Dataset statistics
| Number of variables | 1 |
|---|---|
| Number of observations | 13880 |
| Missing cells | 76 |
| Missing cells (%) | 0.5% |
| Duplicate rows | 1895 |
| Duplicate rows (%) | 13.7% |
| Total size in memory | 216.9 KiB |
| Average record size in memory | 16.0 B |
Variable types
| TimeSeries | 1 |
|---|
Timeseries statistics
| Number of series | 1 |
|---|---|
| Time series length | 13880 |
| Starting point | 1983-01-01 00:00:00 |
| Ending point | 2020-12-31 00:00:00 |
| Period | 1 day |
| Dataset has 1895 (13.7%) duplicate rows | Duplicates |
Flow is non stationary | Non stationary |
Flow is seasonal | Seasonal |
Reproduction
| Analysis started | 2024-05-12 18:17:32.289640 |
|---|---|
| Analysis finished | 2024-05-12 18:17:34.876678 |
| Duration | 2.59 seconds |
| Missing | Q_Station_NA_26207080_ok_Missing.csv |
| Download configuration | config.json |
Flow
Numeric time series
NON STATIONARY SEASONAL
| Distinct | 5567 |
|---|---|
| Distinct (%) | 40.3% |
| Missing | 76 |
| Missing (%) | 0.5% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 842.96732 |
|---|---|
| Minimum | 135.23 |
| Maximum | 3183.2 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Memory size | 216.9 KiB |
Quantile statistics
| Minimum | 135.23 |
|---|---|
| 5-th percentile | 323 |
| Q1 | 491 |
| median | 724.135 |
| Q3 | 1092 |
| 95-th percentile | 1729.85 |
| Maximum | 3183.2 |
| Range | 3047.97 |
| Interquartile range (IQR) | 601 |
Descriptive statistics
| Standard deviation | 460.17439 |
|---|---|
| Coefficient of variation (CV) | 0.54589825 |
| Kurtosis | 1.8190493 |
| Mean | 842.96732 |
| Median Absolute Deviation (MAD) | 273.69 |
| Skewness | 1.2572127 |
| Sum | 11636321 |
| Variance | 211760.46 |
| Monotonicity | Not monotonic |
| Augmented Dickey-Fuller test p-value | 3.693264709 × 10-16 |
Histogram with fixed size bins (bins=50)
Gap statistics
| number of gaps | 10 |
|---|---|
| min | 3 days |
| max | 3 weeks and 6 days |
| mean | 1 week, 4 hours and 48 minutes |
| std | 1 week, 13 hours and 39 minutes |
| Value | Count | Frequency (%) |
| 648 | 23 | 0.2% |
| 442 | 22 | 0.2% |
| 436 | 21 | 0.2% |
| 472 | 21 | 0.2% |
| 540 | 21 | 0.2% |
| 560 | 20 | 0.1% |
| 450 | 20 | 0.1% |
| 657 | 19 | 0.1% |
| 619 | 18 | 0.1% |
| 910 | 18 | 0.1% |
| Other values (5557) | 13601 | |
| (Missing) | 76 | 0.5% |
| Value | Count | Frequency (%) |
| 135.23 | 1 | |
| 139.27 | 1 | |
| 139.35 | 1 | |
| 139.5 | 1 | |
| 140.89 | 1 | |
| 144.51 | 1 | |
| 145.06 | 1 | |
| 145.45 | 1 | |
| 146.17 | 1 | |
| 147.14 | 1 |
| Value | Count | Frequency (%) |
| 3183.2 | 1 | < 0.1% |
| 3035 | 1 | < 0.1% |
| 3029 | 1 | < 0.1% |
| 3012 | 1 | < 0.1% |
| 2998.1 | 1 | < 0.1% |
| 2946 | 1 | < 0.1% |
| 2931 | 5 | |
| 2916 | 1 | < 0.1% |
| 2904 | 1 | < 0.1% |
| 2901 | 5 |
ACF and PACF
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.
| Flow | |
|---|---|
| Date | |
| 1983-01-01 | 910.0 |
| 1983-01-02 | 842.0 |
| 1983-01-03 | 829.0 |
| 1983-01-04 | 787.0 |
| 1983-01-05 | 730.0 |
| 1983-01-06 | 695.0 |
| 1983-01-07 | 723.0 |
| 1983-01-08 | 706.0 |
| 1983-01-09 | 679.0 |
| 1983-01-10 | 653.0 |
| Flow | |
|---|---|
| Date | |
| 2020-12-22 | 572.51 |
| 2020-12-23 | 548.03 |
| 2020-12-24 | 579.82 |
| 2020-12-25 | 738.92 |
| 2020-12-26 | 1019.60 |
| 2020-12-27 | 1025.10 |
| 2020-12-28 | 1209.30 |
| 2020-12-29 | 1250.00 |
| 2020-12-30 | 1211.10 |
| 2020-12-31 | NaN |
Most frequently occurring
| Flow | # duplicates | |
|---|---|---|
| 1894 | NaN | 76 |
| 676 | 648.0 | 23 |
| 300 | 442.0 | 22 |
| 293 | 436.0 | 21 |
| 359 | 472.0 | 21 |
| 492 | 540.0 | 21 |
| 313 | 450.0 | 20 |
| 523 | 560.0 | 20 |
| 688 | 657.0 | 19 |
| 279 | 428.0 | 18 |