![]() ![]() I created a new custom mplstyle for this plot. Normally you would do this conversion inside read_csv by including a parse_dates argument, but this method works as well. It will serve as the x-axis variable on the plot. With our datetime parsing out of the way, we should convert the date column to datetime64. There is no option but we can specify seconds and divide by 3600. This operation introduces another data type, timedelta64, which is really a numpy float64 under the hood. And since every day is 24 hours long, we can get dark hours by subtracting daylight hours from 24. To get this information we’ll need to subtract the new columns.ĭaylight hours can be calculated by subtracting sunrise from sunset. Remember the goal is to plot duration of day and night, not sunrise and sunset times. string, and the new columns are datetime64. The original columns are still object, i.e. Now the DataFrame’s head() and dtype look like this. The provides one-second precision, which is perfect for this application. This is done by concatenating each day’s date and time strings together, then converting type to datetime64. import pandas as pdįrom matplotlib.dates import MonthLocator, DateFormatterįrom matplotlib.offsetbox import OffsetImage, AnnotationBboxĭf = pd.read_csv("lincoln_sunrise_sunset_2021.csv")Ĭreate two new columns to hold sunrise and sunset datetimes. It will be easier to manipulate it as a string. Let’s skip converting the date column into a datetime format for now. date,sunrise,sunsetīegin by reading the CSV into a pandas DataFrame. We’ll have to address this when we convert timestamps into datetime types. Notice that date and time are stored in separate columns. Since exact times vary depending on latitude, I’ll pick a city near the center of the U.S.-Lincoln, Nebraska. Calculate daylight and dark duration for each day.Get a dataset with daily sunrise and sunset information.I’ll also demonstrate an easy way to add images to Matplotlib plots. It offers an opportunity to work with datetime data, which I remember seemed so opaque when I started programming. I think plotting the annual progression of sunlight and dark hours will help put the change into perspective. Personally I’m a fan of summer and its endless sunlight, and the change of season always feels like an old friend going away. ![]() It also marked the beginning of fall-at least according to astronomical seasons. Here in the northern hemisphere we recently experienced the autumnal equinox, which means we saw an equal 12 hours each of day and night. ![]()
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