Overview

Dataset statistics

Number of variables7
Number of observations57
Missing cells2
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory60.3 B

Variable types

Categorical3
Text2
Numeric2

Dataset

Description이 데이터는 과천시 관내 종교시설 현황에 대한 데이터로 종교명, 시설명, 소재지 주소, 위도, 경도 등의 항목을 제공합니다.
Author경기도 과천시
URLhttps://www.data.go.kr/data/15091552/fileData.do

Alerts

시군명 has constant value ""Constant
데이터기준일 has constant value ""Constant
위도 has 1 (1.8%) missing valuesMissing
경도 has 1 (1.8%) missing valuesMissing
시설명 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:51:56.901107
Analysis finished2023-12-12 15:51:58.066883
Duration1.17 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
경기도 과천시
57 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 과천시
2nd row경기도 과천시
3rd row경기도 과천시
4th row경기도 과천시
5th row경기도 과천시

Common Values

ValueCountFrequency (%)
경기도 과천시 57
100.0%

Length

2023-12-13T00:51:58.132690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:51:58.210769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 57
50.0%
과천시 57
50.0%

종교명
Categorical

Distinct5
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
개신교
42 
불교
10 
천주교
 
3
미얀마불교
 
1
원불교
 
1

Length

Max length5
Median length3
Mean length2.8596491
Min length2

Unique

Unique2 ?
Unique (%)3.5%

Sample

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

Common Values

ValueCountFrequency (%)
개신교 42
73.7%
불교 10
 
17.5%
천주교 3
 
5.3%
미얀마불교 1
 
1.8%
원불교 1
 
1.8%

Length

2023-12-13T00:51:58.300819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:51:58.400646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개신교 42
73.7%
불교 10
 
17.5%
천주교 3
 
5.3%
미얀마불교 1
 
1.8%
원불교 1
 
1.8%

시설명
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-13T00:51:58.623461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length7.9122807
Min length3

Characters and Unicode

Total characters451
Distinct characters118
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

Unique57 ?
Unique (%)100.0%

Sample

1st row과천교회
2nd row대한예수교 과천복음교회
3rd row과천성결교회
4th row과천소망교회
5th row대한예수교장로회과천약수교회
ValueCountFrequency (%)
대한불교조계종 4
 
5.3%
천주교 2
 
2.7%
과천교회 2
 
2.7%
보리수선원 1
 
1.3%
사)한국테라와다불교 1
 
1.3%
엘림교회 1
 
1.3%
예복교회 1
 
1.3%
예수중심교회 1
 
1.3%
과천성전 1
 
1.3%
은혜교회 1
 
1.3%
Other values (60) 60
80.0%
2023-12-13T00:51:59.303560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 58
 
12.9%
회 45
 
10.0%
천 29
 
6.4%
과 24
 
5.3%
18
 
4.0%
한 12
 
2.7%
수 10
 
2.2%
사 10
 
2.2%
예 8
 
1.8%
대 8
 
1.8%
Other values (108) 229
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 423
93.8%
Space Separator 18
 
4.0%
Open Punctuation 5
 
1.1%
Close Punctuation 5
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 58
 
13.7%
회 45
 
10.6%
천 29
 
6.9%
과 24
 
5.7%
한 12
 
2.8%
수 10
 
2.4%
사 10
 
2.4%
예 8
 
1.9%
대 8
 
1.9%
불 7
 
1.7%
Other values (105) 212
50.1%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 423
93.8%
Common 28
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 58
 
13.7%
회 45
 
10.6%
천 29
 
6.9%
과 24
 
5.7%
한 12
 
2.8%
수 10
 
2.4%
사 10
 
2.4%
예 8
 
1.9%
대 8
 
1.9%
불 7
 
1.7%
Other values (105) 212
50.1%
Common
ValueCountFrequency (%)
18
64.3%
( 5
 
17.9%
) 5
 
17.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 423
93.8%
ASCII 28
 
6.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 58
 
13.7%
회 45
 
10.6%
천 29
 
6.9%
과 24
 
5.7%
한 12
 
2.8%
수 10
 
2.4%
사 10
 
2.4%
예 8
 
1.9%
대 8
 
1.9%
불 7
 
1.7%
Other values (105) 212
50.1%
ASCII
ValueCountFrequency (%)
18
64.3%
( 5
 
17.9%
) 5
 
17.9%

도로명주소
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-13T00:51:59.572848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length30
Mean length24.350877
Min length15

Characters and Unicode

Total characters1388
Distinct characters107
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

Unique57 ?
Unique (%)100.0%

Sample

1st row경기도 과천시 관악산길 103 (중앙동)
2nd row경기도 과천시 관문로 166, 10단지상가 205호
3rd row경기도 과천시 별양동 93 자이상가 301호
4th row경기도 과천시 문원청계2길 50 (문원동)
5th row경기도 과천시 별양로 86 (별양동)
ValueCountFrequency (%)
경기도 57
18.4%
과천시 52
 
16.8%
중앙동 12
 
3.9%
별양동 12
 
3.9%
과천동 9
 
2.9%
별양로 7
 
2.3%
갈현동 5
 
1.6%
경마공원대로 5
 
1.6%
과천시시 5
 
1.6%
관문로 4
 
1.3%
Other values (120) 141
45.6%
2023-12-13T00:52:00.015092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
252
18.2%
과 68
 
4.9%
천 68
 
4.9%
경 63
 
4.5%
시 63
 
4.5%
1 60
 
4.3%
도 57
 
4.1%
기 57
 
4.1%
동 52
 
3.7%
( 45
 
3.2%
Other values (97) 603
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 795
57.3%
Space Separator 252
 
18.2%
Decimal Number 214
 
15.4%
Open Punctuation 45
 
3.2%
Close Punctuation 45
 
3.2%
Dash Punctuation 20
 
1.4%
Other Punctuation 16
 
1.2%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 68
 
8.6%
천 68
 
8.6%
경 63
 
7.9%
시 63
 
7.9%
도 57
 
7.2%
기 57
 
7.2%
동 52
 
6.5%
로 35
 
4.4%
양 25
 
3.1%
별 25
 
3.1%
Other values (81) 282
35.5%
Decimal Number
ValueCountFrequency (%)
1 60
28.0%
2 31
14.5%
5 23
 
10.7%
0 20
 
9.3%
4 19
 
8.9%
6 17
 
7.9%
3 15
 
7.0%
9 15
 
7.0%
8 8
 
3.7%
7 6
 
2.8%
Space Separator
ValueCountFrequency (%)
252
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 795
57.3%
Common 592
42.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 68
 
8.6%
천 68
 
8.6%
경 63
 
7.9%
시 63
 
7.9%
도 57
 
7.2%
기 57
 
7.2%
동 52
 
6.5%
로 35
 
4.4%
양 25
 
3.1%
별 25
 
3.1%
Other values (81) 282
35.5%
Common
ValueCountFrequency (%)
252
42.6%
1 60
 
10.1%
( 45
 
7.6%
) 45
 
7.6%
2 31
 
5.2%
5 23
 
3.9%
0 20
 
3.4%
- 20
 
3.4%
4 19
 
3.2%
6 17
 
2.9%
Other values (5) 60
 
10.1%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 795
57.3%
ASCII 593
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
252
42.5%
1 60
 
10.1%
( 45
 
7.6%
) 45
 
7.6%
2 31
 
5.2%
5 23
 
3.9%
0 20
 
3.4%
- 20
 
3.4%
4 19
 
3.2%
6 17
 
2.9%
Other values (6) 61
 
10.3%
Hangul
ValueCountFrequency (%)
과 68
 
8.6%
천 68
 
8.6%
경 63
 
7.9%
시 63
 
7.9%
도 57
 
7.2%
기 57
 
7.2%
동 52
 
6.5%
로 35
 
4.4%
양 25
 
3.1%
별 25
 
3.1%
Other values (81) 282
35.5%

위도
Real number (ℝ)

MISSING 

Distinct55
Distinct (%)98.2%
Missing1
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean37.43512
Minimum37.402979
Maximum37.463346
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-13T00:52:00.179164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.402979
5-th percentile37.421711
Q137.425538
median37.432878
Q337.443663
95-th percentile37.457139
Maximum37.463346
Range0.060367
Interquartile range (IQR)0.0181245

Descriptive statistics

Standard deviation0.012649989
Coefficient of variation (CV)0.00033791768
Kurtosis-0.091833475
Mean37.43512
Median Absolute Deviation (MAD)0.0084935
Skewness0.40599587
Sum2096.3667
Variance0.00016002222
MonotonicityNot monotonic
2023-12-13T00:52:00.336013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4243 2
 
3.5%
37.43505 1
 
1.8%
37.426825 1
 
1.8%
37.450311 1
 
1.8%
37.428183 1
 
1.8%
37.454451 1
 
1.8%
37.45591 1
 
1.8%
37.423837 1
 
1.8%
37.443306 1
 
1.8%
37.415846 1
 
1.8%
Other values (45) 45
78.9%
ValueCountFrequency (%)
37.402979 1
1.8%
37.415846 1
1.8%
37.421271 1
1.8%
37.421858 1
1.8%
37.422789 1
1.8%
37.4236 1
1.8%
37.423837 1
1.8%
37.424228 1
1.8%
37.4243 2
3.5%
37.424479 1
1.8%
ValueCountFrequency (%)
37.463346 1
1.8%
37.461534 1
1.8%
37.460826 1
1.8%
37.45591 1
1.8%
37.454727 1
1.8%
37.454451 1
1.8%
37.454095 1
1.8%
37.453719 1
1.8%
37.450311 1
1.8%
37.449046 1
1.8%

경도
Real number (ℝ)

MISSING 

Distinct55
Distinct (%)98.2%
Missing1
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean126.99704
Minimum126.9655
Maximum127.03352
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-13T00:52:00.491119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.9655
5-th percentile126.98029
Q1126.99137
median126.99397
Q3127.0025
95-th percentile127.02863
Maximum127.03352
Range0.068023
Interquartile range (IQR)0.0111285

Descriptive statistics

Standard deviation0.01365908
Coefficient of variation (CV)0.00010755432
Kurtosis1.752281
Mean126.99704
Median Absolute Deviation (MAD)0.0055415
Skewness0.74933155
Sum7111.834
Variance0.00018657047
MonotonicityNot monotonic
2023-12-13T00:52:00.648342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.994245 2
 
3.5%
126.991584 1
 
1.8%
126.992555 1
 
1.8%
127.000028 1
 
1.8%
126.996083 1
 
1.8%
127.000826 1
 
1.8%
127.029071 1
 
1.8%
126.991422 1
 
1.8%
127.006224 1
 
1.8%
126.98195 1
 
1.8%
Other values (45) 45
78.9%
ValueCountFrequency (%)
126.965502 1
1.8%
126.96571 1
1.8%
126.975294 1
1.8%
126.98195 1
1.8%
126.982988 1
1.8%
126.984784 1
1.8%
126.986903 1
1.8%
126.987408 1
1.8%
126.987586 1
1.8%
126.987981 1
1.8%
ValueCountFrequency (%)
127.033525 1
1.8%
127.03348 1
1.8%
127.029071 1
1.8%
127.02848 1
1.8%
127.022582 1
1.8%
127.011424 1
1.8%
127.009575 1
1.8%
127.007302 1
1.8%
127.006915 1
1.8%
127.006277 1
1.8%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
2022-10-05
57 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-10-05
2nd row2022-10-05
3rd row2022-10-05
4th row2022-10-05
5th row2022-10-05

Common Values

ValueCountFrequency (%)
2022-10-05 57
100.0%

Length

2023-12-13T00:52:00.815469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:52:00.913673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-10-05 57
100.0%

Interactions

2023-12-13T00:51:57.466074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:51:57.226657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:51:57.606654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:51:57.328627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:52:00.984948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종교명시설명도로명주소위도경도
종교명1.0001.0001.0000.2190.280
시설명1.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.000
위도0.2191.0001.0001.0000.827
경도0.2801.0001.0000.8271.000
2023-12-13T00:52:01.101995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도종교명
위도1.0000.3980.111
경도0.3981.0000.150
종교명0.1110.1501.000

Missing values

2023-12-13T00:51:57.776783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:51:57.929743image/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.
2023-12-13T00:51:58.023173image/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

시군명종교명시설명도로명주소위도경도데이터기준일
0경기도 과천시개신교과천교회경기도 과천시 관악산길 103 (중앙동)37.43505126.9915842022-10-05
1경기도 과천시개신교대한예수교 과천복음교회경기도 과천시 관문로 166, 10단지상가 205호37.434788126.9956322022-10-05
2경기도 과천시개신교과천성결교회경기도 과천시 별양동 93 자이상가 301호37.43051126.998922022-10-05
3경기도 과천시개신교과천소망교회경기도 과천시 문원청계2길 50 (문원동)37.421858127.0095752022-10-05
4경기도 과천시개신교대한예수교장로회과천약수교회경기도 과천시 별양로 86 (별양동)37.426215126.9953732022-10-05
5경기도 과천시개신교한국기독교장로회 과천영광교회경기도 과천시 별양로 66-10, 401호(별양동)37.4243126.9942452022-10-05
6경기도 과천시개신교과천은파교회경기도 과천시 관문로 155 (중앙동)37.434925126.9939582022-10-05
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8경기도 과천시개신교과천중앙교회경기도 과천시 대공원나들길 32 (별양동)37.432958127.0019292022-10-05
9경기도 과천시개신교구세군과천교회경기도 과천시 관악산길 216 (중앙동)37.431912126.9869032022-10-05
시군명종교명시설명도로명주소위도경도데이터기준일
47경기도 과천시불교대한불교조계종 보광사경기도 과천시 교육원로 41 (갈현동)37.422789126.9847842022-10-05
48경기도 과천시불교서광사 (서광명상센터)경기도 과천시 용마로 46 (과천동, 서광사)37.444991126.9912572022-10-05
49경기도 과천시불교송암사경기도 과천시 용마1로 59-49 (과천동)37.449046126.9888782022-10-05
50경기도 과천시불교(재)선학원문천선원경기도 과천시 문원로 95 (문원동)37.425526127.0073022022-10-05
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52경기도 과천시불교대한불교조계종 허공장불교신행회 안면암경기도 과천시 재경길 172-1 (갈현동)37.402979126.9829882022-10-05
53경기도 과천시불교백운사경기도 과천시 교육원로 114-1 (중앙동)37.425542126.9752942022-10-05
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56경기도 과천시원불교(재)원불교 과천교당경기도 과천시 관문로 135 (중앙동)37.433559126.9928032022-10-05