I have time-series data in a pandas DataFrame that looks like this:
ID HeartRate 1 120 1 118 1 115 2 98 2 110 2 112 3 128 3 115 3 90
And I want to create a separate line plot for each of the distinct IDs (i.e. patients). How can I go about this preferably using matplotlib? Will I have to create a “time-interval” variable?
df = my_data[['ID', 'HR']].copy() ## creating a new "mini" dataframe from the
larger one that I've got.
n_ids = df.ID.unique().size
n_cols = int(n_ids ** 0.5)
n_rows = int(n_ids + n_ids % n_cols)
fig, axes = plt.subplots(n_rows, n_cols)
for i, (ids, hr) in enumerate(df.groupby('ID')['HR']):
hr.plot(ax=axes[i], title=f"ID:{idx}")
fig.tight_layout()
However, as I get the following error:
'numpy.ndarray' object has no attribute 'get_figure'
Answer
Just groupby and plot it:
df.groupby('ID')['HeartRate'].plot()
Or using multiple axes, without worrying (so much at least) with the size of the category:
n_ids = df.ID.unique().size
n_cols = int(n_ids ** 0.5)
n_rows = n_cols + (1 if n_ids % n_cols else 0)
fig, axes = plt.subplots(n_rows, n_cols)
axes = axes.ravel()
for i, (idx, series) in enumerate(df.groupby('ID')['HeartRate']):
series.plot(ax=axes[i], title=f"ID:{idx}")
fig.tight_layout()
Output:
