Overview

Dataset statistics

Number of variables13
Number of observations37
Missing cells9
Missing cells (%)1.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory113.6 B

Variable types

Numeric6
Categorical2
Text4
DateTime1

Dataset

Description인천광역시 미추홀구 장애인복지시설에 대한 데이터로 장애인 복지시설의 연번, 유형, 종류, 기관명, 도로명주소, 근무자수, 이용정원, 이용현원, 시설장명, 설치신고일, 전화번호, 좌표값 등의 항목을 제공합니다.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15011882/fileData.do

Alerts

연번 is highly overall correlated with 이용현원 and 2 other fieldsHigh correlation
근무자수 is highly overall correlated with 이용정원 and 2 other fieldsHigh correlation
이용정원 is highly overall correlated with 근무자수 and 3 other fieldsHigh correlation
이용현원 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
유형 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
종류 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
이용정원 has 7 (18.9%) missing valuesMissing
이용현원 has 2 (5.4%) missing valuesMissing
연번 has unique valuesUnique
기관명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:16:02.403582
Analysis finished2023-12-12 12:16:07.484432
Duration5.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19
Minimum1
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T21:16:07.602718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.8
Q110
median19
Q328
95-th percentile35.2
Maximum37
Range36
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.824355
Coefficient of variation (CV)0.56970291
Kurtosis-1.2
Mean19
Median Absolute Deviation (MAD)9
Skewness0
Sum703
Variance117.16667
MonotonicityStrictly increasing
2023-12-12T21:16:07.916908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 1
 
2.7%
29 1
 
2.7%
22 1
 
2.7%
23 1
 
2.7%
24 1
 
2.7%
25 1
 
2.7%
26 1
 
2.7%
27 1
 
2.7%
28 1
 
2.7%
30 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
1 1
2.7%
2 1
2.7%
3 1
2.7%
4 1
2.7%
5 1
2.7%
6 1
2.7%
7 1
2.7%
8 1
2.7%
9 1
2.7%
10 1
2.7%
ValueCountFrequency (%)
37 1
2.7%
36 1
2.7%
35 1
2.7%
34 1
2.7%
33 1
2.7%
32 1
2.7%
31 1
2.7%
30 1
2.7%
29 1
2.7%
28 1
2.7%

유형
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size428.0 B
장애인 지역사회재활시설
12 
장애인 거주시설
12 
장애인 직업재활시설
8 
기타시설
4 
장애인 의료재활시설
 
1

Length

Max length12
Median length10
Mean length9.3513514
Min length4

Unique

Unique1 ?
Unique (%)2.7%

Sample

1st row장애인 지역사회재활시설
2nd row장애인 지역사회재활시설
3rd row장애인 지역사회재활시설
4th row장애인 지역사회재활시설
5th row장애인 지역사회재활시설

Common Values

ValueCountFrequency (%)
장애인 지역사회재활시설 12
32.4%
장애인 거주시설 12
32.4%
장애인 직업재활시설 8
21.6%
기타시설 4
 
10.8%
장애인 의료재활시설 1
 
2.7%

Length

2023-12-12T21:16:08.093572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:16:08.232924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장애인 33
47.1%
지역사회재활시설 12
 
17.1%
거주시설 12
 
17.1%
직업재활시설 8
 
11.4%
기타시설 4
 
5.7%
의료재활시설 1
 
1.4%

종류
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
직업재활시설
8 
공동생활가정
8 
주간보호시설
7 
장애인복지관
2 
재가복지센터
2 
Other values (7)
10 

Length

Max length10
Median length6
Mean length6.1891892
Min length5

Unique

Unique4 ?
Unique (%)10.8%

Sample

1st row장애인복지관
2nd row장애인복지관
3rd row재가복지센터
4th row재가복지센터
5th row주간보호시설

Common Values

ValueCountFrequency (%)
직업재활시설 8
21.6%
공동생활가정 8
21.6%
주간보호시설 7
18.9%
장애인복지관 2
 
5.4%
재가복지센터 2
 
5.4%
단기보호시설 2
 
5.4%
중증장애인 거주시설 2
 
5.4%
자립생활주택 2
 
5.4%
점자도서관 1
 
2.7%
의료재활시설 1
 
2.7%
Other values (2) 2
 
5.4%

Length

2023-12-12T21:16:08.422378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
직업재활시설 8
20.5%
공동생활가정 8
20.5%
주간보호시설 7
17.9%
장애인복지관 2
 
5.1%
재가복지센터 2
 
5.1%
단기보호시설 2
 
5.1%
중증장애인 2
 
5.1%
거주시설 2
 
5.1%
자립생활주택 2
 
5.1%
점자도서관 1
 
2.6%
Other values (3) 3
 
7.7%

기관명
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T21:16:08.684202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length9.8918919
Min length4

Characters and Unicode

Total characters366
Distinct characters101
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row미추홀구장애인종합복지관
2nd row인천시각장애인복지관
3rd row미추홀구장애인복지관 재가복지센터
4th row시각장애인복지관 재가복지센터
5th row미추홀구장애인복지관 주간보호센터
ValueCountFrequency (%)
주간보호센터 7
 
13.2%
미추홀구장애인복지관 2
 
3.8%
재가복지센터 2
 
3.8%
시각장애인복지관 2
 
3.8%
인천밀알장애인 2
 
3.8%
미추홀구장애인종합복지관 1
 
1.9%
공동생활가정2호 1
 
1.9%
길벗그룹홈 1
 
1.9%
길벗숭의그룹홈 1
 
1.9%
기분좋은그룹홈1 1
 
1.9%
Other values (33) 33
62.3%
2023-12-12T21:16:09.170202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 19
 
5.2%
장 17
 
4.6%
터 16
 
4.4%
16
 
4.4%
애 15
 
4.1%
센 13
 
3.6%
미 13
 
3.6%
호 13
 
3.6%
추 12
 
3.3%
보 10
 
2.7%
Other values (91) 222
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 339
92.6%
Space Separator 16
 
4.4%
Lowercase Letter 6
 
1.6%
Decimal Number 4
 
1.1%
Uppercase Letter 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 19
 
5.6%
장 17
 
5.0%
터 16
 
4.7%
애 15
 
4.4%
센 13
 
3.8%
미 13
 
3.8%
호 13
 
3.8%
추 12
 
3.5%
보 10
 
2.9%
지 9
 
2.7%
Other values (81) 202
59.6%
Lowercase Letter
ValueCountFrequency (%)
i 2
33.3%
v 1
16.7%
s 1
16.7%
o 1
16.7%
n 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
3 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 339
92.6%
Common 20
 
5.5%
Latin 7
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 19
 
5.6%
장 17
 
5.0%
터 16
 
4.7%
애 15
 
4.4%
센 13
 
3.8%
미 13
 
3.8%
호 13
 
3.8%
추 12
 
3.5%
보 10
 
2.9%
지 9
 
2.7%
Other values (81) 202
59.6%
Latin
ValueCountFrequency (%)
i 2
28.6%
v 1
14.3%
s 1
14.3%
o 1
14.3%
n 1
14.3%
N 1
14.3%
Common
ValueCountFrequency (%)
16
80.0%
1 2
 
10.0%
3 1
 
5.0%
2 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 339
92.6%
ASCII 27
 
7.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 19
 
5.6%
장 17
 
5.0%
터 16
 
4.7%
애 15
 
4.4%
센 13
 
3.8%
미 13
 
3.8%
호 13
 
3.8%
추 12
 
3.5%
보 10
 
2.9%
지 9
 
2.7%
Other values (81) 202
59.6%
ASCII
ValueCountFrequency (%)
16
59.3%
1 2
 
7.4%
i 2
 
7.4%
3 1
 
3.7%
2 1
 
3.7%
v 1
 
3.7%
s 1
 
3.7%
o 1
 
3.7%
n 1
 
3.7%
N 1
 
3.7%

도로명주소
Text

Distinct32
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T21:16:09.508797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length33
Mean length28.297297
Min length21

Characters and Unicode

Total characters1047
Distinct characters64
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)81.1%

Sample

1st row인천광역시 미추홀구 경원대로 714(관교동)
2nd row인천광역시 미추홀구 한나루로 357번길 105-19(학익동)
3rd row인천광역시 미추홀구 경원대로 714(관교동)
4th row인천광역시 미추홀구 한나루로 357번길 105-19(학익동)
5th row인천광역시 미추홀구 경원대로 714(관교동)
ValueCountFrequency (%)
인천광역시 37
22.0%
미추홀구 37
22.0%
105-19(학익동 4
 
2.4%
경원대로 4
 
2.4%
714(관교동 4
 
2.4%
한나루로 4
 
2.4%
경인로 3
 
1.8%
357번길 3
 
1.8%
염창로 2
 
1.2%
18 2
 
1.2%
Other values (64) 68
40.5%
2023-12-12T21:16:10.137630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
132
 
12.6%
인 45
 
4.3%
1 41
 
3.9%
동 39
 
3.7%
추 38
 
3.6%
홀 38
 
3.6%
천 38
 
3.6%
미 38
 
3.6%
시 37
 
3.5%
역 37
 
3.5%
Other values (54) 564
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 625
59.7%
Decimal Number 194
 
18.5%
Space Separator 132
 
12.6%
Close Punctuation 37
 
3.5%
Open Punctuation 37
 
3.5%
Dash Punctuation 11
 
1.1%
Other Punctuation 11
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 45
 
7.2%
동 39
 
6.2%
추 38
 
6.1%
홀 38
 
6.1%
천 38
 
6.1%
미 38
 
6.1%
시 37
 
5.9%
역 37
 
5.9%
광 37
 
5.9%
구 37
 
5.9%
Other values (38) 241
38.6%
Decimal Number
ValueCountFrequency (%)
1 41
21.1%
2 27
13.9%
0 26
13.4%
4 24
12.4%
3 18
9.3%
5 18
9.3%
7 18
9.3%
9 12
 
6.2%
6 6
 
3.1%
8 4
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 10
90.9%
. 1
 
9.1%
Space Separator
ValueCountFrequency (%)
132
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 625
59.7%
Common 422
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 45
 
7.2%
동 39
 
6.2%
추 38
 
6.1%
홀 38
 
6.1%
천 38
 
6.1%
미 38
 
6.1%
시 37
 
5.9%
역 37
 
5.9%
광 37
 
5.9%
구 37
 
5.9%
Other values (38) 241
38.6%
Common
ValueCountFrequency (%)
132
31.3%
1 41
 
9.7%
) 37
 
8.8%
( 37
 
8.8%
2 27
 
6.4%
0 26
 
6.2%
4 24
 
5.7%
3 18
 
4.3%
5 18
 
4.3%
7 18
 
4.3%
Other values (6) 44
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 625
59.7%
ASCII 422
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
132
31.3%
1 41
 
9.7%
) 37
 
8.8%
( 37
 
8.8%
2 27
 
6.4%
0 26
 
6.2%
4 24
 
5.7%
3 18
 
4.3%
5 18
 
4.3%
7 18
 
4.3%
Other values (6) 44
 
10.4%
Hangul
ValueCountFrequency (%)
인 45
 
7.2%
동 39
 
6.2%
추 38
 
6.1%
홀 38
 
6.1%
천 38
 
6.1%
미 38
 
6.1%
시 37
 
5.9%
역 37
 
5.9%
광 37
 
5.9%
구 37
 
5.9%
Other values (38) 241
38.6%

근무자수
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.7297297
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T21:16:10.324563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median4
Q36
95-th percentile26.6
Maximum43
Range42
Interquartile range (IQR)5

Descriptive statistics

Standard deviation9.3827521
Coefficient of variation (CV)1.3942242
Kurtosis7.0772881
Mean6.7297297
Median Absolute Deviation (MAD)2
Skewness2.6894492
Sum249
Variance88.036036
MonotonicityNot monotonic
2023-12-12T21:16:10.451688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 10
27.0%
6 6
16.2%
3 5
13.5%
5 4
 
10.8%
4 3
 
8.1%
25 2
 
5.4%
2 2
 
5.4%
9 1
 
2.7%
7 1
 
2.7%
33 1
 
2.7%
Other values (2) 2
 
5.4%
ValueCountFrequency (%)
1 10
27.0%
2 2
 
5.4%
3 5
13.5%
4 3
 
8.1%
5 4
 
10.8%
6 6
16.2%
7 1
 
2.7%
9 1
 
2.7%
10 1
 
2.7%
25 2
 
5.4%
ValueCountFrequency (%)
43 1
 
2.7%
33 1
 
2.7%
25 2
 
5.4%
10 1
 
2.7%
9 1
 
2.7%
7 1
 
2.7%
6 6
16.2%
5 4
10.8%
4 3
8.1%
3 5
13.5%

이용정원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)36.7%
Missing7
Missing (%)18.9%
Infinite0
Infinite (%)0.0%
Mean22.766667
Minimum2
Maximum256
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T21:16:10.579963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.45
Q14
median13.5
Q324.5
95-th percentile35.5
Maximum256
Range254
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation45.330726
Coefficient of variation (CV)1.9911007
Kurtosis26.405576
Mean22.766667
Median Absolute Deviation (MAD)9.5
Skewness5.0031856
Sum683
Variance2054.8747
MonotonicityNot monotonic
2023-12-12T21:16:10.715504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
4 8
21.6%
30 5
13.5%
15 4
10.8%
20 3
 
8.1%
10 3
 
8.1%
12 2
 
5.4%
26 1
 
2.7%
40 1
 
2.7%
256 1
 
2.7%
2 1
 
2.7%
(Missing) 7
18.9%
ValueCountFrequency (%)
2 1
 
2.7%
3 1
 
2.7%
4 8
21.6%
10 3
 
8.1%
12 2
 
5.4%
15 4
10.8%
20 3
 
8.1%
26 1
 
2.7%
30 5
13.5%
40 1
 
2.7%
ValueCountFrequency (%)
256 1
 
2.7%
40 1
 
2.7%
30 5
13.5%
26 1
 
2.7%
20 3
 
8.1%
15 4
10.8%
12 2
 
5.4%
10 3
 
8.1%
4 8
21.6%
3 1
 
2.7%

이용현원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24
Distinct (%)68.6%
Missing2
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean265.14286
Minimum2
Maximum3243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T21:16:10.835848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14
median14
Q328
95-th percentile1654.7
Maximum3243
Range3241
Interquartile range (IQR)24

Descriptive statistics

Standard deviation732.73726
Coefficient of variation (CV)2.7635565
Kurtosis10.928823
Mean265.14286
Median Absolute Deviation (MAD)11
Skewness3.3379458
Sum9280
Variance536903.89
MonotonicityNot monotonic
2023-12-12T21:16:11.006012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3 5
 
13.5%
2 3
 
8.1%
27 2
 
5.4%
15 2
 
5.4%
4 2
 
5.4%
10 2
 
5.4%
29 2
 
5.4%
188 1
 
2.7%
11 1
 
2.7%
34 1
 
2.7%
Other values (14) 14
37.8%
(Missing) 2
 
5.4%
ValueCountFrequency (%)
2 3
8.1%
3 5
13.5%
4 2
 
5.4%
6 1
 
2.7%
8 1
 
2.7%
9 1
 
2.7%
10 2
 
5.4%
11 1
 
2.7%
12 1
 
2.7%
14 1
 
2.7%
ValueCountFrequency (%)
3243 1
2.7%
2732 1
2.7%
1193 1
2.7%
937 1
2.7%
625 1
2.7%
188 1
2.7%
34 1
2.7%
29 2
5.4%
27 2
5.4%
24 1
2.7%

시설장명
Text

Distinct28
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T21:16:11.235466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.8918919
Min length2

Characters and Unicode

Total characters107
Distinct characters56
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

Unique22 ?
Unique (%)59.5%

Sample

1st row조흥식
2nd row이춘노
3rd row조흥식
4th row이춘노
5th row조흥식
ValueCountFrequency (%)
조흥식 3
 
8.1%
이춘노 3
 
8.1%
김솔 3
 
8.1%
하연희 2
 
5.4%
김명희 2
 
5.4%
동명희 2
 
5.4%
공보연 1
 
2.7%
백락운 1
 
2.7%
장경희 1
 
2.7%
이상빈 1
 
2.7%
Other values (18) 18
48.6%
2023-12-12T21:16:11.547997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
희 7
 
6.5%
명 6
 
5.6%
김 6
 
5.6%
조 4
 
3.7%
이 4
 
3.7%
연 4
 
3.7%
춘 3
 
2.8%
노 3
 
2.8%
경 3
 
2.8%
솔 3
 
2.8%
Other values (46) 64
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
희 7
 
6.5%
명 6
 
5.6%
김 6
 
5.6%
조 4
 
3.7%
이 4
 
3.7%
연 4
 
3.7%
춘 3
 
2.8%
노 3
 
2.8%
경 3
 
2.8%
솔 3
 
2.8%
Other values (46) 64
59.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 107
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
희 7
 
6.5%
명 6
 
5.6%
김 6
 
5.6%
조 4
 
3.7%
이 4
 
3.7%
연 4
 
3.7%
춘 3
 
2.8%
노 3
 
2.8%
경 3
 
2.8%
솔 3
 
2.8%
Other values (46) 64
59.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 107
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
희 7
 
6.5%
명 6
 
5.6%
김 6
 
5.6%
조 4
 
3.7%
이 4
 
3.7%
연 4
 
3.7%
춘 3
 
2.8%
노 3
 
2.8%
경 3
 
2.8%
솔 3
 
2.8%
Other values (46) 64
59.8%

설치신고일
Date

Distinct35
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size428.0 B
Minimum1999-09-13 00:00:00
Maximum2021-06-22 00:00:00
2023-12-12T21:16:11.671239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:11.806136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

전화번호
Text

Distinct30
Distinct (%)81.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T21:16:12.019715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.081081
Min length12

Characters and Unicode

Total characters447
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

Unique27 ?
Unique (%)73.0%

Sample

1st row032-426-1382
2nd row032-876-3500
3rd row032-426-1382
4th row032-876-3500
5th row032-426-1382
ValueCountFrequency (%)
032-426-1382 4
 
10.8%
032-876-3500 3
 
8.1%
032-886-4880 3
 
8.1%
032-881-3961 1
 
2.7%
032-861-0107 1
 
2.7%
032-427-8880 1
 
2.7%
032-515-0066 1
 
2.7%
032-883-7029 1
 
2.7%
032-421-4396 1
 
2.7%
032-863-5854 1
 
2.7%
Other values (20) 20
54.1%
2023-12-12T21:16:12.379084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 74
16.6%
0 65
14.5%
2 63
14.1%
8 57
12.8%
3 51
11.4%
6 37
8.3%
1 24
 
5.4%
7 23
 
5.1%
4 20
 
4.5%
5 18
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 373
83.4%
Dash Punctuation 74
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 65
17.4%
2 63
16.9%
8 57
15.3%
3 51
13.7%
6 37
9.9%
1 24
 
6.4%
7 23
 
6.2%
4 20
 
5.4%
5 18
 
4.8%
9 15
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 447
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 74
16.6%
0 65
14.5%
2 63
14.1%
8 57
12.8%
3 51
11.4%
6 37
8.3%
1 24
 
5.4%
7 23
 
5.1%
4 20
 
4.5%
5 18
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 447
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 74
16.6%
0 65
14.5%
2 63
14.1%
8 57
12.8%
3 51
11.4%
6 37
8.3%
1 24
 
5.4%
7 23
 
5.1%
4 20
 
4.5%
5 18
 
4.0%

위도
Real number (ℝ)

Distinct29
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.45646
Minimum37.438118
Maximum37.472484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T21:16:12.505345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.438118
5-th percentile37.438118
Q137.447004
median37.458829
Q337.465598
95-th percentile37.46849
Maximum37.472484
Range0.03436675
Interquartile range (IQR)0.01859414

Descriptive statistics

Standard deviation0.010454576
Coefficient of variation (CV)0.00027911277
Kurtosis-1.075855
Mean37.45646
Median Absolute Deviation (MAD)0.008399
Skewness-0.43985454
Sum1385.889
Variance0.00010929817
MonotonicityNot monotonic
2023-12-12T21:16:12.647754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
37.44625854 4
 
10.8%
37.43811766 4
 
10.8%
37.45882943 2
 
5.4%
37.46720152 2
 
5.4%
37.45043043 1
 
2.7%
37.45692083 1
 
2.7%
37.46385484 1
 
2.7%
37.46498085 1
 
2.7%
37.46562508 1
 
2.7%
37.45187469 1
 
2.7%
Other values (19) 19
51.4%
ValueCountFrequency (%)
37.43811766 4
10.8%
37.44041801 1
 
2.7%
37.44625854 4
10.8%
37.44700433 1
 
2.7%
37.44734598 1
 
2.7%
37.44959256 1
 
2.7%
37.45043043 1
 
2.7%
37.45187469 1
 
2.7%
37.45669018 1
 
2.7%
37.45692083 1
 
2.7%
ValueCountFrequency (%)
37.47248441 1
2.7%
37.46927133 1
2.7%
37.46829492 1
2.7%
37.46801586 1
2.7%
37.46762663 1
2.7%
37.46758653 1
2.7%
37.46720152 2
5.4%
37.46562508 1
2.7%
37.46559847 1
2.7%
37.46498085 1
2.7%

경도
Real number (ℝ)

Distinct29
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.67044
Minimum126.64498
Maximum126.69466
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T21:16:12.774323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.64498
5-th percentile126.64897
Q1126.65603
median126.67071
Q3126.6831
95-th percentile126.69151
Maximum126.69466
Range0.0496808
Interquartile range (IQR)0.0270695

Descriptive statistics

Standard deviation0.015153193
Coefficient of variation (CV)0.0001196269
Kurtosis-1.3772346
Mean126.67044
Median Absolute Deviation (MAD)0.0142473
Skewness0.024042086
Sum4686.8064
Variance0.00022961925
MonotonicityNot monotonic
2023-12-12T21:16:12.924148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
126.6903305 4
 
10.8%
126.6560275 4
 
10.8%
126.6784203 2
 
5.4%
126.6584837 2
 
5.4%
126.6707085 1
 
2.7%
126.6533126 1
 
2.7%
126.6773452 1
 
2.7%
126.6741 1
 
2.7%
126.6788763 1
 
2.7%
126.6686253 1
 
2.7%
Other values (19) 19
51.4%
ValueCountFrequency (%)
126.6449826 1
 
2.7%
126.6474753 1
 
2.7%
126.6493397 1
 
2.7%
126.6510581 1
 
2.7%
126.6533126 1
 
2.7%
126.6539591 1
 
2.7%
126.6560275 4
10.8%
126.6564905 1
 
2.7%
126.6584837 2
5.4%
126.6592379 1
 
2.7%
ValueCountFrequency (%)
126.6946634 1
 
2.7%
126.693169 1
 
2.7%
126.6910965 1
 
2.7%
126.6903305 4
10.8%
126.6850557 1
 
2.7%
126.6849558 1
 
2.7%
126.683097 1
 
2.7%
126.680592 1
 
2.7%
126.6788763 1
 
2.7%
126.6784203 2
5.4%

Interactions

2023-12-12T21:16:06.637577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:03.124060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:03.899090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:04.554930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:05.281673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:05.863418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:06.719580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:03.254312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:04.007288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:04.675217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:05.377257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:05.978410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:06.794131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:03.382574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:04.099953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:04.788823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:05.471204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:06.064759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:06.866339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:03.514961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:04.190442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:04.903092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:05.566388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:06.145084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:06.941747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:03.650919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:04.316333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:05.044077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:05.661288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:06.218624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:07.030594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:03.778632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:04.438936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:05.170996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:05.764825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:16:06.294133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:16:13.047200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번유형종류기관명도로명주소근무자수이용정원이용현원시설장명설치신고일전화번호위도경도
연번1.0000.9760.8791.0000.8750.4730.5300.0000.9760.9650.9570.0000.000
유형0.9761.0001.0001.0000.9700.6350.7950.0001.0000.9780.9950.7200.448
종류0.8791.0001.0001.0000.5310.9640.8520.8590.7840.8890.0000.6190.000
기관명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소0.8750.9700.5311.0001.0000.0000.6840.0000.9941.0001.0001.0001.000
근무자수0.4730.6350.9641.0000.0001.0000.7550.6880.9020.6580.7790.7290.561
이용정원0.5300.7950.8521.0000.6840.7551.000NaN1.0000.6840.8630.9600.410
이용현원0.0000.0000.8591.0000.0000.688NaN1.0000.0000.0000.0000.0000.000
시설장명0.9761.0000.7841.0000.9940.9021.0000.0001.0000.9920.9960.9430.944
설치신고일0.9650.9780.8891.0001.0000.6580.6840.0000.9921.0001.0001.0001.000
전화번호0.9570.9950.0001.0001.0000.7790.8630.0000.9961.0001.0000.9890.995
위도0.0000.7200.6191.0001.0000.7290.9600.0000.9431.0000.9891.0000.748
경도0.0000.4480.0001.0001.0000.5610.4100.0000.9441.0000.9950.7481.000
2023-12-12T21:16:13.216031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류유형
종류1.0000.884
유형0.8841.000
2023-12-12T21:16:13.355240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번근무자수이용정원이용현원위도경도유형종류
연번1.000-0.335-0.404-0.5960.346-0.0770.7300.626
근무자수-0.3351.0000.8680.7910.051-0.1230.4840.650
이용정원-0.4040.8681.0000.9650.133-0.1570.7820.764
이용현원-0.5960.7910.9651.000-0.254-0.1460.0000.627
위도0.3460.0510.133-0.2541.000-0.2490.4840.286
경도-0.077-0.123-0.157-0.146-0.2491.0000.1650.000
유형0.7300.4840.7820.0000.4840.1651.0000.884
종류0.6260.6500.7640.6270.2860.0000.8841.000

Missing values

2023-12-12T21:16:07.150859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:16:07.308085image/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.
2023-12-12T21:16:07.419790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번유형종류기관명도로명주소근무자수이용정원이용현원시설장명설치신고일전화번호위도경도
01장애인 지역사회재활시설장애인복지관미추홀구장애인종합복지관인천광역시 미추홀구 경원대로 714(관교동)25<NA>1193조흥식2007-08-09032-426-138237.446259126.690331
12장애인 지역사회재활시설장애인복지관인천시각장애인복지관인천광역시 미추홀구 한나루로 357번길 105-19(학익동)25<NA>2732이춘노1999-09-13032-876-350037.438118126.656027
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