Overview

Dataset statistics

Number of variables5
Number of observations202
Missing cells5
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.2 KiB
Average record size in memory41.7 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description2017년 5월 대구동구경로당현황
Author대구광역시 동구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=3072347&dataSetDetailId=3072347282e1509ff3a8_201909091700&provdMethod=FILE

Alerts

연 번 is highly overall correlated with 비 고High correlation
비 고 is highly overall correlated with 연 번High correlation
연락처 has 5 (2.5%) missing valuesMissing
연 번 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-10 18:01:19.333541
Analysis finished2023-12-10 18:01:20.578341
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연 번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct202
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.5
Minimum1
Maximum202
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T03:01:20.683915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.05
Q151.25
median101.5
Q3151.75
95-th percentile191.95
Maximum202
Range201
Interquartile range (IQR)100.5

Descriptive statistics

Standard deviation58.456537
Coefficient of variation (CV)0.57592647
Kurtosis-1.2
Mean101.5
Median Absolute Deviation (MAD)50.5
Skewness0
Sum20503
Variance3417.1667
MonotonicityStrictly increasing
2023-12-11T03:01:20.885934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
140 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
Other values (192) 192
95.0%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
202 1
0.5%
201 1
0.5%
200 1
0.5%
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%

경로당명
Text

Distinct200
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T03:01:21.205635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length8.1732673
Min length2

Characters and Unicode

Total characters1651
Distinct characters202
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)98.0%

Sample

1st row신암1경로당
2nd row제일경로당(제1)
3rd row새터경로당
4th row안평경로당
5th row신암1동뜨란채A경로당
ValueCountFrequency (%)
제1경로당 2
 
1.0%
제2경로당 2
 
1.0%
율하휴먼시아9단지경로당 1
 
0.5%
동화해오름타운a경로당 1
 
0.5%
세계육상선수촌2단지경로당 1
 
0.5%
율하우방아이유쉘경로당 1
 
0.5%
매여경로당 1
 
0.5%
백자맨션a경로당 1
 
0.5%
용계1경로당 1
 
0.5%
용계2경로당 1
 
0.5%
Other values (192) 192
94.1%
2023-12-11T03:01:21.754339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 206
 
12.5%
경 203
 
12.3%
당 201
 
12.2%
A 64
 
3.9%
신 39
 
2.4%
1 36
 
2.2%
동 33
 
2.0%
지 32
 
1.9%
2 30
 
1.8%
아 27
 
1.6%
Other values (192) 780
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1465
88.7%
Decimal Number 90
 
5.5%
Uppercase Letter 70
 
4.2%
Close Punctuation 11
 
0.7%
Open Punctuation 11
 
0.7%
Space Separator 2
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 206
 
14.1%
경 203
 
13.9%
당 201
 
13.7%
신 39
 
2.7%
동 33
 
2.3%
지 32
 
2.2%
아 27
 
1.8%
단 23
 
1.6%
차 20
 
1.4%
제 20
 
1.4%
Other values (175) 661
45.1%
Decimal Number
ValueCountFrequency (%)
1 36
40.0%
2 30
33.3%
3 10
 
11.1%
5 5
 
5.6%
4 3
 
3.3%
6 3
 
3.3%
7 1
 
1.1%
0 1
 
1.1%
9 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
A 64
91.4%
L 3
 
4.3%
H 3
 
4.3%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
. 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1465
88.7%
Common 116
 
7.0%
Latin 70
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 206
 
14.1%
경 203
 
13.9%
당 201
 
13.7%
신 39
 
2.7%
동 33
 
2.3%
지 32
 
2.2%
아 27
 
1.8%
단 23
 
1.6%
차 20
 
1.4%
제 20
 
1.4%
Other values (175) 661
45.1%
Common
ValueCountFrequency (%)
1 36
31.0%
2 30
25.9%
) 11
 
9.5%
( 11
 
9.5%
3 10
 
8.6%
5 5
 
4.3%
4 3
 
2.6%
6 3
 
2.6%
2
 
1.7%
: 1
 
0.9%
Other values (4) 4
 
3.4%
Latin
ValueCountFrequency (%)
A 64
91.4%
L 3
 
4.3%
H 3
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1465
88.7%
ASCII 186
 
11.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 206
 
14.1%
경 203
 
13.9%
당 201
 
13.7%
신 39
 
2.7%
동 33
 
2.3%
지 32
 
2.2%
아 27
 
1.8%
단 23
 
1.6%
차 20
 
1.4%
제 20
 
1.4%
Other values (175) 661
45.1%
ASCII
ValueCountFrequency (%)
A 64
34.4%
1 36
19.4%
2 30
16.1%
) 11
 
5.9%
( 11
 
5.9%
3 10
 
5.4%
5 5
 
2.7%
L 3
 
1.6%
4 3
 
1.6%
H 3
 
1.6%
Other values (7) 10
 
5.4%

소재지
Text

UNIQUE 

Distinct202
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T03:01:22.114839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length19.50495
Min length7

Characters and Unicode

Total characters3940
Distinct characters139
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)100.0%

Sample

1st row신암북로 7길 37(신암1동 669)
2nd row아양로 11길 36-5(신암1동 630-87)
3rd row경대로 72(신암1동 703-39)
4th row평화로 20-20(신암1동 786-8)
5th row아양로7길 12(신암1동 766)
ValueCountFrequency (%)
팔공로 13
 
1.8%
동촌로 11
 
1.5%
화랑로 11
 
1.5%
아양로 11
 
1.5%
율하동로 9
 
1.3%
안심로 8
 
1.1%
16길 7
 
1.0%
해동로 7
 
1.0%
지묘동 7
 
1.0%
송라로 6
 
0.8%
Other values (515) 621
87.3%
2023-12-11T03:01:22.702202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
509
 
12.9%
1 315
 
8.0%
동 246
 
6.2%
2 207
 
5.3%
로 202
 
5.1%
) 196
 
5.0%
( 196
 
5.0%
3 170
 
4.3%
5 149
 
3.8%
- 142
 
3.6%
Other values (129) 1608
40.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1483
37.6%
Other Letter 1409
35.8%
Space Separator 509
 
12.9%
Close Punctuation 196
 
5.0%
Open Punctuation 196
 
5.0%
Dash Punctuation 142
 
3.6%
Uppercase Letter 3
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 246
17.5%
로 202
 
14.3%
길 127
 
9.0%
신 83
 
5.9%
촌 31
 
2.2%
암 31
 
2.2%
천 30
 
2.1%
율 24
 
1.7%
하 23
 
1.6%
공 23
 
1.6%
Other values (111) 589
41.8%
Decimal Number
ValueCountFrequency (%)
1 315
21.2%
2 207
14.0%
3 170
11.5%
5 149
10.0%
0 137
9.2%
4 126
 
8.5%
6 121
 
8.2%
7 101
 
6.8%
8 85
 
5.7%
9 72
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
H 1
33.3%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
509
100.0%
Close Punctuation
ValueCountFrequency (%)
) 196
100.0%
Open Punctuation
ValueCountFrequency (%)
( 196
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 142
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2528
64.2%
Hangul 1409
35.8%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 246
17.5%
로 202
 
14.3%
길 127
 
9.0%
신 83
 
5.9%
촌 31
 
2.2%
암 31
 
2.2%
천 30
 
2.1%
율 24
 
1.7%
하 23
 
1.6%
공 23
 
1.6%
Other values (111) 589
41.8%
Common
ValueCountFrequency (%)
509
20.1%
1 315
12.5%
2 207
8.2%
) 196
 
7.8%
( 196
 
7.8%
3 170
 
6.7%
5 149
 
5.9%
- 142
 
5.6%
0 137
 
5.4%
4 126
 
5.0%
Other values (5) 381
15.1%
Latin
ValueCountFrequency (%)
L 1
33.3%
H 1
33.3%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2531
64.2%
Hangul 1409
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
509
20.1%
1 315
12.4%
2 207
8.2%
) 196
 
7.7%
( 196
 
7.7%
3 170
 
6.7%
5 149
 
5.9%
- 142
 
5.6%
0 137
 
5.4%
4 126
 
5.0%
Other values (8) 384
15.2%
Hangul
ValueCountFrequency (%)
동 246
17.5%
로 202
 
14.3%
길 127
 
9.0%
신 83
 
5.9%
촌 31
 
2.2%
암 31
 
2.2%
천 30
 
2.1%
율 24
 
1.7%
하 23
 
1.6%
공 23
 
1.6%
Other values (111) 589
41.8%

연락처
Text

MISSING 

Distinct195
Distinct (%)99.0%
Missing5
Missing (%)2.5%
Memory size1.7 KiB
2023-12-11T03:01:23.048471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2364
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

Unique193 ?
Unique (%)98.0%

Sample

1st row053-943-2586
2nd row053-958-0323
3rd row053-959-9990
4th row053-959-1119
5th row053-958-8903
ValueCountFrequency (%)
053-955-4982 2
 
1.0%
053-984-1267 2
 
1.0%
053-243-3140 1
 
0.5%
053-981-2754 1
 
0.5%
053-964-0900 1
 
0.5%
053-941-1459 1
 
0.5%
053-961-2276 1
 
0.5%
053-964-4262 1
 
0.5%
053-963-1448 1
 
0.5%
053-964-0383 1
 
0.5%
Other values (185) 185
93.9%
2023-12-11T03:01:23.640603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 394
16.7%
5 331
14.0%
3 319
13.5%
0 295
12.5%
9 240
10.2%
8 165
7.0%
4 155
 
6.6%
2 134
 
5.7%
6 129
 
5.5%
1 112
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1970
83.3%
Dash Punctuation 394
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 331
16.8%
3 319
16.2%
0 295
15.0%
9 240
12.2%
8 165
8.4%
4 155
7.9%
2 134
6.8%
6 129
 
6.5%
1 112
 
5.7%
7 90
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 394
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2364
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 394
16.7%
5 331
14.0%
3 319
13.5%
0 295
12.5%
9 240
10.2%
8 165
7.0%
4 155
 
6.6%
2 134
 
5.7%
6 129
 
5.5%
1 112
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2364
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 394
16.7%
5 331
14.0%
3 319
13.5%
0 295
12.5%
9 240
10.2%
8 165
7.0%
4 155
 
6.6%
2 134
 
5.7%
6 129
 
5.5%
1 112
 
4.7%

비 고
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
안심3.4동
32 
공산동
29 
안심1동
22 
불로봉무동
14 
방촌동
13 
Other values (15)
92 

Length

Max length6
Median length5
Mean length4.1435644
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신암1동
2nd row신암1동
3rd row신암1동
4th row신암1동
5th row신암1동

Common Values

ValueCountFrequency (%)
안심3.4동 32
15.8%
공산동 29
14.4%
안심1동 22
10.9%
불로봉무동 14
 
6.9%
방촌동 13
 
6.4%
신천1.2동 11
 
5.4%
해안동 11
 
5.4%
안심2동 8
 
4.0%
신천3동 7
 
3.5%
동촌동 7
 
3.5%
Other values (10) 48
23.8%

Length

2023-12-11T03:01:23.887864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안심3.4동 32
15.8%
공산동 29
14.4%
안심1동 22
10.9%
불로봉무동 14
 
6.9%
방촌동 13
 
6.4%
신천1.2동 11
 
5.4%
해안동 11
 
5.4%
안심2동 8
 
4.0%
신천3동 7
 
3.5%
동촌동 7
 
3.5%
Other values (10) 48
23.8%

Interactions

2023-12-11T03:01:20.196150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T03:01:24.045450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연 번비 고
연 번1.0000.991
비 고0.9911.000
2023-12-11T03:01:24.171191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연 번비 고
연 번1.0000.818
비 고0.8181.000

Missing values

2023-12-11T03:01:20.378833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T03:01:20.524326image/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

연 번경로당명소재지연락처비 고
01신암1경로당신암북로 7길 37(신암1동 669)053-943-2586신암1동
12제일경로당(제1)아양로 11길 36-5(신암1동 630-87)053-958-0323신암1동
23새터경로당경대로 72(신암1동 703-39)053-959-9990신암1동
34안평경로당평화로 20-20(신암1동 786-8)053-959-1119신암1동
45신암1동뜨란채A경로당아양로7길 12(신암1동 766)053-958-8903신암1동
56강남A경로당신성로 60(신암2동 483-3)053-959-8874신암2동
67신암2경로당신성로 113-3(신암2동 489-11)053-957-7057신암2동
78신암그린타운A경로당신성로30(신암2동 461-1)053-951-6324신암2동
89신천가람A경로당신암로 16길 33(신천동 551-23)053-944-0268신암2동
910신암청아람경로당신암로 20길(신암동 480)053-929-9410신암2동
연 번경로당명소재지연락처비 고
192193지묘2동경로당파계로19길 11,B동 202호(지묘동 772)053-981-6906공산동
193194팔공2차보성A경로당팔공로101길 55 (지묘동 327)053-243-6900공산동
194195팔공보성1차A경로당팔공로 489 (지묘동 215)053-981-0030공산동
195196왕산우방A경로당파계로6길 30 (지묘동 337)053-983-4363공산동
196197화성명산A경로당파계로22길 7 (지묘동 500)053-984-9373공산동
197198태왕그린힐즈A경로당파계로46 (지묘동 360)053-981-2754공산동
198199팔공보성3차A경로당파계로71 (지묘동 824)053-243-3140공산동
199200진인2동경로당인산로67 (진인동563)<NA>공산동
200201옥정경로당내동로67 (내동 416-3)053-982-0339공산동
201202태정경로당팔공산로 1166 (용수동 96-5)053-982-3885공산동