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How to make a customized graph from a dataframe using python

I'm trying to draw a specific graph from the dataframe shown below :

      Type   Test  Speed  Efficiency  Durability
0  Model A     OK      3           3           3
1  Model A  nonOK      2           2           2
2  Model B     OK      1           1           2
3  Model B  nonOK      3           3           2
4  Model C     OK      3           2           6
5  Model C  nonOK      3           4           0

This is the expected graph output :

enter image description here

I tried something very basic with plotly express but I got a different output :

fig = px.bar(df, x="Type", y=['Speed', 'Efficiency', 'Durability'],
            color="Test", height=450, width=500)

fig.show()

enter image description here

Do you have any suggestions please ?

Solution

  • plotly express has facet plots link to docu
    Kudos to this answer from Saaru Lindestøkke from where I got this info.

    Figure result (code see below): enter image description here

    Dataframe needs to be reshaped from wide to long, e.g. with melt:

    import pandas as pd
import io

data_provided = '''                  
   Type,   Test,  Speed,  Efficiency,  Durability
Model A,     OK,      3,           3,           3
Model A,  nonOK,      2,           2,           2
Model B,     OK,      1,           1,           2
Model B,  nonOK,      3,           3,           2
Model C,     OK,      3,           2,           6
Model C,  nonOK,      3,           4,           0
'''
df_fromstring = pd.read_csv(io.StringIO(data_provided), skipinitialspace=True)

df_long = pd.melt(df_fromstring, id_vars=['Type', 'Test'], 
                  value_vars=['Speed', 'Efficiency', 'Durability'],
                  var_name='Characteristics', value_name='amount')

print(df_long)

           Type   Test Characteristics  amount
0   Model A     OK           Speed       3
1   Model A  nonOK           Speed       2
2   Model B     OK           Speed       1
3   Model B  nonOK           Speed       3
4   Model C     OK           Speed       3
5   Model C  nonOK           Speed       3
6   Model A     OK      Efficiency       3
7   Model A  nonOK      Efficiency       2
8   Model B     OK      Efficiency       1
9   Model B  nonOK      Efficiency       3
10  Model C     OK      Efficiency       2
11  Model C  nonOK      Efficiency       4
12  Model A     OK      Durability       3
13  Model A  nonOK      Durability       2
14  Model B     OK      Durability       2
15  Model B  nonOK      Durability       2
16  Model C     OK      Durability       6
17  Model C  nonOK      Durability       0

    Stacked and grouped bar plot:

    import plotly.express as px

fig = px.bar(df_long, x="Characteristics", y="amount", facet_col="Type", color="Test",
             text_auto=True)  # text_auto=True to print the values inside the bars

fig.show()

    Note: Figure result was posted on top.

    Add-on 1: Some example to change the plot title and axis (no plot picture added, give it a try):

    import plotly.graph_objects as go

fig = px.bar(df_long, x="Characteristics", y="amount", facet_col="Type", color="Test", 
             title="Some Title", text_auto=True)  

# remove x axis subplots titles (bottom)
for axis in fig.layout:
    if type(fig.layout[axis]) == go.layout.XAxis:
        fig.layout[axis].title.text = ''   

# set some new figure titels 
fig.update_layout(title = "Some Other Title", title_x=0.5,
     xaxis_title = 'Type', yaxis_title = 'Value')
    
fig.show()

    Add-on 2: Plotly Static Image Export in Python (just mentioned as I had to look that up as well):

    Required - if not installed already:

    $ pip install -U kaleido
    or
    $ conda install -c conda-forge python-kaleido

    fig.write_image("Plotly_Bar_Stacked_Grouped.png")