Overview

Dataset statistics

Number of variables4
Number of observations219
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory34.6 B

Variable types

Numeric2
Categorical1
Text1

Dataset

Description한국건강가정진흥원에서 제공하는 자료로 전국의 다문화가족지원센터의 방문지도사 현황 자료입니다.파일데이터 항목구성은 NO, 지역, 센터, 방문지도사수입니다.
Author한국건강가정진흥원
URLhttps://www.data.go.kr/data/15074218/fileData.do

Alerts

순번(NO) is highly overall correlated with 지역High correlation
지역 is highly overall correlated with 순번(NO)High correlation
순번(NO) has unique valuesUnique
센터 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:06:33.642267
Analysis finished2023-12-12 00:06:34.633221
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번(NO)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct219
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110
Minimum1
Maximum219
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T09:06:34.716034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.9
Q155.5
median110
Q3164.5
95-th percentile208.1
Maximum219
Range218
Interquartile range (IQR)109

Descriptive statistics

Standard deviation63.364028
Coefficient of variation (CV)0.57603661
Kurtosis-1.2
Mean110
Median Absolute Deviation (MAD)55
Skewness0
Sum24090
Variance4015
MonotonicityStrictly increasing
2023-12-12T09:06:34.871231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
152 1
 
0.5%
141 1
 
0.5%
142 1
 
0.5%
143 1
 
0.5%
144 1
 
0.5%
145 1
 
0.5%
146 1
 
0.5%
147 1
 
0.5%
148 1
 
0.5%
Other values (209) 209
95.4%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
219 1
0.5%
218 1
0.5%
217 1
0.5%
216 1
0.5%
215 1
0.5%
214 1
0.5%
213 1
0.5%
212 1
0.5%
211 1
0.5%
210 1
0.5%

지역
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
경기
30 
서울
23 
전남
22 
경북
22 
경남
19 
Other values (12)
103 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
경기 30
13.7%
서울 23
10.5%
전남 22
10.0%
경북 22
10.0%
경남 19
8.7%
강원 18
8.2%
충남 15
6.8%
전북 14
6.4%
충북 12
 
5.5%
부산 10
 
4.6%
Other values (7) 34
15.5%

Length

2023-12-12T09:06:35.046305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 30
13.7%
서울 23
10.5%
전남 22
10.0%
경북 22
10.0%
경남 19
8.7%
강원 18
8.2%
충남 15
6.8%
전북 14
6.4%
충북 12
 
5.5%
부산 10
 
4.6%
Other values (7) 34
15.5%

센터
Text

UNIQUE 

Distinct219
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T09:06:35.260525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length8
Mean length8.716895
Min length8

Characters and Unicode

Total characters1909
Distinct characters141
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique219 ?
Unique (%)100.0%

Sample

1st row강남구 가족센터
2nd row강동구 가족센터
3rd row강북구 가족센터
4th row강서구 가족센터
5th row관악구 가족센터
ValueCountFrequency (%)
가족센터 196
47.2%
청양군 1
 
0.2%
태안군 1
 
0.2%
무안군 1
 
0.2%
홍성군 1
 
0.2%
고창군 1
 
0.2%
군산시 1
 
0.2%
김제시 1
 
0.2%
남원시 1
 
0.2%
무주군 1
 
0.2%
Other values (210) 210
50.6%
2023-12-12T09:06:35.655710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 220
11.5%
족 219
11.5%
센 219
11.5%
터 219
11.5%
196
 
10.3%
군 83
 
4.3%
시 80
 
4.2%
구 69
 
3.6%
원 32
 
1.7%
산 30
 
1.6%
Other values (131) 542
28.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1713
89.7%
Space Separator 196
 
10.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 220
12.8%
족 219
12.8%
센 219
12.8%
터 219
12.8%
군 83
 
4.8%
시 80
 
4.7%
구 69
 
4.0%
원 32
 
1.9%
산 30
 
1.8%
천 28
 
1.6%
Other values (130) 514
30.0%
Space Separator
ValueCountFrequency (%)
196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1713
89.7%
Common 196
 
10.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 220
12.8%
족 219
12.8%
센 219
12.8%
터 219
12.8%
군 83
 
4.8%
시 80
 
4.7%
구 69
 
4.0%
원 32
 
1.9%
산 30
 
1.8%
천 28
 
1.6%
Other values (130) 514
30.0%
Common
ValueCountFrequency (%)
196
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1713
89.7%
ASCII 196
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 220
12.8%
족 219
12.8%
센 219
12.8%
터 219
12.8%
군 83
 
4.8%
시 80
 
4.7%
구 69
 
4.0%
원 32
 
1.9%
산 30
 
1.8%
천 28
 
1.6%
Other values (130) 514
30.0%
ASCII
ValueCountFrequency (%)
196
100.0%

방문지도사수
Real number (ℝ)

Distinct19
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.4931507
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T09:06:35.786046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q15
median8
Q311.5
95-th percentile16
Maximum19
Range18
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation4.1919209
Coefficient of variation (CV)0.49356488
Kurtosis-0.49419458
Mean8.4931507
Median Absolute Deviation (MAD)3
Skewness0.57356845
Sum1860
Variance17.572201
MonotonicityNot monotonic
2023-12-12T09:06:35.910840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
5 28
12.8%
8 21
9.6%
4 20
9.1%
7 19
8.7%
10 16
 
7.3%
3 16
 
7.3%
6 16
 
7.3%
9 14
 
6.4%
12 13
 
5.9%
13 12
 
5.5%
Other values (9) 44
20.1%
ValueCountFrequency (%)
1 1
 
0.5%
2 3
 
1.4%
3 16
7.3%
4 20
9.1%
5 28
12.8%
6 16
7.3%
7 19
8.7%
8 21
9.6%
9 14
6.4%
10 16
7.3%
ValueCountFrequency (%)
19 3
 
1.4%
18 4
 
1.8%
17 3
 
1.4%
16 5
 
2.3%
15 10
4.6%
14 5
 
2.3%
13 12
5.5%
12 13
5.9%
11 10
4.6%
10 16
7.3%

Interactions

2023-12-12T09:06:34.019816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:06:33.816819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:06:34.101426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:06:33.928251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:06:36.010826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번(NO)지역방문지도사수
순번(NO)1.0000.9770.395
지역0.9771.0000.406
방문지도사수0.3950.4061.000
2023-12-12T09:06:36.121761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번(NO)방문지도사수지역
순번(NO)1.000-0.1090.879
방문지도사수-0.1091.0000.167
지역0.8790.1671.000

Missing values

2023-12-12T09:06:34.513825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:06:34.592334image/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

순번(NO)지역센터방문지도사수
01서울강남구 가족센터4
12서울강동구 가족센터10
23서울강북구 가족센터11
34서울강서구 가족센터11
45서울관악구 가족센터7
56서울광진구 가족센터7
67서울구로구 가족센터11
78서울금천구 가족센터10
89서울노원구 가족센터7
910서울도봉구 가족센터8
순번(NO)지역센터방문지도사수
209210경남창녕군 가족센터6
210211경남창원시 가족센터15
211212경남창원시마산 가족센터15
212213경남통영시 가족센터8
213214경남하동군 가족센터5
214215경남함안군 가족센터10
215216경남함양군 가족센터6
216217경남합천군 가족센터4
217218제주서귀포시 가족센터9
218219제주제주시 가족센터15