Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells8671
Missing cells (%)17.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory468.8 KiB
Average record size in memory48.0 B

Variable types

Text3
Categorical2

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 8671 (86.7%) missing valuesMissing

Reproduction

Analysis started2024-01-09 22:57:47.584595
Analysis finished2024-01-09 22:57:48.256755
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

표찰번호
Text

Distinct9993
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T07:57:48.447151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.0936
Min length3

Characters and Unicode

Total characters60936
Distinct characters58
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

Unique9986 ?
Unique (%)99.9%

Sample

1st row대천1동064
2nd row웅천읍144
3rd row웅천읍1054
4th row청소면038
5th row대천1동341
ValueCountFrequency (%)
07월 27
 
0.3%
03월 20
 
0.2%
04월 18
 
0.2%
08월 17
 
0.2%
11월 12
 
0.1%
02월 12
 
0.1%
05월 11
 
0.1%
25일 9
 
0.1%
06월 9
 
0.1%
15일 9
 
0.1%
Other values (9881) 10009
98.6%
2024-01-10T07:57:48.836074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5703
 
9.4%
2 4814
 
7.9%
3 4715
 
7.7%
면 4192
 
6.9%
천 3724
 
6.1%
5 3565
 
5.9%
0 3356
 
5.5%
4 3344
 
5.5%
- 3125
 
5.1%
6 2967
 
4.9%
Other values (48) 21431
35.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35728
58.6%
Other Letter 20711
34.0%
Dash Punctuation 3125
 
5.1%
Lowercase Letter 796
 
1.3%
Uppercase Letter 403
 
0.7%
Space Separator 154
 
0.3%
Close Punctuation 9
 
< 0.1%
Open Punctuation 9
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 4192
20.2%
천 3724
18.0%
대 1815
8.8%
동 1815
8.8%
주 1374
 
6.6%
청 869
 
4.2%
웅 835
 
4.0%
포 754
 
3.6%
산 729
 
3.5%
읍 716
 
3.5%
Other values (10) 3888
18.8%
Lowercase Letter
ValueCountFrequency (%)
a 118
14.8%
u 90
11.3%
e 90
11.3%
r 79
9.9%
n 70
8.8%
p 67
8.4%
c 51
6.4%
b 40
 
5.0%
y 38
 
4.8%
o 32
 
4.0%
Other values (4) 121
15.2%
Decimal Number
ValueCountFrequency (%)
1 5703
16.0%
2 4814
13.5%
3 4715
13.2%
5 3565
10.0%
0 3356
9.4%
4 3344
9.4%
6 2967
8.3%
7 2523
7.1%
9 2391
6.7%
8 2350
6.6%
Uppercase Letter
ValueCountFrequency (%)
J 102
25.3%
M 77
19.1%
A 72
17.9%
F 40
 
9.9%
N 32
 
7.9%
O 28
 
6.9%
S 27
 
6.7%
D 23
 
5.7%
B 2
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 3125
100.0%
Space Separator
ValueCountFrequency (%)
154
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39026
64.0%
Hangul 20711
34.0%
Latin 1199
 
2.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 118
 
9.8%
J 102
 
8.5%
u 90
 
7.5%
e 90
 
7.5%
r 79
 
6.6%
M 77
 
6.4%
A 72
 
6.0%
n 70
 
5.8%
p 67
 
5.6%
c 51
 
4.3%
Other values (13) 383
31.9%
Hangul
ValueCountFrequency (%)
면 4192
20.2%
천 3724
18.0%
대 1815
8.8%
동 1815
8.8%
주 1374
 
6.6%
청 869
 
4.2%
웅 835
 
4.0%
포 754
 
3.6%
산 729
 
3.5%
읍 716
 
3.5%
Other values (10) 3888
18.8%
Common
ValueCountFrequency (%)
1 5703
14.6%
2 4814
12.3%
3 4715
12.1%
5 3565
9.1%
0 3356
8.6%
4 3344
8.6%
- 3125
8.0%
6 2967
7.6%
7 2523
6.5%
9 2391
6.1%
Other values (5) 2523
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40225
66.0%
Hangul 20711
34.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5703
14.2%
2 4814
12.0%
3 4715
11.7%
5 3565
8.9%
0 3356
8.3%
4 3344
8.3%
- 3125
7.8%
6 2967
7.4%
7 2523
6.3%
9 2391
5.9%
Other values (28) 3722
9.3%
Hangul
ValueCountFrequency (%)
면 4192
20.2%
천 3724
18.0%
대 1815
8.8%
동 1815
8.8%
주 1374
 
6.6%
청 869
 
4.2%
웅 835
 
4.0%
포 754
 
3.6%
산 729
 
3.5%
읍 716
 
3.5%
Other values (10) 3888
18.8%

행정동
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대천5동
1295 
웅천읍
1069 
대천4동
973 
대천3동
828 
오천면
767 
Other values (11)
5068 

Length

Max length4
Median length3
Mean length3.4002
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대천1동
2nd row웅천읍
3rd row웅천읍
4th row청소면
5th row대천1동

Common Values

ValueCountFrequency (%)
대천5동 1295
13.0%
웅천읍 1069
10.7%
대천4동 973
9.7%
대천3동 828
 
8.3%
오천면 767
 
7.7%
남포면 738
 
7.4%
주교면 669
 
6.7%
청라면 612
 
6.1%
대천1동 531
 
5.3%
천북면 447
 
4.5%
Other values (6) 2071
20.7%

Length

2024-01-10T07:57:48.977111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대천5동 1295
13.0%
웅천읍 1069
10.7%
대천4동 973
9.7%
대천3동 828
 
8.3%
오천면 767
 
7.7%
남포면 738
 
7.4%
주교면 669
 
6.7%
청라면 612
 
6.1%
대천1동 531
 
5.3%
천북면 447
 
4.5%
Other values (6) 2071
20.7%

지번주소
Text

Distinct7213
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T07:57:49.334070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length11.0565
Min length4

Characters and Unicode

Total characters110565
Distinct characters128
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

Unique6206 ?
Unique (%)62.1%

Sample

1st row대천동 288-95
2nd row웅천읍 구룡리 113-2
3rd row웅천읍 두룡리 502-3
4th row청소면 성연리 732
5th row대천동 983-127
ValueCountFrequency (%)
웅천읍 1068
 
4.1%
신흑동 827
 
3.2%
오천면 767
 
2.9%
명천동 766
 
2.9%
남포면 738
 
2.8%
주교면 669
 
2.6%
대천동 668
 
2.6%
동대동 658
 
2.5%
청라면 612
 
2.3%
천북면 447
 
1.7%
Other values (5563) 18934
72.4%
2024-01-10T07:57:49.818906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16233
 
14.7%
- 6823
 
6.2%
1 6741
 
6.1%
리 5999
 
5.4%
2 5295
 
4.8%
동 4980
 
4.5%
면 4930
 
4.5%
3 4176
 
3.8%
천 3922
 
3.5%
4 3739
 
3.4%
Other values (118) 47727
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49121
44.4%
Decimal Number 38388
34.7%
Space Separator 16233
 
14.7%
Dash Punctuation 6823
 
6.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 5999
 
12.2%
동 4980
 
10.1%
면 4930
 
10.0%
천 3922
 
8.0%
산 2049
 
4.2%
주 1945
 
4.0%
대 1745
 
3.6%
신 1144
 
2.3%
포 1132
 
2.3%
읍 1113
 
2.3%
Other values (106) 20162
41.0%
Decimal Number
ValueCountFrequency (%)
1 6741
17.6%
2 5295
13.8%
3 4176
10.9%
4 3739
9.7%
5 3468
9.0%
6 3303
8.6%
8 3125
8.1%
9 3109
8.1%
7 3018
7.9%
0 2414
 
6.3%
Space Separator
ValueCountFrequency (%)
16233
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6823
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61444
55.6%
Hangul 49121
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 5999
 
12.2%
동 4980
 
10.1%
면 4930
 
10.0%
천 3922
 
8.0%
산 2049
 
4.2%
주 1945
 
4.0%
대 1745
 
3.6%
신 1144
 
2.3%
포 1132
 
2.3%
읍 1113
 
2.3%
Other values (106) 20162
41.0%
Common
ValueCountFrequency (%)
16233
26.4%
- 6823
11.1%
1 6741
11.0%
2 5295
 
8.6%
3 4176
 
6.8%
4 3739
 
6.1%
5 3468
 
5.6%
6 3303
 
5.4%
8 3125
 
5.1%
9 3109
 
5.1%
Other values (2) 5432
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61444
55.6%
Hangul 49121
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16233
26.4%
- 6823
11.1%
1 6741
11.0%
2 5295
 
8.6%
3 4176
 
6.8%
4 3739
 
6.1%
5 3468
 
5.6%
6 3303
 
5.4%
8 3125
 
5.1%
9 3109
 
5.1%
Other values (2) 5432
 
8.8%
Hangul
ValueCountFrequency (%)
리 5999
 
12.2%
동 4980
 
10.1%
면 4930
 
10.0%
천 3922
 
8.0%
산 2049
 
4.2%
주 1945
 
4.0%
대 1745
 
3.6%
신 1144
 
2.3%
포 1132
 
2.3%
읍 1113
 
2.3%
Other values (106) 20162
41.0%

상세위치
Text

MISSING 

Distinct658
Distinct (%)49.5%
Missing8671
Missing (%)86.7%
Memory size156.2 KiB
2024-01-10T07:57:50.057018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.2167043
Min length1

Characters and Unicode

Total characters9591
Distinct characters432
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

Unique470 ?
Unique (%)35.4%

Sample

1st row미산초등학교축장앞
2nd row게임랜드앞
3rd row대천항역객터미널입구
4th row가람민박
5th row원의교차로
ValueCountFrequency (%)
명천택지개발지구 65
 
4.8%
화산교차로상부도로 43
 
3.1%
원산안면대교 23
 
1.7%
남포방조제도로 18
 
1.3%
백사장가로등 16
 
1.2%
웅천사격장이주단지 16
 
1.2%
교량등 15
 
1.1%
휴먼시아공원등 15
 
1.1%
원의교차로 13
 
1.0%
남포궁촌간도로sk주유소옆 13
 
1.0%
Other values (655) 1130
82.7%
2024-01-10T07:57:50.409873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 322
 
3.4%
교 314
 
3.3%
앞 305
 
3.2%
천 249
 
2.6%
장 227
 
2.4%
구 220
 
2.3%
차 205
 
2.1%
지 193
 
2.0%
주 189
 
2.0%
도 174
 
1.8%
Other values (422) 7193
75.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9162
95.5%
Decimal Number 243
 
2.5%
Uppercase Letter 121
 
1.3%
Space Separator 39
 
0.4%
Close Punctuation 10
 
0.1%
Open Punctuation 10
 
0.1%
Dash Punctuation 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 322
 
3.5%
교 314
 
3.4%
앞 305
 
3.3%
천 249
 
2.7%
장 227
 
2.5%
구 220
 
2.4%
차 205
 
2.2%
지 193
 
2.1%
주 189
 
2.1%
도 174
 
1.9%
Other values (389) 6764
73.8%
Uppercase Letter
ValueCountFrequency (%)
S 34
28.1%
K 32
26.4%
C 10
 
8.3%
G 9
 
7.4%
I 5
 
4.1%
P 5
 
4.1%
J 4
 
3.3%
L 4
 
3.3%
N 4
 
3.3%
D 3
 
2.5%
Other values (6) 11
 
9.1%
Decimal Number
ValueCountFrequency (%)
0 67
27.6%
1 57
23.5%
2 29
11.9%
4 25
 
10.3%
3 24
 
9.9%
5 14
 
5.8%
8 8
 
3.3%
6 8
 
3.3%
7 7
 
2.9%
9 4
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9162
95.5%
Common 306
 
3.2%
Latin 123
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 322
 
3.5%
교 314
 
3.4%
앞 305
 
3.3%
천 249
 
2.7%
장 227
 
2.5%
구 220
 
2.4%
차 205
 
2.2%
지 193
 
2.1%
주 189
 
2.1%
도 174
 
1.9%
Other values (389) 6764
73.8%
Latin
ValueCountFrequency (%)
S 34
27.6%
K 32
26.0%
C 10
 
8.1%
G 9
 
7.3%
I 5
 
4.1%
P 5
 
4.1%
J 4
 
3.3%
L 4
 
3.3%
N 4
 
3.3%
D 3
 
2.4%
Other values (8) 13
 
10.6%
Common
ValueCountFrequency (%)
0 67
21.9%
1 57
18.6%
39
12.7%
2 29
9.5%
4 25
 
8.2%
3 24
 
7.8%
5 14
 
4.6%
) 10
 
3.3%
( 10
 
3.3%
8 8
 
2.6%
Other values (5) 23
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9162
95.5%
ASCII 429
 
4.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 322
 
3.5%
교 314
 
3.4%
앞 305
 
3.3%
천 249
 
2.7%
장 227
 
2.5%
구 220
 
2.4%
차 205
 
2.2%
지 193
 
2.1%
주 189
 
2.1%
도 174
 
1.9%
Other values (389) 6764
73.8%
ASCII
ValueCountFrequency (%)
0 67
15.6%
1 57
13.3%
39
 
9.1%
S 34
 
7.9%
K 32
 
7.5%
2 29
 
6.8%
4 25
 
5.8%
3 24
 
5.6%
5 14
 
3.3%
) 10
 
2.3%
Other values (23) 98
22.8%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-10-29
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-10-29
2nd row2021-10-29
3rd row2021-10-29
4th row2021-10-29
5th row2021-10-29

Common Values

ValueCountFrequency (%)
2021-10-29 10000
100.0%

Length

2024-01-10T07:57:50.531660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:57:50.613080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-10-29 10000
100.0%

Missing values

2024-01-10T07:57:48.119389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:57:48.212709image/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
6805대천1동064대천1동대천동 288-95<NA>2021-10-29
12326웅천읍144웅천읍웅천읍 구룡리 113-2<NA>2021-10-29
12098웅천읍1054웅천읍웅천읍 두룡리 502-3<NA>2021-10-29
16558청소면038청소면청소면 성연리 732<NA>2021-10-29
7075대천1동341대천1동대천동 983-127<NA>2021-10-29
2231247-2미산면미산면 도화담리 94미산초등학교축장앞2021-10-29
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