Overview

Dataset statistics

Number of variables4
Number of observations175
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory33.8 B

Variable types

Categorical1
Text2
Numeric1

Dataset

Description한국건강가정진흥원에서 제공하는 전국 다문화가족지원센터 사례관리 담당자수 정보입니다.구성 항목은 지역, 센터, 대표전화, 사례관리담당자수(재직중)입니다.
Author한국건강가정진흥원
URLhttps://www.data.go.kr/data/15087749/fileData.do

Alerts

센터 has unique valuesUnique
사례관리담당자수(재직중) has 14 (8.0%) zerosZeros

Reproduction

Analysis started2023-12-12 15:02:54.750896
Analysis finished2023-12-12 15:02:55.245839
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

Distinct17
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
서울특별시
25 
경기도
22 
전라남도
22 
경상북도
15 
충청남도
12 
Other values (12)
79 

Length

Max length7
Median length5
Mean length4.2342857
Min length3

Unique

Unique2 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 25
14.3%
경기도 22
12.6%
전라남도 22
12.6%
경상북도 15
8.6%
충청남도 12
 
6.9%
충청북도 11
 
6.3%
인천광역시 10
 
5.7%
부산광역시 10
 
5.7%
경상남도 9
 
5.1%
강원도 9
 
5.1%
Other values (7) 30
17.1%

Length

2023-12-13T00:02:55.336028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 25
14.3%
전라남도 22
12.6%
경기도 22
12.6%
경상북도 15
8.6%
충청남도 12
 
6.9%
충청북도 11
 
6.3%
인천광역시 10
 
5.7%
부산광역시 10
 
5.7%
전라북도 9
 
5.1%
경상남도 9
 
5.1%
Other values (7) 30
17.1%

센터
Text

UNIQUE 

Distinct175
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T00:02:55.609642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length7
Mean length7.7142857
Min length7

Characters and Unicode

Total characters1350
Distinct characters124
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

Unique175 ?
Unique (%)100.0%

Sample

1st row강남구가족센터
2nd row강동구가족센터
3rd row강북구가족센터
4th row강서구가족센터
5th row관악구가족센터
ValueCountFrequency (%)
강남구가족센터 1
 
0.6%
보령시가족센터 1
 
0.6%
서산시가족센터 1
 
0.6%
서천군가족센터 1
 
0.6%
아산시가족센터 1
 
0.6%
천안시다문화가족지원센터 1
 
0.6%
청양군가족센터 1
 
0.6%
홍성군가족센터 1
 
0.6%
군산시가족센터 1
 
0.6%
김제시가족센터 1
 
0.6%
Other values (165) 165
94.3%
2023-12-13T00:02:56.040710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 176
13.0%
족 175
13.0%
센 175
13.0%
터 175
13.0%
구 67
 
5.0%
시 67
 
5.0%
군 54
 
4.0%
산 25
 
1.9%
천 23
 
1.7%
원 22
 
1.6%
Other values (114) 391
29.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1350
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 176
13.0%
족 175
13.0%
센 175
13.0%
터 175
13.0%
구 67
 
5.0%
시 67
 
5.0%
군 54
 
4.0%
산 25
 
1.9%
천 23
 
1.7%
원 22
 
1.6%
Other values (114) 391
29.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1350
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 176
13.0%
족 175
13.0%
센 175
13.0%
터 175
13.0%
구 67
 
5.0%
시 67
 
5.0%
군 54
 
4.0%
산 25
 
1.9%
천 23
 
1.7%
원 22
 
1.6%
Other values (114) 391
29.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1350
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 176
13.0%
족 175
13.0%
센 175
13.0%
터 175
13.0%
구 67
 
5.0%
시 67
 
5.0%
군 54
 
4.0%
산 25
 
1.9%
천 23
 
1.7%
원 22
 
1.6%
Other values (114) 391
29.0%

대표전화
Text

Distinct172
Distinct (%)98.9%
Missing1
Missing (%)0.6%
Memory size1.5 KiB
2023-12-13T00:02:56.287363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.908046
Min length11

Characters and Unicode

Total characters2072
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

Unique170 ?
Unique (%)97.7%

Sample

1st row02-3412-2222
2nd row02-471-0812
3rd row02-987-2567
4th row02-2606-2017
5th row02-883-9383
ValueCountFrequency (%)
051-465-7171 2
 
1.1%
055-225-3951 2
 
1.1%
063-433-4888 1
 
0.6%
063-531-0309 1
 
0.6%
061-832-5399 1
 
0.6%
061-433-9004 1
 
0.6%
02-3412-2222 1
 
0.6%
063-545-8506 1
 
0.6%
041-664-2710 1
 
0.6%
041-953-2911 1
 
0.6%
Other values (162) 162
93.1%
2023-12-13T00:02:56.651175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 348
16.8%
0 297
14.3%
3 257
12.4%
5 195
9.4%
1 184
8.9%
2 176
8.5%
4 170
8.2%
6 119
 
5.7%
8 112
 
5.4%
9 111
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1724
83.2%
Dash Punctuation 348
 
16.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 297
17.2%
3 257
14.9%
5 195
11.3%
1 184
10.7%
2 176
10.2%
4 170
9.9%
6 119
6.9%
8 112
 
6.5%
9 111
 
6.4%
7 103
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 348
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2072
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 348
16.8%
0 297
14.3%
3 257
12.4%
5 195
9.4%
1 184
8.9%
2 176
8.5%
4 170
8.2%
6 119
 
5.7%
8 112
 
5.4%
9 111
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2072
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 348
16.8%
0 297
14.3%
3 257
12.4%
5 195
9.4%
1 184
8.9%
2 176
8.5%
4 170
8.2%
6 119
 
5.7%
8 112
 
5.4%
9 111
 
5.4%

사례관리담당자수(재직중)
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4971429
Minimum0
Maximum8
Zeros14
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T00:02:56.758713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1590438
Coefficient of variation (CV)0.7741705
Kurtosis8.9375149
Mean1.4971429
Median Absolute Deviation (MAD)0
Skewness2.4376735
Sum262
Variance1.3433826
MonotonicityNot monotonic
2023-12-13T00:02:56.852823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 101
57.7%
2 39
 
22.3%
0 14
 
8.0%
3 11
 
6.3%
4 6
 
3.4%
5 1
 
0.6%
6 1
 
0.6%
7 1
 
0.6%
8 1
 
0.6%
ValueCountFrequency (%)
0 14
 
8.0%
1 101
57.7%
2 39
 
22.3%
3 11
 
6.3%
4 6
 
3.4%
5 1
 
0.6%
6 1
 
0.6%
7 1
 
0.6%
8 1
 
0.6%
ValueCountFrequency (%)
8 1
 
0.6%
7 1
 
0.6%
6 1
 
0.6%
5 1
 
0.6%
4 6
 
3.4%
3 11
 
6.3%
2 39
 
22.3%
1 101
57.7%
0 14
 
8.0%

Interactions

2023-12-13T00:02:54.937568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:02:56.933754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역사례관리담당자수(재직중)
지역1.0000.684
사례관리담당자수(재직중)0.6841.000
2023-12-13T00:02:57.007808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사례관리담당자수(재직중)지역
사례관리담당자수(재직중)1.0000.345
지역0.3451.000

Missing values

2023-12-13T00:02:55.087247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:02:55.197024image/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

지역센터대표전화사례관리담당자수(재직중)
0서울특별시강남구가족센터02-3412-22221
1서울특별시강동구가족센터02-471-08121
2서울특별시강북구가족센터02-987-25671
3서울특별시강서구가족센터02-2606-20171
4서울특별시관악구가족센터02-883-93834
5서울특별시광진구가족센터02-458-06221
6서울특별시구로구가족센터02-869-03175
7서울특별시금천구가족센터02-803-77471
8서울특별시노원구가족센터02-979-35012
9서울특별시도봉구가족센터02-995-68002
지역센터대표전화사례관리담당자수(재직중)
165경상남도김해시가족센터055-329-63493
166경상남도밀양시가족센터055-351-44043
167경상남도양산시가족센터055-382-09881
168경상남도진주시가족센터055-749-54431
169경상남도창원시가족센터055-225-39510
170경상남도창원시마산가족센터055-225-39511
171경상남도통영시가족센터055-640-77411
172경상남도함안군가족센터055-583-54301
173제주특별자치도서귀포시가족센터064-762-11411
174제주특별자치도제주시가족센터064-725-80051