Set and change time series frequency
In the video, you have seen how to assign a frequency to a DateTimeIndex, and then change this frequency.
Now, you'll use data on the daily carbon monoxide concentration in NYC, LA and Chicago from 2005-17.
You'll set the frequency to calendar daily and then resample to monthly frequency, and visualize both series to see how the different frequencies affect the data.
Diese Übung ist Teil des Kurses
Manipulating Time Series Data in Python
Anleitung zur Übung
We have already imported pandas as pd and matplotlib.pyplot as plt and we have already loaded the co_cities.csv file in a variable co.
- Inspect
cousing.info(). - Use
.asfreq()to set the frequency to calendar daily. - Show a plot of
'co'usingsubplots=True. - Change the the frequency to monthly using the alias
'M'. - Show another plot of
cousingsubplots=True.
Interaktive Übung
Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.
# Inspect data
print(____)
# Set the frequency to calendar daily
co = ____
# Plot the data
# Set frequency to monthly
co = ____
# Plot the data