) 아동양육시설
3rd row(아동) 아동양육시설
4th row(아동) 아동양육시설
5th row(아동) 아동양육시설

Common Values

ValueCountFrequency (%)
(아동) 지역아동센터 555
59.4%
(아동) 다함께돌봄센터 216
 
23.1%
(아동) 공동생활가정 84
 
9.0%
(아동) 아동양육시설 44
 
4.7%
(아동) 지역아동센터(지역아동복지센터) 14
 
1.5%
(아동) 자립지원시설 4
 
0.4%
(아동) 아동일시보호시설 4
 
0.4%
(아동) 아동보호치료시설 3
 
0.3%
(아동) 아동종합시설 3
 
0.3%
(아동) 학대피해아동쉼터 3
 
0.3%
Other values (3) 5
 
0.5%

Length

2024-04-18T16:08:44.469414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아동 935
50.0%
지역아동센터 555
29.7%
다함께돌봄센터 216
 
11.6%
공동생활가정 84
 
4.5%
아동양육시설 44
 
2.4%
지역아동센터(지역아동복지센터 14
 
0.7%
자립지원시설 4
 
0.2%
아동일시보호시설 4
 
0.2%
아동보호치료시설 3
 
0.2%
아동종합시설 3
 
0.2%
Other values (4) 8
 
0.4%

시설종류상세명(시설종류)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
아동복지시설
935 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아동복지시설 935
100.0%

Length

2024-04-18T16:08:44.583037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:08:44.661600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아동복지시설 935
100.0%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
자치구
935 

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 935
100.0%

Length

2024-04-18T16:08:44.740808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:08:44.824136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 935
100.0%

시설장명
Text

Distinct724
Distinct (%)77.7%
Missing3
Missing (%)0.3%
Memory size7.4 KiB
2024-04-18T16:08:45.078040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters2796
Distinct characters172
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

Unique553 ?
Unique (%)59.3%

Sample

1st row김호규
2nd row박흥식
3rd row권명심
4th row최은미
5th row김두식
ValueCountFrequency (%)
이현정 5
 
0.5%
김현숙 5
 
0.5%
김희정 5
 
0.5%
김성숙 4
 
0.4%
이명희 4
 
0.4%
이경희 4
 
0.4%
김은영 4
 
0.4%
김혜숙 4
 
0.4%
김미경 4
 
0.4%
김지연 3
 
0.3%
Other values (714) 890
95.5%
2024-04-18T16:08:45.508503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 187
 
6.7%
이 166
 
5.9%
정 123
 
4.4%
영 110
 
3.9%
미 102
 
3.6%
숙 99
 
3.5%
희 90
 
3.2%
경 87
 
3.1%
박 71
 
2.5%
선 70
 
2.5%
Other values (162) 1691
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2796
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 187
 
6.7%
이 166
 
5.9%
정 123
 
4.4%
영 110
 
3.9%
미 102
 
3.6%
숙 99
 
3.5%
희 90
 
3.2%
경 87
 
3.1%
박 71
 
2.5%
선 70
 
2.5%
Other values (162) 1691
60.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2796
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 187
 
6.7%
이 166
 
5.9%
정 123
 
4.4%
영 110
 
3.9%
미 102
 
3.6%
숙 99
 
3.5%
희 90
 
3.2%
경 87
 
3.1%
박 71
 
2.5%
선 70
 
2.5%
Other values (162) 1691
60.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2796
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 187
 
6.7%
이 166
 
5.9%
정 123
 
4.4%
영 110
 
3.9%
미 102
 
3.6%
숙 99
 
3.5%
희 90
 
3.2%
경 87
 
3.1%
박 71
 
2.5%
선 70
 
2.5%
Other values (162) 1691
60.5%

시군구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1440952 × 109
Minimum1.1 × 109
Maximum1.174 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2024-04-18T16:08:45.629390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1 × 109
5-th percentile1.117 × 109
Q11.1305 × 109
median1.147 × 109
Q31.156 × 109
95-th percentile1.171 × 109
Maximum1.174 × 109
Range74000000
Interquartile range (IQR)25500000

Descriptive statistics

Standard deviation17004818
Coefficient of variation (CV)0.014863115
Kurtosis-0.95787623
Mean1.1440952 × 109
Median Absolute Deviation (MAD)12000000
Skewness-0.092435202
Sum1.069729 × 1012
Variance2.8916384 × 1014
MonotonicityNot monotonic
2024-04-18T16:08:45.758177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1159000000 60
 
6.4%
1135000000 58
 
6.2%
1153000000 58
 
6.2%
1162000000 56
 
6.0%
1138000000 56
 
6.0%
1154500000 49
 
5.2%
1147000000 49
 
5.2%
1129000000 48
 
5.1%
1150000000 46
 
4.9%
1171000000 46
 
4.9%
Other values (16) 409
43.7%
ValueCountFrequency (%)
1100000000 2
 
0.2%
1111000000 18
 
1.9%
1114000000 23
2.5%
1117000000 18
 
1.9%
1120000000 29
3.1%
1121500000 29
3.1%
1123000000 20
2.1%
1126000000 38
4.1%
1129000000 48
5.1%
1130500000 36
3.9%
ValueCountFrequency (%)
1174000000 37
4.0%
1171000000 46
4.9%
1168000000 8
 
0.9%
1165000000 23
 
2.5%
1162000000 56
6.0%
1159000000 60
6.4%
1156000000 43
4.6%
1154500000 49
5.2%
1153000000 58
6.2%
1150000000 46
4.9%

시군구명
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
동작구
 
60
노원구
 
58
구로구
 
58
관악구
 
56
은평구
 
56
Other values (21)
647 

Length

Max length5
Median length3
Mean length3.0780749
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서대문구
2nd row중구
3rd row서대문구
4th row강동구
5th row중구

Common Values

ValueCountFrequency (%)
동작구 60
 
6.4%
노원구 58
 
6.2%
구로구 58
 
6.2%
관악구 56
 
6.0%
은평구 56
 
6.0%
금천구 49
 
5.2%
양천구 49
 
5.2%
성북구 48
 
5.1%
강서구 46
 
4.9%
송파구 46
 
4.9%
Other values (16) 409
43.7%

Length

2024-04-18T16:08:45.879014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
동작구 60
 
6.4%
노원구 58
 
6.2%
구로구 58
 
6.2%
관악구 56
 
6.0%
은평구 56
 
6.0%
금천구 49
 
5.2%
양천구 49
 
5.2%
성북구 48
 
5.1%
강서구 46
 
4.9%
송파구 46
 
4.9%
Other values (16) 409
43.7%

시설주소
Text

Distinct915
Distinct (%)98.4%
Missing5
Missing (%)0.5%
Memory size7.4 KiB
2024-04-18T16:08:46.240010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length50
Mean length29.492473
Min length16

Characters and Unicode

Total characters27428
Distinct characters381
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique901 ?
Unique (%)96.9%

Sample

1st row서울특별시 서대문구 독립문로8길 41(영천동)
2nd row서울특별시 중구 소파로2길 31남산원
3rd row서울특별시 서대문구 송죽길 23
4th row서울특별시 강동구 천호대로186길 21 (둔촌동)
5th row경기도 안성시 용소길 65-0리라아동복지관
ValueCountFrequency (%)
서울특별시 922
 
18.1%
2층 129
 
2.5%
3층 78
 
1.5%
1층 70
 
1.4%
동작구 60
 
1.2%
구로구 58
 
1.1%
노원구 57
 
1.1%
은평구 56
 
1.1%
관악구 54
 
1.1%
금천구 49
 
1.0%
Other values (1884) 3560
69.9%
2024-04-18T16:08:46.712126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4174
 
15.2%
동 1094
 
4.0%
서 1089
 
4.0%
구 1034
 
3.8%
1 1023
 
3.7%
시 969
 
3.5%
로 954
 
3.5%
울 937
 
3.4%
별 925
 
3.4%
특 923
 
3.4%
Other values (371) 14306
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16236
59.2%
Decimal Number 4768
 
17.4%
Space Separator 4174
 
15.2%
Close Punctuation 722
 
2.6%
Open Punctuation 722
 
2.6%
Other Punctuation 570
 
2.1%
Dash Punctuation 200
 
0.7%
Uppercase Letter 24
 
0.1%
Math Symbol 11
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1094
 
6.7%
서 1089
 
6.7%
구 1034
 
6.4%
시 969
 
6.0%
로 954
 
5.9%
울 937
 
5.8%
별 925
 
5.7%
특 923
 
5.7%
길 651
 
4.0%
층 509
 
3.1%
Other values (340) 7151
44.0%
Uppercase Letter
ValueCountFrequency (%)
B 8
33.3%
A 3
 
12.5%
F 2
 
8.3%
C 2
 
8.3%
K 2
 
8.3%
H 1
 
4.2%
L 1
 
4.2%
W 1
 
4.2%
E 1
 
4.2%
I 1
 
4.2%
Other values (2) 2
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 1023
21.5%
2 881
18.5%
3 610
12.8%
0 483
10.1%
4 443
9.3%
5 327
 
6.9%
6 296
 
6.2%
7 258
 
5.4%
8 240
 
5.0%
9 207
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 565
99.1%
. 3
 
0.5%
/ 2
 
0.4%
Space Separator
ValueCountFrequency (%)
4174
100.0%
Close Punctuation
ValueCountFrequency (%)
) 722
100.0%
Open Punctuation
ValueCountFrequency (%)
( 722
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 200
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16236
59.2%
Common 11167
40.7%
Latin 25
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1094
 
6.7%
서 1089
 
6.7%
구 1034
 
6.4%
시 969
 
6.0%
로 954
 
5.9%
울 937
 
5.8%
별 925
 
5.7%
특 923
 
5.7%
길 651
 
4.0%
층 509
 
3.1%
Other values (340) 7151
44.0%
Common
ValueCountFrequency (%)
4174
37.4%
1 1023
 
9.2%
2 881
 
7.9%
) 722
 
6.5%
( 722
 
6.5%
3 610
 
5.5%
, 565
 
5.1%
0 483
 
4.3%
4 443
 
4.0%
5 327
 
2.9%
Other values (8) 1217
 
10.9%
Latin
ValueCountFrequency (%)
B 8
32.0%
A 3
 
12.0%
F 2
 
8.0%
C 2
 
8.0%
K 2
 
8.0%
e 1
 
4.0%
H 1
 
4.0%
L 1
 
4.0%
W 1
 
4.0%
E 1
 
4.0%
Other values (3) 3
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16236
59.2%
ASCII 11192
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4174
37.3%
1 1023
 
9.1%
2 881
 
7.9%
) 722
 
6.5%
( 722
 
6.5%
3 610
 
5.5%
, 565
 
5.0%
0 483
 
4.3%
4 443
 
4.0%
5 327
 
2.9%
Other values (21) 1242
 
11.1%
Hangul
ValueCountFrequency (%)
동 1094
 
6.7%
서 1089
 
6.7%
구 1034
 
6.4%
시 969
 
6.0%
로 954
 
5.9%
울 937
 
5.8%
별 925
 
5.7%
특 923
 
5.7%
길 651
 
4.0%
층 509
 
3.1%
Other values (340) 7151
44.0%

정원(수용인원)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct63
Distinct (%)7.1%
Missing51
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean29.331448
Minimum0
Maximum300
Zeros4
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2024-04-18T16:08:46.842315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q119
median27.5
Q335
95-th percentile50
Maximum300
Range300
Interquartile range (IQR)16

Descriptive statistics

Standard deviation20.14005
Coefficient of variation (CV)0.68663675
Kurtosis74.935137
Mean29.331448
Median Absolute Deviation (MAD)7.5
Skewness6.3215608
Sum25929
Variance405.62161
MonotonicityNot monotonic
2024-04-18T16:08:46.960008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19 124
13.3%
20 81
 
8.7%
29 76
 
8.1%
35 71
 
7.6%
7 71
 
7.6%
25 69
 
7.4%
30 43
 
4.6%
49 39
 
4.2%
40 32
 
3.4%
32 28
 
3.0%
Other values (53) 250
26.7%
(Missing) 51
 
5.5%
ValueCountFrequency (%)
0 4
 
0.4%
5 10
 
1.1%
6 6
 
0.6%
7 71
7.6%
9 1
 
0.1%
10 1
 
0.1%
15 5
 
0.5%
16 1
 
0.1%
17 3
 
0.3%
18 2
 
0.2%
ValueCountFrequency (%)
300 2
0.2%
125 1
 
0.1%
120 2
0.2%
106 1
 
0.1%
100 2
0.2%
99 2
0.2%
90 4
0.4%
87 1
 
0.1%
85 1
 
0.1%
80 2
0.2%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct68
Distinct (%)11.6%
Missing350
Missing (%)37.4%
Infinite0
Infinite (%)0.0%
Mean26.45641
Minimum0
Maximum169
Zeros3
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2024-04-18T16:08:47.083978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q118
median26
Q333
95-th percentile49.8
Maximum169
Range169
Interquartile range (IQR)15

Descriptive statistics

Standard deviation14.563109
Coefficient of variation (CV)0.55045672
Kurtosis15.618208
Mean26.45641
Median Absolute Deviation (MAD)8
Skewness1.9501984
Sum15477
Variance212.08414
MonotonicityNot monotonic
2024-04-18T16:08:47.207519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19 44
 
4.7%
29 29
 
3.1%
33 26
 
2.8%
25 25
 
2.7%
35 25
 
2.7%
18 24
 
2.6%
31 24
 
2.6%
30 23
 
2.5%
23 21
 
2.2%
6 19
 
2.0%
Other values (58) 325
34.8%
(Missing) 350
37.4%
ValueCountFrequency (%)
0 3
 
0.3%
1 4
 
0.4%
2 5
 
0.5%
3 6
 
0.6%
4 13
1.4%
5 17
1.8%
6 19
2.0%
7 5
 
0.5%
8 1
 
0.1%
9 3
 
0.3%
ValueCountFrequency (%)
169 1
0.1%
79 1
0.1%
74 1
0.1%
72 2
0.2%
70 1
0.1%
65 1
0.1%
64 1
0.1%
63 1
0.1%
62 2
0.2%
61 1
0.1%

전화번호
Text

Distinct899
Distinct (%)96.3%
Missing1
Missing (%)0.1%
Memory size7.4 KiB
2024-04-18T16:08:47.420448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.571734
Min length9

Characters and Unicode

Total characters9874
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

Unique867 ?
Unique (%)92.8%

Sample

1st row023727937
2nd row02-752-9836
3rd row02-391-3385
4th row02-478-3290
5th row031-653-3281
ValueCountFrequency (%)
0226079560 4
 
0.4%
027450794 3
 
0.3%
029975474 2
 
0.2%
029542801 2
 
0.2%
028352924 2
 
0.2%
024548891 2
 
0.2%
0262672510 2
 
0.2%
0234926161 2
 
0.2%
07048483067 2
 
0.2%
029245907 2
 
0.2%
Other values (889) 911
97.5%
2024-04-18T16:08:47.771943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1715
17.4%
2 1629
16.5%
- 947
9.6%
7 744
7.5%
8 736
7.5%
3 730
7.4%
9 716
7.3%
1 707
7.2%
6 674
 
6.8%
4 651
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8927
90.4%
Dash Punctuation 947
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1715
19.2%
2 1629
18.2%
7 744
8.3%
8 736
8.2%
3 730
8.2%
9 716
8.0%
1 707
7.9%
6 674
 
7.6%
4 651
 
7.3%
5 625
 
7.0%
Dash Punctuation
ValueCountFrequency (%)
- 947
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9874
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1715
17.4%
2 1629
16.5%
- 947
9.6%
7 744
7.5%
8 736
7.5%
3 730
7.4%
9 716
7.3%
1 707
7.2%
6 674
 
6.8%
4 651
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9874
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1715
17.4%
2 1629
16.5%
- 947
9.6%
7 744
7.5%
8 736
7.5%
3 730
7.4%
9 716
7.3%
1 707
7.2%
6 674
 
6.8%
4 651
 
6.6%

우편번호
Text

Distinct742
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2024-04-18T16:08:48.099204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0641711
Min length5

Characters and Unicode

Total characters4735
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

Unique586 ?
Unique (%)62.7%

Sample

1st row03745
2nd row04628
3rd row03643
4th row05361
5th row456812
ValueCountFrequency (%)
05056 4
 
0.4%
06677 4
 
0.4%
08859 4
 
0.4%
07626 4
 
0.4%
06942 4
 
0.4%
08574 4
 
0.4%
03428 4
 
0.4%
07638 4
 
0.4%
122600 4
 
0.4%
07914 3
 
0.3%
Other values (732) 896
95.8%
2024-04-18T16:08:48.512399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1210
25.6%
7 459
 
9.7%
8 437
 
9.2%
2 432
 
9.1%
3 430
 
9.1%
1 418
 
8.8%
4 381
 
8.0%
6 366
 
7.7%
5 359
 
7.6%
9 242
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4734
> 99.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1210
25.6%
7 459
 
9.7%
8 437
 
9.2%
2 432
 
9.1%
3 430
 
9.1%
1 418
 
8.8%
4 381
 
8.0%
6 366
 
7.7%
5 359
 
7.6%
9 242
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4735
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1210
25.6%
7 459
 
9.7%
8 437
 
9.2%
2 432
 
9.1%
3 430
 
9.1%
1 418
 
8.8%
4 381
 
8.0%
6 366
 
7.7%
5 359
 
7.6%
9 242
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4735
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1210
25.6%
7 459
 
9.7%
8 437
 
9.2%
2 432
 
9.1%
3 430
 
9.1%
1 418
 
8.8%
4 381
 
8.0%
6 366
 
7.7%
5 359
 
7.6%
9 242
 
5.1%

Interactions

2024-04-18T16:08:42.178831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T16:08:41.570307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T16:08:41.888284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T16:08:42.271670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T16:08:41.669104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T16:08:41.991759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T16:08:42.373251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T16:08:41.793113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T16:08:42.082074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T16:08:48.606858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시군구코드시군구명정원(수용인원)현인원
시설종류명(시설유형)1.0000.2580.6170.7350.716
시군구코드0.2581.0001.0000.1260.190
시군구명0.6171.0001.0000.1820.282
정원(수용인원)0.7350.1260.1821.0000.913
현인원0.7160.1900.2820.9131.000
2024-04-18T16:08:48.719696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명시설종류명(시설유형)
시군구명1.0000.214
시설종류명(시설유형)0.2141.000
2024-04-18T16:08:48.802422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구코드정원(수용인원)현인원시설종류명(시설유형)시군구명
시군구코드1.0000.012-0.0010.1960.991
정원(수용인원)0.0121.0000.9430.3650.128
현인원-0.0010.9431.0000.4690.128
시설종류명(시설유형)0.1960.3650.4691.0000.214
시군구명0.9910.1280.1280.2141.000

Missing values

2024-04-18T16:08:42.501441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T16:08:42.664577image/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.
2024-04-18T16:08:42.801559image/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
0구세군서울후생원B0001(아동) 아동양육시설아동복지시설자치구김호규1141000000서대문구서울특별시 서대문구 독립문로8길 41(영천동)1007202372793703745
1남산원B0002(아동) 아동양육시설아동복지시설자치구박흥식1114000000중구서울특별시 중구 소파로2길 31남산원604902-752-983604628
2송죽원B0003(아동) 아동양육시설아동복지시설자치구권명심1141000000서대문구서울특별시 서대문구 송죽길 23544502-391-338503643
3강동꿈마을B0006(아동) 아동양육시설아동복지시설자치구최은미1174000000강동구서울특별시 강동구 천호대로186길 21 (둔촌동)705602-478-329005361
4리라아동복지관B0009(아동) 아동양육시설아동복지시설자치구김두식1114000000중구경기도 안성시 용소길 65-0리라아동복지관5032031-653-3281456812
5은평천사원B0040(아동) 아동양육시설아동복지시설자치구조성아1138000000은평구서울특별시 은평구 갈현로11길 30906402-355-170103428
6삼동소년촌B0042(아동) 아동양육시설아동복지시설자치구현재우1144000000마포구서울특별시 마포구 가양대로 124707002-372-753403906
7청운자립생활관B0043(아동) 자립지원시설아동복지시설자치구유병욱1159000000동작구서울특별시 동작구 국사봉1길 145자립생활관302702823138107043
8시온원B0044(아동) 아동양육시설아동복지시설자치구김성숙1159000000동작구서울특별시 동작구 상도1동 460-9시온원353102-815-858206968
9혜명보육원B0045(아동) 아동양육시설아동복지시설자치구박혜정1154500000금천구서울특별시 금천구 탑골로 35혜명보육원705702-802-035808575
시설명시설코드시설종류명(시설유형)시설종류상세명(시설종류)자치구(시)구분시설장명시군구코드시군구명시설주소정원(수용인원)현인원전화번호우편번호
925무지개그룹홈K2466(아동) 공동생활가정아동복지시설자치구유채정1129000000성북구서울특별시 성북구 장월로1마길1-8 (하월곡동)7<NA>02942491902748
926서울숲아이꿈누리터(성동12호점 우리동네키움센터) 센터장: 한미영K2474(아동) 다함께돌봄센터아동복지시설자치구한미영1120000000성동구서울특별시 성동구 성수동1가 685번지 63호30<NA>02464100204778
927거여2동 송파키움센터K2478(아동) 다함께돌봄센터아동복지시설자치구강미령1171000000송파구서울특별시 송파구 오금로 551, 관리동 1층 (거여동, e편한세상 송파 파크센트럴)25<NA>0707700966605764
928신길7동 아이랜드(영등포12호점 우리동네키움센터)K2510(아동) 다함께돌봄센터아동복지시설자치구이선영1156000000영등포구서울특별시 영등포구 여의대방로43길7-5, 1층 (신길동)20<NA>02846161207360
929꿈누리학대피해아동쉼터K2517(아동) 공동생활가정아동복지시설자치구조승혜1147000000양천구서울특별시 양천구 목동남로4길 6-23, 211동 205호 (신정동)7<NA>022062139108104
930은평10호점 우리동네키움센터K2522(아동) 다함께돌봄센터아동복지시설자치구나정복1138000000은평구서울특별시 은평구 은평로 114, 3층 (응암동)25<NA>026267251003454
931은평11호점 우리동네키움센터K2545(아동) 다함께돌봄센터아동복지시설자치구강신정1138000000은평구서울특별시 은평구 통일로73길 16, 2층 (대조동)25<NA>02357835203385
932은평12호점 우리동네키움센터K2551(아동) 다함께돌봄센터아동복지시설자치구승다영1138000000은평구서울특별시 은평구 통일로627, 3층 (녹번동)25<NA>0105322538403382
933조대봉님P0002(아동) 아동양육시설아동복지시설자치구조대봉1165000000서초구서울특별시 서초구 방배로20길 45층방배동0<NA>02-3273-413306664
934지온보육원X9433(아동) 아동양육시설아동복지시설자치구박국자1150000000강서구서울특별시 강서구 금낭화로26가길 120685602-2662-345707501