Overview

Dataset statistics

Number of variables6
Number of observations64
Missing cells64
Missing cells (%)16.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory54.1 B

Variable types

Categorical2
Text1
Numeric2
Unsupported1

Alerts

기타 has 64 (100.0%) missing valuesMissing
공동체명 has unique valuesUnique
기타 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 21:33:35.260725
Analysis finished2023-12-10 21:33:36.155446
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Categorical

Distinct4
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size644.0 B
2021
25 
2020
19 
2022
18 
2019
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2021 25
39.1%
2020 19
29.7%
2022 18
28.1%
2019 2
 
3.1%

Length

2023-12-11T06:33:36.231554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:36.324190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 25
39.1%
2020 19
29.7%
2022 18
28.1%
2019 2
 
3.1%

시군명
Categorical

Distinct26
Distinct (%)40.6%
Missing0
Missing (%)0.0%
Memory size644.0 B
양주시
6 
포천시
6 
양평군
5 
파주시
4 
평택시
4 
Other values (21)
39 

Length

Max length4
Median length3
Mean length3.0625
Min length3

Unique

Unique12 ?
Unique (%)18.8%

Sample

1st row남양주시
2nd row부천시
3rd row성남시
4th row수원시
5th row안성시

Common Values

ValueCountFrequency (%)
양주시 6
 
9.4%
포천시 6
 
9.4%
양평군 5
 
7.8%
파주시 4
 
6.2%
평택시 4
 
6.2%
고양시 4
 
6.2%
이천시 4
 
6.2%
화성시 3
 
4.7%
남양주시 3
 
4.7%
수원시 3
 
4.7%
Other values (16) 22
34.4%

Length

2023-12-11T06:33:36.475561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
양주시 6
 
9.4%
포천시 6
 
9.4%
양평군 5
 
7.8%
파주시 4
 
6.2%
평택시 4
 
6.2%
고양시 4
 
6.2%
이천시 4
 
6.2%
화성시 3
 
4.7%
남양주시 3
 
4.7%
수원시 3
 
4.7%
Other values (16) 22
34.4%

공동체명
Text

UNIQUE 

Distinct64
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size644.0 B
2023-12-11T06:33:36.741558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length8.890625
Min length2

Characters and Unicode

Total characters569
Distinct characters184
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)100.0%

Sample

1st row에듀케어 인 수동
2nd row산방과후
3rd row킹덤스쿨
4th row도담어린이작은도서관
5th row두린아이 꿈터
ValueCountFrequency (%)
공동육아 4
 
3.2%
작은 3
 
2.4%
사람들 3
 
2.4%
공동체 2
 
1.6%
함께 2
 
1.6%
the 2
 
1.6%
놀이터 2
 
1.6%
도서관 2
 
1.6%
돌봄공동체 2
 
1.6%
행복한 2
 
1.6%
Other values (98) 101
80.8%
2023-12-11T06:33:37.204126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
62
 
10.9%
동 27
 
4.7%
공 18
 
3.2%
터 16
 
2.8%
마 16
 
2.8%
아 16
 
2.8%
이 16
 
2.8%
체 12
 
2.1%
을 10
 
1.8%
교 10
 
1.8%
Other values (174) 366
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 478
84.0%
Space Separator 62
 
10.9%
Lowercase Letter 11
 
1.9%
Uppercase Letter 8
 
1.4%
Open Punctuation 4
 
0.7%
Close Punctuation 4
 
0.7%
Other Punctuation 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 27
 
5.6%
공 18
 
3.8%
터 16
 
3.3%
마 16
 
3.3%
아 16
 
3.3%
이 16
 
3.3%
체 12
 
2.5%
을 10
 
2.1%
교 10
 
2.1%
사 10
 
2.1%
Other values (155) 327
68.4%
Lowercase Letter
ValueCountFrequency (%)
t 3
27.3%
m 2
18.2%
e 2
18.2%
n 1
 
9.1%
o 1
 
9.1%
h 1
 
9.1%
a 1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
T 2
25.0%
N 1
12.5%
O 1
12.5%
H 1
12.5%
E 1
12.5%
M 1
12.5%
A 1
12.5%
Space Separator
ValueCountFrequency (%)
62
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 477
83.8%
Common 72
 
12.7%
Latin 19
 
3.3%
Han 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 27
 
5.7%
공 18
 
3.8%
터 16
 
3.4%
마 16
 
3.4%
아 16
 
3.4%
이 16
 
3.4%
체 12
 
2.5%
을 10
 
2.1%
교 10
 
2.1%
사 10
 
2.1%
Other values (154) 326
68.3%
Latin
ValueCountFrequency (%)
t 3
15.8%
T 2
10.5%
m 2
10.5%
e 2
10.5%
N 1
 
5.3%
O 1
 
5.3%
H 1
 
5.3%
E 1
 
5.3%
n 1
 
5.3%
o 1
 
5.3%
Other values (4) 4
21.1%
Common
ValueCountFrequency (%)
62
86.1%
( 4
 
5.6%
) 4
 
5.6%
, 1
 
1.4%
- 1
 
1.4%
Han
ValueCountFrequency (%)
攄 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 477
83.8%
ASCII 91
 
16.0%
CJK 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
62
68.1%
( 4
 
4.4%
) 4
 
4.4%
t 3
 
3.3%
T 2
 
2.2%
m 2
 
2.2%
e 2
 
2.2%
N 1
 
1.1%
O 1
 
1.1%
, 1
 
1.1%
Other values (9) 9
 
9.9%
Hangul
ValueCountFrequency (%)
동 27
 
5.7%
공 18
 
3.8%
터 16
 
3.4%
마 16
 
3.4%
아 16
 
3.4%
이 16
 
3.4%
체 12
 
2.5%
을 10
 
2.1%
교 10
 
2.1%
사 10
 
2.1%
Other values (154) 326
68.3%
CJK
ValueCountFrequency (%)
攄 1
100.0%

공동체구성원수
Real number (ℝ)

Distinct18
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.1875
Minimum10
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-11T06:33:37.334587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10
Q111
median12.5
Q316
95-th percentile28.7
Maximum44
Range34
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.4509751
Coefficient of variation (CV)0.42475556
Kurtosis6.1631574
Mean15.1875
Median Absolute Deviation (MAD)2.5
Skewness2.2342611
Sum972
Variance41.615079
MonotonicityNot monotonic
2023-12-11T06:33:37.455975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
10 12
18.8%
12 11
17.2%
11 9
14.1%
15 7
10.9%
16 6
9.4%
20 3
 
4.7%
14 2
 
3.1%
13 2
 
3.1%
21 2
 
3.1%
17 2
 
3.1%
Other values (8) 8
12.5%
ValueCountFrequency (%)
10 12
18.8%
11 9
14.1%
12 11
17.2%
13 2
 
3.1%
14 2
 
3.1%
15 7
10.9%
16 6
9.4%
17 2
 
3.1%
19 1
 
1.6%
20 3
 
4.7%
ValueCountFrequency (%)
44 1
 
1.6%
33 1
 
1.6%
30 1
 
1.6%
29 1
 
1.6%
27 1
 
1.6%
25 1
 
1.6%
23 1
 
1.6%
21 2
3.1%
20 3
4.7%
19 1
 
1.6%

돌봄아동수
Real number (ℝ)

Distinct13
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.328125
Minimum10
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-11T06:33:37.600378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10
Q115
median20
Q320
95-th percentile40
Maximum99
Range89
Interquartile range (IQR)5

Descriptive statistics

Standard deviation13.473142
Coefficient of variation (CV)0.63170774
Kurtosis18.456239
Mean21.328125
Median Absolute Deviation (MAD)5
Skewness3.7887525
Sum1365
Variance181.52555
MonotonicityNot monotonic
2023-12-11T06:33:37.713301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
20 23
35.9%
15 13
20.3%
10 6
 
9.4%
30 5
 
7.8%
12 4
 
6.2%
25 4
 
6.2%
16 2
 
3.1%
40 2
 
3.1%
45 1
 
1.6%
14 1
 
1.6%
Other values (3) 3
 
4.7%
ValueCountFrequency (%)
10 6
 
9.4%
12 4
 
6.2%
14 1
 
1.6%
15 13
20.3%
16 2
 
3.1%
17 1
 
1.6%
20 23
35.9%
25 4
 
6.2%
30 5
 
7.8%
40 2
 
3.1%
ValueCountFrequency (%)
99 1
 
1.6%
65 1
 
1.6%
45 1
 
1.6%
40 2
 
3.1%
30 5
 
7.8%
25 4
 
6.2%
20 23
35.9%
17 1
 
1.6%
16 2
 
3.1%
15 13
20.3%

기타
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing64
Missing (%)100.0%
Memory size708.0 B

Interactions

2023-12-11T06:33:35.726350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:35.549720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:35.830930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:35.645968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:33:37.785822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명공동체명공동체구성원수돌봄아동수
기준년도1.0000.5861.0000.2920.232
시군명0.5861.0001.0000.4770.524
공동체명1.0001.0001.0001.0001.000
공동체구성원수0.2920.4771.0001.0000.822
돌봄아동수0.2320.5241.0000.8221.000
2023-12-11T06:33:37.900288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명기준년도
시군명1.0000.266
기준년도0.2661.000
2023-12-11T06:33:38.017993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공동체구성원수돌봄아동수기준년도시군명
공동체구성원수1.0000.2500.2160.139
돌봄아동수0.2501.0000.1440.201
기준년도0.2160.1441.0000.266
시군명0.1390.2010.2661.000

Missing values

2023-12-11T06:33:35.957479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:33:36.105762image/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

기준년도시군명공동체명공동체구성원수돌봄아동수기타
02022남양주시에듀케어 인 수동2320<NA>
12022부천시산방과후1112<NA>
22022성남시킹덤스쿨1116<NA>
32022수원시도담어린이작은도서관1330<NA>
42022안성시두린아이 꿈터1520<NA>
52022안성시코아루 깐부 사랑방1020<NA>
62022양평군나무숲세움터2145<NA>
72022여주시국경없는 청소년교실1620<NA>
82022이천시더이븐1015<NA>
92022의정부시ATM - at the moment1020<NA>
기준년도시군명공동체명공동체구성원수돌봄아동수기타
542021평택시다인숲다함께 돌봄센터3030<NA>
552021포천시포천일동 마을교육공동체1520<NA>
562021포천시THE 공감1120<NA>
572021화성시모아사랑터1215<NA>
582021화성시풍경채 작은도서관1225<NA>
592021화성시글로벌리더클럽2510<NA>
602022고양시화전마을학교1015<NA>
612022광명시공동육아 방과후 놀이터 마법숲1212<NA>
622022구리시경계선지능지원네트워크1010<NA>
632022남양주시달뫼놀이터2010<NA>