Overview

Dataset statistics

Number of variables17
Number of observations28
Missing cells25
Missing cells (%)5.3%
Duplicate rows1
Duplicate rows (%)3.6%
Total size in memory4.3 KiB
Average record size in memory156.7 B

Variable types

Text1
Categorical16

Dataset

Description제주에너지공사의 중소기업, 여성기업, 장애인기업 대상 물품, 공사, 용역 구매액과 전체 구매액 실적 현황입니다.(분기)
Author제주에너지공사
URLhttps://www.data.go.kr/data/15119621/fileData.do

Alerts

Dataset has 1 (3.6%) duplicate rowsDuplicates
중소기업제품구매액(공사) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
중소기업제품구매액(용역) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
장애인기업제품구매액(계) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
총구매액(물품) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
여성기업제품구매액(공사) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
장애인기업제품구매액(공사) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
총구매액(용역) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
장애인기업제품구매액(물품) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
여성기업제품구매액(용역) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
총구매액(계) is highly overall correlated with 총구매액(물품) and 14 other fieldsHigh correlation
장애인기업제품구매액(용역) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
여성기업제품구매액(물품) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
중소기업제품구매액(물품) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
여성기업제품구매액(계) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
총구매액(공사) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
중소기업제품구매액(계) is highly overall correlated with 총구매액(계) and 14 other fieldsHigh correlation
총구매액(계) is highly imbalanced (66.9%)Imbalance
총구매액(물품) is highly imbalanced (66.9%)Imbalance
총구매액(공사) is highly imbalanced (66.9%)Imbalance
총구매액(용역) is highly imbalanced (66.9%)Imbalance
중소기업제품구매액(계) is highly imbalanced (66.9%)Imbalance
중소기업제품구매액(물품) is highly imbalanced (66.9%)Imbalance
중소기업제품구매액(공사) is highly imbalanced (66.9%)Imbalance
중소기업제품구매액(용역) is highly imbalanced (66.9%)Imbalance
여성기업제품구매액(계) is highly imbalanced (66.9%)Imbalance
여성기업제품구매액(물품) is highly imbalanced (66.9%)Imbalance
여성기업제품구매액(공사) is highly imbalanced (66.9%)Imbalance
여성기업제품구매액(용역) is highly imbalanced (66.9%)Imbalance
장애인기업제품구매액(계) is highly imbalanced (66.9%)Imbalance
장애인기업제품구매액(물품) is highly imbalanced (66.9%)Imbalance
장애인기업제품구매액(공사) is highly imbalanced (50.9%)Imbalance
장애인기업제품구매액(용역) is highly imbalanced (66.9%)Imbalance
구분 has 25 (89.3%) missing valuesMissing

Reproduction

Analysis started2024-04-18 06:07:20.767299
Analysis finished2024-04-18 06:07:24.342886
Duration3.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing25
Missing (%)89.3%
Memory size356.0 B
2024-04-18T15:07:24.423166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9
Distinct characters4
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

Unique3 ?
Unique (%)100.0%

Sample

1st row10월
2nd row11월
3rd row12월
ValueCountFrequency (%)
10월 1
33.3%
11월 1
33.3%
12월 1
33.3%
2024-04-18T15:07:24.676165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
44.4%
월 3
33.3%
0 1
 
11.1%
2 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
66.7%
Other Letter 3
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
66.7%
0 1
 
16.7%
2 1
 
16.7%
Other Letter
ValueCountFrequency (%)
월 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6
66.7%
Hangul 3
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
66.7%
0 1
 
16.7%
2 1
 
16.7%
Hangul
ValueCountFrequency (%)
월 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
66.7%
Hangul 3
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
66.7%
0 1
 
16.7%
2 1
 
16.7%
Hangul
ValueCountFrequency (%)
월 3
100.0%

총구매액(계)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
268524520
 
1
274685270
 
1
724532561
 
1

Length

Max length9
Median length4
Mean length4.5357143
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row268524520
2nd row274685270
3rd row724532561
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
268524520 1
 
3.6%
274685270 1
 
3.6%
724532561 1
 
3.6%

Length

2024-04-18T15:07:24.799594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:24.895355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
268524520 1
 
3.6%
274685270 1
 
3.6%
724532561 1
 
3.6%

총구매액(물품)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
128795050
 
1
43152330
 
1
210664570
 
1

Length

Max length9
Median length4
Mean length4.5
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row128795050
2nd row43152330
3rd row210664570
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
128795050 1
 
3.6%
43152330 1
 
3.6%
210664570 1
 
3.6%

Length

2024-04-18T15:07:25.003030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:25.117878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
128795050 1
 
3.6%
43152330 1
 
3.6%
210664570 1
 
3.6%

총구매액(공사)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
1959000
 
1
130345300
 
1
124673380
 
1

Length

Max length9
Median length4
Mean length4.4642857
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row1959000
2nd row130345300
3rd row124673380
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
1959000 1
 
3.6%
130345300 1
 
3.6%
124673380 1
 
3.6%

Length

2024-04-18T15:07:25.226417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:25.326359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
1959000 1
 
3.6%
130345300 1
 
3.6%
124673380 1
 
3.6%

총구매액(용역)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
137770470
 
1
101187640
 
1
389194611
 
1

Length

Max length9
Median length4
Mean length4.5357143
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row137770470
2nd row101187640
3rd row389194611
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
137770470 1
 
3.6%
101187640 1
 
3.6%
389194611 1
 
3.6%

Length

2024-04-18T15:07:25.429077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:25.535152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
137770470 1
 
3.6%
101187640 1
 
3.6%
389194611 1
 
3.6%

중소기업제품구매액(계)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
91305490
 
1
139217220
 
1
657426651
 
1

Length

Max length9
Median length4
Mean length4.5
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row91305490
2nd row139217220
3rd row657426651
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
91305490 1
 
3.6%
139217220 1
 
3.6%
657426651 1
 
3.6%

Length

2024-04-18T15:07:25.647805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:25.747562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
91305490 1
 
3.6%
139217220 1
 
3.6%
657426651 1
 
3.6%

중소기업제품구매액(물품)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
58414020
 
1
30654120
 
1
195816660
 
1

Length

Max length9
Median length4
Mean length4.4642857
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row58414020
2nd row30654120
3rd row195816660
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
58414020 1
 
3.6%
30654120 1
 
3.6%
195816660 1
 
3.6%

Length

2024-04-18T15:07:25.849661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:25.954229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
58414020 1
 
3.6%
30654120 1
 
3.6%
195816660 1
 
3.6%

중소기업제품구매액(공사)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
1959000
 
1
34132000
 
1
124673380
 
1

Length

Max length9
Median length4
Mean length4.4285714
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row1959000
2nd row34132000
3rd row124673380
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
1959000 1
 
3.6%
34132000 1
 
3.6%
124673380 1
 
3.6%

Length

2024-04-18T15:07:26.056039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:26.155383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
1959000 1
 
3.6%
34132000 1
 
3.6%
124673380 1
 
3.6%

중소기업제품구매액(용역)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
30932470
 
1
74431100
 
1
336936611
 
1

Length

Max length9
Median length4
Mean length4.4642857
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row30932470
2nd row74431100
3rd row336936611
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
30932470 1
 
3.6%
74431100 1
 
3.6%
336936611 1
 
3.6%

Length

2024-04-18T15:07:26.264277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:26.380855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
30932470 1
 
3.6%
74431100 1
 
3.6%
336936611 1
 
3.6%

여성기업제품구매액(계)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
43924710
 
1
52239300
 
1
237464908
 
1

Length

Max length9
Median length4
Mean length4.4642857
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row43924710
2nd row52239300
3rd row237464908
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
43924710 1
 
3.6%
52239300 1
 
3.6%
237464908 1
 
3.6%

Length

2024-04-18T15:07:26.484198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:26.578277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
43924710 1
 
3.6%
52239300 1
 
3.6%
237464908 1
 
3.6%

여성기업제품구매액(물품)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
6154710
 
1
14318300
 
1
59203480
 
1

Length

Max length8
Median length4
Mean length4.3928571
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row6154710
2nd row14318300
3rd row59203480
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
6154710 1
 
3.6%
14318300 1
 
3.6%
59203480 1
 
3.6%

Length

2024-04-18T15:07:26.696317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:26.799706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
6154710 1
 
3.6%
14318300 1
 
3.6%
59203480 1
 
3.6%

여성기업제품구매액(공사)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
34132000
 
1
5621000
 
1
83826908
 
1

Length

Max length8
Median length4
Mean length4.3928571
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row34132000
2nd row5621000
3rd row83826908
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
34132000 1
 
3.6%
5621000 1
 
3.6%
83826908 1
 
3.6%

Length

2024-04-18T15:07:26.917952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:27.027121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
34132000 1
 
3.6%
5621000 1
 
3.6%
83826908 1
 
3.6%

여성기업제품구매액(용역)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
3638000
 
1
32300000
 
1
94434520
 
1

Length

Max length8
Median length4
Mean length4.3928571
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row3638000
2nd row32300000
3rd row94434520
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
3638000 1
 
3.6%
32300000 1
 
3.6%
94434520 1
 
3.6%

Length

2024-04-18T15:07:27.140570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:27.247461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
3638000 1
 
3.6%
32300000 1
 
3.6%
94434520 1
 
3.6%

장애인기업제품구매액(계)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
0
 
1
56884000
 
1
79128000
 
1

Length

Max length8
Median length4
Mean length4.1785714
Min length1

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row0
2nd row56884000
3rd row79128000
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
0 1
 
3.6%
56884000 1
 
3.6%
79128000 1
 
3.6%

Length

2024-04-18T15:07:27.364102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:27.480565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
0 1
 
3.6%
56884000 1
 
3.6%
79128000 1
 
3.6%

장애인기업제품구매액(물품)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
0
 
1
2884000
 
1
3024000
 
1

Length

Max length7
Median length4
Mean length4.1071429
Min length1

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row0
2nd row2884000
3rd row3024000
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
0 1
 
3.6%
2884000 1
 
3.6%
3024000 1
 
3.6%

Length

2024-04-18T15:07:27.599127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:27.711371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
0 1
 
3.6%
2884000 1
 
3.6%
3024000 1
 
3.6%

장애인기업제품구매액(공사)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
0
3 

Length

Max length4
Median length4
Mean length3.6785714
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
0 3
 
10.7%

Length

2024-04-18T15:07:27.827258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:27.917657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
0 3
 
10.7%

장애인기업제품구매액(용역)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
0
 
1
54000000
 
1
76104000
 
1

Length

Max length8
Median length4
Mean length4.1785714
Min length1

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row0
2nd row54000000
3rd row76104000
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
0 1
 
3.6%
54000000 1
 
3.6%
76104000 1
 
3.6%

Length

2024-04-18T15:07:28.031487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T15:07:28.132149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
0 1
 
3.6%
54000000 1
 
3.6%
76104000 1
 
3.6%

Correlations

2024-04-18T15:07:29.271891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분총구매액(계)총구매액(물품)총구매액(공사)총구매액(용역)중소기업제품구매액(계)중소기업제품구매액(물품)중소기업제품구매액(공사)중소기업제품구매액(용역)여성기업제품구매액(계)여성기업제품구매액(물품)여성기업제품구매액(공사)여성기업제품구매액(용역)장애인기업제품구매액(계)장애인기업제품구매액(물품)장애인기업제품구매액(용역)
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
총구매액(계)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
총구매액(물품)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
총구매액(공사)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
총구매액(용역)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중소기업제품구매액(계)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중소기업제품구매액(물품)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중소기업제품구매액(공사)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중소기업제품구매액(용역)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
여성기업제품구매액(계)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
여성기업제품구매액(물품)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
여성기업제품구매액(공사)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
여성기업제품구매액(용역)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장애인기업제품구매액(계)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장애인기업제품구매액(물품)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장애인기업제품구매액(용역)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-04-18T15:07:29.429437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
중소기업제품구매액(공사)중소기업제품구매액(용역)장애인기업제품구매액(계)총구매액(물품)여성기업제품구매액(공사)장애인기업제품구매액(공사)총구매액(용역)장애인기업제품구매액(물품)여성기업제품구매액(용역)총구매액(계)장애인기업제품구매액(용역)여성기업제품구매액(물품)중소기업제품구매액(물품)여성기업제품구매액(계)총구매액(공사)중소기업제품구매액(계)
중소기업제품구매액(공사)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중소기업제품구매액(용역)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장애인기업제품구매액(계)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
총구매액(물품)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
여성기업제품구매액(공사)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장애인기업제품구매액(공사)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
총구매액(용역)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장애인기업제품구매액(물품)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
여성기업제품구매액(용역)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
총구매액(계)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장애인기업제품구매액(용역)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
여성기업제품구매액(물품)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중소기업제품구매액(물품)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
여성기업제품구매액(계)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
총구매액(공사)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중소기업제품구매액(계)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-04-18T15:07:29.617099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총구매액(계)총구매액(물품)총구매액(공사)총구매액(용역)중소기업제품구매액(계)중소기업제품구매액(물품)중소기업제품구매액(공사)중소기업제품구매액(용역)여성기업제품구매액(계)여성기업제품구매액(물품)여성기업제품구매액(공사)여성기업제품구매액(용역)장애인기업제품구매액(계)장애인기업제품구매액(물품)장애인기업제품구매액(공사)장애인기업제품구매액(용역)
총구매액(계)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
총구매액(물품)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
총구매액(공사)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
총구매액(용역)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중소기업제품구매액(계)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중소기업제품구매액(물품)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중소기업제품구매액(공사)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
중소기업제품구매액(용역)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
여성기업제품구매액(계)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
여성기업제품구매액(물품)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
여성기업제품구매액(공사)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
여성기업제품구매액(용역)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장애인기업제품구매액(계)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장애인기업제품구매액(물품)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장애인기업제품구매액(공사)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
장애인기업제품구매액(용역)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2024-04-18T15:07:24.259482image/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.

Sample

구분총구매액(계)총구매액(물품)총구매액(공사)총구매액(용역)중소기업제품구매액(계)중소기업제품구매액(물품)중소기업제품구매액(공사)중소기업제품구매액(용역)여성기업제품구매액(계)여성기업제품구매액(물품)여성기업제품구매액(공사)여성기업제품구매액(용역)장애인기업제품구매액(계)장애인기업제품구매액(물품)장애인기업제품구매액(공사)장애인기업제품구매액(용역)
010월268524520128795050195900013777047091305490584140201959000309324704392471061547103413200036380000000
111월274685270431523301303453001011876401392172203065412034132000744311005223930014318300562100032300000568840002884000054000000
212월724532561210664570124673380389194611657426651195816660124673380336936611237464908592034808382690894434520791280003024000076104000
3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
구분총구매액(계)총구매액(물품)총구매액(공사)총구매액(용역)중소기업제품구매액(계)중소기업제품구매액(물품)중소기업제품구매액(공사)중소기업제품구매액(용역)여성기업제품구매액(계)여성기업제품구매액(물품)여성기업제품구매액(공사)여성기업제품구매액(용역)장애인기업제품구매액(계)장애인기업제품구매액(물품)장애인기업제품구매액(공사)장애인기업제품구매액(용역)
18<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
25<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

구분총구매액(계)총구매액(물품)총구매액(공사)총구매액(용역)중소기업제품구매액(계)중소기업제품구매액(물품)중소기업제품구매액(공사)중소기업제품구매액(용역)여성기업제품구매액(계)여성기업제품구매액(물품)여성기업제품구매액(공사)여성기업제품구매액(용역)장애인기업제품구매액(계)장애인기업제품구매액(물품)장애인기업제품구매액(공사)장애인기업제품구매액(용역)# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>25