Overview

Dataset statistics

Number of variables12
Number of observations24
Missing cells19
Missing cells (%)6.6%
Duplicate rows1
Duplicate rows (%)4.2%
Total size in memory2.4 KiB
Average record size in memory101.5 B

Variable types

Text1
Unsupported11

Dataset

Description도립여성중고졸업생상급학교진학현황20203
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=203185

Alerts

Dataset has 1 (4.2%) duplicate rowsDuplicates
전라북도립여성중고등학교 졸업생 상급학교 진급률 has 2 (8.3%) missing valuesMissing
Unnamed: 1 has 1 (4.2%) missing valuesMissing
Unnamed: 2 has 2 (8.3%) missing valuesMissing
Unnamed: 3 has 2 (8.3%) missing valuesMissing
Unnamed: 4 has 1 (4.2%) missing valuesMissing
Unnamed: 5 has 2 (8.3%) missing valuesMissing
Unnamed: 6 has 1 (4.2%) missing valuesMissing
Unnamed: 7 has 2 (8.3%) missing valuesMissing
Unnamed: 8 has 2 (8.3%) missing valuesMissing
Unnamed: 10 has 2 (8.3%) missing valuesMissing
Unnamed: 11 has 2 (8.3%) 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
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

Reproduction

Analysis started2024-03-14 02:20:17.389109
Analysis finished2024-03-14 02:20:18.200601
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전라북도립여성중고등학교 졸업생 상급학교 진급률
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing2
Missing (%)8.3%
Memory size324.0 B
2024-03-14T11:20:18.288309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.2727273
Min length1

Characters and Unicode

Total characters204
Distinct characters18
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row구 분
2nd row계
3rd row제20회(2020)
4th row제19회(2019)
5th row제18회(2018)
ValueCountFrequency (%)
제 9
28.1%
제12회(2012 1
 
3.1%
계 1
 
3.1%
제11회(2011 1
 
3.1%
2회(2002 1
 
3.1%
3회(2003 1
 
3.1%
4회(2004 1
 
3.1%
5회(2005 1
 
3.1%
6회(2006 1
 
3.1%
7회(2007 1
 
3.1%
Other values (14) 14
43.8%
2024-03-14T11:20:18.521977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33
16.2%
2 26
12.7%
1 24
11.8%
제 20
9.8%
회 20
9.8%
( 20
9.8%
) 20
9.8%
10
 
4.9%
5 4
 
2.0%
3 4
 
2.0%
Other values (8) 23
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 111
54.4%
Other Letter 43
 
21.1%
Open Punctuation 20
 
9.8%
Close Punctuation 20
 
9.8%
Space Separator 10
 
4.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33
29.7%
2 26
23.4%
1 24
21.6%
5 4
 
3.6%
3 4
 
3.6%
4 4
 
3.6%
8 4
 
3.6%
6 4
 
3.6%
7 4
 
3.6%
9 4
 
3.6%
Other Letter
ValueCountFrequency (%)
제 20
46.5%
회 20
46.5%
구 1
 
2.3%
계 1
 
2.3%
분 1
 
2.3%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 161
78.9%
Hangul 43
 
21.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 33
20.5%
2 26
16.1%
1 24
14.9%
( 20
12.4%
) 20
12.4%
10
 
6.2%
5 4
 
2.5%
3 4
 
2.5%
4 4
 
2.5%
8 4
 
2.5%
Other values (3) 12
 
7.5%
Hangul
ValueCountFrequency (%)
제 20
46.5%
회 20
46.5%
구 1
 
2.3%
계 1
 
2.3%
분 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 161
78.9%
Hangul 43
 
21.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33
20.5%
2 26
16.1%
1 24
14.9%
( 20
12.4%
) 20
12.4%
10
 
6.2%
5 4
 
2.5%
3 4
 
2.5%
4 4
 
2.5%
8 4
 
2.5%
Other values (3) 12
 
7.5%
Hangul
ValueCountFrequency (%)
제 20
46.5%
회 20
46.5%
구 1
 
2.3%
계 1
 
2.3%
분 1
 
2.3%

Unnamed: 1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Unnamed: 9
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size324.0 B

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Missing values

2024-03-14T11:20:17.796212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:20:17.931082image/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.
2024-03-14T11:20:18.083076image/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

전라북도립여성중고등학교 졸업생 상급학교 진급률Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
0구 분졸 업 생NaNNaN상급학교 진학NaNNaNNaNNaN진급률(%)NaN진급률
1<NA>계중고계고대학NaNNaN고등대학NaN
2<NA>NaNNaNNaNNaNNaN계4년제2년제학교NaNNaN
3계14377367019915824091152940.7907610.58345268.71
4제20회(2020)5421333418166100.8571430.48484867.1
5제19회(2019)6326374123182160.8846150.48648668.56
6제18회(2018)5623333220122100.8695650.36363661.66
7제17회(2017)7035354429153120.8285710.42857162.86
8제16회(2016)7036345126258170.7222220.73529472.88
9제15회(2015)7439355428267190.7179490.74285773.04
전라북도립여성중고등학교 졸업생 상급학교 진급률Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
14제10회(2010)7436385928314270.7777780.81578979.68
15제 9회(2009)6833353722154110.6666670.42857154.76
16제 8회(2008)6835334220224180.5714290.66666761.9
17제 7회(2007)9047436437277200.7872340.62790770.76
18제 6회(2006)7839395132197120.8205130.48717965.38
19제 5회(2005)8548376946237160.9583330.62162279
20제 4회(2004)7440345730279180.750.79411877.21
21제 3회(2003)6845235237151140.8222220.65217473.72
22제 2회(2002)7145265545106410.38461569.23
23제 1회(2001)7842364730171160.7142860.47222259.33

Duplicate rows

Most frequently occurring

전라북도립여성중고등학교 졸업생 상급학교 진급률# duplicates
0<NA>2