Create Custom Heatmap From Pandas Dataframe

I have a dataframe with 8 rows and 6028 columns. I want to create a heatmap of the 8 rows for the first column (eventually I will create an animation so the map updates reading thr

Solution 1:

The data in your indices needs to be part of the cells and you probably want a pivot. For explanation, I created some similar dataframe with less columns to illustrate what I am doing. I hope this is the structure you are using?

df = pd.DataFrame(index=["Anterior Distal", "Anterior Proximal", "Lateral Distal", "Lateral Proximal"], data={0.:[1,2,3,4], 1.:[5,6,7,8]})
print(df)                                                                     
>>>
                   0.01.0
region                     
Anterior Distal      15
Anterior Proximal    26
Lateral Distal       37
Lateral Proximal     48

As I understand it, you want to explicitly refer to the two parts of your index, so you will need to split the index first. You can do this for example in this way which first uses a pandas method to split the strings and then transforms it to a numpy array which you can slice

index_parts = np.array(df.index.str.split().values.tolist())
index_parts[:,0]
>>> array(['Anterior', 'Anterior', 'Lateral', 'Lateral'], dtype='<U8')

Now, you can add those as new columns

df["antlat"] = index_parts[:,0]
df["distprox"] = index_parts[:,1]
print(df)
>>>
                   0.01.0    antlat  distprox
region                                         
Anterior Distal      15  Anterior    Distal
Anterior Proximal    26  Anterior  Proximal
Lateral Distal       37   Lateral    Distal
Lateral Proximal     48   Lateral  Proximal

Then you can create the pivot for the value you are interested in

df_pivot = df.pivot(index="antlat", columns="distprox", values=0.0)
print(df_pivot)
>>>
distprox  Distal  Proximal
antlat                    
Anterior       12
Lateral        34

And plot it (note that this is only 2x2, since I did not add Medial and Posterior to the example)

sns.heatmap(df_pivot)

Solution 2:

Why not using directly matplotlib? :D

import matplotlib.pyplot as plt
plt.imshow(df.reset_index(drop=True).values[:,1:].astype("float"))