Plotting a wideform matrix with hues in seaborn stripplot

Question

I am trying to plot a dataset using stripplot. Here is the head (there are 25 columns):

    Labels  Acidobacteria  Actinobacteria  Armatimonadetes  Bacteroidetes  
0       0              0             495              NaN          27859   
1       1              0            1256              NaN          46582
2       0              0            1081              NaN          23798   
3       1              0            2523              NaN          35088   
4       0              0            1383              NaN          19338  

I have this dataset stored in a pandas DataFrame and can plot it using:

   def plot():
    ax = sns.stripplot(data = df)
    ax.set(xlabel='Bacteria',ylabel='Abundance')
    plt.setp(ax.get_xticklabels(),rotation=45)
    plt.show()

To produce this plot.

I would like to set the hues to reflect the 'Labels' column. When I try:

sns.stripplot(x=df.columns.values.tolist(),y=df,data=df,hue='Labels') 

I get:

ValueError: cannot copy sequence with size 26 to array axis with dimension 830

Answer 1

I would like to expand on your answer (actually I will compact it) because this could be done in a "one-liner":

# To select specific columns:
cols = ["Acidobacteria", "Actinobacteria", "Armatimonadetes", "Bacteroidetes"]
df.set_index("Labels")[cols]\
    .stack()\
    .reset_index()\
    .rename(columns={'level_1':'Bacteria', 0:'Abundance'})

# If you want to stack all columns but "Labels", this is enough:
df.set_index("Labels")\
    .stack()\
    .reset_index()\
    .rename(columns={'level_1':'Bacteria', 0:'Abundance'})

The trick to avoid recreating the "Labels" column, is to set it as index before stacking.

Output:

    Labels        Bacteria  Abundance
0        0   Acidobacteria        0.0
1        0  Actinobacteria      495.0
2        0   Bacteroidetes    27859.0
3        1   Acidobacteria        0.0
4        1  Actinobacteria     1256.0
5        1   Bacteroidetes    46582.0
6        0   Acidobacteria        0.0
7        0  Actinobacteria     1081.0
8        0   Bacteroidetes    23798.0
9        1   Acidobacteria        0.0
10       1  Actinobacteria     2523.0
11       1   Bacteroidetes    35088.0
12       0   Acidobacteria        0.0
13       0  Actinobacteria     1383.0
14       0   Bacteroidetes    19338.0

Answer 2

So I figured it out. I had to rearrange my data by stacking and re-indexing:

cols = df.columns.values.tolist()[3:]
stacked = df[cols].stack().reset_index()
stacked.rename(columns={'level_0':'index','level_1':'Bacteria',0:'Abundance'},inplace=True)

Which outputs:

           index          Bacteria  Abundance
0          0     Acidobacteria   0.000000
1          0    Actinobacteria   0.005003
2          0   Armatimonadetes   0.000000
3          0     Bacteroidetes   0.281586

Next I had to create a new column to assign labels to each data point:

label_col = np.array([[label for _ in range(len(cols))] for label in df['Labels']])
label_col = label_col.flatten()

stacked['Labels'] = label_col

So now:

   index         Bacteria  Abundance  Labels
0      0    Acidobacteria   0.000000       0
1      0   Actinobacteria   0.005003       0
2      0  Armatimonadetes   0.000000       0
3      0    Bacteroidetes   0.281586       0
4      0       Chlamydiae   0.000000       0

And then plot:

def plot():
    ax = sns.stripplot(x='Bacteria',y='Abundance',data=stacked,hue='Labels',jitter=True)
    ax.set(xlabel='Bacteria',ylabel='Abundance')
    plt.setp(ax.get_xticklabels(),rotation=45)
    plt.show()
plot()

To produce this graph.

Thanks for the help!