gimi9 Pandas Profiling

Dataset statistics

Number of variables	4
Number of observations	47
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	1.7 KiB
Average record size in memory	37.8 B

Variable types

DateTime	1
Numeric	3

Dataset

Description	한국가스공사 인천기지본부의 연간 상수도 사용량으로, 용도별(설비용, 사무용) 상수도 사용량(㎥)에 대한 정보를 나타냄
Author	한국가스공사
URL	https://data.incheon.go.kr/findData/publicDataDetail?dataId=15087687&srcSe=7661IVAWM27C61E190

Alerts

`설비용사용량` is highly overall correlated with `합계`	High correlation
`합계` is highly overall correlated with `설비용사용량`	High correlation
`사용 월` has unique values	Unique
`설비용사용량` has unique values	Unique

Reproduction

Analysis started	2024-04-06 09:45:45.257766
Analysis finished	2024-04-06 09:45:47.085650
Duration	1.83 second
Software version	ydata-profiling vv4.5.1
Download configuration	config.json

사용 월
Date

UNIQUE

Distinct	47
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	508.0 B

Minimum	2020-01-01 00:00:00
Maximum	2023-11-01 00:00:00

Histogram

Histogram with fixed size bins (bins=47)

설비용사용량
Real number (ℝ)

HIGH CORRELATION UNIQUE

Distinct	47
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	14512.66

Minimum	4300
Maximum	50749
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	555.0 B

Quantile statistics

Minimum	4300
5-th percentile	6586.3
Q1	7555.5
median	11389
Q3	16205
95-th percentile	45908.3
Maximum	50749
Range	46449
Interquartile range (IQR)	8649.5

Descriptive statistics

Standard deviation	11237.996
Coefficient of variation (CV)	0.7743581
Kurtosis	4.3167035
Mean	14512.66
Median Absolute Deviation (MAD)	3890
Skewness	2.2090685
Sum	682095
Variance	1.2629254 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=47)

Value	Count	Frequency (%)
8729	1	2.1%
7100	1	2.1%
17489	1	2.1%
12302	1	2.1%
42829	1	2.1%
50749	1	2.1%
13526	1	2.1%
8708	1	2.1%
10211	1	2.1%
17287	1	2.1%
Other values (37)	37	78.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
4300	1	2.1%
5927	1	2.1%
6580	1	2.1%
6601	1	2.1%
6696	1	2.1%
6744	1	2.1%
6810	1	2.1%
6883	1	2.1%
7100	1	2.1%
7155	1	2.1%

Value	Count	Frequency (%)
50749	1	2.1%
47718	1	2.1%
47228	1	2.1%
42829	1	2.1%
29044	1	2.1%
23924	1	2.1%
20933	1	2.1%
18032	1	2.1%
17489	1	2.1%
17287	1	2.1%

사무용사용량
Real number (ℝ)

Distinct	46
Distinct (%)	97.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3242.5319

Minimum	1813
Maximum	6598
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	555.0 B

Quantile statistics

Minimum	1813
5-th percentile	1856.9
Q1	2479
median	2950
Q3	3511.5
95-th percentile	5826.9
Maximum	6598
Range	4785
Interquartile range (IQR)	1032.5

Descriptive statistics

Standard deviation	1186.2417
Coefficient of variation (CV)	0.3658381
Kurtosis	1.1366676
Mean	3242.5319
Median Absolute Deviation (MAD)	560
Skewness	1.2931464
Sum	152399
Variance	1407169.4
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=46)

Value	Count	Frequency (%)
1813	2	4.3%
2567	1	2.1%
6073	1	2.1%
3709	1	2.1%
1922	1	2.1%
2248	1	2.1%
4539	1	2.1%
4284	1	2.1%
4482	1	2.1%
4146	1	2.1%
Other values (36)	36	76.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1813	2	4.3%
1829	1	2.1%
1922	1	2.1%
2020	1	2.1%
2140	1	2.1%
2183	1	2.1%
2238	1	2.1%
2248	1	2.1%
2351	1	2.1%
2381	1	2.1%

Value	Count	Frequency (%)
6598	1	2.1%
6073	1	2.1%
5835	1	2.1%
5808	1	2.1%
5658	1	2.1%
4539	1	2.1%
4482	1	2.1%
4337	1	2.1%
4284	1	2.1%
4146	1	2.1%

합계
Real number (ℝ)

HIGH CORRELATION

Distinct	46
Distinct (%)	97.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	17755.191

Minimum	7321
Maximum	52997
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	555.0 B

Quantile statistics

Minimum	7321
5-th percentile	8920.9
Q1	10116
median	14582
Q3	19649
95-th percentile	47765.2
Maximum	52997
Range	45676
Interquartile range (IQR)	9533

Descriptive statistics

Standard deviation	11158.821
Coefficient of variation (CV)	0.62848217
Kurtosis	3.5215898
Mean	17755.191
Median Absolute Deviation (MAD)	4898
Skewness	1.994658
Sum	834494
Variance	1.2451929 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=46)

Value	Count	Frequency (%)
9682	2	4.3%
11296	1	2.1%
27006	1	2.1%
16011	1	2.1%
44751	1	2.1%
52997	1	2.1%
18065	1	2.1%
12992	1	2.1%
14693	1	2.1%
21433	1	2.1%
Other values (36)	36	76.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
7321	1	2.1%
7740	1	2.1%
8716	1	2.1%
9399	1	2.1%
9438	1	2.1%
9451	1	2.1%
9478	1	2.1%
9500	1	2.1%
9623	1	2.1%
9682	2	4.3%

Value	Count	Frequency (%)
52997	1	2.1%
49531	1	2.1%
49057	1	2.1%
44751	1	2.1%
33381	1	2.1%
27184	1	2.1%
27006	1	2.1%
23867	1	2.1%
21433	1	2.1%
20993	1	2.1%

Phik (φk)
Auto

Heatmap
Table

	사용 월	설비용사용량	사무용사용량	합계
사용 월	1.000	1.000	1.000	1.000
설비용사용량	1.000	1.000	0.630	0.992
사무용사용량	1.000	0.630	1.000	0.780
합계	1.000	0.992	0.780	1.000

Heatmap
Table

	설비용사용량	사무용사용량	합계
설비용사용량	1.000	0.226	0.983
사무용사용량	0.226	1.000	0.325
합계	0.983	0.325	1.000

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows
Last rows

	사용 월	설비용사용량	사무용사용량	합계
0	2020-01-01 00:00	8729	2567	11296
1	2020-02-01 00:00	7100	2351	9451
2	2020-03-01 00:00	5927	1813	7740
3	2020-04-01 00:00	7155	2468	9623
4	2020-05-01 00:00	7525	2381	9906
5	2020-06-01 00:00	6744	2655	9399
6	2020-07-01 00:00	4300	3021	7321
7	2020-08-01 00:00	6580	2898	9478
8	2020-09-01 00:00	6601	3081	9682
9	2020-10-01 00:00	6883	2555	9438

	사용 월	설비용사용량	사무용사용량	합계
37	2023-02-01 00:00	12882	6598	19480
38	2023-03-01 00:00	11400	5808	17208
39	2023-04-01 00:00	8361	5658	14019
40	2023-05-01 00:00	8786	2140	10926
41	2023-06-01 00:00	10327	2950	13277
42	2023-07-01 00:00	6810	2690	9500
43	2023-08-01 00:00	7701	3470	11171
44	2023-09-01 00:00	7586	2740	10326
45	2023-10-01 00:00	6696	2020	8716
46	2023-11-01 00:00	11389	3020	14409

Overview

Variables

Interactions

Correlations

Missing values

Sample