Overview

Dataset statistics

Number of variables2
Number of observations680
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.8 KiB
Average record size in memory16.2 B

Variable types

Text2

Dataset

Description국토지리정보원에서 생성하는 국토지표 데이터(인구와 사회, 토지와 주택, 생활과 복지, 국토인프라, 환경과 안전)의 레이어명, 원천파일명을 제공합니다.
Author국토교통부 국토지리정보원
URLhttps://www.data.go.kr/data/15122714/fileData.do

Alerts

레이어명 has unique valuesUnique
원천파일명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:56:19.258647
Analysis finished2023-12-12 00:56:19.573208
Duration0.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

레이어명
Text

UNIQUE 

Distinct680
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-12T09:56:19.835925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length35.907353
Min length17

Characters and Unicode

Total characters24417
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique680 ?
Unique (%)100.0%

Sample

1st rowsmall_population_2019
2nd rowold_house_20_2019
3rd rowold_house_30_2019
4th rowold_house_r_20_2019
5th rowold_house_r_30_2019
ValueCountFrequency (%)
small_population_2019 1
 
0.1%
highspeedrail_accessibility_025_2021 1
 
0.1%
pharmacy_accessibility_e_2021 1
 
0.1%
shelter_accessibility_e_2021 1
 
0.1%
parkinglot_accessibility_025_2021 1
 
0.1%
parkinglot_accessibility_2021 1
 
0.1%
parkinglot_accessibility_e_2021 1
 
0.1%
highway_ic_accessibility_025_2021 1
 
0.1%
highway_ic_accessibility_2021 1
 
0.1%
highway_ic_accessibility_e_2021 1
 
0.1%
Other values (670) 670
98.5%
2023-12-12T09:56:20.230323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 3305
13.5%
s 1740
 
7.1%
a 1718
 
7.0%
c 1615
 
6.6%
i 1448
 
5.9%
p 1425
 
5.8%
o 1355
 
5.5%
l 1340
 
5.5%
0 1340
 
5.5%
e 1321
 
5.4%
Other values (24) 7810
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17098
70.0%
Decimal Number 4013
 
16.4%
Connector Punctuation 3305
 
13.5%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 1740
10.2%
a 1718
10.0%
c 1615
9.4%
i 1448
8.5%
p 1425
8.3%
o 1355
7.9%
l 1340
7.8%
e 1321
7.7%
t 1067
 
6.2%
r 811
 
4.7%
Other values (14) 3258
19.1%
Decimal Number
ValueCountFrequency (%)
0 1340
33.4%
2 1167
29.1%
1 807
20.1%
5 371
 
9.2%
9 128
 
3.2%
8 108
 
2.7%
7 76
 
1.9%
3 16
 
0.4%
Connector Punctuation
ValueCountFrequency (%)
_ 3305
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17099
70.0%
Common 7318
30.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 1740
10.2%
a 1718
10.0%
c 1615
9.4%
i 1448
8.5%
p 1425
8.3%
o 1355
7.9%
l 1340
7.8%
e 1321
7.7%
t 1067
 
6.2%
r 811
 
4.7%
Other values (15) 3259
19.1%
Common
ValueCountFrequency (%)
_ 3305
45.2%
0 1340
18.3%
2 1167
 
15.9%
1 807
 
11.0%
5 371
 
5.1%
9 128
 
1.7%
8 108
 
1.5%
7 76
 
1.0%
3 16
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24417
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 3305
13.5%
s 1740
 
7.1%
a 1718
 
7.0%
c 1615
 
6.6%
i 1448
 
5.9%
p 1425
 
5.8%
o 1355
 
5.5%
l 1340
 
5.5%
0 1340
 
5.5%
e 1321
 
5.4%
Other values (24) 7810
32.0%

원천파일명
Text

UNIQUE 

Distinct680
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-12T09:56:20.477031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length31.626471
Min length9

Characters and Unicode

Total characters21506
Distinct characters128
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique680 ?
Unique (%)100.0%

Sample

1st row1.2.인구과소지역비율_2019
2nd row5.1.노후주택수(20년이상)_격자_2019
3rd row5.4.노후주택수(30년이상)_격자_2019
4th row6.1.노후주택비율(20년이상)_격자_2019
5th row6.4.노후주택비율(30년이상)_격자_2019
ValueCountFrequency (%)
서비스권역 313
 
14.0%
내 250
 
11.2%
접근성_2021 82
 
3.7%
외 63
 
2.8%
접근성_2020 27
 
1.2%
의료취약인구 21
 
0.9%
인구비율(1.0km)_2021 19
 
0.9%
인구비율(0.75km)_2021 19
 
0.9%
인구비율(1.5km)_2021 19
 
0.9%
인구비율(0.5km)_2021 19
 
0.9%
Other values (874) 1398
62.7%
2023-12-12T09:56:20.873601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1550
 
7.2%
2 1428
 
6.6%
0 1233
 
5.7%
. 1230
 
5.7%
1 1184
 
5.5%
) 821
 
3.8%
( 821
 
3.8%
비 813
 
3.8%
_ 632
 
2.9%
구 618
 
2.9%
Other values (118) 11176
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9768
45.4%
Decimal Number 5712
26.6%
Space Separator 1550
 
7.2%
Other Punctuation 1234
 
5.7%
Lowercase Letter 956
 
4.4%
Close Punctuation 821
 
3.8%
Open Punctuation 821
 
3.8%
Connector Punctuation 632
 
2.9%
Uppercase Letter 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 813
 
8.3%
구 618
 
6.3%
서 545
 
5.6%
인 531
 
5.4%
권 504
 
5.2%
역 482
 
4.9%
스 478
 
4.9%
내 377
 
3.9%
율 335
 
3.4%
시 311
 
3.2%
Other values (98) 4774
48.9%
Decimal Number
ValueCountFrequency (%)
2 1428
25.0%
0 1233
21.6%
1 1184
20.7%
5 508
 
8.9%
4 287
 
5.0%
3 286
 
5.0%
7 224
 
3.9%
9 222
 
3.9%
6 189
 
3.3%
8 151
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 1230
99.7%
· 4
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
k 478
50.0%
m 478
50.0%
Uppercase Letter
ValueCountFrequency (%)
C 6
50.0%
I 6
50.0%
Space Separator
ValueCountFrequency (%)
1550
100.0%
Close Punctuation
ValueCountFrequency (%)
) 821
100.0%
Open Punctuation
ValueCountFrequency (%)
( 821
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 632
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10770
50.1%
Hangul 9768
45.4%
Latin 968
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 813
 
8.3%
구 618
 
6.3%
서 545
 
5.6%
인 531
 
5.4%
권 504
 
5.2%
역 482
 
4.9%
스 478
 
4.9%
내 377
 
3.9%
율 335
 
3.4%
시 311
 
3.2%
Other values (98) 4774
48.9%
Common
ValueCountFrequency (%)
1550
14.4%
2 1428
13.3%
0 1233
11.4%
. 1230
11.4%
1 1184
11.0%
) 821
7.6%
( 821
7.6%
_ 632
5.9%
5 508
 
4.7%
4 287
 
2.7%
Other values (6) 1076
10.0%
Latin
ValueCountFrequency (%)
k 478
49.4%
m 478
49.4%
C 6
 
0.6%
I 6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11734
54.6%
Hangul 9768
45.4%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1550
13.2%
2 1428
12.2%
0 1233
10.5%
. 1230
10.5%
1 1184
10.1%
) 821
7.0%
( 821
7.0%
_ 632
 
5.4%
5 508
 
4.3%
k 478
 
4.1%
Other values (9) 1849
15.8%
Hangul
ValueCountFrequency (%)
비 813
 
8.3%
구 618
 
6.3%
서 545
 
5.6%
인 531
 
5.4%
권 504
 
5.2%
역 482
 
4.9%
스 478
 
4.9%
내 377
 
3.9%
율 335
 
3.4%
시 311
 
3.2%
Other values (98) 4774
48.9%
None
ValueCountFrequency (%)
· 4
100.0%

Missing values

2023-12-12T09:56:19.456293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:56:19.542459image/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

레이어명원천파일명
0small_population_20191.2.인구과소지역비율_2019
1old_house_20_20195.1.노후주택수(20년이상)_격자_2019
2old_house_30_20195.4.노후주택수(30년이상)_격자_2019
3old_house_r_20_20196.1.노후주택비율(20년이상)_격자_2019
4old_house_r_30_20196.4.노후주택비율(30년이상)_격자_2019
5Long_delayed_facility_poa_201924.1.장기미집행도시계획시설면적비율_시군구_2019
6bldg_mixeduse_201927.1.토지이용(건물)복합도_격자_2019
7bldg_compactness_201926.1.토지이용(건물)압축도_격자_2019
8sports_fac_access_population_05_201977.1.공공체육시설서비스권역내인구(0.5km)_2019
9sports_fac_access_population_075_201977.2.공공체육시설서비스권역내인구(0.75km)_2019
레이어명원천파일명
670shelter_access_population_e_10_2021202.3 지진옥외대피소(읍면동) 서비스권역 내 인구비율(1.0km)_2021
671shelter_access_population_e_15_2021202.4 지진옥외대피소(읍면동) 서비스권역 내 인구비율(1.5km)_2021
672sports_fac_accessibility_025_202174.1 공공체육시설(읍면동격자) 접근성_2021
673sports_fac_accessibility_202174.2 공공체육시설(시군구격자) 접근성_2021
674sports_fac_accessibility_e_202174.3 공공체육시설(읍면동) 접근성_2021
675electric_car_access_population_r_05_2021시범 전기차충전소(시군구) 서비스권역 내 인구비율(0.5km)_2021
676electric_car_access_population_r_075_2021시범 전기차충전소(시군구) 서비스권역 내 인구비율(0.75km)_2021
677electric_car_access_population_r_10_2021시범 전기차충전소(시군구) 서비스권역 내 인구비율(1.0km)_2021
678electric_car_access_population_r_15_2021시범 전기차충전소(시군구) 서비스권역 내 인구비율(1.5km)_2021
679electric_car_accessibility_2021시범 전기차충전소(시군구격자) 접근성_2021