Overview

Dataset statistics

Number of variables6
Number of observations187
Missing cells12
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory49.7 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description인천광역시 남동구 경로당 현황에 대한 데이터로 연번, 구분, 경로당명, 전화번호, 등록일, 면적, 회원수, 도로명주소 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://www.data.go.kr/data/3077664/fileData.do

Alerts

연번 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 연번High correlation
전화번호 has 12 (6.4%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-06 12:36:57.929083
Analysis finished2024-01-06 12:37:00.046734
Duration2.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct187
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94
Minimum1
Maximum187
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-01-06T12:37:00.361561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.3
Q147.5
median94
Q3140.5
95-th percentile177.7
Maximum187
Range186
Interquartile range (IQR)93

Descriptive statistics

Standard deviation54.126395
Coefficient of variation (CV)0.57581272
Kurtosis-1.2
Mean94
Median Absolute Deviation (MAD)47
Skewness0
Sum17578
Variance2929.6667
MonotonicityStrictly increasing
2024-01-06T12:37:01.252376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
130 1
 
0.5%
121 1
 
0.5%
122 1
 
0.5%
123 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
Other values (177) 177
94.7%
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 (%)
187 1
0.5%
186 1
0.5%
185 1
0.5%
184 1
0.5%
183 1
0.5%
182 1
0.5%
181 1
0.5%
180 1
0.5%
179 1
0.5%
178 1
0.5%

행정동
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
논현1동
15 
서창2동
15 
논현고잔동
14 
논현2동
13 
남촌도림동
13 
Other values (15)
117 

Length

Max length5
Median length4
Mean length4.2085561
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row구월1동
2nd row구월1동
3rd row구월1동
4th row구월1동
5th row구월1동

Common Values

ValueCountFrequency (%)
논현1동 15
 
8.0%
서창2동 15
 
8.0%
논현고잔동 14
 
7.5%
논현2동 13
 
7.0%
남촌도림동 13
 
7.0%
만수6동 12
 
6.4%
장수서창동 12
 
6.4%
구월1동 12
 
6.4%
간석4동 12
 
6.4%
간석3동 11
 
5.9%
Other values (10) 58
31.0%

Length

2024-01-06T12:37:01.853142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
논현1동 15
 
8.0%
서창2동 15
 
8.0%
논현고잔동 14
 
7.5%
논현2동 13
 
7.0%
남촌도림동 13
 
7.0%
만수6동 12
 
6.4%
장수서창동 12
 
6.4%
구월1동 12
 
6.4%
간석4동 12
 
6.4%
간석3동 11
 
5.9%
Other values (10) 58
31.0%

구분
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
사립
141 
구립
46 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row구립
2nd row사립
3rd row사립
4th row사립
5th row사립

Common Values

ValueCountFrequency (%)
사립 141
75.4%
구립 46
 
24.6%

Length

2024-01-06T12:37:02.450631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:37:03.028348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 141
75.4%
구립 46
 
24.6%

경로당명
Text

Distinct185
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-01-06T12:37:04.411604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length7.0106952
Min length2

Characters and Unicode

Total characters1311
Distinct characters192
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

Unique183 ?
Unique (%)97.9%

Sample

1st row대구월
2nd row동남아파트
3rd row팬더아파트
4th row동아아파트
5th row구월아시아드선수촌센트럴자이아파트
ValueCountFrequency (%)
1단지 4
 
2.0%
논현주공아파트 3
 
1.5%
동남아파트 2
 
1.0%
팬더아파트 2
 
1.0%
7단지 2
 
1.0%
주공아파트 2
 
1.0%
소래휴먼시아 2
 
1.0%
2단지 2
 
1.0%
논현하늘마을 2
 
1.0%
3단지 2
 
1.0%
Other values (178) 179
88.6%
2024-01-06T12:37:06.387498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 112
 
8.5%
트 102
 
7.8%
파 88
 
6.7%
지 62
 
4.7%
단 59
 
4.5%
1 32
 
2.4%
수 29
 
2.2%
동 28
 
2.1%
주 24
 
1.8%
공 23
 
1.8%
Other values (182) 752
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1166
88.9%
Decimal Number 92
 
7.0%
Uppercase Letter 23
 
1.8%
Space Separator 16
 
1.2%
Close Punctuation 5
 
0.4%
Open Punctuation 5
 
0.4%
Dash Punctuation 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 112
 
9.6%
트 102
 
8.7%
파 88
 
7.5%
지 62
 
5.3%
단 59
 
5.1%
수 29
 
2.5%
동 28
 
2.4%
주 24
 
2.1%
공 23
 
2.0%
현 22
 
1.9%
Other values (164) 617
52.9%
Decimal Number
ValueCountFrequency (%)
1 32
34.8%
2 22
23.9%
3 8
 
8.7%
4 7
 
7.6%
5 6
 
6.5%
6 5
 
5.4%
7 5
 
5.4%
8 4
 
4.3%
9 2
 
2.2%
0 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
H 11
47.8%
L 11
47.8%
A 1
 
4.3%
Space Separator
ValueCountFrequency (%)
16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1166
88.9%
Common 122
 
9.3%
Latin 23
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 112
 
9.6%
트 102
 
8.7%
파 88
 
7.5%
지 62
 
5.3%
단 59
 
5.1%
수 29
 
2.5%
동 28
 
2.4%
주 24
 
2.1%
공 23
 
2.0%
현 22
 
1.9%
Other values (164) 617
52.9%
Common
ValueCountFrequency (%)
1 32
26.2%
2 22
18.0%
16
13.1%
3 8
 
6.6%
4 7
 
5.7%
5 6
 
4.9%
6 5
 
4.1%
7 5
 
4.1%
) 5
 
4.1%
( 5
 
4.1%
Other values (5) 11
 
9.0%
Latin
ValueCountFrequency (%)
H 11
47.8%
L 11
47.8%
A 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1166
88.9%
ASCII 145
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 112
 
9.6%
트 102
 
8.7%
파 88
 
7.5%
지 62
 
5.3%
단 59
 
5.1%
수 29
 
2.5%
동 28
 
2.4%
주 24
 
2.1%
공 23
 
2.0%
현 22
 
1.9%
Other values (164) 617
52.9%
ASCII
ValueCountFrequency (%)
1 32
22.1%
2 22
15.2%
16
11.0%
H 11
 
7.6%
L 11
 
7.6%
3 8
 
5.5%
4 7
 
4.8%
5 6
 
4.1%
6 5
 
3.4%
7 5
 
3.4%
Other values (8) 22
15.2%

전화번호
Text

MISSING 

Distinct175
Distinct (%)100.0%
Missing12
Missing (%)6.4%
Memory size1.6 KiB
2024-01-06T12:37:07.455927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length12
Mean length12.28
Min length12

Characters and Unicode

Total characters2149
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)100.0%

Sample

1st row032-467-8158
2nd row032-463-8388
3rd row032-461-5253
4th row032-465-1092
5th row032-469-1110
ValueCountFrequency (%)
032-467-8158 1
 
0.6%
032-466-2585 1
 
0.6%
032-467-4121 1
 
0.6%
032-466-5199 1
 
0.6%
032-461-9989 1
 
0.6%
032-466-7288 1
 
0.6%
032-472-1803 1
 
0.6%
032-464-0337 1
 
0.6%
032-465-0209 1
 
0.6%
032-466-1131 1
 
0.6%
Other values (165) 165
94.3%
2024-01-06T12:37:08.801204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 356
16.6%
2 335
15.6%
3 290
13.5%
0 280
13.0%
4 230
10.7%
6 166
7.7%
1 125
 
5.8%
7 95
 
4.4%
5 95
 
4.4%
8 86
 
4.0%
Other values (3) 91
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1782
82.9%
Dash Punctuation 356
 
16.6%
Space Separator 8
 
0.4%
Math Symbol 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 335
18.8%
3 290
16.3%
0 280
15.7%
4 230
12.9%
6 166
9.3%
1 125
 
7.0%
7 95
 
5.3%
5 95
 
5.3%
8 86
 
4.8%
9 80
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 356
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2149
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 356
16.6%
2 335
15.6%
3 290
13.5%
0 280
13.0%
4 230
10.7%
6 166
7.7%
1 125
 
5.8%
7 95
 
4.4%
5 95
 
4.4%
8 86
 
4.0%
Other values (3) 91
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2149
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 356
16.6%
2 335
15.6%
3 290
13.5%
0 280
13.0%
4 230
10.7%
6 166
7.7%
1 125
 
5.8%
7 95
 
4.4%
5 95
 
4.4%
8 86
 
4.0%
Other values (3) 91
 
4.2%

도로명주소
Text

Distinct186
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-01-06T12:37:09.588709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length40
Mean length32.064171
Min length16

Characters and Unicode

Total characters5996
Distinct characters225
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

Unique185 ?
Unique (%)98.9%

Sample

1st row인천광역시 남동구 용천로4번길 63-6 (구월동)
2nd row인천광역시 남동구 인주대로676번길 19 (구월동, 동남아파트)
3rd row인천광역시 남동구 인주대로662번길 32 (구월동, 팬더아파트)
4th row인천광역시 남동구 인주대로676번길 22 (구월동, 동아아파트)
5th row인천광역시 남동구 선수촌로 55(구월동,구월아시아드선수촌센트럴자이)
ValueCountFrequency (%)
인천광역시 187
 
17.9%
남동구 187
 
17.9%
만수동 44
 
4.2%
간석동 31
 
3.0%
논현동 30
 
2.9%
구월동 16
 
1.5%
서창동 15
 
1.4%
서창남순환로 10
 
1.0%
도림동 6
 
0.6%
만수주공아파트 6
 
0.6%
Other values (378) 514
49.1%
2024-01-06T12:37:11.106107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
862
 
14.4%
동 389
 
6.5%
구 248
 
4.1%
남 229
 
3.8%
시 205
 
3.4%
인 201
 
3.4%
천 195
 
3.3%
로 193
 
3.2%
역 192
 
3.2%
광 192
 
3.2%
Other values (215) 3090
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3895
65.0%
Space Separator 862
 
14.4%
Decimal Number 699
 
11.7%
Close Punctuation 184
 
3.1%
Open Punctuation 184
 
3.1%
Other Punctuation 129
 
2.2%
Dash Punctuation 22
 
0.4%
Uppercase Letter 21
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 389
 
10.0%
구 248
 
6.4%
남 229
 
5.9%
시 205
 
5.3%
인 201
 
5.2%
천 195
 
5.0%
로 193
 
5.0%
역 192
 
4.9%
광 192
 
4.9%
아 125
 
3.2%
Other values (195) 1726
44.3%
Decimal Number
ValueCountFrequency (%)
1 126
18.0%
2 99
14.2%
4 67
9.6%
5 64
9.2%
3 62
8.9%
6 59
8.4%
7 58
8.3%
8 56
8.0%
9 54
7.7%
0 54
7.7%
Other Punctuation
ValueCountFrequency (%)
, 127
98.4%
& 1
 
0.8%
. 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
H 10
47.6%
L 10
47.6%
B 1
 
4.8%
Space Separator
ValueCountFrequency (%)
862
100.0%
Close Punctuation
ValueCountFrequency (%)
) 184
100.0%
Open Punctuation
ValueCountFrequency (%)
( 184
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3895
65.0%
Common 2080
34.7%
Latin 21
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 389
 
10.0%
구 248
 
6.4%
남 229
 
5.9%
시 205
 
5.3%
인 201
 
5.2%
천 195
 
5.0%
로 193
 
5.0%
역 192
 
4.9%
광 192
 
4.9%
아 125
 
3.2%
Other values (195) 1726
44.3%
Common
ValueCountFrequency (%)
862
41.4%
) 184
 
8.8%
( 184
 
8.8%
, 127
 
6.1%
1 126
 
6.1%
2 99
 
4.8%
4 67
 
3.2%
5 64
 
3.1%
3 62
 
3.0%
6 59
 
2.8%
Other values (7) 246
 
11.8%
Latin
ValueCountFrequency (%)
H 10
47.6%
L 10
47.6%
B 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3895
65.0%
ASCII 2101
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
862
41.0%
) 184
 
8.8%
( 184
 
8.8%
, 127
 
6.0%
1 126
 
6.0%
2 99
 
4.7%
4 67
 
3.2%
5 64
 
3.0%
3 62
 
3.0%
6 59
 
2.8%
Other values (10) 267
 
12.7%
Hangul
ValueCountFrequency (%)
동 389
 
10.0%
구 248
 
6.4%
남 229
 
5.9%
시 205
 
5.3%
인 201
 
5.2%
천 195
 
5.0%
로 193
 
5.0%
역 192
 
4.9%
광 192
 
4.9%
아 125
 
3.2%
Other values (195) 1726
44.3%

Interactions

2024-01-06T12:36:58.820338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-06T12:37:11.505042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동구분
연번1.0000.9960.415
행정동0.9961.0000.397
구분0.4150.3971.000
2024-01-06T12:37:11.827092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동구분
행정동1.0000.298
구분0.2981.000
2024-01-06T12:37:12.176980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동구분
연번1.0000.8610.311
행정동0.8611.0000.298
구분0.3110.2981.000

Missing values

2024-01-06T12:36:59.300525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-06T12:36:59.861605image/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

연번행정동구분경로당명전화번호도로명주소
01구월1동구립대구월032-467-8158인천광역시 남동구 용천로4번길 63-6 (구월동)
12구월1동사립동남아파트032-463-8388인천광역시 남동구 인주대로676번길 19 (구월동, 동남아파트)
23구월1동사립팬더아파트032-461-5253인천광역시 남동구 인주대로662번길 32 (구월동, 팬더아파트)
34구월1동사립동아아파트032-465-1092인천광역시 남동구 인주대로676번길 22 (구월동, 동아아파트)
45구월1동사립구월아시아드선수촌센트럴자이아파트032-469-1110인천광역시 남동구 선수촌로 55(구월동,구월아시아드선수촌센트럴자이)
56구월1동사립구월아시아드선수촌1단지032-466-6410인천광역시 남동구 선수촌공원로 85(구월동,구월아시아드선수촌1단지)
67구월1동사립구월아시아드선수촌2단지032-472-2688인천광역시 남동구 선수촌공원로 96(구월동,구월아시아드선수촌2단지)
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179180논현고잔동사립에코메트로6단지032-433-8150인천광역시 남동구 아암대로1503번길 98(논현동)
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182183논현고잔동사립에코메트로10단지032-432-6300인천광역시 남동구 아암대로1503번길 21(논현동)
183184논현고잔동사립에코메트로한화11단지032-433-5070+032-441-1844인천광역시 남동구 논고개로 17 (논현동, 에코메트로11단지한화꿈에그린아파트)
184185논현고잔동사립에코메트로한화12단지032-201-6471인천광역시 남동구 논고개로 10 (논현동, 에코메트로12단지한화꿈에그린아파트)
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186187논현고잔동사립에코메트로더타워032-423-1180인천광역시 남동구 소래역남로 40(논현동,에코메트로더타워아파트)