Overview

Dataset statistics

Number of variables3
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory860.0 B
Average record size in memory30.7 B

Variable types

Numeric2
DateTime1

Dataset

Description서울특별시 중랑구의 가정폐기물 현황에대한 데이터입니다. 연번,날짜, 발생량(톤)에대한 데이터를 제공합니다. 참고해주십시오. 감사합니다.
Author서울특별시 중랑구
URLhttps://www.data.go.kr/data/15089466/fileData.do

Alerts

연번 has unique valuesUnique
날짜 has unique valuesUnique
발생량(톤) has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:19:13.660395
Analysis finished2023-12-12 15:19:14.592079
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T00:19:14.667157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.35
Q17.75
median14.5
Q321.25
95-th percentile26.65
Maximum28
Range27
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.2259751
Coefficient of variation (CV)0.56730863
Kurtosis-1.2
Mean14.5
Median Absolute Deviation (MAD)7
Skewness0
Sum406
Variance67.666667
MonotonicityStrictly increasing
2023-12-13T00:19:14.798648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 1
 
3.6%
16 1
 
3.6%
28 1
 
3.6%
27 1
 
3.6%
26 1
 
3.6%
25 1
 
3.6%
24 1
 
3.6%
23 1
 
3.6%
22 1
 
3.6%
21 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1 1
3.6%
2 1
3.6%
3 1
3.6%
4 1
3.6%
5 1
3.6%
6 1
3.6%
7 1
3.6%
8 1
3.6%
9 1
3.6%
10 1
3.6%
ValueCountFrequency (%)
28 1
3.6%
27 1
3.6%
26 1
3.6%
25 1
3.6%
24 1
3.6%
23 1
3.6%
22 1
3.6%
21 1
3.6%
20 1
3.6%
19 1
3.6%

날짜
Date

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2020-10-01 00:00:00
Maximum2023-01-01 00:00:00
2023-12-13T00:19:14.954957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:19:15.098656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

발생량(톤)
Real number (ℝ)

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2339.075
Minimum2019.59
Maximum2650.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T00:19:15.258600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2019.59
5-th percentile2079.332
Q12235.92
median2353.71
Q32432.0825
95-th percentile2584.8575
Maximum2650.83
Range631.24
Interquartile range (IQR)196.1625

Descriptive statistics

Standard deviation156.56304
Coefficient of variation (CV)0.066933741
Kurtosis-0.31071446
Mean2339.075
Median Absolute Deviation (MAD)98.92
Skewness-0.086445713
Sum65494.1
Variance24511.986
MonotonicityNot monotonic
2023-12-13T00:19:15.440755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2425.86 1
 
3.6%
2219.14 1
 
3.6%
2240.61 1
 
3.6%
2288.68 1
 
3.6%
2529.41 1
 
3.6%
2221.85 1
 
3.6%
2276.86 1
 
3.6%
2422.21 1
 
3.6%
2454.4 1
 
3.6%
2389.58 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
2019.59 1
3.6%
2063.61 1
3.6%
2108.53 1
3.6%
2153.86 1
3.6%
2192.84 1
3.6%
2219.14 1
3.6%
2221.85 1
3.6%
2240.61 1
3.6%
2256.56 1
3.6%
2273.17 1
3.6%
ValueCountFrequency (%)
2650.83 1
3.6%
2605.14 1
3.6%
2547.19 1
3.6%
2529.41 1
3.6%
2469.62 1
3.6%
2454.4 1
3.6%
2450.75 1
3.6%
2425.86 1
3.6%
2422.21 1
3.6%
2419.59 1
3.6%

Interactions

2023-12-13T00:19:14.248905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:19:13.745547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:19:14.353768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:19:14.149142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:19:15.565275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번날짜발생량(톤)
연번1.0001.0000.000
날짜1.0001.0001.000
발생량(톤)0.0001.0001.000
2023-12-13T00:19:15.673045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번발생량(톤)
연번1.000-0.079
발생량(톤)-0.0791.000

Missing values

2023-12-13T00:19:14.484339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:19:14.556489image/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

연번날짜발생량(톤)
012020-10-012425.86
122020-11-012547.19
232020-12-012409.33
342021-01-012108.53
452021-02-012063.61
562021-03-012273.17
672021-04-012153.86
782021-05-012336.8
892021-06-012469.62
9102021-07-012650.83
연번날짜발생량(톤)
18192022-04-012192.84
19202022-05-012360.67
20212022-06-012389.58
21222022-07-012454.4
22232022-08-012422.21
23242022-09-012276.86
24252022-10-012221.85
25262022-11-012529.41
26272022-12-012288.68
27282023-01-012240.61