{ "cells": [ { "cell_type": "markdown", "id": "70653c4f", "metadata": {}, "source": [ "# Plotting timeseries data\n", "\n", "Most of the data that we want to plot with `Matplotlib` will be in tabular format. In the second demo of this week, we will make some plots to display daily reservoir levels of [Fall Creek Reservoir](https://en.wikipedia.org/wiki/Fall_Creek_Lake) in the Willamette National Forest. \n", "\n", "```{image} images/fall_creek.jpg\n", ":alt: fall creek reservoir\n", ":class: bg-primary mb-1\n", ":width: 600px\n", ":align: center\n", "```" ] }, { "cell_type": "markdown", "id": "35ea1266", "metadata": {}, "source": [ "## Daily reservoir levels" ] }, { "cell_type": "code", "execution_count": 2, "id": "fcbcfdc3", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | date | \n", "level | \n", "
---|---|---|
0 | \n", "2020-11-05 | \n", "677.94 | \n", "
1 | \n", "2020-11-06 | \n", "691.36 | \n", "
2 | \n", "2020-11-07 | \n", "693.29 | \n", "
3 | \n", "2020-11-08 | \n", "694.50 | \n", "
4 | \n", "2020-11-09 | \n", "694.56 | \n", "
... | \n", "... | \n", "... | \n", "
582 | \n", "2022-06-10 | \n", "829.63 | \n", "
583 | \n", "2022-06-11 | \n", "830.73 | \n", "
584 | \n", "2022-06-12 | \n", "830.90 | \n", "
585 | \n", "2022-06-13 | \n", "830.65 | \n", "
586 | \n", "2022-06-14 | \n", "830.19 | \n", "
587 rows × 2 columns
\n", "\n", " | date | \n", "level | \n", "
---|---|---|
0 | \n", "2020-11-05 | \n", "677.94 | \n", "
1 | \n", "2020-11-06 | \n", "691.36 | \n", "
2 | \n", "2020-11-07 | \n", "693.29 | \n", "
3 | \n", "2020-11-08 | \n", "694.50 | \n", "
4 | \n", "2020-11-09 | \n", "694.56 | \n", "
... | \n", "... | \n", "... | \n", "
582 | \n", "2022-06-10 | \n", "829.63 | \n", "
583 | \n", "2022-06-11 | \n", "830.73 | \n", "
584 | \n", "2022-06-12 | \n", "830.90 | \n", "
585 | \n", "2022-06-13 | \n", "830.65 | \n", "
586 | \n", "2022-06-14 | \n", "830.19 | \n", "
587 rows × 2 columns
\n", "\n", " | date | \n", "time | \n", "air_temp | \n", "
---|---|---|---|
0 | \n", "20220610 | \n", "10 | \n", "24.3 | \n", "
1 | \n", "20220610 | \n", "15 | \n", "24.0 | \n", "
2 | \n", "20220610 | \n", "20 | \n", "23.7 | \n", "
3 | \n", "20220610 | \n", "25 | \n", "23.1 | \n", "
4 | \n", "20220610 | \n", "30 | \n", "22.7 | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "
1650 | \n", "20220615 | \n", "1740 | \n", "13.9 | \n", "
1651 | \n", "20220615 | \n", "1745 | \n", "14.7 | \n", "
1652 | \n", "20220615 | \n", "1750 | \n", "14.6 | \n", "
1653 | \n", "20220615 | \n", "1755 | \n", "14.9 | \n", "
1654 | \n", "20220615 | \n", "1800 | \n", "14.8 | \n", "
1655 rows × 3 columns
\n", "\n", " | datetime | \n", "air_temp | \n", "
---|---|---|
0 | \n", "2022-06-10 00:10:00 | \n", "24.3 | \n", "
1 | \n", "2022-06-10 00:15:00 | \n", "24.0 | \n", "
2 | \n", "2022-06-10 00:20:00 | \n", "23.7 | \n", "
3 | \n", "2022-06-10 00:25:00 | \n", "23.1 | \n", "
4 | \n", "2022-06-10 00:30:00 | \n", "22.7 | \n", "
... | \n", "... | \n", "... | \n", "
1650 | \n", "2022-06-15 17:40:00 | \n", "13.9 | \n", "
1651 | \n", "2022-06-15 17:45:00 | \n", "14.7 | \n", "
1652 | \n", "2022-06-15 17:50:00 | \n", "14.6 | \n", "
1653 | \n", "2022-06-15 17:55:00 | \n", "14.9 | \n", "
1654 | \n", "2022-06-15 18:00:00 | \n", "14.8 | \n", "
1655 rows × 2 columns
\n", "\n", " | datetime | \n", "air_temp | \n", "
---|---|---|
863 | \n", "2022-06-13 00:05:00 | \n", "13.1 | \n", "
864 | \n", "2022-06-13 00:10:00 | \n", "13.0 | \n", "
865 | \n", "2022-06-13 00:15:00 | \n", "12.7 | \n", "
866 | \n", "2022-06-13 00:20:00 | \n", "12.6 | \n", "
867 | \n", "2022-06-13 00:25:00 | \n", "12.5 | \n", "
... | \n", "... | \n", "... | \n", "
1145 | \n", "2022-06-13 23:35:00 | \n", "14.9 | \n", "
1146 | \n", "2022-06-13 23:40:00 | \n", "14.9 | \n", "
1147 | \n", "2022-06-13 23:45:00 | \n", "14.7 | \n", "
1148 | \n", "2022-06-13 23:50:00 | \n", "14.5 | \n", "
1149 | \n", "2022-06-13 23:55:00 | \n", "15.0 | \n", "
287 rows × 2 columns
\n", "\n", " | air_temp | \n", "
---|---|
datetime | \n", "\n", " |
2022-06-10 00:10:00 | \n", "24.3 | \n", "
2022-06-10 00:15:00 | \n", "24.0 | \n", "
2022-06-10 00:20:00 | \n", "23.7 | \n", "
2022-06-10 00:25:00 | \n", "23.1 | \n", "
2022-06-10 00:30:00 | \n", "22.7 | \n", "
... | \n", "... | \n", "
2022-06-15 17:40:00 | \n", "13.9 | \n", "
2022-06-15 17:45:00 | \n", "14.7 | \n", "
2022-06-15 17:50:00 | \n", "14.6 | \n", "
2022-06-15 17:55:00 | \n", "14.9 | \n", "
2022-06-15 18:00:00 | \n", "14.8 | \n", "
1655 rows × 1 columns
\n", "\n", " | air_temp | \n", "pacific_time | \n", "
---|---|---|
datetime | \n", "\n", " | \n", " |
2022-06-10 00:10:00 | \n", "24.3 | \n", "2022-06-09 16:10:00 | \n", "
2022-06-10 00:15:00 | \n", "24.0 | \n", "2022-06-09 16:15:00 | \n", "
2022-06-10 00:20:00 | \n", "23.7 | \n", "2022-06-09 16:20:00 | \n", "
2022-06-10 00:25:00 | \n", "23.1 | \n", "2022-06-09 16:25:00 | \n", "
2022-06-10 00:30:00 | \n", "22.7 | \n", "2022-06-09 16:30:00 | \n", "
... | \n", "... | \n", "... | \n", "
2022-06-15 17:40:00 | \n", "13.9 | \n", "2022-06-15 09:40:00 | \n", "
2022-06-15 17:45:00 | \n", "14.7 | \n", "2022-06-15 09:45:00 | \n", "
2022-06-15 17:50:00 | \n", "14.6 | \n", "2022-06-15 09:50:00 | \n", "
2022-06-15 17:55:00 | \n", "14.9 | \n", "2022-06-15 09:55:00 | \n", "
2022-06-15 18:00:00 | \n", "14.8 | \n", "2022-06-15 10:00:00 | \n", "
1655 rows × 2 columns
\n", "\n", " | air_temp | \n", "
---|---|
pacific_time | \n", "\n", " |
2022-06-09 16:10:00 | \n", "24.3 | \n", "
2022-06-09 16:15:00 | \n", "24.0 | \n", "
2022-06-09 16:20:00 | \n", "23.7 | \n", "
2022-06-09 16:25:00 | \n", "23.1 | \n", "
2022-06-09 16:30:00 | \n", "22.7 | \n", "
... | \n", "... | \n", "
2022-06-15 09:40:00 | \n", "13.9 | \n", "
2022-06-15 09:45:00 | \n", "14.7 | \n", "
2022-06-15 09:50:00 | \n", "14.6 | \n", "
2022-06-15 09:55:00 | \n", "14.9 | \n", "
2022-06-15 10:00:00 | \n", "14.8 | \n", "
1655 rows × 1 columns
\n", "