Overview

Dataset statistics

Number of variables7
Number of observations239
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.1 KiB
Average record size in memory60.6 B

Variable types

Categorical3
Numeric3
DateTime1

Dataset

Description광주광역시 서구 관급봉투관리시스템의 종량제봉투(납부필증) 재고관리 정보입니다. 박스바코드, 팩바코드, 낱장바코드, 봉투구분, 낱장수량 등의 정보를 제공합니다.
Author광주광역시 서구
URLhttps://www.data.go.kr/data/15039804/fileData.do

Alerts

기관명 has constant value ""Constant
봉투구분 is highly overall correlated with 박스바코드 and 3 other fieldsHigh correlation
낱장수량 is highly overall correlated with 박스바코드 and 3 other fieldsHigh correlation
박스바코드 is highly overall correlated with 팩바코드 and 3 other fieldsHigh correlation
팩바코드 is highly overall correlated with 박스바코드 and 3 other fieldsHigh correlation
낱장바코드 is highly overall correlated with 박스바코드 and 3 other fieldsHigh correlation
봉투구분 is highly imbalanced (62.7%)Imbalance
낱장수량 is highly imbalanced (83.1%)Imbalance
팩바코드 has unique valuesUnique
데이터기준일자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:34:23.929744
Analysis finished2023-12-12 07:34:25.318767
Duration1.39 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
서구청
239 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서구청 239
100.0%

Length

2023-12-12T16:34:25.397887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:34:25.506811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구청 239
100.0%

박스바코드
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4854184 × 1010
Minimum3.744 × 1010
Maximum9.19 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:34:25.612838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.744 × 1010
5-th percentile3.744 × 1010
Q13.744 × 1010
median4.935 × 1010
Q34.935 × 1010
95-th percentile1.898 × 1011
Maximum9.19 × 1011
Range8.8156 × 1011
Interquartile range (IQR)1.191 × 1010

Descriptive statistics

Standard deviation1.2856114 × 1011
Coefficient of variation (CV)1.7174877
Kurtosis21.043316
Mean7.4854184 × 1010
Median Absolute Deviation (MAD)1
Skewness4.6084569
Sum1.789015 × 1013
Variance1.6527966 × 1022
MonotonicityNot monotonic
2023-12-12T16:34:25.747095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
49350000001 90
37.7%
49350000002 59
24.7%
37440000002 25
 
10.5%
37440000003 25
 
10.5%
37440000001 25
 
10.5%
584000000000 1
 
0.4%
561000000000 1
 
0.4%
919000000000 1
 
0.4%
503000000000 1
 
0.4%
215000000000 1
 
0.4%
Other values (10) 10
 
4.2%
ValueCountFrequency (%)
37440000001 25
 
10.5%
37440000002 25
 
10.5%
37440000003 25
 
10.5%
49350000001 90
37.7%
49350000002 59
24.7%
140000000000 1
 
0.4%
157000000000 1
 
0.4%
187000000000 1
 
0.4%
215000000000 1
 
0.4%
503000000000 1
 
0.4%
ValueCountFrequency (%)
919000000000 1
0.4%
792000000000 1
0.4%
765000000000 1
0.4%
710000000000 1
0.4%
591000000000 1
0.4%
584000000000 1
0.4%
563000000000 1
0.4%
561000000000 1
0.4%
533000000000 1
0.4%
509000000000 1
0.4%

팩바코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct239
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4863557 × 1010
Minimum3.745 × 1010
Maximum9.19 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:34:25.890812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.745 × 1010
5-th percentile3.745 × 1010
Q13.745 × 1010
median4.936 × 1010
Q34.936 × 1010
95-th percentile1.898 × 1011
Maximum9.19 × 1011
Range8.8155 × 1011
Interquartile range (IQR)1.191 × 1010

Descriptive statistics

Standard deviation1.2855898 × 1011
Coefficient of variation (CV)1.7172438
Kurtosis21.043563
Mean7.4863557 × 1010
Median Absolute Deviation (MAD)75
Skewness4.6084807
Sum1.789239 × 1013
Variance1.6527411 × 1022
MonotonicityNot monotonic
2023-12-12T16:34:26.041884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187000000000 1
 
0.4%
157000000000 1
 
0.4%
49360000130 1
 
0.4%
49360000129 1
 
0.4%
49360000128 1
 
0.4%
49360000126 1
 
0.4%
49360000125 1
 
0.4%
49360000124 1
 
0.4%
49360000123 1
 
0.4%
49360000122 1
 
0.4%
Other values (229) 229
95.8%
ValueCountFrequency (%)
37450000001 1
0.4%
37450000002 1
0.4%
37450000003 1
0.4%
37450000004 1
0.4%
37450000005 1
0.4%
37450000006 1
0.4%
37450000007 1
0.4%
37450000008 1
0.4%
37450000009 1
0.4%
37450000010 1
0.4%
ValueCountFrequency (%)
919000000000 1
0.4%
792000000000 1
0.4%
765000000000 1
0.4%
710000000000 1
0.4%
591000000000 1
0.4%
584000000000 1
0.4%
563000000000 1
0.4%
561000000000 1
0.4%
533000000000 1
0.4%
509000000000 1
0.4%

낱장바코드
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7487.2385
Minimum3746
Maximum91949
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T16:34:26.157641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3746
5-th percentile3746
Q13746
median4937
Q34937
95-th percentile18952.4
Maximum91949
Range88203
Interquartile range (IQR)1191

Descriptive statistics

Standard deviation12857.397
Coefficient of variation (CV)1.7172416
Kurtosis21.05406
Mean7487.2385
Median Absolute Deviation (MAD)0
Skewness4.6094227
Sum1789450
Variance1.6531267 × 108
MonotonicityNot monotonic
2023-12-12T16:34:26.264811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
4937 149
62.3%
3746 75
31.4%
53279 1
 
0.4%
58427 1
 
0.4%
56135 1
 
0.4%
91949 1
 
0.4%
50348 1
 
0.4%
21458 1
 
0.4%
79229 1
 
0.4%
18674 1
 
0.4%
Other values (7) 7
 
2.9%
ValueCountFrequency (%)
3746 75
31.4%
4937 149
62.3%
13988 1
 
0.4%
15674 1
 
0.4%
18674 1
 
0.4%
21458 1
 
0.4%
50348 1
 
0.4%
50858 1
 
0.4%
53279 1
 
0.4%
56135 1
 
0.4%
ValueCountFrequency (%)
91949 1
0.4%
79229 1
0.4%
76484 1
0.4%
70988 1
0.4%
59069 1
0.4%
58427 1
0.4%
56327 1
0.4%
56135 1
0.4%
53279 1
0.4%
50858 1
0.4%

봉투구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct13
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
20리터
150 
75리터
75 
5리터
 
3
10리터
 
2
100리터
 
1
Other values (8)
 
8

Length

Max length9
Median length4
Mean length4.0627615
Min length3

Unique

Unique9 ?
Unique (%)3.8%

Sample

1st row20리터
2nd row100리터
3rd row30리터
4th row50리터
5th row재사용20리터

Common Values

ValueCountFrequency (%)
20리터 150
62.8%
75리터 75
31.4%
5리터 3
 
1.3%
10리터 2
 
0.8%
100리터 1
 
0.4%
30리터 1
 
0.4%
50리터 1
 
0.4%
재사용20리터 1
 
0.4%
음식물3리터 1
 
0.4%
업소용120터 1
 
0.4%
Other values (3) 3
 
1.3%

Length

2023-12-12T16:34:26.409410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20리터 150
62.8%
75리터 75
31.4%
5리터 3
 
1.3%
10리터 2
 
0.8%
100리터 1
 
0.4%
30리터 1
 
0.4%
50리터 1
 
0.4%
재사용20리터 1
 
0.4%
음식물3리터 1
 
0.4%
업소용120터 1
 
0.4%
Other values (3) 3
 
1.3%

낱장수량
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
20
233 
10
 
6

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20
2nd row10
3rd row20
4th row20
5th row20

Common Values

ValueCountFrequency (%)
20 233
97.5%
10 6
 
2.5%

Length

2023-12-12T16:34:26.536603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:34:26.623034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20 233
97.5%
10 6
 
2.5%

데이터기준일자
Date

UNIQUE 

Distinct239
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2021-01-07 00:00:00
Maximum2021-09-02 00:00:00
2023-12-12T16:34:26.729437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:26.881493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T16:34:24.799067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:24.219151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:24.510015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:24.892720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:24.326136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:24.621536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:24.991472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:24.428160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:34:24.715876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:34:27.320254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
박스바코드팩바코드낱장바코드봉투구분낱장수량
박스바코드1.0001.0001.0000.9720.924
팩바코드1.0001.0001.0000.9720.926
낱장바코드1.0001.0001.0000.9900.921
봉투구분0.9720.9720.9901.0001.000
낱장수량0.9240.9260.9211.0001.000
2023-12-12T16:34:27.412602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
봉투구분낱장수량
봉투구분1.0000.977
낱장수량0.9771.000
2023-12-12T16:34:27.496572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
박스바코드팩바코드낱장바코드봉투구분낱장수량
박스바코드1.0000.9630.8850.9010.754
팩바코드0.9631.0000.8530.9010.754
낱장바코드0.8850.8531.0000.9010.754
봉투구분0.9010.9010.9011.0000.977
낱장수량0.7540.7540.7540.9771.000

Missing values

2023-12-12T16:34:25.124744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:34:25.271295image/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

기관명박스바코드팩바코드낱장바코드봉투구분낱장수량데이터기준일자
0서구청1870000000001870000000001867420리터202021-01-07
1서구청15700000000015700000000015674100리터102021-01-08
2서구청5090000000005090000000005085830리터202021-01-09
3서구청1400000000001400000000001398850리터202021-01-10
4서구청76500000000076500000000076484재사용20리터202021-01-11
5서구청710000000000710000000000709885리터202021-01-12
6서구청5910000000005910000000005906910리터202021-01-13
7서구청563000000000563000000000563275리터202021-01-14
8서구청4935000000149360000037493720리터202021-01-15
9서구청4935000000149360000036493720리터202021-01-16
기관명박스바코드팩바코드낱장바코드봉투구분낱장수량데이터기준일자
229서구청4935000000149360000040493720리터202021-08-24
230서구청4935000000149360000039493720리터202021-08-25
231서구청4935000000149360000038493720리터202021-08-26
232서구청53300000000053300000000053279음식물3리터102021-08-27
233서구청79200000000079200000000079229업소용120터102021-08-28
234서구청21500000000021500000000021458음식물업소용6리터102021-08-29
235서구청50300000000050300000000050348업소용20터102021-08-30
236서구청91900000000091900000000091949음식물6리터102021-08-31
237서구청561000000000561000000000561355리터202021-09-01
238서구청5840000000005840000000005842710리터202021-09-02