Heatmaps are not populating all values

[Stegosaurus]

Hi everyone,

As the title implies, I am trying to create heatmaps but not all values are being shown.

This is on a Jupyter Notebook.

# Show correlation heatmap and matrix
df_corr = df[['floor_area_sqm', 'resale_price', 'lease_commence_date']]

# Calculate the correlation matrix
corrmat = df_corr.corr()

# Show the heatmap
import seaborn as sns
import matplotlib.pyplot as plt

sns.heatmap(corrmat, annot=True)

plt.show()

import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.preprocessing import LabelEncoder

# Create a copy with only the columns we need
df_corr = df[['floor_area_sqm', 'resale_price', 'lease_commence_date', 'storey_range']].copy()

# Convert storey_range to numeric using LabelEncoder
le = LabelEncoder()
df_corr['storey_range'] = le.fit_transform(df_corr['storey_range'])

# Ensure all columns are numeric
df_corr = df_corr.apply(pd.to_numeric, errors='coerce')

# Drop rows with any NaN values to ensure clean data
df_corr = df_corr.dropna()

# Compute correlation matrix
corrmat = df_corr.corr(method='pearson')

# Debugging: Print correlation matrix and its shape
print("\nCorrelation matrix shape:", corrmat.shape)
print("\nCorrelation matrix:")
print(corrmat)

# Ensure there are no NaN values in the correlation matrix
if corrmat.isnull().values.any():
   print("NaN values found in the correlation matrix!")
else:
   print("No NaN values in the correlation matrix.")

# Modified heatmap code
plt.figure(figsize=(12, 10))
sns.heatmap(corrmat, 
           annot=True)   # Add this to ensure annotations are visible

# Ensure the full matrix is displayed
plt.subplots_adjust(bottom=0.15)

# Rotate x-axis labels for better readability
plt.xticks(rotation=45, ha='right')
plt.yticks(rotation=0)

# Set title and adjust layout
plt.title('Correlation Matrix Heatmap')
plt.tight_layout()
plt.show()

I tried debugging it and the values do seem to be calculated correctly:



Any help is much appreciated! :)