Overview

Dataset statistics

Number of variables6
Number of observations21
Missing cells4
Missing cells (%)3.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory54.3 B

Variable types

Text1
Unsupported5

Dataset

Description시군별지적재조사사업대상현황201510
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202583

Alerts

시군별 지적재조사 사업대상 현황 has 1 (4.8%) missing valuesMissing
Unnamed: 2 has 1 (4.8%) missing valuesMissing
Unnamed: 3 has 1 (4.8%) missing valuesMissing
Unnamed: 5 has 1 (4.8%) missing valuesMissing
Unnamed: 1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:13:52.304149
Analysis finished2024-03-14 02:13:52.577193
Duration0.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군별 지적재조사 사업대상 현황
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing1
Missing (%)4.8%
Memory size300.0 B
2024-03-14T11:13:52.693920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9
Min length2

Characters and Unicode

Total characters58
Distinct characters34
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st row구 분
2nd row합 계
3rd row전주시
4th row완산구
5th row덕진구
ValueCountFrequency (%)
구 1
 
4.5%
분 1
 
4.5%
고창군 1
 
4.5%
순창군 1
 
4.5%
임실군 1
 
4.5%
장수군 1
 
4.5%
무주군 1
 
4.5%
진안군 1
 
4.5%
완주군 1
 
4.5%
김제시 1
 
4.5%
Other values (12) 12
54.5%
2024-03-14T11:13:53.057481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 9
 
15.5%
시 6
 
10.3%
구 3
 
5.2%
주 3
 
5.2%
산 3
 
5.2%
창 2
 
3.4%
2
 
3.4%
안 2
 
3.4%
완 2
 
3.4%
진 2
 
3.4%
Other values (24) 24
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56
96.6%
Space Separator 2
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 9
 
16.1%
시 6
 
10.7%
구 3
 
5.4%
주 3
 
5.4%
산 3
 
5.4%
창 2
 
3.6%
안 2
 
3.6%
완 2
 
3.6%
진 2
 
3.6%
장 1
 
1.8%
Other values (23) 23
41.1%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56
96.6%
Common 2
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 9
 
16.1%
시 6
 
10.7%
구 3
 
5.4%
주 3
 
5.4%
산 3
 
5.4%
창 2
 
3.6%
안 2
 
3.6%
완 2
 
3.6%
진 2
 
3.6%
장 1
 
1.8%
Other values (23) 23
41.1%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56
96.6%
ASCII 2
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 9
 
16.1%
시 6
 
10.7%
구 3
 
5.4%
주 3
 
5.4%
산 3
 
5.4%
창 2
 
3.6%
안 2
 
3.6%
완 2
 
3.6%
진 2
 
3.6%
장 1
 
1.8%
Other values (23) 23
41.1%
ASCII
ValueCountFrequency (%)
2
100.0%

Unnamed: 1
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size300.0 B

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)4.8%
Memory size300.0 B

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)4.8%
Memory size300.0 B

Unnamed: 4
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size300.0 B

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)4.8%
Memory size300.0 B

Missing values

2024-03-14T11:13:52.372301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:13:52.453749image/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.
2024-03-14T11:13:52.530993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군별 지적재조사 사업대상 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
0구 분대상지 현황NaNNaN비 율(%)NaN
1<NA>지구수필지수(필지)대장면적(천㎢)필지면적
2합 계725555881842681915.15.3
3전주시924660772042633.99.9
4완산구40626342520738.65.4
5덕진구518397351521938.613.7
6군산시537354991244914.43.2
7익산시102013169511792633.823.2
8본청608771446627031.721.8
9함열412545515165637.325.3
시군별 지적재조사 사업대상 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
11남원시51030266158769.62.1
12김제시426570601925616.23.4
13완주군310290017273011.28.9
14진안군8713251921873132.7
15무주군960417682490328.33.9
16장수군5291514691089.11.7
17임실군2113274910.60.1
18순창군19218371126519.12.5
19고창군646418765066813.28.3
20부안군25218759106287.82.1