sns.clustermap ticks are missing - matplotlib

Question

I'm trying to visualize what filters are learning in CNN text classification model. To do this, I extracted feature maps of text samples right after the convolutional layer, and for size 3 filter, I got an (filter_num)*(length_of_sentences) sized tensor.
df = pd.DataFrame(-np.random.randn(50,50), index = range(50), columns= range(50))
g= sns.clustermap(df,row_cluster=True,col_cluster=False)
plt.setp(g.ax_heatmap.yaxis.get_majorticklabels(), rotation=0) # ytick rotate
g.cax.remove() # remove colorbar
plt.show()
This code results in :
Where I can't see all the ticks in the y-axis. This is necessary
because I need to see which filters learn which information. Is there
any way to properly exhibit all the ticks in the y-axis?

Answer 1

kwargs from sns.clustermap get passed on to sns.heatmap, which has an option yticklabels, whose documentation states (emphasis mine):
If True, plot the column names of the dataframe. If False, don’t plot the column names. If list-like, plot these alternate labels as the xticklabels. If an integer, use the column names but plot only every n label. If “auto”, try to densely plot non-overlapping labels.
Here, the easiest option is to set it to an integer, so it will plot every n labels. We want every label, so we want to set it to 1, i.e.:
g = sns.clustermap(df, row_cluster=True, col_cluster=False, yticklabels=1)
In your complete example:
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
df = pd.DataFrame(-np.random.randn(50,50), index=range(50), columns=range(50))
g = sns.clustermap(df, row_cluster=True, col_cluster=False, yticklabels=1)
plt.setp(g.ax_heatmap.yaxis.get_majorticklabels(), rotation=0) # ytick rotate
g.cax.remove() # remove colorbar
plt.show()