Overview

Dataset statistics

Number of variables16
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory143.0 B

Variable types

Numeric4
Text2
Categorical10

Dataset

Description인천광역시 중구 관내에 위치한 쓰레기종량제봉투 발주정보에 대한 데이터 입니다.<br/><br/>파일명 인천광역시_중구_쓰레기종량제봉투_발주정보<br/>파일내용 전표번호, 발주일자, 협회코드, 제작업체, 수량, 수수료, 단가 등
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15060083&srcSe=7661IVAWM27C61E190

Alerts

조달수수료 has constant value ""Constant
미입고수량 has constant value ""Constant
로트(LOT)발생구분 has constant value ""Constant
전송구분 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 수량High correlation
수량 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
금액 is highly overall correlated with 수량High correlation
발주일자 is highly overall correlated with 협회코드 and 3 other fieldsHigh correlation
협회코드 is highly overall correlated with 발주일자 and 2 other fieldsHigh correlation
제작업체 is highly overall correlated with 발주일자 and 2 other fieldsHigh correlation
수정구분 is highly overall correlated with 발주일자High correlation
수정일자 is highly overall correlated with 발주일자 and 2 other fieldsHigh correlation
협회코드 is highly imbalanced (56.1%)Imbalance
제작업체 is highly imbalanced (56.1%)Imbalance
수정구분 is highly imbalanced (56.1%)Imbalance
연번 has unique valuesUnique
전표번호 has unique valuesUnique

Reproduction

Analysis started2024-03-18 04:35:52.302082
Analysis finished2024-03-18 04:35:54.170098
Duration1.87 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-03-18T13:35:54.219385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.05
Q16.25
median11.5
Q316.75
95-th percentile20.95
Maximum22
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.5646597
Kurtosis-1.2
Mean11.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum253
Variance42.166667
MonotonicityStrictly increasing
2024-03-18T13:35:54.317362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 1
 
4.5%
13 1
 
4.5%
22 1
 
4.5%
21 1
 
4.5%
20 1
 
4.5%
19 1
 
4.5%
18 1
 
4.5%
17 1
 
4.5%
16 1
 
4.5%
15 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1 1
4.5%
2 1
4.5%
3 1
4.5%
4 1
4.5%
5 1
4.5%
6 1
4.5%
7 1
4.5%
8 1
4.5%
9 1
4.5%
10 1
4.5%
ValueCountFrequency (%)
22 1
4.5%
21 1
4.5%
20 1
4.5%
19 1
4.5%
18 1
4.5%
17 1
4.5%
16 1
4.5%
15 1
4.5%
14 1
4.5%
13 1
4.5%

전표번호
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-03-18T13:35:54.467254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters198
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowA00001915
2nd rowA00001916
3rd rowA00001927
4th rowA00001917
5th rowA00001918
ValueCountFrequency (%)
a00001915 1
 
4.5%
a00001916 1
 
4.5%
a00001960 1
 
4.5%
a00001959 1
 
4.5%
a00001958 1
 
4.5%
a00001957 1
 
4.5%
a00001956 1
 
4.5%
a00001955 1
 
4.5%
a00001950 1
 
4.5%
a00001946 1
 
4.5%
Other values (12) 12
54.5%
2024-03-18T13:35:54.762992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 92
46.5%
1 28
 
14.1%
9 24
 
12.1%
A 22
 
11.1%
5 8
 
4.0%
6 5
 
2.5%
3 5
 
2.5%
2 4
 
2.0%
4 4
 
2.0%
7 3
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 176
88.9%
Uppercase Letter 22
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 92
52.3%
1 28
 
15.9%
9 24
 
13.6%
5 8
 
4.5%
6 5
 
2.8%
3 5
 
2.8%
2 4
 
2.3%
4 4
 
2.3%
7 3
 
1.7%
8 3
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
A 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 176
88.9%
Latin 22
 
11.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 92
52.3%
1 28
 
15.9%
9 24
 
13.6%
5 8
 
4.5%
6 5
 
2.8%
3 5
 
2.8%
2 4
 
2.3%
4 4
 
2.3%
7 3
 
1.7%
8 3
 
1.7%
Latin
ValueCountFrequency (%)
A 22
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 198
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 92
46.5%
1 28
 
14.1%
9 24
 
12.1%
A 22
 
11.1%
5 8
 
4.0%
6 5
 
2.5%
3 5
 
2.5%
2 4
 
2.0%
4 4
 
2.0%
7 3
 
1.5%

발주일자
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-01-31
7 
2023-02-22
6 
2023-01-25
2 
2023-04-10
2 
2023-05-26
2 
Other values (2)
3 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)4.5%

Sample

1st row2023-01-25
2nd row2023-01-25
3rd row2023-01-30
4th row2023-01-31
5th row2023-01-31

Common Values

ValueCountFrequency (%)
2023-01-31 7
31.8%
2023-02-22 6
27.3%
2023-01-25 2
 
9.1%
2023-04-10 2
 
9.1%
2023-05-26 2
 
9.1%
2023-08-08 2
 
9.1%
2023-01-30 1
 
4.5%

Length

2024-03-18T13:35:54.865653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:35:54.965298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-01-31 7
31.8%
2023-02-22 6
27.3%
2023-01-25 2
 
9.1%
2023-04-10 2
 
9.1%
2023-05-26 2
 
9.1%
2023-08-08 2
 
9.1%
2023-01-30 1
 
4.5%

봉투 종류
Text

Distinct17
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-03-18T13:35:55.110346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length9.4090909
Min length6

Characters and Unicode

Total characters207
Distinct characters32
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)59.1%

Sample

1st row대형폐기물스티커 1000원권
2nd row대형폐기물스티커 5000원권
3rd row일반용 75L
4th row일반용 5L
5th row일반용 10L
ValueCountFrequency (%)
일반용 8
16.0%
음식물 8
16.0%
필증 6
12.0%
대형폐기물스티커 4
8.0%
75l 4
8.0%
20l 3
 
6.0%
5l 2
 
4.0%
10l 2
 
4.0%
1000원권 2
 
4.0%
5000원권 2
 
4.0%
Other values (8) 9
18.0%
2024-03-18T13:35:55.531430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
 
13.5%
0 20
 
9.7%
L 18
 
8.7%
물 12
 
5.8%
용 10
 
4.8%
5 10
 
4.8%
일 8
 
3.9%
반 8
 
3.9%
식 8
 
3.9%
음 8
 
3.9%
Other values (22) 77
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 110
53.1%
Decimal Number 47
22.7%
Space Separator 28
 
13.5%
Uppercase Letter 18
 
8.7%
Open Punctuation 2
 
1.0%
Close Punctuation 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
물 12
 
10.9%
용 10
 
9.1%
일 8
 
7.3%
반 8
 
7.3%
식 8
 
7.3%
음 8
 
7.3%
증 6
 
5.5%
필 6
 
5.5%
권 4
 
3.6%
원 4
 
3.6%
Other values (12) 36
32.7%
Decimal Number
ValueCountFrequency (%)
0 20
42.6%
5 10
21.3%
2 6
 
12.8%
1 5
 
10.6%
7 4
 
8.5%
3 2
 
4.3%
Space Separator
ValueCountFrequency (%)
28
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 110
53.1%
Common 79
38.2%
Latin 18
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
물 12
 
10.9%
용 10
 
9.1%
일 8
 
7.3%
반 8
 
7.3%
식 8
 
7.3%
음 8
 
7.3%
증 6
 
5.5%
필 6
 
5.5%
권 4
 
3.6%
원 4
 
3.6%
Other values (12) 36
32.7%
Common
ValueCountFrequency (%)
28
35.4%
0 20
25.3%
5 10
 
12.7%
2 6
 
7.6%
1 5
 
6.3%
7 4
 
5.1%
( 2
 
2.5%
) 2
 
2.5%
3 2
 
2.5%
Latin
ValueCountFrequency (%)
L 18
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 110
53.1%
ASCII 97
46.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28
28.9%
0 20
20.6%
L 18
18.6%
5 10
 
10.3%
2 6
 
6.2%
1 5
 
5.2%
7 4
 
4.1%
( 2
 
2.1%
) 2
 
2.1%
3 2
 
2.1%
Hangul
ValueCountFrequency (%)
물 12
 
10.9%
용 10
 
9.1%
일 8
 
7.3%
반 8
 
7.3%
식 8
 
7.3%
음 8
 
7.3%
증 6
 
5.5%
필 6
 
5.5%
권 4
 
3.6%
원 4
 
3.6%
Other values (12) 36
32.7%

협회코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
1
20 
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 20
90.9%
3 2
 
9.1%

Length

2024-03-18T13:35:55.663904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:35:55.759611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 20
90.9%
3 2
 
9.1%

제작업체
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
영광산업
20 
(주)제임스케미칼
 
2

Length

Max length9
Median length4
Mean length4.4545455
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row(주)제임스케미칼
2nd row(주)제임스케미칼
3rd row영광산업
4th row영광산업
5th row영광산업

Common Values

ValueCountFrequency (%)
영광산업 20
90.9%
(주)제임스케미칼 2
 
9.1%

Length

2024-03-18T13:35:55.852861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:35:55.973252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영광산업 20
90.9%
주)제임스케미칼 2
 
9.1%

수량
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean328118.18
Minimum100
Maximum1450000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-03-18T13:35:56.095940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile790
Q135000
median159900
Q3525000
95-th percentile1277495
Maximum1450000
Range1449900
Interquartile range (IQR)490000

Descriptive statistics

Standard deviation421224.59
Coefficient of variation (CV)1.2837588
Kurtosis1.8775359
Mean328118.18
Median Absolute Deviation (MAD)140100
Skewness1.5962745
Sum7218600
Variance1.7743016 × 1011
MonotonicityNot monotonic
2024-03-18T13:35:56.241456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
50000 3
13.6%
300000 3
13.6%
649800 2
 
9.1%
30000 2
 
9.1%
200000 1
 
4.5%
600000 1
 
4.5%
1450000 1
 
4.5%
849900 1
 
4.5%
139800 1
 
4.5%
1300000 1
 
4.5%
Other values (6) 6
27.3%
ValueCountFrequency (%)
100 1
 
4.5%
200 1
 
4.5%
12000 1
 
4.5%
17000 1
 
4.5%
30000 2
9.1%
50000 3
13.6%
60000 1
 
4.5%
139800 1
 
4.5%
180000 1
 
4.5%
200000 1
 
4.5%
ValueCountFrequency (%)
1450000 1
 
4.5%
1300000 1
 
4.5%
849900 1
 
4.5%
649800 2
9.1%
600000 1
 
4.5%
300000 3
13.6%
200000 1
 
4.5%
180000 1
 
4.5%
139800 1
 
4.5%
60000 1
 
4.5%

조달수수료
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
0
22 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22
100.0%

Length

2024-03-18T13:35:56.361633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:35:56.445534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 22
100.0%

조달단가
Real number (ℝ)

Distinct11
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.730455
Minimum1
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-03-18T13:35:56.515040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median51.875
Q3124.91
95-th percentile133.7865
Maximum134
Range133
Interquartile range (IQR)123.91

Descriptive statistics

Standard deviation56.892269
Coefficient of variation (CV)0.89270145
Kurtosis-1.8937409
Mean63.730455
Median Absolute Deviation (MAD)50.875
Skewness0.12445674
Sum1402.07
Variance3236.7303
MonotonicityNot monotonic
2024-03-18T13:35:56.605390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1.0 7
31.8%
124.91 3
13.6%
120.0 2
 
9.1%
134.0 2
 
9.1%
129.73 2
 
9.1%
31.42 1
 
4.5%
41.64 1
 
4.5%
62.11 1
 
4.5%
64.13 1
 
4.5%
24.26 1
 
4.5%
ValueCountFrequency (%)
1.0 7
31.8%
24.26 1
 
4.5%
29.32 1
 
4.5%
31.42 1
 
4.5%
41.64 1
 
4.5%
62.11 1
 
4.5%
64.13 1
 
4.5%
120.0 2
 
9.1%
124.91 3
13.6%
129.73 2
 
9.1%
ValueCountFrequency (%)
134.0 2
9.1%
129.73 2
9.1%
124.91 3
13.6%
120.0 2
9.1%
64.13 1
 
4.5%
62.11 1
 
4.5%
41.64 1
 
4.5%
31.42 1
 
4.5%
29.32 1
 
4.5%
24.26 1
 
4.5%

금액
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23162401
Minimum12491
Maximum1.0616101 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-03-18T13:35:56.702089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12491
5-th percentile26148.7
Q179950
median4020000
Q320937000
95-th percentile89771453
Maximum1.0616101 × 108
Range1.0614852 × 108
Interquartile range (IQR)20857050

Descriptive statistics

Standard deviation37227997
Coefficient of variation (CV)1.6072599
Kurtosis0.12410176
Mean23162401
Median Absolute Deviation (MAD)3980000
Skewness1.382528
Sum5.0957282 × 108
Variance1.3859238 × 1015
MonotonicityNot monotonic
2024-03-18T13:35:56.796840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
30000 2
 
9.1%
6000000 1
 
4.5%
6700000 1
 
4.5%
1608000 1
 
4.5%
2040000 1
 
4.5%
8796000 1
 
4.5%
7278000 1
 
4.5%
12491 1
 
4.5%
25946 1
 
4.5%
60000 1
 
4.5%
Other values (11) 11
50.0%
ValueCountFrequency (%)
12491 1
4.5%
25946 1
4.5%
30000 2
9.1%
50000 1
4.5%
60000 1
4.5%
139800 1
4.5%
180000 1
4.5%
300000 1
4.5%
1608000 1
4.5%
2040000 1
4.5%
ValueCountFrequency (%)
106161009 1
4.5%
90059500 1
4.5%
84298554 1
4.5%
83369000 1
4.5%
81166518 1
4.5%
24984000 1
4.5%
8796000 1
4.5%
7278000 1
4.5%
6700000 1
4.5%
6284000 1
4.5%

미입고수량
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
0
22 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22
100.0%

Length

2024-03-18T13:35:56.893153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:35:56.969026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 22
100.0%

수정구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
M
20 
D
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowM
3rd rowD
4th rowM
5th rowM

Common Values

ValueCountFrequency (%)
M 20
90.9%
D 2
 
9.1%

Length

2024-03-18T13:35:57.058172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:35:57.135241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 20
90.9%
d 2
 
9.1%

수정일자
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-01-31
7 
2023-02-22
6 
2023-01-25
2 
2023-04-10
2 
2023-05-26
2 
Other values (2)
3 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)4.5%

Sample

1st row2023-01-25
2nd row2023-01-25
3rd row2023-01-31
4th row2023-08-16
5th row2023-01-31

Common Values

ValueCountFrequency (%)
2023-01-31 7
31.8%
2023-02-22 6
27.3%
2023-01-25 2
 
9.1%
2023-04-10 2
 
9.1%
2023-05-26 2
 
9.1%
2023-08-08 2
 
9.1%
2023-08-16 1
 
4.5%

Length

2024-03-18T13:35:57.216433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:35:57.303705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-01-31 7
31.8%
2023-02-22 6
27.3%
2023-01-25 2
 
9.1%
2023-04-10 2
 
9.1%
2023-05-26 2
 
9.1%
2023-08-08 2
 
9.1%
2023-08-16 1
 
4.5%

로트(LOT)발생구분
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
0
22 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22
100.0%

Length

2024-03-18T13:35:57.415190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:35:57.497935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 22
100.0%

전송구분
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
0
22 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22
100.0%

Length

2024-03-18T13:35:57.575408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:35:57.661052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 22
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-08-30
22 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-30
2nd row2023-08-30
3rd row2023-08-30
4th row2023-08-30
5th row2023-08-30

Common Values

ValueCountFrequency (%)
2023-08-30 22
100.0%

Length

2024-03-18T13:35:57.747555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:35:57.834718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-30 22
100.0%

Interactions

2024-03-18T13:35:53.540452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:52.689157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:52.941239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:53.234960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:53.602242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:52.745050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:53.014606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:53.296567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:53.678298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:52.812793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:53.087944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:53.372222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:53.768371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:52.879173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:53.161855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:35:53.456884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T13:35:57.899880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전표번호발주일자봉투 종류협회코드제작업체수량조달단가금액수정구분수정일자
연번1.0001.0000.7440.7420.7800.7800.4130.3270.4320.0000.744
전표번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
발주일자0.7441.0001.0000.0001.0001.0000.0000.7880.0000.5520.994
봉투 종류0.7421.0000.0001.0000.0000.0000.8101.0000.5210.0000.000
협회코드0.7801.0001.0000.0001.0000.8980.0000.0000.0000.0001.000
제작업체0.7801.0001.0000.0000.8981.0000.0000.0000.0000.0001.000
수량0.4131.0000.0000.8100.0000.0001.0000.7790.8910.0000.647
조달단가0.3271.0000.7881.0000.0000.0000.7791.0000.6870.0000.870
금액0.4321.0000.0000.5210.0000.0000.8910.6871.0000.0000.000
수정구분0.0001.0000.5520.0000.0000.0000.0000.0000.0001.0000.000
수정일자0.7441.0000.9940.0001.0001.0000.6470.8700.0000.0001.000
2024-03-18T13:35:58.017854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제작업체수정일자발주일자수정구분협회코드
제작업체1.0000.8660.8660.0000.708
수정일자0.8661.0000.8780.0000.866
발주일자0.8660.8781.0000.5050.866
수정구분0.0000.0000.5051.0000.000
협회코드0.7080.8660.8660.0001.000
2024-03-18T13:35:58.107570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번수량조달단가금액발주일자협회코드제작업체수정구분수정일자
연번1.000-0.504-0.143-0.4730.4250.4640.4640.0000.425
수량-0.5041.000-0.0590.8510.0000.0000.0000.0000.241
조달단가-0.143-0.0591.0000.3610.3640.0000.0000.0000.472
금액-0.4730.8510.3611.0000.0000.0000.0000.0000.000
발주일자0.4250.0000.3640.0001.0000.8660.8660.5050.878
협회코드0.4640.0000.0000.0000.8661.0000.7080.0000.866
제작업체0.4640.0000.0000.0000.8660.7081.0000.0000.866
수정구분0.0000.0000.0000.0000.5050.0000.0001.0000.000
수정일자0.4250.2410.4720.0000.8780.8660.8660.0001.000

Missing values

2024-03-18T13:35:53.909552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:35:54.107267image/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

연번전표번호발주일자봉투 종류협회코드제작업체수량조달수수료조달단가금액미입고수량수정구분수정일자로트(LOT)발생구분전송구분데이터기준일자
01A000019152023-01-25대형폐기물스티커 1000원권3(주)제임스케미칼500000120.060000000M2023-01-25002023-08-30
12A000019162023-01-25대형폐기물스티커 5000원권3(주)제임스케미칼500000134.067000000M2023-01-25002023-08-30
23A000019272023-01-30일반용 75L1영광산업6498000124.91811665180D2023-01-31002023-08-30
34A000019172023-01-31일반용 5L1영광산업200000031.4262840000M2023-08-16002023-08-30
45A000019182023-01-31일반용 10L1영광산업600000041.64249840000M2023-01-31002023-08-30
56A000019202023-01-31일반용 20L1영광산업1450000062.11900595000M2023-01-31002023-08-30
67A000019232023-01-31일반용 50L1영광산업6498000129.73842985540M2023-01-31002023-08-30
78A000019392023-01-31일반용 75L1영광산업8499000124.911061610090M2023-01-31002023-08-30
89A000019322023-01-31공공용 75L1영광산업13980001.01398000D2023-01-31002023-08-30
910A000019382023-01-31재사용 20L1영광산업1300000064.13833690000M2023-01-31002023-08-30
연번전표번호발주일자봉투 종류협회코드제작업체수량조달수수료조달단가금액미입고수량수정구분수정일자로트(LOT)발생구분전송구분데이터기준일자
1213A000019432023-02-22음식물 필증 5L1영광산업3000001.0300000M2023-02-22002023-08-30
1314A000019462023-02-22음식물 필증 10L1영광산업5000001.0500000M2023-02-22002023-08-30
1415A000019502023-02-22음식물 필증 20L1영광산업6000001.0600000M2023-02-22002023-08-30
1516A000019552023-02-22음식물 필증 120L1영광산업3000001.0300000M2023-02-22002023-08-30
1617A000019562023-04-10일반용 50L1영광산업2000129.73259460M2023-04-10002023-08-30
1718A000019572023-04-10일반용 75L1영광산업1000124.91124910M2023-04-10002023-08-30
1819A000019582023-05-26음식물 2L(영종)1영광산업300000024.2672780000M2023-05-26002023-08-30
1920A000019592023-05-26음식물 3L(영종)1영광산업300000029.3287960000M2023-05-26002023-08-30
2021A000019602023-08-08대형폐기물스티커 1000원권1영광산업170000120.020400000M2023-08-08002023-08-30
2122A000019612023-08-08대형폐기물스티커 5000원권1영광산업120000134.016080000M2023-08-08002023-08-30