Overview

Dataset statistics

Number of variables6
Number of observations163
Missing cells79
Missing cells (%)8.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.9 KiB
Average record size in memory49.8 B

Variable types

Numeric1
Text4
Categorical1

Dataset

Description인천광역시 미추홀구 종교시설에 대한 데이터로 상호명, 도로명주소, 전화번호, 위도, 경도 등의 정보를 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15087066/fileData.do

Alerts

연번 is highly overall correlated with 분류High correlation
분류 is highly overall correlated with 연번High correlation
도로명주소 has 11 (6.7%) missing valuesMissing
전화번호 has 68 (41.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:01:46.135121
Analysis finished2023-12-12 20:01:46.825374
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct163
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82
Minimum1
Maximum163
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-13T05:01:46.892330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.1
Q141.5
median82
Q3122.5
95-th percentile154.9
Maximum163
Range162
Interquartile range (IQR)81

Descriptive statistics

Standard deviation47.198164
Coefficient of variation (CV)0.57558736
Kurtosis-1.2
Mean82
Median Absolute Deviation (MAD)41
Skewness0
Sum13366
Variance2227.6667
MonotonicityStrictly increasing
2023-12-13T05:01:47.022089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
104 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
112 1
 
0.6%
113 1
 
0.6%
Other values (153) 153
93.9%
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 (%)
163 1
0.6%
162 1
0.6%
161 1
0.6%
160 1
0.6%
159 1
0.6%
158 1
0.6%
157 1
0.6%
156 1
0.6%
155 1
0.6%
154 1
0.6%

상호명
Text

Distinct155
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T05:01:47.282497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length5.9754601
Min length3

Characters and Unicode

Total characters974
Distinct characters187
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)90.2%

Sample

1st row용화선원
2nd row석암산수도사
3rd row경인불교대학 수미정사
4th row대한불교조계종 영산정사
5th row해성암
ValueCountFrequency (%)
천주교용현교회 2
 
1.2%
천주교주안5동교회 2
 
1.2%
일심사 2
 
1.2%
숭의동성당 2
 
1.2%
수녀원 2
 
1.2%
주안교회 2
 
1.2%
인천교회 2
 
1.2%
천주교주안8동교회 2
 
1.2%
천주교주안1동교회입구 2
 
1.2%
행복한교회 2
 
1.2%
Other values (152) 153
88.4%
2023-12-13T05:01:47.681888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 138
 
14.2%
회 116
 
11.9%
주 49
 
5.0%
천 36
 
3.7%
사 35
 
3.6%
동 24
 
2.5%
안 23
 
2.4%
성 21
 
2.2%
인 18
 
1.8%
용 15
 
1.5%
Other values (177) 499
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 946
97.1%
Decimal Number 15
 
1.5%
Space Separator 10
 
1.0%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 138
 
14.6%
회 116
 
12.3%
주 49
 
5.2%
천 36
 
3.8%
사 35
 
3.7%
동 24
 
2.5%
안 23
 
2.4%
성 21
 
2.2%
인 18
 
1.9%
용 15
 
1.6%
Other values (168) 471
49.8%
Decimal Number
ValueCountFrequency (%)
5 6
40.0%
1 3
20.0%
8 3
20.0%
3 2
 
13.3%
7 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
M 1
33.3%
T 1
33.3%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 946
97.1%
Common 25
 
2.6%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 138
 
14.6%
회 116
 
12.3%
주 49
 
5.2%
천 36
 
3.8%
사 35
 
3.7%
동 24
 
2.5%
안 23
 
2.4%
성 21
 
2.2%
인 18
 
1.9%
용 15
 
1.6%
Other values (168) 471
49.8%
Common
ValueCountFrequency (%)
10
40.0%
5 6
24.0%
1 3
 
12.0%
8 3
 
12.0%
3 2
 
8.0%
7 1
 
4.0%
Latin
ValueCountFrequency (%)
A 1
33.3%
M 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 946
97.1%
ASCII 28
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 138
 
14.6%
회 116
 
12.3%
주 49
 
5.2%
천 36
 
3.8%
사 35
 
3.7%
동 24
 
2.5%
안 23
 
2.4%
성 21
 
2.2%
인 18
 
1.9%
용 15
 
1.6%
Other values (168) 471
49.8%
ASCII
ValueCountFrequency (%)
10
35.7%
5 6
21.4%
1 3
 
10.7%
8 3
 
10.7%
3 2
 
7.1%
A 1
 
3.6%
7 1
 
3.6%
M 1
 
3.6%
T 1
 
3.6%

분류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
교회
99 
절
40 
성당
24 

Length

Max length2
Median length2
Mean length1.7546012
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교회 99
60.7%
절 40
24.5%
성당 24
 
14.7%

Length

2023-12-13T05:01:47.805783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:01:47.908283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교회 99
60.7%
절 40
24.5%
성당 24
 
14.7%

지번주소
Text

Distinct151
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T05:01:48.244754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length30
Mean length21.055215
Min length14

Characters and Unicode

Total characters3432
Distinct characters72
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)87.1%

Sample

1st row인천광역시 미추홀구 주안동 16-113
2nd row인천광역시 미추홀구 주안동 1580-23
3rd row인천광역시 미추홀구 문학동 252-3
4th row인천광역시 미추홀구 숭의동 8-90
5th row인천광역시 미추홀구 주안동 619-2
ValueCountFrequency (%)
인천광역시 163
24.3%
미추홀구 163
24.3%
주안동 58
 
8.6%
용현동 31
 
4.6%
도화동 22
 
3.3%
숭의동 19
 
2.8%
학익동 15
 
2.2%
문학동 10
 
1.5%
2층 4
 
0.6%
3층 4
 
0.6%
Other values (166) 182
27.1%
2023-12-13T05:01:48.850983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
529
 
15.4%
1 165
 
4.8%
추 163
 
4.7%
천 163
 
4.7%
동 163
 
4.7%
구 163
 
4.7%
홀 163
 
4.7%
인 163
 
4.7%
미 163
 
4.7%
역 163
 
4.7%
Other values (62) 1434
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2025
59.0%
Decimal Number 726
 
21.2%
Space Separator 529
 
15.4%
Dash Punctuation 151
 
4.4%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 163
8.0%
천 163
8.0%
동 163
8.0%
구 163
8.0%
홀 163
8.0%
인 163
8.0%
미 163
8.0%
역 163
8.0%
시 163
8.0%
광 163
8.0%
Other values (49) 395
19.5%
Decimal Number
ValueCountFrequency (%)
1 165
22.7%
2 93
12.8%
3 74
10.2%
5 72
9.9%
4 71
9.8%
6 67
9.2%
8 59
 
8.1%
0 46
 
6.3%
9 44
 
6.1%
7 35
 
4.8%
Space Separator
ValueCountFrequency (%)
529
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 151
100.0%
Uppercase Letter
ValueCountFrequency (%)
W 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2025
59.0%
Common 1406
41.0%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 163
8.0%
천 163
8.0%
동 163
8.0%
구 163
8.0%
홀 163
8.0%
인 163
8.0%
미 163
8.0%
역 163
8.0%
시 163
8.0%
광 163
8.0%
Other values (49) 395
19.5%
Common
ValueCountFrequency (%)
529
37.6%
1 165
 
11.7%
- 151
 
10.7%
2 93
 
6.6%
3 74
 
5.3%
5 72
 
5.1%
4 71
 
5.0%
6 67
 
4.8%
8 59
 
4.2%
0 46
 
3.3%
Other values (2) 79
 
5.6%
Latin
ValueCountFrequency (%)
W 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2025
59.0%
ASCII 1407
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
529
37.6%
1 165
 
11.7%
- 151
 
10.7%
2 93
 
6.6%
3 74
 
5.3%
5 72
 
5.1%
4 71
 
5.0%
6 67
 
4.8%
8 59
 
4.2%
0 46
 
3.3%
Other values (3) 80
 
5.7%
Hangul
ValueCountFrequency (%)
추 163
8.0%
천 163
8.0%
동 163
8.0%
구 163
8.0%
홀 163
8.0%
인 163
8.0%
미 163
8.0%
역 163
8.0%
시 163
8.0%
광 163
8.0%
Other values (49) 395
19.5%

도로명주소
Text

MISSING 

Distinct144
Distinct (%)94.7%
Missing11
Missing (%)6.7%
Memory size1.4 KiB
2023-12-13T05:01:49.170897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length22.539474
Min length17

Characters and Unicode

Total characters3426
Distinct characters151
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique138 ?
Unique (%)90.8%

Sample

1st row인천광역시 미추홀구 주염로 43
2nd row인천광역시 미추홀구 구월로8번길 36-5
3rd row인천광역시 미추홀구 매소홀로561번길 26-93 수미정사
4th row인천광역시 미추홀구 수봉로85번길 22
5th row인천광역시 미추홀구 한나루로585번길 25-4
ValueCountFrequency (%)
인천광역시 152
23.1%
미추홀구 152
23.1%
인하로 7
 
1.1%
매소홀로 7
 
1.1%
석정로 5
 
0.8%
25 5
 
0.8%
길파로28번길 4
 
0.6%
19 4
 
0.6%
인주대로 4
 
0.6%
80 4
 
0.6%
Other values (258) 314
47.7%
2023-12-13T05:01:49.616303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
507
 
14.8%
인 192
 
5.6%
홀 169
 
4.9%
미 158
 
4.6%
추 156
 
4.6%
구 156
 
4.6%
천 156
 
4.6%
광 152
 
4.4%
역 152
 
4.4%
시 152
 
4.4%
Other values (141) 1476
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2281
66.6%
Decimal Number 609
 
17.8%
Space Separator 507
 
14.8%
Dash Punctuation 28
 
0.8%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 192
 
8.4%
홀 169
 
7.4%
미 158
 
6.9%
추 156
 
6.8%
구 156
 
6.8%
천 156
 
6.8%
광 152
 
6.7%
역 152
 
6.7%
시 152
 
6.7%
로 139
 
6.1%
Other values (128) 699
30.6%
Decimal Number
ValueCountFrequency (%)
1 93
15.3%
2 86
14.1%
3 76
12.5%
5 76
12.5%
4 70
11.5%
6 60
9.9%
8 48
7.9%
7 45
7.4%
9 33
 
5.4%
0 22
 
3.6%
Space Separator
ValueCountFrequency (%)
507
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Uppercase Letter
ValueCountFrequency (%)
W 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2281
66.6%
Common 1144
33.4%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 192
 
8.4%
홀 169
 
7.4%
미 158
 
6.9%
추 156
 
6.8%
구 156
 
6.8%
천 156
 
6.8%
광 152
 
6.7%
역 152
 
6.7%
시 152
 
6.7%
로 139
 
6.1%
Other values (128) 699
30.6%
Common
ValueCountFrequency (%)
507
44.3%
1 93
 
8.1%
2 86
 
7.5%
3 76
 
6.6%
5 76
 
6.6%
4 70
 
6.1%
6 60
 
5.2%
8 48
 
4.2%
7 45
 
3.9%
9 33
 
2.9%
Other values (2) 50
 
4.4%
Latin
ValueCountFrequency (%)
W 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2281
66.6%
ASCII 1145
33.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
507
44.3%
1 93
 
8.1%
2 86
 
7.5%
3 76
 
6.6%
5 76
 
6.6%
4 70
 
6.1%
6 60
 
5.2%
8 48
 
4.2%
7 45
 
3.9%
9 33
 
2.9%
Other values (3) 51
 
4.5%
Hangul
ValueCountFrequency (%)
인 192
 
8.4%
홀 169
 
7.4%
미 158
 
6.9%
추 156
 
6.8%
구 156
 
6.8%
천 156
 
6.8%
광 152
 
6.7%
역 152
 
6.7%
시 152
 
6.7%
로 139
 
6.1%
Other values (128) 699
30.6%

전화번호
Text

MISSING 

Distinct92
Distinct (%)96.8%
Missing68
Missing (%)41.7%
Memory size1.4 KiB
2023-12-13T05:01:49.880860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.210526
Min length12

Characters and Unicode

Total characters1160
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

Unique89 ?
Unique (%)93.7%

Sample

1st row032-872-6061
2nd row032-422-1479
3rd row032-427-8400
4th row032-872-5071
5th row032-868-7711
ValueCountFrequency (%)
032-864-8660 2
 
2.1%
032-867-1157 2
 
2.1%
032-421-3061 2
 
2.1%
032-876-4853 1
 
1.1%
032-888-0524 1
 
1.1%
032-882-9106 1
 
1.1%
032-427-3309 1
 
1.1%
032-863-0288 1
 
1.1%
032-283-0691 1
 
1.1%
032-429-7071 1
 
1.1%
Other values (82) 82
86.3%
2023-12-13T05:01:50.290292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 190
16.4%
0 171
14.7%
2 143
12.3%
3 136
11.7%
8 106
9.1%
7 85
7.3%
6 80
6.9%
1 78
6.7%
4 67
 
5.8%
5 59
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 970
83.6%
Dash Punctuation 190
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 171
17.6%
2 143
14.7%
3 136
14.0%
8 106
10.9%
7 85
8.8%
6 80
8.2%
1 78
8.0%
4 67
 
6.9%
5 59
 
6.1%
9 45
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1160
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 190
16.4%
0 171
14.7%
2 143
12.3%
3 136
11.7%
8 106
9.1%
7 85
7.3%
6 80
6.9%
1 78
6.7%
4 67
 
5.8%
5 59
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 190
16.4%
0 171
14.7%
2 143
12.3%
3 136
11.7%
8 106
9.1%
7 85
7.3%
6 80
6.9%
1 78
6.7%
4 67
 
5.8%
5 59
 
5.1%

Interactions

2023-12-13T05:01:46.447232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:01:50.392589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번분류전화번호
연번1.0000.9340.740
분류0.9341.0000.000
전화번호0.7400.0001.000
2023-12-13T05:01:50.493580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번분류
연번1.0000.894
분류0.8941.000

Missing values

2023-12-13T05:01:46.584526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:01:46.683183image/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.
2023-12-13T05:01:46.771601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번상호명분류지번주소도로명주소전화번호
01용화선원절인천광역시 미추홀구 주안동 16-113인천광역시 미추홀구 주염로 43032-872-6061
12석암산수도사절인천광역시 미추홀구 주안동 1580-23인천광역시 미추홀구 구월로8번길 36-5032-422-1479
23경인불교대학 수미정사절인천광역시 미추홀구 문학동 252-3인천광역시 미추홀구 매소홀로561번길 26-93 수미정사032-427-8400
34대한불교조계종 영산정사절인천광역시 미추홀구 숭의동 8-90인천광역시 미추홀구 수봉로85번길 22032-872-5071
45해성암절인천광역시 미추홀구 주안동 619-2인천광역시 미추홀구 한나루로585번길 25-4<NA>
56부용사절인천광역시 미추홀구 도화동 624-240인천광역시 미추홀구 수봉북로 34<NA>
67백련정사절인천광역시 미추홀구 도화동 산60-18 백련정사인천광역시 미추홀구 경인로252번안길 58-16 백련정사032-868-7711
78불국원미타사절인천광역시 미추홀구 주안동 1417-12인천광역시 미추홀구 한나루로526번길 69032-873-0108
89천영사절인천광역시 미추홀구 도화동 147-11인천광역시 미추홀구 석정로282번길 25-5032-864-5067
910용현사절인천광역시 미추홀구 숭의동 283-17인천광역시 미추홀구 독배로446번길 4<NA>
연번상호명분류지번주소도로명주소전화번호
153154풍성장로교회교회인천광역시 미추홀구 주안동 1583-9인천광역시 미추홀구 구월로 24<NA>
154155인천중앙장로교회교회인천광역시 미추홀구 문학동 395-5인천광역시 미추홀구 문학길125번길 28<NA>
155156주안사랑교회교회인천광역시 미추홀구 주안동 850-43인천광역시 미추홀구 신기길16번길 63-6 동서쉐르빌032-868-0934
156157소망농인교회교회인천광역시 미추홀구 숭의동 62-8인천광역시 미추홀구 경인로 115 소망농인교회<NA>
157158인천교회교회인천광역시 미추홀구 도화동 567-5인천광역시 미추홀구 주안로7번길 4032-866-9585
158159시온성교회교회인천광역시 미추홀구 주안동 1354-4 W빌딩 3층인천광역시 미추홀구 미추홀대로 529 W빌딩 3층032-247-4044
159160천주교주안5동교회교회인천광역시 미추홀구 주안동 16-150인천광역시 미추홀구 길파로28번길 19032-867-1157
160161행복한장로교회교회인천광역시 미추홀구 용현동 565-18인천광역시 미추홀구 낙섬중로91번길 6<NA>
161162작은교회교회인천광역시 미추홀구 문학동 366-2인천광역시 미추홀구 문학길 9-9032-875-6589
162163새생명교회교회인천광역시 미추홀구 학익동 2-9인천광역시 미추홀구 재넘이길 6032-865-2296