Boxplot with pandas
Question:
this is how looks like my dataframe:
PART METHOD J P AVG STD
0 1 meth1 3 50 0.914482 0.007398
1 1 meth2 3 50 0.925134 0.005738
... ... ... ... ... ... ...
190 4 meth4 7 150 0.913014 0.006144
191 4 meth4 7 200 0.914199 0.002962
And I would like to show a Boxplot with Pandas using the AVG and the STD columns (average and standard deviation), and I don’t know how can start.
For instance, I would like to compare the four methods for PART = 1, J = 3 and P = 50 through a boxplot to see if these values are compatibles (similar) or not.
I’m very lost, any guidance?
EDIT: the following image shows what I would like. Where A, B, C and D are the methods and each box is created by the value of AVG in combination with de STD for PART = 1, J = 3 and P = 50.
Answers:
Have you tried
(df.groupby(['PART', 'J', 'P'])
.get_group((1, 3, 50))
.groupby('METHOD')
.boxplot(column=['AVG', 'STD']));
which on the following sample data
PART METHOD J P AVG STD
0 1 meth1 3 50 0.914482 0.6398
1 1 meth1 3 50 0.583014 0.5144
2 1 meth2 3 50 0.425134 0.5738
3 1 meth2 3 50 0.914199 0.2962
4 4 meth4 7 150 0.913014 0.6144
5 4 meth4 7 200 0.914199 0.2962
produces
UPDATE
Given the latest update to the post, please consider doing
(df.groupby(['PART', 'J', 'P'])
.get_group((1, 3, 50))
.boxplot(column=['AVG', 'STD'], by='METHOD'));
resulting in
You can filter the dataframe and create boxplot with parameter by.
filtered_df = df[(df['PART'] == 1) & (df['J'] == 3) & (df['P'] == 50)]
filtered_df.boxplot(column = 'AVG', by = 'METHOD', patch_artist = True)
For the following sample df
df = pd.DataFrame({'PART':np.random.randint(1,4,10000), 'METHOD':np.random.choice(list('ABCD'), 10000), 'J':np.random.randint(3,7, 10000), 'P':np.random.randint(50,100, 10000),'AVG':np.random.randn(10000),'STD':np.random.randn(10000)})
You get
this is how looks like my dataframe:
PART METHOD J P AVG STD
0 1 meth1 3 50 0.914482 0.007398
1 1 meth2 3 50 0.925134 0.005738
... ... ... ... ... ... ...
190 4 meth4 7 150 0.913014 0.006144
191 4 meth4 7 200 0.914199 0.002962
And I would like to show a Boxplot with Pandas using the AVG and the STD columns (average and standard deviation), and I don’t know how can start.
For instance, I would like to compare the four methods for PART = 1, J = 3 and P = 50 through a boxplot to see if these values are compatibles (similar) or not.
I’m very lost, any guidance?
EDIT: the following image shows what I would like. Where A, B, C and D are the methods and each box is created by the value of AVG in combination with de STD for PART = 1, J = 3 and P = 50.
Have you tried
(df.groupby(['PART', 'J', 'P'])
.get_group((1, 3, 50))
.groupby('METHOD')
.boxplot(column=['AVG', 'STD']));
which on the following sample data
PART METHOD J P AVG STD
0 1 meth1 3 50 0.914482 0.6398
1 1 meth1 3 50 0.583014 0.5144
2 1 meth2 3 50 0.425134 0.5738
3 1 meth2 3 50 0.914199 0.2962
4 4 meth4 7 150 0.913014 0.6144
5 4 meth4 7 200 0.914199 0.2962
produces
UPDATE
Given the latest update to the post, please consider doing
(df.groupby(['PART', 'J', 'P'])
.get_group((1, 3, 50))
.boxplot(column=['AVG', 'STD'], by='METHOD'));
resulting in
You can filter the dataframe and create boxplot with parameter by.
filtered_df = df[(df['PART'] == 1) & (df['J'] == 3) & (df['P'] == 50)]
filtered_df.boxplot(column = 'AVG', by = 'METHOD', patch_artist = True)
For the following sample df
df = pd.DataFrame({'PART':np.random.randint(1,4,10000), 'METHOD':np.random.choice(list('ABCD'), 10000), 'J':np.random.randint(3,7, 10000), 'P':np.random.randint(50,100, 10000),'AVG':np.random.randn(10000),'STD':np.random.randn(10000)})
You get