Overview

Dataset statistics

Number of variables4
Number of observations1846
Missing cells0
Missing cells (%)0.0%
Duplicate rows195
Duplicate rows (%)10.6%
Total size in memory57.8 KiB
Average record size in memory32.1 B

Variable types

Text3
Categorical1

Dataset

Description원격탐사 현장조사시 지점의 위치정보 입니다. 주소, PSU 아이디, SSU 아이디, 조사일자 등의 데이터가 포함되며 조사구 체계로 바뀌기 이전의 데이터 입니다.
Author통계청
URLhttps://www.data.go.kr/data/15086661/fileData.do

Alerts

Dataset has 195 (10.6%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 00:02:02.780663
Analysis finished2023-12-12 00:02:03.150654
Duration0.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주소
Text

Distinct1648
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Memory size14.6 KiB
2023-12-12T09:02:03.433488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length90
Median length88
Mean length59.721018
Min length15

Characters and Unicode

Total characters110245
Distinct characters324
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

Unique1450 ?
Unique (%)78.5%

Sample

1st row전라남도 화순군 이서면 월산리 1121번지
2nd row전라남도 신안군 지도읍 봉리 2440-7번지
3rd row광주광역시 남구 임암동 산 48-1번지
4th row전라남도 신안군 지도읍 봉리 2000-23번지
5th row광주광역시 광산구 동산동 98번지
ValueCountFrequency (%)
산 458
 
4.8%
전라남도 291
 
3.1%
경상북도 270
 
2.8%
경기도 222
 
2.3%
충청남도 215
 
2.3%
전라북도 207
 
2.2%
강원도 168
 
1.8%
경상남도 155
 
1.6%
충청북도 137
 
1.4%
제주특별자치도 64
 
0.7%
Other values (3558) 7313
77.0%
2023-12-12T09:02:04.046636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75132
68.2%
0 2005
 
1.8%
도 1861
 
1.7%
리 1558
 
1.4%
1 1385
 
1.3%
면 1274
 
1.2%
- 1189
 
1.1%
지 1187
 
1.1%
번 1088
 
1.0%
시 1001
 
0.9%
Other values (314) 22565
 
20.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 75132
68.2%
Other Letter 25946
 
23.5%
Decimal Number 7978
 
7.2%
Dash Punctuation 1189
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 1861
 
7.2%
리 1558
 
6.0%
면 1274
 
4.9%
지 1187
 
4.6%
번 1088
 
4.2%
시 1001
 
3.9%
산 987
 
3.8%
군 944
 
3.6%
남 856
 
3.3%
북 759
 
2.9%
Other values (302) 14431
55.6%
Decimal Number
ValueCountFrequency (%)
0 2005
25.1%
1 1385
17.4%
2 846
10.6%
3 703
 
8.8%
4 612
 
7.7%
6 555
 
7.0%
5 528
 
6.6%
7 485
 
6.1%
8 433
 
5.4%
9 426
 
5.3%
Space Separator
ValueCountFrequency (%)
75132
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1189
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84299
76.5%
Hangul 25946
 
23.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 1861
 
7.2%
리 1558
 
6.0%
면 1274
 
4.9%
지 1187
 
4.6%
번 1088
 
4.2%
시 1001
 
3.9%
산 987
 
3.8%
군 944
 
3.6%
남 856
 
3.3%
북 759
 
2.9%
Other values (302) 14431
55.6%
Common
ValueCountFrequency (%)
75132
89.1%
0 2005
 
2.4%
1 1385
 
1.6%
- 1189
 
1.4%
2 846
 
1.0%
3 703
 
0.8%
4 612
 
0.7%
6 555
 
0.7%
5 528
 
0.6%
7 485
 
0.6%
Other values (2) 859
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84299
76.5%
Hangul 25946
 
23.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75132
89.1%
0 2005
 
2.4%
1 1385
 
1.6%
- 1189
 
1.4%
2 846
 
1.0%
3 703
 
0.8%
4 612
 
0.7%
6 555
 
0.7%
5 528
 
0.6%
7 485
 
0.6%
Other values (2) 859
 
1.0%
Hangul
ValueCountFrequency (%)
도 1861
 
7.2%
리 1558
 
6.0%
면 1274
 
4.9%
지 1187
 
4.6%
번 1088
 
4.2%
시 1001
 
3.9%
산 987
 
3.8%
군 944
 
3.6%
남 856
 
3.3%
북 759
 
2.9%
Other values (302) 14431
55.6%

대분류_아이디
Text

Distinct1409
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Memory size14.6 KiB
2023-12-12T09:02:04.493336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length8.7648971
Min length7

Characters and Unicode

Total characters16180
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

Unique1058 ?
Unique (%)57.3%

Sample

1st row079-080
2nd row079-053
3rd row079-074
4th row079-053
5th row080-070
ValueCountFrequency (%)
177-072 9
 
0.5%
192-087 8
 
0.4%
118-143 7
 
0.4%
099-069 6
 
0.3%
146-069 5
 
0.3%
120-078 5
 
0.3%
109-082 5
 
0.3%
110-074 5
 
0.3%
154-072 5
 
0.3%
150-081 5
 
0.3%
Other values (1234) 1786
96.7%
2023-12-12T09:02:05.071274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3258
20.1%
1 2691
16.6%
0 2463
15.2%
- 1846
11.4%
7 994
 
6.1%
8 857
 
5.3%
6 803
 
5.0%
9 741
 
4.6%
2 698
 
4.3%
5 630
 
3.9%
Other values (2) 1199
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11076
68.5%
Space Separator 3258
 
20.1%
Dash Punctuation 1846
 
11.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2691
24.3%
0 2463
22.2%
7 994
 
9.0%
8 857
 
7.7%
6 803
 
7.2%
9 741
 
6.7%
2 698
 
6.3%
5 630
 
5.7%
3 624
 
5.6%
4 575
 
5.2%
Space Separator
ValueCountFrequency (%)
3258
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1846
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16180
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3258
20.1%
1 2691
16.6%
0 2463
15.2%
- 1846
11.4%
7 994
 
6.1%
8 857
 
5.3%
6 803
 
5.0%
9 741
 
4.6%
2 698
 
4.3%
5 630
 
3.9%
Other values (2) 1199
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3258
20.1%
1 2691
16.6%
0 2463
15.2%
- 1846
11.4%
7 994
 
6.1%
8 857
 
5.3%
6 803
 
5.0%
9 741
 
4.6%
2 698
 
4.3%
5 630
 
3.9%
Other values (2) 1199
 
7.4%

중분류_아이디
Text

Distinct433
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size14.6 KiB
2023-12-12T09:02:05.461658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length8.7648971
Min length7

Characters and Unicode

Total characters16180
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

Unique43 ?
Unique (%)2.3%

Sample

1st row008-011
2nd row009-012
3rd row009-001
4th row011-011
5th row001-000
ValueCountFrequency (%)
000-007 19
 
1.0%
006-013 17
 
0.9%
006-003 16
 
0.9%
014-008 16
 
0.9%
004-010 16
 
0.9%
009-012 16
 
0.9%
005-014 16
 
0.9%
014-007 15
 
0.8%
002-000 15
 
0.8%
011-005 15
 
0.8%
Other values (215) 1685
91.3%
2023-12-12T09:02:05.939107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6624
40.9%
3258
20.1%
- 1846
 
11.4%
1 1793
 
11.1%
4 511
 
3.2%
3 507
 
3.1%
2 484
 
3.0%
7 248
 
1.5%
6 232
 
1.4%
5 232
 
1.4%
Other values (2) 445
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11076
68.5%
Space Separator 3258
 
20.1%
Dash Punctuation 1846
 
11.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6624
59.8%
1 1793
 
16.2%
4 511
 
4.6%
3 507
 
4.6%
2 484
 
4.4%
7 248
 
2.2%
6 232
 
2.1%
5 232
 
2.1%
9 230
 
2.1%
8 215
 
1.9%
Space Separator
ValueCountFrequency (%)
3258
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1846
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16180
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6624
40.9%
3258
20.1%
- 1846
 
11.4%
1 1793
 
11.1%
4 511
 
3.2%
3 507
 
3.1%
2 484
 
3.0%
7 248
 
1.5%
6 232
 
1.4%
5 232
 
1.4%
Other values (2) 445
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6624
40.9%
3258
20.1%
- 1846
 
11.4%
1 1793
 
11.1%
4 511
 
3.2%
3 507
 
3.1%
2 484
 
3.0%
7 248
 
1.5%
6 232
 
1.4%
5 232
 
1.4%
Other values (2) 445
 
2.8%

조사일자
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.6 KiB
2013-01-01
1086 
2015-01-01
390 
2014-01-01
370 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2013-01-01
2nd row2013-01-01
3rd row2013-01-01
4th row2013-01-01
5th row2013-01-01

Common Values

ValueCountFrequency (%)
2013-01-01 1086
58.8%
2015-01-01 390
 
21.1%
2014-01-01 370
 
20.0%

Length

2023-12-12T09:02:06.085953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:02:06.205044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013-01-01 1086
58.8%
2015-01-01 390
 
21.1%
2014-01-01 370
 
20.0%

Missing values

2023-12-12T09:02:03.019149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:02:03.102558image/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

주소대분류_아이디중분류_아이디조사일자
0전라남도 화순군 이서면 월산리 1121번지079-080008-0112013-01-01
1전라남도 신안군 지도읍 봉리 2440-7번지079-053009-0122013-01-01
2광주광역시 남구 임암동 산 48-1번지079-074009-0012013-01-01
3전라남도 신안군 지도읍 봉리 2000-23번지079-053011-0112013-01-01
4광주광역시 광산구 동산동 98번지080-070001-0002013-01-01
5광주광역시 광산구 동산동 산 267번지080-069009-0012013-01-01
6경상남도 하동군 악양면 봉대리 566-13번지081-099004-0042013-01-01
7전라남도 곡성군 죽곡면 유봉리 산 103번지081-088004-0072013-01-01
8전라남도 구례군 문척면 죽마리 산 177번지081-092008-0112013-01-01
9전라남도 순천시 황전면 비촌리 산 186-1번지081-090013-0132013-01-01
주소대분류_아이디중분류_아이디조사일자
1836경상북도 경주시 서면 도계리 58-1108-140013-0032015-01-01
1837경상북도 칠곡군 약목면 덕산리 113-2113-120011-0022015-01-01
1838경상북도 포항시 북구 기북면 율산리 715-1118-143000-0072015-01-01
1839경상북도 안동시 길안면 천지리 418129-135011-0002015-01-01
1840경상북도 안동시 도산면 태자리 산 171-5142-133000-0052015-01-01
1841충청북도 충주시 호암동 331-5147-106010-0042015-01-01
1842제주특별자치도 서귀포시 표선면 가시리 992014-071011-0022015-01-01
1843제주특별자치도 제주시 애월읍 광령리 985-1018-060010-0072015-01-01
1844제주특별자치도 제주시 구좌읍 하도리 562021-074003-0082015-01-01
1845전라남도 해남군 북평면 영전리 791-1051-065011-0052015-01-01

Duplicate rows

Most frequently occurring

주소대분류_아이디중분류_아이디조사일자# duplicates
0강원도 강릉시 연곡면 퇴곡리 98181-129006-0132015-01-012
1강원도 고성군 죽왕면 문암진리 270-7197-123014-0092015-01-012
2강원도 고성군 토성면 용암리 380196-123007-0092015-01-012
3강원도 양양군 양양읍 내곡리 161189-125013-0122015-01-012
4강원도 인제군 기린면 방동리 1297185-118001-0102015-01-012
5강원도 인제군 남면 신남리 279-1185-110006-0092015-01-012
6강원도 평창군 봉평면 원길리 649-1172-118013-0122015-01-012
7강원도 홍천군 내면 광원리 산 514180-120005-0062015-01-012
8경기도 광주시 곤지암읍 삼리 207162-087013-0142015-01-012
9경기도 부천시 오정구 고강동 111-1169-073007-0002015-01-012