Overview

Dataset statistics

Number of variables15
Number of observations1912
Missing cells4802
Missing cells (%)16.7%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory237.3 KiB
Average record size in memory127.1 B

Variable types

Text1
DateTime2
Categorical8
Numeric4

Dataset

Description인천광역시 서구 쓰레기종량제봉투 발주정보에 대한 데이터로 발주일자, 봉투 종류, 수량 등의 정보가 포함되어 있습니다.
Author인천광역시 서구
URLhttps://www.data.go.kr/data/15090855/fileData.do

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates
데이터기준일자 is highly overall correlated with 수량 and 10 other fieldsHigh correlation
조달수수료 is highly overall correlated with 제작업체 and 2 other fieldsHigh correlation
전송구분 is highly overall correlated with 수량 and 10 other fieldsHigh correlation
제작업체 is highly overall correlated with 조달수수료 and 2 other fieldsHigh correlation
협회코드 is highly overall correlated with 전송구분 and 1 other fieldsHigh correlation
봉투 종류 is highly overall correlated with 조달단가 and 2 other fieldsHigh correlation
수정구분 is highly overall correlated with 전송구분 and 1 other fieldsHigh correlation
LOT발생구분 is highly overall correlated with 전송구분 and 1 other fieldsHigh correlation
수량 is highly overall correlated with 금액 and 2 other fieldsHigh correlation
조달단가 is highly overall correlated with 봉투 종류 and 2 other fieldsHigh correlation
금액 is highly overall correlated with 수량 and 2 other fieldsHigh correlation
미입고수량 is highly overall correlated with 전송구분 and 1 other fieldsHigh correlation
전표번호 has 686 (35.9%) missing valuesMissing
발주일자 has 686 (35.9%) missing valuesMissing
수량 has 686 (35.9%) missing valuesMissing
조달단가 has 686 (35.9%) missing valuesMissing
금액 has 686 (35.9%) missing valuesMissing
미입고수량 has 686 (35.9%) missing valuesMissing
수정일자 has 686 (35.9%) missing valuesMissing
미입고수량 has 1189 (62.2%) zerosZeros

Reproduction

Analysis started2023-12-12 10:32:04.283845
Analysis finished2023-12-12 10:32:08.149718
Duration3.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전표번호
Text

MISSING 

Distinct1226
Distinct (%)100.0%
Missing686
Missing (%)35.9%
Memory size15.1 KiB
2023-12-12T19:32:08.454171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters11034
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

Unique1226 ?
Unique (%)100.0%

Sample

1st rowA00000001
2nd rowA00000002
3rd rowA00000004
4th rowA00000007
5th rowA00000011
ValueCountFrequency (%)
a00000022 1
 
0.1%
a00000442 1
 
0.1%
a00000359 1
 
0.1%
a00000358 1
 
0.1%
a00000357 1
 
0.1%
a00000354 1
 
0.1%
a00000352 1
 
0.1%
a00000351 1
 
0.1%
a00000349 1
 
0.1%
a00000347 1
 
0.1%
Other values (1216) 1216
99.2%
2023-12-12T19:32:09.025620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5883
53.3%
A 1226
 
11.1%
1 722
 
6.5%
2 634
 
5.7%
3 451
 
4.1%
4 361
 
3.3%
6 357
 
3.2%
9 356
 
3.2%
5 350
 
3.2%
8 349
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9808
88.9%
Uppercase Letter 1226
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5883
60.0%
1 722
 
7.4%
2 634
 
6.5%
3 451
 
4.6%
4 361
 
3.7%
6 357
 
3.6%
9 356
 
3.6%
5 350
 
3.6%
8 349
 
3.6%
7 345
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
A 1226
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9808
88.9%
Latin 1226
 
11.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5883
60.0%
1 722
 
7.4%
2 634
 
6.5%
3 451
 
4.6%
4 361
 
3.7%
6 357
 
3.6%
9 356
 
3.6%
5 350
 
3.6%
8 349
 
3.6%
7 345
 
3.5%
Latin
ValueCountFrequency (%)
A 1226
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11034
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5883
53.3%
A 1226
 
11.1%
1 722
 
6.5%
2 634
 
5.7%
3 451
 
4.1%
4 361
 
3.3%
6 357
 
3.2%
9 356
 
3.2%
5 350
 
3.2%
8 349
 
3.2%

발주일자
Date

MISSING 

Distinct327
Distinct (%)26.7%
Missing686
Missing (%)35.9%
Memory size15.1 KiB
Minimum2000-12-08 00:00:00
Maximum2022-08-05 00:00:00
2023-12-12T19:32:09.198134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:09.370450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

봉투 종류
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size15.1 KiB
<NA>
686 
일반용 10L
115 
일반용 20L
113 
일반용 50L
100 
일반용 100L
92 
Other values (30)
806 

Length

Max length12
Median length11
Mean length6.5632845
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반용 5L
2nd row일반용 5L
3rd row일반용 10L
4th row일반용 10L
5th row일반용 20L

Common Values

ValueCountFrequency (%)
<NA> 686
35.9%
일반용 10L 115
 
6.0%
일반용 20L 113
 
5.9%
일반용 50L 100
 
5.2%
일반용 100L 92
 
4.8%
일반용 5L 67
 
3.5%
재사용 20L 55
 
2.9%
사업계용125L 50
 
2.6%
사업계용 60L 46
 
2.4%
스티커 5000원권 46
 
2.4%
Other values (25) 542
28.3%

Length

2023-12-12T19:32:09.544170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 686
22.8%
일반용 545
18.1%
20l 185
 
6.2%
스티커 148
 
4.9%
10l 147
 
4.9%
50l 127
 
4.2%
재사용 107
 
3.6%
필증 95
 
3.2%
5l 94
 
3.1%
100l 92
 
3.1%
Other values (22) 780
25.9%

협회코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.1 KiB
<NA>
686 
경인프라스틱 조합
537 
인천.경기프라스틱공업협동조합
537 
스티커발주
123 
직발주
 
29

Length

Max length15
Median length9
Mean length8.542887
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경인프라스틱 조합
2nd row인천.경기프라스틱공업협동조합
3rd row경인프라스틱 조합
4th row인천.경기프라스틱공업협동조합
5th row경인프라스틱 조합

Common Values

ValueCountFrequency (%)
<NA> 686
35.9%
경인프라스틱 조합 537
28.1%
인천.경기프라스틱공업협동조합 537
28.1%
스티커발주 123
 
6.4%
직발주 29
 
1.5%

Length

2023-12-12T19:32:10.081033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:10.216946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 686
28.0%
경인프라스틱 537
21.9%
조합 537
21.9%
인천.경기프라스틱공업협동조합 537
21.9%
스티커발주 123
 
5.0%
직발주 29
 
1.2%

제작업체
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size15.1 KiB
<NA>
686 
장애인직업재활시설
455 
세창화학
240 
에스엠티
170 
성광디자인(주)
161 
Other values (8)
200 

Length

Max length9
Median length4
Mean length5.707636
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 686
35.9%
장애인직업재활시설 455
23.8%
세창화학 240
 
12.6%
에스엠티 170
 
8.9%
성광디자인(주) 161
 
8.4%
대화수지공업 105
 
5.5%
제임스케미칼 52
 
2.7%
영광산업 20
 
1.0%
대영화학공업 8
 
0.4%
동양인쇄사 8
 
0.4%
Other values (3) 7
 
0.4%

Length

2023-12-12T19:32:10.379047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 686
35.9%
장애인직업재활시설 455
23.8%
세창화학 240
 
12.6%
에스엠티 170
 
8.9%
성광디자인(주 161
 
8.4%
대화수지공업 105
 
5.5%
제임스케미칼 52
 
2.7%
영광산업 20
 
1.0%
대영화학공업 8
 
0.4%
동양인쇄사 8
 
0.4%
Other values (3) 7
 
0.4%

수량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct78
Distinct (%)6.4%
Missing686
Missing (%)35.9%
Infinite0
Infinite (%)0.0%
Mean166742.9
Minimum100
Maximum900000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.9 KiB
2023-12-12T19:32:10.531596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile1000
Q120000
median100000
Q3300000
95-th percentile500000
Maximum900000
Range899900
Interquartile range (IQR)280000

Descriptive statistics

Standard deviation186163.42
Coefficient of variation (CV)1.1164698
Kurtosis0.58320104
Mean166742.9
Median Absolute Deviation (MAD)92000
Skewness1.1990172
Sum2.044268 × 108
Variance3.4656821 × 1010
MonotonicityNot monotonic
2023-12-12T19:32:10.692140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 148
 
7.7%
500000 125
 
6.5%
200000 116
 
6.1%
10000 96
 
5.0%
20000 91
 
4.8%
300000 84
 
4.4%
1000 62
 
3.2%
50000 48
 
2.5%
5000 45
 
2.4%
400000 40
 
2.1%
Other values (68) 371
19.4%
(Missing) 686
35.9%
ValueCountFrequency (%)
100 2
 
0.1%
500 2
 
0.1%
1000 62
3.2%
2000 22
 
1.2%
3000 8
 
0.4%
4000 4
 
0.2%
5000 45
2.4%
6000 9
 
0.5%
7000 2
 
0.1%
8000 15
 
0.8%
ValueCountFrequency (%)
900000 2
 
0.1%
850000 2
 
0.1%
800000 2
 
0.1%
780000 2
 
0.1%
700000 11
 
0.6%
640000 2
 
0.1%
600000 12
 
0.6%
580000 4
 
0.2%
550000 2
 
0.1%
500000 125
6.5%

조달수수료
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.1 KiB
0.0
1031 
<NA>
686 
0.8
 
98
0.54
 
66
0.72
 
31

Length

Max length4
Median length3
Mean length3.4095188
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.8
2nd row0.8
3rd row0.8
4th row0.8
5th row0.8

Common Values

ValueCountFrequency (%)
0.0 1031
53.9%
<NA> 686
35.9%
0.8 98
 
5.1%
0.54 66
 
3.5%
0.72 31
 
1.6%

Length

2023-12-12T19:32:10.850594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:10.968229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 1031
53.9%
na 686
35.9%
0.8 98
 
5.1%
0.54 66
 
3.5%
0.72 31
 
1.6%

조달단가
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct93
Distinct (%)7.6%
Missing686
Missing (%)35.9%
Infinite0
Infinite (%)0.0%
Mean90.193206
Minimum1
Maximum456
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.9 KiB
2023-12-12T19:32:11.099618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q131
median54
Q3132
95-th percentile226
Maximum456
Range455
Interquartile range (IQR)101

Descriptive statistics

Standard deviation90.941963
Coefficient of variation (CV)1.0083017
Kurtosis5.5344139
Mean90.193206
Median Absolute Deviation (MAD)34
Skewness2.1481863
Sum110576.87
Variance8270.4406
MonotonicityNot monotonic
2023-12-12T19:32:11.249246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
139.0 89
 
4.7%
55.0 69
 
3.6%
1.0 66
 
3.5%
53.0 52
 
2.7%
114.0 51
 
2.7%
34.0 45
 
2.4%
21.0 41
 
2.1%
36.0 40
 
2.1%
41.0 39
 
2.0%
132.0 38
 
2.0%
Other values (83) 696
36.4%
(Missing) 686
35.9%
ValueCountFrequency (%)
1.0 66
3.5%
13.35 2
 
0.1%
13.4 4
 
0.2%
13.8 5
 
0.3%
16.0 2
 
0.1%
17.05 2
 
0.1%
18.3 16
 
0.8%
19.6 9
 
0.5%
20.0 26
 
1.4%
20.93 4
 
0.2%
ValueCountFrequency (%)
456.0 30
1.6%
421.0 8
 
0.4%
352.0 7
 
0.4%
330.0 3
 
0.2%
242.0 2
 
0.1%
226.0 28
1.5%
216.0 6
 
0.3%
212.0 8
 
0.4%
208.0 14
0.7%
207.0 29
1.5%

금액
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct337
Distinct (%)27.5%
Missing686
Missing (%)35.9%
Infinite0
Infinite (%)0.0%
Mean8711051.4
Minimum500
Maximum56160000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.9 KiB
2023-12-12T19:32:11.428200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile14209.25
Q11591500
median5200000
Q311897900
95-th percentile27575000
Maximum56160000
Range56159500
Interquartile range (IQR)10306400

Descriptive statistics

Standard deviation9518100.2
Coefficient of variation (CV)1.0926465
Kurtosis2.6021649
Mean8711051.4
Median Absolute Deviation (MAD)4198250
Skewness1.6206461
Sum1.0679749 × 1010
Variance9.0594231 × 1013
MonotonicityNot monotonic
2023-12-12T19:32:11.592502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000 54
 
2.8%
2780000 29
 
1.5%
1390000 22
 
1.2%
11000000 18
 
0.9%
1320000 17
 
0.9%
16500000 15
 
0.8%
2900000 14
 
0.7%
5200000 13
 
0.7%
11400000 12
 
0.6%
21600000 12
 
0.6%
Other values (327) 1020
53.3%
(Missing) 686
35.9%
ValueCountFrequency (%)
500 2
 
0.1%
1000 54
2.8%
2000 4
 
0.2%
12279 2
 
0.1%
20000 4
 
0.2%
41000 1
 
0.1%
52000 2
 
0.1%
100000 2
 
0.1%
105000 1
 
0.1%
109000 2
 
0.1%
ValueCountFrequency (%)
56160000 2
0.1%
46750000 2
0.1%
43200000 2
0.1%
42164840 2
0.1%
41600000 4
0.2%
41400000 4
0.2%
38605000 2
0.1%
38600000 2
0.1%
38500000 4
0.2%
37440000 2
0.1%

미입고수량
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct13
Distinct (%)1.1%
Missing686
Missing (%)35.9%
Infinite0
Infinite (%)0.0%
Mean862.15334
Minimum-700000
Maximum400000
Zeros1189
Zeros (%)62.2%
Negative4
Negative (%)0.2%
Memory size16.9 KiB
2023-12-12T19:32:11.722270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-700000
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum400000
Range1100000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation37324.388
Coefficient of variation (CV)43.292053
Kurtosis236.38226
Mean862.15334
Median Absolute Deviation (MAD)0
Skewness-7.0386523
Sum1057000
Variance1.39311 × 109
MonotonicityNot monotonic
2023-12-12T19:32:11.851481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 1189
62.2%
5000 10
 
0.5%
1000 8
 
0.4%
300000 4
 
0.2%
8000 2
 
0.1%
150000 2
 
0.1%
400000 2
 
0.1%
30000 2
 
0.1%
-700000 2
 
0.1%
-1000 2
 
0.1%
Other values (3) 3
 
0.2%
(Missing) 686
35.9%
ValueCountFrequency (%)
-700000 2
 
0.1%
-1000 2
 
0.1%
0 1189
62.2%
1000 8
 
0.4%
3000 1
 
0.1%
5000 10
 
0.5%
7000 1
 
0.1%
8000 2
 
0.1%
15000 1
 
0.1%
30000 2
 
0.1%
ValueCountFrequency (%)
400000 2
 
0.1%
300000 4
 
0.2%
150000 2
 
0.1%
30000 2
 
0.1%
15000 1
 
0.1%
8000 2
 
0.1%
7000 1
 
0.1%
5000 10
0.5%
3000 1
 
0.1%
1000 8
0.4%

수정구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.1 KiB
M
1187 
<NA>
686 
D
 
35
I
 
4

Length

Max length4
Median length1
Mean length2.0763598
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 1187
62.1%
<NA> 686
35.9%
D 35
 
1.8%
I 4
 
0.2%

Length

2023-12-12T19:32:12.020830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:12.155887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 1187
62.1%
na 686
35.9%
d 35
 
1.8%
i 4
 
0.2%

수정일자
Date

MISSING 

Distinct503
Distinct (%)41.0%
Missing686
Missing (%)35.9%
Memory size15.1 KiB
Minimum2001-01-18 00:00:00
Maximum2022-08-31 00:00:00
2023-12-12T19:32:12.324068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:12.510109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

LOT발생구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.1 KiB
1
1218 
<NA>
686 
0
 
8

Length

Max length4
Median length1
Mean length2.0763598
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 1218
63.7%
<NA> 686
35.9%
0 8
 
0.4%

Length

2023-12-12T19:32:12.668609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:12.795215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1218
63.7%
na 686
35.9%
0 8
 
0.4%

전송구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.1 KiB
0
1226 
<NA>
686 

Length

Max length4
Median length1
Mean length2.0763598
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1226
64.1%
<NA> 686
35.9%

Length

2023-12-12T19:32:12.922940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:13.081579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1226
64.1%
na 686
35.9%

데이터기준일자
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.1 KiB
2022-09-06
1226 
<NA>
686 

Length

Max length10
Median length10
Mean length7.8472803
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-06
2nd row2022-09-06
3rd row2022-09-06
4th row2022-09-06
5th row2022-09-06

Common Values

ValueCountFrequency (%)
2022-09-06 1226
64.1%
<NA> 686
35.9%

Length

2023-12-12T19:32:13.221641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:32:13.341657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-06 1226
64.1%
na 686
35.9%

Interactions

2023-12-12T19:32:06.864828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:05.406383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:05.893620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:06.427716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:06.985268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:05.521297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:06.023144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:06.535108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:07.098416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:05.634477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:06.143039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:06.629300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:07.217136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:05.770676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:06.298404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:32:06.750502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:32:13.436928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
봉투 종류협회코드제작업체수량조달수수료조달단가금액미입고수량수정구분LOT발생구분
봉투 종류1.0000.6630.8560.7380.4680.9300.6650.2730.4290.142
협회코드0.6631.0000.7640.2670.2210.5840.2140.0000.0240.145
제작업체0.8560.7641.0000.4370.8510.6450.3630.2350.4670.129
수량0.7380.2670.4371.0000.3490.4190.8700.2050.0870.025
조달수수료0.4680.2210.8510.3491.0000.2790.3070.0000.0270.000
조달단가0.9300.5840.6450.4190.2791.0000.4220.0890.0480.041
금액0.6650.2140.3630.8700.3070.4221.0000.1830.0770.000
미입고수량0.2730.0000.2350.2050.0000.0890.1831.0000.6730.000
수정구분0.4290.0240.4670.0870.0270.0480.0770.6731.0000.292
LOT발생구분0.1420.1450.1290.0250.0000.0410.0000.0000.2921.000
2023-12-12T19:32:13.611300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터기준일자조달수수료전송구분제작업체협회코드봉투 종류수정구분LOT발생구분
데이터기준일자1.0001.0001.0001.0001.0001.0001.0001.000
조달수수료1.0001.0001.0000.5490.0880.2540.0260.000
전송구분1.0001.0001.0001.0001.0001.0001.0001.000
제작업체1.0000.5491.0001.0000.4500.4770.2380.100
협회코드1.0000.0881.0000.4501.0000.4000.0220.096
봉투 종류1.0000.2541.0000.4770.4001.0000.2370.112
수정구분1.0000.0261.0000.2380.0220.2371.0000.471
LOT발생구분1.0000.0001.0000.1000.0960.1120.4711.000
2023-12-12T19:32:13.773820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수량조달단가금액미입고수량봉투 종류협회코드제작업체조달수수료수정구분LOT발생구분전송구분데이터기준일자
수량1.000-0.3420.849-0.1540.3610.1620.2000.2150.0510.0191.0001.000
조달단가-0.3421.0000.117-0.0240.6970.2920.3370.1280.0300.0301.0001.000
금액0.8490.1171.000-0.1450.2990.1280.1610.1880.0450.0001.0001.000
미입고수량-0.154-0.024-0.1451.0000.0970.0000.0840.0870.3310.0001.0001.000
봉투 종류0.3610.6970.2990.0971.0000.4000.4770.2540.2370.1121.0001.000
협회코드0.1620.2920.1280.0000.4001.0000.4500.0880.0220.0961.0001.000
제작업체0.2000.3370.1610.0840.4770.4501.0000.5490.2380.1001.0001.000
조달수수료0.2150.1280.1880.0870.2540.0880.5491.0000.0260.0001.0001.000
수정구분0.0510.0300.0450.3310.2370.0220.2380.0261.0000.4711.0001.000
LOT발생구분0.0190.0300.0000.0000.1120.0960.1000.0000.4711.0001.0001.000
전송구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
데이터기준일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T19:32:07.414899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:32:07.670182image/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.
2023-12-12T19:32:07.899367image/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

전표번호발주일자봉투 종류협회코드제작업체수량조달수수료조달단가금액미입고수량수정구분수정일자LOT발생구분전송구분데이터기준일자
0A000000012000-12-08일반용 5L경인프라스틱 조합대화수지공업1000000.813.3513350000M2001-01-18102022-09-06
1A000000022000-12-08일반용 5L인천.경기프라스틱공업협동조합대화수지공업1000000.813.3513350000M2001-01-18102022-09-06
2A000000042000-12-08일반용 10L경인프라스틱 조합대화수지공업5000000.817.0585250000M2001-01-18102022-09-06
3A000000072000-12-08일반용 10L인천.경기프라스틱공업협동조합대화수지공업5000000.817.0585250000M2001-01-18102022-09-06
4A000000112000-12-08일반용 20L경인프라스틱 조합대화수지공업3000000.826.9780910000M2001-01-18102022-09-06
5A000000122001-02-07일반용 20L인천.경기프라스틱공업협동조합대화수지공업3000000.826.9780910000M2001-06-05102022-09-06
6A000000132001-02-07일반용 50L경인프라스틱 조합제임스케미칼800000.859.8847904000M2001-06-05102022-09-06
7A000000152001-02-07일반용 50L인천.경기프라스틱공업협동조합제임스케미칼800000.859.8847904000M2001-06-05102022-09-06
8A000000182001-02-07일반용 100L경인프라스틱 조합대화수지공업400000.8108.5843432000M2001-06-05102022-09-06
9A000000192001-04-12일반용 100L인천.경기프라스틱공업협동조합대화수지공업400000.8108.5843432000M2001-06-05102022-09-06
전표번호발주일자봉투 종류협회코드제작업체수량조달수수료조달단가금액미입고수량수정구분수정일자LOT발생구분전송구분데이터기준일자
1902<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1903<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1904<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1905<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1906<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1907<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1908<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1909<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1910<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1911<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

전표번호발주일자봉투 종류협회코드제작업체수량조달수수료조달단가금액미입고수량수정구분수정일자LOT발생구분전송구분데이터기준일자# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>686