Overview

Dataset statistics

Number of variables8
Number of observations246
Missing cells7
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.7 KiB
Average record size in memory65.5 B

Variable types

Numeric1
Categorical3
Text3
DateTime1

Dataset

Description대구광역시 수성구_노인복지시설_20200920
Author대구광역시 수성구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15013805&dataSetDetailId=1501380519348dc4e8bf8&provdMethod=FILE

Alerts

데이터기준일자 has constant value ""Constant
구분 is highly overall correlated with 기타 유의사항High correlation
동별 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
기타 유의사항 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 동별 and 1 other fieldsHigh correlation
기타 유의사항 is highly imbalanced (81.3%)Imbalance
연락처 has 7 (2.8%) missing valuesMissing
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2024-04-22 00:32:42.931185
Analysis finished2024-04-22 00:32:43.490387
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct246
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123.5
Minimum1
Maximum246
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-22T09:32:43.579911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.25
Q162.25
median123.5
Q3184.75
95-th percentile233.75
Maximum246
Range245
Interquartile range (IQR)122.5

Descriptive statistics

Standard deviation71.158274
Coefficient of variation (CV)0.57618036
Kurtosis-1.2
Mean123.5
Median Absolute Deviation (MAD)61.5
Skewness0
Sum30381
Variance5063.5
MonotonicityStrictly increasing
2024-04-22T09:32:43.733573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
156 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
165 1
 
0.4%
Other values (236) 236
95.9%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
246 1
0.4%
245 1
0.4%
244 1
0.4%
243 1
0.4%
242 1
0.4%
241 1
0.4%
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%

동별
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
고산3동
29 
고산2동
24 
고산1동
21 
수성1가
16 
지산2동
 
14
Other values (18)
142 

Length

Max length6
Median length4
Mean length3.9186992
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row범어1동
2nd row범어1동
3rd row범어1동
4th row범어1동
5th row범어1동

Common Values

ValueCountFrequency (%)
고산3동 29
 
11.8%
고산2동 24
 
9.8%
고산1동 21
 
8.5%
수성1가 16
 
6.5%
지산2동 14
 
5.7%
범물2동 13
 
5.3%
지산1동 13
 
5.3%
파 동 11
 
4.5%
만촌1동 11
 
4.5%
수성4가 11
 
4.5%
Other values (13) 83
33.7%

Length

2024-04-22T09:32:43.884404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고산3동 29
 
11.0%
고산2동 24
 
9.1%
고산1동 21
 
8.0%
동 18
 
6.8%
수성1가 16
 
6.1%
지산2동 14
 
5.3%
범물2동 13
 
4.9%
지산1동 13
 
4.9%
파 11
 
4.2%
만촌1동 11
 
4.2%
Other values (14) 94
35.6%

구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
아파트
182 
공설
62 
사설
 
2

Length

Max length3
Median length3
Mean length2.7398374
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공설
2nd row공설
3rd row아파트
4th row아파트
5th row아파트

Common Values

ValueCountFrequency (%)
아파트 182
74.0%
공설 62
 
25.2%
사설 2
 
0.8%

Length

2024-04-22T09:32:44.019468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:32:44.113838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아파트 182
74.0%
공설 62
 
25.2%
사설 2
 
0.8%

시설명
Text

UNIQUE 

Distinct246
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-22T09:32:44.296242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length10.089431
Min length5

Characters and Unicode

Total characters2482
Distinct characters209
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)100.0%

Sample

1st row범어1동 제1경로당
2nd row범어1동 제2경로당
3rd row궁전맨션경로당
4th row우방1차경로당
5th row우방2차경로당
ValueCountFrequency (%)
제1경로당 8
 
3.0%
제2경로당 5
 
1.9%
파동 3
 
1.1%
범어2동 3
 
1.1%
범어1동 2
 
0.7%
태왕리더스경로당 2
 
0.7%
사월화성파크드림 2
 
0.7%
2단지경로당 2
 
0.7%
황금2동 2
 
0.7%
시지효성백년가약 2
 
0.7%
Other values (237) 238
88.5%
2024-04-22T09:32:44.647818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
322
 
13.0%
로 252
 
10.2%
당 247
 
10.0%
경 246
 
9.9%
지 60
 
2.4%
성 60
 
2.4%
운 43
 
1.7%
타 43
 
1.7%
동 35
 
1.4%
수 32
 
1.3%
Other values (199) 1142
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2077
83.7%
Space Separator 322
 
13.0%
Decimal Number 72
 
2.9%
Other Punctuation 4
 
0.2%
Lowercase Letter 2
 
0.1%
Uppercase Letter 2
 
0.1%
Open Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 252
 
12.1%
당 247
 
11.9%
경 246
 
11.8%
지 60
 
2.9%
성 60
 
2.9%
운 43
 
2.1%
타 43
 
2.1%
동 35
 
1.7%
수 32
 
1.5%
시 28
 
1.3%
Other values (186) 1031
49.6%
Decimal Number
ValueCountFrequency (%)
2 27
37.5%
1 25
34.7%
3 12
16.7%
5 4
 
5.6%
4 4
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
322
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2077
83.7%
Common 401
 
16.2%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 252
 
12.1%
당 247
 
11.9%
경 246
 
11.8%
지 60
 
2.9%
성 60
 
2.9%
운 43
 
2.1%
타 43
 
2.1%
동 35
 
1.7%
수 32
 
1.5%
시 28
 
1.3%
Other values (186) 1031
49.6%
Common
ValueCountFrequency (%)
322
80.3%
2 27
 
6.7%
1 25
 
6.2%
3 12
 
3.0%
5 4
 
1.0%
, 4
 
1.0%
4 4
 
1.0%
( 1
 
0.2%
- 1
 
0.2%
) 1
 
0.2%
Latin
ValueCountFrequency (%)
e 2
50.0%
K 1
25.0%
S 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2077
83.7%
ASCII 405
 
16.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
322
79.5%
2 27
 
6.7%
1 25
 
6.2%
3 12
 
3.0%
5 4
 
1.0%
, 4
 
1.0%
4 4
 
1.0%
e 2
 
0.5%
( 1
 
0.2%
K 1
 
0.2%
Other values (3) 3
 
0.7%
Hangul
ValueCountFrequency (%)
로 252
 
12.1%
당 247
 
11.9%
경 246
 
11.8%
지 60
 
2.9%
성 60
 
2.9%
운 43
 
2.1%
타 43
 
2.1%
동 35
 
1.7%
수 32
 
1.5%
시 28
 
1.3%
Other values (186) 1031
49.6%

소재지
Text

Distinct243
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-22T09:32:44.941350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length18.589431
Min length15

Characters and Unicode

Total characters4573
Distinct characters71
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

Unique240 ?
Unique (%)97.6%

Sample

1st row대구광역시 수성구 동대구로54길 7
2nd row대구광역시 수성구 청솔로16길 35
3rd row대구광역시 수성구 동대구로 274
4th row대구광역시 수성구 동대구로 230
5th row대구광역시 수성구 동대구로48길 33
ValueCountFrequency (%)
대구광역시 246
25.2%
수성구 246
25.2%
달구벌대로 12
 
1.2%
동대구로 8
 
0.8%
용학로 8
 
0.8%
파동로 8
 
0.8%
천을로 7
 
0.7%
욱수천로 7
 
0.7%
40 7
 
0.7%
고산로 6
 
0.6%
Other values (281) 421
43.1%
2024-04-22T09:32:45.327565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
730
16.0%
구 545
11.9%
대 299
 
6.5%
수 279
 
6.1%
성 265
 
5.8%
시 249
 
5.4%
광 246
 
5.4%
역 246
 
5.4%
로 244
 
5.3%
1 149
 
3.3%
Other values (61) 1321
28.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2945
64.4%
Decimal Number 866
 
18.9%
Space Separator 730
 
16.0%
Dash Punctuation 32
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 545
18.5%
대 299
10.2%
수 279
9.5%
성 265
9.0%
시 249
8.5%
광 246
8.4%
역 246
8.4%
로 244
8.3%
길 117
 
4.0%
벌 41
 
1.4%
Other values (49) 414
14.1%
Decimal Number
ValueCountFrequency (%)
1 149
17.2%
2 118
13.6%
3 117
13.5%
4 94
10.9%
5 87
10.0%
6 85
9.8%
0 79
9.1%
7 49
 
5.7%
9 45
 
5.2%
8 43
 
5.0%
Space Separator
ValueCountFrequency (%)
730
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2945
64.4%
Common 1628
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 545
18.5%
대 299
10.2%
수 279
9.5%
성 265
9.0%
시 249
8.5%
광 246
8.4%
역 246
8.4%
로 244
8.3%
길 117
 
4.0%
벌 41
 
1.4%
Other values (49) 414
14.1%
Common
ValueCountFrequency (%)
730
44.8%
1 149
 
9.2%
2 118
 
7.2%
3 117
 
7.2%
4 94
 
5.8%
5 87
 
5.3%
6 85
 
5.2%
0 79
 
4.9%
7 49
 
3.0%
9 45
 
2.8%
Other values (2) 75
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2945
64.4%
ASCII 1628
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
730
44.8%
1 149
 
9.2%
2 118
 
7.2%
3 117
 
7.2%
4 94
 
5.8%
5 87
 
5.3%
6 85
 
5.2%
0 79
 
4.9%
7 49
 
3.0%
9 45
 
2.8%
Other values (2) 75
 
4.6%
Hangul
ValueCountFrequency (%)
구 545
18.5%
대 299
10.2%
수 279
9.5%
성 265
9.0%
시 249
8.5%
광 246
8.4%
역 246
8.4%
로 244
8.3%
길 117
 
4.0%
벌 41
 
1.4%
Other values (49) 414
14.1%

연락처
Text

MISSING 

Distinct235
Distinct (%)98.3%
Missing7
Missing (%)2.8%
Memory size2.1 KiB
2024-04-22T09:32:45.546966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2868
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

Unique232 ?
Unique (%)97.1%

Sample

1st row053-743-3288
2nd row053-765-1330
3rd row053-756-8020
4th row053-746-5595
5th row053-752-4878
ValueCountFrequency (%)
053-741-3651 3
 
1.3%
053-783-2801 2
 
0.8%
053-795-2477 2
 
0.8%
053-793-4020 1
 
0.4%
053-784-8334 1
 
0.4%
053-261-3232 1
 
0.4%
053-793-7720 1
 
0.4%
053-743-3288 1
 
0.4%
053-784-9950 1
 
0.4%
053-784-1245 1
 
0.4%
Other values (225) 225
94.1%
2024-04-22T09:32:45.883426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 478
16.7%
5 404
14.1%
3 381
13.3%
0 355
12.4%
7 298
10.4%
1 196
6.8%
4 168
 
5.9%
6 154
 
5.4%
2 154
 
5.4%
9 141
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2390
83.3%
Dash Punctuation 478
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 404
16.9%
3 381
15.9%
0 355
14.9%
7 298
12.5%
1 196
8.2%
4 168
7.0%
6 154
 
6.4%
2 154
 
6.4%
9 141
 
5.9%
8 139
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 478
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2868
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 478
16.7%
5 404
14.1%
3 381
13.3%
0 355
12.4%
7 298
10.4%
1 196
6.8%
4 168
 
5.9%
6 154
 
5.4%
2 154
 
5.4%
9 141
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2868
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 478
16.7%
5 404
14.1%
3 381
13.3%
0 355
12.4%
7 298
10.4%
1 196
6.8%
4 168
 
5.9%
6 154
 
5.4%
2 154
 
5.4%
9 141
 
4.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2020-09-20 00:00:00
Maximum2020-09-20 00:00:00
2024-04-22T09:32:46.004528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T09:32:46.090300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

기타 유의사항
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
239 
데이터 미집계
 
7

Length

Max length7
Median length4
Mean length4.0853659
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 239
97.2%
데이터 미집계 7
 
2.8%

Length

2024-04-22T09:32:46.209726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:32:46.304939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 239
94.5%
데이터 7
 
2.8%
미집계 7
 
2.8%

Interactions

2024-04-22T09:32:43.212564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-22T09:32:46.363313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동별구분
연번1.0000.9870.314
동별0.9871.0000.245
구분0.3140.2451.000
2024-04-22T09:32:46.447868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분동별기타 유의사항
구분1.0000.1231.000
동별0.1231.0001.000
기타 유의사항1.0001.0001.000
2024-04-22T09:32:46.540549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동별구분기타 유의사항
연번1.0000.8970.1891.000
동별0.8971.0000.1231.000
구분0.1890.1231.0001.000
기타 유의사항1.0001.0001.0001.000

Missing values

2024-04-22T09:32:43.321393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T09:32:43.443569image/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

연번동별구분시설명소재지연락처데이터기준일자기타 유의사항
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