Overview

Dataset statistics

Number of variables14
Number of observations33
Missing cells113
Missing cells (%)24.5%
Duplicate rows4
Duplicate rows (%)12.1%
Total size in memory3.7 KiB
Average record size in memory116.0 B

Variable types

Text2
Unsupported12

Dataset

Description직급별공무원정현원현황2016
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202122

Alerts

Dataset has 4 (12.1%) duplicate rowsDuplicates
전라북도 직급별 정.현원 has 24 (72.7%) missing valuesMissing
Unnamed: 1 has 6 (18.2%) missing valuesMissing
Unnamed: 3 has 1 (3.0%) missing valuesMissing
Unnamed: 5 has 1 (3.0%) missing valuesMissing
Unnamed: 6 has 7 (21.2%) missing valuesMissing
Unnamed: 7 has 13 (39.4%) missing valuesMissing
Unnamed: 8 has 7 (21.2%) missing valuesMissing
Unnamed: 9 has 13 (39.4%) missing valuesMissing
Unnamed: 10 has 7 (21.2%) missing valuesMissing
Unnamed: 11 has 13 (39.4%) missing valuesMissing
Unnamed: 12 has 7 (21.2%) missing valuesMissing
Unnamed: 13 has 14 (42.4%) missing valuesMissing
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
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 01:05:50.631608
Analysis finished2024-03-14 01:05:51.160353
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전라북도 직급별 정.현원
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing24
Missing (%)72.7%
Memory size396.0 B
2024-03-14T10:05:51.231897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.3333333
Min length1

Characters and Unicode

Total characters30
Distinct characters18
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

Unique9 ?
Unique (%)100.0%

Sample

1st row구 분
2nd row계
3rd row일반직
4th row연구지도
5th row소 방 직
ValueCountFrequency (%)
직 2
14.3%
구 1
 
7.1%
분 1
 
7.1%
계 1
 
7.1%
일반직 1
 
7.1%
연구지도 1
 
7.1%
소 1
 
7.1%
방 1
 
7.1%
기능직 1
 
7.1%
정 1
 
7.1%
Other values (3) 3
21.4%
2024-03-14T10:05:51.489137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
직 6
20.0%
5
16.7%
구 2
 
6.7%
계 2
 
6.7%
정 2
 
6.7%
방 1
 
3.3%
별 1
 
3.3%
무 1
 
3.3%
능 1
 
3.3%
기 1
 
3.3%
Other values (8) 8
26.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25
83.3%
Space Separator 5
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
직 6
24.0%
구 2
 
8.0%
계 2
 
8.0%
정 2
 
8.0%
방 1
 
4.0%
별 1
 
4.0%
무 1
 
4.0%
능 1
 
4.0%
기 1
 
4.0%
도 1
 
4.0%
Other values (7) 7
28.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25
83.3%
Common 5
 
16.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
직 6
24.0%
구 2
 
8.0%
계 2
 
8.0%
정 2
 
8.0%
방 1
 
4.0%
별 1
 
4.0%
무 1
 
4.0%
능 1
 
4.0%
기 1
 
4.0%
도 1
 
4.0%
Other values (7) 7
28.0%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25
83.3%
ASCII 5
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
직 6
24.0%
구 2
 
8.0%
계 2
 
8.0%
정 2
 
8.0%
방 1
 
4.0%
별 1
 
4.0%
무 1
 
4.0%
능 1
 
4.0%
기 1
 
4.0%
도 1
 
4.0%
Other values (7) 7
28.0%
ASCII
ValueCountFrequency (%)
5
100.0%

Unnamed: 1
Text

MISSING 

Distinct22
Distinct (%)81.5%
Missing6
Missing (%)18.2%
Memory size396.0 B
2024-03-14T10:05:51.663547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.8148148
Min length2

Characters and Unicode

Total characters76
Distinct characters24
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

Unique17 ?
Unique (%)63.0%

Sample

1st row고위공무원
2nd row1급
3rd row2급
4th row3급
5th row4급
ValueCountFrequency (%)
6급 2
 
7.4%
8급 2
 
7.4%
9급 2
 
7.4%
5급 2
 
7.4%
7급 2
 
7.4%
4급상당 1
 
3.7%
지도사 1
 
3.7%
8급상당 1
 
3.7%
7급상당 1
 
3.7%
6급상당 1
 
3.7%
Other values (12) 12
44.4%
2024-03-14T10:05:51.967301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
급 22
28.9%
당 7
 
9.2%
상 7
 
9.2%
6 3
 
3.9%
7 3
 
3.9%
8 3
 
3.9%
9 3
 
3.9%
5 3
 
3.9%
1 3
 
3.9%
도 2
 
2.6%
Other values (14) 20
26.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53
69.7%
Decimal Number 23
30.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
급 22
41.5%
당 7
 
13.2%
상 7
 
13.2%
도 2
 
3.8%
지 2
 
3.8%
사 2
 
3.8%
관 2
 
3.8%
구 2
 
3.8%
연 2
 
3.8%
고 1
 
1.9%
Other values (4) 4
 
7.5%
Decimal Number
ValueCountFrequency (%)
6 3
13.0%
7 3
13.0%
8 3
13.0%
9 3
13.0%
5 3
13.0%
1 3
13.0%
4 2
8.7%
3 1
 
4.3%
2 1
 
4.3%
0 1
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53
69.7%
Common 23
30.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
급 22
41.5%
당 7
 
13.2%
상 7
 
13.2%
도 2
 
3.8%
지 2
 
3.8%
사 2
 
3.8%
관 2
 
3.8%
구 2
 
3.8%
연 2
 
3.8%
고 1
 
1.9%
Other values (4) 4
 
7.5%
Common
ValueCountFrequency (%)
6 3
13.0%
7 3
13.0%
8 3
13.0%
9 3
13.0%
5 3
13.0%
1 3
13.0%
4 2
8.7%
3 1
 
4.3%
2 1
 
4.3%
0 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53
69.7%
ASCII 23
30.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
급 22
41.5%
당 7
 
13.2%
상 7
 
13.2%
도 2
 
3.8%
지 2
 
3.8%
사 2
 
3.8%
관 2
 
3.8%
구 2
 
3.8%
연 2
 
3.8%
고 1
 
1.9%
Other values (4) 4
 
7.5%
ASCII
ValueCountFrequency (%)
6 3
13.0%
7 3
13.0%
8 3
13.0%
9 3
13.0%
5 3
13.0%
1 3
13.0%
4 2
8.7%
3 1
 
4.3%
2 1
 
4.3%
0 1
 
4.3%

Unnamed: 2
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size396.0 B

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)3.0%
Memory size396.0 B

Unnamed: 4
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size396.0 B

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)3.0%
Memory size396.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7
Missing (%)21.2%
Memory size396.0 B

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing13
Missing (%)39.4%
Memory size396.0 B

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7
Missing (%)21.2%
Memory size396.0 B

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing13
Missing (%)39.4%
Memory size396.0 B

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7
Missing (%)21.2%
Memory size396.0 B

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing13
Missing (%)39.4%
Memory size396.0 B

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7
Missing (%)21.2%
Memory size396.0 B

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing14
Missing (%)42.4%
Memory size396.0 B

Correlations

2024-03-14T10:05:52.036312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전라북도 직급별 정.현원Unnamed: 1
전라북도 직급별 정.현원1.0001.000
Unnamed: 11.0001.000

Missing values

2024-03-14T10:05:50.782284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:05:50.925400image/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.
2024-03-14T10:05:51.055465image/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

전라북도 직급별 정.현원Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13
0구 분<NA>2011년NaN2012년NaN2013년NaN2014년NaN2015년NaN2016년NaN
1<NA><NA>현원여성현원여성현원여성현원여성현원여성현원여성
2계<NA>155144818157825012154855016155905214158855486161565772
3일반직고위공무원303030303030
4<NA>1급000000000000
5<NA>2급202020202020
6<NA>3급120130121141151152
7<NA>4급1254124712681318138101399
8<NA>5급841548525585965867788928090091
9<NA>6급299252432697633615935375811193948130741331458
전라북도 직급별 정.현원Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13
23<NA>10급19000NaNNaNNaNNaNNaNNaNNaNNaN
24정 무 직<NA>150150140150140150
25별정직1급상당10101NaN1NaN1NaN1NaN
26<NA>4급상당30302NaN2NaN1NaN2NaN
27<NA>5급상당61512NaN2NaN4NaN4NaN
28<NA>6급상당229201471313NaN12NaN12NaN12NaN
29<NA>7급상당64215313317171162
30<NA>8급상당84651131110NaN
31<NA>9급상당00001NaN1NaN0NaN1NaN
32계약직<NA>2479225089NaNNaNNaNNaNNaNNaNNaNNaN

Duplicate rows

Most frequently occurring

전라북도 직급별 정.현원Unnamed: 1# duplicates
0<NA>6급2
1<NA>7급2
2<NA>8급2
3<NA>9급2