Overview

Dataset statistics

Number of variables13
Number of observations25
Missing cells3
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory113.3 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-20415/S/1/datasetView.do

Alerts

시설종류상세명(시설종류) has constant value ""Constant
자치구(시)구분 has constant value ""Constant
정원(수용인원) is highly overall correlated with 현인원High correlation
현인원 is highly overall correlated with 정원(수용인원)High correlation
정원(수용인원) has 1 (4.0%) missing valuesMissing
현인원 has 2 (8.0%) missing valuesMissing
시설명 has unique valuesUnique
시설코드 has unique valuesUnique
시설장명 has unique valuesUnique
시설주소 has unique valuesUnique
전화번호 has unique valuesUnique
우편번호 has unique valuesUnique

Reproduction

Analysis started2024-05-04 02:43:10.814333
Analysis finished2024-05-04 02:43:18.408882
Duration7.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-05-04T02:43:18.786323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length7.68
Min length3

Characters and Unicode

Total characters192
Distinct characters85
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

Unique25 ?
Unique (%)100.0%

Sample

1st row청운양로원
2nd row홍파양로원
3rd row혜명양로원
4th row시립고덕양로원
5th row서울성모원
ValueCountFrequency (%)
청운양로원 1
 
3.4%
시립수락양로원 1
 
3.4%
실버하우스 1
 
3.4%
더시그넘하우스 1
 
3.4%
노블레스타워 1
 
3.4%
500 1
 
3.4%
classic 1
 
3.4%
the 1
 
3.4%
서울본부 1
 
3.4%
서울시니어스타워(주 1
 
3.4%
Other values (19) 19
65.5%
2024-05-04T02:43:19.768025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 9
 
4.7%
원 9
 
4.7%
스 8
 
4.2%
서 7
 
3.6%
울 6
 
3.1%
니 6
 
3.1%
로 6
 
3.1%
양 6
 
3.1%
집 5
 
2.6%
어 5
 
2.6%
Other values (75) 125
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 168
87.5%
Uppercase Letter 10
 
5.2%
Space Separator 4
 
2.1%
Open Punctuation 3
 
1.6%
Close Punctuation 3
 
1.6%
Decimal Number 3
 
1.6%
Other Symbol 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 9
 
5.4%
원 9
 
5.4%
스 8
 
4.8%
서 7
 
4.2%
울 6
 
3.6%
니 6
 
3.6%
로 6
 
3.6%
양 6
 
3.6%
집 5
 
3.0%
어 5
 
3.0%
Other values (61) 101
60.1%
Uppercase Letter
ValueCountFrequency (%)
C 2
20.0%
S 2
20.0%
L 1
10.0%
E 1
10.0%
T 1
10.0%
H 1
10.0%
A 1
10.0%
I 1
10.0%
Decimal Number
ValueCountFrequency (%)
0 2
66.7%
5 1
33.3%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 169
88.0%
Common 13
 
6.8%
Latin 10
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 9
 
5.3%
원 9
 
5.3%
스 8
 
4.7%
서 7
 
4.1%
울 6
 
3.6%
니 6
 
3.6%
로 6
 
3.6%
양 6
 
3.6%
집 5
 
3.0%
어 5
 
3.0%
Other values (62) 102
60.4%
Latin
ValueCountFrequency (%)
C 2
20.0%
S 2
20.0%
L 1
10.0%
E 1
10.0%
T 1
10.0%
H 1
10.0%
A 1
10.0%
I 1
10.0%
Common
ValueCountFrequency (%)
4
30.8%
( 3
23.1%
) 3
23.1%
0 2
15.4%
5 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 168
87.5%
ASCII 23
 
12.0%
None 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 9
 
5.4%
원 9
 
5.4%
스 8
 
4.8%
서 7
 
4.2%
울 6
 
3.6%
니 6
 
3.6%
로 6
 
3.6%
양 6
 
3.6%
집 5
 
3.0%
어 5
 
3.0%
Other values (61) 101
60.1%
ASCII
ValueCountFrequency (%)
4
17.4%
( 3
13.0%
) 3
13.0%
C 2
8.7%
S 2
8.7%
0 2
8.7%
L 1
 
4.3%
E 1
 
4.3%
T 1
 
4.3%
H 1
 
4.3%
Other values (3) 3
13.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

시설코드
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-05-04T02:43:20.356103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.04
Min length5

Characters and Unicode

Total characters126
Distinct characters13
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

Unique25 ?
Unique (%)100.0%

Sample

1st rowA0002
2nd rowA0004
3rd rowA0019
4th rowA0098
5th rowA2156
ValueCountFrequency (%)
a0002 1
 
4.0%
a6971 1
 
4.0%
g3309 1
 
4.0%
g2642 1
 
4.0%
g2640 1
 
4.0%
g2203 1
 
4.0%
g1824 1
 
4.0%
g1767 1
 
4.0%
g1222 1
 
4.0%
f04322 1
 
4.0%
Other values (15) 15
60.0%
2024-05-04T02:43:21.268322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
15.9%
2 19
15.1%
A 16
12.7%
6 12
9.5%
1 9
7.1%
8 9
7.1%
3 9
7.1%
4 8
 
6.3%
G 8
 
6.3%
9 6
 
4.8%
Other values (3) 10
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101
80.2%
Uppercase Letter 25
 
19.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
19.8%
2 19
18.8%
6 12
11.9%
1 9
8.9%
8 9
8.9%
3 9
8.9%
4 8
 
7.9%
9 6
 
5.9%
7 5
 
5.0%
5 4
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
A 16
64.0%
G 8
32.0%
F 1
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common 101
80.2%
Latin 25
 
19.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
19.8%
2 19
18.8%
6 12
11.9%
1 9
8.9%
8 9
8.9%
3 9
8.9%
4 8
 
7.9%
9 6
 
5.9%
7 5
 
5.0%
5 4
 
4.0%
Latin
ValueCountFrequency (%)
A 16
64.0%
G 8
32.0%
F 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 126
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
15.9%
2 19
15.1%
A 16
12.7%
6 12
9.5%
1 9
7.1%
8 9
7.1%
3 9
7.1%
4 8
 
6.3%
G 8
 
6.3%
9 6
 
4.8%
Other values (3) 10
7.9%

시설종류명(시설유형)
Categorical

Distinct3
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
(노인) 양로시설
12 
(노인) 노인복지주택
10 
(노인) 노인공동생활가정
3 

Length

Max length13
Median length11
Mean length10.28
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row(노인) 양로시설
2nd row(노인) 양로시설
3rd row(노인) 양로시설
4th row(노인) 양로시설
5th row(노인) 양로시설

Common Values

ValueCountFrequency (%)
(노인) 양로시설 12
48.0%
(노인) 노인복지주택 10
40.0%
(노인) 노인공동생활가정 3
 
12.0%

Length

2024-05-04T02:43:21.779355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:43:22.283079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인 25
50.0%
양로시설 12
24.0%
노인복지주택 10
 
20.0%
노인공동생활가정 3
 
6.0%

시설종류상세명(시설종류)
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
노인주거복지시설
25 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노인주거복지시설 25
100.0%

Length

2024-05-04T02:43:22.790458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:43:23.194058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인주거복지시설 25
100.0%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
자치구
25 

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 25
100.0%

Length

2024-05-04T02:43:23.469447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:43:23.768625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 25
100.0%

시설장명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-05-04T02:43:24.119678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.04
Min length2

Characters and Unicode

Total characters76
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

Unique25 ?
Unique (%)100.0%

Sample

1st row이종명
2nd row김우리
3rd row채명석
4th row박기아
5th row오양식
ValueCountFrequency (%)
이종명 1
 
4.0%
김민철 1
 
4.0%
김종길 1
 
4.0%
손완상 1
 
4.0%
김경환 1
 
4.0%
백나영 1
 
4.0%
강진영 1
 
4.0%
박은아 1
 
4.0%
김옥순 1
 
4.0%
이상순 1
 
4.0%
Other values (15) 15
60.0%
2024-05-04T02:43:25.169650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 7
 
9.2%
박 5
 
6.6%
상 4
 
5.3%
경 3
 
3.9%
영 3
 
3.9%
이 3
 
3.9%
명 3
 
3.9%
채 2
 
2.6%
미 2
 
2.6%
순 2
 
2.6%
Other values (36) 42
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 7
 
9.2%
박 5
 
6.6%
상 4
 
5.3%
경 3
 
3.9%
영 3
 
3.9%
이 3
 
3.9%
명 3
 
3.9%
채 2
 
2.6%
미 2
 
2.6%
순 2
 
2.6%
Other values (36) 42
55.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 7
 
9.2%
박 5
 
6.6%
상 4
 
5.3%
경 3
 
3.9%
영 3
 
3.9%
이 3
 
3.9%
명 3
 
3.9%
채 2
 
2.6%
미 2
 
2.6%
순 2
 
2.6%
Other values (36) 42
55.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 7
 
9.2%
박 5
 
6.6%
상 4
 
5.3%
경 3
 
3.9%
영 3
 
3.9%
이 3
 
3.9%
명 3
 
3.9%
채 2
 
2.6%
미 2
 
2.6%
순 2
 
2.6%
Other values (36) 42
55.3%

시군구코드
Real number (ℝ)

Distinct16
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.13816 × 109
Minimum1.1 × 109
Maximum1.174 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T02:43:25.560594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1 × 109
5-th percentile1.1116 × 109
Q11.1215 × 109
median1.138 × 109
Q31.15 × 109
95-th percentile1.168 × 109
Maximum1.174 × 109
Range74000000
Interquartile range (IQR)28500000

Descriptive statistics

Standard deviation19358848
Coefficient of variation (CV)0.017008899
Kurtosis-0.64960828
Mean1.13816 × 109
Median Absolute Deviation (MAD)16500000
Skewness-0.027338616
Sum2.8454 × 1010
Variance3.74765 × 1014
MonotonicityNot monotonic
2024-05-04T02:43:25.917381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1150000000 3
12.0%
1132000000 2
 
8.0%
1168000000 2
 
8.0%
1154500000 2
 
8.0%
1138000000 2
 
8.0%
1121500000 2
 
8.0%
1135000000 2
 
8.0%
1114000000 2
 
8.0%
1147000000 1
 
4.0%
1129000000 1
 
4.0%
Other values (6) 6
24.0%
ValueCountFrequency (%)
1100000000 1
4.0%
1111000000 1
4.0%
1114000000 2
8.0%
1117000000 1
4.0%
1121500000 2
8.0%
1129000000 1
4.0%
1132000000 2
8.0%
1135000000 2
8.0%
1138000000 2
8.0%
1144000000 1
4.0%
ValueCountFrequency (%)
1174000000 1
 
4.0%
1168000000 2
8.0%
1156000000 1
 
4.0%
1154500000 2
8.0%
1150000000 3
12.0%
1147000000 1
 
4.0%
1144000000 1
 
4.0%
1138000000 2
8.0%
1135000000 2
8.0%
1132000000 2
8.0%

시군구명
Text

Distinct16
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-05-04T02:43:26.349757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.04
Min length2

Characters and Unicode

Total characters76
Distinct characters31
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

Unique8 ?
Unique (%)32.0%

Sample

1st row종로구
2nd row노원구
3rd row금천구
4th row강동구
5th row영등포구
ValueCountFrequency (%)
강서구 3
12.0%
노원구 2
 
8.0%
금천구 2
 
8.0%
은평구 2
 
8.0%
광진구 2
 
8.0%
도봉구 2
 
8.0%
중구 2
 
8.0%
강남구 2
 
8.0%
종로구 1
 
4.0%
강동구 1
 
4.0%
Other values (6) 6
24.0%
2024-05-04T02:43:27.261873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 24
31.6%
강 6
 
7.9%
서 4
 
5.3%
천 3
 
3.9%
진 2
 
2.6%
포 2
 
2.6%
남 2
 
2.6%
중 2
 
2.6%
봉 2
 
2.6%
도 2
 
2.6%
Other values (21) 27
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 24
31.6%
강 6
 
7.9%
서 4
 
5.3%
천 3
 
3.9%
진 2
 
2.6%
포 2
 
2.6%
남 2
 
2.6%
중 2
 
2.6%
봉 2
 
2.6%
도 2
 
2.6%
Other values (21) 27
35.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 24
31.6%
강 6
 
7.9%
서 4
 
5.3%
천 3
 
3.9%
진 2
 
2.6%
포 2
 
2.6%
남 2
 
2.6%
중 2
 
2.6%
봉 2
 
2.6%
도 2
 
2.6%
Other values (21) 27
35.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 24
31.6%
강 6
 
7.9%
서 4
 
5.3%
천 3
 
3.9%
진 2
 
2.6%
포 2
 
2.6%
남 2
 
2.6%
중 2
 
2.6%
봉 2
 
2.6%
도 2
 
2.6%
Other values (21) 27
35.5%

시설주소
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-05-04T02:43:27.856297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length26.72
Min length20

Characters and Unicode

Total characters668
Distinct characters107
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

Unique25 ?
Unique (%)100.0%

Sample

1st row서울특별시 종로구 비봉길 76 (구기동)
2nd row서울특별시 노원구 동일로248길 30 (상계동)
3rd row서울특별시 금천구 금하로29길 36(시흥동)
4th row서울특별시 강동구 고덕로 199(고덕동)
5th row서울특별시 영등포구 대림로12가길 7-1
ValueCountFrequency (%)
서울특별시 24
 
19.8%
강서구 3
 
2.5%
도봉구 2
 
1.7%
자곡로 2
 
1.7%
강남구 2
 
1.7%
은평구 2
 
1.7%
광진구 2
 
1.7%
90 2
 
1.7%
자곡동 2
 
1.7%
등촌동 2
 
1.7%
Other values (74) 78
64.5%
2024-05-04T02:43:29.143436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
 
14.4%
시 32
 
4.8%
서 30
 
4.5%
동 29
 
4.3%
특 26
 
3.9%
별 26
 
3.9%
울 26
 
3.9%
로 25
 
3.7%
구 25
 
3.7%
) 23
 
3.4%
Other values (97) 330
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 406
60.8%
Decimal Number 108
 
16.2%
Space Separator 96
 
14.4%
Close Punctuation 23
 
3.4%
Open Punctuation 23
 
3.4%
Dash Punctuation 9
 
1.3%
Other Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 32
 
7.9%
서 30
 
7.4%
동 29
 
7.1%
특 26
 
6.4%
별 26
 
6.4%
울 26
 
6.4%
로 25
 
6.2%
구 25
 
6.2%
길 17
 
4.2%
강 9
 
2.2%
Other values (82) 161
39.7%
Decimal Number
ValueCountFrequency (%)
2 18
16.7%
1 18
16.7%
3 13
12.0%
4 13
12.0%
0 12
11.1%
9 9
8.3%
5 8
7.4%
6 7
 
6.5%
7 6
 
5.6%
8 4
 
3.7%
Space Separator
ValueCountFrequency (%)
96
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 406
60.8%
Common 262
39.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 32
 
7.9%
서 30
 
7.4%
동 29
 
7.1%
특 26
 
6.4%
별 26
 
6.4%
울 26
 
6.4%
로 25
 
6.2%
구 25
 
6.2%
길 17
 
4.2%
강 9
 
2.2%
Other values (82) 161
39.7%
Common
ValueCountFrequency (%)
96
36.6%
) 23
 
8.8%
( 23
 
8.8%
2 18
 
6.9%
1 18
 
6.9%
3 13
 
5.0%
4 13
 
5.0%
0 12
 
4.6%
- 9
 
3.4%
9 9
 
3.4%
Other values (5) 28
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 406
60.8%
ASCII 262
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
36.6%
) 23
 
8.8%
( 23
 
8.8%
2 18
 
6.9%
1 18
 
6.9%
3 13
 
5.0%
4 13
 
5.0%
0 12
 
4.6%
- 9
 
3.4%
9 9
 
3.4%
Other values (5) 28
 
10.7%
Hangul
ValueCountFrequency (%)
시 32
 
7.9%
서 30
 
7.4%
동 29
 
7.1%
특 26
 
6.4%
별 26
 
6.4%
울 26
 
6.4%
로 25
 
6.2%
구 25
 
6.2%
길 17
 
4.2%
강 9
 
2.2%
Other values (82) 161
39.7%

정원(수용인원)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct21
Distinct (%)87.5%
Missing1
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean151.95833
Minimum9
Maximum760
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T02:43:29.525789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile9
Q125.75
median89
Q3167.5
95-th percentile581.7
Maximum760
Range751
Interquartile range (IQR)141.75

Descriptive statistics

Standard deviation195.79214
Coefficient of variation (CV)1.2884594
Kurtosis3.9196838
Mean151.95833
Median Absolute Deviation (MAD)63.5
Skewness2.0704709
Sum3647
Variance38334.563
MonotonicityNot monotonic
2024-05-04T02:43:29.981742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
9 4
 
16.0%
57 1
 
4.0%
98 1
 
4.0%
230 1
 
4.0%
478 1
 
4.0%
760 1
 
4.0%
144 1
 
4.0%
114 1
 
4.0%
105 1
 
4.0%
80 1
 
4.0%
Other values (11) 11
44.0%
ValueCountFrequency (%)
9 4
16.0%
24 1
 
4.0%
25 1
 
4.0%
26 1
 
4.0%
28 1
 
4.0%
44 1
 
4.0%
57 1
 
4.0%
64 1
 
4.0%
80 1
 
4.0%
98 1
 
4.0%
ValueCountFrequency (%)
760 1
4.0%
600 1
4.0%
478 1
4.0%
240 1
4.0%
230 1
4.0%
220 1
4.0%
150 1
4.0%
144 1
4.0%
124 1
4.0%
114 1
4.0%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)95.7%
Missing2
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean122.86957
Minimum8
Maximum580
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T02:43:30.537489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile9
Q126.5
median87
Q3141.5
95-th percentile429.5
Maximum580
Range572
Interquartile range (IQR)115

Descriptive statistics

Standard deviation145.05181
Coefficient of variation (CV)1.1805349
Kurtosis4.1644866
Mean122.86957
Median Absolute Deviation (MAD)61
Skewness2.0530684
Sum2826
Variance21040.028
MonotonicityNot monotonic
2024-05-04T02:43:31.121720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
9 2
 
8.0%
26 1
 
4.0%
97 1
 
4.0%
299 1
 
4.0%
580 1
 
4.0%
133 1
 
4.0%
96 1
 
4.0%
95 1
 
4.0%
74 1
 
4.0%
240 1
 
4.0%
Other values (12) 12
48.0%
(Missing) 2
 
8.0%
ValueCountFrequency (%)
8 1
4.0%
9 2
8.0%
20 1
4.0%
24 1
4.0%
26 1
4.0%
27 1
4.0%
32 1
4.0%
50 1
4.0%
55 1
4.0%
74 1
4.0%
ValueCountFrequency (%)
580 1
4.0%
444 1
4.0%
299 1
4.0%
240 1
4.0%
173 1
4.0%
150 1
4.0%
133 1
4.0%
98 1
4.0%
97 1
4.0%
96 1
4.0%

전화번호
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-05-04T02:43:32.128575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.72
Min length9

Characters and Unicode

Total characters268
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 (%)100.0%

Sample

1st row02-379-9232
2nd row02-939-0735
3rd row02-802-6765
4th row02-441-8886
5th row02-831-9311
ValueCountFrequency (%)
02-379-9232 1
 
4.0%
027733477 1
 
4.0%
025764400 1
 
4.0%
02-917-6090 1
 
4.0%
02-2218-5539 1
 
4.0%
02-2232-9003 1
 
4.0%
02-790-3843 1
 
4.0%
0222233350 1
 
4.0%
0234938001 1
 
4.0%
031-405-4132 1
 
4.0%
Other values (15) 15
60.0%
2024-05-04T02:43:33.695674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 53
19.8%
2 45
16.8%
- 32
11.9%
3 32
11.9%
7 19
 
7.1%
8 17
 
6.3%
9 15
 
5.6%
5 15
 
5.6%
4 15
 
5.6%
6 13
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 236
88.1%
Dash Punctuation 32
 
11.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 53
22.5%
2 45
19.1%
3 32
13.6%
7 19
 
8.1%
8 17
 
7.2%
9 15
 
6.4%
5 15
 
6.4%
4 15
 
6.4%
6 13
 
5.5%
1 12
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 268
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 53
19.8%
2 45
16.8%
- 32
11.9%
3 32
11.9%
7 19
 
7.1%
8 17
 
6.3%
9 15
 
5.6%
5 15
 
5.6%
4 15
 
5.6%
6 13
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 268
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 53
19.8%
2 45
16.8%
- 32
11.9%
3 32
11.9%
7 19
 
7.1%
8 17
 
6.3%
9 15
 
5.6%
5 15
 
5.6%
4 15
 
5.6%
6 13
 
4.9%

우편번호
Real number (ℝ)

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10547.4
Minimum1314
Maximum135660
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-05-04T02:43:34.458735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1314
5-th percentile1425.2
Q13337
median4993
Q37591
95-th percentile13717.6
Maximum135660
Range134346
Interquartile range (IQR)4254

Descriptive statistics

Standard deviation26245.452
Coefficient of variation (CV)2.4883338
Kurtosis24.230598
Mean10547.4
Median Absolute Deviation (MAD)2445
Skewness4.8906703
Sum263685
Variance6.8882373 × 108
MonotonicityNot monotonic
2024-05-04T02:43:35.164671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3001 1
 
4.0%
1623 1
 
4.0%
7959 1
 
4.0%
6373 1
 
4.0%
2797 1
 
4.0%
5065 1
 
4.0%
4597 1
 
4.0%
4382 1
 
4.0%
135660 1
 
4.0%
1314 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1314 1
4.0%
1376 1
4.0%
1622 1
4.0%
1623 1
4.0%
2797 1
4.0%
3001 1
4.0%
3337 1
4.0%
3382 1
4.0%
3911 1
4.0%
4382 1
4.0%
ValueCountFrequency (%)
135660 1
4.0%
14983 1
4.0%
8656 1
4.0%
8648 1
4.0%
7959 1
4.0%
7674 1
4.0%
7591 1
4.0%
7550 1
4.0%
7438 1
4.0%
6373 1
4.0%

Interactions

2024-05-04T02:43:15.903411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:12.065651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:13.383016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:14.582289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:16.184601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:12.393114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:13.695233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:14.952737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:16.451247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:12.740775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:13.958603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:15.336629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:16.744449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:13.109246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:14.242296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:43:15.625588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T02:43:35.921578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명시설코드시설종류명(시설유형)시설장명시군구코드시군구명시설주소정원(수용인원)현인원전화번호우편번호
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시설코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시설종류명(시설유형)1.0001.0001.0001.0000.0000.6541.0000.6120.5451.0000.000
시설장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시군구코드1.0001.0000.0001.0001.0001.0001.0000.6530.6721.0000.000
시군구명1.0001.0000.6541.0001.0001.0001.0000.7120.8081.0000.734
시설주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
정원(수용인원)1.0001.0000.6121.0000.6530.7121.0001.0000.9921.0000.000
현인원1.0001.0000.5451.0000.6720.8081.0000.9921.0001.0000.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
우편번호1.0001.0000.0001.0000.0000.7341.0000.0000.0001.0001.000
2024-05-04T02:43:36.413847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구코드정원(수용인원)현인원우편번호시설종류명(시설유형)
시군구코드1.000-0.001-0.0800.4630.000
정원(수용인원)-0.0011.0000.9770.0380.447
현인원-0.0800.9771.0000.1180.374
우편번호0.4630.0380.1181.0000.000
시설종류명(시설유형)0.0000.4470.3740.0001.000

Missing values

2024-05-04T02:43:17.205726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T02:43:17.962276image/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.
2024-05-04T02:43:18.277744image/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
0청운양로원A0002(노인) 양로시설노인주거복지시설자치구이종명1111000000종로구서울특별시 종로구 비봉길 76 (구기동)575002-379-92323001
1홍파양로원A0004(노인) 양로시설노인주거복지시설자치구김우리1135000000노원구서울특별시 노원구 동일로248길 30 (상계동)443202-939-07351623
2혜명양로원A0019(노인) 양로시설노인주거복지시설자치구채명석1154500000금천구서울특별시 금천구 금하로29길 36(시흥동)645502-802-67658656
3시립고덕양로원A0098(노인) 양로시설노인주거복지시설자치구박기아1174000000강동구서울특별시 강동구 고덕로 199(고덕동)1248702-441-88865235
4서울성모원A2156(노인) 양로시설노인주거복지시설자치구오양식1156000000영등포구서울특별시 영등포구 대림로12가길 7-19902-831-93117438
5성우회A2218(노인) 양로시설노인주거복지시설자치구남상미1138000000은평구서울특별시 은평구 통일로92길 13 (불광동)252002-354-81163337
6서울시니어스타워㈜강서본부A3022(노인) 노인복지주택노인주거복지시설자치구김영채1150000000강서구서울특별시 강서구 공항대로 315 (등촌동)22017302-2660-38007591
7섭리의집A3167(노인) 양로시설노인주거복지시설자치구박정희1154500000금천구서울특별시 금천구 시흥대로40길 111-5섭리의집282702-803-30558648
8서울시니어스타워(주)가양본부A4603(노인) 노인복지주택노인주거복지시설자치구박경숙1150000000강서구서울특별시 강서구 화곡로68길 102 (등촌동, 서울특별시니어스가양타워)60044402-3660-77007550
9시니어캐슬클라시온A6023(노인) 노인복지주택노인주거복지시설자치구조기상1138000000은평구서울특별시 은평구 은평로21길 34-5 (녹번동)150150010-7327-82043382
시설명시설코드시설종류명(시설유형)시설종류상세명(시설종류)자치구(시)구분시설장명시군구코드시군구명시설주소정원(수용인원)현인원전화번호우편번호
15시립수락양로원A8880(노인) 양로시설노인주거복지시설자치구김경란1135000000노원구서울특별시 노원구 동일로250길 44-142 (상계동)807402-932-04051622
16애림원F04322(노인) 양로시설노인주거복지시설자치구이상순1100000000서울특별시경기도 시흥시 동서로 895-6 (물왕동)<NA><NA>031-405-413214983
17요셉의집G1222(노인) 노인공동생활가정노인주거복지시설자치구김옥순1132000000도봉구서울특별시 도봉구 시루봉로15라길69 (방학동)9902349380011314
18서울시니어스타워(주)강남본부G1767(노인) 노인복지주택노인주거복지시설자치구박은아1168000000강남구서울특별시 강남구 자곡로 100-2 (자곡동, 서울특별시니어스강남타워)105950222233350135660
19하이원빌리지G1824(노인) 노인복지주택노인주거복지시설자치구강진영1117000000용산구서울특별시 용산구 한강대로40가길 24103호(한강로2가)1149602-790-38434382
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21THE CLASSIC 500G2640(노인) 양로시설노인주거복지시설자치구김경환1121500000광진구서울특별시 광진구 능동로 90 (자양동)76058002-2218-55395065
22노블레스타워G2642(노인) 노인복지주택노인주거복지시설자치구손완상1129000000성북구서울특별시 성북구 종암로 90 (종암동)47829902-917-60902797
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