Pandas groupby filter on column, and then plot the results

Question

I have the following df:

subject_id	name	day	value
1	sld	0	0
1	sld	1	5
1	sld	2	12
1	dsld	0	0
1	dsld	1	-1
2	sld	0	0
2	sld	1	7
2	sld	2	8
2	sld	3	4
2	dsld	0	0

I want to make a line plot with the following criteria:

1. Group by subject_id
2. for each group, only take the rows where name == sld
3. line plot the data where x is the day , and y is the value

I want to plot all the groups on the same plot. Preferably using seaborn

fig, ax = plt.subplots(figsize=(8, 6))
df_sld = df[df['name'] == 'sld']
df_sld.groupby('subject_id').plot(x = 'day', y = 'value', ax = ax)

However, this is taking a long time. Is there a faster way to group by subject_id and then only take the rows where name == sld

I also tried

df.groupby('subject_id')['name'].apply(lambda x: x == 'sld').plot(x = 'day', y = 'value')
df.groupby('subject_id').apply(lambda x: x['name'] == 'sld').plot(x = 'day', y = 'value')

But get an error saying no numerical data

Answer 1

IIUC,

df.query('name == "sld"').set_index(['day', 'subject_id'])['value'].unstack().plot()

Output: