Overview

Dataset statistics

Number of variables6
Number of observations345
Missing cells168
Missing cells (%)8.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.3 KiB
Average record size in memory48.4 B

Variable types

Categorical2
Text4

Dataset

Description이 데이터는 충청남도 금산군 경로당에 대한 데이터(행정구역, 행정리, 경로당명, 연락처, 도로명주소, 데이터기준일자)를 제공하고 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=104&beforeMenuCd=DOM_000000201001001000&publicdatapk=15099753

Alerts

데이터기준일자 has constant value ""Constant
연락처 has 167 (48.4%) missing valuesMissing

Reproduction

Analysis started2024-01-09 21:53:27.161155
Analysis finished2024-01-09 21:53:27.668519
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정구역
Categorical

Distinct10
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
금산읍
66 
금성면
39 
진산면
35 
제원면
34 
부리면
33 
Other values (5)
138 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
금산읍 66
19.1%
금성면 39
11.3%
진산면 35
10.1%
제원면 34
9.9%
부리면 33
9.6%
남이면 30
8.7%
복수면 29
8.4%
추부면 28
8.1%
군북면 26
 
7.5%
남일면 25
 
7.2%

Length

2024-01-10T06:53:27.732854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:53:27.855578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
금산읍 66
19.1%
금성면 39
11.3%
진산면 35
10.1%
제원면 34
9.9%
부리면 33
9.6%
남이면 30
8.7%
복수면 29
8.4%
추부면 28
8.1%
군북면 26
 
7.5%
남일면 25
 
7.2%

행정리
Text

Distinct252
Distinct (%)73.3%
Missing1
Missing (%)0.3%
Memory size2.8 KiB
2024-01-10T06:53:28.148766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length4
Mean length3.8837209
Min length2

Characters and Unicode

Total characters1336
Distinct characters122
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)49.7%

Sample

1st row신대1리
2nd row신대1리
3rd row신대2리
4th row신대2리
5th row중도1리
ValueCountFrequency (%)
신대1리 4
 
1.1%
하옥4리 4
 
1.1%
신대2리 4
 
1.1%
음대리 3
 
0.9%
아인1리 3
 
0.9%
음지2리 3
 
0.9%
양전3리 3
 
0.9%
상1리 3
 
0.9%
신촌2 2
 
0.6%
신천2리 2
 
0.6%
Other values (244) 317
91.1%
2024-01-10T06:53:28.519325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 310
23.2%
1 127
 
9.5%
2 116
 
8.7%
3 36
 
2.7%
곡 35
 
2.6%
상 31
 
2.3%
신 28
 
2.1%
대 25
 
1.9%
도 21
 
1.6%
지 18
 
1.3%
Other values (112) 589
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 998
74.7%
Decimal Number 322
 
24.1%
Open Punctuation 4
 
0.3%
Close Punctuation 4
 
0.3%
Other Punctuation 4
 
0.3%
Space Separator 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 310
31.1%
곡 35
 
3.5%
상 31
 
3.1%
신 28
 
2.8%
대 25
 
2.5%
도 21
 
2.1%
지 18
 
1.8%
중 17
 
1.7%
천 17
 
1.7%
하 17
 
1.7%
Other values (98) 479
48.0%
Decimal Number
ValueCountFrequency (%)
1 127
39.4%
2 116
36.0%
3 36
 
11.2%
4 14
 
4.3%
5 8
 
2.5%
7 5
 
1.6%
6 5
 
1.6%
8 4
 
1.2%
9 4
 
1.2%
0 3
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 998
74.7%
Common 338
 
25.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 310
31.1%
곡 35
 
3.5%
상 31
 
3.1%
신 28
 
2.8%
대 25
 
2.5%
도 21
 
2.1%
지 18
 
1.8%
중 17
 
1.7%
천 17
 
1.7%
하 17
 
1.7%
Other values (98) 479
48.0%
Common
ValueCountFrequency (%)
1 127
37.6%
2 116
34.3%
3 36
 
10.7%
4 14
 
4.1%
5 8
 
2.4%
7 5
 
1.5%
6 5
 
1.5%
8 4
 
1.2%
( 4
 
1.2%
) 4
 
1.2%
Other values (4) 15
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 998
74.7%
ASCII 338
 
25.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 310
31.1%
곡 35
 
3.5%
상 31
 
3.1%
신 28
 
2.8%
대 25
 
2.5%
도 21
 
2.1%
지 18
 
1.8%
중 17
 
1.7%
천 17
 
1.7%
하 17
 
1.7%
Other values (98) 479
48.0%
ASCII
ValueCountFrequency (%)
1 127
37.6%
2 116
34.3%
3 36
 
10.7%
4 14
 
4.1%
5 8
 
2.4%
7 5
 
1.5%
6 5
 
1.5%
8 4
 
1.2%
( 4
 
1.2%
) 4
 
1.2%
Other values (4) 15
 
4.4%

경로당명
Text

Distinct343
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-01-10T06:53:28.710962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length7.5913043
Min length5

Characters and Unicode

Total characters2619
Distinct characters193
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique341 ?
Unique (%)98.8%

Sample

1st row신대1리경로당
2nd row신대1리(엄정리)경로당
3rd row신대2리경로당
4th row신대2리(하영처)경로당
5th row중도1리경로당
ValueCountFrequency (%)
경로당 195
35.2%
여자경로당 4
 
0.7%
남자경로당 4
 
0.7%
신촌 2
 
0.4%
성곡1리 2
 
0.4%
남자 2
 
0.4%
제원2리 2
 
0.4%
제원1리 2
 
0.4%
명암리 2
 
0.4%
대산1리 2
 
0.4%
Other values (336) 337
60.8%
2024-01-10T06:53:28.992058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 353
13.5%
경 348
13.3%
로 345
 
13.2%
리 229
 
8.7%
212
 
8.1%
1 84
 
3.2%
2 78
 
3.0%
성 38
 
1.5%
여 37
 
1.4%
상 29
 
1.1%
Other values (183) 866
33.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2159
82.4%
Space Separator 212
 
8.1%
Decimal Number 209
 
8.0%
Open Punctuation 19
 
0.7%
Close Punctuation 19
 
0.7%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 353
16.4%
경 348
16.1%
로 345
16.0%
리 229
 
10.6%
성 38
 
1.8%
여 37
 
1.7%
상 29
 
1.3%
신 25
 
1.2%
곡 24
 
1.1%
대 24
 
1.1%
Other values (170) 707
32.7%
Decimal Number
ValueCountFrequency (%)
1 84
40.2%
2 78
37.3%
3 23
 
11.0%
4 5
 
2.4%
5 4
 
1.9%
6 4
 
1.9%
7 4
 
1.9%
9 4
 
1.9%
8 3
 
1.4%
Space Separator
ValueCountFrequency (%)
212
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2159
82.4%
Common 460
 
17.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 353
16.4%
경 348
16.1%
로 345
16.0%
리 229
 
10.6%
성 38
 
1.8%
여 37
 
1.7%
상 29
 
1.3%
신 25
 
1.2%
곡 24
 
1.1%
대 24
 
1.1%
Other values (170) 707
32.7%
Common
ValueCountFrequency (%)
212
46.1%
1 84
 
18.3%
2 78
 
17.0%
3 23
 
5.0%
( 19
 
4.1%
) 19
 
4.1%
4 5
 
1.1%
5 4
 
0.9%
6 4
 
0.9%
7 4
 
0.9%
Other values (3) 8
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2159
82.4%
ASCII 460
 
17.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 353
16.4%
경 348
16.1%
로 345
16.0%
리 229
 
10.6%
성 38
 
1.8%
여 37
 
1.7%
상 29
 
1.3%
신 25
 
1.2%
곡 24
 
1.1%
대 24
 
1.1%
Other values (170) 707
32.7%
ASCII
ValueCountFrequency (%)
212
46.1%
1 84
 
18.3%
2 78
 
17.0%
3 23
 
5.0%
( 19
 
4.1%
) 19
 
4.1%
4 5
 
1.1%
5 4
 
0.9%
6 4
 
0.9%
7 4
 
0.9%
Other values (3) 8
 
1.7%

연락처
Text

MISSING 

Distinct173
Distinct (%)97.2%
Missing167
Missing (%)48.4%
Memory size2.8 KiB
2024-01-10T06:53:29.205575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.882022
Min length1

Characters and Unicode

Total characters2115
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

Unique168 ?
Unique (%)94.4%

Sample

1st row041-751-6010
2nd row041-753-8850
3rd row041-754-1030
4th row041-751-3677
5th row041-754-2515
ValueCountFrequency (%)
041-751-4882 2
 
1.1%
041-754-7599 2
 
1.1%
041-752-2647 2
 
1.1%
041-753-6115 2
 
1.1%
041-752-8893 1
 
0.6%
041-754-7535 1
 
0.6%
041-752-0218 1
 
0.6%
041-752-2587 1
 
0.6%
041-754-9339 1
 
0.6%
041-752-1129 1
 
0.6%
Other values (162) 162
92.0%
2024-01-10T06:53:29.530212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 352
16.6%
1 283
13.4%
4 271
12.8%
0 257
12.2%
5 249
11.8%
7 244
11.5%
3 124
 
5.9%
2 115
 
5.4%
9 83
 
3.9%
6 70
 
3.3%
Other values (2) 67
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1760
83.2%
Dash Punctuation 352
 
16.6%
Space Separator 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 283
16.1%
4 271
15.4%
0 257
14.6%
5 249
14.1%
7 244
13.9%
3 124
7.0%
2 115
6.5%
9 83
 
4.7%
6 70
 
4.0%
8 64
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 352
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2115
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 352
16.6%
1 283
13.4%
4 271
12.8%
0 257
12.2%
5 249
11.8%
7 244
11.5%
3 124
 
5.9%
2 115
 
5.4%
9 83
 
3.9%
6 70
 
3.3%
Other values (2) 67
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2115
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 352
16.6%
1 283
13.4%
4 271
12.8%
0 257
12.2%
5 249
11.8%
7 244
11.5%
3 124
 
5.9%
2 115
 
5.4%
9 83
 
3.9%
6 70
 
3.3%
Other values (2) 67
 
3.2%

도로명주소
Text

Distinct321
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-01-10T06:53:29.836792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length35
Mean length20.266667
Min length17

Characters and Unicode

Total characters6992
Distinct characters239
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

Unique297 ?
Unique (%)86.1%

Sample

1st row충청남도 금산군 금산읍 증티길 6
2nd row충청남도 금산군 금산읍 엄나무길 15
3rd row충청남도 금산군 금산읍 상영처길 19-2
4th row충청남도 금산군 금산읍 하영처길 58
5th row충청남도 금산군 금산읍 건삼전1길 26
ValueCountFrequency (%)
충청남도 345
20.3%
금산군 345
20.3%
금산읍 66
 
3.9%
금성면 39
 
2.3%
진산면 35
 
2.1%
제원면 34
 
2.0%
부리면 33
 
1.9%
남이면 30
 
1.8%
복수면 29
 
1.7%
추부면 28
 
1.6%
Other values (454) 716
42.1%
2024-01-10T06:53:30.258452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1361
19.5%
산 469
 
6.7%
금 462
 
6.6%
남 401
 
5.7%
군 379
 
5.4%
청 349
 
5.0%
도 347
 
5.0%
충 345
 
4.9%
길 281
 
4.0%
면 279
 
4.0%
Other values (229) 2319
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4682
67.0%
Space Separator 1361
 
19.5%
Decimal Number 876
 
12.5%
Dash Punctuation 64
 
0.9%
Other Punctuation 6
 
0.1%
Close Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 469
 
10.0%
금 462
 
9.9%
남 401
 
8.6%
군 379
 
8.1%
청 349
 
7.5%
도 347
 
7.4%
충 345
 
7.4%
길 281
 
6.0%
면 279
 
6.0%
읍 66
 
1.4%
Other values (213) 1304
27.9%
Decimal Number
ValueCountFrequency (%)
1 207
23.6%
2 129
14.7%
3 105
12.0%
4 84
9.6%
5 81
 
9.2%
6 71
 
8.1%
7 53
 
6.1%
8 50
 
5.7%
0 50
 
5.7%
9 46
 
5.3%
Space Separator
ValueCountFrequency (%)
1361
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4682
67.0%
Common 2309
33.0%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 469
 
10.0%
금 462
 
9.9%
남 401
 
8.6%
군 379
 
8.1%
청 349
 
7.5%
도 347
 
7.4%
충 345
 
7.4%
길 281
 
6.0%
면 279
 
6.0%
읍 66
 
1.4%
Other values (213) 1304
27.9%
Common
ValueCountFrequency (%)
1361
58.9%
1 207
 
9.0%
2 129
 
5.6%
3 105
 
4.5%
4 84
 
3.6%
5 81
 
3.5%
6 71
 
3.1%
- 64
 
2.8%
7 53
 
2.3%
8 50
 
2.2%
Other values (5) 104
 
4.5%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4682
67.0%
ASCII 2310
33.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1361
58.9%
1 207
 
9.0%
2 129
 
5.6%
3 105
 
4.5%
4 84
 
3.6%
5 81
 
3.5%
6 71
 
3.1%
- 64
 
2.8%
7 53
 
2.3%
8 50
 
2.2%
Other values (6) 105
 
4.5%
Hangul
ValueCountFrequency (%)
산 469
 
10.0%
금 462
 
9.9%
남 401
 
8.6%
군 379
 
8.1%
청 349
 
7.5%
도 347
 
7.4%
충 345
 
7.4%
길 281
 
6.0%
면 279
 
6.0%
읍 66
 
1.4%
Other values (213) 1304
27.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-03-31
345 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-31
2nd row2023-03-31
3rd row2023-03-31
4th row2023-03-31
5th row2023-03-31

Common Values

ValueCountFrequency (%)
2023-03-31 345
100.0%

Length

2024-01-10T06:53:30.370721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:53:30.445875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-31 345
100.0%

Missing values

2024-01-10T06:53:27.453554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:53:27.533512image/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.
2024-01-10T06:53:27.624365image/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

행정구역행정리경로당명연락처도로명주소데이터기준일자
0금산읍신대1리신대1리경로당<NA>충청남도 금산군 금산읍 증티길 62023-03-31
1금산읍신대1리신대1리(엄정리)경로당041-751-6010충청남도 금산군 금산읍 엄나무길 152023-03-31
2금산읍신대2리신대2리경로당041-753-8850충청남도 금산군 금산읍 상영처길 19-22023-03-31
3금산읍신대2리신대2리(하영처)경로당041-754-1030충청남도 금산군 금산읍 하영처길 582023-03-31
4금산읍중도1리중도1리경로당041-751-3677충청남도 금산군 금산읍 건삼전1길 262023-03-31
5금산읍중도1리금홍회경로당<NA>충청남도 금산군 금산읍 금산천1길 1092023-03-31
6금산읍중도2리건국경로당041-754-2515충청남도 금산군 금산읍 건삼전3길 13-62023-03-31
7금산읍중도2리건국여성경로당041-751-0393충청남도 금산군 금산읍 건삼전3길 13-62023-03-31
8금산읍중도3리중도3리경로당041-754-8890충청남도 금산군 금산읍 금산천길 1402023-03-31
9금산읍중도3리중도3리여자경로당041-754-4450충청남도 금산군 금산읍 금산천길 1402023-03-31
행정구역행정리경로당명연락처도로명주소데이터기준일자
335추부면요광2리요광2리 경로당<NA>충청남도 금산군 추부면 박오재길 202023-03-31
336추부면요광3리요광3리 경로당<NA>충청남도 금산군 추부면 장산길 342023-03-31
337추부면신평1리신평1리 경로당<NA>충청남도 금산군 추부면 신평길 12-142023-03-31
338추부면신평1리신평1리여성 경로당<NA>충청남도 금산군 추부면 군북로 1450-142023-03-31
339추부면신평2리신평2리 경로당<NA>충청남도 금산군 추부면 신평1길 592023-03-31
340추부면성당1리성당1리 경로당041-753-7873충청남도 금산군 추부면 성당로 712023-03-31
341추부면성당2리성당2리 경로당041-752-1744충청남도 금산군 추부면 성덕길 102023-03-31
342추부면서대1리서대1리 경로당041-752-6368충청남도 금산군 추부면 서대수통1길 65-32023-03-31
343추부면서대2리서대2리 경로당<NA>충청남도 금산군 추부면 군북로 1199-72023-03-31
344추부면서대2리대동 경로당<NA>충청남도 금산군 추부면 동석길 52023-03-31