Overview

Dataset statistics

Number of variables19
Number of observations265
Missing cells217
Missing cells (%)4.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.5 KiB
Average record size in memory152.5 B

Variable types

Unsupported3
Text3
Categorical13

Dataset

Description장수군 1대~8대 의안 처리 현황(년도, 건명, 발의자, 발의일, 소관, 집행부 이송일, 공포일, 공포번호 등)에 대하여 설명
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=1&menuCd=DOM_000000103007001000&pListTypeStr=&pId=15040018

Alerts

Unnamed: 16 is highly overall correlated with Unnamed: 6 and 8 other fieldsHigh correlation
Unnamed: 12 is highly overall correlated with Unnamed: 6 and 10 other fieldsHigh correlation
Unnamed: 11 is highly overall correlated with Unnamed: 7 and 7 other fieldsHigh correlation
Unnamed: 17 is highly overall correlated with Unnamed: 6 and 8 other fieldsHigh correlation
Unnamed: 7 is highly overall correlated with Unnamed: 6 and 10 other fieldsHigh correlation
Unnamed: 13 is highly overall correlated with Unnamed: 6 and 10 other fieldsHigh correlation
Unnamed: 9 is highly overall correlated with Unnamed: 6 and 10 other fieldsHigh correlation
Unnamed: 14 is highly overall correlated with Unnamed: 6 and 10 other fieldsHigh correlation
Unnamed: 15 is highly overall correlated with Unnamed: 7 and 7 other fieldsHigh correlation
Unnamed: 10 is highly overall correlated with Unnamed: 6 and 10 other fieldsHigh correlation
Unnamed: 8 is highly overall correlated with Unnamed: 6 and 10 other fieldsHigh correlation
Unnamed: 4 is highly overall correlated with Unnamed: 6High correlation
Unnamed: 6 is highly overall correlated with Unnamed: 4 and 9 other fieldsHigh correlation
Unnamed: 4 is highly imbalanced (51.5%)Imbalance
Unnamed: 15 is highly imbalanced (71.8%)Imbalance
의 안 처 리 부 has 34 (12.8%) missing valuesMissing
Unnamed: 1 has 43 (16.2%) missing valuesMissing
Unnamed: 5 has 3 (1.1%) missing valuesMissing
Unnamed: 18 has 134 (50.6%) missing valuesMissing
의 안 처 리 부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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

Reproduction

Analysis started2024-04-21 18:52:49.426533
Analysis finished2024-04-21 18:52:54.251180
Duration4.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

의 안 처 리 부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)12.8%
Memory size2.2 KiB

Unnamed: 1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)16.2%
Memory size2.2 KiB

Unnamed: 2
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.4%
Memory size2.2 KiB

Unnamed: 3
Text

Distinct235
Distinct (%)89.4%
Missing2
Missing (%)0.8%
Memory size2.2 KiB
2024-04-22T03:52:55.180641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length37
Mean length24.91635
Min length12

Characters and Unicode

Total characters6553
Distinct characters308
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique217 ?
Unique (%)82.5%

Sample

1st row건 명
2nd row2021회계연도 기금 결산안
3rd row2021년도 예비비지출 승인안
4th row장수군수 및 관계공무원 출석요구의 건
5th row예산결산특별위원회 구성의 건
ValueCountFrequency (%)
장수군 129
 
8.7%
조례 82
 
5.5%
일부개정조례안 76
 
5.1%
및 65
 
4.4%
건 54
 
3.6%
조례안 42
 
2.8%
관한 40
 
2.7%
동의안 34
 
2.3%
운영 24
 
1.6%
지원 22
 
1.5%
Other values (426) 913
61.6%
2024-04-22T03:52:56.481409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1228
 
18.7%
조 234
 
3.6%
수 229
 
3.5%
례 223
 
3.4%
안 222
 
3.4%
장 193
 
2.9%
군 188
 
2.9%
2 175
 
2.7%
정 146
 
2.2%
의 146
 
2.2%
Other values (298) 3569
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4904
74.8%
Space Separator 1228
 
18.7%
Decimal Number 347
 
5.3%
Close Punctuation 22
 
0.3%
Open Punctuation 22
 
0.3%
Other Punctuation 19
 
0.3%
Uppercase Letter 10
 
0.2%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 234
 
4.8%
수 229
 
4.7%
례 223
 
4.5%
안 222
 
4.5%
장 193
 
3.9%
군 188
 
3.8%
정 146
 
3.0%
의 146
 
3.0%
관 109
 
2.2%
회 102
 
2.1%
Other values (271) 3112
63.5%
Decimal Number
ValueCountFrequency (%)
2 175
50.4%
0 71
20.5%
3 55
 
15.9%
4 20
 
5.8%
1 9
 
2.6%
5 8
 
2.3%
6 5
 
1.4%
7 2
 
0.6%
8 2
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 2
20.0%
G 1
10.0%
V 1
10.0%
P 1
10.0%
L 1
10.0%
T 1
10.0%
B 1
10.0%
O 1
10.0%
J 1
10.0%
Other Punctuation
ValueCountFrequency (%)
· 16
84.2%
‧ 2
 
10.5%
․ 1
 
5.3%
Close Punctuation
ValueCountFrequency (%)
) 21
95.5%
」 1
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 21
95.5%
「 1
 
4.5%
Space Separator
ValueCountFrequency (%)
1228
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4904
74.8%
Common 1639
 
25.0%
Latin 10
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 234
 
4.8%
수 229
 
4.7%
례 223
 
4.5%
안 222
 
4.5%
장 193
 
3.9%
군 188
 
3.8%
정 146
 
3.0%
의 146
 
3.0%
관 109
 
2.2%
회 102
 
2.1%
Other values (271) 3112
63.5%
Common
ValueCountFrequency (%)
1228
74.9%
2 175
 
10.7%
0 71
 
4.3%
3 55
 
3.4%
) 21
 
1.3%
( 21
 
1.3%
4 20
 
1.2%
· 16
 
1.0%
1 9
 
0.5%
5 8
 
0.5%
Other values (8) 15
 
0.9%
Latin
ValueCountFrequency (%)
C 2
20.0%
G 1
10.0%
V 1
10.0%
P 1
10.0%
L 1
10.0%
T 1
10.0%
B 1
10.0%
O 1
10.0%
J 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4899
74.8%
ASCII 1628
 
24.8%
None 18
 
0.3%
Compat Jamo 5
 
0.1%
Punctuation 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1228
75.4%
2 175
 
10.7%
0 71
 
4.4%
3 55
 
3.4%
) 21
 
1.3%
( 21
 
1.3%
4 20
 
1.2%
1 9
 
0.6%
5 8
 
0.5%
6 5
 
0.3%
Other values (12) 15
 
0.9%
Hangul
ValueCountFrequency (%)
조 234
 
4.8%
수 229
 
4.7%
례 223
 
4.6%
안 222
 
4.5%
장 193
 
3.9%
군 188
 
3.8%
정 146
 
3.0%
의 146
 
3.0%
관 109
 
2.2%
회 102
 
2.1%
Other values (270) 3107
63.4%
None
ValueCountFrequency (%)
· 16
88.9%
」 1
 
5.6%
「 1
 
5.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 5
100.0%
Punctuation
ValueCountFrequency (%)
‧ 2
66.7%
․ 1
33.3%

Unnamed: 4
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct23
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
장수군수
181 
김광훈의원
 
11
장정복의원
 
9
유경자의원
 
7
이종섭의원
 
7
Other values (18)
50 

Length

Max length18
Median length4
Mean length4.8679245
Min length4

Unique

Unique7 ?
Unique (%)2.6%

Sample

1st row발의자 (제출자)
2nd row<NA>
3rd row장수군수
4th row장수군수
5th row장수군수

Common Values

ValueCountFrequency (%)
장수군수 181
68.3%
김광훈의원 11
 
4.2%
장정복의원 9
 
3.4%
유경자의원 7
 
2.6%
이종섭의원 7
 
2.6%
김남수의원외2 6
 
2.3%
김남수의원 6
 
2.3%
최한주의원 6
 
2.3%
유경자의원외2 4
 
1.5%
김광훈의원외2 4
 
1.5%
Other values (13) 24
 
9.1%

Length

2024-04-22T03:52:56.916262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
장수군수 181
67.5%
김광훈의원 11
 
4.1%
장정복의원 9
 
3.4%
유경자의원 7
 
2.6%
이종섭의원 7
 
2.6%
김남수의원 7
 
2.6%
김남수의원외2 6
 
2.2%
최한주의원 6
 
2.2%
유경자의원외2 4
 
1.5%
김광훈의원외2 4
 
1.5%
Other values (15) 26
 
9.7%

Unnamed: 5
Text

MISSING 

Distinct85
Distinct (%)32.4%
Missing3
Missing (%)1.1%
Memory size2.2 KiB
2024-04-22T03:52:57.554737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length10.28626
Min length9

Characters and Unicode

Total characters2695
Distinct characters20
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)13.0%

Sample

1st row발의일 (제출일)
2nd row2022.7.5.
3rd row2022.7.5.
4th row2022.7.8.
5th row2022.7.25.
ValueCountFrequency (%)
23 169
26.4%
11 54
 
8.5%
9 50
 
7.8%
5 29
 
4.5%
10 23
 
3.6%
30 22
 
3.4%
13 22
 
3.4%
4 19
 
3.0%
2 19
 
3.0%
12 17
 
2.7%
Other values (49) 215
33.6%
2024-04-22T03:52:58.662455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 783
29.1%
2 567
21.0%
376
14.0%
1 281
 
10.4%
3 234
 
8.7%
0 168
 
6.2%
9 64
 
2.4%
5 59
 
2.2%
8 46
 
1.7%
7 45
 
1.7%
Other values (10) 72
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1527
56.7%
Other Punctuation 783
29.1%
Space Separator 376
 
14.0%
Other Letter 6
 
0.2%
Control 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 567
37.1%
1 281
18.4%
3 234
15.3%
0 168
 
11.0%
9 64
 
4.2%
5 59
 
3.9%
8 46
 
3.0%
7 45
 
2.9%
4 34
 
2.2%
6 29
 
1.9%
Other Letter
ValueCountFrequency (%)
일 2
33.3%
발 1
16.7%
의 1
16.7%
제 1
16.7%
출 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 783
100.0%
Space Separator
ValueCountFrequency (%)
376
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2689
99.8%
Hangul 6
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 783
29.1%
2 567
21.1%
376
14.0%
1 281
 
10.4%
3 234
 
8.7%
0 168
 
6.2%
9 64
 
2.4%
5 59
 
2.2%
8 46
 
1.7%
7 45
 
1.7%
Other values (5) 66
 
2.5%
Hangul
ValueCountFrequency (%)
일 2
33.3%
발 1
16.7%
의 1
16.7%
제 1
16.7%
출 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2689
99.8%
Hangul 6
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 783
29.1%
2 567
21.1%
376
14.0%
1 281
 
10.4%
3 234
 
8.7%
0 168
 
6.2%
9 64
 
2.4%
5 59
 
2.2%
8 46
 
1.7%
7 45
 
1.7%
Other values (5) 66
 
2.5%
Hangul
ValueCountFrequency (%)
일 2
33.3%
발 1
16.7%
의 1
16.7%
제 1
16.7%
출 1
16.7%

Unnamed: 6
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
행정복지
126 
산업건설
59 
<NA>
41 
예산결산
27 
실태조사특위
 
6
Other values (4)
 
6

Length

Max length15
Median length4
Mean length4.2188679
Min length4

Unique

Unique2 ?
Unique (%)0.8%

Sample

1st row소 관 (위원회)
2nd row<NA>
3rd row예산결산
4th row예산결산
5th row예산결산

Common Values

ValueCountFrequency (%)
행정복지 126
47.5%
산업건설 59
22.3%
<NA> 41
 
15.5%
예산결산 27
 
10.2%
실태조사특위 6
 
2.3%
행정사무감사특별위원회 2
 
0.8%
군정주요사업실태조사특별위원회 2
 
0.8%
소 관 (위원회) 1
 
0.4%
행감특위 1
 
0.4%

Length

2024-04-22T03:52:59.079442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:52:59.427999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행정복지 126
47.2%
산업건설 59
22.1%
na 41
 
15.4%
예산결산 27
 
10.1%
실태조사특위 6
 
2.2%
행정사무감사특별위원회 2
 
0.7%
군정주요사업실태조사특별위원회 2
 
0.7%
소 1
 
0.4%
관 1
 
0.4%
위원회 1
 
0.4%

Unnamed: 7
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
49 
23. 11. 13.
28 
23. 9. 4.
19 
22. 11. 14.
15 
23. 2. 20.
 
13
Other values (32)
141 

Length

Max length25
Median length11
Mean length9.0679245
Min length3

Unique

Unique7 ?
Unique (%)2.6%

Sample

1st row위 원 회
2nd row회부일
3rd row22. 9. 13.
4th row22. 9. 13.
5th row22. 9. 13.

Common Values

ValueCountFrequency (%)
<NA> 49
18.5%
23. 11. 13. 28
 
10.6%
23. 9. 4. 19
 
7.2%
22. 11. 14. 15
 
5.7%
23. 2. 20. 13
 
4.9%
23. 5. 15. 13
 
4.9%
22. 11. 24. 12
 
4.5%
23. 4. 4. 10
 
3.8%
23. 10. 20. 10
 
3.8%
22. 12. 7. 9
 
3.4%
Other values (27) 87
32.8%

Length

2024-04-22T03:52:59.854223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23 140
20.1%
22 75
10.8%
11 61
 
8.8%
na 49
 
7.1%
9 45
 
6.5%
4 43
 
6.2%
13 33
 
4.7%
10 30
 
4.3%
7 26
 
3.7%
12 25
 
3.6%
Other values (22) 168
24.2%

Unnamed: 8
Categorical

HIGH CORRELATION 

Distinct38
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
48 
23. 9. 6.
19 
23. 11. 14.
19 
23. 5. 17.
19 
22. 11. 15.
17 
Other values (33)
143 

Length

Max length11
Median length10
Mean length9.0679245
Min length3

Unique

Unique7 ?
Unique (%)2.6%

Sample

1st row<NA>
2nd row보고일
3rd row22. 9. 16.
4th row22. 9. 16.
5th row22. 9. 16.

Common Values

ValueCountFrequency (%)
<NA> 48
18.1%
23. 9. 6. 19
 
7.2%
23. 11. 14. 19
 
7.2%
23. 5. 17. 19
 
7.2%
22. 11. 15. 17
 
6.4%
23. 2. 22. 13
 
4.9%
23. 10. 25. 10
 
3.8%
22. 11. 25. 10
 
3.8%
23. 11. 23. 10
 
3.8%
23. 4. 5. 10
 
3.8%
Other values (28) 90
34.0%

Length

2024-04-22T03:53:00.275778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23 152
21.8%
22 89
12.8%
11 84
12.1%
na 48
 
6.9%
5 44
 
6.3%
9 38
 
5.5%
10 27
 
3.9%
6 24
 
3.4%
14 24
 
3.4%
12 24
 
3.4%
Other values (16) 143
20.5%

Unnamed: 9
Categorical

HIGH CORRELATION 

Distinct38
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
48 
23. 9. 6.
19 
23. 11. 14.
19 
23. 5. 17.
19 
22. 11. 15.
17 
Other values (33)
143 

Length

Max length11
Median length10
Mean length9.0679245
Min length3

Unique

Unique7 ?
Unique (%)2.6%

Sample

1st row<NA>
2nd row상정일
3rd row22. 9. 16.
4th row22. 9. 16.
5th row22. 9. 16.

Common Values

ValueCountFrequency (%)
<NA> 48
18.1%
23. 9. 6. 19
 
7.2%
23. 11. 14. 19
 
7.2%
23. 5. 17. 19
 
7.2%
22. 11. 15. 17
 
6.4%
23. 2. 22. 13
 
4.9%
23. 10. 25. 10
 
3.8%
22. 11. 25. 10
 
3.8%
23. 11. 23. 10
 
3.8%
23. 4. 5. 10
 
3.8%
Other values (28) 90
34.0%

Length

2024-04-22T03:53:00.726032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23 152
21.8%
22 89
12.8%
11 84
12.1%
na 48
 
6.9%
5 44
 
6.3%
9 38
 
5.5%
10 27
 
3.9%
6 24
 
3.4%
14 24
 
3.4%
12 24
 
3.4%
Other values (16) 143
20.5%

Unnamed: 10
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
50 
23. 11. 14.
19 
23. 5. 17.
19 
23. 9. 6.
19 
22. 11. 15.
17 
Other values (25)
141 

Length

Max length11
Median length10
Mean length9.0264151
Min length3

Unique

Unique3 ?
Unique (%)1.1%

Sample

1st row<NA>
2nd row처리일
3rd row22. 9. 29.
4th row22. 9. 29.
5th row22. 9. 29.

Common Values

ValueCountFrequency (%)
<NA> 50
18.9%
23. 11. 14. 19
 
7.2%
23. 5. 17. 19
 
7.2%
23. 9. 6. 19
 
7.2%
22. 11. 15. 17
 
6.4%
23. 2. 22. 13
 
4.9%
22. 11. 25. 10
 
3.8%
23. 11. 23. 10
 
3.8%
23. 10. 25. 10
 
3.8%
23. 4. 5. 10
 
3.8%
Other values (20) 88
33.2%

Length

2024-04-22T03:53:01.177657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23 150
21.6%
22 88
12.7%
11 79
11.4%
na 50
 
7.2%
5 43
 
6.2%
9 38
 
5.5%
10 27
 
3.9%
15 25
 
3.6%
6 22
 
3.2%
25 22
 
3.2%
Other values (15) 149
21.5%

Unnamed: 11
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
원안가결
190 
<NA>
63 
수정가결
 
11
결 과
 
1

Length

Max length6
Median length4
Mean length4.0075472
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row<NA>
2nd row결 과
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
원안가결 190
71.7%
<NA> 63
 
23.8%
수정가결 11
 
4.2%
결 과 1
 
0.4%

Length

2024-04-22T03:53:01.615750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:53:01.963729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원안가결 190
71.4%
na 63
 
23.7%
수정가결 11
 
4.1%
결 1
 
0.4%
과 1
 
0.4%

Unnamed: 12
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
23. 9. 19.
26 
23. 5. 24.
20 
22. 11. 17.
19 
23. 11. 16.
19 
23. 2. 28.
 
15
Other values (26)
166 

Length

Max length17
Median length10
Mean length10.154717
Min length3

Unique

Unique5 ?
Unique (%)1.9%

Sample

1st row본 회 의
2nd row보고일
3rd row22. 9. 30.
4th row22. 9. 30.
5th row22. 9. 30.

Common Values

ValueCountFrequency (%)
23. 9. 19. 26
 
9.8%
23. 5. 24. 20
 
7.5%
22. 11. 17. 19
 
7.2%
23. 11. 16. 19
 
7.2%
23. 2. 28. 15
 
5.7%
23. 4. 11. 15
 
5.7%
23. 11. 27. 13
 
4.9%
22. 11. 28. 12
 
4.5%
22. 12. 16. 11
 
4.2%
23. 10. 31. 11
 
4.2%
Other values (21) 104
39.2%

Length

2024-04-22T03:53:02.340991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23 163
21.0%
11 99
12.8%
22 98
12.6%
9 46
 
5.9%
19 38
 
4.9%
16 35
 
4.5%
10 33
 
4.3%
28 27
 
3.5%
5 25
 
3.2%
2 24
 
3.1%
Other values (18) 187
24.1%

Unnamed: 13
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
23. 9. 19.
26 
23. 5. 24.
20 
22. 11. 17.
19 
23. 11. 16.
19 
23. 4. 11.
 
15
Other values (25)
166 

Length

Max length11
Median length10
Mean length10.083019
Min length3

Unique

Unique4 ?
Unique (%)1.5%

Sample

1st row<NA>
2nd row상정일
3rd row22. 9. 30.
4th row22. 9. 30.
5th row22. 9. 30.

Common Values

ValueCountFrequency (%)
23. 9. 19. 26
 
9.8%
23. 5. 24. 20
 
7.5%
22. 11. 17. 19
 
7.2%
23. 11. 16. 19
 
7.2%
23. 4. 11. 15
 
5.7%
23. 2. 28. 15
 
5.7%
23. 11. 27. 13
 
4.9%
22. 11. 28. 12
 
4.5%
<NA> 11
 
4.2%
23. 10. 31. 11
 
4.2%
Other values (20) 104
39.2%

Length

2024-04-22T03:53:02.765906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23 162
21.0%
11 99
12.8%
22 98
12.7%
9 46
 
6.0%
19 38
 
4.9%
16 35
 
4.5%
10 33
 
4.3%
28 27
 
3.5%
2 24
 
3.1%
5 24
 
3.1%
Other values (15) 185
24.0%

Unnamed: 14
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
23. 9. 19.
24 
23. 5. 24.
20 
22. 11. 17.
19 
23. 11. 16.
19 
22. 12. 16.
17 
Other values (26)
166 

Length

Max length11
Median length10
Mean length10.045283
Min length3

Unique

Unique4 ?
Unique (%)1.5%

Sample

1st row<NA>
2nd row처리일
3rd row22. 9. 30.
4th row22. 9. 30.
5th row22. 9. 30.

Common Values

ValueCountFrequency (%)
23. 9. 19. 24
 
9.1%
23. 5. 24. 20
 
7.5%
22. 11. 17. 19
 
7.2%
23. 11. 16. 19
 
7.2%
22. 12. 16. 17
 
6.4%
23. 2. 28. 15
 
5.7%
23. 4. 11. 13
 
4.9%
<NA> 13
 
4.9%
23. 10. 31. 11
 
4.2%
23. 11. 27. 11
 
4.2%
Other values (21) 103
38.9%

Length

2024-04-22T03:53:03.202413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23 160
20.9%
22 98
12.8%
11 93
12.1%
9 46
 
6.0%
16 41
 
5.3%
19 38
 
5.0%
10 33
 
4.3%
28 25
 
3.3%
5 24
 
3.1%
2 24
 
3.1%
Other values (15) 185
24.1%

Unnamed: 15
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
원안가결
240 
<NA>
 
13
수정가결
 
11
결 과
 
1

Length

Max length6
Median length4
Mean length4.0075472
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row<NA>
2nd row결 과
3rd row원안가결
4th row원안가결
5th row원안가결

Common Values

ValueCountFrequency (%)
원안가결 240
90.6%
<NA> 13
 
4.9%
수정가결 11
 
4.2%
결 과 1
 
0.4%

Length

2024-04-22T03:53:03.638595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T03:53:03.981111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원안가결 240
90.2%
na 13
 
4.9%
수정가결 11
 
4.1%
결 1
 
0.4%
과 1
 
0.4%

Unnamed: 16
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
58 
23. 9. 19.
20 
23. 11. 16.
19 
23. 5. 25.
18 
22. 11. 17.
17 
Other values (21)
133 

Length

Max length11
Median length10
Mean length9.0226415
Min length4

Unique

Unique3 ?
Unique (%)1.1%

Sample

1st row집행부 이송일
2nd row<NA>
3rd row22. 9. 30.
4th row22. 9. 30.
5th row22. 9. 30.

Common Values

ValueCountFrequency (%)
<NA> 58
21.9%
23. 9. 19. 20
 
7.5%
23. 11. 16. 19
 
7.2%
23. 5. 25. 18
 
6.8%
22. 11. 17. 17
 
6.4%
22. 12. 16. 17
 
6.4%
23. 2. 28. 13
 
4.9%
23. 4. 11. 11
 
4.2%
22. 11. 29. 10
 
3.8%
23. 11. 27. 10
 
3.8%
Other values (16) 72
27.2%

Length

2024-04-22T03:53:04.357213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23 135
19.9%
11 81
11.9%
22 75
11.1%
na 58
 
8.6%
16 39
 
5.8%
9 35
 
5.2%
10 25
 
3.7%
19 22
 
3.2%
2 20
 
2.9%
5 18
 
2.7%
Other values (18) 170
25.1%

Unnamed: 17
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
134 
23. 6. 15.
17 
23. 10. 16.
14 
23. 12. 1.
 
12
22. 12. 1.
 
12
Other values (18)
76 

Length

Max length11
Median length4
Mean length6.9924528
Min length3

Unique

Unique5 ?
Unique (%)1.9%

Sample

1st row공포일
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 134
50.6%
23. 6. 15. 17
 
6.4%
23. 10. 16. 14
 
5.3%
23. 12. 1. 12
 
4.5%
22. 12. 1. 12
 
4.5%
23. 3. 15. 9
 
3.4%
23. 12. 15. 8
 
3.0%
23. 5. 1. 8
 
3.0%
22. 12. 15. 7
 
2.6%
23. 11. 1. 6
 
2.3%
Other values (13) 38
 
14.3%

Length

2024-04-22T03:53:04.791353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 134
25.7%
23 93
17.9%
1 52
 
10.0%
15 46
 
8.8%
12 46
 
8.8%
22 35
 
6.7%
6 17
 
3.3%
11 16
 
3.1%
10 14
 
2.7%
16 14
 
2.7%
Other values (10) 54
10.4%

Unnamed: 18
Text

MISSING 

Distinct129
Distinct (%)98.5%
Missing134
Missing (%)50.6%
Memory size2.2 KiB
2024-04-22T03:53:06.036288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9541985
Min length2

Characters and Unicode

Total characters518
Distinct characters14
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

Unique127 ?
Unique (%)96.9%

Sample

1st row공포번호
2nd row2608
3rd row2609
4th row2610
5th row2611
ValueCountFrequency (%)
2731 2
 
1.5%
13 2
 
1.5%
2703 1
 
0.8%
2701 1
 
0.8%
2690 1
 
0.8%
2691 1
 
0.8%
2692 1
 
0.8%
2693 1
 
0.8%
2695 1
 
0.8%
2684 1
 
0.8%
Other values (119) 119
90.8%
2024-04-22T03:53:07.729098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 160
30.9%
6 112
21.6%
7 57
 
11.0%
1 37
 
7.1%
3 30
 
5.8%
0 25
 
4.8%
9 25
 
4.8%
5 23
 
4.4%
8 23
 
4.4%
4 22
 
4.2%
Other values (4) 4
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 514
99.2%
Other Letter 4
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 160
31.1%
6 112
21.8%
7 57
 
11.1%
1 37
 
7.2%
3 30
 
5.8%
0 25
 
4.9%
9 25
 
4.9%
5 23
 
4.5%
8 23
 
4.5%
4 22
 
4.3%
Other Letter
ValueCountFrequency (%)
공 1
25.0%
포 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 514
99.2%
Hangul 4
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 160
31.1%
6 112
21.8%
7 57
 
11.1%
1 37
 
7.2%
3 30
 
5.8%
0 25
 
4.9%
9 25
 
4.9%
5 23
 
4.5%
8 23
 
4.5%
4 22
 
4.3%
Hangul
ValueCountFrequency (%)
공 1
25.0%
포 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 514
99.2%
Hangul 4
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 160
31.1%
6 112
21.8%
7 57
 
11.1%
1 37
 
7.2%
3 30
 
5.8%
0 25
 
4.9%
9 25
 
4.9%
5 23
 
4.5%
8 23
 
4.5%
4 22
 
4.3%
Hangul
ValueCountFrequency (%)
공 1
25.0%
포 1
25.0%
번 1
25.0%
호 1
25.0%

Correlations

2024-04-22T03:53:08.017334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
Unnamed: 41.0000.9830.9370.7540.7410.7410.7790.0000.8740.8500.8460.0000.7900.796
Unnamed: 50.9831.0000.9341.0000.9990.9990.9990.3480.9980.9980.9990.2450.9990.989
Unnamed: 60.9370.9341.0000.9280.8940.8940.8670.1510.8930.8350.8590.1490.9830.882
Unnamed: 70.7541.0000.9281.0000.9980.9980.9980.8930.9980.9980.9980.8770.9990.993
Unnamed: 80.7410.9990.8940.9981.0001.0001.0000.9051.0001.0001.0000.9051.0001.000
Unnamed: 90.7410.9990.8940.9981.0001.0001.0000.9051.0001.0001.0000.9051.0001.000
Unnamed: 100.7790.9990.8670.9981.0001.0001.0000.9180.9990.9991.0000.9181.0001.000
Unnamed: 110.0000.3480.1510.8930.9050.9050.9181.0000.8700.8700.9211.0000.2280.000
Unnamed: 120.8740.9980.8930.9981.0001.0000.9990.8701.0001.0000.9980.8660.9981.000
Unnamed: 130.8500.9980.8350.9981.0001.0000.9990.8701.0001.0000.9980.8660.9981.000
Unnamed: 140.8460.9990.8590.9981.0001.0001.0000.9210.9980.9981.0000.9091.0001.000
Unnamed: 150.0000.2450.1490.8770.9050.9050.9181.0000.8660.8660.9091.0000.0000.000
Unnamed: 160.7900.9990.9830.9991.0001.0001.0000.2280.9980.9981.0000.0001.0001.000
Unnamed: 170.7960.9890.8820.9931.0001.0001.0000.0001.0001.0001.0000.0001.0001.000
2024-04-22T03:53:08.337222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 16Unnamed: 12Unnamed: 11Unnamed: 17Unnamed: 7Unnamed: 4Unnamed: 13Unnamed: 9Unnamed: 14Unnamed: 15Unnamed: 10Unnamed: 6Unnamed: 8
Unnamed: 161.0000.9620.1690.9780.9440.3880.9600.9830.9960.0000.9970.7910.983
Unnamed: 120.9621.0000.6730.9780.9410.4191.0000.9730.9610.6530.9700.6030.973
Unnamed: 110.1690.6731.0000.0000.6750.0000.6730.6940.6751.0000.6680.1830.694
Unnamed: 170.9780.9780.0001.0000.9140.4380.9780.9780.9780.0000.9780.6780.978
Unnamed: 70.9440.9410.6750.9141.0000.3430.9380.9260.9410.6540.9470.6730.926
Unnamed: 40.3880.4190.0000.4380.3431.0000.3820.3300.3830.0000.3830.7740.330
Unnamed: 130.9601.0000.6730.9780.9380.3821.0000.9750.9610.6530.9700.5260.975
Unnamed: 90.9830.9730.6940.9780.9260.3300.9751.0000.9810.6970.9840.5761.000
Unnamed: 140.9960.9610.6750.9780.9410.3830.9610.9811.0000.6600.9940.5610.981
Unnamed: 150.0000.6531.0000.0000.6540.0000.6530.6970.6601.0000.6690.1570.697
Unnamed: 100.9970.9700.6680.9780.9470.3830.9700.9840.9940.6691.0000.6080.984
Unnamed: 60.7910.6030.1830.6780.6730.7740.5260.5760.5610.1570.6081.0000.576
Unnamed: 80.9830.9730.6940.9780.9260.3300.9751.0000.9810.6970.9840.5761.000
2024-04-22T03:53:08.602687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
Unnamed: 41.0000.7740.3430.3300.3300.3830.0000.4190.3820.3830.0000.3880.438
Unnamed: 60.7741.0000.6730.5760.5760.6080.1830.6030.5260.5610.1570.7910.678
Unnamed: 70.3430.6731.0000.9260.9260.9470.6750.9410.9380.9410.6540.9440.914
Unnamed: 80.3300.5760.9261.0001.0000.9840.6940.9730.9750.9810.6970.9830.978
Unnamed: 90.3300.5760.9261.0001.0000.9840.6940.9730.9750.9810.6970.9830.978
Unnamed: 100.3830.6080.9470.9840.9841.0000.6680.9700.9700.9940.6690.9970.978
Unnamed: 110.0000.1830.6750.6940.6940.6681.0000.6730.6730.6751.0000.1690.000
Unnamed: 120.4190.6030.9410.9730.9730.9700.6731.0001.0000.9610.6530.9620.978
Unnamed: 130.3820.5260.9380.9750.9750.9700.6731.0001.0000.9610.6530.9600.978
Unnamed: 140.3830.5610.9410.9810.9810.9940.6750.9610.9611.0000.6600.9960.978
Unnamed: 150.0000.1570.6540.6970.6970.6691.0000.6530.6530.6601.0000.0000.000
Unnamed: 160.3880.7910.9440.9830.9830.9970.1690.9620.9600.9960.0001.0000.978
Unnamed: 170.4380.6780.9140.9780.9780.9780.0000.9780.9780.9780.0000.9781.000

Missing values

2024-04-22T03:52:53.177927image/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.
2024-04-22T03:52:53.770209image/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

의 안 처 리 부Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18
0연도회기의안\n번호건 명발의자 (제출자)발의일 (제출일)소 관 (위원회)위 원 회<NA><NA><NA><NA>본 회 의<NA><NA><NA>집행부 이송일공포일공포번호
1NaNNaNNaN<NA><NA><NA><NA>회부일보고일상정일처리일결 과보고일상정일처리일결 과<NA><NA><NA>
220223411<NA>장수군수2022.7.5.예산결산22. 9. 13.22. 9. 16.22. 9. 16.22. 9. 29.<NA>22. 9. 30.22. 9. 30.22. 9. 30.원안가결22. 9. 30.<NA><NA>
3202234122021회계연도 기금 결산안장수군수2022.7.5.예산결산22. 9. 13.22. 9. 16.22. 9. 16.22. 9. 29.<NA>22. 9. 30.22. 9. 30.22. 9. 30.원안가결22. 9. 30.<NA><NA>
4202234132021년도 예비비지출 승인안장수군수2022.7.8.예산결산22. 9. 13.22. 9. 16.22. 9. 16.22. 9. 29.<NA>22. 9. 30.22. 9. 30.22. 9. 30.원안가결22. 9. 30.<NA><NA>
520223394장수군수 및 관계공무원 출석요구의 건유경자의원외22022.7.25.<NA><NA><NA><NA><NA><NA>22. 8. 1.22. 8. 1.22. 8. 1.원안가결<NA><NA><NA>
620223395예산결산특별위원회 구성의 건유경자의원외22022.7.26.<NA><NA><NA><NA><NA><NA>22. 8. 1.22. 8. 1.22. 8. 1.원안가결<NA><NA><NA>
720223396윤리특별위원회 구성의 건유경자의원외22022.7.26.<NA><NA><NA><NA><NA><NA>22. 8. 1.22. 8. 1.22. 8. 1.원안가결<NA><NA><NA>
820223407장수군수 및 관계공무원 출석요구의 건김남수의원외22022.8.25.<NA><NA><NA><NA><NA><NA>22. 8. 31.22. 8. 31.22. 8. 31.원안가결<NA><NA><NA>
920223408장수군 금고지정 및 운영에 관한 조례 일부개정조례안장수군수2022.8.22.행정복지22. 8. 25.22. 8. 26.22. 8. 26.22. 8. 26.원안가결22. 8. 31.22. 8. 31.22. 8. 31.원안가결22. 8. 31.22. 9. 8.2608
의 안 처 리 부Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18
255NaNNaN254장수군 공유재산 관리 조례 일부개정조례안장수군수23. 11. 23.행정복지23. 11. 23.23. 11. 23.23. 11. 23.23. 11. 23.원안가결23. 11. 27.23. 11. 27.23. 11. 27.원안가결23. 11. 27.23. 12. 15.2729
256NaNNaN255제356회 장수군의회 제2차 정례회 본회의 휴회의 건장수군의회의장<NA><NA><NA><NA><NA><NA><NA>23. 11. 27.23. 11. 27.23. 11. 27.원안가결<NA><NA><NA>
257NaNNaN2562024년도 제4회 추가경정예산안장수군수23. 11. 24.예산결산23. 11. 29.23. 12. 5.23. 12. 5.<NA><NA>23. 12. 5.<NA><NA><NA><NA><NA><NA>
258NaNNaN257제356회 장수군의회 제2차 정례회 본회의 휴회의 건장수군의회의장<NA><NA><NA><NA><NA><NA><NA>23. 12. 5.23. 12. 5.23. 12. 5.원안가결<NA><NA><NA>
259NaNNaN258장수한우 지리적 표시 증명표장 사용 및 운영에 관한 조례안장수군수23. 12. 1.산업건설23. 12. 7.23. 12. 8.23. 12. 8.23. 12. 8.원안가결<NA><NA><NA><NA><NA><NA><NA>
260NaNNaN2592023년도 행정사무감사 결과보고서 채택의 건행정사무감사특별위원회위원장23. 12. 4.<NA><NA>23. 12. 4.23. 12. 4.23. 12. 4.원안가결23. 12. 5.23. 12. 5.23. 12. 5.원안가결<NA><NA><NA>
261NaNNaN2602024년도 일반회계 및 특별회계 세입·세출 수정예산안장수군수23. 12. 6.예산결산23. 12. 7.23. 12. 11.23. 12. 11.<NA><NA><NA><NA><NA><NA><NA><NA><NA>
262NaNNaN2612023년 7차 수시분 공유재산 관리계획안장수군수23. 12. 7.행정복지23. 12. 7.23. 12. 8.23. 12. 8.23. 12. 8.원안가결<NA><NA><NA><NA><NA><NA><NA>
263NaNNaN262장수 군관리계획(용도지구) 결정(변경)(안) 의회의견청취의 건장수군수23. 12. 7.산업건설23. 12. 7.23. 12. 8.23. 12. 8.23. 12. 8.원안가결<NA><NA><NA><NA><NA><NA><NA>
264NaNNaN263장수 군관리계획(용도지역) 결정(변경)(안) 의회의견청취의 건장수군수23. 12. 7.산업건설23. 12. 7.23. 12. 8.23. 12. 8.23. 12. 8.원안가결<NA><NA><NA><NA><NA><NA><NA>