Using a time index to zoom in
When a time-series is represented with a time index, we can use this index for the x-axis when plotting. We can also select a range of dates to zoom in on a particular period within the time-series using pandas' indexing facilities. In this exercise, you will select a portion of a time-series dataset and you will plot that period.
The data to use is stored in a DataFrame called climate_change
, which has a time-index with dates of measurements and two data columns: "co2"
and "relative_temp"
.
This exercise is part of the course
Introduction to Data Visualization with Matplotlib
Exercise instructions
- Use
plt.subplots
to create a Figure with one Axes calledfig
andax
, respectively. - Create a variable called
seventies
that includes all the data between"1970-01-01"
and"1979-12-31"
. - Add the data from
seventies
to the plot: use the DataFrameindex
for the x value and the"co2"
column for the y values.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
import matplotlib.pyplot as plt
# Use plt.subplots to create fig and ax
____
# Create variable seventies with data from "1970-01-01" to "1979-12-31"
seventies = climate_change[____]
# Add the time-series for "co2" data from seventies to the plot
____(____, ____["co2"])
# Show the figure
____