Reputation: 348
I have all the data I want to plot in one pandas data frame, e.g.:
date flower_color flower_count
0 2017-08-01 blue 1
1 2017-08-01 red 2
2 2017-08-02 blue 5
3 2017-08-02 red 2
I need a few different lines on one plot: x-value should be the date from the first column and y-value should be flower_count, and the y-value should depend on the flower_color given in the second column.
How can I do that without filtering the original df and saving it as a new object first? My only idea was to create a data frame for only red flowers and then specifying it like:
figure.line(x="date", y="flower_count", source=red_flower_ds)
figure.line(x="date", y="flower_count", source=blue_flower_ds)
Upvotes: 3
Views: 4434
Reputation: 444
If my understanding is right, you need a plot with two subplots. The X for both subplots are dates, and the Ys are the flower counts for each color?
In this case, you can employ the subplots in pandas visualization.
fig, axes = plt.subplots(2)
z[z.flower_color == 'blue'].plot(x=['date'], y= ['flower_count'],ax=axes[0]).set_ylabel('blue')
z[z.flower_color == 'red'].plot(x=['date'], y= ['flower_count'],ax=axes[1]).set_ylabel('red')
plt.show()
The output will be like:
Hope it helps.
Upvotes: 2
Reputation: 38425
You can try this
fig, ax = plt.subplots()
for name, group in df.groupby('flower_color'):
group.plot('date', y='flower_count', ax=ax, label=name)
Upvotes: 8