Overview

Dataset statistics

Number of variables19
Number of observations24
Missing cells63
Missing cells (%)13.8%
Duplicate rows1
Duplicate rows (%)4.2%
Total size in memory3.7 KiB
Average record size in memory157.5 B

Variable types

Text1
Unsupported18

Dataset

Description복사본03232016년지역별RD투자현황-공공데이터
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202423

Alerts

Dataset has 1 (4.2%) duplicate rowsDuplicates
Unnamed: 0 has 4 (16.7%) missing valuesMissing
2016년 지역별 R&D 투자현황 has 4 (16.7%) missing valuesMissing
Unnamed: 2 has 3 (12.5%) missing valuesMissing
Unnamed: 3 has 5 (20.8%) missing valuesMissing
Unnamed: 4 has 3 (12.5%) missing valuesMissing
Unnamed: 5 has 4 (16.7%) missing valuesMissing
Unnamed: 6 has 3 (12.5%) missing valuesMissing
Unnamed: 7 has 4 (16.7%) missing valuesMissing
Unnamed: 8 has 3 (12.5%) missing valuesMissing
Unnamed: 9 has 4 (16.7%) missing valuesMissing
Unnamed: 10 has 3 (12.5%) missing valuesMissing
Unnamed: 11 has 4 (16.7%) missing valuesMissing
Unnamed: 12 has 3 (12.5%) missing valuesMissing
구분 has 2 (8.3%) missing valuesMissing
국비 has 1 (4.2%) missing valuesMissing
지방비 has 3 (12.5%) missing valuesMissing
국비+지방비 has 4 (16.7%) missing valuesMissing
지방비/ (국비+지방비) has 3 (12.5%) missing valuesMissing
지방비/국비 has 3 (12.5%) missing valuesMissing
2016년 지역별 R&D 투자현황 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
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
국비 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지방비 is an unsupported type, check if it needs cleaning or further analysisUnsupported
국비+지방비 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지방비/ (국비+지방비) is an unsupported type, check if it needs cleaning or further analysisUnsupported
지방비/국비 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 01:08:40.260180
Analysis finished2024-03-14 01:08:41.170420
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing4
Missing (%)16.7%
Memory size324.0 B
2024-03-14T10:08:41.285101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.15
Min length2

Characters and Unicode

Total characters43
Distinct characters28
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 row구분
2nd row단위:억원
3rd row서울
4th row인천
5th row경기
ValueCountFrequency (%)
구분 1
 
5.0%
단위:억원 1
 
5.0%
세종 1
 
5.0%
제주 1
 
5.0%
경남 1
 
5.0%
경북 1
 
5.0%
전남 1
 
5.0%
전북 1
 
5.0%
충남 1
 
5.0%
충북 1
 
5.0%
Other values (10) 10
50.0%
2024-03-14T10:08:41.569677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 3
 
7.0%
경 3
 
7.0%
남 3
 
7.0%
북 3
 
7.0%
충 2
 
4.7%
주 2
 
4.7%
산 2
 
4.7%
대 2
 
4.7%
구 2
 
4.7%
울 2
 
4.7%
Other values (18) 19
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42
97.7%
Other Punctuation 1
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 3
 
7.1%
경 3
 
7.1%
남 3
 
7.1%
북 3
 
7.1%
충 2
 
4.8%
주 2
 
4.8%
산 2
 
4.8%
대 2
 
4.8%
구 2
 
4.8%
울 2
 
4.8%
Other values (17) 18
42.9%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42
97.7%
Common 1
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 3
 
7.1%
경 3
 
7.1%
남 3
 
7.1%
북 3
 
7.1%
충 2
 
4.8%
주 2
 
4.8%
산 2
 
4.8%
대 2
 
4.8%
구 2
 
4.8%
울 2
 
4.8%
Other values (17) 18
42.9%
Common
ValueCountFrequency (%)
: 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42
97.7%
ASCII 1
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 3
 
7.1%
경 3
 
7.1%
남 3
 
7.1%
북 3
 
7.1%
충 2
 
4.8%
주 2
 
4.8%
산 2
 
4.8%
대 2
 
4.8%
구 2
 
4.8%
울 2
 
4.8%
Other values (17) 18
42.9%
ASCII
ValueCountFrequency (%)
: 1
100.0%

2016년 지역별 R&D 투자현황
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4
Missing (%)16.7%
Memory size324.0 B

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)12.5%
Memory size324.0 B

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5
Missing (%)20.8%
Memory size324.0 B

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)12.5%
Memory size324.0 B

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4
Missing (%)16.7%
Memory size324.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)12.5%
Memory size324.0 B

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4
Missing (%)16.7%
Memory size324.0 B

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)12.5%
Memory size324.0 B

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4
Missing (%)16.7%
Memory size324.0 B

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)12.5%
Memory size324.0 B

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4
Missing (%)16.7%
Memory size324.0 B

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)12.5%
Memory size324.0 B

구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)8.3%
Memory size324.0 B

국비
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)4.2%
Memory size324.0 B

지방비
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)12.5%
Memory size324.0 B

국비+지방비
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4
Missing (%)16.7%
Memory size324.0 B

지방비/ (국비+지방비)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)12.5%
Memory size324.0 B

지방비/국비
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)12.5%
Memory size324.0 B

Missing values

2024-03-14T10:08:40.377099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:08:40.588100image/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.
2024-03-14T10:08:40.986968image/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

Unnamed: 02016년 지역별 R&D 투자현황Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12구분국비지방비국비+지방비지방비/ (국비+지방비)지방비/국비
0<NA>NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN전국18335630411649340.01840.0188
1<NA>NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN전북671224169530.03470.0359
2<NA>NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3구분국비(a)지방정부NaN대학NaN대기업/중견기업NaN중소기업NaN기타NaN합계NaN합계지방비/(국비+지방비)지방비 매칭비중국비지원 순위순지방비 매칭순위
4단위:억원현금현금(b)현물현금현물현금현물현금현물현금현물현금현물현금+현물b/(a+b)NaNab
5서울35925181120144751911305842267464754461354389105240.00471529
6인천438518121229361319435547202075477540.004516916
7경기23740823758268582141584430662232761789506268510.003117312
8대전56115278292612332468231115552142411153263137840.00591415
9부산657293NaN491134981112465316433472310570.017711611
Unnamed: 02016년 지역별 R&D 투자현황Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12구분국비지방비국비+지방비지방비/ (국비+지방비)지방비/국비
14충북496248314949341087832622602315748050.0124121014
15충남4843154113712949198142588697045199614470.0327810
16전북67122414124924559625741434144088220.03473124
17전남30572003225828284015914553033036060.09692147
18경북616544414315592156382653436671111473116426370.0644551
19경남972123018236419236712051315146716100717230.0286846
20제주141023-71314159039491171660.0269101615
21세종41701-222716--615210.0106131717
22합계183356303830182617092097492933331111256741740149681979134759NaNNaNNaNNaN
23<NA>NaN304130082417082097493033341111456751740149721979234764NaNNaNNaNNaN

Duplicate rows

Most frequently occurring

Unnamed: 0# duplicates
0<NA>4