Dataset statistics
| Number of variables | 1 |
|---|---|
| Number of observations | 13880 |
| Missing cells | 1623 |
| Missing cells (%) | 11.7% |
| Duplicate rows | 1257 |
| Duplicate rows (%) | 9.1% |
| 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 1257 (9.1%) duplicate rows | Duplicates |
Flow has 1623 (11.7%) missing values | Missing |
Flow has 906 (6.5%) zeros | Zeros |
Reproduction
| Analysis started | 2024-05-12 19:35:19.872021 |
|---|---|
| Analysis finished | 2024-05-12 19:35:22.280527 |
| Duration | 2.41 seconds |
| Missing | Q_Station_NA_28037030_ok_Missing.csv |
| Download configuration | config.json |
Flow
Numeric time series
MISSING ZEROS
| Distinct | 6649 |
|---|---|
| Distinct (%) | 54.2% |
| Missing | 1623 |
| Missing (%) | 11.7% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.063454344 |
|---|---|
| Minimum | -357.32 |
| Maximum | 196.59 |
| Zeros | 906 |
| Zeros (%) | 6.5% |
| Memory size | 216.9 KiB |
Quantile statistics
| Minimum | -357.32 |
|---|---|
| 5-th percentile | -23.42 |
| Q1 | -0.52 |
| median | 0.1 |
| Q3 | 2.376 |
| 95-th percentile | 21.92 |
| Maximum | 196.59 |
| Range | 553.91 |
| Interquartile range (IQR) | 2.896 |
Descriptive statistics
| Standard deviation | 19.776896 |
|---|---|
| Coefficient of variation (CV) | 311.67127 |
| Kurtosis | 33.074187 |
| Mean | 0.063454344 |
| Median Absolute Deviation (MAD) | 1.4 |
| Skewness | -1.7325433 |
| Sum | 777.7599 |
| Variance | 391.12562 |
| Monotonicity | Not monotonic |
| Augmented Dickey-Fuller test p-value | 0 |
Histogram with fixed size bins (bins=50)
Gap statistics
| number of gaps | 36 |
|---|---|
| min | 4 days |
| max | 2 years and 6 days |
| mean | 6 weeks, 4 days and 40 minutes |
| std | 17 weeks, 5 days and 17 hours |
| Value | Count | Frequency (%) |
| 0 | 906 | 6.5% |
| 0.141 | 124 | 0.9% |
| -0.141 | 112 | 0.8% |
| 0.1 | 96 | 0.7% |
| -0.1 | 82 | 0.6% |
| 0.2 | 60 | 0.4% |
| 0.1 | 59 | 0.4% |
| -0.1 | 54 | 0.4% |
| -0.2 | 48 | 0.3% |
| -8.881784197 × 10-16 | 48 | 0.3% |
| Other values (6639) | 10668 | |
| (Missing) | 1623 | 11.7% |
| Value | Count | Frequency (%) |
| -357.32 | 1 | |
| -229.9 | 1 | |
| -208.36 | 1 | |
| -204.6 | 1 | |
| -188.7 | 1 | |
| -185.4 | 1 | |
| -184.3 | 1 | |
| -180.2 | 1 | |
| -179.7 | 1 | |
| -171.68 | 1 |
| Value | Count | Frequency (%) |
| 196.59 | 1 | |
| 180.76 | 1 | |
| 173.8 | 1 | |
| 161.82 | 1 | |
| 158.46 | 1 | |
| 154.8 | 1 | |
| 154.1 | 1 | |
| 150.1 | 1 | |
| 147.57 | 1 | |
| 145.2 | 1 |
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 | NaN |
| 1983-01-02 | NaN |
| 1983-01-03 | 0.000000e+00 |
| 1983-01-04 | -3.000000e-01 |
| 1983-01-05 | 4.000000e-01 |
| 1983-01-06 | -8.881784e-16 |
| 1983-01-07 | -1.000000e-01 |
| 1983-01-08 | 3.000000e-01 |
| 1983-01-09 | -4.000000e-01 |
| 1983-01-10 | -1.600000e+00 |
| Flow | |
|---|---|
| Date | |
| 2020-12-22 | 1.5380 |
| 2020-12-23 | -3.3780 |
| 2020-12-24 | -2.3070 |
| 2020-12-25 | 0.4420 |
| 2020-12-26 | -2.1110 |
| 2020-12-27 | 1.4480 |
| 2020-12-28 | -1.4330 |
| 2020-12-29 | 1.2120 |
| 2020-12-30 | 1.5483 |
| 2020-12-31 | -0.7971 |
Most frequently occurring
| Flow | # duplicates | |
|---|---|---|
| 1256 | NaN | 1623 |
| 484 | 0.000 | 906 |
| 548 | 0.141 | 124 |
| 419 | -0.141 | 112 |
| 522 | 0.100 | 96 |
| 449 | -0.100 | 82 |
| 563 | 0.200 | 60 |
| 524 | 0.100 | 59 |
| 447 | -0.100 | 54 |
| 406 | -0.200 | 48 |