Overview

Dataset statistics

Number of variables15
Number of observations31
Missing cells62
Missing cells (%)13.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory131.3 B

Variable types

Unsupported2
Text7
Numeric5
Categorical1

Dataset

Description경기도_다문화 가족지원센터 현황
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=2721

Alerts

집계년월 has 31 (100.0%) missing valuesMissing
비고 has 31 (100.0%) missing valuesMissing
시군명 has unique valuesUnique
시군코드 has unique valuesUnique
기관단체명 has unique valuesUnique
연락처 has unique valuesUnique
대표자명 has unique valuesUnique
센터장명 has unique valuesUnique
소재지우편번호 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
집계년월 is an unsupported type, check if it needs cleaning or further analysisUnsupported
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-09 22:14:25.320635
Analysis finished2024-01-09 22:14:27.877657
Duration2.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년월
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

시군명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-01-10T07:14:27.991993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0967742
Min length3

Characters and Unicode

Total characters96
Distinct characters38
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

Unique31 ?
Unique (%)100.0%

Sample

1st row수원시
2nd row고양시
3rd row성남시
4th row부천시
5th row안산시
ValueCountFrequency (%)
수원시 1
 
3.2%
군포시 1
 
3.2%
과천시 1
 
3.2%
가평군 1
 
3.2%
동두천시 1
 
3.2%
여주시 1
 
3.2%
양평군 1
 
3.2%
의왕시 1
 
3.2%
포천시 1
 
3.2%
안성시 1
 
3.2%
Other values (21) 21
67.7%
2024-01-10T07:14:28.273638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
30.2%
천 6
 
6.2%
양 5
 
5.2%
주 5
 
5.2%
군 4
 
4.2%
안 3
 
3.1%
포 3
 
3.1%
평 3
 
3.1%
성 3
 
3.1%
남 3
 
3.1%
Other values (28) 32
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
30.2%
천 6
 
6.2%
양 5
 
5.2%
주 5
 
5.2%
군 4
 
4.2%
안 3
 
3.1%
포 3
 
3.1%
평 3
 
3.1%
성 3
 
3.1%
남 3
 
3.1%
Other values (28) 32
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
30.2%
천 6
 
6.2%
양 5
 
5.2%
주 5
 
5.2%
군 4
 
4.2%
안 3
 
3.1%
포 3
 
3.1%
평 3
 
3.1%
성 3
 
3.1%
남 3
 
3.1%
Other values (28) 32
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
30.2%
천 6
 
6.2%
양 5
 
5.2%
주 5
 
5.2%
군 4
 
4.2%
안 3
 
3.1%
포 3
 
3.1%
평 3
 
3.1%
성 3
 
3.1%
남 3
 
3.1%
Other values (28) 32
33.3%

시군코드
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41424.194
Minimum41110
Maximum41830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-10T07:14:28.388421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41110
5-th percentile41140
Q141260
median41410
Q341580
95-th percentile41810
Maximum41830
Range720
Interquartile range (IQR)320

Descriptive statistics

Standard deviation208.81849
Coefficient of variation (CV)0.005040979
Kurtosis-0.78287209
Mean41424.194
Median Absolute Deviation (MAD)160
Skewness0.36277728
Sum1284150
Variance43605.161
MonotonicityNot monotonic
2024-01-10T07:14:28.513816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
41110 1
 
3.2%
41280 1
 
3.2%
41800 1
 
3.2%
41290 1
 
3.2%
41820 1
 
3.2%
41250 1
 
3.2%
41670 1
 
3.2%
41830 1
 
3.2%
41430 1
 
3.2%
41650 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
41110 1
3.2%
41130 1
3.2%
41150 1
3.2%
41170 1
3.2%
41190 1
3.2%
41210 1
3.2%
41220 1
3.2%
41250 1
3.2%
41270 1
3.2%
41280 1
3.2%
ValueCountFrequency (%)
41830 1
3.2%
41820 1
3.2%
41800 1
3.2%
41670 1
3.2%
41650 1
3.2%
41630 1
3.2%
41610 1
3.2%
41590 1
3.2%
41570 1
3.2%
41550 1
3.2%

기관단체명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-01-10T07:14:28.725007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length15.193548
Min length12

Characters and Unicode

Total characters471
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

Unique31 ?
Unique (%)100.0%

Sample

1st row수원시다문화가족지원센터
2nd row고양시다문화가족지원센터
3rd row성남시다문화가족지원센터
4th row부천시다문화가족지원센터
5th row안산시다문화가족지원센터
ValueCountFrequency (%)
수원시다문화가족지원센터 1
 
3.2%
군포시건강가정다문화가족지원센터 1
 
3.2%
과천시건강가정다문화가족지원센터 1
 
3.2%
가평군건강가정다문화가족지원센터 1
 
3.2%
동두천시건강가정다문화가족지원센터 1
 
3.2%
여주시건강가정다문화가족지원센터 1
 
3.2%
양평군건강가정다문화가족지원센터 1
 
3.2%
의왕시건강가정다문화가족지원센터 1
 
3.2%
포천시건강가정다문화가족지원센터 1
 
3.2%
안성시건강가정다문화가족지원센터 1
 
3.2%
Other values (21) 21
67.7%
2024-01-10T07:14:28.997136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 56
11.9%
화 32
 
6.8%
원 32
 
6.8%
다 31
 
6.6%
문 31
 
6.6%
족 31
 
6.6%
지 31
 
6.6%
센 31
 
6.6%
터 31
 
6.6%
시 29
 
6.2%
Other values (36) 136
28.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 471
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 56
11.9%
화 32
 
6.8%
원 32
 
6.8%
다 31
 
6.6%
문 31
 
6.6%
족 31
 
6.6%
지 31
 
6.6%
센 31
 
6.6%
터 31
 
6.6%
시 29
 
6.2%
Other values (36) 136
28.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 471
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 56
11.9%
화 32
 
6.8%
원 32
 
6.8%
다 31
 
6.6%
문 31
 
6.6%
족 31
 
6.6%
지 31
 
6.6%
센 31
 
6.6%
터 31
 
6.6%
시 29
 
6.2%
Other values (36) 136
28.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 471
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 56
11.9%
화 32
 
6.8%
원 32
 
6.8%
다 31
 
6.6%
문 31
 
6.6%
족 31
 
6.6%
지 31
 
6.6%
센 31
 
6.6%
터 31
 
6.6%
시 29
 
6.2%
Other values (36) 136
28.9%

연락처
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-01-10T07:14:29.167010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.032258
Min length11

Characters and Unicode

Total characters373
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 row031-257-8504
2nd row031-938-9801
3rd row031-740-1175
4th row032-327-1370
5th row031-599-1700
ValueCountFrequency (%)
031-257-8504 1
 
3.2%
031-395-1811 1
 
3.2%
02-503-0070 1
 
3.2%
070-7510-5876 1
 
3.2%
031-863-3822 1
 
3.2%
031-886-0327 1
 
3.2%
031-775-5952 1
 
3.2%
031-429-4782 1
 
3.2%
031-532-2065 1
 
3.2%
031-677-7191 1
 
3.2%
Other values (21) 21
67.7%
2024-01-10T07:14:29.442113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 62
16.6%
3 52
13.9%
1 52
13.9%
0 51
13.7%
7 30
8.0%
5 27
7.2%
2 25
6.7%
9 23
 
6.2%
8 22
 
5.9%
6 18
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 311
83.4%
Dash Punctuation 62
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 52
16.7%
1 52
16.7%
0 51
16.4%
7 30
9.6%
5 27
8.7%
2 25
8.0%
9 23
7.4%
8 22
7.1%
6 18
 
5.8%
4 11
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 373
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 62
16.6%
3 52
13.9%
1 52
13.9%
0 51
13.7%
7 30
8.0%
5 27
7.2%
2 25
6.7%
9 23
 
6.2%
8 22
 
5.9%
6 18
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 373
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 62
16.6%
3 52
13.9%
1 52
13.9%
0 51
13.7%
7 30
8.0%
5 27
7.2%
2 25
6.7%
9 23
 
6.2%
8 22
 
5.9%
6 18
 
4.8%

기관형태구분명
Categorical

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
학교법인
14 
사회복지법인
8 
사단법인
5 
재단법인
3 
비영리민간단체
 
1

Length

Max length7
Median length4
Mean length4.6129032
Min length4

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row사회복지법인
2nd row사회복지법인
3rd row학교법인
4th row사회복지법인
5th row비영리민간단체

Common Values

ValueCountFrequency (%)
학교법인 14
45.2%
사회복지법인 8
25.8%
사단법인 5
 
16.1%
재단법인 3
 
9.7%
비영리민간단체 1
 
3.2%

Length

2024-01-10T07:14:29.548199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:14:29.631186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학교법인 14
45.2%
사회복지법인 8
25.8%
사단법인 5
 
16.1%
재단법인 3
 
9.7%
비영리민간단체 1
 
3.2%

대표자명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-01-10T07:14:29.783399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters93
Distinct characters45
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

Unique31 ?
Unique (%)100.0%

Sample

1st row유경선
2nd row임유진
3rd row박서영
4th row오욱제
5th row문숙현
ValueCountFrequency (%)
유경선 1
 
3.2%
박성희 1
 
3.2%
정명희 1
 
3.2%
이승분 1
 
3.2%
이정숙 1
 
3.2%
박지현 1
 
3.2%
박우영 1
 
3.2%
정성순 1
 
3.2%
김지영 1
 
3.2%
임선희 1
 
3.2%
Other values (21) 21
67.7%
2024-01-10T07:14:30.042408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
희 6
 
6.5%
이 6
 
6.5%
박 6
 
6.5%
영 5
 
5.4%
성 4
 
4.3%
정 4
 
4.3%
은 3
 
3.2%
문 3
 
3.2%
연 3
 
3.2%
오 3
 
3.2%
Other values (35) 50
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
희 6
 
6.5%
이 6
 
6.5%
박 6
 
6.5%
영 5
 
5.4%
성 4
 
4.3%
정 4
 
4.3%
은 3
 
3.2%
문 3
 
3.2%
연 3
 
3.2%
오 3
 
3.2%
Other values (35) 50
53.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
희 6
 
6.5%
이 6
 
6.5%
박 6
 
6.5%
영 5
 
5.4%
성 4
 
4.3%
정 4
 
4.3%
은 3
 
3.2%
문 3
 
3.2%
연 3
 
3.2%
오 3
 
3.2%
Other values (35) 50
53.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
희 6
 
6.5%
이 6
 
6.5%
박 6
 
6.5%
영 5
 
5.4%
성 4
 
4.3%
정 4
 
4.3%
은 3
 
3.2%
문 3
 
3.2%
연 3
 
3.2%
오 3
 
3.2%
Other values (35) 50
53.8%

센터장명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-01-10T07:14:30.209243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters93
Distinct characters48
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

Unique31 ?
Unique (%)100.0%

Sample

1st row유경선
2nd row임유진
3rd row박서영
4th row오욱제
5th row문숙현
ValueCountFrequency (%)
유경선 1
 
3.2%
박성희 1
 
3.2%
창기정 1
 
3.2%
이승분 1
 
3.2%
이정숙 1
 
3.2%
박지현 1
 
3.2%
박우영 1
 
3.2%
정성순 1
 
3.2%
홍승현 1
 
3.2%
임선희 1
 
3.2%
Other values (21) 21
67.7%
2024-01-10T07:14:30.471024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
박 6
 
6.5%
이 6
 
6.5%
희 5
 
5.4%
영 4
 
4.3%
성 4
 
4.3%
정 4
 
4.3%
문 3
 
3.2%
은 3
 
3.2%
현 3
 
3.2%
연 3
 
3.2%
Other values (38) 52
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
박 6
 
6.5%
이 6
 
6.5%
희 5
 
5.4%
영 4
 
4.3%
성 4
 
4.3%
정 4
 
4.3%
문 3
 
3.2%
은 3
 
3.2%
현 3
 
3.2%
연 3
 
3.2%
Other values (38) 52
55.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
박 6
 
6.5%
이 6
 
6.5%
희 5
 
5.4%
영 4
 
4.3%
성 4
 
4.3%
정 4
 
4.3%
문 3
 
3.2%
은 3
 
3.2%
현 3
 
3.2%
연 3
 
3.2%
Other values (38) 52
55.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
박 6
 
6.5%
이 6
 
6.5%
희 5
 
5.4%
영 4
 
4.3%
성 4
 
4.3%
정 4
 
4.3%
문 3
 
3.2%
은 3
 
3.2%
현 3
 
3.2%
연 3
 
3.2%
Other values (38) 52
55.9%

개소년도
Real number (ℝ)

Distinct6
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2009.6129
Minimum2007
Maximum2013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-10T07:14:30.558203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2007
Q12008
median2010
Q32010
95-th percentile2012
Maximum2013
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5848747
Coefficient of variation (CV)0.00078864678
Kurtosis-0.081912209
Mean2009.6129
Median Absolute Deviation (MAD)1
Skewness-0.0062030952
Sum62298
Variance2.511828
MonotonicityNot monotonic
2024-01-10T07:14:30.639687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2010 14
45.2%
2008 5
 
16.1%
2011 5
 
16.1%
2007 4
 
12.9%
2013 2
 
6.5%
2009 1
 
3.2%
ValueCountFrequency (%)
2007 4
 
12.9%
2008 5
 
16.1%
2009 1
 
3.2%
2010 14
45.2%
2011 5
 
16.1%
2013 2
 
6.5%
ValueCountFrequency (%)
2013 2
 
6.5%
2011 5
 
16.1%
2010 14
45.2%
2009 1
 
3.2%
2008 5
 
16.1%
2007 4
 
12.9%

소재지우편번호
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13874.645
Minimum10071
Maximum18372
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-10T07:14:30.737107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10071
5-th percentile10642.5
Q111801.5
median13175
Q315915
95-th percentile17932.5
Maximum18372
Range8301
Interquartile range (IQR)4113.5

Descriptive statistics

Standard deviation2516.7005
Coefficient of variation (CV)0.18138846
Kurtosis-1.1347119
Mean13874.645
Median Absolute Deviation (MAD)1877
Skewness0.34764595
Sum430114
Variance6333781.6
MonotonicityNot monotonic
2024-01-10T07:14:30.831715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
16305 1
 
3.2%
10362 1
 
3.2%
11026 1
 
3.2%
13801 1
 
3.2%
12414 1
 
3.2%
11330 1
 
3.2%
12631 1
 
3.2%
12550 1
 
3.2%
16007 1
 
3.2%
11160 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
10071 1
3.2%
10362 1
3.2%
10923 1
3.2%
11026 1
3.2%
11160 1
3.2%
11330 1
3.2%
11443 1
3.2%
11649 1
3.2%
11954 1
3.2%
12284 1
3.2%
ValueCountFrequency (%)
18372 1
3.2%
18135 1
3.2%
17730 1
3.2%
17590 1
3.2%
17375 1
3.2%
16942 1
3.2%
16305 1
3.2%
16007 1
3.2%
15823 1
3.2%
15385 1
3.2%

소재지지번주소
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-01-10T07:14:31.031562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length20.741935
Min length17

Characters and Unicode

Total characters643
Distinct characters103
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 row경기도 수원시 장안구 송죽동 506-8번지
2nd row경기도 고양시 일산동구 정발산동 677-1번지
3rd row경기도 성남시 중원구 금광동 2661번지
4th row경기도 부천시 원미동 184-5번지
5th row경기도 안산시 단원구 초지동 667-2번지
ValueCountFrequency (%)
경기도 31
 
22.8%
198-1번지 1
 
0.7%
포천시 1
 
0.7%
296-5번지 1
 
0.7%
숭인동 1
 
0.7%
안성시 1
 
0.7%
390번지 1
 
0.7%
교문동 1
 
0.7%
구리시 1
 
0.7%
187번지 1
 
0.7%
Other values (96) 96
70.6%
2024-01-10T07:14:31.347804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
 
16.3%
지 34
 
5.3%
동 32
 
5.0%
경 31
 
4.8%
1 31
 
4.8%
도 31
 
4.8%
기 31
 
4.8%
번 31
 
4.8%
시 29
 
4.5%
- 20
 
3.1%
Other values (93) 268
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 396
61.6%
Decimal Number 122
 
19.0%
Space Separator 105
 
16.3%
Dash Punctuation 20
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 34
 
8.6%
동 32
 
8.1%
경 31
 
7.8%
도 31
 
7.8%
기 31
 
7.8%
번 31
 
7.8%
시 29
 
7.3%
산 10
 
2.5%
구 8
 
2.0%
천 6
 
1.5%
Other values (81) 153
38.6%
Decimal Number
ValueCountFrequency (%)
1 31
25.4%
5 14
11.5%
7 13
10.7%
8 13
10.7%
6 13
10.7%
2 13
10.7%
9 7
 
5.7%
3 6
 
4.9%
4 6
 
4.9%
0 6
 
4.9%
Space Separator
ValueCountFrequency (%)
105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 396
61.6%
Common 247
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 34
 
8.6%
동 32
 
8.1%
경 31
 
7.8%
도 31
 
7.8%
기 31
 
7.8%
번 31
 
7.8%
시 29
 
7.3%
산 10
 
2.5%
구 8
 
2.0%
천 6
 
1.5%
Other values (81) 153
38.6%
Common
ValueCountFrequency (%)
105
42.5%
1 31
 
12.6%
- 20
 
8.1%
5 14
 
5.7%
7 13
 
5.3%
8 13
 
5.3%
6 13
 
5.3%
2 13
 
5.3%
9 7
 
2.8%
3 6
 
2.4%
Other values (2) 12
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 396
61.6%
ASCII 247
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
42.5%
1 31
 
12.6%
- 20
 
8.1%
5 14
 
5.7%
7 13
 
5.3%
8 13
 
5.3%
6 13
 
5.3%
2 13
 
5.3%
9 7
 
2.8%
3 6
 
2.4%
Other values (2) 12
 
4.9%
Hangul
ValueCountFrequency (%)
지 34
 
8.6%
동 32
 
8.1%
경 31
 
7.8%
도 31
 
7.8%
기 31
 
7.8%
번 31
 
7.8%
시 29
 
7.3%
산 10
 
2.5%
구 8
 
2.0%
천 6
 
1.5%
Other values (81) 153
38.6%

소재지도로명주소
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-01-10T07:14:31.561998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length17.290323
Min length14

Characters and Unicode

Total characters536
Distinct characters95
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 row경기도 수원시 장안구 송원로 63
2nd row경기도 고양시 일산동구 대산로 27
3rd row경기도 성남시 중원구 광명로395번길 1
4th row경기도 부천시 조종로68번가길 4
5th row경기도 안산시 단원구 화정로 26
ValueCountFrequency (%)
경기도 31
 
23.1%
중앙로 2
 
1.5%
19 2
 
1.5%
송원로 1
 
0.7%
해룡로 1
 
0.7%
15 1
 
0.7%
산수유길 1
 
0.7%
안성시 1
 
0.7%
453 1
 
0.7%
아차산로 1
 
0.7%
Other values (92) 92
68.7%
2024-01-10T07:14:31.869438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
103
19.2%
경 32
 
6.0%
도 31
 
5.8%
기 31
 
5.8%
로 29
 
5.4%
시 29
 
5.4%
1 21
 
3.9%
2 13
 
2.4%
5 13
 
2.4%
4 11
 
2.1%
Other values (85) 223
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 338
63.1%
Space Separator 103
 
19.2%
Decimal Number 94
 
17.5%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 32
 
9.5%
도 31
 
9.2%
기 31
 
9.2%
로 29
 
8.6%
시 29
 
8.6%
길 10
 
3.0%
천 9
 
2.7%
산 8
 
2.4%
번 8
 
2.4%
구 7
 
2.1%
Other values (73) 144
42.6%
Decimal Number
ValueCountFrequency (%)
1 21
22.3%
2 13
13.8%
5 13
13.8%
4 11
11.7%
9 10
10.6%
3 10
10.6%
6 6
 
6.4%
8 4
 
4.3%
0 3
 
3.2%
7 3
 
3.2%
Space Separator
ValueCountFrequency (%)
103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 338
63.1%
Common 198
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 32
 
9.5%
도 31
 
9.2%
기 31
 
9.2%
로 29
 
8.6%
시 29
 
8.6%
길 10
 
3.0%
천 9
 
2.7%
산 8
 
2.4%
번 8
 
2.4%
구 7
 
2.1%
Other values (73) 144
42.6%
Common
ValueCountFrequency (%)
103
52.0%
1 21
 
10.6%
2 13
 
6.6%
5 13
 
6.6%
4 11
 
5.6%
9 10
 
5.1%
3 10
 
5.1%
6 6
 
3.0%
8 4
 
2.0%
0 3
 
1.5%
Other values (2) 4
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 338
63.1%
ASCII 198
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
103
52.0%
1 21
 
10.6%
2 13
 
6.6%
5 13
 
6.6%
4 11
 
5.6%
9 10
 
5.1%
3 10
 
5.1%
6 6
 
3.0%
8 4
 
2.0%
0 3
 
1.5%
Other values (2) 4
 
2.0%
Hangul
ValueCountFrequency (%)
경 32
 
9.5%
도 31
 
9.2%
기 31
 
9.2%
로 29
 
8.6%
시 29
 
8.6%
길 10
 
3.0%
천 9
 
2.7%
산 8
 
2.4%
번 8
 
2.4%
구 7
 
2.1%
Other values (73) 144
42.6%

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

위도
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.489898
Minimum37.009005
Maximum38.030645
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-10T07:14:31.979231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.009005
5-th percentile37.107443
Q137.315991
median37.447593
Q337.658392
95-th percentile37.886992
Maximum38.030645
Range1.0216399
Interquartile range (IQR)0.34240093

Descriptive statistics

Standard deviation0.25234443
Coefficient of variation (CV)0.0067309979
Kurtosis-0.45345893
Mean37.489898
Median Absolute Deviation (MAD)0.15523135
Skewness0.25262761
Sum1162.1868
Variance0.06367771
MonotonicityNot monotonic
2024-01-10T07:14:32.075280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
37.30077556 1
 
3.2%
37.44759315 1
 
3.2%
38.03064477 1
 
3.2%
37.83046633 1
 
3.2%
37.90400569 1
 
3.2%
37.86997801 1
 
3.2%
37.60155489 1
 
3.2%
37.82168325 1
 
3.2%
37.75682566 1
 
3.2%
37.73659912 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
37.00900485 1
3.2%
37.06571556 1
3.2%
37.14916972 1
3.2%
37.20308359 1
3.2%
37.27825003 1
3.2%
37.2923618 1
3.2%
37.29965686 1
3.2%
37.30077556 1
3.2%
37.33120573 1
3.2%
37.34812172 1
3.2%
ValueCountFrequency (%)
38.03064477 1
3.2%
37.90400569 1
3.2%
37.86997801 1
3.2%
37.83046633 1
3.2%
37.82168325 1
3.2%
37.75682566 1
3.2%
37.73659912 1
3.2%
37.67008305 1
3.2%
37.64670009 1
3.2%
37.61049919 1
3.2%

경도
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.0698
Minimum126.62017
Maximum127.63629
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-10T07:14:32.179377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.62017
5-th percentile126.7598
Q1126.93524
median127.05338
Q3127.17049
95-th percentile127.50466
Maximum127.63629
Range1.016124
Interquartile range (IQR)0.2352503

Descriptive statistics

Standard deviation0.23652366
Coefficient of variation (CV)0.0018613681
Kurtosis0.26942418
Mean127.0698
Median Absolute Deviation (MAD)0.1178302
Skewness0.51324471
Sum3939.1637
Variance0.055943443
MonotonicityNot monotonic
2024-01-10T07:14:32.278936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
127.0083826 1
 
3.2%
127.1697646 1
 
3.2%
127.0671694 1
 
3.2%
127.5100224 1
 
3.2%
127.0533777 1
 
3.2%
127.1556769 1
 
3.2%
127.131276 1
 
3.2%
127.0467581 1
 
3.2%
126.7793008 1
 
3.2%
127.0389401 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
126.6201709 1
3.2%
126.7463509 1
3.2%
126.7732558 1
3.2%
126.7793008 1
3.2%
126.792458 1
3.2%
126.8153867 1
3.2%
126.8711594 1
3.2%
126.9190355 1
3.2%
126.9514364 1
3.2%
126.9924339 1
3.2%
ValueCountFrequency (%)
127.6362949 1
3.2%
127.5100224 1
3.2%
127.4993032 1
3.2%
127.4410457 1
3.2%
127.2748051 1
3.2%
127.2553625 1
3.2%
127.2038881 1
3.2%
127.1712079 1
3.2%
127.1697646 1
3.2%
127.1556769 1
3.2%

Interactions

2024-01-10T07:14:27.334538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:25.797246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:26.356278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:26.690405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:27.015162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:27.401216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:25.867131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:26.423779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:26.760636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:27.084794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:27.466437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:25.943151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:26.491557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:26.829374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:27.150819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:27.525369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:26.009792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:26.558654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:26.891017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:27.211676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:27.586882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:26.075207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:26.626103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:26.954642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:14:27.271132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:14:32.359279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명시군코드기관단체명연락처기관형태구분명대표자명센터장명개소년도소재지우편번호소재지지번주소소재지도로명주소위도경도
시군명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시군코드1.0001.0001.0001.0000.0001.0001.0000.4750.3851.0001.0000.0000.504
기관단체명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
기관형태구분명1.0000.0001.0001.0001.0001.0001.0000.0000.6961.0001.0000.4510.457
대표자명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
센터장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
개소년도1.0000.4751.0001.0000.0001.0001.0001.0000.0001.0001.0000.7690.000
소재지우편번호1.0000.3851.0001.0000.6961.0001.0000.0001.0001.0001.0000.0000.265
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도1.0000.0001.0001.0000.4511.0001.0000.7690.0001.0001.0001.0000.395
경도1.0000.5041.0001.0000.4571.0001.0000.0000.2651.0001.0000.3951.000
2024-01-10T07:14:32.695506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군코드개소년도소재지우편번호위도경도기관형태구분명
시군코드1.0000.438-0.2180.3350.2770.000
개소년도0.4381.000-0.0970.2710.1350.045
소재지우편번호-0.218-0.0971.000-0.217-0.2880.311
위도0.3350.271-0.2171.000-0.0950.151
경도0.2770.135-0.288-0.0951.0000.245
기관형태구분명0.0000.0450.3110.1510.2451.000

Missing values

2024-01-10T07:14:27.682487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:14:27.823578image/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

집계년월시군명시군코드기관단체명연락처기관형태구분명대표자명센터장명개소년도소재지우편번호소재지지번주소소재지도로명주소비고위도경도
0<NA>수원시41110수원시다문화가족지원센터031-257-8504사회복지법인유경선유경선200716305경기도 수원시 장안구 송죽동 506-8번지경기도 수원시 장안구 송원로 63<NA>37.300776127.008383
1<NA>고양시41280고양시다문화가족지원센터031-938-9801사회복지법인임유진임유진200810362경기도 고양시 일산동구 정발산동 677-1번지경기도 고양시 일산동구 대산로 27<NA>37.447593127.169765
2<NA>성남시41130성남시다문화가족지원센터031-740-1175학교법인박서영박서영200813175경기도 성남시 중원구 금광동 2661번지경기도 성남시 중원구 광명로395번길 1<NA>37.299657127.074328
3<NA>부천시41190부천시다문화가족지원센터032-327-1370사회복지법인오욱제오욱제200714646경기도 부천시 원미동 184-5번지경기도 부천시 조종로68번가길 4<NA>37.491826126.792458
4<NA>안산시41270안산시다문화가족지원센터031-599-1700비영리민간단체문숙현문숙현200815385경기도 안산시 단원구 초지동 667-2번지경기도 안산시 단원구 화정로 26<NA>37.331206126.815387
5<NA>용인시41460용인시건강가정다문화가족지원센터031-323-7133사회복지법인이수희이수희201016942경기도 용인시 수지구 상현동 1129-2번지경기도 용인시 수지구 법조로 230<NA>37.392584126.951436
6<NA>화성시41590화성시다문화가족지원센터031-267-8786학교법인박미경박미경201018372경기도 화성시 병점동 734번지경기도 화성시 태안로 145<NA>37.203084127.033289
7<NA>남양주시41360남양주시건강가정다문화가족지원센터031-553-8211학교법인이주연이주연200912284경기도 남양주시 다산동 3159-7번지경기도 남양주시 경춘로 522<NA>37.065716127.066134
8<NA>안양시41170안양시건강가정다문화가족지원센터031-8045-5572학교법인오연주오연주201014047경기도 안양시 동안구 비산동 1111번지경기도 안양시 동안구 동안로 158<NA>37.348122126.746351
9<NA>평택시41220평택시건강가정다문화가족지원센터031-615-3959재단법인송문영송문영201017730경기도 평택시 서정동 산12번지경기도 평택시 서정로 295<NA>37.6467126.620171
집계년월시군명시군코드기관단체명연락처기관형태구분명대표자명센터장명개소년도소재지우편번호소재지지번주소소재지도로명주소비고위도경도
21<NA>구리시41310구리시건강가정다문화가족지원센터031-556-4140학교법인윤성은윤성은200811954경기도 구리시 교문동 390번지경기도 구리시 아차산로 453<NA>37.670083126.773256
22<NA>안성시41550안성시건강가정다문화가족지원센터031-677-7191사회복지법인임선희임선희200717590경기도 안성시 숭인동 296-5번지경기도 안성시 산수유길 15<NA>37.610499127.171208
23<NA>포천시41650포천시건강가정다문화가족지원센터031-532-2065학교법인김지영홍승현200811160경기도 포천시 동교동 198-1번지경기도 포천시 해룡로 120<NA>37.736599127.03894
24<NA>의왕시41430의왕시건강가정다문화가족지원센터031-429-4782사회복지법인정성순정성순201016007경기도 의왕시 청계동 983번지경기도 의왕시 덕장로 19<NA>37.756826126.779301
25<NA>양평군41830양평군건강가정다문화가족지원센터031-775-5952학교법인박우영박우영201012550경기도 양평군 양평읍 공흥리 310-8번지경기도 양평군 양평읍 중앙로111번길 34-23<NA>37.821683127.046758
26<NA>여주시41670여주시건강가정다문화가족지원센터031-886-0327학교법인박지현박지현201112631경기도 여주시 홍문동 181번지 현대아파트경기도 여주시 세종로 61<NA>37.601555127.131276
27<NA>동두천시41250동두천시건강가정다문화가족지원센터031-863-3822학교법인이정숙이정숙201111330경기도 동두천시 생연동 665-2번지경기도 동두천시 중앙로 249<NA>37.869978127.155677
28<NA>가평군41820가평군건강가정다문화가족지원센터070-7510-5876재단법인이승분이승분201012414경기도 가평군 가평읍 읍내리 608-5번지 가평군2청사경기도 가평군 가평읍 석봉로 191번길 10<NA>37.904006127.053378
29<NA>과천시41290과천시건강가정다문화가족지원센터02-503-0070재단법인정명희창기정201013801경기도 과천시 관문동 107-5번지경기도 과천시 관악산길 58<NA>37.830466127.510022
30<NA>연천군41800연천군건강가정다문화가족지원센터031-835-1107학교법인조금랑조금랑201111026경기도 연천군 전곡읍 은대리 541-6번지경기도 연천군 전곡읍 전영로 11<NA>38.030645127.067169