Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells9013
Missing cells (%)18.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory468.8 KiB
Average record size in memory48.0 B

Variable types

Text3
Categorical1
DateTime1

Dataset

Description보령시에 설치된 가로등 현황 데이터로 가로등 표찰 번호, 가로등이 설치된 행정동, 가로등이 설치된 지번주소, 가로등 설치 상세위치가 제공됩니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=331&beforeMenuCd=DOM_000000201001001000&publicdatapk=15088946

Alerts

데이터기준일 has constant value ""Constant
상세위치 has 9013 (90.1%) missing valuesMissing

Reproduction

Analysis started2024-01-09 22:57:43.590638
Analysis finished2024-01-09 22:57:44.528752
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

표찰번호
Text

Distinct9998
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T07:57:44.729070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.0875
Min length5

Characters and Unicode

Total characters60875
Distinct characters40
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

Unique9996 ?
Unique (%)> 99.9%

Sample

1st row114-12
2nd row주산면177
3rd row주교면784
4th row주포면087
5th row청라면443
ValueCountFrequency (%)
11월 19
 
0.2%
10월 8
 
0.1%
12월 8
 
0.1%
15일 4
 
< 0.1%
14일 3
 
< 0.1%
16일 3
 
< 0.1%
30일 3
 
< 0.1%
21일 3
 
< 0.1%
20일 2
 
< 0.1%
17일 2
 
< 0.1%
Other values (9979) 9981
99.5%
2024-01-10T07:57:45.134261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6008
 
9.9%
3 4892
 
8.0%
2 4860
 
8.0%
면 4383
 
7.2%
천 3902
 
6.4%
5 3693
 
6.1%
4 3446
 
5.7%
0 3313
 
5.4%
6 2947
 
4.8%
- 2918
 
4.8%
Other values (30) 20513
33.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36413
59.8%
Other Letter 21480
35.3%
Dash Punctuation 2918
 
4.8%
Space Separator 37
 
0.1%
Open Punctuation 10
 
< 0.1%
Close Punctuation 10
 
< 0.1%
Uppercase Letter 5
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 4383
20.4%
천 3902
18.2%
동 1926
9.0%
대 1926
9.0%
주 1432
 
6.7%
청 910
 
4.2%
웅 871
 
4.1%
포 815
 
3.8%
읍 738
 
3.4%
산 738
 
3.4%
Other values (13) 3839
17.9%
Decimal Number
ValueCountFrequency (%)
1 6008
16.5%
3 4892
13.4%
2 4860
13.3%
5 3693
10.1%
4 3446
9.5%
0 3313
9.1%
6 2947
8.1%
7 2525
6.9%
9 2378
 
6.5%
8 2351
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
A 3
60.0%
B 2
40.0%
Dash Punctuation
ValueCountFrequency (%)
- 2918
100.0%
Space Separator
ValueCountFrequency (%)
37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39390
64.7%
Hangul 21480
35.3%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 4383
20.4%
천 3902
18.2%
동 1926
9.0%
대 1926
9.0%
주 1432
 
6.7%
청 910
 
4.2%
웅 871
 
4.1%
포 815
 
3.8%
읍 738
 
3.4%
산 738
 
3.4%
Other values (13) 3839
17.9%
Common
ValueCountFrequency (%)
1 6008
15.3%
3 4892
12.4%
2 4860
12.3%
5 3693
9.4%
4 3446
8.7%
0 3313
8.4%
6 2947
7.5%
- 2918
7.4%
7 2525
6.4%
9 2378
 
6.0%
Other values (5) 2410
6.1%
Latin
ValueCountFrequency (%)
A 3
60.0%
B 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39395
64.7%
Hangul 21480
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6008
15.3%
3 4892
12.4%
2 4860
12.3%
5 3693
9.4%
4 3446
8.7%
0 3313
8.4%
6 2947
7.5%
- 2918
7.4%
7 2525
6.4%
9 2378
 
6.0%
Other values (7) 2415
6.1%
Hangul
ValueCountFrequency (%)
면 4383
20.4%
천 3902
18.2%
동 1926
9.0%
대 1926
9.0%
주 1432
 
6.7%
청 910
 
4.2%
웅 871
 
4.1%
포 815
 
3.8%
읍 738
 
3.4%
산 738
 
3.4%
Other values (13) 3839
17.9%

행정동
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대천5동
1366 
웅천읍
1106 
대천4동
850 
오천면
803 
남포면
782 
Other values (11)
5093 

Length

Max length4
Median length3
Mean length3.3716
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대천4동
2nd row주산면
3rd row주교면
4th row주포면
5th row청라면

Common Values

ValueCountFrequency (%)
대천5동 1366
13.7%
웅천읍 1106
11.1%
대천4동 850
8.5%
오천면 803
 
8.0%
남포면 782
 
7.8%
주교면 710
 
7.1%
청라면 671
 
6.7%
대천3동 631
 
6.3%
대천1동 507
 
5.1%
천북면 467
 
4.7%
Other values (6) 2107
21.1%

Length

2024-01-10T07:57:45.267138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대천5동 1366
13.7%
웅천읍 1106
11.1%
대천4동 850
8.5%
오천면 803
 
8.0%
남포면 782
 
7.8%
주교면 710
 
7.1%
청라면 671
 
6.7%
대천3동 631
 
6.3%
대천1동 507
 
5.1%
천북면 467
 
4.7%
Other values (6) 2107
21.1%

지번주소
Text

Distinct7313
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T07:57:45.625533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length11.1786
Min length4

Characters and Unicode

Total characters111786
Distinct characters121
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

Unique6298 ?
Unique (%)63.0%

Sample

1st row명천동 384
2nd row주산면 황율리 388-2
3rd row주교면 은포리 1679
4th row주포면 보령리 522-1
5th row청라면 의평리 124-6
ValueCountFrequency (%)
웅천읍 1106
 
4.2%
신흑동 881
 
3.3%
오천면 803
 
3.0%
남포면 782
 
3.0%
주교면 710
 
2.7%
명천동 674
 
2.5%
청라면 671
 
2.5%
대천동 649
 
2.5%
천북면 467
 
1.8%
동대동 463
 
1.8%
Other values (5620) 19235
72.7%
2024-01-10T07:57:46.114813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16528
 
14.8%
- 6868
 
6.1%
1 6810
 
6.1%
리 6284
 
5.6%
2 5480
 
4.9%
면 5178
 
4.6%
동 4513
 
4.0%
3 4164
 
3.7%
천 3926
 
3.5%
4 3814
 
3.4%
Other values (111) 48221
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49990
44.7%
Decimal Number 38400
34.4%
Space Separator 16528
 
14.8%
Dash Punctuation 6868
 
6.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 6284
 
12.6%
면 5178
 
10.4%
동 4513
 
9.0%
천 3926
 
7.9%
산 2119
 
4.2%
주 2036
 
4.1%
대 1560
 
3.1%
신 1217
 
2.4%
포 1201
 
2.4%
청 1164
 
2.3%
Other values (99) 20792
41.6%
Decimal Number
ValueCountFrequency (%)
1 6810
17.7%
2 5480
14.3%
3 4164
10.8%
4 3814
9.9%
5 3409
8.9%
6 3186
8.3%
7 3071
8.0%
8 3060
8.0%
9 2955
7.7%
0 2451
 
6.4%
Space Separator
ValueCountFrequency (%)
16528
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6868
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61796
55.3%
Hangul 49990
44.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 6284
 
12.6%
면 5178
 
10.4%
동 4513
 
9.0%
천 3926
 
7.9%
산 2119
 
4.2%
주 2036
 
4.1%
대 1560
 
3.1%
신 1217
 
2.4%
포 1201
 
2.4%
청 1164
 
2.3%
Other values (99) 20792
41.6%
Common
ValueCountFrequency (%)
16528
26.7%
- 6868
11.1%
1 6810
11.0%
2 5480
 
8.9%
3 4164
 
6.7%
4 3814
 
6.2%
5 3409
 
5.5%
6 3186
 
5.2%
7 3071
 
5.0%
8 3060
 
5.0%
Other values (2) 5406
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61796
55.3%
Hangul 49990
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16528
26.7%
- 6868
11.1%
1 6810
11.0%
2 5480
 
8.9%
3 4164
 
6.7%
4 3814
 
6.2%
5 3409
 
5.5%
6 3186
 
5.2%
7 3071
 
5.0%
8 3060
 
5.0%
Other values (2) 5406
 
8.7%
Hangul
ValueCountFrequency (%)
리 6284
 
12.6%
면 5178
 
10.4%
동 4513
 
9.0%
천 3926
 
7.9%
산 2119
 
4.2%
주 2036
 
4.1%
대 1560
 
3.1%
신 1217
 
2.4%
포 1201
 
2.4%
청 1164
 
2.3%
Other values (99) 20792
41.6%

상세위치
Text

MISSING 

Distinct416
Distinct (%)42.1%
Missing9013
Missing (%)90.1%
Memory size156.2 KiB
2024-01-10T07:57:46.367389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.1306991
Min length1

Characters and Unicode

Total characters7038
Distinct characters352
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique273 ?
Unique (%)27.7%

Sample

1st row남포진입도로(대천방향)
2nd row무창포입구
3rd row대천해수욕장교회뒤편공원등
4th row대천학생해양수련원
5th row요나성당옆공영주차장등
ValueCountFrequency (%)
명천택지개발지구 67
 
6.7%
화산교차로상부도로 44
 
4.4%
원산안면대교 26
 
2.6%
원의교차로 19
 
1.9%
웅천사격장이주단지 15
 
1.5%
백사장가로등 14
 
1.4%
충혼탑공원내 14
 
1.4%
남포방조제도로 13
 
1.3%
선촌교차로 13
 
1.3%
해수욕장사업소주차장 13
 
1.3%
Other values (414) 766
76.3%
2024-01-10T07:57:46.795836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 277
 
3.9%
교 237
 
3.4%
장 208
 
3.0%
차 191
 
2.7%
지 180
 
2.6%
천 178
 
2.5%
구 178
 
2.5%
주 156
 
2.2%
앞 152
 
2.2%
원 138
 
2.0%
Other values (342) 5143
73.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6773
96.2%
Uppercase Letter 116
 
1.6%
Decimal Number 102
 
1.4%
Space Separator 17
 
0.2%
Open Punctuation 11
 
0.2%
Close Punctuation 11
 
0.2%
Dash Punctuation 5
 
0.1%
Lowercase Letter 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 277
 
4.1%
교 237
 
3.5%
장 208
 
3.1%
차 191
 
2.8%
지 180
 
2.7%
천 178
 
2.6%
구 178
 
2.6%
주 156
 
2.3%
앞 152
 
2.2%
원 138
 
2.0%
Other values (312) 4878
72.0%
Uppercase Letter
ValueCountFrequency (%)
S 30
25.9%
K 29
25.0%
C 12
 
10.3%
G 12
 
10.3%
P 7
 
6.0%
N 6
 
5.2%
L 6
 
5.2%
U 4
 
3.4%
I 3
 
2.6%
M 3
 
2.6%
Other values (3) 4
 
3.4%
Decimal Number
ValueCountFrequency (%)
1 32
31.4%
0 23
22.5%
2 13
12.7%
3 10
 
9.8%
4 8
 
7.8%
5 7
 
6.9%
7 3
 
2.9%
8 3
 
2.9%
6 2
 
2.0%
9 1
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6773
96.2%
Common 147
 
2.1%
Latin 118
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 277
 
4.1%
교 237
 
3.5%
장 208
 
3.1%
차 191
 
2.8%
지 180
 
2.7%
천 178
 
2.6%
구 178
 
2.6%
주 156
 
2.3%
앞 152
 
2.2%
원 138
 
2.0%
Other values (312) 4878
72.0%
Common
ValueCountFrequency (%)
1 32
21.8%
0 23
15.6%
17
11.6%
2 13
8.8%
( 11
 
7.5%
) 11
 
7.5%
3 10
 
6.8%
4 8
 
5.4%
5 7
 
4.8%
- 5
 
3.4%
Other values (5) 10
 
6.8%
Latin
ValueCountFrequency (%)
S 30
25.4%
K 29
24.6%
C 12
 
10.2%
G 12
 
10.2%
P 7
 
5.9%
N 6
 
5.1%
L 6
 
5.1%
U 4
 
3.4%
I 3
 
2.5%
M 3
 
2.5%
Other values (5) 6
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6773
96.2%
ASCII 265
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 277
 
4.1%
교 237
 
3.5%
장 208
 
3.1%
차 191
 
2.8%
지 180
 
2.7%
천 178
 
2.6%
구 178
 
2.6%
주 156
 
2.3%
앞 152
 
2.2%
원 138
 
2.0%
Other values (312) 4878
72.0%
ASCII
ValueCountFrequency (%)
1 32
12.1%
S 30
 
11.3%
K 29
 
10.9%
0 23
 
8.7%
17
 
6.4%
2 13
 
4.9%
C 12
 
4.5%
G 12
 
4.5%
( 11
 
4.2%
) 11
 
4.2%
Other values (20) 75
28.3%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-09-16 00:00:00
Maximum2022-09-16 00:00:00
2024-01-10T07:57:46.900859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:57:46.980954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-01-10T07:57:44.392244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:57:44.481195image/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.

Sample

표찰번호행정동지번주소상세위치데이터기준일
222114-12대천4동명천동 384<NA>2022-09-16
13246주산면177주산면주산면 황율리 388-2<NA>2022-09-16
13003주교면784주교면주교면 은포리 1679<NA>2022-09-16
13818주포면087주포면주포면 보령리 522-1<NA>2022-09-16
15223청라면443청라면청라면 의평리 124-6<NA>2022-09-16
14466천북면379천북면천북면 궁포리 696-1<NA>2022-09-16
13761주포면030주포면주포면 마강리 125-19<NA>2022-09-16
9737오천면060오천면오천면 오포리 1074<NA>2022-09-16
15806청소면214청소면청소면 죽림리 190<NA>2022-09-16
8588대천5동901대천5동요암동<NA>2022-09-16
표찰번호행정동지번주소상세위치데이터기준일
10701오천면913오천면오천면 원산도리 448-1<NA>2022-09-16
1041159-13대천5동신흑동 2108왕건조개구이2022-09-16
9912오천면1152오천면오천면 원산도리 301<NA>2022-09-16
9157미산면487미산면미산면 삼계리 37<NA>2022-09-16
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