Overview

Dataset statistics

Number of variables7
Number of observations278
Missing cells86
Missing cells (%)4.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.6 KiB
Average record size in memory57.5 B

Variable types

Numeric1
Categorical1
Text4
DateTime1

Dataset

Description충청남도 부여군 종교시설 데이터입니다. 종교구분, 시설명, 도로명주소, 지번주소, 전화번호를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15117639/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 종교구분High correlation
종교구분 is highly overall correlated with 연번High correlation
종교구분 is highly imbalanced (57.0%)Imbalance
전화번호 has 85 (30.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:31:03.343185
Analysis finished2023-12-12 21:31:04.105708
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct278
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.5
Minimum1
Maximum278
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T06:31:04.194348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.85
Q170.25
median139.5
Q3208.75
95-th percentile264.15
Maximum278
Range277
Interquartile range (IQR)138.5

Descriptive statistics

Standard deviation80.395895
Coefficient of variation (CV)0.57631466
Kurtosis-1.2
Mean139.5
Median Absolute Deviation (MAD)69.5
Skewness0
Sum38781
Variance6463.5
MonotonicityStrictly increasing
2023-12-13T06:31:04.634934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
185 1
 
0.4%
191 1
 
0.4%
190 1
 
0.4%
189 1
 
0.4%
188 1
 
0.4%
187 1
 
0.4%
186 1
 
0.4%
184 1
 
0.4%
176 1
 
0.4%
Other values (268) 268
96.4%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
278 1
0.4%
277 1
0.4%
276 1
0.4%
275 1
0.4%
274 1
0.4%
273 1
0.4%
272 1
0.4%
271 1
0.4%
270 1
0.4%
269 1
0.4%

종교구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
기독교
236 
불교
38 
천주교
 
4

Length

Max length3
Median length3
Mean length2.8633094
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기독교 236
84.9%
불교 38
 
13.7%
천주교 4
 
1.4%

Length

2023-12-13T06:31:04.782675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:31:04.893448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기독교 236
84.9%
불교 38
 
13.7%
천주교 4
 
1.4%

시설명
Text

Distinct275
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-13T06:31:05.141596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length8.7661871
Min length3

Characters and Unicode

Total characters2437
Distinct characters213
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique272 ?
Unique (%)97.8%

Sample

1st row조왕사
2nd row고란사
3rd row보리사
4th row대한불교조계종 가탑사
5th row법륜사
ValueCountFrequency (%)
기독교대한성결교회 17
 
4.5%
대한예수교장로회 13
 
3.4%
한국기독교장로회 11
 
2.9%
기독교대한감리회 7
 
1.9%
기독교한국침례회 6
 
1.6%
부여교회 5
 
1.3%
예수교대한성결교회 4
 
1.1%
대한불교조계종 4
 
1.1%
사단법인 2
 
0.5%
기도원 2
 
0.5%
Other values (296) 307
81.2%
2023-12-13T06:31:05.617265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 368
 
15.1%
회 332
 
13.6%
한 108
 
4.4%
100
 
4.1%
기 77
 
3.2%
대 76
 
3.1%
독 66
 
2.7%
성 65
 
2.7%
장 54
 
2.2%
로 52
 
2.1%
Other values (203) 1139
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2324
95.4%
Space Separator 100
 
4.1%
Open Punctuation 6
 
0.2%
Close Punctuation 6
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 368
 
15.8%
회 332
 
14.3%
한 108
 
4.6%
기 77
 
3.3%
대 76
 
3.3%
독 66
 
2.8%
성 65
 
2.8%
장 54
 
2.3%
로 52
 
2.2%
부 39
 
1.7%
Other values (199) 1087
46.8%
Space Separator
ValueCountFrequency (%)
100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2324
95.4%
Common 113
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 368
 
15.8%
회 332
 
14.3%
한 108
 
4.6%
기 77
 
3.3%
대 76
 
3.3%
독 66
 
2.8%
성 65
 
2.8%
장 54
 
2.3%
로 52
 
2.2%
부 39
 
1.7%
Other values (199) 1087
46.8%
Common
ValueCountFrequency (%)
100
88.5%
( 6
 
5.3%
) 6
 
5.3%
. 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2324
95.4%
ASCII 113
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 368
 
15.8%
회 332
 
14.3%
한 108
 
4.6%
기 77
 
3.3%
대 76
 
3.3%
독 66
 
2.8%
성 65
 
2.8%
장 54
 
2.3%
로 52
 
2.2%
부 39
 
1.7%
Other values (199) 1087
46.8%
ASCII
ValueCountFrequency (%)
100
88.5%
( 6
 
5.3%
) 6
 
5.3%
. 1
 
0.9%

도로명주소
Text

Distinct273
Distinct (%)98.6%
Missing1
Missing (%)0.4%
Memory size2.3 KiB
2023-12-13T06:31:05.908730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length22.357401
Min length18

Characters and Unicode

Total characters6193
Distinct characters147
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

Unique269 ?
Unique (%)97.1%

Sample

1st row충청남도 부여군 부여읍 계백로 334-47
2nd row충청남도 부여군 부여읍 부소로 1-25
3rd row충청남도 부여군 부여읍 삼충로743번길 33
4th row충청남도 부여군 부여읍 왕릉로 25
5th row충청남도 부여군 규암면 규암로7번길 14-5
ValueCountFrequency (%)
부여군 277
20.0%
충청남도 274
19.8%
부여읍 54
 
3.9%
규암면 29
 
2.1%
은산면 21
 
1.5%
임천면 19
 
1.4%
세도면 17
 
1.2%
외산면 16
 
1.2%
장암면 16
 
1.2%
석성면 15
 
1.1%
Other values (429) 646
46.7%
2023-12-13T06:31:06.312640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1107
17.9%
부 344
 
5.6%
여 331
 
5.3%
충 316
 
5.1%
남 299
 
4.8%
도 293
 
4.7%
군 277
 
4.5%
청 274
 
4.4%
로 271
 
4.4%
면 223
 
3.6%
Other values (137) 2458
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3877
62.6%
Space Separator 1107
 
17.9%
Decimal Number 1098
 
17.7%
Dash Punctuation 111
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 344
 
8.9%
여 331
 
8.5%
충 316
 
8.2%
남 299
 
7.7%
도 293
 
7.6%
군 277
 
7.1%
청 274
 
7.1%
로 271
 
7.0%
면 223
 
5.8%
길 130
 
3.4%
Other values (125) 1119
28.9%
Decimal Number
ValueCountFrequency (%)
1 219
19.9%
2 148
13.5%
3 136
12.4%
4 99
9.0%
6 96
8.7%
7 91
8.3%
5 91
8.3%
9 76
 
6.9%
8 73
 
6.6%
0 69
 
6.3%
Space Separator
ValueCountFrequency (%)
1107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3877
62.6%
Common 2316
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 344
 
8.9%
여 331
 
8.5%
충 316
 
8.2%
남 299
 
7.7%
도 293
 
7.6%
군 277
 
7.1%
청 274
 
7.1%
로 271
 
7.0%
면 223
 
5.8%
길 130
 
3.4%
Other values (125) 1119
28.9%
Common
ValueCountFrequency (%)
1107
47.8%
1 219
 
9.5%
2 148
 
6.4%
3 136
 
5.9%
- 111
 
4.8%
4 99
 
4.3%
6 96
 
4.1%
7 91
 
3.9%
5 91
 
3.9%
9 76
 
3.3%
Other values (2) 142
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3877
62.6%
ASCII 2316
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1107
47.8%
1 219
 
9.5%
2 148
 
6.4%
3 136
 
5.9%
- 111
 
4.8%
4 99
 
4.3%
6 96
 
4.1%
7 91
 
3.9%
5 91
 
3.9%
9 76
 
3.3%
Other values (2) 142
 
6.1%
Hangul
ValueCountFrequency (%)
부 344
 
8.9%
여 331
 
8.5%
충 316
 
8.2%
남 299
 
7.7%
도 293
 
7.6%
군 277
 
7.1%
청 274
 
7.1%
로 271
 
7.0%
면 223
 
5.8%
길 130
 
3.4%
Other values (125) 1119
28.9%

지번주소
Text

Distinct274
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-13T06:31:06.687878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length21.428058
Min length15

Characters and Unicode

Total characters5957
Distinct characters142
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

Unique270 ?
Unique (%)97.1%

Sample

1st row충청남도 부여군 부여읍 동남리 20-4
2nd row충청남도 부여군 부여읍 쌍북리 산 1
3rd row충청남도 부여군 부여읍 저석리 산 14
4th row충청남도 부여군 부여읍 가탑리 168-12
5th row충청남도 부여군 규암면 규암리 86-25
ValueCountFrequency (%)
부여군 278
19.6%
충청남도 276
19.5%
부여읍 54
 
3.8%
규암면 28
 
2.0%
산 26
 
1.8%
은산면 21
 
1.5%
임천면 20
 
1.4%
세도면 18
 
1.3%
외산면 17
 
1.2%
석성면 15
 
1.1%
Other values (420) 662
46.8%
2023-12-13T06:31:07.255348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1137
19.1%
부 333
 
5.6%
여 333
 
5.6%
남 308
 
5.2%
도 294
 
4.9%
충 289
 
4.9%
군 281
 
4.7%
청 279
 
4.7%
리 276
 
4.6%
면 223
 
3.7%
Other values (132) 2204
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3618
60.7%
Space Separator 1137
 
19.1%
Decimal Number 999
 
16.8%
Dash Punctuation 203
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 333
 
9.2%
여 333
 
9.2%
남 308
 
8.5%
도 294
 
8.1%
충 289
 
8.0%
군 281
 
7.8%
청 279
 
7.7%
리 276
 
7.6%
면 223
 
6.2%
산 135
 
3.7%
Other values (120) 867
24.0%
Decimal Number
ValueCountFrequency (%)
1 187
18.7%
2 148
14.8%
3 122
12.2%
4 106
10.6%
6 91
9.1%
5 82
8.2%
0 75
7.5%
7 70
 
7.0%
9 62
 
6.2%
8 56
 
5.6%
Space Separator
ValueCountFrequency (%)
1137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 203
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3618
60.7%
Common 2339
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 333
 
9.2%
여 333
 
9.2%
남 308
 
8.5%
도 294
 
8.1%
충 289
 
8.0%
군 281
 
7.8%
청 279
 
7.7%
리 276
 
7.6%
면 223
 
6.2%
산 135
 
3.7%
Other values (120) 867
24.0%
Common
ValueCountFrequency (%)
1137
48.6%
- 203
 
8.7%
1 187
 
8.0%
2 148
 
6.3%
3 122
 
5.2%
4 106
 
4.5%
6 91
 
3.9%
5 82
 
3.5%
0 75
 
3.2%
7 70
 
3.0%
Other values (2) 118
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3618
60.7%
ASCII 2339
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1137
48.6%
- 203
 
8.7%
1 187
 
8.0%
2 148
 
6.3%
3 122
 
5.2%
4 106
 
4.5%
6 91
 
3.9%
5 82
 
3.5%
0 75
 
3.2%
7 70
 
3.0%
Other values (2) 118
 
5.0%
Hangul
ValueCountFrequency (%)
부 333
 
9.2%
여 333
 
9.2%
남 308
 
8.5%
도 294
 
8.1%
충 289
 
8.0%
군 281
 
7.8%
청 279
 
7.7%
리 276
 
7.6%
면 223
 
6.2%
산 135
 
3.7%
Other values (120) 867
24.0%

전화번호
Text

MISSING 

Distinct191
Distinct (%)99.0%
Missing85
Missing (%)30.6%
Memory size2.3 KiB
2023-12-13T06:31:07.574964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.062176
Min length11

Characters and Unicode

Total characters2328
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique189 ?
Unique (%)97.9%

Sample

1st row041-835-4091
2nd row041-835-2062
3rd row041-832-7754
4th row041-837-4488
5th row041-835-6684
ValueCountFrequency (%)
041-833-3228 2
 
1.0%
041-835-1976 2
 
1.0%
041-833-0840 1
 
0.5%
041-832-1060 1
 
0.5%
0507-1364-7716 1
 
0.5%
041-834-0834 1
 
0.5%
041-835-4091 1
 
0.5%
041-835-0932 1
 
0.5%
041-836-5540 1
 
0.5%
041-836-6637 1
 
0.5%
Other values (181) 181
93.8%
2023-12-13T06:31:07.992571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 386
16.6%
3 322
13.8%
0 299
12.8%
1 286
12.3%
4 285
12.2%
8 240
10.3%
2 125
 
5.4%
6 111
 
4.8%
5 106
 
4.6%
7 95
 
4.1%
Other values (2) 73
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1941
83.4%
Dash Punctuation 386
 
16.6%
Control 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 322
16.6%
0 299
15.4%
1 286
14.7%
4 285
14.7%
8 240
12.4%
2 125
 
6.4%
6 111
 
5.7%
5 106
 
5.5%
7 95
 
4.9%
9 72
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 386
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2328
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 386
16.6%
3 322
13.8%
0 299
12.8%
1 286
12.3%
4 285
12.2%
8 240
10.3%
2 125
 
5.4%
6 111
 
4.8%
5 106
 
4.6%
7 95
 
4.1%
Other values (2) 73
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2328
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 386
16.6%
3 322
13.8%
0 299
12.8%
1 286
12.3%
4 285
12.2%
8 240
10.3%
2 125
 
5.4%
6 111
 
4.8%
5 106
 
4.6%
7 95
 
4.1%
Other values (2) 73
 
3.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2023-07-31 00:00:00
Maximum2023-07-31 00:00:00
2023-12-13T06:31:08.137429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:31:08.244892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T06:31:03.702390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:31:08.331702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종교구분
연번1.0000.785
종교구분0.7851.000
2023-12-13T06:31:08.435006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종교구분
연번1.0000.661
종교구분0.6611.000

Missing values

2023-12-13T06:31:03.820014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:31:03.960066image/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.
2023-12-13T06:31:04.051562image/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

연번종교구분시설명도로명주소지번주소전화번호데이터기준일자
01불교조왕사충청남도 부여군 부여읍 계백로 334-47충청남도 부여군 부여읍 동남리 20-4041-835-40912023-07-31
12불교고란사충청남도 부여군 부여읍 부소로 1-25충청남도 부여군 부여읍 쌍북리 산 1041-835-20622023-07-31
23불교보리사충청남도 부여군 부여읍 삼충로743번길 33충청남도 부여군 부여읍 저석리 산 14041-832-77542023-07-31
34불교대한불교조계종 가탑사충청남도 부여군 부여읍 왕릉로 25충청남도 부여군 부여읍 가탑리 168-12041-837-44882023-07-31
45불교법륜사충청남도 부여군 규암면 규암로7번길 14-5충청남도 부여군 규암면 규암리 86-25041-835-66842023-07-31
56불교구암사충청남도 부여군 규암면 충절로2368번길 47충청남도 부여군 규암면 반산리 24-1041-836-40962023-07-31
67불교호암사충청남도 부여군 규암면 백제문로호암길 106-24충청남도 부여군 호암리 산5<NA>2023-07-31
78불교청룡사충청남도 부여군 규암면 진변로 172-64충청남도 부여군 규암면 신리 503-3041-835-56292023-07-31
89불교성문사충청남도 부여군 규암면 서궁로 510충청남도 부여군 규암면 신성리 517<NA>2023-07-31
910불교사단법인 성주산문만선동귀회충청남도 부여군 은산면 매화로 96충청남도 부여군 은산면 가곡리 209-2041-833-85682023-07-31
연번종교구분시설명도로명주소지번주소전화번호데이터기준일자
268269기독교부양교회충청남도 부여군 부여읍 동문로 219충청남도 부여군 부여읍 염창리 340-2<NA>2023-07-31
269270기독교천국교회기도원충청남도 부여군 부여읍 능안로 77충청남도 부여군 부여읍 능산리 108<NA>2023-07-31
270271기독교찬양천국교회충청남도 부여군 부여읍 능안로 88충청남도 부여군 부여읍 능산리 100-10<NA>2023-07-31
271272기독교성신교회충청남도 부여군 석성면 대백제로 3206충청남도 부여군 석성면 증산리 1142-15<NA>2023-07-31
272273기독교반조원교회충청남도 부여군 세도면 세도로431번길 21충청남도 부여군 세도면 반조원리 350-5041-833-08402023-07-31
273274기독교세도복음교회충청남도 부여군 세도면 인세로75번길 9충청남도 부여군 세도면 귀덕리 201-5<NA>2023-07-31
274275천주교부여천주교회(부여성당)충청남도 부여군 부여읍 사비로 51충청남도 부여군 부여읍 동남리 720041-832-07122023-07-31
275276천주교규암천주교회(규암성당)충청남도 부여군 규암면 충절로2291번길 11충청남도 부여군 규암면 외리 226-2041-835-72612023-07-31
276277천주교구룡천주교회(금사리성당)충청남도 부여군 구룡면 성충로1342번길 21충청남도 부여군 구룡면 금사리 334041-832-53552023-07-31
277278천주교홍산천주교회(홍산성당)충청남도 부여군 홍산면 홍산로 53-14충청남도 부여군 홍산면 남촌리 161-3041-836-00672023-07-31