Overview

Dataset statistics

Number of variables6
Number of observations99
Missing cells99
Missing cells (%)16.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory50.3 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description전라남도 곡성군 종교시설 현황을 제공합니다(구분 : 개신교, 불교, 원불교, 천주교, 시설명, 주소 포함하여 제공)
URLhttps://www.data.go.kr/data/15117846/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연번High correlation
도로명주소 has 5 (5.1%) missing valuesMissing
지번주소 has 94 (94.9%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:18:37.233630
Analysis finished2023-12-12 12:18:38.301572
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-12T21:18:38.441363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.9
Q125.5
median50
Q374.5
95-th percentile94.1
Maximum99
Range98
Interquartile range (IQR)49

Descriptive statistics

Standard deviation28.722813
Coefficient of variation (CV)0.57445626
Kurtosis-1.2
Mean50
Median Absolute Deviation (MAD)25
Skewness0
Sum4950
Variance825
MonotonicityStrictly increasing
2023-12-12T21:18:38.692492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
64 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
Other values (89) 89
89.9%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%
90 1
1.0%

구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
개신교
71 
불교
23 
천주교
 
3
원불교
 
2

Length

Max length3
Median length3
Mean length2.7676768
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개신교 71
71.7%
불교 23
 
23.2%
천주교 3
 
3.0%
원불교 2
 
2.0%

Length

2023-12-12T21:18:38.928221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:18:39.107639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개신교 71
71.7%
불교 23
 
23.2%
천주교 3
 
3.0%
원불교 2
 
2.0%

시설명
Text

Distinct98
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2023-12-12T21:18:39.518318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.6666667
Min length3

Characters and Unicode

Total characters462
Distinct characters121
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)98.0%

Sample

1st row곡성읍교회
2nd row곡성동막교회
3rd row곡성동부교회
4th row곡성예사랑교회
5th row곡성순복음교회
ValueCountFrequency (%)
곡성교회 2
 
2.0%
원불교 2
 
2.0%
곡성연화교회 1
 
1.0%
도림사 1
 
1.0%
서산사 1
 
1.0%
미타선원 1
 
1.0%
명산교회 1
 
1.0%
오곡교회 1
 
1.0%
압록교회 1
 
1.0%
송정교회 1
 
1.0%
Other values (90) 90
88.2%
2023-12-12T21:18:40.224916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 75
 
16.2%
회 72
 
15.6%
곡 26
 
5.6%
성 23
 
5.0%
사 20
 
4.3%
복 8
 
1.7%
원 8
 
1.7%
순 7
 
1.5%
음 7
 
1.5%
정 7
 
1.5%
Other values (111) 209
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 459
99.4%
Space Separator 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 75
 
16.3%
회 72
 
15.7%
곡 26
 
5.7%
성 23
 
5.0%
사 20
 
4.4%
복 8
 
1.7%
원 8
 
1.7%
순 7
 
1.5%
음 7
 
1.5%
정 7
 
1.5%
Other values (110) 206
44.9%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 459
99.4%
Common 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 75
 
16.3%
회 72
 
15.7%
곡 26
 
5.7%
성 23
 
5.0%
사 20
 
4.4%
복 8
 
1.7%
원 8
 
1.7%
순 7
 
1.5%
음 7
 
1.5%
정 7
 
1.5%
Other values (110) 206
44.9%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 459
99.4%
ASCII 3
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 75
 
16.3%
회 72
 
15.7%
곡 26
 
5.7%
성 23
 
5.0%
사 20
 
4.4%
복 8
 
1.7%
원 8
 
1.7%
순 7
 
1.5%
음 7
 
1.5%
정 7
 
1.5%
Other values (110) 206
44.9%
ASCII
ValueCountFrequency (%)
3
100.0%

도로명주소
Text

MISSING 

Distinct94
Distinct (%)100.0%
Missing5
Missing (%)5.1%
Memory size924.0 B
2023-12-12T21:18:40.783555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length17.06383
Min length14

Characters and Unicode

Total characters1604
Distinct characters115
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

Unique94 ?
Unique (%)100.0%

Sample

1st row전라남도 전라남도 곡성읍 읍내19길 8
2nd row전라남도 전라남도 곡성읍 동막평지길 6
3rd row전라남도 곡성읍 곡고로 245
4th row전라남도 곡성읍 읍내2길 10
5th row전라남도 곡성읍 읍내1길 18
ValueCountFrequency (%)
전라남도 96
25.4%
곡성읍 20
 
5.3%
죽곡면 14
 
3.7%
옥과면 10
 
2.6%
오곡면 9
 
2.4%
겸면 8
 
2.1%
입면 6
 
1.6%
석곡면 6
 
1.6%
삼기면 6
 
1.6%
목사동면 5
 
1.3%
Other values (160) 198
52.4%
2023-12-12T21:18:41.455232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
284
17.7%
전 98
 
6.1%
남 97
 
6.0%
도 97
 
6.0%
라 96
 
6.0%
면 74
 
4.6%
1 70
 
4.4%
길 65
 
4.1%
곡 55
 
3.4%
2 54
 
3.4%
Other values (105) 614
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 969
60.4%
Decimal Number 308
 
19.2%
Space Separator 284
 
17.7%
Dash Punctuation 43
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 98
 
10.1%
남 97
 
10.0%
도 97
 
10.0%
라 96
 
9.9%
면 74
 
7.6%
길 65
 
6.7%
곡 55
 
5.7%
로 29
 
3.0%
읍 28
 
2.9%
오 21
 
2.2%
Other values (93) 309
31.9%
Decimal Number
ValueCountFrequency (%)
1 70
22.7%
2 54
17.5%
3 35
11.4%
4 26
 
8.4%
8 26
 
8.4%
6 26
 
8.4%
5 25
 
8.1%
7 20
 
6.5%
0 15
 
4.9%
9 11
 
3.6%
Space Separator
ValueCountFrequency (%)
284
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 969
60.4%
Common 635
39.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 98
 
10.1%
남 97
 
10.0%
도 97
 
10.0%
라 96
 
9.9%
면 74
 
7.6%
길 65
 
6.7%
곡 55
 
5.7%
로 29
 
3.0%
읍 28
 
2.9%
오 21
 
2.2%
Other values (93) 309
31.9%
Common
ValueCountFrequency (%)
284
44.7%
1 70
 
11.0%
2 54
 
8.5%
- 43
 
6.8%
3 35
 
5.5%
4 26
 
4.1%
8 26
 
4.1%
6 26
 
4.1%
5 25
 
3.9%
7 20
 
3.1%
Other values (2) 26
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 969
60.4%
ASCII 635
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
284
44.7%
1 70
 
11.0%
2 54
 
8.5%
- 43
 
6.8%
3 35
 
5.5%
4 26
 
4.1%
8 26
 
4.1%
6 26
 
4.1%
5 25
 
3.9%
7 20
 
3.1%
Other values (2) 26
 
4.1%
Hangul
ValueCountFrequency (%)
전 98
 
10.1%
남 97
 
10.0%
도 97
 
10.0%
라 96
 
9.9%
면 74
 
7.6%
길 65
 
6.7%
곡 55
 
5.7%
로 29
 
3.0%
읍 28
 
2.9%
오 21
 
2.2%
Other values (93) 309
31.9%

지번주소
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing94
Missing (%)94.9%
Memory size924.0 B
2023-12-12T21:18:41.654349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length16.4
Min length14

Characters and Unicode

Total characters82
Distinct characters34
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

Unique5 ?
Unique (%)100.0%

Sample

1st row전라남도 석곡면 덕흥리 60-1
2nd row전라남도 겸면 괴정리 439-9
3rd row전라남도 죽곡면 유봉리 456
4th row전라남도 죽곡면 연화리 산11번지
5th row전라남도 오산면 선세리 2
ValueCountFrequency (%)
전라남도 5
25.0%
죽곡면 2
 
10.0%
석곡면 1
 
5.0%
덕흥리 1
 
5.0%
60-1 1
 
5.0%
겸면 1
 
5.0%
괴정리 1
 
5.0%
439-9 1
 
5.0%
유봉리 1
 
5.0%
456 1
 
5.0%
Other values (5) 5
25.0%
2023-12-12T21:18:42.077879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
18.3%
전 5
 
6.1%
남 5
 
6.1%
도 5
 
6.1%
면 5
 
6.1%
리 5
 
6.1%
라 5
 
6.1%
1 3
 
3.7%
곡 3
 
3.7%
죽 2
 
2.4%
Other values (24) 29
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52
63.4%
Space Separator 15
 
18.3%
Decimal Number 13
 
15.9%
Dash Punctuation 2
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 5
 
9.6%
남 5
 
9.6%
도 5
 
9.6%
면 5
 
9.6%
리 5
 
9.6%
라 5
 
9.6%
곡 3
 
5.8%
죽 2
 
3.8%
산 2
 
3.8%
번 1
 
1.9%
Other values (14) 14
26.9%
Decimal Number
ValueCountFrequency (%)
1 3
23.1%
9 2
15.4%
4 2
15.4%
6 2
15.4%
5 1
 
7.7%
3 1
 
7.7%
0 1
 
7.7%
2 1
 
7.7%
Space Separator
ValueCountFrequency (%)
15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52
63.4%
Common 30
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 5
 
9.6%
남 5
 
9.6%
도 5
 
9.6%
면 5
 
9.6%
리 5
 
9.6%
라 5
 
9.6%
곡 3
 
5.8%
죽 2
 
3.8%
산 2
 
3.8%
번 1
 
1.9%
Other values (14) 14
26.9%
Common
ValueCountFrequency (%)
15
50.0%
1 3
 
10.0%
9 2
 
6.7%
4 2
 
6.7%
6 2
 
6.7%
- 2
 
6.7%
5 1
 
3.3%
3 1
 
3.3%
0 1
 
3.3%
2 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52
63.4%
ASCII 30
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
50.0%
1 3
 
10.0%
9 2
 
6.7%
4 2
 
6.7%
6 2
 
6.7%
- 2
 
6.7%
5 1
 
3.3%
3 1
 
3.3%
0 1
 
3.3%
2 1
 
3.3%
Hangul
ValueCountFrequency (%)
전 5
 
9.6%
남 5
 
9.6%
도 5
 
9.6%
면 5
 
9.6%
리 5
 
9.6%
라 5
 
9.6%
곡 3
 
5.8%
죽 2
 
3.8%
산 2
 
3.8%
번 1
 
1.9%
Other values (14) 14
26.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2023-08-01
99 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-01
2nd row2023-08-01
3rd row2023-08-01
4th row2023-08-01
5th row2023-08-01

Common Values

ValueCountFrequency (%)
2023-08-01 99
100.0%

Length

2023-12-12T21:18:42.217279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:18:42.342002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-01 99
100.0%

Interactions

2023-12-12T21:18:37.730678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:18:42.429273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분시설명도로명주소지번주소
연번1.0000.7920.9411.0001.000
구분0.7921.0001.0001.0001.000
시설명0.9411.0001.0001.0001.000
도로명주소1.0001.0001.0001.000NaN
지번주소1.0001.0001.000NaN1.000
2023-12-12T21:18:42.561438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분
연번1.0000.593
구분0.5931.000

Missing values

2023-12-12T21:18:37.901178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:18:38.078765image/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.
2023-12-12T21:18:38.218621image/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

연번구분시설명도로명주소지번주소데이터기준일자
01개신교곡성읍교회전라남도 전라남도 곡성읍 읍내19길 8<NA>2023-08-01
12개신교곡성동막교회전라남도 전라남도 곡성읍 동막평지길 6<NA>2023-08-01
23개신교곡성동부교회전라남도 곡성읍 곡고로 245<NA>2023-08-01
34개신교곡성예사랑교회전라남도 곡성읍 읍내2길 10<NA>2023-08-01
45개신교곡성순복음교회전라남도 곡성읍 읍내1길 18<NA>2023-08-01
56개신교곡성은혜교회전라남도 곡성읍 학교로 95<NA>2023-08-01
67개신교순복음장선교회전라남도 곡성읍 장선2길 35-2<NA>2023-08-01
78개신교장신교회전라남도 곡성읍 장신2길 19-19<NA>2023-08-01
89개신교곡성중앙교회전라남도 곡성읍 읍내11길 6<NA>2023-08-01
910개신교곡성은광교회전라남도 곡성읍 학교로 168<NA>2023-08-01
연번구분시설명도로명주소지번주소데이터기준일자
8990불교청정사전라남도 오산면 보정길 110-65<NA>2023-08-01
9091불교용주사전라남도 오산면 무옥로 230-91<NA>2023-08-01
9192불교관음사<NA>전라남도 오산면 선세리 22023-08-01
9293불교명산정사전라남도 오곡면 명산길 123-138<NA>2023-08-01
9394불교무각사전라남도 오곡면 미산길 268-68<NA>2023-08-01
9495원불교원불교 곡성교당전라남도 곡성읍 읍내17길 25<NA>2023-08-01
9596원불교원불교 옥과교당전라남도 옥과면 죽림5길 30<NA>2023-08-01
9697천주교곡성성당전라남도 곡성읍 읍내11길 20<NA>2023-08-01
9798천주교석곡천주교회전라남도 석곡면 석곡3길 22-2<NA>2023-08-01
9899천주교옥과성당전라남도 옥과면 옥과1길 14<NA>2023-08-01