Overview

Dataset statistics

Number of variables5
Number of observations155
Missing cells3
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory41.9 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description계양구 관내 경로당 현황 정보에 대한 데이터로 경로당에 대한 행정동, 경로당명, 주소, 연락처를 포함한 데이터파일입니다.
Author인천광역시 계양구
URLhttps://www.data.go.kr/data/3070942/fileData.do

Alerts

연번 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연번High correlation
연락처 has 3 (1.9%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:34:35.982211
Analysis finished2023-12-12 21:34:36.460168
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct155
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78
Minimum1
Maximum155
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T06:34:36.831246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.7
Q139.5
median78
Q3116.5
95-th percentile147.3
Maximum155
Range154
Interquartile range (IQR)77

Descriptive statistics

Standard deviation44.888751
Coefficient of variation (CV)0.57549681
Kurtosis-1.2
Mean78
Median Absolute Deviation (MAD)39
Skewness0
Sum12090
Variance2015
MonotonicityStrictly increasing
2023-12-13T06:34:36.970361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
108 1
 
0.6%
101 1
 
0.6%
102 1
 
0.6%
103 1
 
0.6%
104 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
109 1
 
0.6%
Other values (145) 145
93.5%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
155 1
0.6%
154 1
0.6%
153 1
0.6%
152 1
0.6%
151 1
0.6%
150 1
0.6%
149 1
0.6%
148 1
0.6%
147 1
0.6%
146 1
0.6%

구분
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
계양1동
20 
작전1동
19 
효성2동
17 
효성1동
14 
계산3동
14 
Other values (7)
71 

Length

Max length5
Median length4
Mean length4.0903226
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row효성1동
2nd row효성1동
3rd row효성1동
4th row효성1동
5th row효성1동

Common Values

ValueCountFrequency (%)
계양1동 20
12.9%
작전1동 19
12.3%
효성2동 17
11.0%
효성1동 14
9.0%
계산3동 14
9.0%
작전서운동 14
9.0%
계양3동 12
7.7%
계산4동 11
7.1%
계양2동 11
7.1%
계산2동 8
 
5.2%
Other values (2) 15
9.7%

Length

2023-12-13T06:34:37.132415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계양1동 20
12.9%
작전1동 19
12.3%
효성2동 17
11.0%
효성1동 14
9.0%
계산3동 14
9.0%
작전서운동 14
9.0%
계양3동 12
7.7%
계산4동 11
7.1%
계양2동 11
7.1%
계산2동 8
 
5.2%
Other values (2) 15
9.7%

경로당명
Text

Distinct146
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T06:34:37.441556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.116129
Min length2

Characters and Unicode

Total characters793
Distinct characters165
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique138 ?
Unique (%)89.0%

Sample

1st row효성1동경로당
2nd row효성1동이촌경로당
3rd row뉴서울1차
4th row뉴서울2차
5th row대림
ValueCountFrequency (%)
경로당 4
 
2.5%
한국 3
 
1.9%
하나 2
 
1.3%
아주 2
 
1.3%
현대1차 2
 
1.3%
신진 2
 
1.3%
현대3차 2
 
1.3%
뉴서울1차 2
 
1.3%
뉴서울2차 2
 
1.3%
계양그대가 1
 
0.6%
Other values (137) 137
86.2%
2023-12-13T06:34:37.931159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 43
 
5.4%
경 35
 
4.4%
차 35
 
4.4%
로 32
 
4.0%
당 31
 
3.9%
1 25
 
3.2%
2 21
 
2.6%
마 19
 
2.4%
을 19
 
2.4%
한 15
 
1.9%
Other values (155) 518
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 718
90.5%
Decimal Number 57
 
7.2%
Space Separator 5
 
0.6%
Close Punctuation 4
 
0.5%
Open Punctuation 4
 
0.5%
Dash Punctuation 2
 
0.3%
Other Punctuation 2
 
0.3%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 43
 
6.0%
경 35
 
4.9%
차 35
 
4.9%
로 32
 
4.5%
당 31
 
4.3%
마 19
 
2.6%
을 19
 
2.6%
한 15
 
2.1%
아 15
 
2.1%
대 14
 
1.9%
Other values (143) 460
64.1%
Decimal Number
ValueCountFrequency (%)
1 25
43.9%
2 21
36.8%
3 7
 
12.3%
4 2
 
3.5%
6 1
 
1.8%
5 1
 
1.8%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Other Symbol
ValueCountFrequency (%)
ⓐ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 718
90.5%
Common 75
 
9.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 43
 
6.0%
경 35
 
4.9%
차 35
 
4.9%
로 32
 
4.5%
당 31
 
4.3%
마 19
 
2.6%
을 19
 
2.6%
한 15
 
2.1%
아 15
 
2.1%
대 14
 
1.9%
Other values (143) 460
64.1%
Common
ValueCountFrequency (%)
1 25
33.3%
2 21
28.0%
3 7
 
9.3%
5
 
6.7%
) 4
 
5.3%
( 4
 
5.3%
- 2
 
2.7%
4 2
 
2.7%
, 2
 
2.7%
6 1
 
1.3%
Other values (2) 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 718
90.5%
ASCII 74
 
9.3%
Enclosed Alphanum 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 43
 
6.0%
경 35
 
4.9%
차 35
 
4.9%
로 32
 
4.5%
당 31
 
4.3%
마 19
 
2.6%
을 19
 
2.6%
한 15
 
2.1%
아 15
 
2.1%
대 14
 
1.9%
Other values (143) 460
64.1%
ASCII
ValueCountFrequency (%)
1 25
33.8%
2 21
28.4%
3 7
 
9.5%
5
 
6.8%
) 4
 
5.4%
( 4
 
5.4%
- 2
 
2.7%
4 2
 
2.7%
, 2
 
2.7%
6 1
 
1.4%
Enclosed Alphanum
ValueCountFrequency (%)
ⓐ 1
100.0%

주소
Text

Distinct150
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T06:34:38.308238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length19.464516
Min length14

Characters and Unicode

Total characters3017
Distinct characters89
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

Unique145 ?
Unique (%)93.5%

Sample

1st row인천광역시 계양구 봉오대로 516
2nd row인천광역시 계양구 봉오대로531번길 27
3rd row인천광역시 계양구 안남로573번길 16
4th row인천광역시 계양구 안남로 560
5th row인천광역시 계양구 안남로 583
ValueCountFrequency (%)
인천광역시 155
25.0%
계양구 155
25.0%
효서로 8
 
1.3%
10 7
 
1.1%
8 5
 
0.8%
26 5
 
0.8%
장제로 5
 
0.8%
12 5
 
0.8%
27 5
 
0.8%
9 5
 
0.8%
Other values (182) 266
42.8%
2023-12-13T06:34:38.794882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
466
15.4%
계 175
 
5.8%
양 166
 
5.5%
역 156
 
5.2%
시 156
 
5.2%
천 156
 
5.2%
인 155
 
5.1%
광 155
 
5.1%
구 155
 
5.1%
로 143
 
4.7%
Other values (79) 1134
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1962
65.0%
Decimal Number 577
 
19.1%
Space Separator 466
 
15.4%
Dash Punctuation 12
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 175
 
8.9%
양 166
 
8.5%
역 156
 
8.0%
시 156
 
8.0%
천 156
 
8.0%
인 155
 
7.9%
광 155
 
7.9%
구 155
 
7.9%
로 143
 
7.3%
길 96
 
4.9%
Other values (67) 449
22.9%
Decimal Number
ValueCountFrequency (%)
1 127
22.0%
2 75
13.0%
3 69
12.0%
4 59
10.2%
5 51
8.8%
7 43
 
7.5%
8 39
 
6.8%
9 39
 
6.8%
0 38
 
6.6%
6 37
 
6.4%
Space Separator
ValueCountFrequency (%)
466
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1962
65.0%
Common 1055
35.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 175
 
8.9%
양 166
 
8.5%
역 156
 
8.0%
시 156
 
8.0%
천 156
 
8.0%
인 155
 
7.9%
광 155
 
7.9%
구 155
 
7.9%
로 143
 
7.3%
길 96
 
4.9%
Other values (67) 449
22.9%
Common
ValueCountFrequency (%)
466
44.2%
1 127
 
12.0%
2 75
 
7.1%
3 69
 
6.5%
4 59
 
5.6%
5 51
 
4.8%
7 43
 
4.1%
8 39
 
3.7%
9 39
 
3.7%
0 38
 
3.6%
Other values (2) 49
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1962
65.0%
ASCII 1055
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
466
44.2%
1 127
 
12.0%
2 75
 
7.1%
3 69
 
6.5%
4 59
 
5.6%
5 51
 
4.8%
7 43
 
4.1%
8 39
 
3.7%
9 39
 
3.7%
0 38
 
3.6%
Other values (2) 49
 
4.6%
Hangul
ValueCountFrequency (%)
계 175
 
8.9%
양 166
 
8.5%
역 156
 
8.0%
시 156
 
8.0%
천 156
 
8.0%
인 155
 
7.9%
광 155
 
7.9%
구 155
 
7.9%
로 143
 
7.3%
길 96
 
4.9%
Other values (67) 449
22.9%

연락처
Text

MISSING 

Distinct152
Distinct (%)100.0%
Missing3
Missing (%)1.9%
Memory size1.3 KiB
2023-12-13T06:34:39.133177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.019737
Min length12

Characters and Unicode

Total characters1827
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

Unique152 ?
Unique (%)100.0%

Sample

1st row032-548-4872
2nd row032-546-2443
3rd row032-549-0056
4th row032-547-9025
5th row032-542-8874
ValueCountFrequency (%)
032-541-5378 1
 
0.7%
032-549-3863 1
 
0.7%
032-515-9710 1
 
0.7%
032-544-2150 1
 
0.7%
032-545-6621 1
 
0.7%
032-541-4186 1
 
0.7%
032-547-8487 1
 
0.7%
032-541-5030 1
 
0.7%
032-543-9770 1
 
0.7%
032-543-7677 1
 
0.7%
Other values (142) 142
93.4%
2023-12-13T06:34:39.495655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 304
16.6%
5 256
14.0%
2 238
13.0%
3 227
12.4%
0 217
11.9%
4 183
10.0%
1 89
 
4.9%
7 82
 
4.5%
8 80
 
4.4%
6 80
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1523
83.4%
Dash Punctuation 304
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 256
16.8%
2 238
15.6%
3 227
14.9%
0 217
14.2%
4 183
12.0%
1 89
 
5.8%
7 82
 
5.4%
8 80
 
5.3%
6 80
 
5.3%
9 71
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 304
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1827
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 304
16.6%
5 256
14.0%
2 238
13.0%
3 227
12.4%
0 217
11.9%
4 183
10.0%
1 89
 
4.9%
7 82
 
4.5%
8 80
 
4.4%
6 80
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1827
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 304
16.6%
5 256
14.0%
2 238
13.0%
3 227
12.4%
0 217
11.9%
4 183
10.0%
1 89
 
4.9%
7 82
 
4.5%
8 80
 
4.4%
6 80
 
4.4%

Interactions

2023-12-13T06:34:36.210124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:34:39.581958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분
연번1.0000.955
구분0.9551.000
2023-12-13T06:34:39.673238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분
연번1.0000.817
구분0.8171.000

Missing values

2023-12-13T06:34:36.333771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:34:36.418446image/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

연번구분경로당명주소연락처
01효성1동효성1동경로당인천광역시 계양구 봉오대로 516032-548-4872
12효성1동효성1동이촌경로당인천광역시 계양구 봉오대로531번길 27032-546-2443
23효성1동뉴서울1차인천광역시 계양구 안남로573번길 16032-549-0056
34효성1동뉴서울2차인천광역시 계양구 안남로 560032-547-9025
45효성1동대림인천광역시 계양구 안남로 583032-542-8874
56효성1동동아인천광역시 계양구 새벌로 159032-543-7712
67효성1동두산인천광역시 계양구 안남로573번길 18032-541-4646
78효성1동신한인천광역시 계양구 봉오대로555번길 5032-552-6863
89효성1동중앙인천광역시 계양구 봉오대로628번길 8032-541-5378
910효성1동중앙하이츠인천광역시 계양구 안남로572번길 17032-543-9983
연번구분경로당명주소연락처
145146계양3동상야동경로당인천광역시 계양구 벌말로565번길 15-16032-544-7170
146147계양3동하야동 경로당인천광역시 계양구 벌말로609번길 16032-544-2611
147148계양3동동양주공1단지인천광역시 계양구 양지로 7032-555-0289
148149계양3동동양주공2단지인천광역시 계양구 동양로 96032-553-0307
149150계양3동한진해모로인천광역시 계양구 동양로 100032-555-8813
150151계양3동동양주공4단지인천광역시 계양구 둥그재산길 29032-555-6542
151152계양3동귤현아이파크인천광역시 계양구 장군봉길 12032-551-4554
152153계양3동휴먼빌인천광역시 계양구 당미길 43032-548-1171
153154계양3동계양센트레빌1단지인천광역시 계양구 형제봉길 100032-541-8014
154155계양3동계양센트레빌3단지인천광역시 계양구 형제봉길 1032-548-4467