Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory322.3 KiB
Average record size in memory33.0 B

Variable types

Numeric1
Text1
Categorical1

Dataset

Description국가 수문기상 공동활용 재난안전 시스템 내 국토교통부 국토지리정보원 공간정보공동활용시스템 내 법정동코드정보 테이블 입니다.
Author국토교통부 국토지리정보원
URLhttps://www.data.go.kr/data/15123142/fileData.do

Alerts

법정동코드 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:20:59.704039
Analysis finished2023-12-12 05:21:00.355676
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

법정동코드
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3366248 × 109
Minimum1.1110106 × 109
Maximum5.013031 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T14:21:00.436136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110106 × 109
5-th percentile2.511011 × 109
Q14.223033 × 109
median4.5170111 × 109
Q34.775035 × 109
95-th percentile4.877537 × 109
Maximum5.013031 × 109
Range3.9020204 × 109
Interquartile range (IQR)5.52002 × 108

Descriptive statistics

Standard deviation7.4159524 × 108
Coefficient of variation (CV)0.17100747
Kurtosis7.7929776
Mean4.3366248 × 109
Median Absolute Deviation (MAD)2.5802595 × 108
Skewness-2.7704918
Sum4.3366248 × 1013
Variance5.4996349 × 1017
MonotonicityNot monotonic
2023-12-12T14:21:00.577699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4482033029 1
 
< 0.1%
4572003008 1
 
< 0.1%
4882025030 1
 
< 0.1%
4773011024 1
 
< 0.1%
1156000500 1
 
< 0.1%
4476037022 1
 
< 0.1%
4786037029 1
 
< 0.1%
2229010100 1
 
< 0.1%
4771035038 1
 
< 0.1%
4821011000 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1111010600 1
< 0.1%
1111010800 1
< 0.1%
1111011300 1
< 0.1%
1111011700 1
< 0.1%
1111012000 1
< 0.1%
1111012100 1
< 0.1%
1111012700 1
< 0.1%
1111013700 1
< 0.1%
1111014100 1
< 0.1%
1111014500 1
< 0.1%
ValueCountFrequency (%)
5013031030 1
< 0.1%
5013031022 1
< 0.1%
5013025927 1
< 0.1%
5013025926 1
< 0.1%
5013025924 1
< 0.1%
5013025300 1
< 0.1%
5013025031 1
< 0.1%
5013025030 1
< 0.1%
5013012000 1
< 0.1%
5013011700 1
< 0.1%

법정동명
Text

Distinct9969
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T14:21:01.114865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length16
Mean length15.0435
Min length4

Characters and Unicode

Total characters150435
Distinct characters393
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9938 ?
Unique (%)99.4%

Sample

1st row충청남도 서산군 팔봉면 진장리
2nd row경상북도 선산군 선산읍 완전리
3rd row전라남도 장성군 북상면 신성리
4th row경상북도 경주군 양남면 상계리
5th row경상남도 의창군 진동면 교동리
ValueCountFrequency (%)
경상북도 1954
 
5.2%
경기도 1421
 
3.8%
경상남도 1300
 
3.4%
충청남도 1181
 
3.1%
전라남도 1044
 
2.8%
전라북도 726
 
1.9%
충청북도 696
 
1.8%
강원도 621
 
1.6%
서울특별시 239
 
0.6%
중구 182
 
0.5%
Other values (7400) 28495
75.3%
2023-12-12T14:21:01.535569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27859
 
18.5%
도 9648
 
6.4%
리 6798
 
4.5%
면 6585
 
4.4%
군 6303
 
4.2%
경 5035
 
3.3%
남 4580
 
3.0%
시 4077
 
2.7%
북 4029
 
2.7%
동 3942
 
2.6%
Other values (383) 71579
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 122142
81.2%
Space Separator 27859
 
18.5%
Decimal Number 424
 
0.3%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 9648
 
7.9%
리 6798
 
5.6%
면 6585
 
5.4%
군 6303
 
5.2%
경 5035
 
4.1%
남 4580
 
3.7%
시 4077
 
3.3%
북 4029
 
3.3%
동 3942
 
3.2%
상 3755
 
3.1%
Other values (371) 67390
55.2%
Decimal Number
ValueCountFrequency (%)
2 141
33.3%
1 132
31.1%
3 76
17.9%
4 45
 
10.6%
5 16
 
3.8%
6 7
 
1.7%
7 4
 
0.9%
8 2
 
0.5%
9 1
 
0.2%
Space Separator
ValueCountFrequency (%)
27859
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 122132
81.2%
Common 28293
 
18.8%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 9648
 
7.9%
리 6798
 
5.6%
면 6585
 
5.4%
군 6303
 
5.2%
경 5035
 
4.1%
남 4580
 
3.8%
시 4077
 
3.3%
북 4029
 
3.3%
동 3942
 
3.2%
상 3755
 
3.1%
Other values (362) 67380
55.2%
Common
ValueCountFrequency (%)
27859
98.5%
2 141
 
0.5%
1 132
 
0.5%
3 76
 
0.3%
4 45
 
0.2%
5 16
 
0.1%
6 7
 
< 0.1%
( 5
 
< 0.1%
) 5
 
< 0.1%
7 4
 
< 0.1%
Other values (2) 3
 
< 0.1%
Han
ValueCountFrequency (%)
山 2
20.0%
華 1
10.0%
花 1
10.0%
洞 1
10.0%
乃 1
10.0%
岩 1
10.0%
基 1
10.0%
平 1
10.0%
沙 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 122132
81.2%
ASCII 28293
 
18.8%
CJK 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27859
98.5%
2 141
 
0.5%
1 132
 
0.5%
3 76
 
0.3%
4 45
 
0.2%
5 16
 
0.1%
6 7
 
< 0.1%
( 5
 
< 0.1%
) 5
 
< 0.1%
7 4
 
< 0.1%
Other values (2) 3
 
< 0.1%
Hangul
ValueCountFrequency (%)
도 9648
 
7.9%
리 6798
 
5.6%
면 6585
 
5.4%
군 6303
 
5.2%
경 5035
 
4.1%
남 4580
 
3.8%
시 4077
 
3.3%
북 4029
 
3.3%
동 3942
 
3.2%
상 3755
 
3.1%
Other values (362) 67380
55.2%
CJK
ValueCountFrequency (%)
山 2
20.0%
華 1
10.0%
花 1
10.0%
洞 1
10.0%
乃 1
10.0%
岩 1
10.0%
基 1
10.0%
平 1
10.0%
沙 1
10.0%

폐지여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
repl
5519 
exst
4481 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
repl 5519
55.2%
exst 4481
44.8%

Length

2023-12-12T14:21:01.662215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:21:01.801835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
repl 5519
55.2%
exst 4481
44.8%

Interactions

2023-12-12T14:21:00.109906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:21:01.902370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동코드폐지여부
법정동코드1.0000.222
폐지여부0.2221.000
2023-12-12T14:21:01.989389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동코드폐지여부
법정동코드1.0000.222
폐지여부0.2221.000

Missing values

2023-12-12T14:21:00.246396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:21:00.322479image/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

법정동코드법정동명폐지여부
319664482033029충청남도 서산군 팔봉면 진장리repl
408754787011039경상북도 선산군 선산읍 완전리repl
360114688003005전라남도 장성군 북상면 신성리repl
390404779532026경상북도 경주군 양남면 상계리repl
450454879036027경상남도 의창군 진동면 교동리repl
327284485040036충청남도 천원군 입장면 연곡리repl
89144476039026충청남도 부여군 충화면 가화리exst
186144824036028경상남도 사천시 곤명면 마곡리exst
201804889034022경상남도 합천군 야로면 청계리exst
455824889003006경상남도 합천군 합천면 내곡리repl
법정동코드법정동명폐지여부
28344146310700경기도 용인시 기흥구 공세동exst
408254787003007경상북도 선산군 선산면 포상동repl
8822714012300대구광역시 동구 각산동exst
322264483034000충청남도 당진군 정미면repl
203955011025301제주특별자치도 제주시 애월읍 용흥리exst
343344583042026전라북도 익산군 춘포면 창평리repl
174374784035034경상북도 성주군 금수면 영천리exst
373604773036021경상북도 의성군 가음면 장동repl
41834182032527경기도 가평군 청평면 삼회리exst
71864376040027충청북도 괴산군 소수면 옥현리exst