Overview

Dataset statistics

Number of variables5
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory45.6 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description인천광역시 관내 노인대학(노인교실) 현황에 대한 데이터로 군구명, 노인대학명, 위치, 연락처 등을 제공합니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15083270&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 군구명High correlation
군구명 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
노인대학명 has unique valuesUnique
연락처 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:47:41.090999
Analysis finished2024-03-18 05:47:43.275837
Duration2.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-03-18T14:47:43.337567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q18
median15
Q322
95-th percentile27.6
Maximum29
Range28
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.5146932
Coefficient of variation (CV)0.56764621
Kurtosis-1.2
Mean15
Median Absolute Deviation (MAD)7
Skewness0
Sum435
Variance72.5
MonotonicityStrictly increasing
2024-03-18T14:47:43.451507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 1
 
3.4%
2 1
 
3.4%
29 1
 
3.4%
28 1
 
3.4%
27 1
 
3.4%
26 1
 
3.4%
25 1
 
3.4%
24 1
 
3.4%
23 1
 
3.4%
22 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
1 1
3.4%
2 1
3.4%
3 1
3.4%
4 1
3.4%
5 1
3.4%
6 1
3.4%
7 1
3.4%
8 1
3.4%
9 1
3.4%
10 1
3.4%
ValueCountFrequency (%)
29 1
3.4%
28 1
3.4%
27 1
3.4%
26 1
3.4%
25 1
3.4%
24 1
3.4%
23 1
3.4%
22 1
3.4%
21 1
3.4%
20 1
3.4%

군구명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Memory size364.0 B
남동구
6 
계양구
6 
부평구
5 
중구
3 
미추홀구
3 
Other values (5)
6 

Length

Max length4
Median length3
Mean length3.1034483
Min length2

Unique

Unique4 ?
Unique (%)13.8%

Sample

1st row중구
2nd row중구
3rd row중구
4th row동구
5th row미추홀구

Common Values

ValueCountFrequency (%)
남동구 6
20.7%
계양구 6
20.7%
부평구 5
17.2%
중구 3
10.3%
미추홀구 3
10.3%
서구 2
 
6.9%
동구 1
 
3.4%
연수구 1
 
3.4%
남동구 1
 
3.4%
강화군 1
 
3.4%

Length

2024-03-18T14:47:43.599819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:47:43.716873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동구 7
24.1%
계양구 6
20.7%
부평구 5
17.2%
중구 3
10.3%
미추홀구 3
10.3%
서구 2
 
6.9%
동구 1
 
3.4%
연수구 1
 
3.4%
강화군 1
 
3.4%

노인대학명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-03-18T14:47:43.892165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length8.7586207
Min length6

Characters and Unicode

Total characters254
Distinct characters76
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

Unique29 ?
Unique (%)100.0%

Sample

1st row중구지회부설노인대학
2nd row내리교회노인대학
3rd row송월교회노인대학
4th row대한노인회동구지회부설 노인대학
5th row미추홀구노인대학
ValueCountFrequency (%)
노인대학 4
 
10.5%
대한노인회 2
 
5.3%
중구지회부설노인대학 1
 
2.6%
효성영광노인대학 1
 
2.6%
선일노인대학 1
 
2.6%
행복한 1
 
2.6%
실버대학 1
 
2.6%
산곡소망소인대학 1
 
2.6%
계양구지회 1
 
2.6%
부설노인대학 1
 
2.6%
Other values (24) 24
63.2%
2024-03-18T14:47:44.226257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 30
 
11.8%
인 29
 
11.4%
노 27
 
10.6%
학 26
 
10.2%
회 14
 
5.5%
10
 
3.9%
구 8
 
3.1%
지 8
 
3.1%
부 7
 
2.8%
한 6
 
2.4%
Other values (66) 89
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 244
96.1%
Space Separator 10
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 30
 
12.3%
인 29
 
11.9%
노 27
 
11.1%
학 26
 
10.7%
회 14
 
5.7%
구 8
 
3.3%
지 8
 
3.3%
부 7
 
2.9%
한 6
 
2.5%
설 5
 
2.0%
Other values (65) 84
34.4%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 244
96.1%
Common 10
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 30
 
12.3%
인 29
 
11.9%
노 27
 
11.1%
학 26
 
10.7%
회 14
 
5.7%
구 8
 
3.3%
지 8
 
3.3%
부 7
 
2.9%
한 6
 
2.5%
설 5
 
2.0%
Other values (65) 84
34.4%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 244
96.1%
ASCII 10
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 30
 
12.3%
인 29
 
11.9%
노 27
 
11.1%
학 26
 
10.7%
회 14
 
5.7%
구 8
 
3.3%
지 8
 
3.3%
부 7
 
2.9%
한 6
 
2.5%
설 5
 
2.0%
Other values (65) 84
34.4%
ASCII
ValueCountFrequency (%)
10
100.0%

연락처
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-03-18T14:47:44.446656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length11

Characters and Unicode

Total characters348
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

Unique29 ?
Unique (%)100.0%

Sample

1st row032-772-2579
2nd row032-760-4052
3rd row032-765-7851
4th row032-773-6404
5th row032-862-0915
ValueCountFrequency (%)
032-772-2579 1
 
3.4%
032-503-1035 1
 
3.4%
032-581-4043 1
 
3.4%
032-572-1460 1
 
3.4%
070-7834-1346 1
 
3.4%
032-544-8909 1
 
3.4%
032-515-3201 1
 
3.4%
032-554-1741 1
 
3.4%
032-547-0003 1
 
3.4%
032-546-2923 1
 
3.4%
Other values (19) 19
65.5%
2024-03-18T14:47:44.775411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 58
16.7%
0 53
15.2%
2 46
13.2%
3 44
12.6%
4 34
9.8%
5 28
8.0%
1 21
 
6.0%
6 20
 
5.7%
7 17
 
4.9%
8 16
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 290
83.3%
Dash Punctuation 58
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 53
18.3%
2 46
15.9%
3 44
15.2%
4 34
11.7%
5 28
9.7%
1 21
 
7.2%
6 20
 
6.9%
7 17
 
5.9%
8 16
 
5.5%
9 11
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 58
16.7%
0 53
15.2%
2 46
13.2%
3 44
12.6%
4 34
9.8%
5 28
8.0%
1 21
 
6.0%
6 20
 
5.7%
7 17
 
4.9%
8 16
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 58
16.7%
0 53
15.2%
2 46
13.2%
3 44
12.6%
4 34
9.8%
5 28
8.0%
1 21
 
6.0%
6 20
 
5.7%
7 17
 
4.9%
8 16
 
4.6%

주소
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-03-18T14:47:45.005642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length11.172414
Min length6

Characters and Unicode

Total characters324
Distinct characters81
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row제물량로80번길 3-24
2nd row우현로67번길 3-1
3rd row동화마을길 65
4th row샛골로 177(송림동)
5th row학익소로37번길 17(주안동)
ValueCountFrequency (%)
11 2
 
3.1%
28 2
 
3.1%
제물량로80번길 1
 
1.6%
굴포로 1
 
1.6%
114 1
 
1.6%
부평대로 1
 
1.6%
63번길 1
 
1.6%
5 1
 
1.6%
세월천로 1
 
1.6%
25번길 1
 
1.6%
Other values (52) 52
81.2%
2024-03-18T14:47:45.314761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
10.8%
로 28
 
8.6%
1 25
 
7.7%
길 17
 
5.2%
번 16
 
4.9%
3 13
 
4.0%
4 12
 
3.7%
6 12
 
3.7%
7 11
 
3.4%
2 11
 
3.4%
Other values (71) 144
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 164
50.6%
Decimal Number 106
32.7%
Space Separator 35
 
10.8%
Open Punctuation 8
 
2.5%
Close Punctuation 8
 
2.5%
Dash Punctuation 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 28
 
17.1%
길 17
 
10.4%
번 16
 
9.8%
동 9
 
5.5%
화 4
 
2.4%
대 4
 
2.4%
부 3
 
1.8%
만 3
 
1.8%
수 3
 
1.8%
서 3
 
1.8%
Other values (57) 74
45.1%
Decimal Number
ValueCountFrequency (%)
1 25
23.6%
3 13
12.3%
4 12
11.3%
6 12
11.3%
7 11
10.4%
2 11
10.4%
8 6
 
5.7%
5 6
 
5.7%
0 5
 
4.7%
9 5
 
4.7%
Space Separator
ValueCountFrequency (%)
35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 164
50.6%
Common 160
49.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 28
 
17.1%
길 17
 
10.4%
번 16
 
9.8%
동 9
 
5.5%
화 4
 
2.4%
대 4
 
2.4%
부 3
 
1.8%
만 3
 
1.8%
수 3
 
1.8%
서 3
 
1.8%
Other values (57) 74
45.1%
Common
ValueCountFrequency (%)
35
21.9%
1 25
15.6%
3 13
 
8.1%
4 12
 
7.5%
6 12
 
7.5%
7 11
 
6.9%
2 11
 
6.9%
( 8
 
5.0%
) 8
 
5.0%
8 6
 
3.8%
Other values (4) 19
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 164
50.6%
ASCII 160
49.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
21.9%
1 25
15.6%
3 13
 
8.1%
4 12
 
7.5%
6 12
 
7.5%
7 11
 
6.9%
2 11
 
6.9%
( 8
 
5.0%
) 8
 
5.0%
8 6
 
3.8%
Other values (4) 19
11.9%
Hangul
ValueCountFrequency (%)
로 28
 
17.1%
길 17
 
10.4%
번 16
 
9.8%
동 9
 
5.5%
화 4
 
2.4%
대 4
 
2.4%
부 3
 
1.8%
만 3
 
1.8%
수 3
 
1.8%
서 3
 
1.8%
Other values (57) 74
45.1%

Interactions

2024-03-18T14:47:42.996770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:47:45.398915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번군구명노인대학명연락처주소
연번1.0000.9541.0001.0001.000
군구명0.9541.0001.0001.0001.000
노인대학명1.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
2024-03-18T14:47:45.485292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번군구명
연번1.0000.632
군구명0.6321.000

Missing values

2024-03-18T14:47:43.149953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:47:43.237227image/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

연번군구명노인대학명연락처주소
01중구중구지회부설노인대학032-772-2579제물량로80번길 3-24
12중구내리교회노인대학032-760-4052우현로67번길 3-1
23중구송월교회노인대학032-765-7851동화마을길 65
34동구대한노인회동구지회부설 노인대학032-773-6404샛골로 177(송림동)
45미추홀구미추홀구노인대학032-862-0915학익소로37번길 17(주안동)
56미추홀구도화교회노인대학032-865-8002장고개로36번길 51(도화동)
67미추홀구한사랑노인대학032-884-3834토금북로 66(용현동)
78연수구대한노인회 연수구지회032-811-7586함박뫼로 194
89남동구남동구 노인지회부설 노인대학032-431-4085문화서로 62번길 13(구월동)
910남동구충효노인대학032-467-301만수로 90(만수동)
연번군구명노인대학명연락처주소
1920부평구산곡소망소인대학032-519-0081부영로189번길 12
2021계양구대한노인회 계양구지회 부설노인대학032-546-2923효서로341번길 11
2122계양구효성영광노인대학032-547-0003봉오대로543번길 4
2223계양구샛별노인대학032-554-1741안남로490번길 11
2324계양구비전시니어대학032-515-3201봉오대로 581
2425계양구작전노인대학032-544-8909주부토로 368
2526계양구노인행복지원센터070-7834-1346황어로134번길 28
2627서구서구지회 노인대학032-572-1460신석로121번길 10(석남동)
2728서구해바라기노인대학032-581-4043열우물로 247(가좌동)
2829강화군강화군노인대학032-934-4086강화읍 중앙로 17-16