Dataset statistics
| Number of variables | 2 |
|---|---|
| Number of observations | 601 |
| Missing cells | 0 |
| Missing cells (%) | 0.0% |
| Duplicate rows | 0 |
| Duplicate rows (%) | 0.0% |
| Total size in memory | 10.7 KiB |
| Average record size in memory | 18.2 B |
Variable types
| Numeric | 2 |
|---|
Dataset
| Description | 기본적으로 기온반응함수는 기온이 도시가스수요에 미치는 영향을 각 개별 기온대별로 나타내어 일종의 함수 형태로 제시한 것으로 기온분포가 도시가스 수요에 미친 영향을 측정한 것으로 해석할 수 있다. 기온반응함수는 일반적으로 기온에 대하여 비선형적 형태를 보이기에 개별 기온이 지방권 도시가스 수요에 미치는 영향의 상대적 중요도를 측정할 수 있다. |
|---|---|
| Author | 한국가스공사 |
| URL | https://www.data.go.kr/data/15088546/fileData.do |
기온(s) has unique values | Unique |
Reproduction
| Analysis started | 2023-12-12 03:20:27.261386 |
|---|---|
| Analysis finished | 2023-12-12 03:20:28.102784 |
| Duration | 0.84 seconds |
| Software version | ydata-profiling vv4.5.1 |
| Download configuration | config.json |
기온(s)
Real number (ℝ)
UNIQUE
| Distinct | 601 |
|---|---|
| Distinct (%) | 100.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 10 |
| Minimum | -20 |
|---|---|
| Maximum | 40 |
| Zeros | 1 |
| Zeros (%) | 0.2% |
| Negative | 200 |
| Negative (%) | 33.3% |
| Memory size | 5.4 KiB |
Quantile statistics
| Minimum | -20 |
|---|---|
| 5-th percentile | -17 |
| Q1 | -5 |
| median | 10 |
| Q3 | 25 |
| 95-th percentile | 37 |
| Maximum | 40 |
| Range | 60 |
| Interquartile range (IQR) | 30 |
Descriptive statistics
| Standard deviation | 17.363803 |
|---|---|
| Coefficient of variation (CV) | 1.7363803 |
| Kurtosis | -1.2 |
| Mean | 10 |
| Median Absolute Deviation (MAD) | 15 |
| Skewness | -7.4370716 × 10-17 |
| Sum | 6010 |
| Variance | 301.50167 |
| Monotonicity | Strictly increasing |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| -20.0 | 1 | 0.2% |
| 19.5 | 1 | 0.2% |
| 19.7 | 1 | 0.2% |
| 19.8 | 1 | 0.2% |
| 19.9 | 1 | 0.2% |
| 20.0 | 1 | 0.2% |
| 20.1 | 1 | 0.2% |
| 20.2 | 1 | 0.2% |
| 20.3 | 1 | 0.2% |
| 20.4 | 1 | 0.2% |
| Other values (591) | 591 |
| Value | Count | Frequency (%) |
| -20.0 | 1 | |
| -19.9 | 1 | |
| -19.8 | 1 | |
| -19.7 | 1 | |
| -19.6 | 1 | |
| -19.5 | 1 | |
| -19.4 | 1 | |
| -19.3 | 1 | |
| -19.2 | 1 | |
| -19.1 | 1 |
| Value | Count | Frequency (%) |
| 40.0 | 1 | |
| 39.9 | 1 | |
| 39.8 | 1 | |
| 39.7 | 1 | |
| 39.6 | 1 | |
| 39.5 | 1 | |
| 39.4 | 1 | |
| 39.3 | 1 | |
| 39.2 | 1 | |
| 39.1 | 1 |
기온반응도(f(s))
Real number (ℝ)
| Distinct | 600 |
|---|---|
| Distinct (%) | 99.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | -0.12193537 |
| Minimum | -1.88369 |
|---|---|
| Maximum | 0.65888 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 339 |
| Negative (%) | 56.4% |
| Memory size | 5.4 KiB |
Quantile statistics
| Minimum | -1.88369 |
|---|---|
| 5-th percentile | -1.28596 |
| Q1 | -0.47291 |
| median | -0.11191 |
| Q3 | 0.34501 |
| 95-th percentile | 0.64527 |
| Maximum | 0.65888 |
| Range | 2.54257 |
| Interquartile range (IQR) | 0.81792 |
Descriptive statistics
| Standard deviation | 0.56719021 |
|---|---|
| Coefficient of variation (CV) | -4.6515641 |
| Kurtosis | 0.46273997 |
| Mean | -0.12193537 |
| Median Absolute Deviation (MAD) | 0.38706 |
| Skewness | -0.72206183 |
| Sum | -73.28316 |
| Variance | 0.32170474 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| -0.38635 | 2 | 0.3% |
| -1.88369 | 1 | 0.2% |
| -0.39616 | 1 | 0.2% |
| -0.40096 | 1 | 0.2% |
| -0.40569 | 1 | 0.2% |
| -0.41034 | 1 | 0.2% |
| -0.41492 | 1 | 0.2% |
| -0.41943 | 1 | 0.2% |
| -0.42386 | 1 | 0.2% |
| -0.42822 | 1 | 0.2% |
| Other values (590) | 590 |
| Value | Count | Frequency (%) |
| -1.88369 | 1 | |
| -1.86347 | 1 | |
| -1.84325 | 1 | |
| -1.82304 | 1 | |
| -1.80285 | 1 | |
| -1.78267 | 1 | |
| -1.7625 | 1 | |
| -1.74235 | 1 | |
| -1.72221 | 1 | |
| -1.7021 | 1 |
| Value | Count | Frequency (%) |
| 0.65888 | 1 | |
| 0.65887 | 1 | |
| 0.65877 | 1 | |
| 0.65874 | 1 | |
| 0.65855 | 1 | |
| 0.65849 | 1 | |
| 0.65821 | 1 | |
| 0.65812 | 1 | |
| 0.65775 | 1 | |
| 0.65763 | 1 |
| 기온(s) | 기온반응도(f(s)) | |
|---|---|---|
| 기온(s) | 1.000 | 0.918 |
| 기온반응도(f(s)) | 0.918 | 1.000 |
| 기온(s) | 기온반응도(f(s)) | |
|---|---|---|
| 기온(s) | 1.000 | -0.038 |
| 기온반응도(f(s)) | -0.038 | 1.000 |
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.
| 기온(s) | 기온반응도(f(s)) | |
|---|---|---|
| 0 | -20.0 | -1.88369 |
| 1 | -19.9 | -1.86347 |
| 2 | -19.8 | -1.84325 |
| 3 | -19.7 | -1.82304 |
| 4 | -19.6 | -1.80285 |
| 5 | -19.5 | -1.78267 |
| 6 | -19.4 | -1.7625 |
| 7 | -19.3 | -1.74235 |
| 8 | -19.2 | -1.72221 |
| 9 | -19.1 | -1.7021 |
| 기온(s) | 기온반응도(f(s)) | |
|---|---|---|
| 591 | 39.1 | 0.20521 |
| 592 | 39.2 | 0.21384 |
| 593 | 39.3 | 0.22247 |
| 594 | 39.4 | 0.2311 |
| 595 | 39.5 | 0.23973 |
| 596 | 39.6 | 0.24835 |
| 597 | 39.7 | 0.25697 |
| 598 | 39.8 | 0.26559 |
| 599 | 39.9 | 0.27419 |
| 600 | 40.0 | 0.2828 |