Overview

Dataset statistics

Number of variables8
Number of observations22
Missing cells18
Missing cells (%)10.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory70.0 B

Variable types

Text8

Dataset

Description대전광역시 시내버스 재정지원금 지원현황에 대한 데이터로 구분, 2013, 2014, 2015, 2016, 2017, 2018, 2019년 항목을 제공합니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15063356/fileData.do

Alerts

2013년 has 3 (13.6%) missing valuesMissing
2014년 has 4 (18.2%) missing valuesMissing
2015년 has 2 (9.1%) missing valuesMissing
2016년 has 1 (4.5%) missing valuesMissing
2017년 has 2 (9.1%) missing valuesMissing
2018년 has 3 (13.6%) missing valuesMissing
2019년 has 3 (13.6%) missing valuesMissing
구분 has unique valuesUnique

Reproduction

Analysis started2023-12-13 00:58:51.744911
Analysis finished2023-12-13 00:58:52.331709
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T09:58:52.443463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.2272727
Min length3

Characters and Unicode

Total characters115
Distinct characters50
Distinct categories3 ?
Distinct scripts3 ?
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 row운전기사인건비
2nd row연료비
3rd row임원인건비
4th row관리직인건비
5th row기타직인건비
ValueCountFrequency (%)
운전기사인건비 1
 
4.2%
연료비 1
 
4.2%
유가보조금 1
 
4.2%
등 1
 
4.2%
조정 1
 
4.2%
전년도분 1
 
4.2%
기타수입금 1
 
4.2%
운송수입금 1
 
4.2%
안전기여성과금 1
 
4.2%
평가성과금 1
 
4.2%
Other values (14) 14
58.3%
2023-12-13T09:58:52.691802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 10
 
8.7%
금 7
 
6.1%
기 6
 
5.2%
인 5
 
4.3%
건 5
 
4.3%
료 5
 
4.3%
수 4
 
3.5%
원 4
 
3.5%
정 4
 
3.5%
가 4
 
3.5%
Other values (40) 61
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 110
95.7%
Uppercase Letter 3
 
2.6%
Space Separator 2
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 10
 
9.1%
금 7
 
6.4%
기 6
 
5.5%
인 5
 
4.5%
건 5
 
4.5%
료 5
 
4.5%
수 4
 
3.6%
원 4
 
3.6%
정 4
 
3.6%
가 4
 
3.6%
Other values (36) 56
50.9%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
N 1
33.3%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 110
95.7%
Latin 3
 
2.6%
Common 2
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 10
 
9.1%
금 7
 
6.4%
기 6
 
5.5%
인 5
 
4.5%
건 5
 
4.5%
료 5
 
4.5%
수 4
 
3.6%
원 4
 
3.6%
정 4
 
3.6%
가 4
 
3.6%
Other values (36) 56
50.9%
Latin
ValueCountFrequency (%)
G 1
33.3%
N 1
33.3%
C 1
33.3%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 110
95.7%
ASCII 5
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 10
 
9.1%
금 7
 
6.4%
기 6
 
5.5%
인 5
 
4.5%
건 5
 
4.5%
료 5
 
4.5%
수 4
 
3.6%
원 4
 
3.6%
정 4
 
3.6%
가 4
 
3.6%
Other values (36) 56
50.9%
ASCII
ValueCountFrequency (%)
2
40.0%
G 1
20.0%
N 1
20.0%
C 1
20.0%

2013년
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing3
Missing (%)13.6%
Memory size308.0 B
2023-12-13T09:58:52.836058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length12.368421
Min length3

Characters and Unicode

Total characters235
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)100.0%

Sample

1st row101,423,417,330
2nd row34,481,538,128
3rd row1,249,966,216
4th row3,778,618,055
5th row1,124,297,650
ValueCountFrequency (%)
101,423,417,330 1
 
5.3%
2,721,228,542 1
 
5.3%
603,700,140 1
 
5.3%
442,849,930 1
 
5.3%
668 1
 
5.3%
1,150,546,422 1
 
5.3%
136,893,535,390 1
 
5.3%
793,915,150 1
 
5.3%
5,705,915,400 1
 
5.3%
3,262,974,767 1
 
5.3%
Other values (9) 9
47.4%
2023-12-13T09:58:53.073678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 50
21.3%
2 22
9.4%
1 21
8.9%
3 20
 
8.5%
5 20
 
8.5%
0 18
 
7.7%
4 18
 
7.7%
9 17
 
7.2%
6 17
 
7.2%
7 16
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 185
78.7%
Other Punctuation 50
 
21.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 22
11.9%
1 21
11.4%
3 20
10.8%
5 20
10.8%
0 18
9.7%
4 18
9.7%
9 17
9.2%
6 17
9.2%
7 16
8.6%
8 16
8.6%
Other Punctuation
ValueCountFrequency (%)
, 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 235
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 50
21.3%
2 22
9.4%
1 21
8.9%
3 20
 
8.5%
5 20
 
8.5%
0 18
 
7.7%
4 18
 
7.7%
9 17
 
7.2%
6 17
 
7.2%
7 16
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 50
21.3%
2 22
9.4%
1 21
8.9%
3 20
 
8.5%
5 20
 
8.5%
0 18
 
7.7%
4 18
 
7.7%
9 17
 
7.2%
6 17
 
7.2%
7 16
 
6.8%

2014년
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing4
Missing (%)18.2%
Memory size308.0 B
2023-12-13T09:58:53.223869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length12.444444
Min length3

Characters and Unicode

Total characters224
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row104,301,975,021
2nd row35,572,872,572
3rd row1,348,528,962
4th row4,011,084,775
5th row1,377,928,302
ValueCountFrequency (%)
858,618,802 1
 
5.6%
1,348,528,962 1
 
5.6%
3,329,588,724 1
 
5.6%
710 1
 
5.6%
1,032,162,561 1
 
5.6%
136,605,822,910 1
 
5.6%
793,915,150 1
 
5.6%
5,882,040,600 1
 
5.6%
2,599,016,622 1
 
5.6%
104,301,975,021 1
 
5.6%
Other values (8) 8
44.4%
2023-12-13T09:58:53.470490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 48
21.4%
0 23
10.3%
2 23
10.3%
1 21
9.4%
8 19
 
8.5%
5 19
 
8.5%
6 18
 
8.0%
3 16
 
7.1%
7 14
 
6.2%
4 12
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 176
78.6%
Other Punctuation 48
 
21.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23
13.1%
2 23
13.1%
1 21
11.9%
8 19
10.8%
5 19
10.8%
6 18
10.2%
3 16
9.1%
7 14
8.0%
4 12
6.8%
9 11
6.2%
Other Punctuation
ValueCountFrequency (%)
, 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 224
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 48
21.4%
0 23
10.3%
2 23
10.3%
1 21
9.4%
8 19
 
8.5%
5 19
 
8.5%
6 18
 
8.0%
3 16
 
7.1%
7 14
 
6.2%
4 12
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 224
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 48
21.4%
0 23
10.3%
2 23
10.3%
1 21
9.4%
8 19
 
8.5%
5 19
 
8.5%
6 18
 
8.0%
3 16
 
7.1%
7 14
 
6.2%
4 12
 
5.4%

2015년
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing2
Missing (%)9.1%
Memory size308.0 B
2023-12-13T09:58:53.629870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length12.5
Min length3

Characters and Unicode

Total characters250
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row107,974,806,812
2nd row28,765,531,887
3rd row1,389,800,744
4th row4,206,638,330
5th row1,408,693,886
ValueCountFrequency (%)
28,765,531,887 1
 
5.0%
1,389,800,744 1
 
5.0%
952,372,382 1
 
5.0%
211,280,290 1
 
5.0%
707 1
 
5.0%
1,069,021,253 1
 
5.0%
138,007,868,651 1
 
5.0%
1,680,426,360 1
 
5.0%
5,339,635,287 1
 
5.0%
2,494,623,516 1
 
5.0%
Other values (10) 10
50.0%
2023-12-13T09:58:53.875242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 54
21.6%
0 28
11.2%
8 25
10.0%
6 24
9.6%
3 24
9.6%
2 23
9.2%
1 17
 
6.8%
9 16
 
6.4%
7 14
 
5.6%
5 13
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 196
78.4%
Other Punctuation 54
 
21.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28
14.3%
8 25
12.8%
6 24
12.2%
3 24
12.2%
2 23
11.7%
1 17
8.7%
9 16
8.2%
7 14
7.1%
5 13
6.6%
4 12
6.1%
Other Punctuation
ValueCountFrequency (%)
, 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 250
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 54
21.6%
0 28
11.2%
8 25
10.0%
6 24
9.6%
3 24
9.6%
2 23
9.2%
1 17
 
6.8%
9 16
 
6.4%
7 14
 
5.6%
5 13
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 54
21.6%
0 28
11.2%
8 25
10.0%
6 24
9.6%
3 24
9.6%
2 23
9.2%
1 17
 
6.8%
9 16
 
6.4%
7 14
 
5.6%
5 13
 
5.2%

2016년
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing1
Missing (%)4.5%
Memory size308.0 B
2023-12-13T09:58:54.033857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length12.52381
Min length3

Characters and Unicode

Total characters263
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row111,959,557,355
2nd row22,896,784,374
3rd row1,431,631,901
4th row4,415,565,859
5th row1,547,559,682
ValueCountFrequency (%)
111,959,557,355 1
 
4.8%
1,506,380,863 1
 
4.8%
341,471,140 1
 
4.8%
684 1
 
4.8%
1,221,196,509 1
 
4.8%
141,264,743,684 1
 
4.8%
268,363,601 1
 
4.8%
2,002,587,300 1
 
4.8%
4,672,616,160 1
 
4.8%
2,480,738,250 1
 
4.8%
Other values (11) 11
52.4%
2023-12-13T09:58:54.281085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 57
21.7%
1 26
9.9%
0 25
9.5%
4 24
9.1%
8 23
8.7%
5 22
 
8.4%
3 21
 
8.0%
2 20
 
7.6%
6 19
 
7.2%
7 16
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 206
78.3%
Other Punctuation 57
 
21.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 26
12.6%
0 25
12.1%
4 24
11.7%
8 23
11.2%
5 22
10.7%
3 21
10.2%
2 20
9.7%
6 19
9.2%
7 16
7.8%
9 10
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 263
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 57
21.7%
1 26
9.9%
0 25
9.5%
4 24
9.1%
8 23
8.7%
5 22
 
8.4%
3 21
 
8.0%
2 20
 
7.6%
6 19
 
7.2%
7 16
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 263
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 57
21.7%
1 26
9.9%
0 25
9.5%
4 24
9.1%
8 23
8.7%
5 22
 
8.4%
3 21
 
8.0%
2 20
 
7.6%
6 19
 
7.2%
7 16
 
6.1%

2017년
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing2
Missing (%)9.1%
Memory size308.0 B
2023-12-13T09:58:54.434107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length12.1
Min length3

Characters and Unicode

Total characters242
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row119,278,601,179
2nd row24,601,096,029
3rd row1,459,195,661
4th row5,065,388,641
5th row -
ValueCountFrequency (%)
24,601,096,029 1
 
5.0%
1,459,195,661 1
 
5.0%
1,437,987,114 1
 
5.0%
1,545,475,805 1
 
5.0%
674 1
 
5.0%
430,387,182 1
 
5.0%
138,660,997,403 1
 
5.0%
2,740,028,652 1
 
5.0%
4,109,158,480 1
 
5.0%
3,628,780,407 1
 
5.0%
Other values (10) 10
50.0%
2023-12-13T09:58:54.677596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 52
21.5%
0 30
12.4%
4 24
9.9%
1 23
9.5%
8 21
8.7%
6 19
 
7.9%
5 17
 
7.0%
2 15
 
6.2%
7 15
 
6.2%
9 14
 
5.8%
Other values (3) 12
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 187
77.3%
Other Punctuation 52
 
21.5%
Space Separator 2
 
0.8%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30
16.0%
4 24
12.8%
1 23
12.3%
8 21
11.2%
6 19
10.2%
5 17
9.1%
2 15
8.0%
7 15
8.0%
9 14
7.5%
3 9
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 52
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 52
21.5%
0 30
12.4%
4 24
9.9%
1 23
9.5%
8 21
8.7%
6 19
 
7.9%
5 17
 
7.0%
2 15
 
6.2%
7 15
 
6.2%
9 14
 
5.8%
Other values (3) 12
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 52
21.5%
0 30
12.4%
4 24
9.9%
1 23
9.5%
8 21
8.7%
6 19
 
7.9%
5 17
 
7.0%
2 15
 
6.2%
7 15
 
6.2%
9 14
 
5.8%
Other values (3) 12
 
5.0%

2018년
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing3
Missing (%)13.6%
Memory size308.0 B
2023-12-13T09:58:54.828177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length12.578947
Min length3

Characters and Unicode

Total characters239
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)100.0%

Sample

1st row126,215,455,272
2nd row24,432,705,495
3rd row1,457,792,164
4th row5,247,961,616
5th row -
ValueCountFrequency (%)
126,215,455,272 1
 
5.3%
1,290,565,304 1
 
5.3%
24,432,705,495 1
 
5.3%
2,591,761,988 1
 
5.3%
254,572,790 1
 
5.3%
137,123,268,128 1
 
5.3%
3,514,450,680 1
 
5.3%
3,514,261,140 1
 
5.3%
3,758,595,027 1
 
5.3%
4,074,983,460 1
 
5.3%
Other values (9) 9
47.4%
2023-12-13T09:58:55.073486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 52
21.8%
5 24
10.0%
0 23
9.6%
2 22
9.2%
4 22
9.2%
1 21
8.8%
7 18
 
7.5%
6 15
 
6.3%
9 14
 
5.9%
8 14
 
5.9%
Other values (3) 14
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 184
77.0%
Other Punctuation 52
 
21.8%
Space Separator 2
 
0.8%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 24
13.0%
0 23
12.5%
2 22
12.0%
4 22
12.0%
1 21
11.4%
7 18
9.8%
6 15
8.2%
9 14
7.6%
8 14
7.6%
3 11
6.0%
Other Punctuation
ValueCountFrequency (%)
, 52
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 239
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 52
21.8%
5 24
10.0%
0 23
9.6%
2 22
9.2%
4 22
9.2%
1 21
8.8%
7 18
 
7.5%
6 15
 
6.3%
9 14
 
5.9%
8 14
 
5.9%
Other values (3) 14
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 239
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 52
21.8%
5 24
10.0%
0 23
9.6%
2 22
9.2%
4 22
9.2%
1 21
8.8%
7 18
 
7.5%
6 15
 
6.3%
9 14
 
5.9%
8 14
 
5.9%
Other values (3) 14
 
5.9%

2019년
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing3
Missing (%)13.6%
Memory size308.0 B
2023-12-13T09:58:55.222447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length12.684211
Min length3

Characters and Unicode

Total characters241
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)100.0%

Sample

1st row132,377,201,848
2nd row25,775,955,387
3rd row1,430,727,710
4th row5,705,314,924
5th row -
ValueCountFrequency (%)
132,377,201,848 1
 
5.3%
1,641,102,796 1
 
5.3%
25,775,955,387 1
 
5.3%
2,578,425,770 1
 
5.3%
6,970,052,230 1
 
5.3%
138,667,237,201 1
 
5.3%
3,514,450,680 1
 
5.3%
3,514,090,554 1
 
5.3%
3,902,676,893 1
 
5.3%
4,327,417,016 1
 
5.3%
Other values (9) 9
47.4%
2023-12-13T09:58:55.467448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 53
22.0%
7 26
10.8%
0 26
10.8%
5 24
10.0%
4 19
 
7.9%
1 17
 
7.1%
2 17
 
7.1%
3 15
 
6.2%
9 14
 
5.8%
6 14
 
5.8%
Other values (3) 16
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 185
76.8%
Other Punctuation 53
 
22.0%
Space Separator 2
 
0.8%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 26
14.1%
0 26
14.1%
5 24
13.0%
4 19
10.3%
1 17
9.2%
2 17
9.2%
3 15
8.1%
9 14
7.6%
6 14
7.6%
8 13
7.0%
Other Punctuation
ValueCountFrequency (%)
, 53
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 241
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 53
22.0%
7 26
10.8%
0 26
10.8%
5 24
10.0%
4 19
 
7.9%
1 17
 
7.1%
2 17
 
7.1%
3 15
 
6.2%
9 14
 
5.8%
6 14
 
5.8%
Other values (3) 16
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 241
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 53
22.0%
7 26
10.8%
0 26
10.8%
5 24
10.0%
4 19
 
7.9%
1 17
 
7.1%
2 17
 
7.1%
3 15
 
6.2%
9 14
 
5.8%
6 14
 
5.8%
Other values (3) 16
 
6.6%

Correlations

2023-12-13T09:58:55.545143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분2013년2014년2015년2016년2017년2018년2019년
구분1.0001.0001.0001.0001.0001.0001.0001.000
2013년1.0001.0001.0001.0001.0001.0001.0001.000
2014년1.0001.0001.0001.0001.0001.0001.0001.000
2015년1.0001.0001.0001.0001.0001.0001.0001.000
2016년1.0001.0001.0001.0001.0001.0001.0001.000
2017년1.0001.0001.0001.0001.0001.0001.0001.000
2018년1.0001.0001.0001.0001.0001.0001.0001.000
2019년1.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-13T09:58:52.067397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:58:52.155906image/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.
2023-12-13T09:58:52.256737image/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

구분2013년2014년2015년2016년2017년2018년2019년
0운전기사인건비101,423,417,330104,301,975,021107,974,806,812111,959,557,355119,278,601,179126,215,455,272132,377,201,848
1연료비34,481,538,12835,572,872,57228,765,531,88722,896,784,37424,601,096,02924,432,705,49525,775,955,387
2임원인건비1,249,966,2161,348,528,9621,389,800,7441,431,631,9011,459,195,6611,457,792,1641,430,727,710
3관리직인건비3,778,618,0554,011,084,7754,206,638,3304,415,565,8595,065,388,6415,247,961,6165,705,314,924
4기타직인건비1,124,297,6501,377,928,3021,408,693,8861,547,559,682---
5정비직인건비5,308,351,6245,647,848,1005,926,432,2666,255,632,3226,452,825,0626,697,449,0757,309,996,490
6정비재료비4,127,278,8064,336,860,2344,598,009,4934,498,523,0704,676,100,9404,581,110,2804,257,548,564
7감가상각비7,563,792,5227,476,231,6627,709,069,7388,281,317,7828,597,950,4119,283,423,5199,540,667,957
8CNG구매지원금<NA><NA>1,212,000,0001,450,000,0002,425,000,0002,685,000,0001,852,200,000
9임차료938,691,988858,618,802809,975,628784,887,497761,038,042783,870,744858,018,487
구분2013년2014년2015년2016년2017년2018년2019년
12기타원가2,721,228,5422,599,016,6222,494,623,5162,480,738,2503,628,780,4073,758,595,0273,902,676,893
13기본이윤5,705,915,4005,882,040,6005,339,635,2874,672,616,1604,109,158,4803,514,261,1403,514,090,554
14성과이윤793,915,150793,915,150<NA><NA><NA><NA><NA>
15평가성과금<NA><NA>1,680,426,3602,002,587,3002,740,028,6523,514,450,6803,514,450,680
16안전기여성과금<NA><NA><NA>268,363,601<NA><NA><NA>
17운송수입금136,893,535,390136,605,822,910138,007,868,651141,264,743,684138,660,997,403137,123,268,128138,667,237,201
18기타수입금1,150,546,4221,032,162,5611,069,021,2531,221,196,509430,387,182254,572,7906,970,052,230
19전년도분 조정 등668710707684674<NA><NA>
20유가보조금442,849,930<NA>211,280,290341,471,1401,545,475,8052,591,761,9882,578,425,770
21재정지원금34,596,753,90840,862,138,90038,336,182,08235,048,514,83048,460,508,45157,568,020,19057,791,653,540