Simple plot,
you can use:
df.plot(x='Date',y='adj_close')
Or you can set the index to be Date
beforehand, then it’s easy to plot the column you want:
df.set_index('Date', inplace=True) df['adj_close'].plot()
If you want a chart with one series by ticker
on it
You need to groupby before:
df.set_index('Date', inplace=True) df.groupby('ticker')['adj_close'].plot(legend=True)
If you want a chart with individual subplots:
grouped = df.groupby('ticker') ncols=2 nrows = int(np.ceil(grouped.ngroups/ncols)) fig, axes = plt.subplots(nrows=nrows, ncols=ncols, figsize=(12,4), sharey=True) for (key, ax) in zip(grouped.groups.keys(), axes.flatten()): grouped.get_group(key).plot(ax=ax) ax.legend() plt.show()
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