Overview

Dataset statistics

Number of variables14
Number of observations33
Missing cells113
Missing cells (%)24.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory116.0 B

Variable types

Text14

Dataset

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

Alerts

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

Reproduction

Analysis started2024-03-14 01:05:42.597118
Analysis finished2024-03-14 01:05:43.553469
Duration0.96 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
2024-03-14T10:05:43.617326image/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%
2024-03-14T10:05:43.922119image/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
2024-03-14T10:05:44.075071image/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%
2024-03-14T10:05:44.344665image/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
Text

Distinct30
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-03-14T10:05:44.486901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)84.8%

Sample

1st row2011년
2nd row현원
3rd row15,514
4th row3
5th row0
ValueCountFrequency (%)
0 3
 
9.1%
3 2
 
6.1%
2011년 1
 
3.0%
407 1
 
3.0%
8 1
 
3.0%
64 1
 
3.0%
229 1
 
3.0%
6 1
 
3.0%
1 1
 
3.0%
15 1
 
3.0%
Other values (20) 20
60.6%
2024-03-14T10:05:44.722759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
19.3%
2 11
13.3%
5 10
12.0%
4 10
12.0%
0 8
9.6%
9 7
8.4%
7 6
 
7.2%
6 5
 
6.0%
3 3
 
3.6%
, 2
 
2.4%
Other values (4) 5
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
94.0%
Other Letter 3
 
3.6%
Other Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
20.5%
2 11
14.1%
5 10
12.8%
4 10
12.8%
0 8
10.3%
9 7
9.0%
7 6
 
7.7%
6 5
 
6.4%
3 3
 
3.8%
8 2
 
2.6%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
20.0%
2 11
13.8%
5 10
12.5%
4 10
12.5%
0 8
10.0%
9 7
8.8%
7 6
 
7.5%
6 5
 
6.2%
3 3
 
3.8%
, 2
 
2.5%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
20.0%
2 11
13.8%
5 10
12.5%
4 10
12.5%
0 8
10.0%
9 7
8.8%
7 6
 
7.5%
6 5
 
6.2%
3 3
 
3.8%
, 2
 
2.5%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%

Unnamed: 3
Text

MISSING 

Distinct21
Distinct (%)65.6%
Missing1
Missing (%)3.0%
Memory size396.0 B
2024-03-14T10:05:44.838729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length1.96875
Min length1

Characters and Unicode

Total characters63
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)56.2%

Sample

1st row여성
2nd row4,818
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 10
31.2%
4 2
 
6.2%
1 2
 
6.2%
119 1
 
3.1%
105 1
 
3.1%
21 1
 
3.1%
201 1
 
3.1%
204 1
 
3.1%
297 1
 
3.1%
133 1
 
3.1%
Other values (11) 11
34.4%
2024-03-14T10:05:45.063159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
23.8%
1 10
15.9%
2 10
15.9%
4 7
11.1%
9 6
 
9.5%
5 4
 
6.3%
3 3
 
4.8%
8 2
 
3.2%
7 2
 
3.2%
, 1
 
1.6%
Other values (3) 3
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
95.2%
Other Letter 2
 
3.2%
Other Punctuation 1
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
25.0%
1 10
16.7%
2 10
16.7%
4 7
11.7%
9 6
 
10.0%
5 4
 
6.7%
3 3
 
5.0%
8 2
 
3.3%
7 2
 
3.3%
6 1
 
1.7%
Other Letter
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61
96.8%
Hangul 2
 
3.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
24.6%
1 10
16.4%
2 10
16.4%
4 7
11.5%
9 6
 
9.8%
5 4
 
6.6%
3 3
 
4.9%
8 2
 
3.3%
7 2
 
3.3%
, 1
 
1.6%
Hangul
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61
96.8%
Hangul 2
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
24.6%
1 10
16.4%
2 10
16.4%
4 7
11.5%
9 6
 
9.8%
5 4
 
6.6%
3 3
 
4.9%
8 2
 
3.3%
7 2
 
3.3%
, 1
 
1.6%
Hangul
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%

Unnamed: 4
Text

Distinct29
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-03-14T10:05:45.189611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4848485
Min length1

Characters and Unicode

Total characters82
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)81.8%

Sample

1st row2012년
2nd row현원
3rd row15,782
4th row3
5th row0
ValueCountFrequency (%)
0 4
 
12.1%
3 2
 
6.1%
1,818 1
 
3.0%
2012년 1
 
3.0%
407 1
 
3.0%
6 1
 
3.0%
53 1
 
3.0%
47 1
 
3.0%
5 1
 
3.0%
1 1
 
3.0%
Other values (19) 19
57.6%
2024-03-14T10:05:45.686758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
15.9%
2 11
13.4%
4 11
13.4%
0 8
9.8%
8 8
9.8%
5 8
9.8%
3 6
7.3%
7 6
7.3%
6 4
 
4.9%
, 2
 
2.4%
Other values (4) 5
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
93.9%
Other Letter 3
 
3.7%
Other Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
16.9%
2 11
14.3%
4 11
14.3%
0 8
10.4%
8 8
10.4%
5 8
10.4%
3 6
7.8%
7 6
7.8%
6 4
 
5.2%
9 2
 
2.6%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
16.5%
2 11
13.9%
4 11
13.9%
0 8
10.1%
8 8
10.1%
5 8
10.1%
3 6
7.6%
7 6
7.6%
6 4
 
5.1%
, 2
 
2.5%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
16.5%
2 11
13.9%
4 11
13.9%
0 8
10.1%
8 8
10.1%
5 8
10.1%
3 6
7.6%
7 6
7.6%
6 4
 
5.1%
, 2
 
2.5%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%

Unnamed: 5
Text

MISSING 

Distinct21
Distinct (%)65.6%
Missing1
Missing (%)3.0%
Memory size396.0 B
2024-03-14T10:05:45.794205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length1.9375
Min length1

Characters and Unicode

Total characters62
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)56.2%

Sample

1st row여성
2nd row5,012
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 10
31.2%
7 2
 
6.2%
13 2
 
6.2%
130 1
 
3.1%
110 1
 
3.1%
5 1
 
3.1%
1 1
 
3.1%
122 1
 
3.1%
199 1
 
3.1%
185 1
 
3.1%
Other values (11) 11
34.4%
2024-03-14T10:05:46.109191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
22.6%
1 12
19.4%
7 6
9.7%
9 6
9.7%
3 5
 
8.1%
5 5
 
8.1%
2 5
 
8.1%
8 3
 
4.8%
4 2
 
3.2%
, 1
 
1.6%
Other values (3) 3
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
95.2%
Other Letter 2
 
3.2%
Other Punctuation 1
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
23.7%
1 12
20.3%
7 6
10.2%
9 6
10.2%
3 5
 
8.5%
5 5
 
8.5%
2 5
 
8.5%
8 3
 
5.1%
4 2
 
3.4%
6 1
 
1.7%
Other Letter
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
96.8%
Hangul 2
 
3.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
23.3%
1 12
20.0%
7 6
10.0%
9 6
10.0%
3 5
 
8.3%
5 5
 
8.3%
2 5
 
8.3%
8 3
 
5.0%
4 2
 
3.3%
, 1
 
1.7%
Hangul
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
96.8%
Hangul 2
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
23.3%
1 12
20.0%
7 6
10.0%
9 6
10.0%
3 5
 
8.3%
5 5
 
8.3%
2 5
 
8.3%
8 3
 
5.0%
4 2
 
3.3%
, 1
 
1.7%
Hangul
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct21
Distinct (%)80.8%
Missing7
Missing (%)21.2%
Memory size396.0 B
2024-03-14T10:05:46.235679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5
Min length1

Characters and Unicode

Total characters65
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)69.2%

Sample

1st row2013년
2nd row현원
3rd row15,485
4th row3
5th row0
ValueCountFrequency (%)
2 3
 
11.5%
1 3
 
11.5%
3 2
 
7.7%
2208 1
 
3.8%
2013년 1
 
3.8%
1058 1
 
3.8%
14 1
 
3.8%
1,812 1
 
3.8%
406 1
 
3.8%
44 1
 
3.8%
Other values (11) 11
42.3%
2024-03-14T10:05:46.466506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
24.6%
2 10
15.4%
5 7
10.8%
0 6
 
9.2%
3 5
 
7.7%
4 5
 
7.7%
8 5
 
7.7%
6 3
 
4.6%
, 2
 
3.1%
7 2
 
3.1%
Other values (4) 4
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
92.3%
Other Letter 3
 
4.6%
Other Punctuation 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
26.7%
2 10
16.7%
5 7
11.7%
0 6
 
10.0%
3 5
 
8.3%
4 5
 
8.3%
8 5
 
8.3%
6 3
 
5.0%
7 2
 
3.3%
9 1
 
1.7%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62
95.4%
Hangul 3
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
25.8%
2 10
16.1%
5 7
11.3%
0 6
 
9.7%
3 5
 
8.1%
4 5
 
8.1%
8 5
 
8.1%
6 3
 
4.8%
, 2
 
3.2%
7 2
 
3.2%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
95.4%
Hangul 3
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
25.8%
2 10
16.1%
5 7
11.3%
0 6
 
9.7%
3 5
 
8.1%
4 5
 
8.1%
8 5
 
8.1%
6 3
 
4.8%
, 2
 
3.2%
7 2
 
3.2%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct15
Distinct (%)75.0%
Missing13
Missing (%)39.4%
Memory size396.0 B
2024-03-14T10:05:46.585483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4.5
Mean length2
Min length1

Characters and Unicode

Total characters40
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)65.0%

Sample

1st row여성
2nd row5,016
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 4
20.0%
1 3
15.0%
여성 1
 
5.0%
5,016 1
 
5.0%
8 1
 
5.0%
65 1
 
5.0%
935 1
 
5.0%
2191 1
 
5.0%
959 1
 
5.0%
551 1
 
5.0%
Other values (5) 5
25.0%
2024-03-14T10:05:46.805031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
27.5%
5 7
17.5%
0 6
15.0%
9 4
 
10.0%
6 2
 
5.0%
3 2
 
5.0%
2 2
 
5.0%
여 1
 
2.5%
성 1
 
2.5%
, 1
 
2.5%
Other values (3) 3
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37
92.5%
Other Letter 2
 
5.0%
Other Punctuation 1
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
29.7%
5 7
18.9%
0 6
16.2%
9 4
 
10.8%
6 2
 
5.4%
3 2
 
5.4%
2 2
 
5.4%
8 1
 
2.7%
4 1
 
2.7%
7 1
 
2.7%
Other Letter
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38
95.0%
Hangul 2
 
5.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
28.9%
5 7
18.4%
0 6
15.8%
9 4
 
10.5%
6 2
 
5.3%
3 2
 
5.3%
2 2
 
5.3%
, 1
 
2.6%
8 1
 
2.6%
4 1
 
2.6%
Hangul
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38
95.0%
Hangul 2
 
5.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
28.9%
5 7
18.4%
0 6
15.8%
9 4
 
10.5%
6 2
 
5.3%
3 2
 
5.3%
2 2
 
5.3%
, 1
 
2.6%
8 1
 
2.6%
4 1
 
2.6%
Hangul
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%

Unnamed: 8
Text

MISSING 

Distinct22
Distinct (%)84.6%
Missing7
Missing (%)21.2%
Memory size396.0 B
2024-03-14T10:05:46.931424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5
Min length1

Characters and Unicode

Total characters65
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)73.1%

Sample

1st row2014년
2nd row현원
3rd row15,590
4th row3
5th row0
ValueCountFrequency (%)
2 3
 
11.5%
1 2
 
7.7%
3 2
 
7.7%
175 1
 
3.8%
2014년 1
 
3.8%
30 1
 
3.8%
12 1
 
3.8%
15 1
 
3.8%
1,931 1
 
3.8%
380 1
 
3.8%
Other values (12) 12
46.2%
2024-03-14T10:05:47.155151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
21.5%
2 9
13.8%
3 8
12.3%
0 6
9.2%
7 6
9.2%
5 5
 
7.7%
4 5
 
7.7%
9 3
 
4.6%
8 3
 
4.6%
, 2
 
3.1%
Other values (4) 4
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
92.3%
Other Letter 3
 
4.6%
Other Punctuation 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
23.3%
2 9
15.0%
3 8
13.3%
0 6
10.0%
7 6
10.0%
5 5
 
8.3%
4 5
 
8.3%
9 3
 
5.0%
8 3
 
5.0%
6 1
 
1.7%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62
95.4%
Hangul 3
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
22.6%
2 9
14.5%
3 8
12.9%
0 6
9.7%
7 6
9.7%
5 5
 
8.1%
4 5
 
8.1%
9 3
 
4.8%
8 3
 
4.8%
, 2
 
3.2%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
95.4%
Hangul 3
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
22.6%
2 9
14.5%
3 8
12.9%
0 6
9.7%
7 6
9.7%
5 5
 
8.1%
4 5
 
8.1%
9 3
 
4.8%
8 3
 
4.8%
, 2
 
3.2%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct15
Distinct (%)75.0%
Missing13
Missing (%)39.4%
Memory size396.0 B
2024-03-14T10:05:47.259356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4.5
Mean length2.1
Min length1

Characters and Unicode

Total characters42
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)65.0%

Sample

1st row여성
2nd row5,214
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 4
20.0%
1 3
15.0%
여성 1
 
5.0%
5,214 1
 
5.0%
8 1
 
5.0%
78 1
 
5.0%
1119 1
 
5.0%
2081 1
 
5.0%
1049 1
 
5.0%
548 1
 
5.0%
Other values (5) 5
25.0%
2024-03-14T10:05:47.490288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
28.6%
0 9
21.4%
5 4
 
9.5%
8 4
 
9.5%
4 3
 
7.1%
2 2
 
4.8%
9 2
 
4.8%
여 1
 
2.4%
성 1
 
2.4%
, 1
 
2.4%
Other values (3) 3
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39
92.9%
Other Letter 2
 
4.8%
Other Punctuation 1
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
30.8%
0 9
23.1%
5 4
 
10.3%
8 4
 
10.3%
4 3
 
7.7%
2 2
 
5.1%
9 2
 
5.1%
7 1
 
2.6%
3 1
 
2.6%
6 1
 
2.6%
Other Letter
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40
95.2%
Hangul 2
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
30.0%
0 9
22.5%
5 4
 
10.0%
8 4
 
10.0%
4 3
 
7.5%
2 2
 
5.0%
9 2
 
5.0%
, 1
 
2.5%
7 1
 
2.5%
3 1
 
2.5%
Hangul
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40
95.2%
Hangul 2
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
30.0%
0 9
22.5%
5 4
 
10.0%
8 4
 
10.0%
4 3
 
7.5%
2 2
 
5.0%
9 2
 
5.0%
, 1
 
2.5%
7 1
 
2.5%
3 1
 
2.5%
Hangul
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%

Unnamed: 10
Text

MISSING 

Distinct23
Distinct (%)88.5%
Missing7
Missing (%)21.2%
Memory size396.0 B
2024-03-14T10:05:47.628085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5384615
Min length1

Characters and Unicode

Total characters66
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)80.8%

Sample

1st row2015년
2nd row현원
3rd row15,885
4th row3
5th row0
ValueCountFrequency (%)
1 3
 
11.5%
0 2
 
7.7%
1277 1
 
3.8%
2015년 1
 
3.8%
33 1
 
3.8%
12 1
 
3.8%
4 1
 
3.8%
14 1
 
3.8%
1,918 1
 
3.8%
379 1
 
3.8%
Other values (13) 13
50.0%
2024-03-14T10:05:47.880521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
22.7%
8 7
10.6%
5 6
 
9.1%
3 6
 
9.1%
2 6
 
9.1%
9 6
 
9.1%
4 6
 
9.1%
7 6
 
9.1%
0 3
 
4.5%
, 2
 
3.0%
Other values (3) 3
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
92.4%
Other Letter 3
 
4.5%
Other Punctuation 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
24.6%
8 7
11.5%
5 6
 
9.8%
3 6
 
9.8%
2 6
 
9.8%
9 6
 
9.8%
4 6
 
9.8%
7 6
 
9.8%
0 3
 
4.9%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
23.8%
8 7
11.1%
5 6
 
9.5%
3 6
 
9.5%
2 6
 
9.5%
9 6
 
9.5%
4 6
 
9.5%
7 6
 
9.5%
0 3
 
4.8%
, 2
 
3.2%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
23.8%
8 7
11.1%
5 6
 
9.5%
3 6
 
9.5%
2 6
 
9.5%
9 6
 
9.5%
4 6
 
9.5%
7 6
 
9.5%
0 3
 
4.8%
, 2
 
3.2%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%

Unnamed: 11
Text

MISSING 

Distinct15
Distinct (%)75.0%
Missing13
Missing (%)39.4%
Memory size396.0 B
2024-03-14T10:05:48.004333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.15
Min length1

Characters and Unicode

Total characters43
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)65.0%

Sample

1st row여성
2nd row5,486
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 4
20.0%
1 3
15.0%
여성 1
 
5.0%
5,486 1
 
5.0%
10 1
 
5.0%
80 1
 
5.0%
1307 1
 
5.0%
2042 1
 
5.0%
1058 1
 
5.0%
661 1
 
5.0%
Other values (5) 5
25.0%
2024-03-14T10:05:48.281135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
23.3%
1 9
20.9%
5 4
 
9.3%
4 3
 
7.0%
8 3
 
7.0%
6 3
 
7.0%
9 3
 
7.0%
3 2
 
4.7%
2 2
 
4.7%
여 1
 
2.3%
Other values (3) 3
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40
93.0%
Other Letter 2
 
4.7%
Other Punctuation 1
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
25.0%
1 9
22.5%
5 4
 
10.0%
4 3
 
7.5%
8 3
 
7.5%
6 3
 
7.5%
9 3
 
7.5%
3 2
 
5.0%
2 2
 
5.0%
7 1
 
2.5%
Other Letter
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41
95.3%
Hangul 2
 
4.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
24.4%
1 9
22.0%
5 4
 
9.8%
4 3
 
7.3%
8 3
 
7.3%
6 3
 
7.3%
9 3
 
7.3%
3 2
 
4.9%
2 2
 
4.9%
, 1
 
2.4%
Hangul
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41
95.3%
Hangul 2
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
24.4%
1 9
22.0%
5 4
 
9.8%
4 3
 
7.3%
8 3
 
7.3%
6 3
 
7.3%
9 3
 
7.3%
3 2
 
4.9%
2 2
 
4.9%
, 1
 
2.4%
Hangul
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%

Unnamed: 12
Text

MISSING 

Distinct22
Distinct (%)84.6%
Missing7
Missing (%)21.2%
Memory size396.0 B
2024-03-14T10:05:48.441144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5
Min length1

Characters and Unicode

Total characters65
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)69.2%

Sample

1st row2016년
2nd row현원
3rd row16,156
4th row3
5th row0
ValueCountFrequency (%)
2 2
 
7.7%
1 2
 
7.7%
0 2
 
7.7%
15 2
 
7.7%
2142 1
 
3.8%
2016년 1
 
3.8%
37 1
 
3.8%
12 1
 
3.8%
4 1
 
3.8%
1,980 1
 
3.8%
Other values (12) 12
46.2%
2024-03-14T10:05:48.683812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
21.5%
2 7
10.8%
3 7
10.8%
0 6
9.2%
4 6
9.2%
6 6
9.2%
5 4
 
6.2%
8 4
 
6.2%
7 3
 
4.6%
9 3
 
4.6%
Other values (4) 5
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
92.3%
Other Letter 3
 
4.6%
Other Punctuation 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
23.3%
2 7
11.7%
3 7
11.7%
0 6
10.0%
4 6
10.0%
6 6
10.0%
5 4
 
6.7%
8 4
 
6.7%
7 3
 
5.0%
9 3
 
5.0%
Other Letter
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62
95.4%
Hangul 3
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
22.6%
2 7
11.3%
3 7
11.3%
0 6
9.7%
4 6
9.7%
6 6
9.7%
5 4
 
6.5%
8 4
 
6.5%
7 3
 
4.8%
9 3
 
4.8%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
95.4%
Hangul 3
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
22.6%
2 7
11.3%
3 7
11.3%
0 6
9.7%
4 6
9.7%
6 6
9.7%
5 4
 
6.5%
8 4
 
6.5%
7 3
 
4.8%
9 3
 
4.8%
Hangul
ValueCountFrequency (%)
현 1
33.3%
원 1
33.3%
년 1
33.3%

Unnamed: 13
Text

MISSING 

Distinct14
Distinct (%)73.7%
Missing14
Missing (%)42.4%
Memory size396.0 B
2024-03-14T10:05:48.786682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1578947
Min length1

Characters and Unicode

Total characters41
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)63.2%

Sample

1st row여성
2nd row5,772
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 4
21.1%
2 3
15.8%
여성 1
 
5.3%
5,772 1
 
5.3%
9 1
 
5.3%
91 1
 
5.3%
1458 1
 
5.3%
2002 1
 
5.3%
1074 1
 
5.3%
794 1
 
5.3%
Other values (4) 4
21.1%
2024-03-14T10:05:49.035317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8
19.5%
2 7
17.1%
5 5
12.2%
1 5
12.2%
7 4
9.8%
9 4
9.8%
4 4
9.8%
여 1
 
2.4%
성 1
 
2.4%
, 1
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38
92.7%
Other Letter 2
 
4.9%
Other Punctuation 1
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8
21.1%
2 7
18.4%
5 5
13.2%
1 5
13.2%
7 4
10.5%
9 4
10.5%
4 4
10.5%
8 1
 
2.6%
Other Letter
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39
95.1%
Hangul 2
 
4.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8
20.5%
2 7
17.9%
5 5
12.8%
1 5
12.8%
7 4
10.3%
9 4
10.3%
4 4
10.3%
, 1
 
2.6%
8 1
 
2.6%
Hangul
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39
95.1%
Hangul 2
 
4.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8
20.5%
2 7
17.9%
5 5
12.8%
1 5
12.8%
7 4
10.3%
9 4
10.3%
4 4
10.3%
, 1
 
2.6%
8 1
 
2.6%
Hangul
ValueCountFrequency (%)
여 1
50.0%
성 1
50.0%

Correlations

2024-03-14T10:05:49.118578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전라북도 직급별 정.현원Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13
전라북도 직급별 정.현원1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 11.0001.0000.8310.0000.7020.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 21.0000.8311.0001.0001.0001.0000.9701.0000.9701.0000.9891.0000.9651.000
Unnamed: 31.0000.0001.0001.0001.0000.9980.9710.9960.9840.9960.9900.9960.9940.990
Unnamed: 41.0000.7021.0001.0001.0001.0000.9701.0000.9701.0000.9891.0000.9651.000
Unnamed: 51.0000.0001.0000.9981.0001.0000.9540.9920.9630.9920.9790.9920.9890.991
Unnamed: 61.0001.0000.9700.9710.9700.9541.0000.9850.9960.9850.9800.9850.9730.984
Unnamed: 71.0001.0001.0000.9961.0000.9920.9851.0000.9851.0001.0001.0000.9791.000
Unnamed: 81.0001.0000.9700.9840.9700.9630.9960.9851.0000.9850.9660.9850.9921.000
Unnamed: 91.0001.0001.0000.9961.0000.9920.9851.0000.9851.0001.0001.0000.9791.000
Unnamed: 101.0001.0000.9890.9900.9890.9790.9801.0000.9661.0001.0001.0000.9721.000
Unnamed: 111.0001.0001.0000.9961.0000.9920.9851.0000.9851.0001.0001.0000.9791.000
Unnamed: 121.0001.0000.9650.9940.9650.9890.9730.9790.9920.9790.9720.9791.0000.984
Unnamed: 131.0001.0001.0000.9901.0000.9910.9841.0001.0001.0001.0001.0000.9841.000

Missing values

2024-03-14T10:05:43.107150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:05:43.271805image/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.
2024-03-14T10:05:43.423009image/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>2011년<NA>2012년<NA>2013년<NA>2014년<NA>2015년<NA>2016년<NA>
1<NA><NA>현원여성현원여성현원여성현원여성현원여성현원여성
2계<NA>15,5144,81815,7825,01215,4855,01615,5905,21415,8855,48616,1565,772
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>10급19000<NA><NA><NA><NA><NA><NA><NA><NA>
24정 무 직<NA>150150140150140150
25별정직1급상당10101<NA>1<NA>1<NA>1<NA>
26<NA>4급상당30302<NA>2<NA>1<NA>2<NA>
27<NA>5급상당61512<NA>2<NA>4<NA>4<NA>
28<NA>6급상당229201471313<NA>12<NA>12<NA>12<NA>
29<NA>7급상당64215313317171162
30<NA>8급상당84651131110<NA>
31<NA>9급상당00001<NA>1<NA>0<NA>1<NA>
32계약직<NA>2479225089<NA><NA><NA><NA><NA><NA><NA><NA>