Overview

Dataset statistics

Number of variables4
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory924.0 B
Average record size in memory38.5 B

Variable types

DateTime1
Categorical1
Text1
Numeric1

Dataset

Description인천광역시 미추홀구 쓰레기봉투물류시스템 발주현황에 대한 데이터로 발주일자, 업체명, 품목, 발주수량 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15086028/fileData.do

Reproduction

Analysis started2023-12-12 16:00:34.582921
Analysis finished2023-12-12 16:00:34.931329
Duration0.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

발주일자
Date

Distinct7
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2023-01-05 00:00:00
Maximum2023-04-20 00:00:00
2023-12-13T01:00:34.976845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:00:35.059584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

업체명
Categorical

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
영광산업
12 
에덴복지재단
5 
성광디자인
5 
서구구립장애인재활
2 

Length

Max length9
Median length7.5
Mean length5.0416667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영광산업 12
50.0%
에덴복지재단 5
20.8%
성광디자인 5
20.8%
서구구립장애인재활 2
 
8.3%

Length

2023-12-13T01:00:35.156150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:00:35.247263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영광산업 12
50.0%
에덴복지재단 5
20.8%
성광디자인 5
20.8%
서구구립장애인재활 2
 
8.3%

품목
Text

Distinct18
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T01:00:35.380118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.2916667
Min length6

Characters and Unicode

Total characters199
Distinct characters24
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)50.0%

Sample

1st row일반용 5L
2nd row일반용 10L
3rd row일반용 20L
4th row재사용 10L
5th row재사용 20L
ValueCountFrequency (%)
일반용 8
15.1%
10l 5
9.4%
스티커 5
9.4%
원권 5
9.4%
음식물 5
9.4%
재사용 4
 
7.5%
20l 4
 
7.5%
5l 3
 
5.7%
10000 2
 
3.8%
사업계용 2
 
3.8%
Other values (10) 10
18.9%
2023-12-13T01:00:35.713103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
21.1%
0 29
14.6%
L 19
 
9.5%
용 14
 
7.0%
1 9
 
4.5%
일 8
 
4.0%
반 8
 
4.0%
5 6
 
3.0%
사 6
 
3.0%
원 5
 
2.5%
Other values (14) 53
26.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84
42.2%
Decimal Number 54
27.1%
Space Separator 42
21.1%
Uppercase Letter 19
 
9.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 14
16.7%
일 8
9.5%
반 8
9.5%
사 6
 
7.1%
원 5
 
6.0%
물 5
 
6.0%
식 5
 
6.0%
음 5
 
6.0%
권 5
 
6.0%
티 5
 
6.0%
Other values (5) 18
21.4%
Decimal Number
ValueCountFrequency (%)
0 29
53.7%
1 9
 
16.7%
5 6
 
11.1%
2 5
 
9.3%
3 3
 
5.6%
7 1
 
1.9%
6 1
 
1.9%
Space Separator
ValueCountFrequency (%)
42
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96
48.2%
Hangul 84
42.2%
Latin 19
 
9.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 14
16.7%
일 8
9.5%
반 8
9.5%
사 6
 
7.1%
원 5
 
6.0%
물 5
 
6.0%
식 5
 
6.0%
음 5
 
6.0%
권 5
 
6.0%
티 5
 
6.0%
Other values (5) 18
21.4%
Common
ValueCountFrequency (%)
42
43.8%
0 29
30.2%
1 9
 
9.4%
5 6
 
6.2%
2 5
 
5.2%
3 3
 
3.1%
7 1
 
1.0%
6 1
 
1.0%
Latin
ValueCountFrequency (%)
L 19
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 115
57.8%
Hangul 84
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
36.5%
0 29
25.2%
L 19
16.5%
1 9
 
7.8%
5 6
 
5.2%
2 5
 
4.3%
3 3
 
2.6%
7 1
 
0.9%
6 1
 
0.9%
Hangul
ValueCountFrequency (%)
용 14
16.7%
일 8
9.5%
반 8
9.5%
사 6
 
7.1%
원 5
 
6.0%
물 5
 
6.0%
식 5
 
6.0%
음 5
 
6.0%
권 5
 
6.0%
티 5
 
6.0%
Other values (5) 18
21.4%

발주수량
Real number (ℝ)

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean677370.83
Minimum1000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T01:00:35.879447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile16400
Q163000
median350000
Q3875000
95-th percentile2040000
Maximum3400000
Range3399000
Interquartile range (IQR)812000

Descriptive statistics

Standard deviation845315.3
Coefficient of variation (CV)1.2479358
Kurtosis3.5340875
Mean677370.83
Median Absolute Deviation (MAD)295500
Skewness1.8406026
Sum16256900
Variance7.1455796 × 1011
MonotonicityNot monotonic
2023-12-13T01:00:36.012970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
300000 2
 
8.3%
1600000 2
 
8.3%
1700000 1
 
4.2%
1000 1
 
4.2%
219900 1
 
4.2%
30000 1
 
4.2%
14000 1
 
4.2%
50000 1
 
4.2%
60000 1
 
4.2%
64000 1
 
4.2%
Other values (12) 12
50.0%
ValueCountFrequency (%)
1000 1
4.2%
14000 1
4.2%
30000 1
4.2%
50000 1
4.2%
59000 1
4.2%
60000 1
4.2%
64000 1
4.2%
156000 1
4.2%
174000 1
4.2%
219900 1
4.2%
ValueCountFrequency (%)
3400000 1
4.2%
2100000 1
4.2%
1700000 1
4.2%
1600000 2
8.3%
1100000 1
4.2%
800000 1
4.2%
650000 1
4.2%
550000 1
4.2%
500000 1
4.2%
429000 1
4.2%

Interactions

2023-12-13T01:00:34.693496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:00:36.114794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발주일자업체명품목발주수량
발주일자1.0001.0000.5270.543
업체명1.0001.0000.6720.623
품목0.5270.6721.0000.000
발주수량0.5430.6230.0001.000
2023-12-13T01:00:36.213452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발주수량업체명
발주수량1.0000.457
업체명0.4571.000

Missing values

2023-12-13T01:00:34.815741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:00:34.898610image/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

발주일자업체명품목발주수량
02023-01-05영광산업일반용 5L300000
12023-01-05영광산업일반용 10L59000
22023-01-05영광산업일반용 20L156000
32023-01-05영광산업재사용 10L174000
42023-01-05영광산업재사용 20L429000
52023-02-09서구구립장애인재활일반용 50L800000
62023-02-09서구구립장애인재활일반용 75L400000
72023-02-13에덴복지재단일반용 5L300000
82023-02-13에덴복지재단일반용 10L1600000
92023-02-13에덴복지재단일반용 20L1600000
발주일자업체명품목발주수량
142023-02-23영광산업음식물 3L1700000
152023-02-23영광산업음식물 5L650000
162023-02-23영광산업음식물 10L550000
172023-03-08성광디자인스티커 1000 원권64000
182023-03-08성광디자인스티커 3000 원권60000
192023-03-08성광디자인스티커 5000 원권50000
202023-03-08성광디자인스티커 10000 원권14000
212023-04-18영광산업사업계용 30L30000
222023-04-18영광산업사업계용 60L219900
232023-04-20성광디자인스티커 10000 원권1000