Overview

Dataset statistics

Number of variables3
Number of observations45
Missing cells2
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory29.9 B

Variable types

Categorical1
Numeric2

Alerts

월 has 1 (2.2%) missing valuesMissing
가스송출량(톤) has 1 (2.2%) missing valuesMissing

Reproduction

Analysis started2024-03-18 02:22:40.243215
Analysis finished2024-03-18 02:22:41.298249
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

Distinct5
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size492.0 B
2020
12 
2021
12 
2022
12 
2023
8 
<NA>
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 12
26.7%
2021 12
26.7%
2022 12
26.7%
2023 8
17.8%
<NA> 1
 
2.2%

Length

2024-03-18T11:22:41.376219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:22:41.514064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 12
26.7%
2021 12
26.7%
2022 12
26.7%
2023 8
17.8%
na 1
 
2.2%

월
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)27.3%
Missing1
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean6.1363636
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-03-18T11:22:41.609514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile11.85
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4003482
Coefficient of variation (CV)0.55413082
Kurtosis-1.1054834
Mean6.1363636
Median Absolute Deviation (MAD)3
Skewness0.14159343
Sum270
Variance11.562368
MonotonicityNot monotonic
2024-03-18T11:22:41.736972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 4
8.9%
2 4
8.9%
3 4
8.9%
4 4
8.9%
5 4
8.9%
6 4
8.9%
7 4
8.9%
8 4
8.9%
9 3
6.7%
10 3
6.7%
Other values (2) 6
13.3%
ValueCountFrequency (%)
1 4
8.9%
2 4
8.9%
3 4
8.9%
4 4
8.9%
5 4
8.9%
6 4
8.9%
7 4
8.9%
8 4
8.9%
9 3
6.7%
10 3
6.7%
ValueCountFrequency (%)
12 3
6.7%
11 3
6.7%
10 3
6.7%
9 3
6.7%
8 4
8.9%
7 4
8.9%
6 4
8.9%
5 4
8.9%
4 4
8.9%
3 4
8.9%

가스송출량(톤)
Real number (ℝ)

MISSING 

Distinct44
Distinct (%)100.0%
Missing1
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean1080311.7
Minimum551890.4
Maximum1953632.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-03-18T11:22:41.874104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum551890.4
5-th percentile691559.09
Q1833763.45
median901406
Q31354182.9
95-th percentile1837111.7
Maximum1953632.2
Range1401741.8
Interquartile range (IQR)520419.4

Descriptive statistics

Standard deviation385261.94
Coefficient of variation (CV)0.35662108
Kurtosis-0.31632561
Mean1080311.7
Median Absolute Deviation (MAD)141490.3
Skewness0.94729575
Sum47533717
Variance1.4842676 × 1011
MonotonicityNot monotonic
2024-03-18T11:22:42.220577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1640136.8 1
 
2.2%
1667940.0 1
 
2.2%
1642049.3 1
 
2.2%
1371166.9 1
 
2.2%
830624.1 1
 
2.2%
876625.4 1
 
2.2%
879769.7 1
 
2.2%
866982.3 1
 
2.2%
810965.4 1
 
2.2%
716187.5 1
 
2.2%
Other values (34) 34
75.6%
ValueCountFrequency (%)
551890.4 1
2.2%
570346.7 1
2.2%
687212.9 1
2.2%
716187.5 1
2.2%
747170.7 1
2.2%
751804.2 1
2.2%
767836.6 1
2.2%
769797.6 1
2.2%
810965.4 1
2.2%
829809.7 1
2.2%
ValueCountFrequency (%)
1953632.2 1
2.2%
1889651.9 1
2.2%
1845176.9 1
2.2%
1791408.8 1
2.2%
1706364.8 1
2.2%
1667940.0 1
2.2%
1642049.3 1
2.2%
1640136.8 1
2.2%
1434727.9 1
2.2%
1410168.9 1
2.2%

Interactions

2024-03-18T11:22:40.909256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:22:40.761322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:22:40.992223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:22:40.829114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T11:22:42.321661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도월가스송출량(톤)
년도1.0000.0000.000
월0.0001.0000.526
가스송출량(톤)0.0000.5261.000
2024-03-18T11:22:42.411678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월가스송출량(톤)년도
월1.000-0.2630.000
가스송출량(톤)-0.2631.0000.000
년도0.0000.0001.000

Missing values

2024-03-18T11:22:41.095781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T11:22:41.165248image/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.
2024-03-18T11:22:41.247182image/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

년도월가스송출량(톤)
0202011640136.8
1202021410168.9
2202031095500.8
320204840602.4
420205570346.7
520206551890.4
620207687212.9
720208835219.4
820209747170.7
9202010923042.3
년도월가스송출량(톤)
352022121889651.9
36202311706364.8
37202321348521.5
38202331047497.8
3920234829809.7
4020235769797.6
4120236751804.2
4220237844397.0
4320238870701.0
44<NA><NA><NA>