Overview

Dataset statistics

Number of variables7
Number of observations243
Missing cells2
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.7 KiB
Average record size in memory57.5 B

Variable types

Numeric1
Categorical3
Text3

Dataset

Description대구광역시_수성구_노인복지시설_20180822
Author대구광역시 수성구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15013805&dataSetDetailId=150138051c7b86cadd502_201909051558&provdMethod=FILE

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 동별High correlation
동별 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-19 05:37:19.371191
Analysis finished2024-04-19 05:37:19.869549
Duration0.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct243
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122
Minimum1
Maximum243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-19T14:37:19.962125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.1
Q161.5
median122
Q3182.5
95-th percentile230.9
Maximum243
Range242
Interquartile range (IQR)121

Descriptive statistics

Standard deviation70.292247
Coefficient of variation (CV)0.57616596
Kurtosis-1.2
Mean122
Median Absolute Deviation (MAD)61
Skewness0
Sum29646
Variance4941
MonotonicityStrictly increasing
2024-04-19T14:37:20.125091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
154 1
 
0.4%
156 1
 
0.4%
157 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%
Other values (233) 233
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 (%)
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%
236 1
0.4%
235 1
0.4%
234 1
0.4%

동별
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
고산3동
28 
고산2동
23 
고산1동
21 
수성1가
15 
지산2동
 
14
Other values (18)
142 

Length

Max length6
Median length4
Mean length3.9176955
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고산3동 28
 
11.5%
고산2동 23
 
9.5%
고산1동 21
 
8.6%
수성1가 15
 
6.2%
지산2동 14
 
5.8%
범물2동 13
 
5.3%
지산1동 13
 
5.3%
수성4가 11
 
4.5%
파 동 11
 
4.5%
범어1동 11
 
4.5%
Other values (13) 83
34.2%

Length

2024-04-19T14:37:20.268206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고산3동 28
 
10.7%
고산2동 23
 
8.8%
고산1동 21
 
8.0%
동 18
 
6.9%
수성1가 15
 
5.7%
지산2동 14
 
5.4%
범물2동 13
 
5.0%
지산1동 13
 
5.0%
수성4가 11
 
4.2%
파 11
 
4.2%
Other values (14) 94
36.0%

구분
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
아파트
181 
공설
60 
사설
 
2

Length

Max length3
Median length3
Mean length2.744856
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아파트 181
74.5%
공설 60
 
24.7%
사설 2
 
0.8%

Length

2024-04-19T14:37:20.400702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:37:20.501374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아파트 181
74.5%
공설 60
 
24.7%
사설 2
 
0.8%

시설명
Text

Distinct242
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-19T14:37:20.696780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length10.193416
Min length5

Characters and Unicode

Total characters2477
Distinct characters206
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

Unique241 ?
Unique (%)99.2%

Sample

1st row범어1동 제1경로당
2nd row범어1동 제2경로당
3rd row궁전맨션경로당
4th row우방1차경로당
5th row우방2차경로당
ValueCountFrequency (%)
제1경로당 8
 
3.0%
제2경로당 5
 
1.9%
범어2동 3
 
1.1%
파동 3
 
1.1%
보성맨션경로당 2
 
0.8%
황금2동 2
 
0.8%
범어1동 2
 
0.8%
2단지경로당 2
 
0.8%
시지효성백년가약 2
 
0.8%
수성1가 2
 
0.8%
Other values (232) 235
88.3%
2024-04-19T14:37:21.122909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
355
 
14.3%
로 249
 
10.1%
당 244
 
9.9%
경 243
 
9.8%
지 59
 
2.4%
성 56
 
2.3%
타 42
 
1.7%
운 42
 
1.7%
동 35
 
1.4%
수 30
 
1.2%
Other values (196) 1122
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2040
82.4%
Space Separator 355
 
14.3%
Decimal Number 71
 
2.9%
Other Punctuation 4
 
0.2%
Lowercase Letter 2
 
0.1%
Uppercase Letter 2
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 249
 
12.2%
당 244
 
12.0%
경 243
 
11.9%
지 59
 
2.9%
성 56
 
2.7%
타 42
 
2.1%
운 42
 
2.1%
동 35
 
1.7%
수 30
 
1.5%
시 30
 
1.5%
Other values (183) 1010
49.5%
Decimal Number
ValueCountFrequency (%)
2 26
36.6%
1 26
36.6%
3 11
15.5%
5 4
 
5.6%
4 4
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
355
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2040
82.4%
Common 433
 
17.5%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 249
 
12.2%
당 244
 
12.0%
경 243
 
11.9%
지 59
 
2.9%
성 56
 
2.7%
타 42
 
2.1%
운 42
 
2.1%
동 35
 
1.7%
수 30
 
1.5%
시 30
 
1.5%
Other values (183) 1010
49.5%
Common
ValueCountFrequency (%)
355
82.0%
2 26
 
6.0%
1 26
 
6.0%
3 11
 
2.5%
5 4
 
0.9%
, 4
 
0.9%
4 4
 
0.9%
) 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 2040
82.4%
ASCII 437
 
17.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
355
81.2%
2 26
 
5.9%
1 26
 
5.9%
3 11
 
2.5%
5 4
 
0.9%
, 4
 
0.9%
4 4
 
0.9%
e 2
 
0.5%
) 1
 
0.2%
( 1
 
0.2%
Other values (3) 3
 
0.7%
Hangul
ValueCountFrequency (%)
로 249
 
12.2%
당 244
 
12.0%
경 243
 
11.9%
지 59
 
2.9%
성 56
 
2.7%
타 42
 
2.1%
운 42
 
2.1%
동 35
 
1.7%
수 30
 
1.5%
시 30
 
1.5%
Other values (183) 1010
49.5%

소재지
Text

Distinct240
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-19T14:37:21.437818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length18.559671
Min length15

Characters and Unicode

Total characters4510
Distinct characters72
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

Unique237 ?
Unique (%)97.5%

Sample

1st row대구광역시 수성구 동대구로54길 7
2nd row대구광역시 수성구 청솔로16길 13-3
3rd row대구광역시 수성구 동대구로 274
4th row대구광역시 수성구 동대구로 230
5th row대구광역시 수성구 동대구로48길 33
ValueCountFrequency (%)
대구광역시 243
25.2%
수성구 243
25.2%
달구벌대로 12
 
1.2%
용학로 9
 
0.9%
파동로 8
 
0.8%
동대구로 8
 
0.8%
천을로 7
 
0.7%
욱수천로 7
 
0.7%
40 7
 
0.7%
고산로 6
 
0.6%
Other values (279) 415
43.0%
2024-04-19T14:37:22.218644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
722
16.0%
구 539
12.0%
대 295
 
6.5%
수 275
 
6.1%
성 262
 
5.8%
시 246
 
5.5%
역 243
 
5.4%
광 243
 
5.4%
로 241
 
5.3%
1 145
 
3.2%
Other values (62) 1299
28.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2907
64.5%
Decimal Number 851
 
18.9%
Space Separator 722
 
16.0%
Dash Punctuation 30
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 539
18.5%
대 295
10.1%
수 275
9.5%
성 262
9.0%
시 246
8.5%
역 243
8.4%
광 243
8.4%
로 241
8.3%
길 113
 
3.9%
달 40
 
1.4%
Other values (50) 410
14.1%
Decimal Number
ValueCountFrequency (%)
1 145
17.0%
2 119
14.0%
3 118
13.9%
4 88
10.3%
5 83
9.8%
6 81
9.5%
0 80
9.4%
7 49
 
5.8%
9 46
 
5.4%
8 42
 
4.9%
Space Separator
ValueCountFrequency (%)
722
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2907
64.5%
Common 1603
35.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 539
18.5%
대 295
10.1%
수 275
9.5%
성 262
9.0%
시 246
8.5%
역 243
8.4%
광 243
8.4%
로 241
8.3%
길 113
 
3.9%
달 40
 
1.4%
Other values (50) 410
14.1%
Common
ValueCountFrequency (%)
722
45.0%
1 145
 
9.0%
2 119
 
7.4%
3 118
 
7.4%
4 88
 
5.5%
5 83
 
5.2%
6 81
 
5.1%
0 80
 
5.0%
7 49
 
3.1%
9 46
 
2.9%
Other values (2) 72
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2907
64.5%
ASCII 1603
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
722
45.0%
1 145
 
9.0%
2 119
 
7.4%
3 118
 
7.4%
4 88
 
5.5%
5 83
 
5.2%
6 81
 
5.1%
0 80
 
5.0%
7 49
 
3.1%
9 46
 
2.9%
Other values (2) 72
 
4.5%
Hangul
ValueCountFrequency (%)
구 539
18.5%
대 295
10.1%
수 275
9.5%
성 262
9.0%
시 246
8.5%
역 243
8.4%
광 243
8.4%
로 241
8.3%
길 113
 
3.9%
달 40
 
1.4%
Other values (50) 410
14.1%

연락처
Text

Distinct237
Distinct (%)98.3%
Missing2
Missing (%)0.8%
Memory size2.0 KiB
2024-04-19T14:37:22.440289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.912863
Min length1

Characters and Unicode

Total characters2871
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique234 ?
Unique (%)97.1%

Sample

1st row053-743-3288
2nd row053-756-1330
3rd row053-756-8020
4th row053-746-5595
5th row053-752-4878
ValueCountFrequency (%)
053-783-2801 3
 
1.3%
053-741-3651 2
 
0.8%
053-795-2477 2
 
0.8%
053-794-4494 1
 
0.4%
053-784-8334 1
 
0.4%
053-261-3232 1
 
0.4%
053-218-4737 1
 
0.4%
053-782-2355 1
 
0.4%
053-783-5633 1
 
0.4%
053-784-9950 1
 
0.4%
Other values (225) 225
94.1%
2024-04-19T14:37:22.778367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 478
16.6%
5 401
14.0%
3 380
13.2%
0 354
12.3%
7 302
10.5%
1 197
6.9%
4 168
 
5.9%
2 156
 
5.4%
6 152
 
5.3%
8 140
 
4.9%
Other values (2) 143
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2390
83.2%
Dash Punctuation 478
 
16.6%
Space Separator 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 401
16.8%
3 380
15.9%
0 354
14.8%
7 302
12.6%
1 197
8.2%
4 168
7.0%
2 156
 
6.5%
6 152
 
6.4%
8 140
 
5.9%
9 140
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 478
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2871
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 478
16.6%
5 401
14.0%
3 380
13.2%
0 354
12.3%
7 302
10.5%
1 197
6.9%
4 168
 
5.9%
2 156
 
5.4%
6 152
 
5.3%
8 140
 
4.9%
Other values (2) 143
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2871
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 478
16.6%
5 401
14.0%
3 380
13.2%
0 354
12.3%
7 302
10.5%
1 197
6.9%
4 168
 
5.9%
2 156
 
5.4%
6 152
 
5.3%
8 140
 
4.9%
Other values (2) 143
 
5.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2018-08-22
243 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-08-22
2nd row2018-08-22
3rd row2018-08-22
4th row2018-08-22
5th row2018-08-22

Common Values

ValueCountFrequency (%)
2018-08-22 243
100.0%

Length

2024-04-19T14:37:22.919837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:37:23.003998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-22 243
100.0%

Interactions

2024-04-19T14:37:19.610011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:37:23.066790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동별구분
연번1.0000.9860.304
동별0.9861.0000.263
구분0.3040.2631.000
2024-04-19T14:37:23.146402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동별구분
동별1.0000.133
구분0.1331.000
2024-04-19T14:37:23.230236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동별구분
연번1.0000.8950.184
동별0.8951.0000.133
구분0.1840.1331.000

Missing values

2024-04-19T14:37:19.715880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:37:19.823816image/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

연번동별구분시설명소재지연락처데이터기준일자
01범어1동공설범어1동 제1경로당대구광역시 수성구 동대구로54길 7053-743-32882018-08-22
12범어1동공설범어1동 제2경로당대구광역시 수성구 청솔로16길 13-3053-756-13302018-08-22
23범어1동아파트궁전맨션경로당대구광역시 수성구 동대구로 274053-756-80202018-08-22
34범어1동아파트우방1차경로당대구광역시 수성구 동대구로 230053-746-55952018-08-22
45범어1동아파트우방2차경로당대구광역시 수성구 동대구로48길 33053-752-48782018-08-22
56범어1동아파트아진맨션경로당대구광역시 수성구 동대구로 38길 80053-751-24112018-08-22
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