Overview

Dataset statistics

Number of variables5
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory45.3 B

Variable types

Categorical1
Text3
Numeric1

Dataset

Description경기도 과천시를 소재로 한 관내 경로당에 대한 데이터로 관내 경로당 현황(소재지 동명, 경로당명, 위치, 전화번호, 회원수 등) 정보를 제공합니다.
Author경기도 과천시
URLhttps://www.data.go.kr/data/3071698/fileData.do

Alerts

경로당명 has unique valuesUnique
위 치 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:17:21.245446
Analysis finished2023-12-12 22:17:21.940622
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

동명
Categorical

Distinct6
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size380.0 B
과천동
9 
별양동
5 
문원동
5 
중앙동
4 
갈현동
4 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중앙동
2nd row중앙동
3rd row중앙동
4th row중앙동
5th row갈현동

Common Values

ValueCountFrequency (%)
과천동 9
29.0%
별양동 5
16.1%
문원동 5
16.1%
중앙동 4
12.9%
갈현동 4
12.9%
부림동 4
12.9%

Length

2023-12-13T07:17:22.004808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:17:22.100646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
과천동 9
29.0%
별양동 5
16.1%
문원동 5
16.1%
중앙동 4
12.9%
갈현동 4
12.9%
부림동 4
12.9%

경로당명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T07:17:22.278214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length3.3548387
Min length2

Characters and Unicode

Total characters104
Distinct characters61
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row1단지
2nd row10단지
3rd row에코팰리스(11단지)
4th row교동
5th row가일
ValueCountFrequency (%)
1단지 1
 
3.2%
관문 1
 
3.2%
세곡 1
 
3.2%
문원2단지 1
 
3.2%
청계 1
 
3.2%
문원1단지 1
 
3.2%
한내 1
 
3.2%
삼포 1
 
3.2%
궁말 1
 
3.2%
용머리 1
 
3.2%
Other values (21) 21
67.7%
2023-12-13T07:17:22.617334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 14
 
13.5%
단 14
 
13.5%
1 5
 
4.8%
문 3
 
2.9%
) 2
 
1.9%
별 2
 
1.9%
양 2
 
1.9%
2 2
 
1.9%
가 2
 
1.9%
동 2
 
1.9%
Other values (51) 56
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84
80.8%
Decimal Number 16
 
15.4%
Close Punctuation 2
 
1.9%
Open Punctuation 2
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 14
 
16.7%
단 14
 
16.7%
문 3
 
3.6%
별 2
 
2.4%
양 2
 
2.4%
가 2
 
2.4%
동 2
 
2.4%
원 2
 
2.4%
리 2
 
2.4%
용 2
 
2.4%
Other values (39) 39
46.4%
Decimal Number
ValueCountFrequency (%)
1 5
31.2%
2 2
 
12.5%
3 2
 
12.5%
8 1
 
6.2%
0 1
 
6.2%
4 1
 
6.2%
5 1
 
6.2%
6 1
 
6.2%
7 1
 
6.2%
9 1
 
6.2%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84
80.8%
Common 20
 
19.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 14
 
16.7%
단 14
 
16.7%
문 3
 
3.6%
별 2
 
2.4%
양 2
 
2.4%
가 2
 
2.4%
동 2
 
2.4%
원 2
 
2.4%
리 2
 
2.4%
용 2
 
2.4%
Other values (39) 39
46.4%
Common
ValueCountFrequency (%)
1 5
25.0%
) 2
 
10.0%
2 2
 
10.0%
( 2
 
10.0%
3 2
 
10.0%
8 1
 
5.0%
0 1
 
5.0%
4 1
 
5.0%
5 1
 
5.0%
6 1
 
5.0%
Other values (2) 2
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84
80.8%
ASCII 20
 
19.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 14
 
16.7%
단 14
 
16.7%
문 3
 
3.6%
별 2
 
2.4%
양 2
 
2.4%
가 2
 
2.4%
동 2
 
2.4%
원 2
 
2.4%
리 2
 
2.4%
용 2
 
2.4%
Other values (39) 39
46.4%
ASCII
ValueCountFrequency (%)
1 5
25.0%
) 2
 
10.0%
2 2
 
10.0%
( 2
 
10.0%
3 2
 
10.0%
8 1
 
5.0%
0 1
 
5.0%
4 1
 
5.0%
5 1
 
5.0%
6 1
 
5.0%
Other values (2) 2
 
10.0%

위 치
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T07:17:22.829036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length17.129032
Min length15

Characters and Unicode

Total characters531
Distinct characters64
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

Unique31 ?
Unique (%)100.0%

Sample

1st row과천시 관문로 128 (중앙동)
2nd row과천시 관문로 166 (중앙동)
3rd row과천시 관문로 151 (중앙동)
4th row과천시 희망2길 26 (중앙동)
5th row과천시 가일로 7 (갈현동)
ValueCountFrequency (%)
과천시 31
25.2%
별양로 8
 
6.5%
과천동 6
 
4.9%
별양동 5
 
4.1%
문원동 5
 
4.1%
부림동 4
 
3.3%
중앙동 4
 
3.3%
관문로 3
 
2.4%
주암동 3
 
2.4%
갈현동 2
 
1.6%
Other values (51) 52
42.3%
2023-12-13T07:17:23.174850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
17.3%
과 38
 
7.2%
천 38
 
7.2%
( 31
 
5.8%
동 31
 
5.8%
) 31
 
5.8%
시 31
 
5.8%
1 26
 
4.9%
로 23
 
4.3%
6 13
 
2.4%
Other values (54) 177
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 291
54.8%
Space Separator 92
 
17.3%
Decimal Number 81
 
15.3%
Open Punctuation 31
 
5.8%
Close Punctuation 31
 
5.8%
Dash Punctuation 5
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 38
13.1%
천 38
13.1%
동 31
10.7%
시 31
10.7%
로 23
 
7.9%
양 13
 
4.5%
별 13
 
4.5%
문 12
 
4.1%
원 10
 
3.4%
길 8
 
2.7%
Other values (40) 74
25.4%
Decimal Number
ValueCountFrequency (%)
1 26
32.1%
6 13
16.0%
2 9
 
11.1%
5 6
 
7.4%
4 6
 
7.4%
8 6
 
7.4%
3 6
 
7.4%
0 4
 
4.9%
9 3
 
3.7%
7 2
 
2.5%
Space Separator
ValueCountFrequency (%)
92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 291
54.8%
Common 240
45.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 38
13.1%
천 38
13.1%
동 31
10.7%
시 31
10.7%
로 23
 
7.9%
양 13
 
4.5%
별 13
 
4.5%
문 12
 
4.1%
원 10
 
3.4%
길 8
 
2.7%
Other values (40) 74
25.4%
Common
ValueCountFrequency (%)
92
38.3%
( 31
 
12.9%
) 31
 
12.9%
1 26
 
10.8%
6 13
 
5.4%
2 9
 
3.8%
5 6
 
2.5%
4 6
 
2.5%
8 6
 
2.5%
3 6
 
2.5%
Other values (4) 14
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 291
54.8%
ASCII 240
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
38.3%
( 31
 
12.9%
) 31
 
12.9%
1 26
 
10.8%
6 13
 
5.4%
2 9
 
3.8%
5 6
 
2.5%
4 6
 
2.5%
8 6
 
2.5%
3 6
 
2.5%
Other values (4) 14
 
5.8%
Hangul
ValueCountFrequency (%)
과 38
13.1%
천 38
13.1%
동 31
10.7%
시 31
10.7%
로 23
 
7.9%
양 13
 
4.5%
별 13
 
4.5%
문 12
 
4.1%
원 10
 
3.4%
길 8
 
2.7%
Other values (40) 74
25.4%

전화번호
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T07:17:23.411934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters248
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

Unique31 ?
Unique (%)100.0%

Sample

1st row503-6683
2nd row503-9880
3rd row507-0086
4th row507-0697
5th row507-2665
ValueCountFrequency (%)
503-6683 1
 
3.2%
502-2129 1
 
3.2%
507-5840 1
 
3.2%
504-3268 1
 
3.2%
504-1114 1
 
3.2%
504-1312 1
 
3.2%
507-3399 1
 
3.2%
502-0093 1
 
3.2%
507-0089 1
 
3.2%
575-8226 1
 
3.2%
Other values (21) 21
67.7%
2023-12-13T07:17:23.771701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 50
20.2%
5 38
15.3%
- 31
12.5%
2 28
11.3%
3 19
 
7.7%
1 17
 
6.9%
6 16
 
6.5%
7 14
 
5.6%
8 13
 
5.2%
4 13
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 217
87.5%
Dash Punctuation 31
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 50
23.0%
5 38
17.5%
2 28
12.9%
3 19
 
8.8%
1 17
 
7.8%
6 16
 
7.4%
7 14
 
6.5%
8 13
 
6.0%
4 13
 
6.0%
9 9
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 248
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 50
20.2%
5 38
15.3%
- 31
12.5%
2 28
11.3%
3 19
 
7.7%
1 17
 
6.9%
6 16
 
6.5%
7 14
 
5.6%
8 13
 
5.2%
4 13
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 248
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 50
20.2%
5 38
15.3%
- 31
12.5%
2 28
11.3%
3 19
 
7.7%
1 17
 
6.9%
6 16
 
6.5%
7 14
 
5.6%
8 13
 
5.2%
4 13
 
5.2%

회원수
Real number (ℝ)

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.612903
Minimum23
Maximum333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-13T07:17:23.935656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile36
Q155.5
median83
Q3125.5
95-th percentile193.5
Maximum333
Range310
Interquartile range (IQR)70

Descriptive statistics

Standard deviation63.774434
Coefficient of variation (CV)0.64022263
Kurtosis4.821903
Mean99.612903
Median Absolute Deviation (MAD)31
Skewness1.8624914
Sum3088
Variance4067.1785
MonotonicityNot monotonic
2023-12-13T07:17:24.040019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
76 2
 
6.5%
100 2
 
6.5%
150 2
 
6.5%
87 1
 
3.2%
83 1
 
3.2%
43 1
 
3.2%
186 1
 
3.2%
50 1
 
3.2%
42 1
 
3.2%
56 1
 
3.2%
Other values (18) 18
58.1%
ValueCountFrequency (%)
23 1
3.2%
30 1
3.2%
42 1
3.2%
43 1
3.2%
49 1
3.2%
50 1
3.2%
52 1
3.2%
55 1
3.2%
56 1
3.2%
58 1
3.2%
ValueCountFrequency (%)
333 1
3.2%
200 1
3.2%
187 1
3.2%
186 1
3.2%
150 2
6.5%
140 1
3.2%
135 1
3.2%
116 1
3.2%
113 1
3.2%
100 2
6.5%

Interactions

2023-12-13T07:17:21.452352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:17:24.135361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동명경로당명위 치전화번호회원수
동명1.0001.0001.0001.0000.000
경로당명1.0001.0001.0001.0001.000
위 치1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000
회원수0.0001.0001.0001.0001.000
2023-12-13T07:17:24.241679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회원수동명
회원수1.0000.137
동명0.1371.000

Missing values

2023-12-13T07:17:21.825928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:17:21.907922image/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.

Sample

동명경로당명위 치전화번호회원수
0중앙동1단지과천시 관문로 128 (중앙동)503-668376
1중앙동10단지과천시 관문로 166 (중앙동)503-988058
2중앙동에코팰리스(11단지)과천시 관문로 151 (중앙동)507-008623
3중앙동교동과천시 희망2길 26 (중앙동)507-0697187
4갈현동가일과천시 가일로 7 (갈현동)507-2665100
5갈현동가루개과천시 갈현로 65 (갈현동)502-2813113
6갈현동2단지과천시 별양로 13(원문동)502-9107116
7갈현동레미안슈르(3단지)과천시 별양로 12 (원문동)502-1781150
8별양동별양동과천시 향촌6길 18-9 (별양동)504-7620140
9별양동별양3단지과천시 별양로 66-11 (별양동)502-324530
동명경로당명위 치전화번호회원수
21과천동주암과천시 증촌로 29 (주암동)502-146049
22과천동용머리과천시 장군마을1길 46 (주암동)575-822685
23과천동궁말과천시 궁말로 16 (과천동)507-008956
24과천동삼포과천시 삼부골로 40 (주암동)502-009342
25과천동한내과천시 상하벌로 11 (과천동)507-3399100
26문원동문원1단지과천시 공원마을1길 54 (문원동)504-1312150
27문원동청계과천시 문원청계5길 46 (문원동)504-111450
28문원동문원2단지과천시 문원청계길 9-5 (문원동)504-3268186
29문원동세곡과천시 매봉로 31 (문원동)507-584043
30문원동매봉과천시 사기막길 18 (문원동)507-805083