Overview

Dataset statistics

Number of variables7
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory62.7 B

Variable types

Categorical3
Numeric4

Dataset

Description강원특별자치도 겨울철 도로 정비를 위한 제설제 및 친환경 제설제 사용량 현황Current status of use of snow remover and eco-friendly snow remover for road maintenance in winter in Gangwon Special Self-Governing Province
Author강원특별자치도
URLhttps://www.data.go.kr/data/15033787/fileData.do

Alerts

단위 has constant value ""Constant
사용연도 is highly overall correlated with 재고량High correlation
구매량 is highly overall correlated with 사용량 and 2 other fieldsHigh correlation
사용량 is highly overall correlated with 구매량 and 2 other fieldsHigh correlation
재고량 is highly overall correlated with 사용연도 and 2 other fieldsHigh correlation
종류 is highly overall correlated with 구매량 and 1 other fieldsHigh correlation
구매량 has 1 (2.1%) zerosZeros
사용량 has 2 (4.2%) zerosZeros
재고량 has 8 (16.7%) zerosZeros

Reproduction

Analysis started2024-03-14 19:59:27.049372
Analysis finished2024-03-14 19:59:31.991241
Duration4.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct4
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size512.0 B
원주본소
12 
강릉지소
12 
태백지소
12 
북부지소
12 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row원주본소
2nd row강릉지소
3rd row태백지소
4th row북부지소
5th row원주본소

Common Values

ValueCountFrequency (%)
원주본소 12
25.0%
강릉지소 12
25.0%
태백지소 12
25.0%
북부지소 12
25.0%

Length

2024-03-15T04:59:32.217864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:59:32.638551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원주본소 12
25.0%
강릉지소 12
25.0%
태백지소 12
25.0%
북부지소 12
25.0%

사용연도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.75
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-03-15T04:59:33.039903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12017.75
median2018.5
Q32019.25
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation1.5505661
Coefficient of variation (CV)0.00076808229
Kurtosis-0.37870522
Mean2018.75
Median Absolute Deviation (MAD)1
Skewness0.72358732
Sum96900
Variance2.4042553
MonotonicityIncreasing
2024-03-15T04:59:33.425002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2017 12
25.0%
2018 12
25.0%
2019 12
25.0%
2020 4
 
8.3%
2021 4
 
8.3%
2022 4
 
8.3%
ValueCountFrequency (%)
2017 12
25.0%
2018 12
25.0%
2019 12
25.0%
2020 4
 
8.3%
2021 4
 
8.3%
2022 4
 
8.3%
ValueCountFrequency (%)
2022 4
 
8.3%
2021 4
 
8.3%
2020 4
 
8.3%
2019 12
25.0%
2018 12
25.0%
2017 12
25.0%

종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size512.0 B
소금
12 
염화칼슘
12 
친환경 제설제
12 
제설제
12 

Length

Max length7
Median length3.5
Mean length4
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소금
2nd row소금
3rd row소금
4th row소금
5th row염화칼슘

Common Values

ValueCountFrequency (%)
소금 12
25.0%
염화칼슘 12
25.0%
친환경 제설제 12
25.0%
제설제 12
25.0%

Length

2024-03-15T04:59:33.848982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:59:34.236516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제설제 24
40.0%
소금 12
20.0%
염화칼슘 12
20.0%
친환경 12
20.0%

구매량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3217.75
Minimum0
Maximum10909
Zeros1
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-03-15T04:59:34.656140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.5
Q1139.5
median2015.5
Q36267.5
95-th percentile8613.75
Maximum10909
Range10909
Interquartile range (IQR)6128

Descriptive statistics

Standard deviation3360.8504
Coefficient of variation (CV)1.0444722
Kurtosis-1.1856456
Mean3217.75
Median Absolute Deviation (MAD)1989.5
Skewness0.52097481
Sum154452
Variance11295315
MonotonicityNot monotonic
2024-03-15T04:59:35.158051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
100 3
 
6.2%
10 2
 
4.2%
7630 1
 
2.1%
5616 1
 
2.1%
242 1
 
2.1%
450 1
 
2.1%
74 1
 
2.1%
1529 1
 
2.1%
256 1
 
2.1%
92 1
 
2.1%
Other values (35) 35
72.9%
ValueCountFrequency (%)
0 1
 
2.1%
10 2
4.2%
20 1
 
2.1%
21 1
 
2.1%
74 1
 
2.1%
92 1
 
2.1%
94 1
 
2.1%
100 3
6.2%
138 1
 
2.1%
140 1
 
2.1%
ValueCountFrequency (%)
10909 1
2.1%
9107 1
2.1%
8675 1
2.1%
8500 1
2.1%
7880 1
2.1%
7716 1
2.1%
7630 1
2.1%
6930 1
2.1%
6810 1
2.1%
6734 1
2.1%

사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct43
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2228.1896
Minimum0
Maximum8730
Zeros2
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-03-15T04:59:35.831701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q1103
median1094.5
Q33599.25
95-th percentile6863.9
Maximum8730
Range8730
Interquartile range (IQR)3496.25

Descriptive statistics

Standard deviation2536.0487
Coefficient of variation (CV)1.1381656
Kurtosis-0.29008079
Mean2228.1896
Median Absolute Deviation (MAD)1079.5
Skewness0.91157475
Sum106953.1
Variance6431543.2
MonotonicityNot monotonic
2024-03-15T04:59:36.246063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
100.0 3
 
6.2%
10.0 2
 
4.2%
3000.0 2
 
4.2%
0.0 2
 
4.2%
6013.0 1
 
2.1%
37.0 1
 
2.1%
504.0 1
 
2.1%
256.0 1
 
2.1%
73.1 1
 
2.1%
8730.0 1
 
2.1%
Other values (33) 33
68.8%
ValueCountFrequency (%)
0.0 2
4.2%
10.0 2
4.2%
20.0 1
 
2.1%
21.0 1
 
2.1%
37.0 1
 
2.1%
73.1 1
 
2.1%
77.0 1
 
2.1%
100.0 3
6.2%
104.0 1
 
2.1%
115.0 1
 
2.1%
ValueCountFrequency (%)
8730.0 1
2.1%
7815.0 1
2.1%
7111.0 1
2.1%
6405.0 1
2.1%
6322.0 1
2.1%
6013.0 1
2.1%
5859.0 1
2.1%
5175.0 1
2.1%
5130.0 1
2.1%
4700.0 1
2.1%

재고량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean990.39375
Minimum0
Maximum6195
Zeros8
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-03-15T04:59:36.659158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median408.5
Q31454.5
95-th percentile3300.4
Maximum6195
Range6195
Interquartile range (IQR)1434.5

Descriptive statistics

Standard deviation1326.5917
Coefficient of variation (CV)1.3394589
Kurtosis3.8066715
Mean990.39375
Median Absolute Deviation (MAD)408.5
Skewness1.7946694
Sum47538.9
Variance1759845.7
MonotonicityNot monotonic
2024-03-15T04:59:37.059479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0.0 8
 
16.7%
20.0 3
 
6.2%
100.0 3
 
6.2%
1000.0 2
 
4.2%
2481.0 1
 
2.1%
18.9 1
 
2.1%
377.0 1
 
2.1%
441.0 1
 
2.1%
2270.0 1
 
2.1%
478.0 1
 
2.1%
Other values (26) 26
54.2%
ValueCountFrequency (%)
0.0 8
16.7%
17.0 1
 
2.1%
18.9 1
 
2.1%
20.0 3
 
6.2%
37.0 1
 
2.1%
38.0 1
 
2.1%
40.0 1
 
2.1%
100.0 3
 
6.2%
120.0 1
 
2.1%
138.0 1
 
2.1%
ValueCountFrequency (%)
6195.0 1
2.1%
3601.0 1
2.1%
3404.0 1
2.1%
3108.0 1
2.1%
3094.0 1
2.1%
2763.0 1
2.1%
2500.0 1
2.1%
2481.0 1
2.1%
2270.0 1
2.1%
2110.0 1
2.1%

단위
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size512.0 B
톤
48 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
톤 48
100.0%

Length

2024-03-15T04:59:37.470533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:59:37.880572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
톤 48
100.0%

Interactions

2024-03-15T04:59:30.282259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:27.305411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:28.365654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:29.323709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:30.536958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:27.619652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:28.608653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:29.574500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:30.780823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:27.878895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:28.845338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:29.808990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:31.022106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:28.113697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:29.076308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:59:30.039951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T04:59:37.987743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분사용연도종류구매량사용량재고량
구분1.0000.0000.0000.0000.0000.000
사용연도0.0001.0000.5730.7040.8050.380
종류0.0000.5731.0000.8130.7480.542
구매량0.0000.7040.8131.0000.9510.694
사용량0.0000.8050.7480.9511.0000.778
재고량0.0000.3800.5420.6940.7781.000
2024-03-15T04:59:38.167953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분종류
구분1.0000.000
종류0.0001.000
2024-03-15T04:59:38.315007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용연도구매량사용량재고량구분종류
사용연도1.0000.4880.4050.5150.0000.492
구매량0.4881.0000.9580.8670.0000.595
사용량0.4050.9581.0000.7670.0000.515
재고량0.5150.8670.7671.0000.0000.388
구분0.0000.0000.0000.0001.0000.000
종류0.4920.5950.5150.3880.0001.000

Missing values

2024-03-15T04:59:31.443938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:59:31.846740image/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

구분사용연도종류구매량사용량재고량단위
0원주본소2017소금76305130.02500.0톤
1강릉지소2017소금45003329.01171.0톤
2태백지소2017소금36003000.0600.0톤
3북부지소2017소금35492300.01249.0톤
4원주본소2017염화칼슘155115.040.0톤
5강릉지소2017염화칼슘320200.0120.0톤
6태백지소2017염화칼슘140120.020.0톤
7북부지소2017염화칼슘600400.0200.0톤
8원주본소2017친환경 제설제2020.00.0톤
9강릉지소2017친환경 제설제170170.00.0톤
구분사용연도종류구매량사용량재고량단위
38강릉지소2020제설제86756405.02270.0톤
39북부지소2020제설제64916013.0478.0톤
40원주본소2021제설제77166322.01394.0톤
41태백지소2021제설제54002919.02481.0톤
42강릉지소2021제설제67343330.03404.0톤
43북부지소2021제설제54603525.01935.0톤
44원주본소2022제설제58214185.01636.0톤
45태백지소2022제설제55831982.03601.0톤
46강릉지소2022제설제78801685.06195.0톤
47북부지소2022제설제61933430.02763.0톤